refactor(web): improve workflow block selector (#39377)

Co-authored-by: claude[bot] <41898282+claude[bot]@users.noreply.github.com>
Co-authored-by: yyh <92089059+lyzno1@users.noreply.github.com>

.agents/skills/frontend-testing/SKILL.md

@@ -9,12 +9,11 @@ Use this skill for Vitest work under `web/` and `packages/dify-ui/`. Do not use
 
 ## Required Source
 
-Before writing, changing, or reviewing frontend tests, read `web/docs/test.md` completely. It is the single source of truth. This skill defines the execution workflow and must not add requirements that conflict with or duplicate that guide.
+Before writing, changing, or reviewing frontend tests, read `web/docs/test.md` completely. It is the single source of truth. This skill provides an execution checklist and must not redefine or extend that policy.
 
 ## Workflow
 
 1. Read the source, its behavior owner, nearby specs, and relevant public dependencies.
-1. Identify whether the contract belongs in `web/`, Dify UI Browser Mode, or a styled Storybook test.
 1. Apply the canonical guide to decide whether a test is needed and choose its boundary.
 1. For a behavior change or bug fix, write or identify the failing scenario first when practical.
 1. Implement one coherent scenario at a time and run the focused spec before expanding scope.
@@ -33,4 +32,4 @@ vp test run path/to/spec-or-directory
 vp test run --project unit src/path/to/spec
 ```
 
-For styled Dify UI behavior, run `vp test --project storybook --run`. Run broader checks only after the focused behavior passes.
+Run Dify UI Storybook tests with `vp test --project storybook --run`. Run broader checks only after the focused behavior passes.

.github/workflows/api-tests.yml

@@ -47,9 +47,6 @@ jobs:
       - name: Install dependencies
         run: uv sync --project api --dev
 
-      - name: Run dify config tests
-        run: uv run --project api pytest api/tests/unit_tests/configs/test_env_consistency.py
-
       - name: Run Unit Tests
         run: |
           uv run --project api pytest \

.github/workflows/main-ci.yml

@@ -27,7 +27,7 @@ jobs:
     steps:
       - id: skip_check
         continue-on-error: true
-        uses: fkirc/skip-duplicate-actions@f75f66ce1886f00957d99748a42c724f4330bdcf # v5.3.1
+        uses: fkirc/skip-duplicate-actions@b974a9395958c231af965b70070979a577efa578 # v5.3.2
         with:
           cancel_others: 'true'
           concurrent_skipping: same_content_newer
@@ -81,7 +81,6 @@ jobs:
               - '.npmrc'
               - '.nvmrc'
               - '.github/workflows/cli-tests.yml'
-              - '.github/workflows/cli-docker-build.yml'
               - '.github/actions/setup-web/**'
             web:
               - 'web/**'

.github/workflows/sandbox-runtime-tests.yml

@@ -27,7 +27,7 @@ jobs:
           persist-credentials: false
 
       - name: Setup Go
-        uses: actions/setup-go@d35c59abb061a4a6fb18e82ac0862c26744d6ab5 # v5.5.0
+        uses: actions/setup-go@b7ad1dad31e06c5925ef5d2fc7ad053ef454303e # v7.0.0
         with:
           go-version-file: dify-agent-runtime/go.mod
           cache-dependency-path: dify-agent-runtime/go.sum
@@ -51,13 +51,13 @@ jobs:
           persist-credentials: false
 
       - name: Setup Go
-        uses: actions/setup-go@d35c59abb061a4a6fb18e82ac0862c26744d6ab5 # v5.5.0
+        uses: actions/setup-go@b7ad1dad31e06c5925ef5d2fc7ad053ef454303e # v7.0.0
         with:
           go-version-file: dify-agent-runtime/go.mod
           cache-dependency-path: dify-agent-runtime/go.sum
 
       - name: Run golangci-lint
-        uses: golangci/golangci-lint-action@4afd733a84b1f43292c63897423277bb7f4313a9 # v6.5.0
+        uses: golangci/golangci-lint-action@ba0d7d2ec06a0ea1cb5fa41b2e4a3ab91d21278a # v6.5.0
         with:
           working-directory: dify-agent-runtime
           version: latest
@@ -78,7 +78,7 @@ jobs:
           persist-credentials: false
 
       - name: Setup Go
-        uses: actions/setup-go@d35c59abb061a4a6fb18e82ac0862c26744d6ab5 # v5.5.0
+        uses: actions/setup-go@b7ad1dad31e06c5925ef5d2fc7ad053ef454303e # v7.0.0
         with:
           go-version-file: dify-agent-runtime/go.mod
           cache-dependency-path: dify-agent-runtime/go.sum

.github/workflows/tool-test-sdks.yaml

@@ -29,7 +29,7 @@ jobs:
           persist-credentials: false
 
       - name: Use Node.js
-        uses: actions/setup-node@48b55a011bda9f5d6aeb4c2d9c7362e8dae4041e # v6.4.0
+        uses: actions/setup-node@820762786026740c76f36085b0efc47a31fe5020 # v7.0.0
         with:
           node-version: 22
           cache: ''

.github/workflows/translate-i18n-claude.yml

@@ -158,7 +158,7 @@ jobs:
 
       - name: Run Claude Code for Translation Sync
         if: steps.context.outputs.CHANGED_FILES != ''
-        uses: anthropics/claude-code-action@e90deca47693f9457b72f2b53c17d7c445a87342 # v1.0.171
+        uses: anthropics/claude-code-action@af0559ee4f514d1ef21826982bed13f7edc3c35e # v1.0.178
         with:
           anthropic_api_key: ${{ secrets.ANTHROPIC_API_KEY }}
           github_token: ${{ secrets.GITHUB_TOKEN }}

.github/workflows/web-e2e.yml

@@ -135,16 +135,6 @@ jobs:
             exit 1
           fi
 
-          if [[ -d cucumber-report ]]; then
-            rm -rf cucumber-report-non-external
-            mv cucumber-report cucumber-report-non-external
-          fi
-
-          if [[ -d .logs ]]; then
-            rm -rf .logs-non-external
-            mv .logs .logs-non-external
-          fi
-
           teardown_external_runtime() {
             local run_status=$?
             trap - EXIT

.github/workflows/web-tests.yml

@@ -17,8 +17,6 @@ jobs:
   test:
     name: Web Tests (${{ matrix.shardIndex }}/${{ matrix.shardTotal }})
     runs-on: depot-ubuntu-24.04-4
-    env:
-      VITEST_COVERAGE_SCOPE: app-components
     strategy:
       fail-fast: false
       matrix:

.vscode/launch.json.template

@@ -5,7 +5,9 @@
             "name": "Python: API (gevent)",
             "type": "debugpy",
             "request": "launch",
-            "program": "${workspaceFolder}/api/app.py",
+            "module": "gevent.monkey",
+            "args": ["--module", "app"],
+            "gevent": true,
             "jinja": true,
             "justMyCode": true,
             "cwd": "${workspaceFolder}/api",
@@ -33,22 +35,6 @@
             "justMyCode": false,
             "cwd": "${workspaceFolder}/api",
             "python": "${workspaceFolder}/api/.venv/bin/python"
-        },
-        {
-            "name": "Next.js: debug full stack",
-            "type": "node",
-            "request": "launch",
-            "program": "${workspaceFolder}/web/node_modules/next/dist/bin/next",
-            "runtimeArgs": ["--inspect"],
-            "skipFiles": ["<node_internals>/**"],
-            "serverReadyAction": {
-              "action": "debugWithChrome",
-              "killOnServerStop": true,
-              "pattern": "- Local:.+(https?://.+)",
-              "uriFormat": "%s",
-              "webRoot": "${workspaceFolder}/web"
-            },
-            "cwd": "${workspaceFolder}/web"
-          }
+        }
     ]
 }

Makefile

@@ -107,6 +107,7 @@ test:
 		echo "Target: $(TARGET_TESTS)"; \
 		uv run --project api --dev pytest $(TARGET_TESTS); \
 	else \
+		set -e; \
 		echo "Running backend unit tests"; \
 		uv run --project api --dev pytest -p no:benchmark --timeout "$${PYTEST_TIMEOUT:-20}" -n auto \
 			api/tests/unit_tests \
@@ -124,6 +125,7 @@ test-all:
 		echo "Target: $(TARGET_TESTS)"; \
 		uv run --project api --dev pytest $(TARGET_TESTS); \
 	else \
+		set -e; \
 		echo "Running backend unit tests"; \
 		uv run --project api --dev pytest -p no:benchmark --timeout "$${PYTEST_TIMEOUT:-20}" -n auto \
 			api/tests/unit_tests \

api/.env.example

@@ -561,6 +561,8 @@ WORKFLOW_MAX_EXECUTION_STEPS=500
 WORKFLOW_MAX_EXECUTION_TIME=1200
 WORKFLOW_CALL_MAX_DEPTH=5
 MAX_VARIABLE_SIZE=204800
+# Maximum concurrent node-builder LLM calls per workflow generation request
+WORKFLOW_GENERATOR_NODE_BUILDER_MAX_WORKERS=6
 
 # GraphEngine Worker Pool Configuration
 # Minimum number of workers per GraphEngine instance (default: 1)
@@ -665,10 +667,27 @@ PLUGIN_REMOTE_INSTALL_HOST=localhost
 PLUGIN_MAX_PACKAGE_SIZE=15728640
 PLUGIN_MODEL_SCHEMA_CACHE_TTL=3600
 PLUGIN_MODEL_PROVIDERS_CACHE_TTL=86400
+# Comma-separated marketplace plugin IDs whose latest versions are installed for newly registered users.
+# Example: langgenius/openai,langgenius/gemini
+NEW_USER_DEFAULT_PLUGIN_IDS=
+# Comma-separated model_type:provider:model entries assigned after default plugins finish installing.
+# Example: llm:langgenius/openai/openai:gpt-4o-mini,text-embedding:langgenius/openai/openai:text-embedding-3-small
+NEW_USER_DEFAULT_MODELS=
 INNER_API_KEY_FOR_PLUGIN=QaHbTe77CtuXmsfyhR7+vRjI/+XbV1AaFy691iy+kGDv2Jvy0/eAh8Y1
 
 # Dify Agent backend
 AGENT_BACKEND_BASE_URL=http://localhost:5050
+AGENT_BACKEND_STREAM_READ_TIMEOUT_SECONDS=30
+AGENT_BACKEND_STREAM_MAX_RECONNECTS=3
+AGENT_BACKEND_RUN_TIMEOUT_SECONDS=1200
+
+# KnowledgeFS (Dataset 2.0)
+KNOWLEDGE_FS_ENABLED=false
+KNOWLEDGE_FS_BASE_URL=
+# Shared with KnowledgeFS; use at least 32 random characters.
+KNOWLEDGE_FS_JWT_SECRET=
+KNOWLEDGE_FS_SSE_READ_TIMEOUT_SECONDS=300
+KNOWLEDGE_FS_TIMEOUT_SECONDS=10
 
 # Marketplace configuration
 MARKETPLACE_ENABLED=true

api/app.py

@@ -1,5 +1,24 @@
 from __future__ import annotations
 
+# ``python -m app`` (docker DEBUG=true, or IDE debugging) serves through the
+# gevent pywsgi server at the bottom of this file, so the stdlib must be
+# monkey-patched BEFORE any other import pulls in sockets or locks. Without
+# this, every request runs as a greenlet on one OS thread while blocking
+# calls (LLM invokes, ``Future.result`` waits, DB I/O) pin that thread — the
+# whole process freezes until the call returns. Gunicorn and Celery apply
+# their own patching (see gunicorn.conf.py / celery_entrypoint.py), and
+# ``flask run`` uses real Werkzeug threads, so both skip this branch.
+if __name__ == "__main__":
+    from gevent import monkey
+
+    monkey.patch_all()
+
+    import psycogreen.gevent as psycogreen_gevent
+    from grpc.experimental import gevent as grpc_gevent
+
+    grpc_gevent.init_gevent()
+    psycogreen_gevent.patch_psycopg()
+
 import logging
 import sys
 from typing import TYPE_CHECKING, cast

api/clients/agent_backend/client.py

@@ -8,7 +8,7 @@ creating another wire contract.
 
 from __future__ import annotations
 
-from collections.abc import Iterator
+from collections.abc import Callable, Iterator
 from typing import Protocol
 
 from dify_agent.client import (
@@ -45,7 +45,13 @@ class AgentBackendRunClient(Protocol):
     def cancel_run(self, run_id: str, request: CancelRunRequest | None = None) -> CancelRunResponse:
         """Request explicit cancellation for one Agent backend run."""
 
-    def stream_events(self, run_id: str, *, after: str | None = None) -> Iterator[RunEvent]:
+    def stream_events(
+        self,
+        run_id: str,
+        *,
+        after: str | None = None,
+        should_stop: Callable[[], bool] | None = None,
+    ) -> Iterator[RunEvent]:
         """Yield public ``dify-agent`` run events in stream order."""
 
     def wait_run(self, run_id: str, *, timeout_seconds: float | None = None) -> RunStatusResponse:
@@ -61,7 +67,15 @@ class _DifyAgentSyncClient(Protocol):
     def cancel_run_sync(self, run_id: str, request: CancelRunRequest | None = None) -> CancelRunResponse:
         """Cancel one run synchronously."""
 
-    def stream_events_sync(self, run_id: str, *, after: str | None = None) -> Iterator[RunEvent]:
+    def stream_events_sync(
+        self,
+        run_id: str,
+        *,
+        after: str | None = None,
+        max_reconnects: int | None = None,
+        timeout_seconds: float | None = None,
+        should_stop: Callable[[], bool] | None = None,
+    ) -> Iterator[RunEvent]:
         """Stream run events synchronously."""
 
     def wait_run_sync(self, run_id: str, *, timeout_seconds: float | None = None) -> RunStatusResponse:
@@ -73,8 +87,16 @@ class DifyAgentBackendRunClient:
 
     client: _DifyAgentSyncClient
 
-    def __init__(self, client: _DifyAgentSyncClient) -> None:
+    def __init__(
+        self,
+        client: _DifyAgentSyncClient,
+        *,
+        stream_max_reconnects: int = 3,
+        stream_timeout_seconds: float = 1200,
+    ) -> None:
         self.client = client
+        self._stream_max_reconnects = stream_max_reconnects
+        self._stream_timeout_seconds = stream_timeout_seconds
 
     def create_run(self, request: CreateRunRequest) -> CreateRunResponse:
         """Create one run through ``POST /runs`` and normalize client exceptions."""
@@ -90,10 +112,22 @@ class DifyAgentBackendRunClient:
         except Exception as exc:
             raise _normalize_dify_agent_error(exc) from exc
 
-    def stream_events(self, run_id: str, *, after: str | None = None) -> Iterator[RunEvent]:
+    def stream_events(
+        self,
+        run_id: str,
+        *,
+        after: str | None = None,
+        should_stop: Callable[[], bool] | None = None,
+    ) -> Iterator[RunEvent]:
         """Stream run events from ``/events/sse`` with the wrapped client's reconnect policy."""
         try:
-            yield from self.client.stream_events_sync(run_id, after=after)
+            yield from self.client.stream_events_sync(
+                run_id,
+                after=after,
+                max_reconnects=self._stream_max_reconnects,
+                timeout_seconds=self._stream_timeout_seconds,
+                should_stop=should_stop,
+            )
         except Exception as exc:
             raise _normalize_dify_agent_error(exc) from exc
 

api/clients/agent_backend/factory.py

@@ -13,10 +13,17 @@ def create_agent_backend_run_client(
     base_url: str | None = None,
     use_fake: bool = False,
     fake_scenario: str | FakeAgentBackendScenario = FakeAgentBackendScenario.SUCCESS,
+    stream_read_timeout_seconds: float = 30,
+    stream_max_reconnects: int = 3,
+    stream_run_timeout_seconds: float = 1200,
 ) -> AgentBackendRunClient:
     """Create the API-side run client without hiding the ``dify-agent`` protocol."""
     if use_fake:
         return FakeAgentBackendRunClient(scenario=FakeAgentBackendScenario(fake_scenario))
     if base_url is None:
         raise ValueError("base_url is required when creating a real Agent backend client")
-    return DifyAgentBackendRunClient(Client(base_url=base_url))
+    return DifyAgentBackendRunClient(
+        Client(base_url=base_url, stream_timeout=stream_read_timeout_seconds),
+        stream_max_reconnects=stream_max_reconnects,
+        stream_timeout_seconds=stream_run_timeout_seconds,
+    )

api/clients/agent_backend/fake_client.py

@@ -7,7 +7,7 @@ separate ``agent-backend.v1`` event stream.
 
 from __future__ import annotations
 
-from collections.abc import Iterator
+from collections.abc import Callable, Iterator
 from datetime import UTC, datetime
 from enum import StrEnum
 
@@ -69,9 +69,17 @@ class FakeAgentBackendRunClient:
         del request
         return CancelRunResponse(run_id=run_id, status="cancelled")
 
-    def stream_events(self, run_id: str, *, after: str | None = None) -> Iterator[RunEvent]:
+    def stream_events(
+        self,
+        run_id: str,
+        *,
+        after: str | None = None,
+        should_stop: Callable[[], bool] | None = None,
+    ) -> Iterator[RunEvent]:
         """Yield the deterministic public ``RunEvent`` sequence for ``run_id``."""
         for event in self._events(run_id):
+            if should_stop is not None and should_stop():
+                return
             if after is not None and event.id is not None and event.id <= after:
                 continue
             yield event

api/commands/retention.py

@@ -1,6 +1,8 @@
 import datetime
 import logging
+import re
 import time
+import uuid
 from collections.abc import Callable
 from typing import TypedDict
 
@@ -21,6 +23,7 @@ from tasks.remove_app_and_related_data_task import delete_draft_variables_batch
 logger = logging.getLogger(__name__)
 
 _HEX_PREFIXES = tuple("0123456789abcdef")
+_TARGET_MONTH_PATTERN = re.compile(r"^\d{4}-(0[1-9]|1[0-2])$")
 
 
 class WorkflowRunArchivePlanRow(TypedDict):
@@ -66,6 +69,7 @@ def _parse_tenant_prefixes(prefixes: str | None) -> list[str]:
 
 
 def _parse_comma_separated_ids(raw_ids: str | None, *, param_name: str) -> list[str] | None:
+    """Keep an omitted scope unset while rejecting an explicitly empty scope."""
     if raw_ids is None:
         return None
     parsed = sorted({raw_id.strip() for raw_id in raw_ids.split(",") if raw_id.strip()})
@@ -74,6 +78,27 @@ def _parse_comma_separated_ids(raw_ids: str | None, *, param_name: str) -> list[
     return parsed
 
 
+def _parse_archive_target_month(target_month: str) -> tuple[int, int]:
+    """Validate the V2 catalog month selector and return its numeric components."""
+    if not _TARGET_MONTH_PATTERN.fullmatch(target_month):
+        raise click.BadParameter("target-month must use YYYY-MM format", param_hint="--target-month")
+    year_text, month_text = target_month.split("-", maxsplit=1)
+    return int(year_text), int(month_text)
+
+
+def _parse_archive_catalog_cursor(after_catalog_id: str | None) -> str | None:
+    """Normalize the exclusive V2 catalog keyset cursor when one is provided."""
+    if after_catalog_id is None:
+        return None
+    try:
+        return str(uuid.UUID(after_catalog_id))
+    except ValueError as exc:
+        raise click.BadParameter(
+            "after-catalog-id must be a UUID returned by the same V2 operation and scope",
+            param_hint="--after-catalog-id",
+        ) from exc
+
+
 def _get_archive_candidate_tenant_ids_by_prefix(
     session: Session,
     prefix: str,
@@ -810,9 +835,11 @@ def backfill_workflow_run_archive_bundles(
         click.echo(click.style(f"  ... and {len(summary.errors) - 10} more failures", fg="red"))
 
 
-def _echo_bundle_archive_operation_summary(summary) -> None:
+def _echo_bundle_archive_operation_summary(summary, *, dry_run: bool) -> None:
     status = "completed successfully" if summary.bundles_failed == 0 else "completed with failures"
     fg = "green" if summary.bundles_failed == 0 else "red"
+    cursor_label = "preview_next_catalog_id" if dry_run else "next_catalog_id"
+    cursor_value = summary.preview_next_catalog_id if dry_run else summary.next_catalog_id
     click.echo(
         click.style(
             f"{summary.operation} {status}. "
@@ -821,10 +848,12 @@ def _echo_bundle_archive_operation_summary(summary) -> None:
             f"archive_bytes={summary.archive_bytes} duration={summary.elapsed_time:.2f}s "
             f"validation_time={summary.validation_time:.2f}s "
             f"runs_per_second={summary.runs_per_second:.2f} rows_per_second={summary.rows_per_second:.2f} "
-            f"bytes_per_second={summary.bytes_per_second:.2f}",
+            f"bytes_per_second={summary.bytes_per_second:.2f} {cursor_label}={cursor_value or 'none'}",
             fg=fg,
         )
     )
+    if dry_run:
+        click.echo(click.style("Dry-run cursor is preview-only; do not persist it for a destructive run.", fg="yellow"))
     click.echo(click.style("table,row_count", fg="white"))
     for table_name in [
         "workflow_runs",
@@ -842,7 +871,8 @@ def _echo_bundle_archive_operation_summary(summary) -> None:
                 click.style(
                     f"  bundle={result.bundle_id} tenant={result.tenant_id} runs={result.run_count} "
                     f"rows={result.row_count} archive_bytes={result.archive_bytes} "
-                    f"time={result.elapsed_time:.2f}s validation={result.validation_time:.2f}s",
+                    f"catalog_id={result.catalog_id} time={result.elapsed_time:.2f}s "
+                    f"validation={result.validation_time:.2f}s",
                     fg="white",
                 )
             )
@@ -850,7 +880,7 @@ def _echo_bundle_archive_operation_summary(summary) -> None:
             click.echo(
                 click.style(
                     f"  failed bundle={result.bundle_id} tenant={result.tenant_id} "
-                    f"object_prefix={result.object_prefix} error={result.error}",
+                    f"catalog_id={result.catalog_id} object_prefix={result.object_prefix} error={result.error}",
                     fg="red",
                 )
             )
@@ -867,25 +897,24 @@ def _echo_bundle_archive_operation_summary(summary) -> None:
 )
 @click.option("--run-id", required=False, help="Workflow run ID to restore.")
 @click.option(
-    "--start-from",
-    type=click.DateTime(formats=["%Y-%m-%d", "%Y-%m-%dT%H:%M:%S"]),
+    "--target-month",
+    metavar="YYYY-MM",
     default=None,
-    help="Optional lower bound (inclusive) for created_at; must be paired with --end-before.",
+    help="V2 catalog month to restore; required unless --run-id is used.",
 )
 @click.option(
-    "--end-before",
-    type=click.DateTime(formats=["%Y-%m-%d", "%Y-%m-%dT%H:%M:%S"]),
+    "--after-catalog-id",
     default=None,
-    help="Optional upper bound (exclusive) for created_at; must be paired with --start-from.",
+    help="Exclusive V2 cursor from the same restore month and tenant scope.",
 )
 @click.option("--workers", default=1, show_default=True, type=int, help="V1 --run-id compatibility only.")
-@click.option("--limit", type=int, default=100, show_default=True, help="Maximum number of V2 bundles to restore.")
+@click.option("--limit", type=click.IntRange(min=1), default=100, show_default=True, help="Maximum V2 catalog rows.")
 @click.option("--dry-run", is_flag=True, help="Preview without restoring.")
 def restore_workflow_runs(
     tenant_ids: str | None,
     run_id: str | None,
-    start_from: datetime.datetime | None,
-    end_before: datetime.datetime | None,
+    target_month: str | None,
+    after_catalog_id: str | None,
     workers: int,
     limit: int,
     dry_run: bool,
@@ -905,23 +934,20 @@ def restore_workflow_runs(
     from services.retention.workflow_run.bundle_archive_maintenance import WorkflowRunBundleArchiveMaintenance
     from services.retention.workflow_run.restore_archived_workflow_run import WorkflowRunRestore
 
-    parsed_tenant_ids = None
-    if tenant_ids:
-        parsed_tenant_ids = [tid.strip() for tid in tenant_ids.split(",") if tid.strip()]
-        if not parsed_tenant_ids:
-            raise click.BadParameter("tenant-ids must not be empty")
+    parsed_tenant_ids = _parse_comma_separated_ids(tenant_ids, param_name="tenant-ids")
 
-    if (start_from is None) ^ (end_before is None):
-        raise click.UsageError("--start-from and --end-before must be provided together.")
-    if run_id is None and (start_from is None or end_before is None):
-        raise click.UsageError("--start-from and --end-before are required for batch restore.")
     if workers < 1:
         raise click.BadParameter("workers must be at least 1")
+    if run_id is not None and (target_month is not None or after_catalog_id is not None):
+        raise click.UsageError("--target-month and --after-catalog-id are only valid for V2 batch restore.")
+    if run_id is None and target_month is None:
+        raise click.UsageError("--target-month is required for V2 batch restore.")
 
     start_time = datetime.datetime.now(datetime.UTC)
+    target_desc = f"workflow run {run_id}" if run_id else f"workflow archive catalog month {target_month}"
     click.echo(
         click.style(
-            f"Starting restore of workflow run {run_id} at {start_time.isoformat()}.",
+            f"Starting restore of {target_desc} at {start_time.isoformat()}.",
             fg="white",
         )
     )
@@ -955,17 +981,20 @@ def restore_workflow_runs(
         click.echo(
             click.style("--workers is ignored for V2 bundle restore; bundles are processed serially.", fg="yellow")
         )
-    assert start_from is not None
-    assert end_before is not None
+    assert target_month is not None
+    target_year, target_month_number = _parse_archive_target_month(target_month)
+    catalog_cursor = _parse_archive_catalog_cursor(after_catalog_id)
     bundle_restorer = WorkflowRunBundleArchiveMaintenance(dry_run=dry_run, strict_content_validation=True)
     summary = bundle_restorer.restore_batch(
         tenant_ids=parsed_tenant_ids,
-        start_date=start_from,
-        end_date=end_before,
+        target_year=target_year,
+        target_month=target_month_number,
+        after_catalog_id=catalog_cursor,
         limit=limit,
     )
-    _echo_bundle_archive_operation_summary(summary)
-    return
+    _echo_bundle_archive_operation_summary(summary, dry_run=dry_run)
+    if summary.bundles_failed:
+        raise click.exceptions.Exit(1)
 
 
 @click.command(
@@ -979,23 +1008,41 @@ def restore_workflow_runs(
 )
 @click.option("--run-id", required=False, help="Workflow run ID to delete.")
 @click.option(
-    "--start-from",
-    type=click.DateTime(formats=["%Y-%m-%d", "%Y-%m-%dT%H:%M:%S"]),
+    "--target-month",
+    metavar="YYYY-MM",
     default=None,
-    help="Optional lower bound (inclusive) for created_at; must be paired with --end-before.",
+    help="V2 catalog month to delete; required unless --run-id is used.",
 )
 @click.option(
-    "--end-before",
-    type=click.DateTime(formats=["%Y-%m-%d", "%Y-%m-%dT%H:%M:%S"]),
+    "--after-catalog-id",
     default=None,
-    help="Optional upper bound (exclusive) for created_at; must be paired with --start-from.",
+    help="Exclusive V2 cursor from the same delete month and tenant scope.",
+)
+@click.option(
+    "--run-shard-index",
+    default=None,
+    type=click.IntRange(min=0),
+    help="Zero-based archive shard index. Must be paired with --run-shard-total.",
+)
+@click.option(
+    "--run-shard-total",
+    default=None,
+    type=click.IntRange(min=1, max=16),
+    help="Total archive shard count. Must be paired with --run-shard-index.",
+)
+@click.option("--all-pages", is_flag=True, help="Process catalog pages until an empty page is reached.")
+@click.option(
+    "--limit",
+    type=click.IntRange(min=1),
+    default=100,
+    show_default=True,
+    help="Maximum V2 catalog rows per page.",
 )
-@click.option("--limit", type=int, default=100, show_default=True, help="Maximum number of V2 bundles to delete.")
 @click.option("--dry-run", is_flag=True, help="Preview without deleting.")
 @click.option(
     "--skip-bad-archives",
     is_flag=True,
-    help="Continue batch deletion when one archive object fails validation.",
+    help="V1 --run-id only: continue when one archive object fails validation.",
 )
 @click.option(
     "--restore-sample-interval",
@@ -1007,8 +1054,11 @@ def restore_workflow_runs(
 def delete_archived_workflow_runs(
     tenant_ids: str | None,
     run_id: str | None,
-    start_from: datetime.datetime | None,
-    end_before: datetime.datetime | None,
+    target_month: str | None,
+    after_catalog_id: str | None,
+    run_shard_index: int | None,
+    run_shard_total: int | None,
+    all_pages: bool,
     limit: int,
     dry_run: bool,
     skip_bad_archives: bool,
@@ -1018,26 +1068,38 @@ def delete_archived_workflow_runs(
     Delete archived workflow runs from the database.
 
     Batch delete uses V2 bundle metadata and validates object existence, manifest schema, object size, checksum, row
-    counts, and source/archive content checksums before deleting source rows. `--run-id` keeps the V1 per-run path.
+    counts, and source/archive content checksums before deleting source rows. Parallel workers may select one exact
+    archive shard; all-pages mode keeps only the current bounded page in memory. `--run-id` keeps the V1 per-run path.
     """
     from services.retention.workflow_run.bundle_archive_maintenance import WorkflowRunBundleArchiveMaintenance
     from services.retention.workflow_run.delete_archived_workflow_run import ArchivedWorkflowRunDeletion
 
-    parsed_tenant_ids = None
-    if tenant_ids:
-        parsed_tenant_ids = [tid.strip() for tid in tenant_ids.split(",") if tid.strip()]
-        if not parsed_tenant_ids:
-            raise click.BadParameter("tenant-ids must not be empty")
+    parsed_tenant_ids = _parse_comma_separated_ids(tenant_ids, param_name="tenant-ids")
 
-    if (start_from is None) ^ (end_before is None):
-        raise click.UsageError("--start-from and --end-before must be provided together.")
-    if run_id is None and (start_from is None or end_before is None):
-        raise click.UsageError("--start-from and --end-before are required for batch delete.")
     if restore_sample_interval < 0:
         raise click.BadParameter("restore-sample-interval must be >= 0")
+    if run_id is not None and (
+        target_month is not None
+        or after_catalog_id is not None
+        or run_shard_index is not None
+        or run_shard_total is not None
+        or all_pages
+    ):
+        raise click.UsageError(
+            "--target-month, --after-catalog-id, --run-shard-index, --run-shard-total, and --all-pages "
+            "are only valid for V2 batch delete."
+        )
+    if run_id is None and target_month is None:
+        raise click.UsageError("--target-month is required for V2 batch delete.")
+    if run_id is None and skip_bad_archives:
+        raise click.UsageError("--skip-bad-archives is not supported for V2 catalog batches; they fail fast.")
+    if (run_shard_index is None) ^ (run_shard_total is None):
+        raise click.UsageError("--run-shard-index and --run-shard-total must be provided together.")
+    if run_shard_index is not None and run_shard_total is not None and run_shard_index >= run_shard_total:
+        raise click.UsageError("--run-shard-index must be less than --run-shard-total.")
 
     start_time = datetime.datetime.now(datetime.UTC)
-    target_desc = f"workflow run {run_id}" if run_id else "workflow runs"
+    target_desc = f"workflow run {run_id}" if run_id else f"workflow archive catalog month {target_month}"
     click.echo(
         click.style(
             f"Starting delete of {target_desc} at {start_time.isoformat()}.",
@@ -1110,20 +1172,104 @@ def delete_archived_workflow_runs(
 
     if restore_sample_interval:
         click.echo(click.style("--restore-sample-interval is ignored for V2 bundle delete.", fg="yellow"))
-    assert start_from is not None
-    assert end_before is not None
-    bundle_deleter = WorkflowRunBundleArchiveMaintenance(
-        dry_run=dry_run,
-        strict_content_validation=True,
-        stop_on_error=not skip_bad_archives,
+    assert target_month is not None
+    target_year, target_month_number = _parse_archive_target_month(target_month)
+    catalog_cursor = _parse_archive_catalog_cursor(after_catalog_id)
+    shard = (
+        f"{run_shard_index:02d}-of-{run_shard_total:02d}"
+        if run_shard_index is not None and run_shard_total is not None
+        else None
     )
-    summary = bundle_deleter.delete_batch(
-        tenant_ids=parsed_tenant_ids,
-        start_date=start_from,
-        end_date=end_before,
-        limit=limit,
-    )
-    _echo_bundle_archive_operation_summary(summary)
+    bundle_deleter = WorkflowRunBundleArchiveMaintenance(dry_run=dry_run, strict_content_validation=True)
+    if run_shard_total is not None:
+        try:
+            bundle_deleter.validate_catalog_shards(
+                target_year=target_year,
+                target_month=target_month_number,
+                shard_total=run_shard_total,
+                tenant_ids=parsed_tenant_ids,
+            )
+        except ValueError as exc:
+            logger.exception(
+                "Archive catalog shard preflight failed: target_month=%s shard=%s",
+                target_month,
+                shard,
+            )
+            raise click.ClickException(
+                f"Archive catalog shard preflight failed for target_month={target_month} shard={shard}: {exc}"
+            ) from exc
+
+    initial_catalog_cursor = catalog_cursor
+    pages_processed = 0
+    bundles_succeeded = 0
+    runs_processed = 0
+    rows_processed = 0
+    archive_bytes = 0
+    while True:
+        summary = bundle_deleter.delete_batch(
+            tenant_ids=parsed_tenant_ids,
+            target_year=target_year,
+            target_month=target_month_number,
+            after_catalog_id=catalog_cursor,
+            limit=limit,
+            shard=shard,
+        )
+        _echo_bundle_archive_operation_summary(summary, dry_run=dry_run)
+        if summary.bundles_failed:
+            failed_result = next((result for result in summary.results if not result.success), None)
+            failed_catalog_id = failed_result.catalog_id if failed_result is not None else "unknown"
+            page_resume_cursor = summary.preview_next_catalog_id if dry_run else summary.next_catalog_id
+            resume_cursor = page_resume_cursor or catalog_cursor
+            if dry_run:
+                cursor_details = (
+                    f"preview_after_catalog_id={resume_cursor or 'none'} "
+                    f"destructive_retry_after_catalog_id={initial_catalog_cursor or 'none'}"
+                )
+            else:
+                cursor_details = f"resume_after_catalog_id={resume_cursor or 'none'}"
+            click.echo(
+                click.style(
+                    f"Delete stopped: target_month={target_month} shard={shard or 'all'} "
+                    f"failed_catalog_id={failed_catalog_id} "
+                    f"{cursor_details}",
+                    fg="red",
+                )
+            )
+            raise click.exceptions.Exit(1)
+
+        if not all_pages:
+            break
+        if summary.bundles_processed == 0:
+            break
+
+        pages_processed += 1
+        bundles_succeeded += summary.bundles_succeeded
+        runs_processed += summary.runs_processed
+        rows_processed += summary.rows_processed
+        archive_bytes += summary.archive_bytes
+        next_catalog_id = summary.preview_next_catalog_id if dry_run else summary.next_catalog_id
+        if next_catalog_id is None or (catalog_cursor is not None and next_catalog_id <= catalog_cursor):
+            click.echo(
+                click.style(
+                    f"Delete cursor did not advance: target_month={target_month} shard={shard or 'all'} "
+                    f"after_catalog_id={catalog_cursor or 'none'} next_catalog_id={next_catalog_id or 'none'}",
+                    fg="red",
+                )
+            )
+            raise click.exceptions.Exit(1)
+        catalog_cursor = next_catalog_id
+
+    if all_pages:
+        final_cursor_label = "preview_final_catalog_id" if dry_run else "final_catalog_id"
+        click.echo(
+            click.style(
+                f"Delete all-pages completed successfully. target_month={target_month} shard={shard or 'all'} "
+                f"pages={pages_processed} bundles_success={bundles_succeeded} runs={runs_processed} "
+                f"rows={rows_processed} archive_bytes={archive_bytes} "
+                f"{final_cursor_label}={catalog_cursor or 'none'}",
+                fg="green",
+            )
+        )
 
 
 def _find_orphaned_draft_variables(batch_size: int = 1000) -> list[str]:

api/configs/enterprise/__init__.py

@@ -14,6 +14,12 @@ class EnterpriseFeatureConfig(BaseSettings):
         default=False,
     )
 
+    WEBAPP_PUBLIC_ACCESS_ENABLED: bool = Field(
+        description="Whether admins are allowed to set a webapp's access mode to public (anyone with the link, "
+        "no auth). Disable in security-sensitive on-prem deployments.",
+        default=True,
+    )
+
     CAN_REPLACE_LOGO: bool = Field(
         description="Allow customization of the enterprise logo.",
         default=False,

api/configs/extra/__init__.py

@@ -1,5 +1,6 @@
 from configs.extra.agent_backend_config import AgentBackendConfig
 from configs.extra.archive_config import ArchiveStorageConfig
+from configs.extra.knowledge_fs_config import KnowledgeFSConfig
 from configs.extra.notion_config import NotionConfig
 from configs.extra.sentry_config import SentryConfig
 
@@ -8,6 +9,7 @@ class ExtraServiceConfig(
     # place the configs in alphabet order
     AgentBackendConfig,
     ArchiveStorageConfig,
+    KnowledgeFSConfig,
     NotionConfig,
     SentryConfig,
 ):

api/configs/extra/agent_backend_config.py

@@ -1,4 +1,4 @@
-from pydantic import Field, NonNegativeFloat
+from pydantic import Field, NonNegativeFloat, NonNegativeInt, PositiveFloat
 from pydantic_settings import BaseSettings
 
 
@@ -22,6 +22,21 @@ class AgentBackendConfig(BaseSettings):
         default="success",
     )
 
+    AGENT_BACKEND_STREAM_READ_TIMEOUT_SECONDS: PositiveFloat = Field(
+        description="Read timeout for one Agent backend SSE connection.",
+        default=30,
+    )
+
+    AGENT_BACKEND_STREAM_MAX_RECONNECTS: NonNegativeInt = Field(
+        description="Maximum Agent backend SSE reconnects before failing the run.",
+        default=3,
+    )
+
+    AGENT_BACKEND_RUN_TIMEOUT_SECONDS: PositiveFloat = Field(
+        description="Total deadline for one Agent backend run event stream.",
+        default=1200,
+    )
+
     AGENT_SHELL_ENABLED: bool = Field(
         description=(
             "Inject the dify.shell layer (sandboxed bash workspace) into Agent runs. "

api/configs/extra/knowledge_fs_config.py

@@ -0,0 +1,64 @@
+"""Configuration for the optional KnowledgeFS Console bridge."""
+
+from urllib.parse import urlsplit
+
+from pydantic import Field, PositiveFloat, SecretStr, field_validator, model_validator
+from pydantic_settings import BaseSettings
+
+
+class KnowledgeFSConfig(BaseSettings):
+    """Server-only settings for the KnowledgeFS production connection."""
+
+    KNOWLEDGE_FS_ENABLED: bool = Field(
+        default=False,
+        description="Enable the private KnowledgeFS Console bridge.",
+    )
+    KNOWLEDGE_FS_BASE_URL: str | None = Field(default=None, description="KnowledgeFS gateway base URL.")
+    KNOWLEDGE_FS_JWT_SECRET: SecretStr | None = Field(
+        default=None,
+        min_length=32,
+        description="Shared secret used to sign short-lived KnowledgeFS service JWTs.",
+    )
+    KNOWLEDGE_FS_SSE_READ_TIMEOUT_SECONDS: PositiveFloat = Field(default=300.0, le=3600.0, allow_inf_nan=False)
+    KNOWLEDGE_FS_TIMEOUT_SECONDS: PositiveFloat = Field(default=10.0, le=60.0, allow_inf_nan=False)
+
+    @field_validator(
+        "KNOWLEDGE_FS_BASE_URL",
+        "KNOWLEDGE_FS_JWT_SECRET",
+        mode="before",
+    )
+    @classmethod
+    def normalize_optional_string(cls, value: object) -> object:
+        if isinstance(value, SecretStr):
+            normalized = value.get_secret_value().strip()
+            return SecretStr(normalized) if normalized else None
+        if isinstance(value, str):
+            normalized = value.strip()
+            return normalized or None
+        return value
+
+    @field_validator("KNOWLEDGE_FS_BASE_URL")
+    @classmethod
+    def validate_base_url(cls, value: str | None) -> str | None:
+        if value is None:
+            return None
+        parsed = urlsplit(value)
+        if parsed.scheme not in {"http", "https"} or not parsed.netloc:
+            raise ValueError("KNOWLEDGE_FS_BASE_URL must be an absolute HTTP(S) URL")
+        try:
+            _ = parsed.port
+        except ValueError as exc:
+            raise ValueError("KNOWLEDGE_FS_BASE_URL must include a valid port") from exc
+        if parsed.username or parsed.password or parsed.query or parsed.fragment:
+            raise ValueError("KNOWLEDGE_FS_BASE_URL must not include credentials, query, or fragment")
+        return value.rstrip("/")
+
+    @model_validator(mode="after")
+    def validate_enabled_connection(self) -> "KnowledgeFSConfig":
+        if not self.KNOWLEDGE_FS_ENABLED:
+            return self
+        if bool(self.KNOWLEDGE_FS_BASE_URL) != bool(self.KNOWLEDGE_FS_JWT_SECRET):
+            raise ValueError("KNOWLEDGE_FS_BASE_URL and KNOWLEDGE_FS_JWT_SECRET must be configured together")
+        if not self.KNOWLEDGE_FS_BASE_URL:
+            raise ValueError("KnowledgeFS connection settings are required when the integration is enabled")
+        return self

api/configs/feature/__init__.py

@@ -1,4 +1,4 @@
-from datetime import timedelta
+from datetime import datetime, timedelta
 from enum import StrEnum
 from typing import Literal
 
@@ -11,6 +11,7 @@ from pydantic import (
     PositiveFloat,
     PositiveInt,
     computed_field,
+    field_validator,
 )
 from pydantic_settings import BaseSettings
 
@@ -275,6 +276,63 @@ class PluginConfig(BaseSettings):
         default=50 * 1024 * 1024,
     )
 
+    NEW_USER_DEFAULT_PLUGIN_IDS: str = Field(
+        description="Comma-separated marketplace plugin IDs whose latest versions are installed for new users",
+        default="",
+    )
+
+    @field_validator("PLUGIN_REMOTE_INSTALL_PORT", mode="before")
+    @classmethod
+    def _reject_host_port_shaped_plugin_remote_install_port(cls, v):
+        """Reject ``host:port``-shaped values with an actionable hint.
+
+        ``EXPOSE_PLUGIN_DEBUGGING_PORT`` is overloaded: it feeds both the
+        plugin_daemon ``ports:`` mapping (where ``127.0.0.1:5003`` is valid
+        compose syntax) and this integer app setting advertised in the console.
+        Without this guard a loopback bind spec crashloops the api container
+        with an opaque ``int_parsing`` traceback. See issue #39323.
+        """
+        if isinstance(v, str) and ":" in v.strip():
+            raise ValueError(
+                "PLUGIN_REMOTE_INSTALL_PORT must be a bare port number, got "
+                f"{v!r}. A 'host:port' value usually means "
+                "EXPOSE_PLUGIN_DEBUGGING_PORT was set to a compose publish spec "
+                "like '127.0.0.1:5003'; bind loopback via a "
+                "docker-compose.override.yaml instead of overloading this var."
+            )
+        return v
+
+    @property
+    def NEW_USER_DEFAULT_PLUGIN_ID_LIST(self) -> list[str]:
+        return [item.strip() for item in self.NEW_USER_DEFAULT_PLUGIN_IDS.split(",") if item.strip()]
+
+    NEW_USER_DEFAULT_MODELS: str = Field(
+        description=("Comma-separated default models for new users in 'model_type:provider:model' format"),
+        default="",
+    )
+
+    @property
+    def NEW_USER_DEFAULT_MODEL_LIST(self) -> list[tuple[str, str, str]]:
+        default_models: list[tuple[str, str, str]] = []
+        configured_model_types: set[str] = set()
+
+        for item in self.NEW_USER_DEFAULT_MODELS.split(","):
+            if not item.strip():
+                continue
+
+            parts = tuple(part.strip() for part in item.split(":", 2))
+            if len(parts) != 3 or not all(parts):
+                raise ValueError("NEW_USER_DEFAULT_MODELS entries must use 'model_type:provider:model' format")
+
+            model_type, provider, model = parts
+            if model_type in configured_model_types:
+                raise ValueError(f"NEW_USER_DEFAULT_MODELS contains duplicate model type: {model_type}")
+
+            configured_model_types.add(model_type)
+            default_models.append((model_type, provider, model))
+
+        return default_models
+
 
 class MarketplaceConfig(BaseSettings):
     """
@@ -784,6 +842,11 @@ class WorkflowConfig(BaseSettings):
         default=500,
     )
 
+    WORKFLOW_GENERATOR_NODE_BUILDER_MAX_WORKERS: PositiveInt = Field(
+        description="Maximum concurrent node-builder LLM calls per workflow generation request",
+        default=6,
+    )
+
     WORKFLOW_MAX_EXECUTION_TIME: PositiveInt = Field(
         description="Maximum execution time in seconds for a single workflow",
         default=1200,
@@ -1097,6 +1160,16 @@ class HomepageConfig(BaseSettings):
         default=True,
     )
 
+    ENABLE_STEP_BY_STEP_TOUR: bool = Field(
+        description="Enable account-level Step-by-step Tour eligibility checks",
+        default=False,
+    )
+
+    STEP_BY_STEP_TOUR_ROLLOUT_STARTED_AT: datetime | None = Field(
+        description="UTC timestamp after which newly initialized accounts are eligible for Step-by-step Tour",
+        default=None,
+    )
+
 
 class RagEtlConfig(BaseSettings):
     """

api/controllers/console/__init__.py

@@ -38,7 +38,9 @@ from . import (
     feature,
     human_input_form,
     init_validate,
+    knowledge_fs_proxy,
     notification,
+    onboarding,
     ping,
     setup,
     spec,
@@ -195,6 +197,7 @@ __all__ = [
     "human_input_form",
     "init_validate",
     "installed_app",
+    "knowledge_fs_proxy",
     "load_balancing_config",
     "login",
     "mcp_server",
@@ -207,6 +210,7 @@ __all__ = [
     "notification",
     "oauth",
     "oauth_server",
+    "onboarding",
     "ops_trace",
     "parameter",
     "ping",

api/controllers/console/app/workflow.py

@@ -105,6 +105,7 @@ class SyncDraftWorkflowPayload(BaseModel):
     graph: dict[str, Any]
     features: dict[str, Any]
     hash: str | None = None
+    is_collaborative: bool = Field(default=False, alias="_is_collaborative")
     environment_variables: list[dict[str, Any]] = Field(
         default_factory=list,
     )
@@ -610,6 +611,7 @@ class DraftWorkflowApi(Resource):
                 environment_variables=environment_variables,
                 conversation_variables=conversation_variables,
                 session=db.session(),
+                graph_only=args["is_collaborative"],
             )
         except WorkflowHashNotEqualError:
             raise DraftWorkflowNotSync()

api/controllers/console/datasets/datasets.py

@@ -607,6 +607,13 @@ class DatasetListApi(Resource):
                     ReplaceMemberBindings(scope=RBACResourceWhitelistScope.ALL),
                 )
                 initialize_created_app_rbac_access_task.delay(current_tenant_id, current_user.id, dataset_id=dataset.id)
+            else:
+                enterprise_rbac_service.RBACService.DatasetAccess.replace_whitelist(
+                    current_tenant_id,
+                    current_user.id,
+                    dataset.id,
+                    ReplaceMemberBindings(scope=RBACResourceWhitelistScope.SPECIFIC),
+                )
 
         permission_keys_map = enterprise_rbac_service.RBACService.DatasetPermissions.batch_get(
             current_tenant_id,
@@ -875,7 +882,7 @@ class DatasetIndexingEstimateApi(Resource):
                 file_details = session.scalars(
                     select(UploadFile).where(UploadFile.tenant_id == current_tenant_id, UploadFile.id.in_(file_ids))
                 ).all()
-                if file_details is None:
+                if not file_details:
                     raise NotFound("File not found.")
 
                 if file_details:

api/controllers/console/explore/trial.py

@@ -47,7 +47,9 @@ from controllers.console.explore.error import (
     NotWorkflowAppError,
 )
 from controllers.console.explore.wraps import TrialAppResource, trial_feature_enable
-from controllers.console.wraps import with_current_user
+from controllers.console.files import FILE_UPLOAD_PARAMS, upload_file_from_request
+from controllers.console.remote_files import RemoteFileUploadPayload, upload_remote_file_from_request
+from controllers.console.wraps import cloud_edition_billing_resource_check, with_current_user
 from controllers.web.error import InvokeRateLimitError as InvokeRateLimitHttpError
 from core.app.app_config.common.parameters_mapping import get_parameters_from_feature_dict
 from core.app.apps.base_app_queue_manager import AppQueueManager
@@ -61,12 +63,13 @@ from extensions.ext_database import db
 from extensions.ext_redis import redis_client
 from fields.base import ResponseModel
 from fields.conversation_variable_fields import WorkflowConversationVariableResponse
+from fields.file_fields import FileResponse, FileWithSignedUrl
 from fields.message_fields import SuggestedQuestionsResponse
 from graphon.graph_engine.manager import GraphEngineManager
 from graphon.model_runtime.errors.invoke import InvokeError
 from libs import helper
 from libs.helper import dump_response, to_timestamp, uuid_value
-from models import Account
+from models import Account, App
 from models.account import TenantStatus
 from models.model import AppMode, Site, load_annotation_reply_config
 from models.workflow import Workflow
@@ -428,6 +431,36 @@ register_response_schema_models(
 simple_account_model = console_ns.models[TrialSimpleAccount.__name__]
 
 
+class TrialAppFileUploadApi(TrialAppResource):
+    @trial_feature_enable
+    @cloud_edition_billing_resource_check("documents")
+    @console_ns.doc(consumes=["multipart/form-data"], params=FILE_UPLOAD_PARAMS)
+    @console_ns.response(201, "File uploaded successfully", console_ns.models[FileResponse.__name__])
+    @with_current_user
+    def post(self, current_user: Account, app_model: App):
+        """Upload a file into the tenant that owns the trial app."""
+        upload_file = upload_file_from_request(
+            current_user=current_user,
+            resource_tenant_id=app_model.tenant_id,
+        )
+        return dump_response(FileResponse, upload_file), 201
+
+
+class TrialAppRemoteFileUploadApi(TrialAppResource):
+    @trial_feature_enable
+    @cloud_edition_billing_resource_check("documents")
+    @console_ns.expect(console_ns.models[RemoteFileUploadPayload.__name__])
+    @console_ns.response(201, "File uploaded successfully", console_ns.models[FileWithSignedUrl.__name__])
+    @with_current_user
+    def post(self, current_user: Account, app_model: App):
+        """Upload a remote file into the tenant that owns the trial app."""
+        remote_file = upload_remote_file_from_request(
+            current_user=current_user,
+            resource_tenant_id=app_model.tenant_id,
+        )
+        return remote_file.model_dump(mode="json"), 201
+
+
 class TrialAppWorkflowRunApi(TrialAppResource):
     @trial_feature_enable
     @console_ns.expect(console_ns.models[WorkflowRunRequest.__name__])
@@ -612,7 +645,7 @@ class TrialChatAudioApi(TrialAppResource):
     def post(self, current_user: Account, trial_app):
         app_model = trial_app
 
-        file = request.files["file"]
+        file = request.files.get("file")
 
         try:
             # Get IDs before they might be detached from session
@@ -887,6 +920,18 @@ class DatasetListApi(Resource):
 
 console_ns.add_resource(TrialChatApi, "/trial-apps/<uuid:app_id>/chat-messages", endpoint="trial_app_chat_completion")
 
+console_ns.add_resource(
+    TrialAppFileUploadApi,
+    "/trial-apps/<uuid:app_id>/files/upload",
+    endpoint="trial_app_file_upload",
+)
+
+console_ns.add_resource(
+    TrialAppRemoteFileUploadApi,
+    "/trial-apps/<uuid:app_id>/remote-files/upload",
+    endpoint="trial_app_remote_file_upload",
+)
+
 console_ns.add_resource(
     TrialMessageSuggestedQuestionApi,
     "/trial-apps/<uuid:app_id>/messages/<uuid:message_id>/suggested-questions",

api/controllers/console/files.py

@@ -29,7 +29,7 @@ from extensions.ext_database import db
 from fields.file_fields import FileResponse, UploadConfig
 from libs.helper import dump_response
 from libs.login import login_required
-from models import Account
+from models import Account, UploadFile
 from services.file_service import FileService
 
 from . import console_ns
@@ -39,7 +39,7 @@ register_response_schema_models(console_ns, AllowedExtensionsResponse, TextConte
 
 PREVIEW_WORDS_LIMIT = 3000
 
-_FILE_UPLOAD_PARAMS = {
+FILE_UPLOAD_PARAMS = {
     "file": {
         "description": "File to upload",
         "in": "formData",
@@ -56,6 +56,43 @@ _FILE_UPLOAD_PARAMS = {
 }
 
 
+def upload_file_from_request(*, current_user: Account, resource_tenant_id: str | None = None) -> UploadFile:
+    """Validate the multipart request and persist the file under the requested resource tenant."""
+    source_str = request.form.get("source")
+    source: Literal["datasets"] | None = "datasets" if source_str == "datasets" else None
+
+    if "file" not in request.files:
+        raise NoFileUploadedError()
+
+    if len(request.files) > 1:
+        raise TooManyFilesError()
+    file = request.files["file"]
+
+    if not file.filename:
+        raise FilenameNotExistsError
+    if source == "datasets" and not current_user.is_dataset_editor:
+        raise Forbidden()
+
+    if source not in ("datasets", None):
+        source = None
+
+    try:
+        return FileService(db.engine).upload_file(
+            filename=file.filename,
+            content=file.stream.read(),
+            mimetype=file.mimetype,
+            user=current_user,
+            tenant_id=resource_tenant_id,
+            source=source,
+        )
+    except services.errors.file.FileTooLargeError as file_too_large_error:
+        raise FileTooLargeError(file_too_large_error.description)
+    except services.errors.file.UnsupportedFileTypeError:
+        raise UnsupportedFileTypeError()
+    except services.errors.file.BlockedFileExtensionError as blocked_extension_error:
+        raise BlockedFileExtensionError(blocked_extension_error.description)
+
+
 @console_ns.route("/files/upload")
 class FileApi(Resource):
     @setup_required
@@ -81,42 +118,11 @@ class FileApi(Resource):
     @login_required
     @account_initialization_required
     @cloud_edition_billing_resource_check("documents")
-    @console_ns.doc(consumes=["multipart/form-data"], params=_FILE_UPLOAD_PARAMS)
+    @console_ns.doc(consumes=["multipart/form-data"], params=FILE_UPLOAD_PARAMS)
     @console_ns.response(201, "File uploaded successfully", console_ns.models[FileResponse.__name__])
     @with_current_user
     def post(self, current_user: Account):
-        source_str = request.form.get("source")
-        source: Literal["datasets"] | None = "datasets" if source_str == "datasets" else None
-
-        if "file" not in request.files:
-            raise NoFileUploadedError()
-
-        if len(request.files) > 1:
-            raise TooManyFilesError()
-        file = request.files["file"]
-
-        if not file.filename:
-            raise FilenameNotExistsError
-        if source == "datasets" and not current_user.is_dataset_editor:
-            raise Forbidden()
-
-        if source not in ("datasets", None):
-            source = None
-
-        try:
-            upload_file = FileService(db.engine).upload_file(
-                filename=file.filename,
-                content=file.stream.read(),
-                mimetype=file.mimetype,
-                user=current_user,
-                source=source,
-            )
-        except services.errors.file.FileTooLargeError as file_too_large_error:
-            raise FileTooLargeError(file_too_large_error.description)
-        except services.errors.file.UnsupportedFileTypeError:
-            raise UnsupportedFileTypeError()
-        except services.errors.file.BlockedFileExtensionError as blocked_extension_error:
-            raise BlockedFileExtensionError(blocked_extension_error.description)
+        upload_file = upload_file_from_request(current_user=current_user)
 
         return dump_response(FileResponse, upload_file), 201
 

api/controllers/console/knowledge_fs_proxy.py

@@ -0,0 +1,332 @@
+"""Authenticated transport adapter for the Console-to-KnowledgeFS proxy.
+
+These raw Blueprint routes deliberately stay outside Dify's OpenAPI surface:
+KnowledgeFS owns the wire contract consumed by the frontend. The catch-all path
+avoids resource-specific Dify controllers, while the forwarding module consumes
+only the operations explicitly enabled by Dify's product registry. The registry
+can be validated explicitly against the pinned KnowledgeFS contract during development.
+Console auth and contract-specific dataset RBAC run before forwarding. Request
+bodies are capped at 64 MiB, JSON and binary responses have separate bounds,
+SSE responses remain streaming with a bounded idle read timeout, and only safe
+response headers are exposed. Upstream 401 responses become 502 so they cannot
+trigger Dify browser-session recovery; resource-level 403 responses remain 403.
+"""
+
+from __future__ import annotations
+
+import logging
+from collections.abc import Callable, Iterator
+from functools import wraps
+from http import HTTPStatus
+from typing import NoReturn, cast
+
+import httpx
+from flask import Response, request, stream_with_context
+from flask.typing import ResponseReturnValue
+from werkzeug.exceptions import (
+    BadGateway,
+    Forbidden,
+    GatewayTimeout,
+    NotFound,
+    RequestEntityTooLarge,
+    ServiceUnavailable,
+)
+
+from configs import dify_config
+from controllers.console import api, bp
+from controllers.console.wraps import (
+    account_initialization_required,
+    cloud_edition_billing_rate_limit_check,
+    setup_required,
+)
+from core.helper import ssrf_proxy
+from libs.login import current_account_with_tenant, login_required
+from services.knowledge_fs_proxy import (
+    KnowledgeFSAccessDeniedError,
+    KnowledgeFSConfigurationError,
+    KnowledgeFSMethod,
+    KnowledgeFSRouteNotAllowedError,
+    KnowledgeFSTimeoutError,
+    KnowledgeFSTransportError,
+    KnowledgeFSUpstreamResponse,
+    authorize_knowledge_fs_request,
+    get_knowledge_fs_operation,
+    proxy_knowledge_fs_request,
+)
+
+logger = logging.getLogger(__name__)
+
+_MAX_PROXY_BODY_BYTES = 64 * 1024 * 1024
+_RESPONSE_HEADER_ALLOWLIST = (
+    "Cache-Control",
+    "Content-Disposition",
+    "Content-Type",
+    "Retry-After",
+    "X-Trace-Id",
+)
+_RESPONSE_HEADER_DENYLIST = frozenset(
+    {
+        "authorization",
+        "connection",
+        "cookie",
+        "keep-alive",
+        "proxy-authenticate",
+        "proxy-authorization",
+        "set-cookie",
+        "te",
+        "trailer",
+        "transfer-encoding",
+        "upgrade",
+    }
+)
+
+
+def _console_api_errors[**P](
+    view: Callable[P, ResponseReturnValue],
+) -> Callable[P, ResponseReturnValue]:
+    """Route raw Blueprint exceptions through the Console API JSON handlers."""
+
+    @wraps(view)
+    def decorated(*args: P.args, **kwargs: P.kwargs) -> ResponseReturnValue:
+        try:
+            return view(*args, **kwargs)
+        except Exception as exc:
+            return api.handle_error(exc)
+
+    return decorated
+
+
+def _knowledge_fs_enabled[**P](
+    view: Callable[P, ResponseReturnValue],
+) -> Callable[P, ResponseReturnValue]:
+    """Hide the complete KnowledgeFS route surface while the bridge is disabled."""
+
+    @wraps(view)
+    def decorated(*args: P.args, **kwargs: P.kwargs) -> ResponseReturnValue:
+        if not dify_config.KNOWLEDGE_FS_ENABLED:
+            raise NotFound()
+        return view(*args, **kwargs)
+
+    return decorated
+
+
+def _translate_proxy_error(exc: Exception, *, tenant_id: str) -> NoReturn:
+    """Map forwarding failures to the stable Console HTTP error surface."""
+    if isinstance(exc, KnowledgeFSRouteNotAllowedError):
+        raise NotFound() from exc
+    if isinstance(exc, KnowledgeFSAccessDeniedError):
+        raise Forbidden() from exc
+    if isinstance(exc, KnowledgeFSConfigurationError):
+        logger.error("KnowledgeFS request was blocked by invalid configuration for tenant_id=%s", tenant_id)
+        raise ServiceUnavailable("KnowledgeFS integration is misconfigured") from exc
+    if isinstance(exc, KnowledgeFSTimeoutError):
+        raise GatewayTimeout("KnowledgeFS request timed out") from exc
+    if isinstance(exc, KnowledgeFSTransportError):
+        logger.warning("KnowledgeFS transport request failed for tenant_id=%s", tenant_id)
+        raise BadGateway("KnowledgeFS is unavailable") from exc
+    raise exc
+
+
+def _knowledge_fs_operation_access_required(
+    view: Callable[[KnowledgeFSMethod, str], ResponseReturnValue],
+) -> Callable[[KnowledgeFSMethod, str], ResponseReturnValue]:
+    """Authorize one declared operation before billing and request-body work."""
+
+    @wraps(view)
+    def decorated(method: KnowledgeFSMethod, upstream_path: str) -> ResponseReturnValue:
+        try:
+            operation = get_knowledge_fs_operation(method, upstream_path)
+        except KnowledgeFSRouteNotAllowedError as exc:
+            raise NotFound() from exc
+
+        current_user, tenant_id = current_account_with_tenant()
+        try:
+            authorize_knowledge_fs_request(
+                account=current_user,
+                tenant_id=tenant_id,
+                operation=operation,
+            )
+        except KnowledgeFSAccessDeniedError as exc:
+            _translate_proxy_error(exc, tenant_id=tenant_id)
+        return view(method, upstream_path)
+
+    return decorated
+
+
+def _request_body() -> bytes:
+    """Read the raw body up to the proxy limit or raise RequestEntityTooLarge."""
+    body = request.stream.read(_MAX_PROXY_BODY_BYTES + 1)
+    if len(body) > _MAX_PROXY_BODY_BYTES:
+        raise RequestEntityTooLarge("KnowledgeFS proxy request body is too large")
+    return body
+
+
+def _stream_response_body(
+    upstream: httpx.Response,
+    *,
+    tenant_id: str,
+    max_response_bytes: int,
+) -> Iterator[bytes]:
+    """Yield one bounded SSE response and always release its pooled connection."""
+    total_bytes = 0
+    try:
+        for chunk in upstream.iter_bytes():
+            total_bytes += len(chunk)
+            if total_bytes > max_response_bytes:
+                logger.warning("KnowledgeFS stream exceeded the proxy limit for tenant_id=%s", tenant_id)
+                raise ssrf_proxy.ResponseTooLargeError(f"response exceeded {max_response_bytes} bytes")
+            yield chunk
+    finally:
+        upstream.close()
+
+
+def _proxy_response(
+    upstream_result: KnowledgeFSUpstreamResponse,
+    *,
+    tenant_id: str,
+    contract_response_headers: tuple[str, ...],
+    max_response_bytes: int,
+) -> Response:
+    """Expose raw content, status, and allowlisted headers from KnowledgeFS.
+
+    Raises:
+        BadGateway: KnowledgeFS rejects the configured server credential.
+        Forbidden: KnowledgeFS denies the account access to the requested resource.
+    """
+    upstream = upstream_result.response
+    if upstream.status_code == HTTPStatus.UNAUTHORIZED:
+        upstream.close()
+        logger.error(
+            "KnowledgeFS rejected the Dify server credential with HTTP %s for tenant_id=%s",
+            upstream.status_code,
+            tenant_id,
+        )
+        raise BadGateway("KnowledgeFS authentication failed")
+    if upstream.status_code == HTTPStatus.FORBIDDEN:
+        upstream.close()
+        raise Forbidden()
+
+    allowed_header_names = dict.fromkeys(
+        name.lower() for name in (*_RESPONSE_HEADER_ALLOWLIST, *contract_response_headers)
+    )
+    headers = {
+        name: value
+        for name in allowed_header_names
+        if name not in _RESPONSE_HEADER_DENYLIST
+        if (value := upstream.headers.get(name)) is not None
+    }
+    if upstream_result.response_kind == "stream":
+        response = Response(
+            stream_with_context(  # pyrefly: ignore[no-matching-overload]
+                _stream_response_body(
+                    upstream,
+                    tenant_id=tenant_id,
+                    max_response_bytes=max_response_bytes,
+                )
+            ),
+            status=upstream.status_code,
+            headers=headers,
+        )
+        response.call_on_close(upstream.close)
+        return response
+
+    try:
+        content = upstream.content
+    finally:
+        upstream.close()
+    return Response(content, status=upstream.status_code, headers=headers)
+
+
+def _proxy_request(method: KnowledgeFSMethod, upstream_path: str) -> Response:
+    """Forward the current raw request and return its filtered upstream response.
+
+    The call performs one outbound KnowledgeFS request. Integration failures are
+    converted to Console HTTP exceptions for the outer JSON error adapter.
+    """
+    if not dify_config.KNOWLEDGE_FS_ENABLED:
+        raise NotFound()
+    current_user, tenant_id = current_account_with_tenant()
+    try:
+        proxy_result = proxy_knowledge_fs_request(
+            account=current_user,
+            method=method,
+            path=upstream_path,
+            tenant_id=tenant_id,
+            accept=request.headers.get("Accept"),
+            content_type=request.content_type,
+            query=request.query_string or None,
+            body=_request_body() if method != "GET" else None,
+            request_headers=request.headers,
+        )
+    except (
+        KnowledgeFSConfigurationError,
+        KnowledgeFSAccessDeniedError,
+        KnowledgeFSRouteNotAllowedError,
+        KnowledgeFSTimeoutError,
+        KnowledgeFSTransportError,
+    ) as exc:
+        _translate_proxy_error(exc, tenant_id=tenant_id)
+    return _proxy_response(
+        proxy_result,
+        tenant_id=tenant_id,
+        contract_response_headers=proxy_result.operation.response_headers,
+        max_response_bytes=proxy_result.operation.max_response_bytes,
+    )
+
+
+@_knowledge_fs_enabled
+@_knowledge_fs_operation_access_required
+@cloud_edition_billing_rate_limit_check("knowledge")
+def _proxy_knowledge_fs_non_get(
+    method: KnowledgeFSMethod,
+    upstream_path: str,
+) -> ResponseReturnValue:
+    """Apply knowledge billing checks to one allowlisted non-GET operation."""
+    return _proxy_request(method, upstream_path)
+
+
+@bp.route(
+    "/knowledge-fs/<path:upstream_path>",
+    methods=["GET", "OPTIONS"],
+    provide_automatic_options=False,
+)
+@_console_api_errors
+@_knowledge_fs_enabled
+@setup_required
+@login_required
+@account_initialization_required
+def proxy_knowledge_fs_get(upstream_path: str) -> ResponseReturnValue:
+    """Forward one authenticated, dataset-readable GET request.
+
+    Args:
+        upstream_path: Relative KFS path captured after the Console proxy prefix.
+
+    Returns:
+        The filtered raw KnowledgeFS response or a Console JSON error response.
+    """
+    if request.method != "GET":
+        raise NotFound()
+    return _proxy_request("GET", upstream_path)
+
+
+@bp.route(
+    "/knowledge-fs/<path:upstream_path>",
+    methods=["DELETE", "PATCH", "POST", "PUT"],
+    provide_automatic_options=False,
+)
+@_console_api_errors
+@_knowledge_fs_enabled
+@setup_required
+@login_required
+@account_initialization_required
+def proxy_knowledge_fs_write(upstream_path: str) -> ResponseReturnValue:
+    """Forward one authenticated non-GET request under its contract access policy.
+
+    Args:
+        upstream_path: Relative KFS path captured after the Console proxy prefix.
+
+    Returns:
+        The filtered raw KnowledgeFS response or a Console JSON error response.
+    """
+    method = cast(KnowledgeFSMethod, request.method)
+    return _proxy_knowledge_fs_non_get(method, upstream_path)

api/controllers/console/onboarding.py

@@ -0,0 +1,106 @@
+"""Console onboarding APIs.
+
+This module keeps Step-by-step Tour persistence account-scoped. Workspace IDs
+are accepted only as presentation overrides; UI-only state such as minimized
+panels or the currently active task stays on the frontend. PATCH requests are
+action-based so callers do not replace server-side arrays with stale snapshots.
+"""
+
+from datetime import datetime
+from typing import Literal, cast
+
+from flask_restx import Resource
+from pydantic import BaseModel, ConfigDict, Field, model_validator
+
+from controllers.common.schema import register_response_schema_models, register_schema_models
+from extensions.ext_database import db
+from fields.base import ResponseModel
+from libs.helper import dump_response
+from libs.login import login_required
+from models import Account
+from services.step_by_step_tour_service import StepByStepTourPatch, StepByStepTourService
+
+from . import console_ns
+from .wraps import account_initialization_required, setup_required, with_current_tenant_id, with_current_user
+
+StepByStepTourAction = Literal[
+    "skip",
+    "complete_task",
+    "uncomplete_task",
+    "enable_current_workspace",
+    "disable_current_workspace",
+]
+StepByStepTourTaskId = Literal["home", "studio", "knowledge", "integration"]
+
+
+class StepByStepTourStatePatchPayload(BaseModel):
+    action: StepByStepTourAction = Field(description="State update action")
+    task_id: StepByStepTourTaskId | None = Field(default=None, description="Task ID for task actions")
+
+    model_config = ConfigDict(extra="forbid")
+
+    @model_validator(mode="after")
+    def validate_patch_shape(self) -> "StepByStepTourStatePatchPayload":
+        task_actions = {"complete_task", "uncomplete_task"}
+        if self.action in task_actions and self.task_id is None:
+            raise ValueError("task_id is required for task actions")
+        if self.action not in task_actions and self.task_id is not None:
+            raise ValueError("task_id is only supported for task actions")
+
+        return self
+
+
+class StepByStepTourStateResponse(ResponseModel):
+    first_workspace_id: str | None = None
+    skipped: bool = False
+    completed_task_ids: list[StepByStepTourTaskId] = Field(default_factory=list)
+    manually_enabled_workspace_ids: list[str] = Field(default_factory=list)
+    manually_disabled_workspace_ids: list[str] = Field(default_factory=list)
+    updated_at: datetime | None = None
+
+
+register_schema_models(console_ns, StepByStepTourStatePatchPayload)
+register_response_schema_models(console_ns, StepByStepTourStateResponse)
+
+
+@console_ns.route("/onboarding/step-by-step-tour/state")
+class StepByStepTourStateApi(Resource):
+    @console_ns.doc("get_step_by_step_tour_state")
+    @console_ns.doc(description="Get account-level Step-by-step Tour state")
+    @console_ns.response(200, "Success", console_ns.models[StepByStepTourStateResponse.__name__])
+    @setup_required
+    @login_required
+    @account_initialization_required
+    @with_current_user
+    @with_current_tenant_id
+    def get(self, current_tenant_id: str, current_user: Account):
+        return dump_response(
+            StepByStepTourStateResponse,
+            StepByStepTourService.get_state(
+                account=current_user,
+                current_tenant_id=current_tenant_id,
+                session=db.session,
+            ),
+        )
+
+    @console_ns.doc("patch_step_by_step_tour_state")
+    @console_ns.doc(description="Update account-level Step-by-step Tour state")
+    @console_ns.expect(console_ns.models[StepByStepTourStatePatchPayload.__name__])
+    @console_ns.response(200, "Success", console_ns.models[StepByStepTourStateResponse.__name__])
+    @setup_required
+    @login_required
+    @account_initialization_required
+    @with_current_user
+    @with_current_tenant_id
+    def patch(self, current_tenant_id: str, current_user: Account):
+        payload = StepByStepTourStatePatchPayload.model_validate(console_ns.payload or {})
+        patch = cast(StepByStepTourPatch, payload.model_dump(exclude_unset=True, exclude_none=True))
+        return dump_response(
+            StepByStepTourStateResponse,
+            StepByStepTourService.patch_state(
+                account=current_user,
+                current_tenant_id=current_tenant_id,
+                patch=patch,
+                session=db.session,
+            ),
+        )

api/controllers/console/remote_files.py

@@ -46,6 +46,61 @@ class GetRemoteFileInfo(Resource):
         ).model_dump(mode="json")
 
 
+def upload_remote_file_from_request(
+    *,
+    current_user: Account,
+    resource_tenant_id: str | None = None,
+) -> FileWithSignedUrl:
+    """Validate the JSON request, fetch its remote file, and persist it under the requested tenant."""
+    payload = RemoteFileUploadPayload.model_validate(console_ns.payload)
+    url = payload.url
+
+    # Try to fetch remote file metadata/content first
+    try:
+        resp = remote_fetcher.make_request("HEAD", url=url)
+        if resp.status_code != httpx.codes.OK:
+            resp = remote_fetcher.make_request("GET", url=url, timeout=3, follow_redirects=True)
+        if resp.status_code != httpx.codes.OK:
+            # Normalize into a user-friendly error message expected by tests
+            raise RemoteFileUploadError(f"Failed to fetch file from {url}: {resp.text}")
+    except httpx.RequestError as e:
+        raise RemoteFileUploadError(f"Failed to fetch file from {url}: {str(e)}")
+
+    file_info = helpers.guess_file_info_from_response(resp)
+
+    # Enforce file size limit with 400 (Bad Request) per tests' expectation
+    if not FileService.is_file_size_within_limit(extension=file_info.extension, file_size=file_info.size):
+        raise FileTooLargeError()
+
+    # Load content if needed
+    content = resp.content if resp.request.method == "GET" else remote_fetcher.make_request("GET", url).content
+
+    try:
+        upload_file = FileService(db.engine).upload_file(
+            filename=file_info.filename,
+            content=content,
+            mimetype=file_info.mimetype,
+            user=current_user,
+            tenant_id=resource_tenant_id,
+            source_url=url,
+        )
+    except services.errors.file.FileTooLargeError as file_too_large_error:
+        raise FileTooLargeError(file_too_large_error.description)
+    except services.errors.file.UnsupportedFileTypeError:
+        raise UnsupportedFileTypeError()
+
+    return FileWithSignedUrl(
+        id=upload_file.id,
+        name=upload_file.name,
+        size=upload_file.size,
+        extension=upload_file.extension,
+        url=file_helpers.get_signed_file_url(upload_file_id=upload_file.id),
+        mime_type=upload_file.mime_type,
+        created_by=upload_file.created_by,
+        created_at=int(upload_file.created_at.timestamp()),
+    )
+
+
 @console_ns.route("/remote-files/upload")
 class RemoteFileUpload(Resource):
     @console_ns.expect(console_ns.models[RemoteFileUploadPayload.__name__])
@@ -53,53 +108,8 @@ class RemoteFileUpload(Resource):
     @login_required
     @with_current_user
     def post(self, current_user: Account):
-        payload = RemoteFileUploadPayload.model_validate(console_ns.payload)
-        url = payload.url
-
-        # Try to fetch remote file metadata/content first
-        try:
-            resp = remote_fetcher.make_request("HEAD", url=url)
-            if resp.status_code != httpx.codes.OK:
-                resp = remote_fetcher.make_request("GET", url=url, timeout=3, follow_redirects=True)
-            if resp.status_code != httpx.codes.OK:
-                # Normalize into a user-friendly error message expected by tests
-                raise RemoteFileUploadError(f"Failed to fetch file from {url}: {resp.text}")
-        except httpx.RequestError as e:
-            raise RemoteFileUploadError(f"Failed to fetch file from {url}: {str(e)}")
-
-        file_info = helpers.guess_file_info_from_response(resp)
-
-        # Enforce file size limit with 400 (Bad Request) per tests' expectation
-        if not FileService.is_file_size_within_limit(extension=file_info.extension, file_size=file_info.size):
-            raise FileTooLargeError()
-
-        # Load content if needed
-        content = resp.content if resp.request.method == "GET" else remote_fetcher.make_request("GET", url).content
-
-        try:
-            upload_file = FileService(db.engine).upload_file(
-                filename=file_info.filename,
-                content=content,
-                mimetype=file_info.mimetype,
-                user=current_user,
-                source_url=url,
-            )
-        except services.errors.file.FileTooLargeError as file_too_large_error:
-            raise FileTooLargeError(file_too_large_error.description)
-        except services.errors.file.UnsupportedFileTypeError:
-            raise UnsupportedFileTypeError()
-
-        # Success: return created resource with 201 status
+        remote_file = upload_remote_file_from_request(current_user=current_user)
         return (
-            FileWithSignedUrl(
-                id=upload_file.id,
-                name=upload_file.name,
-                size=upload_file.size,
-                extension=upload_file.extension,
-                url=file_helpers.get_signed_file_url(upload_file_id=upload_file.id),
-                mime_type=upload_file.mime_type,
-                created_by=upload_file.created_by,
-                created_at=int(upload_file.created_at.timestamp()),
-            ).model_dump(mode="json"),
+            remote_file.model_dump(mode="json"),
             201,
         )

api/controllers/console/socketio/workflow.py

@@ -98,6 +98,7 @@ def handle_collaboration_event(sid, data):
     6. workflow_update
     7. comments_update
     8. node_panel_presence
+    9. graph_view_state (session reports tab visibility; drives leader election)
     """
     return collaboration_service.relay_collaboration_event(sid, data)
 

api/controllers/console/workflow_run_archive.py

@@ -4,20 +4,16 @@ from http import HTTPStatus
 from flask import redirect
 from flask_restx import Resource
 from pydantic import BaseModel, Field
-from werkzeug.exceptions import Conflict, NotFound
+from werkzeug.exceptions import Conflict, Forbidden, NotFound
 
 from controllers.common.fields import RedirectResponse
 from controllers.common.schema import register_response_schema_models, register_schema_models
 from controllers.console import console_ns
 from controllers.console.wraps import (
-    RBACPermission,
-    RBACResourceScope,
     account_initialization_required,
     cloud_edition_billing_enabled,
     cloud_edition_billing_paid_plan_required,
-    is_admin_or_owner_required,
     only_edition_cloud,
-    rbac_permission_required,
     setup_required,
 )
 from extensions.ext_database import db
@@ -25,6 +21,7 @@ from fields.base import ResponseModel
 from libs.archive_storage import get_export_storage
 from libs.helper import dump_response
 from libs.login import current_account_with_tenant, login_required
+from models import TenantAccountRole
 from services.retention.workflow_run.archive_download_preparation import ARCHIVE_DOWNLOAD_MIME_TYPE
 from services.retention.workflow_run.archive_download_task_cache import (
     WorkflowRunArchiveDownloadStatus,
@@ -98,11 +95,13 @@ register_response_schema_models(
 )
 
 
-def _current_ids() -> tuple[str, str]:
-    """Return current `(tenant_id, account_id)` or raise when no workspace is selected."""
+def _current_owner_or_admin_ids() -> tuple[str, str]:
+    """Return current Cloud workspace IDs for an owner or admin, independently of enterprise RBAC."""
     current_user, current_tenant_id = current_account_with_tenant()
     if not current_tenant_id:
         raise NotFound("Current workspace not found")
+    if not TenantAccountRole.is_privileged_role(current_user.current_role):
+        raise Forbidden()
     return current_tenant_id, current_user.id
 
 
@@ -124,12 +123,8 @@ class WorkflowRunArchivesApi(Resource):
     @only_edition_cloud
     @cloud_edition_billing_enabled
     @cloud_edition_billing_paid_plan_required
-    @is_admin_or_owner_required
-    @rbac_permission_required(
-        RBACResourceScope.WORKSPACE, RBACPermission.WORKSPACE_ROLE_MANAGE, resource_required=False
-    )
     def get(self):
-        tenant_id, _ = _current_ids()
+        tenant_id, _ = _current_owner_or_admin_ids()
         return dump_response(WorkflowRunArchiveListResponse, list_workflow_run_archives(db.session(), tenant_id))
 
 
@@ -149,12 +144,8 @@ class WorkflowRunArchiveDownloadsApi(Resource):
     @only_edition_cloud
     @cloud_edition_billing_enabled
     @cloud_edition_billing_paid_plan_required
-    @is_admin_or_owner_required
-    @rbac_permission_required(
-        RBACResourceScope.WORKSPACE, RBACPermission.WORKSPACE_ROLE_MANAGE, resource_required=False
-    )
     def post(self):
-        tenant_id, account_id = _current_ids()
+        tenant_id, account_id = _current_owner_or_admin_ids()
         payload = WorkflowRunArchiveDownloadPayload.model_validate(console_ns.payload or {})
         try:
             task = create_workflow_run_archive_download_task(
@@ -180,12 +171,8 @@ class WorkflowRunArchiveDownloadApi(Resource):
     @only_edition_cloud
     @cloud_edition_billing_enabled
     @cloud_edition_billing_paid_plan_required
-    @is_admin_or_owner_required
-    @rbac_permission_required(
-        RBACResourceScope.WORKSPACE, RBACPermission.WORKSPACE_ROLE_MANAGE, resource_required=False
-    )
     def get(self, download_id: str):
-        tenant_id, _ = _current_ids()
+        tenant_id, _ = _current_owner_or_admin_ids()
         try:
             task = get_workflow_run_archive_download_task(tenant_id=tenant_id, download_id=download_id)
         except WorkflowRunArchiveDownloadTaskNotFoundError as exc:
@@ -209,12 +196,8 @@ class WorkflowRunArchiveDownloadFileApi(Resource):
     @only_edition_cloud
     @cloud_edition_billing_enabled
     @cloud_edition_billing_paid_plan_required
-    @is_admin_or_owner_required
-    @rbac_permission_required(
-        RBACResourceScope.WORKSPACE, RBACPermission.WORKSPACE_ROLE_MANAGE, resource_required=False
-    )
     def get(self, download_id: str):
-        tenant_id, _ = _current_ids()
+        tenant_id, _ = _current_owner_or_admin_ids()
         try:
             task = get_ready_workflow_run_archive_download_task(tenant_id=tenant_id, download_id=download_id)
         except WorkflowRunArchiveDownloadTaskNotFoundError as exc:

api/controllers/service_api/app/audio.py

@@ -101,7 +101,7 @@ class AudioApi(Resource):
 
         Accepts an audio file upload and returns the transcribed text.
         """
-        file = request.files["file"]
+        file = request.files.get("file")
 
         try:
             response = AudioService.transcript_asr(

api/controllers/service_api/dataset/dataset.py

@@ -531,14 +531,22 @@ class DatasetListApi(DatasetApiResource):
         except services.errors.dataset.DatasetNameDuplicateError:
             raise DatasetNameDuplicateError()
 
-        if payload.permission == DatasetPermissionEnum.ALL_TEAM and dify_config.RBAC_ENABLED:
-            RBACService.DatasetAccess.replace_whitelist(
-                tenant_id,
-                current_user.id,
-                dataset.id,
-                ReplaceMemberBindings(scope=RBACResourceWhitelistScope.ALL),
-            )
-            initialize_created_app_rbac_access_task.delay(tenant_id, current_user.id, dataset_id=dataset.id)
+        if dify_config.RBAC_ENABLED:
+            if payload.permission == DatasetPermissionEnum.ALL_TEAM:
+                RBACService.DatasetAccess.replace_whitelist(
+                    tenant_id,
+                    current_user.id,
+                    dataset.id,
+                    ReplaceMemberBindings(scope=RBACResourceWhitelistScope.ALL),
+                )
+                initialize_created_app_rbac_access_task.delay(tenant_id, current_user.id, dataset_id=dataset.id)
+            else:
+                RBACService.DatasetAccess.replace_whitelist(
+                    tenant_id,
+                    current_user.id,
+                    dataset.id,
+                    ReplaceMemberBindings(scope=RBACResourceWhitelistScope.SPECIFIC),
+                )
 
         return _dump_service_dataset_detail(dataset, session=session), 200
 

api/controllers/web/audio.py

@@ -76,7 +76,7 @@ class AudioApi(WebApiResource):
     @web_ns.response(200, "Success", web_ns.models[AudioToTextResponse.__name__])
     def post(self, app_model: App, end_user: EndUser):
         """Convert audio to text"""
-        file = request.files["file"]
+        file = request.files.get("file")
 
         try:
             response = AudioService.transcript_asr(

api/core/app/apps/advanced_chat/app_generator.py

@@ -625,7 +625,11 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
                 message=message_snapshot,
                 user=user,
                 stream=stream,
-                draft_var_saver_factory=self._get_draft_var_saver_factory(invoke_from, account=user),
+                draft_var_saver_factory=self._get_draft_var_saver_factory(
+                    invoke_from,
+                    account=user,
+                    tenant_id=application_generate_entity.app_config.tenant_id,
+                ),
             )
 
             return AdvancedChatAppGenerateResponseConverter.convert(response=response, invoke_from=invoke_from)

api/core/app/apps/agent_app/app_generator.py

@@ -540,6 +540,9 @@ class AgentAppGenerator(MessageBasedAppGenerator):
                 base_url=dify_config.AGENT_BACKEND_BASE_URL,
                 use_fake=dify_config.AGENT_BACKEND_USE_FAKE,
                 fake_scenario=dify_config.AGENT_BACKEND_FAKE_SCENARIO,
+                stream_read_timeout_seconds=dify_config.AGENT_BACKEND_STREAM_READ_TIMEOUT_SECONDS,
+                stream_max_reconnects=dify_config.AGENT_BACKEND_STREAM_MAX_RECONNECTS,
+                stream_run_timeout_seconds=dify_config.AGENT_BACKEND_RUN_TIMEOUT_SECONDS,
             ),
             event_adapter=AgentBackendRunEventAdapter(),
             session_store=AgentAppRuntimeSessionStore(),

api/core/app/apps/agent_app/app_runner.py

@@ -941,48 +941,64 @@ class AgentAppRunner:
             if pending_text:
                 persist_answer_text(pending_text)
 
-        for public_event in self._agent_backend_client.stream_events(run_id):
-            if queue_manager.is_stopped():
-                flush_pending_agent_message_text()
-                self._cancel_run(run_id)
-                raise GenerateTaskStoppedError()
-            for internal_event in self._event_adapter.adapt(public_event):
+        try:
+            public_events = self._agent_backend_client.stream_events(
+                run_id,
+                should_stop=queue_manager.is_stopped,
+            )
+            for public_event in public_events:
                 if queue_manager.is_stopped():
                     flush_pending_agent_message_text()
                     self._cancel_run(run_id)
                     raise GenerateTaskStoppedError()
-                if internal_event.type in (
-                    AgentBackendInternalEventType.RUN_STARTED,
-                    AgentBackendInternalEventType.STREAM_EVENT,
-                    AgentBackendInternalEventType.AGENT_MESSAGE_DELTA,
-                ):
-                    if isinstance(internal_event, AgentBackendAgentMessageDeltaInternalEvent):
-                        debounced_delta = text_delta_debouncer.push(internal_event.delta)
-                        if debounced_delta:
-                            persist_answer_text(debounced_delta)
-                        continue
-
-                    if isinstance(internal_event, AgentBackendStreamInternalEvent):
+                for internal_event in self._event_adapter.adapt(public_event):
+                    if queue_manager.is_stopped():
                         flush_pending_agent_message_text()
-                        try:
-                            process_recorder.handle_stream_event(internal_event)
-                        except Exception:
-                            db.session.rollback()
-                            logger.warning(
-                                "Failed to persist Agent App process event: run_id=%s message_id=%s event_kind=%s",
-                                run_id,
-                                message_id,
-                                internal_event.event_kind,
-                                exc_info=True,
-                            )
+                        self._cancel_run(run_id)
+                        raise GenerateTaskStoppedError()
+                    if internal_event.type in (
+                        AgentBackendInternalEventType.RUN_STARTED,
+                        AgentBackendInternalEventType.STREAM_EVENT,
+                        AgentBackendInternalEventType.AGENT_MESSAGE_DELTA,
+                    ):
+                        if isinstance(internal_event, AgentBackendAgentMessageDeltaInternalEvent):
+                            debounced_delta = text_delta_debouncer.push(internal_event.delta)
+                            if debounced_delta:
+                                persist_answer_text(debounced_delta)
+                            continue
+
+                        if isinstance(internal_event, AgentBackendStreamInternalEvent):
+                            flush_pending_agent_message_text()
+                            try:
+                                process_recorder.handle_stream_event(internal_event)
+                            except Exception:
+                                db.session.rollback()
+                                logger.warning(
+                                    "Failed to persist Agent App process event: run_id=%s message_id=%s event_kind=%s",
+                                    run_id,
+                                    message_id,
+                                    internal_event.event_kind,
+                                    exc_info=True,
+                                )
+                            continue
                         continue
-                    continue
-                flush_pending_agent_message_text()
-                terminal = internal_event
-                break
-            if terminal is not None:
-                break
+                    flush_pending_agent_message_text()
+                    terminal = internal_event
+                    break
+                if terminal is not None:
+                    break
+        except GenerateTaskStoppedError:
+            raise
+        except Exception as error:
+            flush_pending_agent_message_text()
+            self._cancel_run(run_id)
+            if queue_manager.is_stopped():
+                raise GenerateTaskStoppedError() from error
+            raise
         flush_pending_agent_message_text()
+        if queue_manager.is_stopped():
+            self._cancel_run(run_id)
+            raise GenerateTaskStoppedError()
         return terminal, process_recorder
 
     def _cancel_run(self, run_id: str) -> None:

api/core/app/apps/base_app_generator.py

@@ -32,6 +32,7 @@ class _DebuggerDraftVariableSaver:
         self,
         *,
         account: Account,
+        tenant_id: str,
         app_id: str,
         node_id: str,
         node_type: NodeType,
@@ -39,6 +40,7 @@ class _DebuggerDraftVariableSaver:
         enclosing_node_id: str | None = None,
     ) -> None:
         self._account = account
+        self._tenant_id = tenant_id
         self._app_id = app_id
         self._node_id = node_id
         self._node_type = node_type
@@ -49,6 +51,7 @@ class _DebuggerDraftVariableSaver:
         with Session(db.engine) as session, session.begin():
             DraftVariableSaverImpl(
                 session=session,
+                tenant_id=self._tenant_id,
                 app_id=self._app_id,
                 node_id=self._node_id,
                 node_type=self._node_type,
@@ -287,7 +290,12 @@ class BaseAppGenerator:
 
     @final
     @staticmethod
-    def _get_draft_var_saver_factory(invoke_from: InvokeFrom, account: Account | EndUser) -> DraftVariableSaverFactory:
+    def _get_draft_var_saver_factory(
+        invoke_from: InvokeFrom,
+        account: Account | EndUser,
+        *,
+        tenant_id: str,
+    ) -> DraftVariableSaverFactory:
         if invoke_from == InvokeFrom.DEBUGGER:
             assert isinstance(account, Account)
 
@@ -300,6 +308,7 @@ class BaseAppGenerator:
             ) -> DraftVariableSaver:
                 return _DebuggerDraftVariableSaver(
                     account=account,
+                    tenant_id=tenant_id,
                     app_id=app_id,
                     node_id=node_id,
                     node_type=node_type,

api/core/app/apps/base_app_queue_manager.py

@@ -21,6 +21,7 @@ from core.app.entities.queue_entities import (
     WorkflowQueueMessage,
 )
 from extensions.ext_redis import redis_client
+from graphon.graph_engine.manager import GraphEngineManager
 from graphon.runtime import GraphRuntimeState
 
 logger = logging.getLogger(__name__)
@@ -51,6 +52,9 @@ class AppQueueManager(ABC):
         self._graph_runtime_state: GraphRuntimeState | None = None
         self._stopped_cache: TTLCache[tuple, bool] = TTLCache(maxsize=1, ttl=1)
         self._cache_lock = threading.Lock()
+        self._execution_terminal = threading.Event()
+        self._abort_sent = threading.Event()
+        self._lifecycle_lock = threading.Lock()
 
     def listen(self):
         """
@@ -59,7 +63,7 @@ class AppQueueManager(ABC):
         """
         # wait for APP_MAX_EXECUTION_TIME seconds to stop listen
         listen_timeout = dify_config.APP_MAX_EXECUTION_TIME
-        start_time = time.time()
+        start_time = time.monotonic()
         last_ping_time: int | float = 0
         try:
             while True:
@@ -72,8 +76,14 @@ class AppQueueManager(ABC):
                 except queue.Empty:
                     continue
                 finally:
-                    elapsed_time = time.time() - start_time
-                    if elapsed_time >= listen_timeout or self._is_stopped():
+                    elapsed_time = time.monotonic() - start_time
+                    timed_out = elapsed_time >= listen_timeout
+                    manually_stopped = self._is_stopped()
+                    if not self._execution_terminal.is_set() and (timed_out or manually_stopped):
+                        reason = (
+                            f"App execution exceeded {listen_timeout} seconds" if timed_out else "App task was stopped"
+                        )
+                        self._abort_execution(reason)
                         # publish two messages to make sure the client can receive the stop signal
                         # and stop listening after the stop signal processed
                         self.publish(
@@ -84,16 +94,33 @@ class AppQueueManager(ABC):
                         self.publish(QueuePingEvent(), PublishFrom.TASK_PIPELINE)
                         last_ping_time = elapsed_time // 10
         finally:
+            if not self._execution_terminal.is_set():
+                self._abort_execution("Client response stream closed before app execution completed")
             self._graph_runtime_state = None  # Release reference once consumers finish or close the generator.
 
-    def stop_listen(self):
+    def stop_listen(self, *, execution_terminal: bool = False):
         """
         Stop listen to queue
         :return:
         """
+        if execution_terminal:
+            self._execution_terminal.set()
         self._clear_task_belong_cache()
         self._q.put(None)
 
+    def _abort_execution(self, reason: str) -> None:
+        """Propagate response timeout/disconnect to legacy and GraphEngine runners."""
+        with self._lifecycle_lock:
+            if self._execution_terminal.is_set() or self._abort_sent.is_set():
+                return
+            self._abort_sent.set()
+
+        try:
+            self.set_stop_flag_no_user_check(self._task_id)
+            GraphEngineManager(redis_client).send_stop_command(self._task_id, reason=reason)
+        except Exception:
+            logger.exception("Failed to abort app execution for task %s", self._task_id)
+
     def _clear_task_belong_cache(self) -> None:
         """
         Remove the task belong cache key once listening is finished.

api/core/app/apps/message_based_app_queue_manager.py

@@ -45,7 +45,7 @@ class MessageBasedAppQueueManager(AppQueueManager):
         if isinstance(
             event, QueueStopEvent | QueueErrorEvent | QueueMessageEndEvent | QueueAdvancedChatMessageEndEvent
         ):
-            self.stop_listen()
+            self.stop_listen(execution_terminal=True)
 
         if pub_from == PublishFrom.APPLICATION_MANAGER and self._is_stopped():
             if self._app_mode == AppMode.ADVANCED_CHAT.value:

api/core/app/apps/pipeline/pipeline_generator.py

@@ -349,6 +349,7 @@ class PipelineGenerator(BaseAppGenerator):
             draft_var_saver_factory = self._get_draft_var_saver_factory(
                 invoke_from,
                 user,
+                tenant_id=pipeline.tenant_id,
             )
             # return response or stream generator
             response = self._handle_response(

api/core/app/apps/pipeline/pipeline_queue_manager.py

@@ -42,7 +42,7 @@ class PipelineQueueManager(AppQueueManager):
             | QueueWorkflowFailedEvent
             | QueueWorkflowPartialSuccessEvent,
         ):
-            self.stop_listen()
+            self.stop_listen(execution_terminal=True)
 
         if pub_from == PublishFrom.APPLICATION_MANAGER and self._is_stopped():
             raise GenerateTaskStoppedError()

api/core/app/apps/workflow/app_generator.py

@@ -399,7 +399,11 @@ class WorkflowAppGenerator(BaseAppGenerator):
 
             worker_thread.start()
 
-            draft_var_saver_factory = self._get_draft_var_saver_factory(invoke_from, user)
+            draft_var_saver_factory = self._get_draft_var_saver_factory(
+                invoke_from,
+                user,
+                tenant_id=app_model.tenant_id,
+            )
 
             # return response or stream generator
             response = self._handle_response(

api/core/app/apps/workflow/app_queue_manager.py

@@ -41,4 +41,4 @@ class WorkflowAppQueueManager(AppQueueManager):
             | QueueWorkflowFailedEvent
             | QueueWorkflowPartialSuccessEvent,
         ):
-            self.stop_listen()
+            self.stop_listen(execution_terminal=True)

api/core/app/apps/workflow_app_runner.py

@@ -26,6 +26,7 @@ from core.app.entities.queue_entities import (
     QueueNodeSucceededEvent,
     QueueReasoningChunkEvent,
     QueueRetrieverResourcesEvent,
+    QueueStopEvent,
     QueueTextChunkEvent,
     QueueWorkflowFailedEvent,
     QueueWorkflowPartialSuccessEvent,
@@ -424,7 +425,12 @@ class WorkflowBasedAppRunner:
                     QueueWorkflowFailedEvent(error=event.error, exceptions_count=event.exceptions_count)
                 )
             case GraphRunAbortedEvent():
-                self._publish_event(QueueWorkflowFailedEvent(error=event.reason or "Unknown error", exceptions_count=0))
+                self._publish_event(
+                    QueueStopEvent(
+                        stopped_by=QueueStopEvent.StopBy.USER_MANUAL,
+                        reason=event.reason or "Workflow execution aborted",
+                    )
+                )
             case GraphRunPausedEvent():
                 runtime_state = workflow_entry.graph_engine.graph_runtime_state
                 paused_nodes = runtime_state.get_paused_nodes()

api/core/app/entities/queue_entities.py

@@ -500,11 +500,15 @@ class QueueStopEvent(AppQueueEvent):
 
     event: QueueEvent = QueueEvent.STOP
     stopped_by: StopBy
+    reason: str | None = None
 
     def get_stop_reason(self) -> str:
         """
         To stop reason
         """
+        if self.reason:
+            return self.reason
+
         reason_mapping = {
             QueueStopEvent.StopBy.USER_MANUAL: "Stopped by user.",
             QueueStopEvent.StopBy.ANNOTATION_REPLY: "Stopped by annotation reply.",

api/core/helper/ssrf_proxy.py

@@ -47,6 +47,24 @@ class MaxRetriesExceededError(ValueError):
     pass
 
 
+class ResponseLimitError(ValueError):
+    """Base error for responses that cannot be safely bounded."""
+
+    pass
+
+
+class ResponseTooLargeError(ResponseLimitError):
+    """Raised when an identity response exceeds the configured byte limit."""
+
+    pass
+
+
+class UnsupportedResponseEncodingError(ResponseLimitError):
+    """Raised when response encoding prevents safe decoded-size enforcement."""
+
+    pass
+
+
 request_error = httpx.RequestError
 max_retries_exceeded_error = MaxRetriesExceededError
 
@@ -142,7 +160,31 @@ def _inject_trace_headers(headers: Headers | None) -> Headers:
     return headers
 
 
-def make_request(method: str, url: str, max_retries: int = SSRF_DEFAULT_MAX_RETRIES, **kwargs: Any) -> httpx.Response:
+def make_request(
+    method: str,
+    url: str,
+    max_retries: int = SSRF_DEFAULT_MAX_RETRIES,
+    stream_response: bool = False,
+    **kwargs: Any,
+) -> httpx.Response:
+    """Send one SSRF-protected request with optional streaming.
+
+    Args:
+        method: HTTP method sent through the configured SSRF client.
+        url: Absolute request URL.
+        max_retries: Number of retry attempts after the initial request.
+        stream_response: Return an open streaming response that the caller must close.
+        **kwargs: Additional keyword arguments forwarded to ``httpx.Client``.
+
+    Returns:
+        A buffered response, or an open response when ``stream_response`` is true.
+
+    Raises:
+        ToolSSRFError: The configured SSRF proxy rejects the destination.
+        MaxRetriesExceededError: All configured request attempts fail.
+        httpx.RequestError: A request fails while retries are disabled.
+        ValueError: The SSL verification option or request headers are invalid.
+    """
     # Convert requests-style allow_redirects to httpx-style follow_redirects
     if "allow_redirects" in kwargs:
         allow_redirects = kwargs.pop("allow_redirects")
@@ -175,6 +217,11 @@ def make_request(method: str, url: str, max_retries: int = SSRF_DEFAULT_MAX_RETR
     # When using a forward proxy, httpx may override the Host header based on the URL.
     # We extract and preserve any explicitly set Host header to support virtual hosting.
     user_provided_host = _get_user_provided_host_header(headers)
+    send_kwargs: dict[str, Any] = {}
+    if "auth" in kwargs:
+        send_kwargs["auth"] = kwargs.pop("auth")
+    if "follow_redirects" in kwargs:
+        send_kwargs["follow_redirects"] = kwargs.pop("follow_redirects")
 
     retries = 0
     while retries <= max_retries:
@@ -185,7 +232,11 @@ def make_request(method: str, url: str, max_retries: int = SSRF_DEFAULT_MAX_RETR
             if user_provided_host is not None:
                 headers["host"] = user_provided_host
             kwargs["headers"] = headers
-            response = client.request(method=method, url=url, **kwargs)
+            request = client.build_request(method=method, url=url, **kwargs)
+            if stream_response:
+                response = client.send(request, stream=True, **send_kwargs)
+            else:
+                response = client.send(request, **send_kwargs)
 
             # Check for SSRF protection by Squid proxy
             if response.status_code in (401, 403):
@@ -195,6 +246,7 @@ def make_request(method: str, url: str, max_retries: int = SSRF_DEFAULT_MAX_RETR
 
                 # Squid typically identifies itself in Server or Via headers
                 if "squid" in server_header or "squid" in via_header:
+                    response.close()
                     raise ToolSSRFError(
                         f"Access to '{url}' was blocked by SSRF protection. "
                         f"The URL may point to a private or local network address. "
@@ -208,6 +260,7 @@ def make_request(method: str, url: str, max_retries: int = SSRF_DEFAULT_MAX_RETR
                     response.status_code,
                     url,
                 )
+                response.close()
 
         except httpx.RequestError as e:
             logger.warning("Request to URL %s failed on attempt %s: %s", url, retries + 1, e)
@@ -220,6 +273,42 @@ def make_request(method: str, url: str, max_retries: int = SSRF_DEFAULT_MAX_RETR
     raise MaxRetriesExceededError(f"Reached maximum retries ({max_retries}) for URL {url}")
 
 
+def buffer_response(response: httpx.Response, *, max_response_bytes: int) -> httpx.Response:
+    """Consume one open identity response under a decoded byte limit and close its stream."""
+    if max_response_bytes <= 0:
+        raise ValueError("max_response_bytes must be positive")
+
+    try:
+        content_encoding = response.headers.get("content-encoding", "identity").strip().lower()
+        if content_encoding not in {"", "identity"}:
+            raise UnsupportedResponseEncodingError(f"content encoding {content_encoding} cannot be safely bounded")
+        content = bytearray()
+        for chunk in response.iter_bytes():
+            if len(content) + len(chunk) > max_response_bytes:
+                raise ResponseTooLargeError(f"response exceeded {max_response_bytes} bytes")
+            content.extend(chunk)
+        decoded_headers = {
+            name: value
+            for name, value in response.headers.items()
+            if name.lower() not in {"content-encoding", "content-length", "transfer-encoding"}
+        }
+        try:
+            request = response.request
+        except RuntimeError:
+            request = None
+        return httpx.Response(
+            response.status_code,
+            headers=decoded_headers,
+            content=bytes(content),
+            request=request,
+            extensions=response.extensions,
+            history=response.history,
+            default_encoding=response.default_encoding,
+        )
+    finally:
+        response.close()
+
+
 def get(url: str, max_retries: int = SSRF_DEFAULT_MAX_RETRIES, **kwargs: Any) -> httpx.Response:
     return make_request("GET", url, max_retries=max_retries, **kwargs)
 

api/core/llm_generator/llm_generator.py

@@ -403,55 +403,6 @@ class LLMGenerator:
             return ""
         return "\n\n".join(sections) + "\n\n"
 
-    @classmethod
-    def classify_workflow_mode(
-        cls,
-        tenant_id: str,
-        instruction: str,
-        model_config: ModelConfig,
-    ) -> Literal["workflow", "advanced-chat"]:
-        """Classify a free-text instruction into a concrete app mode.
-
-        One tiny LLM call using the model the user already picked (so no extra
-        provider setup is needed). Parsed leniently; defaults to
-        ``advanced-chat`` on anything unexpected or any error, so a
-        ``mode="auto"`` request never blocks generation. NEVER raises.
-        """
-        default_mode: Literal["workflow", "advanced-chat"] = "advanced-chat"
-        try:
-            model_instance = ModelManager.for_tenant(tenant_id=tenant_id).get_model_instance(
-                tenant_id=tenant_id,
-                model_type=ModelType.LLM,
-                provider=model_config.provider,
-                model=model_config.name,
-            )
-            prompt_messages: list[PromptMessage] = [
-                UserPromptMessage(
-                    content=(
-                        "Reply with exactly one word: 'workflow' (one-shot automation, no chat) "
-                        "or 'advanced-chat' (conversational multi-turn). "
-                        f"Instruction: {instruction.strip()}"
-                    )
-                ),
-            ]
-            response: LLMResult = model_instance.invoke_llm(
-                prompt_messages=prompt_messages,
-                model_parameters={"max_tokens": 4, "temperature": 0},
-                stream=False,
-            )
-            text = (response.message.get_text_content() or "").strip().lower()
-        except Exception:
-            logger.info("Workflow mode classification failed; defaulting to %s", default_mode, exc_info=True)
-            return default_mode
-
-        # Lenient parse: an affirmative "workflow" wins; everything else
-        # (including a truncated / empty / garbled reply) falls back to the
-        # conversational default. "advanced-chat" needs no positive match
-        # because it IS the default.
-        if "workflow" in text:
-            return "workflow"
-        return default_mode
-
     @classmethod
     def generate_rule_config(cls, tenant_id: str, args: RuleGeneratePayload):
         output_parser = RuleConfigGeneratorOutputParser()

api/core/rag/extractor/watercrawl/client.py

@@ -131,7 +131,10 @@ class WaterCrawlAPIClient(BaseAPIClient):
         content_type = response.headers.get("Content-Type", "")
         media_type = content_type.split(";", 1)[0].strip().lower()
         if media_type == "application/json":
-            return response.json() or {}
+            try:
+                return response.json() or {}
+            except ValueError as exc:
+                raise ValueError("Invalid JSON response from WaterCrawl") from exc
 
         if media_type == "application/octet-stream":
             return response.content

api/core/rag/extractor/watercrawl/exceptions.py

@@ -1,5 +1,15 @@
+"""WaterCrawl domain exceptions.
+
+These exceptions are constructed from upstream HTTP responses, which may be
+JSON API errors or plain text/HTML proxy errors. Keep the exception type stable
+even when the body is not JSON so callers can handle WaterCrawl failures by
+domain type instead of low-level parser errors.
+"""
+
 import json
-from typing import override
+from typing import Any, override
+
+from httpx import Response
 
 
 class WaterCrawlError(Exception):
@@ -7,11 +17,16 @@ class WaterCrawlError(Exception):
 
 
 class WaterCrawlBadRequestError(WaterCrawlError):
-    def __init__(self, response):
+    def __init__(self, response: Response):
         self.status_code = response.status_code
         self.response = response
-        data = response.json()
-        self.message = data.get("message", "Unknown error occurred")
+        try:
+            data: Any = response.json()
+        except ValueError:
+            data = {}
+        if not isinstance(data, dict):
+            data = {}
+        self.message = data.get("message") or response.text or "Unknown error occurred"
         self.errors = data.get("errors", {})
         super().__init__(self.message)
 

api/core/workflow/generator/__init__.py

@@ -4,12 +4,12 @@ Workflow generator package.
 Generates a Dify workflow graph (nodes, edges, viewport) from a natural-language
 instruction. Intended for the cmd+k `/create` slash command's preview/apply flow.
 
-Pipeline (slim, single-shot variant):
+Pipeline:
 
     runner.WorkflowGenerator.generate_workflow_graph(...)
-        ├── planner_prompts: short LLM call → high-level node plan
-        └── builder_prompts: structured-output LLM call → full graph JSON
-            └── postprocess: fill defaults, auto-layout viewport, sanity-check edges
+        ├── planner_prompts: short LLM call → node and edge plan
+        ├── node_builder_prompts: bounded parallel calls → semantic node configs
+        └── postprocess: assemble wrappers, auto-layout, validate graph
 
 The runner is pure domain logic; ``WorkflowGeneratorService`` (in ``services/``)
 owns the model-manager dependency and is what controllers call.

api/core/workflow/generator/prompts/builder_prompts.py

@@ -1,19 +1,4 @@
-"""
-Builder prompts.
-
-The builder is the second step of the slim planner→builder pipeline. It takes
-the planner's high-level node list and emits the *full* graph JSON consumed by
-``WorkflowService.sync_draft_workflow``.
-
-The builder owns: node configuration (prompts, code, headers, etc.), edge wiring,
-handle ids ("source"/"target"), positions, and the viewport. It is the only
-prompt that needs to know the concrete shape of each node type — keep its
-examples accurate or the LLM will invent fields.
-"""
-
-import json
-from collections.abc import Iterable
-from typing import Any
+"""Compact semantic configuration references for workflow node builders."""
 
 # Per-node-type configuration cheatsheet.
 #
@@ -23,50 +8,9 @@ from typing import Any
 # both ``WorkflowService.sync_draft_workflow``'s structural checks and the
 # runtime entity validation each node performs when the workflow runs.
 #
-# The cheatsheet is assembled DYNAMICALLY per request: the planner decides
-# which node types the workflow needs, and ``build_node_config_cheatsheet``
-# stitches together only the snippets for those types (plus the always-needed
-# wrapper / shared-field / edge-handle preamble, and the containers section
-# when an iteration / loop is planned). This keeps the builder prompt tight —
-# a 3-node summariser no longer carries the schema for 12 unrelated node
-# types — and lets each snippet document its FULL schema (e.g. a "file" start
-# variable's required ``allowed_file_types``) without bloating every prompt.
-#
-# The postprocessor in ``runner.py`` fills missing wrapper fields (``type``,
-# ``positionAbsolute``, ``width``, ``height``, ``sourcePosition`` /
-# ``targetPosition``, edge ``data.sourceType`` / ``data.targetType``), so the
-# LLM only needs to emit semantically meaningful fields.
-
-# Always-included preamble: the node/edge wrapper shape and the shared
-# ``data`` fields that apply to every node type, plus the "## Per type" header
-# the per-type snippets slot under.
-_CHEATSHEET_PREAMBLE = """\
-## Node wrapper (every node, top-level)
-
-    {"id": "node1" (digits + letters only — see "Node IDs" below),
-     "type": "custom",                # ReactFlow renderer key. Iteration/loop
-                                      # *start* children use special types
-                                      # (see Containers below).
-     "position": {"x": <number>, "y": <number>},
-     "data": { ... per-type fields ... }}
-
-Children of iteration / loop containers additionally need
-``parentId``, ``zIndex: 1002`` and ``extent: "parent"`` — see Containers.
-
-## Shared "data" fields (every node)
-
-    {"type": "<node-type>",          # e.g. "llm", "start", "if-else"
-     "title": "<short label>",
-     "desc": "<one-liner>",
-     "selected": false}
-
-## Per type — additional "data" fields (only the node types in your plan are shown)"""
-
-
-# node_type → its per-type schema snippet. Keyed by the exact ``node_type``
-# string the planner emits so ``build_node_config_cheatsheet`` can look each
-# one up directly. Iteration / loop are documented in the Containers section
-# (they are subgraphs, not leaf nodes) rather than here.
+# Each snippet mirrors the production node default closely enough for one
+# model call to emit only meaningful ``data`` fields. The runner owns wrappers,
+# topology, container metadata, layout, and validation.
 _NODE_SNIPPETS: dict[str, str] = {
     "start": """\
 - start:
@@ -248,484 +192,30 @@ _NODE_SNIPPETS: dict[str, str] = {
     Enable only the sub-features you need; ``conditions`` reuse the if-else
     condition shape (key / comparison_operator / value). Outputs: ``result``
     (the processed array), ``first_record``, ``last_record``.""",
+    "assigner": """\
+- assigner  (write to an existing conversation / loop variable):
+    {"version": "2",
+     "items": [{"variable_selector": ["<target-node>", "<target-var>"],
+                "input_type": "variable",
+                "operation": "over-write",
+                "value": ["<source-node>", "<source-var>"]}]}
+    ``input_type`` is "variable" (value is a selector) or "constant".
+    Operations: over-write | clear | append | extend | set | += | -= | *= |
+    /= | remove-first | remove-last.""",
+    "human-input": """\
+- human-input  (pause for a person; use webapp delivery by default):
+    {"delivery_methods": [{"id": "webapp", "type": "webapp", "enabled": true}],
+     "form_content": "<short review / approval instructions>",
+     "inputs": [{"type": "paragraph", "output_variable_name": "comment",
+                 "default": {"type": "constant", "selector": [], "value": ""}}],
+     "user_actions": [{"id": "approve", "title": "Approve",
+                       "button_style": "primary"}],
+     "timeout": 3, "timeout_unit": "day"}
+    Each ``inputs[].output_variable_name`` is an output variable. Outgoing
+    edges use the matching user-action id as ``sourceHandle``.""",
 }
 
 
-# Pulled into the cheatsheet only when an iteration / loop appears in the plan.
-_CONTAINERS_SECTION = """\
-## Containers — iteration / loop
-
-These are SUBGRAPH nodes. To use one you MUST emit, in order:
-
-1. The container node itself, e.g. for iteration:
-       id: "nodeK"
-       type: "custom"
-       data: {"type": "iteration",
-              "title": "<label>",
-              "desc": "",
-              "selected": false,
-              "start_node_id": "nodeKstart",
-              "iterator_selector": ["<src>", "<list-var>"],
-              "output_selector": ["<inner-last-node>", "<out-var>"],
-              "is_parallel": false,
-              "parallel_nums": 10,
-              "error_handle_mode": "terminated",
-              "flatten_output": true}
-       width: 808
-       height: 204
-       zIndex: 1
-
-   For loop, swap "iteration" → "loop" and use:
-       data: {"type": "loop", "title": "...", "desc": "",
-              "selected": false, "start_node_id": "nodeKstart",
-              "break_conditions": [], "loop_count": 10,
-              "logical_operator": "and"}
-
-2. The auto-start child (one per container):
-       id: "nodeKstart"
-       type: "custom-iteration-start"          # loop → "custom-loop-start"
-       parentId: "nodeK"
-       extent: "parent"
-       draggable: false
-       selectable: false
-       zIndex: 1002
-       position: {"x": 60, "y": 78}            # relative to parent
-       data: {"type": "iteration-start",       # loop → "loop-start"
-              "title": "", "desc": "",
-              "isInIteration": true,           # loop → "isInLoop": true
-              "selected": false}
-
-3. Each inner-pipeline node (any node type, follows normal data rules) MUST add:
-       parentId: "nodeK"
-       extent: "parent"
-       zIndex: 1002
-       position: {x, y}                         # relative to parent
-       data: {..., "isInIteration": true,       # loop → "isInLoop": true
-              "iteration_id": "nodeK"}         # loop → "loop_id"
-
-4. Edges INSIDE a container must add to ``data``:
-       "isInIteration": true                    # loop → "isInLoop": true
-       "iteration_id": "nodeK"                 # loop → "loop_id"
-   and use ``zIndex: 1002``. Edges OUTSIDE containers use the default
-   ``isInIteration: false`` / ``isInLoop: false``.
-
-5. The container's incoming/outgoing edges connect to the container's id
-   (``nodeK``), NOT to inner nodes. The first inner edge connects from
-   ``nodeKstart``."""
-
-
-# Always-included trailer: edge handle conventions for every graph.
-_EDGE_HANDLES_SECTION = """\
-## Edge handles
-
-- Most nodes:           sourceHandle "source", targetHandle "target".
-- if-else cases:        sourceHandle is the case_id ("true" / "false" / ...).
-- question-classifier:  sourceHandle is the class_id ("1" / "2" / ...).
-- iteration-start /     sourceHandle "source"; the edge from the *start node
-  loop-start:           is what kicks off the first inner step."""
-
-
-# Container node types are described in ``_CONTAINERS_SECTION`` rather than as
-# leaf snippets; their presence in a plan pulls that section in.
-_CONTAINER_NODE_TYPES = frozenset({"iteration", "loop"})
-
-
-def build_node_config_cheatsheet(node_types: Iterable[str] | None = None) -> str:
-    """
-    Assemble the builder cheatsheet for exactly the node types in the plan.
-
-    ``node_types`` is the set of ``node_type`` strings the planner chose. We
-    emit the always-on preamble (wrapper / shared fields), then only the
-    per-type snippets for the requested types (``start`` is always included —
-    every graph has one), the Containers section when an iteration / loop is
-    planned, and the edge-handles trailer. Unknown / unrecognised type strings
-    are ignored (the runtime / structural validator catches genuinely bogus
-    types).
-
-    ``None`` returns the FULL cheatsheet (every snippet + containers) — used to
-    build the static back-compat constants below and as a safe fallback.
-    """
-    if node_types is None:
-        requested: set[str] = set(_NODE_SNIPPETS) | set(_CONTAINER_NODE_TYPES)
-    else:
-        requested = {str(t).strip() for t in node_types if str(t).strip()}
-        requested.add("start")  # every workflow has exactly one start node
-
-    parts: list[str] = [_CHEATSHEET_PREAMBLE]
-    # Iterate _NODE_SNIPPETS (not ``requested``) to keep a stable, readable order.
-    parts.extend(snippet for node_type, snippet in _NODE_SNIPPETS.items() if node_type in requested)
-    if requested & _CONTAINER_NODE_TYPES:
-        parts.append(_CONTAINERS_SECTION)
-    parts.append(_EDGE_HANDLES_SECTION)
-    return "\n\n".join(parts) + "\n"
-
-
-# Full cheatsheet (all node types) — retained as a module constant so callers
-# and tests that want the complete reference can import it directly. The
-# dynamic per-request prompt is built by ``get_builder_system_prompt``.
-NODE_CONFIG_CHEATSHEET = build_node_config_cheatsheet()
-
-
-_BASE_SYSTEM_PROMPT_HEAD = """You are a Dify workflow builder.
-
-You are given:
-  1. A user instruction (what the workflow should do).
-  2. A node plan from the planner (which nodes to use, in execution order).
-
-Your job: emit a complete Dify workflow graph as JSON. The graph will be written
-directly into a Studio draft, so it must be syntactically valid and structurally
-correct.
-
-# Hard rules
-
-1. The output is a single JSON object — no prose, no Markdown, no code fences.
-2. NODE IDs MUST USE ONLY ALPHANUMERICS + UNDERSCORES — never hyphens.
-   Dify's run-time placeholder regex (see ``variable_pool.VARIABLE_PATTERN``)
-   is ``\\{\\{#([a-zA-Z0-9_]{1,50}(?:\\.[a-zA-Z_][a-zA-Z0-9_]{0,29}){1,10})#\\}\\}``,
-   so any placeholder pointing at a hyphenated id (e.g. ``{{#node-1.text#}}``)
-   silently fails to match at run time and the literal string survives into
-   the prompt — the user then sees ``{{#node-1.text#}}`` in their output.
-   Use the EXACT ids from the plan, formatted as ``node1``, ``node2``, ... in
-   plan order. Edge ``source`` / ``target`` must reference these ids.
-3. Every node has top-level fields: id, type, position, data.
-   - "type" is always "custom" (ReactFlow node renderer).
-   - "data.type" is the actual node type ("llm", "start", etc.).
-4. Every edge has top-level fields: id, source, target, type, sourceHandle, targetHandle.
-   - "type" is always "custom".
-   - "sourceHandle"/"targetHandle" follow the cheatsheet (default: "source"/"target").
-   - Edge id format: "<source>-<sourceHandle>-<target>-<targetHandle>".
-5. Use the model from the planner context for ALL "llm" / "question-classifier" /
-   "parameter-extractor" nodes (provider, name, mode, completion_params).
-6. Reference upstream outputs with the literal placeholder syntax
-   ``{{#<node-id>.<output-var>#}}`` — that's DOUBLE curly braces with ``#``
-   markers inside (matching Dify's runtime placeholder regex
-   ``\\{\\{#[^#]+#\\}\\}``). NEVER emit single-brace ``{#…#}`` — Dify will
-   not interpolate it, so the LLM at run time would see the literal
-   placeholder string in its prompt and echo it back as output. Use
-   ``["<node-id>", "<output-var>"]`` for ``value_selector`` /
-   ``query_variable_selector`` / etc.
-7. The "start" node owns input variables; downstream nodes reference them as
-   ``["<start-node-id>", "<var-name>"]`` for selectors or
-   ``{{#<start-node-id>.<var-name>#}}`` inside prompt strings.
-8. NEVER emit "code" or "http-request" nodes if a tool from the "Available tools"
-   section below covers the same task — replace them with a "tool" node referencing
-   the exact provider/tool identifier from the catalogue. "code" / "http-request"
-   are last-resort escape hatches for arbitrary transformations and APIs that no
-   installed tool can express.
-9. EVERY variable reference MUST resolve to a real, declared variable on the
-   source node — never invent a variable name. Specifically:
-   - ``{{#<node-id>.<var>#}}`` inside a prompt / ``answer`` / ``template-transform``
-     template (DOUBLE braces — single ``{#…#}`` is NOT a Dify placeholder
-     and will NOT be substituted), AND ``["<node-id>", "<var>"]`` inside a
-     ``value_selector`` /
-     ``query_variable_selector`` / ``iterator_selector`` / ``output_selector`` /
-     ``tool_parameters[*].value`` (when ``type: "variable"``), MUST point at a
-     value that the source node actually exposes:
-       * ``start``  → one of the ``data.variables[*].variable`` entries you
-         declared on the start node. Add an entry if you need a new input.
-       * ``llm``    → ``text`` (the default LLM output) or, when structured
-         output is enabled, a key from its schema.
-       * ``code``   → a key in ``data.outputs``.
-       * ``knowledge-retrieval`` → ``result`` (the standard array output).
-       * ``parameter-extractor`` → one of the ``data.parameters[*].name``.
-       * ``document-extractor`` → ``text`` (extracted file text; an array of
-         strings when ``is_array_file`` is true).
-       * ``variable-aggregator`` → ``output``.
-       * ``list-operator`` → ``result`` (array), ``first_record``,
-         ``last_record``.
-       * ``tool``   → any parameter declared by the tool — the run time
-         validates these, so you can name them freely, but pick from the
-         documented provider/tool.
-     If the planner's "Start inputs" list (see user prompt) is non-empty,
-     copy each entry verbatim into ``start.data.variables`` so the
-     downstream references resolve.
-   - In Advanced-Chat mode you may also reference ``sys.query`` and
-     ``sys.files`` without declaring them. In selector fields, spell these as
-     exactly ``["sys", "query"]`` and ``["sys", "files"]`` — never as a
-     one-item array such as ``["sys,query"]`` or ``["sys.query"]``.
-10. MULTIPLE KNOWLEDGE-RETRIEVAL INPUTS TO ONE LLM require a template fan-in.
-    ``context.variable_selector accepts only one selector`` and therefore
-    cannot carry two retrieval outputs. When an LLM must synthesize two or
-    more retrieval results:
-    - Run the retrieval nodes as parallel siblings from the same query input.
-    - Add one ``template-transform`` node after them. Give it one variable per
-      retrieval, such as ``value_selector: ["node2", "result"]`` and
-      ``value_selector: ["node3", "result"]``, and render every source's
-      content into one labelled text output.
-    - Add an edge from EACH retrieval node to the template, then one edge from
-      the template to the LLM. The LLM must NOT receive direct retrieval edges.
-    - Enable the LLM's context, set ``context.variable_selector`` to the
-      template's ``["<template-node-id>", "output"]``, and put
-      ``{{#context#}}`` in its prompt.
-    - Do not use ``variable-aggregator`` for this: it selects the first value
-      produced by mutually exclusive branches; it does not concatenate two
-      retrieval results that both ran.
-
-"""
-
-
-_BASE_SYSTEM_PROMPT_TAIL = """\
-
-# Layout
-
-- Place nodes left-to-right with x=80 + 320 * index, y=280.
-- Viewport: {"x": 0, "y": 0, "zoom": 0.7}.
-
-"""
-
-
-_BASE_SYSTEM_PROMPT_FOOTER = """
-
-# Output schema
-
-{
-  "nodes": [...],
-  "edges": [...],
-  "viewport": {"x": 0, "y": 0, "zoom": 0.7}
-}
-"""
-
-
-_WORKFLOW_MODE_RULES = """# Mode-specific rules — Workflow
-
-- The graph MUST start with exactly one "start" node and end with exactly one "end" node.
-- Do NOT use "answer" nodes (those are for Advanced Chat only).
-- The "end" node's outputs[].value_selector must point at a real upstream output.
-"""
-
-
-_ADVANCED_CHAT_MODE_RULES = """# Mode-specific rules — Advanced Chat (Chatflow)
-
-- The graph MUST start with exactly one "start" node and end with exactly one "answer" node.
-- Do NOT use "end" nodes (those are for plain Workflow apps).
-- The "start" node should expose "sys.query" / "sys.files" automatically; user-defined
-  variables go in start.data.variables.
-- The "answer" node's "answer" field references upstream outputs as
-  {{#<node-id>.<var>#}} and is what the user sees in chat.
-"""
-
-
-def _assemble_builder_system_prompt(mode: str, node_types: Iterable[str] | None) -> str:
-    """Stitch the builder system prompt for ``mode`` around a cheatsheet built
-    for ``node_types`` (``None`` → full cheatsheet)."""
-    mode_rules = _ADVANCED_CHAT_MODE_RULES if mode == "advanced-chat" else _WORKFLOW_MODE_RULES
-    return (
-        _BASE_SYSTEM_PROMPT_HEAD
-        + mode_rules
-        + _BASE_SYSTEM_PROMPT_TAIL
-        + build_node_config_cheatsheet(node_types)
-        + _BASE_SYSTEM_PROMPT_FOOTER
-    )
-
-
-# Static full-cheatsheet prompts — the back-compat default returned by
-# ``get_builder_system_prompt`` when the caller doesn't pin a node-type set.
-BUILDER_SYSTEM_PROMPT_WORKFLOW = _assemble_builder_system_prompt("workflow", None)
-
-BUILDER_SYSTEM_PROMPT_ADVANCED_CHAT = _assemble_builder_system_prompt("advanced-chat", None)
-
-
-BUILDER_USER_PROMPT = """# User instruction
-
-{instruction}
-
-{ideal_output_section}\
-{existing_graph_section}\
-# Selected model (use for all LLM-based nodes)
-
-provider={provider}, name={name}, mode={mode_label}
-
-{tool_catalogue_section}\
-{start_inputs_section}\
-# Node plan (from planner — use these labels and node_types in this order)
-
-{plan_block}
-
-Now emit the complete workflow graph JSON.
-"""
-
-
-# Node wrapper fields that carry no meaning the builder needs: pure canvas /
-# selection state, plus geometry the runner's postprocess recomputes anyway.
-# Stripping them out of the refine prompt cuts its size roughly in half on
-# hand-edited graphs — fewer tokens in, and (because the builder echoes
-# untouched nodes verbatim) far fewer tokens out, which is where the latency
-# lives.
-_PRUNED_NODE_KEYS = frozenset(
-    {
-        "positionAbsolute",
-        "sourcePosition",
-        "targetPosition",
-        "selected",
-        "dragging",
-        "measured",
-    }
-)
-
-# Additionally pruned from TOP-LEVEL nodes only: the layered auto-layout
-# recomputes their position and size defaults, so the builder never needs to
-# reproduce them. Container children keep ``position`` (relative to the
-# parent, which we cannot recompute) and containers keep ``width`` /
-# ``height`` (their canvas size is real config, not a default).
-_PRUNED_TOP_LEVEL_NODE_KEYS = _PRUNED_NODE_KEYS | {"position", "width", "height"}
-
-_CONTAINER_DATA_TYPES = frozenset({"iteration", "loop"})
-
-# Edge fields the builder must echo; everything else (ids, zIndex,
-# sourceType / targetType, isInIteration / isInLoop markers) is recomputed
-# by the runner's postprocess from the node topology.
-_KEPT_EDGE_KEYS = ("source", "target", "sourceHandle", "targetHandle")
-
-
-def compact_graph_for_builder(current_graph: dict) -> dict:
-    """
-    Strip canvas noise out of a draft graph before prompt injection.
-
-    Keeps everything semantically meaningful — ids, wrapper ``type``,
-    ``parentId``, the full ``data`` config, child positions, container
-    sizes — and drops geometry / selection state the postprocess pass
-    recomputes. The builder echoes untouched nodes verbatim, so every byte
-    removed here is removed twice (prompt AND completion).
-    """
-    nodes_out: list[dict] = []
-    for node in current_graph.get("nodes") or []:
-        if not isinstance(node, dict):
-            continue
-        is_child = bool(node.get("parentId"))
-        is_container = isinstance(node.get("data"), dict) and node["data"].get("type") in _CONTAINER_DATA_TYPES
-        pruned = _PRUNED_NODE_KEYS if (is_child or is_container) else _PRUNED_TOP_LEVEL_NODE_KEYS
-        compact = {k: v for k, v in node.items() if k not in pruned}
-        if is_container:
-            # Container position is still recomputed by the layout pass.
-            compact.pop("position", None)
-        nodes_out.append(compact)
-    edges_out = [
-        {k: edge[k] for k in _KEPT_EDGE_KEYS if k in edge}
-        for edge in (current_graph.get("edges") or [])
-        if isinstance(edge, dict)
-    ]
-    return {"nodes": nodes_out, "edges": edges_out}
-
-
-def format_builder_existing_graph_section(current_graph: dict | None) -> str:
-    """
-    Refine mode: give the builder the existing graph JSON so it can keep
-    every node and edge the user's change does not touch byte-for-byte — same
-    ids, same config, same prompt templates. Without the full config the
-    builder would regenerate untouched nodes from scratch and silently drop
-    the user's hand-tuned settings. Canvas-only fields are stripped first
-    (see ``compact_graph_for_builder``) — they're recomputed in postprocess,
-    so carrying them only slows the call down.
-
-    Returns an empty string in create mode (no ``current_graph``); the builder
-    then behaves exactly as before, constructing the graph purely from the
-    planner's node plan.
-    """
-    if not current_graph:
-        return ""
-    graph_json = json.dumps(compact_graph_for_builder(current_graph), ensure_ascii=False, separators=(",", ":"))
-    return (
-        "# Existing graph to refine (JSON)\n\n"
-        "You are REFINING this existing graph, NOT building from scratch. Apply "
-        "ONLY the change the user instruction describes. Every node and edge the "
-        "change does not affect MUST be preserved verbatim — keep the same node "
-        "ids, the same `data` config, and the same prompt templates. The node "
-        "plan below is the target node set after your change; use the existing "
-        "graph as the source of truth for the config of nodes that carry over.\n\n"
-        f"```json\n{graph_json}\n```\n\n"
-    )
-
-
-def format_start_inputs_section(start_inputs: list[dict[str, Any]]) -> str:
-    """
-    Surface the planner's ``start_inputs`` list to the builder so it can
-    populate ``start.data.variables`` with the exact set of inputs every
-    downstream variable reference will need. Empty list → empty section,
-    because the builder may then declare no input variables (e.g. an
-    Advanced-Chat workflow that only consumes ``sys.query``).
-    """
-    if not start_inputs:
-        return ""
-    lines = ["# Start inputs (copy each entry verbatim into start.data.variables)"]
-    lines.append("")
-    for inp in start_inputs:
-        variable = str(inp.get("variable") or "").strip()
-        label = str(inp.get("label") or "").strip()
-        type_ = str(inp.get("type") or "paragraph").strip()
-        if not variable:
-            continue
-        lines.append(f"- variable={variable!r}  label={label!r}  type={type_!r}")
-    lines.append("")
-    return "\n".join(lines) + "\n"
-
-
-def format_builder_tool_catalogue_section(catalogue_text: str) -> str:
-    """
-    Builder-facing catalogue block. The builder needs the same identifiers
-    the planner saw, plus a stern reminder that ``tool`` nodes MUST set
-    ``provider_id`` / ``provider_name`` / ``tool_name`` to entries that
-    actually exist in this list — hallucinated tools fail at draft sync.
-    """
-    if not catalogue_text.strip():
-        return ""
-    return (
-        "# Available tools (use these exact provider/tool identifiers — "
-        "for each 'tool' node, set provider_id and provider_name to the "
-        "provider portion and tool_name to the tool portion)\n\n"
-        f"{catalogue_text}\n\n"
-    )
-
-
-def format_plan_block(plan_nodes: list[dict[str, Any]]) -> str:
-    """
-    Render the planner output as a numbered list the builder can quote.
-
-    Node IDs use no separator (``node1``, ``node2``, ...) because Dify's
-    run-time placeholder regex requires ``[a-zA-Z0-9_]`` in the node-id
-    slot — a hyphenated id like ``node-1`` would silently fail to match
-    at run time and the literal ``{{#node-1.var#}}`` survives into the
-    LLM prompt.
-
-    For container children (planner emitted a ``"parent": "<label>"`` key),
-    we resolve the parent label to its ``nodeN`` id and surface it on the
-    same line so the builder knows to set ``parentId`` and the
-    ``isInIteration`` / ``isInLoop`` markers on inner nodes.
-    """
-    # First pass: label → node-id so we can resolve "parent" hints.
-    label_to_id: dict[str, str] = {}
-    for idx, node in enumerate(plan_nodes, start=1):
-        label = str(node.get("label") or "")
-        if label and label not in label_to_id:
-            label_to_id[label] = f"node{idx}"
-
-    lines = []
-    for idx, node in enumerate(plan_nodes, start=1):
-        node_id = f"node{idx}"
-        label = node.get("label", "")
-        node_type = node.get("node_type", "")
-        purpose = node.get("purpose", "")
-        parent_label = str(node.get("parent") or "")
-        parent_clause = ""
-        if parent_label:
-            parent_id = label_to_id.get(parent_label, "")
-            if parent_id:
-                parent_clause = f"  parent={parent_id}"
-            else:
-                parent_clause = f"  parent={parent_label!r}"
-        lines.append(f"{idx}. id={node_id}  type={node_type}  label={label!r}{parent_clause}\n   purpose: {purpose}")
-    return "\n".join(lines)
-
-
-def get_builder_system_prompt(mode: str, node_types: Iterable[str] | None = None) -> str:
-    """
-    Build the builder system prompt for ``mode``, with a cheatsheet scoped to
-    ``node_types`` (the planner's chosen node types).
-
-    When ``node_types`` is ``None`` we return the cached full-cheatsheet
-    constant (back-compat default). When the runner passes the plan's node-type
-    set we assemble a fresh prompt carrying only the relevant per-type schemas,
-    so the builder isn't handed config for node types the workflow never uses.
-    """
-    if node_types is None:
-        return BUILDER_SYSTEM_PROMPT_ADVANCED_CHAT if mode == "advanced-chat" else BUILDER_SYSTEM_PROMPT_WORKFLOW
-    return _assemble_builder_system_prompt(mode, node_types)
+def get_node_config_snippet(node_type: str) -> str:
+    """Return the semantic config reference for one leaf node type."""
+    return _NODE_SNIPPETS.get(node_type, "")

api/core/workflow/generator/prompts/node_builder_prompts.py

@@ -0,0 +1,138 @@
+"""Compact prompts for parallel, per-node workflow configuration.
+
+Each call produces only the semantic ``data`` fields for one planned node.
+Canvas wrappers, shared labels, topology, layout, and edge defaults are owned
+by ``WorkflowGenerator`` so completion length scales with node configuration
+rather than with the full ReactFlow graph.
+"""
+
+import json
+from typing import Any
+
+from core.workflow.generator.prompts.builder_prompts import get_node_config_snippet
+
+_CONTAINER_CONFIG_SNIPPETS = {
+    "iteration": """- iteration:
+    {"iterator_selector": ["<src>", "<list-var>"],
+     "output_selector": ["<last-child>", "<out-var>"],
+     "is_parallel": false, "parallel_nums": 10,
+     "error_handle_mode": "terminated", "flatten_output": true}
+    The runner supplies start_node_id, child wrappers, and the synthetic start node.""",
+    "loop": """- loop:
+    {"break_conditions": [{"id": "c1",
+                            "variable_selector": ["<child>", "<var>"],
+                            "comparison_operator": "is",
+                            "value": "<value>"}],
+     "loop_count": 10, "logical_operator": "and"}
+    The runner supplies start_node_id, child wrappers, and the synthetic start node.""",
+}
+
+_NODE_BUILDER_HEAD = """You configure exactly ONE node in a Dify workflow.
+
+Return one JSON object with exactly this shape: {"config": {...}}.
+``config`` contains only node-type-specific ``data`` fields. Do NOT repeat id,
+type, title, desc, selected, position, wrapper fields, edges, or viewport.
+
+Rules:
+- Use only ids from the supplied normalized plan.
+- Placeholder strings use ``{{#node_id.variable#}}``; selector fields use
+  ``["node_id", "variable"]``. Never invent an upstream output.
+- Use the selected model verbatim for llm, question-classifier, and
+  parameter-extractor nodes.
+- Keep prompts/code concise but complete for the user's requested behavior.
+- Emit strict JSON only: no prose, Markdown, comments, or trailing commas.
+
+# Target node schema
+
+"""
+
+
+NODE_BUILDER_USER_PROMPT = """# Target node
+
+id={node_id}, type={node_type}, label={label!r}
+purpose={purpose}
+
+# User instruction
+
+{instruction}
+
+{ideal_output_section}{mode_section}{model_section}{tool_catalogue_section}{start_inputs_section}{existing_config_section}\
+# Normalized plan and topology
+
+{plan_json}
+
+Return {{"config": {{...}}}} for target node {node_id} now.
+"""
+
+
+def get_node_builder_system_prompt(node_type: str) -> str:
+    """Build a one-node prompt containing only that node's semantic schema."""
+    snippet = _CONTAINER_CONFIG_SNIPPETS.get(node_type) or get_node_config_snippet(node_type)
+    return _NODE_BUILDER_HEAD + (snippet or f"- {node_type}: emit the minimum valid config fields.")
+
+
+def format_parallel_plan(
+    plan_nodes: list[dict[str, Any]],
+    plan_edges: list[dict[str, Any]],
+    start_inputs: list[dict[str, Any]] | None = None,
+) -> str:
+    """Serialize the shared plan compactly so every node call has graph context.
+
+    ``start_inputs`` rides along so downstream builders reference the declared
+    ``{{#<start-id>.<variable>#}}`` names instead of guessing them from prose
+    — a guessed name gets auto-injected as a spurious form input later.
+    """
+    payload: dict[str, Any] = {"nodes": plan_nodes, "edges": plan_edges}
+    if start_inputs:
+        payload["start_inputs"] = start_inputs
+    return json.dumps(payload, ensure_ascii=False, separators=(",", ":"))
+
+
+def format_mode_section(mode: str) -> str:
+    """Tell each builder which app mode it is configuring for.
+
+    Matters most in advanced-chat, where ``sys.query`` / ``sys.files`` are the
+    sanctioned way to reference the user's message — without this the model
+    invents start-node variables that postprocess then materializes as
+    spurious form inputs.
+    """
+    if mode == "advanced-chat":
+        return (
+            "# App mode\n\n"
+            "advanced-chat: the user's chat message is available as sys.query and uploaded files "
+            'as sys.files — placeholder {{#sys.query#}}, selector ["sys", "query"]. Reference them '
+            "directly; do NOT invent start-node variables for the chat message.\n\n"
+        )
+    return (
+        "# App mode\n\n"
+        "workflow: there are NO automatic system variables; reference user input only through "
+        "the start node's declared variables.\n\n"
+    )
+
+
+def format_start_inputs_section(start_inputs: list[dict[str, Any]]) -> str:
+    """Render planner-declared inputs for the start-node builder only."""
+    if not start_inputs:
+        return ""
+    lines = ["# Start inputs (copy each entry verbatim into start.data.variables)", ""]
+    for input_ in start_inputs:
+        variable = str(input_.get("variable") or "").strip()
+        if not variable:
+            continue
+        label = str(input_.get("label") or "").strip()
+        type_ = str(input_.get("type") or "paragraph").strip()
+        lines.append(f"- variable={variable!r}  label={label!r}  type={type_!r}")
+    lines.append("")
+    return "\n".join(lines) + "\n"
+
+
+def format_tool_catalogue_section(catalogue_text: str) -> str:
+    """Render exact tool identifiers for a tool-node builder only."""
+    if not catalogue_text.strip():
+        return ""
+    return (
+        "# Available tools (use these exact provider/tool identifiers — "
+        "set provider_id and provider_name to the provider portion and "
+        "tool_name to the tool portion)\n\n"
+        f"{catalogue_text}\n\n"
+    )

api/core/workflow/generator/prompts/planner_prompts.py

@@ -1,13 +1,14 @@
 """
 Planner prompts.
 
-The planner is the lightweight first step in the slim planner→builder pipeline.
+The planner is the lightweight first step in the slim planner→node-builders pipeline.
 It receives the user's natural-language instruction and emits a high-level
-node plan in JSON. The builder later turns that plan into the final graph.
+node and edge plan in JSON. Node builders later produce configs that the runner
+assembles into the final graph.
 
 We keep the planner deliberately short — the heavy lifting (config schemas,
-edge wiring, default values) belongs in the builder. The planner only commits
-to the *which-node-types* decision so the builder gets a tight scaffold.
+default values) belongs in the builders. The planner commits to the minimum
+topology and node types so every builder gets a tight scaffold.
 """
 
 PLANNER_SYSTEM_PROMPT = """You are a Dify workflow planner.
@@ -39,6 +40,8 @@ minimum set of Dify workflow nodes needed to fulfil it, in execution order.
                           mutually-exclusive paths before "end" / "answer".
 - "list-operator"       — filter / sort / slice an array variable (e.g. the items
                           fed into or produced by an "iteration").
+- "assigner"            — update an existing conversation or loop variable.
+- "human-input"         — pause for a person to review, approve, or enter data.
 
 # Rules
 
@@ -97,22 +100,45 @@ minimum set of Dify workflow nodes needed to fulfil it, in execution order.
     variables are automatic — downstream nodes may reference them without
     a ``start_inputs`` entry. In Workflow mode there is NO automatic
     variable; everything the user supplies must be in ``start_inputs``.
-11. Output strictly the JSON object — no prose, no Markdown, no code fences.
+11. Give every node a unique runtime-safe ``id`` using only letters, digits,
+    and underscores. In create mode use ``node1``, ``node2``, ... in node-list
+    order. In refine mode preserve the existing id for every retained node.
+12. Emit the target graph's edges in ``edges``. Each edge is
+    ``{"source": "<id>", "target": "<id>"}``; add ``source_handle`` only
+    for branch nodes: if-else case id, question-classifier class id, or
+    human-input action id. Container children reference the container id in
+    their ``parent`` field; do not emit the synthetic iteration/loop start node.
+13. In refine mode add ``action`` to every retained target node:
+    ``"keep"`` when its data config is unchanged, ``"update"`` when the user
+    asked to change its config, and ``"add"`` for a new node. Removed nodes are
+    omitted. Edge-only rewiring does not require changing a node's action.
+14. Output strictly the JSON object — no prose, no Markdown, no code fences.
+15. Echo the app mode in the ``mode`` output field — exactly "workflow" or
+    "advanced-chat". When the ``# Mode`` section says auto, YOU decide:
+    "workflow" for one-shot automations (run once with form inputs, return a
+    result), "advanced-chat" for conversational multi-turn assistants. The
+    terminal node must match the chosen mode (rule 2): "end" for workflow,
+    "answer" for advanced-chat.
 
 # Output schema
 
 {
   "title": "<≤ 40-char title of the workflow>",
   "description": "<one-sentence summary>",
+  "mode": "workflow | advanced-chat",
   "app_name": "<≤ 30-char product-style name, e.g. 'URL Summarizer'>",
   "icon": "<single emoji that captures the workflow's purpose, e.g. '📰'>",
   "start_inputs": [
     {"variable": "url", "label": "URL", "type": "text-input"}
   ],
   "nodes": [
-    {"label": "Start",      "node_type": "start", "purpose": "..."},
-    {"label": "Summarize",  "node_type": "llm",   "purpose": "..."},
-    {"label": "End",        "node_type": "end",   "purpose": "..."}
+    {"id": "node1", "label": "Start",     "node_type": "start", "purpose": "..."},
+    {"id": "node2", "label": "Summarize", "node_type": "llm",   "purpose": "..."},
+    {"id": "node3", "label": "End",       "node_type": "end",   "purpose": "..."}
+  ],
+  "edges": [
+    {"source": "node1", "target": "node2"},
+    {"source": "node2", "target": "node3"}
   ]
 }
 """
@@ -140,7 +166,8 @@ def format_existing_graph_section(current_graph: dict | None) -> str:
 
     We pass only ids / node-types / titles + edge endpoints here — the planner
     decides *which nodes* exist, so it needs the shape, not the per-node config.
-    The builder gets the full graph JSON to preserve untouched node config.
+    Node builders receive only the config of a node marked ``update``;
+    configs marked ``keep`` are reused directly.
     """
     if not current_graph:
         return ""
@@ -156,7 +183,13 @@ def format_existing_graph_section(current_graph: dict | None) -> str:
     for edge in edges:
         if not isinstance(edge, dict):
             continue
-        edge_lines.append(f"- {edge.get('source', '')} -> {edge.get('target', '')}")
+        # Branch wiring (if-else case ids, classifier class ids, human-input
+        # action ids) lives in ``sourceHandle``. The planner is the only
+        # source of edges for the rebuilt graph, so the real handle must be
+        # surfaced here or refine silently rewires branches.
+        handle = str(edge.get("sourceHandle") or "")
+        handle_suffix = f" (source_handle={handle!r})" if handle and handle != "source" else ""
+        edge_lines.append(f"- {edge.get('source', '')} -> {edge.get('target', '')}{handle_suffix}")
     nodes_block = "\n".join(node_lines) or "(none)"
     edges_block = "\n".join(edge_lines) or "(none)"
     return (
@@ -166,7 +199,9 @@ def format_existing_graph_section(current_graph: dict | None) -> str:
         "node list to reflect that change while keeping everything the "
         "instruction does not mention — preserve existing nodes, their order, "
         "and their labels wherever the change leaves them untouched. Only add, "
-        "remove, or rename nodes the requested change actually requires.\n\n"
+        "remove, or rename nodes the requested change actually requires. "
+        "For every retained edge, copy its source_handle verbatim from the "
+        "list below — branch wiring must survive the refine unchanged.\n\n"
         f"Current nodes:\n{nodes_block}\n\n"
         f"Current edges:\n{edges_block}\n\n"
     )

api/core/workflow/generator/runner.py

@@ -1,14 +1,14 @@
 """
 Workflow generator runner.
 
-Slim planner→builder pipeline. Pure domain logic; the model instance is
+Slim planner→parallel-node-builder pipeline. Pure domain logic; the model instance is
 injected by ``WorkflowGeneratorService`` so this module stays cleanly
 separated from the infrastructure layer.
 
 Pipeline:
 
     1. PLANNER  — short LLM call producing a high-level node list.
-    2. BUILDER  — structured-output LLM call producing the full graph JSON.
+    2. BUILDERS — bounded concurrent LLM calls producing compact node configs.
     3. POSTPROC — fill safe defaults, lay nodes out left-to-right, dedupe
                   edge ids, and run a final structural sanity check.
 
@@ -20,7 +20,8 @@ Intentionally NOT here (deferred to a future iteration):
     - Tool / model catalogue filtering
 
 If quality regresses below product threshold we add those back; for now the
-single planner+builder pair shipped behind cmd+k `/create` is enough.
+planner and bounded parallel node builders shipped behind cmd+k `/create` are
+enough.
 """
 
 import json
@@ -28,17 +29,22 @@ import logging
 import re
 import time
 from collections.abc import Iterator
+from concurrent.futures import ThreadPoolExecutor, as_completed
+from copy import deepcopy
 from typing import Any, ClassVar, cast
 
 import json_repair
 
-from core.workflow.generator.prompts.builder_prompts import (
-    BUILDER_USER_PROMPT,
-    format_builder_existing_graph_section,
-    format_builder_tool_catalogue_section,
-    format_plan_block,
+from configs import dify_config
+from core.workflow.generator.prompts.node_builder_prompts import (
+    NODE_BUILDER_USER_PROMPT,
+    format_mode_section,
+    format_parallel_plan,
     format_start_inputs_section,
-    get_builder_system_prompt,
+    get_node_builder_system_prompt,
+)
+from core.workflow.generator.prompts.node_builder_prompts import (
+    format_tool_catalogue_section as format_node_tool_catalogue_section,
 )
 from core.workflow.generator.prompts.planner_prompts import (
     PLANNER_SYSTEM_PROMPT,
@@ -55,6 +61,7 @@ from core.workflow.generator.types import (
     WorkflowGenerateErrorDict,
     WorkflowGenerateResultDict,
     WorkflowGenerationMode,
+    WorkflowGenerationModeRequest,
 )
 from graphon.enums import BuiltinNodeTypes
 from graphon.model_runtime.entities.llm_entities import LLMResult
@@ -96,11 +103,31 @@ _DEFAULT_FILE_UPLOAD_METHODS = ("local_file", "remote_url")
 
 # Token ceiling for the planner call when the caller didn't pin one. The plan
 # is a short JSON node list (a handful of nodes with labels/purposes), so this
-# is generous headroom while still bounding a runaway response. The builder is
-# left on the caller's budget — it emits the full graph and genuinely needs it.
+# is generous headroom while still bounding a runaway response. Builder calls
+# keep the caller's budget so complex node configs are not truncated.
 _PLANNER_DEFAULT_MAX_TOKENS = 4096
 
 
+# Per-node calls trade a larger request count for a shorter critical path.
+# The cap comes from ``WORKFLOW_GENERATOR_NODE_BUILDER_MAX_WORKERS`` (default 6,
+# enough to run the planner's recommended 3–6-node plans as a single wave);
+# provider rate-limit bursts are absorbed by ``_invoke_with_retry``'s bounded
+# backoff, and operators can dial the env var back down if their provider is
+# stricter. Read at call time so tests (and live config reloads) can adjust it
+# without re-importing.
+def _node_builder_max_workers() -> int:
+    return dify_config.WORKFLOW_GENERATOR_NODE_BUILDER_MAX_WORKERS
+
+
+_MODEL_NODE_TYPES = frozenset(
+    {
+        BuiltinNodeTypes.LLM,
+        BuiltinNodeTypes.QUESTION_CLASSIFIER,
+        BuiltinNodeTypes.PARAMETER_EXTRACTOR,
+    }
+)
+
+
 # Appended as a trailing user message on the SECOND (and only) attempt when
 # the first response wasn't parseable as JSON. Keep this terse — the model
 # already has its full instructions in the original system message; this is
@@ -110,6 +137,12 @@ _JSON_RETRY_HINT = (
     "Do not include any prose, markdown code fences, comments, or trailing commas."
 )
 
+_PLANNER_SCHEMA_RETRY_HINT = (
+    "Your plan did not match the required topology schema. Return the complete plan again with "
+    "a unique non-empty id on every node and a non-empty edges array whose source and target "
+    "reference those ids. Return ONLY the JSON object."
+)
+
 
 # Provider hiccups we retry: a dropped connection, a 5xx, or a rate-limit are
 # all transient — the same request usually succeeds moments later. We do NOT
@@ -189,14 +222,58 @@ def _result_with_errors(
 def _with_mode(result: WorkflowGenerateResultDict, mode: WorkflowGenerationMode) -> WorkflowGenerateResultDict:
     """Stamp the resolved concrete ``mode`` onto a result envelope.
 
-    ``mode="auto"`` requests are resolved to a concrete mode before planning;
-    echoing it back lets the frontend pick the right app type to create. It's
-    present for explicit modes too so the response shape stays uniform.
+    ``mode="auto"`` requests are resolved to a concrete mode from the planner
+    output; echoing it back lets the frontend pick the right app type to
+    create. It's present for explicit modes too so the response shape stays
+    uniform.
     """
     result["mode"] = mode
     return result
 
 
+def _fallback_mode(mode: WorkflowGenerationModeRequest) -> WorkflowGenerationMode:
+    """Concrete mode for envelopes emitted before the planner resolved one.
+
+    ``auto`` maps to the conversational default — the same never-fail fallback
+    the old standalone classifier used — so ``result.mode`` never leaks the
+    ``auto`` sentinel to the frontend.
+    """
+    return "advanced-chat" if mode == "auto" else mode
+
+
+def _planner_prompt_mode(mode: WorkflowGenerationModeRequest) -> str:
+    """Mode string interpolated into the planner user prompt.
+
+    For ``auto`` the value is self-describing so the planner knows the choice
+    is delegated to it (system-prompt rule 15).
+    """
+    return "auto (choose workflow or advanced-chat)" if mode == "auto" else mode
+
+
+def _resolve_generation_mode(
+    requested: WorkflowGenerationModeRequest, plan: PlannerResultDict
+) -> WorkflowGenerationMode:
+    """Resolve the request mode into the concrete generation mode.
+
+    An explicit request always wins — a contradictory planner ``mode`` field is
+    ignored. For ``auto``: trust the planner's echoed ``mode``, else infer from
+    the plan's terminal node type (the structural source of truth the graph is
+    validated against), else fall back to the conversational default. Lenient
+    on purpose — a bad ``mode`` value must never fail the plan.
+    """
+    if requested != "auto":
+        return requested
+    planner_mode = str(plan.get("mode") or "").strip().lower()
+    if planner_mode in ("workflow", "advanced-chat"):
+        return cast(WorkflowGenerationMode, planner_mode)
+    node_types = {str(node.get("node_type") or "") for node in plan.get("nodes") or [] if isinstance(node, dict)}
+    if BuiltinNodeTypes.ANSWER in node_types:
+        return "advanced-chat"
+    if BuiltinNodeTypes.END in node_types:
+        return "workflow"
+    return "advanced-chat"
+
+
 def _build_plan_event(
     *,
     plan: PlannerResultDict,
@@ -255,7 +332,7 @@ class WorkflowGenerator:
         provider: str,
         model_name: str,
         model_mode: str,
-        mode: WorkflowGenerationMode,
+        mode: WorkflowGenerationModeRequest,
         instruction: str,
         ideal_output: str = "",
         tool_catalogue_text: str = "",
@@ -263,20 +340,26 @@ class WorkflowGenerator:
         current_graph: dict[str, Any] | None = None,
     ) -> WorkflowGenerateResultDict:
         """
-        Run planner → builder → postprocess and return a graph payload.
+        Run planner → node builders → postprocess and return a graph payload.
+
+        ``mode`` accepts the ``"auto"`` sentinel — the planner then chooses the
+        concrete mode itself (echoed in its ``mode`` output field) so no extra
+        classification call is needed; the resolution is stamped onto the
+        result envelope.
 
         ``current_graph`` switches the pipeline from create mode to REFINE
-        mode: the existing draft graph is injected into both the planner
-        (compact node/edge summary) and the builder (full JSON) so the LLM
-        amends the graph the user is editing instead of inventing a new one.
-        ``None`` (the default) is plain create-from-scratch behaviour.
+        mode: the existing draft graph is summarized for the planner. Node
+        builders receive only the config of the node they update, while configs
+        marked ``keep`` are reused without an LLM call. ``None`` (the default)
+        is plain create-from-scratch behaviour.
 
         ``tool_catalogue_text`` is the formatted list of installed tools for
         the calling tenant (see ``tool_catalogue.build_tool_catalogue`` /
         ``format_tool_catalogue``). It's injected into both the planner and
         builder prompts so the LLM can pick concrete ``provider/tool``
-        identifiers instead of inventing names; an empty string skips the
-        section entirely (useful for unit tests).
+        identifiers instead of inventing names; node builders receive it
+        only for tool nodes. An empty string skips the section entirely (useful
+        for unit tests).
 
         ``installed_tools`` is the structural sibling — a set of
         ``(provider_name, tool_name)`` pairs the validator consults to reject
@@ -316,7 +399,7 @@ class WorkflowGenerator:
         # The event generator always emits exactly one result envelope; this
         # fallback only guards against a future refactor that forgets to.
         if result is None:
-            result = _with_mode(_empty_result(), mode)
+            result = _with_mode(_empty_result(), _fallback_mode(mode))
         return result
 
     @classmethod
@@ -328,7 +411,7 @@ class WorkflowGenerator:
         provider: str,
         model_name: str,
         model_mode: str,
-        mode: WorkflowGenerationMode,
+        mode: WorkflowGenerationModeRequest,
         instruction: str,
         ideal_output: str = "",
         tool_catalogue_text: str = "",
@@ -368,7 +451,7 @@ class WorkflowGenerator:
         provider: str,
         model_name: str,
         model_mode: str,
-        mode: WorkflowGenerationMode,
+        mode: WorkflowGenerationModeRequest,
         instruction: str,
         ideal_output: str = "",
         tool_catalogue_text: str = "",
@@ -376,7 +459,7 @@ class WorkflowGenerator:
         current_graph: dict[str, Any] | None = None,
     ) -> Iterator[tuple[str, dict[str, Any]]]:
         """
-        Drive planner → builder → postprocess and yield generation events.
+        Drive planner → node builders → postprocess and yield generation events.
 
         Shared core for both ``generate_workflow_graph`` (keeps only the final
         ``result``) and ``generate_workflow_graph_stream`` (streams every
@@ -402,11 +485,16 @@ class WorkflowGenerator:
             ),
         )
         if plan_err is not None:
-            yield "result", cast(dict[str, Any], _with_mode(_result_with_errors(_empty_result(), [plan_err]), mode))
+            failed = _with_mode(_result_with_errors(_empty_result(), [plan_err]), _fallback_mode(mode))
+            yield "result", cast(dict[str, Any], failed)
             return
 
         # The lambda return is non-None when no error fired — narrow it for type-checkers.
         plan = cast(PlannerResultDict, plan)
+        # ``auto`` requests resolve here — the planner echoed its mode choice
+        # (or we infer it from the plan's terminal node). Explicit modes pass
+        # through unchanged. Everything downstream uses the concrete mode.
+        resolved_mode = _resolve_generation_mode(mode, plan)
         plan_nodes: list[dict[str, Any]] = cast(list[dict[str, Any]], plan.get("nodes", []))
         if not plan_nodes:
             empty_plan = _with_mode(
@@ -414,15 +502,12 @@ class WorkflowGenerator:
                     _empty_result(),
                     [_err(WorkflowGenerateErrorCode.EMPTY_PLAN, "Planner returned no nodes")],
                 ),
-                mode,
+                resolved_mode,
             )
             yield "result", cast(dict[str, Any], empty_plan)
             return
 
-        # A single LLM cannot select multiple retrieval outputs as context.
-        # Make the required template fan-in explicit in the plan so the
-        # builder receives its schema and assigns stable sequential ids.
-        cls._insert_multi_retrieval_template_plan(plan_nodes)
+        plan_edges = [cast(dict[str, Any], edge) for edge in (plan.get("edges") or []) if isinstance(edge, dict)]
 
         # Planner-supplied user-input declarations. The builder uses these to
         # populate ``start.data.variables`` so downstream ``{#start.<var>#}``
@@ -436,34 +521,48 @@ class WorkflowGenerator:
 
         # First event the stream sees: the high-level plan, before the slower
         # builder call. Non-streaming callers ignore it.
-        yield "plan", _build_plan_event(plan=plan, plan_nodes=plan_nodes, start_inputs=start_inputs, mode=mode)
+        yield "plan", _build_plan_event(plan=plan, plan_nodes=plan_nodes, start_inputs=start_inputs, mode=resolved_mode)
 
         # ── 2. BUILDER ────────────────────────────────────────────────────
-        graph, build_err = cls._run_stage(
-            stage="Builder",
-            failure_fallback_message="Failed to build workflow graph",
-            run=lambda: cls._run_builder(
+        builder_started_at = time.monotonic()
+
+        def build_graph() -> GraphDict:
+            return cls._run_parallel_node_builders(
                 model_instance=model_instance,
                 model_parameters=model_parameters,
                 provider=provider,
                 model_name=model_name,
                 model_mode=model_mode,
-                mode=mode,
+                mode=resolved_mode,
                 instruction=instruction,
                 ideal_output=ideal_output,
                 plan_nodes=plan_nodes,
+                plan_edges=plan_edges,
                 tool_catalogue_text=tool_catalogue_text,
                 start_inputs=start_inputs,
                 current_graph=current_graph,
-            ),
+            )
+
+        graph, build_err = cls._run_stage(
+            stage="Builder",
+            failure_fallback_message="Failed to build workflow graph",
+            run=build_graph,
+        )
+        logger.info(
+            "Workflow generator: node builders completed nodes=%s elapsed_ms=%.1f",
+            len(plan_nodes),
+            (time.monotonic() - builder_started_at) * 1000,
         )
         if build_err is not None:
-            yield "result", cast(dict[str, Any], _with_mode(_result_with_errors(_empty_result(), [build_err]), mode))
+            yield (
+                "result",
+                cast(dict[str, Any], _with_mode(_result_with_errors(_empty_result(), [build_err]), resolved_mode)),
+            )
             return
         graph = cast(GraphDict, graph)
 
         # ── 3. POSTPROC + VALIDATE ────────────────────────────────────────
-        graph = cls._postprocess_graph(graph=graph, mode=mode)
+        graph = cls._postprocess_graph(graph=graph, mode=resolved_mode)
 
         # ``app_name`` / ``icon`` are planner display metadata; both default
         # to "" when the LLM omits them — the FE owns the fallback.
@@ -475,13 +574,13 @@ class WorkflowGenerator:
             "error": "",
             "errors": [],
         }
-        _with_mode(result, mode)
+        _with_mode(result, resolved_mode)
 
         # Final structural sanity check — fail closed if start/end shape is
         # wrong, container topology is broken, a tool was hallucinated, or a
         # variable reference points at a node that won't expose it. We still
         # return the partial graph so the caller can debug or salvage it.
-        structural_errors = cls._validate_structure(graph=graph, mode=mode, installed_tools=installed_tools)
+        structural_errors = cls._validate_structure(graph=graph, mode=resolved_mode, installed_tools=installed_tools)
         if structural_errors:
             logger.warning("Workflow generator: structural validation failed: %s", structural_errors)
             yield "result", cast(dict[str, Any], _result_with_errors(result, structural_errors))
@@ -622,14 +721,14 @@ class WorkflowGenerator:
         *,
         model_instance,
         model_parameters: dict[str, Any],
-        mode: WorkflowGenerationMode,
+        mode: WorkflowGenerationModeRequest,
         instruction: str,
         ideal_output: str,
         tool_catalogue_text: str,
         current_graph: dict[str, Any] | None = None,
     ) -> PlannerResultDict:
         user_prompt = PLANNER_USER_PROMPT.format(
-            mode=mode,
+            mode=_planner_prompt_mode(mode),
             instruction=instruction.strip(),
             existing_graph_section=format_existing_graph_section(current_graph),
             ideal_output_section=format_ideal_output_section(ideal_output),
@@ -639,59 +738,65 @@ class WorkflowGenerator:
             SystemPromptMessage(content=PLANNER_SYSTEM_PROMPT),
             UserPromptMessage(content=user_prompt),
         ]
+        clamped_parameters = _clamp_for_planner(model_parameters)
         parsed = cls._invoke_and_parse_json(
             model_instance=model_instance,
             messages=messages,
-            model_parameters=_clamp_for_planner(model_parameters),
+            model_parameters=clamped_parameters,
             stage="Planner",
         )
+        try:
+            return cls._validate_planner_schema(parsed)
+        except _StageSchemaError:
+            logger.info("Workflow generator: planner schema invalid; retrying once")
+        parsed = cls._invoke_and_parse_json(
+            model_instance=model_instance,
+            messages=[*messages, UserPromptMessage(content=_PLANNER_SCHEMA_RETRY_HINT)],
+            model_parameters=clamped_parameters,
+            stage="Planner",
+        )
+        return cls._validate_planner_schema(parsed)
 
+    @staticmethod
+    def _validate_planner_schema(parsed: dict[str, Any]) -> PlannerResultDict:
+        """Require the single planner contract consumed by node builders."""
         nodes = parsed.get("nodes")
         if not isinstance(nodes, list):
             raise _StageSchemaError("Planner", "missing 'nodes' array")
+        if not nodes:
+            return cast(PlannerResultDict, parsed)
+
+        node_ids: set[str] = set()
         for node in nodes:
-            if not isinstance(node, dict) or "node_type" not in node:
+            if not isinstance(node, dict) or not node.get("node_type"):
                 raise _StageSchemaError("Planner", f"malformed node entry: {node!r}")
+            node_id = node.get("id")
+            if not isinstance(node_id, str) or not node_id.strip():
+                raise _StageSchemaError("Planner", f"node missing non-empty id: {node!r}")
+            if node_id in node_ids:
+                raise _StageSchemaError("Planner", f"duplicate node id: {node_id!r}")
+            node_ids.add(node_id)
+
+        edges = parsed.get("edges")
+        if not isinstance(edges, list) or not edges:
+            raise _StageSchemaError("Planner", "missing non-empty 'edges' array")
+        for edge in edges:
+            if not isinstance(edge, dict):
+                raise _StageSchemaError("Planner", f"malformed edge entry: {edge!r}")
+            source = edge.get("source")
+            target = edge.get("target")
+            if not isinstance(source, str) or not isinstance(target, str):
+                raise _StageSchemaError("Planner", f"edge missing source or target: {edge!r}")
+            if source not in node_ids or target not in node_ids:
+                raise _StageSchemaError("Planner", f"edge references unknown node: {edge!r}")
 
         return cast(PlannerResultDict, parsed)
 
-    # ------------------------------------------------------------------
-    # Plan normalization
-    # ------------------------------------------------------------------
-    @staticmethod
-    def _insert_multi_retrieval_template_plan(plan_nodes: list[dict[str, Any]]) -> None:
-        """Insert the unambiguous multi-retrieval template step when omitted.
-
-        Multiple LLM nodes make ownership ambiguous, so that case remains in
-        the planner's hands. With exactly one LLM, every independent retrieval
-        result can safely fan into one template immediately before that LLM.
-        """
-        node_types = [str(node.get("node_type") or "") for node in plan_nodes]
-        if node_types.count(BuiltinNodeTypes.KNOWLEDGE_RETRIEVAL) < 2:
-            return
-        if node_types.count(BuiltinNodeTypes.LLM) != 1:
-            return
-        if BuiltinNodeTypes.TEMPLATE_TRANSFORM in node_types:
-            return
-
-        llm_index = node_types.index(BuiltinNodeTypes.LLM)
-        retrievals_before_llm = node_types[:llm_index].count(BuiltinNodeTypes.KNOWLEDGE_RETRIEVAL)
-        if retrievals_before_llm < 2:
-            return
-        plan_nodes.insert(
-            llm_index,
-            {
-                "label": "Combine Knowledge",
-                "node_type": BuiltinNodeTypes.TEMPLATE_TRANSFORM,
-                "purpose": "Combine every knowledge retrieval result into one labelled context for the LLM.",
-            },
-        )
-
     # ------------------------------------------------------------------
     # Builder
     # ------------------------------------------------------------------
     @classmethod
-    def _run_builder(
+    def _run_parallel_node_builders(
         cls,
         *,
         model_instance,
@@ -703,53 +808,275 @@ class WorkflowGenerator:
         instruction: str,
         ideal_output: str,
         plan_nodes: list[dict[str, Any]],
+        plan_edges: list[dict[str, Any]],
         tool_catalogue_text: str,
-        start_inputs: list[dict[str, Any]] | None = None,
-        current_graph: dict[str, Any] | None = None,
+        start_inputs: list[dict[str, Any]],
+        current_graph: dict[str, Any] | None,
     ) -> GraphDict:
-        user_prompt = BUILDER_USER_PROMPT.format(
+        """Build changed node configs concurrently and expand them into a graph.
+
+        Refine plans can mark existing nodes as ``keep``; those nodes bypass
+        the model entirely and retain their full data config. Every other node
+        gets one compact call, with at most ``_node_builder_max_workers()``
+        calls in flight. Any fragment failure aborts the graph, preserving the
+        generator's existing fail-closed contract.
+        """
+        existing_by_id = {
+            str(node.get("id")): node
+            for node in ((current_graph or {}).get("nodes") or [])
+            if isinstance(node, dict) and node.get("id")
+        }
+        existing_edges = [edge for edge in ((current_graph or {}).get("edges") or []) if isinstance(edge, dict)]
+        nodes_to_build = [
+            node for node in plan_nodes if not (node.get("action") == "keep" and str(node.get("id")) in existing_by_id)
+        ]
+
+        # Shared across every builder call in this request — compute once.
+        plan_json = format_parallel_plan(plan_nodes, plan_edges, start_inputs)
+        mode_section = format_mode_section(mode)
+
+        configs_by_id: dict[str, dict[str, Any]] = {}
+        if nodes_to_build:
+            max_workers = min(_node_builder_max_workers(), len(nodes_to_build))
+            with ThreadPoolExecutor(max_workers=max_workers, thread_name_prefix="workflow-node-builder") as executor:
+                futures = {
+                    executor.submit(
+                        cls._run_node_builder,
+                        model_instance=model_instance,
+                        model_parameters=model_parameters,
+                        provider=provider,
+                        model_name=model_name,
+                        model_mode=model_mode,
+                        mode_section=mode_section,
+                        instruction=instruction,
+                        ideal_output=ideal_output,
+                        target_node=node,
+                        plan_json=plan_json,
+                        tool_catalogue_text=tool_catalogue_text,
+                        start_inputs=start_inputs,
+                        existing_node=existing_by_id.get(str(node.get("id"))),
+                    ): str(node.get("id"))
+                    for node in nodes_to_build
+                }
+                try:
+                    for future in as_completed(futures):
+                        node_id = futures[future]
+                        configs_by_id[node_id] = future.result()
+                except BaseException:
+                    # Fail fast: one failed fragment aborts the whole graph, so
+                    # queued builder calls would only burn quota and delay the
+                    # error envelope. In-flight calls cannot be interrupted;
+                    # they finish while the pool shuts down.
+                    for pending in futures:
+                        pending.cancel()
+                    raise
+
+        return cls._assemble_parallel_graph(
+            plan_nodes=plan_nodes,
+            plan_edges=plan_edges,
+            configs_by_id=configs_by_id,
+            existing_by_id=existing_by_id,
+            existing_edges=existing_edges,
+        )
+
+    @classmethod
+    def _run_node_builder(
+        cls,
+        *,
+        model_instance,
+        model_parameters: dict[str, Any],
+        provider: str,
+        model_name: str,
+        model_mode: str,
+        mode_section: str,
+        instruction: str,
+        ideal_output: str,
+        target_node: dict[str, Any],
+        plan_json: str,
+        tool_catalogue_text: str,
+        start_inputs: list[dict[str, Any]],
+        existing_node: dict[str, Any] | None,
+    ) -> dict[str, Any]:
+        """Generate only the semantic config for one normalized plan node."""
+        node_id = str(target_node.get("id") or "")
+        node_type = str(target_node.get("node_type") or "")
+        model_section = ""
+        if node_type in _MODEL_NODE_TYPES:
+            model_section = (
+                f"# Selected model (copy verbatim)\n\nprovider={provider}, name={model_name}, mode={model_mode}\n\n"
+            )
+        existing_config_section = ""
+        if existing_node:
+            existing_data = existing_node.get("data") if isinstance(existing_node.get("data"), dict) else {}
+            existing_config_section = (
+                "# Existing config to preserve unless the instruction changes it\n\n"
+                f"{json.dumps(existing_data, ensure_ascii=False, separators=(',', ':'))}\n\n"
+            )
+        user_prompt = NODE_BUILDER_USER_PROMPT.format(
+            node_id=node_id,
+            node_type=node_type,
+            label=str(target_node.get("label") or ""),
+            purpose=str(target_node.get("purpose") or ""),
             instruction=instruction.strip(),
             ideal_output_section=format_ideal_output_section(ideal_output),
-            existing_graph_section=format_builder_existing_graph_section(current_graph),
-            provider=provider,
-            name=model_name,
-            mode_label=model_mode,
-            plan_block=format_plan_block(plan_nodes),
-            tool_catalogue_section=format_builder_tool_catalogue_section(tool_catalogue_text),
-            start_inputs_section=format_start_inputs_section(start_inputs or []),
+            mode_section=mode_section,
+            model_section=model_section,
+            tool_catalogue_section=(
+                format_node_tool_catalogue_section(tool_catalogue_text) if node_type == BuiltinNodeTypes.TOOL else ""
+            ),
+            start_inputs_section=(
+                format_start_inputs_section(start_inputs) if node_type == BuiltinNodeTypes.START else ""
+            ),
+            existing_config_section=existing_config_section,
+            plan_json=plan_json,
         )
-        # Scope the builder cheatsheet to exactly the node types the planner
-        # chose, so the prompt carries each type's FULL schema (e.g. a file
-        # start variable's required ``allowed_file_types``) without dragging in
-        # config for unrelated node types.
-        plan_node_types = {
-            str(node.get("node_type") or "").strip() for node in plan_nodes if str(node.get("node_type") or "").strip()
-        }
-        messages = [
-            SystemPromptMessage(content=get_builder_system_prompt(mode, plan_node_types)),
-            UserPromptMessage(content=user_prompt),
-        ]
         parsed = cls._invoke_and_parse_json(
             model_instance=model_instance,
-            messages=messages,
+            messages=[
+                SystemPromptMessage(content=get_node_builder_system_prompt(node_type)),
+                UserPromptMessage(content=user_prompt),
+            ],
             model_parameters=model_parameters,
-            stage="Builder",
+            stage=f"Builder {node_id}",
         )
+        config = parsed.get("config")
+        if not isinstance(config, dict):
+            raise _StageSchemaError(f"Builder {node_id}", "missing 'config' object")
+        return cast(dict[str, Any], config)
 
-        nodes = parsed.get("nodes")
-        edges = parsed.get("edges")
-        if not isinstance(nodes, list) or not isinstance(edges, list):
-            raise _StageSchemaError("Builder", "graph missing 'nodes' or 'edges' arrays")
+    @classmethod
+    def _assemble_parallel_graph(
+        cls,
+        *,
+        plan_nodes: list[dict[str, Any]],
+        plan_edges: list[dict[str, Any]],
+        configs_by_id: dict[str, dict[str, Any]],
+        existing_by_id: dict[str, dict[str, Any]],
+        existing_edges: list[dict[str, Any]] | None = None,
+    ) -> GraphDict:
+        """Expand compact node configs and planner topology into graph JSON.
 
-        viewport = parsed.get("viewport") or _DEFAULT_VIEWPORT
-        return cast(
-            GraphDict,
-            {
-                "nodes": nodes,
-                "edges": edges,
-                "viewport": viewport,
-            },
-        )
+        ``existing_edges`` (refine only) preserves wiring the planner cannot
+        express: the synthetic ``<container>start`` entry edge keeps its
+        existing target instead of being re-pointed at whichever child the
+        planner happened to list first.
+        """
+        label_to_id = {
+            str(node.get("label")): str(node.get("id")) for node in plan_nodes if node.get("label") and node.get("id")
+        }
+        type_by_id = {str(node.get("id")): str(node.get("node_type") or "") for node in plan_nodes}
+        children_by_parent: dict[str, list[str]] = {}
+        nodes: list[dict[str, Any]] = []
+
+        for planned in plan_nodes:
+            node_id = str(planned.get("id") or "")
+            node_type = str(planned.get("node_type") or "")
+            existing = existing_by_id.get(node_id)
+            node: dict[str, Any]
+            if planned.get("action") == "keep" and existing is not None:
+                node = deepcopy(existing)
+            else:
+                config = dict(configs_by_id.get(node_id) or {})
+                for shared_key in ("type", "title", "desc", "selected"):
+                    config.pop(shared_key, None)
+                data: dict[str, Any] = {
+                    "type": node_type,
+                    "title": str(planned.get("label") or node_id),
+                    "desc": str(planned.get("purpose") or ""),
+                    **config,
+                }
+                node = deepcopy(existing) if existing is not None else {"id": node_id}
+                node["id"] = node_id
+                node["data"] = data
+
+            parent_ref = str(planned.get("parent") or "")
+            parent_id = label_to_id.get(parent_ref, parent_ref)
+            if not parent_id and str(node.get("parentId") or "") in type_by_id:
+                # Kept nodes rarely re-state containment — recover the parent
+                # from the deepcopied wrapper so entry-edge synthesis still
+                # counts this child.
+                parent_id = str(node["parentId"])
+            if parent_id:
+                child_index = len(children_by_parent.get(parent_id, []))
+                node["parentId"] = parent_id
+                node.setdefault("position", {"x": 240 + 260 * child_index, "y": 60})
+                node.setdefault("data", {})
+                parent_type = type_by_id.get(parent_id)
+                if parent_type == BuiltinNodeTypes.ITERATION:
+                    node["data"].setdefault("isInIteration", True)
+                    node["data"].setdefault("iteration_id", parent_id)
+                elif parent_type == BuiltinNodeTypes.LOOP:
+                    node["data"].setdefault("isInLoop", True)
+                    node["data"].setdefault("loop_id", parent_id)
+                children_by_parent.setdefault(parent_id, []).append(node_id)
+            elif node.get("parentId"):
+                # The container was dropped from the plan: strip the stale
+                # containment markers so the kept node rejoins the top level
+                # (and its auto-layout) instead of pointing at a deleted parent.
+                for wrapper_key in ("parentId", "extent", "zIndex", "position", "positionAbsolute"):
+                    node.pop(wrapper_key, None)
+                if isinstance(node.get("data"), dict):
+                    for marker_key in ("isInIteration", "iteration_id", "isInLoop", "loop_id"):
+                        node["data"].pop(marker_key, None)
+
+            nodes.append(node)
+            if node_type in cls._CONTAINER_TYPES:
+                start_id = f"{node_id}start"
+                node.setdefault("data", {})["start_node_id"] = start_id
+                node.setdefault("width", 808)
+                node.setdefault("height", 204)
+                node.setdefault("zIndex", 1)
+                is_iteration = node_type == BuiltinNodeTypes.ITERATION
+                nodes.append(
+                    {
+                        "id": start_id,
+                        "type": "custom-iteration-start" if is_iteration else "custom-loop-start",
+                        "parentId": node_id,
+                        "extent": "parent",
+                        "draggable": False,
+                        "selectable": False,
+                        "zIndex": 1002,
+                        "position": {"x": 60, "y": 78},
+                        "data": {
+                            "type": "iteration-start" if is_iteration else "loop-start",
+                            "title": "",
+                            "desc": "",
+                            "selected": False,
+                            "isInIteration" if is_iteration else "isInLoop": True,
+                        },
+                    }
+                )
+
+        edges: list[dict[str, Any]] = []
+        for planned_edge in plan_edges:
+            edge: dict[str, Any] = {
+                "source": str(planned_edge.get("source") or ""),
+                "target": str(planned_edge.get("target") or ""),
+            }
+            source_handle = planned_edge.get("source_handle") or planned_edge.get("sourceHandle")
+            target_handle = planned_edge.get("target_handle") or planned_edge.get("targetHandle")
+            if source_handle:
+                edge["sourceHandle"] = str(source_handle)
+            if target_handle:
+                edge["targetHandle"] = str(target_handle)
+            edges.append(edge)
+
+        # Synthesize each container's entry edge. Refine keeps the existing
+        # entry target when it is still a child — the planner's node listing
+        # order says nothing about execution order inside a kept container.
+        planned_sources = {str(edge.get("source") or "") for edge in edges}
+        existing_entry_targets = {
+            str(edge.get("source") or ""): str(edge.get("target") or "") for edge in (existing_edges or [])
+        }
+        for parent_id, child_ids in children_by_parent.items():
+            start_id = f"{parent_id}start"
+            if not child_ids or start_id in planned_sources:
+                continue
+            preferred = existing_entry_targets.get(start_id, "")
+            entry_target = preferred if preferred in child_ids else child_ids[0]
+            edges.append({"source": start_id, "target": entry_target})
+
+        return cast(GraphDict, {"nodes": nodes, "edges": edges, "viewport": _DEFAULT_VIEWPORT})
 
     # ------------------------------------------------------------------
     # Postprocessing
@@ -1225,6 +1552,11 @@ class WorkflowGenerator:
             return var == "output"
         if node_type == BuiltinNodeTypes.LIST_OPERATOR:
             return var in {"result", "first_record", "last_record"}
+        if node_type == BuiltinNodeTypes.HUMAN_INPUT:
+            return any(
+                isinstance(item, dict) and item.get("output_variable_name") == var
+                for item in (data.get("inputs") or [])
+            )
         # Other node types (if-else, iteration-start, loop-start, ...) don't
         # produce outputs of their own.
         return False
@@ -1247,6 +1579,15 @@ class WorkflowGenerator:
                 if isinstance(parameter, dict) and isinstance(parameter.get("name"), str)
             ]
             return parameters[0] if len(parameters) == 1 else None
+        if node_type == BuiltinNodeTypes.HUMAN_INPUT:
+            human_outputs: list[str] = []
+            for item in data.get("inputs") or []:
+                if not isinstance(item, dict):
+                    continue
+                output_name = item.get("output_variable_name")
+                if isinstance(output_name, str):
+                    human_outputs.append(output_name)
+            return human_outputs[0] if len(human_outputs) == 1 else None
         if not isinstance(node_type, str):
             return None
         single_output_by_type: dict[str, str] = {
@@ -1533,6 +1874,12 @@ class WorkflowGenerator:
                     for klass in (data.get("classes") or [])
                     if isinstance(klass, dict) and klass.get("id")
                 ]
+            elif node_type == BuiltinNodeTypes.HUMAN_INPUT:
+                branch_handles = [
+                    str(action["id"])
+                    for action in (data.get("user_actions") or [])
+                    if isinstance(action, dict) and action.get("id")
+                ]
             else:
                 continue
 
@@ -1941,8 +2288,8 @@ class WorkflowGenerator:
         """
         Validate iteration / loop topology:
 
-          * every container has at least one child whose ``parentId``
-            points at it;
+          * every container has at least one executable child whose
+            ``parentId`` points at it;
           * every non-container node with a ``parentId`` points at a real
             container, not at a non-container node;
           * no cycles in the parent chain (a node cannot be its own
@@ -1959,7 +2306,9 @@ class WorkflowGenerator:
             if not isinstance(parent, str) or not parent:
                 continue
             if parent in container_ids:
-                children_by_parent.setdefault(parent, []).append(n.get("id", ""))
+                node_type = (n.get("data") or {}).get("type")
+                if node_type not in {"iteration-start", "loop-start"}:
+                    children_by_parent.setdefault(parent, []).append(n.get("id", ""))
             elif parent in by_id:
                 # Parent exists but isn't a container — that's a topology bug.
                 out.append(

api/core/workflow/generator/types.py

@@ -1,10 +1,10 @@
 """
 Typed payloads for workflow generation.
 
-These TypedDicts describe the shape that the planner and builder LLM calls are
-required to return after ``json_repair`` parsing. They mirror the runtime
-``graph`` shape consumed by ``WorkflowService.sync_draft_workflow`` so the output
-can be written straight into a draft workflow without further translation.
+These TypedDicts describe the planner payload and the runtime graph assembled
+from builder LLM responses after ``json_repair`` parsing. The graph types mirror
+the shape consumed by ``WorkflowService.sync_draft_workflow`` so the output can
+be written straight into a draft workflow.
 """
 
 from enum import StrEnum
@@ -12,11 +12,10 @@ from typing import Literal, NotRequired, TypedDict
 
 WorkflowGenerationMode = Literal["workflow", "advanced-chat"]
 
-# The mode accepted at the API boundary. ``auto`` is a sentinel that asks the
-# service to classify the instruction into a concrete ``WorkflowGenerationMode``
-# (one tiny LLM call) BEFORE planning — see
-# ``WorkflowGeneratorService._resolve_mode`` and
-# ``LLMGenerator.classify_workflow_mode``.
+# The mode accepted at the API boundary. ``auto`` is a sentinel that delegates
+# the choice to the planner: it echoes a concrete mode in its ``mode`` output
+# field (falling back to terminal-node inference, then ``advanced-chat``) —
+# see ``runner._resolve_generation_mode``. No extra LLM call is involved.
 WorkflowGenerationModeRequest = Literal["workflow", "advanced-chat", "auto"]
 
 
@@ -58,9 +57,21 @@ class WorkflowGenerateErrorDict(TypedDict):
 class PlannerNodeDict(TypedDict):
     """One node from the planner's high-level plan."""
 
+    id: NotRequired[str]
     label: str
     node_type: str
     purpose: str
+    parent: NotRequired[str]
+    action: NotRequired[Literal["keep", "update", "add"]]
+
+
+class PlannerEdgeDict(TypedDict):
+    """Compact topology emitted by the planner for parallel node building."""
+
+    source: str
+    target: str
+    source_handle: NotRequired[str]
+    target_handle: NotRequired[str]
 
 
 class PlannerStartInputDict(TypedDict):
@@ -82,10 +93,15 @@ class PlannerResultDict(TypedDict):
 
     title: str
     description: str
+    # Concrete mode the planner chose ("workflow" / "advanced-chat"). Parsed
+    # leniently — an ``auto`` request infers the mode from the terminal node
+    # when this is missing or invalid, so a bad value never fails the plan.
+    mode: NotRequired[str]
     app_name: NotRequired[str]
     icon: NotRequired[str]
     start_inputs: NotRequired[list[PlannerStartInputDict]]
     nodes: list[PlannerNodeDict]
+    edges: NotRequired[list[PlannerEdgeDict]]
 
 
 class GraphNodePositionDict(TypedDict):

api/core/workflow/node_factory.py

@@ -499,6 +499,9 @@ class DifyNodeFactory(NodeFactory):
                     base_url=dify_config.AGENT_BACKEND_BASE_URL,
                     use_fake=dify_config.AGENT_BACKEND_USE_FAKE,
                     fake_scenario=dify_config.AGENT_BACKEND_FAKE_SCENARIO,
+                    stream_read_timeout_seconds=dify_config.AGENT_BACKEND_STREAM_READ_TIMEOUT_SECONDS,
+                    stream_max_reconnects=dify_config.AGENT_BACKEND_STREAM_MAX_RECONNECTS,
+                    stream_run_timeout_seconds=dify_config.AGENT_BACKEND_RUN_TIMEOUT_SECONDS,
                 ),
                 "event_adapter": AgentBackendRunEventAdapter(),
                 # Agent Files §4.6: reback file outputs from the ToolFile row so

api/core/workflow/nodes/agent_v2/agent_node.py

@@ -5,6 +5,7 @@ from collections.abc import Generator, Mapping, Sequence
 from typing import TYPE_CHECKING, Any, override
 
 from agenton.compositor import CompositorSessionSnapshot
+from dify_agent.protocol import CancelRunRequest
 
 from clients.agent_backend import (
     AgentBackendAgentMessageDeltaInternalEvent,
@@ -473,7 +474,10 @@ class DifyAgentNode(Node[DifyAgentNodeData]):
         """
         stream_event_count = 0
         try:
-            for public_event in self._agent_backend_client.stream_events(run_id):
+            for public_event in self._agent_backend_client.stream_events(
+                run_id,
+                should_stop=self._is_graph_aborted,
+            ):
                 stream_event_count += 1
                 for internal_event in self._event_adapter.adapt(public_event):
                     if internal_event.type == AgentBackendInternalEventType.RUN_STARTED:
@@ -501,6 +505,7 @@ class DifyAgentNode(Node[DifyAgentNodeData]):
                         | AgentBackendDeferredToolCallInternalEvent,
                     ):
                         return internal_event, None
+                    self._cancel_backend_run(run_id, reason="unexpected_event")
                     return None, self._failure_event(
                         inputs={},
                         process_data={},
@@ -509,6 +514,7 @@ class DifyAgentNode(Node[DifyAgentNodeData]):
                         error_type="agent_backend_stream_error",
                     )
         except AgentBackendError as error:
+            self._cancel_backend_run(run_id, reason=self._stream_stop_reason())
             return None, self._failure_event(
                 inputs={},
                 process_data={},
@@ -517,6 +523,7 @@ class DifyAgentNode(Node[DifyAgentNodeData]):
                 error_type=self._agent_backend_error_type(error),
             )
         except Exception as error:
+            self._cancel_backend_run(run_id, reason=self._stream_stop_reason())
             return None, self._failure_event(
                 inputs={},
                 process_data={},
@@ -525,8 +532,28 @@ class DifyAgentNode(Node[DifyAgentNodeData]):
                 error_type="agent_backend_stream_error",
             )
 
+        self._cancel_backend_run(run_id, reason="stream_ended_without_terminal_event")
         return None, None
 
+    def _is_graph_aborted(self) -> bool:
+        """Let Agent SSE consumption observe GraphEngine's cooperative abort state."""
+        try:
+            return self.graph_runtime_state.graph_execution.aborted
+        except (AttributeError, RuntimeError):
+            return False
+
+    def _stream_stop_reason(self) -> str:
+        return "workflow_graph_aborted" if self._is_graph_aborted() else "event_stream_failed"
+
+    def _cancel_backend_run(self, run_id: str, *, reason: str) -> None:
+        try:
+            self._agent_backend_client.cancel_run(
+                run_id,
+                CancelRunRequest(reason=reason, message="Workflow Agent event consumption stopped"),
+            )
+        except Exception:
+            logger.warning("Failed to cancel Workflow Agent backend run: run_id=%s", run_id, exc_info=True)
+
     @staticmethod
     def _record_type_check_metadata(metadata: dict[str, Any], outcome: OutputTypeCheckOutcome) -> None:
         # Surface enough detail in metadata for Inspector / debug logs without

api/core/workflow/nodes/agent_v2/validators.py

@@ -61,16 +61,33 @@ class WorkflowAgentNodeValidator:
 
     @classmethod
     def validate_draft_workflow(cls, *, session: Session, workflow: Workflow) -> None:
-        cls._validate_workflow(session=session, workflow=workflow, require_binding=False)
+        cls._validate_workflow(
+            session=session,
+            workflow=workflow,
+            require_binding=False,
+            validate_previous_node_topology=False,
+        )
 
     @classmethod
     def validate_published_workflow(cls, *, session: Session, workflow: Workflow) -> None:
-        cls._validate_workflow(session=session, workflow=workflow, require_binding=True)
+        cls._validate_workflow(
+            session=session,
+            workflow=workflow,
+            require_binding=True,
+            validate_previous_node_topology=True,
+        )
 
     @classmethod
-    def _validate_workflow(cls, *, session: Session, workflow: Workflow, require_binding: bool) -> None:
+    def _validate_workflow(
+        cls,
+        *,
+        session: Session,
+        workflow: Workflow,
+        require_binding: bool,
+        validate_previous_node_topology: bool,
+    ) -> None:
         graph = workflow.graph_dict
-        topology = _WorkflowGraphTopology.from_graph(graph)
+        topology = _WorkflowGraphTopology.from_graph(graph) if validate_previous_node_topology else None
         for node_id, node_data in cls.iter_agent_v2_nodes(graph):
             cls._validate_node_schema(node_id=node_id, node_data=node_data)
             binding = cls._find_binding(
@@ -185,12 +202,12 @@ class WorkflowAgentNodeValidator:
                 raise WorkflowAgentNodeValidationError(
                     f"Workflow Agent node {binding.node_id} has invalid previous node output ref."
                 )
-            if topology is None:
-                continue
             if len(selector) < 2:
                 raise WorkflowAgentNodeValidationError(
                     f"Workflow Agent node {binding.node_id} has incomplete previous node output ref."
                 )
+            if topology is None:
+                continue
             source_node_id = selector[0]
             if not topology.has_node(source_node_id):
                 raise WorkflowAgentNodeValidationError(

api/dev/generate_knowledge_fs_contract.py

@@ -0,0 +1,255 @@
+"""Validate Dify Console KnowledgeFS declarations against a pinned OpenAPI document.
+
+The OpenAPI document is exported only during explicit development validation. Runtime declarations live with Dify
+product policy; this module validates their transport metadata without generating a complete operation catalog.
+"""
+
+from __future__ import annotations
+
+import argparse
+import hashlib
+import json
+import subprocess
+import sys
+import tempfile
+from pathlib import Path
+from typing import Any, Literal, TypedDict
+
+API_ROOT = Path(__file__).resolve().parents[1]
+if str(API_ROOT) not in sys.path:
+    sys.path.insert(0, str(API_ROOT))
+
+WORKSPACE_ROOT = API_ROOT.parent
+LOCK_PATH = API_ROOT / "knowledge-fs-contract.lock.json"
+DEFAULT_REPOSITORY = WORKSPACE_ROOT.parent / "knowledge-fs"
+OPENAPI_METHODS = ("delete", "get", "head", "options", "patch", "post", "put", "trace")
+PROXY_METHODS = frozenset({"delete", "get", "patch", "post", "put"})
+
+
+class ContractDeclaration(TypedDict):
+    """KnowledgeFS transport contract declared by one Dify Console registry entry."""
+
+    operation_id: str
+    method: str
+    path: str
+    required_scope: str | None
+    response_kind: str
+    max_response_bytes: int
+    request_headers: tuple[str, ...]
+    response_headers: tuple[str, ...]
+    response_media_types: tuple[str, ...]
+
+
+type DeclarationField = Literal[
+    "method",
+    "path",
+    "required_scope",
+    "response_kind",
+    "max_response_bytes",
+    "request_headers",
+    "response_headers",
+    "response_media_types",
+]
+
+DECLARATION_FIELDS: tuple[DeclarationField, ...] = (
+    "method",
+    "path",
+    "required_scope",
+    "response_kind",
+    "max_response_bytes",
+    "request_headers",
+    "response_headers",
+    "response_media_types",
+)
+
+
+def main() -> None:
+    """Update or verify the pin and validate Console declarations against its OpenAPI document."""
+    parser = argparse.ArgumentParser()
+    mode = parser.add_mutually_exclusive_group()
+    mode.add_argument("--check", action="store_true")
+    mode.add_argument("--update-lock", action="store_true")
+    parser.add_argument("--repository", type=Path, default=DEFAULT_REPOSITORY)
+    args = parser.parse_args()
+
+    repository = args.repository.resolve()
+    lock = json.loads(LOCK_PATH.read_text())
+    tracked_changes = run("git", "status", "--porcelain", "--untracked-files=no", cwd=repository).strip()
+    if tracked_changes:
+        raise RuntimeError("KnowledgeFS checkout must not contain tracked changes during contract export")
+
+    commit = run("git", "rev-parse", "HEAD", cwd=repository).strip()
+    if not args.update_lock and commit != lock["commit"]:
+        raise RuntimeError(
+            f"KnowledgeFS checkout mismatch: expected {lock['commit']}, received {commit}. "
+            "Use the pinned commit or pass --update-lock intentionally."
+        )
+
+    with tempfile.TemporaryDirectory(prefix="dify-knowledge-fs-contract-") as directory:
+        openapi_path = Path(directory) / "knowledge-fs.openapi.json"
+        subprocess.run(
+            ["pnpm", "openapi:export", "--", "--output", str(openapi_path)],
+            cwd=repository,
+            check=True,
+        )
+        openapi_content = openapi_path.read_bytes()
+
+    openapi_sha256 = sha256(openapi_content)
+    if not args.update_lock and openapi_sha256 != lock["openapiSha256"]:
+        raise RuntimeError(
+            f"KnowledgeFS OpenAPI hash mismatch: expected {lock['openapiSha256']}, received {openapi_sha256}"
+        )
+
+    document: dict[str, Any] = json.loads(openapi_content)
+    validate_declarations(document, console_contract_declarations())
+
+    if args.update_lock:
+        LOCK_PATH.write_text(
+            json.dumps(
+                {
+                    "commit": commit,
+                    "openapiSha256": openapi_sha256,
+                    "repository": lock["repository"],
+                },
+                indent=2,
+            )
+            + "\n"
+        )
+
+
+def validate_declarations(document: dict[str, Any], declarations: tuple[ContractDeclaration, ...]) -> None:
+    """Validate Dify Console declarations against matching pinned OpenAPI operations."""
+    operations_by_id: dict[str, list[tuple[str, str, dict[str, Any], dict[str, Any]]]] = {}
+    for path, path_item in document.get("paths", {}).items():
+        for method in OPENAPI_METHODS:
+            operation = path_item.get(method)
+            if operation is None:
+                continue
+            operation_id = operation.get("operationId")
+            if isinstance(operation_id, str) and operation_id:
+                operations_by_id.setdefault(operation_id, []).append((method, path, path_item, operation))
+
+    declared_ids: set[str] = set()
+    for declaration in declarations:
+        operation_id = declaration["operation_id"]
+        if operation_id in declared_ids:
+            raise ValueError(f"Dify Console registry has duplicate operationId: {operation_id}")
+        declared_ids.add(operation_id)
+
+        matches = operations_by_id.get(operation_id, [])
+        if not matches:
+            raise ValueError(f"KnowledgeFS OpenAPI has no operationId: {operation_id}")
+        if len(matches) > 1:
+            raise ValueError(f"KnowledgeFS OpenAPI has duplicate operationId: {operation_id}")
+
+        method, path, path_item, operation = matches[0]
+        if not path.startswith("/"):
+            raise ValueError(f"KnowledgeFS OpenAPI path must be absolute: {path}")
+        if method not in PROXY_METHODS:
+            raise ValueError(f"KnowledgeFS proxy does not support {method.upper()} {path}")
+        expected: ContractDeclaration = {
+            "operation_id": operation_id,
+            "method": method.upper(),
+            "path": path[1:],
+            "required_scope": required_scope(operation),
+            "response_kind": response_kind(operation),
+            "max_response_bytes": required_max_response_bytes(operation),
+            "request_headers": request_header_names(path_item, operation),
+            "response_headers": response_header_names(operation),
+            "response_media_types": response_media_types(operation),
+        }
+        for field in DECLARATION_FIELDS:
+            expected_value = expected[field]
+            received_value = declaration[field]
+            if received_value != expected_value:
+                raise ValueError(
+                    f"KnowledgeFS operation {operation_id} field {field} drifted: "
+                    f"expected {expected_value!r}, received {received_value!r}"
+                )
+
+
+def console_contract_declarations() -> tuple[ContractDeclaration, ...]:
+    """Return transport declarations from the runtime Console operation registry."""
+    from services.knowledge_fs_proxy import KNOWLEDGE_FS_CONSOLE_OPERATIONS
+
+    return tuple(
+        {
+            "operation_id": operation.operation_id,
+            "method": operation.method,
+            "path": operation.path,
+            "required_scope": operation.required_scope,
+            "response_kind": operation.response_kind,
+            "max_response_bytes": operation.max_response_bytes,
+            "request_headers": operation.request_headers,
+            "response_headers": operation.response_headers,
+            "response_media_types": operation.response_media_types,
+        }
+        for operation in KNOWLEDGE_FS_CONSOLE_OPERATIONS
+    )
+
+
+def response_kind(operation: dict[str, Any]) -> str:
+    media_types = response_media_types(operation)
+    if "text/event-stream" in media_types:
+        return "stream"
+    if "application/octet-stream" in media_types:
+        return "binary"
+    return "buffered"
+
+
+def response_media_types(operation: dict[str, Any]) -> tuple[str, ...]:
+    media_types: set[str] = set()
+    for status, response in operation.get("responses", {}).items():
+        if status == "2XX" or (len(status) == 3 and status.startswith("2") and status.isdigit()):
+            media_types.update(response.get("content", {}))
+    return tuple(sorted(media_types))
+
+
+def required_scope(operation: dict[str, Any]) -> str | None:
+    scope = operation.get("x-knowledge-fs-required-scope")
+    if scope in ("knowledge-spaces:read", "knowledge-spaces:write"):
+        return scope
+    if operation.get("security") == []:
+        return None
+    raise ValueError(f"KnowledgeFS operation has no supported required scope: {scope}")
+
+
+def required_max_response_bytes(operation: dict[str, Any]) -> int:
+    value = operation.get("x-knowledge-fs-max-response-bytes")
+    if not isinstance(value, int) or isinstance(value, bool) or value <= 0:
+        raise ValueError(f"KnowledgeFS operation has no valid response byte limit: {value}")
+    return value
+
+
+def request_header_names(path_item: dict[str, Any], operation: dict[str, Any]) -> tuple[str, ...]:
+    names: set[str] = set()
+    for parameter in [*path_item.get("parameters", []), *operation.get("parameters", [])]:
+        if "$ref" in parameter:
+            raise ValueError(f"KnowledgeFS request header references are not supported: {parameter['$ref']}")
+        if parameter.get("in") == "header":
+            names.add(parameter["name"].lower())
+    return tuple(sorted(names))
+
+
+def response_header_names(operation: dict[str, Any]) -> tuple[str, ...]:
+    return tuple(
+        sorted(
+            {
+                name.lower()
+                for response in operation.get("responses", {}).values()
+                for name in response.get("headers", {})
+            }
+        )
+    )
+
+
+def sha256(content: bytes) -> str:
+    return hashlib.sha256(content).hexdigest()
+
+
+def run(*command: str, cwd: Path) -> str:
+    return subprocess.run(command, cwd=cwd, check=True, capture_output=True, text=True).stdout
+
+
+if __name__ == "__main__":
+    main()

api/events/event_handlers/__init__.py

@@ -7,6 +7,9 @@ from .delete_tool_parameters_cache_when_sync_draft_workflow import (
     handle as handle_delete_tool_parameters_cache_when_sync_draft_workflow,
 )
 from .queue_credential_sync_when_tenant_created import handle as handle_queue_credential_sync_when_tenant_created
+from .queue_default_plugin_install_when_tenant_created import (
+    handle as handle_queue_default_plugin_install_when_tenant_created,
+)
 from .sync_plugin_trigger_when_app_created import handle as handle_sync_plugin_trigger_when_app_created
 from .sync_webhook_when_app_created import handle as handle_sync_webhook_when_app_created
 from .sync_workflow_schedule_when_app_published import handle as handle_sync_workflow_schedule_when_app_published
@@ -32,6 +35,7 @@ __all__ = [
     "handle_create_site_record_when_app_created",
     "handle_delete_tool_parameters_cache_when_sync_draft_workflow",
     "handle_queue_credential_sync_when_tenant_created",
+    "handle_queue_default_plugin_install_when_tenant_created",
     "handle_sync_plugin_trigger_when_app_created",
     "handle_sync_webhook_when_app_created",
     "handle_sync_workflow_schedule_when_app_published",

api/events/event_handlers/queue_default_plugin_install_when_tenant_created.py

@@ -0,0 +1,22 @@
+"""Queue default marketplace plugin installation after tenant creation."""
+
+import logging
+
+from configs import dify_config
+from events.tenant_event import tenant_was_created
+from tasks.install_default_plugins_task import install_default_plugins_task
+
+logger = logging.getLogger(__name__)
+
+
+@tenant_was_created.connect
+def handle(sender, **kwargs) -> None:
+    """Keep tenant creation non-blocking while installing configured plugins asynchronously."""
+    plugin_ids = dify_config.NEW_USER_DEFAULT_PLUGIN_ID_LIST
+    if not plugin_ids:
+        return
+
+    try:
+        install_default_plugins_task.delay(sender.id, plugin_ids)
+    except Exception:
+        logger.exception("Failed to queue default plugin installation for tenant %s", sender.id)

api/extensions/ext_celery.py

@@ -156,6 +156,7 @@ def init_app(app: DifyApp) -> Celery:
         "tasks.generate_summary_index_task",  # summary index generation
         "tasks.regenerate_summary_index_task",  # summary index regeneration
         "tasks.initialize_created_app_rbac_access_task",  # app access initialization
+        "tasks.install_default_plugins_task",  # tenant default plugin installation
         "tasks.app_generate.resume_agent_app_task",  # ENG-635: Agent v2 chat ask_human resume
         "tasks.workflow_run_archive_download_tasks",  # workflow-run archive download preparation
     ]

api/knowledge-fs-contract.lock.json

@@ -0,0 +1,5 @@
+{
+  "commit": "4310e2d582d25e7de58183f27720afab01e123cf",
+  "openapiSha256": "5827ca930ce38462bfd1b2bef387efbf37eb7ffcaedde4558af2fbaeccbfbc4b",
+  "repository": "https://github.com/langgenius/knowledge-fs"
+}

api/libs/archive_storage.py

@@ -16,12 +16,19 @@ from urllib.parse import quote
 import boto3
 import orjson
 from botocore.client import Config
-from botocore.exceptions import ClientError
+from botocore.exceptions import BotoCoreError, ClientError
 
 from configs import dify_config
 
 logger = logging.getLogger(__name__)
 
+_OBJECT_NOT_FOUND_ERROR_CODES = frozenset({"404", "NoSuchKey", "NotFound"})
+
+
+def _is_object_not_found_error(error: ClientError) -> bool:
+    error_code = str(error.response.get("Error", {}).get("Code", ""))
+    return error_code in _OBJECT_NOT_FOUND_ERROR_CODES
+
 
 class ArchiveStorageError(Exception):
     """Base exception for archive storage operations."""
@@ -138,10 +145,11 @@ class ArchiveStorage:
             response = self.client.get_object(Bucket=self.bucket, Key=key)
             return response["Body"].read()
         except ClientError as e:
-            error_code = e.response.get("Error", {}).get("Code")
-            if error_code == "NoSuchKey":
-                raise FileNotFoundError(f"Archive object not found: {key}")
-            raise ArchiveStorageError(f"Failed to download object '{key}': {e}")
+            if _is_object_not_found_error(e):
+                raise FileNotFoundError(f"Archive object not found: {key}") from e
+            raise ArchiveStorageError(f"Failed to download object '{key}': {e}") from e
+        except BotoCoreError as e:
+            raise ArchiveStorageError(f"Failed to download object '{key}': {e}") from e
 
     def get_object_stream(self, key: str) -> Generator[bytes, None, None]:
         """
@@ -161,10 +169,11 @@ class ArchiveStorage:
             response = self.client.get_object(Bucket=self.bucket, Key=key)
             yield from response["Body"].iter_chunks()
         except ClientError as e:
-            error_code = e.response.get("Error", {}).get("Code")
-            if error_code == "NoSuchKey":
-                raise FileNotFoundError(f"Archive object not found: {key}")
-            raise ArchiveStorageError(f"Failed to stream object '{key}': {e}")
+            if _is_object_not_found_error(e):
+                raise FileNotFoundError(f"Archive object not found: {key}") from e
+            raise ArchiveStorageError(f"Failed to stream object '{key}': {e}") from e
+        except BotoCoreError as e:
+            raise ArchiveStorageError(f"Failed to stream object '{key}': {e}") from e
 
     def object_exists(self, key: str) -> bool:
         """
@@ -175,12 +184,19 @@ class ArchiveStorage:
 
         Returns:
             True if object exists, False otherwise
+
+        Raises:
+            ArchiveStorageError: If storage cannot authoritatively determine object existence
         """
         try:
             self.client.head_object(Bucket=self.bucket, Key=key)
             return True
-        except ClientError:
-            return False
+        except ClientError as e:
+            if _is_object_not_found_error(e):
+                return False
+            raise ArchiveStorageError(f"Failed to check archive object '{key}': {e}") from e
+        except BotoCoreError as e:
+            raise ArchiveStorageError(f"Failed to check archive object '{key}': {e}") from e
 
     def delete_object(self, key: str) -> None:
         """
@@ -196,7 +212,12 @@ class ArchiveStorage:
             self.client.delete_object(Bucket=self.bucket, Key=key)
             logger.debug("Deleted object: %s", key)
         except ClientError as e:
-            raise ArchiveStorageError(f"Failed to delete object '{key}': {e}")
+            if _is_object_not_found_error(e):
+                logger.debug("Archive object was already absent: %s", key)
+                return
+            raise ArchiveStorageError(f"Failed to delete object '{key}': {e}") from e
+        except BotoCoreError as e:
+            raise ArchiveStorageError(f"Failed to delete object '{key}': {e}") from e
 
     def generate_presigned_url(
         self,

api/migrations/versions/2026_06_29_1200-b8c9d0e1f2a3_add_step_by_step_tour_state.py

@@ -0,0 +1,39 @@
+"""add step by step tour state
+
+Revision ID: b8c9d0e1f2a3
+Revises: 3c9f8e2a1d7b
+Create Date: 2026-06-29 12:00:00.000000
+
+"""
+
+import sqlalchemy as sa
+from alembic import op
+
+import models
+
+# revision identifiers, used by Alembic.
+revision = "b8c9d0e1f2a3"
+down_revision = "3c9f8e2a1d7b"
+branch_labels = None
+depends_on = None
+
+
+def upgrade():
+    op.create_table(
+        "account_step_by_step_tour_states",
+        sa.Column("id", models.types.StringUUID(), nullable=False),
+        sa.Column("account_id", models.types.StringUUID(), nullable=False),
+        sa.Column("first_workspace_id", models.types.StringUUID(), nullable=True),
+        sa.Column("skipped", sa.Boolean(), server_default=sa.text("false"), nullable=False),
+        sa.Column("completed_task_ids", models.types.AdjustedJSON(), nullable=False),
+        sa.Column("manually_enabled_workspace_ids", models.types.AdjustedJSON(), nullable=False),
+        sa.Column("manually_disabled_workspace_ids", models.types.AdjustedJSON(), nullable=False),
+        sa.Column("created_at", sa.DateTime(), server_default=sa.text("CURRENT_TIMESTAMP"), nullable=False),
+        sa.Column("updated_at", sa.DateTime(), server_default=sa.text("CURRENT_TIMESTAMP"), nullable=False),
+        sa.PrimaryKeyConstraint("id", name="account_step_by_step_tour_state_pkey"),
+        sa.UniqueConstraint("account_id", name="account_step_by_step_tour_state_account_id_key"),
+    )
+
+
+def downgrade():
+    op.drop_table("account_step_by_step_tour_states")

api/migrations/versions/2026_07_15_1600-3c9f8e2a1d7b_add_workflow_run_archive_bundle_cursor_indexes.py

@@ -0,0 +1,45 @@
+"""add workflow-run archive bundle cursor indexes
+
+Revision ID: 3c9f8e2a1d7b
+Revises: 7a1c2d9e4b60
+Create Date: 2026-07-15 16:00:00.000000
+
+"""
+
+from alembic import op
+
+# revision identifiers, used by Alembic.
+revision = "3c9f8e2a1d7b"
+down_revision = "7a1c2d9e4b60"
+branch_labels = None
+depends_on = None
+
+_TABLE_NAME = "workflow_run_archive_bundles"
+_INDEXES = (
+    ("workflow_run_archive_bundle_month_id_idx", ("year", "month", "id")),
+    ("workflow_run_archive_bundle_month_shard_id_idx", ("year", "month", "shard", "id")),
+)
+
+
+def _is_postgresql() -> bool:
+    return op.get_bind().dialect.name == "postgresql"
+
+
+def upgrade() -> None:
+    if _is_postgresql():
+        with op.get_context().autocommit_block():
+            for index_name, columns in _INDEXES:
+                op.create_index(index_name, _TABLE_NAME, columns, postgresql_concurrently=True)
+        return
+    for index_name, columns in _INDEXES:
+        op.create_index(index_name, _TABLE_NAME, columns)
+
+
+def downgrade() -> None:
+    if _is_postgresql():
+        with op.get_context().autocommit_block():
+            for index_name, _ in reversed(_INDEXES):
+                op.drop_index(index_name, table_name=_TABLE_NAME, postgresql_concurrently=True)
+        return
+    for index_name, _ in reversed(_INDEXES):
+        op.drop_index(index_name, table_name=_TABLE_NAME)

api/models/__init__.py

@@ -101,6 +101,7 @@ from .model import (
     UploadFile,
 )
 from .oauth import DatasourceOauthParamConfig, DatasourceProvider, OAuthAccessToken
+from .onboarding import AccountStepByStepTourState
 from .provider import (
     LoadBalancingModelConfig,
     Provider,
@@ -155,6 +156,7 @@ __all__ = [
     "Account",
     "AccountIntegrate",
     "AccountStatus",
+    "AccountStepByStepTourState",
     "AccountTrialAppRecord",
     "Agent",
     "AgentConfigDraft",

api/models/onboarding.py

@@ -0,0 +1,59 @@
+"""Account-level onboarding state models."""
+
+from datetime import datetime
+
+import sqlalchemy as sa
+from sqlalchemy import DateTime, func
+from sqlalchemy.orm import Mapped, mapped_column
+
+from .base import TypeBase, gen_uuidv7_string
+from .types import AdjustedJSON, StringUUID
+
+
+class AccountStepByStepTourState(TypeBase):
+    """Persistent account-level Step-by-step Tour state.
+
+    The tour is account-owned, with workspace IDs stored only as presentation
+    overrides. The first workspace is the workspace context where an eligible
+    account first asks for tour state; subsequent workspaces are opt-in only.
+    """
+
+    __tablename__ = "account_step_by_step_tour_states"
+    __table_args__ = (
+        sa.PrimaryKeyConstraint("id", name="account_step_by_step_tour_state_pkey"),
+        sa.UniqueConstraint("account_id", name="account_step_by_step_tour_state_account_id_key"),
+    )
+
+    id: Mapped[str] = mapped_column(
+        StringUUID,
+        insert_default=gen_uuidv7_string,
+        default_factory=gen_uuidv7_string,
+        init=False,
+    )
+    account_id: Mapped[str] = mapped_column(StringUUID, nullable=False)
+    first_workspace_id: Mapped[str | None] = mapped_column(StringUUID, nullable=True, default=None)
+    skipped: Mapped[bool] = mapped_column(sa.Boolean, nullable=False, server_default=sa.text("false"), default=False)
+    completed_task_ids: Mapped[list[str]] = mapped_column(AdjustedJSON, nullable=False, default_factory=list)
+    manually_enabled_workspace_ids: Mapped[list[str]] = mapped_column(
+        AdjustedJSON,
+        nullable=False,
+        default_factory=list,
+    )
+    manually_disabled_workspace_ids: Mapped[list[str]] = mapped_column(
+        AdjustedJSON,
+        nullable=False,
+        default_factory=list,
+    )
+    created_at: Mapped[datetime] = mapped_column(
+        DateTime,
+        server_default=func.current_timestamp(),
+        nullable=False,
+        init=False,
+    )
+    updated_at: Mapped[datetime] = mapped_column(
+        DateTime,
+        server_default=func.current_timestamp(),
+        nullable=False,
+        init=False,
+        onupdate=func.current_timestamp(),
+    )

api/models/workflow.py

@@ -1476,6 +1476,8 @@ class WorkflowRunArchiveBundle(DefaultFieldsDCMixin, TypeBase):
             name="workflow_run_archive_bundle_identity_uq",
         ),
         sa.Index("workflow_run_archive_bundle_tenant_month_idx", "tenant_id", "year", "month"),
+        sa.Index("workflow_run_archive_bundle_month_id_idx", "year", "month", "id"),
+        sa.Index("workflow_run_archive_bundle_month_shard_id_idx", "year", "month", "shard", "id"),
     )
 
     tenant_id: Mapped[str] = mapped_column(StringUUID, nullable=False)

api/openapi/markdown/console-openapi.md

@@ -7787,6 +7787,30 @@ Initiate OAuth login process
 | ---- | ----------- | ------ |
 | 200 | Success | **application/json**: [OAuthProviderTokenResponse](#oauthprovidertokenresponse)<br> |
 
+### [GET] /onboarding/step-by-step-tour/state
+Get account-level Step-by-step Tour state
+
+#### Responses
+
+| Code | Description | Schema |
+| ---- | ----------- | ------ |
+| 200 | Success | **application/json**: [StepByStepTourStateResponse](#stepbysteptourstateresponse)<br> |
+
+### [PATCH] /onboarding/step-by-step-tour/state
+Update account-level Step-by-step Tour state
+
+#### Request Body
+
+| Required | Schema |
+| -------- | ------ |
+|  Yes | **application/json**: [StepByStepTourStatePatchPayload](#stepbysteptourstatepatchpayload)<br> |
+
+#### Responses
+
+| Code | Description | Schema |
+| ---- | ----------- | ------ |
+| 200 | Success | **application/json**: [StepByStepTourStateResponse](#stepbysteptourstateresponse)<br> |
+
 ### [DELETE] /rag/pipeline/customized/templates/{template_id}
 #### Parameters
 
@@ -9639,6 +9663,27 @@ Bedrock retrieval test (internal use only)
 | ---- | ----------- | ------ |
 | 200 | Success | **application/json**: [TrialDatasetListResponse](#trialdatasetlistresponse)<br> |
 
+### [POST] /trial-apps/{app_id}/files/upload
+**Upload a file into the tenant that owns the trial app**
+
+#### Parameters
+
+| Name | Located in | Description | Required | Schema |
+| ---- | ---------- | ----------- | -------- | ------ |
+| app_id | path |  | Yes | string (uuid) |
+
+#### Request Body
+
+| Required | Schema |
+| -------- | ------ |
+|  Yes | **multipart/form-data**: { **"file"**: binary, **"source"**: string, <br>**Available values:** "datasets" }<br> |
+
+#### Responses
+
+| Code | Description | Schema |
+| ---- | ----------- | ------ |
+| 201 | File uploaded successfully | **application/json**: [FileResponse](#fileresponse)<br> |
+
 ### [GET] /trial-apps/{app_id}/messages/{message_id}/suggested-questions
 #### Parameters
 
@@ -9668,6 +9713,27 @@ Bedrock retrieval test (internal use only)
 | ---- | ----------- | ------ |
 | 200 | Success | **application/json**: [Parameters](#parameters)<br> |
 
+### [POST] /trial-apps/{app_id}/remote-files/upload
+**Upload a remote file into the tenant that owns the trial app**
+
+#### Parameters
+
+| Name | Located in | Description | Required | Schema |
+| ---- | ---------- | ----------- | -------- | ------ |
+| app_id | path |  | Yes | string (uuid) |
+
+#### Request Body
+
+| Required | Schema |
+| -------- | ------ |
+|  Yes | **application/json**: [RemoteFileUploadPayload](#remotefileuploadpayload)<br> |
+
+#### Responses
+
+| Code | Description | Schema |
+| ---- | ----------- | ------ |
+| 201 | File uploaded successfully | **application/json**: [FileWithSignedUrl](#filewithsignedurl)<br> |
+
 ### [GET] /trial-apps/{app_id}/site
 **Retrieve app site info**
 
@@ -21746,6 +21812,24 @@ Query parameters for listing snippet published workflows.
 | paused | integer |  | Yes |
 | success | integer |  | Yes |
 
+#### StepByStepTourStatePatchPayload
+
+| Name | Type | Description | Required |
+| ---- | ---- | ----------- | -------- |
+| action | string, <br>**Available values:** "complete_task", "disable_current_workspace", "enable_current_workspace", "skip", "uncomplete_task" | State update action<br>*Enum:* `"complete_task"`, `"disable_current_workspace"`, `"enable_current_workspace"`, `"skip"`, `"uncomplete_task"` | Yes |
+| task_id | string | Task ID for task actions | No |
+
+#### StepByStepTourStateResponse
+
+| Name | Type | Description | Required |
+| ---- | ---- | ----------- | -------- |
+| completed_task_ids | [ string, <br>**Available values:** "home", "integration", "knowledge", "studio" ] |  | No |
+| first_workspace_id | string |  | No |
+| manually_disabled_workspace_ids | [ string ] |  | No |
+| manually_enabled_workspace_ids | [ string ] |  | No |
+| skipped | boolean |  | No |
+| updated_at | string |  | No |
+
 #### Storage
 
 | Name | Type | Description | Required |
@@ -21859,6 +21943,7 @@ The subscription constructor of the trigger provider
 
 | Name | Type | Description | Required |
 | ---- | ---- | ----------- | -------- |
+| _is_collaborative | boolean |  | No |
 | conversation_variables | [ object ] |  | No |
 | environment_variables | [ object ] |  | No |
 | features | object |  | Yes |
@@ -21898,6 +21983,7 @@ Model class for provider system configuration response.
 | enable_learn_app | boolean, <br>**Default:** true |  | Yes |
 | enable_marketplace | boolean |  | Yes |
 | enable_social_oauth_login | boolean |  | Yes |
+| enable_step_by_step_tour | boolean |  | Yes |
 | enable_trial_app | boolean |  | Yes |
 | is_allow_create_workspace | boolean |  | Yes |
 | is_allow_register | boolean |  | Yes |
@@ -22854,6 +22940,7 @@ in form definiton, or a variable while the workflow is running.
 | ---- | ---- | ----------- | -------- |
 | allow_email_code_login | boolean |  | Yes |
 | allow_email_password_login | boolean |  | Yes |
+| allow_public_access | boolean, <br>**Default:** true |  | Yes |
 | allow_sso | boolean |  | Yes |
 | enabled | boolean |  | Yes |
 | sso_config | [WebAppAuthSSOModel](#webappauthssomodel) |  | Yes |

api/openapi/markdown/web-openapi.md

@@ -1577,6 +1577,7 @@ Default configuration for form inputs.
 | enable_learn_app | boolean, <br>**Default:** true |  | Yes |
 | enable_marketplace | boolean |  | Yes |
 | enable_social_oauth_login | boolean |  | Yes |
+| enable_step_by_step_tour | boolean |  | Yes |
 | enable_trial_app | boolean |  | Yes |
 | is_allow_create_workspace | boolean |  | Yes |
 | is_allow_register | boolean |  | Yes |
@@ -1642,6 +1643,7 @@ in form definiton, or a variable while the workflow is running.
 | ---- | ---- | ----------- | -------- |
 | allow_email_code_login | boolean |  | Yes |
 | allow_email_password_login | boolean |  | Yes |
+| allow_public_access | boolean, <br>**Default:** true |  | Yes |
 | allow_sso | boolean |  | Yes |
 | enabled | boolean |  | Yes |
 | sso_config | [WebAppAuthSSOModel](#webappauthssomodel) |  | Yes |

api/providers/conftest.py

@@ -0,0 +1,35 @@
+"""Shared database fixtures for provider tests.
+
+Provider tests live outside ``tests/unit_tests`` and therefore cannot use that
+suite's SQLite fixtures. Keep this fixture scoped to ``providers`` so each
+provider package can exercise real SQLAlchemy queries without a service
+database or mocked sessions.
+"""
+
+from collections.abc import Iterator
+
+import pytest
+from sqlalchemy import create_engine
+from sqlalchemy.orm import Session
+
+from models.base import TypeBase
+
+
+@pytest.fixture
+def sqlite3_session(request: pytest.FixtureRequest) -> Iterator[Session]:
+    """Yield an isolated SQLite session with the parametrized model tables.
+
+    Pass the required ORM classes through indirect parametrization. The engine
+    is per-test so committed rows and identity-map state cannot leak between
+    provider packages.
+    """
+
+    models: tuple[type[TypeBase], ...] = request.param
+    engine = create_engine("sqlite:///:memory:")
+    tables = [model.metadata.tables[model.__tablename__] for model in models]
+    TypeBase.metadata.create_all(engine, tables=tables)
+    try:
+        with Session(engine, expire_on_commit=False) as session:
+            yield session
+    finally:
+        engine.dispose()

api/pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "dify-api"
-version = "1.16.0-rc1"
+version = "1.16.0"
 requires-python = "~=3.12.0"
 
 dependencies = [

api/repositories/workflow_collaboration_repository.py

@@ -3,7 +3,10 @@ from __future__ import annotations
 import json
 from typing import NotRequired, TypedDict, override
 
+from redis.lock import Lock
+
 from extensions.ext_redis import redis_client
+from extensions.redis_names import serialize_redis_name
 
 SESSION_STATE_TTL_SECONDS = 3600
 SERVER_HEARTBEAT_TTL_SECONDS = 90
@@ -12,6 +15,31 @@ WORKFLOW_LEADER_PREFIX = "workflow_leader:"
 WS_SID_MAP_PREFIX = "ws_sid_map:"
 WS_SERVER_HEARTBEAT_PREFIX = "ws_server_heartbeat:"
 WS_SERVER_SESSIONS_PREFIX = "ws_server_sessions:"
+GRAPH_VIEW_STATE_LOCK_PREFIX = "workflow_graph_view_state_lock:"
+GRAPH_VIEW_STATE_LOCK_TIMEOUT_SECONDS = 15
+
+_UPDATE_SESSION_GRAPH_ACTIVE_LUA = """
+local raw = redis.call('HGET', KEYS[1], ARGV[1])
+if not raw then
+    return 0
+end
+
+local decoded_ok, session_info = pcall(cjson.decode, raw)
+if not decoded_ok or type(session_info) ~= 'table' then
+    return 0
+end
+
+local incoming_sequence = tonumber(ARGV[3])
+local current_sequence = tonumber(session_info.graph_active_sequence)
+if current_sequence and incoming_sequence <= current_sequence then
+    return 0
+end
+
+session_info.graph_active = ARGV[2] == '1'
+session_info.graph_active_sequence = incoming_sequence
+redis.call('HSET', KEYS[1], ARGV[1], cjson.encode(session_info))
+return 1
+"""
 
 
 class WorkflowSessionInfo(TypedDict):
@@ -156,6 +184,55 @@ class WorkflowCollaborationRepository:
 
         return users
 
+    def get_session_info(self, workflow_id: str, sid: str) -> WorkflowSessionInfo | None:
+        raw = self._redis.hget(self.workflow_key(workflow_id), sid)
+        value = self._decode(raw)
+        if not value:
+            return None
+        try:
+            session_info = json.loads(value)
+        except (TypeError, json.JSONDecodeError):
+            return None
+
+        if not isinstance(session_info, dict):
+            return None
+        if "user_id" not in session_info or "username" not in session_info or "sid" not in session_info:
+            return None
+
+        user: WorkflowSessionInfo = {
+            "user_id": str(session_info["user_id"]),
+            "username": str(session_info["username"]),
+            "avatar": session_info.get("avatar"),
+            "sid": str(session_info["sid"]),
+            "connected_at": int(session_info.get("connected_at") or 0),
+        }
+        if isinstance(session_info.get("server_id"), str):
+            user["server_id"] = session_info["server_id"]
+        if isinstance(session_info.get("graph_active"), bool):
+            user["graph_active"] = session_info["graph_active"]
+        return user
+
+    def update_session_graph_active(self, workflow_id: str, sid: str, active: bool, sequence: int) -> bool:
+        """Atomically apply a graph visibility update when its client sequence is newer."""
+        # RedisClientWrapper prefixes regular hash calls, but eval is delegated to the raw client.
+        workflow_key = serialize_redis_name(self.workflow_key(workflow_id))
+        result = self._redis.eval(
+            _UPDATE_SESSION_GRAPH_ACTIVE_LUA,
+            1,
+            workflow_key,
+            sid,
+            "1" if active else "0",
+            sequence,
+        )
+        return bool(result)
+
+    def graph_view_state_lock(self, workflow_id: str) -> Lock:
+        """Serialize visibility state changes and their leader-election side effects."""
+        return self._redis.lock(
+            f"{GRAPH_VIEW_STATE_LOCK_PREFIX}{workflow_id}",
+            timeout=GRAPH_VIEW_STATE_LOCK_TIMEOUT_SECONDS,
+        )
+
     def refresh_server_heartbeat(self, server_id: str) -> None:
         self._redis.set(self.server_key(server_id), "1", ex=SERVER_HEARTBEAT_TTL_SECONDS)
 

api/services/agent/observability_service.py

@@ -9,12 +9,13 @@ import sqlalchemy as sa
 from sqlalchemy import and_, func, or_, select
 from sqlalchemy.orm import aliased
 
+from configs import dify_config
 from core.app.entities.app_invoke_entities import InvokeFrom
 from libs.helper import convert_datetime_to_date, escape_like_pattern, to_timestamp
 from models.agent import WorkflowAgentNodeBinding
-from models.enums import MessageStatus
+from models.enums import CreatorUserRole, MessageStatus
 from models.model import App, Conversation, Message
-from models.workflow import WorkflowNodeExecutionModel, WorkflowRun
+from models.workflow import WorkflowNodeExecutionModel, WorkflowRun, WorkflowType
 
 
 @dataclass(frozen=True)
@@ -580,9 +581,26 @@ class AgentObservabilityService:
 
     def _load_daily_statistics(
         self, *, app: App, agent_id: str, params: AgentStatisticsQueryParams, source_filter: AgentSourceFilter
+    ) -> list[dict[str, Any]]:
+        rows: list[dict[str, Any]] = []
+        if source_filter.kind in {"all", "webapp"}:
+            rows.extend(self._load_webapp_daily_statistics(app=app, params=params, source_filter=source_filter))
+        if source_filter.kind in {"all", "workflow"}:
+            rows.extend(
+                self._load_workflow_daily_statistics(
+                    app=app,
+                    agent_id=agent_id,
+                    params=params,
+                    source_filter=source_filter,
+                )
+            )
+        return self._merge_daily_statistics(rows)
+
+    def _load_webapp_daily_statistics(
+        self, *, app: App, params: AgentStatisticsQueryParams, source_filter: AgentSourceFilter
     ) -> list[dict[str, Any]]:
         converted_created_at = convert_datetime_to_date("m.created_at")
-        message_scope = self._statistics_message_scope_sql(source_filter)
+        message_scope = self._statistics_webapp_message_scope_sql(source_filter)
         sql_query = f"""SELECT
     {converted_created_at} AS date,
     COUNT(m.id) AS message_count,
@@ -602,12 +620,154 @@ WHERE
         args: dict[str, Any] = {
             "tz": params.timezone,
             "app_id": app.id,
-            "tenant_id": app.tenant_id,
-            "agent_id": agent_id,
-            "debugger": InvokeFrom.DEBUGGER,
         }
         if source_filter.invoke_from is not None:
             args["source"] = source_filter.invoke_from
+        if params.start:
+            sql_query += " AND m.created_at >= :start"
+            args["start"] = params.start
+        if params.end:
+            sql_query += " AND m.created_at < :end"
+            args["end"] = params.end
+        sql_query += " GROUP BY date ORDER BY date"
+
+        return [dict(row._mapping) for row in self._session.execute(sa.text(sql_query), args).all()]
+
+    @staticmethod
+    def _statistics_webapp_message_scope_sql(source_filter: AgentSourceFilter) -> str:
+        app_scope = "m.app_id = :app_id"
+        if source_filter.invoke_from is not None:
+            app_scope += " AND m.invoke_from = :source"
+        return app_scope
+
+    def _load_workflow_daily_statistics(
+        self,
+        *,
+        app: App,
+        agent_id: str,
+        params: AgentStatisticsQueryParams,
+        source_filter: AgentSourceFilter,
+    ) -> list[dict[str, Any]]:
+        converted_run_created_at = convert_datetime_to_date("aru.created_at")
+        total_tokens = self._workflow_execution_metadata_numeric_sql(("total_tokens",), "BIGINT")
+        nested_total_tokens = self._workflow_execution_metadata_numeric_sql(
+            ("agent_log", "agent_backend", "usage", "total_tokens"), "BIGINT"
+        )
+        total_price = self._workflow_execution_metadata_numeric_sql(("total_price",), "DECIMAL(65, 30)")
+        nested_total_price = self._workflow_execution_metadata_numeric_sql(
+            ("agent_log", "agent_backend", "usage", "total_price"), "DECIMAL(65, 30)"
+        )
+        completion_tokens = self._workflow_execution_metadata_numeric_sql(
+            ("agent_log", "agent_backend", "usage", "completion_tokens"), "BIGINT"
+        )
+        binding_filters = self._statistics_workflow_binding_filters_sql(source_filter)
+        run_date_filters = ""
+        args: dict[str, Any] = {
+            "tz": params.timezone,
+            "tenant_id": app.tenant_id,
+            "agent_id": agent_id,
+            "chat_workflow_type": WorkflowType.CHAT,
+            "end_user_role": CreatorUserRole.END_USER,
+        }
+        if source_filter.app_id:
+            args["source_app_id"] = source_filter.app_id
+        if source_filter.workflow_id:
+            args["workflow_id"] = source_filter.workflow_id
+        if source_filter.workflow_version:
+            args["workflow_version"] = source_filter.workflow_version
+        if source_filter.node_id:
+            args["node_id"] = source_filter.node_id
+        if params.start:
+            run_date_filters += " AND wr.created_at >= :start"
+            args["start"] = params.start
+        if params.end:
+            run_date_filters += " AND wr.created_at < :end"
+            args["end"] = params.end
+
+        run_query = f"""WITH agent_run_usage AS (
+    SELECT
+        wr.id,
+        wr.created_by_role,
+        wr.created_by,
+        wr.created_at,
+        COALESCE(SUM(COALESCE({total_tokens}, {nested_total_tokens}, 0)), 0) AS token_count,
+        COALESCE(SUM(COALESCE({total_price}, {nested_total_price}, 0)), 0) AS total_price,
+        COALESCE(SUM(COALESCE(wne.elapsed_time, 0)), 0) AS latency,
+        COALESCE(SUM(COALESCE({completion_tokens}, 0)), 0) AS answer_tokens
+    FROM workflow_runs wr
+    JOIN workflow_agent_node_bindings wanb
+        ON wanb.tenant_id = :tenant_id
+        AND wanb.agent_id = :agent_id
+        AND wanb.app_id = wr.app_id
+        AND wanb.workflow_id = wr.workflow_id
+        AND wanb.workflow_version = wr.version
+        {binding_filters}
+    JOIN workflow_node_executions wne
+        ON wne.workflow_run_id = wr.id
+        AND wne.node_id = wanb.node_id
+    WHERE wr.type != :chat_workflow_type{run_date_filters}
+    GROUP BY wr.id, wr.created_by_role, wr.created_by, wr.created_at
+)
+SELECT
+    {converted_run_created_at} AS date,
+    COUNT(aru.id) AS message_count,
+    COUNT(aru.id) AS conversation_count,
+    COUNT(DISTINCT CASE
+        WHEN aru.created_by_role = :end_user_role THEN aru.created_by
+        ELSE NULL
+    END) AS end_user_count,
+    COALESCE(SUM(aru.token_count), 0) AS token_count,
+    COALESCE(SUM(aru.total_price), 0) AS total_price,
+    COALESCE(AVG(aru.latency), 0) AS avg_latency,
+    COALESCE(SUM(aru.latency), 0) AS latency_sum,
+    COALESCE(SUM(aru.answer_tokens), 0) AS answer_tokens,
+    0 AS like_count
+FROM agent_run_usage aru
+GROUP BY date
+ORDER BY date"""
+        rows = [dict(row._mapping) for row in self._session.execute(sa.text(run_query), args).all()]
+        rows.extend(
+            self._load_workflow_chat_daily_context(
+                app=app,
+                agent_id=agent_id,
+                params=params,
+                source_filter=source_filter,
+            )
+        )
+        return self._merge_daily_statistics(rows)
+
+    def _load_workflow_chat_daily_context(
+        self,
+        *,
+        app: App,
+        agent_id: str,
+        params: AgentStatisticsQueryParams,
+        source_filter: AgentSourceFilter,
+    ) -> list[dict[str, Any]]:
+        converted_created_at = convert_datetime_to_date("m.created_at")
+        workflow_scope = self._statistics_workflow_message_scope_sql(source_filter)
+        sql_query = f"""SELECT
+    {converted_created_at} AS date,
+    COUNT(m.id) AS message_count,
+    COUNT(DISTINCT m.conversation_id) AS conversation_count,
+    COUNT(DISTINCT m.from_end_user_id) AS end_user_count,
+    COALESCE(SUM(COALESCE(m.message_tokens, 0) + COALESCE(m.answer_tokens, 0)), 0) AS token_count,
+    COALESCE(SUM(COALESCE(m.total_price, 0)), 0) AS total_price,
+    COALESCE(AVG(m.provider_response_latency), 0) AS avg_latency,
+    COALESCE(SUM(m.provider_response_latency), 0) AS latency_sum,
+    COALESCE(SUM(m.answer_tokens), 0) AS answer_tokens,
+    COUNT(mf.id) AS like_count
+FROM messages m
+LEFT JOIN message_feedbacks mf
+    ON mf.message_id = m.id AND mf.rating = 'like'
+WHERE
+    {workflow_scope}"""
+        args: dict[str, Any] = {
+            "tz": params.timezone,
+            "tenant_id": app.tenant_id,
+            "agent_id": agent_id,
+            "chat_workflow_type": WorkflowType.CHAT,
+        }
         if source_filter.app_id:
             args["source_app_id"] = source_filter.app_id
         if source_filter.workflow_id:
@@ -627,10 +787,7 @@ WHERE
         return [dict(row._mapping) for row in self._session.execute(sa.text(sql_query), args).all()]
 
     @staticmethod
-    def _statistics_message_scope_sql(source_filter: AgentSourceFilter) -> str:
-        app_scope = "m.app_id = :app_id"
-        if source_filter.invoke_from is not None:
-            app_scope += " AND m.invoke_from = :source"
+    def _statistics_workflow_binding_filters_sql(source_filter: AgentSourceFilter) -> str:
         workflow_binding_filters = []
         if source_filter.app_id:
             workflow_binding_filters.append("wanb.app_id = :source_app_id")
@@ -640,8 +797,12 @@ WHERE
             workflow_binding_filters.append("wanb.workflow_version = :workflow_version")
         if source_filter.node_id:
             workflow_binding_filters.append("wanb.node_id = :node_id")
-        extra_workflow_filters = f"AND {' AND '.join(workflow_binding_filters)}" if workflow_binding_filters else ""
-        workflow_scope = f"""m.workflow_run_id IS NOT NULL
+        return f"AND {' AND '.join(workflow_binding_filters)}" if workflow_binding_filters else ""
+
+    @classmethod
+    def _statistics_workflow_message_scope_sql(cls, source_filter: AgentSourceFilter) -> str:
+        binding_filters = cls._statistics_workflow_binding_filters_sql(source_filter)
+        return f"""m.workflow_run_id IS NOT NULL
         AND EXISTS (
             SELECT 1
             FROM workflow_runs wr
@@ -651,17 +812,65 @@ WHERE
                 AND wanb.app_id = wr.app_id
                 AND wanb.workflow_id = wr.workflow_id
                 AND wanb.workflow_version = wr.version
-                {extra_workflow_filters}
+                {binding_filters}
             JOIN workflow_node_executions wne
                 ON wne.workflow_run_id = wr.id
                 AND wne.node_id = wanb.node_id
             WHERE wr.id = m.workflow_run_id
+                AND wr.type = :chat_workflow_type
         )"""
-        if source_filter.kind == "webapp":
-            return app_scope
-        if source_filter.kind == "workflow":
-            return workflow_scope
-        return f"(({app_scope}) OR ({workflow_scope}))"
+
+    @staticmethod
+    def _workflow_execution_metadata_numeric_sql(path: tuple[str, ...], numeric_type: str) -> str:
+        if dify_config.DB_TYPE == "postgresql":
+            json_path = ",".join(path)
+            value = f"CAST(wne.execution_metadata AS JSONB) #>> '{{{json_path}}}'"
+            return f"CAST(NULLIF({value}, '') AS {numeric_type})"
+        if dify_config.DB_TYPE in {"mysql", "oceanbase", "seekdb"}:
+            json_path = "$." + ".".join(path)
+            mysql_numeric_type = "UNSIGNED" if numeric_type == "BIGINT" else numeric_type
+            value = f"JSON_UNQUOTE(JSON_EXTRACT(wne.execution_metadata, '{json_path}'))"
+            return f"CAST(NULLIF(NULLIF({value}, ''), 'null') AS {mysql_numeric_type})"
+        raise NotImplementedError(f"Unsupported database type: {dify_config.DB_TYPE}")
+
+    @staticmethod
+    def _merge_daily_statistics(rows: list[dict[str, Any]]) -> list[dict[str, Any]]:
+        merged: dict[Any, dict[str, Any]] = {}
+        weighted_latency: dict[Any, float] = {}
+        for row in rows:
+            date = row["date"]
+            target = merged.setdefault(
+                date,
+                {
+                    "date": date,
+                    "message_count": 0,
+                    "conversation_count": 0,
+                    "end_user_count": 0,
+                    "token_count": 0,
+                    "total_price": Decimal(0),
+                    "avg_latency": 0.0,
+                    "latency_sum": 0.0,
+                    "answer_tokens": 0,
+                    "like_count": 0,
+                },
+            )
+            message_count = int(row.get("message_count") or 0)
+            target["message_count"] += message_count
+            target["conversation_count"] += int(row.get("conversation_count") or 0)
+            target["end_user_count"] += int(row.get("end_user_count") or 0)
+            target["token_count"] += int(row.get("token_count") or 0)
+            target["total_price"] += Decimal(str(row.get("total_price") or 0))
+            target["latency_sum"] += float(row.get("latency_sum") or 0)
+            target["answer_tokens"] += int(row.get("answer_tokens") or 0)
+            target["like_count"] += int(row.get("like_count") or 0)
+            weighted_latency[date] = (
+                weighted_latency.get(date, 0.0) + float(row.get("avg_latency") or 0) * message_count
+            )
+
+        for date, row in merged.items():
+            message_count = int(row["message_count"])
+            row["avg_latency"] = weighted_latency[date] / message_count if message_count else 0.0
+        return sorted(merged.values(), key=lambda row: str(row["date"]))
 
     @staticmethod
     def _build_charts(rows: list[dict[str, Any]]) -> dict[str, list[dict[str, Any]]]:

api/services/app_service.py

@@ -408,6 +408,7 @@ class AppService:
         default_model_config = app_template.get("model_config")
         default_model_config = default_model_config.copy() if default_model_config else None
         if default_model_config and "model" in default_model_config:
+            default_model_dict = default_model_config["model"]
             # get model provider
             model_manager = ModelManager.for_tenant(tenant_id=account.current_tenant_id or "")
 
@@ -422,7 +423,7 @@ class AppService:
                 logger.exception("Get default model instance failed, tenant_id: %s", tenant_id)
                 model_instance = None
 
-            if model_instance:
+            if model_instance is not None:
                 if (
                     model_instance.model_name == default_model_config["model"]["name"]
                     and model_instance.provider == default_model_config["model"]["provider"]
@@ -430,17 +431,28 @@ class AppService:
                     default_model_dict = default_model_config["model"]
                 else:
                     llm_model = cast(LargeLanguageModel, model_instance.model_type_instance)
-                    model_schema = llm_model.get_model_schema(model_instance.model_name, model_instance.credentials)
-                    if model_schema is None:
-                        raise ValueError(f"model schema not found for model {model_instance.model_name}")
-
-                    default_model_dict = {
-                        "provider": model_instance.provider,
-                        "name": model_instance.model_name,
-                        "mode": model_schema.model_properties.get(ModelPropertyKey.MODE),
-                        "completion_params": {},
-                    }
-            else:
+                    try:
+                        model_schema = llm_model.get_model_schema(model_instance.model_name, model_instance.credentials)
+                        if model_schema is None:
+                            raise ValueError(f"model schema not found for model {model_instance.model_name}")
+                    except Exception:
+                        # A removed provider model must not prevent creating an app.
+                        logger.warning(
+                            "Default model schema is unavailable, tenant_id: %s, provider: %s, model: %s",
+                            tenant_id,
+                            model_instance.provider,
+                            model_instance.model_name,
+                            exc_info=True,
+                        )
+                        model_instance = None
+                    else:
+                        default_model_dict = {
+                            "provider": model_instance.provider,
+                            "name": model_instance.model_name,
+                            "mode": model_schema.model_properties.get(ModelPropertyKey.MODE),
+                            "completion_params": {},
+                        }
+            if model_instance is None:
                 try:
                     provider, model = model_manager.get_default_provider_model_name(
                         tenant_id=account.current_tenant_id or "", model_type=ModelType.LLM

api/services/dataset_service.py

@@ -739,8 +739,13 @@ class DatasetService:
             dataset.id, external_knowledge_id, external_knowledge_api_id, session
         )
 
-        # Commit changes to database
-        session.commit()
+        # Flush changes to the database without closing the caller-managed
+        # transaction. This helper receives a session opened by the caller
+        # (`with Session(...) as session`); calling commit() here closed that
+        # context manager early and raised
+        # sqlalchemy.exc.InvalidRequestError: Can't operate on closed transaction
+        # (#39191).
+        session.flush()
 
         return dataset
 
@@ -810,9 +815,15 @@ class DatasetService:
         if data.get("icon_info"):
             filtered_data["icon_info"] = data.get("icon_info")
 
-        # Update dataset in database
+        # Update dataset in database. Use flush() rather than commit() so the
+        # caller-managed transaction (opened with `with Session(...) as session`)
+        # stays open for subsequent operations — _update_pipeline_knowledge_base
+        # node data and any caller follow-ups run on the same session. Calling
+        # commit() here closed the context manager early and raised
+        # sqlalchemy.exc.InvalidRequestError: Can't operate on closed transaction
+        # (#39191).
         session.execute(update(Dataset).where(Dataset.id == dataset.id).values(**filtered_data))
-        session.commit()
+        session.flush()
 
         # Reload dataset to get updated values
         session.refresh(dataset)

api/services/enterprise/rbac_service.py

@@ -317,9 +317,6 @@ _LEGACY_WORKSPACE_OWNER_KEYS: list[str] = [
     "credential.use",
     "credential.create",
     "credential.manage",
-    "billing.view",
-    "billing.subscription.manage",
-    "billing.manage",
     "app.acl.preview",
     "app_library.access",
     "app.create_and_management",
@@ -349,9 +346,6 @@ _LEGACY_WORKSPACE_ADMIN_KEYS: list[str] = [
     "credential.use",
     "credential.create",
     "credential.manage",
-    "billing.view",
-    "billing.subscription.manage",
-    "billing.manage",
     "app_library.access",
     "app.create_and_management",
     "app.tag.manage",
@@ -377,9 +371,6 @@ _LEGACY_WORKSPACE_EDITOR_KEYS: list[str] = [
     "dataset.external.connect",
     "snippets.create_and_modify",
     "tool.manage",
-    "billing.view",
-    "billing.subscription.manage",
-    "billing.manage",
 ]
 
 _LEGACY_WORKSPACE_NORMAL_KEYS: list[str] = [
@@ -387,9 +378,6 @@ _LEGACY_WORKSPACE_NORMAL_KEYS: list[str] = [
     "plugin.install",
     "credential.use",
     "app_library.access",
-    "billing.view",
-    "billing.subscription.manage",
-    "billing.manage",
 ]
 
 _LEGACY_WORKSPACE_DATASET_OPERATOR_KEYS: list[str] = [
@@ -805,7 +793,6 @@ class RBACService:
             data = _inner_call(
                 "GET",
                 f"{_INNER_PREFIX}/role-permissions/catalog",
-                params={"billing_enabled": dify_config.BILLING_ENABLED},
                 tenant_id=tenant_id,
                 account_id=account_id,
             )

api/services/feature_service.py

@@ -100,6 +100,7 @@ class WebAppAuthModel(FeatureResponseModel):
     sso_config: WebAppAuthSSOModel = WebAppAuthSSOModel()
     allow_email_code_login: bool = False
     allow_email_password_login: bool = False
+    allow_public_access: bool = True
 
 
 class KnowledgePipeline(FeatureResponseModel):
@@ -183,6 +184,7 @@ class SystemFeatureModel(FeatureResponseModel):
     enable_trial_app: bool = False
     enable_explore_banner: bool = False
     enable_learn_app: bool = True
+    enable_step_by_step_tour: bool = False
     rbac_enabled: bool = False
 
 
@@ -285,6 +287,8 @@ class FeatureService:
         system_features.enable_trial_app = dify_config.ENABLE_TRIAL_APP
         system_features.enable_explore_banner = dify_config.ENABLE_EXPLORE_BANNER
         system_features.enable_learn_app = dify_config.ENABLE_LEARN_APP
+        system_features.webapp_auth.allow_public_access = dify_config.WEBAPP_PUBLIC_ACCESS_ENABLED
+        system_features.enable_step_by_step_tour = dify_config.ENABLE_STEP_BY_STEP_TOUR
 
     @classmethod
     def _fulfill_trial_models_from_env(cls) -> list[str]:

api/services/knowledge_fs_proxy.py

@@ -0,0 +1,358 @@
+"""Transport-only forwarding for the explicitly enabled KnowledgeFS Console operations.
+
+KnowledgeFS owns the request and response contract. This module binds short-lived
+account and workspace identities, enforces Dify's coarse workspace policy, and
+normalizes transport failures. Dify deliberately maintains a small product-facing
+operation registry instead of exposing the full upstream OpenAPI surface. The
+dedicated request path uses Dify's shared SSRF policy, never follows redirects,
+bounds buffered responses, and rejects compressed responses.
+"""
+
+from __future__ import annotations
+
+from collections.abc import Iterable, Mapping
+from datetime import UTC, datetime, timedelta
+from http import HTTPStatus
+from typing import Final, Literal, NamedTuple, Protocol
+
+import httpx
+import jwt
+
+from configs import dify_config
+from core.helper import ssrf_proxy
+from core.rbac import RBACPermission, RBACResourceScope
+from core.tools.errors import ToolSSRFError
+from models import Account
+from services.enterprise.rbac_service import RBACService
+
+type KnowledgeFSMethod = Literal["DELETE", "GET", "PATCH", "POST", "PUT"]
+type KnowledgeFSResponseKind = Literal["binary", "buffered", "stream"]
+type KnowledgeFSRequiredScope = Literal["knowledge-spaces:read", "knowledge-spaces:write"]
+
+_JWT_AUDIENCE = "knowledge-fs"
+_JWT_ISSUER = "dify"
+_JWT_TTL_SECONDS = 60
+_MAX_BUFFERED_RESPONSE_BYTES = 1024 * 1024
+
+
+class KnowledgeFSOperation(NamedTuple):
+    operation_id: str
+    method: KnowledgeFSMethod
+    path: str
+    response_kind: KnowledgeFSResponseKind
+    required_scope: KnowledgeFSRequiredScope
+    rbac_permission: RBACPermission
+    requires_dataset_editor: bool
+    max_response_bytes: int
+    request_headers: tuple[str, ...]
+    response_headers: tuple[str, ...]
+    response_media_types: tuple[str, ...]
+
+
+KNOWLEDGE_FS_CONSOLE_OPERATIONS: Final[tuple[KnowledgeFSOperation, ...]] = (
+    KnowledgeFSOperation(
+        operation_id="listKnowledgeSpaces",
+        method="GET",
+        path="knowledge-spaces",
+        response_kind="buffered",
+        required_scope="knowledge-spaces:read",
+        rbac_permission=RBACPermission.DATASET_READONLY,
+        requires_dataset_editor=False,
+        max_response_bytes=1_048_576,
+        request_headers=("x-trace-id",),
+        response_headers=("x-trace-id",),
+        response_media_types=("application/json",),
+    ),
+    KnowledgeFSOperation(
+        operation_id="createKnowledgeSpace",
+        method="POST",
+        path="knowledge-spaces",
+        response_kind="buffered",
+        required_scope="knowledge-spaces:write",
+        rbac_permission=RBACPermission.DATASET_CREATE_AND_MANAGEMENT,
+        requires_dataset_editor=True,
+        max_response_bytes=1_048_576,
+        request_headers=("x-trace-id",),
+        response_headers=("x-trace-id",),
+        response_media_types=("application/json",),
+    ),
+)
+
+
+class KnowledgeFSUpstreamResponse(NamedTuple):
+    response: httpx.Response
+    response_kind: KnowledgeFSResponseKind
+    operation: KnowledgeFSOperation
+
+
+class _RequestHeaders(Protocol):
+    def items(self) -> Iterable[tuple[str, str]]: ...
+
+
+class KnowledgeFSConfigurationError(RuntimeError):
+    """KnowledgeFS is incompletely configured or blocked by outbound policy."""
+
+
+class KnowledgeFSTimeoutError(RuntimeError):
+    """KnowledgeFS exceeded the configured request timeout."""
+
+
+class KnowledgeFSTransportError(RuntimeError):
+    """KnowledgeFS could not be reached or returned a response outside safety bounds."""
+
+
+class KnowledgeFSRouteNotAllowedError(RuntimeError):
+    """The requested path is outside the Console-visible KnowledgeFS surface."""
+
+
+class KnowledgeFSAccessDeniedError(RuntimeError):
+    """The Dify account lacks the workspace permission required by the operation."""
+
+
+def authorize_knowledge_fs_request(
+    *,
+    account: Account,
+    tenant_id: str,
+    operation: KnowledgeFSOperation,
+) -> None:
+    """Enforce Dify's workspace policy before KFS performs resource authorization.
+
+    Args:
+        account: Authenticated Dify account with its current workspace role.
+        tenant_id: Current Dify workspace identifier.
+        operation: Dify-maintained KnowledgeFS operation and policy metadata.
+
+    Raises:
+        KnowledgeFSAccessDeniedError: The account lacks a required legacy or enterprise permission.
+    """
+    if operation.requires_dataset_editor and not account.is_dataset_editor:
+        raise KnowledgeFSAccessDeniedError("KnowledgeFS mutations require dataset edit access")
+    if not RBACService.CheckAccess.check(
+        tenant_id,
+        account.id,
+        scene=operation.rbac_permission.value,
+        resource_type=RBACResourceScope.DATASET.value,
+    ):
+        raise KnowledgeFSAccessDeniedError("KnowledgeFS operation is denied by workspace RBAC")
+
+
+def proxy_knowledge_fs_request(
+    *,
+    account: Account,
+    method: KnowledgeFSMethod,
+    path: str,
+    tenant_id: str,
+    accept: str | None = None,
+    content_type: str | None = None,
+    query: bytes | None = None,
+    body: bytes | None = None,
+    request_headers: _RequestHeaders | None = None,
+) -> KnowledgeFSUpstreamResponse:
+    """Authorize and forward one allowlisted KnowledgeFS request as a single use case."""
+    operation = get_knowledge_fs_operation(method, path)
+    authorize_knowledge_fs_request(
+        account=account,
+        tenant_id=tenant_id,
+        operation=operation,
+    )
+    incoming_request_headers = {name.lower(): value for name, value in (request_headers or {}).items()}
+    contract_request_headers = {
+        name: incoming_request_headers[name] for name in operation.request_headers if name in incoming_request_headers
+    }
+    return _forward_knowledge_fs_request(
+        account_id=account.id,
+        method=method,
+        path=path,
+        tenant_id=tenant_id,
+        accept=accept,
+        content_type=content_type,
+        query=query,
+        body=body,
+        request_headers=contract_request_headers,
+    )
+
+
+def _forward_knowledge_fs_request(
+    *,
+    account_id: str,
+    method: KnowledgeFSMethod,
+    path: str,
+    tenant_id: str,
+    accept: str | None = None,
+    content_type: str | None = None,
+    query: bytes | None = None,
+    body: bytes | None = None,
+    request_headers: Mapping[str, str] | None = None,
+) -> KnowledgeFSUpstreamResponse:
+    """Forward one fixed-route request without parsing its KnowledgeFS payload.
+
+    Args:
+        account_id: Current Dify account used as the KFS member identity.
+        method: Allowlisted upstream HTTP method.
+        path: Relative KnowledgeFS path under an allowlisted product surface.
+        tenant_id: Current Dify workspace used as the KFS tenant identity.
+        accept: Original Accept header, when present.
+        content_type: Original request Content-Type header, when present.
+        query: Original encoded query string from the Console request.
+        body: Original request body, when present.
+        request_headers: Contract-declared request headers forwarded by the Console adapter.
+
+    Returns:
+        The KnowledgeFS response and its actual transport kind. Non-success responses are buffered.
+
+    Raises:
+        KnowledgeFSConfigurationError: The connection is incomplete or blocked by outbound policy.
+        KnowledgeFSRouteNotAllowedError: The path is outside the allowlisted product surface.
+        KnowledgeFSTimeoutError: KnowledgeFS exceeds the configured timeout.
+        KnowledgeFSTransportError: The request fails or its response cannot be safely bounded.
+
+    Each request is bound to stable Dify account and workspace principals with a short expiration.
+    """
+    operation = get_knowledge_fs_operation(method, path)
+    base_url = dify_config.KNOWLEDGE_FS_BASE_URL
+    jwt_secret = dify_config.KNOWLEDGE_FS_JWT_SECRET
+    if base_url is None or jwt_secret is None:
+        raise KnowledgeFSConfigurationError("KnowledgeFS connection configuration is incomplete")
+    now = datetime.now(UTC)
+    token = jwt.encode(
+        {
+            "aud": _JWT_AUDIENCE,
+            "caller_kind": "interactive",
+            "dify_account_id": f"dify-account:{account_id}",
+            "exp": now + timedelta(seconds=_JWT_TTL_SECONDS),
+            "iat": now,
+            "iss": _JWT_ISSUER,
+            "scopes": [operation.required_scope],
+            "sub": f"dify-workspace:{tenant_id}",
+            "tenant_id": tenant_id,
+        },
+        jwt_secret.get_secret_value(),
+        algorithm="HS256",
+    )
+    headers = {
+        "Accept": accept or "application/json",
+        "Accept-Encoding": "identity",
+        "Authorization": f"Bearer {token}",
+    }
+    if body is not None:
+        headers["Content-Type"] = content_type or "application/json"
+    allowed_request_headers = set(operation.request_headers)
+    for name, value in (request_headers or {}).items():
+        normalized_name = name.lower()
+        if normalized_name not in allowed_request_headers:
+            raise KnowledgeFSRouteNotAllowedError("KnowledgeFS request header is not allowed")
+        headers[normalized_name] = value
+
+    try:
+        upstream_url = httpx.URL(f"{base_url}/").join(operation.path)
+        response = ssrf_proxy.make_request(
+            method=operation.method,
+            url=str(upstream_url),
+            params=query,
+            content=body,
+            headers=headers,
+            timeout=dify_config.KNOWLEDGE_FS_TIMEOUT_SECONDS,
+            follow_redirects=False,
+            max_retries=0,
+            stream_response=True,
+        )
+        response_kind = _classify_response(operation, response)
+        if response_kind == "stream":
+            content_encoding = response.headers.get("content-encoding", "identity").strip().lower()
+            if content_encoding not in {"", "identity"}:
+                response.close()
+                raise KnowledgeFSTransportError("KnowledgeFS streaming response used an unsupported encoding")
+            _set_response_read_timeout(response, dify_config.KNOWLEDGE_FS_SSE_READ_TIMEOUT_SECONDS)
+            return KnowledgeFSUpstreamResponse(response, response_kind, operation)
+
+        max_response_bytes = (
+            operation.max_response_bytes
+            if HTTPStatus.OK <= response.status_code < HTTPStatus.MULTIPLE_CHOICES
+            else _MAX_BUFFERED_RESPONSE_BYTES
+        )
+        buffered_response = ssrf_proxy.buffer_response(response, max_response_bytes=max_response_bytes)
+        if buffered_response.content and not buffered_response.headers.get("content-type", "").strip():
+            buffered_response.close()
+            raise KnowledgeFSTransportError("KnowledgeFS buffered response used an unsupported media type")
+        return KnowledgeFSUpstreamResponse(buffered_response, response_kind, operation)
+    except ssrf_proxy.ResponseLimitError as exc:
+        raise KnowledgeFSTransportError("KnowledgeFS response violated the proxy limit") from exc
+    except ToolSSRFError as exc:
+        raise KnowledgeFSConfigurationError("KnowledgeFS origin was blocked by outbound policy") from exc
+    except httpx.TimeoutException as exc:
+        raise KnowledgeFSTimeoutError("KnowledgeFS request timed out") from exc
+    except httpx.RequestError as exc:
+        raise KnowledgeFSTransportError("KnowledgeFS transport request failed") from exc
+
+
+def get_knowledge_fs_operation(method: KnowledgeFSMethod, path: str) -> KnowledgeFSOperation:
+    """Resolve an exact operation and its transport/access contract metadata."""
+    for operation in KNOWLEDGE_FS_CONSOLE_OPERATIONS:
+        if method == operation.method and _matches_route_template(operation.path, path):
+            return operation._replace(path=path)
+    raise KnowledgeFSRouteNotAllowedError("KnowledgeFS route is not allowed")
+
+
+def _classify_response(operation: KnowledgeFSOperation, response: httpx.Response) -> KnowledgeFSResponseKind:
+    """Resolve the actual response kind from status and Content-Type before reading its body."""
+    content_type = response.headers.get("content-type", "").partition(";")[0].strip().lower()
+    is_success = HTTPStatus.OK <= response.status_code < HTTPStatus.MULTIPLE_CHOICES
+    if not is_success:
+        if content_type and not _is_json_content_type(content_type):
+            response.close()
+            raise KnowledgeFSTransportError("KnowledgeFS error response used an unsupported media type")
+        return "buffered"
+
+    if operation.response_kind == "stream":
+        if content_type != "text/event-stream":
+            response.close()
+            raise KnowledgeFSTransportError("KnowledgeFS stream response used an unsupported media type")
+        return "stream"
+    if operation.response_kind == "binary":
+        if content_type not in operation.response_media_types:
+            response.close()
+            raise KnowledgeFSTransportError("KnowledgeFS binary response used an unsupported media type")
+        return "binary"
+    if content_type and not _is_json_content_type(content_type):
+        response.close()
+        raise KnowledgeFSTransportError("KnowledgeFS buffered response used an unsupported media type")
+    return "buffered"
+
+
+def _is_json_content_type(content_type: str) -> bool:
+    return content_type == "application/json" or content_type.endswith("+json")
+
+
+def _set_response_read_timeout(response: httpx.Response, timeout_seconds: float | None) -> None:
+    """Set the body-read timeout after headers identify a valid SSE response."""
+    try:
+        request = response.request
+    except RuntimeError:
+        return
+    timeout = request.extensions.get("timeout")
+    if isinstance(timeout, dict):
+        timeout["read"] = timeout_seconds
+
+
+def _matches_route_template(template: str, path: str) -> bool:
+    """Match path parameters without permitting encoded or traversal-like segments."""
+    template_segments = template.split("/")
+    path_segments = path.split("/")
+    if len(template_segments) != len(path_segments):
+        return False
+
+    for template_segment, path_segment in zip(template_segments, path_segments, strict=True):
+        if template_segment.startswith("{") and template_segment.endswith("}"):
+            if (
+                not path_segment
+                or path_segment in {".", ".."}
+                or "\\" in path_segment
+                or "%" in path_segment
+                or "?" in path_segment
+                or "#" in path_segment
+            ):
+                return False
+            continue
+        if template_segment != path_segment:
+            return False
+    return True

api/services/rag_pipeline/rag_pipeline.py

@@ -601,6 +601,7 @@ class RagPipelineService:
         with sessionmaker(bind=db.engine).begin() as session:
             draft_var_saver = DraftVariableSaver(
                 session=session,
+                tenant_id=pipeline.tenant_id,
                 app_id=pipeline.id,
                 node_id=workflow_node_execution.node_id,
                 node_type=workflow_node_execution.node_type,
@@ -1391,6 +1392,7 @@ class RagPipelineService:
         with sessionmaker(bind=db.engine).begin() as session:
             draft_var_saver = DraftVariableSaver(
                 session=session,
+                tenant_id=pipeline.tenant_id,
                 app_id=pipeline.id,
                 node_id=workflow_node_execution_db_model.node_id,
                 node_type=workflow_node_execution_db_model.node_type,

api/services/retention/workflow_run/archive_paid_plan_workflow_run.py

@@ -6,7 +6,10 @@ This service archives workflow run logs for paid plan users older than the confi
 
 Archive V2 writes bundle-level Parquet objects. A bundle contains many workflow runs and their related table rows.
 Bundle metadata lives in the object-store manifest as the recoverable source of truth. Completed bundles are also
-mirrored into a small database index so console listing and download jobs do not list object storage online.
+published into a small database catalog so console listing, download, and maintenance jobs do not list object storage
+online. Archive success requires that catalog publication to commit. A retry reconciles only its known manifest key
+against an already-published shard index; a missing shard index fails closed rather than rebuilding it by scanning
+historical manifests.
 
 Archive campaigns should use fixed absolute UTC windows for every tenant-prefix/shard execution. Relative windows are
 evaluated at process start and are not safe for multi-day rollout because each command would scan a different window.
@@ -639,7 +642,6 @@ class WorkflowRunArchiver:
                 if storage is None:
                     raise ArchiveStorageNotConfiguredError("Archive storage not configured")
                 if storage.object_exists(self._get_manifest_object_key(identity)):
-                    self._write_bundle_index(storage, identity)
                     self._sync_existing_bundle_index(session, storage, identity)
                     result.success = True
                     result.skipped = True
@@ -651,6 +653,8 @@ class WorkflowRunArchiver:
                 runs = [run for run in runs if run.id not in archived_run_ids]
                 result.skipped_run_count = original_run_count - len(runs)
                 if not runs:
+                    # Historical catalog rows are a rollout precondition. New bundles commit their catalog row before
+                    # publishing the shard index, so this idempotency path never needs to rescan prior manifests.
                     result.run_count = 0
                     result.success = True
                     result.skipped = True
@@ -663,7 +667,6 @@ class WorkflowRunArchiver:
                 result.object_prefix = identity.object_prefix
                 result.run_count = len(runs)
                 if storage.object_exists(self._get_manifest_object_key(identity)):
-                    self._write_bundle_index(storage, identity)
                     self._sync_existing_bundle_index(session, storage, identity)
                     result.success = True
                     result.skipped = True
@@ -695,10 +698,10 @@ class WorkflowRunArchiver:
                 for table_name, payload in table_payloads.items():
                     storage.put_object(self._get_table_object_key(identity, table_name), payload)
                 storage.put_object(self._get_manifest_object_key(identity), manifest_data)
-                self._merge_bundle_manifest_into_index(storage, identity, [run.id for run in runs])
                 manifest = decode_archive_bundle_manifest(manifest_data)
                 upsert_archive_bundle_index_from_manifest(session, manifest, len(manifest_data))
                 session.commit()
+                self._merge_bundle_manifest_into_index(storage, identity, [run.id for run in runs])
 
                 logger.info(
                     "Archived workflow run bundle %s: tenant=%s runs=%s tables=%s object_prefix=%s",
@@ -730,16 +733,18 @@ class WorkflowRunArchiver:
         storage: ArchiveStorage,
         identity: ArchiveBundleIdentity,
     ) -> None:
-        """Best-effort DB index sync for a bundle whose manifest already exists in archive storage."""
+        """Publish a known manifest to the DB catalog and reconcile its existing shard index."""
         manifest_key = self._get_manifest_object_key(identity)
-        try:
-            manifest_data = storage.get_object(manifest_key)
-            manifest = decode_archive_bundle_manifest(manifest_data)
-            upsert_archive_bundle_index_from_manifest(session, manifest, len(manifest_data))
-            session.commit()
-        except Exception:
-            session.rollback()
-            logger.warning("Failed to sync workflow archive bundle index for %s", manifest_key, exc_info=True)
+        manifest_data = storage.get_object(manifest_key)
+        manifest = decode_archive_bundle_manifest(manifest_data)
+        upsert_archive_bundle_index_from_manifest(session, manifest, len(manifest_data))
+        session.commit()
+        self._merge_bundle_manifest_into_index(
+            storage,
+            identity,
+            manifest["run_ids"],
+            require_existing_index=True,
+        )
 
     def _lock_runs_for_archive(
         self,
@@ -1029,10 +1034,20 @@ class WorkflowRunArchiver:
         storage: ArchiveStorage,
         identity: ArchiveBundleIdentity,
         run_ids: Sequence[str],
+        *,
+        require_existing_index: bool = False,
     ) -> ArchiveBundleIndexDict:
+        """
+        Merge one bundle into its shard index.
+
+        Retries for a known manifest set ``require_existing_index`` so they never create a partial index by scanning
+        or overwriting a shard whose historical entries cannot be proven from this one manifest.
+        """
         index_key = self._get_index_object_key(identity)
         if storage.object_exists(index_key):
             index = self._load_bundle_index(storage, identity)
+        elif require_existing_index:
+            raise RuntimeError(f"archive shard index missing while reconciling known manifest: {index_key}")
         else:
             index = self._build_bundle_index(storage, identity)
 

api/services/retention/workflow_run/bundle_archive_maintenance.py

@@ -1,14 +1,16 @@
 """
 Maintain V2 workflow-run archive bundles.
 
-Archive V2 keeps object-store manifests as the recoverable bundle source of truth. This maintenance module still
-discovers delete/restore targets by listing `manifest.json` objects and uses object-store marker files for
-delete/restore state. The separate database bundle index is intended for console listing and download jobs, not as the
-source of truth for destructive maintenance.
+Archive V2 keeps object-store manifests as the recoverable bundle source of truth. Delete and restore discover a
+bounded page of candidates from `workflow_run_archive_bundles`, optionally restricted to one exact archive shard, then
+construct each immutable manifest key from the catalog identity. They never list the object-store namespace.
+Object-store marker files keep delete/restore idempotent, while the caller persists a non-dry-run cursor only after a
+candidate succeeds.
 
 Each bundle is processed in its own database transaction. A failed bundle leaves source rows unchanged unless the
 transaction has already committed; marker handling makes the next run able to reconcile the common committed-but-marker
-not-updated case.
+not-updated case. Restore never skips a bundle with a missing deleted marker when deletion started or source rows have
+drifted, so an external cursor cannot pass an interrupted delete.
 """
 
 import datetime
@@ -38,6 +40,7 @@ from models.workflow import (
     WorkflowPause,
     WorkflowPauseReason,
     WorkflowRun,
+    WorkflowRunArchiveBundle,
 )
 from services.retention.workflow_run.constants import (
     ARCHIVE_BUNDLE_DELETE_STARTED_MARKER_NAME,
@@ -51,7 +54,6 @@ from services.retention.workflow_run.constants import (
 
 logger = logging.getLogger(__name__)
 
-_ARCHIVE_ROOT_PREFIX = "workflow-runs/v2/"
 _CHUNK_SIZE = 5_000
 
 
@@ -84,11 +86,28 @@ class BundleManifest(TypedDict):
 
 
 @dataclass(frozen=True)
-class BundleReference:
-    """Object-store reference for one V2 archive bundle."""
+class ArchiveBundleCatalogEntry:
+    """Immutable catalog identity and manifest-derived metrics for one V2 archive bundle."""
 
+    catalog_id: str
+    tenant_id: str
+    year: int
+    month: int
+    shard: str
+    bundle_id: str
+    workflow_run_count: int
+    row_count: int
+    archive_bytes: int
+
+
+@dataclass(frozen=True)
+class BundleReference:
+    """Verified object-store reference for one catalog candidate."""
+
+    catalog: ArchiveBundleCatalogEntry
     object_prefix: str
     manifest_key: str
+    manifest_size_bytes: int
     manifest: BundleManifest
 
 
@@ -96,6 +115,7 @@ class BundleReference:
 class BundleOperationResult:
     """Result for one V2 bundle delete or restore operation."""
 
+    catalog_id: str
     bundle_id: str
     tenant_id: str
     object_prefix: str
@@ -128,6 +148,8 @@ class BundleOperationSummary:
     archive_bytes: int = 0
     elapsed_time: float = 0.0
     validation_time: float = 0.0
+    next_catalog_id: str | None = None
+    preview_next_catalog_id: str | None = None
     table_counts: dict[str, int] = field(default_factory=dict)
     results: list[BundleOperationResult] = field(default_factory=list)
 
@@ -180,162 +202,334 @@ RESTORE_ORDER = [
     "workflow_trigger_logs",
 ]
 
+DELETE_ORDER = [
+    "workflow_pause_reasons",
+    "workflow_node_execution_offload",
+    "workflow_trigger_logs",
+    "workflow_app_logs",
+    "workflow_node_executions",
+    "workflow_pauses",
+    "workflow_runs",
+]
+
 
 class WorkflowRunBundleArchiveMaintenance:
     """
     Delete and restore V2 workflow-run archive bundles.
 
+    Delete accepts already-missing source rows only when every remaining row in the bundle scope is an unchanged
+    archive subset. It then removes only those verified primary keys, so unrelated or unarchived rows fail closed.
+    Non-dry-run delete and restore serialize on the existing archive catalog row before checking markers or changing
+    source rows.
+
     Args:
         dry_run: Validate and report counts without changing source rows or object-store markers.
-        strict_content_validation: Compare source-table content checksums against Parquet content before destructive
-            delete and after restore. Keep enabled for real maintenance.
-        stop_on_error: Stop batch processing after the first failed bundle.
+        strict_content_validation: Compare restored source-table content checksums against Parquet content. Delete
+            always validates that every remaining live row belongs to and matches the archive before removing it.
+        storage: Optional archive storage implementation. Tests may provide an in-memory implementation.
+        session_factory: Optional session factory. Each candidate is processed in its own transaction.
+
+    Batches stop at the first error so a returned cursor cannot pass an unhandled candidate.
     """
 
     dry_run: bool
     strict_content_validation: bool
-    stop_on_error: bool
+    storage: ArchiveStorage | None
+    session_factory: sessionmaker[Session]
 
     def __init__(
         self,
         *,
         dry_run: bool = False,
         strict_content_validation: bool = True,
-        stop_on_error: bool = True,
+        storage: ArchiveStorage | None = None,
+        session_factory: sessionmaker[Session] | None = None,
     ) -> None:
         self.dry_run = dry_run
         self.strict_content_validation = strict_content_validation
-        self.stop_on_error = stop_on_error
+        self.storage = storage
+        self.session_factory = session_factory or sessionmaker(bind=db.engine, expire_on_commit=False)
 
     def delete_batch(
         self,
         *,
         tenant_ids: Sequence[str] | None,
-        start_date: datetime.datetime,
-        end_date: datetime.datetime,
+        target_year: int,
+        target_month: int,
+        after_catalog_id: str | None,
         limit: int,
+        shard: str | None = None,
     ) -> BundleOperationSummary:
-        """Validate and delete source rows for archived V2 bundles in the requested created_at window."""
+        """Validate and delete one keyset page, optionally scoped to an exact archive shard."""
         return self._process_batch(
             operation="delete",
             tenant_ids=tenant_ids,
-            start_date=start_date,
-            end_date=end_date,
+            target_year=target_year,
+            target_month=target_month,
+            after_catalog_id=after_catalog_id,
             limit=limit,
+            shard=shard,
         )
 
     def restore_batch(
         self,
         *,
         tenant_ids: Sequence[str] | None,
-        start_date: datetime.datetime,
-        end_date: datetime.datetime,
+        target_year: int,
+        target_month: int,
+        after_catalog_id: str | None,
         limit: int,
     ) -> BundleOperationSummary:
-        """Restore source rows for deleted V2 bundles in the requested created_at window."""
+        """Restore source rows for a keyset page of deleted V2 bundles in one calendar month."""
         return self._process_batch(
             operation="restore",
             tenant_ids=tenant_ids,
-            start_date=start_date,
-            end_date=end_date,
+            target_year=target_year,
+            target_month=target_month,
+            after_catalog_id=after_catalog_id,
             limit=limit,
+            shard=None,
         )
 
+    def validate_catalog_shards(
+        self,
+        *,
+        target_year: int,
+        target_month: int,
+        shard_total: int,
+        tenant_ids: Sequence[str] | None = None,
+    ) -> None:
+        """
+        Fail before a parallel delete when the requested closed-month scope contains a different shard layout.
+
+        A subset of the expected shards is valid because an archive shard may legitimately contain no bundles. Any
+        other shard name indicates a historical or mixed-layout month that must be handled by the serial delete path.
+        """
+        if not 1 <= shard_total <= 16:
+            raise ValueError("shard_total must be between 1 and 16")
+        expected_shards = tuple(f"{index:02d}-of-{shard_total:02d}" for index in range(shard_total))
+        conditions = [
+            WorkflowRunArchiveBundle.year == target_year,
+            WorkflowRunArchiveBundle.month == target_month,
+        ]
+        if tenant_ids is not None:
+            conditions.append(WorkflowRunArchiveBundle.tenant_id.in_(tenant_ids))
+        statement = (
+            select(WorkflowRunArchiveBundle.shard)
+            .where(
+                *conditions,
+                WorkflowRunArchiveBundle.shard.not_in(expected_shards),
+            )
+            .distinct()
+            .order_by(WorkflowRunArchiveBundle.shard.asc())
+        )
+        with self.session_factory() as session:
+            unexpected_shards = list(session.scalars(statement))
+        if unexpected_shards:
+            raise ValueError(
+                "archive catalog month contains unexpected shards for "
+                f"{shard_total}-way delete: {', '.join(unexpected_shards)}"
+            )
+
     def _process_batch(
         self,
         *,
         operation: str,
         tenant_ids: Sequence[str] | None,
-        start_date: datetime.datetime,
-        end_date: datetime.datetime,
+        target_year: int,
+        target_month: int,
+        after_catalog_id: str | None,
         limit: int,
+        shard: str | None,
     ) -> BundleOperationSummary:
         start_time = time.time()
         summary = BundleOperationSummary(operation=operation)
         if tenant_ids is not None and not tenant_ids:
             return summary
 
-        storage = self._get_archive_storage()
-        bundle_refs = self._list_bundle_refs(
-            storage,
-            operation=operation,
+        storage = self.storage or self._get_archive_storage()
+        catalog_entries = self._list_catalog_entries(
             tenant_ids=tenant_ids,
-            start_date=start_date,
-            end_date=end_date,
+            target_year=target_year,
+            target_month=target_month,
+            after_catalog_id=after_catalog_id,
             limit=limit,
+            shard=shard,
         )
 
-        logger.info("Found %s V2 archive bundles for %s", len(bundle_refs), operation)
-        session_maker = sessionmaker(bind=db.engine, expire_on_commit=False)
-        for bundle_ref in bundle_refs:
-            with session_maker() as session:
-                if operation == "delete":
-                    result = self._delete_bundle(session, storage, bundle_ref)
-                elif operation == "restore":
-                    result = self._restore_bundle(session, storage, bundle_ref)
-                else:
-                    raise ValueError(f"Unsupported operation: {operation}")
+        logger.info(
+            "Found %s V2 archive catalog candidates for %s: year=%s month=%s shard=%s after_catalog_id=%s",
+            len(catalog_entries),
+            operation,
+            target_year,
+            target_month,
+            shard,
+            after_catalog_id,
+        )
+        for catalog_entry in catalog_entries:
+            try:
+                bundle_ref = self._build_bundle_reference(storage, catalog_entry)
+                with self.session_factory() as session:
+                    if operation == "delete":
+                        result = self._delete_bundle(session, storage, bundle_ref)
+                    elif operation == "restore":
+                        result = self._restore_bundle(session, storage, bundle_ref)
+                    else:
+                        raise ValueError(f"Unsupported operation: {operation}")
+            except Exception as exc:
+                result = self._new_result_from_catalog_entry(catalog_entry)
+                result.error = str(exc)
+                logger.exception(
+                    "Failed to prepare V2 archive bundle %s from catalog %s",
+                    catalog_entry.bundle_id,
+                    catalog_entry.catalog_id,
+                )
 
             self._merge_result(summary, result)
-            if not result.success and self.stop_on_error:
+            if result.success:
+                if self.dry_run:
+                    summary.preview_next_catalog_id = catalog_entry.catalog_id
+                else:
+                    summary.next_catalog_id = catalog_entry.catalog_id
+            else:
                 logger.error("Stopping V2 bundle %s after failure: %s", operation, result.error)
                 break
 
         summary.elapsed_time = time.time() - start_time
         return summary
 
-    def _list_bundle_refs(
+    def _list_catalog_entries(
         self,
-        storage: ArchiveStorage,
         *,
-        operation: str,
         tenant_ids: Sequence[str] | None,
-        start_date: datetime.datetime,
-        end_date: datetime.datetime,
+        target_year: int,
+        target_month: int,
+        after_catalog_id: str | None,
         limit: int,
-    ) -> list[BundleReference]:
-        start_date = self._to_naive_utc(start_date)
-        end_date = self._to_naive_utc(end_date)
-        manifest_keys = self._list_manifest_keys(storage, tenant_ids)
-        refs: list[BundleReference] = []
-        for manifest_key in manifest_keys:
-            manifest_data = self._get_checked_object(storage, manifest_key)
-            object_prefix = manifest_key.removesuffix(f"/{ARCHIVE_BUNDLE_MANIFEST_NAME}")
-            manifest = self._load_and_validate_manifest(manifest_data, object_prefix=object_prefix)
-            min_created_at = self._parse_manifest_datetime(manifest["min_created_at"])
-            max_created_at = self._parse_manifest_datetime(manifest["max_created_at"])
-            if max_created_at < start_date or min_created_at >= end_date:
-                continue
-            if tenant_ids and manifest["tenant_id"] not in tenant_ids:
-                continue
-            if operation == "delete" and self._is_deleted(storage, object_prefix):
-                continue
-            if operation == "restore" and not self._is_deleted(storage, object_prefix):
-                continue
-            refs.append(BundleReference(object_prefix=object_prefix, manifest_key=manifest_key, manifest=manifest))
+        shard: str | None = None,
+    ) -> list[ArchiveBundleCatalogEntry]:
+        """Read one bounded, stable-order candidate page from the database catalog."""
+        conditions = [
+            WorkflowRunArchiveBundle.year == target_year,
+            WorkflowRunArchiveBundle.month == target_month,
+        ]
+        if tenant_ids:
+            conditions.append(WorkflowRunArchiveBundle.tenant_id.in_(tenant_ids))
+        if shard is not None:
+            conditions.append(WorkflowRunArchiveBundle.shard == shard)
+        if after_catalog_id:
+            conditions.append(WorkflowRunArchiveBundle.id > after_catalog_id)
 
-        refs.sort(
-            key=lambda ref: (
-                self._parse_manifest_datetime(ref.manifest["min_created_at"]),
-                ref.manifest["tenant_id"],
-                ref.manifest["bundle_id"],
-            )
+        statement = (
+            select(WorkflowRunArchiveBundle).where(*conditions).order_by(WorkflowRunArchiveBundle.id.asc()).limit(limit)
         )
-        return refs[:limit]
+        with self.session_factory() as session:
+            if after_catalog_id:
+                cursor_bundle = session.get(WorkflowRunArchiveBundle, after_catalog_id)
+                self._validate_catalog_cursor_scope(
+                    cursor_bundle,
+                    tenant_ids=tenant_ids,
+                    target_year=target_year,
+                    target_month=target_month,
+                    shard=shard,
+                )
+            bundles = list(session.scalars(statement))
+        return [
+            ArchiveBundleCatalogEntry(
+                catalog_id=bundle.id,
+                tenant_id=bundle.tenant_id,
+                year=bundle.year,
+                month=bundle.month,
+                shard=bundle.shard,
+                bundle_id=bundle.bundle_id,
+                workflow_run_count=bundle.workflow_run_count,
+                row_count=bundle.row_count,
+                archive_bytes=bundle.archive_bytes,
+            )
+            for bundle in bundles
+        ]
 
     @staticmethod
-    def _list_manifest_keys(storage: ArchiveStorage, tenant_ids: Sequence[str] | None) -> list[str]:
-        keys: list[str] = []
-        if tenant_ids:
-            prefixes = [
-                f"{_ARCHIVE_ROOT_PREFIX}tenant_prefix={tenant_id[0].lower()}/tenant_id={tenant_id}/"
-                for tenant_id in tenant_ids
-            ]
-        else:
-            prefixes = [_ARCHIVE_ROOT_PREFIX]
-        for prefix in prefixes:
-            keys.extend(storage.list_objects(prefix))
-        return sorted(key for key in keys if key.endswith(f"/{ARCHIVE_BUNDLE_MANIFEST_NAME}"))
+    def _validate_catalog_cursor_scope(
+        cursor_bundle: WorkflowRunArchiveBundle | None,
+        *,
+        tenant_ids: Sequence[str] | None,
+        target_year: int,
+        target_month: int,
+        shard: str | None,
+    ) -> None:
+        """Reject a keyset cursor that cannot safely represent the requested catalog scope."""
+        if cursor_bundle is None:
+            raise ValueError("after_catalog_id does not exist in the workflow run archive bundle catalog")
+        if cursor_bundle.year != target_year or cursor_bundle.month != target_month:
+            raise ValueError("after_catalog_id is outside the requested archive month")
+        if tenant_ids is not None and cursor_bundle.tenant_id not in tenant_ids:
+            raise ValueError("after_catalog_id is outside the requested tenant scope")
+        if shard is not None and cursor_bundle.shard != shard:
+            raise ValueError("after_catalog_id is outside the requested archive shard")
+
+    def _build_bundle_reference(
+        self,
+        storage: ArchiveStorage,
+        catalog_entry: ArchiveBundleCatalogEntry,
+    ) -> BundleReference:
+        """Load and bind one manifest to the catalog row that selected it."""
+        object_prefix = self._catalog_object_prefix(catalog_entry)
+        manifest_key = f"{object_prefix}/{ARCHIVE_BUNDLE_MANIFEST_NAME}"
+        manifest_data = storage.get_object(manifest_key)
+        manifest = self._load_and_validate_manifest(manifest_data, object_prefix=object_prefix)
+        self._validate_manifest_catalog_identity(manifest, catalog_entry)
+        return BundleReference(
+            catalog=catalog_entry,
+            object_prefix=object_prefix,
+            manifest_key=manifest_key,
+            manifest_size_bytes=len(manifest_data),
+            manifest=manifest,
+        )
+
+    @staticmethod
+    def _catalog_object_prefix(catalog_entry: ArchiveBundleCatalogEntry) -> str:
+        """Construct the immutable V2 bundle prefix from its database catalog identity."""
+        if not catalog_entry.tenant_id:
+            raise ValueError("archive catalog tenant_id must not be empty")
+        if not 1 <= catalog_entry.month <= 12:
+            raise ValueError(f"archive catalog month is invalid: {catalog_entry.month}")
+        return (
+            f"workflow-runs/v2/tenant_prefix={catalog_entry.tenant_id[0].lower()}/"
+            f"tenant_id={catalog_entry.tenant_id}/year={catalog_entry.year:04d}/"
+            f"month={catalog_entry.month:02d}/shard={catalog_entry.shard}/bundle={catalog_entry.bundle_id}"
+        )
+
+    @staticmethod
+    def _validate_manifest_catalog_identity(
+        manifest: BundleManifest,
+        catalog_entry: ArchiveBundleCatalogEntry,
+    ) -> None:
+        """Fail closed when the catalog locator and manifest identify different immutable bundles."""
+        expected_identity = (
+            catalog_entry.tenant_id,
+            catalog_entry.year,
+            catalog_entry.month,
+            catalog_entry.shard,
+            catalog_entry.bundle_id,
+        )
+        manifest_identity = (
+            manifest["tenant_id"],
+            manifest["year"],
+            manifest["month"],
+            manifest["shard"],
+            manifest["bundle_id"],
+        )
+        if manifest_identity != expected_identity:
+            raise ValueError(
+                f"archive manifest identity does not match catalog: expected={expected_identity}, "
+                f"actual={manifest_identity}"
+            )
+        if manifest["workflow_run_count"] != catalog_entry.workflow_run_count:
+            raise ValueError("archive manifest workflow_run_count does not match catalog")
+        manifest_row_count = sum(table["row_count"] for table in manifest["tables"].values())
+        if manifest_row_count != catalog_entry.row_count:
+            raise ValueError("archive manifest row_count does not match catalog")
 
     def _delete_bundle(
         self,
@@ -344,37 +538,61 @@ class WorkflowRunBundleArchiveMaintenance:
         bundle_ref: BundleReference,
     ) -> BundleOperationResult:
         start_time = time.time()
-        result = self._new_result(bundle_ref.manifest)
+        result = self._new_result(bundle_ref.manifest, bundle_ref.catalog.catalog_id)
         try:
             validation_start = time.time()
+            if not self.dry_run:
+                self._lock_catalog_entry(session, bundle_ref.catalog)
+            if self._is_restore_started(storage, bundle_ref.object_prefix):
+                raise ValueError("restore started marker exists; reconcile restore before delete")
+
+            deleted_marker_exists = self._is_deleted(storage, bundle_ref.object_prefix)
             manifest, table_records, archive_bytes = self._validate_archive_object(storage, bundle_ref)
             result.table_counts = self._manifest_table_counts(manifest)
             result.archive_bytes = archive_bytes
 
-            self._lock_workflow_runs(session, manifest["run_ids"])
-            if self._is_delete_started(storage, bundle_ref.object_prefix) and self._live_counts_match(
-                session, manifest, expected_present=False
-            ):
+            live_records = self._load_live_bundle_records(
+                session,
+                manifest,
+                table_records,
+                lock=not self.dry_run,
+            )
+            if deleted_marker_exists:
+                live_counts = {table_name: len(live_records[table_name]) for table_name in ARCHIVED_TABLES}
+                if any(live_counts.values()):
+                    raise ValueError(f"Live rows exist for bundle with deleted marker: {live_counts}")
+                if not self.dry_run:
+                    self._delete_marker(storage, bundle_ref.object_prefix, ARCHIVE_BUNDLE_DELETE_STARTED_MARKER_NAME)
+                    self._delete_marker(storage, bundle_ref.object_prefix, ARCHIVE_BUNDLE_RESTORED_MARKER_NAME)
                 result.validation_time = time.time() - validation_start
+                result.success = True
+                result.elapsed_time = time.time() - start_time
+                return result
+
+            self._validate_live_archive_subset(manifest, table_records, live_records)
+            result.validation_time = time.time() - validation_start
+
+            if not any(live_records[table_name] for table_name in ARCHIVED_TABLES):
                 if not self.dry_run:
                     self._mark_deleted(storage, bundle_ref.object_prefix)
                     self._delete_marker(storage, bundle_ref.object_prefix, ARCHIVE_BUNDLE_DELETE_STARTED_MARKER_NAME)
+                    self._delete_marker(storage, bundle_ref.object_prefix, ARCHIVE_BUNDLE_RESTORED_MARKER_NAME)
                 result.success = True
+                result.elapsed_time = time.time() - start_time
                 return result
 
-            self._validate_live_counts(session, manifest, expected_present=True)
-            if self.strict_content_validation:
-                self._validate_live_content(session, table_records)
-            result.validation_time = time.time() - validation_start
-
             if not self.dry_run:
                 self._put_marker(storage, bundle_ref.object_prefix, ARCHIVE_BUNDLE_DELETE_STARTED_MARKER_NAME)
-                deleted_counts = self._delete_bundle_rows(session, table_records)
-                if deleted_counts != result.table_counts:
+                expected_deleted_counts = {table_name: len(live_records[table_name]) for table_name in ARCHIVED_TABLES}
+                deleted_counts = self._delete_bundle_rows(session, live_records)
+                if deleted_counts != expected_deleted_counts:
                     raise ValueError(
-                        f"Deleted row count mismatch: expected={result.table_counts}, actual={deleted_counts}"
+                        f"Deleted row count mismatch: expected={expected_deleted_counts}, actual={deleted_counts}"
                     )
-                self._validate_live_counts(session, manifest, expected_present=False)
+                remaining_records = self._load_live_bundle_records(session, manifest, table_records, lock=True)
+                remaining_counts = {table_name: len(remaining_records[table_name]) for table_name in ARCHIVED_TABLES}
+                if any(remaining_counts.values()):
+                    raise ValueError(f"Live rows remain after bundle delete: {remaining_counts}")
                 session.commit()
                 self._mark_deleted(storage, bundle_ref.object_prefix)
                 self._delete_marker(storage, bundle_ref.object_prefix, ARCHIVE_BUNDLE_DELETE_STARTED_MARKER_NAME)
@@ -394,9 +612,25 @@ class WorkflowRunBundleArchiveMaintenance:
         bundle_ref: BundleReference,
     ) -> BundleOperationResult:
         start_time = time.time()
-        result = self._new_result(bundle_ref.manifest)
+        result = self._new_result(bundle_ref.manifest, bundle_ref.catalog.catalog_id)
         try:
             validation_start = time.time()
+            if not self.dry_run:
+                self._lock_catalog_entry(session, bundle_ref.catalog)
+            if not self._is_deleted(storage, bundle_ref.object_prefix):
+                # A committed delete may be interrupted before `.deleted` is written. Do not let restore advance its
+                # cursor over that state: retry delete to reconcile it, or investigate source-row drift first.
+                if self._is_delete_started(storage, bundle_ref.object_prefix):
+                    raise ValueError("delete started marker exists without a deleted marker; reconcile delete first")
+                restore_started = self._is_restore_started(storage, bundle_ref.object_prefix)
+                self._validate_live_counts(session, bundle_ref.manifest, expected_present=True)
+                result.validation_time = time.time() - validation_start
+                if restore_started and not self.dry_run:
+                    self._mark_restored(storage, bundle_ref.object_prefix)
+                result.success = True
+                result.elapsed_time = time.time() - start_time
+                return result
+
             manifest, table_records, archive_bytes = self._validate_archive_object(storage, bundle_ref)
             result.table_counts = self._manifest_table_counts(manifest)
             result.archive_bytes = archive_bytes
@@ -408,6 +642,7 @@ class WorkflowRunBundleArchiveMaintenance:
                 if not self.dry_run:
                     self._mark_restored(storage, bundle_ref.object_prefix)
                 result.success = True
+                result.elapsed_time = time.time() - start_time
                 return result
 
             self._validate_live_counts(session, manifest, expected_present=False)
@@ -432,13 +667,40 @@ class WorkflowRunBundleArchiveMaintenance:
         return result
 
     @staticmethod
-    def _new_result(manifest: BundleManifest) -> BundleOperationResult:
+    def _new_result(manifest: BundleManifest, catalog_id: str) -> BundleOperationResult:
         return BundleOperationResult(
+            catalog_id=catalog_id,
             bundle_id=manifest["bundle_id"],
             tenant_id=manifest["tenant_id"],
             object_prefix=manifest["object_prefix"],
         )
 
+    @staticmethod
+    def _new_result_from_catalog_entry(catalog_entry: ArchiveBundleCatalogEntry) -> BundleOperationResult:
+        try:
+            object_prefix = WorkflowRunBundleArchiveMaintenance._catalog_object_prefix(catalog_entry)
+        except ValueError:
+            object_prefix = "<invalid archive catalog identity>"
+        return BundleOperationResult(
+            catalog_id=catalog_entry.catalog_id,
+            bundle_id=catalog_entry.bundle_id,
+            tenant_id=catalog_entry.tenant_id,
+            object_prefix=object_prefix,
+        )
+
+    @staticmethod
+    def _lock_catalog_entry(session: Session, catalog_entry: ArchiveBundleCatalogEntry) -> None:
+        locked_catalog_id = session.scalar(
+            select(WorkflowRunArchiveBundle.id)
+            .where(
+                WorkflowRunArchiveBundle.id == catalog_entry.catalog_id,
+                WorkflowRunArchiveBundle.tenant_id == catalog_entry.tenant_id,
+            )
+            .with_for_update()
+        )
+        if locked_catalog_id is None:
+            raise ValueError("archive catalog row disappeared before bundle maintenance")
+
     def _validate_archive_object(
         self,
         storage: ArchiveStorage,
@@ -446,7 +708,7 @@ class WorkflowRunBundleArchiveMaintenance:
     ) -> tuple[BundleManifest, dict[str, list[dict[str, Any]]], int]:
         manifest = bundle_ref.manifest
         table_records: dict[str, list[dict[str, Any]]] = {}
-        total_size = len(storage.get_object(bundle_ref.manifest_key))
+        total_size = bundle_ref.manifest_size_bytes
         for table_name in ARCHIVED_TABLES:
             info = manifest["tables"][table_name]
             payload = self._get_checked_object(storage, info["object_key"])
@@ -469,12 +731,14 @@ class WorkflowRunBundleArchiveMaintenance:
                     f"expected={info['row_count']}, actual={len(records)}"
                 )
             table_records[table_name] = records
+        if total_size != bundle_ref.catalog.archive_bytes:
+            raise ValueError(
+                f"Archive object total size mismatch: expected={bundle_ref.catalog.archive_bytes}, actual={total_size}"
+            )
         return manifest, table_records, total_size
 
     @staticmethod
     def _get_checked_object(storage: ArchiveStorage, object_key: str) -> bytes:
-        if not storage.object_exists(object_key):
-            raise FileNotFoundError(f"Archive object not found: {object_key}")
         return storage.get_object(object_key)
 
     @staticmethod
@@ -539,6 +803,110 @@ class WorkflowRunBundleArchiveMaintenance:
         table = pq.read_table(io.BytesIO(payload))
         return table.to_pylist()
 
+    def _load_live_bundle_records(
+        self,
+        session: Session,
+        manifest: BundleManifest,
+        table_records: dict[str, list[dict[str, Any]]],
+        *,
+        lock: bool,
+    ) -> dict[str, list[dict[str, Any]]]:
+        """Load the complete live scope for a bundle, including archived rows whose relationship fields drifted."""
+        run_ids = manifest["run_ids"]
+        archive_ids = {
+            table_name: [str(record["id"]) for record in table_records[table_name]] for table_name in ARCHIVED_TABLES
+        }
+        live_node_ids = self._select_ids_by_run_ids(session, WorkflowNodeExecutionModel, run_ids)
+        live_pause_ids = self._select_ids_by_run_ids(session, WorkflowPause, run_ids)
+        node_ids = sorted(set(archive_ids["workflow_node_executions"]) | set(live_node_ids))
+        pause_ids = sorted(set(archive_ids["workflow_pauses"]) | set(live_pause_ids))
+
+        def load_scope(
+            table_name: str,
+            model: Any,
+            scope_column: Any,
+            scope_ids: Sequence[str],
+        ) -> list[dict[str, Any]]:
+            return self._merge_records_by_id(
+                self._load_records_by_column(session, model, scope_column, scope_ids, lock=lock),
+                self._load_records_by_column(session, model, model.id, archive_ids[table_name], lock=lock),
+            )
+
+        return {
+            "workflow_pause_reasons": load_scope(
+                "workflow_pause_reasons", WorkflowPauseReason, WorkflowPauseReason.pause_id, pause_ids
+            ),
+            "workflow_node_execution_offload": load_scope(
+                "workflow_node_execution_offload",
+                WorkflowNodeExecutionOffload,
+                WorkflowNodeExecutionOffload.node_execution_id,
+                node_ids,
+            ),
+            "workflow_trigger_logs": load_scope(
+                "workflow_trigger_logs", WorkflowTriggerLog, WorkflowTriggerLog.workflow_run_id, run_ids
+            ),
+            "workflow_app_logs": load_scope(
+                "workflow_app_logs", WorkflowAppLog, WorkflowAppLog.workflow_run_id, run_ids
+            ),
+            "workflow_node_executions": load_scope(
+                "workflow_node_executions",
+                WorkflowNodeExecutionModel,
+                WorkflowNodeExecutionModel.workflow_run_id,
+                run_ids,
+            ),
+            "workflow_pauses": load_scope("workflow_pauses", WorkflowPause, WorkflowPause.workflow_run_id, run_ids),
+            "workflow_runs": self._load_records_by_column(
+                session,
+                WorkflowRun,
+                WorkflowRun.id,
+                sorted(set(run_ids) | set(archive_ids["workflow_runs"])),
+                lock=lock,
+            ),
+        }
+
+    @classmethod
+    def _validate_live_archive_subset(
+        cls,
+        manifest: BundleManifest,
+        table_records: dict[str, list[dict[str, Any]]],
+        live_records: dict[str, list[dict[str, Any]]],
+    ) -> None:
+        """Require every live row in the bundle scope to exist unchanged in the validated archive."""
+        manifest_run_ids = {str(run_id) for run_id in manifest["run_ids"]}
+        if len(manifest_run_ids) != len(manifest["run_ids"]):
+            raise ValueError("archive manifest contains duplicate workflow run IDs")
+
+        archive_records_by_id: dict[str, dict[str, dict[str, Any]]] = {}
+        for table_name in ARCHIVED_TABLES:
+            records_by_id = {str(record["id"]): record for record in table_records[table_name]}
+            if len(records_by_id) != len(table_records[table_name]):
+                raise ValueError(f"archive contains duplicate row IDs for {table_name}")
+            archive_records_by_id[table_name] = records_by_id
+
+        if set(archive_records_by_id["workflow_runs"]) != manifest_run_ids:
+            raise ValueError("archive workflow run IDs do not match manifest run_ids")
+
+        for table_name in ARCHIVED_TABLES:
+            live_ids = [str(record["id"]) for record in live_records[table_name]]
+            if len(set(live_ids)) != len(live_ids):
+                raise ValueError(f"live scope contains duplicate row IDs for {table_name}")
+
+            archive_by_id = archive_records_by_id[table_name]
+            extra_ids = sorted(set(live_ids) - set(archive_by_id))
+            if extra_ids:
+                raise ValueError(
+                    f"Live bundle scope contains rows missing from archive for {table_name}: {extra_ids[:10]}"
+                )
+
+            archive_subset = [archive_by_id[row_id] for row_id in live_ids]
+            live_checksum = cls._records_checksum(live_records[table_name])
+            archive_checksum = cls._records_checksum(archive_subset)
+            if live_checksum != archive_checksum:
+                raise ValueError(
+                    f"Live/archive subset content checksum mismatch for {table_name}: "
+                    f"expected={archive_checksum}, actual={live_checksum}"
+                )
+
     def _validate_live_counts(
         self,
         session: Session,
@@ -617,26 +985,13 @@ class WorkflowRunBundleArchiveMaintenance:
     def _delete_bundle_rows(
         self,
         session: Session,
-        table_records: dict[str, list[dict[str, Any]]],
+        live_records: dict[str, list[dict[str, Any]]],
     ) -> dict[str, int]:
-        run_ids = [str(record["id"]) for record in table_records["workflow_runs"]]
-        node_ids = [str(record["id"]) for record in table_records["workflow_node_executions"]]
-        pause_ids = [str(record["id"]) for record in table_records["workflow_pauses"]]
-
         deleted_counts = dict.fromkeys(ARCHIVED_TABLES, 0)
-        deleted_counts["workflow_pause_reasons"] = self._delete_by_column(
-            session, WorkflowPauseReason, WorkflowPauseReason.pause_id, pause_ids
-        )
-        deleted_counts["workflow_node_execution_offload"] = self._delete_by_column(
-            session, WorkflowNodeExecutionOffload, WorkflowNodeExecutionOffload.node_execution_id, node_ids
-        )
-        deleted_counts["workflow_trigger_logs"] = self._delete_by_run_ids(session, WorkflowTriggerLog, run_ids)
-        deleted_counts["workflow_app_logs"] = self._delete_by_run_ids(session, WorkflowAppLog, run_ids)
-        deleted_counts["workflow_node_executions"] = self._delete_by_run_ids(
-            session, WorkflowNodeExecutionModel, run_ids
-        )
-        deleted_counts["workflow_pauses"] = self._delete_by_run_ids(session, WorkflowPause, run_ids)
-        deleted_counts["workflow_runs"] = self._delete_by_run_ids(session, WorkflowRun, run_ids)
+        for table_name in DELETE_ORDER:
+            model = TABLE_MODELS[table_name]
+            row_ids = [str(record["id"]) for record in live_records[table_name]]
+            deleted_counts[table_name] = self._delete_by_column(session, model, model.id, row_ids)
         return deleted_counts
 
     def _restore_bundle_rows(
@@ -708,11 +1063,6 @@ class WorkflowRunBundleArchiveMaintenance:
         payload = json.dumps(normalized, sort_keys=True, default=str, ensure_ascii=False, separators=(",", ":"))
         return ArchiveStorage.compute_checksum(payload.encode("utf-8"))
 
-    @staticmethod
-    def _lock_workflow_runs(session: Session, run_ids: Sequence[str]) -> None:
-        for chunk in WorkflowRunBundleArchiveMaintenance._chunks(run_ids, _CHUNK_SIZE):
-            list(session.scalars(select(WorkflowRun.id).where(WorkflowRun.id.in_(chunk)).with_for_update()))
-
     @staticmethod
     def _select_ids_by_run_ids(
         session: Session,
@@ -757,8 +1107,16 @@ class WorkflowRunBundleArchiveMaintenance:
         session: Session,
         model: Any,
         run_ids: Sequence[str],
+        *,
+        lock: bool = False,
     ) -> list[dict[str, Any]]:
-        return self._load_records_by_column(session, model, self._run_id_column(model), run_ids)
+        return self._load_records_by_column(
+            session,
+            model,
+            self._run_id_column(model),
+            run_ids,
+            lock=lock,
+        )
 
     def _load_records_by_column(
         self,
@@ -766,23 +1124,23 @@ class WorkflowRunBundleArchiveMaintenance:
         model: Any,
         column: Any,
         values: Sequence[str],
+        *,
+        lock: bool = False,
     ) -> list[dict[str, Any]]:
         if not values:
             return []
         rows: list[Any] = []
         for chunk in self._chunks(values, _CHUNK_SIZE):
-            rows.extend(session.scalars(select(model).where(column.in_(chunk))))
+            statement = select(model).where(column.in_(chunk)).order_by(model.id.asc())
+            if lock:
+                statement = statement.with_for_update()
+            rows.extend(session.scalars(statement))
         return [self._row_to_dict(row) for row in rows]
 
     @staticmethod
-    def _delete_by_run_ids(
-        session: Session,
-        model: Any,
-        run_ids: Sequence[str],
-    ) -> int:
-        return WorkflowRunBundleArchiveMaintenance._delete_by_column(
-            session, model, WorkflowRunBundleArchiveMaintenance._run_id_column(model), run_ids
-        )
+    def _merge_records_by_id(*record_groups: list[dict[str, Any]]) -> list[dict[str, Any]]:
+        records_by_id = {str(record["id"]): record for record_group in record_groups for record in record_group}
+        return [records_by_id[row_id] for row_id in sorted(records_by_id)]
 
     @staticmethod
     def _run_id_column(model: Any) -> Any:
@@ -813,6 +1171,10 @@ class WorkflowRunBundleArchiveMaintenance:
     def _is_delete_started(storage: ArchiveStorage, object_prefix: str) -> bool:
         return storage.object_exists(f"{object_prefix}/{ARCHIVE_BUNDLE_DELETE_STARTED_MARKER_NAME}")
 
+    @staticmethod
+    def _is_restore_started(storage: ArchiveStorage, object_prefix: str) -> bool:
+        return storage.object_exists(f"{object_prefix}/{ARCHIVE_BUNDLE_RESTORE_STARTED_MARKER_NAME}")
+
     @staticmethod
     def _mark_deleted(storage: ArchiveStorage, object_prefix: str) -> None:
         WorkflowRunBundleArchiveMaintenance._put_marker(storage, object_prefix, ARCHIVE_BUNDLE_DELETED_MARKER_NAME)
@@ -820,10 +1182,13 @@ class WorkflowRunBundleArchiveMaintenance:
     @staticmethod
     def _mark_restored(storage: ArchiveStorage, object_prefix: str) -> None:
         WorkflowRunBundleArchiveMaintenance._delete_marker(storage, object_prefix, ARCHIVE_BUNDLE_DELETED_MARKER_NAME)
+        WorkflowRunBundleArchiveMaintenance._put_marker(storage, object_prefix, ARCHIVE_BUNDLE_RESTORED_MARKER_NAME)
+        WorkflowRunBundleArchiveMaintenance._delete_marker(
+            storage, object_prefix, ARCHIVE_BUNDLE_DELETE_STARTED_MARKER_NAME
+        )
         WorkflowRunBundleArchiveMaintenance._delete_marker(
             storage, object_prefix, ARCHIVE_BUNDLE_RESTORE_STARTED_MARKER_NAME
         )
-        WorkflowRunBundleArchiveMaintenance._put_marker(storage, object_prefix, ARCHIVE_BUNDLE_RESTORED_MARKER_NAME)
 
     @staticmethod
     def _put_marker(storage: ArchiveStorage, object_prefix: str, marker_name: str) -> None:
@@ -836,16 +1201,6 @@ class WorkflowRunBundleArchiveMaintenance:
         if storage.object_exists(marker_key):
             storage.delete_object(marker_key)
 
-    @staticmethod
-    def _parse_manifest_datetime(value: str) -> datetime.datetime:
-        return WorkflowRunBundleArchiveMaintenance._to_naive_utc(datetime.datetime.fromisoformat(value))
-
-    @staticmethod
-    def _to_naive_utc(value: datetime.datetime) -> datetime.datetime:
-        if value.tzinfo is None:
-            return value
-        return value.astimezone(datetime.UTC).replace(tzinfo=None)
-
     @staticmethod
     def _chunks(values: Sequence[Any], size: int) -> list[Sequence[Any]]:
         return [values[index : index + size] for index in range(0, len(values), size)]

api/services/step_by_step_tour_service.py

@@ -0,0 +1,221 @@
+"""Account-level Step-by-step Tour persistence."""
+
+from datetime import datetime
+from typing import NotRequired, TypedDict
+
+from sqlalchemy import select
+from sqlalchemy.exc import IntegrityError
+from sqlalchemy.orm import Session, scoped_session
+
+from configs import dify_config
+from libs.datetime_utils import ensure_naive_utc
+from models.account import Account
+from models.onboarding import AccountStepByStepTourState
+
+STEP_BY_STEP_TOUR_TASK_IDS = frozenset(("home", "studio", "knowledge", "integration"))
+
+
+class StepByStepTourStateResponse(TypedDict):
+    first_workspace_id: str | None
+    skipped: bool
+    completed_task_ids: list[str]
+    manually_enabled_workspace_ids: list[str]
+    manually_disabled_workspace_ids: list[str]
+    updated_at: datetime | None
+
+
+class StepByStepTourPatch(TypedDict):
+    action: str
+    task_id: NotRequired[str | None]
+
+
+class StepByStepTourService:
+    """Coordinate persisted tour state with account eligibility rules."""
+
+    @classmethod
+    def get_state(
+        cls,
+        *,
+        account: Account,
+        current_tenant_id: str,
+        session: Session | scoped_session,
+    ) -> StepByStepTourStateResponse:
+        eligible = cls.is_eligible(account)
+        state = cls._get_state(account.id, session=session)
+
+        if eligible:
+            state = cls._ensure_state(account.id, session=session, state=state)
+            if state.first_workspace_id is None:
+                state.first_workspace_id = current_tenant_id
+                session.commit()
+                session.refresh(state)
+
+        return cls._build_response(state=state)
+
+    @classmethod
+    def patch_state(
+        cls,
+        *,
+        account: Account,
+        current_tenant_id: str,
+        patch: StepByStepTourPatch,
+        session: Session | scoped_session,
+    ) -> StepByStepTourStateResponse:
+        state = cls._ensure_state(account.id, session=session, state=None)
+        cls._apply_action(
+            state=state,
+            action=patch["action"],
+            task_id=patch.get("task_id"),
+            current_tenant_id=current_tenant_id,
+        )
+
+        session.commit()
+        session.refresh(state)
+        return cls._build_response(state=state)
+
+    @classmethod
+    def is_eligible(cls, account: Account) -> bool:
+        if not dify_config.ENABLE_STEP_BY_STEP_TOUR:
+            return False
+
+        rollout_started_at = dify_config.STEP_BY_STEP_TOUR_ROLLOUT_STARTED_AT
+        if rollout_started_at is None:
+            return False
+
+        account_started_at = account.initialized_at or account.created_at
+        if account_started_at is None:
+            return False
+
+        return ensure_naive_utc(account_started_at) >= ensure_naive_utc(rollout_started_at)
+
+    @classmethod
+    def _get_state(
+        cls,
+        account_id: str,
+        *,
+        session: Session | scoped_session,
+    ) -> AccountStepByStepTourState | None:
+        stmt = select(AccountStepByStepTourState).where(AccountStepByStepTourState.account_id == account_id).limit(1)
+        return session.execute(stmt).scalar_one_or_none()
+
+    @classmethod
+    def _ensure_state(
+        cls,
+        account_id: str,
+        *,
+        session: Session | scoped_session,
+        state: AccountStepByStepTourState | None,
+    ) -> AccountStepByStepTourState:
+        if state is None:
+            state = cls._get_state(account_id, session=session)
+        if state is not None:
+            return state
+
+        state = AccountStepByStepTourState(account_id=account_id)
+        session.add(state)
+        try:
+            session.flush()
+        except IntegrityError:
+            # Another tab/device can create the account row between our read and insert.
+            session.rollback()
+            state = cls._get_state(account_id, session=session)
+            if state is None:
+                raise
+        return state
+
+    @classmethod
+    def _apply_action(
+        cls,
+        *,
+        state: AccountStepByStepTourState,
+        action: str,
+        task_id: str | None,
+        current_tenant_id: str,
+    ) -> None:
+        match action:
+            case "skip":
+                state.skipped = True
+                state.manually_enabled_workspace_ids = cls._remove_id(
+                    state.manually_enabled_workspace_ids,
+                    current_tenant_id,
+                )
+            case "complete_task":
+                if task_id is None:
+                    raise ValueError("task_id is required")
+                cls._validate_task_id(task_id)
+                state.completed_task_ids = cls._add_id(state.completed_task_ids, task_id)
+            case "uncomplete_task":
+                if task_id is None:
+                    raise ValueError("task_id is required")
+                cls._validate_task_id(task_id)
+                state.completed_task_ids = cls._remove_id(state.completed_task_ids, task_id)
+            case "enable_current_workspace":
+                state.skipped = False
+                state.manually_enabled_workspace_ids = cls._add_id(
+                    state.manually_enabled_workspace_ids,
+                    current_tenant_id,
+                )
+                state.manually_disabled_workspace_ids = cls._remove_id(
+                    state.manually_disabled_workspace_ids,
+                    current_tenant_id,
+                )
+            case "disable_current_workspace":
+                state.manually_enabled_workspace_ids = cls._remove_id(
+                    state.manually_enabled_workspace_ids,
+                    current_tenant_id,
+                )
+                state.manually_disabled_workspace_ids = cls._add_id(
+                    state.manually_disabled_workspace_ids,
+                    current_tenant_id,
+                )
+            case _:
+                raise ValueError(f"Unsupported action: {action}")
+
+    @classmethod
+    def _build_response(
+        cls,
+        *,
+        state: AccountStepByStepTourState | None,
+    ) -> StepByStepTourStateResponse:
+        if state is None:
+            return {
+                "first_workspace_id": None,
+                "skipped": False,
+                "completed_task_ids": [],
+                "manually_enabled_workspace_ids": [],
+                "manually_disabled_workspace_ids": [],
+                "updated_at": None,
+            }
+
+        return {
+            "first_workspace_id": state.first_workspace_id,
+            "skipped": state.skipped,
+            "completed_task_ids": cls._normalize_ids(state.completed_task_ids),
+            "manually_enabled_workspace_ids": cls._normalize_ids(state.manually_enabled_workspace_ids),
+            "manually_disabled_workspace_ids": cls._normalize_ids(state.manually_disabled_workspace_ids),
+            "updated_at": state.updated_at,
+        }
+
+    @staticmethod
+    def _validate_task_id(task_id: str) -> None:
+        if task_id not in STEP_BY_STEP_TOUR_TASK_IDS:
+            raise ValueError(f"Unsupported task_id: {task_id}")
+
+    @classmethod
+    def _add_id(cls, values: list[str], value: str) -> list[str]:
+        normalized = cls._normalize_ids(values)
+        if value in normalized:
+            return normalized
+        return [*normalized, value]
+
+    @classmethod
+    def _remove_id(cls, values: list[str], value: str) -> list[str]:
+        return [item for item in cls._normalize_ids(values) if item != value]
+
+    @staticmethod
+    def _normalize_ids(values: list[str]) -> list[str]:
+        normalized: list[str] = []
+        for value in values:
+            if value not in normalized:
+                normalized.append(value)
+        return normalized

api/services/workflow_collaboration_service.py

@@ -8,6 +8,7 @@ import uuid
 from collections.abc import Mapping
 from typing import Any, override
 
+from socketio.exceptions import TimeoutError as SocketIOTimeoutError  # type: ignore[reportMissingTypeStubs]
 from sqlalchemy import select
 from sqlalchemy.orm import Session
 
@@ -18,6 +19,7 @@ from repositories.workflow_collaboration_repository import WorkflowCollaboration
 logger = logging.getLogger(__name__)
 
 SERVER_HEARTBEAT_INTERVAL_SECONDS = 30
+SYNC_REQUEST_TIMEOUT_SECONDS = 15
 _PROCESS_SERVER_ID: str | None = None
 _PROCESS_SERVER_ID_PID: int | None = None
 
@@ -38,7 +40,8 @@ class WorkflowCollaborationService:
 
     Socket.IO rooms are process-local unless backed by a message queue, while online users and leader election live in
     Redis. Each websocket worker writes a small heartbeat keyed by `server_id`; session rows store their owner so a
-    worker can distinguish a live remote sid from a stale sid left behind by a dead worker.
+    worker can distinguish a live remote sid from a stale sid left behind by a dead worker. Visibility events are
+    ordered per socket, and sync requests wait for the selected saver to acknowledge its draft write.
     """
 
     _heartbeat_started: bool
@@ -128,6 +131,9 @@ class WorkflowCollaborationService:
             "sid": sid,
             "connected_at": int(time.time()),
             "server_id": self.server_id,
+            # Joins are assumed visible; hidden tabs re-report via a graph_view_state
+            # event right after receiving the post-join "status" emit.
+            "graph_active": True,
         }
 
         self._repository.set_session_info(workflow_id, session_info)
@@ -158,7 +164,8 @@ class WorkflowCollaborationService:
         self.handle_leader_disconnect(workflow_id, sid)
         self.broadcast_online_users(workflow_id)
 
-    def relay_collaboration_event(self, sid: str, data: Mapping[str, object]) -> tuple[dict[str, str], int]:
+    def relay_collaboration_event(self, sid: str, data: Mapping[str, object]) -> tuple[dict[str, object], int]:
+        """Route collaboration control events, directing save and graph-resync requests to the active leader."""
         mapping = self._repository.get_sid_mapping(sid)
         if not mapping:
             return {"msg": "unauthorized"}, 401
@@ -174,11 +181,54 @@ class WorkflowCollaborationService:
         if not event_type:
             return {"msg": "invalid event type"}, 400
 
+        if event_type == "graph_view_state":
+            if not isinstance(event_data, Mapping):
+                return {"msg": "invalid graph_view_state"}, 400
+
+            graph_active = event_data.get("graphActive")
+            sequence = event_data.get("sequence")
+            if not isinstance(graph_active, bool):
+                return {"msg": "invalid graph_view_state"}, 400
+            if not isinstance(sequence, int) or isinstance(sequence, bool) or sequence < 0:
+                return {"msg": "invalid graph_view_state"}, 400
+
+            # Sequence the visibility write together with its leader side effect. Otherwise a newer
+            # visible event can land after the Lua write but before an older hidden handler demotes.
+            with self._repository.graph_view_state_lock(workflow_id):
+                applied = self._repository.update_session_graph_active(workflow_id, sid, graph_active, sequence)
+                if not applied:
+                    return {"msg": "graph_view_state_ignored"}, 200
+
+                # Write the flag before re-electing so tier-1 selection already excludes the
+                # session that just went hidden (including one _ensure_leader just promoted).
+                if not graph_active:
+                    self._demote_leader_if_hidden(workflow_id, sid)
+            return {"msg": "graph_view_state_updated"}, 200
+
         if event_type == "sync_request":
+            if not isinstance(event_data, Mapping):
+                return {"msg": "invalid sync_request"}, 400
+            request_id = event_data.get("requestId")
+            if not isinstance(request_id, str) or not request_id.strip():
+                return {"msg": "invalid sync_request"}, 400
+
             leader_sid = self._repository.get_current_leader(workflow_id)
             target_sid: str | None
             if leader_sid and self.is_session_active(workflow_id, leader_sid):
-                target_sid = leader_sid
+                if self._is_session_graph_active(workflow_id, leader_sid):
+                    target_sid = leader_sid
+                else:
+                    # The leader is connected but its tab is hidden: its canvas is frozen
+                    # (rAF paused), so saving through it would persist stale data. Hand
+                    # leadership to a visible session — or, if every tab is hidden, to the
+                    # requester, whose canvas at least contains its own edits.
+                    replacement = self._select_graph_leader(workflow_id, preferred_sid=sid)
+                    if replacement and replacement != leader_sid:
+                        self._repository.set_leader(workflow_id, replacement)
+                        self.broadcast_leader_change(workflow_id, replacement)
+                        target_sid = replacement
+                    else:
+                        target_sid = leader_sid
             else:
                 if leader_sid:
                     self._repository.delete_leader(workflow_id)
@@ -188,15 +238,73 @@ class WorkflowCollaborationService:
                     self.broadcast_leader_change(workflow_id, target_sid)
 
             if not target_sid:
-                return {"msg": "no_active_leader"}, 200
+                return {"msg": "no_active_leader", "requestId": request_id}, 503
+
+            target_data = dict(event_data)
+            target_data["requestId"] = request_id
+            try:
+                result = self._socketio.call(
+                    "collaboration_update",
+                    {"type": event_type, "userId": user_id, "data": target_data, "timestamp": timestamp},
+                    to=target_sid,
+                    timeout=SYNC_REQUEST_TIMEOUT_SECONDS,
+                )
+            except SocketIOTimeoutError:
+                logger.warning(
+                    "Workflow collaboration sync request timed out: workflow_id=%s requester_sid=%s target_sid=%s",
+                    workflow_id,
+                    sid,
+                    target_sid,
+                )
+                return {"msg": "sync_request_timeout", "requestId": request_id}, 504
+
+            if not isinstance(result, Mapping) or result.get("success") is not True:
+                response: dict[str, object] = {
+                    "msg": "workflow_sync_failed",
+                    "requestId": request_id,
+                    "success": False,
+                }
+                if isinstance(result, Mapping) and isinstance(result.get("error"), str):
+                    response["error"] = result["error"]
+                return response, 502
+
+            workflow_hash = result.get("hash")
+            updated_at = result.get("updatedAt")
+            if not isinstance(workflow_hash, str) or not workflow_hash:
+                return {"msg": "invalid_sync_response", "requestId": request_id}, 502
+            if not isinstance(updated_at, int) or isinstance(updated_at, bool):
+                return {"msg": "invalid_sync_response", "requestId": request_id}, 502
+
+            return {
+                "msg": "workflow_synced",
+                "requestId": request_id,
+                "success": True,
+                "hash": workflow_hash,
+                "updatedAt": updated_at,
+            }, 200
+
+        if event_type == "graph_resync_request":
+            leader_sid = self._repository.get_current_leader(workflow_id)
+            resync_target_sid: str | None
+            if leader_sid and self.is_session_active(workflow_id, leader_sid):
+                resync_target_sid = leader_sid
+            else:
+                if leader_sid:
+                    self._repository.delete_leader(workflow_id)
+                resync_target_sid = self._select_graph_leader(workflow_id, preferred_sid=sid)
+                if resync_target_sid:
+                    self._repository.set_leader(workflow_id, resync_target_sid)
+                    self.broadcast_leader_change(workflow_id, resync_target_sid)
+
+            if not resync_target_sid:
+                return {"msg": "no_active_leader"}, 503
 
             self._socketio.emit(
                 "collaboration_update",
                 {"type": event_type, "userId": user_id, "data": event_data, "timestamp": timestamp},
-                room=target_sid,
+                to=resync_target_sid,
             )
-
-            return {"msg": "sync_request_forwarded"}, 200
+            return {"msg": "graph_resync_request_forwarded"}, 200
 
         self._socketio.emit(
             "collaboration_update",
@@ -329,17 +437,56 @@ class WorkflowCollaborationService:
         self._repository.set_leader(workflow_id, sid)
         self.broadcast_leader_change(workflow_id, sid)
 
-    def _select_graph_leader(self, workflow_id: str, preferred_sid: str | None = None) -> str | None:
-        session_sids = [
-            session["sid"]
+    def _select_graph_leader(
+        self,
+        workflow_id: str,
+        preferred_sid: str | None = None,
+        *,
+        require_graph_active: bool = False,
+    ) -> str | None:
+        """Pick a leader, preferring sessions whose canvas tab is visible.
+
+        Hidden tabs freeze rAF-driven CRDT->canvas application, so a visible session is
+        always the freshest saver. When every tab is hidden the room must still keep a
+        leader (followers drop sync_requests unless they believe they are the leader),
+        so tier 2 falls back to any active session unless require_graph_active is set.
+        """
+        active_sessions = [
+            session
             for session in self._repository.list_sessions(workflow_id)
-            if session.get("graph_active", True) and self.is_session_active(workflow_id, session["sid"])
+            if self.is_session_active(workflow_id, session["sid"])
         ]
-        if not session_sids:
+        visible_sids = [session["sid"] for session in active_sessions if session.get("graph_active", True)]
+
+        candidate_sids = visible_sids
+        if not candidate_sids and not require_graph_active:
+            candidate_sids = [session["sid"] for session in active_sessions]
+
+        if not candidate_sids:
             return None
-        if preferred_sid and preferred_sid in session_sids:
+        if preferred_sid and preferred_sid in candidate_sids:
             return preferred_sid
-        return session_sids[0]
+        return candidate_sids[0]
+
+    def _is_session_graph_active(self, workflow_id: str, sid: str) -> bool:
+        """Default to True on missing/unreadable session data so read failures never churn leadership."""
+        session_info = self._repository.get_session_info(workflow_id, sid)
+        if session_info is None:
+            return True
+        return bool(session_info.get("graph_active", True))
+
+    def _demote_leader_if_hidden(self, workflow_id: str, hidden_sid: str) -> None:
+        current_leader = self._repository.get_current_leader(workflow_id)
+        if current_leader != hidden_sid:
+            return
+
+        new_leader = self._select_graph_leader(workflow_id, require_graph_active=True)
+        # No visible session: keep the hidden leader rather than leaving the room leaderless.
+        if not new_leader or new_leader == hidden_sid:
+            return
+
+        self._repository.set_leader(workflow_id, new_leader)
+        self.broadcast_leader_change(workflow_id, new_leader)
 
     def is_session_active(self, workflow_id: str, sid: str) -> bool:
         if not sid:

api/services/workflow_draft_variable_service.py

@@ -823,6 +823,8 @@ _FILENAME_TRANS_TABLE = _make_filename_trans_table()
 
 
 class DraftVariableSaver:
+    """Persist draft outputs under the tenant that owns the app or pipeline."""
+
     # _DUMMY_OUTPUT_IDENTITY is a placeholder output for workflow nodes.
     # Its sole possible value is `None`.
     #
@@ -842,6 +844,10 @@ class DraftVariableSaver:
     # Database session used for persisting draft variables.
     _session: Session
 
+    # Resource owner tenant. An account's current tenant may be unset or point elsewhere
+    # when draft variables are persisted by an asynchronous workflow execution.
+    _tenant_id: str
+
     # The application ID associated with the draft variables.
     # This should match the `Workflow.app_id` of the workflow to which the current node belongs.
     _app_id: str
@@ -867,6 +873,7 @@ class DraftVariableSaver:
     def __init__(
         self,
         session: Session,
+        tenant_id: str,
         app_id: str,
         node_id: str,
         node_type: NodeType,
@@ -878,6 +885,7 @@ class DraftVariableSaver:
         # WorkflowNodeExecutionModel/WorkflowNodeExecution, not their `node_execution_id`
         # field. These are distinct database fields with different purposes.
         self._session = session
+        self._tenant_id = tenant_id
         self._app_id = app_id
         self._node_id = node_id
         self._node_type = node_type
@@ -885,12 +893,6 @@ class DraftVariableSaver:
         self._user = user
         self._enclosing_node_id = enclosing_node_id
 
-    def _resolve_app_tenant_id(self) -> str:
-        tenant_id = self._session.scalar(select(App.tenant_id).where(App.id == self._app_id))
-        if not tenant_id:
-            raise ValueError(f"Unable to resolve tenant_id for app {self._app_id}")
-        return tenant_id
-
     def _create_dummy_output_variable(self):
         return WorkflowDraftVariable.new_node_variable(
             app_id=self._app_id,
@@ -949,11 +951,10 @@ class DraftVariableSaver:
                 if name == SystemVariableKey.FILES:
                     # Here we know the type of variable must be `array[file]`, we
                     # just rebuild files from the serialized payload.
-                    tenant_id = self._resolve_app_tenant_id()
                     files = [
                         build_file_from_stored_mapping(
                             file_mapping=v,
-                            tenant_id=tenant_id,
+                            tenant_id=self._tenant_id,
                         )
                         for v in value
                     ]
@@ -1096,8 +1097,8 @@ class DraftVariableSaver:
             content=original_content_serialized.encode(),
             mimetype=content_type,
             user=self._user,
+            tenant_id=self._tenant_id,
         )
-        assert self._user.current_tenant_id
         # Create WorkflowDraftVariableFile record
         variable_file = WorkflowDraftVariableFile(
             upload_file_id=upload_file.id,
@@ -1105,7 +1106,7 @@ class DraftVariableSaver:
             length=original_length,
             value_type=value_seg.value_type,
             app_id=self._app_id,
-            tenant_id=self._user.current_tenant_id,
+            tenant_id=self._tenant_id,
             user_id=self._user.id,
         )
         variable_file.id = str(uuidv7())

api/services/workflow_event_snapshot_service.py

@@ -13,6 +13,7 @@ from sqlalchemy import desc, select
 from sqlalchemy.orm import Session, sessionmaker
 
 from core.app.apps.message_generator import MessageGenerator
+from core.app.entities.app_invoke_entities import AdvancedChatAppGenerateEntity
 from core.app.entities.task_entities import (
     HumanInputRequiredResponse,
     MessageReplaceStreamResponse,
@@ -84,9 +85,6 @@ def build_workflow_event_stream(
     topic = MessageGenerator.get_response_topic(app_mode, workflow_run.id)
     workflow_run_repo = DifyAPIRepositoryFactory.create_api_workflow_run_repository(session_maker)
     node_execution_repo = DifyAPIRepositoryFactory.create_api_workflow_node_execution_repository(session_maker)
-    message_context = (
-        _get_message_context(session_maker, workflow_run.id) if app_mode == AppMode.ADVANCED_CHAT else None
-    )
 
     pause_entity: WorkflowPauseEntity | None = None
     if workflow_run.status == WorkflowExecutionStatus.PAUSED:
@@ -97,6 +95,38 @@ def build_workflow_event_stream(
             pause_entity = None
 
     resumption_context = _load_resumption_context(pause_entity)
+    message_context: MessageContext | None = None
+    if app_mode == AppMode.ADVANCED_CHAT:
+        if workflow_run.status == WorkflowExecutionStatus.PAUSED:
+            if resumption_context is None:
+                raise AssertionError(
+                    "WorkflowResumptionContext is required for advanced-chat snapshot replay, "
+                    f"workflow_run_id={workflow_run.id}"
+                )
+            generate_entity = resumption_context.get_generate_entity()
+            if not isinstance(generate_entity, AdvancedChatAppGenerateEntity):
+                raise AssertionError(
+                    "AdvancedChatAppGenerateEntity is required for advanced-chat snapshot replay, "
+                    f"workflow_run_id={workflow_run.id}, generate_entity_type={type(generate_entity).__name__}"
+                )
+            if not generate_entity.conversation_id:
+                raise AssertionError(
+                    f"conversation_id is required for advanced-chat snapshot replay, workflow_run_id={workflow_run.id}"
+                )
+            message_context = _get_message_context_by_conversation(
+                session_maker,
+                conversation_id=generate_entity.conversation_id,
+                workflow_run_id=workflow_run.id,
+            )
+        else:
+            # Compatibility fallback for non-suspended snapshot requests. This app-scoped lookup is not optimal;
+            # a dedicated index or stronger lookup key would be preferable.
+            message_context = _get_message_context_by_app(
+                session_maker,
+                app_id=app_id,
+                workflow_run_id=workflow_run.id,
+            )
+
     node_snapshots = node_execution_repo.get_execution_snapshots_by_workflow_run(
         tenant_id=tenant_id,
         app_id=app_id,
@@ -175,19 +205,68 @@ def build_workflow_event_stream(
     return _generate()
 
 
-def _get_message_context(session_maker: sessionmaker[Session], workflow_run_id: str) -> MessageContext | None:
+def _get_message_context_by_conversation(
+    session_maker: sessionmaker[Session],
+    *,
+    conversation_id: str,
+    workflow_run_id: str,
+) -> MessageContext | None:
+    """Look up a paused or suspended Advanced Chat snapshot message by conversation and workflow run.
+
+    Use this exact lookup after recovering ``conversation_id`` from persisted resumption context. Its predicates match
+    ``message_workflow_run_id_idx``.
+    """
     with session_maker() as session:
-        stmt = select(Message).where(Message.workflow_run_id == workflow_run_id).order_by(desc(Message.created_at))
+        stmt = (
+            select(Message)
+            .where(
+                Message.conversation_id == conversation_id,
+                Message.workflow_run_id == workflow_run_id,
+            )
+            .order_by(desc(Message.created_at))
+            .limit(1)
+        )
         message = session.scalar(stmt)
         if message is None:
             return None
-        created_at = int(message.created_at.timestamp()) if message.created_at else 0
-        return MessageContext(
-            conversation_id=message.conversation_id,
-            message_id=message.id,
-            created_at=created_at,
-            answer=message.answer,
+        return _to_message_context(message)
+
+
+def _get_message_context_by_app(
+    session_maker: sessionmaker[Session],
+    *,
+    app_id: str,
+    workflow_run_id: str,
+) -> MessageContext | None:
+    """Look up a non-suspended or running Advanced Chat reconnect snapshot by app and workflow run.
+
+    This compatibility path applies only when no resumption context is expected. The app-scoped query is not optimal;
+    a dedicated index or stronger lookup key would be preferable.
+    """
+    with session_maker() as session:
+        stmt = (
+            select(Message)
+            .where(
+                Message.app_id == app_id,
+                Message.workflow_run_id == workflow_run_id,
+            )
+            .order_by(desc(Message.created_at))
+            .limit(1)
         )
+        message = session.scalar(stmt)
+        if message is None:
+            return None
+        return _to_message_context(message)
+
+
+def _to_message_context(message: Message) -> MessageContext:
+    created_at = int(message.created_at.timestamp()) if message.created_at else 0
+    return MessageContext(
+        conversation_id=message.conversation_id,
+        message_id=message.id,
+        created_at=created_at,
+        answer=message.answer,
+    )
 
 
 def _load_resumption_context(pause_entity: WorkflowPauseEntity | None) -> WorkflowResumptionContext | None:

api/services/workflow_generator_service.py

@@ -16,13 +16,11 @@ from collections.abc import Iterator
 from typing import Any
 
 from core.app.app_config.entities import ModelConfig
-from core.llm_generator.llm_generator import LLMGenerator
 from core.model_manager import ModelInstance, ModelManager
 from core.workflow.generator import WorkflowGenerator
 from core.workflow.generator.tool_catalogue import build_tool_catalogue, format_tool_catalogue, installed_tool_keys
 from core.workflow.generator.types import (
     WorkflowGenerateResultDict,
-    WorkflowGenerationMode,
     WorkflowGenerationModeRequest,
 )
 from graphon.model_runtime.entities.model_entities import ModelType
@@ -52,11 +50,9 @@ class WorkflowGeneratorService:
         """
         Resolve a model instance for the tenant and run the generator.
 
-        ``mode`` accepts the ``"auto"`` sentinel — when set, the instruction is
-        classified into a concrete ``workflow`` / ``advanced-chat`` mode (one
-        tiny LLM call) before planning so the rest of the pipeline runs against
-        a concrete mode. The resolved mode is echoed back under the result's
-        ``mode`` key.
+        ``mode`` accepts the ``"auto"`` sentinel — the planner itself picks the
+        concrete ``workflow`` / ``advanced-chat`` mode (no extra LLM call) and
+        the resolution is echoed back under the result's ``mode`` key.
 
         ``current_graph`` is the existing draft graph for the cmd+k `/refine`
         flow — when present the generator refines it instead of creating a new
@@ -66,9 +62,6 @@ class WorkflowGeneratorService:
         controller can map them to existing HTTP error envelopes (same
         envelope as ``/rule-generate``).
         """
-        resolved_mode = cls._resolve_mode(
-            tenant_id=tenant_id, mode=mode, instruction=instruction, model_config=model_config
-        )
         model_instance, model_parameters, tool_catalogue_text, installed_tools = cls._resolve_generation_context(
             tenant_id=tenant_id, model_config=model_config
         )
@@ -79,7 +72,7 @@ class WorkflowGeneratorService:
             provider=model_config.provider,
             model_name=model_config.name,
             model_mode=model_config.mode.value,
-            mode=resolved_mode,
+            mode=mode,
             instruction=instruction,
             ideal_output=ideal_output,
             tool_catalogue_text=tool_catalogue_text,
@@ -101,16 +94,13 @@ class WorkflowGeneratorService:
         """
         Streaming sibling of ``generate_workflow_graph``.
 
-        Resolves the same model instance / tool catalogue / concrete mode, then
-        delegates to ``WorkflowGenerator.generate_workflow_graph_stream`` and
-        yields its ``(event_name, payload)`` tuples through to the controller's
-        SSE writer. Provider-init / invoke errors raised while resolving the
-        model instance propagate to the caller (the controller emits them as a
+        Resolves the same model instance / tool catalogue, then delegates to
+        ``WorkflowGenerator.generate_workflow_graph_stream`` and yields its
+        ``(event_name, payload)`` tuples through to the controller's SSE
+        writer. Provider-init / invoke errors raised while resolving the model
+        instance propagate to the caller (the controller emits them as a
         single ``result`` SSE event).
         """
-        resolved_mode = cls._resolve_mode(
-            tenant_id=tenant_id, mode=mode, instruction=instruction, model_config=model_config
-        )
         model_instance, model_parameters, tool_catalogue_text, installed_tools = cls._resolve_generation_context(
             tenant_id=tenant_id, model_config=model_config
         )
@@ -121,7 +111,7 @@ class WorkflowGeneratorService:
             provider=model_config.provider,
             model_name=model_config.name,
             model_mode=model_config.mode.value,
-            mode=resolved_mode,
+            mode=mode,
             instruction=instruction,
             ideal_output=ideal_output,
             tool_catalogue_text=tool_catalogue_text,
@@ -129,28 +119,6 @@ class WorkflowGeneratorService:
             current_graph=current_graph,
         )
 
-    @classmethod
-    def _resolve_mode(
-        cls,
-        *,
-        tenant_id: str,
-        mode: WorkflowGenerationModeRequest,
-        instruction: str,
-        model_config: ModelConfig,
-    ) -> WorkflowGenerationMode:
-        """Resolve the request mode into a concrete generation mode.
-
-        ``"auto"`` triggers a one-word LLM classification using the model the
-        user already picked; everything else passes through unchanged. The
-        classifier never raises (defaults to ``advanced-chat``), so ``auto``
-        never blocks generation.
-        """
-        if mode == "auto":
-            return LLMGenerator.classify_workflow_mode(
-                tenant_id=tenant_id, instruction=instruction, model_config=model_config
-            )
-        return mode
-
     @classmethod
     def _resolve_generation_context(
         cls,

api/services/workflow_service.py

@@ -322,6 +322,7 @@ class WorkflowService:
         session: Session,
         commit: bool = True,
         sync_agent_bindings: bool = True,
+        graph_only: bool = False,
     ) -> Workflow:
         """
         Sync draft workflow.
@@ -338,8 +339,10 @@ class WorkflowService:
         if workflow and workflow.unique_hash != unique_hash:
             raise WorkflowHashNotEqualError()
 
-        # validate features structure
-        self.validate_features_structure(app_model=app_model, features=features)
+        # Collaboration persists features and variables through dedicated endpoints. A graph save
+        # must not overwrite those newer database values with another collaborator's stale cache.
+        if not graph_only or not workflow:
+            self.validate_features_structure(app_model=app_model, features=features)
 
         # validate graph structure
         self.validate_graph_structure(graph=graph)
@@ -361,11 +364,12 @@ class WorkflowService:
         # update draft workflow if found
         else:
             workflow.graph = json.dumps(graph)
-            workflow.features = json.dumps(features)
             workflow.updated_by = account.id
             workflow.updated_at = naive_utc_now()
-            workflow.environment_variables = environment_variables
-            workflow.conversation_variables = conversation_variables
+            if not graph_only:
+                workflow.features = json.dumps(features)
+                workflow.environment_variables = environment_variables
+                workflow.conversation_variables = conversation_variables
 
         from services.agent.workflow_publish_service import WorkflowAgentPublishService
 
@@ -1056,6 +1060,7 @@ class WorkflowService:
         with sessionmaker(bind=db.engine).begin() as session:
             draft_var_saver = DraftVariableSaver(
                 session=session,
+                tenant_id=app_model.tenant_id,
                 app_id=app_model.id,
                 node_id=workflow_node_execution.node_id,
                 node_type=workflow_node_execution.node_type,
@@ -1206,6 +1211,7 @@ class WorkflowService:
         with sessionmaker(bind=db.engine).begin() as session:
             draft_var_saver = DraftVariableSaver(
                 session=session,
+                tenant_id=app_model.tenant_id,
                 app_id=app_model.id,
                 node_id=node_id,
                 node_type=BuiltinNodeTypes.HUMAN_INPUT,

api/tasks/agent_backend_session_cleanup_task.py

@@ -24,6 +24,9 @@ def _create_agent_backend_client():
         base_url=dify_config.AGENT_BACKEND_BASE_URL,
         use_fake=dify_config.AGENT_BACKEND_USE_FAKE,
         fake_scenario=dify_config.AGENT_BACKEND_FAKE_SCENARIO,
+        stream_read_timeout_seconds=dify_config.AGENT_BACKEND_STREAM_READ_TIMEOUT_SECONDS,
+        stream_max_reconnects=dify_config.AGENT_BACKEND_STREAM_MAX_RECONNECTS,
+        stream_run_timeout_seconds=dify_config.AGENT_BACKEND_RUN_TIMEOUT_SECONDS,
     )
 
 

api/tasks/install_default_plugins_task.py

@@ -0,0 +1,99 @@
+"""Install configured marketplace plugins for a newly created tenant."""
+
+import logging
+
+from celery import shared_task
+
+from configs import dify_config
+from core.helper import marketplace
+from core.plugin.entities.plugin_daemon import PluginInstallTaskStatus
+from core.plugin.plugin_service import PluginService
+from services.model_provider_service import ModelProviderService
+
+logger = logging.getLogger(__name__)
+
+
+@shared_task(queue="plugin", bind=True, max_retries=60, default_retry_delay=5)
+def configure_default_models_task(self, tenant_id: str, plugin_install_task_id: str | None) -> None:
+    """Set explicitly configured default models after default plugins finish installing."""
+    if not dify_config.NEW_USER_DEFAULT_MODELS:
+        return
+
+    plugin_install_failed = False
+    if plugin_install_task_id:
+        try:
+            install_task = PluginService.fetch_install_task(tenant_id, plugin_install_task_id)
+        except Exception as exc:
+            logger.warning(
+                "Failed to fetch default plugin installation task for tenant %s; retrying",
+                tenant_id,
+            )
+            raise self.retry(exc=exc)
+
+        if install_task.status in (PluginInstallTaskStatus.Pending, PluginInstallTaskStatus.Running):
+            raise self.retry()
+
+        plugin_install_failed = install_task.status == PluginInstallTaskStatus.Failed
+        if plugin_install_failed:
+            failed_plugin_ids = [
+                plugin.plugin_id for plugin in install_task.plugins if plugin.status == PluginInstallTaskStatus.Failed
+            ]
+            logger.error(
+                "Default plugin installation failed for tenant %s: %s",
+                tenant_id,
+                ", ".join(failed_plugin_ids),
+            )
+
+    model_provider_service = ModelProviderService()
+    failed_model_types: list[str] = []
+    for model_type, provider, model in dify_config.NEW_USER_DEFAULT_MODEL_LIST:
+        try:
+            model_provider_service.update_default_model_of_model_type(
+                tenant_id=tenant_id,
+                model_type=model_type,
+                provider=provider,
+                model=model,
+            )
+        except Exception:
+            failed_model_types.append(model_type)
+            logger.exception(
+                "Failed to configure default model for tenant %s: model_type=%s provider=%s model=%s",
+                tenant_id,
+                model_type,
+                provider,
+                model,
+            )
+
+    if plugin_install_failed or failed_model_types:
+        raise RuntimeError(
+            f"Failed to initialize defaults for tenant {tenant_id}; "
+            f"model types: {', '.join(failed_model_types) or 'none'}"
+        )
+
+
+@shared_task(queue="plugin")
+def install_default_plugins_task(tenant_id: str, plugin_ids: list[str]) -> None:
+    """Install the latest marketplace versions of the configured plugins."""
+    if not plugin_ids:
+        return
+
+    try:
+        manifests = {manifest.plugin_id: manifest for manifest in marketplace.batch_fetch_plugin_manifests(plugin_ids)}
+        plugin_identifiers = [
+            manifests[plugin_id].latest_package_identifier for plugin_id in plugin_ids if plugin_id in manifests
+        ]
+        missing_plugin_ids = [plugin_id for plugin_id in plugin_ids if plugin_id not in manifests]
+        if missing_plugin_ids:
+            logger.warning("Default plugins not found in marketplace: %s", ", ".join(missing_plugin_ids))
+        if not plugin_identifiers:
+            return
+
+        response = PluginService.install_from_marketplace_pkg(tenant_id, plugin_identifiers)
+        if dify_config.NEW_USER_DEFAULT_MODELS:
+            configure_default_models_task.delay(
+                tenant_id,
+                None if response.all_installed else response.task_id,
+            )
+    except Exception:
+        logger.exception("Failed to install default plugins for tenant %s", tenant_id)
+        raise

api/tests/integration_tests/.env.example

@@ -1,5 +1,6 @@
 FLASK_APP=app.py
 FLASK_DEBUG=0
+ENABLE_COLLABORATION_MODE=false
 SECRET_KEY='uhySf6a3aZuvRNfAlcr47paOw9TRYBY6j8ZHXpVw1yx5RP27Yj3w2uvI'
 
 CONSOLE_API_URL=http://127.0.0.1:5001

api/tests/integration_tests/services/retention/test_workflow_run_archiver.py

@@ -513,11 +513,94 @@ class TestArchiveRunIdempotency:
         storage = MagicMock()
         storage.object_exists.return_value = True
 
-        result = archiver._archive_bundle(MagicMock(), storage, [run])
+        with patch.object(archiver, "_sync_existing_bundle_index") as sync_existing_bundle_index:
+            result = archiver._archive_bundle(MagicMock(), storage, [run])
 
         assert result.success is True
         assert result.skipped is True
         assert result.error == "bundle already archived"
+        sync_existing_bundle_index.assert_called_once()
+
+    def test_existing_bundle_catalog_publication_failure_is_not_success(self):
+        archiver = WorkflowRunArchiver(days=90)
+        run = _run()
+        session = MagicMock()
+        storage = MagicMock()
+        storage.object_exists.return_value = True
+
+        with patch.object(archiver, "_sync_existing_bundle_index", side_effect=RuntimeError("catalog unavailable")):
+            result = archiver._archive_bundle(session, storage, [run])
+
+        assert result.success is False
+        assert result.error == "catalog unavailable"
+        session.rollback.assert_called_once()
+
+    def test_retry_repairs_index_after_catalog_commit_then_index_write_failure(self):
+        archiver = WorkflowRunArchiver(days=90)
+        run = _run()
+        identity = archiver._build_bundle_identity([run])
+        index_key = archiver._get_index_object_key(identity)
+        manifest_key = archiver._get_manifest_object_key(identity)
+        storage = FakeArchiveStorage()
+        original_put_object = storage.put_object
+        index_write_count = 0
+
+        def put_object(key: str, data: bytes) -> str:
+            nonlocal index_write_count
+            if key == index_key:
+                index_write_count += 1
+                if index_write_count == 2:
+                    raise RuntimeError("index write failed")
+            return original_put_object(key, data)
+
+        storage.put_object = MagicMock(side_effect=put_object)
+        first_session = MagicMock()
+        first_session.scalar.return_value = None
+        table_data = {"workflow_runs": [{"id": run.id, "tenant_id": run.tenant_id}]}
+
+        with (
+            patch.object(archiver, "_lock_runs_for_archive", return_value=[run]),
+            patch.object(archiver, "_extract_bundle_data", return_value=table_data),
+        ):
+            first_result = archiver._archive_bundle(first_session, storage, [run])
+
+        assert first_result.success is False
+        assert first_result.error == "index write failed"
+        assert manifest_key in storage.objects
+        assert json.loads(storage.objects[index_key])["run_ids"] == []
+
+        storage.list_objects = MagicMock(wraps=storage.list_objects)
+        retry_session = MagicMock()
+        retry_session.scalar.return_value = None
+
+        retry_result = archiver._archive_bundle(retry_session, storage, [run])
+
+        assert retry_result.success is True
+        assert retry_result.skipped is True
+        assert json.loads(storage.objects[index_key])["manifest_keys"] == [manifest_key]
+        assert json.loads(storage.objects[index_key])["run_ids"] == [run.id]
+        storage.list_objects.assert_not_called()
+
+    def test_existing_manifest_with_missing_index_fails_without_partial_rebuild(self):
+        archiver = WorkflowRunArchiver(days=90)
+        run = _run()
+        identity = archiver._build_bundle_identity([run])
+        _, _, manifest_data = archiver._build_archive_payload(
+            identity,
+            [run],
+            {"workflow_runs": [{"id": run.id, "tenant_id": run.tenant_id}]},
+        )
+        manifest_key = archiver._get_manifest_object_key(identity)
+        index_key = archiver._get_index_object_key(identity)
+        storage = FakeArchiveStorage({manifest_key: manifest_data})
+        storage.list_objects = MagicMock(wraps=storage.list_objects)
+
+        result = archiver._archive_bundle(MagicMock(), storage, [run])
+
+        assert result.success is False
+        assert "archive shard index missing" in (result.error or "")
+        assert index_key not in storage.objects
+        storage.list_objects.assert_not_called()
 
     def test_successful_bundle_persists_archive_index(self):
         archiver = WorkflowRunArchiver(days=90)
@@ -550,6 +633,28 @@ class TestArchiveRunIdempotency:
         assert archived_bundle.row_count == 2
         session.commit.assert_called_once()
 
+    def test_new_bundle_catalog_commit_failure_is_not_success(self):
+        archiver = WorkflowRunArchiver(days=90)
+        run = _run(str(uuid.uuid4()))
+        run.tenant_id = str(uuid.uuid4())
+        session = MagicMock()
+        session.scalar.return_value = None
+        session.commit.side_effect = RuntimeError("catalog commit failed")
+        storage = MagicMock()
+        storage.object_exists.return_value = False
+        storage.list_objects.return_value = []
+        table_data = {"workflow_runs": [{"id": run.id, "tenant_id": run.tenant_id}]}
+
+        with (
+            patch.object(archiver, "_lock_runs_for_archive", return_value=[run]),
+            patch.object(archiver, "_extract_bundle_data", return_value=table_data),
+        ):
+            result = archiver._archive_bundle(session, storage, [run])
+
+        assert result.success is False
+        assert result.error == "catalog commit failed"
+        session.rollback.assert_called_once()
+
     def test_index_skips_all_already_archived_runs(self):
         archiver = WorkflowRunArchiver(days=90)
         run = MagicMock()

api/tests/integration_tests/services/test_workflow_draft_variable_service.py

@@ -311,6 +311,7 @@ class TestDraftVariableLoader(unittest.TestCase):
                 # Use DraftVariableSaver to create offloaded variable (this mimics production)
                 saver = DraftVariableSaver(
                     session=session,
+                    tenant_id=self._test_tenant_id,
                     app_id=self._test_app_id,
                     node_id="test_offload_node",
                     node_type=BuiltinNodeTypes.LLM,  # Use a real node type

api/tests/test_containers_integration_tests/controllers/console/app/test_app_import_api.py

@@ -1,179 +0,0 @@
-"""Testcontainers integration tests for controllers.console.app.app_import endpoints."""
-
-from __future__ import annotations
-
-from inspect import unwrap
-from types import SimpleNamespace
-from unittest.mock import MagicMock
-
-import pytest
-from flask import Flask
-
-from controllers.console.app import app_import as app_import_module
-from services.app_dsl_service import ImportStatus
-
-
-class _Result:
-    def __init__(self, status: ImportStatus, app_id: str | None = "app-1"):
-        self.status = status
-        self.app_id = app_id
-
-    def model_dump(self, mode: str = "json"):
-        return {"status": self.status, "app_id": self.app_id}
-
-
-def _install_features(monkeypatch: pytest.MonkeyPatch, enabled: bool) -> None:
-    features = SimpleNamespace(webapp_auth=SimpleNamespace(enabled=enabled))
-    monkeypatch.setattr(app_import_module.FeatureService, "get_system_features", lambda: features)
-
-
-class TestAppImportApi:
-    @pytest.fixture
-    def app(self, flask_app_with_containers: Flask):
-        return flask_app_with_containers
-
-    def test_import_post_returns_failed_status(self, app: Flask, monkeypatch: pytest.MonkeyPatch) -> None:
-        api = app_import_module.AppImportApi()
-        method = unwrap(api.post)
-
-        _install_features(monkeypatch, enabled=False)
-        monkeypatch.setattr(
-            app_import_module.AppDslService,
-            "import_app",
-            lambda *_args, **_kwargs: _Result(ImportStatus.FAILED, app_id=None),
-        )
-
-        with app.test_request_context("/console/api/apps/imports", method="POST", json={"mode": "yaml-content"}):
-            response, status = method(api, SimpleNamespace(id="u1"))
-
-        assert status == 400
-        assert response["status"] == ImportStatus.FAILED
-
-    def test_import_post_returns_pending_status(self, app: Flask, monkeypatch: pytest.MonkeyPatch) -> None:
-        api = app_import_module.AppImportApi()
-        method = unwrap(api.post)
-
-        _install_features(monkeypatch, enabled=False)
-        monkeypatch.setattr(
-            app_import_module.AppDslService,
-            "import_app",
-            lambda *_args, **_kwargs: _Result(ImportStatus.PENDING),
-        )
-
-        with app.test_request_context("/console/api/apps/imports", method="POST", json={"mode": "yaml-content"}):
-            response, status = method(api, SimpleNamespace(id="u1"))
-
-        assert status == 202
-        assert response["status"] == ImportStatus.PENDING
-
-    def test_import_post_updates_webapp_auth_when_enabled(self, app: Flask, monkeypatch: pytest.MonkeyPatch) -> None:
-        api = app_import_module.AppImportApi()
-        method = unwrap(api.post)
-
-        _install_features(monkeypatch, enabled=True)
-        monkeypatch.setattr(
-            app_import_module.AppDslService,
-            "import_app",
-            lambda *_args, **_kwargs: _Result(ImportStatus.COMPLETED, app_id="app-123"),
-        )
-        update_access = MagicMock()
-        monkeypatch.setattr(app_import_module.EnterpriseService.WebAppAuth, "update_app_access_mode", update_access)
-
-        with app.test_request_context("/console/api/apps/imports", method="POST", json={"mode": "yaml-content"}):
-            response, status = method(api, SimpleNamespace(id="u1"))
-
-        update_access.assert_called_once_with("app-123", "private")
-        assert status == 200
-        assert response["status"] == ImportStatus.COMPLETED
-
-    def test_import_post_commits_session_on_success(self, app: Flask, monkeypatch: pytest.MonkeyPatch) -> None:
-        api = app_import_module.AppImportApi()
-        method = unwrap(api.post)
-
-        _install_features(monkeypatch, enabled=False)
-        monkeypatch.setattr(
-            app_import_module.AppDslService,
-            "import_app",
-            lambda *_args, **_kwargs: _Result(ImportStatus.COMPLETED, app_id="app-123"),
-        )
-
-        fake_session = MagicMock()
-        fake_session.__enter__.return_value = fake_session
-        fake_session.__exit__.return_value = None
-        monkeypatch.setattr(app_import_module, "Session", lambda *_args, **_kwargs: fake_session)
-
-        with app.test_request_context("/console/api/apps/imports", method="POST", json={"mode": "yaml-content"}):
-            response, status = method(api, SimpleNamespace(id="u1"))
-
-        fake_session.commit.assert_called_once_with()
-        fake_session.rollback.assert_not_called()
-        assert status == 200
-        assert response["status"] == ImportStatus.COMPLETED
-
-    def test_import_post_rolls_back_session_on_failure(self, app: Flask, monkeypatch: pytest.MonkeyPatch) -> None:
-        api = app_import_module.AppImportApi()
-        method = unwrap(api.post)
-
-        _install_features(monkeypatch, enabled=False)
-        monkeypatch.setattr(
-            app_import_module.AppDslService,
-            "import_app",
-            lambda *_args, **_kwargs: _Result(ImportStatus.FAILED, app_id=None),
-        )
-
-        fake_session = MagicMock()
-        fake_session.__enter__.return_value = fake_session
-        fake_session.__exit__.return_value = None
-        monkeypatch.setattr(app_import_module, "Session", lambda *_args, **_kwargs: fake_session)
-
-        with app.test_request_context("/console/api/apps/imports", method="POST", json={"mode": "yaml-content"}):
-            response, status = method(api, SimpleNamespace(id="u1"))
-
-        fake_session.rollback.assert_called_once_with()
-        fake_session.commit.assert_not_called()
-        assert status == 400
-        assert response["status"] == ImportStatus.FAILED
-
-
-class TestAppImportConfirmApi:
-    @pytest.fixture
-    def app(self, flask_app_with_containers: Flask):
-        return flask_app_with_containers
-
-    def test_import_confirm_returns_failed_status(self, app: Flask, monkeypatch: pytest.MonkeyPatch) -> None:
-        api = app_import_module.AppImportConfirmApi()
-        method = unwrap(api.post)
-
-        monkeypatch.setattr(
-            app_import_module.AppDslService,
-            "confirm_import",
-            lambda *_args, **_kwargs: _Result(ImportStatus.FAILED),
-        )
-
-        with app.test_request_context("/console/api/apps/imports/import-1/confirm", method="POST"):
-            response, status = method(api, SimpleNamespace(id="u1"), import_id="import-1")
-
-        assert status == 400
-        assert response["status"] == ImportStatus.FAILED
-
-
-class TestAppImportCheckDependenciesApi:
-    @pytest.fixture
-    def app(self, flask_app_with_containers: Flask):
-        return flask_app_with_containers
-
-    def test_import_check_dependencies_returns_result(self, app: Flask, monkeypatch: pytest.MonkeyPatch) -> None:
-        api = app_import_module.AppImportCheckDependenciesApi()
-        method = unwrap(api.get)
-
-        monkeypatch.setattr(
-            app_import_module.AppDslService,
-            "check_dependencies",
-            lambda *_args, **_kwargs: SimpleNamespace(model_dump=lambda mode="json": {"leaked_dependencies": []}),
-        )
-
-        with app.test_request_context("/console/api/apps/imports/app-1/check-dependencies", method="GET"):
-            response, status = method(api, app_model=SimpleNamespace(id="app-1"))
-
-        assert status == 200
-        assert response["leaked_dependencies"] == []

api/tests/unit_tests/clients/agent_backend/test_client.py

@@ -1,4 +1,4 @@
-from collections.abc import Iterator
+from collections.abc import Callable, Iterator
 from typing import override
 
 import pytest
@@ -47,6 +47,8 @@ def _request():
 
 
 class _SuccessfulClient:
+    stream_options: tuple[int | None, float | None, Callable[[], bool] | None] | None = None
+
     def create_run_sync(self, request: CreateRunRequest) -> CreateRunResponse:
         assert isinstance(request, CreateRunRequest)
         return CreateRunResponse(run_id="run-1", status="running")
@@ -55,8 +57,17 @@ class _SuccessfulClient:
         del request
         return CancelRunResponse(run_id=run_id, status="cancelled")
 
-    def stream_events_sync(self, run_id: str, *, after: str | None = None) -> Iterator[RunEvent]:
+    def stream_events_sync(
+        self,
+        run_id: str,
+        *,
+        after: str | None = None,
+        max_reconnects: int | None = None,
+        timeout_seconds: float | None = None,
+        should_stop: Callable[[], bool] | None = None,
+    ) -> Iterator[RunEvent]:
         del after
+        self.stream_options = (max_reconnects, timeout_seconds, should_stop)
         yield RunStartedEvent(id="1-0", run_id=run_id)
 
     def wait_run_sync(self, run_id: str, *, timeout_seconds: float | None = None) -> RunStatusResponse:
@@ -72,17 +83,22 @@ class _SuccessfulClient:
 
 
 def test_dify_agent_backend_run_client_delegates_sync_methods():
-    client = DifyAgentBackendRunClient(_SuccessfulClient())
+    wrapped = _SuccessfulClient()
+    client = DifyAgentBackendRunClient(wrapped, stream_max_reconnects=2, stream_timeout_seconds=45)
+
+    def should_stop() -> bool:
+        return False
 
     created = client.create_run(_request())
     cancelled = client.cancel_run(created.run_id)
-    events = list(client.stream_events(created.run_id))
+    events = list(client.stream_events(created.run_id, should_stop=should_stop))
     status = client.wait_run(created.run_id)
 
     assert created.run_id == "run-1"
     assert cancelled.status == "cancelled"
     assert events[0].type == "run_started"
     assert status.status == "succeeded"
+    assert wrapped.stream_options == (2, 45, should_stop)
 
 
 def test_dify_agent_backend_run_client_maps_validation_error():
@@ -125,7 +141,16 @@ def test_dify_agent_backend_run_client_maps_timeout_error():
 def test_dify_agent_backend_run_client_maps_stream_error():
     class StreamClient(_SuccessfulClient):
         @override
-        def stream_events_sync(self, run_id: str, *, after: str | None = None) -> Iterator[RunEvent]:
+        def stream_events_sync(
+            self,
+            run_id: str,
+            *,
+            after: str | None = None,
+            max_reconnects: int | None = None,
+            timeout_seconds: float | None = None,
+            should_stop: Callable[[], bool] | None = None,
+        ) -> Iterator[RunEvent]:
+            del run_id, after, max_reconnects, timeout_seconds, should_stop
             raise DifyAgentStreamError("bad stream")
             yield
 

api/tests/unit_tests/clients/agent_backend/test_event_adapter.py

@@ -1,3 +1,5 @@
+from decimal import Decimal
+
 import pytest
 from agenton.compositor import CompositorSessionSnapshot
 from dify_agent.protocol import (
@@ -83,7 +85,19 @@ def test_event_adapter_maps_run_succeeded_to_final_output():
             data=RunSucceededEventData(
                 output={"summary": "done"},
                 session_snapshot=snapshot,
-                usage=AgentRunUsage(prompt_tokens=2, completion_tokens=3),
+                usage=AgentRunUsage(
+                    prompt_tokens=2,
+                    prompt_unit_price=Decimal(5),
+                    prompt_price_unit=Decimal("0.000001"),
+                    prompt_price=Decimal("0.000010"),
+                    completion_tokens=3,
+                    completion_unit_price=Decimal(30),
+                    completion_price_unit=Decimal("0.000001"),
+                    completion_price=Decimal("0.000090"),
+                    total_price=Decimal("0.000100"),
+                    currency="USD",
+                    latency=0.4,
+                ),
             ),
         )
     )
@@ -94,7 +108,22 @@ def test_event_adapter_maps_run_succeeded_to_final_output():
             source_event_id="3-0",
             output={"summary": "done"},
             session_snapshot=snapshot,
-            usage={"prompt_tokens": 2, "completion_tokens": 3, "total_tokens": 5},
+            usage={
+                "prompt_tokens": 2,
+                "prompt_unit_price": "5",
+                "prompt_price_unit": "0.000001",
+                "prompt_price": "0.000010",
+                "completion_tokens": 3,
+                "completion_unit_price": "30",
+                "completion_price_unit": "0.000001",
+                "completion_price": "0.000090",
+                "total_tokens": 5,
+                "total_price": "0.000100",
+                "currency": "USD",
+                "latency": 0.4,
+                "time_to_first_token": None,
+                "time_to_generate": None,
+            },
         )
     ]
 

api/tests/unit_tests/commands/test_archive_workflow_runs.py

@@ -3,9 +3,19 @@ from unittest.mock import MagicMock
 
 import click
 import pytest
+from click.testing import CliRunner
 from sqlalchemy.exc import OperationalError
 
 from commands import retention
+from services.retention.workflow_run import bundle_archive_maintenance
+from services.retention.workflow_run.bundle_archive_maintenance import (
+    BundleOperationResult,
+    BundleOperationSummary,
+)
+
+_CURSOR_0 = "00000000-0000-0000-0000-000000000000"
+_CURSOR_1 = "00000000-0000-0000-0000-000000000001"
+_CURSOR_2 = "00000000-0000-0000-0000-000000000002"
 
 
 def _db_disconnect_error() -> OperationalError:
@@ -24,6 +34,58 @@ def _session_context(session):
     return context
 
 
+def _delete_summary(
+    *,
+    processed: int,
+    succeeded: int = 0,
+    failed: int = 0,
+    next_catalog_id: str | None = None,
+    preview_next_catalog_id: str | None = None,
+    results: list[BundleOperationResult] | None = None,
+) -> BundleOperationSummary:
+    return BundleOperationSummary(
+        operation="delete",
+        bundles_processed=processed,
+        bundles_succeeded=succeeded,
+        bundles_failed=failed,
+        next_catalog_id=next_catalog_id,
+        preview_next_catalog_id=preview_next_catalog_id,
+        results=results or [],
+    )
+
+
+def _patch_bundle_deleter(
+    monkeypatch: pytest.MonkeyPatch,
+    summaries: list[BundleOperationSummary],
+) -> MagicMock:
+    deleter = MagicMock()
+    deleter.delete_batch.side_effect = summaries
+    monkeypatch.setattr(
+        bundle_archive_maintenance,
+        "WorkflowRunBundleArchiveMaintenance",
+        MagicMock(return_value=deleter),
+    )
+    return deleter
+
+
+@pytest.mark.parametrize(
+    "command",
+    [retention.restore_workflow_runs, retention.delete_archived_workflow_runs],
+)
+def test_v2_archive_maintenance_rejects_explicitly_empty_tenant_ids(command):
+    result = CliRunner().invoke(
+        command,
+        ["--tenant-ids", "", "--target-month", "2025-03"],
+    )
+
+    assert result.exit_code == 2
+    assert "tenant-ids must not be empty" in result.output
+
+
+def test_archive_tenant_id_parser_keeps_omitted_scope_unset():
+    assert retention._parse_comma_separated_ids(None, param_name="tenant-ids") is None
+
+
 def test_resolve_archive_tenant_ids_from_plan_uses_explicit_sessions(monkeypatch):
     end_before = datetime.datetime(2025, 4, 1, tzinfo=datetime.UTC)
     sessions = [MagicMock(name="session-a"), MagicMock(name="session-b")]
@@ -137,3 +199,265 @@ def test_archive_workflow_runs_raises_click_exception_when_tenant_plan_fails(mon
             dry_run=True,
             delete_after_archive=False,
         )
+
+
+def test_delete_archived_workflow_runs_keeps_single_page_behavior_without_all_pages(monkeypatch):
+    deleter = _patch_bundle_deleter(
+        monkeypatch,
+        [_delete_summary(processed=2, succeeded=2, next_catalog_id=_CURSOR_1)],
+    )
+
+    result = CliRunner().invoke(
+        retention.delete_archived_workflow_runs,
+        ["--target-month", "2025-03", "--limit", "2"],
+    )
+
+    assert result.exit_code == 0
+    deleter.delete_batch.assert_called_once()
+    assert deleter.delete_batch.call_args.kwargs["target_year"] == 2025
+    assert deleter.delete_batch.call_args.kwargs["target_month"] == 3
+    assert deleter.delete_batch.call_args.kwargs["after_catalog_id"] is None
+    assert deleter.delete_batch.call_args.kwargs["limit"] == 2
+
+
+def test_delete_archived_workflow_runs_all_pages_continues_until_empty_page(monkeypatch):
+    deleter = _patch_bundle_deleter(
+        monkeypatch,
+        [
+            _delete_summary(processed=2, succeeded=2, next_catalog_id=_CURSOR_1),
+            _delete_summary(processed=1, succeeded=1, next_catalog_id=_CURSOR_2),
+            _delete_summary(processed=0),
+        ],
+    )
+
+    result = CliRunner().invoke(
+        retention.delete_archived_workflow_runs,
+        ["--target-month", "2025-03", "--all-pages", "--limit", "2"],
+    )
+
+    assert result.exit_code == 0
+    assert [call.kwargs["after_catalog_id"] for call in deleter.delete_batch.call_args_list] == [
+        None,
+        _CURSOR_1,
+        _CURSOR_2,
+    ]
+
+
+def test_delete_archived_workflow_runs_all_pages_fetches_empty_page_after_exact_full_page(monkeypatch):
+    deleter = _patch_bundle_deleter(
+        monkeypatch,
+        [
+            _delete_summary(processed=2, succeeded=2, next_catalog_id=_CURSOR_1),
+            _delete_summary(processed=0),
+        ],
+    )
+
+    result = CliRunner().invoke(
+        retention.delete_archived_workflow_runs,
+        ["--target-month", "2025-03", "--all-pages", "--limit", "2"],
+    )
+
+    assert result.exit_code == 0
+    assert deleter.delete_batch.call_count == 2
+    assert deleter.delete_batch.call_args_list[1].kwargs["after_catalog_id"] == _CURSOR_1
+
+
+def test_delete_archived_workflow_runs_all_pages_stops_at_first_failed_page(monkeypatch):
+    failed_result = BundleOperationResult(
+        catalog_id=_CURSOR_2,
+        bundle_id="bundle-failed",
+        tenant_id="tenant-1",
+        object_prefix="workflow-runs/v2/tenant-1/2025/03/00-of-16/bundle-failed",
+        error="archive checksum mismatch",
+    )
+    deleter = _patch_bundle_deleter(
+        monkeypatch,
+        [
+            _delete_summary(processed=1, succeeded=1, next_catalog_id=_CURSOR_1),
+            _delete_summary(processed=1, failed=1, results=[failed_result]),
+            _delete_summary(processed=0),
+        ],
+    )
+
+    result = CliRunner().invoke(
+        retention.delete_archived_workflow_runs,
+        ["--target-month", "2025-03", "--all-pages"],
+    )
+
+    assert result.exit_code == 1
+    assert deleter.delete_batch.call_count == 2
+    assert "target_month=2025-03" in result.output
+    assert f"failed_catalog_id={_CURSOR_2}" in result.output
+    assert f"resume_after_catalog_id={_CURSOR_1}" in result.output
+
+
+def test_delete_archived_workflow_runs_all_pages_fails_when_cursor_does_not_advance(monkeypatch):
+    deleter = _patch_bundle_deleter(
+        monkeypatch,
+        [_delete_summary(processed=1, succeeded=1, next_catalog_id=None)],
+    )
+
+    result = CliRunner().invoke(
+        retention.delete_archived_workflow_runs,
+        ["--target-month", "2025-03", "--all-pages"],
+    )
+
+    assert result.exit_code == 1
+    deleter.delete_batch.assert_called_once()
+    assert "cursor did not advance" in result.output.lower()
+
+
+def test_delete_archived_workflow_runs_all_pages_uses_preview_cursor_for_dry_run(monkeypatch):
+    deleter = _patch_bundle_deleter(
+        monkeypatch,
+        [
+            _delete_summary(processed=1, succeeded=1, preview_next_catalog_id=_CURSOR_1),
+            _delete_summary(processed=0),
+        ],
+    )
+
+    result = CliRunner().invoke(
+        retention.delete_archived_workflow_runs,
+        ["--target-month", "2025-03", "--all-pages", "--dry-run"],
+    )
+
+    assert result.exit_code == 0
+    assert [call.kwargs["after_catalog_id"] for call in deleter.delete_batch.call_args_list] == [
+        None,
+        _CURSOR_1,
+    ]
+
+
+def test_delete_archived_workflow_runs_dry_run_failure_separates_preview_and_destructive_cursors(monkeypatch):
+    failed_result = BundleOperationResult(
+        catalog_id=_CURSOR_2,
+        bundle_id="bundle-failed",
+        tenant_id="tenant-1",
+        object_prefix="workflow-runs/v2/tenant-1/2025/03/00-of-16/bundle-failed",
+        error="archive checksum mismatch",
+    )
+    deleter = _patch_bundle_deleter(
+        monkeypatch,
+        [
+            _delete_summary(
+                processed=1,
+                succeeded=1,
+                preview_next_catalog_id=_CURSOR_1,
+            ),
+            _delete_summary(
+                processed=1,
+                failed=1,
+                results=[failed_result],
+            ),
+        ],
+    )
+
+    result = CliRunner().invoke(
+        retention.delete_archived_workflow_runs,
+        [
+            "--target-month",
+            "2025-03",
+            "--after-catalog-id",
+            _CURSOR_0,
+            "--all-pages",
+            "--dry-run",
+        ],
+    )
+
+    assert result.exit_code == 1
+    assert deleter.delete_batch.call_count == 2
+    assert f"failed_catalog_id={_CURSOR_2}" in result.output
+    assert f"preview_after_catalog_id={_CURSOR_1}" in result.output
+    assert f"destructive_retry_after_catalog_id={_CURSOR_0}" in result.output
+
+
+def test_delete_archived_workflow_runs_all_pages_starts_after_explicit_cursor(monkeypatch):
+    deleter = _patch_bundle_deleter(monkeypatch, [_delete_summary(processed=0)])
+
+    result = CliRunner().invoke(
+        retention.delete_archived_workflow_runs,
+        [
+            "--target-month",
+            "2025-03",
+            "--after-catalog-id",
+            _CURSOR_0,
+            "--all-pages",
+        ],
+    )
+
+    assert result.exit_code == 0
+    deleter.delete_batch.assert_called_once()
+    assert deleter.delete_batch.call_args.kwargs["after_catalog_id"] == _CURSOR_0
+
+
+@pytest.mark.parametrize(
+    "shard_args",
+    [
+        ["--run-shard-index", "0"],
+        ["--run-shard-total", "16"],
+        ["--run-shard-index", "16", "--run-shard-total", "16"],
+        ["--run-shard-index", "-1", "--run-shard-total", "16"],
+        ["--run-shard-index", "0", "--run-shard-total", "0"],
+        ["--run-shard-index", "0", "--run-shard-total", "17"],
+    ],
+)
+def test_delete_archived_workflow_runs_rejects_invalid_run_shard_options(monkeypatch, shard_args):
+    deleter = _patch_bundle_deleter(monkeypatch, [_delete_summary(processed=0)])
+
+    result = CliRunner().invoke(
+        retention.delete_archived_workflow_runs,
+        ["--target-month", "2025-03", *shard_args],
+    )
+
+    assert result.exit_code == 2
+    deleter.delete_batch.assert_not_called()
+
+
+def test_delete_archived_workflow_runs_passes_formatted_run_shard_to_service(monkeypatch):
+    deleter = _patch_bundle_deleter(monkeypatch, [_delete_summary(processed=0)])
+
+    result = CliRunner().invoke(
+        retention.delete_archived_workflow_runs,
+        [
+            "--target-month",
+            "2025-03",
+            "--tenant-ids",
+            "tenant-1",
+            "--run-shard-index",
+            "3",
+            "--run-shard-total",
+            "16",
+        ],
+    )
+
+    assert result.exit_code == 0
+    deleter.validate_catalog_shards.assert_called_once_with(
+        target_year=2025,
+        target_month=3,
+        shard_total=16,
+        tenant_ids=["tenant-1"],
+    )
+    deleter.delete_batch.assert_called_once()
+    assert deleter.delete_batch.call_args.kwargs["shard"] == "03-of-16"
+
+
+def test_delete_archived_workflow_runs_rejects_mixed_catalog_shards_before_delete(monkeypatch):
+    deleter = _patch_bundle_deleter(monkeypatch, [_delete_summary(processed=0)])
+    deleter.validate_catalog_shards.side_effect = ValueError("unexpected shards: 00-of-01")
+
+    result = CliRunner().invoke(
+        retention.delete_archived_workflow_runs,
+        [
+            "--target-month",
+            "2025-03",
+            "--run-shard-index",
+            "3",
+            "--run-shard-total",
+            "16",
+        ],
+    )
+
+    assert result.exit_code == 1
+    assert "shard preflight failed" in result.output.lower()
+    assert "00-of-01" in result.output
+    deleter.delete_batch.assert_not_called()

api/tests/unit_tests/configs/test_dify_config.py

@@ -8,8 +8,13 @@ from yarl import URL
 from configs.app_config import DifyConfig
 
 
+def _clear_environment(monkeypatch: pytest.MonkeyPatch) -> None:
+    for name in tuple(os.environ):
+        monkeypatch.delenv(name)
+
+
 def _set_basic_config_env(monkeypatch: pytest.MonkeyPatch) -> None:
-    os.environ.clear()
+    _clear_environment(monkeypatch)
     monkeypatch.setenv("CONSOLE_API_URL", "https://example.com")
     monkeypatch.setenv("CONSOLE_WEB_URL", "https://example.com")
     monkeypatch.setenv("DB_TYPE", "postgresql")
@@ -51,7 +56,7 @@ def test_dify_config_preserves_explicit_secret_key(
 
 def test_dify_config(monkeypatch: pytest.MonkeyPatch):
     # clear system environment variables
-    os.environ.clear()
+    _clear_environment(monkeypatch)
 
     # Set environment variables using monkeypatch
     monkeypatch.setenv("CONSOLE_API_URL", "https://example.com")
@@ -89,10 +94,76 @@ def test_dify_config(monkeypatch: pytest.MonkeyPatch):
     assert Version(config.project.version) >= Version("1.0.0")
 
 
+def test_new_user_default_plugin_ids_are_parsed_from_env(monkeypatch: pytest.MonkeyPatch) -> None:
+    _set_basic_config_env(monkeypatch)
+    monkeypatch.setenv(
+        "NEW_USER_DEFAULT_PLUGIN_IDS",
+        "langgenius/openai, langgenius/gemini",
+    )
+
+    config = DifyConfig(_env_file=None)
+
+    assert config.NEW_USER_DEFAULT_PLUGIN_ID_LIST == [
+        "langgenius/openai",
+        "langgenius/gemini",
+    ]
+
+
+def test_plugin_remote_install_port_rejects_host_port_spec(monkeypatch: pytest.MonkeyPatch) -> None:
+    """A 'host:port' compose publish spec must produce an actionable error, not an opaque int_parsing traceback."""
+    _set_basic_config_env(monkeypatch)
+    monkeypatch.setenv("PLUGIN_REMOTE_INSTALL_PORT", "127.0.0.1:5003")
+
+    with pytest.raises(ValueError, match="must be a bare port number"):
+        DifyConfig(_env_file=None)
+
+
+def test_plugin_remote_install_port_accepts_bare_port(monkeypatch: pytest.MonkeyPatch) -> None:
+    _set_basic_config_env(monkeypatch)
+    monkeypatch.setenv("PLUGIN_REMOTE_INSTALL_PORT", "5003")
+
+    config = DifyConfig(_env_file=None)
+
+    assert config.PLUGIN_REMOTE_INSTALL_PORT == 5003
+
+
+def test_new_user_default_models_are_parsed_from_env(monkeypatch: pytest.MonkeyPatch) -> None:
+    _set_basic_config_env(monkeypatch)
+    monkeypatch.setenv(
+        "NEW_USER_DEFAULT_MODELS",
+        (
+            "llm:langgenius/openai/openai:gpt-4o-mini, "
+            "text-embedding:langgenius/openai/openai:text-embedding-3-small, "
+            "rerank:langgenius/ollama/ollama:reranker:latest"
+        ),
+    )
+
+    config = DifyConfig(_env_file=None)
+
+    assert config.NEW_USER_DEFAULT_MODEL_LIST == [
+        ("llm", "langgenius/openai/openai", "gpt-4o-mini"),
+        ("text-embedding", "langgenius/openai/openai", "text-embedding-3-small"),
+        ("rerank", "langgenius/ollama/ollama", "reranker:latest"),
+    ]
+
+
+def test_new_user_default_models_reject_duplicate_model_types(monkeypatch: pytest.MonkeyPatch) -> None:
+    _set_basic_config_env(monkeypatch)
+    monkeypatch.setenv(
+        "NEW_USER_DEFAULT_MODELS",
+        "llm:langgenius/openai/openai:gpt-4o-mini,llm:langgenius/anthropic/anthropic:claude-sonnet-4",
+    )
+
+    config = DifyConfig(_env_file=None)
+
+    with pytest.raises(ValueError, match="duplicate model type: llm"):
+        _ = config.NEW_USER_DEFAULT_MODEL_LIST
+
+
 def test_http_timeout_defaults(monkeypatch: pytest.MonkeyPatch):
     """Test that HTTP timeout defaults are correctly set"""
     # clear system environment variables
-    os.environ.clear()
+    _clear_environment(monkeypatch)
 
     # Set minimal required env vars
     monkeypatch.setenv("DB_TYPE", "postgresql")
@@ -112,7 +183,7 @@ def test_http_timeout_defaults(monkeypatch: pytest.MonkeyPatch):
 
 
 def test_internal_files_url_falls_back_to_server_console_api_url(monkeypatch: pytest.MonkeyPatch):
-    os.environ.clear()
+    _clear_environment(monkeypatch)
     monkeypatch.setenv("SERVER_CONSOLE_API_URL", "http://api:5001")
 
     config = DifyConfig(_env_file=None)
@@ -121,7 +192,7 @@ def test_internal_files_url_falls_back_to_server_console_api_url(monkeypatch: py
 
 
 def test_internal_files_url_prefers_explicit_value(monkeypatch: pytest.MonkeyPatch):
-    os.environ.clear()
+    _clear_environment(monkeypatch)
     monkeypatch.setenv("INTERNAL_FILES_URL", "http://files-internal:5001")
     monkeypatch.setenv("SERVER_CONSOLE_API_URL", "http://api:5001")
 
@@ -135,7 +206,7 @@ def test_internal_files_url_prefers_explicit_value(monkeypatch: pytest.MonkeyPat
 def test_flask_configs(monkeypatch: pytest.MonkeyPatch):
     flask_app = Flask("app")
     # clear system environment variables
-    os.environ.clear()
+    _clear_environment(monkeypatch)
 
     # Set environment variables using monkeypatch
     monkeypatch.setenv("CONSOLE_API_URL", "https://example.com")
@@ -242,7 +313,7 @@ def test_db_session_timezone_override_can_disable_app_level_timezone_injection(m
 
 
 def test_pubsub_redis_url_default(monkeypatch: pytest.MonkeyPatch):
-    os.environ.clear()
+    _clear_environment(monkeypatch)
 
     monkeypatch.setenv("CONSOLE_API_URL", "https://example.com")
     monkeypatch.setenv("CONSOLE_WEB_URL", "https://example.com")
@@ -265,7 +336,7 @@ def test_pubsub_redis_url_default(monkeypatch: pytest.MonkeyPatch):
 
 
 def test_pubsub_redis_url_override(monkeypatch: pytest.MonkeyPatch):
-    os.environ.clear()
+    _clear_environment(monkeypatch)
 
     monkeypatch.setenv("CONSOLE_API_URL", "https://example.com")
     monkeypatch.setenv("CONSOLE_WEB_URL", "https://example.com")
@@ -282,7 +353,7 @@ def test_pubsub_redis_url_override(monkeypatch: pytest.MonkeyPatch):
 
 
 def test_pubsub_redis_url_required_when_default_unavailable(monkeypatch: pytest.MonkeyPatch):
-    os.environ.clear()
+    _clear_environment(monkeypatch)
 
     monkeypatch.setenv("CONSOLE_API_URL", "https://example.com")
     monkeypatch.setenv("CONSOLE_WEB_URL", "https://example.com")
@@ -298,7 +369,7 @@ def test_pubsub_redis_url_required_when_default_unavailable(monkeypatch: pytest.
 
 
 def test_dify_config_exposes_redis_key_prefix_default(monkeypatch: pytest.MonkeyPatch):
-    os.environ.clear()
+    _clear_environment(monkeypatch)
 
     monkeypatch.setenv("CONSOLE_API_URL", "https://example.com")
     monkeypatch.setenv("CONSOLE_WEB_URL", "https://example.com")
@@ -315,7 +386,7 @@ def test_dify_config_exposes_redis_key_prefix_default(monkeypatch: pytest.Monkey
 
 
 def test_dify_config_reads_redis_key_prefix_from_env(monkeypatch: pytest.MonkeyPatch):
-    os.environ.clear()
+    _clear_environment(monkeypatch)
 
     monkeypatch.setenv("CONSOLE_API_URL", "https://example.com")
     monkeypatch.setenv("CONSOLE_WEB_URL", "https://example.com")
@@ -367,7 +438,7 @@ def test_celery_broker_url_with_special_chars_password(
     from kombu.utils.url import parse_url
 
     # clear system environment variables
-    os.environ.clear()
+    _clear_environment(monkeypatch)
 
     # Set up basic required environment variables (following existing pattern)
     monkeypatch.setenv("CONSOLE_API_URL", "https://example.com")