chore: remove pm2 from web docker

Co-authored-by: hyoban <38493346+hyoban@users.noreply.github.com>

.agents/skills/backend-code-review/SKILL.md

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+---
+name: backend-code-review
+description: Review backend code for quality, security, maintainability, and best practices based on established checklist rules. Use when the user requests a review, analysis, or improvement of backend files (e.g., `.py`) under the `api/` directory. Do NOT use for frontend files (e.g., `.tsx`, `.ts`, `.js`). Supports pending-change review, code snippets review, and file-focused review.
+---
+
+# Backend Code Review
+
+## When to use this skill
+
+Use this skill whenever the user asks to **review, analyze, or improve** backend code (e.g., `.py`) under the `api/` directory. Supports the following review modes:
+
+- **Pending-change review**: when the user asks to review current changes (inspect staged/working-tree files slated for commit to get the changes).
+- **Code snippets review**: when the user pastes code snippets (e.g., a function/class/module excerpt) into the chat and asks for a review.
+- **File-focused review**: when the user points to specific files and asks for a review of those files (one file or a small, explicit set of files, e.g., `api/...`, `api/app.py`).
+
+Do NOT use this skill when:
+
+- The request is about frontend code or UI (e.g., `.tsx`, `.ts`, `.js`, `web/`).
+- The user is not asking for a review/analysis/improvement of backend code.
+- The scope is not under `api/` (unless the user explicitly asks to review backend-related changes outside `api/`).
+
+## How to use this skill
+
+Follow these steps when using this skill:
+
+1. **Identify the review mode** (pending-change vs snippet vs file-focused) based on the user’s input. Keep the scope tight: review only what the user provided or explicitly referenced.
+2. Follow the rules defined in **Checklist** to perform the review. If no Checklist rule matches, apply **General Review Rules** as a fallback to perform the best-effort review.
+3. Compose the final output strictly follow the **Required Output Format**.
+
+Notes when using this skill:
+- Always include actionable fixes or suggestions (including possible code snippets).
+- Use best-effort `File:Line` references when a file path and line numbers are available; otherwise, use the most specific identifier you can.
+
+## Checklist
+
+- db schema design: if the review scope includes code/files under `api/models/` or `api/migrations/`, follow [references/db-schema-rule.md](references/db-schema-rule.md) to perform the review
+- architecture: if the review scope involves controller/service/core-domain/libs/model layering, dependency direction, or moving responsibilities across modules, follow [references/architecture-rule.md](references/architecture-rule.md) to perform the review
+- repositories abstraction: if the review scope contains table/model operations (e.g., `select(...)`, `session.execute(...)`, joins, CRUD) and is not under `api/repositories`, `api/core/repositories`, or `api/extensions/*/repositories/`, follow [references/repositories-rule.md](references/repositories-rule.md) to perform the review
+- sqlalchemy patterns: if the review scope involves SQLAlchemy session/query usage, db transaction/crud usage, or raw SQL usage, follow [references/sqlalchemy-rule.md](references/sqlalchemy-rule.md) to perform the review
+
+## General Review Rules
+
+### 1. Security Review
+
+Check for:
+- SQL injection vulnerabilities
+- Server-Side Request Forgery (SSRF)
+- Command injection
+- Insecure deserialization
+- Hardcoded secrets/credentials
+- Improper authentication/authorization
+- Insecure direct object references
+
+### 2. Performance Review
+
+Check for:
+- N+1 queries
+- Missing database indexes
+- Memory leaks
+- Blocking operations in async code
+- Missing caching opportunities
+
+### 3. Code Quality Review
+
+Check for:
+- Code forward compatibility
+- Code duplication (DRY violations)
+- Functions doing too much (SRP violations)
+- Deep nesting / complex conditionals
+- Magic numbers/strings
+- Poor naming
+- Missing error handling
+- Incomplete type coverage
+
+### 4. Testing Review
+
+Check for:
+- Missing test coverage for new code
+- Tests that don't test behavior
+- Flaky test patterns
+- Missing edge cases
+
+## Required Output Format
+
+When this skill invoked, the response must exactly follow one of the two templates:
+
+### Template A (any findings)
+
+```markdown
+# Code Review Summary
+
+Found <X> critical issues need to be fixed:
+
+## 🔴 Critical (Must Fix)
+
+### 1. <brief description of the issue>
+
+FilePath: <path> line <line>
+<relevant code snippet or pointer>
+
+#### Explanation
+
+<detailed explanation and references of the issue>
+
+#### Suggested Fix
+
+1. <brief description of suggested fix>
+2. <code example> (optional, omit if not applicable)
+
+---
+... (repeat for each critical issue) ...
+
+Found <Y> suggestions for improvement:
+
+## 🟡 Suggestions (Should Consider)
+
+### 1. <brief description of the suggestion>
+
+FilePath: <path> line <line>
+<relevant code snippet or pointer>
+
+#### Explanation
+
+<detailed explanation and references of the suggestion>
+
+#### Suggested Fix
+
+1. <brief description of suggested fix>
+2. <code example> (optional, omit if not applicable)
+
+---
+... (repeat for each suggestion) ...
+
+Found <Z> optional nits:
+
+## 🟢 Nits (Optional)
+### 1. <brief description of the nit>
+
+FilePath: <path> line <line>
+<relevant code snippet or pointer>
+
+#### Explanation
+
+<explanation and references of the optional nit>
+
+#### Suggested Fix
+
+- <minor suggestions>
+
+---
+... (repeat for each nits) ...
+
+## ✅ What's Good
+
+- <Positive feedback on good patterns>
+```
+
+- If there are no critical issues or suggestions or option nits or good points, just omit that section.
+- If the issue number is more than 10, summarize as "Found 10+ critical issues/suggestions/optional nits" and only output the first 10 items.
+- Don't compress the blank lines between sections; keep them as-is for readability.
+- If there is any issue requires code changes, append a brief follow-up question to ask whether the user wants to apply the fix(es) after the structured output. For example: "Would you like me to use the Suggested fix(es) to address these issues?"
+
+### Template B (no issues)
+
+```markdown
+## Code Review Summary
+✅ No issues found.
+```

.agents/skills/backend-code-review/references/architecture-rule.md

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+# Rule Catalog — Architecture
+
+## Scope
+- Covers: controller/service/core-domain/libs/model layering, dependency direction, responsibility placement, observability-friendly flow.
+
+## Rules
+
+### Keep business logic out of controllers
+- Category: maintainability
+- Severity: critical
+- Description: Controllers should parse input, call services, and return serialized responses. Business decisions inside controllers make behavior hard to reuse and test.
+- Suggested fix: Move domain/business logic into the service or core/domain layer. Keep controller handlers thin and orchestration-focused.
+- Example:
+  - Bad:
+    ```python
+    @bp.post("/apps/<app_id>/publish")
+    def publish_app(app_id: str):
+        payload = request.get_json() or {}
+        if payload.get("force") and current_user.role != "admin":
+            raise ValueError("only admin can force publish")
+        app = App.query.get(app_id)
+        app.status = "published"
+        db.session.commit()
+        return {"result": "ok"}
+    ```
+  - Good:
+    ```python
+    @bp.post("/apps/<app_id>/publish")
+    def publish_app(app_id: str):
+        payload = PublishRequest.model_validate(request.get_json() or {})
+        app_service.publish_app(app_id=app_id, force=payload.force, actor_id=current_user.id)
+        return {"result": "ok"}
+    ```
+
+### Preserve layer dependency direction
+- Category: best practices
+- Severity: critical
+- Description: Controllers may depend on services, and services may depend on core/domain abstractions. Reversing this direction (for example, core importing controller/web modules) creates cycles and leaks transport concerns into domain code.
+- Suggested fix: Extract shared contracts into core/domain or service-level modules and make upper layers depend on lower, not the reverse.
+- Example:
+  - Bad:
+    ```python
+    # core/policy/publish_policy.py
+    from controllers.console.app import request_context
+
+    def can_publish() -> bool:
+        return request_context.current_user.is_admin
+    ```
+  - Good:
+    ```python
+    # core/policy/publish_policy.py
+    def can_publish(role: str) -> bool:
+        return role == "admin"
+
+    # service layer adapts web/user context to domain input
+    allowed = can_publish(role=current_user.role)
+    ```
+
+### Keep libs business-agnostic
+- Category: maintainability
+- Severity: critical
+- Description: Modules under `api/libs/` should remain reusable, business-agnostic building blocks. They must not encode product/domain-specific rules, workflow orchestration, or business decisions.
+- Suggested fix:
+  - If business logic appears in `api/libs/`, extract it into the appropriate `services/` or `core/` module and keep `libs` focused on generic, cross-cutting helpers.
+  - Keep `libs` dependencies clean: avoid importing service/controller/domain-specific modules into `api/libs/`.
+- Example:
+  - Bad:
+    ```python
+    # api/libs/conversation_filter.py
+    from services.conversation_service import ConversationService
+
+    def should_archive_conversation(conversation, tenant_id: str) -> bool:
+        # Domain policy and service dependency are leaking into libs.
+        service = ConversationService()
+        if service.has_paid_plan(tenant_id):
+            return conversation.idle_days > 90
+        return conversation.idle_days > 30
+    ```
+  - Good:
+    ```python
+    # api/libs/datetime_utils.py (business-agnostic helper)
+    def older_than_days(idle_days: int, threshold_days: int) -> bool:
+        return idle_days > threshold_days
+
+    # services/conversation_service.py (business logic stays in service/core)
+    from libs.datetime_utils import older_than_days
+
+    def should_archive_conversation(conversation, tenant_id: str) -> bool:
+        threshold_days = 90 if has_paid_plan(tenant_id) else 30
+        return older_than_days(conversation.idle_days, threshold_days)
+    ```

.agents/skills/backend-code-review/references/db-schema-rule.md

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+# Rule Catalog — DB Schema Design
+
+## Scope
+- Covers: model/base inheritance, schema boundaries in model properties, tenant-aware schema design, index redundancy checks, dialect portability in models, and cross-database compatibility in migrations.
+- Does NOT cover: session lifecycle, transaction boundaries, and query execution patterns (handled by `sqlalchemy-rule.md`).
+
+## Rules
+
+### Do not query other tables inside `@property`
+- Category: [maintainability, performance]
+- Severity: critical
+- Description: A model `@property` must not open sessions or query other tables. This hides dependencies across models, tightly couples schema objects to data access, and can cause N+1 query explosions when iterating collections.
+- Suggested fix:
+  - Keep model properties pure and local to already-loaded fields.
+  - Move cross-table data fetching to service/repository methods.
+  - For list/batch reads, fetch required related data explicitly (join/preload/bulk query) before rendering derived values.
+- Example:
+  - Bad:
+    ```python
+    class Conversation(TypeBase):
+        __tablename__ = "conversations"
+
+        @property
+        def app_name(self) -> str:
+            with Session(db.engine, expire_on_commit=False) as session:
+                app = session.execute(select(App).where(App.id == self.app_id)).scalar_one()
+                return app.name
+    ```
+  - Good:
+    ```python
+    class Conversation(TypeBase):
+        __tablename__ = "conversations"
+
+        @property
+        def display_title(self) -> str:
+            return self.name or "Untitled"
+
+
+    # Service/repository layer performs explicit batch fetch for related App rows.
+    ```
+
+### Prefer including `tenant_id` in model definitions
+- Category: maintainability
+- Severity: suggestion
+- Description: In multi-tenant domains, include `tenant_id` in schema definitions whenever the entity belongs to tenant-owned data. This improves data isolation safety and keeps future partitioning/sharding strategies practical as data volume grows.
+- Suggested fix:
+  - Add a `tenant_id` column and ensure related unique/index constraints include tenant dimension when applicable.
+  - Propagate `tenant_id` through service/repository contracts to keep access paths tenant-aware.
+  - Exception: if a table is explicitly designed as non-tenant-scoped global metadata, document that design decision clearly.
+- Example:
+  - Bad:
+    ```python
+    from sqlalchemy.orm import Mapped
+
+    class Dataset(TypeBase):
+        __tablename__ = "datasets"
+        id: Mapped[str] = mapped_column(StringUUID, primary_key=True)
+        name: Mapped[str] = mapped_column(sa.String(255), nullable=False)
+    ```
+  - Good:
+    ```python
+    from sqlalchemy.orm import Mapped
+
+    class Dataset(TypeBase):
+        __tablename__ = "datasets"
+        id: Mapped[str] = mapped_column(StringUUID, primary_key=True)
+        tenant_id: Mapped[str] = mapped_column(StringUUID, nullable=False, index=True)
+        name: Mapped[str] = mapped_column(sa.String(255), nullable=False)
+    ```
+
+### Detect and avoid duplicate/redundant indexes
+- Category: performance
+- Severity: suggestion
+- Description: Review index definitions for leftmost-prefix redundancy. For example, index `(a, b, c)` can safely cover most lookups for `(a, b)`. Keeping both may increase write overhead and can mislead the optimizer into suboptimal execution plans.
+- Suggested fix:
+  - Before adding an index, compare against existing composite indexes by leftmost-prefix rules.
+  - Drop or avoid creating redundant prefixes unless there is a proven query-pattern need.
+  - Apply the same review standard in both model `__table_args__` and migration index DDL.
+- Example:
+  - Bad:
+    ```python
+    __table_args__ = (
+        sa.Index("idx_msg_tenant_app", "tenant_id", "app_id"),
+        sa.Index("idx_msg_tenant_app_created", "tenant_id", "app_id", "created_at"),
+    )
+    ```
+  - Good:
+    ```python
+    __table_args__ = (
+        # Keep the wider index unless profiling proves a dedicated short index is needed.
+        sa.Index("idx_msg_tenant_app_created", "tenant_id", "app_id", "created_at"),
+    )
+    ```
+
+### Avoid PostgreSQL-only dialect usage in models; wrap in `models.types`
+- Category: maintainability
+- Severity: critical
+- Description: Model/schema definitions should avoid PostgreSQL-only constructs directly in business models. When database-specific behavior is required, encapsulate it in `api/models/types.py` using both PostgreSQL and MySQL dialect implementations, then consume that abstraction from model code.
+- Suggested fix:
+  - Do not directly place dialect-only types/operators in model columns when a portable wrapper can be used.
+  - Add or extend wrappers in `models.types` (for example, `AdjustedJSON`, `LongText`, `BinaryData`) to normalize behavior across PostgreSQL and MySQL.
+- Example:
+  - Bad:
+    ```python
+    from sqlalchemy.dialects.postgresql import JSONB
+    from sqlalchemy.orm import Mapped
+
+    class ToolConfig(TypeBase):
+        __tablename__ = "tool_configs"
+        config: Mapped[dict] = mapped_column(JSONB, nullable=False)
+    ```
+  - Good:
+    ```python
+    from sqlalchemy.orm import Mapped
+
+    from models.types import AdjustedJSON
+
+    class ToolConfig(TypeBase):
+        __tablename__ = "tool_configs"
+        config: Mapped[dict] = mapped_column(AdjustedJSON(), nullable=False)
+    ```
+
+### Guard migration incompatibilities with dialect checks and shared types
+- Category: maintainability
+- Severity: critical
+- Description: Migration scripts under `api/migrations/versions/` must account for PostgreSQL/MySQL incompatibilities explicitly. For dialect-sensitive DDL or defaults, branch on the active dialect (for example, `conn.dialect.name == "postgresql"`), and prefer reusable compatibility abstractions from `models.types` where applicable.
+- Suggested fix:
+  - In migration upgrades/downgrades, bind connection and branch by dialect for incompatible SQL fragments.
+  - Reuse `models.types` wrappers in column definitions when that keeps behavior aligned with runtime models.
+  - Avoid one-dialect-only migration logic unless there is a documented, deliberate compatibility exception.
+- Example:
+  - Bad:
+    ```python
+    with op.batch_alter_table("dataset_keyword_tables") as batch_op:
+        batch_op.add_column(
+            sa.Column(
+                "data_source_type",
+                sa.String(255),
+                server_default=sa.text("'database'::character varying"),
+                nullable=False,
+            )
+        )
+    ```
+  - Good:
+    ```python
+    def _is_pg(conn) -> bool:
+        return conn.dialect.name == "postgresql"
+
+
+    conn = op.get_bind()
+    default_expr = sa.text("'database'::character varying") if _is_pg(conn) else sa.text("'database'")
+
+    with op.batch_alter_table("dataset_keyword_tables") as batch_op:
+        batch_op.add_column(
+            sa.Column("data_source_type", sa.String(255), server_default=default_expr, nullable=False)
+        )
+    ```

.agents/skills/backend-code-review/references/repositories-rule.md

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+# Rule Catalog - Repositories Abstraction
+
+## Scope
+- Covers: when to reuse existing repository abstractions, when to introduce new repositories, and how to preserve dependency direction between service/core and infrastructure implementations.
+- Does NOT cover: SQLAlchemy session lifecycle and query-shape specifics (handled by `sqlalchemy-rule.md`), and table schema/migration design (handled by `db-schema-rule.md`).
+
+## Rules
+
+### Introduce repositories abstraction
+- Category: maintainability
+- Severity: suggestion
+- Description: If a table/model already has a repository abstraction, all reads/writes/queries for that table should use the existing repository. If no repository exists, introduce one only when complexity justifies it, such as large/high-volume tables, repeated complex query logic, or likely storage-strategy variation.
+- Suggested fix:
+  - First check  `api/repositories`, `api/core/repositories`, and `api/extensions/*/repositories/` to verify whether the table/model already has a repository abstraction. If it exists, route all operations through it and add missing repository methods instead of bypassing it with ad-hoc SQLAlchemy access.
+  - If no repository exists, add one only when complexity warrants it (for example, repeated complex queries, large data domains, or multiple storage strategies), while preserving dependency direction (service/core depends on abstraction; infra provides implementation).
+- Example:
+  - Bad:
+    ```python
+    # Existing repository is ignored and service uses ad-hoc table queries.
+    class AppService:
+        def archive_app(self, app_id: str, tenant_id: str) -> None:
+            app = self.session.execute(
+                select(App).where(App.id == app_id, App.tenant_id == tenant_id)
+            ).scalar_one()
+            app.archived = True
+            self.session.commit()
+    ```
+  - Good:
+    ```python
+    # Case A: Existing repository must be reused for all table operations.
+    class AppService:
+        def archive_app(self, app_id: str, tenant_id: str) -> None:
+            app = self.app_repo.get_by_id(app_id=app_id, tenant_id=tenant_id)
+            app.archived = True
+            self.app_repo.save(app)
+
+    # If the query is missing, extend the existing abstraction.
+    active_apps = self.app_repo.list_active_for_tenant(tenant_id=tenant_id)
+    ```
+  - Bad:
+    ```python
+    # No repository exists, but large-domain query logic is scattered in service code.
+    class ConversationService:
+        def list_recent_for_app(self, app_id: str, tenant_id: str, limit: int) -> list[Conversation]:
+            ...
+            # many filters/joins/pagination variants duplicated across services
+    ```
+  - Good:
+    ```python
+    # Case B: Introduce repository for large/complex domains or storage variation.
+    class ConversationRepository(Protocol):
+        def list_recent_for_app(self, app_id: str, tenant_id: str, limit: int) -> list[Conversation]: ...
+
+    class SqlAlchemyConversationRepository:
+        def list_recent_for_app(self, app_id: str, tenant_id: str, limit: int) -> list[Conversation]:
+            ...
+
+    class ConversationService:
+        def __init__(self, conversation_repo: ConversationRepository):
+            self.conversation_repo = conversation_repo
+    ```

.agents/skills/backend-code-review/references/sqlalchemy-rule.md

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+# Rule Catalog — SQLAlchemy Patterns
+
+## Scope
+- Covers: SQLAlchemy session and transaction lifecycle, query construction, tenant scoping, raw SQL boundaries, and write-path concurrency safeguards.
+- Does NOT cover: table/model schema and migration design details (handled by `db-schema-rule.md`).
+
+## Rules
+
+### Use Session context manager with explicit transaction control behavior
+- Category: best practices
+- Severity: critical
+- Description: Session and transaction lifecycle must be explicit and bounded on write paths. Missing commits can silently drop intended updates, while ad-hoc or long-lived transactions increase contention, lock duration, and deadlock risk.
+- Suggested fix:
+  - Use **explicit `session.commit()`** after completing a related write unit.
+  - Or use **`session.begin()` context manager** for automatic commit/rollback on a scoped block.
+  - Keep transaction windows short: avoid network I/O, heavy computation, or unrelated work inside the transaction.
+- Example:
+  - Bad:
+    ```python
+    # Missing commit: write may never be persisted.
+    with Session(db.engine, expire_on_commit=False) as session:
+        run = session.get(WorkflowRun, run_id)
+        run.status = "cancelled"
+
+    # Long transaction: external I/O inside a DB transaction.
+    with Session(db.engine, expire_on_commit=False) as session, session.begin():
+        run = session.get(WorkflowRun, run_id)
+        run.status = "cancelled"
+        call_external_api()
+    ```
+  - Good:
+    ```python
+    # Option 1: explicit commit.
+    with Session(db.engine, expire_on_commit=False) as session:
+        run = session.get(WorkflowRun, run_id)
+        run.status = "cancelled"
+        session.commit()
+
+    # Option 2: scoped transaction with automatic commit/rollback.
+    with Session(db.engine, expire_on_commit=False) as session, session.begin():
+        run = session.get(WorkflowRun, run_id)
+        run.status = "cancelled"
+
+    # Keep non-DB work outside transaction scope.
+    call_external_api()
+    ```
+
+### Enforce tenant_id scoping on shared-resource queries
+- Category: security
+- Severity: critical
+- Description: Reads and writes against shared tables must be scoped by `tenant_id` to prevent cross-tenant data leakage or corruption.
+- Suggested fix: Add `tenant_id` predicate to all tenant-owned entity queries and propagate tenant context through service/repository interfaces.
+- Example:
+  - Bad:
+    ```python
+    stmt = select(Workflow).where(Workflow.id == workflow_id)
+    workflow = session.execute(stmt).scalar_one_or_none()
+    ```
+  - Good:
+    ```python
+    stmt = select(Workflow).where(
+        Workflow.id == workflow_id,
+        Workflow.tenant_id == tenant_id,
+    )
+    workflow = session.execute(stmt).scalar_one_or_none()
+    ```
+
+### Prefer SQLAlchemy expressions over raw SQL by default
+- Category: maintainability
+- Severity: suggestion
+- Description: Raw SQL should be exceptional. ORM/Core expressions are easier to evolve, safer to compose, and more consistent with the codebase.
+- Suggested fix: Rewrite straightforward raw SQL into SQLAlchemy `select/update/delete` expressions; keep raw SQL only when required by clear technical constraints.
+- Example:
+  - Bad:
+    ```python
+    row = session.execute(
+        text("SELECT * FROM workflows WHERE id = :id AND tenant_id = :tenant_id"),
+        {"id": workflow_id, "tenant_id": tenant_id},
+    ).first()
+    ```
+  - Good:
+    ```python
+    stmt = select(Workflow).where(
+        Workflow.id == workflow_id,
+        Workflow.tenant_id == tenant_id,
+    )
+    row = session.execute(stmt).scalar_one_or_none()
+    ```
+
+### Protect write paths with concurrency safeguards
+- Category: quality
+- Severity: critical
+- Description: Multi-writer paths without explicit concurrency control can silently overwrite data. Choose the safeguard based on contention level, lock scope, and throughput cost instead of defaulting to one strategy.
+- Suggested fix:
+  - **Optimistic locking**: Use when contention is usually low and retries are acceptable. Add a version (or updated_at) guard in `WHERE` and treat `rowcount == 0` as a conflict.
+  - **Redis distributed lock**: Use when the critical section spans multiple steps/processes (or includes non-DB side effects) and you need cross-worker mutual exclusion.
+  - **SELECT ... FOR UPDATE**: Use when contention is high on the same rows and strict in-transaction serialization is required. Keep transactions short to reduce lock wait/deadlock risk.
+  - In all cases, scope by `tenant_id` and verify affected row counts for conditional writes.
+- Example:
+  - Bad:
+    ```python
+    # No tenant scope, no conflict detection, and no lock on a contested write path.
+    session.execute(update(WorkflowRun).where(WorkflowRun.id == run_id).values(status="cancelled"))
+    session.commit()  # silently overwrites concurrent updates
+    ```
+  - Good:
+    ```python
+    # 1) Optimistic lock (low contention, retry on conflict)
+    result = session.execute(
+        update(WorkflowRun)
+        .where(
+            WorkflowRun.id == run_id,
+            WorkflowRun.tenant_id == tenant_id,
+            WorkflowRun.version == expected_version,
+        )
+        .values(status="cancelled", version=WorkflowRun.version + 1)
+    )
+    if result.rowcount == 0:
+        raise WorkflowStateConflictError("stale version, retry")
+
+    # 2) Redis distributed lock (cross-worker critical section)
+    lock_name = f"workflow_run_lock:{tenant_id}:{run_id}"
+    with redis_client.lock(lock_name, timeout=20):
+        session.execute(
+            update(WorkflowRun)
+            .where(WorkflowRun.id == run_id, WorkflowRun.tenant_id == tenant_id)
+            .values(status="cancelled")
+        )
+        session.commit()
+
+    # 3) Pessimistic lock with SELECT ... FOR UPDATE (high contention)
+    run = session.execute(
+        select(WorkflowRun)
+        .where(WorkflowRun.id == run_id, WorkflowRun.tenant_id == tenant_id)
+        .with_for_update()
+    ).scalar_one()
+    run.status = "cancelled"
+    session.commit()
+    ```

.claude/skills/backend-code-review

@@ -0,0 +1 @@
+../../.agents/skills/backend-code-review

.github/dependabot.yml

@@ -1,12 +1,25 @@
 version: 2
+
+multi-ecosystem-groups:
+  python:
+    schedule:
+      interval: "weekly"  # or whatever schedule you want
+
 updates:
+  - package-ecosystem: "pip"
+    directory: "/api"
+    open-pull-requests-limit: 2
+    patterns: ["*"]
+    schedule:
+      interval: "weekly"
+  - package-ecosystem: "uv"
+    directory: "/api"
+    open-pull-requests-limit: 2
+    patterns: ["*"]
+    schedule:
+      interval: "weekly"
   - package-ecosystem: "npm"
     directory: "/web"
     schedule:
       interval: "weekly"
     open-pull-requests-limit: 2
-  - package-ecosystem: "uv"
-    directory: "/api"
-    schedule:
-      interval: "weekly"
-    open-pull-requests-limit: 2

.github/workflows/pyrefly-diff-comment.yml

@@ -0,0 +1,88 @@
+name: Comment with Pyrefly Diff
+
+on:
+  workflow_run:
+    workflows:
+      - Pyrefly Diff Check
+    types:
+      - completed
+
+permissions: {}
+
+jobs:
+  comment:
+    name: Comment PR with pyrefly diff
+    runs-on: ubuntu-latest
+    permissions:
+      actions: read
+      contents: read
+      issues: write
+      pull-requests: write
+    if: ${{ github.event.workflow_run.conclusion == 'success' && github.event.workflow_run.pull_requests[0].head.repo.full_name != github.repository }}
+    steps:
+      - name: Download pyrefly diff artifact
+        uses: actions/github-script@v8
+        with:
+          github-token: ${{ secrets.GITHUB_TOKEN }}
+          script: |
+            const fs = require('fs');
+            const artifacts = await github.rest.actions.listWorkflowRunArtifacts({
+              owner: context.repo.owner,
+              repo: context.repo.repo,
+              run_id: ${{ github.event.workflow_run.id }},
+            });
+            const match = artifacts.data.artifacts.find((artifact) =>
+              artifact.name === 'pyrefly_diff'
+            );
+            if (!match) {
+              throw new Error('pyrefly_diff artifact not found');
+            }
+            const download = await github.rest.actions.downloadArtifact({
+              owner: context.repo.owner,
+              repo: context.repo.repo,
+              artifact_id: match.id,
+              archive_format: 'zip',
+            });
+            fs.writeFileSync('pyrefly_diff.zip', Buffer.from(download.data));
+
+      - name: Unzip artifact
+        run: unzip -o pyrefly_diff.zip
+
+      - name: Post comment
+        uses: actions/github-script@v8
+        with:
+          github-token: ${{ secrets.GITHUB_TOKEN }}
+          script: |
+            const fs = require('fs');
+            let diff = fs.readFileSync('pyrefly_diff.txt', { encoding: 'utf8' });
+            let prNumber = null;
+            try {
+              prNumber = parseInt(fs.readFileSync('pr_number.txt', { encoding: 'utf8' }), 10);
+            } catch (err) {
+              // Fallback to workflow_run payload if artifact is missing or incomplete.
+              const prs = context.payload.workflow_run.pull_requests || [];
+              if (prs.length > 0 && prs[0].number) {
+                prNumber = prs[0].number;
+              }
+            }
+            if (!prNumber) {
+              throw new Error('PR number not found in artifact or workflow_run payload');
+            }
+
+            const MAX_CHARS = 65000;
+            if (diff.length > MAX_CHARS) {
+              diff = diff.slice(0, MAX_CHARS);
+              diff = diff.slice(0, diff.lastIndexOf('\\n'));
+              diff += '\\n\\n... (truncated) ...';
+            }
+
+            const body = diff.trim()
+              ? '### Pyrefly Diff\n<details>\n<summary>base → PR</summary>\n\n```diff\n' + diff + '\n```\n</details>'
+              : '### Pyrefly Diff\nNo changes detected.';
+
+            await github.rest.issues.createComment({
+              issue_number: prNumber,
+              owner: context.repo.owner,
+              repo: context.repo.repo,
+              body,
+            });

.github/workflows/pyrefly-diff.yml

@@ -0,0 +1,94 @@
+name: Pyrefly Diff Check
+
+on:
+  pull_request:
+    paths:
+      - 'api/**/*.py'
+
+permissions:
+  contents: read
+
+jobs:
+  pyrefly-diff:
+    runs-on: ubuntu-latest
+    permissions:
+      contents: read
+      issues: write
+      pull-requests: write
+    steps:
+      - name: Checkout PR branch
+        uses: actions/checkout@v6
+        with:
+          fetch-depth: 0
+
+      - name: Setup Python & UV
+        uses: astral-sh/setup-uv@v5
+        with:
+          enable-cache: true
+
+      - name: Install dependencies
+        run: uv sync --project api --dev
+
+      - name: Run pyrefly on PR branch
+        run: |
+          uv run --directory api pyrefly check > /tmp/pyrefly_pr.txt 2>&1 || true
+
+      - name: Checkout base branch
+        run: git checkout ${{ github.base_ref }}
+
+      - name: Run pyrefly on base branch
+        run: |
+          uv run --directory api pyrefly check > /tmp/pyrefly_base.txt 2>&1 || true
+
+      - name: Compute diff
+        run: |
+          diff /tmp/pyrefly_base.txt /tmp/pyrefly_pr.txt > pyrefly_diff.txt || true
+
+      - name: Save PR number
+        run: |
+          echo ${{ github.event.pull_request.number }} > pr_number.txt
+
+      - name: Upload pyrefly diff
+        uses: actions/upload-artifact@v4
+        with:
+          name: pyrefly_diff
+          path: |
+            pyrefly_diff.txt
+            pr_number.txt
+
+      - name: Comment PR with pyrefly diff
+        if: ${{ github.event.pull_request.head.repo.full_name == github.repository }}
+        uses: actions/github-script@v8
+        with:
+          github-token: ${{ secrets.GITHUB_TOKEN }}
+          script: |
+            const fs = require('fs');
+            let diff = fs.readFileSync('pyrefly_diff.txt', { encoding: 'utf8' });
+            const prNumber = context.payload.pull_request.number;
+
+            const MAX_CHARS = 65000;
+            if (diff.length > MAX_CHARS) {
+              diff = diff.slice(0, MAX_CHARS);
+              diff = diff.slice(0, diff.lastIndexOf('\n'));
+              diff += '\n\n... (truncated) ...';
+            }
+
+            const body = diff.trim()
+              ? [
+                  '### Pyrefly Diff',
+                  '<details>',
+                  '<summary>base → PR</summary>',
+                  '',
+                  '```diff',
+                  diff,
+                  '```',
+                  '</details>',
+                ].join('\n')
+              : '### Pyrefly Diff\nNo changes detected.';
+
+            await github.rest.issues.createComment({
+              issue_number: prNumber,
+              owner: context.repo.owner,
+              repo: context.repo.repo,
+              body,
+            });

.github/workflows/web-tests.yml

@@ -3,14 +3,22 @@ name: Web Tests
 on:
   workflow_call:
 
+permissions:
+  contents: read
+
 concurrency:
   group: web-tests-${{ github.head_ref || github.run_id }}
   cancel-in-progress: true
 
 jobs:
   test:
-    name: Web Tests
+    name: Web Tests (${{ matrix.shardIndex }}/${{ matrix.shardTotal }})
     runs-on: ubuntu-latest
+    strategy:
+      fail-fast: false
+      matrix:
+        shardIndex: [1, 2, 3, 4]
+        shardTotal: [4]
     defaults:
       run:
         shell: bash
@@ -39,7 +47,58 @@ jobs:
         run: pnpm install --frozen-lockfile
 
       - name: Run tests
-        run: pnpm test:ci
+        run: pnpm vitest run --reporter=blob --shard=${{ matrix.shardIndex }}/${{ matrix.shardTotal }} --coverage
+
+      - name: Upload blob report
+        if: ${{ !cancelled() }}
+        uses: actions/upload-artifact@v6
+        with:
+          name: blob-report-${{ matrix.shardIndex }}
+          path: web/.vitest-reports/*
+          include-hidden-files: true
+          retention-days: 1
+
+  merge-reports:
+    name: Merge Test Reports
+    if: ${{ !cancelled() }}
+    needs: [test]
+    runs-on: ubuntu-latest
+    defaults:
+      run:
+        shell: bash
+        working-directory: ./web
+
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v6
+        with:
+          persist-credentials: false
+
+      - name: Install pnpm
+        uses: pnpm/action-setup@v4
+        with:
+          package_json_file: web/package.json
+          run_install: false
+
+      - name: Setup Node.js
+        uses: actions/setup-node@v6
+        with:
+          node-version: 24
+          cache: pnpm
+          cache-dependency-path: ./web/pnpm-lock.yaml
+
+      - name: Install dependencies
+        run: pnpm install --frozen-lockfile
+
+      - name: Download blob reports
+        uses: actions/download-artifact@v6
+        with:
+          path: web/.vitest-reports
+          pattern: blob-report-*
+          merge-multiple: true
+
+      - name: Merge reports
+        run: pnpm vitest --merge-reports --coverage --silent=passed-only
 
       - name: Coverage Summary
         if: always()

README.md

@@ -1,9 +1,5 @@
 ![cover-v5-optimized](./images/GitHub_README_if.png)
 
-<p align="center">
-  📌 <a href="https://dify.ai/blog/introducing-dify-workflow-file-upload-a-demo-on-ai-podcast">Introducing Dify Workflow File Upload: Recreate Google NotebookLM Podcast</a>
-</p>
-
 <p align="center">
   <a href="https://cloud.dify.ai">Dify Cloud</a> ·
   <a href="https://docs.dify.ai/getting-started/install-self-hosted">Self-hosting</a> ·

api/.env.example

@@ -553,6 +553,8 @@ WORKFLOW_LOG_CLEANUP_ENABLED=false
 WORKFLOW_LOG_RETENTION_DAYS=30
 # Batch size for workflow log cleanup operations (default: 100)
 WORKFLOW_LOG_CLEANUP_BATCH_SIZE=100
+# Comma-separated list of workflow IDs to clean logs for
+WORKFLOW_LOG_CLEANUP_SPECIFIC_WORKFLOW_IDS=
 
 # App configuration
 APP_MAX_EXECUTION_TIME=1200
@@ -715,6 +717,7 @@ ANNOTATION_IMPORT_MAX_CONCURRENT=5
 # Sandbox expired records clean configuration
 SANDBOX_EXPIRED_RECORDS_CLEAN_GRACEFUL_PERIOD=21
 SANDBOX_EXPIRED_RECORDS_CLEAN_BATCH_SIZE=1000
+SANDBOX_EXPIRED_RECORDS_CLEAN_BATCH_MAX_INTERVAL=200
 SANDBOX_EXPIRED_RECORDS_RETENTION_DAYS=30
 SANDBOX_EXPIRED_RECORDS_CLEAN_TASK_LOCK_TTL=90000
 

api/.importlinter

@@ -50,14 +50,11 @@ forbidden_modules =
 allow_indirect_imports = True
 ignore_imports =
     core.workflow.nodes.agent.agent_node -> extensions.ext_database
-    core.workflow.nodes.datasource.datasource_node -> extensions.ext_database
     core.workflow.nodes.knowledge_index.knowledge_index_node -> extensions.ext_database
     core.workflow.nodes.llm.file_saver -> extensions.ext_database
     core.workflow.nodes.llm.llm_utils -> extensions.ext_database
     core.workflow.nodes.llm.node -> extensions.ext_database
     core.workflow.nodes.tool.tool_node -> extensions.ext_database
-    core.workflow.graph_engine.command_channels.redis_channel -> extensions.ext_redis
-    core.workflow.graph_engine.manager -> extensions.ext_redis
     # TODO(QuantumGhost): use DI to avoid depending on global DB.
     core.workflow.nodes.human_input.human_input_node -> extensions.ext_database
 
@@ -91,7 +88,6 @@ forbidden_modules =
     core.logging
     core.mcp
     core.memory
-    core.model_manager
     core.moderation
     core.ops
     core.plugin
@@ -105,29 +101,17 @@ forbidden_modules =
     core.variables
 ignore_imports =
     core.workflow.nodes.loop.loop_node -> core.app.workflow.node_factory
-    core.workflow.graph_engine.command_channels.redis_channel -> extensions.ext_redis
     core.workflow.workflow_entry -> core.app.workflow.layers.observability
     core.workflow.nodes.agent.agent_node -> core.model_manager
     core.workflow.nodes.agent.agent_node -> core.provider_manager
     core.workflow.nodes.agent.agent_node -> core.tools.tool_manager
-    core.workflow.nodes.code.code_node -> core.helper.code_executor.code_executor
-    core.workflow.nodes.datasource.datasource_node -> models.model
-    core.workflow.nodes.datasource.datasource_node -> models.tools
-    core.workflow.nodes.datasource.datasource_node -> services.datasource_provider_service
-    core.workflow.nodes.document_extractor.node -> configs
-    core.workflow.nodes.document_extractor.node -> core.file.file_manager
     core.workflow.nodes.document_extractor.node -> core.helper.ssrf_proxy
-    core.workflow.nodes.http_request.entities -> configs
-    core.workflow.nodes.http_request.executor -> configs
-    core.workflow.nodes.http_request.executor -> core.file.file_manager
-    core.workflow.nodes.http_request.node -> configs
     core.workflow.nodes.http_request.node -> core.tools.tool_file_manager
     core.workflow.nodes.iteration.iteration_node -> core.app.workflow.node_factory
     core.workflow.nodes.knowledge_index.knowledge_index_node -> core.rag.index_processor.index_processor_factory
     core.workflow.nodes.llm.llm_utils -> configs
-    core.workflow.nodes.llm.llm_utils -> core.app.entities.app_invoke_entities
-    core.workflow.nodes.llm.llm_utils -> core.file.models
     core.workflow.nodes.llm.llm_utils -> core.model_manager
+    core.workflow.nodes.llm.protocols -> core.model_manager
     core.workflow.nodes.llm.llm_utils -> core.model_runtime.model_providers.__base.large_language_model
     core.workflow.nodes.llm.llm_utils -> models.model
     core.workflow.nodes.llm.llm_utils -> models.provider
@@ -144,60 +128,25 @@ ignore_imports =
     core.workflow.nodes.human_input.human_input_node -> core.app.entities.app_invoke_entities
     core.workflow.nodes.knowledge_index.knowledge_index_node -> core.app.entities.app_invoke_entities
     core.workflow.nodes.knowledge_retrieval.knowledge_retrieval_node -> core.app.app_config.entities
-    core.workflow.nodes.llm.node -> core.app.entities.app_invoke_entities
-    core.workflow.nodes.parameter_extractor.parameter_extractor_node -> core.app.entities.app_invoke_entities
     core.workflow.nodes.parameter_extractor.parameter_extractor_node -> core.prompt.advanced_prompt_transform
     core.workflow.nodes.parameter_extractor.parameter_extractor_node -> core.prompt.simple_prompt_transform
     core.workflow.nodes.parameter_extractor.parameter_extractor_node -> core.model_runtime.model_providers.__base.large_language_model
-    core.workflow.nodes.question_classifier.question_classifier_node -> core.app.entities.app_invoke_entities
-    core.workflow.nodes.question_classifier.question_classifier_node -> core.prompt.advanced_prompt_transform
     core.workflow.nodes.question_classifier.question_classifier_node -> core.prompt.simple_prompt_transform
     core.workflow.nodes.start.entities -> core.app.app_config.entities
     core.workflow.nodes.start.start_node -> core.app.app_config.entities
     core.workflow.workflow_entry -> core.app.apps.exc
     core.workflow.workflow_entry -> core.app.entities.app_invoke_entities
     core.workflow.workflow_entry -> core.app.workflow.node_factory
-    core.workflow.nodes.datasource.datasource_node -> core.datasource.datasource_manager
-    core.workflow.nodes.datasource.datasource_node -> core.datasource.utils.message_transformer
     core.workflow.nodes.llm.llm_utils -> core.entities.provider_entities
     core.workflow.nodes.parameter_extractor.parameter_extractor_node -> core.model_manager
     core.workflow.nodes.question_classifier.question_classifier_node -> core.model_manager
-    core.workflow.node_events.node -> core.file
-    core.workflow.nodes.agent.agent_node -> core.file
-    core.workflow.nodes.datasource.datasource_node -> core.file
-    core.workflow.nodes.datasource.datasource_node -> core.file.enums
-    core.workflow.nodes.document_extractor.node -> core.file
-    core.workflow.nodes.http_request.executor -> core.file.enums
-    core.workflow.nodes.http_request.node -> core.file
-    core.workflow.nodes.http_request.node -> core.file.file_manager
-    core.workflow.nodes.knowledge_retrieval.knowledge_retrieval_node -> core.file.models
-    core.workflow.nodes.list_operator.node -> core.file
-    core.workflow.nodes.llm.file_saver -> core.file
-    core.workflow.nodes.llm.llm_utils -> core.variables.segments
-    core.workflow.nodes.llm.node -> core.file
-    core.workflow.nodes.llm.node -> core.file.file_manager
-    core.workflow.nodes.llm.node -> core.file.models
-    core.workflow.nodes.loop.entities -> core.variables.types
-    core.workflow.nodes.parameter_extractor.parameter_extractor_node -> core.file
-    core.workflow.nodes.protocols -> core.file
-    core.workflow.nodes.question_classifier.question_classifier_node -> core.file.models
-    core.workflow.nodes.tool.tool_node -> core.file
     core.workflow.nodes.tool.tool_node -> core.tools.utils.message_transformer
     core.workflow.nodes.tool.tool_node -> models
-    core.workflow.nodes.trigger_webhook.node -> core.file
-    core.workflow.runtime.variable_pool -> core.file
-    core.workflow.runtime.variable_pool -> core.file.file_manager
-    core.workflow.system_variable -> core.file.models
-    core.workflow.utils.condition.processor -> core.file
-    core.workflow.utils.condition.processor -> core.file.file_manager
-    core.workflow.workflow_entry -> core.file.models
-    core.workflow.workflow_type_encoder -> core.file.models
     core.workflow.nodes.agent.agent_node -> models.model
     core.workflow.nodes.code.code_node -> core.helper.code_executor.code_node_provider
     core.workflow.nodes.code.code_node -> core.helper.code_executor.javascript.javascript_code_provider
     core.workflow.nodes.code.code_node -> core.helper.code_executor.python3.python3_code_provider
     core.workflow.nodes.code.entities -> core.helper.code_executor.code_executor
-    core.workflow.nodes.datasource.datasource_node -> core.variables.variables
     core.workflow.nodes.http_request.executor -> core.helper.ssrf_proxy
     core.workflow.nodes.http_request.node -> core.helper.ssrf_proxy
     core.workflow.nodes.llm.file_saver -> core.helper.ssrf_proxy
@@ -227,58 +176,7 @@ ignore_imports =
     core.workflow.nodes.llm.file_saver -> core.tools.signature
     core.workflow.nodes.llm.file_saver -> core.tools.tool_file_manager
     core.workflow.nodes.tool.tool_node -> core.tools.errors
-    core.workflow.conversation_variable_updater -> core.variables
-    core.workflow.graph_engine.entities.commands -> core.variables.variables
-    core.workflow.nodes.agent.agent_node -> core.variables.segments
-    core.workflow.nodes.answer.answer_node -> core.variables
-    core.workflow.nodes.code.code_node -> core.variables.segments
-    core.workflow.nodes.code.code_node -> core.variables.types
-    core.workflow.nodes.code.entities -> core.variables.types
-    core.workflow.nodes.datasource.datasource_node -> core.variables.segments
-    core.workflow.nodes.document_extractor.node -> core.variables
-    core.workflow.nodes.document_extractor.node -> core.variables.segments
-    core.workflow.nodes.http_request.executor -> core.variables.segments
-    core.workflow.nodes.http_request.node -> core.variables.segments
-    core.workflow.nodes.human_input.entities -> core.variables.consts
-    core.workflow.nodes.iteration.iteration_node -> core.variables
-    core.workflow.nodes.iteration.iteration_node -> core.variables.segments
-    core.workflow.nodes.iteration.iteration_node -> core.variables.variables
-    core.workflow.nodes.knowledge_retrieval.knowledge_retrieval_node -> core.variables
-    core.workflow.nodes.knowledge_retrieval.knowledge_retrieval_node -> core.variables.segments
-    core.workflow.nodes.list_operator.node -> core.variables
-    core.workflow.nodes.list_operator.node -> core.variables.segments
-    core.workflow.nodes.llm.node -> core.variables
-    core.workflow.nodes.loop.loop_node -> core.variables
-    core.workflow.nodes.parameter_extractor.entities -> core.variables.types
-    core.workflow.nodes.parameter_extractor.exc -> core.variables.types
-    core.workflow.nodes.parameter_extractor.parameter_extractor_node -> core.variables.types
-    core.workflow.nodes.tool.tool_node -> core.variables.segments
-    core.workflow.nodes.tool.tool_node -> core.variables.variables
-    core.workflow.nodes.trigger_webhook.node -> core.variables.types
-    core.workflow.nodes.trigger_webhook.node -> core.variables.variables
-    core.workflow.nodes.variable_aggregator.entities -> core.variables.types
-    core.workflow.nodes.variable_aggregator.variable_aggregator_node -> core.variables.segments
-    core.workflow.nodes.variable_assigner.common.helpers -> core.variables
-    core.workflow.nodes.variable_assigner.common.helpers -> core.variables.consts
-    core.workflow.nodes.variable_assigner.common.helpers -> core.variables.types
-    core.workflow.nodes.variable_assigner.v1.node -> core.variables
-    core.workflow.nodes.variable_assigner.v2.helpers -> core.variables
-    core.workflow.nodes.variable_assigner.v2.node -> core.variables
-    core.workflow.nodes.variable_assigner.v2.node -> core.variables.consts
-    core.workflow.runtime.graph_runtime_state_protocol -> core.variables.segments
-    core.workflow.runtime.read_only_wrappers -> core.variables.segments
-    core.workflow.runtime.variable_pool -> core.variables
-    core.workflow.runtime.variable_pool -> core.variables.consts
-    core.workflow.runtime.variable_pool -> core.variables.segments
-    core.workflow.runtime.variable_pool -> core.variables.variables
-    core.workflow.utils.condition.processor -> core.variables
-    core.workflow.utils.condition.processor -> core.variables.segments
-    core.workflow.variable_loader -> core.variables
-    core.workflow.variable_loader -> core.variables.consts
-    core.workflow.workflow_type_encoder -> core.variables
-    core.workflow.graph_engine.manager -> extensions.ext_redis
     core.workflow.nodes.agent.agent_node -> extensions.ext_database
-    core.workflow.nodes.datasource.datasource_node -> extensions.ext_database
     core.workflow.nodes.knowledge_index.knowledge_index_node -> extensions.ext_database
     core.workflow.nodes.llm.file_saver -> extensions.ext_database
     core.workflow.nodes.llm.llm_utils -> extensions.ext_database

api/.vscode/launch.json.example

@@ -54,7 +54,7 @@
                 "--loglevel",
                 "DEBUG",
                 "-Q",
-                "dataset,priority_pipeline,pipeline,mail,ops_trace,app_deletion,plugin,workflow_storage,conversation,workflow,schedule_poller,schedule_executor,triggered_workflow_dispatcher,trigger_refresh_executor"
+                "dataset,priority_pipeline,pipeline,mail,ops_trace,app_deletion,plugin,workflow_storage,conversation,workflow,workflow_based_app_execution,schedule_poller,schedule_executor,triggered_workflow_dispatcher,trigger_refresh_executor"
             ]
         }
     ]

api/README.md

@@ -42,7 +42,7 @@ The scripts resolve paths relative to their location, so you can run them from a
 
 1. Set up your application by visiting `http://localhost:3000`.
 
-1. Optional: start the worker service (async tasks, runs from `api`).
+1. Start the worker service (async and scheduler tasks, runs from `api`).
 
    ```bash
    ./dev/start-worker
@@ -54,86 +54,6 @@ The scripts resolve paths relative to their location, so you can run them from a
    ./dev/start-beat
    ```
 
-### Manual commands
-
-<details>
-<summary>Show manual setup and run steps</summary>
-
-These commands assume you start from the repository root.
-
-1. Start the docker-compose stack.
-
-   The backend requires middleware, including PostgreSQL, Redis, and Weaviate, which can be started together using `docker-compose`.
-
-   ```bash
-   cp docker/middleware.env.example docker/middleware.env
-   # Use mysql or another vector database profile if you are not using postgres/weaviate.
-   docker compose -f docker/docker-compose.middleware.yaml --profile postgresql --profile weaviate -p dify up -d
-   ```
-
-1. Copy env files.
-
-   ```bash
-   cp api/.env.example api/.env
-   cp web/.env.example web/.env.local
-   ```
-
-1. Install UV if needed.
-
-   ```bash
-   pip install uv
-   # Or on macOS
-   brew install uv
-   ```
-
-1. Install API dependencies.
-
-   ```bash
-   cd api
-   uv sync --group dev
-   ```
-
-1. Install web dependencies.
-
-   ```bash
-   cd web
-   pnpm install
-   cd ..
-   ```
-
-1. Start backend (runs migrations first, in a new terminal).
-
-   ```bash
-   cd api
-   uv run flask db upgrade
-   uv run flask run --host 0.0.0.0 --port=5001 --debug
-   ```
-
-1. Start Dify [web](../web) service (in a new terminal).
-
-   ```bash
-   cd web
-   pnpm dev:inspect
-   ```
-
-1. Set up your application by visiting `http://localhost:3000`.
-
-1. Optional: start the worker service (async tasks, in a new terminal).
-
-   ```bash
-   cd api
-   uv run celery -A app.celery worker -P threads -c 2 --loglevel INFO -Q api_token,dataset,priority_dataset,priority_pipeline,pipeline,mail,ops_trace,app_deletion,plugin,workflow_storage,conversation,workflow,schedule_poller,schedule_executor,triggered_workflow_dispatcher,trigger_refresh_executor,retention
-   ```
-
-1. Optional: start Celery Beat (scheduled tasks, in a new terminal).
-
-   ```bash
-   cd api
-   uv run celery -A app.celery beat
-   ```
-
-</details>
-
 ### Environment notes
 
 > [!IMPORTANT]

api/commands.py

@@ -30,6 +30,7 @@ from extensions.ext_redis import redis_client
 from extensions.ext_storage import storage
 from extensions.storage.opendal_storage import OpenDALStorage
 from extensions.storage.storage_type import StorageType
+from libs.db_migration_lock import DbMigrationAutoRenewLock
 from libs.helper import email as email_validate
 from libs.password import hash_password, password_pattern, valid_password
 from libs.rsa import generate_key_pair
@@ -54,6 +55,8 @@ from tasks.remove_app_and_related_data_task import delete_draft_variables_batch
 
 logger = logging.getLogger(__name__)
 
+DB_UPGRADE_LOCK_TTL_SECONDS = 60
+
 
 @click.command("reset-password", help="Reset the account password.")
 @click.option("--email", prompt=True, help="Account email to reset password for")
@@ -727,8 +730,15 @@ def create_tenant(email: str, language: str | None = None, name: str | None = No
 @click.command("upgrade-db", help="Upgrade the database")
 def upgrade_db():
     click.echo("Preparing database migration...")
-    lock = redis_client.lock(name="db_upgrade_lock", timeout=60)
+    lock = DbMigrationAutoRenewLock(
+        redis_client=redis_client,
+        name="db_upgrade_lock",
+        ttl_seconds=DB_UPGRADE_LOCK_TTL_SECONDS,
+        logger=logger,
+        log_context="db_migration",
+    )
     if lock.acquire(blocking=False):
+        migration_succeeded = False
         try:
             click.echo(click.style("Starting database migration.", fg="green"))
 
@@ -737,6 +747,7 @@ def upgrade_db():
 
             flask_migrate.upgrade()
 
+            migration_succeeded = True
             click.echo(click.style("Database migration successful!", fg="green"))
 
         except Exception as e:
@@ -744,7 +755,8 @@ def upgrade_db():
             click.echo(click.style(f"Database migration failed: {e}", fg="red"))
             raise SystemExit(1)
         finally:
-            lock.release()
+            status = "successful" if migration_succeeded else "failed"
+            lock.release_safely(status=status)
     else:
         click.echo("Database migration skipped")
 

api/configs/feature/__init__.py

@@ -265,6 +265,11 @@ class PluginConfig(BaseSettings):
         default=60 * 60,
     )
 
+    PLUGIN_MAX_FILE_SIZE: PositiveInt = Field(
+        description="Maximum allowed size (bytes) for plugin-generated files",
+        default=50 * 1024 * 1024,
+    )
+
 
 class MarketplaceConfig(BaseSettings):
     """
@@ -1314,6 +1319,9 @@ class WorkflowLogConfig(BaseSettings):
     WORKFLOW_LOG_CLEANUP_BATCH_SIZE: int = Field(
         default=100, description="Batch size for workflow run log cleanup operations"
     )
+    WORKFLOW_LOG_CLEANUP_SPECIFIC_WORKFLOW_IDS: str = Field(
+        default="", description="Comma-separated list of workflow IDs to clean logs for"
+    )
 
 
 class SwaggerUIConfig(BaseSettings):
@@ -1344,6 +1352,10 @@ class SandboxExpiredRecordsCleanConfig(BaseSettings):
         description="Maximum number of records to process in each batch",
         default=1000,
     )
+    SANDBOX_EXPIRED_RECORDS_CLEAN_BATCH_MAX_INTERVAL: PositiveInt = Field(
+        description="Maximum interval in milliseconds between batches",
+        default=200,
+    )
     SANDBOX_EXPIRED_RECORDS_RETENTION_DAYS: PositiveInt = Field(
         description="Retention days for sandbox expired workflow_run records and message records",
         default=30,

api/configs/middleware/__init__.py

@@ -259,11 +259,20 @@ class CeleryConfig(DatabaseConfig):
         description="Password of the Redis Sentinel master.",
         default=None,
     )
+
     CELERY_SENTINEL_SOCKET_TIMEOUT: PositiveFloat | None = Field(
         description="Timeout for Redis Sentinel socket operations in seconds.",
         default=0.1,
     )
 
+    CELERY_TASK_ANNOTATIONS: dict[str, Any] | None = Field(
+        description=(
+            "Annotations for Celery tasks as a JSON mapping of task name -> options "
+            "(for example, rate limits or other task-specific settings)."
+        ),
+        default=None,
+    )
+
     @computed_field
     def CELERY_RESULT_BACKEND(self) -> str | None:
         if self.CELERY_BACKEND in ("database", "rabbitmq"):

api/configs/middleware/vdb/oceanbase_config.py

@@ -1,3 +1,5 @@
+from typing import Literal
+
 from pydantic import Field, PositiveInt
 from pydantic_settings import BaseSettings
 
@@ -49,3 +51,43 @@ class OceanBaseVectorConfig(BaseSettings):
         ),
         default="ik",
     )
+
+    OCEANBASE_VECTOR_BATCH_SIZE: PositiveInt = Field(
+        description="Number of documents to insert per batch",
+        default=100,
+    )
+
+    OCEANBASE_VECTOR_METRIC_TYPE: Literal["l2", "cosine", "inner_product"] = Field(
+        description="Distance metric type for vector index: l2, cosine, or inner_product",
+        default="l2",
+    )
+
+    OCEANBASE_HNSW_M: PositiveInt = Field(
+        description="HNSW M parameter (max number of connections per node)",
+        default=16,
+    )
+
+    OCEANBASE_HNSW_EF_CONSTRUCTION: PositiveInt = Field(
+        description="HNSW efConstruction parameter (index build-time search width)",
+        default=256,
+    )
+
+    OCEANBASE_HNSW_EF_SEARCH: int = Field(
+        description="HNSW efSearch parameter (query-time search width, -1 uses server default)",
+        default=-1,
+    )
+
+    OCEANBASE_VECTOR_POOL_SIZE: PositiveInt = Field(
+        description="SQLAlchemy connection pool size",
+        default=5,
+    )
+
+    OCEANBASE_VECTOR_MAX_OVERFLOW: int = Field(
+        description="SQLAlchemy connection pool max overflow connections",
+        default=10,
+    )
+
+    OCEANBASE_HNSW_REFRESH_THRESHOLD: int = Field(
+        description="Minimum number of inserted documents to trigger an automatic HNSW index refresh (0 to disable)",
+        default=1000,
+    )

api/constants/languages.py

@@ -21,6 +21,7 @@ language_timezone_mapping = {
     "th-TH": "Asia/Bangkok",
     "id-ID": "Asia/Jakarta",
     "ar-TN": "Africa/Tunis",
+    "nl-NL": "Europe/Amsterdam",
 }
 
 languages = list(language_timezone_mapping.keys())

api/controllers/common/fields.py

@@ -4,7 +4,7 @@ from typing import Any, TypeAlias
 
 from pydantic import BaseModel, ConfigDict, computed_field
 
-from core.file import helpers as file_helpers
+from core.workflow.file import helpers as file_helpers
 from models.model import IconType
 
 JSONValue: TypeAlias = str | int | float | bool | None | dict[str, Any] | list[Any]

api/controllers/console/app/app.py

@@ -23,10 +23,10 @@ from controllers.console.wraps import (
     is_admin_or_owner_required,
     setup_required,
 )
-from core.file import helpers as file_helpers
 from core.ops.ops_trace_manager import OpsTraceManager
 from core.rag.retrieval.retrieval_methods import RetrievalMethod
 from core.workflow.enums import NodeType, WorkflowExecutionStatus
+from core.workflow.file import helpers as file_helpers
 from extensions.ext_database import db
 from libs.login import current_account_with_tenant, login_required
 from models import App, DatasetPermissionEnum, Workflow
@@ -660,6 +660,19 @@ class AppCopyApi(Resource):
             )
             session.commit()
 
+            # Inherit web app permission from original app
+            if result.app_id and FeatureService.get_system_features().webapp_auth.enabled:
+                try:
+                    # Get the original app's access mode
+                    original_settings = EnterpriseService.WebAppAuth.get_app_access_mode_by_id(app_model.id)
+                    access_mode = original_settings.access_mode
+                except Exception:
+                    # If original app has no settings (old app), default to public to match fallback behavior
+                    access_mode = "public"
+
+                # Apply the same access mode to the copied app
+                EnterpriseService.WebAppAuth.update_app_access_mode(result.app_id, access_mode)
+
             stmt = select(App).where(App.id == result.app_id)
             app = session.scalar(stmt)
 

api/controllers/console/app/conversation.py

@@ -599,7 +599,12 @@ def _get_conversation(app_model, conversation_id):
     db.session.execute(
         sa.update(Conversation)
         .where(Conversation.id == conversation_id, Conversation.read_at.is_(None))
-        .values(read_at=naive_utc_now(), read_account_id=current_user.id)
+        # Keep updated_at unchanged when only marking a conversation as read.
+        .values(
+            read_at=naive_utc_now(),
+            read_account_id=current_user.id,
+            updated_at=Conversation.updated_at,
+        )
     )
     db.session.commit()
     db.session.refresh(conversation)

api/controllers/console/app/workflow.py

@@ -20,7 +20,6 @@ from core.app.app_config.features.file_upload.manager import FileUploadConfigMan
 from core.app.apps.base_app_queue_manager import AppQueueManager
 from core.app.apps.workflow.app_generator import SKIP_PREPARE_USER_INPUTS_KEY
 from core.app.entities.app_invoke_entities import InvokeFrom
-from core.file.models import File
 from core.helper.trace_id_helper import get_external_trace_id
 from core.model_runtime.utils.encoders import jsonable_encoder
 from core.plugin.impl.exc import PluginInvokeError
@@ -31,8 +30,10 @@ from core.trigger.debug.event_selectors import (
     select_trigger_debug_events,
 )
 from core.workflow.enums import NodeType
+from core.workflow.file.models import File
 from core.workflow.graph_engine.manager import GraphEngineManager
 from extensions.ext_database import db
+from extensions.ext_redis import redis_client
 from factories import file_factory, variable_factory
 from fields.member_fields import simple_account_fields
 from fields.workflow_fields import workflow_fields, workflow_pagination_fields
@@ -740,7 +741,7 @@ class WorkflowTaskStopApi(Resource):
         AppQueueManager.set_stop_flag_no_user_check(task_id)
 
         # New graph engine command channel mechanism
-        GraphEngineManager.send_stop_command(task_id)
+        GraphEngineManager(redis_client).send_stop_command(task_id)
 
         return {"result": "success"}
 

api/controllers/console/app/workflow_draft_variable.py

@@ -15,11 +15,11 @@ from controllers.console.app.error import (
 from controllers.console.app.wraps import get_app_model
 from controllers.console.wraps import account_initialization_required, edit_permission_required, setup_required
 from controllers.web.error import InvalidArgumentError, NotFoundError
-from core.file import helpers as file_helpers
-from core.variables.segment_group import SegmentGroup
-from core.variables.segments import ArrayFileSegment, FileSegment, Segment
-from core.variables.types import SegmentType
 from core.workflow.constants import CONVERSATION_VARIABLE_NODE_ID, SYSTEM_VARIABLE_NODE_ID
+from core.workflow.file import helpers as file_helpers
+from core.workflow.variables.segment_group import SegmentGroup
+from core.workflow.variables.segments import ArrayFileSegment, FileSegment, Segment
+from core.workflow.variables.types import SegmentType
 from extensions.ext_database import db
 from factories.file_factory import build_from_mapping, build_from_mappings
 from factories.variable_factory import build_segment_with_type
@@ -112,11 +112,11 @@ _WORKFLOW_DRAFT_VARIABLE_WITHOUT_VALUE_FIELDS = {
     "is_truncated": fields.Boolean(attribute=lambda model: model.file_id is not None),
 }
 
-_WORKFLOW_DRAFT_VARIABLE_FIELDS = dict(
-    _WORKFLOW_DRAFT_VARIABLE_WITHOUT_VALUE_FIELDS,
-    value=fields.Raw(attribute=_serialize_var_value),
-    full_content=fields.Raw(attribute=_serialize_full_content),
-)
+_WORKFLOW_DRAFT_VARIABLE_FIELDS = {
+    **_WORKFLOW_DRAFT_VARIABLE_WITHOUT_VALUE_FIELDS,
+    "value": fields.Raw(attribute=_serialize_var_value),
+    "full_content": fields.Raw(attribute=_serialize_full_content),
+}
 
 _WORKFLOW_DRAFT_ENV_VARIABLE_FIELDS = {
     "id": fields.String,

api/controllers/console/datasets/rag_pipeline/rag_pipeline_draft_variable.py

@@ -21,8 +21,8 @@ from controllers.console.app.workflow_draft_variable import (
 from controllers.console.datasets.wraps import get_rag_pipeline
 from controllers.console.wraps import account_initialization_required, setup_required
 from controllers.web.error import InvalidArgumentError, NotFoundError
-from core.variables.types import SegmentType
 from core.workflow.constants import CONVERSATION_VARIABLE_NODE_ID, SYSTEM_VARIABLE_NODE_ID
+from core.workflow.variables.types import SegmentType
 from extensions.ext_database import db
 from factories.file_factory import build_from_mapping, build_from_mappings
 from factories.variable_factory import build_segment_with_type

api/controllers/console/explore/trial.py

@@ -10,7 +10,7 @@ import services
 from controllers.common.fields import Parameters as ParametersResponse
 from controllers.common.fields import Site as SiteResponse
 from controllers.common.schema import get_or_create_model
-from controllers.console import api, console_ns
+from controllers.console import console_ns
 from controllers.console.app.error import (
     AppUnavailableError,
     AudioTooLargeError,
@@ -44,6 +44,7 @@ from core.errors.error import (
 from core.model_runtime.errors.invoke import InvokeError
 from core.workflow.graph_engine.manager import GraphEngineManager
 from extensions.ext_database import db
+from extensions.ext_redis import redis_client
 from fields.app_fields import (
     app_detail_fields_with_site,
     deleted_tool_fields,
@@ -225,7 +226,7 @@ class TrialAppWorkflowTaskStopApi(TrialAppResource):
         AppQueueManager.set_stop_flag_no_user_check(task_id)
 
         # New graph engine command channel mechanism
-        GraphEngineManager.send_stop_command(task_id)
+        GraphEngineManager(redis_client).send_stop_command(task_id)
 
         return {"result": "success"}
 
@@ -469,7 +470,7 @@ class TrialSitApi(Resource):
     """Resource for trial app sites."""
 
     @trial_feature_enable
-    @get_app_model_with_trial
+    @get_app_model_with_trial(None)
     def get(self, app_model):
         """Retrieve app site info.
 
@@ -491,7 +492,7 @@ class TrialAppParameterApi(Resource):
     """Resource for app variables."""
 
     @trial_feature_enable
-    @get_app_model_with_trial
+    @get_app_model_with_trial(None)
     def get(self, app_model):
         """Retrieve app parameters."""
 
@@ -520,7 +521,7 @@ class TrialAppParameterApi(Resource):
 
 class AppApi(Resource):
     @trial_feature_enable
-    @get_app_model_with_trial
+    @get_app_model_with_trial(None)
     @marshal_with(app_detail_with_site_model)
     def get(self, app_model):
         """Get app detail"""
@@ -533,7 +534,7 @@ class AppApi(Resource):
 
 class AppWorkflowApi(Resource):
     @trial_feature_enable
-    @get_app_model_with_trial
+    @get_app_model_with_trial(None)
     @marshal_with(workflow_model)
     def get(self, app_model):
         """Get workflow detail"""
@@ -552,7 +553,7 @@ class AppWorkflowApi(Resource):
 
 class DatasetListApi(Resource):
     @trial_feature_enable
-    @get_app_model_with_trial
+    @get_app_model_with_trial(None)
     def get(self, app_model):
         page = request.args.get("page", default=1, type=int)
         limit = request.args.get("limit", default=20, type=int)
@@ -570,27 +571,31 @@ class DatasetListApi(Resource):
         return response
 
 
-api.add_resource(TrialChatApi, "/trial-apps/<uuid:app_id>/chat-messages", endpoint="trial_app_chat_completion")
+console_ns.add_resource(TrialChatApi, "/trial-apps/<uuid:app_id>/chat-messages", endpoint="trial_app_chat_completion")
 
-api.add_resource(
+console_ns.add_resource(
     TrialMessageSuggestedQuestionApi,
     "/trial-apps/<uuid:app_id>/messages/<uuid:message_id>/suggested-questions",
     endpoint="trial_app_suggested_question",
 )
 
-api.add_resource(TrialChatAudioApi, "/trial-apps/<uuid:app_id>/audio-to-text", endpoint="trial_app_audio")
-api.add_resource(TrialChatTextApi, "/trial-apps/<uuid:app_id>/text-to-audio", endpoint="trial_app_text")
+console_ns.add_resource(TrialChatAudioApi, "/trial-apps/<uuid:app_id>/audio-to-text", endpoint="trial_app_audio")
+console_ns.add_resource(TrialChatTextApi, "/trial-apps/<uuid:app_id>/text-to-audio", endpoint="trial_app_text")
 
-api.add_resource(TrialCompletionApi, "/trial-apps/<uuid:app_id>/completion-messages", endpoint="trial_app_completion")
+console_ns.add_resource(
+    TrialCompletionApi, "/trial-apps/<uuid:app_id>/completion-messages", endpoint="trial_app_completion"
+)
 
-api.add_resource(TrialSitApi, "/trial-apps/<uuid:app_id>/site")
+console_ns.add_resource(TrialSitApi, "/trial-apps/<uuid:app_id>/site")
 
-api.add_resource(TrialAppParameterApi, "/trial-apps/<uuid:app_id>/parameters", endpoint="trial_app_parameters")
+console_ns.add_resource(TrialAppParameterApi, "/trial-apps/<uuid:app_id>/parameters", endpoint="trial_app_parameters")
 
-api.add_resource(AppApi, "/trial-apps/<uuid:app_id>", endpoint="trial_app")
+console_ns.add_resource(AppApi, "/trial-apps/<uuid:app_id>", endpoint="trial_app")
 
-api.add_resource(TrialAppWorkflowRunApi, "/trial-apps/<uuid:app_id>/workflows/run", endpoint="trial_app_workflow_run")
-api.add_resource(TrialAppWorkflowTaskStopApi, "/trial-apps/<uuid:app_id>/workflows/tasks/<string:task_id>/stop")
+console_ns.add_resource(
+    TrialAppWorkflowRunApi, "/trial-apps/<uuid:app_id>/workflows/run", endpoint="trial_app_workflow_run"
+)
+console_ns.add_resource(TrialAppWorkflowTaskStopApi, "/trial-apps/<uuid:app_id>/workflows/tasks/<string:task_id>/stop")
 
-api.add_resource(AppWorkflowApi, "/trial-apps/<uuid:app_id>/workflows", endpoint="trial_app_workflow")
-api.add_resource(DatasetListApi, "/trial-apps/<uuid:app_id>/datasets", endpoint="trial_app_datasets")
+console_ns.add_resource(AppWorkflowApi, "/trial-apps/<uuid:app_id>/workflows", endpoint="trial_app_workflow")
+console_ns.add_resource(DatasetListApi, "/trial-apps/<uuid:app_id>/datasets", endpoint="trial_app_datasets")

api/controllers/console/explore/workflow.py

@@ -23,6 +23,7 @@ from core.errors.error import (
 )
 from core.model_runtime.errors.invoke import InvokeError
 from core.workflow.graph_engine.manager import GraphEngineManager
+from extensions.ext_redis import redis_client
 from libs import helper
 from libs.login import current_account_with_tenant
 from models.model import AppMode, InstalledApp
@@ -100,6 +101,6 @@ class InstalledAppWorkflowTaskStopApi(InstalledAppResource):
         AppQueueManager.set_stop_flag_no_user_check(task_id)
 
         # New graph engine command channel mechanism
-        GraphEngineManager.send_stop_command(task_id)
+        GraphEngineManager(redis_client).send_stop_command(task_id)
 
         return {"result": "success"}

api/controllers/console/explore/wraps.py

@@ -105,9 +105,9 @@ def trial_app_required(view: Callable[Concatenate[App, P], R] | None = None):
     return decorator
 
 
-def trial_feature_enable(view: Callable[..., R]) -> Callable[..., R]:
+def trial_feature_enable(view: Callable[P, R]):
     @wraps(view)
-    def decorated(*args, **kwargs):
+    def decorated(*args: P.args, **kwargs: P.kwargs):
         features = FeatureService.get_system_features()
         if not features.enable_trial_app:
             abort(403, "Trial app feature is not enabled.")
@@ -116,9 +116,9 @@ def trial_feature_enable(view: Callable[..., R]) -> Callable[..., R]:
     return decorated
 
 
-def explore_banner_enabled(view: Callable[..., R]) -> Callable[..., R]:
+def explore_banner_enabled(view: Callable[P, R]):
     @wraps(view)
-    def decorated(*args, **kwargs):
+    def decorated(*args: P.args, **kwargs: P.kwargs):
         features = FeatureService.get_system_features()
         if not features.enable_explore_banner:
             abort(403, "Explore banner feature is not enabled.")

api/controllers/console/remote_files.py

@@ -1,6 +1,7 @@
 import urllib.parse
 
 import httpx
+from flask_restx import Resource
 from pydantic import BaseModel, Field
 
 import services
@@ -10,12 +11,12 @@ from controllers.common.errors import (
     RemoteFileUploadError,
     UnsupportedFileTypeError,
 )
-from controllers.fastopenapi import console_router
-from core.file import helpers as file_helpers
+from controllers.console import console_ns
 from core.helper import ssrf_proxy
+from core.workflow.file import helpers as file_helpers
 from extensions.ext_database import db
 from fields.file_fields import FileWithSignedUrl, RemoteFileInfo
-from libs.login import current_account_with_tenant
+from libs.login import current_account_with_tenant, login_required
 from services.file_service import FileService
 
 
@@ -23,69 +24,73 @@ class RemoteFileUploadPayload(BaseModel):
     url: str = Field(..., description="URL to fetch")
 
 
-@console_router.get(
-    "/remote-files/<path:url>",
-    response_model=RemoteFileInfo,
-    tags=["console"],
-)
-def get_remote_file_info(url: str) -> RemoteFileInfo:
-    decoded_url = urllib.parse.unquote(url)
-    resp = ssrf_proxy.head(decoded_url)
-    if resp.status_code != httpx.codes.OK:
-        resp = ssrf_proxy.get(decoded_url, timeout=3)
-    resp.raise_for_status()
-    return RemoteFileInfo(
-        file_type=resp.headers.get("Content-Type", "application/octet-stream"),
-        file_length=int(resp.headers.get("Content-Length", 0)),
-    )
-
-
-@console_router.post(
-    "/remote-files/upload",
-    response_model=FileWithSignedUrl,
-    tags=["console"],
-    status_code=201,
-)
-def upload_remote_file(payload: RemoteFileUploadPayload) -> FileWithSignedUrl:
-    url = payload.url
-
-    try:
-        resp = ssrf_proxy.head(url=url)
+@console_ns.route("/remote-files/<path:url>")
+class GetRemoteFileInfo(Resource):
+    @login_required
+    def get(self, url: str):
+        decoded_url = urllib.parse.unquote(url)
+        resp = ssrf_proxy.head(decoded_url)
         if resp.status_code != httpx.codes.OK:
-            resp = ssrf_proxy.get(url=url, timeout=3, follow_redirects=True)
-        if resp.status_code != httpx.codes.OK:
-            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)}")
+            resp = ssrf_proxy.get(decoded_url, timeout=3)
+        resp.raise_for_status()
+        return RemoteFileInfo(
+            file_type=resp.headers.get("Content-Type", "application/octet-stream"),
+            file_length=int(resp.headers.get("Content-Length", 0)),
+        ).model_dump(mode="json")
 
-    file_info = helpers.guess_file_info_from_response(resp)
 
-    if not FileService.is_file_size_within_limit(extension=file_info.extension, file_size=file_info.size):
-        raise FileTooLargeError
+@console_ns.route("/remote-files/upload")
+class RemoteFileUpload(Resource):
+    @login_required
+    def post(self):
+        payload = RemoteFileUploadPayload.model_validate(console_ns.payload)
+        url = payload.url
 
-    content = resp.content if resp.request.method == "GET" else ssrf_proxy.get(url).content
+        # Try to fetch remote file metadata/content first
+        try:
+            resp = ssrf_proxy.head(url=url)
+            if resp.status_code != httpx.codes.OK:
+                resp = ssrf_proxy.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)}")
 
-    try:
-        user, _ = current_account_with_tenant()
-        upload_file = FileService(db.engine).upload_file(
-            filename=file_info.filename,
-            content=content,
-            mimetype=file_info.mimetype,
-            user=user,
-            source_url=url,
+        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 ssrf_proxy.get(url).content
+
+        try:
+            user, _ = current_account_with_tenant()
+            upload_file = FileService(db.engine).upload_file(
+                filename=file_info.filename,
+                content=content,
+                mimetype=file_info.mimetype,
+                user=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
+        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"),
+            201,
         )
-    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()),
-    )

api/controllers/console/setup.py

@@ -42,7 +42,15 @@ class SetupResponse(BaseModel):
     tags=["console"],
 )
 def get_setup_status_api() -> SetupStatusResponse:
-    """Get system setup status."""
+    """Get system setup status.
+
+    NOTE: This endpoint is unauthenticated by design.
+
+    During first-time bootstrap there is no admin account yet, so frontend initialization must be
+    able to query setup progress before any login flow exists.
+
+    Only bootstrap-safe status information should be returned by this endpoint.
+    """
     if dify_config.EDITION == "SELF_HOSTED":
         setup_status = get_setup_status()
         if setup_status and not isinstance(setup_status, bool):
@@ -61,7 +69,12 @@ def get_setup_status_api() -> SetupStatusResponse:
 )
 @only_edition_self_hosted
 def setup_system(payload: SetupRequestPayload) -> SetupResponse:
-    """Initialize system setup with admin account."""
+    """Initialize system setup with admin account.
+
+    NOTE: This endpoint is unauthenticated by design for first-time bootstrap.
+    Access is restricted by deployment mode (`SELF_HOSTED`), one-time setup guards,
+    and init-password validation rather than user session authentication.
+    """
     if get_setup_status():
         raise AlreadySetupError()
 

api/controllers/files/image_preview.py

@@ -137,7 +137,7 @@ class FilePreviewApi(Resource):
         if args.as_attachment:
             encoded_filename = quote(upload_file.name)
             response.headers["Content-Disposition"] = f"attachment; filename*=UTF-8''{encoded_filename}"
-            response.headers["Content-Type"] = "application/octet-stream"
+        response.headers["Content-Type"] = "application/octet-stream"
 
         enforce_download_for_html(
             response,

api/controllers/files/tool_files.py

@@ -64,6 +64,10 @@ class ToolFileApi(Resource):
 
             if not stream or not tool_file:
                 raise NotFound("file is not found")
+
+        except NotFound:
+            raise
+
         except Exception:
             raise UnsupportedFileTypeError()
 

api/controllers/files/upload.py

@@ -7,8 +7,8 @@ from pydantic import BaseModel, Field
 from werkzeug.exceptions import Forbidden
 
 import services
-from core.file.helpers import verify_plugin_file_signature
 from core.tools.tool_file_manager import ToolFileManager
+from core.workflow.file.helpers import verify_plugin_file_signature
 from fields.file_fields import FileResponse
 
 from ..common.errors import (

api/controllers/inner_api/plugin/plugin.py

@@ -4,7 +4,6 @@ from controllers.console.wraps import setup_required
 from controllers.inner_api import inner_api_ns
 from controllers.inner_api.plugin.wraps import get_user_tenant, plugin_data
 from controllers.inner_api.wraps import plugin_inner_api_only
-from core.file.helpers import get_signed_file_url_for_plugin
 from core.model_runtime.utils.encoders import jsonable_encoder
 from core.plugin.backwards_invocation.app import PluginAppBackwardsInvocation
 from core.plugin.backwards_invocation.base import BaseBackwardsInvocationResponse
@@ -30,6 +29,7 @@ from core.plugin.entities.request import (
     RequestRequestUploadFile,
 )
 from core.tools.entities.tool_entities import ToolProviderType
+from core.workflow.file.helpers import get_signed_file_url_for_plugin
 from libs.helper import length_prefixed_response
 from models import Account, Tenant
 from models.model import EndUser

api/controllers/service_api/app/workflow.py

@@ -31,6 +31,7 @@ from core.model_runtime.errors.invoke import InvokeError
 from core.workflow.enums import WorkflowExecutionStatus
 from core.workflow.graph_engine.manager import GraphEngineManager
 from extensions.ext_database import db
+from extensions.ext_redis import redis_client
 from fields.workflow_app_log_fields import build_workflow_app_log_pagination_model
 from libs import helper
 from libs.helper import OptionalTimestampField, TimestampField
@@ -280,7 +281,7 @@ class WorkflowTaskStopApi(Resource):
         AppQueueManager.set_stop_flag_no_user_check(task_id)
 
         # New graph engine command channel mechanism
-        GraphEngineManager.send_stop_command(task_id)
+        GraphEngineManager(redis_client).send_stop_command(task_id)
 
         return {"result": "success"}
 

api/controllers/service_api/dataset/rag_pipeline/rag_pipeline_workflow.py

@@ -3,7 +3,8 @@ from typing import Any
 
 from flask import request
 from pydantic import BaseModel
-from werkzeug.exceptions import Forbidden
+from sqlalchemy import select
+from werkzeug.exceptions import Forbidden, NotFound
 
 import services
 from controllers.common.errors import FilenameNotExistsError, NoFileUploadedError, TooManyFilesError
@@ -17,7 +18,7 @@ from core.app.entities.app_invoke_entities import InvokeFrom
 from libs import helper
 from libs.login import current_user
 from models import Account
-from models.dataset import Pipeline
+from models.dataset import Dataset, Pipeline
 from models.engine import db
 from services.errors.file import FileTooLargeError, UnsupportedFileTypeError
 from services.file_service import FileService
@@ -65,6 +66,12 @@ class DatasourcePluginsApi(DatasetApiResource):
     )
     def get(self, tenant_id: str, dataset_id: str):
         """Resource for getting datasource plugins."""
+        # Verify dataset ownership
+        stmt = select(Dataset).where(Dataset.tenant_id == tenant_id, Dataset.id == dataset_id)
+        dataset = db.session.scalar(stmt)
+        if not dataset:
+            raise NotFound("Dataset not found.")
+
         # Get query parameter to determine published or draft
         is_published: bool = request.args.get("is_published", default=True, type=bool)
 
@@ -104,6 +111,12 @@ class DatasourceNodeRunApi(DatasetApiResource):
     @service_api_ns.expect(service_api_ns.models[DatasourceNodeRunPayload.__name__])
     def post(self, tenant_id: str, dataset_id: str, node_id: str):
         """Resource for getting datasource plugins."""
+        # Verify dataset ownership
+        stmt = select(Dataset).where(Dataset.tenant_id == tenant_id, Dataset.id == dataset_id)
+        dataset = db.session.scalar(stmt)
+        if not dataset:
+            raise NotFound("Dataset not found.")
+
         payload = DatasourceNodeRunPayload.model_validate(service_api_ns.payload or {})
         assert isinstance(current_user, Account)
         rag_pipeline_service: RagPipelineService = RagPipelineService()
@@ -161,6 +174,12 @@ class PipelineRunApi(DatasetApiResource):
     @service_api_ns.expect(service_api_ns.models[PipelineRunApiEntity.__name__])
     def post(self, tenant_id: str, dataset_id: str):
         """Resource for running a rag pipeline."""
+        # Verify dataset ownership
+        stmt = select(Dataset).where(Dataset.tenant_id == tenant_id, Dataset.id == dataset_id)
+        dataset = db.session.scalar(stmt)
+        if not dataset:
+            raise NotFound("Dataset not found.")
+
         payload = PipelineRunApiEntity.model_validate(service_api_ns.payload or {})
 
         if not isinstance(current_user, Account):

api/controllers/web/remote_files.py

@@ -10,8 +10,8 @@ from controllers.common.errors import (
     RemoteFileUploadError,
     UnsupportedFileTypeError,
 )
-from core.file import helpers as file_helpers
 from core.helper import ssrf_proxy
+from core.workflow.file import helpers as file_helpers
 from extensions.ext_database import db
 from fields.file_fields import FileWithSignedUrl, RemoteFileInfo
 from services.file_service import FileService

api/controllers/web/workflow.py

@@ -24,6 +24,7 @@ from core.errors.error import (
 )
 from core.model_runtime.errors.invoke import InvokeError
 from core.workflow.graph_engine.manager import GraphEngineManager
+from extensions.ext_redis import redis_client
 from libs import helper
 from models.model import App, AppMode, EndUser
 from services.app_generate_service import AppGenerateService
@@ -121,6 +122,6 @@ class WorkflowTaskStopApi(WebApiResource):
         AppQueueManager.set_stop_flag_no_user_check(task_id)
 
         # New graph engine command channel mechanism
-        GraphEngineManager.send_stop_command(task_id)
+        GraphEngineManager(redis_client).send_stop_command(task_id)
 
         return {"result": "success"}

api/core/agent/base_agent_runner.py

@@ -17,7 +17,6 @@ from core.app.entities.app_invoke_entities import (
 )
 from core.callback_handler.agent_tool_callback_handler import DifyAgentCallbackHandler
 from core.callback_handler.index_tool_callback_handler import DatasetIndexToolCallbackHandler
-from core.file import file_manager
 from core.memory.token_buffer_memory import TokenBufferMemory
 from core.model_manager import ModelInstance
 from core.model_runtime.entities import (
@@ -40,6 +39,7 @@ from core.tools.entities.tool_entities import (
 )
 from core.tools.tool_manager import ToolManager
 from core.tools.utils.dataset_retriever_tool import DatasetRetrieverTool
+from core.workflow.file import file_manager
 from extensions.ext_database import db
 from factories import file_factory
 from models.enums import CreatorUserRole
@@ -112,7 +112,7 @@ class BaseAgentRunner(AppRunner):
 
         # check if model supports stream tool call
         llm_model = cast(LargeLanguageModel, model_instance.model_type_instance)
-        model_schema = llm_model.get_model_schema(model_instance.model, model_instance.credentials)
+        model_schema = llm_model.get_model_schema(model_instance.model_name, model_instance.credentials)
         features = model_schema.features if model_schema and model_schema.features else []
         self.stream_tool_call = ModelFeature.STREAM_TOOL_CALL in features
         self.files = application_generate_entity.files if ModelFeature.VISION in features else []

api/core/agent/cot_agent_runner.py

@@ -245,7 +245,7 @@ class CotAgentRunner(BaseAgentRunner, ABC):
             iteration_step += 1
 
         yield LLMResultChunk(
-            model=model_instance.model,
+            model=model_instance.model_name,
             prompt_messages=prompt_messages,
             delta=LLMResultChunkDelta(
                 index=0, message=AssistantPromptMessage(content=final_answer), usage=llm_usage["usage"]
@@ -268,7 +268,7 @@ class CotAgentRunner(BaseAgentRunner, ABC):
         self.queue_manager.publish(
             QueueMessageEndEvent(
                 llm_result=LLMResult(
-                    model=model_instance.model,
+                    model=model_instance.model_name,
                     prompt_messages=prompt_messages,
                     message=AssistantPromptMessage(content=final_answer),
                     usage=llm_usage["usage"] or LLMUsage.empty_usage(),

api/core/agent/cot_chat_agent_runner.py

@@ -1,7 +1,6 @@
 import json
 
 from core.agent.cot_agent_runner import CotAgentRunner
-from core.file import file_manager
 from core.model_runtime.entities import (
     AssistantPromptMessage,
     PromptMessage,
@@ -11,6 +10,7 @@ from core.model_runtime.entities import (
 )
 from core.model_runtime.entities.message_entities import ImagePromptMessageContent, PromptMessageContentUnionTypes
 from core.model_runtime.utils.encoders import jsonable_encoder
+from core.workflow.file import file_manager
 
 
 class CotChatAgentRunner(CotAgentRunner):

api/core/agent/fc_agent_runner.py

@@ -7,7 +7,6 @@ from typing import Any, Union
 from core.agent.base_agent_runner import BaseAgentRunner
 from core.app.apps.base_app_queue_manager import PublishFrom
 from core.app.entities.queue_entities import QueueAgentThoughtEvent, QueueMessageEndEvent, QueueMessageFileEvent
-from core.file import file_manager
 from core.model_runtime.entities import (
     AssistantPromptMessage,
     LLMResult,
@@ -25,6 +24,7 @@ from core.model_runtime.entities.message_entities import ImagePromptMessageConte
 from core.prompt.agent_history_prompt_transform import AgentHistoryPromptTransform
 from core.tools.entities.tool_entities import ToolInvokeMeta
 from core.tools.tool_engine import ToolEngine
+from core.workflow.file import file_manager
 from core.workflow.nodes.agent.exc import AgentMaxIterationError
 from models.model import Message
 
@@ -178,7 +178,7 @@ class FunctionCallAgentRunner(BaseAgentRunner):
                 )
 
                 yield LLMResultChunk(
-                    model=model_instance.model,
+                    model=model_instance.model_name,
                     prompt_messages=result.prompt_messages,
                     system_fingerprint=result.system_fingerprint,
                     delta=LLMResultChunkDelta(
@@ -308,7 +308,7 @@ class FunctionCallAgentRunner(BaseAgentRunner):
         self.queue_manager.publish(
             QueueMessageEndEvent(
                 llm_result=LLMResult(
-                    model=model_instance.model,
+                    model=model_instance.model_name,
                     prompt_messages=prompt_messages,
                     message=AssistantPromptMessage(content=final_answer),
                     usage=llm_usage["usage"] or LLMUsage.empty_usage(),

api/core/app/app_config/entities.py

@@ -5,9 +5,9 @@ from typing import Any, Literal
 from jsonschema import Draft7Validator, SchemaError
 from pydantic import BaseModel, Field, field_validator
 
-from core.file import FileTransferMethod, FileType, FileUploadConfig
 from core.model_runtime.entities.llm_entities import LLMMode
 from core.model_runtime.entities.message_entities import PromptMessageRole
+from core.workflow.file import FileTransferMethod, FileType, FileUploadConfig
 from models.model import AppMode
 
 

api/core/app/app_config/features/file_upload/manager.py

@@ -2,7 +2,7 @@ from collections.abc import Mapping
 from typing import Any
 
 from constants import DEFAULT_FILE_NUMBER_LIMITS
-from core.file import FileUploadConfig
+from core.workflow.file import FileUploadConfig
 
 
 class FileUploadConfigManager:

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

@@ -25,7 +25,6 @@ from core.app.workflow.layers.persistence import PersistenceWorkflowInfo, Workfl
 from core.db.session_factory import session_factory
 from core.moderation.base import ModerationError
 from core.moderation.input_moderation import InputModeration
-from core.variables.variables import Variable
 from core.workflow.enums import WorkflowType
 from core.workflow.graph_engine.command_channels.redis_channel import RedisChannel
 from core.workflow.graph_engine.layers.base import GraphEngineLayer
@@ -34,6 +33,7 @@ from core.workflow.repositories.workflow_node_execution_repository import Workfl
 from core.workflow.runtime import GraphRuntimeState, VariablePool
 from core.workflow.system_variable import SystemVariable
 from core.workflow.variable_loader import VariableLoader
+from core.workflow.variables.variables import Variable
 from core.workflow.workflow_entry import WorkflowEntry
 from extensions.ext_database import db
 from extensions.ext_redis import redis_client

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

@@ -669,16 +669,14 @@ class AdvancedChatAppGenerateTaskPipeline(GraphRuntimeStateSupport):
     ) -> Generator[StreamResponse, None, None]:
         """Handle retriever resources events."""
         self._message_cycle_manager.handle_retriever_resources(event)
-        return
-        yield  # Make this a generator
+        yield from ()
 
     def _handle_annotation_reply_event(
         self, event: QueueAnnotationReplyEvent, **kwargs
     ) -> Generator[StreamResponse, None, None]:
         """Handle annotation reply events."""
         self._message_cycle_manager.handle_annotation_reply(event)
-        return
-        yield  # Make this a generator
+        yield from ()
 
     def _handle_message_replace_event(
         self, event: QueueMessageReplaceEvent, **kwargs

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

@@ -178,7 +178,7 @@ class AgentChatAppRunner(AppRunner):
 
         # change function call strategy based on LLM model
         llm_model = cast(LargeLanguageModel, model_instance.model_type_instance)
-        model_schema = llm_model.get_model_schema(model_instance.model, model_instance.credentials)
+        model_schema = llm_model.get_model_schema(model_instance.model_name, model_instance.credentials)
         if not model_schema:
             raise ValueError("Model schema not found")
 

api/core/app/apps/base_app_generator.py

@@ -5,8 +5,8 @@ from sqlalchemy.orm import Session
 
 from core.app.app_config.entities import VariableEntityType
 from core.app.entities.app_invoke_entities import InvokeFrom
-from core.file import File, FileUploadConfig
 from core.workflow.enums import NodeType
+from core.workflow.file import File, FileUploadConfig
 from core.workflow.repositories.draft_variable_repository import (
     DraftVariableSaver,
     DraftVariableSaverFactory,

api/core/app/apps/base_app_queue_manager.py

@@ -2,7 +2,7 @@ import logging
 import queue
 import threading
 import time
-from abc import abstractmethod
+from abc import ABC, abstractmethod
 from enum import IntEnum, auto
 from typing import Any
 
@@ -31,7 +31,7 @@ class PublishFrom(IntEnum):
     TASK_PIPELINE = auto()
 
 
-class AppQueueManager:
+class AppQueueManager(ABC):
     def __init__(self, task_id: str, user_id: str, invoke_from: InvokeFrom):
         if not user_id:
             raise ValueError("user is required")
@@ -122,7 +122,7 @@ class AppQueueManager:
         """Attach the live graph runtime state reference for downstream consumers."""
         self._graph_runtime_state = graph_runtime_state
 
-    def publish(self, event: AppQueueEvent, pub_from: PublishFrom):
+    def publish(self, event: AppQueueEvent, pub_from: PublishFrom) -> None:
         """
         Publish event to queue
         :param event:
@@ -133,7 +133,7 @@ class AppQueueManager:
         self._publish(event, pub_from)
 
     @abstractmethod
-    def _publish(self, event: AppQueueEvent, pub_from: PublishFrom):
+    def _publish(self, event: AppQueueEvent, pub_from: PublishFrom) -> None:
         """
         Publish event to queue
         :param event:

api/core/app/apps/base_app_runner.py

@@ -22,7 +22,6 @@ from core.app.entities.queue_entities import (
 from core.app.features.annotation_reply.annotation_reply import AnnotationReplyFeature
 from core.app.features.hosting_moderation.hosting_moderation import HostingModerationFeature
 from core.external_data_tool.external_data_fetch import ExternalDataFetch
-from core.file.enums import FileTransferMethod, FileType
 from core.memory.token_buffer_memory import TokenBufferMemory
 from core.model_manager import ModelInstance
 from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta, LLMUsage
@@ -39,12 +38,13 @@ from core.prompt.advanced_prompt_transform import AdvancedPromptTransform
 from core.prompt.entities.advanced_prompt_entities import ChatModelMessage, CompletionModelPromptTemplate, MemoryConfig
 from core.prompt.simple_prompt_transform import ModelMode, SimplePromptTransform
 from core.tools.tool_file_manager import ToolFileManager
+from core.workflow.file.enums import FileTransferMethod, FileType
 from extensions.ext_database import db
 from models.enums import CreatorUserRole
 from models.model import App, AppMode, Message, MessageAnnotation, MessageFile
 
 if TYPE_CHECKING:
-    from core.file.models import File
+    from core.workflow.file.models import File
 
 _logger = logging.getLogger(__name__)
 

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

@@ -11,12 +11,12 @@ from core.app.entities.app_invoke_entities import (
 )
 from core.app.entities.queue_entities import QueueAnnotationReplyEvent
 from core.callback_handler.index_tool_callback_handler import DatasetIndexToolCallbackHandler
-from core.file import File
 from core.memory.token_buffer_memory import TokenBufferMemory
 from core.model_manager import ModelInstance
 from core.model_runtime.entities.message_entities import ImagePromptMessageContent
 from core.moderation.base import ModerationError
 from core.rag.retrieval.dataset_retrieval import DatasetRetrieval
+from core.workflow.file import File
 from extensions.ext_database import db
 from models.model import App, Conversation, Message
 

api/core/app/apps/common/workflow_response_converter.py

@@ -45,12 +45,10 @@ from core.app.entities.task_entities import (
     WorkflowPauseStreamResponse,
     WorkflowStartStreamResponse,
 )
-from core.file import FILE_MODEL_IDENTITY, File
 from core.plugin.impl.datasource import PluginDatasourceManager
 from core.tools.entities.tool_entities import ToolProviderType
 from core.tools.tool_manager import ToolManager
 from core.trigger.trigger_manager import TriggerManager
-from core.variables.segments import ArrayFileSegment, FileSegment, Segment
 from core.workflow.entities.pause_reason import HumanInputRequired
 from core.workflow.entities.workflow_start_reason import WorkflowStartReason
 from core.workflow.enums import (
@@ -60,8 +58,10 @@ from core.workflow.enums import (
     WorkflowNodeExecutionMetadataKey,
     WorkflowNodeExecutionStatus,
 )
+from core.workflow.file import FILE_MODEL_IDENTITY, File
 from core.workflow.runtime import GraphRuntimeState
 from core.workflow.system_variable import SystemVariable
+from core.workflow.variables.segments import ArrayFileSegment, FileSegment, Segment
 from core.workflow.workflow_entry import WorkflowEntry
 from core.workflow.workflow_type_encoder import WorkflowRuntimeTypeConverter
 from extensions.ext_database import db

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

@@ -10,11 +10,11 @@ from core.app.entities.app_invoke_entities import (
     CompletionAppGenerateEntity,
 )
 from core.callback_handler.index_tool_callback_handler import DatasetIndexToolCallbackHandler
-from core.file import File
 from core.model_manager import ModelInstance
 from core.model_runtime.entities.message_entities import ImagePromptMessageContent
 from core.moderation.base import ModerationError
 from core.rag.retrieval.dataset_retrieval import DatasetRetrieval
+from core.workflow.file import File
 from extensions.ext_database import db
 from models.model import App, Message
 

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

@@ -11,7 +11,6 @@ from core.app.entities.app_invoke_entities import (
 )
 from core.app.workflow.layers.persistence import PersistenceWorkflowInfo, WorkflowPersistenceLayer
 from core.app.workflow.node_factory import DifyNodeFactory
-from core.variables.variables import RAGPipelineVariable, RAGPipelineVariableInput
 from core.workflow.entities.graph_init_params import GraphInitParams
 from core.workflow.enums import WorkflowType
 from core.workflow.graph import Graph
@@ -21,6 +20,7 @@ from core.workflow.repositories.workflow_node_execution_repository import Workfl
 from core.workflow.runtime import GraphRuntimeState, VariablePool
 from core.workflow.system_variable import SystemVariable
 from core.workflow.variable_loader import VariableLoader
+from core.workflow.variables.variables import RAGPipelineVariable, RAGPipelineVariableInput
 from core.workflow.workflow_entry import WorkflowEntry
 from extensions.ext_database import db
 from models.dataset import Document, Pipeline

api/core/app/apps/streaming_utils.py

@@ -34,7 +34,7 @@ def stream_topic_events(
             on_subscribe()
         while True:
             try:
-                msg = sub.receive(timeout=0.1)
+                msg = sub.receive(timeout=1)
             except SubscriptionClosedError:
                 return
             if msg is None:

api/core/app/entities/app_invoke_entities.py

@@ -7,8 +7,8 @@ from pydantic import BaseModel, ConfigDict, Field, ValidationInfo, field_validat
 from constants import UUID_NIL
 from core.app.app_config.entities import EasyUIBasedAppConfig, WorkflowUIBasedAppConfig
 from core.entities.provider_configuration import ProviderModelBundle
-from core.file import File, FileUploadConfig
 from core.model_runtime.entities.model_entities import AIModelEntity
+from core.workflow.file import File, FileUploadConfig
 
 if TYPE_CHECKING:
     from core.ops.ops_trace_manager import TraceQueueManager

api/core/app/layers/conversation_variable_persist_layer.py

@@ -1,12 +1,12 @@
 import logging
 
-from core.variables import VariableBase
 from core.workflow.constants import CONVERSATION_VARIABLE_NODE_ID
 from core.workflow.conversation_variable_updater import ConversationVariableUpdater
 from core.workflow.enums import NodeType
 from core.workflow.graph_engine.layers.base import GraphEngineLayer
 from core.workflow.graph_events import GraphEngineEvent, NodeRunSucceededEvent
 from core.workflow.nodes.variable_assigner.common import helpers as common_helpers
+from core.workflow.variables import VariableBase
 
 logger = logging.getLogger(__name__)
 

api/core/app/llm/__init__.py

@@ -0,0 +1 @@
+"""LLM-related application services."""

api/core/app/llm/model_access.py

@@ -0,0 +1,110 @@
+from __future__ import annotations
+
+from typing import Any
+
+from core.app.entities.app_invoke_entities import ModelConfigWithCredentialsEntity
+from core.errors.error import ProviderTokenNotInitError
+from core.model_manager import ModelInstance, ModelManager
+from core.model_runtime.entities.model_entities import ModelType
+from core.provider_manager import ProviderManager
+from core.workflow.nodes.llm.entities import ModelConfig
+from core.workflow.nodes.llm.exc import LLMModeRequiredError, ModelNotExistError
+from core.workflow.nodes.llm.protocols import CredentialsProvider, ModelFactory
+
+
+class DifyCredentialsProvider:
+    tenant_id: str
+    provider_manager: ProviderManager
+
+    def __init__(self, tenant_id: str, provider_manager: ProviderManager | None = None) -> None:
+        self.tenant_id = tenant_id
+        self.provider_manager = provider_manager or ProviderManager()
+
+    def fetch(self, provider_name: str, model_name: str) -> dict[str, Any]:
+        provider_configurations = self.provider_manager.get_configurations(self.tenant_id)
+        provider_configuration = provider_configurations.get(provider_name)
+        if not provider_configuration:
+            raise ValueError(f"Provider {provider_name} does not exist.")
+
+        provider_model = provider_configuration.get_provider_model(model_type=ModelType.LLM, model=model_name)
+        if provider_model is None:
+            raise ModelNotExistError(f"Model {model_name} not exist.")
+        provider_model.raise_for_status()
+
+        credentials = provider_configuration.get_current_credentials(model_type=ModelType.LLM, model=model_name)
+        if credentials is None:
+            raise ProviderTokenNotInitError(f"Model {model_name} credentials is not initialized.")
+
+        return credentials
+
+
+class DifyModelFactory:
+    tenant_id: str
+    model_manager: ModelManager
+
+    def __init__(self, tenant_id: str, model_manager: ModelManager | None = None) -> None:
+        self.tenant_id = tenant_id
+        self.model_manager = model_manager or ModelManager()
+
+    def init_model_instance(self, provider_name: str, model_name: str) -> ModelInstance:
+        return self.model_manager.get_model_instance(
+            tenant_id=self.tenant_id,
+            provider=provider_name,
+            model_type=ModelType.LLM,
+            model=model_name,
+        )
+
+
+def build_dify_model_access(tenant_id: str) -> tuple[CredentialsProvider, ModelFactory]:
+    return (
+        DifyCredentialsProvider(tenant_id=tenant_id),
+        DifyModelFactory(tenant_id=tenant_id),
+    )
+
+
+def fetch_model_config(
+    *,
+    node_data_model: ModelConfig,
+    credentials_provider: CredentialsProvider,
+    model_factory: ModelFactory,
+) -> tuple[ModelInstance, ModelConfigWithCredentialsEntity]:
+    if not node_data_model.mode:
+        raise LLMModeRequiredError("LLM mode is required.")
+
+    credentials = credentials_provider.fetch(node_data_model.provider, node_data_model.name)
+    model_instance = model_factory.init_model_instance(node_data_model.provider, node_data_model.name)
+    provider_model_bundle = model_instance.provider_model_bundle
+
+    provider_model = provider_model_bundle.configuration.get_provider_model(
+        model=node_data_model.name,
+        model_type=ModelType.LLM,
+    )
+    if provider_model is None:
+        raise ModelNotExistError(f"Model {node_data_model.name} not exist.")
+    provider_model.raise_for_status()
+
+    completion_params = dict(node_data_model.completion_params)
+    stop = completion_params.pop("stop", [])
+    if not isinstance(stop, list):
+        stop = []
+
+    model_schema = model_instance.model_type_instance.get_model_schema(node_data_model.name, credentials)
+    if not model_schema:
+        raise ModelNotExistError(f"Model {node_data_model.name} not exist.")
+
+    model_instance.provider = node_data_model.provider
+    model_instance.model_name = node_data_model.name
+    model_instance.credentials = credentials
+    model_instance.parameters = completion_params
+    model_instance.stop = tuple(stop)
+
+    return model_instance, ModelConfigWithCredentialsEntity(
+        provider=node_data_model.provider,
+        model=node_data_model.name,
+        model_schema=model_schema,
+        mode=node_data_model.mode,
+        provider_model_bundle=provider_model_bundle,
+        credentials=credentials,
+        parameters=completion_params,
+        stop=stop,
+    )

api/core/app/task_pipeline/easy_ui_based_generate_task_pipeline.py

@@ -56,10 +56,13 @@ from core.ops.entities.trace_entity import TraceTaskName
 from core.ops.ops_trace_manager import TraceQueueManager, TraceTask
 from core.prompt.utils.prompt_message_util import PromptMessageUtil
 from core.prompt.utils.prompt_template_parser import PromptTemplateParser
+from core.tools.signature import sign_tool_file
+from core.workflow.file import helpers as file_helpers
+from core.workflow.file.enums import FileTransferMethod
 from events.message_event import message_was_created
 from extensions.ext_database import db
 from libs.datetime_utils import naive_utc_now
-from models.model import AppMode, Conversation, Message, MessageAgentThought
+from models.model import AppMode, Conversation, Message, MessageAgentThought, MessageFile, UploadFile
 
 logger = logging.getLogger(__name__)
 
@@ -463,6 +466,85 @@ class EasyUIBasedGenerateTaskPipeline(BasedGenerateTaskPipeline):
             metadata=metadata_dict,
         )
 
+    def _record_files(self):
+        with Session(db.engine, expire_on_commit=False) as session:
+            message_files = session.scalars(select(MessageFile).where(MessageFile.message_id == self._message_id)).all()
+            if not message_files:
+                return None
+
+            files_list = []
+            upload_file_ids = [
+                mf.upload_file_id
+                for mf in message_files
+                if mf.transfer_method == FileTransferMethod.LOCAL_FILE and mf.upload_file_id
+            ]
+            upload_files_map = {}
+            if upload_file_ids:
+                upload_files = session.scalars(select(UploadFile).where(UploadFile.id.in_(upload_file_ids))).all()
+                upload_files_map = {uf.id: uf for uf in upload_files}
+
+            for message_file in message_files:
+                upload_file = None
+                if message_file.transfer_method == FileTransferMethod.LOCAL_FILE and message_file.upload_file_id:
+                    upload_file = upload_files_map.get(message_file.upload_file_id)
+
+                url = None
+                filename = "file"
+                mime_type = "application/octet-stream"
+                size = 0
+                extension = ""
+
+                if message_file.transfer_method == FileTransferMethod.REMOTE_URL:
+                    url = message_file.url
+                    if message_file.url:
+                        filename = message_file.url.split("/")[-1].split("?")[0]  # Remove query params
+                elif message_file.transfer_method == FileTransferMethod.LOCAL_FILE:
+                    if upload_file:
+                        url = file_helpers.get_signed_file_url(upload_file_id=str(upload_file.id))
+                        filename = upload_file.name
+                        mime_type = upload_file.mime_type or "application/octet-stream"
+                        size = upload_file.size or 0
+                        extension = f".{upload_file.extension}" if upload_file.extension else ""
+                    elif message_file.upload_file_id:
+                        # Fallback: generate URL even if upload_file not found
+                        url = file_helpers.get_signed_file_url(upload_file_id=str(message_file.upload_file_id))
+                elif message_file.transfer_method == FileTransferMethod.TOOL_FILE and message_file.url:
+                    # For tool files, use URL directly if it's HTTP, otherwise sign it
+                    if message_file.url.startswith("http"):
+                        url = message_file.url
+                        filename = message_file.url.split("/")[-1].split("?")[0]
+                    else:
+                        # Extract tool file id and extension from URL
+                        url_parts = message_file.url.split("/")
+                        if url_parts:
+                            file_part = url_parts[-1].split("?")[0]  # Remove query params first
+                            # Use rsplit to correctly handle filenames with multiple dots
+                            if "." in file_part:
+                                tool_file_id, ext = file_part.rsplit(".", 1)
+                                extension = f".{ext}"
+                            else:
+                                tool_file_id = file_part
+                                extension = ".bin"
+                            url = sign_tool_file(tool_file_id=tool_file_id, extension=extension)
+                            filename = file_part
+
+                transfer_method_value = message_file.transfer_method
+                remote_url = message_file.url if message_file.transfer_method == FileTransferMethod.REMOTE_URL else ""
+                file_dict = {
+                    "related_id": message_file.id,
+                    "extension": extension,
+                    "filename": filename,
+                    "size": size,
+                    "mime_type": mime_type,
+                    "transfer_method": transfer_method_value,
+                    "type": message_file.type,
+                    "url": url or "",
+                    "upload_file_id": message_file.upload_file_id or message_file.id,
+                    "remote_url": remote_url,
+                }
+                files_list.append(file_dict)
+            return files_list or None
+
     def _agent_message_to_stream_response(self, answer: str, message_id: str) -> AgentMessageStreamResponse:
         """
         Agent message to stream response.

api/core/app/task_pipeline/message_cycle_manager.py

@@ -64,7 +64,13 @@ class MessageCycleManager:
 
         # Use SQLAlchemy 2.x style session.scalar(select(...))
         with session_factory.create_session() as session:
-            message_file = session.scalar(select(MessageFile).where(MessageFile.message_id == message_id))
+            message_file = session.scalar(
+                select(MessageFile)
+                .where(
+                    MessageFile.message_id == message_id,
+                )
+                .where(MessageFile.belongs_to == "assistant")
+            )
 
         if message_file:
             self._message_has_file.add(message_id)

api/core/app/workflow/file_runtime.py

@@ -0,0 +1,47 @@
+from __future__ import annotations
+
+from collections.abc import Generator
+
+from configs import dify_config
+from core.helper.ssrf_proxy import ssrf_proxy
+from core.tools.signature import sign_tool_file
+from core.workflow.file.protocols import HttpResponseProtocol, WorkflowFileRuntimeProtocol
+from core.workflow.file.runtime import set_workflow_file_runtime
+from extensions.ext_storage import storage
+
+
+class DifyWorkflowFileRuntime(WorkflowFileRuntimeProtocol):
+    """Production runtime wiring for ``core.workflow.file``."""
+
+    @property
+    def files_url(self) -> str:
+        return dify_config.FILES_URL
+
+    @property
+    def internal_files_url(self) -> str | None:
+        return dify_config.INTERNAL_FILES_URL
+
+    @property
+    def secret_key(self) -> str:
+        return dify_config.SECRET_KEY
+
+    @property
+    def files_access_timeout(self) -> int:
+        return dify_config.FILES_ACCESS_TIMEOUT
+
+    @property
+    def multimodal_send_format(self) -> str:
+        return dify_config.MULTIMODAL_SEND_FORMAT
+
+    def http_get(self, url: str, *, follow_redirects: bool = True) -> HttpResponseProtocol:
+        return ssrf_proxy.get(url, follow_redirects=follow_redirects)
+
+    def storage_load(self, path: str, *, stream: bool = False) -> bytes | Generator:
+        return storage.load(path, stream=stream)
+
+    def sign_tool_file(self, *, tool_file_id: str, extension: str, for_external: bool = True) -> str:
+        return sign_tool_file(tool_file_id=tool_file_id, extension=extension, for_external=for_external)
+
+
+def bind_dify_workflow_file_runtime() -> None:
+    set_workflow_file_runtime(DifyWorkflowFileRuntime())

api/core/app/workflow/node_factory.py

@@ -1,28 +1,42 @@
-from collections.abc import Callable, Sequence
-from typing import TYPE_CHECKING, final
+from collections.abc import Mapping
+from typing import TYPE_CHECKING, Any, cast, final
 
 from typing_extensions import override
 
 from configs import dify_config
-from core.file.file_manager import file_manager
-from core.helper.code_executor.code_executor import CodeExecutor
+from core.app.llm.model_access import build_dify_model_access
+from core.datasource.datasource_manager import DatasourceManager
+from core.helper.code_executor.code_executor import CodeExecutionError, CodeExecutor
 from core.helper.code_executor.code_node_provider import CodeNodeProvider
 from core.helper.ssrf_proxy import ssrf_proxy
+from core.model_manager import ModelInstance
+from core.model_runtime.entities.model_entities import ModelType
+from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel
+from core.prompt.entities.advanced_prompt_entities import MemoryConfig
 from core.rag.retrieval.dataset_retrieval import DatasetRetrieval
 from core.tools.tool_file_manager import ToolFileManager
 from core.workflow.entities.graph_config import NodeConfigDict
 from core.workflow.enums import NodeType
+from core.workflow.file.file_manager import file_manager
 from core.workflow.graph.graph import NodeFactory
 from core.workflow.nodes.base.node import Node
-from core.workflow.nodes.code.code_node import CodeNode
+from core.workflow.nodes.code.code_node import CodeNode, WorkflowCodeExecutor
+from core.workflow.nodes.code.entities import CodeLanguage
 from core.workflow.nodes.code.limits import CodeNodeLimits
-from core.workflow.nodes.http_request.node import HttpRequestNode
+from core.workflow.nodes.datasource import DatasourceNode
+from core.workflow.nodes.document_extractor import DocumentExtractorNode, UnstructuredApiConfig
+from core.workflow.nodes.http_request import HttpRequestNode, build_http_request_config
 from core.workflow.nodes.knowledge_retrieval.knowledge_retrieval_node import KnowledgeRetrievalNode
+from core.workflow.nodes.llm import llm_utils
+from core.workflow.nodes.llm.entities import ModelConfig
+from core.workflow.nodes.llm.exc import LLMModeRequiredError, ModelNotExistError
+from core.workflow.nodes.llm.node import LLMNode
+from core.workflow.nodes.llm.protocols import PromptMessageMemory
 from core.workflow.nodes.node_mapping import LATEST_VERSION, NODE_TYPE_CLASSES_MAPPING
-from core.workflow.nodes.protocols import FileManagerProtocol, HttpClientProtocol
+from core.workflow.nodes.parameter_extractor.parameter_extractor_node import ParameterExtractorNode
+from core.workflow.nodes.question_classifier.question_classifier_node import QuestionClassifierNode
 from core.workflow.nodes.template_transform.template_renderer import (
     CodeExecutorJinja2TemplateRenderer,
-    Jinja2TemplateRenderer,
 )
 from core.workflow.nodes.template_transform.template_transform_node import TemplateTransformNode
 
@@ -31,6 +45,24 @@ if TYPE_CHECKING:
     from core.workflow.runtime import GraphRuntimeState
 
 
+class DefaultWorkflowCodeExecutor:
+    def execute(
+        self,
+        *,
+        language: CodeLanguage,
+        code: str,
+        inputs: Mapping[str, Any],
+    ) -> Mapping[str, Any]:
+        return CodeExecutor.execute_workflow_code_template(
+            language=language,
+            code=code,
+            inputs=inputs,
+        )
+
+    def is_execution_error(self, error: Exception) -> bool:
+        return isinstance(error, CodeExecutionError)
+
+
 @final
 class DifyNodeFactory(NodeFactory):
     """
@@ -44,23 +76,12 @@ class DifyNodeFactory(NodeFactory):
         self,
         graph_init_params: "GraphInitParams",
         graph_runtime_state: "GraphRuntimeState",
-        *,
-        code_executor: type[CodeExecutor] | None = None,
-        code_providers: Sequence[type[CodeNodeProvider]] | None = None,
-        code_limits: CodeNodeLimits | None = None,
-        template_renderer: Jinja2TemplateRenderer | None = None,
-        template_transform_max_output_length: int | None = None,
-        http_request_http_client: HttpClientProtocol | None = None,
-        http_request_tool_file_manager_factory: Callable[[], ToolFileManager] = ToolFileManager,
-        http_request_file_manager: FileManagerProtocol | None = None,
     ) -> None:
         self.graph_init_params = graph_init_params
         self.graph_runtime_state = graph_runtime_state
-        self._code_executor: type[CodeExecutor] = code_executor or CodeExecutor
-        self._code_providers: tuple[type[CodeNodeProvider], ...] = (
-            tuple(code_providers) if code_providers else CodeNode.default_code_providers()
-        )
-        self._code_limits = code_limits or CodeNodeLimits(
+        self._code_executor: WorkflowCodeExecutor = DefaultWorkflowCodeExecutor()
+        self._code_providers: tuple[type[CodeNodeProvider], ...] = CodeNode.default_code_providers()
+        self._code_limits = CodeNodeLimits(
             max_string_length=dify_config.CODE_MAX_STRING_LENGTH,
             max_number=dify_config.CODE_MAX_NUMBER,
             min_number=dify_config.CODE_MIN_NUMBER,
@@ -70,14 +91,27 @@ class DifyNodeFactory(NodeFactory):
             max_string_array_length=dify_config.CODE_MAX_STRING_ARRAY_LENGTH,
             max_object_array_length=dify_config.CODE_MAX_OBJECT_ARRAY_LENGTH,
         )
-        self._template_renderer = template_renderer or CodeExecutorJinja2TemplateRenderer()
-        self._template_transform_max_output_length = (
-            template_transform_max_output_length or dify_config.TEMPLATE_TRANSFORM_MAX_LENGTH
-        )
-        self._http_request_http_client = http_request_http_client or ssrf_proxy
-        self._http_request_tool_file_manager_factory = http_request_tool_file_manager_factory
-        self._http_request_file_manager = http_request_file_manager or file_manager
+        self._template_renderer = CodeExecutorJinja2TemplateRenderer()
+        self._template_transform_max_output_length = dify_config.TEMPLATE_TRANSFORM_MAX_LENGTH
+        self._http_request_http_client = ssrf_proxy
+        self._http_request_tool_file_manager_factory = ToolFileManager
+        self._http_request_file_manager = file_manager
         self._rag_retrieval = DatasetRetrieval()
+        self._document_extractor_unstructured_api_config = UnstructuredApiConfig(
+            api_url=dify_config.UNSTRUCTURED_API_URL,
+            api_key=dify_config.UNSTRUCTURED_API_KEY or "",
+        )
+        self._http_request_config = build_http_request_config(
+            max_connect_timeout=dify_config.HTTP_REQUEST_MAX_CONNECT_TIMEOUT,
+            max_read_timeout=dify_config.HTTP_REQUEST_MAX_READ_TIMEOUT,
+            max_write_timeout=dify_config.HTTP_REQUEST_MAX_WRITE_TIMEOUT,
+            max_binary_size=dify_config.HTTP_REQUEST_NODE_MAX_BINARY_SIZE,
+            max_text_size=dify_config.HTTP_REQUEST_NODE_MAX_TEXT_SIZE,
+            ssl_verify=dify_config.HTTP_REQUEST_NODE_SSL_VERIFY,
+            ssrf_default_max_retries=dify_config.SSRF_DEFAULT_MAX_RETRIES,
+        )
+
+        self._llm_credentials_provider, self._llm_model_factory = build_dify_model_access(graph_init_params.tenant_id)
 
     @override
     def create_node(self, node_config: NodeConfigDict) -> Node:
@@ -138,11 +172,35 @@ class DifyNodeFactory(NodeFactory):
                 config=node_config,
                 graph_init_params=self.graph_init_params,
                 graph_runtime_state=self.graph_runtime_state,
+                http_request_config=self._http_request_config,
                 http_client=self._http_request_http_client,
                 tool_file_manager_factory=self._http_request_tool_file_manager_factory,
                 file_manager=self._http_request_file_manager,
             )
 
+        if node_type == NodeType.LLM:
+            model_instance = self._build_model_instance_for_llm_node(node_data)
+            memory = self._build_memory_for_llm_node(node_data=node_data, model_instance=model_instance)
+            return LLMNode(
+                id=node_id,
+                config=node_config,
+                graph_init_params=self.graph_init_params,
+                graph_runtime_state=self.graph_runtime_state,
+                credentials_provider=self._llm_credentials_provider,
+                model_factory=self._llm_model_factory,
+                model_instance=model_instance,
+                memory=memory,
+            )
+
+        if node_type == NodeType.DATASOURCE:
+            return DatasourceNode(
+                id=node_id,
+                config=node_config,
+                graph_init_params=self.graph_init_params,
+                graph_runtime_state=self.graph_runtime_state,
+                datasource_manager=DatasourceManager,
+            )
+
         if node_type == NodeType.KNOWLEDGE_RETRIEVAL:
             return KnowledgeRetrievalNode(
                 id=node_id,
@@ -152,9 +210,94 @@ class DifyNodeFactory(NodeFactory):
                 rag_retrieval=self._rag_retrieval,
             )
 
+        if node_type == NodeType.DOCUMENT_EXTRACTOR:
+            return DocumentExtractorNode(
+                id=node_id,
+                config=node_config,
+                graph_init_params=self.graph_init_params,
+                graph_runtime_state=self.graph_runtime_state,
+                unstructured_api_config=self._document_extractor_unstructured_api_config,
+            )
+
+        if node_type == NodeType.QUESTION_CLASSIFIER:
+            model_instance = self._build_model_instance_for_llm_node(node_data)
+            return QuestionClassifierNode(
+                id=node_id,
+                config=node_config,
+                graph_init_params=self.graph_init_params,
+                graph_runtime_state=self.graph_runtime_state,
+                credentials_provider=self._llm_credentials_provider,
+                model_factory=self._llm_model_factory,
+                model_instance=model_instance,
+            )
+
+        if node_type == NodeType.PARAMETER_EXTRACTOR:
+            model_instance = self._build_model_instance_for_llm_node(node_data)
+            return ParameterExtractorNode(
+                id=node_id,
+                config=node_config,
+                graph_init_params=self.graph_init_params,
+                graph_runtime_state=self.graph_runtime_state,
+                credentials_provider=self._llm_credentials_provider,
+                model_factory=self._llm_model_factory,
+                model_instance=model_instance,
+            )
+
         return node_class(
             id=node_id,
             config=node_config,
             graph_init_params=self.graph_init_params,
             graph_runtime_state=self.graph_runtime_state,
         )
+
+    def _build_model_instance_for_llm_node(self, node_data: Mapping[str, Any]) -> ModelInstance:
+        node_data_model = ModelConfig.model_validate(node_data["model"])
+        if not node_data_model.mode:
+            raise LLMModeRequiredError("LLM mode is required.")
+
+        credentials = self._llm_credentials_provider.fetch(node_data_model.provider, node_data_model.name)
+        model_instance = self._llm_model_factory.init_model_instance(node_data_model.provider, node_data_model.name)
+        provider_model_bundle = model_instance.provider_model_bundle
+
+        provider_model = provider_model_bundle.configuration.get_provider_model(
+            model=node_data_model.name,
+            model_type=ModelType.LLM,
+        )
+        if provider_model is None:
+            raise ModelNotExistError(f"Model {node_data_model.name} not exist.")
+        provider_model.raise_for_status()
+
+        completion_params = dict(node_data_model.completion_params)
+        stop = completion_params.pop("stop", [])
+        if not isinstance(stop, list):
+            stop = []
+
+        model_schema = model_instance.model_type_instance.get_model_schema(node_data_model.name, credentials)
+        if not model_schema:
+            raise ModelNotExistError(f"Model {node_data_model.name} not exist.")
+
+        model_instance.provider = node_data_model.provider
+        model_instance.model_name = node_data_model.name
+        model_instance.credentials = credentials
+        model_instance.parameters = completion_params
+        model_instance.stop = tuple(stop)
+        model_instance.model_type_instance = cast(LargeLanguageModel, model_instance.model_type_instance)
+        return model_instance
+
+    def _build_memory_for_llm_node(
+        self,
+        *,
+        node_data: Mapping[str, Any],
+        model_instance: ModelInstance,
+    ) -> PromptMessageMemory | None:
+        raw_memory_config = node_data.get("memory")
+        if raw_memory_config is None:
+            return None
+
+        node_memory = MemoryConfig.model_validate(raw_memory_config)
+        return llm_utils.fetch_memory(
+            variable_pool=self.graph_runtime_state.variable_pool,
+            app_id=self.graph_init_params.app_id,
+            node_data_memory=node_memory,
+            model_instance=model_instance,
+        )

api/core/datasource/datasource_file_manager.py

@@ -213,6 +213,6 @@ class DatasourceFileManager:
 
 
 # init tool_file_parser
-# from core.file.datasource_file_parser import datasource_file_manager
+# from core.workflow.file.datasource_file_parser import datasource_file_manager
 #
 # datasource_file_manager["manager"] = DatasourceFileManager

api/core/datasource/datasource_manager.py

@@ -1,16 +1,39 @@
 import logging
+from collections.abc import Generator
 from threading import Lock
+from typing import Any, cast
+
+from sqlalchemy import select
 
 import contexts
 from core.datasource.__base.datasource_plugin import DatasourcePlugin
 from core.datasource.__base.datasource_provider import DatasourcePluginProviderController
-from core.datasource.entities.datasource_entities import DatasourceProviderType
+from core.datasource.entities.datasource_entities import (
+    DatasourceMessage,
+    DatasourceProviderType,
+    GetOnlineDocumentPageContentRequest,
+    OnlineDriveDownloadFileRequest,
+)
 from core.datasource.errors import DatasourceProviderNotFoundError
 from core.datasource.local_file.local_file_provider import LocalFileDatasourcePluginProviderController
+from core.datasource.online_document.online_document_plugin import OnlineDocumentDatasourcePlugin
 from core.datasource.online_document.online_document_provider import OnlineDocumentDatasourcePluginProviderController
+from core.datasource.online_drive.online_drive_plugin import OnlineDriveDatasourcePlugin
 from core.datasource.online_drive.online_drive_provider import OnlineDriveDatasourcePluginProviderController
+from core.datasource.utils.message_transformer import DatasourceFileMessageTransformer
 from core.datasource.website_crawl.website_crawl_provider import WebsiteCrawlDatasourcePluginProviderController
+from core.db.session_factory import session_factory
 from core.plugin.impl.datasource import PluginDatasourceManager
+from core.workflow.entities.workflow_node_execution import WorkflowNodeExecutionStatus
+from core.workflow.enums import WorkflowNodeExecutionMetadataKey
+from core.workflow.file import File
+from core.workflow.file.enums import FileTransferMethod, FileType
+from core.workflow.node_events import NodeRunResult, StreamChunkEvent, StreamCompletedEvent
+from core.workflow.repositories.datasource_manager_protocol import DatasourceParameter, OnlineDriveDownloadFileParam
+from factories import file_factory
+from models.model import UploadFile
+from models.tools import ToolFile
+from services.datasource_provider_service import DatasourceProviderService
 
 logger = logging.getLogger(__name__)
 
@@ -103,3 +126,238 @@ class DatasourceManager:
             tenant_id,
             datasource_type,
         ).get_datasource(datasource_name)
+
+    @classmethod
+    def get_icon_url(cls, provider_id: str, tenant_id: str, datasource_name: str, datasource_type: str) -> str:
+        datasource_runtime = cls.get_datasource_runtime(
+            provider_id=provider_id,
+            datasource_name=datasource_name,
+            tenant_id=tenant_id,
+            datasource_type=DatasourceProviderType.value_of(datasource_type),
+        )
+        return datasource_runtime.get_icon_url(tenant_id)
+
+    @classmethod
+    def stream_online_results(
+        cls,
+        *,
+        user_id: str,
+        datasource_name: str,
+        datasource_type: str,
+        provider_id: str,
+        tenant_id: str,
+        provider: str,
+        plugin_id: str,
+        credential_id: str,
+        datasource_param: DatasourceParameter | None = None,
+        online_drive_request: OnlineDriveDownloadFileParam | None = None,
+    ) -> Generator[DatasourceMessage, None, Any]:
+        """
+        Pull-based streaming of domain messages from datasource plugins.
+        Returns a generator that yields DatasourceMessage and finally returns a minimal final payload.
+        Only ONLINE_DOCUMENT and ONLINE_DRIVE are streamable here; other types are handled by nodes directly.
+        """
+        ds_type = DatasourceProviderType.value_of(datasource_type)
+        runtime = cls.get_datasource_runtime(
+            provider_id=provider_id,
+            datasource_name=datasource_name,
+            tenant_id=tenant_id,
+            datasource_type=ds_type,
+        )
+
+        dsp_service = DatasourceProviderService()
+        credentials = dsp_service.get_datasource_credentials(
+            tenant_id=tenant_id,
+            provider=provider,
+            plugin_id=plugin_id,
+            credential_id=credential_id,
+        )
+
+        if ds_type == DatasourceProviderType.ONLINE_DOCUMENT:
+            doc_runtime = cast(OnlineDocumentDatasourcePlugin, runtime)
+            if credentials:
+                doc_runtime.runtime.credentials = credentials
+            if datasource_param is None:
+                raise ValueError("datasource_param is required for ONLINE_DOCUMENT streaming")
+            inner_gen: Generator[DatasourceMessage, None, None] = doc_runtime.get_online_document_page_content(
+                user_id=user_id,
+                datasource_parameters=GetOnlineDocumentPageContentRequest(
+                    workspace_id=datasource_param.workspace_id,
+                    page_id=datasource_param.page_id,
+                    type=datasource_param.type,
+                ),
+                provider_type=ds_type,
+            )
+        elif ds_type == DatasourceProviderType.ONLINE_DRIVE:
+            drive_runtime = cast(OnlineDriveDatasourcePlugin, runtime)
+            if credentials:
+                drive_runtime.runtime.credentials = credentials
+            if online_drive_request is None:
+                raise ValueError("online_drive_request is required for ONLINE_DRIVE streaming")
+            inner_gen = drive_runtime.online_drive_download_file(
+                user_id=user_id,
+                request=OnlineDriveDownloadFileRequest(
+                    id=online_drive_request.id,
+                    bucket=online_drive_request.bucket,
+                ),
+                provider_type=ds_type,
+            )
+        else:
+            raise ValueError(f"Unsupported datasource type for streaming: {ds_type}")
+
+        # Bridge through to caller while preserving generator return contract
+        yield from inner_gen
+        # No structured final data here; node/adapter will assemble outputs
+        return {}
+
+    @classmethod
+    def stream_node_events(
+        cls,
+        *,
+        node_id: str,
+        user_id: str,
+        datasource_name: str,
+        datasource_type: str,
+        provider_id: str,
+        tenant_id: str,
+        provider: str,
+        plugin_id: str,
+        credential_id: str,
+        parameters_for_log: dict[str, Any],
+        datasource_info: dict[str, Any],
+        variable_pool: Any,
+        datasource_param: DatasourceParameter | None = None,
+        online_drive_request: OnlineDriveDownloadFileParam | None = None,
+    ) -> Generator[StreamChunkEvent | StreamCompletedEvent, None, None]:
+        ds_type = DatasourceProviderType.value_of(datasource_type)
+
+        messages = cls.stream_online_results(
+            user_id=user_id,
+            datasource_name=datasource_name,
+            datasource_type=datasource_type,
+            provider_id=provider_id,
+            tenant_id=tenant_id,
+            provider=provider,
+            plugin_id=plugin_id,
+            credential_id=credential_id,
+            datasource_param=datasource_param,
+            online_drive_request=online_drive_request,
+        )
+
+        transformed = DatasourceFileMessageTransformer.transform_datasource_invoke_messages(
+            messages=messages, user_id=user_id, tenant_id=tenant_id, conversation_id=None
+        )
+
+        variables: dict[str, Any] = {}
+        file_out: File | None = None
+
+        for message in transformed:
+            mtype = message.type
+            if mtype in {
+                DatasourceMessage.MessageType.IMAGE_LINK,
+                DatasourceMessage.MessageType.BINARY_LINK,
+                DatasourceMessage.MessageType.IMAGE,
+            }:
+                wanted_ds_type = ds_type in {
+                    DatasourceProviderType.ONLINE_DRIVE,
+                    DatasourceProviderType.ONLINE_DOCUMENT,
+                }
+                if wanted_ds_type and isinstance(message.message, DatasourceMessage.TextMessage):
+                    url = message.message.text
+
+                    datasource_file_id = str(url).split("/")[-1].split(".")[0]
+                    with session_factory.create_session() as session:
+                        stmt = select(ToolFile).where(
+                            ToolFile.id == datasource_file_id, ToolFile.tenant_id == tenant_id
+                        )
+                        datasource_file = session.scalar(stmt)
+                        if not datasource_file:
+                            raise ValueError(
+                                f"ToolFile not found for file_id={datasource_file_id}, tenant_id={tenant_id}"
+                            )
+                        mime_type = datasource_file.mimetype
+                    if datasource_file is not None:
+                        mapping = {
+                            "tool_file_id": datasource_file_id,
+                            "type": file_factory.get_file_type_by_mime_type(mime_type),
+                            "transfer_method": FileTransferMethod.TOOL_FILE,
+                            "url": url,
+                        }
+                        file_out = file_factory.build_from_mapping(mapping=mapping, tenant_id=tenant_id)
+            elif mtype == DatasourceMessage.MessageType.TEXT:
+                assert isinstance(message.message, DatasourceMessage.TextMessage)
+                yield StreamChunkEvent(selector=[node_id, "text"], chunk=message.message.text, is_final=False)
+            elif mtype == DatasourceMessage.MessageType.LINK:
+                assert isinstance(message.message, DatasourceMessage.TextMessage)
+                yield StreamChunkEvent(
+                    selector=[node_id, "text"], chunk=f"Link: {message.message.text}\n", is_final=False
+                )
+            elif mtype == DatasourceMessage.MessageType.VARIABLE:
+                assert isinstance(message.message, DatasourceMessage.VariableMessage)
+                name = message.message.variable_name
+                value = message.message.variable_value
+                if message.message.stream:
+                    assert isinstance(value, str), "stream variable_value must be str"
+                    variables[name] = variables.get(name, "") + value
+                    yield StreamChunkEvent(selector=[node_id, name], chunk=value, is_final=False)
+                else:
+                    variables[name] = value
+            elif mtype == DatasourceMessage.MessageType.FILE:
+                if ds_type == DatasourceProviderType.ONLINE_DRIVE and message.meta:
+                    f = message.meta.get("file")
+                    if isinstance(f, File):
+                        file_out = f
+            else:
+                pass
+
+        yield StreamChunkEvent(selector=[node_id, "text"], chunk="", is_final=True)
+
+        if ds_type == DatasourceProviderType.ONLINE_DRIVE and file_out is not None:
+            variable_pool.add([node_id, "file"], file_out)
+
+        if ds_type == DatasourceProviderType.ONLINE_DOCUMENT:
+            yield StreamCompletedEvent(
+                node_run_result=NodeRunResult(
+                    status=WorkflowNodeExecutionStatus.SUCCEEDED,
+                    inputs=parameters_for_log,
+                    metadata={WorkflowNodeExecutionMetadataKey.DATASOURCE_INFO: datasource_info},
+                    outputs={**variables},
+                )
+            )
+        else:
+            yield StreamCompletedEvent(
+                node_run_result=NodeRunResult(
+                    status=WorkflowNodeExecutionStatus.SUCCEEDED,
+                    inputs=parameters_for_log,
+                    metadata={WorkflowNodeExecutionMetadataKey.DATASOURCE_INFO: datasource_info},
+                    outputs={
+                        "file": file_out,
+                        "datasource_type": ds_type,
+                    },
+                )
+            )
+
+    @classmethod
+    def get_upload_file_by_id(cls, file_id: str, tenant_id: str) -> File:
+        with session_factory.create_session() as session:
+            upload_file = (
+                session.query(UploadFile).where(UploadFile.id == file_id, UploadFile.tenant_id == tenant_id).first()
+            )
+            if not upload_file:
+                raise ValueError(f"UploadFile not found for file_id={file_id}, tenant_id={tenant_id}")
+
+        file_info = File(
+            id=upload_file.id,
+            filename=upload_file.name,
+            extension="." + upload_file.extension,
+            mime_type=upload_file.mime_type,
+            tenant_id=tenant_id,
+            type=FileType.CUSTOM,
+            transfer_method=FileTransferMethod.LOCAL_FILE,
+            remote_url=upload_file.source_url,
+            related_id=upload_file.id,
+            size=upload_file.size,
+            storage_key=upload_file.key,
+            url=upload_file.source_url,
+        )
+        return file_info

api/core/datasource/entities/datasource_entities.py

@@ -379,4 +379,11 @@ class OnlineDriveDownloadFileRequest(BaseModel):
     """
 
     id: str = Field(..., description="The id of the file")
-    bucket: str | None = Field(None, description="The name of the bucket")
+    bucket: str = Field("", description="The name of the bucket")
+
+    @field_validator("bucket", mode="before")
+    @classmethod
+    def _coerce_bucket(cls, v) -> str:
+        if v is None:
+            return ""
+        return str(v)

api/core/datasource/utils/message_transformer.py

@@ -3,8 +3,8 @@ from collections.abc import Generator
 from mimetypes import guess_extension, guess_type
 
 from core.datasource.entities.datasource_entities import DatasourceMessage
-from core.file import File, FileTransferMethod, FileType
 from core.tools.tool_file_manager import ToolFileManager
+from core.workflow.file import File, FileTransferMethod, FileType
 from models.tools import ToolFile
 
 logger = logging.getLogger(__name__)

api/core/entities/mcp_provider.py

@@ -10,12 +10,12 @@ from pydantic import BaseModel
 
 from configs import dify_config
 from core.entities.provider_entities import BasicProviderConfig
-from core.file import helpers as file_helpers
 from core.helper import encrypter
 from core.helper.provider_cache import NoOpProviderCredentialCache
 from core.mcp.types import OAuthClientInformation, OAuthClientMetadata, OAuthTokens
 from core.tools.entities.common_entities import I18nObject
 from core.tools.entities.tool_entities import ToolProviderType
+from core.workflow.file import helpers as file_helpers
 
 if TYPE_CHECKING:
     from models.tools import MCPToolProvider

api/core/file/tool_file_parser.py

@@ -1,12 +0,0 @@
-from collections.abc import Callable
-from typing import TYPE_CHECKING
-
-if TYPE_CHECKING:
-    from core.tools.tool_file_manager import ToolFileManager
-
-_tool_file_manager_factory: Callable[[], "ToolFileManager"] | None = None
-
-
-def set_tool_file_manager_factory(factory: Callable[[], "ToolFileManager"]):
-    global _tool_file_manager_factory
-    _tool_file_manager_factory = factory

api/core/helper/code_executor/template_transformer.py

@@ -5,7 +5,7 @@ from base64 import b64encode
 from collections.abc import Mapping
 from typing import Any
 
-from core.variables.utils import dumps_with_segments
+from core.workflow.variables.utils import dumps_with_segments
 
 
 class TemplateTransformer(ABC):

api/core/memory/token_buffer_memory.py

@@ -4,7 +4,6 @@ from sqlalchemy import select
 from sqlalchemy.orm import sessionmaker
 
 from core.app.app_config.features.file_upload.manager import FileUploadConfigManager
-from core.file import file_manager
 from core.model_manager import ModelInstance
 from core.model_runtime.entities import (
     AssistantPromptMessage,
@@ -16,6 +15,7 @@ from core.model_runtime.entities import (
 )
 from core.model_runtime.entities.message_entities import PromptMessageContentUnionTypes
 from core.prompt.utils.extract_thread_messages import extract_thread_messages
+from core.workflow.file import file_manager
 from extensions.ext_database import db
 from factories import file_factory
 from models.model import AppMode, Conversation, Message, MessageFile

api/core/model_manager.py

@@ -1,5 +1,5 @@
 import logging
-from collections.abc import Callable, Generator, Iterable, Sequence
+from collections.abc import Callable, Generator, Iterable, Mapping, Sequence
 from typing import IO, Any, Literal, Optional, Union, cast, overload
 
 from configs import dify_config
@@ -35,9 +35,12 @@ class ModelInstance:
 
     def __init__(self, provider_model_bundle: ProviderModelBundle, model: str):
         self.provider_model_bundle = provider_model_bundle
-        self.model = model
+        self.model_name = model
         self.provider = provider_model_bundle.configuration.provider.provider
         self.credentials = self._fetch_credentials_from_bundle(provider_model_bundle, model)
+        # Runtime LLM invocation fields.
+        self.parameters: Mapping[str, Any] = {}
+        self.stop: Sequence[str] = ()
         self.model_type_instance = self.provider_model_bundle.model_type_instance
         self.load_balancing_manager = self._get_load_balancing_manager(
             configuration=provider_model_bundle.configuration,
@@ -163,7 +166,7 @@ class ModelInstance:
             Union[LLMResult, Generator],
             self._round_robin_invoke(
                 function=self.model_type_instance.invoke,
-                model=self.model,
+                model=self.model_name,
                 credentials=self.credentials,
                 prompt_messages=prompt_messages,
                 model_parameters=model_parameters,
@@ -191,7 +194,7 @@ class ModelInstance:
             int,
             self._round_robin_invoke(
                 function=self.model_type_instance.get_num_tokens,
-                model=self.model,
+                model=self.model_name,
                 credentials=self.credentials,
                 prompt_messages=prompt_messages,
                 tools=tools,
@@ -215,7 +218,7 @@ class ModelInstance:
             EmbeddingResult,
             self._round_robin_invoke(
                 function=self.model_type_instance.invoke,
-                model=self.model,
+                model=self.model_name,
                 credentials=self.credentials,
                 texts=texts,
                 user=user,
@@ -243,7 +246,7 @@ class ModelInstance:
             EmbeddingResult,
             self._round_robin_invoke(
                 function=self.model_type_instance.invoke,
-                model=self.model,
+                model=self.model_name,
                 credentials=self.credentials,
                 multimodel_documents=multimodel_documents,
                 user=user,
@@ -264,7 +267,7 @@ class ModelInstance:
             list[int],
             self._round_robin_invoke(
                 function=self.model_type_instance.get_num_tokens,
-                model=self.model,
+                model=self.model_name,
                 credentials=self.credentials,
                 texts=texts,
             ),
@@ -294,7 +297,7 @@ class ModelInstance:
             RerankResult,
             self._round_robin_invoke(
                 function=self.model_type_instance.invoke,
-                model=self.model,
+                model=self.model_name,
                 credentials=self.credentials,
                 query=query,
                 docs=docs,
@@ -328,7 +331,7 @@ class ModelInstance:
             RerankResult,
             self._round_robin_invoke(
                 function=self.model_type_instance.invoke_multimodal_rerank,
-                model=self.model,
+                model=self.model_name,
                 credentials=self.credentials,
                 query=query,
                 docs=docs,
@@ -352,7 +355,7 @@ class ModelInstance:
             bool,
             self._round_robin_invoke(
                 function=self.model_type_instance.invoke,
-                model=self.model,
+                model=self.model_name,
                 credentials=self.credentials,
                 text=text,
                 user=user,
@@ -373,7 +376,7 @@ class ModelInstance:
             str,
             self._round_robin_invoke(
                 function=self.model_type_instance.invoke,
-                model=self.model,
+                model=self.model_name,
                 credentials=self.credentials,
                 file=file,
                 user=user,
@@ -396,7 +399,7 @@ class ModelInstance:
             Iterable[bytes],
             self._round_robin_invoke(
                 function=self.model_type_instance.invoke,
-                model=self.model,
+                model=self.model_name,
                 credentials=self.credentials,
                 content_text=content_text,
                 user=user,
@@ -469,7 +472,7 @@ class ModelInstance:
         if not isinstance(self.model_type_instance, TTSModel):
             raise Exception("Model type instance is not TTSModel")
         return self.model_type_instance.get_tts_model_voices(
-            model=self.model, credentials=self.credentials, language=language
+            model=self.model_name, credentials=self.credentials, language=language
         )
 
 

api/core/moderation/base.py

@@ -39,7 +39,7 @@ class Moderation(Extensible, ABC):
 
     @classmethod
     @abstractmethod
-    def validate_config(cls, tenant_id: str, config: dict):
+    def validate_config(cls, tenant_id: str, config: dict) -> None:
         """
         Validate the incoming form config data.
 

api/core/ops/aliyun_trace/aliyun_trace.py

@@ -14,6 +14,7 @@ from core.ops.aliyun_trace.data_exporter.traceclient import (
 )
 from core.ops.aliyun_trace.entities.aliyun_trace_entity import SpanData, TraceMetadata
 from core.ops.aliyun_trace.entities.semconv import (
+    DIFY_APP_ID,
     GEN_AI_COMPLETION,
     GEN_AI_INPUT_MESSAGE,
     GEN_AI_OUTPUT_MESSAGE,
@@ -99,6 +100,16 @@ class AliyunDataTrace(BaseTraceInstance):
             logger.info("Aliyun get project url failed: %s", str(e), exc_info=True)
             raise ValueError(f"Aliyun get project url failed: {str(e)}")
 
+    def _extract_app_id(self, trace_info: BaseTraceInfo) -> str:
+        """Extract app_id from trace_info, trying metadata first then message_data."""
+        app_id = trace_info.metadata.get("app_id")
+        if app_id:
+            return str(app_id)
+        message_data = getattr(trace_info, "message_data", None)
+        if message_data is not None:
+            return str(getattr(message_data, "app_id", ""))
+        return ""
+
     def workflow_trace(self, trace_info: WorkflowTraceInfo):
         trace_metadata = TraceMetadata(
             trace_id=convert_to_trace_id(trace_info.workflow_run_id),
@@ -143,13 +154,16 @@ class AliyunDataTrace(BaseTraceInstance):
             name="message",
             start_time=convert_datetime_to_nanoseconds(trace_info.start_time),
             end_time=convert_datetime_to_nanoseconds(trace_info.end_time),
-            attributes=create_common_span_attributes(
-                session_id=trace_metadata.session_id,
-                user_id=trace_metadata.user_id,
-                span_kind=GenAISpanKind.CHAIN,
-                inputs=inputs_json,
-                outputs=outputs_str,
-            ),
+            attributes={
+                **create_common_span_attributes(
+                    session_id=trace_metadata.session_id,
+                    user_id=trace_metadata.user_id,
+                    span_kind=GenAISpanKind.CHAIN,
+                    inputs=inputs_json,
+                    outputs=outputs_str,
+                ),
+                DIFY_APP_ID: self._extract_app_id(trace_info),
+            },
             status=status,
             links=trace_metadata.links,
             span_kind=SpanKind.SERVER,
@@ -441,6 +455,8 @@ class AliyunDataTrace(BaseTraceInstance):
         inputs_json = serialize_json_data(trace_info.workflow_run_inputs)
         outputs_json = serialize_json_data(trace_info.workflow_run_outputs)
 
+        app_id = self._extract_app_id(trace_info)
+
         if message_span_id:
             message_span = SpanData(
                 trace_id=trace_metadata.trace_id,
@@ -449,13 +465,16 @@ class AliyunDataTrace(BaseTraceInstance):
                 name="message",
                 start_time=convert_datetime_to_nanoseconds(trace_info.start_time),
                 end_time=convert_datetime_to_nanoseconds(trace_info.end_time),
-                attributes=create_common_span_attributes(
-                    session_id=trace_metadata.session_id,
-                    user_id=trace_metadata.user_id,
-                    span_kind=GenAISpanKind.CHAIN,
-                    inputs=trace_info.workflow_run_inputs.get("sys.query") or "",
-                    outputs=outputs_json,
-                ),
+                attributes={
+                    **create_common_span_attributes(
+                        session_id=trace_metadata.session_id,
+                        user_id=trace_metadata.user_id,
+                        span_kind=GenAISpanKind.CHAIN,
+                        inputs=trace_info.workflow_run_inputs.get("sys.query") or "",
+                        outputs=outputs_json,
+                    ),
+                    DIFY_APP_ID: app_id,
+                },
                 status=status,
                 links=trace_metadata.links,
                 span_kind=SpanKind.SERVER,
@@ -469,13 +488,16 @@ class AliyunDataTrace(BaseTraceInstance):
             name="workflow",
             start_time=convert_datetime_to_nanoseconds(trace_info.start_time),
             end_time=convert_datetime_to_nanoseconds(trace_info.end_time),
-            attributes=create_common_span_attributes(
-                session_id=trace_metadata.session_id,
-                user_id=trace_metadata.user_id,
-                span_kind=GenAISpanKind.CHAIN,
-                inputs=inputs_json,
-                outputs=outputs_json,
-            ),
+            attributes={
+                **create_common_span_attributes(
+                    session_id=trace_metadata.session_id,
+                    user_id=trace_metadata.user_id,
+                    span_kind=GenAISpanKind.CHAIN,
+                    inputs=inputs_json,
+                    outputs=outputs_json,
+                ),
+                **({DIFY_APP_ID: app_id} if message_span_id is None else {}),
+            },
             status=status,
             links=trace_metadata.links,
             span_kind=SpanKind.SERVER if message_span_id is None else SpanKind.INTERNAL,

api/core/ops/aliyun_trace/entities/semconv.py

@@ -3,6 +3,9 @@ from typing import Final
 
 ACS_ARMS_SERVICE_FEATURE: Final[str] = "acs.arms.service.feature"
 
+# Dify-specific attributes
+DIFY_APP_ID: Final[str] = "dify.app_id"
+
 # Public attributes
 GEN_AI_SESSION_ID: Final[str] = "gen_ai.session.id"
 GEN_AI_USER_ID: Final[str] = "gen_ai.user.id"

api/core/ops/langfuse_trace/entities/langfuse_trace_entity.py

@@ -129,11 +129,11 @@ class LangfuseSpan(BaseModel):
         default=None,
         description="The id of the user that triggered the execution. Used to provide user-level analytics.",
     )
-    start_time: datetime | str | None = Field(
+    start_time: datetime | None = Field(
         default_factory=datetime.now,
         description="The time at which the span started, defaults to the current time.",
     )
-    end_time: datetime | str | None = Field(
+    end_time: datetime | None = Field(
         default=None,
         description="The time at which the span ended. Automatically set by span.end().",
     )
@@ -146,7 +146,7 @@ class LangfuseSpan(BaseModel):
         description="Additional metadata of the span. Can be any JSON object. Metadata is merged when being updated "
         "via the API.",
     )
-    level: str | None = Field(
+    level: LevelEnum | None = Field(
         default=None,
         description="The level of the span. Can be DEBUG, DEFAULT, WARNING or ERROR. Used for sorting/filtering of "
         "traces with elevated error levels and for highlighting in the UI.",
@@ -222,16 +222,16 @@ class LangfuseGeneration(BaseModel):
         default=None,
         description="Identifier of the generation. Useful for sorting/filtering in the UI.",
     )
-    start_time: datetime | str | None = Field(
+    start_time: datetime | None = Field(
         default_factory=datetime.now,
         description="The time at which the generation started, defaults to the current time.",
     )
-    completion_start_time: datetime | str | None = Field(
+    completion_start_time: datetime | None = Field(
         default=None,
         description="The time at which the completion started (streaming). Set it to get latency analytics broken "
         "down into time until completion started and completion duration.",
     )
-    end_time: datetime | str | None = Field(
+    end_time: datetime | None = Field(
         default=None,
         description="The time at which the generation ended. Automatically set by generation.end().",
     )

api/core/ops/tencent_trace/client.py

@@ -18,8 +18,7 @@ except ImportError:
     from importlib_metadata import version  # type: ignore[import-not-found]
 
 if TYPE_CHECKING:
-    from opentelemetry.metrics import Meter
-    from opentelemetry.metrics._internal.instrument import Histogram
+    from opentelemetry.metrics import Histogram, Meter
     from opentelemetry.sdk.metrics.export import MetricReader
 
 from opentelemetry import trace as trace_api

api/core/plugin/impl/tool.py

@@ -3,6 +3,8 @@ from typing import Any
 
 from pydantic import BaseModel
 
+from configs import dify_config
+
 # from core.plugin.entities.plugin import GenericProviderID, ToolProviderID
 from core.plugin.entities.plugin_daemon import CredentialType, PluginBasicBooleanResponse, PluginToolProviderEntity
 from core.plugin.impl.base import BasePluginClient
@@ -122,7 +124,7 @@ class PluginToolManager(BasePluginClient):
             },
         )
 
-        return merge_blob_chunks(response)
+        return merge_blob_chunks(response, max_file_size=dify_config.PLUGIN_MAX_FILE_SIZE)
 
     def validate_provider_credentials(
         self, tenant_id: str, user_id: str, provider: str, credentials: dict[str, Any]

api/core/plugin/utils/converter.py

@@ -1,7 +1,7 @@
 from typing import Any
 
-from core.file.models import File
 from core.tools.entities.tool_entities import ToolSelector
+from core.workflow.file.models import File
 
 
 def convert_parameters_to_plugin_format(parameters: dict[str, Any]) -> dict[str, Any]:

api/core/prompt/advanced_prompt_transform.py

@@ -2,10 +2,9 @@ from collections.abc import Mapping, Sequence
 from typing import cast
 
 from core.app.entities.app_invoke_entities import ModelConfigWithCredentialsEntity
-from core.file import file_manager
-from core.file.models import File
 from core.helper.code_executor.jinja2.jinja2_formatter import Jinja2Formatter
 from core.memory.token_buffer_memory import TokenBufferMemory
+from core.model_manager import ModelInstance
 from core.model_runtime.entities import (
     AssistantPromptMessage,
     PromptMessage,
@@ -18,6 +17,8 @@ from core.model_runtime.entities.message_entities import ImagePromptMessageConte
 from core.prompt.entities.advanced_prompt_entities import ChatModelMessage, CompletionModelPromptTemplate, MemoryConfig
 from core.prompt.prompt_transform import PromptTransform
 from core.prompt.utils.prompt_template_parser import PromptTemplateParser
+from core.workflow.file import file_manager
+from core.workflow.file.models import File
 from core.workflow.runtime import VariablePool
 
 
@@ -44,7 +45,8 @@ class AdvancedPromptTransform(PromptTransform):
         context: str | None,
         memory_config: MemoryConfig | None,
         memory: TokenBufferMemory | None,
-        model_config: ModelConfigWithCredentialsEntity,
+        model_config: ModelConfigWithCredentialsEntity | None = None,
+        model_instance: ModelInstance | None = None,
         image_detail_config: ImagePromptMessageContent.DETAIL | None = None,
     ) -> list[PromptMessage]:
         prompt_messages = []
@@ -59,6 +61,7 @@ class AdvancedPromptTransform(PromptTransform):
                 memory_config=memory_config,
                 memory=memory,
                 model_config=model_config,
+                model_instance=model_instance,
                 image_detail_config=image_detail_config,
             )
         elif isinstance(prompt_template, list) and all(isinstance(item, ChatModelMessage) for item in prompt_template):
@@ -71,6 +74,7 @@ class AdvancedPromptTransform(PromptTransform):
                 memory_config=memory_config,
                 memory=memory,
                 model_config=model_config,
+                model_instance=model_instance,
                 image_detail_config=image_detail_config,
             )
 
@@ -85,7 +89,8 @@ class AdvancedPromptTransform(PromptTransform):
         context: str | None,
         memory_config: MemoryConfig | None,
         memory: TokenBufferMemory | None,
-        model_config: ModelConfigWithCredentialsEntity,
+        model_config: ModelConfigWithCredentialsEntity | None = None,
+        model_instance: ModelInstance | None = None,
         image_detail_config: ImagePromptMessageContent.DETAIL | None = None,
     ) -> list[PromptMessage]:
         """
@@ -111,6 +116,7 @@ class AdvancedPromptTransform(PromptTransform):
                     parser=parser,
                     prompt_inputs=prompt_inputs,
                     model_config=model_config,
+                    model_instance=model_instance,
                 )
 
             if query:
@@ -146,7 +152,8 @@ class AdvancedPromptTransform(PromptTransform):
         context: str | None,
         memory_config: MemoryConfig | None,
         memory: TokenBufferMemory | None,
-        model_config: ModelConfigWithCredentialsEntity,
+        model_config: ModelConfigWithCredentialsEntity | None = None,
+        model_instance: ModelInstance | None = None,
         image_detail_config: ImagePromptMessageContent.DETAIL | None = None,
     ) -> list[PromptMessage]:
         """
@@ -198,8 +205,13 @@ class AdvancedPromptTransform(PromptTransform):
 
         prompt_message_contents: list[PromptMessageContentUnionTypes] = []
         if memory and memory_config:
-            prompt_messages = self._append_chat_histories(memory, memory_config, prompt_messages, model_config)
-
+            prompt_messages = self._append_chat_histories(
+                memory,
+                memory_config,
+                prompt_messages,
+                model_config=model_config,
+                model_instance=model_instance,
+            )
             if files and query is not None:
                 for file in files:
                     prompt_message_contents.append(
@@ -276,7 +288,8 @@ class AdvancedPromptTransform(PromptTransform):
         role_prefix: MemoryConfig.RolePrefix,
         parser: PromptTemplateParser,
         prompt_inputs: Mapping[str, str],
-        model_config: ModelConfigWithCredentialsEntity,
+        model_config: ModelConfigWithCredentialsEntity | None = None,
+        model_instance: ModelInstance | None = None,
     ) -> Mapping[str, str]:
         prompt_inputs = dict(prompt_inputs)
         if "#histories#" in parser.variable_keys:
@@ -286,7 +299,11 @@ class AdvancedPromptTransform(PromptTransform):
                 prompt_inputs = {k: inputs[k] for k in parser.variable_keys if k in inputs}
                 tmp_human_message = UserPromptMessage(content=parser.format(prompt_inputs))
 
-                rest_tokens = self._calculate_rest_token([tmp_human_message], model_config)
+                rest_tokens = self._calculate_rest_token(
+                    [tmp_human_message],
+                    model_config=model_config,
+                    model_instance=model_instance,
+                )
 
                 histories = self._get_history_messages_from_memory(
                     memory=memory,

api/core/prompt/agent_history_prompt_transform.py

@@ -41,13 +41,15 @@ class AgentHistoryPromptTransform(PromptTransform):
         if not self.memory:
             return prompt_messages
 
-        max_token_limit = self._calculate_rest_token(self.prompt_messages, self.model_config)
+        max_token_limit = self._calculate_rest_token(self.prompt_messages, model_config=self.model_config)
 
         model_type_instance = self.model_config.provider_model_bundle.model_type_instance
         model_type_instance = cast(LargeLanguageModel, model_type_instance)
 
         curr_message_tokens = model_type_instance.get_num_tokens(
-            self.memory.model_instance.model, self.memory.model_instance.credentials, self.history_messages
+            self.model_config.model,
+            self.model_config.credentials,
+            self.history_messages,
         )
         if curr_message_tokens <= max_token_limit:
             return self.history_messages
@@ -63,7 +65,9 @@ class AgentHistoryPromptTransform(PromptTransform):
             # a message is start with UserPromptMessage
             if isinstance(prompt_message, UserPromptMessage):
                 curr_message_tokens = model_type_instance.get_num_tokens(
-                    self.memory.model_instance.model, self.memory.model_instance.credentials, prompt_messages
+                    self.model_config.model,
+                    self.model_config.credentials,
+                    prompt_messages,
                 )
                 # if current message token is overflow, drop all the prompts in current message and break
                 if curr_message_tokens > max_token_limit:

api/core/prompt/prompt_transform.py

@@ -4,45 +4,83 @@ from core.app.entities.app_invoke_entities import ModelConfigWithCredentialsEnti
 from core.memory.token_buffer_memory import TokenBufferMemory
 from core.model_manager import ModelInstance
 from core.model_runtime.entities.message_entities import PromptMessage
-from core.model_runtime.entities.model_entities import ModelPropertyKey
+from core.model_runtime.entities.model_entities import AIModelEntity, ModelPropertyKey
 from core.prompt.entities.advanced_prompt_entities import MemoryConfig
 
 
 class PromptTransform:
+    def _resolve_model_runtime(
+        self,
+        *,
+        model_config: ModelConfigWithCredentialsEntity | None = None,
+        model_instance: ModelInstance | None = None,
+    ) -> tuple[ModelInstance, AIModelEntity]:
+        if model_instance is None:
+            if model_config is None:
+                raise ValueError("Either model_config or model_instance must be provided.")
+            model_instance = ModelInstance(
+                provider_model_bundle=model_config.provider_model_bundle, model=model_config.model
+            )
+            model_instance.credentials = model_config.credentials
+            model_instance.parameters = model_config.parameters
+            model_instance.stop = model_config.stop
+
+        model_schema = model_instance.model_type_instance.get_model_schema(
+            model=model_instance.model_name,
+            credentials=model_instance.credentials,
+        )
+        if model_schema is None:
+            if model_config is None:
+                raise ValueError("Model schema not found for the provided model instance.")
+            model_schema = model_config.model_schema
+
+        return model_instance, model_schema
+
     def _append_chat_histories(
         self,
         memory: TokenBufferMemory,
         memory_config: MemoryConfig,
         prompt_messages: list[PromptMessage],
-        model_config: ModelConfigWithCredentialsEntity,
+        *,
+        model_config: ModelConfigWithCredentialsEntity | None = None,
+        model_instance: ModelInstance | None = None,
     ) -> list[PromptMessage]:
-        rest_tokens = self._calculate_rest_token(prompt_messages, model_config)
+        rest_tokens = self._calculate_rest_token(
+            prompt_messages,
+            model_config=model_config,
+            model_instance=model_instance,
+        )
         histories = self._get_history_messages_list_from_memory(memory, memory_config, rest_tokens)
         prompt_messages.extend(histories)
 
         return prompt_messages
 
     def _calculate_rest_token(
-        self, prompt_messages: list[PromptMessage], model_config: ModelConfigWithCredentialsEntity
+        self,
+        prompt_messages: list[PromptMessage],
+        *,
+        model_config: ModelConfigWithCredentialsEntity | None = None,
+        model_instance: ModelInstance | None = None,
     ) -> int:
+        model_instance, model_schema = self._resolve_model_runtime(
+            model_config=model_config,
+            model_instance=model_instance,
+        )
+        model_parameters = model_instance.parameters
         rest_tokens = 2000
 
-        model_context_tokens = model_config.model_schema.model_properties.get(ModelPropertyKey.CONTEXT_SIZE)
+        model_context_tokens = model_schema.model_properties.get(ModelPropertyKey.CONTEXT_SIZE)
         if model_context_tokens:
-            model_instance = ModelInstance(
-                provider_model_bundle=model_config.provider_model_bundle, model=model_config.model
-            )
-
             curr_message_tokens = model_instance.get_llm_num_tokens(prompt_messages)
 
             max_tokens = 0
-            for parameter_rule in model_config.model_schema.parameter_rules:
+            for parameter_rule in model_schema.parameter_rules:
                 if parameter_rule.name == "max_tokens" or (
                     parameter_rule.use_template and parameter_rule.use_template == "max_tokens"
                 ):
                     max_tokens = (
-                        model_config.parameters.get(parameter_rule.name)
-                        or model_config.parameters.get(parameter_rule.use_template or "")
+                        model_parameters.get(parameter_rule.name)
+                        or model_parameters.get(parameter_rule.use_template or "")
                     ) or 0
 
             rest_tokens = model_context_tokens - max_tokens - curr_message_tokens

api/core/prompt/simple_prompt_transform.py

@@ -6,7 +6,6 @@ from typing import TYPE_CHECKING, Any, cast
 
 from core.app.app_config.entities import PromptTemplateEntity
 from core.app.entities.app_invoke_entities import ModelConfigWithCredentialsEntity
-from core.file import file_manager
 from core.memory.token_buffer_memory import TokenBufferMemory
 from core.model_runtime.entities.message_entities import (
     ImagePromptMessageContent,
@@ -19,10 +18,11 @@ from core.model_runtime.entities.message_entities import (
 from core.prompt.entities.advanced_prompt_entities import MemoryConfig
 from core.prompt.prompt_transform import PromptTransform
 from core.prompt.utils.prompt_template_parser import PromptTemplateParser
+from core.workflow.file import file_manager
 from models.model import AppMode
 
 if TYPE_CHECKING:
-    from core.file.models import File
+    from core.workflow.file.models import File
 
 
 class ModelMode(StrEnum):
@@ -252,7 +252,7 @@ class SimplePromptTransform(PromptTransform):
         if memory:
             tmp_human_message = UserPromptMessage(content=prompt)
 
-            rest_tokens = self._calculate_rest_token([tmp_human_message], model_config)
+            rest_tokens = self._calculate_rest_token([tmp_human_message], model_config=model_config)
             histories = self._get_history_messages_from_memory(
                 memory=memory,
                 memory_config=MemoryConfig(

api/core/rag/datasource/vdb/oceanbase/oceanbase_vector.py

@@ -1,12 +1,13 @@
 import json
 import logging
-import math
-from typing import Any
+import re
+from typing import Any, Literal
 
 from pydantic import BaseModel, model_validator
-from pyobvector import VECTOR, ObVecClient, l2_distance  # type: ignore
+from pyobvector import VECTOR, ObVecClient, cosine_distance, inner_product, l2_distance  # type: ignore
 from sqlalchemy import JSON, Column, String
 from sqlalchemy.dialects.mysql import LONGTEXT
+from sqlalchemy.exc import SQLAlchemyError
 
 from configs import dify_config
 from core.rag.datasource.vdb.vector_base import BaseVector
@@ -19,10 +20,14 @@ from models.dataset import Dataset
 
 logger = logging.getLogger(__name__)
 
-DEFAULT_OCEANBASE_HNSW_BUILD_PARAM = {"M": 16, "efConstruction": 256}
-DEFAULT_OCEANBASE_HNSW_SEARCH_PARAM = {"efSearch": 64}
 OCEANBASE_SUPPORTED_VECTOR_INDEX_TYPE = "HNSW"
-DEFAULT_OCEANBASE_VECTOR_METRIC_TYPE = "l2"
+_VALID_TABLE_NAME_RE = re.compile(r"^[a-zA-Z0-9_]+$")
+
+_DISTANCE_FUNC_MAP = {
+    "l2": l2_distance,
+    "cosine": cosine_distance,
+    "inner_product": inner_product,
+}
 
 
 class OceanBaseVectorConfig(BaseModel):
@@ -32,6 +37,14 @@ class OceanBaseVectorConfig(BaseModel):
     password: str
     database: str
     enable_hybrid_search: bool = False
+    batch_size: int = 100
+    metric_type: Literal["l2", "cosine", "inner_product"] = "l2"
+    hnsw_m: int = 16
+    hnsw_ef_construction: int = 256
+    hnsw_ef_search: int = -1
+    pool_size: int = 5
+    max_overflow: int = 10
+    hnsw_refresh_threshold: int = 1000
 
     @model_validator(mode="before")
     @classmethod
@@ -49,14 +62,23 @@ class OceanBaseVectorConfig(BaseModel):
 
 class OceanBaseVector(BaseVector):
     def __init__(self, collection_name: str, config: OceanBaseVectorConfig):
+        if not _VALID_TABLE_NAME_RE.match(collection_name):
+            raise ValueError(
+                f"Invalid collection name '{collection_name}': "
+                "only alphanumeric characters and underscores are allowed."
+            )
         super().__init__(collection_name)
         self._config = config
-        self._hnsw_ef_search = -1
+        self._hnsw_ef_search = self._config.hnsw_ef_search
         self._client = ObVecClient(
             uri=f"{self._config.host}:{self._config.port}",
             user=self._config.user,
             password=self._config.password,
             db_name=self._config.database,
+            pool_size=self._config.pool_size,
+            max_overflow=self._config.max_overflow,
+            pool_recycle=3600,
+            pool_pre_ping=True,
         )
         self._fields: list[str] = []  # List of fields in the collection
         if self._client.check_table_exists(collection_name):
@@ -136,8 +158,8 @@ class OceanBaseVector(BaseVector):
                 field_name="vector",
                 index_type=OCEANBASE_SUPPORTED_VECTOR_INDEX_TYPE,
                 index_name="vector_index",
-                metric_type=DEFAULT_OCEANBASE_VECTOR_METRIC_TYPE,
-                params=DEFAULT_OCEANBASE_HNSW_BUILD_PARAM,
+                metric_type=self._config.metric_type,
+                params={"M": self._config.hnsw_m, "efConstruction": self._config.hnsw_ef_construction},
             )
 
             self._client.create_table_with_index_params(
@@ -178,6 +200,17 @@ class OceanBaseVector(BaseVector):
             else:
                 logger.debug("DEBUG: Hybrid search is NOT enabled for '%s'", self._collection_name)
 
+            try:
+                self._client.perform_raw_text_sql(
+                    f"CREATE INDEX IF NOT EXISTS idx_metadata_doc_id ON `{self._collection_name}` "
+                    f"((CAST(metadata->>'$.document_id' AS CHAR(64))))"
+                )
+            except SQLAlchemyError:
+                logger.warning(
+                    "Failed to create metadata functional index on '%s'; metadata queries may be slow without it.",
+                    self._collection_name,
+                )
+
             self._client.refresh_metadata([self._collection_name])
             self._load_collection_fields()
             redis_client.set(collection_exist_cache_key, 1, ex=3600)
@@ -205,24 +238,49 @@ class OceanBaseVector(BaseVector):
 
     def add_texts(self, documents: list[Document], embeddings: list[list[float]], **kwargs):
         ids = self._get_uuids(documents)
-        for id, doc, emb in zip(ids, documents, embeddings):
+        batch_size = self._config.batch_size
+        total = len(documents)
+
+        all_data = [
+            {
+                "id": doc_id,
+                "vector": emb,
+                "text": doc.page_content,
+                "metadata": doc.metadata,
+            }
+            for doc_id, doc, emb in zip(ids, documents, embeddings)
+        ]
+
+        for start in range(0, total, batch_size):
+            batch = all_data[start : start + batch_size]
             try:
                 self._client.insert(
                     table_name=self._collection_name,
-                    data={
-                        "id": id,
-                        "vector": emb,
-                        "text": doc.page_content,
-                        "metadata": doc.metadata,
-                    },
+                    data=batch,
                 )
             except Exception as e:
                 logger.exception(
-                    "Failed to insert document with id '%s' in collection '%s'",
-                    id,
+                    "Failed to insert batch [%d:%d] into collection '%s'",
+                    start,
+                    start + len(batch),
+                    self._collection_name,
+                )
+                raise Exception(
+                    f"Failed to insert batch [{start}:{start + len(batch)}] into collection '{self._collection_name}'"
+                ) from e
+
+        if self._config.hnsw_refresh_threshold > 0 and total >= self._config.hnsw_refresh_threshold:
+            try:
+                self._client.refresh_index(
+                    table_name=self._collection_name,
+                    index_name="vector_index",
+                )
+            except SQLAlchemyError:
+                logger.warning(
+                    "Failed to refresh HNSW index after inserting %d documents into '%s'",
+                    total,
                     self._collection_name,
                 )
-                raise Exception(f"Failed to insert document with id '{id}'") from e
 
     def text_exists(self, id: str) -> bool:
         try:
@@ -412,7 +470,7 @@ class OceanBaseVector(BaseVector):
                 vec_column_name="vector",
                 vec_data=query_vector,
                 topk=topk,
-                distance_func=l2_distance,
+                distance_func=self._get_distance_func(),
                 output_column_names=["text", "metadata"],
                 with_dist=True,
                 where_clause=_where_clause,
@@ -424,14 +482,31 @@ class OceanBaseVector(BaseVector):
             )
             raise Exception(f"Vector search failed for collection '{self._collection_name}'") from e
 
-        # Convert distance to score and prepare results for processing
         results = []
         for _text, metadata_str, distance in cur:
-            score = 1 - distance / math.sqrt(2)
+            score = self._distance_to_score(distance)
             results.append((_text, metadata_str, score))
 
         return self._process_search_results(results, score_threshold=score_threshold)
 
+    def _get_distance_func(self):
+        func = _DISTANCE_FUNC_MAP.get(self._config.metric_type)
+        if func is None:
+            raise ValueError(
+                f"Unsupported metric_type '{self._config.metric_type}'. Supported: {', '.join(_DISTANCE_FUNC_MAP)}"
+            )
+        return func
+
+    def _distance_to_score(self, distance: float) -> float:
+        metric = self._config.metric_type
+        if metric == "l2":
+            return 1.0 / (1.0 + distance)
+        elif metric == "cosine":
+            return 1.0 - distance
+        elif metric == "inner_product":
+            return -distance
+        raise ValueError(f"Unsupported metric_type '{metric}'")
+
     def delete(self):
         try:
             self._client.drop_table_if_exist(self._collection_name)
@@ -464,5 +539,13 @@ class OceanBaseVectorFactory(AbstractVectorFactory):
                 password=(dify_config.OCEANBASE_VECTOR_PASSWORD or ""),
                 database=dify_config.OCEANBASE_VECTOR_DATABASE or "",
                 enable_hybrid_search=dify_config.OCEANBASE_ENABLE_HYBRID_SEARCH or False,
+                batch_size=dify_config.OCEANBASE_VECTOR_BATCH_SIZE,
+                metric_type=dify_config.OCEANBASE_VECTOR_METRIC_TYPE,
+                hnsw_m=dify_config.OCEANBASE_HNSW_M,
+                hnsw_ef_construction=dify_config.OCEANBASE_HNSW_EF_CONSTRUCTION,
+                hnsw_ef_search=dify_config.OCEANBASE_HNSW_EF_SEARCH,
+                pool_size=dify_config.OCEANBASE_VECTOR_POOL_SIZE,
+                max_overflow=dify_config.OCEANBASE_VECTOR_MAX_OVERFLOW,
+                hnsw_refresh_threshold=dify_config.OCEANBASE_HNSW_REFRESH_THRESHOLD,
             ),
         )

api/core/rag/datasource/vdb/vector_base.py

@@ -15,11 +15,11 @@ class BaseVector(ABC):
         raise NotImplementedError
 
     @abstractmethod
-    def create(self, texts: list[Document], embeddings: list[list[float]], **kwargs):
+    def create(self, texts: list[Document], embeddings: list[list[float]], **kwargs) -> list[str] | None:
         raise NotImplementedError
 
     @abstractmethod
-    def add_texts(self, documents: list[Document], embeddings: list[list[float]], **kwargs):
+    def add_texts(self, documents: list[Document], embeddings: list[list[float]], **kwargs) -> list[str]:
         raise NotImplementedError
 
     @abstractmethod
@@ -27,14 +27,14 @@ class BaseVector(ABC):
         raise NotImplementedError
 
     @abstractmethod
-    def delete_by_ids(self, ids: list[str]):
+    def delete_by_ids(self, ids: list[str]) -> None:
         raise NotImplementedError
 
     def get_ids_by_metadata_field(self, key: str, value: str):
         raise NotImplementedError
 
     @abstractmethod
-    def delete_by_metadata_field(self, key: str, value: str):
+    def delete_by_metadata_field(self, key: str, value: str) -> None:
         raise NotImplementedError
 
     @abstractmethod
@@ -46,7 +46,7 @@ class BaseVector(ABC):
         raise NotImplementedError
 
     @abstractmethod
-    def delete(self):
+    def delete(self) -> None:
         raise NotImplementedError
 
     def _filter_duplicate_texts(self, texts: list[Document]) -> list[Document]:

api/core/rag/embedding/cached_embedding.py

@@ -35,7 +35,9 @@ class CacheEmbedding(Embeddings):
             embedding = (
                 db.session.query(Embedding)
                 .filter_by(
-                    model_name=self._model_instance.model, hash=hash, provider_name=self._model_instance.provider
+                    model_name=self._model_instance.model_name,
+                    hash=hash,
+                    provider_name=self._model_instance.provider,
                 )
                 .first()
             )
@@ -52,7 +54,7 @@ class CacheEmbedding(Embeddings):
             try:
                 model_type_instance = cast(TextEmbeddingModel, self._model_instance.model_type_instance)
                 model_schema = model_type_instance.get_model_schema(
-                    self._model_instance.model, self._model_instance.credentials
+                    self._model_instance.model_name, self._model_instance.credentials
                 )
                 max_chunks = (
                     model_schema.model_properties[ModelPropertyKey.MAX_CHUNKS]
@@ -87,7 +89,7 @@ class CacheEmbedding(Embeddings):
                         hash = helper.generate_text_hash(texts[i])
                         if hash not in cache_embeddings:
                             embedding_cache = Embedding(
-                                model_name=self._model_instance.model,
+                                model_name=self._model_instance.model_name,
                                 hash=hash,
                                 provider_name=self._model_instance.provider,
                                 embedding=pickle.dumps(n_embedding, protocol=pickle.HIGHEST_PROTOCOL),
@@ -114,7 +116,9 @@ class CacheEmbedding(Embeddings):
             embedding = (
                 db.session.query(Embedding)
                 .filter_by(
-                    model_name=self._model_instance.model, hash=file_id, provider_name=self._model_instance.provider
+                    model_name=self._model_instance.model_name,
+                    hash=file_id,
+                    provider_name=self._model_instance.provider,
                 )
                 .first()
             )
@@ -131,7 +135,7 @@ class CacheEmbedding(Embeddings):
             try:
                 model_type_instance = cast(TextEmbeddingModel, self._model_instance.model_type_instance)
                 model_schema = model_type_instance.get_model_schema(
-                    self._model_instance.model, self._model_instance.credentials
+                    self._model_instance.model_name, self._model_instance.credentials
                 )
                 max_chunks = (
                     model_schema.model_properties[ModelPropertyKey.MAX_CHUNKS]
@@ -168,7 +172,7 @@ class CacheEmbedding(Embeddings):
                         file_id = multimodel_documents[i]["file_id"]
                         if file_id not in cache_embeddings:
                             embedding_cache = Embedding(
-                                model_name=self._model_instance.model,
+                                model_name=self._model_instance.model_name,
                                 hash=file_id,
                                 provider_name=self._model_instance.provider,
                                 embedding=pickle.dumps(n_embedding, protocol=pickle.HIGHEST_PROTOCOL),
@@ -190,7 +194,7 @@ class CacheEmbedding(Embeddings):
         """Embed query text."""
         # use doc embedding cache or store if not exists
         hash = helper.generate_text_hash(text)
-        embedding_cache_key = f"{self._model_instance.provider}_{self._model_instance.model}_{hash}"
+        embedding_cache_key = f"{self._model_instance.provider}_{self._model_instance.model_name}_{hash}"
         embedding = redis_client.get(embedding_cache_key)
         if embedding:
             redis_client.expire(embedding_cache_key, 600)
@@ -233,7 +237,7 @@ class CacheEmbedding(Embeddings):
         """Embed multimodal documents."""
         # use doc embedding cache or store if not exists
         file_id = multimodel_document["file_id"]
-        embedding_cache_key = f"{self._model_instance.provider}_{self._model_instance.model}_{file_id}"
+        embedding_cache_key = f"{self._model_instance.provider}_{self._model_instance.model_name}_{file_id}"
         embedding = redis_client.get(embedding_cache_key)
         if embedding:
             redis_client.expire(embedding_cache_key, 600)

api/core/rag/index_processor/processor/paragraph_index_processor.py

@@ -9,7 +9,6 @@ from typing import Any, cast
 logger = logging.getLogger(__name__)
 
 from core.entities.knowledge_entities import PreviewDetail
-from core.file import File, FileTransferMethod, FileType, file_manager
 from core.llm_generator.prompts import DEFAULT_GENERATOR_SUMMARY_PROMPT
 from core.model_manager import ModelInstance
 from core.model_runtime.entities.llm_entities import LLMResult, LLMUsage
@@ -35,6 +34,7 @@ from core.rag.index_processor.index_processor_base import BaseIndexProcessor
 from core.rag.models.document import AttachmentDocument, Document, MultimodalGeneralStructureChunk
 from core.rag.retrieval.retrieval_methods import RetrievalMethod
 from core.tools.utils.text_processing_utils import remove_leading_symbols
+from core.workflow.file import File, FileTransferMethod, FileType, file_manager
 from core.workflow.nodes.llm import llm_utils
 from extensions.ext_database import db
 from factories.file_factory import build_from_mapping
@@ -469,7 +469,7 @@ class ParagraphIndexProcessor(BaseIndexProcessor):
         if not isinstance(result, LLMResult):
             raise ValueError("Expected LLMResult when stream=False")
 
-        summary_content = getattr(result.message, "content", "")
+        summary_content = result.message.get_text_content()
         usage = result.usage
 
         # Deduct quota for summary generation (same as workflow nodes)

api/core/rag/models/document.py

@@ -4,7 +4,7 @@ from typing import Any
 
 from pydantic import BaseModel, Field
 
-from core.file import File
+from core.workflow.file import File
 
 
 class ChildDocument(BaseModel):

api/core/rag/rerank/rerank_model.py

@@ -38,7 +38,7 @@ class RerankModelRunner(BaseRerankRunner):
         is_support_vision = model_manager.check_model_support_vision(
             tenant_id=self.rerank_model_instance.provider_model_bundle.configuration.tenant_id,
             provider=self.rerank_model_instance.provider,
-            model=self.rerank_model_instance.model,
+            model=self.rerank_model_instance.model_name,
             model_type=ModelType.RERANK,
         )
         if not is_support_vision:

api/core/rag/retrieval/dataset_retrieval.py

@@ -23,7 +23,6 @@ from core.callback_handler.index_tool_callback_handler import DatasetIndexToolCa
 from core.db.session_factory import session_factory
 from core.entities.agent_entities import PlanningStrategy
 from core.entities.model_entities import ModelStatus
-from core.file import File, FileTransferMethod, FileType
 from core.memory.token_buffer_memory import TokenBufferMemory
 from core.model_manager import ModelInstance, ModelManager
 from core.model_runtime.entities.llm_entities import LLMResult, LLMUsage
@@ -61,6 +60,7 @@ from core.rag.retrieval.template_prompts import (
 )
 from core.tools.signature import sign_upload_file
 from core.tools.utils.dataset_retriever.dataset_retriever_base_tool import DatasetRetrieverBaseTool
+from core.workflow.file import File, FileTransferMethod, FileType
 from core.workflow.nodes.knowledge_retrieval import exc
 from core.workflow.repositories.rag_retrieval_protocol import (
     KnowledgeRetrievalRequest,

api/core/tools/__base/tool.py

@@ -5,7 +5,7 @@ from collections.abc import Generator
 from copy import deepcopy
 from typing import TYPE_CHECKING, Any
 
-if TYPE_CHECKING:
+if TYPE_CHECKING:  # pragma: no cover
     from models.model import File
 
 from core.tools.__base.tool_runtime import ToolRuntime
@@ -171,7 +171,7 @@ class Tool(ABC):
     def create_file_message(self, file: File) -> ToolInvokeMessage:
         return ToolInvokeMessage(
             type=ToolInvokeMessage.MessageType.FILE,
-            message=ToolInvokeMessage.FileMessage(),
+            message=ToolInvokeMessage.FileMessage(file_marker="file_marker"),
             meta={"file": file},
         )
 

api/core/tools/builtin_tool/providers/audio/tools/asr.py

@@ -2,14 +2,14 @@ import io
 from collections.abc import Generator
 from typing import Any
 
-from core.file.enums import FileType
-from core.file.file_manager import download
 from core.model_manager import ModelManager
 from core.model_runtime.entities.model_entities import ModelType
 from core.plugin.entities.parameters import PluginParameterOption
 from core.tools.builtin_tool.tool import BuiltinTool
 from core.tools.entities.common_entities import I18nObject
 from core.tools.entities.tool_entities import ToolInvokeMessage, ToolParameter
+from core.workflow.file.enums import FileType
+from core.workflow.file.file_manager import download
 from services.model_provider_service import ModelProviderService
 
 

api/core/tools/custom_tool/tool.py

@@ -7,13 +7,13 @@ from urllib.parse import urlencode
 
 import httpx
 
-from core.file.file_manager import download
 from core.helper import ssrf_proxy
 from core.tools.__base.tool import Tool
 from core.tools.__base.tool_runtime import ToolRuntime
 from core.tools.entities.tool_bundle import ApiToolBundle
 from core.tools.entities.tool_entities import ToolEntity, ToolInvokeMessage, ToolProviderType
 from core.tools.errors import ToolInvokeError, ToolParameterValidationError, ToolProviderCredentialValidationError
+from core.workflow.file.file_manager import download
 
 API_TOOL_DEFAULT_TIMEOUT = (
     int(getenv("API_TOOL_DEFAULT_CONNECT_TIMEOUT", "10")),

api/core/tools/tool_engine.py

@@ -12,8 +12,6 @@ from yarl import URL
 from core.app.entities.app_invoke_entities import InvokeFrom
 from core.callback_handler.agent_tool_callback_handler import DifyAgentCallbackHandler
 from core.callback_handler.workflow_tool_callback_handler import DifyWorkflowCallbackHandler
-from core.file import FileType
-from core.file.models import FileTransferMethod
 from core.ops.ops_trace_manager import TraceQueueManager
 from core.tools.__base.tool import Tool
 from core.tools.entities.tool_entities import (
@@ -33,6 +31,8 @@ from core.tools.errors import (
 )
 from core.tools.utils.message_transformer import ToolFileMessageTransformer, safe_json_value
 from core.tools.workflow_as_tool.tool import WorkflowTool
+from core.workflow.file import FileType
+from core.workflow.file.models import FileTransferMethod
 from extensions.ext_database import db
 from models.enums import CreatorUserRole
 from models.model import Message, MessageFile

api/core/tools/tool_file_manager.py

@@ -243,7 +243,7 @@ class ToolFileManager:
 
 
 # init tool_file_parser
-from core.file.tool_file_parser import set_tool_file_manager_factory
+from core.workflow.file.tool_file_parser import set_tool_file_manager_factory
 
 
 def _factory() -> ToolFileManager:

api/core/tools/utils/message_transformer.py

@@ -8,9 +8,9 @@ from uuid import UUID
 import numpy as np
 import pytz
 
-from core.file import File, FileTransferMethod, FileType
 from core.tools.entities.tool_entities import ToolInvokeMessage
 from core.tools.tool_file_manager import ToolFileManager
+from core.workflow.file import File, FileTransferMethod, FileType
 from libs.login import current_user
 from models import Account
 

api/core/tools/utils/model_invocation_utils.py

@@ -47,7 +47,7 @@ class ModelInvocationUtils:
             raise InvokeModelError("Model not found")
 
         llm_model = cast(LargeLanguageModel, model_instance.model_type_instance)
-        schema = llm_model.get_model_schema(model_instance.model, model_instance.credentials)
+        schema = llm_model.get_model_schema(model_instance.model_name, model_instance.credentials)
 
         if not schema:
             raise InvokeModelError("No model schema found")

api/core/tools/utils/parser.py

@@ -2,7 +2,7 @@ import re
 from json import dumps as json_dumps
 from json import loads as json_loads
 from json.decoder import JSONDecodeError
-from typing import Any
+from typing import Any, TypedDict
 
 import httpx
 from flask import request
@@ -14,6 +14,12 @@ from core.tools.entities.tool_entities import ApiProviderSchemaType, ToolParamet
 from core.tools.errors import ToolApiSchemaError, ToolNotSupportedError, ToolProviderNotFoundError
 
 
+class InterfaceDict(TypedDict):
+    path: str
+    method: str
+    operation: dict[str, Any]
+
+
 class ApiBasedToolSchemaParser:
     @staticmethod
     def parse_openapi_to_tool_bundle(
@@ -35,7 +41,7 @@ class ApiBasedToolSchemaParser:
             server_url = matched_servers[0] if matched_servers else server_url
 
         # list all interfaces
-        interfaces = []
+        interfaces: list[InterfaceDict] = []
         for path, path_item in openapi["paths"].items():
             methods = ["get", "post", "put", "delete", "patch", "head", "options", "trace"]
             for method in methods:

api/core/tools/workflow_as_tool/tool.py

@@ -8,7 +8,6 @@ from typing import Any, cast
 from sqlalchemy import select
 
 from core.db.session_factory import session_factory
-from core.file import FILE_MODEL_IDENTITY, File, FileTransferMethod
 from core.model_runtime.entities.llm_entities import LLMUsage, LLMUsageMetadata
 from core.tools.__base.tool import Tool
 from core.tools.__base.tool_runtime import ToolRuntime
@@ -19,6 +18,7 @@ from core.tools.entities.tool_entities import (
     ToolProviderType,
 )
 from core.tools.errors import ToolInvokeError
+from core.workflow.file import FILE_MODEL_IDENTITY, File, FileTransferMethod
 from factories.file_factory import build_from_mapping
 from models import Account, Tenant
 from models.model import App, EndUser