fix: wrong web sso protocal source in json

fix: remove debug logs
fix: allow empty list api
2025-04-24 23:48:18 -04:00 · 2025-04-23 23:09:45 -04:00 · 2025-04-22 22:20:29 -04:00 · 2025-04-22 02:54:30 -04:00 · 2025-04-21 19:40:51 -04:00 · 2025-04-21 19:03:10 -04:00
280 changed files with 4734 additions and 4126 deletions
@@ -26,9 +26,6 @@ jobs:
    steps:
      - name: Checkout code
        uses: actions/checkout@v4
-        with:
-          fetch-depth: 0
-          persist-credentials: false

      - name: Setup Poetry and Python ${{ matrix.python-version }}
        uses: ./.github/actions/setup-poetry
@@ -5,6 +5,8 @@ on:
    branches:
      - "main"
      - "deploy/dev"
+      - "deploy/enterprise"
+      - "e-0154"
  release:
    types: [published]

@@ -79,12 +81,10 @@ jobs:
          cache-to: type=gha,mode=max,scope=${{ matrix.service_name }}

      - name: Export digest
-        env:
-          DIGEST: ${{ steps.build.outputs.digest }}
        run: |
          mkdir -p /tmp/digests
-          sanitized_digest=${DIGEST#sha256:}
-          touch "/tmp/digests/${sanitized_digest}"
+          digest="${{ steps.build.outputs.digest }}"
+          touch "/tmp/digests/${digest#sha256:}"

      - name: Upload digest
        uses: actions/upload-artifact@v4
@@ -134,15 +134,10 @@ jobs:

      - name: Create manifest list and push
        working-directory: /tmp/digests
-        env:
-          IMAGE_NAME: ${{ env[matrix.image_name_env] }}
        run: |
          docker buildx imagetools create $(jq -cr '.tags | map("-t " + .) | join(" ")' <<< "$DOCKER_METADATA_OUTPUT_JSON") \
-            $(printf "$IMAGE_NAME@sha256:%s " *)
+            $(printf '${{ env[matrix.image_name_env] }}@sha256:%s ' *)

      - name: Inspect image
-        env:
-          IMAGE_NAME: ${{ env[matrix.image_name_env] }}
-          IMAGE_VERSION: ${{ steps.meta.outputs.version }}
        run: |
-          docker buildx imagetools inspect "$IMAGE_NAME:$IMAGE_VERSION"
+          docker buildx imagetools inspect ${{ env[matrix.image_name_env] }}:${{ steps.meta.outputs.version }}
@@ -19,9 +19,6 @@ jobs:
    steps:
      - name: Checkout code
        uses: actions/checkout@v4
-        with:
-          fetch-depth: 0
-          persist-credentials: false

      - name: Setup Poetry and Python
        uses: ./.github/actions/setup-poetry
@@ -0,0 +1,29 @@
+name: Deploy Enterprise
+
+permissions:
+  contents: read
+
+on:
+  workflow_run:
+    workflows: ["Build and Push API & Web"]
+    branches:
+      - "deploy/enterprise"
+    types:
+      - completed
+
+jobs:
+  deploy:
+    runs-on: ubuntu-latest
+    if: |
+      github.event.workflow_run.conclusion == 'success' &&
+      github.event.workflow_run.head_branch == 'deploy/enterprise'
+
+    steps:
+      - name: Deploy to server
+        uses: appleboy/ssh-action@v0.1.8
+        with:
+          host: ${{ secrets.ENTERPRISE_SSH_HOST }}
+          username: ${{ secrets.ENTERPRISE_SSH_USER }}
+          password: ${{ secrets.ENTERPRISE_SSH_PASSWORD }}
+          script: |
+            ${{ vars.ENTERPRISE_SSH_SCRIPT || secrets.ENTERPRISE_SSH_SCRIPT }}
@@ -9,6 +9,6 @@ yq eval '.services["pgvecto-rs"].ports += ["5431:5432"]' -i docker/docker-compos
 yq eval '.services["elasticsearch"].ports += ["9200:9200"]' -i docker/docker-compose.yaml
 yq eval '.services.couchbase-server.ports += ["8091-8096:8091-8096"]' -i docker/docker-compose.yaml
 yq eval '.services.couchbase-server.ports += ["11210:11210"]' -i docker/docker-compose.yaml
-yq eval '.services.tidb.ports += ["4000:4000"]' -i docker/tidb/docker-compose.yaml
+yq eval '.services.tidb.ports += ["4000:4000"]' -i docker/docker-compose.yaml

 echo "Ports exposed for sandbox, weaviate, tidb, qdrant, chroma, milvus, pgvector, pgvecto-rs, elasticsearch, couchbase"
@@ -17,9 +17,6 @@ jobs:
    steps:
      - name: Checkout code
        uses: actions/checkout@v4
-        with:
-          fetch-depth: 0
-          persist-credentials: false

      - name: Check changed files
        id: changed-files
@@ -62,9 +59,6 @@ jobs:
    steps:
      - name: Checkout code
        uses: actions/checkout@v4
-        with:
-          fetch-depth: 0
-          persist-credentials: false

      - name: Check changed files
        id: changed-files
@@ -95,9 +89,6 @@ jobs:
    steps:
      - name: Checkout code
        uses: actions/checkout@v4
-        with:
-          fetch-depth: 0
-          persist-credentials: false

      - name: Check changed files
        id: changed-files
@@ -126,9 +117,6 @@ jobs:
    steps:
      - name: Checkout code
        uses: actions/checkout@v4
-        with:
-          fetch-depth: 0
-          persist-credentials: false

      - name: Check changed files
        id: changed-files
@@ -26,9 +26,6 @@ jobs:

    steps:
      - uses: actions/checkout@v4
-        with:
-          fetch-depth: 0
-          persist-credentials: false

      - name: Use Node.js ${{ matrix.node-version }}
        uses: actions/setup-node@v4
@@ -16,7 +16,6 @@ jobs:
      - uses: actions/checkout@v4
        with:
          fetch-depth: 2 # last 2 commits
-          persist-credentials: false

      - name: Check for file changes in i18n/en-US
        id: check_files
@@ -28,9 +28,6 @@ jobs:
    steps:
      - name: Checkout code
        uses: actions/checkout@v4
-        with:
-          fetch-depth: 0
-          persist-credentials: false

      - name: Setup Poetry and Python ${{ matrix.python-version }}
        uses: ./.github/actions/setup-poetry
@@ -54,15 +51,7 @@ jobs:
      - name: Expose Service Ports
        run: sh .github/workflows/expose_service_ports.sh

-      - name: Set up Vector Store (TiDB)
-        uses: hoverkraft-tech/compose-action@v2.0.2
-        with:
-          compose-file: docker/tidb/docker-compose.yaml
-          services: |
-            tidb
-            tiflash
-
-      - name: Set up Vector Stores (Weaviate, Qdrant, PGVector, Milvus, PgVecto-RS, Chroma, MyScale, ElasticSearch, Couchbase)
+      - name: Set up Vector Stores (TiDB, Weaviate, Qdrant, PGVector, Milvus, PgVecto-RS, Chroma, MyScale, ElasticSearch, Couchbase)
        uses: hoverkraft-tech/compose-action@v2.0.2
        with:
          compose-file: |
@@ -78,9 +67,7 @@ jobs:
            pgvector
            chroma
            elasticsearch
-
-      - name: Check TiDB Ready
-        run: poetry run -P api python api/tests/integration_tests/vdb/tidb_vector/check_tiflash_ready.py
+            tidb

      - name: Test Vector Stores
        run: poetry run -P api bash dev/pytest/pytest_vdb.sh
@@ -22,9 +22,6 @@ jobs:
    steps:
      - name: Checkout code
        uses: actions/checkout@v4
-        with:
-          fetch-depth: 0
-          persist-credentials: false

      - name: Check changed files
        id: changed-files
@@ -163,7 +163,6 @@ docker/volumes/db/data/*
 docker/volumes/redis/data/*
 docker/volumes/weaviate/*
 docker/volumes/qdrant/*
-docker/tidb/volumes/*
 docker/volumes/etcd/*
 docker/volumes/minio/*
 docker/volumes/milvus/*
@@ -108,72 +108,6 @@ Please refer to our [FAQ](https://docs.dify.ai/getting-started/install-self-host
 **7. Backend-as-a-Service**: 
  All of Dify's offerings come with corresponding APIs, so you could effortlessly integrate Dify into your own business logic.

-## Feature Comparison
-<table style="width: 100%;">
-  <tr>
-    <th align="center">Feature</th>
-    <th align="center">Dify.AI</th>
-    <th align="center">LangChain</th>
-    <th align="center">Flowise</th>
-    <th align="center">OpenAI Assistants API</th>
-  </tr>
-  <tr>
-    <td align="center">Programming Approach</td>
-    <td align="center">API + App-oriented</td>
-    <td align="center">Python Code</td>
-    <td align="center">App-oriented</td>
-    <td align="center">API-oriented</td>
-  </tr>
-  <tr>
-    <td align="center">Supported LLMs</td>
-    <td align="center">Rich Variety</td>
-    <td align="center">Rich Variety</td>
-    <td align="center">Rich Variety</td>
-    <td align="center">OpenAI-only</td>
-  </tr>
-  <tr>
-    <td align="center">RAG Engine</td>
-    <td align="center">✅</td>
-    <td align="center">✅</td>
-    <td align="center">✅</td>
-    <td align="center">✅</td>
-  </tr>
-  <tr>
-    <td align="center">Agent</td>
-    <td align="center">✅</td>
-    <td align="center">✅</td>
-    <td align="center">❌</td>
-    <td align="center">✅</td>
-  </tr>
-  <tr>
-    <td align="center">Workflow</td>
-    <td align="center">✅</td>
-    <td align="center">❌</td>
-    <td align="center">✅</td>
-    <td align="center">❌</td>
-  </tr>
-  <tr>
-    <td align="center">Observability</td>
-    <td align="center">✅</td>
-    <td align="center">✅</td>
-    <td align="center">❌</td>
-    <td align="center">❌</td>
-  </tr>
-  <tr>
-    <td align="center">Enterprise Feature (SSO/Access control)</td>
-    <td align="center">✅</td>
-    <td align="center">❌</td>
-    <td align="center">❌</td>
-    <td align="center">❌</td>
-  </tr>
-  <tr>
-    <td align="center">Local Deployment</td>
-    <td align="center">✅</td>
-    <td align="center">✅</td>
-    <td align="center">✅</td>
-    <td align="center">❌</td>
-  </tr>
-</table>

 ## Using Dify

@@ -87,7 +87,9 @@ Dify is an open-source LLM app development platform. Its intuitive interface com

 ## Feature Comparison
 <table style="width: 100%;">
-  <tr>
+  <tr
+
+>
    <th align="center">Feature</th>
    <th align="center">Dify.AI</th>
    <th align="center">LangChain</th>
@@ -106,73 +106,6 @@ Prosimo, glejte naša pogosta vprašanja [FAQ](https://docs.dify.ai/getting-star
 **7. Backend-as-a-Service**: 
  AVse ponudbe Difyja so opremljene z ustreznimi API-ji, tako da lahko Dify brez težav integrirate v svojo poslovno logiko.

-## Primerjava Funkcij
-
-<table style="width: 100%;">
-  <tr>
-    <th align="center">Funkcija</th>
-    <th align="center">Dify.AI</th>
-    <th align="center">LangChain</th>
-    <th align="center">Flowise</th>
-    <th align="center">OpenAI Assistants API</th>
-  </tr>
-  <tr>
-    <td align="center">Programski pristop</td>
-    <td align="center">API + usmerjeno v aplikacije</td>
-    <td align="center">Python koda</td>
-    <td align="center">Usmerjeno v aplikacije</td>
-    <td align="center">Usmerjeno v API</td>
-  </tr>
-  <tr>
-    <td align="center">Podprti LLM-ji</td>
-    <td align="center">Bogata izbira</td>
-    <td align="center">Bogata izbira</td>
-    <td align="center">Bogata izbira</td>
-    <td align="center">Samo OpenAI</td>
-  </tr>
-  <tr>
-    <td align="center">RAG pogon</td>
-    <td align="center">✅</td>
-    <td align="center">✅</td>
-    <td align="center">✅</td>
-    <td align="center">✅</td>
-  </tr>
-  <tr>
-    <td align="center">Agent</td>
-    <td align="center">✅</td>
-    <td align="center">✅</td>
-    <td align="center">❌</td>
-    <td align="center">✅</td>
-  </tr>
-  <tr>
-    <td align="center">Potek dela</td>
-    <td align="center">✅</td>
-    <td align="center">❌</td>
-    <td align="center">✅</td>
-    <td align="center">❌</td>
-  </tr>
-  <tr>
-    <td align="center">Spremljanje</td>
-    <td align="center">✅</td>
-    <td align="center">✅</td>
-    <td align="center">❌</td>
-    <td align="center">❌</td>
-  </tr>
-  <tr>
-    <td align="center">Funkcija za podjetja (SSO/nadzor dostopa)</td>
-    <td align="center">✅</td>
-    <td align="center">❌</td>
-    <td align="center">❌</td>
-    <td align="center">❌</td>
-  </tr>
-  <tr>
-    <td align="center">Lokalna namestitev</td>
-    <td align="center">✅</td>
-    <td align="center">✅</td>
-    <td align="center">✅</td>
-    <td align="center">❌</td>
-  </tr>
-</table>

 ## Uporaba Dify

@@ -254,4 +187,4 @@ Zaradi zaščite vaše zasebnosti se izogibajte objavljanju varnostnih vprašanj

 ## Licenca

-To skladišče je na voljo pod [odprtokodno licenco Dify](LICENSE) , ki je v bistvu Apache 2.0 z nekaj dodatnimi omejitvami.
+To skladišče je na voljo pod [odprtokodno licenco Dify](LICENSE) , ki je v bistvu Apache 2.0 z nekaj dodatnimi omejitvami.
@@ -37,13 +37,7 @@

 4. Create environment.

-   Dify API service uses [Poetry](https://python-poetry.org/docs/) to manage dependencies. First, you need to add the poetry shell plugin, if you don't have it already, in order to run in a virtual environment. [Note: Poetry shell is no longer a native command so you need to install the poetry plugin beforehand]
-
-   ```bash
-   poetry self add poetry-plugin-shell
-   ```
-   
-   Then, You can execute `poetry shell` to activate the environment.
+   Dify API service uses [Poetry](https://python-poetry.org/docs/) to manage dependencies. You can execute `poetry shell` to activate the environment.

 5. Install dependencies

@@ -315,8 +315,8 @@ class HttpConfig(BaseSettings):
    )

    RESPECT_XFORWARD_HEADERS_ENABLED: bool = Field(
-        description="Enable handling of X-Forwarded-For, X-Forwarded-Proto, and X-Forwarded-Port headers"
-        " when the app is behind a single trusted reverse proxy.",
+        description="Enable or disable the X-Forwarded-For Proxy Fix middleware from Werkzeug"
+        " to respect X-* headers to redirect clients",
        default=False,
    )

@@ -498,11 +498,6 @@ class AuthConfig(BaseSettings):
        default=86400,
    )

-    FORGOT_PASSWORD_LOCKOUT_DURATION: PositiveInt = Field(
-        description="Time (in seconds) a user must wait before retrying password reset after exceeding the rate limit.",
-        default=86400,
-    )
-

 class ModerationConfig(BaseSettings):
    """
@@ -9,7 +9,7 @@ class PackagingInfo(BaseSettings):

    CURRENT_VERSION: str = Field(
        description="Dify version",
-        default="0.15.3",
+        default="0.15.4",
    )

    COMMIT_SHA: str = Field(
@@ -15,7 +15,7 @@ AUDIO_EXTENSIONS.extend([ext.upper() for ext in AUDIO_EXTENSIONS])

 if dify_config.ETL_TYPE == "Unstructured":
    DOCUMENT_EXTENSIONS = ["txt", "markdown", "md", "mdx", "pdf", "html", "htm", "xlsx", "xls"]
-    DOCUMENT_EXTENSIONS.extend(("doc", "docx", "csv", "eml", "msg", "pptx", "xml", "epub"))
+    DOCUMENT_EXTENSIONS.extend(("docx", "csv", "eml", "msg", "pptx", "xml", "epub"))
    if dify_config.UNSTRUCTURED_API_URL:
        DOCUMENT_EXTENSIONS.append("ppt")
    DOCUMENT_EXTENSIONS.extend([ext.upper() for ext in DOCUMENT_EXTENSIONS])
@@ -2,30 +2,28 @@ import uuid
 from typing import cast

 from flask_login import current_user  # type: ignore
-from flask_restful import Resource, inputs, marshal, marshal_with, reqparse  # type: ignore
+from flask_restful import (Resource, inputs, marshal,  # type: ignore
+                           marshal_with, reqparse)
 from sqlalchemy import select
 from sqlalchemy.orm import Session
 from werkzeug.exceptions import BadRequest, Forbidden, abort

 from controllers.console import api
 from controllers.console.app.wraps import get_app_model
-from controllers.console.wraps import (
-    account_initialization_required,
-    cloud_edition_billing_resource_check,
-    enterprise_license_required,
-    setup_required,
-)
+from controllers.console.wraps import (account_initialization_required,
+                                       cloud_edition_billing_resource_check,
+                                       enterprise_license_required,
+                                       setup_required)
 from core.ops.ops_trace_manager import OpsTraceManager
 from extensions.ext_database import db
-from fields.app_fields import (
-    app_detail_fields,
-    app_detail_fields_with_site,
-    app_pagination_fields,
-)
+from fields.app_fields import (app_detail_fields, app_detail_fields_with_site,
+                               app_pagination_fields)
 from libs.login import login_required
 from models import Account, App
 from services.app_dsl_service import AppDslService, ImportMode
 from services.app_service import AppService
+from services.enterprise.enterprise_service import EnterpriseService
+from services.feature_service import FeatureService

 ALLOW_CREATE_APP_MODES = ["chat", "agent-chat", "advanced-chat", "workflow", "completion"]

@@ -67,7 +65,17 @@ class AppListApi(Resource):
        if not app_pagination:
            return {"data": [], "total": 0, "page": 1, "limit": 20, "has_more": False}

-        return marshal(app_pagination, app_pagination_fields)
+        if FeatureService.get_system_features().webapp_auth.enabled:
+            app_ids = [str(app.id) for app in app_pagination.items]
+            res = EnterpriseService.WebAppAuth.batch_get_app_access_mode_by_id(app_ids=app_ids)
+            if len(res) != len(app_ids):
+                raise BadRequest("Invalid app id in webapp auth")
+
+            for app in app_pagination.items:
+                if str(app.id) in res:
+                    app.access_mode = res[str(app.id)].access_mode
+
+        return marshal(app_pagination, app_pagination_fields), 200

    @setup_required
    @login_required
@@ -111,6 +119,10 @@ class AppApi(Resource):

        app_model = app_service.get_app(app_model)

+        if FeatureService.get_system_features().webapp_auth.enabled:
+            app_setting = EnterpriseService.WebAppAuth.get_app_access_mode_by_id(app_id=str(app_model.id))
+            app_model.access_mode = app_setting.access_mode
+
        return app_model

    @setup_required
@@ -59,9 +59,3 @@ class EmailCodeAccountDeletionRateLimitExceededError(BaseHTTPException):
    error_code = "email_code_account_deletion_rate_limit_exceeded"
    description = "Too many account deletion emails have been sent. Please try again in 5 minutes."
    code = 429
-
-
-class EmailPasswordResetLimitError(BaseHTTPException):
-    error_code = "email_password_reset_limit"
-    description = "Too many failed password reset attempts. Please try again in 24 hours."
-    code = 429
@@ -6,15 +6,13 @@ from flask_restful import Resource, reqparse  # type: ignore

 from constants.languages import languages
 from controllers.console import api
-from controllers.console.auth.error import (
-    EmailCodeError,
-    EmailPasswordResetLimitError,
-    InvalidEmailError,
-    InvalidTokenError,
-    PasswordMismatchError,
-)
-from controllers.console.error import AccountInFreezeError, AccountNotFound, EmailSendIpLimitError
-from controllers.console.wraps import setup_required
+from controllers.console.auth.error import (EmailCodeError, InvalidEmailError,
+                                            InvalidTokenError,
+                                            PasswordMismatchError)
+from controllers.console.error import (AccountInFreezeError, AccountNotFound,
+                                       EmailSendIpLimitError)
+from controllers.console.wraps import (email_password_login_enabled,
+                                       setup_required)
 from events.tenant_event import tenant_was_created
 from extensions.ext_database import db
 from libs.helper import email, extract_remote_ip
@@ -28,6 +26,7 @@ from services.feature_service import FeatureService

 class ForgotPasswordSendEmailApi(Resource):
    @setup_required
+    @email_password_login_enabled
    def post(self):
        parser = reqparse.RequestParser()
        parser.add_argument("email", type=email, required=True, location="json")
@@ -59,6 +58,7 @@ class ForgotPasswordSendEmailApi(Resource):

 class ForgotPasswordCheckApi(Resource):
    @setup_required
+    @email_password_login_enabled
    def post(self):
        parser = reqparse.RequestParser()
        parser.add_argument("email", type=str, required=True, location="json")
@@ -68,10 +68,6 @@ class ForgotPasswordCheckApi(Resource):

        user_email = args["email"]

-        is_forgot_password_error_rate_limit = AccountService.is_forgot_password_error_rate_limit(args["email"])
-        if is_forgot_password_error_rate_limit:
-            raise EmailPasswordResetLimitError()
-
        token_data = AccountService.get_reset_password_data(args["token"])
        if token_data is None:
            raise InvalidTokenError()
@@ -80,15 +76,22 @@ class ForgotPasswordCheckApi(Resource):
            raise InvalidEmailError()

        if args["code"] != token_data.get("code"):
-            AccountService.add_forgot_password_error_rate_limit(args["email"])
            raise EmailCodeError()

-        AccountService.reset_forgot_password_error_rate_limit(args["email"])
-        return {"is_valid": True, "email": token_data.get("email")}
+        # Verified, revoke the first token
+        AccountService.revoke_reset_password_token(args["token"])
+
+        # Refresh token data by generating a new token
+        _, new_token = AccountService.generate_reset_password_token(
+            user_email, code=args["code"], additional_data={"phase": "reset"}
+        )
+
+        return {"is_valid": True, "email": token_data.get("email"), "token": new_token}


 class ForgotPasswordResetApi(Resource):
    @setup_required
+    @email_password_login_enabled
    def post(self):
        parser = reqparse.RequestParser()
        parser.add_argument("token", type=str, required=True, nullable=False, location="json")
@@ -107,6 +110,9 @@ class ForgotPasswordResetApi(Resource):

        if reset_data is None:
            raise InvalidTokenError()
+        # Must use token in reset phase
+        if reset_data.get("phase", "") != "reset":
+            raise InvalidTokenError()

        AccountService.revoke_reset_password_token(token)

@@ -22,7 +22,7 @@ from controllers.console.error import (
    EmailSendIpLimitError,
    NotAllowedCreateWorkspace,
 )
-from controllers.console.wraps import setup_required
+from controllers.console.wraps import email_password_login_enabled, setup_required
 from events.tenant_event import tenant_was_created
 from libs.helper import email, extract_remote_ip
 from libs.password import valid_password
@@ -38,6 +38,7 @@ class LoginApi(Resource):
    """Resource for user login."""

    @setup_required
+    @email_password_login_enabled
    def post(self):
        """Authenticate user and login."""
        parser = reqparse.RequestParser()
@@ -110,6 +111,7 @@ class LogoutApi(Resource):

 class ResetPasswordSendEmailApi(Resource):
    @setup_required
+    @email_password_login_enabled
    def post(self):
        parser = reqparse.RequestParser()
        parser.add_argument("email", type=email, required=True, location="json")
@@ -23,3 +23,9 @@ class AppSuggestedQuestionsAfterAnswerDisabledError(BaseHTTPException):
    error_code = "app_suggested_questions_after_answer_disabled"
    description = "Function Suggested questions after answer disabled."
    code = 403
+
+
+class AppAccessDeniedError(BaseHTTPException):
+    error_code = "access_denied"
+    description = "App access denied."
+    code = 403
@@ -1,20 +1,26 @@
+import logging
 from datetime import UTC, datetime
 from typing import Any

 from flask import request
 from flask_login import current_user  # type: ignore
-from flask_restful import Resource, inputs, marshal_with, reqparse  # type: ignore
+from flask_restful import (Resource, inputs, marshal_with,  # type: ignore
+                           reqparse)
 from sqlalchemy import and_
 from werkzeug.exceptions import BadRequest, Forbidden, NotFound

 from controllers.console import api
 from controllers.console.explore.wraps import InstalledAppResource
-from controllers.console.wraps import account_initialization_required, cloud_edition_billing_resource_check
+from controllers.console.wraps import (account_initialization_required,
+                                       cloud_edition_billing_resource_check)
 from extensions.ext_database import db
 from fields.installed_app_fields import installed_app_list_fields
 from libs.login import login_required
 from models import App, InstalledApp, RecommendedApp
 from services.account_service import TenantService
+from services.app_service import AppService
+from services.enterprise.enterprise_service import EnterpriseService
+from services.feature_service import FeatureService


 class InstalledAppsListApi(Resource):
@@ -48,6 +54,23 @@ class InstalledAppsListApi(Resource):
            for installed_app in installed_apps
            if installed_app.app is not None
        ]
+
+        # filter out apps that user doesn't have access to
+        if FeatureService.get_system_features().webapp_auth.enabled:
+            user_id = current_user.id
+            res = []
+            for installed_app in installed_app_list:
+                app_code = AppService.get_app_code_by_id(str(installed_app["app"].id))
+                if EnterpriseService.WebAppAuth.is_user_allowed_to_access_webapp(
+                    user_id=user_id,
+                    app_code=app_code,
+                ):
+                    res.append(installed_app)
+            installed_app_list = res
+            logging.info(
+                f"installed_app_list: {installed_app_list}, user_id: {user_id}"
+            )
+
        installed_app_list.sort(
            key=lambda app: (
                -app["is_pinned"],
@@ -4,10 +4,14 @@ from flask_login import current_user  # type: ignore
 from flask_restful import Resource  # type: ignore
 from werkzeug.exceptions import NotFound

+from controllers.console.explore.error import AppAccessDeniedError
 from controllers.console.wraps import account_initialization_required
 from extensions.ext_database import db
 from libs.login import login_required
 from models import InstalledApp
+from services.app_service import AppService
+from services.enterprise.enterprise_service import EnterpriseService
+from services.feature_service import FeatureService


 def installed_app_required(view=None):
@@ -48,6 +52,30 @@ def installed_app_required(view=None):
    return decorator


+def user_allowed_to_access_app(view=None):
+    def decorator(view):
+        @wraps(view)
+        def decorated(installed_app: InstalledApp, *args, **kwargs):
+            feature = FeatureService.get_system_features()
+            if feature.webapp_auth.enabled:
+                app_id = installed_app.app_id
+                app_code = AppService.get_app_code_by_id(app_id)
+                res = EnterpriseService.WebAppAuth.is_user_allowed_to_access_webapp(
+                    user_id=str(current_user.id),
+                    app_code=app_code,
+                )
+                if not res:
+                    raise AppAccessDeniedError()
+
+            return view(installed_app, *args, **kwargs)
+
+        return decorated
+    if view:
+        return decorator(view)
+    return decorator
+
+
 class InstalledAppResource(Resource):
    # must be reversed if there are multiple decorators
-    method_decorators = [installed_app_required, account_initialization_required, login_required]
+
+    method_decorators = [user_allowed_to_access_app, installed_app_required, account_initialization_required, login_required]
@@ -11,7 +11,8 @@ from models.model import DifySetup
 from services.feature_service import FeatureService, LicenseStatus
 from services.operation_service import OperationService

-from .error import NotInitValidateError, NotSetupError, UnauthorizedAndForceLogout
+from .error import (NotInitValidateError, NotSetupError,
+                    UnauthorizedAndForceLogout)


 def account_initialization_required(view):
@@ -39,6 +40,17 @@ def only_edition_cloud(view):
    return decorated


+def only_enterprise_edition(view):
+    @wraps(view)
+    def decorated(*args, **kwargs):
+        if not dify_config.ENTERPRISE_ENABLED:
+            abort(404)
+
+        return view(*args, **kwargs)
+
+    return decorated
+
+
 def only_edition_self_hosted(view):
    @wraps(view)
    def decorated(*args, **kwargs):
@@ -154,3 +166,16 @@ def enterprise_license_required(view):
        return view(*args, **kwargs)

    return decorated
+
+
+def email_password_login_enabled(view):
+    @wraps(view)
+    def decorated(*args, **kwargs):
+        features = FeatureService.get_system_features()
+        if features.enable_email_password_login:
+            return view(*args, **kwargs)
+
+        # otherwise, return 403
+        abort(403)
+
+    return decorated
@@ -5,4 +5,5 @@ from libs.external_api import ExternalApi
 bp = Blueprint("inner_api", __name__, url_prefix="/inner/api")
 api = ExternalApi(bp)

+from . import mail
 from .workspace import workspace
@@ -0,0 +1,27 @@
+from flask_restful import (
+    Resource,  # type: ignore
+    reqparse,
+)
+
+from controllers.console.wraps import setup_required
+from controllers.inner_api import api
+from controllers.inner_api.wraps import inner_api_only
+from services.enterprise.mail_service import DifyMail, EnterpriseMailService
+
+
+class EnterpriseMail(Resource):
+    @setup_required
+    @inner_api_only
+    def post(self):
+        parser = reqparse.RequestParser()
+        parser.add_argument("to", type=str, action="append", required=True)
+        parser.add_argument("subject", type=str, required=True)
+        parser.add_argument("body", type=str, required=True)
+        parser.add_argument("substitutions", type=dict, required=False)
+        args = parser.parse_args()
+
+        EnterpriseMailService.send_mail(DifyMail(**args))
+        return {"message": "success"}, 200
+
+
+api.add_resource(EnterpriseMail, "/enterprise/mail")
@@ -50,8 +50,8 @@ class EnterpriseWorkspaceNoOwnerEmail(Resource):
            "plan": tenant.plan,
            "status": tenant.status,
            "custom_config": json.loads(tenant.custom_config) if tenant.custom_config else {},
-            "created_at": tenant.created_at.isoformat() + "Z" if tenant.created_at else None,
-            "updated_at": tenant.updated_at.isoformat() + "Z" if tenant.updated_at else None,
+            "created_at": tenant.created_at.isoformat() if tenant.created_at else None,
+            "updated_at": tenant.updated_at.isoformat() if tenant.updated_at else None,
        }

        return {
@@ -1,12 +1,16 @@
-from flask_restful import marshal_with  # type: ignore
+
+from flask import request
+from flask_restful import Resource, marshal_with, reqparse  # type: ignore

 from controllers.common import fields
 from controllers.common import helpers as controller_helpers
 from controllers.web import api
 from controllers.web.error import AppUnavailableError
 from controllers.web.wraps import WebApiResource
+from libs.passport import PassportService
 from models.model import App, AppMode
 from services.app_service import AppService
+from services.enterprise.enterprise_service import EnterpriseService


 class AppParameterApi(WebApiResource):
@@ -42,5 +46,51 @@ class AppMeta(WebApiResource):
        return AppService().get_app_meta(app_model)


+class AppAccessMode(Resource):
+    def get(self):
+        parser = reqparse.RequestParser()
+        parser.add_argument("appId", type=str, required=True, location="args")
+        args = parser.parse_args()
+
+        app_id = args["appId"]
+        res = EnterpriseService.WebAppAuth.get_app_access_mode_by_id(app_id)
+
+        return {"accessMode": res.access_mode}
+
+
+class AppWebAuthPermission(Resource):
+    def get(self):
+        user_id = "visitor"
+        try:
+            auth_header = request.headers.get("Authorization")
+            if auth_header is None:
+                raise
+            if " " not in auth_header:
+                raise
+
+            auth_scheme, tk = auth_header.split(None, 1)
+            auth_scheme = auth_scheme.lower()
+            if auth_scheme != "bearer":
+                raise
+
+            decoded = PassportService().verify(tk)
+            user_id = decoded.get("user_id", "visitor")
+        except Exception as e:
+            pass
+
+        parser = reqparse.RequestParser()
+        parser.add_argument("appId", type=str, required=True, location="args")
+        args = parser.parse_args()
+
+        app_id = args["appId"]
+        app_code = AppService.get_app_code_by_id(app_id)
+
+        res = EnterpriseService.WebAppAuth.is_user_allowed_to_access_webapp(str(user_id), app_code)
+        return {"result": res}
+
+
 api.add_resource(AppParameterApi, "/parameters")
 api.add_resource(AppMeta, "/meta")
+# webapp auth apis
+api.add_resource(AppAccessMode, "/webapp/access-mode")
+api.add_resource(AppWebAuthPermission, "/webapp/permission")
@@ -121,9 +121,15 @@ class UnsupportedFileTypeError(BaseHTTPException):
    code = 415


-class WebSSOAuthRequiredError(BaseHTTPException):
+class WebAppAuthRequiredError(BaseHTTPException):
    error_code = "web_sso_auth_required"
-    description = "Web SSO authentication required."
+    description = "Web app authentication required."
+    code = 401
+
+
+class WebAppAuthAccessDeniedError(BaseHTTPException):
+    error_code = "web_app_access_denied"
+    description = "You do not have permission to access this web app."
    code = 401


@@ -0,0 +1,121 @@
+from flask import request
+from flask_restful import Resource, reqparse
+from jwt import InvalidTokenError  # type: ignore
+from web import api
+from werkzeug.exceptions import BadRequest
+
+import services
+from controllers.console.auth.error import EmailCodeError, EmailOrPasswordMismatchError, InvalidEmailError
+from controllers.console.error import AccountBannedError, AccountNotFound
+from controllers.console.wraps import setup_required
+from libs.helper import email
+from libs.password import valid_password
+from services.account_service import AccountService
+from services.webapp_auth_service import WebAppAuthService
+
+
+class LoginApi(Resource):
+    """Resource for web app email/password login."""
+
+    def post(self):
+        """Authenticate user and login."""
+        parser = reqparse.RequestParser()
+        parser.add_argument("email", type=email, required=True, location="json")
+        parser.add_argument("password", type=valid_password, required=True, location="json")
+        args = parser.parse_args()
+
+        app_code = request.headers.get("X-App-Code")
+        if app_code is None:
+            raise BadRequest("X-App-Code header is missing.")
+
+        try:
+            account = WebAppAuthService.authenticate(args["email"], args["password"])
+        except services.errors.account.AccountLoginError:
+            raise AccountBannedError()
+        except services.errors.account.AccountPasswordError:
+            raise EmailOrPasswordMismatchError()
+        except services.errors.account.AccountNotFoundError:
+            raise AccountNotFound()
+
+        WebAppAuthService._validate_user_accessibility(account=account, app_code=app_code)
+
+        end_user = WebAppAuthService.create_end_user(email=args["email"], app_code=app_code)
+
+        token = WebAppAuthService.login(account=account, app_code=app_code, end_user_id=end_user.id)
+        return {"result": "success", "token": token}
+
+
+# class LogoutApi(Resource):
+#     @setup_required
+#     def get(self):
+#         account = cast(Account, flask_login.current_user)
+#         if isinstance(account, flask_login.AnonymousUserMixin):
+#             return {"result": "success"}
+#         flask_login.logout_user()
+#         return {"result": "success"}
+
+
+class EmailCodeLoginSendEmailApi(Resource):
+    @setup_required
+    def post(self):
+        parser = reqparse.RequestParser()
+        parser.add_argument("email", type=email, required=True, location="json")
+        parser.add_argument("language", type=str, required=False, location="json")
+        args = parser.parse_args()
+
+        if args["language"] is not None and args["language"] == "zh-Hans":
+            language = "zh-Hans"
+        else:
+            language = "en-US"
+
+        account = WebAppAuthService.get_user_through_email(args["email"])
+        if account is None:
+            raise AccountNotFound()
+        else:
+            token = WebAppAuthService.send_email_code_login_email(account=account, language=language)
+
+        return {"result": "success", "data": token}
+
+
+class EmailCodeLoginApi(Resource):
+    @setup_required
+    def post(self):
+        parser = reqparse.RequestParser()
+        parser.add_argument("email", type=str, required=True, location="json")
+        parser.add_argument("code", type=str, required=True, location="json")
+        parser.add_argument("token", type=str, required=True, location="json")
+        args = parser.parse_args()
+
+        user_email = args["email"]
+        app_code = request.headers.get("X-App-Code")
+        if app_code is None:
+            raise BadRequest("X-App-Code header is missing.")
+
+        token_data = WebAppAuthService.get_email_code_login_data(args["token"])
+        if token_data is None:
+            raise InvalidTokenError()
+
+        if token_data["email"] != args["email"]:
+            raise InvalidEmailError()
+
+        if token_data["code"] != args["code"]:
+            raise EmailCodeError()
+
+        WebAppAuthService.revoke_email_code_login_token(args["token"])
+        account = WebAppAuthService.get_user_through_email(user_email)
+        if not account:
+            raise AccountNotFound()
+
+        WebAppAuthService._validate_user_accessibility(account=account, app_code=app_code)
+
+        end_user = WebAppAuthService.create_end_user(email=user_email, app_code=app_code)
+
+        token = WebAppAuthService.login(account=account, app_code=app_code, end_user_id=end_user.id)
+        AccountService.reset_login_error_rate_limit(args["email"])
+        return {"result": "success", "token": token}
+
+
+api.add_resource(LoginApi, "/login")
+# api.add_resource(LogoutApi, "/logout")
+api.add_resource(EmailCodeLoginSendEmailApi, "/email-code-login")
+api.add_resource(EmailCodeLoginApi, "/email-code-login/validity")
@@ -5,7 +5,7 @@ from flask_restful import Resource  # type: ignore
 from werkzeug.exceptions import NotFound, Unauthorized

 from controllers.web import api
-from controllers.web.error import WebSSOAuthRequiredError
+from controllers.web.error import WebAppAuthRequiredError
 from extensions.ext_database import db
 from libs.passport import PassportService
 from models.model import App, EndUser, Site
@@ -22,10 +22,10 @@ class PassportResource(Resource):
        if app_code is None:
            raise Unauthorized("X-App-Code header is missing.")

-        if system_features.sso_enforced_for_web:
-            app_web_sso_enabled = EnterpriseService.get_app_web_sso_enabled(app_code).get("enabled", False)
-            if app_web_sso_enabled:
-                raise WebSSOAuthRequiredError()
+        if system_features.webapp_auth.enabled:
+            app_settings = EnterpriseService.WebAppAuth.get_app_access_mode_by_code(app_code=app_code)
+            if not app_settings or not app_settings.access_mode == "public":
+                raise WebAppAuthRequiredError()

        # get site from db and check if it is normal
        site = db.session.query(Site).filter(Site.code == app_code, Site.status == "normal").first()
@@ -4,7 +4,7 @@ from flask import request
 from flask_restful import Resource  # type: ignore
 from werkzeug.exceptions import BadRequest, NotFound, Unauthorized

-from controllers.web.error import WebSSOAuthRequiredError
+from controllers.web.error import WebAppAuthAccessDeniedError, WebAppAuthRequiredError
 from extensions.ext_database import db
 from libs.passport import PassportService
 from models.model import App, EndUser, Site
@@ -57,35 +57,53 @@ def decode_jwt_token():
        if not end_user:
            raise NotFound()

-        _validate_web_sso_token(decoded, system_features, app_code)
+        # for enterprise webapp auth
+        app_web_auth_enabled = False
+        if system_features.webapp_auth.enabled:
+            app_web_auth_enabled = (
+                EnterpriseService.WebAppAuth.get_app_access_mode_by_code(app_code=app_code).access_mode != "public"
+            )
+
+        _validate_webapp_token(decoded, app_web_auth_enabled, system_features.webapp_auth.enabled)
+        _validate_user_accessibility(decoded, app_code, app_web_auth_enabled, system_features.webapp_auth.enabled)

        return app_model, end_user
    except Unauthorized as e:
-        if system_features.sso_enforced_for_web:
-            app_web_sso_enabled = EnterpriseService.get_app_web_sso_enabled(app_code).get("enabled", False)
-            if app_web_sso_enabled:
-                raise WebSSOAuthRequiredError()
+        if system_features.webapp_auth.enabled:
+            app_web_auth_enabled = (
+                EnterpriseService.WebAppAuth.get_app_access_mode_by_code(app_code=app_code).access_mode != "public"
+            )
+            if app_web_auth_enabled:
+                raise WebAppAuthRequiredError()

        raise Unauthorized(e.description)


-def _validate_web_sso_token(decoded, system_features, app_code):
-    app_web_sso_enabled = False
-
-    # Check if SSO is enforced for web, and if the token source is not SSO, raise an error and redirect to SSO login
-    if system_features.sso_enforced_for_web:
-        app_web_sso_enabled = EnterpriseService.get_app_web_sso_enabled(app_code).get("enabled", False)
-        if app_web_sso_enabled:
-            source = decoded.get("token_source")
-            if not source or source != "sso":
-                raise WebSSOAuthRequiredError()
-
-    # Check if SSO is not enforced for web, and if the token source is SSO,
-    # raise an error and redirect to normal passport login
-    if not system_features.sso_enforced_for_web or not app_web_sso_enabled:
+def _validate_webapp_token(decoded, app_web_auth_enabled: bool, system_webapp_auth_enabled: bool):
+    # Check if authentication is enforced for web app, and if the token source is not webapp,
+    # raise an error and redirect to login
+    if system_webapp_auth_enabled and app_web_auth_enabled:
        source = decoded.get("token_source")
-        if source and source == "sso":
-            raise Unauthorized("sso token expired.")
+        if not source or source != "webapp":
+            raise WebAppAuthRequiredError()
+
+    # Check if authentication is not enforced for web, and if the token source is webapp,
+    # raise an error and redirect to normal passport login
+    if not system_webapp_auth_enabled or not app_web_auth_enabled:
+        source = decoded.get("token_source")
+        if source and source == "webapp":
+            raise Unauthorized("webapp token expired.")
+
+
+def _validate_user_accessibility(decoded, app_code, app_web_auth_enabled: bool, system_webapp_auth_enabled: bool):
+    if system_webapp_auth_enabled and app_web_auth_enabled:
+        # Check if the user is allowed to access the web app
+        user_id = decoded.get("user_id")
+        if not user_id:
+            raise WebAppAuthRequiredError()
+
+        if not EnterpriseService.WebAppAuth.is_user_allowed_to_access_webapp(user_id, app_code=app_code):
+            raise WebAppAuthAccessDeniedError()


 class WebApiResource(Resource):
@@ -140,7 +140,9 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
            app_config=app_config,
            file_upload_config=file_extra_config,
            conversation_id=conversation.id if conversation else None,
-            inputs=self._prepare_user_inputs(
+            inputs=conversation.inputs
+            if conversation
+            else self._prepare_user_inputs(
                user_inputs=inputs, variables=app_config.variables, tenant_id=app_model.tenant_id
            ),
            query=query,
@@ -148,7 +148,9 @@ class AgentChatAppGenerator(MessageBasedAppGenerator):
            model_conf=ModelConfigConverter.convert(app_config),
            file_upload_config=file_extra_config,
            conversation_id=conversation.id if conversation else None,
-            inputs=self._prepare_user_inputs(
+            inputs=conversation.inputs
+            if conversation
+            else self._prepare_user_inputs(
                user_inputs=inputs, variables=app_config.variables, tenant_id=app_model.tenant_id
            ),
            query=query,
@@ -141,7 +141,9 @@ class ChatAppGenerator(MessageBasedAppGenerator):
            model_conf=ModelConfigConverter.convert(app_config),
            file_upload_config=file_extra_config,
            conversation_id=conversation.id if conversation else None,
-            inputs=self._prepare_user_inputs(
+            inputs=conversation.inputs
+            if conversation
+            else self._prepare_user_inputs(
                user_inputs=inputs, variables=app_config.variables, tenant_id=app_model.tenant_id
            ),
            query=query,
@@ -842,4 +842,4 @@ class WorkflowCycleManage:
        if node_execution_id not in self._workflow_node_executions:
            raise ValueError(f"Workflow node execution not found: {node_execution_id}")
        cached_workflow_node_execution = self._workflow_node_executions[node_execution_id]
-        return session.merge(cached_workflow_node_execution)
+        return cached_workflow_node_execution
@@ -30,6 +30,11 @@ from core.model_runtime.model_providers.__base.ai_model import AIModel

 logger = logging.getLogger(__name__)

+HTML_THINKING_TAG = (
+    '<details style="color:gray;background-color: #f8f8f8;padding: 8px;border-radius: 4px;" open> '
+    "<summary> Thinking... </summary>"
+)
+

 class LargeLanguageModel(AIModel):
    """
@@ -403,7 +408,7 @@ if you are not sure about the structure.
    def _wrap_thinking_by_reasoning_content(self, delta: dict, is_reasoning: bool) -> tuple[str, bool]:
        """
        If the reasoning response is from delta.get("reasoning_content"), we wrap
-        it with HTML think tag.
+        it with HTML details tag.

        :param delta: delta dictionary from LLM streaming response
        :param is_reasoning: is reasoning
@@ -415,17 +420,25 @@ if you are not sure about the structure.

        if reasoning_content:
            if not is_reasoning:
-                content = "<think>\n" + reasoning_content
+                content = HTML_THINKING_TAG + reasoning_content
                is_reasoning = True
            else:
                content = reasoning_content
-        elif is_reasoning and content:
-            # do not end reasoning when content is empty
-            # there may be more reasoning_content later that follows previous reasoning closely
-            content = "\n</think>" + content
+        elif is_reasoning:
+            content = "</details>" + content
            is_reasoning = False
        return content, is_reasoning

+    def _wrap_thinking_by_tag(self, content: str) -> str:
+        """
+        if the reasoning response is a <think>...</think> block from delta.get("content"),
+        we replace <think> to <detail>.
+
+        :param content: delta.get("content")
+        :return: processed_content
+        """
+        return content.replace("<think>", HTML_THINKING_TAG).replace("</think>", "</details>")
+
    def _invoke_result_generator(
        self,
        model: str,
@@ -1,6 +1,5 @@
 - gemini-2.0-flash-001
 - gemini-2.0-flash-exp
- gemini-2.0-flash-lite-preview-02-05
 - gemini-2.0-pro-exp-02-05
 - gemini-2.0-flash-thinking-exp-1219
 - gemini-2.0-flash-thinking-exp-01-21
@@ -1,41 +0,0 @@
-model: gemini-2.0-flash-lite-preview-02-05
-label:
-  en_US: Gemini 2.0 Flash Lite Preview 0205
-model_type: llm
-features:
-  - agent-thought
-  - vision
-  - tool-call
-  - stream-tool-call
-  - document
-  - video
-  - audio
-model_properties:
-  mode: chat
-  context_size: 1048576
-parameter_rules:
-  - name: temperature
-    use_template: temperature
-  - name: top_p
-    use_template: top_p
-  - name: top_k
-    label:
-      zh_Hans: 取样数量
-      en_US: Top k
-    type: int
-    help:
-      zh_Hans: 仅从每个后续标记的前 K 个选项中采样。
-      en_US: Only sample from the top K options for each subsequent token.
-    required: false
-  - name: max_output_tokens
-    use_template: max_tokens
-    default: 8192
-    min: 1
-    max: 8192
-  - name: json_schema
-    use_template: json_schema
-pricing:
-  input: '0.00'
-  output: '0.00'
-  unit: '0.000001'
-  currency: USD
@@ -367,6 +367,7 @@ class OllamaLargeLanguageModel(LargeLanguageModel):

                # transform assistant message to prompt message
                text = chunk_json["response"]
+            text = self._wrap_thinking_by_tag(text)

            assistant_prompt_message = AssistantPromptMessage(content=text)

@@ -528,6 +528,7 @@ class OAIAPICompatLargeLanguageModel(_CommonOaiApiCompat, LargeLanguageModel):
                    delta_content, is_reasoning_started = self._wrap_thinking_by_reasoning_content(
                        delta, is_reasoning_started
                    )
+                    delta_content = self._wrap_thinking_by_tag(delta_content)

                    assistant_message_tool_calls = None

@@ -807,37 +808,34 @@ class OAIAPICompatLargeLanguageModel(_CommonOaiApiCompat, LargeLanguageModel):

            # calculate num tokens for function object
            num_tokens += self._get_num_tokens_by_gpt2("name")
-            if hasattr(tool, "name"):
-                num_tokens += self._get_num_tokens_by_gpt2(tool.name)
+            num_tokens += self._get_num_tokens_by_gpt2(tool.name)
            num_tokens += self._get_num_tokens_by_gpt2("description")
-            if hasattr(tool, "description"):
-                num_tokens += self._get_num_tokens_by_gpt2(tool.description)
-            if hasattr(tool, "parameters"):
-                parameters = tool.parameters
-                num_tokens += self._get_num_tokens_by_gpt2("parameters")
-                if "title" in parameters:
-                    num_tokens += self._get_num_tokens_by_gpt2("title")
-                    num_tokens += self._get_num_tokens_by_gpt2(parameters.get("title"))
-                num_tokens += self._get_num_tokens_by_gpt2("type")
-                num_tokens += self._get_num_tokens_by_gpt2(parameters.get("type"))
-                if "properties" in parameters:
-                    num_tokens += self._get_num_tokens_by_gpt2("properties")
-                    for key, value in parameters.get("properties", {}).items():
-                        num_tokens += self._get_num_tokens_by_gpt2(key)
-                        for field_key, field_value in value.items():
+            num_tokens += self._get_num_tokens_by_gpt2(tool.description)
+            parameters = tool.parameters
+            num_tokens += self._get_num_tokens_by_gpt2("parameters")
+            if "title" in parameters:
+                num_tokens += self._get_num_tokens_by_gpt2("title")
+                num_tokens += self._get_num_tokens_by_gpt2(parameters.get("title"))
+            num_tokens += self._get_num_tokens_by_gpt2("type")
+            num_tokens += self._get_num_tokens_by_gpt2(parameters.get("type"))
+            if "properties" in parameters:
+                num_tokens += self._get_num_tokens_by_gpt2("properties")
+                for key, value in parameters.get("properties").items():
+                    num_tokens += self._get_num_tokens_by_gpt2(key)
+                    for field_key, field_value in value.items():
+                        num_tokens += self._get_num_tokens_by_gpt2(field_key)
+                        if field_key == "enum":
+                            for enum_field in field_value:
+                                num_tokens += 3
+                                num_tokens += self._get_num_tokens_by_gpt2(enum_field)
+                        else:
                            num_tokens += self._get_num_tokens_by_gpt2(field_key)
-                            if field_key == "enum":
-                                for enum_field in field_value:
-                                    num_tokens += 3
-                                    num_tokens += self._get_num_tokens_by_gpt2(enum_field)
-                            else:
-                                num_tokens += self._get_num_tokens_by_gpt2(field_key)
-                                num_tokens += self._get_num_tokens_by_gpt2(str(field_value))
-                if "required" in parameters:
-                    num_tokens += self._get_num_tokens_by_gpt2("required")
-                    for required_field in parameters["required"]:
-                        num_tokens += 3
-                        num_tokens += self._get_num_tokens_by_gpt2(required_field)
+                            num_tokens += self._get_num_tokens_by_gpt2(str(field_value))
+            if "required" in parameters:
+                num_tokens += self._get_num_tokens_by_gpt2("required")
+                for required_field in parameters["required"]:
+                    num_tokens += 3
+                    num_tokens += self._get_num_tokens_by_gpt2(required_field)

        return num_tokens

@@ -430,7 +430,7 @@ class SageMakerLargeLanguageModel(LargeLanguageModel):
                type=ParameterType.INT,
                use_template="max_tokens",
                min=1,
-                max=int(credentials.get("context_length", 2048)),
+                max=credentials.get("context_length", 2048),
                default=512,
                label=I18nObject(zh_Hans="最大生成长度", en_US="Max Tokens"),
            ),
@@ -448,7 +448,7 @@ class SageMakerLargeLanguageModel(LargeLanguageModel):
        if support_vision:
            features.append(ModelFeature.VISION)

-        context_length = int(credentials.get("context_length", 2048))
+        context_length = credentials.get("context_length", 2048)

        entity = AIModelEntity(
            model=model,
@@ -59,19 +59,6 @@ model_credential_schema:
      placeholder:
        zh_Hans: 请输出你的Sagemaker推理端点
        en_US: Enter your Sagemaker Inference endpoint
-    - variable: context_length
-      show_on:
-        - variable: __model_type
-          value: llm
-      label:
-        zh_Hans: 模型上下文长度
-        en_US: Model context size
-      type: text-input
-      default: '4096'
-      required: true
-      placeholder:
-        zh_Hans: 在此输入您的模型上下文长度
-        en_US: Enter your Model context size
    - variable: audio_s3_cache_bucket
      show_on:
        - variable: __model_type
@@ -17,13 +17,6 @@
 - deepseek-ai/DeepSeek-V2.5
 - deepseek-ai/DeepSeek-V3
 - deepseek-ai/DeepSeek-Coder-V2-Instruct
- deepseek-ai/DeepSeek-R1-Distill-Llama-8B
- deepseek-ai/DeepSeek-R1-Distill-Llama-70B
- deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B
- deepseek-ai/DeepSeek-R1-Distill-Qwen-7B
- deepseek-ai/DeepSeek-R1-Distill-Qwen-14B
- deepseek-ai/DeepSeek-R1-Distill-Qwen-32B
- deepseek-ai/Janus-Pro-7B
 - THUDM/glm-4-9b-chat
 - 01-ai/Yi-1.5-34B-Chat-16K
 - 01-ai/Yi-1.5-9B-Chat-16K
@@ -1,21 +0,0 @@
-model: deepseek-ai/DeepSeek-R1-Distill-Llama-70B
-label:
-  zh_Hans: deepseek-ai/DeepSeek-R1-Distill-Llama-70B
-  en_US: deepseek-ai/DeepSeek-R1-Distill-Llama-70B
-model_type: llm
-features:
-  - agent-thought
-model_properties:
-  mode: chat
-  context_size: 32000
-parameter_rules:
-  - name: max_tokens
-    use_template: max_tokens
-    min: 1
-    max: 8192
-    default: 4096
-pricing:
-  input: "0.00"
-  output: "4.3"
-  unit: "0.000001"
-  currency: RMB
@@ -1,21 +0,0 @@
-model: deepseek-ai/DeepSeek-R1-Distill-Llama-8B
-label:
-  zh_Hans: deepseek-ai/DeepSeek-R1-Distill-Llama-8B
-  en_US: deepseek-ai/DeepSeek-R1-Distill-Llama-8B
-model_type: llm
-features:
-  - agent-thought
-model_properties:
-  mode: chat
-  context_size: 32000
-parameter_rules:
-  - name: max_tokens
-    use_template: max_tokens
-    min: 1
-    max: 8192
-    default: 4096
-pricing:
-  input: "0.00"
-  output: "0.00"
-  unit: "0.000001"
-  currency: RMB
@@ -1,21 +0,0 @@
-model: deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B
-label:
-  zh_Hans: deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B
-  en_US: deepseek-ai/DeepSeek-R1-Distill-Qwen-1.5B
-model_type: llm
-features:
-  - agent-thought
-model_properties:
-  mode: chat
-  context_size: 32000
-parameter_rules:
-  - name: max_tokens
-    use_template: max_tokens
-    min: 1
-    max: 8192
-    default: 4096
-pricing:
-  input: "0.00"
-  output: "1.26"
-  unit: "0.000001"
-  currency: RMB
@@ -1,21 +0,0 @@
-model: deepseek-ai/DeepSeek-R1-Distill-Qwen-14B
-label:
-  zh_Hans: deepseek-ai/DeepSeek-R1-Distill-Qwen-14B
-  en_US: deepseek-ai/DeepSeek-R1-Distill-Qwen-14B
-model_type: llm
-features:
-  - agent-thought
-model_properties:
-  mode: chat
-  context_size: 32000
-parameter_rules:
-  - name: max_tokens
-    use_template: max_tokens
-    min: 1
-    max: 8192
-    default: 4096
-pricing:
-  input: "0.00"
-  output: "0.70"
-  unit: "0.000001"
-  currency: RMB
@@ -1,21 +0,0 @@
-model: deepseek-ai/DeepSeek-R1-Distill-Qwen-32B
-label:
-  zh_Hans: deepseek-ai/DeepSeek-R1-Distill-Qwen-32B
-  en_US: deepseek-ai/DeepSeek-R1-Distill-Qwen-32B
-model_type: llm
-features:
-  - agent-thought
-model_properties:
-  mode: chat
-  context_size: 32000
-parameter_rules:
-  - name: max_tokens
-    use_template: max_tokens
-    min: 1
-    max: 8192
-    default: 4096
-pricing:
-  input: "0.00"
-  output: "1.26"
-  unit: "0.000001"
-  currency: RMB
@@ -1,21 +0,0 @@
-model: deepseek-ai/DeepSeek-R1-Distill-Qwen-7B
-label:
-  zh_Hans: deepseek-ai/DeepSeek-R1-Distill-Qwen-7B
-  en_US: deepseek-ai/DeepSeek-R1-Distill-Qwen-7B
-model_type: llm
-features:
-  - agent-thought
-model_properties:
-  mode: chat
-  context_size: 32000
-parameter_rules:
-  - name: max_tokens
-    use_template: max_tokens
-    min: 1
-    max: 8192
-    default: 4096
-pricing:
-  input: "0.00"
-  output: "0.00"
-  unit: "0.000001"
-  currency: RMB
@@ -1,22 +0,0 @@
-model: deepseek-ai/Janus-Pro-7B
-label:
-  zh_Hans: deepseek-ai/Janus-Pro-7B
-  en_US: deepseek-ai/Janus-Pro-7B
-model_type: llm
-features:
-  - agent-thought
-  - vision
-model_properties:
-  mode: chat
-  context_size: 32000
-parameter_rules:
-  - name: max_tokens
-    use_template: max_tokens
-    min: 1
-    max: 8192
-    default: 4096
-pricing:
-  input: "0.00"
-  output: "0.00"
-  unit: "0.000001"
-  currency: RMB
@@ -1,7 +1,3 @@
- deepseek-r1
- deepseek-r1-distill-qwen-14b
- deepseek-r1-distill-qwen-32b
- deepseek-v3
 - qwen-vl-max-0809
 - qwen-vl-max-0201
 - qwen-vl-max
@@ -1,21 +0,0 @@
-model: deepseek-r1-distill-qwen-14b
-label:
-  zh_Hans: DeepSeek-R1-Distill-Qwen-14B
-  en_US: DeepSeek-R1-Distill-Qwen-14B
-model_type: llm
-features:
-  - agent-thought
-model_properties:
-  mode: chat
-  context_size: 32000
-parameter_rules:
-  - name: max_tokens
-    use_template: max_tokens
-    min: 1
-    max: 8192
-    default: 4096
-pricing:
-  input: "0.001"
-  output: "0.003"
-  unit: "0.001"
-  currency: RMB
@@ -1,21 +0,0 @@
-model: deepseek-r1-distill-qwen-32b
-label:
-  zh_Hans: DeepSeek-R1-Distill-Qwen-32B
-  en_US: DeepSeek-R1-Distill-Qwen-32B
-model_type: llm
-features:
-  - agent-thought
-model_properties:
-  mode: chat
-  context_size: 32000
-parameter_rules:
-  - name: max_tokens
-    use_template: max_tokens
-    min: 1
-    max: 8192
-    default: 4096
-pricing:
-  input: "0.002"
-  output: "0.006"
-  unit: "0.001"
-  currency: RMB
@@ -1,21 +0,0 @@
-model: deepseek-r1
-label:
-  zh_Hans: DeepSeek-R1
-  en_US: DeepSeek-R1
-model_type: llm
-features:
-  - agent-thought
-model_properties:
-  mode: chat
-  context_size: 64000
-parameter_rules:
-  - name: max_tokens
-    use_template: max_tokens
-    min: 1
-    max: 8192
-    default: 4096
-pricing:
-  input: "0.004"
-  output: "0.016"
-  unit: '0.001'
-  currency: RMB
@@ -1,52 +0,0 @@
-model: deepseek-v3
-label:
-  zh_Hans: DeepSeek-V3
-  en_US: DeepSeek-V3
-model_type: llm
-features:
-  - agent-thought
-model_properties:
-  mode: chat
-  context_size: 64000
-parameter_rules:
-  - name: temperature
-    use_template: temperature
-  - name: max_tokens
-    use_template: max_tokens
-    type: int
-    default: 512
-    min: 1
-    max: 4096
-    help:
-      zh_Hans: 指定生成结果长度的上限。如果生成结果截断，可以调大该参数。
-      en_US: Specifies the upper limit on the length of generated results. If the generated results are truncated, you can increase this parameter.
-  - name: top_p
-    use_template: top_p
-  - name: top_k
-    label:
-      zh_Hans: 取样数量
-      en_US: Top k
-    type: int
-    help:
-      zh_Hans: 仅从每个后续标记的前 K 个选项中采样。
-      en_US: Only sample from the top K options for each subsequent token.
-    required: false
-  - name: frequency_penalty
-    use_template: frequency_penalty
-  - name: response_format
-    label:
-      zh_Hans: 回复格式
-      en_US: Response Format
-    type: string
-    help:
-      zh_Hans: 指定模型必须输出的格式
-      en_US: specifying the format that the model must output
-    required: false
-    options:
-      - text
-      - json_object
-pricing:
-  input: "0.002"
-  output: "0.008"
-  unit: "0.001"
-  currency: RMB
@@ -197,7 +197,8 @@ class TongyiLargeLanguageModel(LargeLanguageModel):
        else:
            # nothing different between chat model and completion model in tongyi
            params["messages"] = self._convert_prompt_messages_to_tongyi_messages(prompt_messages)
-            response = Generation.call(**params, result_format="message", stream=stream, incremental_output=stream)
+            response = Generation.call(**params, result_format="message", stream=stream)
+
        if stream:
            return self._handle_generate_stream_response(model, credentials, response, prompt_messages)

@@ -257,9 +258,6 @@ class TongyiLargeLanguageModel(LargeLanguageModel):
        """
        full_text = ""
        tool_calls = []
-        is_reasoning_started = False
-        # for index, response in enumerate(responses):
-        index = 0
        for index, response in enumerate(responses):
            if response.status_code not in {200, HTTPStatus.OK}:
                raise ServiceUnavailableError(
@@ -313,11 +311,7 @@ class TongyiLargeLanguageModel(LargeLanguageModel):
                    ),
                )
            else:
-                message = response.output.choices[0].message
-
-                resp_content, is_reasoning_started = self._wrap_thinking_by_reasoning_content(
-                    message, is_reasoning_started
-                )
+                resp_content = response.output.choices[0].message.content
                if not resp_content:
                    if "tool_calls" in response.output.choices[0].message:
                        tool_calls = response.output.choices[0].message["tool_calls"]
@@ -69,15 +69,6 @@ parameter_rules:
    help:
      zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。
      en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment.
-  - name: enable_search
-    type: boolean
-    default: false
-    label:
-      zh_Hans: 联网搜索
-      en_US: Web Search
-    help:
-      zh_Hans: 模型内置了互联网搜索服务，该参数控制模型在生成文本时是否参考使用互联网搜索结果。启用互联网搜索，模型会将搜索结果作为文本生成过程中的参考信息，但模型会基于其内部逻辑“自行判断”是否使用互联网搜索结果。
-      en_US: The model has a built-in Internet search service. This parameter controls whether the model refers to Internet search results when generating text. When Internet search is enabled, the model will use the search results as reference information in the text generation process, but the model will "judge" whether to use Internet search results based on its internal logic.
  - name: response_format
    use_template: response_format
 pricing:
@@ -69,15 +69,6 @@ parameter_rules:
    help:
      zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。
      en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment.
-  - name: enable_search
-    type: boolean
-    default: false
-    label:
-      zh_Hans: 联网搜索
-      en_US: Web Search
-    help:
-      zh_Hans: 模型内置了互联网搜索服务，该参数控制模型在生成文本时是否参考使用互联网搜索结果。启用互联网搜索，模型会将搜索结果作为文本生成过程中的参考信息，但模型会基于其内部逻辑“自行判断”是否使用互联网搜索结果。
-      en_US: The model has a built-in Internet search service. This parameter controls whether the model refers to Internet search results when generating text. When Internet search is enabled, the model will use the search results as reference information in the text generation process, but the model will "judge" whether to use Internet search results based on its internal logic.
  - name: response_format
    use_template: response_format
 pricing:
@@ -69,15 +69,6 @@ parameter_rules:
    help:
      zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。
      en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment.
-  - name: enable_search
-    type: boolean
-    default: false
-    label:
-      zh_Hans: 联网搜索
-      en_US: Web Search
-    help:
-      zh_Hans: 模型内置了互联网搜索服务，该参数控制模型在生成文本时是否参考使用互联网搜索结果。启用互联网搜索，模型会将搜索结果作为文本生成过程中的参考信息，但模型会基于其内部逻辑“自行判断”是否使用互联网搜索结果。
-      en_US: The model has a built-in Internet search service. This parameter controls whether the model refers to Internet search results when generating text. When Internet search is enabled, the model will use the search results as reference information in the text generation process, but the model will "judge" whether to use Internet search results based on its internal logic.
  - name: response_format
    use_template: response_format
 pricing:
@@ -69,15 +69,6 @@ parameter_rules:
    help:
      zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。
      en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment.
-  - name: enable_search
-    type: boolean
-    default: false
-    label:
-      zh_Hans: 联网搜索
-      en_US: Web Search
-    help:
-      zh_Hans: 模型内置了互联网搜索服务，该参数控制模型在生成文本时是否参考使用互联网搜索结果。启用互联网搜索，模型会将搜索结果作为文本生成过程中的参考信息，但模型会基于其内部逻辑“自行判断”是否使用互联网搜索结果。
-      en_US: The model has a built-in Internet search service. This parameter controls whether the model refers to Internet search results when generating text. When Internet search is enabled, the model will use the search results as reference information in the text generation process, but the model will "judge" whether to use Internet search results based on its internal logic.
  - name: response_format
    use_template: response_format
 pricing:
@@ -68,15 +68,6 @@ parameter_rules:
    help:
      zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。
      en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment.
-  - name: enable_search
-    type: boolean
-    default: false
-    label:
-      zh_Hans: 联网搜索
-      en_US: Web Search
-    help:
-      zh_Hans: 模型内置了互联网搜索服务，该参数控制模型在生成文本时是否参考使用互联网搜索结果。启用互联网搜索，模型会将搜索结果作为文本生成过程中的参考信息，但模型会基于其内部逻辑“自行判断”是否使用互联网搜索结果。
-      en_US: The model has a built-in Internet search service. This parameter controls whether the model refers to Internet search results when generating text. When Internet search is enabled, the model will use the search results as reference information in the text generation process, but the model will "judge" whether to use Internet search results based on its internal logic.
  - name: response_format
    use_template: response_format
 pricing:
@@ -69,15 +69,6 @@ parameter_rules:
    help:
      zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。
      en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment.
-  - name: enable_search
-    type: boolean
-    default: false
-    label:
-      zh_Hans: 联网搜索
-      en_US: Web Search
-    help:
-      zh_Hans: 模型内置了互联网搜索服务，该参数控制模型在生成文本时是否参考使用互联网搜索结果。启用互联网搜索，模型会将搜索结果作为文本生成过程中的参考信息，但模型会基于其内部逻辑“自行判断”是否使用互联网搜索结果。
-      en_US: The model has a built-in Internet search service. This parameter controls whether the model refers to Internet search results when generating text. When Internet search is enabled, the model will use the search results as reference information in the text generation process, but the model will "judge" whether to use Internet search results based on its internal logic.
  - name: response_format
    use_template: response_format
 pricing:
@@ -69,15 +69,6 @@ parameter_rules:
    help:
      zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。
      en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment.
-  - name: enable_search
-    type: boolean
-    default: false
-    label:
-      zh_Hans: 联网搜索
-      en_US: Web Search
-    help:
-      zh_Hans: 模型内置了互联网搜索服务，该参数控制模型在生成文本时是否参考使用互联网搜索结果。启用互联网搜索，模型会将搜索结果作为文本生成过程中的参考信息，但模型会基于其内部逻辑“自行判断”是否使用互联网搜索结果。
-      en_US: The model has a built-in Internet search service. This parameter controls whether the model refers to Internet search results when generating text. When Internet search is enabled, the model will use the search results as reference information in the text generation process, but the model will "judge" whether to use Internet search results based on its internal logic.
  - name: response_format
    use_template: response_format
 pricing:
@@ -67,15 +67,6 @@ parameter_rules:
    help:
      zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。
      en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment.
-  - name: enable_search
-    type: boolean
-    default: false
-    label:
-      zh_Hans: 联网搜索
-      en_US: Web Search
-    help:
-      zh_Hans: 模型内置了互联网搜索服务，该参数控制模型在生成文本时是否参考使用互联网搜索结果。启用互联网搜索，模型会将搜索结果作为文本生成过程中的参考信息，但模型会基于其内部逻辑“自行判断”是否使用互联网搜索结果。
-      en_US: The model has a built-in Internet search service. This parameter controls whether the model refers to Internet search results when generating text. When Internet search is enabled, the model will use the search results as reference information in the text generation process, but the model will "judge" whether to use Internet search results based on its internal logic.
  - name: response_format
    use_template: response_format
 pricing:
@@ -67,15 +67,6 @@ parameter_rules:
    help:
      zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。
      en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment.
-  - name: enable_search
-    type: boolean
-    default: false
-    label:
-      zh_Hans: 联网搜索
-      en_US: Web Search
-    help:
-      zh_Hans: 模型内置了互联网搜索服务，该参数控制模型在生成文本时是否参考使用互联网搜索结果。启用互联网搜索，模型会将搜索结果作为文本生成过程中的参考信息，但模型会基于其内部逻辑“自行判断”是否使用互联网搜索结果。
-      en_US: The model has a built-in Internet search service. This parameter controls whether the model refers to Internet search results when generating text. When Internet search is enabled, the model will use the search results as reference information in the text generation process, but the model will "judge" whether to use Internet search results based on its internal logic.
  - name: response_format
    use_template: response_format
 pricing:
@@ -67,15 +67,6 @@ parameter_rules:
    help:
      zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。
      en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment.
-  - name: enable_search
-    type: boolean
-    default: false
-    label:
-      zh_Hans: 联网搜索
-      en_US: Web Search
-    help:
-      zh_Hans: 模型内置了互联网搜索服务，该参数控制模型在生成文本时是否参考使用互联网搜索结果。启用互联网搜索，模型会将搜索结果作为文本生成过程中的参考信息，但模型会基于其内部逻辑“自行判断”是否使用互联网搜索结果。
-      en_US: The model has a built-in Internet search service. This parameter controls whether the model refers to Internet search results when generating text. When Internet search is enabled, the model will use the search results as reference information in the text generation process, but the model will "judge" whether to use Internet search results based on its internal logic.
  - name: response_format
    use_template: response_format
 pricing:
@@ -67,15 +67,6 @@ parameter_rules:
    help:
      zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。
      en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment.
-  - name: enable_search
-    type: boolean
-    default: false
-    label:
-      zh_Hans: 联网搜索
-      en_US: Web Search
-    help:
-      zh_Hans: 模型内置了互联网搜索服务，该参数控制模型在生成文本时是否参考使用互联网搜索结果。启用互联网搜索，模型会将搜索结果作为文本生成过程中的参考信息，但模型会基于其内部逻辑“自行判断”是否使用互联网搜索结果。
-      en_US: The model has a built-in Internet search service. This parameter controls whether the model refers to Internet search results when generating text. When Internet search is enabled, the model will use the search results as reference information in the text generation process, but the model will "judge" whether to use Internet search results based on its internal logic.
  - name: response_format
    use_template: response_format
 pricing:
@@ -67,15 +67,6 @@ parameter_rules:
    help:
      zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。
      en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment.
-  - name: enable_search
-    type: boolean
-    default: false
-    label:
-      zh_Hans: 联网搜索
-      en_US: Web Search
-    help:
-      zh_Hans: 模型内置了互联网搜索服务，该参数控制模型在生成文本时是否参考使用互联网搜索结果。启用互联网搜索，模型会将搜索结果作为文本生成过程中的参考信息，但模型会基于其内部逻辑“自行判断”是否使用互联网搜索结果。
-      en_US: The model has a built-in Internet search service. This parameter controls whether the model refers to Internet search results when generating text. When Internet search is enabled, the model will use the search results as reference information in the text generation process, but the model will "judge" whether to use Internet search results based on its internal logic.
  - name: response_format
    use_template: response_format
 pricing:
@@ -69,15 +69,6 @@ parameter_rules:
    help:
      zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。
      en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment.
-  - name: enable_search
-    type: boolean
-    default: false
-    label:
-      zh_Hans: 联网搜索
-      en_US: Web Search
-    help:
-      zh_Hans: 模型内置了互联网搜索服务，该参数控制模型在生成文本时是否参考使用互联网搜索结果。启用互联网搜索，模型会将搜索结果作为文本生成过程中的参考信息，但模型会基于其内部逻辑“自行判断”是否使用互联网搜索结果。
-      en_US: The model has a built-in Internet search service. This parameter controls whether the model refers to Internet search results when generating text. When Internet search is enabled, the model will use the search results as reference information in the text generation process, but the model will "judge" whether to use Internet search results based on its internal logic.
  - name: response_format
    use_template: response_format
 pricing:
@@ -67,15 +67,6 @@ parameter_rules:
    help:
      zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。
      en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment.
-  - name: enable_search
-    type: boolean
-    default: false
-    label:
-      zh_Hans: 联网搜索
-      en_US: Web Search
-    help:
-      zh_Hans: 模型内置了互联网搜索服务，该参数控制模型在生成文本时是否参考使用互联网搜索结果。启用互联网搜索，模型会将搜索结果作为文本生成过程中的参考信息，但模型会基于其内部逻辑“自行判断”是否使用互联网搜索结果。
-      en_US: The model has a built-in Internet search service. This parameter controls whether the model refers to Internet search results when generating text. When Internet search is enabled, the model will use the search results as reference information in the text generation process, but the model will "judge" whether to use Internet search results based on its internal logic.
  - name: response_format
    use_template: response_format
 pricing:
@@ -68,15 +68,6 @@ parameter_rules:
    help:
      zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。
      en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment.
-  - name: enable_search
-    type: boolean
-    default: false
-    label:
-      zh_Hans: 联网搜索
-      en_US: Web Search
-    help:
-      zh_Hans: 模型内置了互联网搜索服务，该参数控制模型在生成文本时是否参考使用互联网搜索结果。启用互联网搜索，模型会将搜索结果作为文本生成过程中的参考信息，但模型会基于其内部逻辑“自行判断”是否使用互联网搜索结果。
-      en_US: The model has a built-in Internet search service. This parameter controls whether the model refers to Internet search results when generating text. When Internet search is enabled, the model will use the search results as reference information in the text generation process, but the model will "judge" whether to use Internet search results based on its internal logic.
  - name: response_format
    use_template: response_format
 pricing:
@@ -67,15 +67,6 @@ parameter_rules:
    help:
      zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。
      en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment.
-  - name: enable_search
-    type: boolean
-    default: false
-    label:
-      zh_Hans: 联网搜索
-      en_US: Web Search
-    help:
-      zh_Hans: 模型内置了互联网搜索服务，该参数控制模型在生成文本时是否参考使用互联网搜索结果。启用互联网搜索，模型会将搜索结果作为文本生成过程中的参考信息，但模型会基于其内部逻辑“自行判断”是否使用互联网搜索结果。
-      en_US: The model has a built-in Internet search service. This parameter controls whether the model refers to Internet search results when generating text. When Internet search is enabled, the model will use the search results as reference information in the text generation process, but the model will "judge" whether to use Internet search results based on its internal logic.
  - name: response_format
    use_template: response_format
 pricing:
@@ -67,15 +67,6 @@ parameter_rules:
    help:
      zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。
      en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment.
-  - name: enable_search
-    type: boolean
-    default: false
-    label:
-      zh_Hans: 联网搜索
-      en_US: Web Search
-    help:
-      zh_Hans: 模型内置了互联网搜索服务，该参数控制模型在生成文本时是否参考使用互联网搜索结果。启用互联网搜索，模型会将搜索结果作为文本生成过程中的参考信息，但模型会基于其内部逻辑“自行判断”是否使用互联网搜索结果。
-      en_US: The model has a built-in Internet search service. This parameter controls whether the model refers to Internet search results when generating text. When Internet search is enabled, the model will use the search results as reference information in the text generation process, but the model will "judge" whether to use Internet search results based on its internal logic.
  - name: response_format
    use_template: response_format
 pricing:
@@ -69,15 +69,6 @@ parameter_rules:
    help:
      zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。
      en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment.
-  - name: enable_search
-    type: boolean
-    default: false
-    label:
-      zh_Hans: 联网搜索
-      en_US: Web Search
-    help:
-      zh_Hans: 模型内置了互联网搜索服务，该参数控制模型在生成文本时是否参考使用互联网搜索结果。启用互联网搜索，模型会将搜索结果作为文本生成过程中的参考信息，但模型会基于其内部逻辑“自行判断”是否使用互联网搜索结果。
-      en_US: The model has a built-in Internet search service. This parameter controls whether the model refers to Internet search results when generating text. When Internet search is enabled, the model will use the search results as reference information in the text generation process, but the model will "judge" whether to use Internet search results based on its internal logic.
  - name: response_format
    use_template: response_format
 pricing:
@@ -67,15 +67,6 @@ parameter_rules:
    help:
      zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。
      en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment.
-  - name: enable_search
-    type: boolean
-    default: false
-    label:
-      zh_Hans: 联网搜索
-      en_US: Web Search
-    help:
-      zh_Hans: 模型内置了互联网搜索服务，该参数控制模型在生成文本时是否参考使用互联网搜索结果。启用互联网搜索，模型会将搜索结果作为文本生成过程中的参考信息，但模型会基于其内部逻辑“自行判断”是否使用互联网搜索结果。
-      en_US: The model has a built-in Internet search service. This parameter controls whether the model refers to Internet search results when generating text. When Internet search is enabled, the model will use the search results as reference information in the text generation process, but the model will "judge" whether to use Internet search results based on its internal logic.
  - name: response_format
    use_template: response_format
 pricing:
@@ -1,22 +0,0 @@
- claude-3-haiku@20240307
- claude-3-opus@20240229
- claude-3-sonnet@20240229
- claude-3-5-sonnet-v2@20241022
- claude-3-5-sonnet@20240620
- gemini-1.0-pro-vision-001
- gemini-1.0-pro-002
- gemini-1.5-flash-001
- gemini-1.5-flash-002
- gemini-1.5-pro-001
- gemini-1.5-pro-002
- gemini-2.0-flash-001
- gemini-2.0-flash-exp
- gemini-2.0-flash-lite-preview-02-05
- gemini-2.0-flash-thinking-exp-01-21
- gemini-2.0-flash-thinking-exp-1219
- gemini-2.0-pro-exp-02-05
- gemini-exp-1114
- gemini-exp-1121
- gemini-exp-1206
- gemini-flash-experimental
- gemini-pro-experimental
@@ -1,4 +1,5 @@
 import logging
+import re
 from collections.abc import Generator
 from typing import Optional

@@ -230,17 +231,6 @@ class VolcengineMaaSLargeLanguageModel(LargeLanguageModel):
            return _handle_chat_response()
        return _handle_stream_chat_response()

-    def wrap_thinking(self, delta: dict, is_reasoning: bool) -> tuple[str, bool]:
-        content = ""
-        reasoning_content = None
-        if hasattr(delta, "content"):
-            content = delta.content
-        if hasattr(delta, "reasoning_content"):
-            reasoning_content = delta.reasoning_content
-        return self._wrap_thinking_by_reasoning_content(
-            {"content": content, "reasoning_content": reasoning_content}, is_reasoning
-        )
-
    def _generate_v3(
        self,
        model: str,
@@ -263,7 +253,22 @@ class VolcengineMaaSLargeLanguageModel(LargeLanguageModel):
                content = ""
                if chunk.choices:
                    delta = chunk.choices[0].delta
-                    content, is_reasoning_started = self.wrap_thinking(delta, is_reasoning_started)
+                    if is_reasoning_started and not hasattr(delta, "reasoning_content") and not delta.content:
+                        content = ""
+                    elif hasattr(delta, "reasoning_content"):
+                        if not is_reasoning_started:
+                            is_reasoning_started = True
+                            content = "> 💭 " + delta.reasoning_content
+                        else:
+                            content = delta.reasoning_content
+
+                        if "\n" in content:
+                            content = re.sub(r"\n(?!(>|\n))", "\n> ", content)
+                    elif is_reasoning_started:
+                        content = "\n\n" + delta.content
+                        is_reasoning_started = False
+                    else:
+                        content = delta.content

                yield LLMResultChunk(
                    model=model,
@@ -328,71 +333,54 @@ class VolcengineMaaSLargeLanguageModel(LargeLanguageModel):
        """
        model_config = get_model_config(credentials)

-        if model.startswith("DeepSeek-R1"):
-            rules = [
-                ParameterRule(
-                    name="max_tokens",
-                    type=ParameterType.INT,
-                    use_template="max_tokens",
-                    min=1,
-                    max=model_config.properties.max_tokens,
-                    default=512,
-                    label=I18nObject(zh_Hans="最大生成长度", en_US="Max Tokens"),
+        rules = [
+            ParameterRule(
+                name="temperature",
+                type=ParameterType.FLOAT,
+                use_template="temperature",
+                label=I18nObject(zh_Hans="温度", en_US="Temperature"),
+            ),
+            ParameterRule(
+                name="top_p",
+                type=ParameterType.FLOAT,
+                use_template="top_p",
+                label=I18nObject(zh_Hans="Top P", en_US="Top P"),
+            ),
+            ParameterRule(
+                name="top_k", type=ParameterType.INT, min=1, default=1, label=I18nObject(zh_Hans="Top K", en_US="Top K")
+            ),
+            ParameterRule(
+                name="presence_penalty",
+                type=ParameterType.FLOAT,
+                use_template="presence_penalty",
+                label=I18nObject(
+                    en_US="Presence Penalty",
+                    zh_Hans="存在惩罚",
                ),
-            ]
-        else:
-            rules = [
-                ParameterRule(
-                    name="temperature",
-                    type=ParameterType.FLOAT,
-                    use_template="temperature",
-                    label=I18nObject(zh_Hans="温度", en_US="Temperature"),
+                min=-2.0,
+                max=2.0,
+            ),
+            ParameterRule(
+                name="frequency_penalty",
+                type=ParameterType.FLOAT,
+                use_template="frequency_penalty",
+                label=I18nObject(
+                    en_US="Frequency Penalty",
+                    zh_Hans="频率惩罚",
                ),
-                ParameterRule(
-                    name="top_p",
-                    type=ParameterType.FLOAT,
-                    use_template="top_p",
-                    label=I18nObject(zh_Hans="Top P", en_US="Top P"),
-                ),
-                ParameterRule(
-                    name="top_k",
-                    type=ParameterType.INT,
-                    min=1,
-                    default=1,
-                    label=I18nObject(zh_Hans="Top K", en_US="Top K"),
-                ),
-                ParameterRule(
-                    name="presence_penalty",
-                    type=ParameterType.FLOAT,
-                    use_template="presence_penalty",
-                    label=I18nObject(
-                        en_US="Presence Penalty",
-                        zh_Hans="存在惩罚",
-                    ),
-                    min=-2.0,
-                    max=2.0,
-                ),
-                ParameterRule(
-                    name="frequency_penalty",
-                    type=ParameterType.FLOAT,
-                    use_template="frequency_penalty",
-                    label=I18nObject(
-                        en_US="Frequency Penalty",
-                        zh_Hans="频率惩罚",
-                    ),
-                    min=-2.0,
-                    max=2.0,
-                ),
-                ParameterRule(
-                    name="max_tokens",
-                    type=ParameterType.INT,
-                    use_template="max_tokens",
-                    min=1,
-                    max=model_config.properties.max_tokens,
-                    default=512,
-                    label=I18nObject(zh_Hans="最大生成长度", en_US="Max Tokens"),
-                ),
-            ]
+                min=-2.0,
+                max=2.0,
+            ),
+            ParameterRule(
+                name="max_tokens",
+                type=ParameterType.INT,
+                use_template="max_tokens",
+                min=1,
+                max=model_config.properties.max_tokens,
+                default=512,
+                label=I18nObject(zh_Hans="最大生成长度", en_US="Max Tokens"),
+            ),
+        ]

        model_properties = {}
        model_properties[ModelPropertyKey.CONTEXT_SIZE] = model_config.properties.context_size
@@ -654,6 +654,7 @@ class XinferenceAILargeLanguageModel(LargeLanguageModel):
            if function_call:
                assistant_message_tool_calls += [self._extract_response_function_call(function_call)]

+            delta_content = self._wrap_thinking_by_tag(delta_content)
            # transform assistant message to prompt message
            assistant_prompt_message = AssistantPromptMessage(
                content=delta_content or "", tool_calls=assistant_message_tool_calls
@@ -452,9 +452,11 @@ class ProviderManager:

        provider_name_to_provider_load_balancing_model_configs_dict = defaultdict(list)
        for provider_load_balancing_config in provider_load_balancing_configs:
-            provider_name_to_provider_load_balancing_model_configs_dict[
-                provider_load_balancing_config.provider_name
-            ].append(provider_load_balancing_config)
+            (
+                provider_name_to_provider_load_balancing_model_configs_dict[
+                    provider_load_balancing_config.provider_name
+                ].append(provider_load_balancing_config)
+            )

        return provider_name_to_provider_load_balancing_model_configs_dict

@@ -1,4 +1,3 @@
-import json
 import threading
 from typing import Optional

@@ -172,7 +171,7 @@ class RetrievalService:
                vector = Vector(dataset=dataset)

                documents = vector.search_by_vector(
-                    query,
+                    cls.escape_query_for_search(query),
                    search_type="similarity_score_threshold",
                    top_k=top_k,
                    score_threshold=score_threshold,
@@ -251,7 +250,7 @@ class RetrievalService:

    @staticmethod
    def escape_query_for_search(query: str) -> str:
-        return json.dumps(query).strip('"')
+        return query.replace('"', '\\"')

    @staticmethod
    def format_retrieval_documents(documents: list[Document]) -> list[RetrievalSegments]:
@@ -9,7 +9,6 @@ from sqlalchemy import text as sql_text
 from sqlalchemy.orm import Session, declarative_base

 from configs import dify_config
-from core.rag.datasource.vdb.field import Field
 from core.rag.datasource.vdb.vector_base import BaseVector
 from core.rag.datasource.vdb.vector_factory import AbstractVectorFactory
 from core.rag.datasource.vdb.vector_type import VectorType
@@ -55,13 +54,14 @@ class TiDBVector(BaseVector):
        return Table(
            self._collection_name,
            self._orm_base.metadata,
-            Column(Field.PRIMARY_KEY.value, String(36), primary_key=True, nullable=False),
+            Column("id", String(36), primary_key=True, nullable=False),
            Column(
-                Field.VECTOR.value,
+                "vector",
                VectorType(dim),
                nullable=False,
+                comment="" if self._distance_func is None else f"hnsw(distance={self._distance_func})",
            ),
-            Column(Field.TEXT_KEY.value, TEXT, nullable=False),
+            Column("text", TEXT, nullable=False),
            Column("meta", JSON, nullable=False),
            Column("create_time", DateTime, server_default=sqlalchemy.text("CURRENT_TIMESTAMP")),
            Column(
@@ -96,7 +96,6 @@ class TiDBVector(BaseVector):
            collection_exist_cache_key = "vector_indexing_{}".format(self._collection_name)
            if redis_client.get(collection_exist_cache_key):
                return
-            tidb_dist_func = self._get_distance_func()
            with Session(self._engine) as session:
                session.begin()
                create_statement = sql_text(f"""
@@ -105,14 +104,14 @@ class TiDBVector(BaseVector):
                        text TEXT NOT NULL,
                        meta JSON NOT NULL,
                        doc_id VARCHAR(64) AS (JSON_UNQUOTE(JSON_EXTRACT(meta, '$.doc_id'))) STORED,
-                        vector VECTOR<FLOAT>({dimension}) NOT NULL,
-                        create_time DATETIME DEFAULT CURRENT_TIMESTAMP,
-                        update_time DATETIME DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP,
                        KEY (doc_id),
-                        VECTOR INDEX idx_vector (({tidb_dist_func}(vector))) USING HNSW
+                        vector VECTOR<FLOAT>({dimension}) NOT NULL COMMENT "hnsw(distance={self._distance_func})",
+                        create_time DATETIME DEFAULT CURRENT_TIMESTAMP,
+                        update_time DATETIME DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP
                    );
                """)
                session.execute(create_statement)
+                # tidb vector not support 'CREATE/ADD INDEX' now
                session.commit()
            redis_client.set(collection_exist_cache_key, 1, ex=3600)

@@ -195,30 +194,23 @@ class TiDBVector(BaseVector):
        )

        docs = []
-        tidb_dist_func = self._get_distance_func()
+        if self._distance_func == "l2":
+            tidb_func = "Vec_l2_distance"
+        elif self._distance_func == "cosine":
+            tidb_func = "Vec_Cosine_distance"
+        else:
+            tidb_func = "Vec_Cosine_distance"

        with Session(self._engine) as session:
-            select_statement = sql_text(f"""
-                SELECT meta, text, distance 
-                FROM (
-                  SELECT 
-                    meta,
-                    text,
-                    {tidb_dist_func}(vector, :query_vector_str) AS distance
-                  FROM {self._collection_name}
-                  ORDER BY distance ASC
-                  LIMIT :top_k
-                ) t
-                WHERE distance <= :distance
-                """)
-            res = session.execute(
-                select_statement,
-                params={
-                    "query_vector_str": query_vector_str,
-                    "distance": distance,
-                    "top_k": top_k,
-                },
+            select_statement = sql_text(
+                f"""SELECT meta, text, distance FROM (
+                        SELECT meta, text, {tidb_func}(vector, "{query_vector_str}")  as distance
+                        FROM {self._collection_name}
+                        ORDER BY distance
+                        LIMIT {top_k}
+                    ) t WHERE distance < {distance};"""
            )
+            res = session.execute(select_statement)
            results = [(row[0], row[1], row[2]) for row in res]
            for meta, text, distance in results:
                metadata = json.loads(meta)
@@ -235,16 +227,6 @@ class TiDBVector(BaseVector):
            session.execute(sql_text(f"""DROP TABLE IF EXISTS {self._collection_name};"""))
            session.commit()

-    def _get_distance_func(self) -> str:
-        match self._distance_func:
-            case "l2":
-                tidb_dist_func = "VEC_L2_DISTANCE"
-            case "cosine":
-                tidb_dist_func = "VEC_COSINE_DISTANCE"
-            case _:
-                tidb_dist_func = "VEC_COSINE_DISTANCE"
-        return tidb_dist_func
-

 class TiDBVectorFactory(AbstractVectorFactory):
    def init_vector(self, dataset: Dataset, attributes: list, embeddings: Embeddings) -> TiDBVector:
@@ -77,5 +77,4 @@
 - onebot
 - regex
 - trello
- vanna
 - fal
@@ -1,134 +0,0 @@
-from typing import Any, Union
-
-from vanna.remote import VannaDefault  # type: ignore
-
-from core.tools.entities.tool_entities import ToolInvokeMessage
-from core.tools.errors import ToolProviderCredentialValidationError
-from core.tools.tool.builtin_tool import BuiltinTool
-
-
-class VannaTool(BuiltinTool):
-    def _invoke(
-        self, user_id: str, tool_parameters: dict[str, Any]
-    ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]:
-        """
-        invoke tools
-        """
-        # Ensure runtime and credentials
-        if not self.runtime or not self.runtime.credentials:
-            raise ToolProviderCredentialValidationError("Tool runtime or credentials are missing")
-        api_key = self.runtime.credentials.get("api_key", None)
-        if not api_key:
-            raise ToolProviderCredentialValidationError("Please input api key")
-
-        model = tool_parameters.get("model", "")
-        if not model:
-            return self.create_text_message("Please input RAG model")
-
-        prompt = tool_parameters.get("prompt", "")
-        if not prompt:
-            return self.create_text_message("Please input prompt")
-
-        url = tool_parameters.get("url", "")
-        if not url:
-            return self.create_text_message("Please input URL/Host/DSN")
-
-        db_name = tool_parameters.get("db_name", "")
-        username = tool_parameters.get("username", "")
-        password = tool_parameters.get("password", "")
-        port = tool_parameters.get("port", 0)
-
-        base_url = self.runtime.credentials.get("base_url", None)
-        vn = VannaDefault(model=model, api_key=api_key, config={"endpoint": base_url})
-
-        db_type = tool_parameters.get("db_type", "")
-        if db_type in {"Postgres", "MySQL", "Hive", "ClickHouse"}:
-            if not db_name:
-                return self.create_text_message("Please input database name")
-            if not username:
-                return self.create_text_message("Please input username")
-            if port < 1:
-                return self.create_text_message("Please input port")
-
-        schema_sql = "SELECT * FROM INFORMATION_SCHEMA.COLUMNS"
-        match db_type:
-            case "SQLite":
-                schema_sql = "SELECT type, sql FROM sqlite_master WHERE sql is not null"
-                vn.connect_to_sqlite(url)
-            case "Postgres":
-                vn.connect_to_postgres(host=url, dbname=db_name, user=username, password=password, port=port)
-            case "DuckDB":
-                vn.connect_to_duckdb(url=url)
-            case "SQLServer":
-                vn.connect_to_mssql(url)
-            case "MySQL":
-                vn.connect_to_mysql(host=url, dbname=db_name, user=username, password=password, port=port)
-            case "Oracle":
-                vn.connect_to_oracle(user=username, password=password, dsn=url)
-            case "Hive":
-                vn.connect_to_hive(host=url, dbname=db_name, user=username, password=password, port=port)
-            case "ClickHouse":
-                vn.connect_to_clickhouse(host=url, dbname=db_name, user=username, password=password, port=port)
-
-        enable_training = tool_parameters.get("enable_training", False)
-        reset_training_data = tool_parameters.get("reset_training_data", False)
-        if enable_training:
-            if reset_training_data:
-                existing_training_data = vn.get_training_data()
-                if len(existing_training_data) > 0:
-                    for _, training_data in existing_training_data.iterrows():
-                        vn.remove_training_data(training_data["id"])
-
-            ddl = tool_parameters.get("ddl", "")
-            question = tool_parameters.get("question", "")
-            sql = tool_parameters.get("sql", "")
-            memos = tool_parameters.get("memos", "")
-            training_metadata = tool_parameters.get("training_metadata", False)
-
-            if training_metadata:
-                if db_type == "SQLite":
-                    df_ddl = vn.run_sql(schema_sql)
-                    for ddl in df_ddl["sql"].to_list():
-                        vn.train(ddl=ddl)
-                else:
-                    df_information_schema = vn.run_sql(schema_sql)
-                    plan = vn.get_training_plan_generic(df_information_schema)
-                    vn.train(plan=plan)
-
-            if ddl:
-                vn.train(ddl=ddl)
-
-            if sql:
-                if question:
-                    vn.train(question=question, sql=sql)
-                else:
-                    vn.train(sql=sql)
-            if memos:
-                vn.train(documentation=memos)
-
-        #########################################################################################
-        # Due to CVE-2024-5565, we have to disable the chart generation feature
-        # The Vanna library uses a prompt function to present the user with visualized results,
-        # it is possible to alter the prompt using prompt injection and run arbitrary Python code
-        # instead of the intended visualization code.
-        # Specifically - allowing external input to the library’s “ask” method
-        # with "visualize" set to True (default behavior) leads to remote code execution.
-        # Affected versions: <= 0.5.5
-        #########################################################################################
-        allow_llm_to_see_data = tool_parameters.get("allow_llm_to_see_data", False)
-        res = vn.ask(
-            prompt, print_results=False, auto_train=True, visualize=False, allow_llm_to_see_data=allow_llm_to_see_data
-        )
-
-        result = []
-
-        if res is not None:
-            result.append(self.create_text_message(res[0]))
-            if len(res) > 1 and res[1] is not None:
-                result.append(self.create_text_message(res[1].to_markdown()))
-            if len(res) > 2 and res[2] is not None:
-                result.append(
-                    self.create_blob_message(blob=res[2].to_image(format="svg"), meta={"mime_type": "image/svg+xml"})
-                )
-
-        return result
@@ -1,213 +0,0 @@
-identity:
-  name: vanna
-  author: QCTC
-  label:
-    en_US: Vanna.AI
-    zh_Hans: Vanna.AI
-description:
-  human:
-    en_US: The fastest way to get actionable insights from your database just by asking questions.
-    zh_Hans: 一个基于大模型和RAG的Text2SQL工具。
-  llm: A tool for converting text to SQL.
-parameters:
-  - name: prompt
-    type: string
-    required: true
-    label:
-      en_US: Prompt
-      zh_Hans: 提示词
-      pt_BR: Prompt
-    human_description:
-      en_US: used for generating SQL
-      zh_Hans: 用于生成SQL
-    llm_description: key words for generating SQL
-    form: llm
-  - name: model
-    type: string
-    required: true
-    label:
-      en_US: RAG Model
-      zh_Hans: RAG模型
-    human_description:
-      en_US: RAG Model for your database DDL
-      zh_Hans: 存储数据库训练数据的RAG模型
-    llm_description: RAG Model for generating SQL
-    form: llm
-  - name: db_type
-    type: select
-    required: true
-    options:
-      - value: SQLite
-        label:
-          en_US: SQLite
-          zh_Hans: SQLite
-      - value: Postgres
-        label:
-          en_US: Postgres
-          zh_Hans: Postgres
-      - value: DuckDB
-        label:
-          en_US: DuckDB
-          zh_Hans: DuckDB
-      - value: SQLServer
-        label:
-          en_US: Microsoft SQL Server
-          zh_Hans: 微软 SQL Server
-      - value: MySQL
-        label:
-          en_US: MySQL
-          zh_Hans: MySQL
-      - value: Oracle
-        label:
-          en_US: Oracle
-          zh_Hans: Oracle
-      - value: Hive
-        label:
-          en_US: Hive
-          zh_Hans: Hive
-      - value: ClickHouse
-        label:
-          en_US: ClickHouse
-          zh_Hans: ClickHouse
-    default: SQLite
-    label:
-      en_US: DB Type
-      zh_Hans: 数据库类型
-    human_description:
-      en_US: Database type.
-      zh_Hans: 选择要链接的数据库类型。
-    form: form
-  - name: url
-    type: string
-    required: true
-    label:
-      en_US: URL/Host/DSN
-      zh_Hans: URL/Host/DSN
-    human_description:
-      en_US: Please input depending on DB type, visit https://vanna.ai/docs/ for more specification
-      zh_Hans: 请根据数据库类型，填入对应值，详情参考https://vanna.ai/docs/
-    form: form
-  - name: db_name
-    type: string
-    required: false
-    label:
-      en_US: DB name
-      zh_Hans: 数据库名
-    human_description:
-      en_US: Database name
-      zh_Hans: 数据库名
-    form: form
-  - name: username
-    type: string
-    required: false
-    label:
-      en_US: Username
-      zh_Hans: 用户名
-    human_description:
-      en_US: Username
-      zh_Hans: 用户名
-    form: form
-  - name: password
-    type: secret-input
-    required: false
-    label:
-      en_US: Password
-      zh_Hans: 密码
-    human_description:
-      en_US: Password
-      zh_Hans: 密码
-    form: form
-  - name: port
-    type: number
-    required: false
-    label:
-      en_US: Port
-      zh_Hans: 端口
-    human_description:
-      en_US: Port
-      zh_Hans: 端口
-    form: form
-  - name: ddl
-    type: string
-    required: false
-    label:
-      en_US: Training DDL
-      zh_Hans: 训练DDL
-    human_description:
-      en_US: DDL statements for training data
-      zh_Hans: 用于训练RAG Model的建表语句
-    form: llm
-  - name: question
-    type: string
-    required: false
-    label:
-      en_US: Training Question
-      zh_Hans: 训练问题
-    human_description:
-      en_US: Question-SQL Pairs
-      zh_Hans: Question-SQL中的问题
-    form: llm
-  - name: sql
-    type: string
-    required: false
-    label:
-      en_US: Training SQL
-      zh_Hans: 训练SQL
-    human_description:
-      en_US: SQL queries to your training data
-      zh_Hans: 用于训练RAG Model的SQL语句
-    form: llm
-  - name: memos
-    type: string
-    required: false
-    label:
-      en_US: Training Memos
-      zh_Hans: 训练说明
-    human_description:
-      en_US: Sometimes you may want to add documentation about your business terminology or definitions
-      zh_Hans: 添加更多关于数据库的业务说明
-    form: llm
-  - name: enable_training
-    type: boolean
-    required: false
-    default: false
-    label:
-      en_US: Training Data
-      zh_Hans: 训练数据
-    human_description:
-      en_US: You only need to train once. Do not train again unless you want to add more training data
-      zh_Hans: 训练数据无更新时，训练一次即可
-    form: form
-  - name: reset_training_data
-    type: boolean
-    required: false
-    default: false
-    label:
-      en_US: Reset Training Data
-      zh_Hans: 重置训练数据
-    human_description:
-      en_US: Remove all training data in the current RAG Model
-      zh_Hans: 删除当前RAG Model中的所有训练数据
-    form: form
-  - name: training_metadata
-    type: boolean
-    required: false
-    default: false
-    label:
-      en_US: Training Metadata
-      zh_Hans: 训练元数据
-    human_description:
-      en_US: If enabled, it will attempt to train on the metadata of that database
-      zh_Hans: 是否自动从数据库获取元数据来训练
-    form: form
-  - name: allow_llm_to_see_data
-    type: boolean
-    required: false
-    default: false
-    label:
-      en_US: Whether to allow the LLM to see the data
-      zh_Hans: 是否允许LLM查看数据
-    human_description:
-      en_US: Whether to allow the LLM to see the data
-      zh_Hans: 是否允许LLM查看数据
-    form: form
@@ -1,46 +0,0 @@
-import re
-from typing import Any
-from urllib.parse import urlparse
-
-from core.tools.errors import ToolProviderCredentialValidationError
-from core.tools.provider.builtin.vanna.tools.vanna import VannaTool
-from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController
-
-
-class VannaProvider(BuiltinToolProviderController):
-    def _get_protocol_and_main_domain(self, url):
-        parsed_url = urlparse(url)
-        protocol = parsed_url.scheme
-        hostname = parsed_url.hostname
-        port = f":{parsed_url.port}" if parsed_url.port else ""
-
-        # Check if the hostname is an IP address
-        is_ip = re.match(r"^\d{1,3}(\.\d{1,3}){3}$", hostname) is not None
-
-        # Return the full hostname (with port if present) for IP addresses, otherwise return the main domain
-        main_domain = f"{hostname}{port}" if is_ip else ".".join(hostname.split(".")[-2:]) + port
-        return f"{protocol}://{main_domain}"
-
-    def _validate_credentials(self, credentials: dict[str, Any]) -> None:
-        base_url = credentials.get("base_url")
-        if not base_url:
-            base_url = "https://ask.vanna.ai/rpc"
-        else:
-            base_url = base_url.removesuffix("/")
-        credentials["base_url"] = base_url
-        try:
-            VannaTool().fork_tool_runtime(
-                runtime={
-                    "credentials": credentials,
-                }
-            ).invoke(
-                user_id="",
-                tool_parameters={
-                    "model": "chinook",
-                    "db_type": "SQLite",
-                    "url": f"{self._get_protocol_and_main_domain(credentials['base_url'])}/Chinook.sqlite",
-                    "query": "What are the top 10 customers by sales?",
-                },
-            )
-        except Exception as e:
-            raise ToolProviderCredentialValidationError(str(e))
@@ -1,35 +0,0 @@
-identity:
-  author: QCTC
-  name: vanna
-  label:
-    en_US: Vanna.AI
-    zh_Hans: Vanna.AI
-  description:
-    en_US: The fastest way to get actionable insights from your database just by asking questions.
-    zh_Hans: 一个基于大模型和RAG的Text2SQL工具。
-  icon: icon.png
-  tags:
-    - utilities
-    - productivity
-credentials_for_provider:
-  api_key:
-    type: secret-input
-    required: true
-    label:
-      en_US: API key
-      zh_Hans: API key
-    placeholder:
-      en_US: Please input your API key
-      zh_Hans: 请输入你的 API key
-      pt_BR: Please input your API key
-    help:
-      en_US: Get your API key from Vanna.AI
-      zh_Hans: 从 Vanna.AI 获取你的 API key
-    url: https://vanna.ai/account/profile
-  base_url:
-    type: text-input
-    required: false
-    label:
-      en_US: Vanna.AI Endpoint Base URL
-    placeholder:
-      en_US: https://ask.vanna.ai/rpc
@@ -195,14 +195,14 @@ class WorkflowTool(Tool):
            if isinstance(value, list):
                for item in value:
                    if isinstance(item, dict) and item.get("dify_model_identity") == FILE_MODEL_IDENTITY:
-                        item = self._update_file_mapping(item)
+                        item["tool_file_id"] = item.get("related_id")
                        file = build_from_mapping(
                            mapping=item,
                            tenant_id=str(cast(Tool.Runtime, self.runtime).tenant_id),
                        )
                        files.append(file)
            elif isinstance(value, dict) and value.get("dify_model_identity") == FILE_MODEL_IDENTITY:
-                value = self._update_file_mapping(value)
+                value["tool_file_id"] = value.get("related_id")
                file = build_from_mapping(
                    mapping=value,
                    tenant_id=str(cast(Tool.Runtime, self.runtime).tenant_id),
@@ -211,11 +211,3 @@ class WorkflowTool(Tool):

            result[key] = value
        return result, files
-
-    def _update_file_mapping(self, file_dict: dict) -> dict:
-        transfer_method = FileTransferMethod.value_of(file_dict.get("transfer_method"))
-        if transfer_method == FileTransferMethod.TOOL_FILE:
-            file_dict["tool_file_id"] = file_dict.get("related_id")
-        elif transfer_method == FileTransferMethod.LOCAL_FILE:
-            file_dict["upload_file_id"] = file_dict.get("related_id")
-        return file_dict
@@ -648,7 +648,7 @@ class GraphEngine:
                                    retries += 1
                                    route_node_state.node_run_result = run_result
                                    yield NodeRunRetryEvent(
-                                        id=str(uuid.uuid4()),
+                                        id=node_instance.id,
                                        node_id=node_instance.node_id,
                                        node_type=node_instance.node_type,
                                        node_data=node_instance.node_data,
@@ -663,7 +663,7 @@ class GraphEngine:
                                        start_at=retry_start_at,
                                    )
                                    time.sleep(retry_interval)
-                                    break
+                                    continue
                            route_node_state.set_finished(run_result=run_result)

                            if run_result.status == WorkflowNodeExecutionStatus.FAILED:
@@ -107,10 +107,8 @@ def _extract_text_by_mime_type(*, file_content: bytes, mime_type: str) -> str:
            return _extract_text_from_plain_text(file_content)
        case "application/pdf":
            return _extract_text_from_pdf(file_content)
-        case "application/msword":
+        case "application/vnd.openxmlformats-officedocument.wordprocessingml.document" | "application/msword":
            return _extract_text_from_doc(file_content)
-        case "application/vnd.openxmlformats-officedocument.wordprocessingml.document":
-            return _extract_text_from_docx(file_content)
        case "text/csv":
            return _extract_text_from_csv(file_content)
        case "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet" | "application/vnd.ms-excel":
@@ -144,10 +142,8 @@ def _extract_text_by_file_extension(*, file_content: bytes, file_extension: str)
            return _extract_text_from_yaml(file_content)
        case ".pdf":
            return _extract_text_from_pdf(file_content)
-        case ".doc":
+        case ".doc" | ".docx":
            return _extract_text_from_doc(file_content)
-        case ".docx":
-            return _extract_text_from_docx(file_content)
        case ".csv":
            return _extract_text_from_csv(file_content)
        case ".xls" | ".xlsx":
@@ -207,33 +203,7 @@ def _extract_text_from_pdf(file_content: bytes) -> str:

 def _extract_text_from_doc(file_content: bytes) -> str:
    """
-    Extract text from a DOC file.
-    """
-    from unstructured.partition.api import partition_via_api
-
-    if not (dify_config.UNSTRUCTURED_API_URL and dify_config.UNSTRUCTURED_API_KEY):
-        raise TextExtractionError("UNSTRUCTURED_API_URL and UNSTRUCTURED_API_KEY must be set")
-
-    try:
-        with tempfile.NamedTemporaryFile(suffix=".doc", delete=False) as temp_file:
-            temp_file.write(file_content)
-            temp_file.flush()
-            with open(temp_file.name, "rb") as file:
-                elements = partition_via_api(
-                    file=file,
-                    metadata_filename=temp_file.name,
-                    api_url=dify_config.UNSTRUCTURED_API_URL,
-                    api_key=dify_config.UNSTRUCTURED_API_KEY,
-                )
-            os.unlink(temp_file.name)
-        return "\n".join([getattr(element, "text", "") for element in elements])
-    except Exception as e:
-        raise TextExtractionError(f"Failed to extract text from DOC: {str(e)}") from e
-
-
-def _extract_text_from_docx(file_content: bytes) -> str:
-    """
-    Extract text from a DOCX file.
+    Extract text from a DOC/DOCX file.
    For now support only paragraph and table add more if needed
    """
    try:
@@ -285,13 +255,13 @@ def _extract_text_from_docx(file_content: bytes) -> str:

                        text.append(markdown_table)
                except Exception as e:
-                    logger.warning(f"Failed to extract table from DOC: {e}")
+                    logger.warning(f"Failed to extract table from DOC/DOCX: {e}")
                    continue

        return "\n".join(text)

    except Exception as e:
-        raise TextExtractionError(f"Failed to extract text from DOCX: {str(e)}") from e
+        raise TextExtractionError(f"Failed to extract text from DOC/DOCX: {str(e)}") from e


 def _download_file_content(file: File) -> bytes:
@@ -359,29 +329,14 @@ def _extract_text_from_excel(file_content: bytes) -> str:


 def _extract_text_from_ppt(file_content: bytes) -> str:
-    from unstructured.partition.api import partition_via_api
    from unstructured.partition.ppt import partition_ppt

    try:
-        if dify_config.UNSTRUCTURED_API_URL and dify_config.UNSTRUCTURED_API_KEY:
-            with tempfile.NamedTemporaryFile(suffix=".ppt", delete=False) as temp_file:
-                temp_file.write(file_content)
-                temp_file.flush()
-                with open(temp_file.name, "rb") as file:
-                    elements = partition_via_api(
-                        file=file,
-                        metadata_filename=temp_file.name,
-                        api_url=dify_config.UNSTRUCTURED_API_URL,
-                        api_key=dify_config.UNSTRUCTURED_API_KEY,
-                    )
-                os.unlink(temp_file.name)
-        else:
-            with io.BytesIO(file_content) as file:
-                elements = partition_ppt(file=file)
+        with io.BytesIO(file_content) as file:
+            elements = partition_ppt(file=file)
        return "\n".join([getattr(element, "text", "") for element in elements])
-
    except Exception as e:
-        raise TextExtractionError(f"Failed to extract text from PPTX: {str(e)}") from e
+        raise TextExtractionError(f"Failed to extract text from PPT: {str(e)}") from e


 def _extract_text_from_pptx(file_content: bytes) -> str:
@@ -6,4 +6,4 @@ def init_app(app: DifyApp):
    if dify_config.RESPECT_XFORWARD_HEADERS_ENABLED:
        from werkzeug.middleware.proxy_fix import ProxyFix

-        app.wsgi_app = ProxyFix(app.wsgi_app, x_port=1)  # type: ignore
+        app.wsgi_app = ProxyFix(app.wsgi_app)  # type: ignore
@@ -32,11 +32,7 @@ class AwsS3Storage(BaseStorage):
                aws_access_key_id=dify_config.S3_ACCESS_KEY,
                endpoint_url=dify_config.S3_ENDPOINT,
                region_name=dify_config.S3_REGION,
-                config=Config(
-                    s3={"addressing_style": dify_config.S3_ADDRESS_STYLE},
-                    request_checksum_calculation="when_required",
-                    response_checksum_validation="when_required",
-                ),
+                config=Config(s3={"addressing_style": dify_config.S3_ADDRESS_STYLE}),
            )
        # create bucket
        try:
@@ -63,6 +63,7 @@ app_detail_fields = {
    "created_at": TimestampField,
    "updated_by": fields.String,
    "updated_at": TimestampField,
+    "access_mode": fields.String,
 }

 prompt_config_fields = {
@@ -98,6 +99,7 @@ app_partial_fields = {
    "updated_by": fields.String,
    "updated_at": TimestampField,
    "tags": fields.List(fields.Nested(tag_fields)),
+    "access_mode": fields.String,
 }


@@ -170,6 +172,7 @@ app_detail_fields_with_site = {
    "updated_by": fields.String,
    "updated_at": TimestampField,
    "deleted_tools": fields.List(fields.String),
+    "access_mode": fields.String,
 }

 app_site_fields = {
@@ -88,7 +88,7 @@ tencentcloud-sdk-python-hunyuan = "~3.0.1294"
 tiktoken = "~0.8.0"
 tokenizers = "~0.15.0"
 transformers = "~4.35.0"
-unstructured = { version = "~0.16.13", extras = ["docx", "epub", "md", "msg", "ppt", "pptx"] }
+unstructured = { version = "~0.16.1", extras = ["docx", "epub", "md", "msg", "ppt", "pptx"] }
 validators = "0.21.0"
 volcengine-python-sdk = {extras = ["ark"], version = "~1.0.98"}
 websocket-client = "~1.7.0"
@@ -77,7 +77,6 @@ class AccountService:
        prefix="email_code_account_deletion_rate_limit", max_attempts=1, time_window=60 * 1
    )
    LOGIN_MAX_ERROR_LIMITS = 5
-    FORGOT_PASSWORD_MAX_ERROR_LIMITS = 5

    @staticmethod
    def _get_refresh_token_key(refresh_token: str) -> str:
@@ -407,10 +406,8 @@ class AccountService:

            raise PasswordResetRateLimitExceededError()

-        code = "".join([str(random.randint(0, 9)) for _ in range(6)])
-        token = TokenManager.generate_token(
-            account=account, email=email, token_type="reset_password", additional_data={"code": code}
-        )
+        code, token = cls.generate_reset_password_token(account_email, account)
+
        send_reset_password_mail_task.delay(
            language=language,
            to=account_email,
@@ -419,6 +416,22 @@ class AccountService:
        cls.reset_password_rate_limiter.increment_rate_limit(account_email)
        return token

+    @classmethod
+    def generate_reset_password_token(
+        cls,
+        email: str,
+        account: Optional[Account] = None,
+        code: Optional[str] = None,
+        additional_data: dict[str, Any] = {},
+    ):
+        if not code:
+            code = "".join([str(random.randint(0, 9)) for _ in range(6)])
+        additional_data["code"] = code
+        token = TokenManager.generate_token(
+            account=account, email=email, token_type="reset_password", additional_data=additional_data
+        )
+        return code, token
+
    @classmethod
    def revoke_reset_password_token(cls, token: str):
        TokenManager.revoke_token(token, "reset_password")
@@ -504,32 +517,6 @@ class AccountService:
        key = f"login_error_rate_limit:{email}"
        redis_client.delete(key)

-    @staticmethod
-    def add_forgot_password_error_rate_limit(email: str) -> None:
-        key = f"forgot_password_error_rate_limit:{email}"
-        count = redis_client.get(key)
-        if count is None:
-            count = 0
-        count = int(count) + 1
-        redis_client.setex(key, dify_config.FORGOT_PASSWORD_LOCKOUT_DURATION, count)
-
-    @staticmethod
-    def is_forgot_password_error_rate_limit(email: str) -> bool:
-        key = f"forgot_password_error_rate_limit:{email}"
-        count = redis_client.get(key)
-        if count is None:
-            return False
-
-        count = int(count)
-        if count > AccountService.FORGOT_PASSWORD_MAX_ERROR_LIMITS:
-            return True
-        return False
-
-    @staticmethod
-    def reset_forgot_password_error_rate_limit(email: str):
-        key = f"forgot_password_error_rate_limit:{email}"
-        redis_client.delete(key)
-
    @staticmethod
    def is_email_send_ip_limit(ip_address: str):
        minute_key = f"email_send_ip_limit_minute:{ip_address}"
--- a/Show More
+++ b/Show More
Author	SHA1	Message	Date
GareArc	fc3d3e0565	fix: wrong web sso protocal source in json	2025-04-24 23:48:18 -04:00
GareArc	3761944a3f	fix: remove debug logs	2025-04-23 23:09:45 -04:00
GareArc	09f8da1429	fix: allow empty list api	2025-04-22 22:20:29 -04:00
GareArc	fcc274d679	fix: add filter in installedapp list api	2025-04-22 02:54:30 -04:00
GareArc	bfa5828259	fix: temp fix for unauthorized user in explore page	2025-04-21 19:40:51 -04:00
GareArc	455d14296f	fix: get app id from upstream decorator	2025-04-21 19:03:10 -04:00
GareArc	d1a25e54e5	fix: add logging	2025-04-21 18:48:24 -04:00
GareArc	9462ed7bbf	fix: add auth constraint to explore apps	2025-04-21 18:47:24 -04:00
GareArc	c6e63ac816	Revert "fix: update webapp auth api path" This reverts commit `a27db51b83`.	2025-04-21 02:07:43 -04:00
GareArc	a27db51b83	fix: update webapp auth api path	2025-04-21 02:06:07 -04:00
GareArc	e52a9fbfb7	fix: remove curr user in webapp permission api	2025-04-20 23:33:51 -04:00
GareArc	2af1dd6de3	feat: add webapp auth apis	2025-04-20 23:30:59 -04:00
NFishandGitHub	509733fbf0	fix: update reset password token when email code verify success (#18367 )	2025-04-18 17:15:02 +08:00
GareArc	7770a45253	fix: add password security update	2025-04-18 05:02:26 -04:00
GareArc	bafdbade52	fix: wrong json structure	2025-04-11 17:19:34 -04:00
GareArc	fa76590c24	chore: add log	2025-04-11 16:59:52 -04:00
GareArc	d5b75470e4	fix: bad request	2025-04-11 16:48:09 -04:00
GareArc	5f87bdbe3a	fix: add batch get access mode api	2025-04-11 15:24:32 -04:00
GareArc	cb13b53ccd	fix: update webapp sso features	2025-04-11 03:25:58 -04:00
GareArc	a1dc3cfdec	fix: update code for access denied error	2025-04-11 02:45:46 -04:00
GareArc	7a4ec9cf23	fix: change error code for webapp auth	2025-04-11 02:41:02 -04:00
GareArc	4785c061a9	feat: add webapp clean up	2025-04-10 15:19:28 -04:00
GareArc	4105c8ff70	fix: bad api call	2025-04-10 06:27:00 -04:00
GareArc	b922c8c215	fix: make app private when created	2025-04-10 00:36:35 -04:00
GareArc	cbea30e65f	fix: bad field name	2025-04-09 17:21:16 -04:00
GareArc	e9a207b38e	fix: adjust enterprise api	2025-04-09 16:30:41 -04:00
GareArc	5e50570739	fix: update webapp jwt claim and add user accessibility support	2025-04-07 18:41:02 -04:00
GareArc	46d43e6758	feat: add web app auth	2025-04-07 17:03:26 -04:00
GareArc	1045f6db7a	fix: wrong arg parsing	2025-03-26 01:37:45 -04:00
GareArc	50d36612f0	fix: bad import	2025-03-26 00:34:04 -04:00
GareArc	e38631db8a	feat: add inner mail api	2025-03-25 21:47:30 -04:00
Garfield Dai	7f63cd52a2	update.	2025-03-24 23:08:54 +08:00
NFish	5b357fdbf0	Merge branch 'release/0.15.5' into e-0154	2025-03-24 16:42:11 +08:00
NFish	9283a5414f	fix: update yarn.lock	2025-03-24 16:41:07 +08:00
NFish	8923e64b8d	Merge branch 'release/0.15.5' into e-0154	2025-03-24 15:40:32 +08:00
-LAN-	2a2a0e9be9	fix: update DifySandbox image version to 0.2.11 in docker-compose files Sgned-off-by: -LAN- <laipz8200@outlook.com>	2025-03-24 15:37:55 +08:00
JoelandGitHub	061a765b7d	fix: sanitizer svg to avoid xss (#16608 )	2025-03-24 14:48:40 +08:00
-LAN-	acd7fead87	feat: remove Vanna provider and associated assets from the project Signed-off-by: -LAN- <laipz8200@outlook.com>	2025-03-24 14:34:03 +08:00
KVOJJJinandNFish	64e9d96d84	chore: compatible with es5 (#14268 )	2025-03-24 13:17:48 +08:00
NFish	d27de3818c	Merge branch 'release/0.15.5' into e-0154	2025-03-24 11:46:30 +08:00
NFish	bbb080d5b2	fix: update chatbot help doc link on the create app form	2025-03-24 11:28:35 +08:00
NFish	8c025abb3b	Merge branch 'release/0.15.5' into e-0154	2025-03-24 10:32:56 +08:00
NFish	c01d8a70f3	fix: upgrade nextjs to v14.2.25. a security patch for CVE-2025-29927.	2025-03-24 10:32:18 +08:00
NFish	98606ca558	fix: upgrade nextjs to v14.2.25	2025-03-24 10:12:21 +08:00
Garfield Dai	adf3e18ebd	Merge tag '0.15.4' into e-0154	2025-03-21 18:29:43 +08:00
-LAN-	1ca15989e0	chore: update version to 0.15.4 in configuration and docker files Signed-off-by: -LAN- <laipz8200@outlook.com>	2025-03-21 16:39:06 +08:00
-LAN-	8b5a3a9424	Merge branch 'release/0.15.4' of github.com:langgenius/dify into release/0.15.4	2025-03-21 16:31:06 +08:00
-LAN-	42ddcf1edd	chore: remove 0.15.3 branch config in the build action Signed-off-by: -LAN- <laipz8200@outlook.com>	2025-03-21 16:30:33 +08:00
JoelandGitHub	21561df10f	fix: xss in render svg (#16437 )	2025-03-21 15:24:58 +08:00
Byron.wangandGitHub	4327ec8c4c	fix license expireAt field typo (#16428 )	2025-03-21 13:43:43 +08:00
NFish	bbc5ec8301	fix: expired date calc error	2025-03-21 11:00:07 +08:00
NFish	4a51a72c1d	Merge branch 'e-0154' into deploy/enterprise	2025-03-20 17:34:52 +08:00
NFish	4b6adffa8e	fix: hide copyright on forgot-password/install/reset-password page	2025-03-20 17:34:19 +08:00
NFish	c7fd73d330	Merge branch 'e-0154' into deploy/enterprise	2025-03-20 10:13:09 +08:00
NFish	8a709e445a	fix: remove Dify from Service API doc	2025-03-20 10:12:27 +08:00
NFish	f02b77b99f	fix: Decouple login page logo component to avoid conflict with internal logo	2025-03-20 10:11:26 +08:00
GareArc	abc625bcce	Merge branch 'e-0154' into deploy/enterprise	2025-03-18 22:35:39 -04:00
GareArc	b6bc1f8bc4	fix: adjust logic for branding toggle	2025-03-18 22:35:27 -04:00
NFish	b8f9037cd3	Merge branch 'e-0154' into deploy/enterprise	2025-03-18 16:13:14 +08:00
NFish	02606ba3c7	fix: cannot update webapp copyright info	2025-03-18 16:12:52 +08:00
GareArc	79311d3fb5	Merge branch 'e-0154' into deploy/enterprise	2025-03-18 03:53:18 -04:00
GareArc	31086a1fbf	feat: add webapp copyright feature	2025-03-18 03:53:07 -04:00
NFish	6ae5d052e5	Merge branch 'e-0154' into deploy/enterprise	2025-03-18 14:55:36 +08:00
NFish	c794ecf101	fix: user can edit webapp copyright info only if webapp_copyright_enabled is true	2025-03-18 14:54:34 +08:00
GareArc	d887aae012	Merge branch 'e-0154' into deploy/enterprise	2025-03-18 01:55:38 -04:00
GareArc	1b1e96eff7	fix: typo	2025-03-18 01:55:27 -04:00
GareArc	eecd091063	Merge branch 'e-0154' into deploy/enterprise	2025-03-17 15:34:49 -04:00
GareArc	d38f2cb380	fix: change subject title	2025-03-17 15:34:28 -04:00
GareArc	56aaee5558	fix: wrong branding title	2025-03-17 15:01:31 -04:00
GareArc	d72b4752c9	fix: wrong title location	2025-03-17 15:00:04 -04:00
GareArc	ea769c6483	Merge branch 'e-0154' into deploy/enterprise	2025-03-17 14:24:00 -04:00
GareArc	ec194fa3d4	fix: invalid email template variables	2025-03-17 14:23:46 -04:00
NFish	b877039859	Merge branch 'e-0154' into deploy/enterprise	2025-03-17 10:37:20 +08:00
NFish	54634f26d2	fix: show copyright in webapp	2025-03-17 10:36:51 +08:00
NFish	3bef91a2cd	fix: show loading icon when fetching system features	2025-03-15 12:01:30 +08:00
NFish	7da45ba589	fix: show loading icon when fetching system features	2025-03-15 12:00:22 +08:00
NFish	e0232c67cc	fix: update document title and favicon in client side	2025-03-15 12:00:22 +08:00
GareArc	1dc4a229d4	Merge branch 'e-0154' into deploy/enterprise	2025-03-14 16:37:02 -04:00
GareArc	0e0bada1f3	fix: missing json keys	2025-03-14 16:36:49 -04:00
GareArc	5366a814f9	fix: update json keys	2025-03-14 16:35:05 -04:00
GareArc	f1240a22db	fix: remove default value	2025-03-14 13:26:44 -04:00
NFish	66f35c2b7e	Merge branch 'e-0154' into deploy/enterprise	2025-03-15 01:25:15 +08:00
NFish	766ee48531	fix: update document title and favicon in client side	2025-03-15 01:25:04 +08:00
NFish	083045f45c	Merge branch 'e-0154' into deploy/enterprise	2025-03-14 20:49:17 +08:00
NFish	fe237802c9	fix: update Dify text	2025-03-14 19:10:03 +08:00
NFish	00b923651f	fix: update document title with system features config	2025-03-14 19:10:03 +08:00
NFish	24fce3cc64	chore: use global zustand manage systemFeatures and share between all pages	2025-03-14 19:10:03 +08:00
GareArc	8ba969f67d	fix: add ci workflow	2025-03-13 17:15:11 -04:00
GareArc	6844d59371	fix: add default title name	2025-03-13 17:07:45 -04:00
GareArc	fe5529db85	Trigger workflow	2025-03-13 17:04:13 -04:00
GareArc	d89034d913	feat: add application title	2025-03-13 15:49:04 -04:00
NFish	360fbeb108	fix: update email template, add application_title	2025-03-13 17:28:49 +08:00
GareArc	e7c2fa1cfa	fix: remove system feature is_branding	2025-03-12 10:48:58 -04:00
Hash BrownandNFish	735f09d977	fix: build failed due to `getPrevChatList` no longer exists (#13383 )	2025-03-12 10:22:33 +08:00
GareArc	f83a5e3e49	fix: wrong type	2025-03-11 07:46:48 -04:00
NFish	01a8d4efcc	fix: remove dify from invite template	2025-03-11 19:25:30 +08:00
GareArc	fdb1e649d4	feat: add branding support	2025-03-11 07:14:52 -04:00
NFish	0856792a57	fix: add email templates that are no brands or logo	2025-03-11 16:03:15 +08:00
crazywoola	0e33a3aa5f	chore: add ci	2025-02-19 14:34:36 +08:00
Hash Brownandcrazywoola	d3895bcd6b	revert	2025-02-19 14:32:28 +08:00
Hash Brownandcrazywoola	eeb390650b	fix: build failed	2025-02-19 14:32:28 +08:00