Merge branch 'refs/heads/main' into feat/workflow-parallel-support

# Conflicts:
#	api/core/app/apps/advanced_chat/app_generator.py
#	api/core/app/apps/advanced_chat/app_runner.py
#	api/core/app/apps/advanced_chat/generate_task_pipeline.py
#	api/core/app/apps/base_app_runner.py
#	api/core/app/apps/workflow/app_runner.py
#	api/core/app/apps/workflow/generate_task_pipeline.py
#	api/core/app/task_pipeline/workflow_cycle_state_manager.py
#	api/core/workflow/entities/node_entities.py
#	api/core/workflow/nodes/llm/llm_node.py
#	api/core/workflow/workflow_engine_manager.py
#	api/tests/integration_tests/workflow/nodes/test_llm.py
#	api/tests/integration_tests/workflow/nodes/test_parameter_extractor.py
#	api/tests/unit_tests/core/workflow/nodes/test_answer.py
#	api/tests/unit_tests/core/workflow/nodes/test_if_else.py
#	api/tests/unit_tests/core/workflow/nodes/test_variable_assigner.py

.github/workflows/api-tests.yml

@@ -76,7 +76,7 @@ jobs:
       - name: Run Workflow
         run: poetry run -C api bash dev/pytest/pytest_workflow.sh
 
-      - name: Set up Vector Stores (Weaviate, Qdrant, PGVector, Milvus, PgVecto-RS, Chroma, MyScale)
+      - name: Set up Vector Stores (Weaviate, Qdrant, PGVector, Milvus, PgVecto-RS, Chroma, MyScale, ElasticSearch)
         uses: hoverkraft-tech/compose-action@v2.0.0
         with:
           compose-file: |
@@ -90,5 +90,6 @@ jobs:
             pgvecto-rs
             pgvector
             chroma
+            elasticsearch
       - name: Test Vector Stores
         run: poetry run -C api bash dev/pytest/pytest_vdb.sh

.github/workflows/expose_service_ports.sh

@@ -6,5 +6,6 @@ yq eval '.services.chroma.ports += ["8000:8000"]' -i docker/docker-compose.yaml
 yq eval '.services["milvus-standalone"].ports += ["19530:19530"]' -i docker/docker-compose.yaml
 yq eval '.services.pgvector.ports += ["5433:5432"]' -i docker/docker-compose.yaml
 yq eval '.services["pgvecto-rs"].ports += ["5431:5432"]' -i docker/docker-compose.yaml
+yq eval '.services["elasticsearch"].ports += ["9200:9200"]' -i docker/docker-compose.yaml
 
-echo "Ports exposed for sandbox, weaviate, qdrant, chroma, milvus, pgvector, pgvecto-rs."
+echo "Ports exposed for sandbox, weaviate, qdrant, chroma, milvus, pgvector, pgvecto-rs, elasticsearch"

.github/workflows/style.yml

@@ -45,6 +45,10 @@ jobs:
         if: steps.changed-files.outputs.any_changed == 'true'
         run: poetry run -C api dotenv-linter ./api/.env.example ./web/.env.example
 
+      - name: Ruff formatter check
+        if: steps.changed-files.outputs.any_changed == 'true'
+        run: poetry run -C api ruff format --check ./api
+
       - name: Lint hints
         if: failure()
         run: echo "Please run 'dev/reformat' to fix the fixable linting errors."

api/.env.example

@@ -130,6 +130,12 @@ TENCENT_VECTOR_DB_DATABASE=dify
 TENCENT_VECTOR_DB_SHARD=1
 TENCENT_VECTOR_DB_REPLICAS=2
 
+# ElasticSearch configuration
+ELASTICSEARCH_HOST=127.0.0.1
+ELASTICSEARCH_PORT=9200
+ELASTICSEARCH_USERNAME=elastic
+ELASTICSEARCH_PASSWORD=elastic
+
 # PGVECTO_RS configuration
 PGVECTO_RS_HOST=localhost
 PGVECTO_RS_PORT=5431

api/app.py

@@ -1,6 +1,6 @@
 import os
 
-if os.environ.get("DEBUG", "false").lower() != 'true':
+if os.environ.get("DEBUG", "false").lower() != "true":
     from gevent import monkey
 
     monkey.patch_all()
@@ -57,7 +57,7 @@ warnings.simplefilter("ignore", ResourceWarning)
 if os.name == "nt":
     os.system('tzutil /s "UTC"')
 else:
-    os.environ['TZ'] = 'UTC'
+    os.environ["TZ"] = "UTC"
     time.tzset()
 
 
@@ -70,13 +70,14 @@ class DifyApp(Flask):
 # -------------
 
 
-config_type = os.getenv('EDITION', default='SELF_HOSTED')  # ce edition first
+config_type = os.getenv("EDITION", default="SELF_HOSTED")  # ce edition first
 
 
 # ----------------------------
 # Application Factory Function
 # ----------------------------
 
+
 def create_flask_app_with_configs() -> Flask:
     """
     create a raw flask app
@@ -92,7 +93,7 @@ def create_flask_app_with_configs() -> Flask:
         elif isinstance(value, int | float | bool):
             os.environ[key] = str(value)
         elif value is None:
-            os.environ[key] = ''
+            os.environ[key] = ""
 
     return dify_app
 
@@ -100,10 +101,10 @@ def create_flask_app_with_configs() -> Flask:
 def create_app() -> Flask:
     app = create_flask_app_with_configs()
 
-    app.secret_key = app.config['SECRET_KEY']
+    app.secret_key = app.config["SECRET_KEY"]
 
     log_handlers = None
-    log_file = app.config.get('LOG_FILE')
+    log_file = app.config.get("LOG_FILE")
     if log_file:
         log_dir = os.path.dirname(log_file)
         os.makedirs(log_dir, exist_ok=True)
@@ -111,23 +112,24 @@ def create_app() -> Flask:
             RotatingFileHandler(
                 filename=log_file,
                 maxBytes=1024 * 1024 * 1024,
-                backupCount=5
+                backupCount=5,
             ),
-            logging.StreamHandler(sys.stdout)
+            logging.StreamHandler(sys.stdout),
         ]
 
     logging.basicConfig(
-        level=app.config.get('LOG_LEVEL'),
-        format=app.config.get('LOG_FORMAT'),
-        datefmt=app.config.get('LOG_DATEFORMAT'),
+        level=app.config.get("LOG_LEVEL"),
+        format=app.config.get("LOG_FORMAT"),
+        datefmt=app.config.get("LOG_DATEFORMAT"),
         handlers=log_handlers,
-        force=True
+        force=True,
     )
-    log_tz = app.config.get('LOG_TZ')
+    log_tz = app.config.get("LOG_TZ")
     if log_tz:
         from datetime import datetime
 
         import pytz
+
         timezone = pytz.timezone(log_tz)
 
         def time_converter(seconds):
@@ -162,24 +164,24 @@ def initialize_extensions(app):
 @login_manager.request_loader
 def load_user_from_request(request_from_flask_login):
     """Load user based on the request."""
-    if request.blueprint not in ['console', 'inner_api']:
+    if request.blueprint not in ["console", "inner_api"]:
         return None
     # Check if the user_id contains a dot, indicating the old format
-    auth_header = request.headers.get('Authorization', '')
+    auth_header = request.headers.get("Authorization", "")
     if not auth_header:
-        auth_token = request.args.get('_token')
+        auth_token = request.args.get("_token")
         if not auth_token:
-            raise Unauthorized('Invalid Authorization token.')
+            raise Unauthorized("Invalid Authorization token.")
     else:
-        if ' ' not in auth_header:
-            raise Unauthorized('Invalid Authorization header format. Expected \'Bearer <api-key>\' format.')
+        if " " not in auth_header:
+            raise Unauthorized("Invalid Authorization header format. Expected 'Bearer <api-key>' format.")
         auth_scheme, auth_token = auth_header.split(None, 1)
         auth_scheme = auth_scheme.lower()
-        if auth_scheme != 'bearer':
-            raise Unauthorized('Invalid Authorization header format. Expected \'Bearer <api-key>\' format.')
+        if auth_scheme != "bearer":
+            raise Unauthorized("Invalid Authorization header format. Expected 'Bearer <api-key>' format.")
 
     decoded = PassportService().verify(auth_token)
-    user_id = decoded.get('user_id')
+    user_id = decoded.get("user_id")
 
     account = AccountService.load_logged_in_account(account_id=user_id, token=auth_token)
     if account:
@@ -190,10 +192,11 @@ def load_user_from_request(request_from_flask_login):
 @login_manager.unauthorized_handler
 def unauthorized_handler():
     """Handle unauthorized requests."""
-    return Response(json.dumps({
-        'code': 'unauthorized',
-        'message': "Unauthorized."
-    }), status=401, content_type="application/json")
+    return Response(
+        json.dumps({"code": "unauthorized", "message": "Unauthorized."}),
+        status=401,
+        content_type="application/json",
+    )
 
 
 # register blueprint routers
@@ -204,38 +207,36 @@ def register_blueprints(app):
     from controllers.service_api import bp as service_api_bp
     from controllers.web import bp as web_bp
 
-    CORS(service_api_bp,
-         allow_headers=['Content-Type', 'Authorization', 'X-App-Code'],
-         methods=['GET', 'PUT', 'POST', 'DELETE', 'OPTIONS', 'PATCH']
-         )
+    CORS(
+        service_api_bp,
+        allow_headers=["Content-Type", "Authorization", "X-App-Code"],
+        methods=["GET", "PUT", "POST", "DELETE", "OPTIONS", "PATCH"],
+    )
     app.register_blueprint(service_api_bp)
 
-    CORS(web_bp,
-         resources={
-             r"/*": {"origins": app.config['WEB_API_CORS_ALLOW_ORIGINS']}},
-         supports_credentials=True,
-         allow_headers=['Content-Type', 'Authorization', 'X-App-Code'],
-         methods=['GET', 'PUT', 'POST', 'DELETE', 'OPTIONS', 'PATCH'],
-         expose_headers=['X-Version', 'X-Env']
-         )
+    CORS(
+        web_bp,
+        resources={r"/*": {"origins": app.config["WEB_API_CORS_ALLOW_ORIGINS"]}},
+        supports_credentials=True,
+        allow_headers=["Content-Type", "Authorization", "X-App-Code"],
+        methods=["GET", "PUT", "POST", "DELETE", "OPTIONS", "PATCH"],
+        expose_headers=["X-Version", "X-Env"],
+    )
 
     app.register_blueprint(web_bp)
 
-    CORS(console_app_bp,
-         resources={
-             r"/*": {"origins": app.config['CONSOLE_CORS_ALLOW_ORIGINS']}},
-         supports_credentials=True,
-         allow_headers=['Content-Type', 'Authorization'],
-         methods=['GET', 'PUT', 'POST', 'DELETE', 'OPTIONS', 'PATCH'],
-         expose_headers=['X-Version', 'X-Env']
-         )
+    CORS(
+        console_app_bp,
+        resources={r"/*": {"origins": app.config["CONSOLE_CORS_ALLOW_ORIGINS"]}},
+        supports_credentials=True,
+        allow_headers=["Content-Type", "Authorization"],
+        methods=["GET", "PUT", "POST", "DELETE", "OPTIONS", "PATCH"],
+        expose_headers=["X-Version", "X-Env"],
+    )
 
     app.register_blueprint(console_app_bp)
 
-    CORS(files_bp,
-         allow_headers=['Content-Type'],
-         methods=['GET', 'PUT', 'POST', 'DELETE', 'OPTIONS', 'PATCH']
-         )
+    CORS(files_bp, allow_headers=["Content-Type"], methods=["GET", "PUT", "POST", "DELETE", "OPTIONS", "PATCH"])
     app.register_blueprint(files_bp)
 
     app.register_blueprint(inner_api_bp)
@@ -245,29 +246,29 @@ def register_blueprints(app):
 app = create_app()
 celery = app.extensions["celery"]
 
-if app.config.get('TESTING'):
+if app.config.get("TESTING"):
     print("App is running in TESTING mode")
 
 
 @app.after_request
 def after_request(response):
     """Add Version headers to the response."""
-    response.set_cookie('remember_token', '', expires=0)
-    response.headers.add('X-Version', app.config['CURRENT_VERSION'])
-    response.headers.add('X-Env', app.config['DEPLOY_ENV'])
+    response.set_cookie("remember_token", "", expires=0)
+    response.headers.add("X-Version", app.config["CURRENT_VERSION"])
+    response.headers.add("X-Env", app.config["DEPLOY_ENV"])
     return response
 
 
-@app.route('/health')
+@app.route("/health")
 def health():
-    return Response(json.dumps({
-        'pid': os.getpid(),
-        'status': 'ok',
-        'version': app.config['CURRENT_VERSION']
-    }), status=200, content_type="application/json")
+    return Response(
+        json.dumps({"pid": os.getpid(), "status": "ok", "version": app.config["CURRENT_VERSION"]}),
+        status=200,
+        content_type="application/json",
+    )
 
 
-@app.route('/threads')
+@app.route("/threads")
 def threads():
     num_threads = threading.active_count()
     threads = threading.enumerate()
@@ -278,32 +279,34 @@ def threads():
         thread_id = thread.ident
         is_alive = thread.is_alive()
 
-        thread_list.append({
-            'name': thread_name,
-            'id': thread_id,
-            'is_alive': is_alive
-        })
+        thread_list.append(
+            {
+                "name": thread_name,
+                "id": thread_id,
+                "is_alive": is_alive,
+            }
+        )
 
     return {
-        'pid': os.getpid(),
-        'thread_num': num_threads,
-        'threads': thread_list
+        "pid": os.getpid(),
+        "thread_num": num_threads,
+        "threads": thread_list,
     }
 
 
-@app.route('/db-pool-stat')
+@app.route("/db-pool-stat")
 def pool_stat():
     engine = db.engine
     return {
-        'pid': os.getpid(),
-        'pool_size': engine.pool.size(),
-        'checked_in_connections': engine.pool.checkedin(),
-        'checked_out_connections': engine.pool.checkedout(),
-        'overflow_connections': engine.pool.overflow(),
-        'connection_timeout': engine.pool.timeout(),
-        'recycle_time': db.engine.pool._recycle
+        "pid": os.getpid(),
+        "pool_size": engine.pool.size(),
+        "checked_in_connections": engine.pool.checkedin(),
+        "checked_out_connections": engine.pool.checkedout(),
+        "overflow_connections": engine.pool.overflow(),
+        "connection_timeout": engine.pool.timeout(),
+        "recycle_time": db.engine.pool._recycle,
     }
 
 
-if __name__ == '__main__':
-    app.run(host='0.0.0.0', port=5001)
+if __name__ == "__main__":
+    app.run(host="0.0.0.0", port=5001)

api/commands.py

@@ -27,32 +27,29 @@ from models.provider import Provider, ProviderModel
 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.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.")
 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("sorry. The two passwords do not match.", fg="red"))
         return
 
-    account = db.session.query(Account). \
-        filter(Account.email == email). \
-        one_or_none()
+    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("sorry. the account: [{}] not exist .".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("sorry. The passwords must match {} ".format(password_pattern), fg="red"))
         return
 
     # generate password salt
@@ -65,80 +62,87 @@ 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("Congratulations! Password has been reset.", 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.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.")
 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("Sorry, new email and confirm email do not match.", fg="red"))
         return
 
-    account = db.session.query(Account). \
-        filter(Account.email == email). \
-        one_or_none()
+    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("sorry. the account: [{}] not exist .".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("sorry. {} is not a valid email. ".format(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("Congratulations!, email has been reset.", fg="green"))
 
 
-@click.command('reset-encrypt-key-pair', help='Reset the asymmetric key pair of workspace for encrypt LLM credentials. '
-                                              'After the reset, all LLM credentials will become invalid, '
-                                              'requiring re-entry.'
-                                              'Only support SELF_HOSTED mode.')
-@click.confirmation_option(prompt=click.style('Are you sure you want to reset encrypt key pair?'
-                                              ' this operation cannot be rolled back!', fg='red'))
+@click.command(
+    "reset-encrypt-key-pair",
+    help="Reset the asymmetric key pair of workspace for encrypt LLM credentials. "
+    "After the reset, all LLM credentials will become invalid, "
+    "requiring re-entry."
+    "Only support SELF_HOSTED mode.",
+)
+@click.confirmation_option(
+    prompt=click.style(
+        "Are you sure you want to reset encrypt key pair?" " this operation cannot be rolled back!", fg="red"
+    )
+)
 def reset_encrypt_key_pair():
     """
     Reset the encrypted key pair of workspace for encrypt LLM credentials.
     After the reset, all LLM credentials will become invalid, requiring re-entry.
     Only support SELF_HOSTED mode.
     """
-    if dify_config.EDITION != 'SELF_HOSTED':
-        click.echo(click.style('Sorry, only support SELF_HOSTED mode.', fg='red'))
+    if dify_config.EDITION != "SELF_HOSTED":
+        click.echo(click.style("Sorry, only support SELF_HOSTED mode.", 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("Sorry, no workspace found. Please enter /install to initialize.", fg="red"))
             return
 
         tenant.encrypt_public_key = generate_key_pair(tenant.id)
 
-        db.session.query(Provider).filter(Provider.provider_type == 'custom', Provider.tenant_id == tenant.id).delete()
+        db.session.query(Provider).filter(Provider.provider_type == "custom", Provider.tenant_id == tenant.id).delete()
         db.session.query(ProviderModel).filter(ProviderModel.tenant_id == tenant.id).delete()
         db.session.commit()
 
-        click.echo(click.style('Congratulations! '
-                               'the asymmetric key pair of workspace {} has been reset.'.format(tenant.id), fg='green'))
+        click.echo(
+            click.style(
+                "Congratulations! " "the asymmetric key pair of workspace {} has been reset.".format(tenant.id),
+                fg="green",
+            )
+        )
 
 
-@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.')
+@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']:
+    if scope in ["knowledge", "all"]:
         migrate_knowledge_vector_database()
-    if scope in ['annotation', 'all']:
+    if scope in ["annotation", "all"]:
         migrate_annotation_vector_database()
 
 
@@ -146,7 +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("Start migrate annotation data.", fg="green"))
     create_count = 0
     skipped_count = 0
     total_count = 0
@@ -154,98 +158,103 @@ def migrate_annotation_vector_database():
     while True:
         try:
             # get apps info
-            apps = db.session.query(App).filter(
-                App.status == 'normal'
-            ).order_by(App.created_at.desc()).paginate(page=page, per_page=50)
+            apps = (
+                db.session.query(App)
+                .filter(App.status == "normal")
+                .order_by(App.created_at.desc())
+                .paginate(page=page, per_page=50)
+            )
         except NotFound:
             break
 
         page += 1
         for app in apps:
             total_count = total_count + 1
-            click.echo(f'Processing the {total_count} app {app.id}. '
-                       + f'{create_count} created, {skipped_count} skipped.')
+            click.echo(
+                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))
-                app_annotation_setting = db.session.query(AppAnnotationSetting).filter(
-                    AppAnnotationSetting.app_id == app.id
-                ).first()
+                click.echo("Create 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 is disabled: {}".format(app.id))
                     continue
                 # get dataset_collection_binding info
-                dataset_collection_binding = db.session.query(DatasetCollectionBinding).filter(
-                    DatasetCollectionBinding.id == app_annotation_setting.collection_binding_id
-                ).first()
+                dataset_collection_binding = (
+                    db.session.query(DatasetCollectionBinding)
+                    .filter(DatasetCollectionBinding.id == app_annotation_setting.collection_binding_id)
+                    .first()
+                )
                 if not dataset_collection_binding:
-                    click.echo('App annotation collection binding is not exist: {}'.format(app.id))
+                    click.echo("App annotation collection binding is not exist: {}".format(app.id))
                     continue
                 annotations = db.session.query(MessageAnnotation).filter(MessageAnnotation.app_id == app.id).all()
                 dataset = Dataset(
                     id=app.id,
                     tenant_id=app.tenant_id,
-                    indexing_technique='high_quality',
+                    indexing_technique="high_quality",
                     embedding_model_provider=dataset_collection_binding.provider_name,
                     embedding_model=dataset_collection_binding.model_name,
-                    collection_binding_id=dataset_collection_binding.id
+                    collection_binding_id=dataset_collection_binding.id,
                 )
                 documents = []
                 if annotations:
                     for annotation in annotations:
                         document = Document(
                             page_content=annotation.question,
-                            metadata={
-                                "annotation_id": annotation.id,
-                                "app_id": app.id,
-                                "doc_id": annotation.id
-                            }
+                            metadata={"annotation_id": annotation.id, "app_id": app.id, "doc_id": annotation.id},
                         )
                         documents.append(document)
 
-                vector = Vector(dataset, attributes=['doc_id', 'annotation_id', 'app_id'])
+                vector = Vector(dataset, attributes=["doc_id", "annotation_id", "app_id"])
                 click.echo(f"Start to migrate annotation, app_id: {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"Successfully delete 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'))
+                    click.echo(click.style(f"Failed to delete vector index for app {app.id}.", fg="red"))
                     raise e
                 if documents:
                     try:
-                        click.echo(click.style(
-                            f'Start to created 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.style(
+                                f"Start to created 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"))
                     except Exception as e:
-                        click.echo(click.style(f'Failed to created vector index for app {app.id}.', fg='red'))
+                        click.echo(click.style(f"Failed to created vector index for app {app.id}.", fg="red"))
                         raise e
-                click.echo(f'Successfully migrated app annotation {app.id}.')
+                click.echo(f"Successfully migrated app annotation {app.id}.")
                 create_count += 1
             except Exception as e:
                 click.echo(
-                    click.style('Create app annotation index error: {} {}'.format(e.__class__.__name__, str(e)),
-                                fg='red'))
+                    click.style(
+                        "Create app annotation index error: {} {}".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.',
-                    fg='green'))
+        click.style(
+            f"Congratulations! Create {create_count} app annotation indexes, and skipped {skipped_count} apps.",
+            fg="green",
+        )
+    )
 
 
 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("Start migrate vector db.", fg="green"))
     create_count = 0
     skipped_count = 0
     total_count = 0
@@ -253,87 +262,77 @@ def migrate_knowledge_vector_database():
     page = 1
     while True:
         try:
-            datasets = db.session.query(Dataset).filter(Dataset.indexing_technique == 'high_quality') \
-                .order_by(Dataset.created_at.desc()).paginate(page=page, per_page=50)
+            datasets = (
+                db.session.query(Dataset)
+                .filter(Dataset.indexing_technique == "high_quality")
+                .order_by(Dataset.created_at.desc())
+                .paginate(page=page, per_page=50)
+            )
         except NotFound:
             break
 
         page += 1
         for dataset in datasets:
             total_count = total_count + 1
-            click.echo(f'Processing the {total_count} dataset {dataset.id}. '
-                       + f'{create_count} created, {skipped_count} skipped.')
+            click.echo(
+                f"Processing the {total_count} dataset {dataset.id}. "
+                + f"{create_count} created, {skipped_count} skipped."
+            )
             try:
-                click.echo('Create dataset vdb index: {}'.format(dataset.id))
+                click.echo("Create dataset vdb index: {}".format(dataset.id))
                 if dataset.index_struct_dict:
-                    if dataset.index_struct_dict['type'] == vector_type:
+                    if dataset.index_struct_dict["type"] == vector_type:
                         skipped_count = skipped_count + 1
                         continue
-                collection_name = ''
+                collection_name = ""
                 if vector_type == VectorType.WEAVIATE:
                     dataset_id = dataset.id
                     collection_name = Dataset.gen_collection_name_by_id(dataset_id)
-                    index_struct_dict = {
-                        "type": VectorType.WEAVIATE,
-                        "vector_store": {"class_prefix": collection_name}
-                    }
+                    index_struct_dict = {"type": VectorType.WEAVIATE, "vector_store": {"class_prefix": collection_name}}
                     dataset.index_struct = json.dumps(index_struct_dict)
                 elif vector_type == VectorType.QDRANT:
                     if dataset.collection_binding_id:
-                        dataset_collection_binding = db.session.query(DatasetCollectionBinding). \
-                            filter(DatasetCollectionBinding.id == dataset.collection_binding_id). \
-                            one_or_none()
+                        dataset_collection_binding = (
+                            db.session.query(DatasetCollectionBinding)
+                            .filter(DatasetCollectionBinding.id == dataset.collection_binding_id)
+                            .one_or_none()
+                        )
                         if dataset_collection_binding:
                             collection_name = dataset_collection_binding.collection_name
                         else:
-                            raise ValueError('Dataset Collection Bindings is not exist!')
+                            raise ValueError("Dataset Collection Bindings is not exist!")
                     else:
                         dataset_id = dataset.id
                         collection_name = Dataset.gen_collection_name_by_id(dataset_id)
-                    index_struct_dict = {
-                        "type": VectorType.QDRANT,
-                        "vector_store": {"class_prefix": collection_name}
-                    }
+                    index_struct_dict = {"type": VectorType.QDRANT, "vector_store": {"class_prefix": collection_name}}
                     dataset.index_struct = json.dumps(index_struct_dict)
 
                 elif vector_type == VectorType.MILVUS:
                     dataset_id = dataset.id
                     collection_name = Dataset.gen_collection_name_by_id(dataset_id)
-                    index_struct_dict = {
-                        "type": VectorType.MILVUS,
-                        "vector_store": {"class_prefix": collection_name}
-                    }
+                    index_struct_dict = {"type": VectorType.MILVUS, "vector_store": {"class_prefix": collection_name}}
                     dataset.index_struct = json.dumps(index_struct_dict)
                 elif vector_type == VectorType.RELYT:
                     dataset_id = dataset.id
                     collection_name = Dataset.gen_collection_name_by_id(dataset_id)
-                    index_struct_dict = {
-                        "type": 'relyt',
-                        "vector_store": {"class_prefix": collection_name}
-                    }
+                    index_struct_dict = {"type": "relyt", "vector_store": {"class_prefix": collection_name}}
                     dataset.index_struct = json.dumps(index_struct_dict)
                 elif vector_type == VectorType.TENCENT:
                     dataset_id = dataset.id
                     collection_name = Dataset.gen_collection_name_by_id(dataset_id)
-                    index_struct_dict = {
-                        "type": VectorType.TENCENT,
-                        "vector_store": {"class_prefix": collection_name}
-                    }
+                    index_struct_dict = {"type": VectorType.TENCENT, "vector_store": {"class_prefix": collection_name}}
                     dataset.index_struct = json.dumps(index_struct_dict)
                 elif vector_type == VectorType.PGVECTOR:
                     dataset_id = dataset.id
                     collection_name = Dataset.gen_collection_name_by_id(dataset_id)
-                    index_struct_dict = {
-                        "type": VectorType.PGVECTOR,
-                        "vector_store": {"class_prefix": collection_name}
-                    }
+                    index_struct_dict = {"type": VectorType.PGVECTOR, "vector_store": {"class_prefix": collection_name}}
                     dataset.index_struct = json.dumps(index_struct_dict)
                 elif vector_type == VectorType.OPENSEARCH:
                     dataset_id = dataset.id
                     collection_name = Dataset.gen_collection_name_by_id(dataset_id)
                     index_struct_dict = {
                         "type": VectorType.OPENSEARCH,
-                        "vector_store": {"class_prefix": collection_name}
+                        "vector_store": {"class_prefix": collection_name},
                     }
                     dataset.index_struct = json.dumps(index_struct_dict)
                 elif vector_type == VectorType.ANALYTICDB:
@@ -341,9 +340,14 @@ def migrate_knowledge_vector_database():
                     collection_name = Dataset.gen_collection_name_by_id(dataset_id)
                     index_struct_dict = {
                         "type": VectorType.ANALYTICDB,
-                        "vector_store": {"class_prefix": collection_name}
+                        "vector_store": {"class_prefix": collection_name},
                     }
                     dataset.index_struct = json.dumps(index_struct_dict)
+                elif vector_type == VectorType.ELASTICSEARCH:
+                    dataset_id = dataset.id
+                    index_name = Dataset.gen_collection_name_by_id(dataset_id)
+                    index_struct_dict = {"type": "elasticsearch", "vector_store": {"class_prefix": index_name}}
+                    dataset.index_struct = json.dumps(index_struct_dict)
                 else:
                     raise ValueError(f"Vector store {vector_type} is not supported.")
 
@@ -353,29 +357,41 @@ def migrate_knowledge_vector_database():
                 try:
                     vector.delete()
                     click.echo(
-                        click.style(f'Successfully delete vector index {collection_name} for dataset {dataset.id}.',
-                                    fg='green'))
+                        click.style(
+                            f"Successfully delete vector index {collection_name} for dataset {dataset.id}.", fg="green"
+                        )
+                    )
                 except Exception as e:
                     click.echo(
-                        click.style(f'Failed to delete vector index {collection_name} for dataset {dataset.id}.',
-                                    fg='red'))
+                        click.style(
+                            f"Failed to delete vector index {collection_name} for dataset {dataset.id}.", fg="red"
+                        )
+                    )
                     raise e
 
-                dataset_documents = db.session.query(DatasetDocument).filter(
-                    DatasetDocument.dataset_id == dataset.id,
-                    DatasetDocument.indexing_status == 'completed',
-                    DatasetDocument.enabled == True,
-                    DatasetDocument.archived == False,
-                ).all()
+                dataset_documents = (
+                    db.session.query(DatasetDocument)
+                    .filter(
+                        DatasetDocument.dataset_id == dataset.id,
+                        DatasetDocument.indexing_status == "completed",
+                        DatasetDocument.enabled == True,
+                        DatasetDocument.archived == False,
+                    )
+                    .all()
+                )
 
                 documents = []
                 segments_count = 0
                 for dataset_document in dataset_documents:
-                    segments = db.session.query(DocumentSegment).filter(
-                        DocumentSegment.document_id == dataset_document.id,
-                        DocumentSegment.status == 'completed',
-                        DocumentSegment.enabled == True
-                    ).all()
+                    segments = (
+                        db.session.query(DocumentSegment)
+                        .filter(
+                            DocumentSegment.document_id == dataset_document.id,
+                            DocumentSegment.status == "completed",
+                            DocumentSegment.enabled == True,
+                        )
+                        .all()
+                    )
 
                     for segment in segments:
                         document = Document(
@@ -385,7 +401,7 @@ def migrate_knowledge_vector_database():
                                 "doc_hash": segment.index_node_hash,
                                 "document_id": segment.document_id,
                                 "dataset_id": segment.dataset_id,
-                            }
+                            },
                         )
 
                         documents.append(document)
@@ -393,37 +409,43 @@ def migrate_knowledge_vector_database():
 
                 if documents:
                     try:
-                        click.echo(click.style(
-                            f'Start to created vector index with {len(documents)} documents of {segments_count} segments for dataset {dataset.id}.',
-                            fg='green'))
+                        click.echo(
+                            click.style(
+                                f"Start to created vector index with {len(documents)} documents of {segments_count} 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.style(f"Successfully 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'))
+                        click.echo(click.style(f"Failed to created vector index for dataset {dataset.id}.", fg="red"))
                         raise e
                 db.session.add(dataset)
                 db.session.commit()
-                click.echo(f'Successfully migrated dataset {dataset.id}.')
+                click.echo(f"Successfully migrated dataset {dataset.id}.")
                 create_count += 1
             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("Create dataset index error: {} {}".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'))
+        click.style(
+            f"Congratulations! Create {create_count} dataset indexes, and skipped {skipped_count} datasets.", fg="green"
+        )
+    )
 
 
-@click.command('convert-to-agent-apps', help='Convert Agent Assistant to Agent App.')
+@click.command("convert-to-agent-apps", help="Convert Agent Assistant to Agent App.")
 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("Start convert to agent apps.", fg="green"))
 
     proceeded_app_ids = []
 
@@ -458,7 +480,7 @@ def convert_to_agent_apps():
                 break
 
         for app in apps:
-            click.echo('Converting app: {}'.format(app.id))
+            click.echo("Converting app: {}".format(app.id))
 
             try:
                 app.mode = AppMode.AGENT_CHAT.value
@@ -470,137 +492,139 @@ def convert_to_agent_apps():
                 )
 
                 db.session.commit()
-                click.echo(click.style('Converted app: {}'.format(app.id), fg='green'))
+                click.echo(click.style("Converted app: {}".format(app.id), fg="green"))
             except Exception as e:
-                click.echo(
-                    click.style('Convert app error: {} {}'.format(e.__class__.__name__,
-                                                                  str(e)), fg='red'))
+                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("Congratulations! 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("Start add qdrant doc_id index.", 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("Sorry, only support 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("Sorry, no dataset collection bindings found.", fg="red"))
             return
         import qdrant_client
         from qdrant_client.http.exceptions import UnexpectedResponse
         from qdrant_client.http.models import PayloadSchemaType
 
         from core.rag.datasource.vdb.qdrant.qdrant_vector import QdrantConfig
+
         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,
                 root_path=current_app.root_path,
                 timeout=dify_config.QDRANT_CLIENT_TIMEOUT,
                 grpc_port=dify_config.QDRANT_GRPC_PORT,
-                prefer_grpc=dify_config.QDRANT_GRPC_ENABLED
+                prefer_grpc=dify_config.QDRANT_GRPC_ENABLED,
             )
             try:
                 client = qdrant_client.QdrantClient(**qdrant_config.to_qdrant_params())
                 # create payload index
-                client.create_payload_index(binding.collection_name, field,
-                                            field_schema=PayloadSchemaType.KEYWORD)
+                client.create_payload_index(binding.collection_name, field, field_schema=PayloadSchemaType.KEYWORD)
                 create_count += 1
             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, collection_name:{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'))
+                    click.echo(
+                        click.style(
+                            f"Failed to create qdrant index, collection_name:{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"Congratulations! Create {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('--language', prompt=True, help='Account language, default: en-US.')
+@click.command("create-tenant", help="Create account and tenant.")
+@click.option("--email", prompt=True, help="The email address of the tenant account.")
+@click.option("--language", prompt=True, help="Account language, default: en-US.")
 def create_tenant(email: str, language: Optional[str] = None):
     """
     Create tenant account
     """
     if not email:
-        click.echo(click.style('Sorry, email is required.', fg='red'))
+        click.echo(click.style("Sorry, 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'))
+    if "@" not in email:
+        click.echo(click.style("Sorry, invalid email address.", fg="red"))
         return
 
-    account_name = email.split('@')[0]
+    account_name = email.split("@")[0]
 
     if language not in languages:
-        language = 'en-US'
+        language = "en-US"
 
     # generate random password
     new_password = secrets.token_urlsafe(16)
 
     # register account
-    account = RegisterService.register(
-        email=email,
-        name=account_name,
-        password=new_password,
-        language=language
-    )
+    account = RegisterService.register(email=email, name=account_name, password=new_password, language=language)
 
     TenantService.create_owner_tenant_if_not_exist(account)
 
-    click.echo(click.style('Congratulations! Account and tenant created.\n'
-                           'Account: {}\nPassword: {}'.format(email, new_password), fg='green'))
+    click.echo(
+        click.style(
+            "Congratulations! Account and tenant created.\n" "Account: {}\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)
+    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("Start database migration.", fg="green"))
 
             # run db migration
             import flask_migrate
+
             flask_migrate.upgrade()
 
-            click.echo(click.style('Database migration successful!', fg='green'))
+            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, error: {e}")
         finally:
             lock.release()
     else:
-        click.echo('Database migration skipped')
+        click.echo("Database migration skipped")
 
 
-@click.command('fix-app-site-missing', help='Fix app related site missing issue.')
+@click.command("fix-app-site-missing", help="Fix app related site missing issue.")
 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("Start fix app related site missing issue.", fg="green"))
 
     failed_app_ids = []
     while True:
@@ -631,15 +655,14 @@ where sites.id is null limit 1000"""
                         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'))
-                    logging.exception(f'Fix app related site missing issue failed, error: {e}')
+                    click.echo(click.style("Fix app {} related site missing issue failed!".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("Congratulations! Fix app related site missing issue successful!", fg="green"))
 
 
 def register_commands(app):

api/configs/packaging/__init__.py

@@ -9,7 +9,7 @@ class PackagingInfo(BaseSettings):
 
     CURRENT_VERSION: str = Field(
         description='Dify version',
-        default='0.6.16',
+        default='0.7.0',
     )
 
     COMMIT_SHA: str = Field(

api/constants/__init__.py

@@ -1 +1 @@
-HIDDEN_VALUE = '[__HIDDEN__]'
+HIDDEN_VALUE = "[__HIDDEN__]"

api/constants/languages.py

@@ -1,22 +1,22 @@
 language_timezone_mapping = {
-    'en-US': 'America/New_York',
-    'zh-Hans': 'Asia/Shanghai',
-    'zh-Hant': 'Asia/Taipei',
-    'pt-BR': 'America/Sao_Paulo',
-    'es-ES': 'Europe/Madrid',
-    'fr-FR': 'Europe/Paris',
-    'de-DE': 'Europe/Berlin',
-    'ja-JP': 'Asia/Tokyo',
-    'ko-KR': 'Asia/Seoul',
-    'ru-RU': 'Europe/Moscow',
-    'it-IT': 'Europe/Rome',
-    'uk-UA': 'Europe/Kyiv',
-    'vi-VN': 'Asia/Ho_Chi_Minh',
-    'ro-RO': 'Europe/Bucharest',
-    'pl-PL': 'Europe/Warsaw',
-    'hi-IN': 'Asia/Kolkata',
-    'tr-TR': 'Europe/Istanbul',
-    'fa-IR': 'Asia/Tehran',
+    "en-US": "America/New_York",
+    "zh-Hans": "Asia/Shanghai",
+    "zh-Hant": "Asia/Taipei",
+    "pt-BR": "America/Sao_Paulo",
+    "es-ES": "Europe/Madrid",
+    "fr-FR": "Europe/Paris",
+    "de-DE": "Europe/Berlin",
+    "ja-JP": "Asia/Tokyo",
+    "ko-KR": "Asia/Seoul",
+    "ru-RU": "Europe/Moscow",
+    "it-IT": "Europe/Rome",
+    "uk-UA": "Europe/Kyiv",
+    "vi-VN": "Asia/Ho_Chi_Minh",
+    "ro-RO": "Europe/Bucharest",
+    "pl-PL": "Europe/Warsaw",
+    "hi-IN": "Asia/Kolkata",
+    "tr-TR": "Europe/Istanbul",
+    "fa-IR": "Asia/Tehran",
 }
 
 languages = list(language_timezone_mapping.keys())
@@ -26,6 +26,5 @@ def supported_language(lang):
     if lang in languages:
         return lang
 
-    error = ('{lang} is not a valid language.'
-             .format(lang=lang))
+    error = "{lang} is not a valid language.".format(lang=lang)
     raise ValueError(error)

api/constants/model_template.py

@@ -5,82 +5,79 @@ from models.model import AppMode
 default_app_templates = {
     # workflow default mode
     AppMode.WORKFLOW: {
-        'app': {
-            'mode': AppMode.WORKFLOW.value,
-            'enable_site': True,
-            'enable_api': True
+        "app": {
+            "mode": AppMode.WORKFLOW.value,
+            "enable_site": True,
+            "enable_api": True,
         }
     },
-
     # completion default mode
     AppMode.COMPLETION: {
-        'app': {
-            'mode': AppMode.COMPLETION.value,
-            'enable_site': True,
-            'enable_api': True
+        "app": {
+            "mode": AppMode.COMPLETION.value,
+            "enable_site": True,
+            "enable_api": True,
         },
-        'model_config': {
-            'model': {
+        "model_config": {
+            "model": {
                 "provider": "openai",
                 "name": "gpt-4o",
                 "mode": "chat",
-                "completion_params": {}
+                "completion_params": {},
             },
-            'user_input_form': json.dumps([
-                {
-                    "paragraph": {
-                        "label": "Query",
-                        "variable": "query",
-                        "required": True,
-                        "default": ""
-                    }
-                }
-            ]),
-            'pre_prompt': '{{query}}'
+            "user_input_form": json.dumps(
+                [
+                    {
+                        "paragraph": {
+                            "label": "Query",
+                            "variable": "query",
+                            "required": True,
+                            "default": "",
+                        },
+                    },
+                ]
+            ),
+            "pre_prompt": "{{query}}",
         },
-
     },
-
     # chat default mode
     AppMode.CHAT: {
-        'app': {
-            'mode': AppMode.CHAT.value,
-            'enable_site': True,
-            'enable_api': True
+        "app": {
+            "mode": AppMode.CHAT.value,
+            "enable_site": True,
+            "enable_api": True,
         },
-        'model_config': {
-            'model': {
+        "model_config": {
+            "model": {
                 "provider": "openai",
                 "name": "gpt-4o",
                 "mode": "chat",
-                "completion_params": {}
-            }
-        }
+                "completion_params": {},
+            },
+        },
     },
-
     # advanced-chat default mode
     AppMode.ADVANCED_CHAT: {
-        'app': {
-            'mode': AppMode.ADVANCED_CHAT.value,
-            'enable_site': True,
-            'enable_api': True
-        }
+        "app": {
+            "mode": AppMode.ADVANCED_CHAT.value,
+            "enable_site": True,
+            "enable_api": True,
+        },
     },
-
     # agent-chat default mode
     AppMode.AGENT_CHAT: {
-        'app': {
-            'mode': AppMode.AGENT_CHAT.value,
-            'enable_site': True,
-            'enable_api': True
+        "app": {
+            "mode": AppMode.AGENT_CHAT.value,
+            "enable_site": True,
+            "enable_api": True,
         },
-        'model_config': {
-            'model': {
+        "model_config": {
+            "model": {
                 "provider": "openai",
                 "name": "gpt-4o",
                 "mode": "chat",
-                "completion_params": {}
-            }
-        }
-    }
+                "completion_params": {},
+            },
+        },
+    },
 }

api/contexts/__init__.py

@@ -1,3 +1,7 @@
 from contextvars import ContextVar
 
-tenant_id: ContextVar[str] = ContextVar('tenant_id')
+from core.workflow.entities.variable_pool import VariablePool
+
+tenant_id: ContextVar[str] = ContextVar("tenant_id")
+
+workflow_variable_pool: ContextVar[VariablePool] = ContextVar("workflow_variable_pool")

api/controllers/console/app/conversation.py

@@ -33,7 +33,7 @@ class CompletionConversationApi(Resource):
     @get_app_model(mode=AppMode.COMPLETION)
     @marshal_with(conversation_pagination_fields)
     def get(self, app_model):
-        if not current_user.is_admin_or_owner:
+        if not current_user.is_editor:
             raise Forbidden()
         parser = reqparse.RequestParser()
         parser.add_argument('keyword', type=str, location='args')
@@ -108,7 +108,7 @@ class CompletionConversationDetailApi(Resource):
     @get_app_model(mode=AppMode.COMPLETION)
     @marshal_with(conversation_message_detail_fields)
     def get(self, app_model, conversation_id):
-        if not current_user.is_admin_or_owner:
+        if not current_user.is_editor:
             raise Forbidden()
         conversation_id = str(conversation_id)
 
@@ -119,7 +119,7 @@ class CompletionConversationDetailApi(Resource):
     @account_initialization_required
     @get_app_model(mode=[AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.ADVANCED_CHAT])
     def delete(self, app_model, conversation_id):
-        if not current_user.is_admin_or_owner:
+        if not current_user.is_editor:
             raise Forbidden()
         conversation_id = str(conversation_id)
 
@@ -256,7 +256,7 @@ class ChatConversationDetailApi(Resource):
     @get_app_model(mode=[AppMode.CHAT, AppMode.AGENT_CHAT, AppMode.ADVANCED_CHAT])
     @account_initialization_required
     def delete(self, app_model, conversation_id):
-        if not current_user.is_admin_or_owner:
+        if not current_user.is_editor:
             raise Forbidden()
         conversation_id = str(conversation_id)
 

api/controllers/console/datasets/datasets.py

@@ -555,7 +555,7 @@ class DatasetRetrievalSettingApi(Resource):
                         RetrievalMethod.SEMANTIC_SEARCH.value
                     ]
                 }
-            case VectorType.QDRANT | VectorType.WEAVIATE | VectorType.OPENSEARCH | VectorType.ANALYTICDB | VectorType.MYSCALE | VectorType.ORACLE:
+            case VectorType.QDRANT | VectorType.WEAVIATE | VectorType.OPENSEARCH | VectorType.ANALYTICDB | VectorType.MYSCALE | VectorType.ORACLE | VectorType.ELASTICSEARCH:
                 return {
                     'retrieval_method': [
                         RetrievalMethod.SEMANTIC_SEARCH.value,
@@ -579,7 +579,7 @@ class DatasetRetrievalSettingMockApi(Resource):
                         RetrievalMethod.SEMANTIC_SEARCH.value
                     ]
                 }
-            case VectorType.QDRANT | VectorType.WEAVIATE | VectorType.OPENSEARCH| VectorType.ANALYTICDB | VectorType.MYSCALE | VectorType.ORACLE:
+            case VectorType.QDRANT | VectorType.WEAVIATE | VectorType.OPENSEARCH| VectorType.ANALYTICDB | VectorType.MYSCALE | VectorType.ORACLE | VectorType.ELASTICSEARCH:
                 return {
                     'retrieval_method': [
                         RetrievalMethod.SEMANTIC_SEARCH.value,

api/controllers/console/datasets/datasets_document.py

@@ -178,11 +178,20 @@ class DatasetDocumentListApi(Resource):
                 .subquery()
 
             query = query.outerjoin(sub_query, sub_query.c.document_id == Document.id) \
-                .order_by(sort_logic(db.func.coalesce(sub_query.c.total_hit_count, 0)))
+                .order_by(
+                    sort_logic(db.func.coalesce(sub_query.c.total_hit_count, 0)),
+                    sort_logic(Document.position),
+                )
         elif sort == 'created_at':
-            query = query.order_by(sort_logic(Document.created_at))
+            query = query.order_by(
+                sort_logic(Document.created_at),
+                sort_logic(Document.position),
+            )
         else:
-            query = query.order_by(desc(Document.created_at))
+            query = query.order_by(
+                desc(Document.created_at),
+                desc(Document.position),
+            )
 
         paginated_documents = query.paginate(
             page=page, per_page=limit, max_per_page=100, error_out=False)

api/core/app/app_config/easy_ui_based_app/dataset/manager.py

@@ -93,6 +93,7 @@ class DatasetConfigManager:
                     reranking_model=dataset_configs.get('reranking_model'),
                     weights=dataset_configs.get('weights'),
                     reranking_enabled=dataset_configs.get('reranking_enabled', True),
+                    rerank_mode=dataset_configs["reranking_mode"],
                 )
             )
 

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

@@ -33,7 +33,7 @@ logger = logging.getLogger(__name__)
 
 class AdvancedChatAppGenerator(MessageBasedAppGenerator):
     def generate(
-            self, 
+            self,
             app_model: App,
             workflow: Workflow,
             user: Union[Account, EndUser],
@@ -121,7 +121,7 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
             conversation=conversation,
             stream=stream
         )
-    
+
     def single_iteration_generate(self, app_model: App,
                                   workflow: Workflow,
                                   node_id: str,
@@ -141,10 +141,10 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
         """
         if not node_id:
             raise ValueError('node_id is required')
-        
+
         if args.get('inputs') is None:
             raise ValueError('inputs is required')
-        
+
         # convert to app config
         app_config = AdvancedChatAppConfigManager.get_app_config(
             app_model=app_model,
@@ -191,7 +191,7 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
             -> dict[str, Any] | Generator[str, Any, None]:
         """
         Generate App response.
-        
+
         :param workflow: Workflow
         :param user: account or end user
         :param invoke_from: invoke from source
@@ -232,8 +232,7 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
             'queue_manager': queue_manager,
             'conversation_id': conversation.id,
             'message_id': message.id,
-            'user': user,
-            'context': contextvars.copy_context()
+            'context': contextvars.copy_context(),
         })
 
         worker_thread.start()
@@ -246,7 +245,7 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
             conversation=conversation,
             message=message,
             user=user,
-            stream=stream
+            stream=stream,
         )
 
         return AdvancedChatAppGenerateResponseConverter.convert(
@@ -259,7 +258,6 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
                          queue_manager: AppQueueManager,
                          conversation_id: str,
                          message_id: str,
-                         user: Account,
                          context: contextvars.Context) -> None:
         """
         Generate worker in a new thread.
@@ -307,14 +305,17 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
             finally:
                 db.session.close()
 
-    def _handle_advanced_chat_response(self, application_generate_entity: AdvancedChatAppGenerateEntity,
-                                       workflow: Workflow,
-                                       queue_manager: AppQueueManager,
-                                       conversation: Conversation,
-                                       message: Message,
-                                       user: Union[Account, EndUser],
-                                       stream: bool = False) \
-            -> Union[ChatbotAppBlockingResponse, Generator[ChatbotAppStreamResponse, None, None]]:
+    def _handle_advanced_chat_response(
+        self,
+        *,
+        application_generate_entity: AdvancedChatAppGenerateEntity,
+        workflow: Workflow,
+        queue_manager: AppQueueManager,
+        conversation: Conversation,
+        message: Message,
+        user: Union[Account, EndUser],
+        stream: bool = False,
+    ) -> Union[ChatbotAppBlockingResponse, Generator[ChatbotAppStreamResponse, None, None]]:
         """
         Handle response.
         :param application_generate_entity: application generate entity
@@ -334,7 +335,7 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
             conversation=conversation,
             message=message,
             user=user,
-            stream=stream
+            stream=stream,
         )
 
         try:

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

@@ -3,9 +3,6 @@ import os
 from collections.abc import Mapping
 from typing import Any, cast
 
-from sqlalchemy import select
-from sqlalchemy.orm import Session
-
 from core.app.apps.advanced_chat.app_config_manager import AdvancedChatAppConfig
 from core.app.apps.base_app_queue_manager import AppQueueManager
 from core.app.apps.workflow_app_runner import WorkflowBasedAppRunner
@@ -94,7 +91,7 @@ class AdvancedChatAppRunner(WorkflowBasedAppRunner):
             inputs = self.application_generate_entity.inputs
             query = self.application_generate_entity.query
             files = self.application_generate_entity.files
-            
+
             # moderation
             if self.handle_input_moderation(
                     app_record=app_record,

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

@@ -44,7 +44,7 @@ from core.app.task_pipeline.message_cycle_manage import MessageCycleManage
 from core.app.task_pipeline.workflow_cycle_manage import WorkflowCycleManage
 from core.model_runtime.utils.encoders import jsonable_encoder
 from core.ops.ops_trace_manager import TraceQueueManager
-from core.workflow.entities.node_entities import SystemVariable
+from core.workflow.enums import SystemVariable
 from core.workflow.graph_engine.entities.graph_runtime_state import GraphRuntimeState
 from events.message_event import message_was_created
 from extensions.ext_database import db
@@ -69,14 +69,14 @@ class AdvancedChatAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCyc
     _workflow_system_variables: dict[SystemVariable, Any]
 
     def __init__(
-            self, 
+            self,
             application_generate_entity: AdvancedChatAppGenerateEntity,
             workflow: Workflow,
             queue_manager: AppQueueManager,
             conversation: Conversation,
             message: Message,
             user: Union[Account, EndUser],
-            stream: bool
+            stream: bool,
     ) -> None:
         """
         Initialize AdvancedChatAppGenerateTaskPipeline.
@@ -102,7 +102,7 @@ class AdvancedChatAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCyc
             SystemVariable.QUERY: message.query,
             SystemVariable.FILES: application_generate_entity.files,
             SystemVariable.CONVERSATION_ID: conversation.id,
-            SystemVariable.USER_ID: user_id
+            SystemVariable.USER_ID: user_id,
         }
 
         self._task_state = WorkflowTaskState()
@@ -127,7 +127,7 @@ class AdvancedChatAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCyc
         generator = self._wrapper_process_stream_response(
             trace_manager=self._application_generate_entity.trace_manager
         )
-        
+
         if self._stream:
             return self._to_stream_response(generator)
         else:
@@ -239,7 +239,7 @@ class AdvancedChatAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCyc
         # init fake graph runtime state
         graph_runtime_state = None
         workflow_run = None
-        
+
         for queue_message in self._queue_manager.listen():
             event = queue_message.event
 
@@ -270,9 +270,9 @@ class AdvancedChatAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCyc
             elif isinstance(event, QueueNodeStartedEvent):
                 if not workflow_run:
                     raise Exception('Workflow run not initialized.')
-        
+
                 workflow_node_execution = self._handle_node_execution_start(
-                    workflow_run=workflow_run, 
+                    workflow_run=workflow_run,
                     event=event
                 )
 
@@ -307,7 +307,7 @@ class AdvancedChatAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCyc
             elif isinstance(event, QueueIterationStartEvent):
                 if not workflow_run:
                     raise Exception('Workflow run not initialized.')
-                
+
                 yield self._workflow_iteration_start_to_stream_response(
                     task_id=self._application_generate_entity.task_id,
                     workflow_run=workflow_run,
@@ -316,7 +316,7 @@ class AdvancedChatAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCyc
             elif isinstance(event, QueueIterationNextEvent):
                 if not workflow_run:
                     raise Exception('Workflow run not initialized.')
-                
+
                 yield self._workflow_iteration_next_to_stream_response(
                     task_id=self._application_generate_entity.task_id,
                     workflow_run=workflow_run,
@@ -325,7 +325,7 @@ class AdvancedChatAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCyc
             elif isinstance(event, QueueIterationCompletedEvent):
                 if not workflow_run:
                     raise Exception('Workflow run not initialized.')
-                
+
                 yield self._workflow_iteration_completed_to_stream_response(
                     task_id=self._application_generate_entity.task_id,
                     workflow_run=workflow_run,
@@ -334,10 +334,10 @@ class AdvancedChatAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCyc
             elif isinstance(event, QueueWorkflowSucceededEvent):
                 if not workflow_run:
                     raise Exception('Workflow run not initialized.')
-                
+
                 if not graph_runtime_state:
                     raise Exception('Graph runtime state not initialized.')
-                
+
                 workflow_run = self._handle_workflow_run_success(
                     workflow_run=workflow_run,
                     start_at=graph_runtime_state.start_at,
@@ -360,10 +360,10 @@ class AdvancedChatAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCyc
             elif isinstance(event, QueueWorkflowFailedEvent):
                 if not workflow_run:
                     raise Exception('Workflow run not initialized.')
-                
+
                 if not graph_runtime_state:
                     raise Exception('Graph runtime state not initialized.')
-                
+
                 workflow_run = self._handle_workflow_run_failed(
                     workflow_run=workflow_run,
                     start_at=graph_runtime_state.start_at,
@@ -400,7 +400,7 @@ class AdvancedChatAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCyc
                         task_id=self._application_generate_entity.task_id,
                         workflow_run=workflow_run
                     )
-                
+
                 # Save message
                 self._save_message(graph_runtime_state=graph_runtime_state)
 
@@ -413,7 +413,7 @@ class AdvancedChatAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCyc
 
                 self._message.message_metadata = json.dumps(jsonable_encoder(self._task_state.metadata)) \
                     if self._task_state.metadata else None
-                
+
                 db.session.commit()
                 db.session.close()
             elif isinstance(event, QueueAnnotationReplyEvent):
@@ -421,7 +421,7 @@ class AdvancedChatAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCyc
 
                 self._message.message_metadata = json.dumps(jsonable_encoder(self._task_state.metadata)) \
                     if self._task_state.metadata else None
-                
+
                 db.session.commit()
                 db.session.close()
             elif isinstance(event, QueueTextChunkEvent):
@@ -446,7 +446,7 @@ class AdvancedChatAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCyc
             elif isinstance(event, QueueAdvancedChatMessageEndEvent):
                 if not graph_runtime_state:
                     raise Exception('Graph runtime state not initialized.')
-                
+
                 output_moderation_answer = self._handle_output_moderation_when_task_finished(self._task_state.answer)
                 if output_moderation_answer:
                     self._task_state.answer = output_moderation_answer
@@ -458,11 +458,11 @@ class AdvancedChatAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCyc
                 yield self._message_end_to_stream_response()
             else:
                 continue
-        
+
         # publish None when task finished
         if tts_publisher:
             tts_publisher.publish(None)
-            
+
         if self._conversation_name_generate_thread:
             self._conversation_name_generate_thread.join()
 
@@ -507,7 +507,7 @@ class AdvancedChatAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCyc
         extras = {}
         if self._task_state.metadata:
             extras['metadata'] = self._task_state.metadata.copy()
-            
+
             if 'annotation_reply' in extras['metadata']:
                 del extras['metadata']['annotation_reply']
 

api/core/app/apps/base_app_runner.py

@@ -1,6 +1,6 @@
 import time
 from collections.abc import Generator, Mapping
-from typing import Any, Optional, Union
+from typing import TYPE_CHECKING, Any, Optional, Union
 
 from core.app.app_config.entities import ExternalDataVariableEntity, PromptTemplateEntity
 from core.app.apps.base_app_queue_manager import AppQueueManager, PublishFrom
@@ -14,7 +14,6 @@ from core.app.entities.queue_entities import QueueAgentMessageEvent, QueueLLMChu
 from core.app.features.annotation_reply.annotation_reply import AnnotationReplyFeature
 from core.app.features.hosting_moderation.hosting_moderation import HostingModerationFeature
 from core.external_data_tool.external_data_fetch import ExternalDataFetch
-from core.file.file_obj import FileVar
 from core.memory.token_buffer_memory import TokenBufferMemory
 from core.model_manager import ModelInstance
 from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta, LLMUsage
@@ -27,13 +26,16 @@ from core.prompt.entities.advanced_prompt_entities import ChatModelMessage, Comp
 from core.prompt.simple_prompt_transform import ModelMode, SimplePromptTransform
 from models.model import App, AppMode, Message, MessageAnnotation
 
+if TYPE_CHECKING:
+    from core.file.file_obj import FileVar
+
 
 class AppRunner:
     def get_pre_calculate_rest_tokens(self, app_record: App,
                                       model_config: ModelConfigWithCredentialsEntity,
                                       prompt_template_entity: PromptTemplateEntity,
                                       inputs: dict[str, str],
-                                      files: list[FileVar],
+                                      files: list["FileVar"],
                                       query: Optional[str] = None) -> int:
         """
         Get pre calculate rest tokens
@@ -126,7 +128,7 @@ class AppRunner:
                                  model_config: ModelConfigWithCredentialsEntity,
                                  prompt_template_entity: PromptTemplateEntity,
                                  inputs: dict[str, str],
-                                 files: list[FileVar],
+                                 files: list["FileVar"],
                                  query: Optional[str] = None,
                                  context: Optional[str] = None,
                                  memory: Optional[TokenBufferMemory] = None) \
@@ -366,7 +368,7 @@ class AppRunner:
             message_id=message_id,
             trace_manager=app_generate_entity.trace_manager
         )
-    
+
     def check_hosting_moderation(self, application_generate_entity: EasyUIBasedAppGenerateEntity,
                                  queue_manager: AppQueueManager,
                                  prompt_messages: list[PromptMessage]) -> bool:
@@ -418,7 +420,7 @@ class AppRunner:
             inputs=inputs,
             query=query
         )
-    
+
     def query_app_annotations_to_reply(self, app_record: App,
                                        message: Message,
                                        query: str,

api/core/app/apps/message_based_app_generator.py

@@ -258,7 +258,7 @@ class MessageBasedAppGenerator(BaseAppGenerator):
 
         return introduction
 
-    def _get_conversation(self, conversation_id: str) -> Conversation:
+    def _get_conversation(self, conversation_id: str):
         """
         Get conversation by conversation id
         :param conversation_id: conversation id
@@ -270,6 +270,9 @@ class MessageBasedAppGenerator(BaseAppGenerator):
             .first()
         )
 
+        if not conversation:
+            raise ConversationNotExistsError()
+
         return conversation
 
     def _get_message(self, message_id: str) -> Message:

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

@@ -11,7 +11,8 @@ from core.app.entities.app_invoke_entities import (
     WorkflowAppGenerateEntity,
 )
 from core.workflow.callbacks.base_workflow_callback import WorkflowCallback
-from core.workflow.entities.node_entities import SystemVariable, UserFrom
+from core.workflow.enums import SystemVariable
+from core.workflow.entities.node_entities import UserFrom
 from core.workflow.entities.variable_pool import VariablePool
 from core.workflow.workflow_entry import WorkflowEntry
 from extensions.ext_database import db

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

@@ -41,7 +41,9 @@ from core.app.entities.task_entities import (
 from core.app.task_pipeline.based_generate_task_pipeline import BasedGenerateTaskPipeline
 from core.app.task_pipeline.workflow_cycle_manage import WorkflowCycleManage
 from core.ops.ops_trace_manager import TraceQueueManager
-from core.workflow.entities.node_entities import SystemVariable
+from core.workflow.entities.node_entities import NodeType
+from core.workflow.enums import SystemVariable
+from core.workflow.nodes.end.end_node import EndNode
 from extensions.ext_database import db
 from models.account import Account
 from models.model import EndUser
@@ -179,7 +181,7 @@ class WorkflowAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCycleMa
         if features_dict.get('text_to_speech') and features_dict['text_to_speech'].get('enabled') and features_dict[
                 'text_to_speech'].get('autoPlay') == 'enabled':
             tts_publisher = AppGeneratorTTSPublisher(tenant_id, features_dict['text_to_speech'].get('voice'))
-        
+
         for response in self._process_stream_response(tts_publisher=tts_publisher, trace_manager=trace_manager):
             while True:
                 audio_response = self._listenAudioMsg(tts_publisher, task_id=task_id)
@@ -246,7 +248,7 @@ class WorkflowAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCycleMa
                     raise Exception('Workflow run not initialized.')
 
                 workflow_node_execution = self._handle_node_execution_start(
-                    workflow_run=workflow_run, 
+                    workflow_run=workflow_run,
                     event=event
                 )
 
@@ -281,7 +283,7 @@ class WorkflowAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCycleMa
             elif isinstance(event, QueueIterationStartEvent):
                 if not workflow_run:
                     raise Exception('Workflow run not initialized.')
-                
+
                 yield self._workflow_iteration_start_to_stream_response(
                     task_id=self._application_generate_entity.task_id,
                     workflow_run=workflow_run,
@@ -290,7 +292,7 @@ class WorkflowAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCycleMa
             elif isinstance(event, QueueIterationNextEvent):
                 if not workflow_run:
                     raise Exception('Workflow run not initialized.')
-                
+
                 yield self._workflow_iteration_next_to_stream_response(
                     task_id=self._application_generate_entity.task_id,
                     workflow_run=workflow_run,
@@ -299,7 +301,7 @@ class WorkflowAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCycleMa
             elif isinstance(event, QueueIterationCompletedEvent):
                 if not workflow_run:
                     raise Exception('Workflow run not initialized.')
-                
+
                 yield self._workflow_iteration_completed_to_stream_response(
                     task_id=self._application_generate_entity.task_id,
                     workflow_run=workflow_run,
@@ -308,10 +310,10 @@ class WorkflowAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCycleMa
             elif isinstance(event, QueueWorkflowSucceededEvent):
                 if not workflow_run:
                     raise Exception('Workflow run not initialized.')
-                
+
                 if not graph_runtime_state:
                     raise Exception('Graph runtime state not initialized.')
-                
+
                 workflow_run = self._handle_workflow_run_success(
                     workflow_run=workflow_run,
                     start_at=graph_runtime_state.start_at,
@@ -332,10 +334,10 @@ class WorkflowAppGenerateTaskPipeline(BasedGenerateTaskPipeline, WorkflowCycleMa
             elif isinstance(event, QueueWorkflowFailedEvent | QueueStopEvent):
                 if not workflow_run:
                     raise Exception('Workflow run not initialized.')
-                
+
                 if not graph_runtime_state:
                     raise Exception('Graph runtime state not initialized.')
-                
+
                 workflow_run = self._handle_workflow_run_failed(
                     workflow_run=workflow_run,
                     start_at=graph_runtime_state.start_at,

api/core/app/entities/app_invoke_entities.py

@@ -166,4 +166,4 @@ class WorkflowAppGenerateEntity(AppGenerateEntity):
         node_id: str
         inputs: dict
 
-    single_iteration_run: Optional[SingleIterationRunEntity] = None
+    single_iteration_run: Optional[SingleIterationRunEntity] = None

api/core/app/segments/__init__.py

@@ -2,7 +2,6 @@ from .segment_group import SegmentGroup
 from .segments import (
     ArrayAnySegment,
     ArraySegment,
-    FileSegment,
     FloatSegment,
     IntegerSegment,
     NoneSegment,
@@ -13,11 +12,9 @@ from .segments import (
 from .types import SegmentType
 from .variables import (
     ArrayAnyVariable,
-    ArrayFileVariable,
     ArrayNumberVariable,
     ArrayObjectVariable,
     ArrayStringVariable,
-    FileVariable,
     FloatVariable,
     IntegerVariable,
     NoneVariable,
@@ -32,7 +29,6 @@ __all__ = [
     'FloatVariable',
     'ObjectVariable',
     'SecretVariable',
-    'FileVariable',
     'StringVariable',
     'ArrayAnyVariable',
     'Variable',
@@ -45,11 +41,9 @@ __all__ = [
     'FloatSegment',
     'ObjectSegment',
     'ArrayAnySegment',
-    'FileSegment',
     'StringSegment',
     'ArrayStringVariable',
     'ArrayNumberVariable',
     'ArrayObjectVariable',
-    'ArrayFileVariable',
     'ArraySegment',
 ]

api/core/app/segments/factory.py

@@ -2,12 +2,10 @@ from collections.abc import Mapping
 from typing import Any
 
 from configs import dify_config
-from core.file.file_obj import FileVar
 
 from .exc import VariableError
 from .segments import (
     ArrayAnySegment,
-    FileSegment,
     FloatSegment,
     IntegerSegment,
     NoneSegment,
@@ -17,11 +15,9 @@ from .segments import (
 )
 from .types import SegmentType
 from .variables import (
-    ArrayFileVariable,
     ArrayNumberVariable,
     ArrayObjectVariable,
     ArrayStringVariable,
-    FileVariable,
     FloatVariable,
     IntegerVariable,
     ObjectVariable,
@@ -49,8 +45,6 @@ def build_variable_from_mapping(mapping: Mapping[str, Any], /) -> Variable:
             result = FloatVariable.model_validate(mapping)
         case SegmentType.NUMBER if not isinstance(value, float | int):
             raise VariableError(f'invalid number value {value}')
-        case SegmentType.FILE:
-            result = FileVariable.model_validate(mapping)
         case SegmentType.OBJECT if isinstance(value, dict):
             result = ObjectVariable.model_validate(mapping)
         case SegmentType.ARRAY_STRING if isinstance(value, list):
@@ -59,10 +53,6 @@ def build_variable_from_mapping(mapping: Mapping[str, Any], /) -> Variable:
             result = ArrayNumberVariable.model_validate(mapping)
         case SegmentType.ARRAY_OBJECT if isinstance(value, list):
             result = ArrayObjectVariable.model_validate(mapping)
-        case SegmentType.ARRAY_FILE if isinstance(value, list):
-            mapping = dict(mapping)
-            mapping['value'] = [{'value': v} for v in value]
-            result = ArrayFileVariable.model_validate(mapping)
         case _:
             raise VariableError(f'not supported value type {value_type}')
     if result.size > dify_config.MAX_VARIABLE_SIZE:
@@ -83,6 +73,4 @@ def build_segment(value: Any, /) -> Segment:
         return ObjectSegment(value=value)
     if isinstance(value, list):
         return ArrayAnySegment(value=value)
-    if isinstance(value, FileVar):
-        return FileSegment(value=value)
     raise ValueError(f'not supported value {value}')

api/core/app/segments/segments.py

@@ -5,8 +5,6 @@ from typing import Any
 
 from pydantic import BaseModel, ConfigDict, field_validator
 
-from core.file.file_obj import FileVar
-
 from .types import SegmentType
 
 
@@ -78,14 +76,7 @@ class IntegerSegment(Segment):
     value: int
 
 
-class FileSegment(Segment):
-    value_type: SegmentType = SegmentType.FILE
-    # TODO: embed FileVar in this model.
-    value: FileVar
 
-    @property
-    def markdown(self) -> str:
-        return self.value.to_markdown()
 
 
 class ObjectSegment(Segment):
@@ -108,7 +99,13 @@ class ObjectSegment(Segment):
 class ArraySegment(Segment):
     @property
     def markdown(self) -> str:
-        return '\n'.join(['- ' + item.markdown for item in self.value])
+        items = []
+        for item in self.value:
+            if hasattr(item, 'to_markdown'):
+                items.append(item.to_markdown())
+            else:
+                items.append(str(item))
+        return '\n'.join(items)
 
 
 class ArrayAnySegment(ArraySegment):
@@ -130,7 +127,3 @@ class ArrayObjectSegment(ArraySegment):
     value_type: SegmentType = SegmentType.ARRAY_OBJECT
     value: Sequence[Mapping[str, Any]]
 
-
-class ArrayFileSegment(ArraySegment):
-    value_type: SegmentType = SegmentType.ARRAY_FILE
-    value: Sequence[FileSegment]

api/core/app/segments/types.py

@@ -10,8 +10,6 @@ class SegmentType(str, Enum):
     ARRAY_STRING = 'array[string]'
     ARRAY_NUMBER = 'array[number]'
     ARRAY_OBJECT = 'array[object]'
-    ARRAY_FILE = 'array[file]'
     OBJECT = 'object'
-    FILE = 'file'
 
     GROUP = 'group'

api/core/app/segments/variables.py

@@ -4,11 +4,9 @@ from core.helper import encrypter
 
 from .segments import (
     ArrayAnySegment,
-    ArrayFileSegment,
     ArrayNumberSegment,
     ArrayObjectSegment,
     ArrayStringSegment,
-    FileSegment,
     FloatSegment,
     IntegerSegment,
     NoneSegment,
@@ -44,10 +42,6 @@ class IntegerVariable(IntegerSegment, Variable):
     pass
 
 
-class FileVariable(FileSegment, Variable):
-    pass
-
-
 class ObjectVariable(ObjectSegment, Variable):
     pass
 
@@ -68,9 +62,6 @@ class ArrayObjectVariable(ArrayObjectSegment, Variable):
     pass
 
 
-class ArrayFileVariable(ArrayFileSegment, Variable):
-    pass
-
 
 class SecretVariable(StringVariable):
     value_type: SegmentType = SegmentType.SECRET

api/core/file/message_file_parser.py

@@ -99,7 +99,7 @@ class MessageFileParser:
         # return all file objs
         return new_files
 
-    def transform_message_files(self, files: list[MessageFile], file_extra_config: FileExtraConfig) -> list[FileVar]:
+    def transform_message_files(self, files: list[MessageFile], file_extra_config: FileExtraConfig):
         """
         transform message files
 
@@ -144,7 +144,7 @@ class MessageFileParser:
 
         return type_file_objs
 
-    def _to_file_obj(self, file: Union[dict, MessageFile], file_extra_config: FileExtraConfig) -> FileVar:
+    def _to_file_obj(self, file: Union[dict, MessageFile], file_extra_config: FileExtraConfig):
         """
         transform file to file obj
 

api/core/model_runtime/entities/defaults.py

@@ -1,4 +1,3 @@
-
 from core.model_runtime.entities.model_entities import DefaultParameterName
 
 PARAMETER_RULE_TEMPLATE: dict[DefaultParameterName, dict] = {
@@ -94,5 +93,16 @@ PARAMETER_RULE_TEMPLATE: dict[DefaultParameterName, dict] = {
         },
         'required': False,
         'options': ['JSON', 'XML'],
-    }
-}
+    },
+    DefaultParameterName.JSON_SCHEMA: {
+        'label': {
+            'en_US': 'JSON Schema',
+        },
+        'type': 'text',
+        'help': {
+            'en_US': 'Set a response json schema will ensure LLM to adhere it.',
+            'zh_Hans': '设置返回的json schema，llm将按照它返回',
+        },
+        'required': False,
+    },
+}

api/core/model_runtime/entities/model_entities.py

@@ -95,6 +95,7 @@ class DefaultParameterName(Enum):
     FREQUENCY_PENALTY = "frequency_penalty"
     MAX_TOKENS = "max_tokens"
     RESPONSE_FORMAT = "response_format"
+    JSON_SCHEMA = "json_schema"
 
     @classmethod
     def value_of(cls, value: Any) -> 'DefaultParameterName':
@@ -118,6 +119,7 @@ class ParameterType(Enum):
     INT = "int"
     STRING = "string"
     BOOLEAN = "boolean"
+    TEXT = "text"
 
 
 class ModelPropertyKey(Enum):

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

@@ -2,6 +2,7 @@
 - gpt-4o
 - gpt-4o-2024-05-13
 - gpt-4o-2024-08-06
+- chatgpt-4o-latest
 - gpt-4o-mini
 - gpt-4o-mini-2024-07-18
 - gpt-4-turbo

api/core/model_runtime/model_providers/openai/llm/chatgpt-4o-latest.yaml

@@ -0,0 +1,44 @@
+model: chatgpt-4o-latest
+label:
+  zh_Hans: chatgpt-4o-latest
+  en_US: chatgpt-4o-latest
+model_type: llm
+features:
+  - multi-tool-call
+  - agent-thought
+  - stream-tool-call
+  - vision
+model_properties:
+  mode: chat
+  context_size: 128000
+parameter_rules:
+  - name: temperature
+    use_template: temperature
+  - name: top_p
+    use_template: top_p
+  - name: presence_penalty
+    use_template: presence_penalty
+  - name: frequency_penalty
+    use_template: frequency_penalty
+  - name: max_tokens
+    use_template: max_tokens
+    default: 512
+    min: 1
+    max: 16384
+  - name: response_format
+    label:
+      zh_Hans: 回复格式
+      en_US: response_format
+    type: string
+    help:
+      zh_Hans: 指定模型必须输出的格式
+      en_US: specifying the format that the model must output
+    required: false
+    options:
+      - text
+      - json_object
+pricing:
+  input: '2.50'
+  output: '10.00'
+  unit: '0.000001'
+  currency: USD

api/core/model_runtime/model_providers/openai/llm/gpt-4o-2024-08-06.yaml

@@ -37,6 +37,9 @@ parameter_rules:
     options:
       - text
       - json_object
+      - json_schema
+  - name: json_schema
+    use_template: json_schema
 pricing:
   input: '2.50'
   output: '10.00'

api/core/model_runtime/model_providers/openai/llm/gpt-4o-mini.yaml

@@ -37,6 +37,9 @@ parameter_rules:
     options:
       - text
       - json_object
+      - json_schema
+  - name: json_schema
+    use_template: json_schema
 pricing:
   input: '0.15'
   output: '0.60'

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

@@ -1,3 +1,4 @@
+import json
 import logging
 from collections.abc import Generator
 from typing import Optional, Union, cast
@@ -544,13 +545,18 @@ class OpenAILargeLanguageModel(_CommonOpenAI, LargeLanguageModel):
 
         response_format = model_parameters.get("response_format")
         if response_format:
-            if response_format == "json_object":
-                response_format = {"type": "json_object"}
+            if response_format == "json_schema":
+                json_schema = model_parameters.get("json_schema")
+                if not json_schema:
+                    raise ValueError("Must define JSON Schema when the response format is json_schema")
+                try:
+                    schema = json.loads(json_schema)
+                except:
+                    raise ValueError(f"not currect json_schema format: {json_schema}")
+                model_parameters.pop("json_schema")
+                model_parameters["response_format"] = {"type": "json_schema", "json_schema": schema}
             else:
-                response_format = {"type": "text"}
-
-            model_parameters["response_format"] = response_format
-
+                model_parameters["response_format"] = {"type": response_format}
 
         extra_model_kwargs = {}
 
@@ -922,11 +928,14 @@ class OpenAILargeLanguageModel(_CommonOpenAI, LargeLanguageModel):
                                   tools: Optional[list[PromptMessageTool]] = None) -> int:
         """Calculate num tokens for gpt-3.5-turbo and gpt-4 with tiktoken package.
 
-        Official documentation: https://github.com/openai/openai-cookbook/blob/
-        main/examples/How_to_format_inputs_to_ChatGPT_models.ipynb"""
+        Official documentation: https://github.com/openai/openai-cookbook/blob/main/examples/How_to_format_inputs_to_ChatGPT_models.ipynb"""
         if model.startswith('ft:'):
             model = model.split(':')[1]
 
+        # Currently, we can use gpt4o to calculate chatgpt-4o-latest's token.
+        if model == "chatgpt-4o-latest":
+            model = "gpt-4o"
+
         try:
             encoding = tiktoken.encoding_for_model(model)
         except KeyError:
@@ -946,7 +955,7 @@ class OpenAILargeLanguageModel(_CommonOpenAI, LargeLanguageModel):
             raise NotImplementedError(
                 f"get_num_tokens_from_messages() is not presently implemented "
                 f"for model {model}."
-                "See https://github.com/openai/openai-python/blob/main/chatml.md for "
+                "See https://platform.openai.com/docs/advanced-usage/managing-tokens for "
                 "information on how messages are converted to tokens."
             )
         num_tokens = 0

api/core/model_runtime/model_providers/perfxcloud/llm/Llama3-Chinese_v2.yaml

@@ -0,0 +1,61 @@
+model: Llama3-Chinese_v2
+label:
+  en_US: Llama3-Chinese_v2
+model_type: llm
+features:
+  - agent-thought
+model_properties:
+  mode: chat
+  context_size: 8192
+parameter_rules:
+  - name: temperature
+    use_template: temperature
+    type: float
+    default: 0.5
+    min: 0.0
+    max: 2.0
+    help:
+      zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。
+      en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain.
+  - name: max_tokens
+    use_template: max_tokens
+    type: int
+    default: 600
+    min: 1
+    max: 1248
+    help:
+      zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。
+      en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time.
+  - name: top_p
+    use_template: top_p
+    type: float
+    default: 0.8
+    min: 0.1
+    max: 0.9
+    help:
+      zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。
+      en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated.
+  - name: top_k
+    type: int
+    min: 0
+    max: 99
+    label:
+      zh_Hans: 取样数量
+      en_US: Top k
+    help:
+      zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。
+      en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated.
+  - name: repetition_penalty
+    required: false
+    type: float
+    default: 1.1
+    label:
+      en_US: Repetition penalty
+    help:
+      zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。
+      en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment.
+pricing:
+  input: "0.000"
+  output: "0.000"
+  unit: "0.000"
+  currency: RMB

api/core/model_runtime/model_providers/perfxcloud/llm/Meta-Llama-3-70B-Instruct-GPTQ-Int4.yaml

@@ -0,0 +1,61 @@
+model: Meta-Llama-3-70B-Instruct-GPTQ-Int4
+label:
+  en_US: Meta-Llama-3-70B-Instruct-GPTQ-Int4
+model_type: llm
+features:
+  - agent-thought
+model_properties:
+  mode: chat
+  context_size: 1024
+parameter_rules:
+  - name: temperature
+    use_template: temperature
+    type: float
+    default: 0.5
+    min: 0.0
+    max: 2.0
+    help:
+      zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。
+      en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain.
+  - name: max_tokens
+    use_template: max_tokens
+    type: int
+    default: 600
+    min: 1
+    max: 1248
+    help:
+      zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。
+      en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time.
+  - name: top_p
+    use_template: top_p
+    type: float
+    default: 0.8
+    min: 0.1
+    max: 0.9
+    help:
+      zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。
+      en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated.
+  - name: top_k
+    type: int
+    min: 0
+    max: 99
+    label:
+      zh_Hans: 取样数量
+      en_US: Top k
+    help:
+      zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。
+      en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated.
+  - name: repetition_penalty
+    required: false
+    type: float
+    default: 1.1
+    label:
+      en_US: Repetition penalty
+    help:
+      zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。
+      en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment.
+pricing:
+  input: "0.000"
+  output: "0.000"
+  unit: "0.000"
+  currency: RMB

api/core/model_runtime/model_providers/perfxcloud/llm/Meta-Llama-3-8B-Instruct.yaml

@@ -0,0 +1,61 @@
+model: Meta-Llama-3-8B-Instruct
+label:
+  en_US: Meta-Llama-3-8B-Instruct
+model_type: llm
+features:
+  - agent-thought
+model_properties:
+  mode: chat
+  context_size: 8192
+parameter_rules:
+  - name: temperature
+    use_template: temperature
+    type: float
+    default: 0.5
+    min: 0.0
+    max: 2.0
+    help:
+      zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。
+      en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain.
+  - name: max_tokens
+    use_template: max_tokens
+    type: int
+    default: 600
+    min: 1
+    max: 1248
+    help:
+      zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。
+      en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time.
+  - name: top_p
+    use_template: top_p
+    type: float
+    default: 0.8
+    min: 0.1
+    max: 0.9
+    help:
+      zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。
+      en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated.
+  - name: top_k
+    type: int
+    min: 0
+    max: 99
+    label:
+      zh_Hans: 取样数量
+      en_US: Top k
+    help:
+      zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。
+      en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated.
+  - name: repetition_penalty
+    required: false
+    type: float
+    default: 1.1
+    label:
+      en_US: Repetition penalty
+    help:
+      zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。
+      en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment.
+pricing:
+  input: "0.000"
+  output: "0.000"
+  unit: "0.000"
+  currency: RMB

api/core/model_runtime/model_providers/perfxcloud/llm/Meta-Llama-3.1-405B-Instruct-AWQ-INT4.yaml

@@ -0,0 +1,61 @@
+model: Meta-Llama-3.1-405B-Instruct-AWQ-INT4
+label:
+  en_US: Meta-Llama-3.1-405B-Instruct-AWQ-INT4
+model_type: llm
+features:
+  - agent-thought
+model_properties:
+  mode: chat
+  context_size: 410960
+parameter_rules:
+  - name: temperature
+    use_template: temperature
+    type: float
+    default: 0.5
+    min: 0.0
+    max: 2.0
+    help:
+      zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。
+      en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain.
+  - name: max_tokens
+    use_template: max_tokens
+    type: int
+    default: 600
+    min: 1
+    max: 1248
+    help:
+      zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。
+      en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time.
+  - name: top_p
+    use_template: top_p
+    type: float
+    default: 0.8
+    min: 0.1
+    max: 0.9
+    help:
+      zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。
+      en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated.
+  - name: top_k
+    type: int
+    min: 0
+    max: 99
+    label:
+      zh_Hans: 取样数量
+      en_US: Top k
+    help:
+      zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。
+      en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated.
+  - name: repetition_penalty
+    required: false
+    type: float
+    default: 1.1
+    label:
+      en_US: Repetition penalty
+    help:
+      zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。
+      en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment.
+pricing:
+  input: "0.000"
+  output: "0.000"
+  unit: "0.000"
+  currency: RMB

api/core/model_runtime/model_providers/perfxcloud/llm/Meta-Llama-3.1-8B-Instruct.yaml

@@ -0,0 +1,61 @@
+model: Meta-Llama-3.1-8B-Instruct
+label:
+  en_US: Meta-Llama-3.1-8B-Instruct
+model_type: llm
+features:
+  - agent-thought
+model_properties:
+  mode: chat
+  context_size: 4096
+parameter_rules:
+  - name: temperature
+    use_template: temperature
+    type: float
+    default: 0.1
+    min: 0.0
+    max: 2.0
+    help:
+      zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。
+      en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain.
+  - name: max_tokens
+    use_template: max_tokens
+    type: int
+    default: 600
+    min: 1
+    max: 1248
+    help:
+      zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。
+      en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time.
+  - name: top_p
+    use_template: top_p
+    type: float
+    default: 0.8
+    min: 0.1
+    max: 0.9
+    help:
+      zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。
+      en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated.
+  - name: top_k
+    type: int
+    min: 0
+    max: 99
+    label:
+      zh_Hans: 取样数量
+      en_US: Top k
+    help:
+      zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。
+      en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated.
+  - name: repetition_penalty
+    required: false
+    type: float
+    default: 1.1
+    label:
+      en_US: Repetition penalty
+    help:
+      zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。
+      en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment.
+pricing:
+  input: "0.000"
+  output: "0.000"
+  unit: "0.000"
+  currency: RMB

api/core/model_runtime/model_providers/perfxcloud/llm/Qwen-14B-Chat-Int4.yaml

@@ -55,7 +55,8 @@ parameter_rules:
       zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。
       en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment.
 pricing:
-  input: '0.000'
-  output: '0.000'
-  unit: '0.000'
+  input: "0.000"
+  output: "0.000"
+  unit: "0.000"
   currency: RMB
+deprecated: true

api/core/model_runtime/model_providers/perfxcloud/llm/Qwen1.5-110B-Chat-GPTQ-Int4.yaml

@@ -55,7 +55,8 @@ parameter_rules:
       zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。
       en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment.
 pricing:
-  input: '0.000'
-  output: '0.000'
-  unit: '0.000'
+  input: "0.000"
+  output: "0.000"
+  unit: "0.000"
   currency: RMB
+deprecated: true

api/core/model_runtime/model_providers/perfxcloud/llm/Qwen1.5-72B-Chat-GPTQ-Int4.yaml

@@ -6,7 +6,7 @@ features:
   - agent-thought
 model_properties:
   mode: chat
-  context_size: 8192
+  context_size: 2048
 parameter_rules:
   - name: temperature
     use_template: temperature
@@ -55,7 +55,7 @@ parameter_rules:
       zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。
       en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment.
 pricing:
-  input: '0.000'
-  output: '0.000'
-  unit: '0.000'
+  input: "0.000"
+  output: "0.000"
+  unit: "0.000"
   currency: RMB

api/core/model_runtime/model_providers/perfxcloud/llm/Qwen1.5-7B.yaml

@@ -6,7 +6,7 @@ features:
   - agent-thought
 model_properties:
   mode: completion
-  context_size: 8192
+  context_size: 32768
 parameter_rules:
   - name: temperature
     use_template: temperature
@@ -55,7 +55,7 @@ parameter_rules:
       zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。
       en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment.
 pricing:
-  input: '0.000'
-  output: '0.000'
-  unit: '0.000'
+  input: "0.000"
+  output: "0.000"
+  unit: "0.000"
   currency: RMB

api/core/model_runtime/model_providers/perfxcloud/llm/Qwen2-72B-Instruct-GPTQ-Int4.yaml

@@ -8,12 +8,12 @@ features:
   - stream-tool-call
 model_properties:
   mode: chat
-  context_size: 8192
+  context_size: 2048
 parameter_rules:
   - name: temperature
     use_template: temperature
     type: float
-    default: 0.3
+    default: 0.7
     min: 0.0
     max: 2.0
     help:
@@ -57,7 +57,7 @@ parameter_rules:
       zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。
       en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment.
 pricing:
-  input: '0.000'
-  output: '0.000'
-  unit: '0.000'
+  input: "0.000"
+  output: "0.000"
+  unit: "0.000"
   currency: RMB

api/core/model_runtime/model_providers/perfxcloud/llm/Qwen2-72B-Instruct.yaml

@@ -0,0 +1,61 @@
+model: Qwen2-72B-Instruct
+label:
+  en_US: Qwen2-72B-Instruct
+model_type: llm
+features:
+  - agent-thought
+model_properties:
+  mode: chat
+  context_size: 131072
+parameter_rules:
+  - name: temperature
+    use_template: temperature
+    type: float
+    default: 0.5
+    min: 0.0
+    max: 2.0
+    help:
+      zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。
+      en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain.
+  - name: max_tokens
+    use_template: max_tokens
+    type: int
+    default: 600
+    min: 1
+    max: 1248
+    help:
+      zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。
+      en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time.
+  - name: top_p
+    use_template: top_p
+    type: float
+    default: 0.8
+    min: 0.1
+    max: 0.9
+    help:
+      zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。
+      en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated.
+  - name: top_k
+    type: int
+    min: 0
+    max: 99
+    label:
+      zh_Hans: 取样数量
+      en_US: Top k
+    help:
+      zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。
+      en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated.
+  - name: repetition_penalty
+    required: false
+    type: float
+    default: 1.1
+    label:
+      en_US: Repetition penalty
+    help:
+      zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。
+      en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment.
+pricing:
+  input: "0.000"
+  output: "0.000"
+  unit: "0.000"
+  currency: RMB

api/core/model_runtime/model_providers/perfxcloud/llm/Qwen2-7B.yaml

@@ -8,7 +8,7 @@ features:
   - stream-tool-call
 model_properties:
   mode: completion
-  context_size: 8192
+  context_size: 32768
 parameter_rules:
   - name: temperature
     use_template: temperature
@@ -57,7 +57,7 @@ parameter_rules:
       zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。
       en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment.
 pricing:
-  input: '0.000'
-  output: '0.000'
-  unit: '0.000'
+  input: "0.000"
+  output: "0.000"
+  unit: "0.000"
   currency: RMB

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

@@ -1,6 +1,15 @@
+- Meta-Llama-3.1-405B-Instruct-AWQ-INT4
+- Meta-Llama-3.1-8B-Instruct
+- Meta-Llama-3-70B-Instruct-GPTQ-Int4
+- Meta-Llama-3-8B-Instruct
 - Qwen2-72B-Instruct-GPTQ-Int4
+- Qwen2-72B-Instruct
 - Qwen2-7B
-- Qwen1.5-110B-Chat-GPTQ-Int4
+- Qwen-14B-Chat-Int4
 - Qwen1.5-72B-Chat-GPTQ-Int4
 - Qwen1.5-7B
-- Qwen-14B-Chat-Int4
+- Qwen1.5-110B-Chat-GPTQ-Int4
+- deepseek-v2-chat
+- deepseek-v2-lite-chat
+- Llama3-Chinese_v2
+- chatglm3-6b

api/core/model_runtime/model_providers/perfxcloud/llm/chatglm3-6b.yaml

@@ -0,0 +1,61 @@
+model: chatglm3-6b
+label:
+  en_US: chatglm3-6b
+model_type: llm
+features:
+  - agent-thought
+model_properties:
+  mode: chat
+  context_size: 8192
+parameter_rules:
+  - name: temperature
+    use_template: temperature
+    type: float
+    default: 0.5
+    min: 0.0
+    max: 2.0
+    help:
+      zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。
+      en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain.
+  - name: max_tokens
+    use_template: max_tokens
+    type: int
+    default: 600
+    min: 1
+    max: 1248
+    help:
+      zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。
+      en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time.
+  - name: top_p
+    use_template: top_p
+    type: float
+    default: 0.8
+    min: 0.1
+    max: 0.9
+    help:
+      zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。
+      en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated.
+  - name: top_k
+    type: int
+    min: 0
+    max: 99
+    label:
+      zh_Hans: 取样数量
+      en_US: Top k
+    help:
+      zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。
+      en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated.
+  - name: repetition_penalty
+    required: false
+    type: float
+    default: 1.1
+    label:
+      en_US: Repetition penalty
+    help:
+      zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。
+      en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment.
+pricing:
+  input: "0.000"
+  output: "0.000"
+  unit: "0.000"
+  currency: RMB

api/core/model_runtime/model_providers/perfxcloud/llm/deepseek-v2-chat.yaml

@@ -0,0 +1,61 @@
+model: deepseek-v2-chat
+label:
+  en_US: deepseek-v2-chat
+model_type: llm
+features:
+  - agent-thought
+model_properties:
+  mode: chat
+  context_size: 4096
+parameter_rules:
+  - name: temperature
+    use_template: temperature
+    type: float
+    default: 0.5
+    min: 0.0
+    max: 2.0
+    help:
+      zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。
+      en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain.
+  - name: max_tokens
+    use_template: max_tokens
+    type: int
+    default: 600
+    min: 1
+    max: 1248
+    help:
+      zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。
+      en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time.
+  - name: top_p
+    use_template: top_p
+    type: float
+    default: 0.8
+    min: 0.1
+    max: 0.9
+    help:
+      zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。
+      en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated.
+  - name: top_k
+    type: int
+    min: 0
+    max: 99
+    label:
+      zh_Hans: 取样数量
+      en_US: Top k
+    help:
+      zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。
+      en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated.
+  - name: repetition_penalty
+    required: false
+    type: float
+    default: 1.1
+    label:
+      en_US: Repetition penalty
+    help:
+      zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。
+      en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment.
+pricing:
+  input: "0.000"
+  output: "0.000"
+  unit: "0.000"
+  currency: RMB

api/core/model_runtime/model_providers/perfxcloud/llm/deepseek-v2-lite-chat.yaml

@@ -0,0 +1,61 @@
+model: deepseek-v2-lite-chat
+label:
+  en_US: deepseek-v2-lite-chat
+model_type: llm
+features:
+  - agent-thought
+model_properties:
+  mode: chat
+  context_size: 2048
+parameter_rules:
+  - name: temperature
+    use_template: temperature
+    type: float
+    default: 0.5
+    min: 0.0
+    max: 2.0
+    help:
+      zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。
+      en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain.
+  - name: max_tokens
+    use_template: max_tokens
+    type: int
+    default: 600
+    min: 1
+    max: 1248
+    help:
+      zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。
+      en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time.
+  - name: top_p
+    use_template: top_p
+    type: float
+    default: 0.8
+    min: 0.1
+    max: 0.9
+    help:
+      zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。
+      en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated.
+  - name: top_k
+    type: int
+    min: 0
+    max: 99
+    label:
+      zh_Hans: 取样数量
+      en_US: Top k
+    help:
+      zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。
+      en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated.
+  - name: repetition_penalty
+    required: false
+    type: float
+    default: 1.1
+    label:
+      en_US: Repetition penalty
+    help:
+      zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。
+      en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment.
+pricing:
+  input: "0.000"
+  output: "0.000"
+  unit: "0.000"
+  currency: RMB

api/core/model_runtime/model_providers/perfxcloud/text_embedding/BAAI-bge-large-en-v1.5.yaml

@@ -0,0 +1,4 @@
+model: BAAI/bge-large-en-v1.5
+model_type: text-embedding
+model_properties:
+  context_size: 32768

api/core/model_runtime/model_providers/perfxcloud/text_embedding/BAAI-bge-large-zh-v1.5.yaml

@@ -0,0 +1,4 @@
+model: BAAI/bge-large-zh-v1.5
+model_type: text-embedding
+model_properties:
+  context_size: 32768

api/core/model_runtime/model_providers/tongyi/llm/farui-plus.yaml

@@ -0,0 +1,81 @@
+model: farui-plus
+label:
+  en_US: farui-plus
+model_type: llm
+features:
+  - multi-tool-call
+  - agent-thought
+  - stream-tool-call
+model_properties:
+  mode: chat
+  context_size: 12288
+parameter_rules:
+  - name: temperature
+    use_template: temperature
+    type: float
+    default: 0.3
+    min: 0.0
+    max: 2.0
+    help:
+      zh_Hans: 用于控制随机性和多样性的程度。具体来说，temperature值控制了生成文本时对每个候选词的概率分布进行平滑的程度。较高的temperature值会降低概率分布的峰值，使得更多的低概率词被选择，生成结果更加多样化；而较低的temperature值则会增强概率分布的峰值，使得高概率词更容易被选择，生成结果更加确定。
+      en_US: Used to control the degree of randomness and diversity. Specifically, the temperature value controls the degree to which the probability distribution of each candidate word is smoothed when generating text. A higher temperature value will reduce the peak value of the probability distribution, allowing more low-probability words to be selected, and the generated results will be more diverse; while a lower temperature value will enhance the peak value of the probability distribution, making it easier for high-probability words to be selected. , the generated results are more certain.
+  - name: max_tokens
+    use_template: max_tokens
+    type: int
+    default: 2000
+    min: 1
+    max: 2000
+    help:
+      zh_Hans: 用于指定模型在生成内容时token的最大数量，它定义了生成的上限，但不保证每次都会生成到这个数量。
+      en_US: It is used to specify the maximum number of tokens when the model generates content. It defines the upper limit of generation, but does not guarantee that this number will be generated every time.
+  - name: top_p
+    use_template: top_p
+    type: float
+    default: 0.8
+    min: 0.1
+    max: 0.9
+    help:
+      zh_Hans: 生成过程中核采样方法概率阈值，例如，取值为0.8时，仅保留概率加起来大于等于0.8的最可能token的最小集合作为候选集。取值范围为（0,1.0)，取值越大，生成的随机性越高；取值越低，生成的确定性越高。
+      en_US: The probability threshold of the kernel sampling method during the generation process. For example, when the value is 0.8, only the smallest set of the most likely tokens with a sum of probabilities greater than or equal to 0.8 is retained as the candidate set. The value range is (0,1.0). The larger the value, the higher the randomness generated; the lower the value, the higher the certainty generated.
+  - name: top_k
+    type: int
+    min: 0
+    max: 99
+    label:
+      zh_Hans: 取样数量
+      en_US: Top k
+    help:
+      zh_Hans: 生成时，采样候选集的大小。例如，取值为50时，仅将单次生成中得分最高的50个token组成随机采样的候选集。取值越大，生成的随机性越高；取值越小，生成的确定性越高。
+      en_US: The size of the sample candidate set when generated. For example, when the value is 50, only the 50 highest-scoring tokens in a single generation form a randomly sampled candidate set. The larger the value, the higher the randomness generated; the smaller the value, the higher the certainty generated.
+  - name: seed
+    required: false
+    type: int
+    default: 1234
+    label:
+      zh_Hans: 随机种子
+      en_US: Random seed
+    help:
+      zh_Hans: 生成时使用的随机数种子，用户控制模型生成内容的随机性。支持无符号64位整数，默认值为 1234。在使用seed时，模型将尽可能生成相同或相似的结果，但目前不保证每次生成的结果完全相同。
+      en_US: The random number seed used when generating, the user controls the randomness of the content generated by the model. Supports unsigned 64-bit integers, default value is 1234. When using seed, the model will try its best to generate the same or similar results, but there is currently no guarantee that the results will be exactly the same every time.
+  - name: repetition_penalty
+    required: false
+    type: float
+    default: 1.1
+    label:
+      en_US: Repetition penalty
+    help:
+      zh_Hans: 用于控制模型生成时的重复度。提高repetition_penalty时可以降低模型生成的重复度。1.0表示不做惩罚。
+      en_US: Used to control the repeatability when generating models. Increasing repetition_penalty can reduce the duplication of model generation. 1.0 means no punishment.
+  - name: enable_search
+    type: boolean
+    default: false
+    help:
+      zh_Hans: 模型内置了互联网搜索服务，该参数控制模型在生成文本时是否参考使用互联网搜索结果。启用互联网搜索，模型会将搜索结果作为文本生成过程中的参考信息，但模型会基于其内部逻辑“自行判断”是否使用互联网搜索结果。
+      en_US: The model has a built-in Internet search service. This parameter controls whether the model refers to Internet search results when generating text. When Internet search is enabled, the model will use the search results as reference information in the text generation process, but the model will "judge" whether to use Internet search results based on its internal logic.
+  - name: response_format
+    use_template: response_format
+pricing:
+  input: '0.02'
+  output: '0.02'
+  unit: '0.001'
+  currency: RMB

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

@@ -159,6 +159,8 @@ You should also complete the text started with ``` but not tell ``` directly.
         """
         if model in ['qwen-turbo-chat', 'qwen-plus-chat']:
             model = model.replace('-chat', '')
+        if model == 'farui-plus':
+            model = 'qwen-farui-plus'
 
         if model in self.tokenizers:
             tokenizer = self.tokenizers[model]

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

@@ -1 +1 @@
-- soloar-1-mini-chat
+- solar-1-mini-chat

api/core/prompt/simple_prompt_transform.py

@@ -1,11 +1,10 @@
 import enum
 import json
 import os
-from typing import Optional
+from typing import TYPE_CHECKING, Optional
 
 from core.app.app_config.entities import PromptTemplateEntity
 from core.app.entities.app_invoke_entities import ModelConfigWithCredentialsEntity
-from core.file.file_obj import FileVar
 from core.memory.token_buffer_memory import TokenBufferMemory
 from core.model_runtime.entities.message_entities import (
     PromptMessage,
@@ -18,6 +17,9 @@ from core.prompt.prompt_transform import PromptTransform
 from core.prompt.utils.prompt_template_parser import PromptTemplateParser
 from models.model import AppMode
 
+if TYPE_CHECKING:
+    from core.file.file_obj import FileVar
+
 
 class ModelMode(enum.Enum):
     COMPLETION = 'completion'
@@ -50,7 +52,7 @@ class SimplePromptTransform(PromptTransform):
                    prompt_template_entity: PromptTemplateEntity,
                    inputs: dict,
                    query: str,
-                   files: list[FileVar],
+                   files: list["FileVar"],
                    context: Optional[str],
                    memory: Optional[TokenBufferMemory],
                    model_config: ModelConfigWithCredentialsEntity) -> \
@@ -163,7 +165,7 @@ class SimplePromptTransform(PromptTransform):
                                         inputs: dict,
                                         query: str,
                                         context: Optional[str],
-                                        files: list[FileVar],
+                                        files: list["FileVar"],
                                         memory: Optional[TokenBufferMemory],
                                         model_config: ModelConfigWithCredentialsEntity) \
             -> tuple[list[PromptMessage], Optional[list[str]]]:
@@ -206,7 +208,7 @@ class SimplePromptTransform(PromptTransform):
                                               inputs: dict,
                                               query: str,
                                               context: Optional[str],
-                                              files: list[FileVar],
+                                              files: list["FileVar"],
                                               memory: Optional[TokenBufferMemory],
                                               model_config: ModelConfigWithCredentialsEntity) \
             -> tuple[list[PromptMessage], Optional[list[str]]]:
@@ -255,7 +257,7 @@ class SimplePromptTransform(PromptTransform):
 
         return [self.get_last_user_message(prompt, files)], stops
 
-    def get_last_user_message(self, prompt: str, files: list[FileVar]) -> UserPromptMessage:
+    def get_last_user_message(self, prompt: str, files: list["FileVar"]) -> UserPromptMessage:
         if files:
             prompt_message_contents = [TextPromptMessageContent(data=prompt)]
             for file in files:

api/core/rag/datasource/vdb/elasticsearch/elasticsearch_vector.py

@@ -0,0 +1,191 @@
+import json
+from typing import Any
+
+import requests
+from elasticsearch import Elasticsearch
+from flask import current_app
+from pydantic import BaseModel, model_validator
+
+from core.rag.datasource.entity.embedding import Embeddings
+from core.rag.datasource.vdb.vector_base import BaseVector
+from core.rag.datasource.vdb.vector_factory import AbstractVectorFactory
+from core.rag.datasource.vdb.vector_type import VectorType
+from core.rag.models.document import Document
+from models.dataset import Dataset
+
+
+class ElasticSearchConfig(BaseModel):
+    host: str
+    port: str
+    username: str
+    password: str
+
+    @model_validator(mode='before')
+    def validate_config(cls, values: dict) -> dict:
+        if not values['host']:
+            raise ValueError("config HOST is required")
+        if not values['port']:
+            raise ValueError("config PORT is required")
+        if not values['username']:
+            raise ValueError("config USERNAME is required")
+        if not values['password']:
+            raise ValueError("config PASSWORD is required")
+        return values
+
+
+class ElasticSearchVector(BaseVector):
+    def __init__(self, index_name: str, config: ElasticSearchConfig, attributes: list):
+        super().__init__(index_name.lower())
+        self._client = self._init_client(config)
+        self._attributes = attributes
+
+    def _init_client(self, config: ElasticSearchConfig) -> Elasticsearch:
+        try:
+            client = Elasticsearch(
+                hosts=f'{config.host}:{config.port}',
+                basic_auth=(config.username, config.password),
+                request_timeout=100000,
+                retry_on_timeout=True,
+                max_retries=10000,
+            )
+        except requests.exceptions.ConnectionError:
+            raise ConnectionError("Vector database connection error")
+
+        return client
+
+    def get_type(self) -> str:
+        return 'elasticsearch'
+
+    def add_texts(self, documents: list[Document], embeddings: list[list[float]], **kwargs):
+        uuids = self._get_uuids(documents)
+        texts = [d.page_content for d in documents]
+        metadatas = [d.metadata for d in documents]
+
+        if not self._client.indices.exists(index=self._collection_name):
+            dim = len(embeddings[0])
+            mapping = {
+                "properties": {
+                    "text": {
+                        "type": "text"
+                    },
+                    "vector": {
+                        "type": "dense_vector",
+                        "index": True,
+                        "dims": dim,
+                        "similarity": "l2_norm"
+                    },
+                }
+            }
+            self._client.indices.create(index=self._collection_name, mappings=mapping)
+
+        added_ids = []
+        for i, text in enumerate(texts):
+            self._client.index(index=self._collection_name,
+                               id=uuids[i],
+                               document={
+                                   "text": text,
+                                   "vector": embeddings[i] if embeddings[i] else None,
+                                   "metadata": metadatas[i] if metadatas[i] else {},
+                               })
+            added_ids.append(uuids[i])
+
+        self._client.indices.refresh(index=self._collection_name)
+        return uuids
+
+    def text_exists(self, id: str) -> bool:
+        return self._client.exists(index=self._collection_name, id=id).__bool__()
+
+    def delete_by_ids(self, ids: list[str]) -> None:
+        for id in ids:
+            self._client.delete(index=self._collection_name, id=id)
+
+    def delete_by_metadata_field(self, key: str, value: str) -> None:
+        query_str = {
+            'query': {
+                'match': {
+                    f'metadata.{key}': f'{value}'
+                }
+            }
+        }
+        results = self._client.search(index=self._collection_name, body=query_str)
+        ids = [hit['_id'] for hit in results['hits']['hits']]
+        if ids:
+            self.delete_by_ids(ids)
+
+    def delete(self) -> None:
+        self._client.indices.delete(index=self._collection_name)
+
+    def search_by_vector(self, query_vector: list[float], **kwargs: Any) -> list[Document]:
+        query_str = {
+            "query": {
+                "script_score": {
+                    "query": {
+                        "match_all": {}
+                    },
+                    "script": {
+                        "source": "cosineSimilarity(params.query_vector, 'vector') + 1.0",
+                        "params": {
+                            "query_vector": query_vector
+                        }
+                    }
+                }
+            }
+        }
+
+        results = self._client.search(index=self._collection_name, body=query_str)
+
+        docs_and_scores = []
+        for hit in results['hits']['hits']:
+            docs_and_scores.append(
+                (Document(page_content=hit['_source']['text'], metadata=hit['_source']['metadata']), hit['_score']))
+
+        docs = []
+        for doc, score in docs_and_scores:
+            score_threshold = kwargs.get("score_threshold", .0) if kwargs.get('score_threshold', .0) else 0.0
+            if score > score_threshold:
+                doc.metadata['score'] = score
+            docs.append(doc)
+
+        # Sort the documents by score in descending order
+        docs = sorted(docs, key=lambda x: x.metadata['score'], reverse=True)
+
+        return docs
+    def search_by_full_text(self, query: str, **kwargs: Any) -> list[Document]:
+        query_str = {
+            "match": {
+                "text": query
+            }
+        }
+        results = self._client.search(index=self._collection_name, query=query_str)
+        docs = []
+        for hit in results['hits']['hits']:
+            docs.append(Document(page_content=hit['_source']['text'], metadata=hit['_source']['metadata']))
+
+        return docs
+
+    def create(self, texts: list[Document], embeddings: list[list[float]], **kwargs):
+        return self.add_texts(texts, embeddings, **kwargs)
+
+
+class ElasticSearchVectorFactory(AbstractVectorFactory):
+    def init_vector(self, dataset: Dataset, attributes: list, embeddings: Embeddings) -> ElasticSearchVector:
+        if dataset.index_struct_dict:
+            class_prefix: str = dataset.index_struct_dict['vector_store']['class_prefix']
+            collection_name = class_prefix
+        else:
+            dataset_id = dataset.id
+            collection_name = Dataset.gen_collection_name_by_id(dataset_id)
+            dataset.index_struct = json.dumps(
+                self.gen_index_struct_dict(VectorType.ELASTICSEARCH, collection_name))
+
+        config = current_app.config
+        return ElasticSearchVector(
+            index_name=collection_name,
+            config=ElasticSearchConfig(
+                host=config.get('ELASTICSEARCH_HOST'),
+                port=config.get('ELASTICSEARCH_PORT'),
+                username=config.get('ELASTICSEARCH_USERNAME'),
+                password=config.get('ELASTICSEARCH_PASSWORD'),
+            ),
+            attributes=[]
+        )

api/core/rag/datasource/vdb/myscale/myscale_vector.py

@@ -93,7 +93,7 @@ class MyScaleVector(BaseVector):
 
     @staticmethod
     def escape_str(value: Any) -> str:
-        return "".join(f"\\{c}" if c in ("\\", "'") else c for c in str(value))
+        return "".join(" " if c in ("\\", "'") else c for c in str(value))
 
     def text_exists(self, id: str) -> bool:
         results = self._client.query(f"SELECT id FROM {self._config.database}.{self._collection_name} WHERE id='{id}'")
@@ -118,7 +118,7 @@ class MyScaleVector(BaseVector):
         return self._search(f"distance(vector, {str(query_vector)})", self._vec_order, **kwargs)
 
     def search_by_full_text(self, query: str, **kwargs: Any) -> list[Document]:
-        return self._search(f"TextSearch(text, '{query}')", SortOrder.DESC, **kwargs)
+        return self._search(f"TextSearch('enable_nlq=false')(text, '{query}')", SortOrder.DESC, **kwargs)
 
     def _search(self, dist: str, order: SortOrder, **kwargs: Any) -> list[Document]:
         top_k = kwargs.get("top_k", 5)

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

@@ -71,6 +71,9 @@ class Vector:
             case VectorType.RELYT:
                 from core.rag.datasource.vdb.relyt.relyt_vector import RelytVectorFactory
                 return RelytVectorFactory
+            case VectorType.ELASTICSEARCH:
+                from core.rag.datasource.vdb.elasticsearch.elasticsearch_vector import ElasticSearchVectorFactory
+                return ElasticSearchVectorFactory
             case VectorType.TIDB_VECTOR:
                 from core.rag.datasource.vdb.tidb_vector.tidb_vector import TiDBVectorFactory
                 return TiDBVectorFactory

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

@@ -15,3 +15,4 @@ class VectorType(str, Enum):
     OPENSEARCH = 'opensearch'
     TENCENT = 'tencent'
     ORACLE = 'oracle'
+    ELASTICSEARCH = 'elasticsearch'

api/core/tools/entities/tool_entities.py

@@ -46,7 +46,7 @@ class ToolProviderType(Enum):
             if mode.value == value:
                 return mode
         raise ValueError(f'invalid mode value {value}')
-    
+
 class ApiProviderSchemaType(Enum):
     """
     Enum class for api provider schema type.
@@ -68,7 +68,7 @@ class ApiProviderSchemaType(Enum):
             if mode.value == value:
                 return mode
         raise ValueError(f'invalid mode value {value}')
-    
+
 class ApiProviderAuthType(Enum):
     """
     Enum class for api provider auth type.
@@ -103,8 +103,8 @@ class ToolInvokeMessage(BaseModel):
     """
         plain text, image url or link url
     """
-    message: Union[str, bytes, dict] = None
-    meta: dict[str, Any] = None
+    message: str | bytes | dict | None = None
+    meta: dict[str, Any] | None = None
     save_as: str = ''
 
 class ToolInvokeMessageBinary(BaseModel):
@@ -154,8 +154,8 @@ class ToolParameter(BaseModel):
     options: Optional[list[ToolParameterOption]] = None
 
     @classmethod
-    def get_simple_instance(cls, 
-                       name: str, llm_description: str, type: ToolParameterType, 
+    def get_simple_instance(cls,
+                       name: str, llm_description: str, type: ToolParameterType,
                        required: bool, options: Optional[list[str]] = None) -> 'ToolParameter':
         """
             get a simple tool parameter
@@ -222,7 +222,7 @@ class ToolProviderCredentials(BaseModel):
                 if mode.value == value:
                     return mode
             raise ValueError(f'invalid mode value {value}')
-        
+
         @staticmethod
         def default(value: str) -> str:
             return ""
@@ -290,7 +290,7 @@ class ToolRuntimeVariablePool(BaseModel):
             'tenant_id': self.tenant_id,
             'pool': [variable.model_dump() for variable in self.pool],
         }
-    
+
     def set_text(self, tool_name: str, name: str, value: str) -> None:
         """
             set a text variable
@@ -301,7 +301,7 @@ class ToolRuntimeVariablePool(BaseModel):
                     variable = cast(ToolRuntimeTextVariable, variable)
                     variable.value = value
                     return
-                
+
         variable = ToolRuntimeTextVariable(
             type=ToolRuntimeVariableType.TEXT,
             name=name,
@@ -334,7 +334,7 @@ class ToolRuntimeVariablePool(BaseModel):
                     variable = cast(ToolRuntimeImageVariable, variable)
                     variable.value = value
                     return
-                
+
         variable = ToolRuntimeImageVariable(
             type=ToolRuntimeVariableType.IMAGE,
             name=name,
@@ -388,21 +388,21 @@ class ToolInvokeMeta(BaseModel):
         Get an empty instance of ToolInvokeMeta
         """
         return cls(time_cost=0.0, error=None, tool_config={})
-    
+
     @classmethod
     def error_instance(cls, error: str) -> 'ToolInvokeMeta':
         """
         Get an instance of ToolInvokeMeta with error
         """
         return cls(time_cost=0.0, error=error, tool_config={})
-    
+
     def to_dict(self) -> dict:
         return {
             'time_cost': self.time_cost,
             'error': self.error,
             'tool_config': self.tool_config,
         }
-    
+
 class ToolLabel(BaseModel):
     """
     Tool label
@@ -416,4 +416,4 @@ class ToolInvokeFrom(Enum):
     Enum class for tool invoke
     """
     WORKFLOW = "workflow"
-    AGENT = "agent"
+    AGENT = "agent"

api/core/tools/provider/builtin/gitlab/_assets/gitlab.svg

@@ -0,0 +1,2 @@
+<?xml version="1.0" encoding="utf-8"?><!-- Uploaded to: SVG Repo, www.svgrepo.com, Generator: SVG Repo Mixer Tools -->
+<svg width="24" height="25" viewBox="0 0 24 25" xmlns="http://www.w3.org/2000/svg" fill="none"><path fill="#FC6D26" d="M14.975 8.904L14.19 6.55l-1.552-4.67a.268.268 0 00-.255-.18.268.268 0 00-.254.18l-1.552 4.667H5.422L3.87 1.879a.267.267 0 00-.254-.179.267.267 0 00-.254.18l-1.55 4.667-.784 2.357a.515.515 0 00.193.583l6.78 4.812 6.778-4.812a.516.516 0 00.196-.583z"/><path fill="#E24329" d="M8 14.296l2.578-7.75H5.423L8 14.296z"/><path fill="#FC6D26" d="M8 14.296l-2.579-7.75H1.813L8 14.296z"/><path fill="#FCA326" d="M1.81 6.549l-.784 2.354a.515.515 0 00.193.583L8 14.3 1.81 6.55z"/><path fill="#E24329" d="M1.812 6.549h3.612L3.87 1.882a.268.268 0 00-.254-.18.268.268 0 00-.255.18L1.812 6.549z"/><path fill="#FC6D26" d="M8 14.296l2.578-7.75h3.614L8 14.296z"/><path fill="#FCA326" d="M14.19 6.549l.783 2.354a.514.514 0 01-.193.583L8 14.296l6.188-7.747h.001z"/><path fill="#E24329" d="M14.19 6.549H10.58l1.551-4.667a.267.267 0 01.255-.18c.115 0 .217.073.254.18l1.552 4.667z"/></svg>

api/core/tools/provider/builtin/gitlab/gitlab.py

@@ -0,0 +1,34 @@
+from typing import Any
+
+import requests
+
+from core.tools.errors import ToolProviderCredentialValidationError
+from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController
+
+
+class GitlabProvider(BuiltinToolProviderController):
+    def _validate_credentials(self, credentials: dict[str, Any]) -> None:
+        try:
+            if 'access_tokens' not in credentials or not credentials.get('access_tokens'):
+                raise ToolProviderCredentialValidationError("Gitlab Access Tokens is required.")
+            
+            if 'site_url' not in credentials or not credentials.get('site_url'):
+                site_url = 'https://gitlab.com'
+            else:
+                site_url = credentials.get('site_url')
+
+            try:
+                headers = {
+                    "Content-Type": "application/vnd.text+json",
+                    "Authorization": f"Bearer {credentials.get('access_tokens')}",
+                }
+
+                response = requests.get(
+                    url= f"{site_url}/api/v4/user",
+                    headers=headers)
+                if response.status_code != 200:
+                    raise ToolProviderCredentialValidationError((response.json()).get('message'))
+            except Exception as e:
+                raise ToolProviderCredentialValidationError("Gitlab Access Tokens and Api Version is invalid. {}".format(e))
+        except Exception as e:
+            raise ToolProviderCredentialValidationError(str(e))

api/core/tools/provider/builtin/gitlab/gitlab.yaml

@@ -0,0 +1,38 @@
+identity:
+  author: Leo.Wang
+  name: gitlab
+  label:
+    en_US: Gitlab
+    zh_Hans: Gitlab
+  description:
+    en_US: Gitlab plugin for commit
+    zh_Hans: 用于获取Gitlab commit的插件
+  icon: gitlab.svg
+credentials_for_provider:
+  access_tokens:
+    type: secret-input
+    required: true
+    label:
+      en_US: Gitlab access token
+      zh_Hans: Gitlab access token
+    placeholder:
+      en_US: Please input your Gitlab access token
+      zh_Hans: 请输入你的 Gitlab access token
+    help:
+      en_US: Get your Gitlab access token from Gitlab
+      zh_Hans: 从 Gitlab 获取您的 access token
+    url: https://docs.gitlab.com/16.9/ee/api/oauth2.html
+  site_url:
+    type: text-input
+    required: false
+    default: 'https://gitlab.com'
+    label:
+      en_US: Gitlab site url
+      zh_Hans: Gitlab site url
+    placeholder:
+      en_US: Please input your Gitlab site url
+      zh_Hans: 请输入你的 Gitlab site url
+    help:
+      en_US: Find your Gitlab url
+      zh_Hans: 找到你的Gitlab url
+    url: https://gitlab.com/help

api/core/tools/provider/builtin/gitlab/tools/gitlab_commits.py

@@ -0,0 +1,101 @@
+import json
+from datetime import datetime, timedelta
+from typing import Any, Union
+
+import requests
+
+from core.tools.entities.tool_entities import ToolInvokeMessage
+from core.tools.tool.builtin_tool import BuiltinTool
+
+
+class GitlabCommitsTool(BuiltinTool):
+    def _invoke(self, 
+                user_id: str,
+                tool_parameters: dict[str, Any]
+        ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]:
+
+        project = tool_parameters.get('project', '')
+        employee = tool_parameters.get('employee', '')
+        start_time = tool_parameters.get('start_time', '')
+        end_time = tool_parameters.get('end_time', '')
+
+        if not project:
+            return self.create_text_message('Project is required')
+
+        if not start_time:
+            start_time = (datetime.utcnow() - timedelta(days=1)).isoformat()
+        if not end_time:
+            end_time = datetime.utcnow().isoformat()
+
+        access_token = self.runtime.credentials.get('access_tokens')
+        site_url = self.runtime.credentials.get('site_url')
+
+        if 'access_tokens' not in self.runtime.credentials or not self.runtime.credentials.get('access_tokens'):
+            return self.create_text_message("Gitlab API Access Tokens is required.")
+        if 'site_url' not in self.runtime.credentials or not self.runtime.credentials.get('site_url'):
+            site_url = 'https://gitlab.com'
+        
+        # Get commit content
+        result = self.fetch(user_id, site_url, access_token, project, employee, start_time, end_time)
+
+        return self.create_text_message(json.dumps(result, ensure_ascii=False))
+    
+    def fetch(self,user_id: str, site_url: str, access_token: str, project: str, employee: str = None, start_time: str = '', end_time: str = '') -> list[dict[str, Any]]:
+        domain = site_url
+        headers = {"PRIVATE-TOKEN": access_token}
+        results = []
+
+        try:
+            # Get all of projects
+            url = f"{domain}/api/v4/projects"
+            response = requests.get(url, headers=headers)
+            response.raise_for_status()
+            projects = response.json()
+
+            filtered_projects = [p for p in projects if project == "*" or p['name'] == project]
+
+            for project in filtered_projects:
+                project_id = project['id']
+                project_name = project['name']
+                print(f"Project: {project_name}")
+
+                # Get all of proejct commits
+                commits_url = f"{domain}/api/v4/projects/{project_id}/repository/commits"
+                params = {
+                    'since': start_time,
+                    'until': end_time
+                }
+                if employee:
+                    params['author'] = employee
+
+                commits_response = requests.get(commits_url, headers=headers, params=params)
+                commits_response.raise_for_status()
+                commits = commits_response.json()
+
+                for commit in commits:
+                    commit_sha = commit['id']
+                    print(f"\tCommit SHA: {commit_sha}")
+
+                    diff_url = f"{domain}/api/v4/projects/{project_id}/repository/commits/{commit_sha}/diff"
+                    diff_response = requests.get(diff_url, headers=headers)
+                    diff_response.raise_for_status()
+                    diffs = diff_response.json()
+                    
+                    for diff in diffs:
+                        # Caculate code lines of changed
+                        added_lines = diff['diff'].count('\n+')
+                        removed_lines = diff['diff'].count('\n-')
+                        total_changes = added_lines + removed_lines
+
+                        if total_changes > 1:
+                            final_code = ''.join([line[1:] for line in diff['diff'].split('\n') if line.startswith('+') and not line.startswith('+++')])
+                            results.append({
+                                "project": project_name,
+                                "commit_sha": commit_sha,
+                                "diff": final_code
+                            })
+                            print(f"Commit code:{final_code}")
+        except requests.RequestException as e:
+            print(f"Error fetching data from GitLab: {e}")
+        
+        return results

api/core/tools/provider/builtin/gitlab/tools/gitlab_commits.yaml

@@ -0,0 +1,56 @@
+identity:
+  name: gitlab_commits
+  author: Leo.Wang
+  label:
+    en_US: Gitlab Commits
+    zh_Hans: Gitlab代码提交内容
+description:
+  human:
+    en_US: A tool for query gitlab commits. Input should be a exists username.
+    zh_Hans: 一个用于查询gitlab代码提交记录的的工具，输入的内容应该是一个已存在的用户名或者项目名。
+  llm: A tool for query gitlab commits. Input should be a exists username or project.
+parameters:
+  - name: employee
+    type: string
+    required: false
+    label:
+      en_US: employee
+      zh_Hans: 员工用户名
+    human_description:
+      en_US: employee
+      zh_Hans: 员工用户名
+    llm_description: employee for gitlab
+    form: llm
+  - name: project
+    type: string
+    required: true
+    label:
+      en_US: project
+      zh_Hans: 项目名
+    human_description:
+      en_US: project
+      zh_Hans: 项目名
+    llm_description: project for gitlab
+    form: llm
+  - name: start_time
+    type: string
+    required: false
+    label:
+      en_US: start_time
+      zh_Hans: 开始时间
+    human_description:
+      en_US: start_time
+      zh_Hans: 开始时间
+    llm_description: start_time for gitlab
+    form: llm
+  - name: end_time
+    type: string
+    required: false
+    label:
+      en_US: end_time
+      zh_Hans: 结束时间
+    human_description:
+      en_US: end_time
+      zh_Hans: 结束时间
+    llm_description: end_time for gitlab
+    form: llm

api/core/tools/tool/tool.py

@@ -2,13 +2,12 @@ from abc import ABC, abstractmethod
 from collections.abc import Mapping
 from copy import deepcopy
 from enum import Enum
-from typing import Any, Optional, Union
+from typing import TYPE_CHECKING, Any, Optional, Union
 
 from pydantic import BaseModel, ConfigDict, field_validator
 from pydantic_core.core_schema import ValidationInfo
 
 from core.app.entities.app_invoke_entities import InvokeFrom
-from core.file.file_obj import FileVar
 from core.tools.entities.tool_entities import (
     ToolDescription,
     ToolIdentity,
@@ -23,6 +22,9 @@ from core.tools.entities.tool_entities import (
 from core.tools.tool_file_manager import ToolFileManager
 from core.tools.utils.tool_parameter_converter import ToolParameterConverter
 
+if TYPE_CHECKING:
+    from core.file.file_obj import FileVar
+
 
 class Tool(BaseModel, ABC):
     identity: Optional[ToolIdentity] = None
@@ -76,7 +78,7 @@ class Tool(BaseModel, ABC):
             description=self.description.model_copy() if self.description else None,
             runtime=Tool.Runtime(**runtime),
         )
-    
+
     @abstractmethod
     def tool_provider_type(self) -> ToolProviderType:
         """
@@ -84,7 +86,7 @@ class Tool(BaseModel, ABC):
 
             :return: the tool provider type
         """
-    
+
     def load_variables(self, variables: ToolRuntimeVariablePool):
         """
             load variables from database
@@ -99,7 +101,7 @@ class Tool(BaseModel, ABC):
         """
         if not self.variables:
             return
-        
+
         self.variables.set_file(self.identity.name, variable_name, image_key)
 
     def set_text_variable(self, variable_name: str, text: str) -> None:
@@ -108,9 +110,9 @@ class Tool(BaseModel, ABC):
         """
         if not self.variables:
             return
-        
+
         self.variables.set_text(self.identity.name, variable_name, text)
-        
+
     def get_variable(self, name: Union[str, Enum]) -> Optional[ToolRuntimeVariable]:
         """
             get a variable
@@ -120,14 +122,14 @@ class Tool(BaseModel, ABC):
         """
         if not self.variables:
             return None
-        
+
         if isinstance(name, Enum):
             name = name.value
-        
+
         for variable in self.variables.pool:
             if variable.name == name:
                 return variable
-            
+
         return None
 
     def get_default_image_variable(self) -> Optional[ToolRuntimeVariable]:
@@ -138,9 +140,9 @@ class Tool(BaseModel, ABC):
         """
         if not self.variables:
             return None
-        
+
         return self.get_variable(self.VARIABLE_KEY.IMAGE)
-    
+
     def get_variable_file(self, name: Union[str, Enum]) -> Optional[bytes]:
         """
             get a variable file
@@ -151,7 +153,7 @@ class Tool(BaseModel, ABC):
         variable = self.get_variable(name)
         if not variable:
             return None
-        
+
         if not isinstance(variable, ToolRuntimeImageVariable):
             return None
 
@@ -160,9 +162,9 @@ class Tool(BaseModel, ABC):
         file_binary = ToolFileManager.get_file_binary_by_message_file_id(message_file_id)
         if not file_binary:
             return None
-        
+
         return file_binary[0]
-    
+
     def list_variables(self) -> list[ToolRuntimeVariable]:
         """
             list all variables
@@ -171,9 +173,9 @@ class Tool(BaseModel, ABC):
         """
         if not self.variables:
             return []
-        
+
         return self.variables.pool
-    
+
     def list_default_image_variables(self) -> list[ToolRuntimeVariable]:
         """
             list all image variables
@@ -182,9 +184,9 @@ class Tool(BaseModel, ABC):
         """
         if not self.variables:
             return []
-        
+
         result = []
-        
+
         for variable in self.variables.pool:
             if variable.name.startswith(self.VARIABLE_KEY.IMAGE.value):
                 result.append(variable)
@@ -225,7 +227,7 @@ class Tool(BaseModel, ABC):
     @abstractmethod
     def _invoke(self, user_id: str, tool_parameters: dict[str, Any]) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]:
         pass
-    
+
     def validate_credentials(self, credentials: dict[str, Any], parameters: dict[str, Any]) -> None:
         """
             validate the credentials
@@ -244,7 +246,7 @@ class Tool(BaseModel, ABC):
             :return: the runtime parameters
         """
         return self.parameters or []
-    
+
     def get_all_runtime_parameters(self) -> list[ToolParameter]:
         """
             get all runtime parameters
@@ -278,7 +280,7 @@ class Tool(BaseModel, ABC):
                 parameters.append(parameter)
 
         return parameters
-    
+
     def create_image_message(self, image: str, save_as: str = '') -> ToolInvokeMessage:
         """
             create an image message
@@ -286,18 +288,18 @@ class Tool(BaseModel, ABC):
             :param image: the url of the image
             :return: the image message
         """
-        return ToolInvokeMessage(type=ToolInvokeMessage.MessageType.IMAGE, 
-                                 message=image, 
+        return ToolInvokeMessage(type=ToolInvokeMessage.MessageType.IMAGE,
+                                 message=image,
                                  save_as=save_as)
-    
-    def create_file_var_message(self, file_var: FileVar) -> ToolInvokeMessage:
+
+    def create_file_var_message(self, file_var: "FileVar") -> ToolInvokeMessage:
         return ToolInvokeMessage(type=ToolInvokeMessage.MessageType.FILE_VAR,
                                  message='',
                                  meta={
                                      'file_var': file_var
                                  },
                                  save_as='')
-    
+
     def create_link_message(self, link: str, save_as: str = '') -> ToolInvokeMessage:
         """
             create a link message
@@ -305,10 +307,10 @@ class Tool(BaseModel, ABC):
             :param link: the url of the link
             :return: the link message
         """
-        return ToolInvokeMessage(type=ToolInvokeMessage.MessageType.LINK, 
-                                 message=link, 
+        return ToolInvokeMessage(type=ToolInvokeMessage.MessageType.LINK,
+                                 message=link,
                                  save_as=save_as)
-    
+
     def create_text_message(self, text: str, save_as: str = '') -> ToolInvokeMessage:
         """
             create a text message
@@ -321,7 +323,7 @@ class Tool(BaseModel, ABC):
             message=text,
             save_as=save_as
         )
-    
+
     def create_blob_message(self, blob: bytes, meta: dict = None, save_as: str = '') -> ToolInvokeMessage:
         """
             create a blob message

api/core/tools/utils/message_transformer.py

@@ -1,7 +1,7 @@
 import logging
 from mimetypes import guess_extension
 
-from core.file.file_obj import FileTransferMethod, FileType, FileVar
+from core.file.file_obj import FileTransferMethod, FileType
 from core.tools.entities.tool_entities import ToolInvokeMessage
 from core.tools.tool_file_manager import ToolFileManager
 
@@ -28,12 +28,12 @@ class ToolFileMessageTransformer:
                 # try to download image
                 try:
                     file = ToolFileManager.create_file_by_url(
-                        user_id=user_id, 
+                        user_id=user_id,
                         tenant_id=tenant_id,
                         conversation_id=conversation_id,
                         file_url=message.message
                     )
-                    
+
                     url = f'/files/tools/{file.id}{guess_extension(file.mimetype) or ".png"}'
 
                     result.append(ToolInvokeMessage(
@@ -56,14 +56,14 @@ class ToolFileMessageTransformer:
                 # if message is str, encode it to bytes
                 if isinstance(message.message, str):
                     message.message = message.message.encode('utf-8')
-                
+
                 file = ToolFileManager.create_file_by_raw(
                     user_id=user_id, tenant_id=tenant_id,
                     conversation_id=conversation_id,
                     file_binary=message.message,
                     mimetype=mimetype
                 )
-                                                            
+
                 url = cls.get_tool_file_url(file.id, guess_extension(file.mimetype))
 
                 # check if file is image
@@ -82,7 +82,7 @@ class ToolFileMessageTransformer:
                         meta=message.meta.copy() if message.meta is not None else {},
                     ))
             elif message.type == ToolInvokeMessage.MessageType.FILE_VAR:
-                file_var: FileVar = message.meta.get('file_var')
+                file_var = message.meta.get('file_var')
                 if file_var:
                     if file_var.transfer_method == FileTransferMethod.TOOL_FILE:
                         url = cls.get_tool_file_url(file_var.related_id, file_var.extension)
@@ -104,7 +104,7 @@ class ToolFileMessageTransformer:
                 result.append(message)
 
         return result
-    
+
     @classmethod
     def get_tool_file_url(cls, tool_file_id: str, extension: str) -> str:
-        return f'/files/tools/{tool_file_id}{extension or ".bin"}'
+        return f'/files/tools/{tool_file_id}{extension or ".bin"}'

api/core/workflow/entities/node_entities.py

@@ -4,13 +4,14 @@ from typing import Any, Optional
 from pydantic import BaseModel
 
 from core.model_runtime.entities.llm_entities import LLMUsage
-from models.workflow import WorkflowNodeExecutionStatus
+from models import WorkflowNodeExecutionStatus
 
 
 class NodeType(Enum):
     """
     Node Types.
     """
+
     START = 'start'
     END = 'end'
     ANSWER = 'answer'
@@ -44,33 +45,11 @@ class NodeType(Enum):
         raise ValueError(f'invalid node type value {value}')
 
 
-class SystemVariable(Enum):
-    """
-    System Variables.
-    """
-    QUERY = 'query'
-    FILES = 'files'
-    CONVERSATION_ID = 'conversation_id'
-    USER_ID = 'user_id'
-
-    @classmethod
-    def value_of(cls, value: str) -> 'SystemVariable':
-        """
-        Get value of given system variable.
-
-        :param value: system variable value
-        :return: system variable
-        """
-        for system_variable in cls:
-            if system_variable.value == value:
-                return system_variable
-        raise ValueError(f'invalid system variable value {value}')
-
-
 class NodeRunMetadataKey(Enum):
     """
     Node Run Metadata Key.
     """
+
     TOTAL_TOKENS = 'total_tokens'
     TOTAL_PRICE = 'total_price'
     CURRENCY = 'currency'
@@ -83,6 +62,7 @@ class NodeRunResult(BaseModel):
     """
     Node Run Result.
     """
+
     status: WorkflowNodeExecutionStatus = WorkflowNodeExecutionStatus.RUNNING
 
     inputs: Optional[dict[str, Any]] = None  # node inputs

api/core/workflow/entities/variable_pool.py

@@ -7,7 +7,7 @@ from typing_extensions import deprecated
 
 from core.app.segments import Segment, Variable, factory
 from core.file.file_obj import FileVar
-from core.workflow.entities.node_entities import SystemVariable
+from core.workflow.enums import SystemVariable
 
 VariableValue = Union[str, int, float, dict, list, FileVar]
 

api/core/workflow/enums.py

@@ -0,0 +1,25 @@
+from enum import Enum
+
+
+class SystemVariable(str, Enum):
+    """
+    System Variables.
+    """
+    QUERY = 'query'
+    FILES = 'files'
+    CONVERSATION_ID = 'conversation_id'
+    USER_ID = 'user_id'
+    DIALOGUE_COUNT = 'dialogue_count'
+
+    @classmethod
+    def value_of(cls, value: str):
+        """
+        Get value of given system variable.
+
+        :param value: system variable value
+        :return: system variable
+        """
+        for system_variable in cls:
+            if system_variable.value == value:
+                return system_variable
+        raise ValueError(f'invalid system variable value {value}')

api/core/workflow/nodes/http_request/http_request_node.py

@@ -140,9 +140,6 @@ class HttpRequestNode(BaseNode):
         """
         files = []
         mimetype, file_binary = response.extract_file()
-        # if not image, return directly
-        if 'image' not in mimetype:
-            return files
 
         if mimetype:
             # extract filename from url

api/core/workflow/nodes/llm/llm_node.py

@@ -1,7 +1,7 @@
 import json
 from collections.abc import Generator, Mapping, Sequence
 from copy import deepcopy
-from typing import Any, Optional, cast
+from typing import TYPE_CHECKING, Any, Optional, cast
 
 from pydantic import BaseModel
 
@@ -9,7 +9,6 @@ from core.app.entities.app_invoke_entities import ModelConfigWithCredentialsEnti
 from core.entities.model_entities import ModelStatus
 from core.entities.provider_entities import QuotaUnit
 from core.errors.error import ModelCurrentlyNotSupportError, ProviderTokenNotInitError, QuotaExceededError
-from core.file.file_obj import FileVar
 from core.memory.token_buffer_memory import TokenBufferMemory
 from core.model_manager import ModelInstance, ModelManager
 from core.model_runtime.entities.llm_entities import LLMResult, LLMUsage
@@ -24,9 +23,10 @@ from core.model_runtime.utils.encoders import jsonable_encoder
 from core.prompt.advanced_prompt_transform import AdvancedPromptTransform
 from core.prompt.entities.advanced_prompt_entities import CompletionModelPromptTemplate, MemoryConfig
 from core.prompt.utils.prompt_message_util import PromptMessageUtil
-from core.workflow.entities.node_entities import NodeRunMetadataKey, NodeRunResult, NodeType, SystemVariable
+from core.workflow.entities.node_entities import NodeRunMetadataKey, NodeRunResult, NodeType
 from core.workflow.entities.variable_pool import VariablePool
 from core.workflow.graph_engine.entities.event import InNodeEvent
+from core.workflow.enums import SystemVariable
 from core.workflow.nodes.base_node import BaseNode
 from core.workflow.nodes.event import RunCompletedEvent, RunEvent, RunRetrieverResourceEvent, RunStreamChunkEvent
 from core.workflow.nodes.llm.entities import (
@@ -41,6 +41,10 @@ from models.model import Conversation
 from models.provider import Provider, ProviderType
 from models.workflow import WorkflowNodeExecutionStatus
 
+if TYPE_CHECKING:
+    from core.file.file_obj import FileVar
+
+
 
 class ModelInvokeCompleted(BaseModel):
     """
@@ -81,7 +85,7 @@ class LLMNode(BaseNode):
             node_inputs = {}
 
             # fetch files
-            files: list[FileVar] = self._fetch_files(node_data, variable_pool)
+            files = self._fetch_files(node_data, variable_pool)
 
             if files:
                 node_inputs['#files#'] = [file.to_dict() for file in files]
@@ -368,7 +372,7 @@ class LLMNode(BaseNode):
 
         return inputs  # type: ignore
 
-    def _fetch_files(self, node_data: LLMNodeData, variable_pool: VariablePool) -> list[FileVar]:
+    def _fetch_files(self, node_data: LLMNodeData, variable_pool: VariablePool) -> list["FileVar"]:
         """
         Fetch files
         :param node_data: node data
@@ -563,7 +567,7 @@ class LLMNode(BaseNode):
                                query: Optional[str],
                                query_prompt_template: Optional[str],
                                inputs: dict[str, str],
-                               files: list[FileVar],
+                               files: list["FileVar"],
                                context: Optional[str],
                                memory: Optional[TokenBufferMemory],
                                model_config: ModelConfigWithCredentialsEntity) \
@@ -678,8 +682,8 @@ class LLMNode(BaseNode):
 
     @classmethod
     def _extract_variable_selector_to_variable_mapping(
-        cls, 
-        graph_config: Mapping[str, Any], 
+        cls,
+        graph_config: Mapping[str, Any],
         node_id: str,
         node_data: LLMNodeData
     ) -> Mapping[str, Sequence[str]]:

api/core/workflow/nodes/tool/tool_node.py

@@ -2,19 +2,20 @@ from collections.abc import Mapping, Sequence
 from os import path
 from typing import Any, cast
 
-from core.app.segments import parser
+from core.app.segments import ArrayAnyVariable, parser
 from core.callback_handler.workflow_tool_callback_handler import DifyWorkflowCallbackHandler
 from core.file.file_obj import FileTransferMethod, FileType, FileVar
 from core.tools.entities.tool_entities import ToolInvokeMessage, ToolParameter
 from core.tools.tool_engine import ToolEngine
 from core.tools.tool_manager import ToolManager
 from core.tools.utils.message_transformer import ToolFileMessageTransformer
-from core.workflow.entities.node_entities import NodeRunMetadataKey, NodeRunResult, NodeType, SystemVariable
+from core.workflow.entities.node_entities import NodeRunMetadataKey, NodeRunResult, NodeType
 from core.workflow.entities.variable_pool import VariablePool
+from core.workflow.enums import SystemVariable
 from core.workflow.nodes.base_node import BaseNode
 from core.workflow.nodes.tool.entities import ToolNodeData
 from core.workflow.utils.variable_template_parser import VariableTemplateParser
-from models.workflow import WorkflowNodeExecutionStatus
+from models import WorkflowNodeExecutionStatus
 
 
 class ToolNode(BaseNode):
@@ -140,9 +141,9 @@ class ToolNode(BaseNode):
         return result
 
     def _fetch_files(self, variable_pool: VariablePool) -> list[FileVar]:
-        # FIXME: ensure this is a ArrayVariable contains FileVariable.
         variable = variable_pool.get(['sys', SystemVariable.FILES.value])
-        return [file_var.value for file_var in variable.value] if variable else []
+        assert isinstance(variable, ArrayAnyVariable)
+        return list(variable.value) if variable else []
 
     def _convert_tool_messages(self, messages: list[ToolInvokeMessage])\
             -> tuple[str, list[FileVar], list[dict]]:

api/events/app_event.py

@@ -1,13 +1,13 @@
 from blinker import signal
 
 # sender: app
-app_was_created = signal('app-was-created')
+app_was_created = signal("app-was-created")
 
 # sender: app, kwargs: app_model_config
-app_model_config_was_updated = signal('app-model-config-was-updated')
+app_model_config_was_updated = signal("app-model-config-was-updated")
 
 # sender: app, kwargs: published_workflow
-app_published_workflow_was_updated = signal('app-published-workflow-was-updated')
+app_published_workflow_was_updated = signal("app-published-workflow-was-updated")
 
 # sender: app, kwargs: synced_draft_workflow
-app_draft_workflow_was_synced = signal('app-draft-workflow-was-synced')
+app_draft_workflow_was_synced = signal("app-draft-workflow-was-synced")

api/events/dataset_event.py

@@ -1,4 +1,4 @@
 from blinker import signal
 
 # sender: dataset
-dataset_was_deleted = signal('dataset-was-deleted')
+dataset_was_deleted = signal("dataset-was-deleted")

api/events/document_event.py

@@ -1,4 +1,4 @@
 from blinker import signal
 
 # sender: document
-document_was_deleted = signal('document-was-deleted')
+document_was_deleted = signal("document-was-deleted")

api/events/event_handlers/clean_when_dataset_deleted.py

@@ -5,5 +5,11 @@ from tasks.clean_dataset_task import clean_dataset_task
 @dataset_was_deleted.connect
 def handle(sender, **kwargs):
     dataset = sender
-    clean_dataset_task.delay(dataset.id, dataset.tenant_id, dataset.indexing_technique,
-                             dataset.index_struct, dataset.collection_binding_id, dataset.doc_form)
+    clean_dataset_task.delay(
+        dataset.id,
+        dataset.tenant_id,
+        dataset.indexing_technique,
+        dataset.index_struct,
+        dataset.collection_binding_id,
+        dataset.doc_form,
+    )

api/events/event_handlers/clean_when_document_deleted.py

@@ -5,7 +5,7 @@ from tasks.clean_document_task import clean_document_task
 @document_was_deleted.connect
 def handle(sender, **kwargs):
     document_id = sender
-    dataset_id = kwargs.get('dataset_id')
-    doc_form = kwargs.get('doc_form')
-    file_id = kwargs.get('file_id')
+    dataset_id = kwargs.get("dataset_id")
+    doc_form = kwargs.get("doc_form")
+    file_id = kwargs.get("file_id")
     clean_document_task.delay(document_id, dataset_id, doc_form, file_id)

api/events/event_handlers/create_document_index.py

@@ -14,21 +14,25 @@ from models.dataset import Document
 @document_index_created.connect
 def handle(sender, **kwargs):
     dataset_id = sender
-    document_ids = kwargs.get('document_ids', None)
+    document_ids = kwargs.get("document_ids", None)
     documents = []
     start_at = time.perf_counter()
     for document_id in document_ids:
-        logging.info(click.style('Start process document: {}'.format(document_id), fg='green'))
+        logging.info(click.style("Start process document: {}".format(document_id), fg="green"))
 
-        document = db.session.query(Document).filter(
-            Document.id == document_id,
-            Document.dataset_id == dataset_id
-        ).first()
+        document = (
+            db.session.query(Document)
+            .filter(
+                Document.id == document_id,
+                Document.dataset_id == dataset_id,
+            )
+            .first()
+        )
 
         if not document:
-            raise NotFound('Document not found')
+            raise NotFound("Document not found")
 
-        document.indexing_status = 'parsing'
+        document.indexing_status = "parsing"
         document.processing_started_at = datetime.datetime.now(datetime.timezone.utc).replace(tzinfo=None)
         documents.append(document)
         db.session.add(document)
@@ -38,8 +42,8 @@ def handle(sender, **kwargs):
         indexing_runner = IndexingRunner()
         indexing_runner.run(documents)
         end_at = time.perf_counter()
-        logging.info(click.style('Processed dataset: {} latency: {}'.format(dataset_id, end_at - start_at), fg='green'))
+        logging.info(click.style("Processed dataset: {} latency: {}".format(dataset_id, end_at - start_at), fg="green"))
     except DocumentIsPausedException as ex:
-        logging.info(click.style(str(ex), fg='yellow'))
+        logging.info(click.style(str(ex), fg="yellow"))
     except Exception:
         pass

api/events/event_handlers/create_installed_app_when_app_created.py

@@ -10,7 +10,7 @@ def handle(sender, **kwargs):
     installed_app = InstalledApp(
         tenant_id=app.tenant_id,
         app_id=app.id,
-        app_owner_tenant_id=app.tenant_id
+        app_owner_tenant_id=app.tenant_id,
     )
     db.session.add(installed_app)
     db.session.commit()

api/events/event_handlers/create_site_record_when_app_created.py

@@ -7,15 +7,15 @@ from models.model import Site
 def handle(sender, **kwargs):
     """Create site record when an app is created."""
     app = sender
-    account = kwargs.get('account')
+    account = kwargs.get("account")
     site = Site(
         app_id=app.id,
         title=app.name,
-        icon = app.icon,
-        icon_background = app.icon_background,
+        icon=app.icon,
+        icon_background=app.icon_background,
         default_language=account.interface_language,
-        customize_token_strategy='not_allow',
-        code=Site.generate_code(16)
+        customize_token_strategy="not_allow",
+        code=Site.generate_code(16),
     )
 
     db.session.add(site)

api/events/event_handlers/deduct_quota_when_messaeg_created.py

@@ -8,7 +8,7 @@ from models.provider import Provider, ProviderType
 @message_was_created.connect
 def handle(sender, **kwargs):
     message = sender
-    application_generate_entity = kwargs.get('application_generate_entity')
+    application_generate_entity = kwargs.get("application_generate_entity")
 
     if not isinstance(application_generate_entity, ChatAppGenerateEntity | AgentChatAppGenerateEntity):
         return
@@ -39,7 +39,7 @@ def handle(sender, **kwargs):
         elif quota_unit == QuotaUnit.CREDITS:
             used_quota = 1
 
-            if 'gpt-4' in model_config.model:
+            if "gpt-4" in model_config.model:
                 used_quota = 20
         else:
             used_quota = 1
@@ -50,6 +50,6 @@ def handle(sender, **kwargs):
             Provider.provider_name == model_config.provider,
             Provider.provider_type == ProviderType.SYSTEM.value,
             Provider.quota_type == system_configuration.current_quota_type.value,
-            Provider.quota_limit > Provider.quota_used
-        ).update({'quota_used': Provider.quota_used + used_quota})
+            Provider.quota_limit > Provider.quota_used,
+        ).update({"quota_used": Provider.quota_used + used_quota})
         db.session.commit()

api/events/event_handlers/delete_tool_parameters_cache_when_sync_draft_workflow.py

@@ -8,8 +8,8 @@ from events.app_event import app_draft_workflow_was_synced
 @app_draft_workflow_was_synced.connect
 def handle(sender, **kwargs):
     app = sender
-    for node_data in kwargs.get('synced_draft_workflow').graph_dict.get('nodes', []):
-        if node_data.get('data', {}).get('type') == NodeType.TOOL.value:
+    for node_data in kwargs.get("synced_draft_workflow").graph_dict.get("nodes", []):
+        if node_data.get("data", {}).get("type") == NodeType.TOOL.value:
             try:
                 tool_entity = ToolEntity(**node_data["data"])
                 tool_runtime = ToolManager.get_tool_runtime(
@@ -23,7 +23,7 @@ def handle(sender, **kwargs):
                     tool_runtime=tool_runtime,
                     provider_name=tool_entity.provider_name,
                     provider_type=tool_entity.provider_type,
-                    identity_id=f'WORKFLOW.{app.id}.{node_data.get("id")}'
+                    identity_id=f'WORKFLOW.{app.id}.{node_data.get("id")}',
                 )
                 manager.delete_tool_parameters_cache()
             except:

api/events/event_handlers/document_index_event.py

@@ -1,4 +1,4 @@
 from blinker import signal
 
 # sender: document
-document_index_created = signal('document-index-created')
+document_index_created = signal("document-index-created")

api/events/event_handlers/update_app_dataset_join_when_app_model_config_updated.py

@@ -7,13 +7,11 @@ from models.model import AppModelConfig
 @app_model_config_was_updated.connect
 def handle(sender, **kwargs):
     app = sender
-    app_model_config = kwargs.get('app_model_config')
+    app_model_config = kwargs.get("app_model_config")
 
     dataset_ids = get_dataset_ids_from_model_config(app_model_config)
 
-    app_dataset_joins = db.session.query(AppDatasetJoin).filter(
-        AppDatasetJoin.app_id == app.id
-    ).all()
+    app_dataset_joins = db.session.query(AppDatasetJoin).filter(AppDatasetJoin.app_id == app.id).all()
 
     removed_dataset_ids = []
     if not app_dataset_joins:
@@ -29,16 +27,12 @@ def handle(sender, **kwargs):
     if removed_dataset_ids:
         for dataset_id in removed_dataset_ids:
             db.session.query(AppDatasetJoin).filter(
-                AppDatasetJoin.app_id == app.id,
-                AppDatasetJoin.dataset_id == dataset_id
+                AppDatasetJoin.app_id == app.id, AppDatasetJoin.dataset_id == dataset_id
             ).delete()
 
     if added_dataset_ids:
         for dataset_id in added_dataset_ids:
-            app_dataset_join = AppDatasetJoin(
-                app_id=app.id,
-                dataset_id=dataset_id
-            )
+            app_dataset_join = AppDatasetJoin(app_id=app.id, dataset_id=dataset_id)
             db.session.add(app_dataset_join)
 
     db.session.commit()
@@ -51,7 +45,7 @@ def get_dataset_ids_from_model_config(app_model_config: AppModelConfig) -> set:
 
     agent_mode = app_model_config.agent_mode_dict
 
-    tools = agent_mode.get('tools', []) or []
+    tools = agent_mode.get("tools", []) or []
     for tool in tools:
         if len(list(tool.keys())) != 1:
             continue
@@ -63,11 +57,11 @@ def get_dataset_ids_from_model_config(app_model_config: AppModelConfig) -> set:
 
     # get dataset from dataset_configs
     dataset_configs = app_model_config.dataset_configs_dict
-    datasets = dataset_configs.get('datasets', {}) or {}
-    for dataset in datasets.get('datasets', []) or []:
+    datasets = dataset_configs.get("datasets", {}) or {}
+    for dataset in datasets.get("datasets", []) or []:
         keys = list(dataset.keys())
-        if len(keys) == 1 and keys[0] == 'dataset':
-            if dataset['dataset'].get('id'):
-                dataset_ids.add(dataset['dataset'].get('id'))
+        if len(keys) == 1 and keys[0] == "dataset":
+            if dataset["dataset"].get("id"):
+                dataset_ids.add(dataset["dataset"].get("id"))
 
     return dataset_ids

api/events/event_handlers/update_app_dataset_join_when_app_published_workflow_updated.py

@@ -11,13 +11,11 @@ from models.workflow import Workflow
 @app_published_workflow_was_updated.connect
 def handle(sender, **kwargs):
     app = sender
-    published_workflow = kwargs.get('published_workflow')
+    published_workflow = kwargs.get("published_workflow")
     published_workflow = cast(Workflow, published_workflow)
 
     dataset_ids = get_dataset_ids_from_workflow(published_workflow)
-    app_dataset_joins = db.session.query(AppDatasetJoin).filter(
-        AppDatasetJoin.app_id == app.id
-    ).all()
+    app_dataset_joins = db.session.query(AppDatasetJoin).filter(AppDatasetJoin.app_id == app.id).all()
 
     removed_dataset_ids = []
     if not app_dataset_joins:
@@ -33,16 +31,12 @@ def handle(sender, **kwargs):
     if removed_dataset_ids:
         for dataset_id in removed_dataset_ids:
             db.session.query(AppDatasetJoin).filter(
-                AppDatasetJoin.app_id == app.id,
-                AppDatasetJoin.dataset_id == dataset_id
+                AppDatasetJoin.app_id == app.id, AppDatasetJoin.dataset_id == dataset_id
             ).delete()
 
     if added_dataset_ids:
         for dataset_id in added_dataset_ids:
-            app_dataset_join = AppDatasetJoin(
-                app_id=app.id,
-                dataset_id=dataset_id
-            )
+            app_dataset_join = AppDatasetJoin(app_id=app.id, dataset_id=dataset_id)
             db.session.add(app_dataset_join)
 
     db.session.commit()
@@ -54,18 +48,19 @@ def get_dataset_ids_from_workflow(published_workflow: Workflow) -> set:
     if not graph:
         return dataset_ids
 
-    nodes = graph.get('nodes', [])
+    nodes = graph.get("nodes", [])
 
     # fetch all knowledge retrieval nodes
-    knowledge_retrieval_nodes = [node for node in nodes
-                                 if node.get('data', {}).get('type') == NodeType.KNOWLEDGE_RETRIEVAL.value]
+    knowledge_retrieval_nodes = [
+        node for node in nodes if node.get("data", {}).get("type") == NodeType.KNOWLEDGE_RETRIEVAL.value
+    ]
 
     if not knowledge_retrieval_nodes:
         return dataset_ids
 
     for node in knowledge_retrieval_nodes:
         try:
-            node_data = KnowledgeRetrievalNodeData(**node.get('data', {}))
+            node_data = KnowledgeRetrievalNodeData(**node.get("data", {}))
             dataset_ids.update(node_data.dataset_ids)
         except Exception as e:
             continue

api/events/event_handlers/update_provider_last_used_at_when_messaeg_created.py

@@ -9,13 +9,13 @@ from models.provider import Provider
 @message_was_created.connect
 def handle(sender, **kwargs):
     message = sender
-    application_generate_entity = kwargs.get('application_generate_entity')
+    application_generate_entity = kwargs.get("application_generate_entity")
 
     if not isinstance(application_generate_entity, ChatAppGenerateEntity | AgentChatAppGenerateEntity):
         return
 
     db.session.query(Provider).filter(
         Provider.tenant_id == application_generate_entity.app_config.tenant_id,
-        Provider.provider_name == application_generate_entity.model_conf.provider
-    ).update({'last_used': datetime.now(timezone.utc).replace(tzinfo=None)})
+        Provider.provider_name == application_generate_entity.model_conf.provider,
+    ).update({"last_used": datetime.now(timezone.utc).replace(tzinfo=None)})
     db.session.commit()

api/events/message_event.py

@@ -1,4 +1,4 @@
 from blinker import signal
 
 # sender: message, kwargs: conversation
-message_was_created = signal('message-was-created')
+message_was_created = signal("message-was-created")

api/events/tenant_event.py

@@ -1,7 +1,7 @@
 from blinker import signal
 
 # sender: tenant
-tenant_was_created = signal('tenant-was-created')
+tenant_was_created = signal("tenant-was-created")
 
 # sender: tenant
-tenant_was_updated = signal('tenant-was-updated')
+tenant_was_updated = signal("tenant-was-updated")

api/extensions/ext_celery.py

@@ -17,7 +17,7 @@ def init_app(app: Flask) -> Celery:
         backend=app.config["CELERY_BACKEND"],
         task_ignore_result=True,
     )
-    
+
     # Add SSL options to the Celery configuration
     ssl_options = {
         "ssl_cert_reqs": None,
@@ -35,7 +35,7 @@ def init_app(app: Flask) -> Celery:
         celery_app.conf.update(
             broker_use_ssl=ssl_options,  # Add the SSL options to the broker configuration
         )
-        
+
     celery_app.set_default()
     app.extensions["celery"] = celery_app
 
@@ -45,18 +45,15 @@ def init_app(app: Flask) -> Celery:
     ]
     day = app.config["CELERY_BEAT_SCHEDULER_TIME"]
     beat_schedule = {
-        'clean_embedding_cache_task': {
-            'task': 'schedule.clean_embedding_cache_task.clean_embedding_cache_task',
-            'schedule': timedelta(days=day),
+        "clean_embedding_cache_task": {
+            "task": "schedule.clean_embedding_cache_task.clean_embedding_cache_task",
+            "schedule": timedelta(days=day),
+        },
+        "clean_unused_datasets_task": {
+            "task": "schedule.clean_unused_datasets_task.clean_unused_datasets_task",
+            "schedule": timedelta(days=day),
         },
-        'clean_unused_datasets_task': {
-            'task': 'schedule.clean_unused_datasets_task.clean_unused_datasets_task',
-            'schedule': timedelta(days=day),
-        }
     }
-    celery_app.conf.update(
-        beat_schedule=beat_schedule,
-        imports=imports
-    )
+    celery_app.conf.update(beat_schedule=beat_schedule, imports=imports)
 
     return celery_app

api/extensions/ext_compress.py

@@ -2,15 +2,14 @@ from flask import Flask
 
 
 def init_app(app: Flask):
-    if app.config.get('API_COMPRESSION_ENABLED'):
+    if app.config.get("API_COMPRESSION_ENABLED"):
         from flask_compress import Compress
 
-        app.config['COMPRESS_MIMETYPES'] = [
-            'application/json',
-            'image/svg+xml',
-            'text/html',
+        app.config["COMPRESS_MIMETYPES"] = [
+            "application/json",
+            "image/svg+xml",
+            "text/html",
         ]
 
         compress = Compress()
         compress.init_app(app)
-

api/extensions/ext_database.py

@@ -2,11 +2,11 @@ from flask_sqlalchemy import SQLAlchemy
 from sqlalchemy import MetaData
 
 POSTGRES_INDEXES_NAMING_CONVENTION = {
-    'ix': '%(column_0_label)s_idx',
-    'uq': '%(table_name)s_%(column_0_name)s_key',
-    'ck': '%(table_name)s_%(constraint_name)s_check',
-    'fk': '%(table_name)s_%(column_0_name)s_fkey',
-    'pk': '%(table_name)s_pkey',
+    "ix": "%(column_0_label)s_idx",
+    "uq": "%(table_name)s_%(column_0_name)s_key",
+    "ck": "%(table_name)s_%(constraint_name)s_check",
+    "fk": "%(table_name)s_%(column_0_name)s_fkey",
+    "pk": "%(table_name)s_pkey",
 }
 
 metadata = MetaData(naming_convention=POSTGRES_INDEXES_NAMING_CONVENTION)

api/extensions/ext_mail.py

@@ -14,67 +14,69 @@ class Mail:
         return self._client is not None
 
     def init_app(self, app: Flask):
-        if app.config.get('MAIL_TYPE'):
-            if app.config.get('MAIL_DEFAULT_SEND_FROM'):
-                self._default_send_from = app.config.get('MAIL_DEFAULT_SEND_FROM')
-            
-            if app.config.get('MAIL_TYPE') == 'resend':
-                api_key = app.config.get('RESEND_API_KEY')
-                if not api_key:
-                    raise ValueError('RESEND_API_KEY is not set')
+        if app.config.get("MAIL_TYPE"):
+            if app.config.get("MAIL_DEFAULT_SEND_FROM"):
+                self._default_send_from = app.config.get("MAIL_DEFAULT_SEND_FROM")
 
-                api_url = app.config.get('RESEND_API_URL')
+            if app.config.get("MAIL_TYPE") == "resend":
+                api_key = app.config.get("RESEND_API_KEY")
+                if not api_key:
+                    raise ValueError("RESEND_API_KEY is not set")
+
+                api_url = app.config.get("RESEND_API_URL")
                 if api_url:
                     resend.api_url = api_url
 
                 resend.api_key = api_key
                 self._client = resend.Emails
-            elif app.config.get('MAIL_TYPE') == 'smtp':
+            elif app.config.get("MAIL_TYPE") == "smtp":
                 from libs.smtp import SMTPClient
-                if not app.config.get('SMTP_SERVER') or not app.config.get('SMTP_PORT'):
-                    raise ValueError('SMTP_SERVER and SMTP_PORT are required for smtp mail type')
-                if not app.config.get('SMTP_USE_TLS') and app.config.get('SMTP_OPPORTUNISTIC_TLS'):
-                    raise ValueError('SMTP_OPPORTUNISTIC_TLS is not supported without enabling SMTP_USE_TLS')
+
+                if not app.config.get("SMTP_SERVER") or not app.config.get("SMTP_PORT"):
+                    raise ValueError("SMTP_SERVER and SMTP_PORT are required for smtp mail type")
+                if not app.config.get("SMTP_USE_TLS") and app.config.get("SMTP_OPPORTUNISTIC_TLS"):
+                    raise ValueError("SMTP_OPPORTUNISTIC_TLS is not supported without enabling SMTP_USE_TLS")
                 self._client = SMTPClient(
-                    server=app.config.get('SMTP_SERVER'),
-                    port=app.config.get('SMTP_PORT'),
-                    username=app.config.get('SMTP_USERNAME'),
-                    password=app.config.get('SMTP_PASSWORD'),
-                    _from=app.config.get('MAIL_DEFAULT_SEND_FROM'),
-                    use_tls=app.config.get('SMTP_USE_TLS'),
-                    opportunistic_tls=app.config.get('SMTP_OPPORTUNISTIC_TLS')
+                    server=app.config.get("SMTP_SERVER"),
+                    port=app.config.get("SMTP_PORT"),
+                    username=app.config.get("SMTP_USERNAME"),
+                    password=app.config.get("SMTP_PASSWORD"),
+                    _from=app.config.get("MAIL_DEFAULT_SEND_FROM"),
+                    use_tls=app.config.get("SMTP_USE_TLS"),
+                    opportunistic_tls=app.config.get("SMTP_OPPORTUNISTIC_TLS"),
                 )
             else:
-                raise ValueError('Unsupported mail type {}'.format(app.config.get('MAIL_TYPE')))
+                raise ValueError("Unsupported mail type {}".format(app.config.get("MAIL_TYPE")))
         else:
-            logging.warning('MAIL_TYPE is not set')
-            
+            logging.warning("MAIL_TYPE is not set")
 
     def send(self, to: str, subject: str, html: str, from_: Optional[str] = None):
         if not self._client:
-            raise ValueError('Mail client is not initialized')
+            raise ValueError("Mail client is not initialized")
 
         if not from_ and self._default_send_from:
             from_ = self._default_send_from
 
         if not from_:
-            raise ValueError('mail from is not set')
+            raise ValueError("mail from is not set")
 
         if not to:
-            raise ValueError('mail to is not set')
+            raise ValueError("mail to is not set")
 
         if not subject:
-            raise ValueError('mail subject is not set')
+            raise ValueError("mail subject is not set")
 
         if not html:
-            raise ValueError('mail html is not set')
+            raise ValueError("mail html is not set")
 
-        self._client.send({
-            "from": from_,
-            "to": to,
-            "subject": subject,
-            "html": html
-        })
+        self._client.send(
+            {
+                "from": from_,
+                "to": to,
+                "subject": subject,
+                "html": html,
+            }
+        )
 
 
 def init_app(app: Flask):

api/extensions/ext_redis.py

@@ -6,18 +6,21 @@ redis_client = redis.Redis()
 
 def init_app(app):
     connection_class = Connection
-    if app.config.get('REDIS_USE_SSL'):
+    if app.config.get("REDIS_USE_SSL"):
         connection_class = SSLConnection
 
-    redis_client.connection_pool = redis.ConnectionPool(**{
-        'host': app.config.get('REDIS_HOST'),
-        'port': app.config.get('REDIS_PORT'),
-        'username': app.config.get('REDIS_USERNAME'),
-        'password': app.config.get('REDIS_PASSWORD'),
-        'db': app.config.get('REDIS_DB'),
-        'encoding': 'utf-8',
-        'encoding_errors': 'strict',
-        'decode_responses': False
-    }, connection_class=connection_class)
+    redis_client.connection_pool = redis.ConnectionPool(
+        **{
+            "host": app.config.get("REDIS_HOST"),
+            "port": app.config.get("REDIS_PORT"),
+            "username": app.config.get("REDIS_USERNAME"),
+            "password": app.config.get("REDIS_PASSWORD"),
+            "db": app.config.get("REDIS_DB"),
+            "encoding": "utf-8",
+            "encoding_errors": "strict",
+            "decode_responses": False,
+        },
+        connection_class=connection_class,
+    )
 
-    app.extensions['redis'] = redis_client
+    app.extensions["redis"] = redis_client

api/extensions/ext_sentry.py

@@ -5,16 +5,13 @@ from werkzeug.exceptions import HTTPException
 
 
 def init_app(app):
-    if app.config.get('SENTRY_DSN'):
+    if app.config.get("SENTRY_DSN"):
         sentry_sdk.init(
-            dsn=app.config.get('SENTRY_DSN'),
-            integrations=[
-                FlaskIntegration(),
-                CeleryIntegration()
-            ],
+            dsn=app.config.get("SENTRY_DSN"),
+            integrations=[FlaskIntegration(), CeleryIntegration()],
             ignore_errors=[HTTPException, ValueError],
-            traces_sample_rate=app.config.get('SENTRY_TRACES_SAMPLE_RATE', 1.0),
-            profiles_sample_rate=app.config.get('SENTRY_PROFILES_SAMPLE_RATE', 1.0),
-            environment=app.config.get('DEPLOY_ENV'),
-            release=f"dify-{app.config.get('CURRENT_VERSION')}-{app.config.get('COMMIT_SHA')}"
+            traces_sample_rate=app.config.get("SENTRY_TRACES_SAMPLE_RATE", 1.0),
+            profiles_sample_rate=app.config.get("SENTRY_PROFILES_SAMPLE_RATE", 1.0),
+            environment=app.config.get("DEPLOY_ENV"),
+            release=f"dify-{app.config.get('CURRENT_VERSION')}-{app.config.get('COMMIT_SHA')}",
         )