chore: update image versions to 0.9.1-fix1

- Added new release branch "release/0.9.2" to GitHub workflow.
- Updated the CURRENT_VERSION field in the packaging configuration.
- Updated Docker images for api, worker, and web services to version 0.9.2.
- Updated web application package.json version to 0.9.2.

.github/workflows/build-push.yml

@@ -125,7 +125,7 @@ jobs:
         with:
           images: ${{ env[matrix.image_name_env] }}
           tags: |
-            type=raw,value=latest,enable=${{ startsWith(github.ref, 'refs/tags/') }}
+            type=raw,value=latest,enable=${{ startsWith(github.ref, 'refs/tags/') && !contains(github.ref, '-beta') }}
             type=ref,event=branch
             type=sha,enable=true,priority=100,prefix=,suffix=,format=long
             type=raw,value=${{ github.ref_name }},enable=${{ startsWith(github.ref, 'refs/tags/') }}

.github/workflows/web-tests.yml

@@ -0,0 +1,46 @@
+name: Web Tests
+
+on:
+  pull_request:
+    branches:
+      - main
+    paths:
+      - web/**
+
+concurrency:
+  group: web-tests-${{ github.head_ref || github.run_id }}
+  cancel-in-progress: true
+
+jobs:
+  test:
+    name: Web Tests
+    runs-on: ubuntu-latest
+    defaults:
+      run:
+        working-directory: ./web
+
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+
+      - name: Check changed files
+        id: changed-files
+        uses: tj-actions/changed-files@v45
+        with:
+          files: web/**
+
+      - name: Setup Node.js
+        uses: actions/setup-node@v4
+        if: steps.changed-files.outputs.any_changed == 'true'
+        with:
+          node-version: 20
+          cache: yarn
+          cache-dependency-path: ./web/package.json
+
+      - name: Install dependencies
+        if: steps.changed-files.outputs.any_changed == 'true'
+        run: yarn install --frozen-lockfile
+
+      - name: Run tests
+        if: steps.changed-files.outputs.any_changed == 'true'
+        run: yarn test

README_JA.md

@@ -68,7 +68,7 @@ DifyはオープンソースのLLMアプリケーション開発プラットフ
   プロンプトの作成、モデルパフォーマンスの比較が行え、チャットベースのアプリに音声合成などの機能も追加できます。
 
 **4. RAGパイプライン**: 
-  ドキュメントの取り込みから検索までをカバーする広範なRAG機能ができます。ほかにもPDF、PPT、その他の一般的なドキュメントフォーマットからのテキスト抽出のサーポイントも提供します。
+  ドキュメントの取り込みから検索までをカバーする広範なRAG機能ができます。ほかにもPDF、PPT、その他の一般的なドキュメントフォーマットからのテキスト抽出のサポートも提供します。
 
 **5. エージェント機能**: 
   LLM Function CallingやReActに基づくエージェントの定義が可能で、AIエージェント用のプリビルトまたはカスタムツールを追加できます。Difyには、Google検索、DALL·E、Stable Diffusion、WolframAlphaなどのAIエージェント用の50以上の組み込みツールが提供します。

api/.env.example

@@ -39,7 +39,7 @@ DB_DATABASE=dify
 
 # Storage configuration
 # use for store upload files, private keys...
-# storage type: local, s3, azure-blob, google-storage, tencent-cos, huawei-obs, volcengine-tos
+# storage type: local, s3, azure-blob, google-storage, tencent-cos, huawei-obs, volcengine-tos, baidu-obs
 STORAGE_TYPE=local
 STORAGE_LOCAL_PATH=storage
 S3_USE_AWS_MANAGED_IAM=false
@@ -79,6 +79,12 @@ HUAWEI_OBS_SECRET_KEY=your-secret-key
 HUAWEI_OBS_ACCESS_KEY=your-access-key
 HUAWEI_OBS_SERVER=your-server-url
 
+# Baidu OBS Storage Configuration
+BAIDU_OBS_BUCKET_NAME=your-bucket-name
+BAIDU_OBS_SECRET_KEY=your-secret-key
+BAIDU_OBS_ACCESS_KEY=your-access-key
+BAIDU_OBS_ENDPOINT=your-server-url
+
 # OCI Storage configuration
 OCI_ENDPOINT=your-endpoint
 OCI_BUCKET_NAME=your-bucket-name
@@ -162,6 +168,8 @@ PGVECTOR_PORT=5433
 PGVECTOR_USER=postgres
 PGVECTOR_PASSWORD=postgres
 PGVECTOR_DATABASE=postgres
+PGVECTOR_MIN_CONNECTION=1
+PGVECTOR_MAX_CONNECTION=5
 
 # Tidb Vector configuration
 TIDB_VECTOR_HOST=xxx.eu-central-1.xxx.aws.tidbcloud.com

api/README.md

@@ -65,14 +65,12 @@
 
 8. Start Dify [web](../web) service.
 9. Setup your application by visiting `http://localhost:3000`...
-10. If you need to debug local async processing, please start the worker service.
+10. If you need to handle and debug the async tasks (e.g. dataset importing and documents indexing), please start the worker service.
 
    ```bash
    poetry run python -m celery -A app.celery worker -P gevent -c 1 --loglevel INFO -Q dataset,generation,mail,ops_trace,app_deletion
    ```
 
-   The started celery app handles the async tasks, e.g. dataset importing and documents indexing.
-
 ## Testing
 
 1. Install dependencies for both the backend and the test environment

api/app.py

@@ -53,11 +53,9 @@ from services.account_service import AccountService
 
 warnings.simplefilter("ignore", ResourceWarning)
 
-# fix windows platform
-if os.name == "nt":
-    os.system('tzutil /s "UTC"')
-else:
-    os.environ["TZ"] = "UTC"
+os.environ["TZ"] = "UTC"
+# windows platform not support tzset
+if hasattr(time, "tzset"):
     time.tzset()
 
 

api/commands.py

@@ -28,28 +28,28 @@ from services.account_service import RegisterService, TenantService
 
 
 @click.command("reset-password", help="Reset the account password.")
-@click.option("--email", prompt=True, help="The email address of the account whose password you need to reset")
-@click.option("--new-password", prompt=True, help="the new password.")
-@click.option("--password-confirm", prompt=True, help="the new password confirm.")
+@click.option("--email", prompt=True, help="Account email to reset password for")
+@click.option("--new-password", prompt=True, help="New password")
+@click.option("--password-confirm", prompt=True, help="Confirm new password")
 def reset_password(email, new_password, password_confirm):
     """
     Reset password of owner account
     Only available in SELF_HOSTED mode
     """
     if str(new_password).strip() != str(password_confirm).strip():
-        click.echo(click.style("sorry. The two passwords do not match.", fg="red"))
+        click.echo(click.style("Passwords do not match.", fg="red"))
         return
 
     account = db.session.query(Account).filter(Account.email == email).one_or_none()
 
     if not account:
-        click.echo(click.style("sorry. the account: [{}] not exist .".format(email), fg="red"))
+        click.echo(click.style("Account not found for email: {}".format(email), fg="red"))
         return
 
     try:
         valid_password(new_password)
     except:
-        click.echo(click.style("sorry. The passwords must match {} ".format(password_pattern), fg="red"))
+        click.echo(click.style("Invalid password. Must match {}".format(password_pattern), fg="red"))
         return
 
     # generate password salt
@@ -62,37 +62,37 @@ def reset_password(email, new_password, password_confirm):
     account.password = base64_password_hashed
     account.password_salt = base64_salt
     db.session.commit()
-    click.echo(click.style("Congratulations! Password has been reset.", fg="green"))
+    click.echo(click.style("Password reset successfully.", fg="green"))
 
 
 @click.command("reset-email", help="Reset the account email.")
-@click.option("--email", prompt=True, help="The old email address of the account whose email you need to reset")
-@click.option("--new-email", prompt=True, help="the new email.")
-@click.option("--email-confirm", prompt=True, help="the new email confirm.")
+@click.option("--email", prompt=True, help="Current account email")
+@click.option("--new-email", prompt=True, help="New email")
+@click.option("--email-confirm", prompt=True, help="Confirm new email")
 def reset_email(email, new_email, email_confirm):
     """
     Replace account email
     :return:
     """
     if str(new_email).strip() != str(email_confirm).strip():
-        click.echo(click.style("Sorry, new email and confirm email do not match.", fg="red"))
+        click.echo(click.style("New emails do not match.", fg="red"))
         return
 
     account = db.session.query(Account).filter(Account.email == email).one_or_none()
 
     if not account:
-        click.echo(click.style("sorry. the account: [{}] not exist .".format(email), fg="red"))
+        click.echo(click.style("Account not found for email: {}".format(email), fg="red"))
         return
 
     try:
         email_validate(new_email)
     except:
-        click.echo(click.style("sorry. {} is not a valid email. ".format(email), fg="red"))
+        click.echo(click.style("Invalid email: {}".format(new_email), fg="red"))
         return
 
     account.email = new_email
     db.session.commit()
-    click.echo(click.style("Congratulations!, email has been reset.", fg="green"))
+    click.echo(click.style("Email updated successfully.", fg="green"))
 
 
 @click.command(
@@ -104,7 +104,7 @@ def reset_email(email, new_email, email_confirm):
 )
 @click.confirmation_option(
     prompt=click.style(
-        "Are you sure you want to reset encrypt key pair? this operation cannot be rolled back!", fg="red"
+        "Are you sure you want to reset encrypt key pair? This operation cannot be rolled back!", fg="red"
     )
 )
 def reset_encrypt_key_pair():
@@ -114,13 +114,13 @@ def reset_encrypt_key_pair():
     Only support SELF_HOSTED mode.
     """
     if dify_config.EDITION != "SELF_HOSTED":
-        click.echo(click.style("Sorry, only support SELF_HOSTED mode.", fg="red"))
+        click.echo(click.style("This command is only for SELF_HOSTED installations.", fg="red"))
         return
 
     tenants = db.session.query(Tenant).all()
     for tenant in tenants:
         if not tenant:
-            click.echo(click.style("Sorry, no workspace found. Please enter /install to initialize.", fg="red"))
+            click.echo(click.style("No workspaces found. Run /install first.", fg="red"))
             return
 
         tenant.encrypt_public_key = generate_key_pair(tenant.id)
@@ -137,7 +137,7 @@ def reset_encrypt_key_pair():
         )
 
 
-@click.command("vdb-migrate", help="migrate vector db.")
+@click.command("vdb-migrate", help="Migrate vector db.")
 @click.option("--scope", default="all", prompt=False, help="The scope of vector database to migrate, Default is All.")
 def vdb_migrate(scope: str):
     if scope in {"knowledge", "all"}:
@@ -150,7 +150,7 @@ def migrate_annotation_vector_database():
     """
     Migrate annotation datas to target vector database .
     """
-    click.echo(click.style("Start migrate annotation data.", fg="green"))
+    click.echo(click.style("Starting annotation data migration.", fg="green"))
     create_count = 0
     skipped_count = 0
     total_count = 0
@@ -174,14 +174,14 @@ def migrate_annotation_vector_database():
                 f"Processing the {total_count} app {app.id}. " + f"{create_count} created, {skipped_count} skipped."
             )
             try:
-                click.echo("Create app annotation index: {}".format(app.id))
+                click.echo("Creating app annotation index: {}".format(app.id))
                 app_annotation_setting = (
                     db.session.query(AppAnnotationSetting).filter(AppAnnotationSetting.app_id == app.id).first()
                 )
 
                 if not app_annotation_setting:
                     skipped_count = skipped_count + 1
-                    click.echo("App annotation setting is disabled: {}".format(app.id))
+                    click.echo("App annotation setting disabled: {}".format(app.id))
                     continue
                 # get dataset_collection_binding info
                 dataset_collection_binding = (
@@ -190,7 +190,7 @@ def migrate_annotation_vector_database():
                     .first()
                 )
                 if not dataset_collection_binding:
-                    click.echo("App annotation collection binding is not exist: {}".format(app.id))
+                    click.echo("App annotation collection binding not found: {}".format(app.id))
                     continue
                 annotations = db.session.query(MessageAnnotation).filter(MessageAnnotation.app_id == app.id).all()
                 dataset = Dataset(
@@ -211,11 +211,11 @@ def migrate_annotation_vector_database():
                         documents.append(document)
 
                 vector = Vector(dataset, attributes=["doc_id", "annotation_id", "app_id"])
-                click.echo(f"Start to migrate annotation, app_id: {app.id}.")
+                click.echo(f"Migrating annotations for app: {app.id}.")
 
                 try:
                     vector.delete()
-                    click.echo(click.style(f"Successfully delete vector index for app: {app.id}.", fg="green"))
+                    click.echo(click.style(f"Deleted vector index for app {app.id}.", fg="green"))
                 except Exception as e:
                     click.echo(click.style(f"Failed to delete vector index for app {app.id}.", fg="red"))
                     raise e
@@ -223,12 +223,12 @@ def migrate_annotation_vector_database():
                     try:
                         click.echo(
                             click.style(
-                                f"Start to created vector index with {len(documents)} annotations for app {app.id}.",
+                                f"Creating vector index with {len(documents)} annotations for app {app.id}.",
                                 fg="green",
                             )
                         )
                         vector.create(documents)
-                        click.echo(click.style(f"Successfully created vector index for app {app.id}.", fg="green"))
+                        click.echo(click.style(f"Created vector index for app {app.id}.", fg="green"))
                     except Exception as e:
                         click.echo(click.style(f"Failed to created vector index for app {app.id}.", fg="red"))
                         raise e
@@ -237,14 +237,14 @@ def migrate_annotation_vector_database():
             except Exception as e:
                 click.echo(
                     click.style(
-                        "Create app annotation index error: {} {}".format(e.__class__.__name__, str(e)), fg="red"
+                        "Error creating app annotation index: {} {}".format(e.__class__.__name__, str(e)), fg="red"
                     )
                 )
                 continue
 
     click.echo(
         click.style(
-            f"Congratulations! Create {create_count} app annotation indexes, and skipped {skipped_count} apps.",
+            f"Migration complete. Created {create_count} app annotation indexes. Skipped {skipped_count} apps.",
             fg="green",
         )
     )
@@ -254,7 +254,7 @@ def migrate_knowledge_vector_database():
     """
     Migrate vector database datas to target vector database .
     """
-    click.echo(click.style("Start migrate vector db.", fg="green"))
+    click.echo(click.style("Starting vector database migration.", fg="green"))
     create_count = 0
     skipped_count = 0
     total_count = 0
@@ -278,7 +278,7 @@ def migrate_knowledge_vector_database():
                 f"Processing the {total_count} dataset {dataset.id}. {create_count} created, {skipped_count} skipped."
             )
             try:
-                click.echo("Create dataset vdb index: {}".format(dataset.id))
+                click.echo("Creating dataset vector database index: {}".format(dataset.id))
                 if dataset.index_struct_dict:
                     if dataset.index_struct_dict["type"] == vector_type:
                         skipped_count = skipped_count + 1
@@ -299,7 +299,7 @@ def migrate_knowledge_vector_database():
                         if dataset_collection_binding:
                             collection_name = dataset_collection_binding.collection_name
                         else:
-                            raise ValueError("Dataset Collection Bindings is not exist!")
+                            raise ValueError("Dataset Collection Binding not found")
                     else:
                         dataset_id = dataset.id
                         collection_name = Dataset.gen_collection_name_by_id(dataset_id)
@@ -351,14 +351,12 @@ def migrate_knowledge_vector_database():
                     raise ValueError(f"Vector store {vector_type} is not supported.")
 
                 vector = Vector(dataset)
-                click.echo(f"Start to migrate dataset {dataset.id}.")
+                click.echo(f"Migrating dataset {dataset.id}.")
 
                 try:
                     vector.delete()
                     click.echo(
-                        click.style(
-                            f"Successfully delete vector index {collection_name} for dataset {dataset.id}.", fg="green"
-                        )
+                        click.style(f"Deleted vector index {collection_name} for dataset {dataset.id}.", fg="green")
                     )
                 except Exception as e:
                     click.echo(
@@ -410,15 +408,13 @@ def migrate_knowledge_vector_database():
                     try:
                         click.echo(
                             click.style(
-                                f"Start to created vector index with {len(documents)} documents of {segments_count}"
+                                f"Creating vector index with {len(documents)} documents of {segments_count}"
                                 f" segments for dataset {dataset.id}.",
                                 fg="green",
                             )
                         )
                         vector.create(documents)
-                        click.echo(
-                            click.style(f"Successfully created vector index for dataset {dataset.id}.", fg="green")
-                        )
+                        click.echo(click.style(f"Created vector index for dataset {dataset.id}.", fg="green"))
                     except Exception as e:
                         click.echo(click.style(f"Failed to created vector index for dataset {dataset.id}.", fg="red"))
                         raise e
@@ -429,13 +425,13 @@ def migrate_knowledge_vector_database():
             except Exception as e:
                 db.session.rollback()
                 click.echo(
-                    click.style("Create dataset index error: {} {}".format(e.__class__.__name__, str(e)), fg="red")
+                    click.style("Error creating dataset index: {} {}".format(e.__class__.__name__, str(e)), fg="red")
                 )
                 continue
 
     click.echo(
         click.style(
-            f"Congratulations! Create {create_count} dataset indexes, and skipped {skipped_count} datasets.", fg="green"
+            f"Migration complete. Created {create_count} dataset indexes. Skipped {skipped_count} datasets.", fg="green"
         )
     )
 
@@ -445,7 +441,7 @@ def convert_to_agent_apps():
     """
     Convert Agent Assistant to Agent App.
     """
-    click.echo(click.style("Start convert to agent apps.", fg="green"))
+    click.echo(click.style("Starting convert to agent apps.", fg="green"))
 
     proceeded_app_ids = []
 
@@ -496,23 +492,23 @@ def convert_to_agent_apps():
             except Exception as e:
                 click.echo(click.style("Convert app error: {} {}".format(e.__class__.__name__, str(e)), fg="red"))
 
-    click.echo(click.style("Congratulations! Converted {} agent apps.".format(len(proceeded_app_ids)), fg="green"))
+    click.echo(click.style("Conversion complete. Converted {} agent apps.".format(len(proceeded_app_ids)), fg="green"))
 
 
-@click.command("add-qdrant-doc-id-index", help="add qdrant doc_id index.")
-@click.option("--field", default="metadata.doc_id", prompt=False, help="index field , default is metadata.doc_id.")
+@click.command("add-qdrant-doc-id-index", help="Add Qdrant doc_id index.")
+@click.option("--field", default="metadata.doc_id", prompt=False, help="Index field , default is metadata.doc_id.")
 def add_qdrant_doc_id_index(field: str):
-    click.echo(click.style("Start add qdrant doc_id index.", fg="green"))
+    click.echo(click.style("Starting Qdrant doc_id index creation.", fg="green"))
     vector_type = dify_config.VECTOR_STORE
     if vector_type != "qdrant":
-        click.echo(click.style("Sorry, only support qdrant vector store.", fg="red"))
+        click.echo(click.style("This command only supports Qdrant vector store.", fg="red"))
         return
     create_count = 0
 
     try:
         bindings = db.session.query(DatasetCollectionBinding).all()
         if not bindings:
-            click.echo(click.style("Sorry, no dataset collection bindings found.", fg="red"))
+            click.echo(click.style("No dataset collection bindings found.", fg="red"))
             return
         import qdrant_client
         from qdrant_client.http.exceptions import UnexpectedResponse
@@ -522,7 +518,7 @@ def add_qdrant_doc_id_index(field: str):
 
         for binding in bindings:
             if dify_config.QDRANT_URL is None:
-                raise ValueError("Qdrant url is required.")
+                raise ValueError("Qdrant URL is required.")
             qdrant_config = QdrantConfig(
                 endpoint=dify_config.QDRANT_URL,
                 api_key=dify_config.QDRANT_API_KEY,
@@ -539,41 +535,39 @@ def add_qdrant_doc_id_index(field: str):
             except UnexpectedResponse as e:
                 # Collection does not exist, so return
                 if e.status_code == 404:
-                    click.echo(
-                        click.style(f"Collection not found, collection_name:{binding.collection_name}.", fg="red")
-                    )
+                    click.echo(click.style(f"Collection not found: {binding.collection_name}.", fg="red"))
                     continue
                 # Some other error occurred, so re-raise the exception
                 else:
                     click.echo(
                         click.style(
-                            f"Failed to create qdrant index, collection_name:{binding.collection_name}.", fg="red"
+                            f"Failed to create Qdrant index for collection: {binding.collection_name}.", fg="red"
                         )
                     )
 
     except Exception as e:
-        click.echo(click.style("Failed to create qdrant client.", fg="red"))
+        click.echo(click.style("Failed to create Qdrant client.", fg="red"))
 
-    click.echo(click.style(f"Congratulations! Create {create_count} collection indexes.", fg="green"))
+    click.echo(click.style(f"Index creation complete. Created {create_count} collection indexes.", fg="green"))
 
 
 @click.command("create-tenant", help="Create account and tenant.")
-@click.option("--email", prompt=True, help="The email address of the tenant account.")
-@click.option("--name", prompt=True, help="The workspace name of the tenant account.")
+@click.option("--email", prompt=True, help="Tenant account email.")
+@click.option("--name", prompt=True, help="Workspace name.")
 @click.option("--language", prompt=True, help="Account language, default: en-US.")
 def create_tenant(email: str, language: Optional[str] = None, name: Optional[str] = None):
     """
     Create tenant account
     """
     if not email:
-        click.echo(click.style("Sorry, email is required.", fg="red"))
+        click.echo(click.style("Email is required.", fg="red"))
         return
 
     # Create account
     email = email.strip()
 
     if "@" not in email:
-        click.echo(click.style("Sorry, invalid email address.", fg="red"))
+        click.echo(click.style("Invalid email address.", fg="red"))
         return
 
     account_name = email.split("@")[0]
@@ -593,19 +587,19 @@ def create_tenant(email: str, language: Optional[str] = None, name: Optional[str
 
     click.echo(
         click.style(
-            "Congratulations! Account and tenant created.\nAccount: {}\nPassword: {}".format(email, new_password),
+            "Account and tenant created.\nAccount: {}\nPassword: {}".format(email, new_password),
             fg="green",
         )
     )
 
 
-@click.command("upgrade-db", help="upgrade the database")
+@click.command("upgrade-db", help="Upgrade the database")
 def upgrade_db():
     click.echo("Preparing database migration...")
     lock = redis_client.lock(name="db_upgrade_lock", timeout=60)
     if lock.acquire(blocking=False):
         try:
-            click.echo(click.style("Start database migration.", fg="green"))
+            click.echo(click.style("Starting database migration.", fg="green"))
 
             # run db migration
             import flask_migrate
@@ -615,7 +609,7 @@ def upgrade_db():
             click.echo(click.style("Database migration successful!", fg="green"))
 
         except Exception as e:
-            logging.exception(f"Database migration failed, error: {e}")
+            logging.exception(f"Database migration failed: {e}")
         finally:
             lock.release()
     else:
@@ -627,7 +621,7 @@ def fix_app_site_missing():
     """
     Fix app related site missing issue.
     """
-    click.echo(click.style("Start fix app related site missing issue.", fg="green"))
+    click.echo(click.style("Starting fix for missing app-related sites.", fg="green"))
 
     failed_app_ids = []
     while True:
@@ -650,22 +644,22 @@ where sites.id is null limit 1000"""
                     if tenant:
                         accounts = tenant.get_accounts()
                         if not accounts:
-                            print("Fix app {} failed.".format(app.id))
+                            print("Fix failed for app {}".format(app.id))
                             continue
 
                         account = accounts[0]
-                        print("Fix app {} related site missing issue.".format(app.id))
+                        print("Fixing missing site for app {}".format(app.id))
                         app_was_created.send(app, account=account)
                 except Exception as e:
                     failed_app_ids.append(app_id)
-                    click.echo(click.style("Fix app {} related site missing issue failed!".format(app_id), fg="red"))
+                    click.echo(click.style("Failed to fix missing site for app {}".format(app_id), fg="red"))
                     logging.exception(f"Fix app related site missing issue failed, error: {e}")
                     continue
 
             if not processed_count:
                 break
 
-    click.echo(click.style("Congratulations! Fix app related site missing issue successful!", fg="green"))
+    click.echo(click.style("Fix for missing app-related sites completed successfully!", fg="green"))
 
 
 def register_commands(app):

api/configs/deploy/__init__.py

@@ -4,30 +4,30 @@ from pydantic_settings import BaseSettings
 
 class DeploymentConfig(BaseSettings):
     """
-    Deployment configs
+    Configuration settings for application deployment
     """
 
     APPLICATION_NAME: str = Field(
-        description="application name",
+        description="Name of the application, used for identification and logging purposes",
         default="langgenius/dify",
     )
 
     DEBUG: bool = Field(
-        description="whether to enable debug mode.",
+        description="Enable debug mode for additional logging and development features",
         default=False,
     )
 
     TESTING: bool = Field(
-        description="",
+        description="Enable testing mode for running automated tests",
         default=False,
     )
 
     EDITION: str = Field(
-        description="deployment edition",
+        description="Deployment edition of the application (e.g., 'SELF_HOSTED', 'CLOUD')",
         default="SELF_HOSTED",
     )
 
     DEPLOY_ENV: str = Field(
-        description="deployment environment, default to PRODUCTION.",
+        description="Deployment environment (e.g., 'PRODUCTION', 'DEVELOPMENT'), default to PRODUCTION",
         default="PRODUCTION",
     )

api/configs/enterprise/__init__.py

@@ -4,17 +4,17 @@ from pydantic_settings import BaseSettings
 
 class EnterpriseFeatureConfig(BaseSettings):
     """
-    Enterprise feature configs.
+    Configuration for enterprise-level features.
     **Before using, please contact business@dify.ai by email to inquire about licensing matters.**
     """
 
     ENTERPRISE_ENABLED: bool = Field(
-        description="whether to enable enterprise features."
+        description="Enable or disable enterprise-level features."
         "Before using, please contact business@dify.ai by email to inquire about licensing matters.",
         default=False,
     )
 
     CAN_REPLACE_LOGO: bool = Field(
-        description="whether to allow replacing enterprise logo.",
+        description="Allow customization of the enterprise logo.",
         default=False,
     )

api/configs/extra/notion_config.py

@@ -6,30 +6,31 @@ from pydantic_settings import BaseSettings
 
 class NotionConfig(BaseSettings):
     """
-    Notion integration configs
+    Configuration settings for Notion integration
     """
 
     NOTION_CLIENT_ID: Optional[str] = Field(
-        description="Notion client ID",
+        description="Client ID for Notion API authentication. Required for OAuth 2.0 flow.",
         default=None,
     )
 
     NOTION_CLIENT_SECRET: Optional[str] = Field(
-        description="Notion client secret key",
+        description="Client secret for Notion API authentication. Required for OAuth 2.0 flow.",
         default=None,
     )
 
     NOTION_INTEGRATION_TYPE: Optional[str] = Field(
-        description="Notion integration type, default to None, available values: internal.",
+        description="Type of Notion integration."
+        " Set to 'internal' for internal integrations, or None for public integrations.",
         default=None,
     )
 
     NOTION_INTERNAL_SECRET: Optional[str] = Field(
-        description="Notion internal secret key",
+        description="Secret key for internal Notion integrations. Required when NOTION_INTEGRATION_TYPE is 'internal'.",
         default=None,
     )
 
     NOTION_INTEGRATION_TOKEN: Optional[str] = Field(
-        description="Notion integration token",
+        description="Integration token for Notion API access. Used for direct API calls without OAuth flow.",
         default=None,
     )

api/configs/extra/sentry_config.py

@@ -6,20 +6,23 @@ from pydantic_settings import BaseSettings
 
 class SentryConfig(BaseSettings):
     """
-    Sentry configs
+    Configuration settings for Sentry error tracking and performance monitoring
     """
 
     SENTRY_DSN: Optional[str] = Field(
-        description="Sentry DSN",
+        description="Sentry Data Source Name (DSN)."
+        " This is the unique identifier of your Sentry project, used to send events to the correct project.",
         default=None,
     )
 
     SENTRY_TRACES_SAMPLE_RATE: NonNegativeFloat = Field(
-        description="Sentry trace sample rate",
+        description="Sample rate for Sentry performance monitoring traces."
+        " Value between 0.0 and 1.0, where 1.0 means 100% of traces are sent to Sentry.",
         default=1.0,
     )
 
     SENTRY_PROFILES_SAMPLE_RATE: NonNegativeFloat = Field(
-        description="Sentry profiles sample rate",
+        description="Sample rate for Sentry profiling."
+        " Value between 0.0 and 1.0, where 1.0 means 100% of profiles are sent to Sentry.",
         default=1.0,
     )

api/configs/feature/__init__.py

@@ -8,145 +8,143 @@ from configs.feature.hosted_service import HostedServiceConfig
 
 class SecurityConfig(BaseSettings):
     """
-    Secret Key configs
+    Security-related configurations for the application
     """
 
     SECRET_KEY: Optional[str] = Field(
-        description="Your App secret key will be used for securely signing the session cookie"
+        description="Secret key for secure session cookie signing."
         "Make sure you are changing this key for your deployment with a strong key."
-        "You can generate a strong key using `openssl rand -base64 42`."
-        "Alternatively you can set it with `SECRET_KEY` environment variable.",
+        "Generate a strong key using `openssl rand -base64 42` or set via the `SECRET_KEY` environment variable.",
         default=None,
     )
 
     RESET_PASSWORD_TOKEN_EXPIRY_HOURS: PositiveInt = Field(
-        description="Expiry time in hours for reset token",
+        description="Duration in hours for which a password reset token remains valid",
         default=24,
     )
 
 
 class AppExecutionConfig(BaseSettings):
     """
-    App Execution configs
+    Configuration parameters for application execution
     """
 
     APP_MAX_EXECUTION_TIME: PositiveInt = Field(
-        description="execution timeout in seconds for app execution",
+        description="Maximum allowed execution time for the application in seconds",
         default=1200,
     )
     APP_MAX_ACTIVE_REQUESTS: NonNegativeInt = Field(
-        description="max active request per app, 0 means unlimited",
+        description="Maximum number of concurrent active requests per app (0 for unlimited)",
         default=0,
     )
 
 
 class CodeExecutionSandboxConfig(BaseSettings):
     """
-    Code Execution Sandbox configs
+    Configuration for the code execution sandbox environment
     """
 
     CODE_EXECUTION_ENDPOINT: HttpUrl = Field(
-        description="endpoint URL of code execution service",
+        description="URL endpoint for the code execution service",
         default="http://sandbox:8194",
     )
 
     CODE_EXECUTION_API_KEY: str = Field(
-        description="API key for code execution service",
+        description="API key for accessing the code execution service",
         default="dify-sandbox",
     )
 
     CODE_EXECUTION_CONNECT_TIMEOUT: Optional[float] = Field(
-        description="connect timeout in seconds for code execution request",
+        description="Connection timeout in seconds for code execution requests",
         default=10.0,
     )
 
     CODE_EXECUTION_READ_TIMEOUT: Optional[float] = Field(
-        description="read timeout in seconds for code execution request",
+        description="Read timeout in seconds for code execution requests",
         default=60.0,
     )
 
     CODE_EXECUTION_WRITE_TIMEOUT: Optional[float] = Field(
-        description="write timeout in seconds for code execution request",
+        description="Write timeout in seconds for code execution request",
         default=10.0,
     )
 
     CODE_MAX_NUMBER: PositiveInt = Field(
-        description="max depth for code execution",
+        description="Maximum allowed numeric value in code execution",
         default=9223372036854775807,
     )
 
     CODE_MIN_NUMBER: NegativeInt = Field(
-        description="",
+        description="Minimum allowed numeric value in code execution",
         default=-9223372036854775807,
     )
 
     CODE_MAX_DEPTH: PositiveInt = Field(
-        description="max depth for code execution",
+        description="Maximum allowed depth for nested structures in code execution",
         default=5,
     )
 
     CODE_MAX_PRECISION: PositiveInt = Field(
-        description="max precision digits for float type in code execution",
+        description="mMaximum number of decimal places for floating-point numbers in code execution",
         default=20,
     )
 
     CODE_MAX_STRING_LENGTH: PositiveInt = Field(
-        description="max string length for code execution",
+        description="Maximum allowed length for strings in code execution",
         default=80000,
     )
 
     CODE_MAX_STRING_ARRAY_LENGTH: PositiveInt = Field(
-        description="",
+        description="Maximum allowed length for string arrays in code execution",
         default=30,
     )
 
     CODE_MAX_OBJECT_ARRAY_LENGTH: PositiveInt = Field(
-        description="",
+        description="Maximum allowed length for object arrays in code execution",
         default=30,
     )
 
     CODE_MAX_NUMBER_ARRAY_LENGTH: PositiveInt = Field(
-        description="",
+        description="Maximum allowed length for numeric arrays in code execution",
         default=1000,
     )
 
 
 class EndpointConfig(BaseSettings):
     """
-    Module URL configs
+    Configuration for various application endpoints and URLs
     """
 
     CONSOLE_API_URL: str = Field(
-        description="The backend URL prefix of the console API."
-        "used to concatenate the login authorization callback or notion integration callback.",
+        description="Base URL for the console API,"
+        "used for login authentication callback or notion integration callbacks",
         default="",
     )
 
     CONSOLE_WEB_URL: str = Field(
-        description="The front-end URL prefix of the console web."
-        "used to concatenate some front-end addresses and for CORS configuration use.",
+        description="Base URL for the console web interface," "used for frontend references and CORS configuration",
         default="",
     )
 
     SERVICE_API_URL: str = Field(
-        description="Service API Url prefix. used to display Service API Base Url to the front-end.",
+        description="Base URL for the service API, displayed to users for API access",
         default="",
     )
 
     APP_WEB_URL: str = Field(
-        description="WebApp Url prefix. used to display WebAPP API Base Url to the front-end.",
+        description="Base URL for the web application, used for frontend references",
         default="",
     )
 
 
 class FileAccessConfig(BaseSettings):
     """
-    File Access configs
+    Configuration for file access and handling
     """
 
     FILES_URL: str = Field(
-        description="File preview or download Url prefix."
-        " used to display File preview or download Url to the front-end or as Multi-model inputs;"
+        description="Base URL for file preview or download,"
+        " used for frontend display and multi-model inputs"
         "Url is signed and has expiration time.",
         validation_alias=AliasChoices("FILES_URL", "CONSOLE_API_URL"),
         alias_priority=1,
@@ -154,49 +152,49 @@ class FileAccessConfig(BaseSettings):
     )
 
     FILES_ACCESS_TIMEOUT: int = Field(
-        description="timeout in seconds for file accessing",
+        description="Expiration time in seconds for file access URLs",
         default=300,
     )
 
 
 class FileUploadConfig(BaseSettings):
     """
-    File Uploading configs
+    Configuration for file upload limitations
     """
 
     UPLOAD_FILE_SIZE_LIMIT: NonNegativeInt = Field(
-        description="size limit in Megabytes for uploading files",
+        description="Maximum allowed file size for uploads in megabytes",
         default=15,
     )
 
     UPLOAD_FILE_BATCH_LIMIT: NonNegativeInt = Field(
-        description="batch size limit for uploading files",
+        description="Maximum number of files allowed in a single upload batch",
         default=5,
     )
 
     UPLOAD_IMAGE_FILE_SIZE_LIMIT: NonNegativeInt = Field(
-        description="image file size limit in Megabytes for uploading files",
+        description="Maximum allowed image file size for uploads in megabytes",
         default=10,
     )
 
     BATCH_UPLOAD_LIMIT: NonNegativeInt = Field(
-        description="",  # todo: to be clarified
+        description="Maximum number of files allowed in a batch upload operation",
         default=20,
     )
 
 
 class HttpConfig(BaseSettings):
     """
-    HTTP configs
+    HTTP-related configurations for the application
     """
 
     API_COMPRESSION_ENABLED: bool = Field(
-        description="whether to enable HTTP response compression of gzip",
+        description="Enable or disable gzip compression for HTTP responses",
         default=False,
     )
 
     inner_CONSOLE_CORS_ALLOW_ORIGINS: str = Field(
-        description="",
+        description="Comma-separated list of allowed origins for CORS in the console",
         validation_alias=AliasChoices("CONSOLE_CORS_ALLOW_ORIGINS", "CONSOLE_WEB_URL"),
         default="",
     )
@@ -218,359 +216,360 @@ class HttpConfig(BaseSettings):
         return self.inner_WEB_API_CORS_ALLOW_ORIGINS.split(",")
 
     HTTP_REQUEST_MAX_CONNECT_TIMEOUT: Annotated[
-        PositiveInt, Field(ge=10, description="connect timeout in seconds for HTTP request")
+        PositiveInt, Field(ge=10, description="Maximum connection timeout in seconds for HTTP requests")
     ] = 10
 
     HTTP_REQUEST_MAX_READ_TIMEOUT: Annotated[
-        PositiveInt, Field(ge=60, description="read timeout in seconds for HTTP request")
+        PositiveInt, Field(ge=60, description="Maximum read timeout in seconds for HTTP requests")
     ] = 60
 
     HTTP_REQUEST_MAX_WRITE_TIMEOUT: Annotated[
-        PositiveInt, Field(ge=10, description="read timeout in seconds for HTTP request")
+        PositiveInt, Field(ge=10, description="Maximum write timeout in seconds for HTTP requests")
     ] = 20
 
     HTTP_REQUEST_NODE_MAX_BINARY_SIZE: PositiveInt = Field(
-        description="",
+        description="Maximum allowed size in bytes for binary data in HTTP requests",
         default=10 * 1024 * 1024,
     )
 
     HTTP_REQUEST_NODE_MAX_TEXT_SIZE: PositiveInt = Field(
-        description="",
+        description="Maximum allowed size in bytes for text data in HTTP requests",
         default=1 * 1024 * 1024,
     )
 
     SSRF_PROXY_HTTP_URL: Optional[str] = Field(
-        description="HTTP URL for SSRF proxy",
+        description="Proxy URL for HTTP requests to prevent Server-Side Request Forgery (SSRF)",
         default=None,
     )
 
     SSRF_PROXY_HTTPS_URL: Optional[str] = Field(
-        description="HTTPS URL for SSRF proxy",
+        description="Proxy URL for HTTPS requests to prevent Server-Side Request Forgery (SSRF)",
         default=None,
     )
 
 
 class InnerAPIConfig(BaseSettings):
     """
-    Inner API configs
+    Configuration for internal API functionality
     """
 
     INNER_API: bool = Field(
-        description="whether to enable the inner API",
+        description="Enable or disable the internal API",
         default=False,
     )
 
     INNER_API_KEY: Optional[str] = Field(
-        description="The inner API key is used to authenticate the inner API",
+        description="API key for accessing the internal API",
         default=None,
     )
 
 
 class LoggingConfig(BaseSettings):
     """
-    Logging configs
+    Configuration for application logging
     """
 
     LOG_LEVEL: str = Field(
-        description="Log output level, default to INFO. It is recommended to set it to ERROR for production.",
+        description="Logging level, default to INFO. Set to ERROR for production environments.",
         default="INFO",
     )
 
     LOG_FILE: Optional[str] = Field(
-        description="logging output file path",
+        description="File path for log output.",
         default=None,
     )
 
     LOG_FORMAT: str = Field(
-        description="log format",
+        description="Format string for log messages",
         default="%(asctime)s.%(msecs)03d %(levelname)s [%(threadName)s] [%(filename)s:%(lineno)d] - %(message)s",
     )
 
     LOG_DATEFORMAT: Optional[str] = Field(
-        description="log date format",
+        description="Date format string for log timestamps",
         default=None,
     )
 
     LOG_TZ: Optional[str] = Field(
-        description="specify log timezone, eg: America/New_York",
+        description="Timezone for log timestamps (e.g., 'America/New_York')",
         default=None,
     )
 
 
 class ModelLoadBalanceConfig(BaseSettings):
     """
-    Model load balance configs
+    Configuration for model load balancing
     """
 
     MODEL_LB_ENABLED: bool = Field(
-        description="whether to enable model load balancing",
+        description="Enable or disable load balancing for models",
         default=False,
     )
 
 
 class BillingConfig(BaseSettings):
     """
-    Platform Billing Configurations
+    Configuration for platform billing features
     """
 
     BILLING_ENABLED: bool = Field(
-        description="whether to enable billing",
+        description="Enable or disable billing functionality",
         default=False,
     )
 
 
 class UpdateConfig(BaseSettings):
     """
-    Update configs
+    Configuration for application update checks
     """
 
     CHECK_UPDATE_URL: str = Field(
-        description="url for checking updates",
+        description="URL to check for application updates",
         default="https://updates.dify.ai",
     )
 
 
 class WorkflowConfig(BaseSettings):
     """
-    Workflow feature configs
+    Configuration for workflow execution
     """
 
     WORKFLOW_MAX_EXECUTION_STEPS: PositiveInt = Field(
-        description="max execution steps in single workflow execution",
+        description="Maximum number of steps allowed in a single workflow execution",
         default=500,
     )
 
     WORKFLOW_MAX_EXECUTION_TIME: PositiveInt = Field(
-        description="max execution time in seconds in single workflow execution",
+        description="Maximum execution time in seconds for a single workflow",
         default=1200,
     )
 
     WORKFLOW_CALL_MAX_DEPTH: PositiveInt = Field(
-        description="max depth of calling in single workflow execution",
+        description="Maximum allowed depth for nested workflow calls",
         default=5,
     )
 
     MAX_VARIABLE_SIZE: PositiveInt = Field(
-        description="The maximum size in bytes of a variable. default to 5KB.",
+        description="Maximum size in bytes for a single variable in workflows. Default to 5KB.",
         default=5 * 1024,
     )
 
 
 class OAuthConfig(BaseSettings):
     """
-    oauth configs
+    Configuration for OAuth authentication
     """
 
     OAUTH_REDIRECT_PATH: str = Field(
-        description="redirect path for OAuth",
+        description="Redirect path for OAuth authentication callbacks",
         default="/console/api/oauth/authorize",
     )
 
     GITHUB_CLIENT_ID: Optional[str] = Field(
-        description="GitHub client id for OAuth",
+        description="GitHub OAuth client secret",
         default=None,
     )
 
     GITHUB_CLIENT_SECRET: Optional[str] = Field(
-        description="GitHub client secret key for OAuth",
+        description="GitHub OAuth client secret",
         default=None,
     )
 
     GOOGLE_CLIENT_ID: Optional[str] = Field(
-        description="Google client id for OAuth",
+        description="Google OAuth client ID",
         default=None,
     )
 
     GOOGLE_CLIENT_SECRET: Optional[str] = Field(
-        description="Google client secret key for OAuth",
+        description="Google OAuth client secret",
         default=None,
     )
 
 
 class ModerationConfig(BaseSettings):
     """
-    Moderation in app configs.
+    Configuration for content moderation
     """
 
     MODERATION_BUFFER_SIZE: PositiveInt = Field(
-        description="buffer size for moderation",
+        description="Size of the buffer for content moderation processing",
         default=300,
     )
 
 
 class ToolConfig(BaseSettings):
     """
-    Tool configs
+    Configuration for tool management
     """
 
     TOOL_ICON_CACHE_MAX_AGE: PositiveInt = Field(
-        description="max age in seconds for tool icon caching",
+        description="Maximum age in seconds for caching tool icons",
         default=3600,
     )
 
 
 class MailConfig(BaseSettings):
     """
-    Mail Configurations
+    Configuration for email services
     """
 
     MAIL_TYPE: Optional[str] = Field(
-        description="Mail provider type name, default to None, available values are `smtp` and `resend`.",
+        description="Email service provider type ('smtp' or 'resend'), default to None.",
         default=None,
     )
 
     MAIL_DEFAULT_SEND_FROM: Optional[str] = Field(
-        description="default email address for sending from ",
+        description="Default email address to use as the sender",
         default=None,
     )
 
     RESEND_API_KEY: Optional[str] = Field(
-        description="API key for Resend",
+        description="API key for Resend email service",
         default=None,
     )
 
     RESEND_API_URL: Optional[str] = Field(
-        description="API URL for Resend",
+        description="API URL for Resend email service",
         default=None,
     )
 
     SMTP_SERVER: Optional[str] = Field(
-        description="smtp server host",
+        description="SMTP server hostname",
         default=None,
     )
 
     SMTP_PORT: Optional[int] = Field(
-        description="smtp server port",
+        description="SMTP server port number",
         default=465,
     )
 
     SMTP_USERNAME: Optional[str] = Field(
-        description="smtp server username",
+        description="Username for SMTP authentication",
         default=None,
     )
 
     SMTP_PASSWORD: Optional[str] = Field(
-        description="smtp server password",
+        description="Password for SMTP authentication",
         default=None,
     )
 
     SMTP_USE_TLS: bool = Field(
-        description="whether to use TLS connection to smtp server",
+        description="Enable TLS encryption for SMTP connections",
         default=False,
     )
 
     SMTP_OPPORTUNISTIC_TLS: bool = Field(
-        description="whether to use opportunistic TLS connection to smtp server",
+        description="Enable opportunistic TLS for SMTP connections",
         default=False,
     )
 
 
 class RagEtlConfig(BaseSettings):
     """
-    RAG ETL Configurations.
+    Configuration for RAG ETL processes
     """
 
     ETL_TYPE: str = Field(
-        description="RAG ETL type name, default to `dify`, available values are `dify` and `Unstructured`. ",
+        description="RAG ETL type ('dify' or 'Unstructured'), default to 'dify'",
         default="dify",
     )
 
     KEYWORD_DATA_SOURCE_TYPE: str = Field(
-        description="source type for keyword data, default to `database`, available values are `database` .",
+        description="Data source type for keyword extraction"
+        " ('database' or other supported types), default to 'database'",
         default="database",
     )
 
     UNSTRUCTURED_API_URL: Optional[str] = Field(
-        description="API URL for Unstructured",
+        description="API URL for Unstructured.io service",
         default=None,
     )
 
     UNSTRUCTURED_API_KEY: Optional[str] = Field(
-        description="API key for Unstructured",
+        description="API key for Unstructured.io service",
         default=None,
     )
 
 
 class DataSetConfig(BaseSettings):
     """
-    Dataset configs
+    Configuration for dataset management
     """
 
     CLEAN_DAY_SETTING: PositiveInt = Field(
-        description="interval in days for cleaning up dataset",
+        description="Interval in days for dataset cleanup operations",
         default=30,
     )
 
     DATASET_OPERATOR_ENABLED: bool = Field(
-        description="whether to enable dataset operator",
+        description="Enable or disable dataset operator functionality",
         default=False,
     )
 
 
 class WorkspaceConfig(BaseSettings):
     """
-    Workspace configs
+    Configuration for workspace management
     """
 
     INVITE_EXPIRY_HOURS: PositiveInt = Field(
-        description="workspaces invitation expiration in hours",
+        description="Expiration time in hours for workspace invitation links",
         default=72,
     )
 
 
 class IndexingConfig(BaseSettings):
     """
-    Indexing configs.
+    Configuration for indexing operations
     """
 
     INDEXING_MAX_SEGMENTATION_TOKENS_LENGTH: PositiveInt = Field(
-        description="max segmentation token length for indexing",
+        description="Maximum token length for text segmentation during indexing",
         default=1000,
     )
 
 
 class ImageFormatConfig(BaseSettings):
     MULTIMODAL_SEND_IMAGE_FORMAT: str = Field(
-        description="multi model send image format, support base64, url, default is base64",
+        description="Format for sending images in multimodal contexts ('base64' or 'url'), default is base64",
         default="base64",
     )
 
 
 class CeleryBeatConfig(BaseSettings):
     CELERY_BEAT_SCHEDULER_TIME: int = Field(
-        description="the time of the celery scheduler, default to 1 day",
+        description="Interval in days for Celery Beat scheduler execution, default to 1 day",
         default=1,
     )
 
 
 class PositionConfig(BaseSettings):
     POSITION_PROVIDER_PINS: str = Field(
-        description="The heads of model providers",
+        description="Comma-separated list of pinned model providers",
         default="",
     )
 
     POSITION_PROVIDER_INCLUDES: str = Field(
-        description="The included model providers",
+        description="Comma-separated list of included model providers",
         default="",
     )
 
     POSITION_PROVIDER_EXCLUDES: str = Field(
-        description="The excluded model providers",
+        description="Comma-separated list of excluded model providers",
         default="",
     )
 
     POSITION_TOOL_PINS: str = Field(
-        description="The heads of tools",
+        description="Comma-separated list of pinned tools",
         default="",
     )
 
     POSITION_TOOL_INCLUDES: str = Field(
-        description="The included tools",
+        description="Comma-separated list of included tools",
         default="",
     )
 
     POSITION_TOOL_EXCLUDES: str = Field(
-        description="The excluded tools",
+        description="Comma-separated list of excluded tools",
         default="",
     )
 

api/configs/feature/hosted_service/__init__.py

@@ -6,31 +6,31 @@ from pydantic_settings import BaseSettings
 
 class HostedOpenAiConfig(BaseSettings):
     """
-    Hosted OpenAI service config
+    Configuration for hosted OpenAI service
     """
 
     HOSTED_OPENAI_API_KEY: Optional[str] = Field(
-        description="",
+        description="API key for hosted OpenAI service",
         default=None,
     )
 
     HOSTED_OPENAI_API_BASE: Optional[str] = Field(
-        description="",
+        description="Base URL for hosted OpenAI API",
         default=None,
     )
 
     HOSTED_OPENAI_API_ORGANIZATION: Optional[str] = Field(
-        description="",
+        description="Organization ID for hosted OpenAI service",
         default=None,
     )
 
     HOSTED_OPENAI_TRIAL_ENABLED: bool = Field(
-        description="",
+        description="Enable trial access to hosted OpenAI service",
         default=False,
     )
 
     HOSTED_OPENAI_TRIAL_MODELS: str = Field(
-        description="",
+        description="Comma-separated list of available models for trial access",
         default="gpt-3.5-turbo,"
         "gpt-3.5-turbo-1106,"
         "gpt-3.5-turbo-instruct,"
@@ -42,17 +42,17 @@ class HostedOpenAiConfig(BaseSettings):
     )
 
     HOSTED_OPENAI_QUOTA_LIMIT: NonNegativeInt = Field(
-        description="",
+        description="Quota limit for hosted OpenAI service usage",
         default=200,
     )
 
     HOSTED_OPENAI_PAID_ENABLED: bool = Field(
-        description="",
+        description="Enable paid access to hosted OpenAI service",
         default=False,
     )
 
     HOSTED_OPENAI_PAID_MODELS: str = Field(
-        description="",
+        description="Comma-separated list of available models for paid access",
         default="gpt-4,"
         "gpt-4-turbo-preview,"
         "gpt-4-turbo-2024-04-09,"
@@ -71,124 +71,122 @@ class HostedOpenAiConfig(BaseSettings):
 
 class HostedAzureOpenAiConfig(BaseSettings):
     """
-    Hosted OpenAI service config
+    Configuration for hosted Azure OpenAI service
     """
 
     HOSTED_AZURE_OPENAI_ENABLED: bool = Field(
-        description="",
+        description="Enable hosted Azure OpenAI service",
         default=False,
     )
 
     HOSTED_AZURE_OPENAI_API_KEY: Optional[str] = Field(
-        description="",
+        description="API key for hosted Azure OpenAI service",
         default=None,
     )
 
     HOSTED_AZURE_OPENAI_API_BASE: Optional[str] = Field(
-        description="",
+        description="Base URL for hosted Azure OpenAI API",
         default=None,
     )
 
     HOSTED_AZURE_OPENAI_QUOTA_LIMIT: NonNegativeInt = Field(
-        description="",
+        description="Quota limit for hosted Azure OpenAI service usage",
         default=200,
     )
 
 
 class HostedAnthropicConfig(BaseSettings):
     """
-    Hosted Azure OpenAI service config
+    Configuration for hosted Anthropic service
     """
 
     HOSTED_ANTHROPIC_API_BASE: Optional[str] = Field(
-        description="",
+        description="Base URL for hosted Anthropic API",
         default=None,
     )
 
     HOSTED_ANTHROPIC_API_KEY: Optional[str] = Field(
-        description="",
+        description="API key for hosted Anthropic service",
         default=None,
     )
 
     HOSTED_ANTHROPIC_TRIAL_ENABLED: bool = Field(
-        description="",
+        description="Enable trial access to hosted Anthropic service",
         default=False,
     )
 
     HOSTED_ANTHROPIC_QUOTA_LIMIT: NonNegativeInt = Field(
-        description="",
+        description="Quota limit for hosted Anthropic service usage",
         default=600000,
     )
 
     HOSTED_ANTHROPIC_PAID_ENABLED: bool = Field(
-        description="",
+        description="Enable paid access to hosted Anthropic service",
         default=False,
     )
 
 
 class HostedMinmaxConfig(BaseSettings):
     """
-    Hosted Minmax service config
+    Configuration for hosted Minmax service
     """
 
     HOSTED_MINIMAX_ENABLED: bool = Field(
-        description="",
+        description="Enable hosted Minmax service",
         default=False,
     )
 
 
 class HostedSparkConfig(BaseSettings):
     """
-    Hosted Spark service config
+    Configuration for hosted Spark service
     """
 
     HOSTED_SPARK_ENABLED: bool = Field(
-        description="",
+        description="Enable hosted Spark service",
         default=False,
     )
 
 
 class HostedZhipuAIConfig(BaseSettings):
     """
-    Hosted Minmax service config
+    Configuration for hosted ZhipuAI service
     """
 
     HOSTED_ZHIPUAI_ENABLED: bool = Field(
-        description="",
+        description="Enable hosted ZhipuAI service",
         default=False,
     )
 
 
 class HostedModerationConfig(BaseSettings):
     """
-    Hosted Moderation service config
+    Configuration for hosted Moderation service
     """
 
     HOSTED_MODERATION_ENABLED: bool = Field(
-        description="",
+        description="Enable hosted Moderation service",
         default=False,
     )
 
     HOSTED_MODERATION_PROVIDERS: str = Field(
-        description="",
+        description="Comma-separated list of moderation providers",
         default="",
     )
 
 
 class HostedFetchAppTemplateConfig(BaseSettings):
     """
-    Hosted Moderation service config
+    Configuration for fetching app templates
     """
 
     HOSTED_FETCH_APP_TEMPLATES_MODE: str = Field(
-        description="the mode for fetching app templates,"
-        " default to remote,"
-        " available values: remote, db, builtin",
+        description="Mode for fetching app templates: remote, db, or builtin" " default to remote,",
         default="remote",
     )
 
     HOSTED_FETCH_APP_TEMPLATES_REMOTE_DOMAIN: str = Field(
-        description="the domain for fetching remote app templates",
+        description="Domain for fetching remote app templates",
         default="https://tmpl.dify.ai",
     )
 

api/configs/middleware/__init__.py

@@ -8,6 +8,7 @@ from configs.middleware.cache.redis_config import RedisConfig
 from configs.middleware.storage.aliyun_oss_storage_config import AliyunOSSStorageConfig
 from configs.middleware.storage.amazon_s3_storage_config import S3StorageConfig
 from configs.middleware.storage.azure_blob_storage_config import AzureBlobStorageConfig
+from configs.middleware.storage.baidu_obs_storage_config import BaiduOBSStorageConfig
 from configs.middleware.storage.google_cloud_storage_config import GoogleCloudStorageConfig
 from configs.middleware.storage.huawei_obs_storage_config import HuaweiCloudOBSStorageConfig
 from configs.middleware.storage.oci_storage_config import OCIStorageConfig
@@ -31,70 +32,71 @@ from configs.middleware.vdb.weaviate_config import WeaviateConfig
 
 class StorageConfig(BaseSettings):
     STORAGE_TYPE: str = Field(
-        description="storage type,"
-        " default to `local`,"
-        " available values are `local`, `s3`, `azure-blob`, `aliyun-oss`, `google-storage`.",
+        description="Type of storage to use."
+        " Options: 'local', 's3', 'azure-blob', 'aliyun-oss', 'google-storage'. Default is 'local'.",
         default="local",
     )
 
     STORAGE_LOCAL_PATH: str = Field(
-        description="local storage path",
+        description="Path for local storage when STORAGE_TYPE is set to 'local'.",
         default="storage",
     )
 
 
 class VectorStoreConfig(BaseSettings):
     VECTOR_STORE: Optional[str] = Field(
-        description="vector store type",
+        description="Type of vector store to use for efficient similarity search."
+        " Set to None if not using a vector store.",
         default=None,
     )
 
 
 class KeywordStoreConfig(BaseSettings):
     KEYWORD_STORE: str = Field(
-        description="keyword store type",
+        description="Method for keyword extraction and storage."
+        " Default is 'jieba', a Chinese text segmentation library.",
         default="jieba",
     )
 
 
 class DatabaseConfig:
     DB_HOST: str = Field(
-        description="db host",
+        description="Hostname or IP address of the database server.",
         default="localhost",
     )
 
     DB_PORT: PositiveInt = Field(
-        description="db port",
+        description="Port number for database connection.",
         default=5432,
     )
 
     DB_USERNAME: str = Field(
-        description="db username",
+        description="Username for database authentication.",
         default="postgres",
     )
 
     DB_PASSWORD: str = Field(
-        description="db password",
+        description="Password for database authentication.",
         default="",
     )
 
     DB_DATABASE: str = Field(
-        description="db database",
+        description="Name of the database to connect to.",
         default="dify",
     )
 
     DB_CHARSET: str = Field(
-        description="db charset",
+        description="Character set for database connection.",
         default="",
     )
 
     DB_EXTRAS: str = Field(
-        description="db extras options. Example: keepalives_idle=60&keepalives=1",
+        description="Additional database connection parameters. Example: 'keepalives_idle=60&keepalives=1'",
         default="",
     )
 
     SQLALCHEMY_DATABASE_URI_SCHEME: str = Field(
-        description="db uri scheme",
+        description="Database URI scheme for SQLAlchemy connection.",
         default="postgresql",
     )
 
@@ -112,27 +114,27 @@ class DatabaseConfig:
         )
 
     SQLALCHEMY_POOL_SIZE: NonNegativeInt = Field(
-        description="pool size of SqlAlchemy",
+        description="Maximum number of database connections in the pool.",
         default=30,
     )
 
     SQLALCHEMY_MAX_OVERFLOW: NonNegativeInt = Field(
-        description="max overflows for SqlAlchemy",
+        description="Maximum number of connections that can be created beyond the pool_size.",
         default=10,
     )
 
     SQLALCHEMY_POOL_RECYCLE: NonNegativeInt = Field(
-        description="SqlAlchemy pool recycle",
+        description="Number of seconds after which a connection is automatically recycled.",
         default=3600,
     )
 
     SQLALCHEMY_POOL_PRE_PING: bool = Field(
-        description="whether to enable pool pre-ping in SqlAlchemy",
+        description="If True, enables connection pool pre-ping feature to check connections.",
         default=False,
     )
 
     SQLALCHEMY_ECHO: bool | str = Field(
-        description="whether to enable SqlAlchemy echo",
+        description="If True, SQLAlchemy will log all SQL statements.",
         default=False,
     )
 
@@ -150,27 +152,27 @@ class DatabaseConfig:
 
 class CeleryConfig(DatabaseConfig):
     CELERY_BACKEND: str = Field(
-        description="Celery backend, available values are `database`, `redis`",
+        description="Backend for Celery task results. Options: 'database', 'redis'.",
         default="database",
     )
 
     CELERY_BROKER_URL: Optional[str] = Field(
-        description="CELERY_BROKER_URL",
+        description="URL of the message broker for Celery tasks.",
         default=None,
     )
 
     CELERY_USE_SENTINEL: Optional[bool] = Field(
-        description="Whether to use Redis Sentinel mode",
+        description="Whether to use Redis Sentinel for high availability.",
         default=False,
     )
 
     CELERY_SENTINEL_MASTER_NAME: Optional[str] = Field(
-        description="Redis Sentinel master name",
+        description="Name of the Redis Sentinel master.",
         default=None,
     )
 
     CELERY_SENTINEL_SOCKET_TIMEOUT: Optional[PositiveFloat] = Field(
-        description="Redis Sentinel socket timeout",
+        description="Timeout for Redis Sentinel socket operations in seconds.",
         default=0.1,
     )
 
@@ -199,12 +201,13 @@ class MiddlewareConfig(
     StorageConfig,
     AliyunOSSStorageConfig,
     AzureBlobStorageConfig,
+    BaiduOBSStorageConfig,
     GoogleCloudStorageConfig,
-    TencentCloudCOSStorageConfig,
     HuaweiCloudOBSStorageConfig,
-    VolcengineTOSStorageConfig,
-    S3StorageConfig,
     OCIStorageConfig,
+    S3StorageConfig,
+    TencentCloudCOSStorageConfig,
+    VolcengineTOSStorageConfig,
     # configs of vdb and vdb providers
     VectorStoreConfig,
     AnalyticdbConfig,

api/configs/middleware/cache/redis_config.py

@@ -6,65 +6,65 @@ from pydantic_settings import BaseSettings
 
 class RedisConfig(BaseSettings):
     """
-    Redis configs
+    Configuration settings for Redis connection
     """
 
     REDIS_HOST: str = Field(
-        description="Redis host",
+        description="Hostname or IP address of the Redis server",
         default="localhost",
     )
 
     REDIS_PORT: PositiveInt = Field(
-        description="Redis port",
+        description="Port number on which the Redis server is listening",
         default=6379,
     )
 
     REDIS_USERNAME: Optional[str] = Field(
-        description="Redis username",
+        description="Username for Redis authentication (if required)",
         default=None,
     )
 
     REDIS_PASSWORD: Optional[str] = Field(
-        description="Redis password",
+        description="Password for Redis authentication (if required)",
         default=None,
     )
 
     REDIS_DB: NonNegativeInt = Field(
-        description="Redis database id, default to 0",
+        description="Redis database number to use (0-15)",
         default=0,
     )
 
     REDIS_USE_SSL: bool = Field(
-        description="whether to use SSL for Redis connection",
+        description="Enable SSL/TLS for the Redis connection",
         default=False,
     )
 
     REDIS_USE_SENTINEL: Optional[bool] = Field(
-        description="Whether to use Redis Sentinel mode",
+        description="Enable Redis Sentinel mode for high availability",
         default=False,
     )
 
     REDIS_SENTINELS: Optional[str] = Field(
-        description="Redis Sentinel nodes",
+        description="Comma-separated list of Redis Sentinel nodes (host:port)",
         default=None,
     )
 
     REDIS_SENTINEL_SERVICE_NAME: Optional[str] = Field(
-        description="Redis Sentinel service name",
+        description="Name of the Redis Sentinel service to monitor",
         default=None,
     )
 
     REDIS_SENTINEL_USERNAME: Optional[str] = Field(
-        description="Redis Sentinel username",
+        description="Username for Redis Sentinel authentication (if required)",
         default=None,
     )
 
     REDIS_SENTINEL_PASSWORD: Optional[str] = Field(
-        description="Redis Sentinel password",
+        description="Password for Redis Sentinel authentication (if required)",
         default=None,
     )
 
     REDIS_SENTINEL_SOCKET_TIMEOUT: Optional[PositiveFloat] = Field(
-        description="Redis Sentinel socket timeout",
+        description="Socket timeout in seconds for Redis Sentinel connections",
         default=0.1,
     )

api/configs/middleware/storage/aliyun_oss_storage_config.py

@@ -6,40 +6,40 @@ from pydantic_settings import BaseSettings
 
 class AliyunOSSStorageConfig(BaseSettings):
     """
-    Aliyun storage configs
+    Configuration settings for Aliyun Object Storage Service (OSS)
     """
 
     ALIYUN_OSS_BUCKET_NAME: Optional[str] = Field(
-        description="Aliyun OSS bucket name",
+        description="Name of the Aliyun OSS bucket to store and retrieve objects",
         default=None,
     )
 
     ALIYUN_OSS_ACCESS_KEY: Optional[str] = Field(
-        description="Aliyun OSS access key",
+        description="Access key ID for authenticating with Aliyun OSS",
         default=None,
     )
 
     ALIYUN_OSS_SECRET_KEY: Optional[str] = Field(
-        description="Aliyun OSS secret key",
+        description="Secret access key for authenticating with Aliyun OSS",
         default=None,
     )
 
     ALIYUN_OSS_ENDPOINT: Optional[str] = Field(
-        description="Aliyun OSS endpoint URL",
+        description="URL of the Aliyun OSS endpoint for your chosen region",
         default=None,
     )
 
     ALIYUN_OSS_REGION: Optional[str] = Field(
-        description="Aliyun OSS region",
+        description="Aliyun OSS region where your bucket is located (e.g., 'oss-cn-hangzhou')",
         default=None,
     )
 
     ALIYUN_OSS_AUTH_VERSION: Optional[str] = Field(
-        description="Aliyun OSS authentication version",
+        description="Version of the authentication protocol to use with Aliyun OSS (e.g., 'v4')",
         default=None,
     )
 
     ALIYUN_OSS_PATH: Optional[str] = Field(
-        description="Aliyun OSS path",
+        description="Base path within the bucket to store objects (e.g., 'my-app-data/')",
         default=None,
     )

api/configs/middleware/storage/amazon_s3_storage_config.py

@@ -6,40 +6,40 @@ from pydantic_settings import BaseSettings
 
 class S3StorageConfig(BaseSettings):
     """
-    S3 storage configs
+    Configuration settings for S3-compatible object storage
     """
 
     S3_ENDPOINT: Optional[str] = Field(
-        description="S3 storage endpoint",
+        description="URL of the S3-compatible storage endpoint (e.g., 'https://s3.amazonaws.com')",
         default=None,
     )
 
     S3_REGION: Optional[str] = Field(
-        description="S3 storage region",
+        description="Region where the S3 bucket is located (e.g., 'us-east-1')",
         default=None,
     )
 
     S3_BUCKET_NAME: Optional[str] = Field(
-        description="S3 storage bucket name",
+        description="Name of the S3 bucket to store and retrieve objects",
         default=None,
     )
 
     S3_ACCESS_KEY: Optional[str] = Field(
-        description="S3 storage access key",
+        description="Access key ID for authenticating with the S3 service",
         default=None,
     )
 
     S3_SECRET_KEY: Optional[str] = Field(
-        description="S3 storage secret key",
+        description="Secret access key for authenticating with the S3 service",
         default=None,
     )
 
     S3_ADDRESS_STYLE: str = Field(
-        description="S3 storage address style",
+        description="S3 addressing style: 'auto', 'path', or 'virtual'",
         default="auto",
     )
 
     S3_USE_AWS_MANAGED_IAM: bool = Field(
-        description="whether to use aws managed IAM for S3",
+        description="Use AWS managed IAM roles for authentication instead of access/secret keys",
         default=False,
     )

api/configs/middleware/storage/azure_blob_storage_config.py

@@ -6,25 +6,25 @@ from pydantic_settings import BaseSettings
 
 class AzureBlobStorageConfig(BaseSettings):
     """
-    Azure Blob storage configs
+    Configuration settings for Azure Blob Storage
     """
 
     AZURE_BLOB_ACCOUNT_NAME: Optional[str] = Field(
-        description="Azure Blob account name",
+        description="Name of the Azure Storage account (e.g., 'mystorageaccount')",
         default=None,
     )
 
     AZURE_BLOB_ACCOUNT_KEY: Optional[str] = Field(
-        description="Azure Blob account key",
+        description="Access key for authenticating with the Azure Storage account",
         default=None,
     )
 
     AZURE_BLOB_CONTAINER_NAME: Optional[str] = Field(
-        description="Azure Blob container name",
+        description="Name of the Azure Blob container to store and retrieve objects",
         default=None,
     )
 
     AZURE_BLOB_ACCOUNT_URL: Optional[str] = Field(
-        description="Azure Blob account URL",
+        description="URL of the Azure Blob storage endpoint (e.g., 'https://mystorageaccount.blob.core.windows.net')",
         default=None,
     )

api/configs/middleware/storage/baidu_obs_storage_config.py

@@ -0,0 +1,29 @@
+from typing import Optional
+
+from pydantic import BaseModel, Field
+
+
+class BaiduOBSStorageConfig(BaseModel):
+    """
+    Configuration settings for Baidu Object Storage Service (OBS)
+    """
+
+    BAIDU_OBS_BUCKET_NAME: Optional[str] = Field(
+        description="Name of the Baidu OBS bucket to store and retrieve objects (e.g., 'my-obs-bucket')",
+        default=None,
+    )
+
+    BAIDU_OBS_ACCESS_KEY: Optional[str] = Field(
+        description="Access Key ID for authenticating with Baidu OBS",
+        default=None,
+    )
+
+    BAIDU_OBS_SECRET_KEY: Optional[str] = Field(
+        description="Secret Access Key for authenticating with Baidu OBS",
+        default=None,
+    )
+
+    BAIDU_OBS_ENDPOINT: Optional[str] = Field(
+        description="URL of the Baidu OSS endpoint for your chosen region (e.g., 'https://.bj.bcebos.com')",
+        default=None,
+    )

api/configs/middleware/storage/google_cloud_storage_config.py

@@ -6,15 +6,15 @@ from pydantic_settings import BaseSettings
 
 class GoogleCloudStorageConfig(BaseSettings):
     """
-    Google Cloud storage configs
+    Configuration settings for Google Cloud Storage
     """
 
     GOOGLE_STORAGE_BUCKET_NAME: Optional[str] = Field(
-        description="Google Cloud storage bucket name",
+        description="Name of the Google Cloud Storage bucket to store and retrieve objects (e.g., 'my-gcs-bucket')",
         default=None,
     )
 
     GOOGLE_STORAGE_SERVICE_ACCOUNT_JSON_BASE64: Optional[str] = Field(
-        description="Google Cloud storage service account json base64",
+        description="Base64-encoded JSON key file for Google Cloud service account authentication",
         default=None,
     )

api/configs/middleware/storage/huawei_obs_storage_config.py

@@ -5,25 +5,25 @@ from pydantic import BaseModel, Field
 
 class HuaweiCloudOBSStorageConfig(BaseModel):
     """
-    Huawei Cloud OBS storage configs
+    Configuration settings for Huawei Cloud Object Storage Service (OBS)
     """
 
     HUAWEI_OBS_BUCKET_NAME: Optional[str] = Field(
-        description="Huawei Cloud OBS bucket name",
+        description="Name of the Huawei Cloud OBS bucket to store and retrieve objects (e.g., 'my-obs-bucket')",
         default=None,
     )
 
     HUAWEI_OBS_ACCESS_KEY: Optional[str] = Field(
-        description="Huawei Cloud OBS Access key",
+        description="Access Key ID for authenticating with Huawei Cloud OBS",
         default=None,
     )
 
     HUAWEI_OBS_SECRET_KEY: Optional[str] = Field(
-        description="Huawei Cloud OBS Secret key",
+        description="Secret Access Key for authenticating with Huawei Cloud OBS",
         default=None,
     )
 
     HUAWEI_OBS_SERVER: Optional[str] = Field(
-        description="Huawei Cloud OBS server URL",
+        description="Endpoint URL for Huawei Cloud OBS (e.g., 'https://obs.cn-north-4.myhuaweicloud.com')",
         default=None,
     )

api/configs/middleware/storage/oci_storage_config.py

@@ -6,30 +6,30 @@ from pydantic_settings import BaseSettings
 
 class OCIStorageConfig(BaseSettings):
     """
-    OCI storage configs
+    Configuration settings for Oracle Cloud Infrastructure (OCI) Object Storage
     """
 
     OCI_ENDPOINT: Optional[str] = Field(
-        description="OCI storage endpoint",
+        description="URL of the OCI Object Storage endpoint (e.g., 'https://objectstorage.us-phoenix-1.oraclecloud.com')",
         default=None,
     )
 
     OCI_REGION: Optional[str] = Field(
-        description="OCI storage region",
+        description="OCI region where the bucket is located (e.g., 'us-phoenix-1')",
         default=None,
     )
 
     OCI_BUCKET_NAME: Optional[str] = Field(
-        description="OCI storage bucket name",
+        description="Name of the OCI Object Storage bucket to store and retrieve objects (e.g., 'my-oci-bucket')",
         default=None,
     )
 
     OCI_ACCESS_KEY: Optional[str] = Field(
-        description="OCI storage access key",
+        description="Access key (also known as API key) for authenticating with OCI Object Storage",
         default=None,
     )
 
     OCI_SECRET_KEY: Optional[str] = Field(
-        description="OCI storage secret key",
+        description="Secret key associated with the access key for authenticating with OCI Object Storage",
         default=None,
     )

api/configs/middleware/storage/tencent_cos_storage_config.py

@@ -6,30 +6,30 @@ from pydantic_settings import BaseSettings
 
 class TencentCloudCOSStorageConfig(BaseSettings):
     """
-    Tencent Cloud COS storage configs
+    Configuration settings for Tencent Cloud Object Storage (COS)
     """
 
     TENCENT_COS_BUCKET_NAME: Optional[str] = Field(
-        description="Tencent Cloud COS bucket name",
+        description="Name of the Tencent Cloud COS bucket to store and retrieve objects",
         default=None,
     )
 
     TENCENT_COS_REGION: Optional[str] = Field(
-        description="Tencent Cloud COS region",
+        description="Tencent Cloud region where the COS bucket is located (e.g., 'ap-guangzhou')",
         default=None,
     )
 
     TENCENT_COS_SECRET_ID: Optional[str] = Field(
-        description="Tencent Cloud COS secret id",
+        description="SecretId for authenticating with Tencent Cloud COS (part of API credentials)",
         default=None,
     )
 
     TENCENT_COS_SECRET_KEY: Optional[str] = Field(
-        description="Tencent Cloud COS secret key",
+        description="SecretKey for authenticating with Tencent Cloud COS (part of API credentials)",
         default=None,
     )
 
     TENCENT_COS_SCHEME: Optional[str] = Field(
-        description="Tencent Cloud COS scheme",
+        description="Protocol scheme for COS requests: 'https' (recommended) or 'http'",
         default=None,
     )

api/configs/middleware/storage/volcengine_tos_storage_config.py

@@ -5,30 +5,30 @@ from pydantic import BaseModel, Field
 
 class VolcengineTOSStorageConfig(BaseModel):
     """
-    Volcengine tos storage configs
+    Configuration settings for Volcengine Tinder Object Storage (TOS)
     """
 
     VOLCENGINE_TOS_BUCKET_NAME: Optional[str] = Field(
-        description="Volcengine TOS Bucket Name",
+        description="Name of the Volcengine TOS bucket to store and retrieve objects (e.g., 'my-tos-bucket')",
         default=None,
     )
 
     VOLCENGINE_TOS_ACCESS_KEY: Optional[str] = Field(
-        description="Volcengine TOS Access Key",
+        description="Access Key ID for authenticating with Volcengine TOS",
         default=None,
     )
 
     VOLCENGINE_TOS_SECRET_KEY: Optional[str] = Field(
-        description="Volcengine TOS Secret Key",
+        description="Secret Access Key for authenticating with Volcengine TOS",
         default=None,
     )
 
     VOLCENGINE_TOS_ENDPOINT: Optional[str] = Field(
-        description="Volcengine TOS Endpoint URL",
+        description="URL of the Volcengine TOS endpoint (e.g., 'https://tos-cn-beijing.volces.com')",
         default=None,
     )
 
     VOLCENGINE_TOS_REGION: Optional[str] = Field(
-        description="Volcengine TOS Region",
+        description="Volcengine region where the TOS bucket is located (e.g., 'cn-beijing')",
         default=None,
     )

api/configs/middleware/vdb/analyticdb_config.py

@@ -5,33 +5,38 @@ from pydantic import BaseModel, Field
 
 class AnalyticdbConfig(BaseModel):
     """
-    Configuration for connecting to AnalyticDB.
+    Configuration for connecting to Alibaba Cloud AnalyticDB for PostgreSQL.
     Refer to the following documentation for details on obtaining credentials:
     https://www.alibabacloud.com/help/en/analyticdb-for-postgresql/getting-started/create-an-instance-instances-with-vector-engine-optimization-enabled
     """
 
     ANALYTICDB_KEY_ID: Optional[str] = Field(
-        default=None, description="The Access Key ID provided by Alibaba Cloud for authentication."
+        default=None, description="The Access Key ID provided by Alibaba Cloud for API authentication."
     )
     ANALYTICDB_KEY_SECRET: Optional[str] = Field(
-        default=None, description="The Secret Access Key corresponding to the Access Key ID for secure access."
+        default=None, description="The Secret Access Key corresponding to the Access Key ID for secure API access."
     )
     ANALYTICDB_REGION_ID: Optional[str] = Field(
-        default=None, description="The region where the AnalyticDB instance is deployed (e.g., 'cn-hangzhou')."
+        default=None,
+        description="The region where the AnalyticDB instance is deployed (e.g., 'cn-hangzhou', 'ap-southeast-1').",
     )
     ANALYTICDB_INSTANCE_ID: Optional[str] = Field(
         default=None,
-        description="The unique identifier of the AnalyticDB instance you want to connect to (e.g., 'gp-ab123456')..",
+        description="The unique identifier of the AnalyticDB instance you want to connect to.",
     )
     ANALYTICDB_ACCOUNT: Optional[str] = Field(
-        default=None, description="The account name used to log in to the AnalyticDB instance."
+        default=None,
+        description="The account name used to log in to the AnalyticDB instance"
+        " (usually the initial account created with the instance).",
     )
     ANALYTICDB_PASSWORD: Optional[str] = Field(
-        default=None, description="The password associated with the AnalyticDB account for authentication."
+        default=None, description="The password associated with the AnalyticDB account for database authentication."
     )
     ANALYTICDB_NAMESPACE: Optional[str] = Field(
-        default=None, description="The namespace within AnalyticDB for schema isolation."
+        default=None, description="The namespace within AnalyticDB for schema isolation (if using namespace feature)."
     )
     ANALYTICDB_NAMESPACE_PASSWORD: Optional[str] = Field(
-        default=None, description="The password for accessing the specified namespace within the AnalyticDB instance."
+        default=None,
+        description="The password for accessing the specified namespace within the AnalyticDB instance"
+        " (if namespace feature is enabled).",
     )

api/configs/middleware/vdb/chroma_config.py

@@ -6,35 +6,35 @@ from pydantic_settings import BaseSettings
 
 class ChromaConfig(BaseSettings):
     """
-    Chroma configs
+    Configuration settings for Chroma vector database
     """
 
     CHROMA_HOST: Optional[str] = Field(
-        description="Chroma host",
+        description="Hostname or IP address of the Chroma server (e.g., 'localhost' or '192.168.1.100')",
         default=None,
     )
 
     CHROMA_PORT: PositiveInt = Field(
-        description="Chroma port",
+        description="Port number on which the Chroma server is listening (default is 8000)",
         default=8000,
     )
 
     CHROMA_TENANT: Optional[str] = Field(
-        description="Chroma database",
+        description="Tenant identifier for multi-tenancy support in Chroma",
         default=None,
     )
 
     CHROMA_DATABASE: Optional[str] = Field(
-        description="Chroma database",
+        description="Name of the Chroma database to connect to",
         default=None,
     )
 
     CHROMA_AUTH_PROVIDER: Optional[str] = Field(
-        description="Chroma authentication provider",
+        description="Authentication provider for Chroma (e.g., 'basic', 'token', or a custom provider)",
         default=None,
     )
 
     CHROMA_AUTH_CREDENTIALS: Optional[str] = Field(
-        description="Chroma authentication credentials",
+        description="Authentication credentials for Chroma (format depends on the auth provider)",
         default=None,
     )

api/configs/middleware/vdb/elasticsearch_config.py

@@ -6,25 +6,25 @@ from pydantic_settings import BaseSettings
 
 class ElasticsearchConfig(BaseSettings):
     """
-    Elasticsearch configs
+    Configuration settings for Elasticsearch
     """
 
     ELASTICSEARCH_HOST: Optional[str] = Field(
-        description="Elasticsearch host",
+        description="Hostname or IP address of the Elasticsearch server (e.g., 'localhost' or '192.168.1.100')",
         default="127.0.0.1",
     )
 
     ELASTICSEARCH_PORT: PositiveInt = Field(
-        description="Elasticsearch port",
+        description="Port number on which the Elasticsearch server is listening (default is 9200)",
         default=9200,
     )
 
     ELASTICSEARCH_USERNAME: Optional[str] = Field(
-        description="Elasticsearch username",
+        description="Username for authenticating with Elasticsearch (default is 'elastic')",
         default="elastic",
     )
 
     ELASTICSEARCH_PASSWORD: Optional[str] = Field(
-        description="Elasticsearch password",
+        description="Password for authenticating with Elasticsearch (default is 'elastic')",
         default="elastic",
     )

api/configs/middleware/vdb/milvus_config.py

@@ -6,30 +6,30 @@ from pydantic_settings import BaseSettings
 
 class MilvusConfig(BaseSettings):
     """
-    Milvus configs
+    Configuration settings for Milvus vector database
     """
 
     MILVUS_URI: Optional[str] = Field(
-        description="Milvus uri",
+        description="URI for connecting to the Milvus server (e.g., 'http://localhost:19530' or 'https://milvus-instance.example.com:19530')",
         default="http://127.0.0.1:19530",
     )
 
     MILVUS_TOKEN: Optional[str] = Field(
-        description="Milvus token",
+        description="Authentication token for Milvus, if token-based authentication is enabled",
         default=None,
     )
 
     MILVUS_USER: Optional[str] = Field(
-        description="Milvus user",
+        description="Username for authenticating with Milvus, if username/password authentication is enabled",
         default=None,
     )
 
     MILVUS_PASSWORD: Optional[str] = Field(
-        description="Milvus password",
+        description="Password for authenticating with Milvus, if username/password authentication is enabled",
         default=None,
     )
 
     MILVUS_DATABASE: str = Field(
-        description="Milvus database, default to `default`",
+        description="Name of the Milvus database to connect to (default is 'default')",
         default="default",
     )

api/configs/middleware/vdb/myscale_config.py

@@ -3,35 +3,35 @@ from pydantic import BaseModel, Field, PositiveInt
 
 class MyScaleConfig(BaseModel):
     """
-    MyScale configs
+    Configuration settings for MyScale vector database
     """
 
     MYSCALE_HOST: str = Field(
-        description="MyScale host",
+        description="Hostname or IP address of the MyScale server (e.g., 'localhost' or 'myscale.example.com')",
         default="localhost",
     )
 
     MYSCALE_PORT: PositiveInt = Field(
-        description="MyScale port",
+        description="Port number on which the MyScale server is listening (default is 8123)",
         default=8123,
     )
 
     MYSCALE_USER: str = Field(
-        description="MyScale user",
+        description="Username for authenticating with MyScale (default is 'default')",
         default="default",
     )
 
     MYSCALE_PASSWORD: str = Field(
-        description="MyScale password",
+        description="Password for authenticating with MyScale (default is an empty string)",
         default="",
     )
 
     MYSCALE_DATABASE: str = Field(
-        description="MyScale database name",
+        description="Name of the MyScale database to connect to (default is 'default')",
         default="default",
     )
 
     MYSCALE_FTS_PARAMS: str = Field(
-        description="MyScale fts index parameters",
+        description="Additional parameters for MyScale Full Text Search index)",
         default="",
     )

api/configs/middleware/vdb/opensearch_config.py

@@ -6,30 +6,30 @@ from pydantic_settings import BaseSettings
 
 class OpenSearchConfig(BaseSettings):
     """
-    OpenSearch configs
+    Configuration settings for OpenSearch
     """
 
     OPENSEARCH_HOST: Optional[str] = Field(
-        description="OpenSearch host",
+        description="Hostname or IP address of the OpenSearch server (e.g., 'localhost' or 'opensearch.example.com')",
         default=None,
     )
 
     OPENSEARCH_PORT: PositiveInt = Field(
-        description="OpenSearch port",
+        description="Port number on which the OpenSearch server is listening (default is 9200)",
         default=9200,
     )
 
     OPENSEARCH_USER: Optional[str] = Field(
-        description="OpenSearch user",
+        description="Username for authenticating with OpenSearch",
         default=None,
     )
 
     OPENSEARCH_PASSWORD: Optional[str] = Field(
-        description="OpenSearch password",
+        description="Password for authenticating with OpenSearch",
         default=None,
     )
 
     OPENSEARCH_SECURE: bool = Field(
-        description="whether to use SSL connection for OpenSearch",
+        description="Whether to use SSL/TLS encrypted connection for OpenSearch (True for HTTPS, False for HTTP)",
         default=False,
     )

api/configs/middleware/vdb/oracle_config.py

@@ -6,30 +6,30 @@ from pydantic_settings import BaseSettings
 
 class OracleConfig(BaseSettings):
     """
-    ORACLE configs
+    Configuration settings for Oracle database
     """
 
     ORACLE_HOST: Optional[str] = Field(
-        description="ORACLE host",
+        description="Hostname or IP address of the Oracle database server (e.g., 'localhost' or 'oracle.example.com')",
         default=None,
     )
 
     ORACLE_PORT: Optional[PositiveInt] = Field(
-        description="ORACLE port",
+        description="Port number on which the Oracle database server is listening (default is 1521)",
         default=1521,
     )
 
     ORACLE_USER: Optional[str] = Field(
-        description="ORACLE user",
+        description="Username for authenticating with the Oracle database",
         default=None,
     )
 
     ORACLE_PASSWORD: Optional[str] = Field(
-        description="ORACLE password",
+        description="Password for authenticating with the Oracle database",
         default=None,
     )
 
     ORACLE_DATABASE: Optional[str] = Field(
-        description="ORACLE database",
+        description="Name of the Oracle database or service to connect to (e.g., 'ORCL' or 'pdborcl')",
         default=None,
     )

api/configs/middleware/vdb/pgvector_config.py

@@ -6,30 +6,40 @@ from pydantic_settings import BaseSettings
 
 class PGVectorConfig(BaseSettings):
     """
-    PGVector configs
+    Configuration settings for PGVector (PostgreSQL with vector extension)
     """
 
     PGVECTOR_HOST: Optional[str] = Field(
-        description="PGVector host",
+        description="Hostname or IP address of the PostgreSQL server with PGVector extension (e.g., 'localhost')",
         default=None,
     )
 
     PGVECTOR_PORT: Optional[PositiveInt] = Field(
-        description="PGVector port",
+        description="Port number on which the PostgreSQL server is listening (default is 5433)",
         default=5433,
     )
 
     PGVECTOR_USER: Optional[str] = Field(
-        description="PGVector user",
+        description="Username for authenticating with the PostgreSQL database",
         default=None,
     )
 
     PGVECTOR_PASSWORD: Optional[str] = Field(
-        description="PGVector password",
+        description="Password for authenticating with the PostgreSQL database",
         default=None,
     )
 
     PGVECTOR_DATABASE: Optional[str] = Field(
-        description="PGVector database",
+        description="Name of the PostgreSQL database to connect to",
         default=None,
     )
+
+    PGVECTOR_MIN_CONNECTION: PositiveInt = Field(
+        description="Min connection of the PostgreSQL database",
+        default=1,
+    )
+
+    PGVECTOR_MAX_CONNECTION: PositiveInt = Field(
+        description="Max connection of the PostgreSQL database",
+        default=5,
+    )

api/configs/middleware/vdb/pgvectors_config.py

@@ -6,30 +6,30 @@ from pydantic_settings import BaseSettings
 
 class PGVectoRSConfig(BaseSettings):
     """
-    PGVectoRS configs
+    Configuration settings for PGVecto.RS (Rust-based vector extension for PostgreSQL)
     """
 
     PGVECTO_RS_HOST: Optional[str] = Field(
-        description="PGVectoRS host",
+        description="Hostname or IP address of the PostgreSQL server with PGVecto.RS extension (e.g., 'localhost')",
         default=None,
     )
 
     PGVECTO_RS_PORT: Optional[PositiveInt] = Field(
-        description="PGVectoRS port",
+        description="Port number on which the PostgreSQL server with PGVecto.RS is listening (default is 5431)",
         default=5431,
     )
 
     PGVECTO_RS_USER: Optional[str] = Field(
-        description="PGVectoRS user",
+        description="Username for authenticating with the PostgreSQL database using PGVecto.RS",
         default=None,
     )
 
     PGVECTO_RS_PASSWORD: Optional[str] = Field(
-        description="PGVectoRS password",
+        description="Password for authenticating with the PostgreSQL database using PGVecto.RS",
         default=None,
     )
 
     PGVECTO_RS_DATABASE: Optional[str] = Field(
-        description="PGVectoRS database",
+        description="Name of the PostgreSQL database with PGVecto.RS extension to connect to",
         default=None,
     )

api/configs/middleware/vdb/qdrant_config.py

@@ -6,30 +6,30 @@ from pydantic_settings import BaseSettings
 
 class QdrantConfig(BaseSettings):
     """
-    Qdrant configs
+    Configuration settings for Qdrant vector database
     """
 
     QDRANT_URL: Optional[str] = Field(
-        description="Qdrant url",
+        description="URL of the Qdrant server (e.g., 'http://localhost:6333' or 'https://qdrant.example.com')",
         default=None,
     )
 
     QDRANT_API_KEY: Optional[str] = Field(
-        description="Qdrant api key",
+        description="API key for authenticating with the Qdrant server",
         default=None,
     )
 
     QDRANT_CLIENT_TIMEOUT: NonNegativeInt = Field(
-        description="Qdrant client timeout in seconds",
+        description="Timeout in seconds for Qdrant client operations (default is 20 seconds)",
         default=20,
     )
 
     QDRANT_GRPC_ENABLED: bool = Field(
-        description="whether enable grpc support for Qdrant connection",
+        description="Whether to enable gRPC support for Qdrant connection (True for gRPC, False for HTTP)",
         default=False,
     )
 
     QDRANT_GRPC_PORT: PositiveInt = Field(
-        description="Qdrant grpc port",
+        description="Port number for gRPC connection to Qdrant server (default is 6334)",
         default=6334,
     )

api/configs/middleware/vdb/relyt_config.py

@@ -6,30 +6,30 @@ from pydantic_settings import BaseSettings
 
 class RelytConfig(BaseSettings):
     """
-    Relyt configs
+    Configuration settings for Relyt database
     """
 
     RELYT_HOST: Optional[str] = Field(
-        description="Relyt host",
+        description="Hostname or IP address of the Relyt server (e.g., 'localhost' or 'relyt.example.com')",
         default=None,
     )
 
     RELYT_PORT: PositiveInt = Field(
-        description="Relyt port",
+        description="Port number on which the Relyt server is listening (default is 9200)",
         default=9200,
     )
 
     RELYT_USER: Optional[str] = Field(
-        description="Relyt user",
+        description="Username for authenticating with the Relyt database",
         default=None,
     )
 
     RELYT_PASSWORD: Optional[str] = Field(
-        description="Relyt password",
+        description="Password for authenticating with the Relyt database",
         default=None,
     )
 
     RELYT_DATABASE: Optional[str] = Field(
-        description="Relyt database",
+        description="Name of the Relyt database to connect to (default is 'default')",
         default="default",
     )

api/configs/middleware/vdb/tencent_vector_config.py

@@ -6,45 +6,45 @@ from pydantic_settings import BaseSettings
 
 class TencentVectorDBConfig(BaseSettings):
     """
-    Tencent Vector configs
+    Configuration settings for Tencent Vector Database
     """
 
     TENCENT_VECTOR_DB_URL: Optional[str] = Field(
-        description="Tencent Vector URL",
+        description="URL of the Tencent Vector Database service (e.g., 'https://vectordb.tencentcloudapi.com')",
         default=None,
     )
 
     TENCENT_VECTOR_DB_API_KEY: Optional[str] = Field(
-        description="Tencent Vector API key",
+        description="API key for authenticating with the Tencent Vector Database service",
         default=None,
     )
 
     TENCENT_VECTOR_DB_TIMEOUT: PositiveInt = Field(
-        description="Tencent Vector timeout in seconds",
+        description="Timeout in seconds for Tencent Vector Database operations (default is 30 seconds)",
         default=30,
     )
 
     TENCENT_VECTOR_DB_USERNAME: Optional[str] = Field(
-        description="Tencent Vector username",
+        description="Username for authenticating with the Tencent Vector Database (if required)",
         default=None,
     )
 
     TENCENT_VECTOR_DB_PASSWORD: Optional[str] = Field(
-        description="Tencent Vector password",
+        description="Password for authenticating with the Tencent Vector Database (if required)",
         default=None,
     )
 
     TENCENT_VECTOR_DB_SHARD: PositiveInt = Field(
-        description="Tencent Vector sharding number",
+        description="Number of shards for the Tencent Vector Database (default is 1)",
         default=1,
     )
 
     TENCENT_VECTOR_DB_REPLICAS: NonNegativeInt = Field(
-        description="Tencent Vector replicas",
+        description="Number of replicas for the Tencent Vector Database (default is 2)",
         default=2,
     )
 
     TENCENT_VECTOR_DB_DATABASE: Optional[str] = Field(
-        description="Tencent Vector Database",
+        description="Name of the specific Tencent Vector Database to connect to",
         default=None,
     )

api/configs/middleware/vdb/tidb_vector_config.py

@@ -6,30 +6,30 @@ from pydantic_settings import BaseSettings
 
 class TiDBVectorConfig(BaseSettings):
     """
-    TiDB Vector configs
+    Configuration settings for TiDB Vector database
     """
 
     TIDB_VECTOR_HOST: Optional[str] = Field(
-        description="TiDB Vector host",
+        description="Hostname or IP address of the TiDB Vector server (e.g., 'localhost' or 'tidb.example.com')",
         default=None,
     )
 
     TIDB_VECTOR_PORT: Optional[PositiveInt] = Field(
-        description="TiDB Vector port",
+        description="Port number on which the TiDB Vector server is listening (default is 4000)",
         default=4000,
     )
 
     TIDB_VECTOR_USER: Optional[str] = Field(
-        description="TiDB Vector user",
+        description="Username for authenticating with the TiDB Vector database",
         default=None,
     )
 
     TIDB_VECTOR_PASSWORD: Optional[str] = Field(
-        description="TiDB Vector password",
+        description="Password for authenticating with the TiDB Vector database",
         default=None,
     )
 
     TIDB_VECTOR_DATABASE: Optional[str] = Field(
-        description="TiDB Vector database",
+        description="Name of the TiDB Vector database to connect to",
         default=None,
     )

api/configs/middleware/vdb/weaviate_config.py

@@ -6,25 +6,25 @@ from pydantic_settings import BaseSettings
 
 class WeaviateConfig(BaseSettings):
     """
-    Weaviate configs
+    Configuration settings for Weaviate vector database
     """
 
     WEAVIATE_ENDPOINT: Optional[str] = Field(
-        description="Weaviate endpoint URL",
+        description="URL of the Weaviate server (e.g., 'http://localhost:8080' or 'https://weaviate.example.com')",
         default=None,
     )
 
     WEAVIATE_API_KEY: Optional[str] = Field(
-        description="Weaviate API key",
+        description="API key for authenticating with the Weaviate server",
         default=None,
     )
 
     WEAVIATE_GRPC_ENABLED: bool = Field(
-        description="whether to enable gRPC for Weaviate connection",
+        description="Whether to enable gRPC for Weaviate connection (True for gRPC, False for HTTP)",
         default=True,
     )
 
     WEAVIATE_BATCH_SIZE: PositiveInt = Field(
-        description="Weaviate batch size",
+        description="Number of objects to be processed in a single batch operation (default is 100)",
         default=100,
     )

api/configs/packaging/__init__.py

@@ -9,7 +9,7 @@ class PackagingInfo(BaseSettings):
 
     CURRENT_VERSION: str = Field(
         description="Dify version",
-        default="0.8.3",
+        default="0.9.1-fix1",
     )
 
     COMMIT_SHA: str = Field(

api/constants/__init__.py

@@ -1 +1,2 @@
 HIDDEN_VALUE = "[__HIDDEN__]"
+UUID_NIL = "00000000-0000-0000-0000-000000000000"

api/controllers/console/__init__.py

@@ -37,7 +37,16 @@ from .auth import activate, data_source_bearer_auth, data_source_oauth, forgot_p
 from .billing import billing
 
 # Import datasets controllers
-from .datasets import data_source, datasets, datasets_document, datasets_segments, file, hit_testing, website
+from .datasets import (
+    data_source,
+    datasets,
+    datasets_document,
+    datasets_segments,
+    external,
+    file,
+    hit_testing,
+    website,
+)
 
 # Import explore controllers
 from .explore import (

api/controllers/console/app/completion.py

@@ -109,6 +109,7 @@ class ChatMessageApi(Resource):
         parser.add_argument("files", type=list, required=False, location="json")
         parser.add_argument("model_config", type=dict, required=True, location="json")
         parser.add_argument("conversation_id", type=uuid_value, location="json")
+        parser.add_argument("parent_message_id", type=uuid_value, required=False, location="json")
         parser.add_argument("response_mode", type=str, choices=["blocking", "streaming"], location="json")
         parser.add_argument("retriever_from", type=str, required=False, default="dev", location="json")
         args = parser.parse_args()

api/controllers/console/app/message.py

@@ -105,8 +105,6 @@ class ChatMessageListApi(Resource):
             if rest_count > 0:
                 has_more = True
 
-        history_messages = list(reversed(history_messages))
-
         return InfiniteScrollPagination(data=history_messages, limit=args["limit"], has_more=has_more)
 
 

api/controllers/console/app/workflow.py

@@ -166,6 +166,8 @@ class AdvancedChatDraftWorkflowRunApi(Resource):
         parser.add_argument("query", type=str, required=True, location="json", default="")
         parser.add_argument("files", type=list, location="json")
         parser.add_argument("conversation_id", type=uuid_value, location="json")
+        parser.add_argument("parent_message_id", type=uuid_value, required=False, location="json")
+
         args = parser.parse_args()
 
         try:

api/controllers/console/datasets/datasets.py

@@ -49,7 +49,7 @@ class DatasetListApi(Resource):
         page = request.args.get("page", default=1, type=int)
         limit = request.args.get("limit", default=20, type=int)
         ids = request.args.getlist("ids")
-        provider = request.args.get("provider", default="vendor")
+        # provider = request.args.get("provider", default="vendor")
         search = request.args.get("keyword", default=None, type=str)
         tag_ids = request.args.getlist("tag_ids")
 
@@ -57,7 +57,7 @@ class DatasetListApi(Resource):
             datasets, total = DatasetService.get_datasets_by_ids(ids, current_user.current_tenant_id)
         else:
             datasets, total = DatasetService.get_datasets(
-                page, limit, provider, current_user.current_tenant_id, current_user, search, tag_ids
+                page, limit, current_user.current_tenant_id, current_user, search, tag_ids
             )
 
         # check embedding setting
@@ -110,6 +110,26 @@ class DatasetListApi(Resource):
             nullable=True,
             help="Invalid indexing technique.",
         )
+        parser.add_argument(
+            "external_knowledge_api_id",
+            type=str,
+            nullable=True,
+            required=False,
+        )
+        parser.add_argument(
+            "provider",
+            type=str,
+            nullable=True,
+            choices=Dataset.PROVIDER_LIST,
+            required=False,
+            default="vendor",
+        )
+        parser.add_argument(
+            "external_knowledge_id",
+            type=str,
+            nullable=True,
+            required=False,
+        )
         args = parser.parse_args()
 
         # The role of the current user in the ta table must be admin, owner, or editor, or dataset_operator
@@ -123,6 +143,9 @@ class DatasetListApi(Resource):
                 indexing_technique=args["indexing_technique"],
                 account=current_user,
                 permission=DatasetPermissionEnum.ONLY_ME,
+                provider=args["provider"],
+                external_knowledge_api_id=args["external_knowledge_api_id"],
+                external_knowledge_id=args["external_knowledge_id"],
             )
         except services.errors.dataset.DatasetNameDuplicateError:
             raise DatasetNameDuplicateError()
@@ -211,6 +234,33 @@ class DatasetApi(Resource):
         )
         parser.add_argument("retrieval_model", type=dict, location="json", help="Invalid retrieval model.")
         parser.add_argument("partial_member_list", type=list, location="json", help="Invalid parent user list.")
+
+        parser.add_argument(
+            "external_retrieval_model",
+            type=dict,
+            required=False,
+            nullable=True,
+            location="json",
+            help="Invalid external retrieval model.",
+        )
+
+        parser.add_argument(
+            "external_knowledge_id",
+            type=str,
+            required=False,
+            nullable=True,
+            location="json",
+            help="Invalid external knowledge id.",
+        )
+
+        parser.add_argument(
+            "external_knowledge_api_id",
+            type=str,
+            required=False,
+            nullable=True,
+            location="json",
+            help="Invalid external knowledge api id.",
+        )
         args = parser.parse_args()
         data = request.get_json()
 
@@ -563,10 +613,10 @@ class DatasetRetrievalSettingApi(Resource):
             case (
                 VectorType.MILVUS
                 | VectorType.RELYT
-                | VectorType.PGVECTOR
                 | VectorType.TIDB_VECTOR
                 | VectorType.CHROMA
                 | VectorType.TENCENT
+                | VectorType.PGVECTO_RS
             ):
                 return {"retrieval_method": [RetrievalMethod.SEMANTIC_SEARCH.value]}
             case (
@@ -577,6 +627,7 @@ class DatasetRetrievalSettingApi(Resource):
                 | VectorType.MYSCALE
                 | VectorType.ORACLE
                 | VectorType.ELASTICSEARCH
+                | VectorType.PGVECTOR
             ):
                 return {
                     "retrieval_method": [

api/controllers/console/datasets/external.py

@@ -0,0 +1,239 @@
+from flask import request
+from flask_login import current_user
+from flask_restful import Resource, marshal, reqparse
+from werkzeug.exceptions import Forbidden, InternalServerError, NotFound
+
+import services
+from controllers.console import api
+from controllers.console.datasets.error import DatasetNameDuplicateError
+from controllers.console.setup import setup_required
+from controllers.console.wraps import account_initialization_required
+from fields.dataset_fields import dataset_detail_fields
+from libs.login import login_required
+from services.dataset_service import DatasetService
+from services.external_knowledge_service import ExternalDatasetService
+from services.hit_testing_service import HitTestingService
+
+
+def _validate_name(name):
+    if not name or len(name) < 1 or len(name) > 100:
+        raise ValueError("Name must be between 1 to 100 characters.")
+    return name
+
+
+def _validate_description_length(description):
+    if description and len(description) > 400:
+        raise ValueError("Description cannot exceed 400 characters.")
+    return description
+
+
+class ExternalApiTemplateListApi(Resource):
+    @setup_required
+    @login_required
+    @account_initialization_required
+    def get(self):
+        page = request.args.get("page", default=1, type=int)
+        limit = request.args.get("limit", default=20, type=int)
+        search = request.args.get("keyword", default=None, type=str)
+
+        external_knowledge_apis, total = ExternalDatasetService.get_external_knowledge_apis(
+            page, limit, current_user.current_tenant_id, search
+        )
+        response = {
+            "data": [item.to_dict() for item in external_knowledge_apis],
+            "has_more": len(external_knowledge_apis) == limit,
+            "limit": limit,
+            "total": total,
+            "page": page,
+        }
+        return response, 200
+
+    @setup_required
+    @login_required
+    @account_initialization_required
+    def post(self):
+        parser = reqparse.RequestParser()
+        parser.add_argument(
+            "name",
+            nullable=False,
+            required=True,
+            help="Name is required. Name must be between 1 to 100 characters.",
+            type=_validate_name,
+        )
+        parser.add_argument(
+            "settings",
+            type=dict,
+            location="json",
+            nullable=False,
+            required=True,
+        )
+        args = parser.parse_args()
+
+        ExternalDatasetService.validate_api_list(args["settings"])
+
+        # The role of the current user in the ta table must be admin, owner, or editor, or dataset_operator
+        if not current_user.is_dataset_editor:
+            raise Forbidden()
+
+        try:
+            external_knowledge_api = ExternalDatasetService.create_external_knowledge_api(
+                tenant_id=current_user.current_tenant_id, user_id=current_user.id, args=args
+            )
+        except services.errors.dataset.DatasetNameDuplicateError:
+            raise DatasetNameDuplicateError()
+
+        return external_knowledge_api.to_dict(), 201
+
+
+class ExternalApiTemplateApi(Resource):
+    @setup_required
+    @login_required
+    @account_initialization_required
+    def get(self, external_knowledge_api_id):
+        external_knowledge_api_id = str(external_knowledge_api_id)
+        external_knowledge_api = ExternalDatasetService.get_external_knowledge_api(external_knowledge_api_id)
+        if external_knowledge_api is None:
+            raise NotFound("API template not found.")
+
+        return external_knowledge_api.to_dict(), 200
+
+    @setup_required
+    @login_required
+    @account_initialization_required
+    def patch(self, external_knowledge_api_id):
+        external_knowledge_api_id = str(external_knowledge_api_id)
+
+        parser = reqparse.RequestParser()
+        parser.add_argument(
+            "name",
+            nullable=False,
+            required=True,
+            help="type is required. Name must be between 1 to 100 characters.",
+            type=_validate_name,
+        )
+        parser.add_argument(
+            "settings",
+            type=dict,
+            location="json",
+            nullable=False,
+            required=True,
+        )
+        args = parser.parse_args()
+        ExternalDatasetService.validate_api_list(args["settings"])
+
+        external_knowledge_api = ExternalDatasetService.update_external_knowledge_api(
+            tenant_id=current_user.current_tenant_id,
+            user_id=current_user.id,
+            external_knowledge_api_id=external_knowledge_api_id,
+            args=args,
+        )
+
+        return external_knowledge_api.to_dict(), 200
+
+    @setup_required
+    @login_required
+    @account_initialization_required
+    def delete(self, external_knowledge_api_id):
+        external_knowledge_api_id = str(external_knowledge_api_id)
+
+        # The role of the current user in the ta table must be admin, owner, or editor
+        if not current_user.is_editor or current_user.is_dataset_operator:
+            raise Forbidden()
+
+        ExternalDatasetService.delete_external_knowledge_api(current_user.current_tenant_id, external_knowledge_api_id)
+        return {"result": "success"}, 200
+
+
+class ExternalApiUseCheckApi(Resource):
+    @setup_required
+    @login_required
+    @account_initialization_required
+    def get(self, external_knowledge_api_id):
+        external_knowledge_api_id = str(external_knowledge_api_id)
+
+        external_knowledge_api_is_using, count = ExternalDatasetService.external_knowledge_api_use_check(
+            external_knowledge_api_id
+        )
+        return {"is_using": external_knowledge_api_is_using, "count": count}, 200
+
+
+class ExternalDatasetCreateApi(Resource):
+    @setup_required
+    @login_required
+    @account_initialization_required
+    def post(self):
+        # The role of the current user in the ta table must be admin, owner, or editor
+        if not current_user.is_editor:
+            raise Forbidden()
+
+        parser = reqparse.RequestParser()
+        parser.add_argument("external_knowledge_api_id", type=str, required=True, nullable=False, location="json")
+        parser.add_argument("external_knowledge_id", type=str, required=True, nullable=False, location="json")
+        parser.add_argument(
+            "name",
+            nullable=False,
+            required=True,
+            help="name is required. Name must be between 1 to 100 characters.",
+            type=_validate_name,
+        )
+        parser.add_argument("description", type=str, required=False, nullable=True, location="json")
+        parser.add_argument("external_retrieval_model", type=dict, required=False, location="json")
+
+        args = parser.parse_args()
+
+        # The role of the current user in the ta table must be admin, owner, or editor, or dataset_operator
+        if not current_user.is_dataset_editor:
+            raise Forbidden()
+
+        try:
+            dataset = ExternalDatasetService.create_external_dataset(
+                tenant_id=current_user.current_tenant_id,
+                user_id=current_user.id,
+                args=args,
+            )
+        except services.errors.dataset.DatasetNameDuplicateError:
+            raise DatasetNameDuplicateError()
+
+        return marshal(dataset, dataset_detail_fields), 201
+
+
+class ExternalKnowledgeHitTestingApi(Resource):
+    @setup_required
+    @login_required
+    @account_initialization_required
+    def post(self, dataset_id):
+        dataset_id_str = str(dataset_id)
+        dataset = DatasetService.get_dataset(dataset_id_str)
+        if dataset is None:
+            raise NotFound("Dataset not found.")
+
+        try:
+            DatasetService.check_dataset_permission(dataset, current_user)
+        except services.errors.account.NoPermissionError as e:
+            raise Forbidden(str(e))
+
+        parser = reqparse.RequestParser()
+        parser.add_argument("query", type=str, location="json")
+        parser.add_argument("external_retrieval_model", type=dict, required=False, location="json")
+        args = parser.parse_args()
+
+        HitTestingService.hit_testing_args_check(args)
+
+        try:
+            response = HitTestingService.external_retrieve(
+                dataset=dataset,
+                query=args["query"],
+                account=current_user,
+                external_retrieval_model=args["external_retrieval_model"],
+            )
+
+            return response
+        except Exception as e:
+            raise InternalServerError(str(e))
+
+
+api.add_resource(ExternalKnowledgeHitTestingApi, "/datasets/<uuid:dataset_id>/external-hit-testing")
+api.add_resource(ExternalDatasetCreateApi, "/datasets/external")
+api.add_resource(ExternalApiTemplateListApi, "/datasets/external-knowledge-api")
+api.add_resource(ExternalApiTemplateApi, "/datasets/external-knowledge-api/<uuid:external_knowledge_api_id>")
+api.add_resource(ExternalApiUseCheckApi, "/datasets/external-knowledge-api/<uuid:external_knowledge_api_id>/use-check")

api/controllers/console/datasets/hit_testing.py

@@ -47,6 +47,7 @@ class HitTestingApi(Resource):
         parser = reqparse.RequestParser()
         parser.add_argument("query", type=str, location="json")
         parser.add_argument("retrieval_model", type=dict, required=False, location="json")
+        parser.add_argument("external_retrieval_model", type=dict, required=False, location="json")
         args = parser.parse_args()
 
         HitTestingService.hit_testing_args_check(args)
@@ -57,6 +58,7 @@ class HitTestingApi(Resource):
                 query=args["query"],
                 account=current_user,
                 retrieval_model=args["retrieval_model"],
+                external_retrieval_model=args["external_retrieval_model"],
                 limit=10,
             )
 

api/controllers/console/datasets/website.py

@@ -14,7 +14,9 @@ class WebsiteCrawlApi(Resource):
     @account_initialization_required
     def post(self):
         parser = reqparse.RequestParser()
-        parser.add_argument("provider", type=str, choices=["firecrawl"], required=True, nullable=True, location="json")
+        parser.add_argument(
+            "provider", type=str, choices=["firecrawl", "jinareader"], required=True, nullable=True, location="json"
+        )
         parser.add_argument("url", type=str, required=True, nullable=True, location="json")
         parser.add_argument("options", type=dict, required=True, nullable=True, location="json")
         args = parser.parse_args()
@@ -33,7 +35,7 @@ class WebsiteCrawlStatusApi(Resource):
     @account_initialization_required
     def get(self, job_id: str):
         parser = reqparse.RequestParser()
-        parser.add_argument("provider", type=str, choices=["firecrawl"], required=True, location="args")
+        parser.add_argument("provider", type=str, choices=["firecrawl", "jinareader"], required=True, location="args")
         args = parser.parse_args()
         # get crawl status
         try:

api/controllers/console/explore/completion.py

@@ -100,6 +100,7 @@ class ChatApi(InstalledAppResource):
         parser.add_argument("query", type=str, required=True, location="json")
         parser.add_argument("files", type=list, required=False, location="json")
         parser.add_argument("conversation_id", type=uuid_value, location="json")
+        parser.add_argument("parent_message_id", type=uuid_value, required=False, location="json")
         parser.add_argument("retriever_from", type=str, required=False, default="explore_app", location="json")
         args = parser.parse_args()
 

api/controllers/console/explore/message.py

@@ -51,7 +51,7 @@ class MessageListApi(InstalledAppResource):
 
         try:
             return MessageService.pagination_by_first_id(
-                app_model, current_user, args["conversation_id"], args["first_id"], args["limit"]
+                app_model, current_user, args["conversation_id"], args["first_id"], args["limit"], "desc"
             )
         except services.errors.conversation.ConversationNotExistsError:
             raise NotFound("Conversation Not Exists.")

api/controllers/console/version.py

@@ -38,11 +38,52 @@ class VersionApi(Resource):
             return result
 
         content = json.loads(response.content)
-        result["version"] = content["version"]
-        result["release_date"] = content["releaseDate"]
-        result["release_notes"] = content["releaseNotes"]
-        result["can_auto_update"] = content["canAutoUpdate"]
+        if _has_new_version(latest_version=content["version"], current_version=f"{args.get('current_version')}"):
+            result["version"] = content["version"]
+            result["release_date"] = content["releaseDate"]
+            result["release_notes"] = content["releaseNotes"]
+            result["can_auto_update"] = content["canAutoUpdate"]
         return result
 
 
+def _has_new_version(*, latest_version: str, current_version: str) -> bool:
+    def parse_version(version: str) -> tuple:
+        # Split version into parts and pre-release suffix if any
+        parts = version.split("-")
+        version_parts = parts[0].split(".")
+        pre_release = parts[1] if len(parts) > 1 else None
+
+        # Validate version format
+        if len(version_parts) != 3:
+            raise ValueError(f"Invalid version format: {version}")
+
+        try:
+            # Convert version parts to integers
+            major, minor, patch = map(int, version_parts)
+            return (major, minor, patch, pre_release)
+        except ValueError:
+            raise ValueError(f"Invalid version format: {version}")
+
+    latest = parse_version(latest_version)
+    current = parse_version(current_version)
+
+    # Compare major, minor, and patch versions
+    for latest_part, current_part in zip(latest[:3], current[:3]):
+        if latest_part > current_part:
+            return True
+        elif latest_part < current_part:
+            return False
+
+    # If versions are equal, check pre-release suffixes
+    if latest[3] is None and current[3] is not None:
+        return True
+    elif latest[3] is not None and current[3] is None:
+        return False
+    elif latest[3] is not None and current[3] is not None:
+        # Simple string comparison for pre-release versions
+        return latest[3] > current[3]
+
+    return False
+
+
 api.add_resource(VersionApi, "/version")

api/controllers/console/workspace/models.py

@@ -72,8 +72,9 @@ class DefaultModelApi(Resource):
                     provider=model_setting["provider"],
                     model=model_setting["model"],
                 )
-            except Exception:
-                logging.warning(f"{model_setting['model_type']} save error")
+            except Exception as ex:
+                logging.exception(f"{model_setting['model_type']} save error: {ex}")
+                raise ex
 
         return {"result": "success"}
 

api/controllers/files/error.py

@@ -0,0 +1,7 @@
+from libs.exception import BaseHTTPException
+
+
+class UnsupportedFileTypeError(BaseHTTPException):
+    error_code = "unsupported_file_type"
+    description = "File type not allowed."
+    code = 415

api/controllers/files/image_preview.py

@@ -4,7 +4,7 @@ from werkzeug.exceptions import NotFound
 
 import services
 from controllers.files import api
-from libs.exception import BaseHTTPException
+from controllers.files.error import UnsupportedFileTypeError
 from services.account_service import TenantService
 from services.file_service import FileService
 
@@ -50,9 +50,3 @@ class WorkspaceWebappLogoApi(Resource):
 
 api.add_resource(ImagePreviewApi, "/files/<uuid:file_id>/image-preview")
 api.add_resource(WorkspaceWebappLogoApi, "/files/workspaces/<uuid:workspace_id>/webapp-logo")
-
-
-class UnsupportedFileTypeError(BaseHTTPException):
-    error_code = "unsupported_file_type"
-    description = "File type not allowed."
-    code = 415

api/controllers/files/tool_files.py

@@ -3,8 +3,8 @@ from flask_restful import Resource, reqparse
 from werkzeug.exceptions import Forbidden, NotFound
 
 from controllers.files import api
+from controllers.files.error import UnsupportedFileTypeError
 from core.tools.tool_file_manager import ToolFileManager
-from libs.exception import BaseHTTPException
 
 
 class ToolFilePreviewApi(Resource):
@@ -43,9 +43,3 @@ class ToolFilePreviewApi(Resource):
 
 
 api.add_resource(ToolFilePreviewApi, "/files/tools/<uuid:file_id>.<string:extension>")
-
-
-class UnsupportedFileTypeError(BaseHTTPException):
-    error_code = "unsupported_file_type"
-    description = "File type not allowed."
-    code = 415

api/controllers/service_api/app/completion.py

@@ -4,6 +4,7 @@ from flask_restful import Resource, reqparse
 from werkzeug.exceptions import InternalServerError, NotFound
 
 import services
+from constants import UUID_NIL
 from controllers.service_api import api
 from controllers.service_api.app.error import (
     AppUnavailableError,
@@ -107,6 +108,7 @@ class ChatApi(Resource):
         parser.add_argument("conversation_id", type=uuid_value, location="json")
         parser.add_argument("retriever_from", type=str, required=False, default="dev", location="json")
         parser.add_argument("auto_generate_name", type=bool, required=False, default=True, location="json")
+        parser.add_argument("parent_message_id", type=uuid_value, required=False, default=UUID_NIL, location="json")
 
         args = parser.parse_args()
 

api/controllers/service_api/app/message.py

@@ -54,6 +54,7 @@ class MessageListApi(Resource):
     message_fields = {
         "id": fields.String,
         "conversation_id": fields.String,
+        "parent_message_id": fields.String,
         "inputs": fields.Raw,
         "query": fields.String,
         "answer": fields.String(attribute="re_sign_file_url_answer"),

api/controllers/service_api/dataset/dataset.py

@@ -28,11 +28,11 @@ class DatasetListApi(DatasetApiResource):
 
         page = request.args.get("page", default=1, type=int)
         limit = request.args.get("limit", default=20, type=int)
-        provider = request.args.get("provider", default="vendor")
+        # provider = request.args.get("provider", default="vendor")
         search = request.args.get("keyword", default=None, type=str)
         tag_ids = request.args.getlist("tag_ids")
 
-        datasets, total = DatasetService.get_datasets(page, limit, provider, tenant_id, current_user, search, tag_ids)
+        datasets, total = DatasetService.get_datasets(page, limit, tenant_id, current_user, search, tag_ids)
         # check embedding setting
         provider_manager = ProviderManager()
         configurations = provider_manager.get_configurations(tenant_id=current_user.current_tenant_id)
@@ -82,6 +82,26 @@ class DatasetListApi(DatasetApiResource):
             required=False,
             nullable=False,
         )
+        parser.add_argument(
+            "external_knowledge_api_id",
+            type=str,
+            nullable=True,
+            required=False,
+            default="_validate_name",
+        )
+        parser.add_argument(
+            "provider",
+            type=str,
+            nullable=True,
+            required=False,
+            default="vendor",
+        )
+        parser.add_argument(
+            "external_knowledge_id",
+            type=str,
+            nullable=True,
+            required=False,
+        )
         args = parser.parse_args()
 
         try:
@@ -91,6 +111,9 @@ class DatasetListApi(DatasetApiResource):
                 indexing_technique=args["indexing_technique"],
                 account=current_user,
                 permission=args["permission"],
+                provider=args["provider"],
+                external_knowledge_api_id=args["external_knowledge_api_id"],
+                external_knowledge_id=args["external_knowledge_id"],
             )
         except services.errors.dataset.DatasetNameDuplicateError:
             raise DatasetNameDuplicateError()

api/controllers/web/completion.py

@@ -96,6 +96,7 @@ class ChatApi(WebApiResource):
         parser.add_argument("files", type=list, required=False, location="json")
         parser.add_argument("response_mode", type=str, choices=["blocking", "streaming"], location="json")
         parser.add_argument("conversation_id", type=uuid_value, location="json")
+        parser.add_argument("parent_message_id", type=uuid_value, required=False, location="json")
         parser.add_argument("retriever_from", type=str, required=False, default="web_app", location="json")
 
         args = parser.parse_args()

api/controllers/web/message.py

@@ -57,6 +57,7 @@ class MessageListApi(WebApiResource):
     message_fields = {
         "id": fields.String,
         "conversation_id": fields.String,
+        "parent_message_id": fields.String,
         "inputs": fields.Raw,
         "query": fields.String,
         "answer": fields.String(attribute="re_sign_file_url_answer"),
@@ -89,7 +90,7 @@ class MessageListApi(WebApiResource):
 
         try:
             return MessageService.pagination_by_first_id(
-                app_model, end_user, args["conversation_id"], args["first_id"], args["limit"]
+                app_model, end_user, args["conversation_id"], args["first_id"], args["limit"], "desc"
             )
         except services.errors.conversation.ConversationNotExistsError:
             raise NotFound("Conversation Not Exists.")

api/core/agent/base_agent_runner.py

@@ -32,6 +32,7 @@ from core.model_runtime.entities.message_entities import (
 from core.model_runtime.entities.model_entities import ModelFeature
 from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel
 from core.model_runtime.utils.encoders import jsonable_encoder
+from core.prompt.utils.extract_thread_messages import extract_thread_messages
 from core.tools.entities.tool_entities import (
     ToolParameter,
     ToolRuntimeVariablePool,
@@ -441,10 +442,12 @@ class BaseAgentRunner(AppRunner):
             .filter(
                 Message.conversation_id == self.message.conversation_id,
             )
-            .order_by(Message.created_at.asc())
+            .order_by(Message.created_at.desc())
             .all()
         )
 
+        messages = list(reversed(extract_thread_messages(messages)))
+
         for message in messages:
             if message.id == self.message.id:
                 continue

api/core/agent/output_parser/cot_output_parser.py

@@ -14,7 +14,7 @@ class CotAgentOutputParser:
     ) -> Generator[Union[str, AgentScratchpadUnit.Action], None, None]:
         def parse_action(json_str):
             try:
-                action = json.loads(json_str)
+                action = json.loads(json_str, strict=False)
                 action_name = None
                 action_input = None
 

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

@@ -121,6 +121,7 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
             inputs=conversation.inputs if conversation else self._get_cleaned_inputs(inputs, app_config),
             query=query,
             files=file_objs,
+            parent_message_id=args.get("parent_message_id"),
             user_id=user.id,
             stream=stream,
             invoke_from=invoke_from,

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

@@ -231,7 +231,8 @@ class AdvancedChatAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCyc
             except Exception as e:
                 logger.error(e)
                 break
-        yield MessageAudioEndStreamResponse(audio="", task_id=task_id)
+        if tts_publisher:
+            yield MessageAudioEndStreamResponse(audio="", task_id=task_id)
 
     def _process_stream_response(
         self,

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

@@ -127,6 +127,7 @@ class AgentChatAppGenerator(MessageBasedAppGenerator):
             inputs=conversation.inputs if conversation else self._get_cleaned_inputs(inputs, app_config),
             query=query,
             files=file_objs,
+            parent_message_id=args.get("parent_message_id"),
             user_id=user.id,
             stream=stream,
             invoke_from=invoke_from,

api/core/app/apps/base_app_generate_response_converter.py

@@ -75,10 +75,10 @@ class AppGenerateResponseConverter(ABC):
         :return:
         """
         # show_retrieve_source
+        updated_resources = []
         if "retriever_resources" in metadata:
-            metadata["retriever_resources"] = []
             for resource in metadata["retriever_resources"]:
-                metadata["retriever_resources"].append(
+                updated_resources.append(
                     {
                         "segment_id": resource["segment_id"],
                         "position": resource["position"],
@@ -87,6 +87,7 @@ class AppGenerateResponseConverter(ABC):
                         "content": resource["content"],
                     }
                 )
+            metadata["retriever_resources"] = updated_resources
 
         # show annotation reply
         if "annotation_reply" in metadata:

api/core/app/apps/base_app_runner.py

@@ -309,7 +309,7 @@ class AppRunner:
             if not prompt_messages:
                 prompt_messages = result.prompt_messages
 
-            if not usage and result.delta.usage:
+            if result.delta.usage:
                 usage = result.delta.usage
 
         if not usage:

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

@@ -128,6 +128,7 @@ class ChatAppGenerator(MessageBasedAppGenerator):
             inputs=conversation.inputs if conversation else self._get_cleaned_inputs(inputs, app_config),
             query=query,
             files=file_objs,
+            parent_message_id=args.get("parent_message_id"),
             user_id=user.id,
             stream=stream,
             invoke_from=invoke_from,

api/core/app/apps/message_based_app_generator.py

@@ -218,6 +218,7 @@ class MessageBasedAppGenerator(BaseAppGenerator):
             answer_tokens=0,
             answer_unit_price=0,
             answer_price_unit=0,
+            parent_message_id=getattr(application_generate_entity, "parent_message_id", None),
             provider_response_latency=0,
             total_price=0,
             currency="USD",

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

@@ -212,7 +212,8 @@ class WorkflowAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCycleMa
             except Exception as e:
                 logger.error(e)
                 break
-        yield MessageAudioEndStreamResponse(audio="", task_id=task_id)
+        if tts_publisher:
+            yield MessageAudioEndStreamResponse(audio="", task_id=task_id)
 
     def _process_stream_response(
         self,

api/core/app/entities/app_invoke_entities.py

@@ -122,6 +122,7 @@ class ChatAppGenerateEntity(EasyUIBasedAppGenerateEntity):
     """
 
     conversation_id: Optional[str] = None
+    parent_message_id: Optional[str] = None
 
 
 class CompletionAppGenerateEntity(EasyUIBasedAppGenerateEntity):
@@ -138,6 +139,7 @@ class AgentChatAppGenerateEntity(EasyUIBasedAppGenerateEntity):
     """
 
     conversation_id: Optional[str] = None
+    parent_message_id: Optional[str] = None
 
 
 class AdvancedChatAppGenerateEntity(AppGenerateEntity):
@@ -149,6 +151,7 @@ class AdvancedChatAppGenerateEntity(AppGenerateEntity):
     app_config: WorkflowUIBasedAppConfig
 
     conversation_id: Optional[str] = None
+    parent_message_id: Optional[str] = None
     query: str
 
     class SingleIterationRunEntity(BaseModel):

api/core/app/segments/exc.py

@@ -1,2 +1,2 @@
-class VariableError(Exception):
+class VariableError(ValueError):
     pass

api/core/app/task_pipeline/easy_ui_based_generate_task_pipeline.py

@@ -248,7 +248,8 @@ class EasyUIBasedGenerateTaskPipeline(BasedGenerateTaskPipeline, MessageCycleMan
             else:
                 start_listener_time = time.time()
                 yield MessageAudioStreamResponse(audio=audio.audio, task_id=task_id)
-        yield MessageAudioEndStreamResponse(audio="", task_id=task_id)
+        if publisher:
+            yield MessageAudioEndStreamResponse(audio="", task_id=task_id)
 
     def _process_stream_response(
         self, publisher: AppGeneratorTTSPublisher, trace_manager: Optional[TraceQueueManager] = None

api/core/callback_handler/index_tool_callback_handler.py

@@ -44,7 +44,6 @@ class DatasetIndexToolCallbackHandler:
                 DocumentSegment.index_node_id == document.metadata["doc_id"]
             )
 
-            # if 'dataset_id' in document.metadata:
             if "dataset_id" in document.metadata:
                 query = query.filter(DocumentSegment.dataset_id == document.metadata["dataset_id"])
 
@@ -59,7 +58,7 @@ class DatasetIndexToolCallbackHandler:
             for item in resource:
                 dataset_retriever_resource = DatasetRetrieverResource(
                     message_id=self._message_id,
-                    position=item.get("position"),
+                    position=item.get("position") or 0,
                     dataset_id=item.get("dataset_id"),
                     dataset_name=item.get("dataset_name"),
                     document_id=item.get("document_id"),

api/core/embedding/cached_embedding.py

@@ -5,6 +5,7 @@ from typing import Optional, cast
 import numpy as np
 from sqlalchemy.exc import IntegrityError
 
+from core.embedding.embedding_constant import EmbeddingInputType
 from core.model_manager import ModelInstance
 from core.model_runtime.entities.model_entities import ModelPropertyKey
 from core.model_runtime.model_providers.__base.text_embedding_model import TextEmbeddingModel
@@ -56,7 +57,9 @@ class CacheEmbedding(Embeddings):
                 for i in range(0, len(embedding_queue_texts), max_chunks):
                     batch_texts = embedding_queue_texts[i : i + max_chunks]
 
-                    embedding_result = self._model_instance.invoke_text_embedding(texts=batch_texts, user=self._user)
+                    embedding_result = self._model_instance.invoke_text_embedding(
+                        texts=batch_texts, user=self._user, input_type=EmbeddingInputType.DOCUMENT
+                    )
 
                     for vector in embedding_result.embeddings:
                         try:
@@ -100,7 +103,9 @@ class CacheEmbedding(Embeddings):
             redis_client.expire(embedding_cache_key, 600)
             return list(np.frombuffer(base64.b64decode(embedding), dtype="float"))
         try:
-            embedding_result = self._model_instance.invoke_text_embedding(texts=[text], user=self._user)
+            embedding_result = self._model_instance.invoke_text_embedding(
+                texts=[text], user=self._user, input_type=EmbeddingInputType.QUERY
+            )
 
             embedding_results = embedding_result.embeddings[0]
             embedding_results = (embedding_results / np.linalg.norm(embedding_results)).tolist()

api/core/embedding/embedding_constant.py

@@ -0,0 +1,10 @@
+from enum import Enum
+
+
+class EmbeddingInputType(Enum):
+    """
+    Enum for embedding input type.
+    """
+
+    DOCUMENT = "document"
+    QUERY = "query"

api/core/entities/provider_configuration.py

@@ -119,7 +119,7 @@ class ProviderConfiguration(BaseModel):
                         credentials = model_configuration.credentials
                         break
 
-            if self.custom_configuration.provider:
+            if not credentials and self.custom_configuration.provider:
                 credentials = self.custom_configuration.provider.credentials
 
             return credentials

api/core/llm_generator/llm_generator.py

@@ -47,6 +47,8 @@ class LLMGenerator:
             )
         answer = response.message.content
         cleaned_answer = re.sub(r"^.*(\{.*\}).*$", r"\1", answer, flags=re.DOTALL)
+        if cleaned_answer is None:
+            return ""
         result_dict = json.loads(cleaned_answer)
         answer = result_dict["Your Output"]
         name = answer.strip()

api/core/llm_generator/prompts.py

@@ -65,7 +65,6 @@ SUGGESTED_QUESTIONS_AFTER_ANSWER_INSTRUCTION_PROMPT = (
     "Please help me predict the three most likely questions that human would ask, "
     "and keeping each question under 20 characters.\n"
     "MAKE SURE your output is the SAME language as the Assistant's latest response"
-    "(if the main response is written in Chinese, then the language of your output must be using Chinese.)!\n"
     "The output must be an array in JSON format following the specified schema:\n"
     '["question1","question2","question3"]\n'
 )

api/core/memory/token_buffer_memory.py

@@ -11,6 +11,7 @@ from core.model_runtime.entities.message_entities import (
     TextPromptMessageContent,
     UserPromptMessage,
 )
+from core.prompt.utils.extract_thread_messages import extract_thread_messages
 from extensions.ext_database import db
 from models.model import AppMode, Conversation, Message, MessageFile
 from models.workflow import WorkflowRun
@@ -33,8 +34,17 @@ class TokenBufferMemory:
 
         # fetch limited messages, and return reversed
         query = (
-            db.session.query(Message.id, Message.query, Message.answer, Message.created_at, Message.workflow_run_id)
-            .filter(Message.conversation_id == self.conversation.id, Message.answer != "")
+            db.session.query(
+                Message.id,
+                Message.query,
+                Message.answer,
+                Message.created_at,
+                Message.workflow_run_id,
+                Message.parent_message_id,
+            )
+            .filter(
+                Message.conversation_id == self.conversation.id,
+            )
             .order_by(Message.created_at.desc())
         )
 
@@ -45,7 +55,12 @@ class TokenBufferMemory:
 
         messages = query.limit(message_limit).all()
 
-        messages = list(reversed(messages))
+        # instead of all messages from the conversation, we only need to extract messages
+        # that belong to the thread of last message
+        thread_messages = extract_thread_messages(messages)
+        thread_messages.pop(0)
+        messages = list(reversed(thread_messages))
+
         message_file_parser = MessageFileParser(tenant_id=app_record.tenant_id, app_id=app_record.id)
         prompt_messages = []
         for message in messages:

api/core/model_manager.py

@@ -3,6 +3,7 @@ import os
 from collections.abc import Callable, Generator, Sequence
 from typing import IO, Optional, Union, cast
 
+from core.embedding.embedding_constant import EmbeddingInputType
 from core.entities.provider_configuration import ProviderConfiguration, ProviderModelBundle
 from core.entities.provider_entities import ModelLoadBalancingConfiguration
 from core.errors.error import ProviderTokenNotInitError
@@ -158,12 +159,15 @@ class ModelInstance:
             tools=tools,
         )
 
-    def invoke_text_embedding(self, texts: list[str], user: Optional[str] = None) -> TextEmbeddingResult:
+    def invoke_text_embedding(
+        self, texts: list[str], user: Optional[str] = None, input_type: EmbeddingInputType = EmbeddingInputType.DOCUMENT
+    ) -> TextEmbeddingResult:
         """
         Invoke large language model
 
         :param texts: texts to embed
         :param user: unique user id
+        :param input_type: input type
         :return: embeddings result
         """
         if not isinstance(self.model_type_instance, TextEmbeddingModel):
@@ -176,6 +180,7 @@ class ModelInstance:
             credentials=self.credentials,
             texts=texts,
             user=user,
+            input_type=input_type,
         )
 
     def get_text_embedding_num_tokens(self, texts: list[str]) -> int:

api/core/model_runtime/callbacks/base_callback.py

@@ -1,3 +1,4 @@
+from abc import ABC, abstractmethod
 from typing import Optional
 
 from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk
@@ -13,7 +14,7 @@ _TEXT_COLOR_MAPPING = {
 }
 
 
-class Callback:
+class Callback(ABC):
     """
     Base class for callbacks.
     Only for LLM.
@@ -21,6 +22,7 @@ class Callback:
 
     raise_error: bool = False
 
+    @abstractmethod
     def on_before_invoke(
         self,
         llm_instance: AIModel,
@@ -48,6 +50,7 @@ class Callback:
         """
         raise NotImplementedError()
 
+    @abstractmethod
     def on_new_chunk(
         self,
         llm_instance: AIModel,
@@ -77,6 +80,7 @@ class Callback:
         """
         raise NotImplementedError()
 
+    @abstractmethod
     def on_after_invoke(
         self,
         llm_instance: AIModel,
@@ -106,6 +110,7 @@ class Callback:
         """
         raise NotImplementedError()
 
+    @abstractmethod
     def on_invoke_error(
         self,
         llm_instance: AIModel,

api/core/model_runtime/docs/en_US/customizable_model_scale_out.md

@@ -0,0 +1,310 @@
+## Custom Integration of Pre-defined Models
+
+### Introduction
+
+After completing the vendors integration, the next step is to connect the vendor's models. To illustrate the entire connection process, we will use Xinference as an example to demonstrate a complete vendor integration.
+
+It is important to note that for custom models, each model connection requires a complete vendor credential.
+
+Unlike pre-defined models, a custom vendor integration always includes the following two parameters, which do not need to be defined in the vendor YAML file.
+
+![](images/index/image-3.png)
+
+As mentioned earlier, vendors do not need to implement validate_provider_credential. The runtime will automatically call the corresponding model layer's validate_credentials to validate the credentials based on the model type and name selected by the user.
+
+### Writing the Vendor YAML
+
+First, we need to identify the types of models supported by the vendor we are integrating.
+
+Currently supported model types are as follows:
+
+- `llm` Text Generation Models
+
+- `text_embedding` Text Embedding Models
+
+- `rerank` Rerank Models
+
+- `speech2text` Speech-to-Text
+
+- `tts` Text-to-Speech
+
+- `moderation` Moderation
+
+Xinference supports LLM, Text Embedding, and Rerank. So we will start by writing xinference.yaml.
+
+```yaml
+provider: xinference #Define the vendor identifier
+label: # Vendor display name, supports both en_US (English) and zh_Hans (Simplified Chinese). If zh_Hans is not set, it will use en_US by default.
+  en_US: Xorbits Inference
+icon_small: # Small icon, refer to other vendors' icons stored in the _assets directory within the vendor implementation directory; follows the same language policy as the label
+  en_US: icon_s_en.svg
+icon_large: # Large icon
+  en_US: icon_l_en.svg
+help: # Help information
+  title:
+    en_US: How to deploy Xinference
+    zh_Hans: 如何部署 Xinference
+  url:
+    en_US: https://github.com/xorbitsai/inference
+supported_model_types: # Supported model types. Xinference supports LLM, Text Embedding, and Rerank
+- llm
+- text-embedding
+- rerank
+configurate_methods: # Since Xinference is a locally deployed vendor with no predefined models, users need to deploy whatever models they need according to Xinference documentation. Thus, it only supports custom models.
+- customizable-model
+provider_credential_schema:
+  credential_form_schemas:
+```
+
+
+Then, we need to determine what credentials are required to define a model in Xinference.
+
+- Since it supports three different types of models, we need to specify the model_type to denote the model type. Here is how we can define it:
+
+```yaml
+provider_credential_schema:
+  credential_form_schemas:
+  - variable: model_type
+    type: select
+    label:
+      en_US: Model type
+      zh_Hans: 模型类型
+    required: true
+    options:
+    - value: text-generation
+      label:
+        en_US: Language Model
+        zh_Hans: 语言模型
+    - value: embeddings
+      label:
+        en_US: Text Embedding
+    - value: reranking
+      label:
+        en_US: Rerank
+```
+
+- Next, each model has its own model_name, so we need to define that here:
+
+```yaml
+  - variable: model_name
+    type: text-input
+    label:
+      en_US: Model name
+      zh_Hans: 模型名称
+    required: true
+    placeholder:
+      zh_Hans: 填写模型名称
+      en_US: Input model name
+```
+
+- Specify the Xinference local deployment address:
+
+```yaml
+  - variable: server_url
+    label:
+      zh_Hans: 服务器URL
+      en_US: Server url
+    type: text-input
+    required: true
+    placeholder:
+      zh_Hans: 在此输入Xinference的服务器地址，如 https://example.com/xxx
+      en_US: Enter the url of your Xinference, for example https://example.com/xxx
+```
+
+- Each model has a unique model_uid, so we also need to define that here:
+
+```yaml
+  - variable: model_uid
+    label:
+      zh_Hans: 模型UID
+      en_US: Model uid
+    type: text-input
+    required: true
+    placeholder:
+      zh_Hans: 在此输入您的Model UID
+      en_US: Enter the model uid
+```
+
+Now, we have completed the basic definition of the vendor.
+
+### Writing the Model Code
+
+Next, let's take the `llm` type as an example and write `xinference.llm.llm.py`.
+
+In `llm.py`, create a Xinference LLM class, we name it `XinferenceAILargeLanguageModel` (this can be arbitrary), inheriting from the `__base.large_language_model.LargeLanguageModel` base class, and implement the following methods:
+
+- LLM Invocation
+
+Implement the core method for LLM invocation, supporting both stream and synchronous responses.
+
+```python
+def _invoke(self, model: str, credentials: dict,
+            prompt_messages: list[PromptMessage], model_parameters: dict,
+            tools: Optional[list[PromptMessageTool]] = None, stop: Optional[list[str]] = None,
+            stream: bool = True, user: Optional[str] = None) \
+        -> Union[LLMResult, Generator]:
+    """
+    Invoke large language model
+    
+    :param model: model name
+	:param credentials: model credentials
+	:param prompt_messages: prompt messages
+	:param model_parameters: model parameters
+	:param tools: tools for tool usage
+	:param stop: stop words
+	:param stream: is the response a stream
+	:param user: unique user id
+	:return: full response or stream response chunk generator result
+	"""
+```
+
+When implementing, ensure to use two functions to return data separately for synchronous and stream responses. This is important because Python treats functions containing the `yield` keyword as generator functions, mandating them to return `Generator` types. Here’s an example (note that the example uses simplified parameters; in real implementation, use the parameter list as defined above):
+
+```python
+def _invoke(self, stream: bool, **kwargs) \
+        -> Union[LLMResult, Generator]:
+    if stream:
+          return self._handle_stream_response(**kwargs)
+    return self._handle_sync_response(**kwargs)
+
+def _handle_stream_response(self, **kwargs) -> Generator:
+    for chunk in response:
+          yield chunk
+def _handle_sync_response(self, **kwargs) -> LLMResult:
+    return LLMResult(**response)
+```
+
+- Pre-compute Input Tokens
+
+If the model does not provide an interface for pre-computing tokens, you can return 0 directly.
+
+```python
+def get_num_tokens(self, model: str, credentials: dict, prompt_messages: list[PromptMessage],tools: Optional[list[PromptMessageTool]] = None) -> int:
+  """
+  Get number of tokens for given prompt messages
+
+  :param model: model name
+  :param credentials: model credentials
+  :param prompt_messages: prompt messages
+  :param tools: tools for tool usage
+  :return: token count
+  """
+```
+
+
+Sometimes, you might not want to return 0 directly. In such cases, you can use `self._get_num_tokens_by_gpt2(text: str)` to get pre-computed tokens. This method is provided by the `AIModel` base class, and it uses GPT2's Tokenizer for calculation. However, it should be noted that this is only a substitute and may not be fully accurate.
+
+- Model Credentials Validation
+
+Similar to vendor credentials validation, this method validates individual model credentials.
+
+```python
+def validate_credentials(self, model: str, credentials: dict) -> None:
+    """
+    Validate model credentials
+    
+    :param model: model name
+	:param credentials: model credentials
+	:return: None
+	"""
+```
+
+- Model Parameter Schema
+
+Unlike custom types, since the YAML file does not define which parameters a model supports, we need to dynamically generate the model parameter schema.
+
+For instance, Xinference supports `max_tokens`, `temperature`, and `top_p` parameters.
+
+However, some vendors may support different parameters for different models. For example, the `OpenLLM` vendor supports `top_k`, but not all models provided by this vendor support `top_k`. Let's say model A supports `top_k` but model B does not. In such cases, we need to dynamically generate the model parameter schema, as illustrated below:
+
+```python
+    def get_customizable_model_schema(self, model: str, credentials: dict) -> AIModelEntity | None:
+        """
+            used to define customizable model schema
+        """
+        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='max_tokens', type=ParameterType.INT,
+                use_template='max_tokens',
+                min=1,
+                default=512,
+                label=I18nObject(
+                    zh_Hans='最大生成长度', en_US='Max Tokens'
+                )
+            )
+        ]
+
+        # if model is A, add top_k to rules
+        if model == 'A':
+            rules.append(
+                ParameterRule(
+                    name='top_k', type=ParameterType.INT,
+                    use_template='top_k',
+                    min=1,
+                    default=50,
+                    label=I18nObject(
+                        zh_Hans='Top K', en_US='Top K'
+                    )
+                )
+            )
+
+        """
+            some NOT IMPORTANT code here
+        """
+
+        entity = AIModelEntity(
+            model=model,
+            label=I18nObject(
+                en_US=model
+            ),
+            fetch_from=FetchFrom.CUSTOMIZABLE_MODEL,
+            model_type=model_type,
+            model_properties={ 
+                ModelPropertyKey.MODE:  ModelType.LLM,
+            },
+            parameter_rules=rules
+        )
+
+        return entity
+```
+
+- Exception Error Mapping
+
+When a model invocation error occurs, it should be mapped to the runtime's specified `InvokeError` type, enabling Dify to handle different errors appropriately.
+
+Runtime Errors:
+
+- `InvokeConnectionError` Connection error during invocation
+- `InvokeServerUnavailableError` Service provider unavailable
+- `InvokeRateLimitError` Rate limit reached
+- `InvokeAuthorizationError` Authorization failure
+- `InvokeBadRequestError` Invalid request parameters
+
+```python
+  @property
+  def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]:
+      """
+      Map model invoke error to unified error
+      The key is the error type thrown to the caller
+      The value is the error type thrown by the model,
+      which needs to be converted into a unified error type for the caller.
+  
+      :return: Invoke error mapping
+      """
+```
+
+For interface method details, see: [Interfaces](./interfaces.md). For specific implementations, refer to: [llm.py](https://github.com/langgenius/dify-runtime/blob/main/lib/model_providers/anthropic/llm/llm.py).

api/core/model_runtime/docs/en_US/predefined_model_scale_out.md

@@ -0,0 +1,173 @@
+## Predefined Model Integration
+
+After completing the vendor integration, the next step is to integrate the models from the vendor.
+
+First, we need to determine the type of model to be integrated and create the corresponding model type `module` under the respective vendor's directory.
+
+Currently supported model types are:
+
+- `llm` Text Generation Model
+- `text_embedding` Text Embedding Model
+- `rerank` Rerank Model
+- `speech2text` Speech-to-Text
+- `tts` Text-to-Speech
+- `moderation` Moderation
+
+Continuing with `Anthropic` as an example, `Anthropic` only supports LLM, so create a `module` named `llm` under `model_providers.anthropic`.
+
+For predefined models, we first need to create a YAML file named after the model under the `llm` `module`, such as `claude-2.1.yaml`.
+
+### Prepare Model YAML
+
+```yaml
+model: claude-2.1  # Model identifier
+# Display name of the model, which can be set to en_US English or zh_Hans Chinese. If zh_Hans is not set, it will default to en_US.
+# This can also be omitted, in which case the model identifier will be used as the label
+label:
+  en_US: claude-2.1
+model_type: llm  # Model type, claude-2.1 is an LLM
+features:  # Supported features, agent-thought supports Agent reasoning, vision supports image understanding
+- agent-thought
+model_properties:  # Model properties
+  mode: chat  # LLM mode, complete for text completion models, chat for conversation models
+  context_size: 200000  # Maximum context size
+parameter_rules:  # Parameter rules for the model call; only LLM requires this
+- name: temperature  # Parameter variable name
+  # Five default configuration templates are provided: temperature/top_p/max_tokens/presence_penalty/frequency_penalty
+  # The template variable name can be set directly in use_template, which will use the default configuration in entities.defaults.PARAMETER_RULE_TEMPLATE
+  # Additional configuration parameters will override the default configuration if set
+  use_template: temperature
+- name: top_p
+  use_template: top_p
+- name: top_k
+  label:  # Display name of the parameter
+    zh_Hans: 取样数量
+    en_US: Top k
+  type: int  # Parameter type, supports float/int/string/boolean
+  help:  # Help information, describing the parameter's function
+    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  # Whether the parameter is mandatory; can be omitted
+- name: max_tokens_to_sample
+  use_template: max_tokens
+  default: 4096  # Default value of the parameter
+  min: 1  # Minimum value of the parameter, applicable to float/int only
+  max: 4096  # Maximum value of the parameter, applicable to float/int only
+pricing:  # Pricing information
+  input: '8.00'  # Input unit price, i.e., prompt price
+  output: '24.00'  # Output unit price, i.e., response content price
+  unit: '0.000001'  # Price unit, meaning the above prices are per 100K
+  currency: USD  # Price currency
+```
+
+It is recommended to prepare all model configurations before starting the implementation of the model code.
+
+You can also refer to the YAML configuration information under the corresponding model type directories of other vendors in the `model_providers` directory. For the complete YAML rules, refer to: [Schema](schema.md#aimodelentity).
+
+### Implement the Model Call Code
+
+Next, create a Python file named `llm.py` under the `llm` `module` to write the implementation code.
+
+Create an Anthropic LLM class named `AnthropicLargeLanguageModel` (or any other name), inheriting from the `__base.large_language_model.LargeLanguageModel` base class, and implement the following methods:
+
+- LLM Call
+
+Implement the core method for calling the LLM, supporting both streaming and synchronous responses.
+
+```python
+  def _invoke(self, model: str, credentials: dict,
+              prompt_messages: list[PromptMessage], model_parameters: dict,
+              tools: Optional[list[PromptMessageTool]] = None, stop: Optional[list[str]] = None,
+              stream: bool = True, user: Optional[str] = None) \
+          -> Union[LLMResult, Generator]:
+      """
+      Invoke large language model
+  
+      :param model: model name
+      :param credentials: model credentials
+      :param prompt_messages: prompt messages
+      :param model_parameters: model parameters
+      :param tools: tools for tool calling
+      :param stop: stop words
+      :param stream: is stream response
+      :param user: unique user id
+      :return: full response or stream response chunk generator result
+      """
+```
+
+Ensure to use two functions for returning data, one for synchronous returns and the other for streaming returns, because Python identifies functions containing the `yield` keyword as generator functions, fixing the return type to `Generator`. Thus, synchronous and streaming returns need to be implemented separately, as shown below (note that the example uses simplified parameters, for actual implementation follow the above parameter list):
+
+```python
+  def _invoke(self, stream: bool, **kwargs) \
+          -> Union[LLMResult, Generator]:
+      if stream:
+            return self._handle_stream_response(**kwargs)
+      return self._handle_sync_response(**kwargs)
+
+  def _handle_stream_response(self, **kwargs) -> Generator:
+      for chunk in response:
+            yield chunk
+  def _handle_sync_response(self, **kwargs) -> LLMResult:
+      return LLMResult(**response)
+```
+
+- Pre-compute Input Tokens
+
+If the model does not provide an interface to precompute tokens, return 0 directly.
+
+```python
+  def get_num_tokens(self, model: str, credentials: dict, prompt_messages: list[PromptMessage],
+                     tools: Optional[list[PromptMessageTool]] = None) -> int:
+      """
+      Get number of tokens for given prompt messages
+
+      :param model: model name
+      :param credentials: model credentials
+      :param prompt_messages: prompt messages
+      :param tools: tools for tool calling
+      :return:
+      """
+```
+
+- Validate Model Credentials
+
+Similar to vendor credential validation, but specific to a single model.
+
+```python
+  def validate_credentials(self, model: str, credentials: dict) -> None:
+      """
+      Validate model credentials
+  
+      :param model: model name
+      :param credentials: model credentials
+      :return:
+      """
+```
+
+- Map Invoke Errors
+
+When a model call fails, map it to a specific `InvokeError` type as required by Runtime, allowing Dify to handle different errors accordingly.
+
+Runtime Errors:
+
+- `InvokeConnectionError` Connection error
+
+- `InvokeServerUnavailableError` Service provider unavailable
+- `InvokeRateLimitError` Rate limit reached
+- `InvokeAuthorizationError` Authorization failed
+- `InvokeBadRequestError` Parameter error
+
+```python
+  @property
+  def _invoke_error_mapping(self) -> dict[type[InvokeError], list[type[Exception]]]:
+      """
+      Map model invoke error to unified error
+      The key is the error type thrown to the caller
+      The value is the error type thrown by the model,
+      which needs to be converted into a unified error type for the caller.
+  
+      :return: Invoke error mapping
+      """
+```
+
+For interface method explanations, see: [Interfaces](./interfaces.md). For detailed implementation, refer to: [llm.py](https://github.com/langgenius/dify-runtime/blob/main/lib/model_providers/anthropic/llm/llm.py).

api/core/model_runtime/docs/en_US/provider_scale_out.md

@@ -58,7 +58,7 @@ provider_credential_schema:  # Provider credential rules, as Anthropic only supp
       en_US: Enter your API URL
 ```
 
-You can also refer to the YAML configuration information under other provider directories in `model_providers`. The complete YAML rules are available at: [Schema](schema.md#Provider).
+You can also refer to the YAML configuration information under other provider directories in `model_providers`. The complete YAML rules are available at: [Schema](schema.md#provider).
 
 ### Implementing Provider Code
 

api/core/model_runtime/docs/zh_Hans/predefined_model_scale_out.md

@@ -62,7 +62,7 @@ pricing:  # 价格信息
 
 建议将所有模型配置都准备完毕后再开始模型代码的实现。
 
-同样，也可以参考  `model_providers` 目录下其他供应商对应模型类型目录下的 YAML 配置信息，完整的 YAML 规则见：[Schema](schema.md#AIModel)。
+同样，也可以参考  `model_providers` 目录下其他供应商对应模型类型目录下的 YAML 配置信息，完整的 YAML 规则见：[Schema](schema.md#aimodelentity)。
 
 ### 实现模型调用代码
 

api/core/model_runtime/docs/zh_Hans/provider_scale_out.md

@@ -117,7 +117,7 @@ model_credential_schema:
       en_US: Enter your API Base
 ```
 
-也可以参考  `model_providers` 目录下其他供应商目录下的 YAML 配置信息，完整的 YAML 规则见：[Schema](schema.md#Provider)。
+也可以参考  `model_providers` 目录下其他供应商目录下的 YAML 配置信息，完整的 YAML 规则见：[Schema](schema.md#provider)。
 
 #### 实现供应商代码
 

api/core/model_runtime/model_providers/__base/text_embedding_model.py

@@ -4,6 +4,7 @@ from typing import Optional
 
 from pydantic import ConfigDict
 
+from core.embedding.embedding_constant import EmbeddingInputType
 from core.model_runtime.entities.model_entities import ModelPropertyKey, ModelType
 from core.model_runtime.entities.text_embedding_entities import TextEmbeddingResult
 from core.model_runtime.model_providers.__base.ai_model import AIModel
@@ -20,35 +21,47 @@ class TextEmbeddingModel(AIModel):
     model_config = ConfigDict(protected_namespaces=())
 
     def invoke(
-        self, model: str, credentials: dict, texts: list[str], user: Optional[str] = None
+        self,
+        model: str,
+        credentials: dict,
+        texts: list[str],
+        user: Optional[str] = None,
+        input_type: EmbeddingInputType = EmbeddingInputType.DOCUMENT,
     ) -> TextEmbeddingResult:
         """
-        Invoke large language model
+        Invoke text embedding model
 
         :param model: model name
         :param credentials: model credentials
         :param texts: texts to embed
         :param user: unique user id
+        :param input_type: input type
         :return: embeddings result
         """
         self.started_at = time.perf_counter()
 
         try:
-            return self._invoke(model, credentials, texts, user)
+            return self._invoke(model, credentials, texts, user, input_type)
         except Exception as e:
             raise self._transform_invoke_error(e)
 
     @abstractmethod
     def _invoke(
-        self, model: str, credentials: dict, texts: list[str], user: Optional[str] = None
+        self,
+        model: str,
+        credentials: dict,
+        texts: list[str],
+        user: Optional[str] = None,
+        input_type: EmbeddingInputType = EmbeddingInputType.DOCUMENT,
     ) -> TextEmbeddingResult:
         """
-        Invoke large language model
+        Invoke text embedding model
 
         :param model: model name
         :param credentials: model credentials
         :param texts: texts to embed
         :param user: unique user id
+        :param input_type: input type
         :return: embeddings result
         """
         raise NotImplementedError

api/core/model_runtime/model_providers/_position.yaml

@@ -37,3 +37,7 @@
 - siliconflow
 - perfxcloud
 - zhinao
+- fireworks
+- mixedbread
+- nomic
+- voyage

api/core/model_runtime/model_providers/azure_openai/text_embedding/text_embedding.py

@@ -7,6 +7,7 @@ import numpy as np
 import tiktoken
 from openai import AzureOpenAI
 
+from core.embedding.embedding_constant import EmbeddingInputType
 from core.model_runtime.entities.model_entities import AIModelEntity, PriceType
 from core.model_runtime.entities.text_embedding_entities import EmbeddingUsage, TextEmbeddingResult
 from core.model_runtime.errors.validate import CredentialsValidateFailedError
@@ -17,8 +18,23 @@ from core.model_runtime.model_providers.azure_openai._constant import EMBEDDING_
 
 class AzureOpenAITextEmbeddingModel(_CommonAzureOpenAI, TextEmbeddingModel):
     def _invoke(
-        self, model: str, credentials: dict, texts: list[str], user: Optional[str] = None
+        self,
+        model: str,
+        credentials: dict,
+        texts: list[str],
+        user: Optional[str] = None,
+        input_type: EmbeddingInputType = EmbeddingInputType.DOCUMENT,
     ) -> TextEmbeddingResult:
+        """
+        Invoke text embedding model
+
+        :param model: model name
+        :param credentials: model credentials
+        :param texts: texts to embed
+        :param user: unique user id
+        :param input_type: input type
+        :return: embeddings result
+        """
         base_model_name = credentials["base_model_name"]
         credentials_kwargs = self._to_credential_kwargs(credentials)
         client = AzureOpenAI(**credentials_kwargs)

api/core/model_runtime/model_providers/baichuan/text_embedding/text_embedding.py

@@ -4,6 +4,7 @@ from typing import Optional
 
 from requests import post
 
+from core.embedding.embedding_constant import EmbeddingInputType
 from core.model_runtime.entities.model_entities import PriceType
 from core.model_runtime.entities.text_embedding_entities import EmbeddingUsage, TextEmbeddingResult
 from core.model_runtime.errors.invoke import (
@@ -35,7 +36,12 @@ class BaichuanTextEmbeddingModel(TextEmbeddingModel):
     api_base: str = "http://api.baichuan-ai.com/v1/embeddings"
 
     def _invoke(
-        self, model: str, credentials: dict, texts: list[str], user: Optional[str] = None
+        self,
+        model: str,
+        credentials: dict,
+        texts: list[str],
+        user: Optional[str] = None,
+        input_type: EmbeddingInputType = EmbeddingInputType.DOCUMENT,
     ) -> TextEmbeddingResult:
         """
         Invoke text embedding model
@@ -44,6 +50,7 @@ class BaichuanTextEmbeddingModel(TextEmbeddingModel):
         :param credentials: model credentials
         :param texts: texts to embed
         :param user: unique user id
+        :param input_type: input type
         :return: embeddings result
         """
         api_key = credentials["api_key"]

api/core/model_runtime/model_providers/bedrock/bedrock.yaml

@@ -50,34 +50,62 @@ provider_credential_schema:
           label:
             en_US: US East (N. Virginia)
             zh_Hans: 美国东部 (弗吉尼亚北部)
+        - value: us-east-2
+          label:
+            en_US: US East (Ohio)
+            zh_Hans: 美国东部 (弗吉尼亚北部)
         - value: us-west-2
           label:
             en_US: US West (Oregon)
             zh_Hans: 美国西部 (俄勒冈州)
+        - value: ap-south-1
+          label:
+            en_US: Asia Pacific (Mumbai)
+            zh_Hans: 亚太地区（孟买）
         - value: ap-southeast-1
           label:
             en_US: Asia Pacific (Singapore)
             zh_Hans: 亚太地区 (新加坡)
-        - value: ap-northeast-1
-          label:
-            en_US: Asia Pacific (Tokyo)
-            zh_Hans: 亚太地区 (东京)
-        - value: eu-central-1
-          label:
-            en_US: Europe (Frankfurt)
-            zh_Hans: 欧洲 (法兰克福)
-        - value: eu-west-2
-          label:
-            en_US: Eu west London (London)
-            zh_Hans: 欧洲西部 (伦敦)
-        - value: us-gov-west-1
-          label:
-            en_US: AWS GovCloud (US-West)
-            zh_Hans: AWS GovCloud (US-West)
         - value: ap-southeast-2
           label:
             en_US: Asia Pacific (Sydney)
             zh_Hans: 亚太地区 (悉尼)
+        - value: ap-northeast-1
+          label:
+            en_US: Asia Pacific (Tokyo)
+            zh_Hans: 亚太地区 (东京)
+        - value: ap-northeast-2
+          label:
+            en_US: Asia Pacific (Seoul)
+            zh_Hans: 亚太地区（首尔）
+        - value: ca-central-1
+          label:
+            en_US: Canada (Central)
+            zh_Hans: 加拿大（中部）
+        - value: eu-central-1
+          label:
+            en_US: Europe (Frankfurt)
+            zh_Hans: 欧洲 (法兰克福)
+        - value: eu-west-1
+          label:
+            en_US: Europe (Ireland)
+            zh_Hans: 欧洲（爱尔兰）
+        - value: eu-west-2
+          label:
+            en_US: Europe (London)
+            zh_Hans: 欧洲西部 (伦敦)
+        - value: eu-west-3
+          label:
+            en_US: Europe (Paris)
+            zh_Hans: 欧洲（巴黎）
+        - value: sa-east-1
+          label:
+            en_US: South America (São Paulo)
+            zh_Hans: 南美洲（圣保罗）
+        - value: us-gov-west-1
+          label:
+            en_US: AWS GovCloud (US-West)
+            zh_Hans: AWS GovCloud (US-West)
     - variable: model_for_validation
       required: false
       label:

api/core/model_runtime/model_providers/bedrock/llm/_position.yaml

@@ -6,6 +6,8 @@
 - anthropic.claude-v2:1
 - anthropic.claude-3-sonnet-v1:0
 - anthropic.claude-3-haiku-v1:0
+- ai21.jamba-1-5-large-v1:0
+- ai21.jamba-1-5-mini-v1:0
 - cohere.command-light-text-v14
 - cohere.command-text-v14
 - cohere.command-r-plus-v1.0
@@ -15,6 +17,10 @@
 - meta.llama3-1-405b-instruct-v1:0
 - meta.llama3-8b-instruct-v1:0
 - meta.llama3-70b-instruct-v1:0
+- us.meta.llama3-2-1b-instruct-v1:0
+- us.meta.llama3-2-3b-instruct-v1:0
+- us.meta.llama3-2-11b-instruct-v1:0
+- us.meta.llama3-2-90b-instruct-v1:0
 - meta.llama2-13b-chat-v1
 - meta.llama2-70b-chat-v1
 - mistral.mistral-large-2407-v1:0

api/core/model_runtime/model_providers/bedrock/llm/ai21.jamba-1-5-large-v1.0.yaml

@@ -0,0 +1,26 @@
+model: ai21.jamba-1-5-large-v1:0
+label:
+  en_US: Jamba 1.5 Large
+model_type: llm
+model_properties:
+  mode: completion
+  context_size: 256000
+parameter_rules:
+  - name: temperature
+    use_template: temperature
+    default: 1
+    min: 0.0
+    max: 2.0
+  - name: top_p
+    use_template: top_p
+  - name: max_gen_len
+    use_template: max_tokens
+    required: true
+    default: 4096
+    min: 1
+    max: 4096
+pricing:
+  input: '0.002'
+  output: '0.008'
+  unit: '0.001'
+  currency: USD

api/core/model_runtime/model_providers/bedrock/llm/ai21.jamba-1-5-mini-v1.0.yaml

@@ -0,0 +1,26 @@
+model: ai21.jamba-1-5-mini-v1:0
+label:
+  en_US: Jamba 1.5 Mini
+model_type: llm
+model_properties:
+  mode: completion
+  context_size: 256000
+parameter_rules:
+  - name: temperature
+    use_template: temperature
+    default: 1
+    min: 0.0
+    max: 2.0
+  - name: top_p
+    use_template: top_p
+  - name: max_gen_len
+    use_template: max_tokens
+    required: true
+    default: 4096
+    min: 1
+    max: 4096
+pricing:
+  input: '0.0002'
+  output: '0.0004'
+  unit: '0.001'
+  currency: USD

api/core/model_runtime/model_providers/bedrock/llm/llm.py

@@ -63,6 +63,7 @@ class BedrockLargeLanguageModel(LargeLanguageModel):
         {"prefix": "us.anthropic.claude-3", "support_system_prompts": True, "support_tool_use": True},
         {"prefix": "eu.anthropic.claude-3", "support_system_prompts": True, "support_tool_use": True},
         {"prefix": "anthropic.claude-3", "support_system_prompts": True, "support_tool_use": True},
+        {"prefix": "us.meta.llama3-2", "support_system_prompts": True, "support_tool_use": True},
         {"prefix": "meta.llama", "support_system_prompts": True, "support_tool_use": False},
         {"prefix": "mistral.mistral-7b-instruct", "support_system_prompts": False, "support_tool_use": False},
         {"prefix": "mistral.mixtral-8x7b-instruct", "support_system_prompts": False, "support_tool_use": False},
@@ -70,6 +71,7 @@ class BedrockLargeLanguageModel(LargeLanguageModel):
         {"prefix": "mistral.mistral-small", "support_system_prompts": True, "support_tool_use": True},
         {"prefix": "cohere.command-r", "support_system_prompts": True, "support_tool_use": True},
         {"prefix": "amazon.titan", "support_system_prompts": False, "support_tool_use": False},
+        {"prefix": "ai21.jamba-1-5", "support_system_prompts": True, "support_tool_use": False},
     ]
 
     @staticmethod