Merge branch 'main' into feat/attachments

.github/workflows/api-tests.yml

@@ -39,7 +39,7 @@ jobs:
             api/pyproject.toml
             api/poetry.lock
 
-      - name: Poetry check
+      - name: Check Poetry lockfile
         run: |
           poetry check -C api --lock
           poetry show -C api
@@ -47,6 +47,9 @@ jobs:
       - name: Install dependencies
         run: poetry install -C api --with dev
 
+      - name: Check dependencies in pyproject.toml
+        run: poetry run -C api bash dev/pytest/pytest_artifacts.sh
+
       - name: Run Unit tests
         run: poetry run -C api bash dev/pytest/pytest_unit_tests.sh
 

README.md

@@ -196,10 +196,14 @@ If you'd like to configure a highly-available setup, there are community-contrib
 
 #### Using Terraform for Deployment
 
+Deploy Dify to Cloud Platform with a single click using [terraform](https://www.terraform.io/)
+
 ##### Azure Global
-Deploy Dify to Azure with a single click using [terraform](https://www.terraform.io/).
 - [Azure Terraform by @nikawang](https://github.com/nikawang/dify-azure-terraform)
 
+##### Google Cloud
+- [Google Cloud Terraform by @sotazum](https://github.com/DeNA/dify-google-cloud-terraform)
+
 ## Contributing
 
 For those who'd like to contribute code, see our [Contribution Guide](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md). 

README_AR.md

@@ -179,10 +179,13 @@ docker compose up -d
 
 #### استخدام Terraform للتوزيع
 
+انشر Dify إلى منصة السحابة بنقرة واحدة باستخدام [terraform](https://www.terraform.io/)
+
 ##### Azure Global
-استخدم [terraform](https://www.terraform.io/) لنشر Dify على Azure بنقرة واحدة.
 - [Azure Terraform بواسطة @nikawang](https://github.com/nikawang/dify-azure-terraform)
 
+##### Google Cloud
+- [Google Cloud Terraform بواسطة @sotazum](https://github.com/DeNA/dify-google-cloud-terraform)
 
 ## المساهمة
 

README_CN.md

@@ -202,10 +202,14 @@ docker compose up -d
 
 #### 使用 Terraform 部署
 
+使用 [terraform](https://www.terraform.io/) 一键将 Dify 部署到云平台
+
 ##### Azure Global
-使用 [terraform](https://www.terraform.io/) 一键部署 Dify 到 Azure。
 - [Azure Terraform by @nikawang](https://github.com/nikawang/dify-azure-terraform)
 
+##### Google Cloud
+- [Google Cloud Terraform by @sotazum](https://github.com/DeNA/dify-google-cloud-terraform)
+
 ## Star History
 
 [![Star History Chart](https://api.star-history.com/svg?repos=langgenius/dify&type=Date)](https://star-history.com/#langgenius/dify&Date)

README_ES.md

@@ -204,10 +204,13 @@ Si desea configurar una configuración de alta disponibilidad, la comunidad prop
 
 #### Uso de Terraform para el despliegue
 
+Despliega Dify en una plataforma en la nube con un solo clic utilizando [terraform](https://www.terraform.io/)
+
 ##### Azure Global
-Utiliza [terraform](https://www.terraform.io/) para desplegar Dify en Azure con un solo clic.
 - [Azure Terraform por @nikawang](https://github.com/nikawang/dify-azure-terraform)
 
+##### Google Cloud
+- [Google Cloud Terraform por @sotazum](https://github.com/DeNA/dify-google-cloud-terraform)
 
 ## Contribuir
 

README_FR.md

@@ -202,10 +202,13 @@ Si vous souhaitez configurer une configuration haute disponibilité, la communau
 
 #### Utilisation de Terraform pour le déploiement
 
+Déployez Dify sur une plateforme cloud en un clic en utilisant [terraform](https://www.terraform.io/)
+
 ##### Azure Global
-Utilisez [terraform](https://www.terraform.io/) pour déployer Dify sur Azure en un clic.
 - [Azure Terraform par @nikawang](https://github.com/nikawang/dify-azure-terraform)
 
+##### Google Cloud
+- [Google Cloud Terraform par @sotazum](https://github.com/DeNA/dify-google-cloud-terraform)
 
 ## Contribuer
 

README_JA.md

@@ -68,7 +68,7 @@ DifyはオープンソースのLLMアプリケーション開発プラットフ
   プロンプトの作成、モデルパフォーマンスの比較が行え、チャットベースのアプリに音声合成などの機能も追加できます。
 
 **4. RAGパイプライン**: 
-  ドキュメントの取り込みから検索までをカバーする広範なRAG機能ができます。ほかにもPDF、PPT、その他の一般的なドキュメントフォーマットからのテキスト抽出のサーポイントも提供します。
+  ドキュメントの取り込みから検索までをカバーする広範なRAG機能ができます。ほかにもPDF、PPT、その他の一般的なドキュメントフォーマットからのテキスト抽出のサポートも提供します。
 
 **5. エージェント機能**: 
   LLM Function CallingやReActに基づくエージェントの定義が可能で、AIエージェント用のプリビルトまたはカスタムツールを追加できます。Difyには、Google検索、DALL·E、Stable Diffusion、WolframAlphaなどのAIエージェント用の50以上の組み込みツールが提供します。
@@ -201,10 +201,13 @@ docker compose up -d
 
 #### Terraformを使用したデプロイ
 
-##### Azure Global
+[terraform](https://www.terraform.io/) を使用して、ワンクリックでDifyをクラウドプラットフォームにデプロイします
-[terraform](https://www.terraform.io/) を使用して、AzureにDifyをワンクリックでデプロイします。
-- [nikawangのAzure Terraform](https://github.com/nikawang/dify-azure-terraform)
 
+##### Azure Global
+- [@nikawangによるAzure Terraform](https://github.com/nikawang/dify-azure-terraform)
+
+##### Google Cloud
+- [@sotazumによるGoogle Cloud Terraform](https://github.com/DeNA/dify-google-cloud-terraform)
 
 ## 貢献
 

README_KL.md

@@ -202,10 +202,13 @@ If you'd like to configure a highly-available setup, there are community-contrib
 
 #### Terraform atorlugu pilersitsineq
 
-##### Azure Global
+wa'logh nIqHom neH ghun deployment toy'wI' [terraform](https://www.terraform.io/) lo'laH.
-Atoruk [terraform](https://www.terraform.io/) Dify-mik Azure-mut ataatsikkut ikkussuilluarlugu.
-- [Azure Terraform atorlugu @nikawang](https://github.com/nikawang/dify-azure-terraform)
 
+##### Azure Global
+- [Azure Terraform mung @nikawang](https://github.com/nikawang/dify-azure-terraform)
+
+##### Google Cloud
+- [Google Cloud Terraform qachlot @sotazum](https://github.com/DeNA/dify-google-cloud-terraform)
 
 ## Contributing
 

README_KR.md

@@ -39,7 +39,6 @@
   <a href="./README_AR.md"><img alt="README بالعربية" src="https://img.shields.io/badge/العربية-d9d9d9"></a>
   <a href="./README_TR.md"><img alt="Türkçe README" src="https://img.shields.io/badge/Türkçe-d9d9d9"></a>
   <a href="./README_VI.md"><img alt="README Tiếng Việt" src="https://img.shields.io/badge/Ti%E1%BA%BFng%20Vi%E1%BB%87t-d9d9d9"></a>
-
 </p>
 
 
@@ -195,10 +194,14 @@ Dify를 Kubernetes에 배포하고 프리미엄 스케일링 설정을 구성했
 
 #### Terraform을 사용한 배포
 
+[terraform](https://www.terraform.io/)을 사용하여 단 한 번의 클릭으로 Dify를 클라우드 플랫폼에 배포하십시오
+
 ##### Azure Global
-[terraform](https://www.terraform.io/)을 사용하여 Azure에 Dify를 원클릭으로 배포하세요.
 - [nikawang의 Azure Terraform](https://github.com/nikawang/dify-azure-terraform)
 
+##### Google Cloud
+- [sotazum의 Google Cloud Terraform](https://github.com/DeNA/dify-google-cloud-terraform)
+
 ## 기여
 
 코드에 기여하고 싶은 분들은 [기여 가이드](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md)를 참조하세요.

README_TR.md

@@ -200,9 +200,13 @@ Yüksek kullanılabilirliğe sahip bir kurulum yapılandırmak isterseniz, Dify'
 
 #### Dağıtım için Terraform Kullanımı
 
+Dify'ı bulut platformuna tek tıklamayla dağıtın [terraform](https://www.terraform.io/) kullanarak
+
 ##### Azure Global
-[Terraform](https://www.terraform.io/) kullanarak Dify'ı Azure'a tek tıklamayla dağıtın.
+- [Azure Terraform tarafından @nikawang](https://github.com/nikawang/dify-azure-terraform)
-- [@nikawang tarafından Azure Terraform](https://github.com/nikawang/dify-azure-terraform)
+
+##### Google Cloud
+- [Google Cloud Terraform tarafından @sotazum](https://github.com/DeNA/dify-google-cloud-terraform)
 
 ## Katkıda Bulunma
 

README_VI.md

@@ -196,10 +196,14 @@ Nếu bạn muốn cấu hình một cài đặt có độ sẵn sàng cao, có
 
 #### Sử dụng Terraform để Triển khai
 
+Triển khai Dify lên nền tảng đám mây với một cú nhấp chuột bằng cách sử dụng [terraform](https://www.terraform.io/)
+
 ##### Azure Global
-Triển khai Dify lên Azure chỉ với một cú nhấp chuột bằng cách sử dụng [terraform](https://www.terraform.io/).
 - [Azure Terraform bởi @nikawang](https://github.com/nikawang/dify-azure-terraform)
 
+##### Google Cloud
+- [Google Cloud Terraform bởi @sotazum](https://github.com/DeNA/dify-google-cloud-terraform)
+
 ## Đóng góp
 
 Đối với những người muốn đóng góp mã, xem [Hướng dẫn Đóng góp](https://github.com/langgenius/dify/blob/main/CONTRIBUTING.md) của chúng tôi. 

api/.env.example

@@ -39,7 +39,7 @@ DB_DATABASE=dify
 
 # Storage configuration
 # use for store upload files, private keys...
-# storage type: local, s3, azure-blob, google-storage, tencent-cos, huawei-obs, volcengine-tos
+# storage type: local, s3, azure-blob, google-storage, tencent-cos, huawei-obs, volcengine-tos, baidu-obs
 STORAGE_TYPE=local
 STORAGE_LOCAL_PATH=storage
 S3_USE_AWS_MANAGED_IAM=false
@@ -79,6 +79,12 @@ HUAWEI_OBS_SECRET_KEY=your-secret-key
 HUAWEI_OBS_ACCESS_KEY=your-access-key
 HUAWEI_OBS_SERVER=your-server-url
 
+# Baidu OBS Storage Configuration
+BAIDU_OBS_BUCKET_NAME=your-bucket-name
+BAIDU_OBS_SECRET_KEY=your-secret-key
+BAIDU_OBS_ACCESS_KEY=your-access-key
+BAIDU_OBS_ENDPOINT=your-server-url
+
 # OCI Storage configuration
 OCI_ENDPOINT=your-endpoint
 OCI_BUCKET_NAME=your-bucket-name
@@ -265,6 +271,9 @@ HTTP_REQUEST_MAX_WRITE_TIMEOUT=600
 HTTP_REQUEST_NODE_MAX_BINARY_SIZE=10485760
 HTTP_REQUEST_NODE_MAX_TEXT_SIZE=1048576
 
+# Respect X-* headers to redirect clients
+RESPECT_XFORWARD_HEADERS_ENABLED=false
+
 # Log file path
 LOG_FILE=
 

api/app.py

@@ -26,7 +26,7 @@ from commands import register_commands
 from configs import dify_config
 
 # DO NOT REMOVE BELOW
-from events import event_handlers
+from events import event_handlers  # noqa: F401
 from extensions import (
     ext_celery,
     ext_code_based_extension,
@@ -36,6 +36,7 @@ from extensions import (
     ext_login,
     ext_mail,
     ext_migrate,
+    ext_proxy_fix,
     ext_redis,
     ext_sentry,
     ext_storage,
@@ -45,7 +46,7 @@ from extensions.ext_login import login_manager
 from libs.passport import PassportService
 
 # TODO: Find a way to avoid importing models here
-from models import account, dataset, model, source, task, tool, tools, web
+from models import account, dataset, model, source, task, tool, tools, web  # noqa: F401
 from services.account_service import AccountService
 
 # DO NOT REMOVE ABOVE
@@ -156,6 +157,7 @@ def initialize_extensions(app):
     ext_mail.init_app(app)
     ext_hosting_provider.init_app(app)
     ext_sentry.init_app(app)
+    ext_proxy_fix.init_app(app)
 
 
 # Flask-Login configuration
@@ -181,10 +183,10 @@ def load_user_from_request(request_from_flask_login):
     decoded = PassportService().verify(auth_token)
     user_id = decoded.get("user_id")
 
-    account = AccountService.load_logged_in_account(account_id=user_id, token=auth_token)
+    logged_in_account = AccountService.load_logged_in_account(account_id=user_id, token=auth_token)
-    if account:
+    if logged_in_account:
-        contexts.tenant_id.set(account.current_tenant_id)
+        contexts.tenant_id.set(logged_in_account.current_tenant_id)
-    return account
+    return logged_in_account
 
 
 @login_manager.unauthorized_handler

api/configs/feature/__init__.py

@@ -247,6 +247,12 @@ class HttpConfig(BaseSettings):
         default=None,
     )
 
+    RESPECT_XFORWARD_HEADERS_ENABLED: bool = Field(
+        description="Enable or disable the X-Forwarded-For Proxy Fix middleware from Werkzeug"
+        " to respect X-* headers to redirect clients",
+        default=False,
+    )
+
 
 class InnerAPIConfig(BaseSettings):
     """

api/configs/middleware/__init__.py

@@ -8,6 +8,7 @@ from configs.middleware.cache.redis_config import RedisConfig
 from configs.middleware.storage.aliyun_oss_storage_config import AliyunOSSStorageConfig
 from configs.middleware.storage.amazon_s3_storage_config import S3StorageConfig
 from configs.middleware.storage.azure_blob_storage_config import AzureBlobStorageConfig
+from configs.middleware.storage.baidu_obs_storage_config import BaiduOBSStorageConfig
 from configs.middleware.storage.google_cloud_storage_config import GoogleCloudStorageConfig
 from configs.middleware.storage.huawei_obs_storage_config import HuaweiCloudOBSStorageConfig
 from configs.middleware.storage.oci_storage_config import OCIStorageConfig
@@ -200,12 +201,13 @@ class MiddlewareConfig(
     StorageConfig,
     AliyunOSSStorageConfig,
     AzureBlobStorageConfig,
+    BaiduOBSStorageConfig,
     GoogleCloudStorageConfig,
-    TencentCloudCOSStorageConfig,
     HuaweiCloudOBSStorageConfig,
-    VolcengineTOSStorageConfig,
-    S3StorageConfig,
     OCIStorageConfig,
+    S3StorageConfig,
+    TencentCloudCOSStorageConfig,
+    VolcengineTOSStorageConfig,
     # configs of vdb and vdb providers
     VectorStoreConfig,
     AnalyticdbConfig,

api/configs/middleware/storage/baidu_obs_storage_config.py

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

api/configs/packaging/__init__.py

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

api/controllers/console/app/conversation.py

@@ -188,6 +188,7 @@ class ChatConversationApi(Resource):
                         subquery.c.from_end_user_session_id.ilike(keyword_filter),
                     ),
                 )
+                .group_by(Conversation.id)
             )
 
         account = current_user

api/controllers/files/error.py

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

api/controllers/files/image_preview.py

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

api/controllers/files/tool_files.py

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

api/controllers/service_api/app/completion.py

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

api/core/agent/cot_agent_runner.py

@@ -369,7 +369,7 @@ class CotAgentRunner(BaseAgentRunner, ABC):
         return message
 
     def _organize_historic_prompt_messages(
-        self, current_session_messages: list[PromptMessage] = None
+        self, current_session_messages: Optional[list[PromptMessage]] = None
     ) -> list[PromptMessage]:
         """
         organize historic prompt messages

api/core/agent/cot_chat_agent_runner.py

@@ -27,7 +27,7 @@ class CotChatAgentRunner(CotAgentRunner):
 
         return SystemPromptMessage(content=system_prompt)
 
-    def _organize_user_query(self, query, prompt_messages: list[PromptMessage] = None) -> list[PromptMessage]:
+    def _organize_user_query(self, query, prompt_messages: list[PromptMessage]) -> list[PromptMessage]:
         """
         Organize user query
         """

api/core/agent/cot_completion_agent_runner.py

@@ -1,4 +1,5 @@
 import json
+from typing import Optional
 
 from core.agent.cot_agent_runner import CotAgentRunner
 from core.model_runtime.entities.message_entities import AssistantPromptMessage, PromptMessage, UserPromptMessage
@@ -21,7 +22,7 @@ class CotCompletionAgentRunner(CotAgentRunner):
 
         return system_prompt
 
-    def _organize_historic_prompt(self, current_session_messages: list[PromptMessage] = None) -> str:
+    def _organize_historic_prompt(self, current_session_messages: Optional[list[PromptMessage]] = None) -> str:
         """
         Organize historic prompt
         """

api/core/agent/fc_agent_runner.py

@@ -2,7 +2,7 @@ import json
 import logging
 from collections.abc import Generator
 from copy import deepcopy
-from typing import Any, Union
+from typing import Any, Optional, Union
 
 from core.agent.base_agent_runner import BaseAgentRunner
 from core.app.apps.base_app_queue_manager import PublishFrom
@@ -370,7 +370,7 @@ class FunctionCallAgentRunner(BaseAgentRunner):
         return tool_calls
 
     def _init_system_message(
-        self, prompt_template: str, prompt_messages: list[PromptMessage] = None
+        self, prompt_template: str, prompt_messages: Optional[list[PromptMessage]] = None
     ) -> list[PromptMessage]:
         """
         Initialize system message
@@ -385,7 +385,7 @@ class FunctionCallAgentRunner(BaseAgentRunner):
 
         return prompt_messages
 
-    def _organize_user_query(self, query, prompt_messages: list[PromptMessage] = None) -> list[PromptMessage]:
+    def _organize_user_query(self, query, prompt_messages: list[PromptMessage]) -> list[PromptMessage]:
         """
         Organize user query
         """

api/core/agent/output_parser/cot_output_parser.py

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

api/core/callback_handler/agent_tool_callback_handler.py

@@ -1,9 +1,9 @@
-import os
 from collections.abc import Mapping, Sequence
 from typing import Any, Optional, TextIO, Union
 
 from pydantic import BaseModel
 
+from configs import dify_config
 from core.ops.entities.trace_entity import TraceTaskName
 from core.ops.ops_trace_manager import TraceQueueManager, TraceTask
 from core.tools.entities.tool_entities import ToolInvokeMessage
@@ -50,6 +50,7 @@ class DifyAgentCallbackHandler(BaseModel):
         tool_inputs: Mapping[str, Any],
     ) -> None:
         """Do nothing."""
+        if dify_config.DEBUG:
             print_text("\n[on_tool_start] ToolCall:" + tool_name + "\n" + str(tool_inputs) + "\n", color=self.color)
 
     def on_tool_end(
@@ -62,6 +63,7 @@ class DifyAgentCallbackHandler(BaseModel):
         trace_manager: Optional[TraceQueueManager] = None,
     ) -> None:
         """If not the final action, print out observation."""
+        if dify_config.DEBUG:
             print_text("\n[on_tool_end]\n", color=self.color)
             print_text("Tool: " + tool_name + "\n", color=self.color)
             print_text("Inputs: " + str(tool_inputs) + "\n", color=self.color)
@@ -82,10 +84,12 @@ class DifyAgentCallbackHandler(BaseModel):
 
     def on_tool_error(self, error: Union[Exception, KeyboardInterrupt], **kwargs: Any) -> None:
         """Do nothing."""
+        if dify_config.DEBUG:
             print_text("\n[on_tool_error] Error: " + str(error) + "\n", color="red")
 
     def on_agent_start(self, thought: str) -> None:
         """Run on agent start."""
+        if dify_config.DEBUG:
             if thought:
                 print_text(
                     "\n[on_agent_start] \nCurrent Loop: " + str(self.current_loop) + "\nThought: " + thought + "\n",
@@ -96,6 +100,7 @@ class DifyAgentCallbackHandler(BaseModel):
 
     def on_agent_finish(self, color: Optional[str] = None, **kwargs: Any) -> None:
         """Run on agent end."""
+        if dify_config.DEBUG:
             print_text("\n[on_agent_finish]\n Loop: " + str(self.current_loop) + "\n", color=self.color)
 
         self.current_loop += 1
@@ -103,9 +108,9 @@ class DifyAgentCallbackHandler(BaseModel):
     @property
     def ignore_agent(self) -> bool:
         """Whether to ignore agent callbacks."""
-        return not os.environ.get("DEBUG") or os.environ.get("DEBUG").lower() != "true"
+        return not dify_config.DEBUG
 
     @property
     def ignore_chat_model(self) -> bool:
         """Whether to ignore chat model callbacks."""
-        return not os.environ.get("DEBUG") or os.environ.get("DEBUG").lower() != "true"
+        return not dify_config.DEBUG

api/core/callback_handler/index_tool_callback_handler.py

@@ -44,7 +44,6 @@ class DatasetIndexToolCallbackHandler:
                 DocumentSegment.index_node_id == document.metadata["doc_id"]
             )
 
-            # if 'dataset_id' in document.metadata:
             if "dataset_id" in document.metadata:
                 query = query.filter(DocumentSegment.dataset_id == document.metadata["dataset_id"])
 

api/core/file/message_file_parser.py

@@ -198,6 +198,8 @@ class MessageFileParser:
                     if "amazonaws.com" not in parsed_url.netloc:
                         return False
                     query_params = parse_qs(parsed_url.query)
+
+                    def check_presign_v2(query_params):
                         required_params = ["Signature", "Expires"]
                         for param in required_params:
                             if param not in query_params:
@@ -207,7 +209,23 @@ class MessageFileParser:
                         signature = query_params["Signature"][0]
                         if not re.match(r"^[A-Za-z0-9+/]+={0,2}$", signature):
                             return False
+
                         return True
+
+                    def check_presign_v4(query_params):
+                        required_params = ["X-Amz-Signature", "X-Amz-Expires"]
+                        for param in required_params:
+                            if param not in query_params:
+                                return False
+                        if not query_params["X-Amz-Expires"][0].isdigit():
+                            return False
+                        signature = query_params["X-Amz-Signature"][0]
+                        if not re.match(r"^[A-Za-z0-9+/]+={0,2}$", signature):
+                            return False
+
+                        return True
+
+                    return check_presign_v4(query_params) or check_presign_v2(query_params)
                 except Exception:
                     return False
 

api/core/indexing_runner.py

@@ -211,9 +211,9 @@ class IndexingRunner:
         tenant_id: str,
         extract_settings: list[ExtractSetting],
         tmp_processing_rule: dict,
-        doc_form: str = None,
+        doc_form: Optional[str] = None,
         doc_language: str = "English",
-        dataset_id: str = None,
+        dataset_id: Optional[str] = None,
         indexing_technique: str = "economy",
     ) -> dict:
         """

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

@@ -169,7 +169,7 @@ class AnthropicLargeLanguageModel(LargeLanguageModel):
         stop: Optional[list[str]] = None,
         stream: bool = True,
         user: Optional[str] = None,
-        callbacks: list[Callback] = None,
+        callbacks: Optional[list[Callback]] = None,
     ) -> Union[LLMResult, Generator]:
         """
         Code block mode wrapper for invoking large language model

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

@@ -1081,8 +1081,81 @@ LLM_BASE_MODELS = [
             ),
         ),
     ),
+    AzureBaseModel(
+        base_model_name="o1-preview",
+        entity=AIModelEntity(
+            model="fake-deployment-name",
+            label=I18nObject(
+                en_US="fake-deployment-name-label",
+            ),
+            model_type=ModelType.LLM,
+            features=[
+                ModelFeature.AGENT_THOUGHT,
+            ],
+            fetch_from=FetchFrom.CUSTOMIZABLE_MODEL,
+            model_properties={
+                ModelPropertyKey.MODE: LLMMode.CHAT.value,
+                ModelPropertyKey.CONTEXT_SIZE: 128000,
+            },
+            parameter_rules=[
+                ParameterRule(
+                    name="response_format",
+                    label=I18nObject(zh_Hans="回复格式", en_US="response_format"),
+                    type="string",
+                    help=I18nObject(
+                        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"],
+                ),
+                _get_max_tokens(default=512, min_val=1, max_val=32768),
+            ],
+            pricing=PriceConfig(
+                input=15.00,
+                output=60.00,
+                unit=0.000001,
+                currency="USD",
+            ),
+        ),
+    ),
+    AzureBaseModel(
+        base_model_name="o1-mini",
+        entity=AIModelEntity(
+            model="fake-deployment-name",
+            label=I18nObject(
+                en_US="fake-deployment-name-label",
+            ),
+            model_type=ModelType.LLM,
+            features=[
+                ModelFeature.AGENT_THOUGHT,
+            ],
+            fetch_from=FetchFrom.CUSTOMIZABLE_MODEL,
+            model_properties={
+                ModelPropertyKey.MODE: LLMMode.CHAT.value,
+                ModelPropertyKey.CONTEXT_SIZE: 128000,
+            },
+            parameter_rules=[
+                ParameterRule(
+                    name="response_format",
+                    label=I18nObject(zh_Hans="回复格式", en_US="response_format"),
+                    type="string",
+                    help=I18nObject(
+                        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"],
+                ),
+                _get_max_tokens(default=512, min_val=1, max_val=65536),
+            ],
+            pricing=PriceConfig(
+                input=3.00,
+                output=12.00,
+                unit=0.000001,
+                currency="USD",
+            ),
+        ),
+    ),
 ]
-
 EMBEDDING_BASE_MODELS = [
     AzureBaseModel(
         base_model_name="text-embedding-ada-002",

api/core/model_runtime/model_providers/azure_openai/azure_openai.yaml

@@ -120,6 +120,18 @@ model_credential_schema:
           show_on:
             - variable: __model_type
               value: llm
+        - label:
+            en_US: o1-mini
+          value: o1-mini
+          show_on:
+            - variable: __model_type
+              value: llm
+        - label:
+            en_US: o1-preview
+          value: o1-preview
+          show_on:
+            - variable: __model_type
+              value: llm
         - label:
             en_US: gpt-4o-mini
           value: gpt-4o-mini

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

@@ -312,10 +312,24 @@ class AzureOpenAILargeLanguageModel(_CommonAzureOpenAI, LargeLanguageModel):
         if user:
             extra_model_kwargs["user"] = user
 
+            # clear illegal prompt messages
+            prompt_messages = self._clear_illegal_prompt_messages(model, prompt_messages)
+
+            block_as_stream = False
+            if model.startswith("o1"):
+                if stream:
+                    block_as_stream = True
+                    stream = False
+
+                    if "stream_options" in extra_model_kwargs:
+                        del extra_model_kwargs["stream_options"]
+
+                if "stop" in extra_model_kwargs:
+                    del extra_model_kwargs["stop"]
+
             # chat model
-        messages = [self._convert_prompt_message_to_dict(m) for m in prompt_messages]
             response = client.chat.completions.create(
-            messages=messages,
+                messages=[self._convert_prompt_message_to_dict(m) for m in prompt_messages],
                 model=model,
                 stream=stream,
                 **model_parameters,
@@ -325,7 +339,91 @@ class AzureOpenAILargeLanguageModel(_CommonAzureOpenAI, LargeLanguageModel):
             if stream:
                 return self._handle_chat_generate_stream_response(model, credentials, response, prompt_messages, tools)
 
-        return self._handle_chat_generate_response(model, credentials, response, prompt_messages, tools)
+            block_result = self._handle_chat_generate_response(model, credentials, response, prompt_messages, tools)
+
+            if block_as_stream:
+                return self._handle_chat_block_as_stream_response(block_result, prompt_messages, stop)
+
+            return block_result
+
+    def _handle_chat_block_as_stream_response(
+        self,
+        block_result: LLMResult,
+        prompt_messages: list[PromptMessage],
+        stop: Optional[list[str]] = None,
+    ) -> Generator[LLMResultChunk, None, None]:
+        """
+        Handle llm chat response
+
+        :param model: model name
+        :param credentials: credentials
+        :param response: response
+        :param prompt_messages: prompt messages
+        :param tools: tools for tool calling
+        :param stop: stop words
+        :return: llm response chunk generator
+        """
+        text = block_result.message.content
+        text = cast(str, text)
+
+        if stop:
+            text = self.enforce_stop_tokens(text, stop)
+
+        yield LLMResultChunk(
+            model=block_result.model,
+            prompt_messages=prompt_messages,
+            system_fingerprint=block_result.system_fingerprint,
+            delta=LLMResultChunkDelta(
+                index=0,
+                message=AssistantPromptMessage(content=text),
+                finish_reason="stop",
+                usage=block_result.usage,
+            ),
+        )
+
+    def _clear_illegal_prompt_messages(self, model: str, prompt_messages: list[PromptMessage]) -> list[PromptMessage]:
+        """
+        Clear illegal prompt messages for OpenAI API
+
+        :param model: model name
+        :param prompt_messages: prompt messages
+        :return: cleaned prompt messages
+        """
+        checklist = ["gpt-4-turbo", "gpt-4-turbo-2024-04-09"]
+
+        if model in checklist:
+            # count how many user messages are there
+            user_message_count = len([m for m in prompt_messages if isinstance(m, UserPromptMessage)])
+            if user_message_count > 1:
+                for prompt_message in prompt_messages:
+                    if isinstance(prompt_message, UserPromptMessage):
+                        if isinstance(prompt_message.content, list):
+                            prompt_message.content = "\n".join(
+                                [
+                                    item.data
+                                    if item.type == PromptMessageContentType.TEXT
+                                    else "[IMAGE]"
+                                    if item.type == PromptMessageContentType.IMAGE
+                                    else ""
+                                    for item in prompt_message.content
+                                ]
+                            )
+
+        if model.startswith("o1"):
+            system_message_count = len([m for m in prompt_messages if isinstance(m, SystemPromptMessage)])
+            if system_message_count > 0:
+                new_prompt_messages = []
+                for prompt_message in prompt_messages:
+                    if isinstance(prompt_message, SystemPromptMessage):
+                        prompt_message = UserPromptMessage(
+                            content=prompt_message.content,
+                            name=prompt_message.name,
+                        )
+
+                    new_prompt_messages.append(prompt_message)
+                prompt_messages = new_prompt_messages
+
+        return prompt_messages
 
     def _handle_chat_generate_response(
         self,
@@ -560,7 +658,7 @@ class AzureOpenAILargeLanguageModel(_CommonAzureOpenAI, LargeLanguageModel):
             tokens_per_message = 4
             # if there's a name, the role is omitted
             tokens_per_name = -1
-        elif model.startswith("gpt-35-turbo") or model.startswith("gpt-4"):
+        elif model.startswith("gpt-35-turbo") or model.startswith("gpt-4") or model.startswith("o1"):
             tokens_per_message = 3
             tokens_per_name = 1
         else:

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

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

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

@@ -92,7 +92,7 @@ class BedrockLargeLanguageModel(LargeLanguageModel):
         stop: Optional[list[str]] = None,
         stream: bool = True,
         user: Optional[str] = None,
-        callbacks: list[Callback] = None,
+        callbacks: Optional[list[Callback]] = None,
     ) -> Union[LLMResult, Generator]:
         """
         Code block mode wrapper for invoking large language model

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

@@ -511,7 +511,7 @@ class FireworksLargeLanguageModel(_CommonFireworks, LargeLanguageModel):
         model: str,
         messages: list[PromptMessage],
         tools: Optional[list[PromptMessageTool]] = None,
-        credentials: dict = None,
+        credentials: Optional[dict] = None,
     ) -> int:
         """
         Approximate num tokens with GPT2 tokenizer.

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

@@ -0,0 +1,15 @@
+- gemini-1.5-pro
+- gemini-1.5-pro-latest
+- gemini-1.5-pro-001
+- gemini-1.5-pro-002
+- gemini-1.5-pro-exp-0801
+- gemini-1.5-pro-exp-0827
+- gemini-1.5-flash
+- gemini-1.5-flash-latest
+- gemini-1.5-flash-001
+- gemini-1.5-flash-002
+- gemini-1.5-flash-exp-0827
+- gemini-1.5-flash-8b-exp-0827
+- gemini-1.5-flash-8b-exp-0924
+- gemini-pro
+- gemini-pro-vision

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

@@ -5,3 +5,4 @@
 - llama3-8b-8192
 - mixtral-8x7b-32768
 - llama2-70b-4096
+- llama-guard-3-8b

api/core/model_runtime/model_providers/groq/llm/llama-guard-3-8b.yaml

@@ -0,0 +1,25 @@
+model: llama-guard-3-8b
+label:
+  zh_Hans: Llama-Guard-3-8B
+  en_US: Llama-Guard-3-8B
+model_type: llm
+features:
+  - agent-thought
+model_properties:
+  mode: chat
+  context_size: 8192
+parameter_rules:
+  - name: temperature
+    use_template: temperature
+  - name: top_p
+    use_template: top_p
+  - name: max_tokens
+    use_template: max_tokens
+    default: 512
+    min: 1
+    max: 8192
+pricing:
+  input: '0.20'
+  output: '0.20'
+  unit: '0.000001'
+  currency: USD

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

@@ -111,7 +111,7 @@ class OpenAILargeLanguageModel(_CommonOpenAI, LargeLanguageModel):
         stop: Optional[list[str]] = None,
         stream: bool = True,
         user: Optional[str] = None,
-        callbacks: list[Callback] = None,
+        callbacks: Optional[list[Callback]] = None,
     ) -> Union[LLMResult, Generator]:
         """
         Code block mode wrapper for invoking large language model

api/core/model_runtime/model_providers/openai/speech2text/speech2text.py

@@ -2,6 +2,8 @@ from typing import IO, Optional
 
 from openai import OpenAI
 
+from core.model_runtime.entities.common_entities import I18nObject
+from core.model_runtime.entities.model_entities import AIModelEntity, FetchFrom, ModelType
 from core.model_runtime.errors.validate import CredentialsValidateFailedError
 from core.model_runtime.model_providers.__base.speech2text_model import Speech2TextModel
 from core.model_runtime.model_providers.openai._common import _CommonOpenAI
@@ -58,3 +60,18 @@ class OpenAISpeech2TextModel(_CommonOpenAI, Speech2TextModel):
         response = client.audio.transcriptions.create(model=model, file=file)
 
         return response.text
+
+    def get_customizable_model_schema(self, model: str, credentials: dict) -> AIModelEntity | None:
+        """
+        used to define customizable model schema
+        """
+        entity = AIModelEntity(
+            model=model,
+            label=I18nObject(en_US=model),
+            fetch_from=FetchFrom.CUSTOMIZABLE_MODEL,
+            model_type=ModelType.SPEECH2TEXT,
+            model_properties={},
+            parameter_rules=[],
+        )
+
+        return entity

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

@@ -688,7 +688,7 @@ class OAIAPICompatLargeLanguageModel(_CommonOaiApiCompat, LargeLanguageModel):
         model: str,
         messages: list[PromptMessage],
         tools: Optional[list[PromptMessageTool]] = None,
-        credentials: dict = None,
+        credentials: Optional[dict] = None,
     ) -> int:
         """
         Approximate num tokens with GPT2 tokenizer.

api/core/model_runtime/model_providers/openai_api_compatible/speech2text/speech2text.py

@@ -3,6 +3,8 @@ from urllib.parse import urljoin
 
 import requests
 
+from core.model_runtime.entities.common_entities import I18nObject
+from core.model_runtime.entities.model_entities import AIModelEntity, FetchFrom, ModelType
 from core.model_runtime.errors.invoke import InvokeBadRequestError
 from core.model_runtime.errors.validate import CredentialsValidateFailedError
 from core.model_runtime.model_providers.__base.speech2text_model import Speech2TextModel
@@ -59,3 +61,18 @@ class OAICompatSpeech2TextModel(_CommonOaiApiCompat, Speech2TextModel):
                 self._invoke(model, credentials, audio_file)
         except Exception as ex:
             raise CredentialsValidateFailedError(str(ex))
+
+    def get_customizable_model_schema(self, model: str, credentials: dict) -> AIModelEntity | None:
+        """
+        used to define customizable model schema
+        """
+        entity = AIModelEntity(
+            model=model,
+            label=I18nObject(en_US=model),
+            fetch_from=FetchFrom.CUSTOMIZABLE_MODEL,
+            model_type=ModelType.SPEECH2TEXT,
+            model_properties={},
+            parameter_rules=[],
+        )
+
+        return entity

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

@@ -14,6 +14,10 @@
 - google/gemini-pro
 - cohere/command-r-plus
 - cohere/command-r
+- meta-llama/llama-3.2-1b-instruct
+- meta-llama/llama-3.2-3b-instruct
+- meta-llama/llama-3.2-11b-vision-instruct
+- meta-llama/llama-3.2-90b-vision-instruct
 - meta-llama/llama-3.1-405b-instruct
 - meta-llama/llama-3.1-70b-instruct
 - meta-llama/llama-3.1-8b-instruct
@@ -22,6 +26,7 @@
 - mistralai/mixtral-8x22b-instruct
 - mistralai/mixtral-8x7b-instruct
 - mistralai/mistral-7b-instruct
+- qwen/qwen-2.5-72b-instruct
 - qwen/qwen-2-72b-instruct
 - deepseek/deepseek-chat
 - deepseek/deepseek-coder

api/core/model_runtime/model_providers/openrouter/llm/claude-3-5-sonnet.yaml

@@ -27,9 +27,9 @@ parameter_rules:
   - name: max_tokens
     use_template: max_tokens
     required: true
-    default: 4096
+    default: 8192
     min: 1
-    max: 4096
+    max: 8192
   - name: response_format
     use_template: response_format
 pricing:

api/core/model_runtime/model_providers/openrouter/llm/llama-3.2-11b-vision-instruct.yaml

@@ -0,0 +1,45 @@
+model: meta-llama/llama-3.2-11b-vision-instruct
+label:
+  zh_Hans: llama-3.2-11b-vision-instruct
+  en_US: llama-3.2-11b-vision-instruct
+model_type: llm
+features:
+  - agent-thought
+model_properties:
+  mode: chat
+  context_size: 131072
+parameter_rules:
+  - name: temperature
+    use_template: temperature
+  - name: top_p
+    use_template: top_p
+  - name: top_k
+    label:
+      zh_Hans: 取样数量
+      en_US: Top k
+    type: int
+    help:
+      zh_Hans: 仅从每个后续标记的前 K 个选项中采样。
+      en_US: Only sample from the top K options for each subsequent token.
+  - name: max_tokens
+    use_template: max_tokens
+  - name: context_length_exceeded_behavior
+    default: None
+    label:
+      zh_Hans: 上下文长度超出行为
+      en_US: Context Length Exceeded Behavior
+    help:
+      zh_Hans: 上下文长度超出行为
+      en_US: Context Length Exceeded Behavior
+    type: string
+    options:
+      - None
+      - truncate
+      - error
+  - name: response_format
+    use_template: response_format
+pricing:
+  input: '0.055'
+  output: '0.055'
+  unit: '0.000001'
+  currency: USD

api/core/model_runtime/model_providers/openrouter/llm/llama-3.2-1b-instruct.yaml

@@ -0,0 +1,45 @@
+model: meta-llama/llama-3.2-1b-instruct
+label:
+  zh_Hans: llama-3.2-1b-instruct
+  en_US: llama-3.2-1b-instruct
+model_type: llm
+features:
+  - agent-thought
+model_properties:
+  mode: chat
+  context_size: 131072
+parameter_rules:
+  - name: temperature
+    use_template: temperature
+  - name: top_p
+    use_template: top_p
+  - name: top_k
+    label:
+      zh_Hans: 取样数量
+      en_US: Top k
+    type: int
+    help:
+      zh_Hans: 仅从每个后续标记的前 K 个选项中采样。
+      en_US: Only sample from the top K options for each subsequent token.
+  - name: max_tokens
+    use_template: max_tokens
+  - name: context_length_exceeded_behavior
+    default: None
+    label:
+      zh_Hans: 上下文长度超出行为
+      en_US: Context Length Exceeded Behavior
+    help:
+      zh_Hans: 上下文长度超出行为
+      en_US: Context Length Exceeded Behavior
+    type: string
+    options:
+      - None
+      - truncate
+      - error
+  - name: response_format
+    use_template: response_format
+pricing:
+  input: '0.01'
+  output: '0.02'
+  unit: '0.000001'
+  currency: USD

api/core/model_runtime/model_providers/openrouter/llm/llama-3.2-3b-instruct.yaml

@@ -0,0 +1,45 @@
+model: meta-llama/llama-3.2-3b-instruct
+label:
+  zh_Hans: llama-3.2-3b-instruct
+  en_US: llama-3.2-3b-instruct
+model_type: llm
+features:
+  - agent-thought
+model_properties:
+  mode: chat
+  context_size: 131072
+parameter_rules:
+  - name: temperature
+    use_template: temperature
+  - name: top_p
+    use_template: top_p
+  - name: top_k
+    label:
+      zh_Hans: 取样数量
+      en_US: Top k
+    type: int
+    help:
+      zh_Hans: 仅从每个后续标记的前 K 个选项中采样。
+      en_US: Only sample from the top K options for each subsequent token.
+  - name: max_tokens
+    use_template: max_tokens
+  - name: context_length_exceeded_behavior
+    default: None
+    label:
+      zh_Hans: 上下文长度超出行为
+      en_US: Context Length Exceeded Behavior
+    help:
+      zh_Hans: 上下文长度超出行为
+      en_US: Context Length Exceeded Behavior
+    type: string
+    options:
+      - None
+      - truncate
+      - error
+  - name: response_format
+    use_template: response_format
+pricing:
+  input: '0.03'
+  output: '0.05'
+  unit: '0.000001'
+  currency: USD

api/core/model_runtime/model_providers/openrouter/llm/llama-3.2-90b-vision-instruct.yaml

@@ -0,0 +1,45 @@
+model: meta-llama/llama-3.2-90b-vision-instruct
+label:
+  zh_Hans: llama-3.2-90b-vision-instruct
+  en_US: llama-3.2-90b-vision-instruct
+model_type: llm
+features:
+  - agent-thought
+model_properties:
+  mode: chat
+  context_size: 131072
+parameter_rules:
+  - name: temperature
+    use_template: temperature
+  - name: top_p
+    use_template: top_p
+  - name: top_k
+    label:
+      zh_Hans: 取样数量
+      en_US: Top k
+    type: int
+    help:
+      zh_Hans: 仅从每个后续标记的前 K 个选项中采样。
+      en_US: Only sample from the top K options for each subsequent token.
+  - name: max_tokens
+    use_template: max_tokens
+  - name: context_length_exceeded_behavior
+    default: None
+    label:
+      zh_Hans: 上下文长度超出行为
+      en_US: Context Length Exceeded Behavior
+    help:
+      zh_Hans: 上下文长度超出行为
+      en_US: Context Length Exceeded Behavior
+    type: string
+    options:
+      - None
+      - truncate
+      - error
+  - name: response_format
+    use_template: response_format
+pricing:
+  input: '0.35'
+  output: '0.4'
+  unit: '0.000001'
+  currency: USD

api/core/model_runtime/model_providers/openrouter/llm/qwen2.5-72b-instruct.yaml

@@ -0,0 +1,30 @@
+model: qwen/qwen-2.5-72b-instruct
+label:
+  en_US: qwen-2.5-72b-instruct
+model_type: llm
+features:
+  - agent-thought
+model_properties:
+  mode: chat
+  context_size: 131072
+parameter_rules:
+  - name: temperature
+    use_template: temperature
+  - name: max_tokens
+    use_template: max_tokens
+    type: int
+    default: 512
+    min: 1
+    max: 8192
+    help:
+      zh_Hans: 指定生成结果长度的上限。如果生成结果截断，可以调大该参数。
+      en_US: Specifies the upper limit on the length of generated results. If the generated results are truncated, you can increase this parameter.
+  - name: top_p
+    use_template: top_p
+  - name: frequency_penalty
+    use_template: frequency_penalty
+pricing:
+  input: "0.35"
+  output: "0.4"
+  unit: "0.000001"
+  currency: USD

api/core/model_runtime/model_providers/sagemaker/tts/tts.py

@@ -77,7 +77,7 @@ class SageMakerText2SpeechModel(TTSModel):
         """
         pass
 
-    def _detect_lang_code(self, content: str, map_dict: dict = None):
+    def _detect_lang_code(self, content: str, map_dict: Optional[dict] = None):
         map_dict = {"zh": "<|zh|>", "en": "<|en|>", "ja": "<|jp|>", "zh-TW": "<|yue|>", "ko": "<|ko|>"}
 
         response = self.comprehend_client.detect_dominant_language(Text=content)

api/core/model_runtime/model_providers/voyage/rerank/_position.yaml

@@ -0,0 +1,4 @@
+- rerank-2
+- rerank-lite-2
+- rerank-1
+- rerank-lite-1

api/core/model_runtime/model_providers/voyage/rerank/rerank-2.yaml

@@ -0,0 +1,4 @@
+model: rerank-2
+model_type: rerank
+model_properties:
+  context_size: 16000

api/core/model_runtime/model_providers/voyage/rerank/rerank-lite-2.yaml

@@ -0,0 +1,4 @@
+model: rerank-lite-2
+model_type: rerank
+model_properties:
+  context_size: 8000

api/core/model_runtime/model_providers/voyage/text_embedding/_position.yaml

@@ -0,0 +1,6 @@
+- voyage-3
+- voyage-3-lite
+- voyage-finance-2
+- voyage-multilingual-2
+- voyage-law-2
+- voyage-code-2

api/core/model_runtime/model_providers/voyage/text_embedding/voyage-code-2.yaml

@@ -0,0 +1,8 @@
+model: voyage-code-2
+model_type: text-embedding
+model_properties:
+  context_size: 16000
+pricing:
+  input: '0.00012'
+  unit: '0.001'
+  currency: USD

api/core/model_runtime/model_providers/voyage/text_embedding/voyage-finance-2.yaml

@@ -0,0 +1,8 @@
+model: voyage-finance-2
+model_type: text-embedding
+model_properties:
+  context_size: 32000
+pricing:
+  input: '0.00012'
+  unit: '0.001'
+  currency: USD

api/core/model_runtime/model_providers/voyage/text_embedding/voyage-law-2.yaml

@@ -0,0 +1,8 @@
+model: voyage-law-2
+model_type: text-embedding
+model_properties:
+  context_size: 16000
+pricing:
+  input: '0.00012'
+  unit: '0.001'
+  currency: USD

api/core/model_runtime/model_providers/voyage/text_embedding/voyage-multilingual-2.yaml

@@ -0,0 +1,8 @@
+model: voyage-multilingual-2
+model_type: text-embedding
+model_properties:
+  context_size: 32000
+pricing:
+  input: '0.00012'
+  unit: '0.001'
+  currency: USD

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

@@ -64,7 +64,7 @@ class ErnieBotLargeLanguageModel(LargeLanguageModel):
         stop: Optional[list[str]] = None,
         stream: bool = True,
         user: Optional[str] = None,
-        callbacks: list[Callback] = None,
+        callbacks: Optional[list[Callback]] = None,
     ) -> Union[LLMResult, Generator]:
         """
         Code block mode wrapper for invoking large language model

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

@@ -223,6 +223,16 @@ class ZhipuAILargeLanguageModel(_CommonZhipuaiAI, LargeLanguageModel):
                 else:
                     new_prompt_messages.append(copy_prompt_message)
 
+        # zhipuai moved web_search param to tools
+        if "web_search" in model_parameters:
+            enable_web_search = model_parameters.get("web_search")
+            model_parameters.pop("web_search")
+            web_search_params = {"type": "web_search", "web_search": {"enable": enable_web_search}}
+            if "tools" in model_parameters:
+                model_parameters["tools"].append(web_search_params)
+            else:
+                model_parameters["tools"] = [web_search_params]
+
         if model in {"glm-4v", "glm-4v-plus"}:
             params = self._construct_glm_4v_parameter(model, new_prompt_messages, model_parameters)
         else:

api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/assistant/assistant.py

@@ -41,8 +41,8 @@ class Assistant(BaseAPI):
         conversation_id: Optional[str] = None,
         attachments: Optional[list[assistant_create_params.AssistantAttachments]] = None,
         metadata: dict | None = None,
-        request_id: str = None,
+        request_id: Optional[str] = None,
-        user_id: str = None,
+        user_id: Optional[str] = None,
         extra_headers: Headers | None = None,
         extra_body: Body | None = None,
         timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN,
@@ -72,9 +72,9 @@ class Assistant(BaseAPI):
     def query_support(
         self,
         *,
-        assistant_id_list: list[str] = None,
+        assistant_id_list: Optional[list[str]] = None,
-        request_id: str = None,
+        request_id: Optional[str] = None,
-        user_id: str = None,
+        user_id: Optional[str] = None,
         extra_headers: Headers | None = None,
         extra_body: Body | None = None,
         timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN,
@@ -99,8 +99,8 @@ class Assistant(BaseAPI):
         page: int = 1,
         page_size: int = 10,
         *,
-        request_id: str = None,
+        request_id: Optional[str] = None,
-        user_id: str = None,
+        user_id: Optional[str] = None,
         extra_headers: Headers | None = None,
         extra_body: Body | None = None,
         timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN,

api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/files.py

@@ -1,7 +1,7 @@
 from __future__ import annotations
 
 from collections.abc import Mapping
-from typing import TYPE_CHECKING, Literal, cast
+from typing import TYPE_CHECKING, Literal, Optional, cast
 
 import httpx
 
@@ -34,11 +34,11 @@ class Files(BaseAPI):
     def create(
         self,
         *,
-        file: FileTypes = None,
+        file: Optional[FileTypes] = None,
-        upload_detail: list[UploadDetail] = None,
+        upload_detail: Optional[list[UploadDetail]] = None,
         purpose: Literal["fine-tune", "retrieval", "batch"],
-        knowledge_id: str = None,
+        knowledge_id: Optional[str] = None,
-        sentence_size: int = None,
+        sentence_size: Optional[int] = None,
         extra_headers: Headers | None = None,
         extra_body: Body | None = None,
         timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN,

api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/knowledge/document/document.py

@@ -34,12 +34,12 @@ class Document(BaseAPI):
     def create(
         self,
         *,
-        file: FileTypes = None,
+        file: Optional[FileTypes] = None,
         custom_separator: Optional[list[str]] = None,
-        upload_detail: list[UploadDetail] = None,
+        upload_detail: Optional[list[UploadDetail]] = None,
         purpose: Literal["retrieval"],
-        knowledge_id: str = None,
+        knowledge_id: Optional[str] = None,
-        sentence_size: int = None,
+        sentence_size: Optional[int] = None,
         extra_headers: Headers | None = None,
         extra_body: Body | None = None,
         timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN,

api/core/model_runtime/model_providers/zhipuai/zhipuai_sdk/api_resource/videos/videos.py

@@ -31,11 +31,11 @@ class Videos(BaseAPI):
         self,
         model: str,
         *,
-        prompt: str = None,
+        prompt: Optional[str] = None,
-        image_url: str = None,
+        image_url: Optional[str] = None,
         sensitive_word_check: Optional[SensitiveWordCheckRequest] | NotGiven = NOT_GIVEN,
-        request_id: str = None,
+        request_id: Optional[str] = None,
-        user_id: str = None,
+        user_id: Optional[str] = None,
         extra_headers: Headers | None = None,
         extra_body: Body | None = None,
         timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN,

api/core/ops/langfuse_trace/langfuse_trace.py

@@ -159,6 +159,16 @@ class LangFuseDataTrace(BaseTraceInstance):
                     "status": status,
                 }
             )
+            process_data = json.loads(node_execution.process_data) if node_execution.process_data else {}
+            model_provider = process_data.get("model_provider", None)
+            model_name = process_data.get("model_name", None)
+            if model_provider is not None and model_name is not None:
+                metadata.update(
+                    {
+                        "model_provider": model_provider,
+                        "model_name": model_name,
+                    }
+                )
 
             # add span
             if trace_info.message_id:
@@ -191,7 +201,6 @@ class LangFuseDataTrace(BaseTraceInstance):
 
             self.add_span(langfuse_span_data=span_data)
 
-            process_data = json.loads(node_execution.process_data) if node_execution.process_data else {}
             if process_data and process_data.get("model_mode") == "chat":
                 total_token = metadata.get("total_tokens", 0)
                 # add generation

api/core/rag/datasource/vdb/relyt/relyt_vector.py

@@ -162,7 +162,7 @@ class RelytVector(BaseVector):
         else:
             return None
 
-    def delete_by_uuids(self, ids: list[str] = None):
+    def delete_by_uuids(self, ids: Optional[list[str]] = None):
         """Delete by vector IDs.
 
         Args:

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

@@ -1,5 +1,5 @@
 from abc import ABC, abstractmethod
-from typing import Any
+from typing import Any, Optional
 
 from configs import dify_config
 from core.embedding.cached_embedding import CacheEmbedding
@@ -25,7 +25,7 @@ class AbstractVectorFactory(ABC):
 
 
 class Vector:
-    def __init__(self, dataset: Dataset, attributes: list = None):
+    def __init__(self, dataset: Dataset, attributes: Optional[list] = None):
         if attributes is None:
             attributes = ["doc_id", "dataset_id", "document_id", "doc_hash"]
         self._dataset = dataset
@@ -106,7 +106,7 @@ class Vector:
             case _:
                 raise ValueError(f"Vector store {vector_type} is not supported.")
 
-    def create(self, texts: list = None, **kwargs):
+    def create(self, texts: Optional[list] = None, **kwargs):
         if texts:
             embeddings = self._embeddings.embed_documents([document.page_content for document in texts])
             self._vector_processor.create(texts=texts, embeddings=embeddings, **kwargs)

api/core/rag/extractor/extract_processor.py

@@ -1,7 +1,7 @@
 import re
 import tempfile
 from pathlib import Path
-from typing import Union
+from typing import Optional, Union
 from urllib.parse import unquote
 
 from configs import dify_config
@@ -84,7 +84,7 @@ class ExtractProcessor:
 
     @classmethod
     def extract(
-        cls, extract_setting: ExtractSetting, is_automatic: bool = False, file_path: str = None
+        cls, extract_setting: ExtractSetting, is_automatic: bool = False, file_path: Optional[str] = None
     ) -> list[Document]:
         if extract_setting.datasource_type == DatasourceType.FILE.value:
             with tempfile.TemporaryDirectory() as temp_dir:

api/core/rag/extractor/unstructured/unstructured_epub_extractor.py

@@ -1,4 +1,5 @@
 import logging
+from typing import Optional
 
 from core.rag.extractor.extractor_base import BaseExtractor
 from core.rag.models.document import Document
@@ -17,7 +18,7 @@ class UnstructuredEpubExtractor(BaseExtractor):
     def __init__(
         self,
         file_path: str,
-        api_url: str = None,
+        api_url: Optional[str] = None,
     ):
         """Initialize with file path."""
         self._file_path = file_path

api/core/tools/entities/tool_entities.py

@@ -341,7 +341,7 @@ class ToolRuntimeVariablePool(BaseModel):
 
         self.pool.append(variable)
 
-    def set_file(self, tool_name: str, value: str, name: str = None) -> None:
+    def set_file(self, tool_name: str, value: str, name: Optional[str] = None) -> None:
         """
         set an image variable
 

api/core/tools/provider/_position.yaml

@@ -5,31 +5,41 @@
 - searchapi
 - serper
 - searxng
+- websearch
+- tavily
+- stackexchange
+- pubmed
+- arxiv
+- aws
+- nominatim
+- devdocs
+- spider
+- firecrawl
+- brave
+- crossref
+- jina
+- webscraper
 - dalle
 - azuredalle
 - stability
-- wikipedia
-- nominatim
-- yahoo
-- alphavantage
-- arxiv
-- pubmed
 - stablediffusion
-- webscraper
+- cogview
-- jina
+- comfyui
-- aippt
+- getimgai
-- youtube
+- siliconflow
-- code
+- spark
-- wolframalpha
+- stepfun
-- maths
+- xinference
-- github
+- alphavantage
-- chart
+- yahoo
-- time
+- openweather
-- vectorizer
 - gaode
-- wecom
+- aippt
-- qrcode
+- chart
+- youtube
+- did
 - dingtalk
+- discord
 - feishu
 - feishu_base
 - feishu_document
@@ -39,4 +49,24 @@
 - feishu_calendar
 - feishu_spreadsheet
 - slack
+- twilio
+- wecom
+- wikipedia
+- code
+- wolframalpha
+- maths
+- github
+- gitlab
+- time
+- vectorizer
+- qrcode
 - tianditu
+- google_translate
+- hap
+- json_process
+- judge0ce
+- novitaai
+- onebot
+- regex
+- trello
+- vanna

api/core/tools/provider/builtin/aws/tools/sagemaker_tts.py

@@ -1,6 +1,6 @@
 import json
 from enum import Enum
-from typing import Any, Union
+from typing import Any, Optional, Union
 
 import boto3
 
@@ -21,7 +21,7 @@ class SageMakerTTSTool(BuiltinTool):
     s3_client: Any = None
     comprehend_client: Any = None
 
-    def _detect_lang_code(self, content: str, map_dict: dict = None):
+    def _detect_lang_code(self, content: str, map_dict: Optional[dict] = None):
         map_dict = {"zh": "<|zh|>", "en": "<|en|>", "ja": "<|jp|>", "zh-TW": "<|yue|>", "ko": "<|ko|>"}
 
         response = self.comprehend_client.detect_dominant_language(Text=content)

api/core/tools/provider/builtin/discord/_assets/icon.svg

@@ -0,0 +1,7 @@
+<!DOCTYPE svg PUBLIC "-//W3C//DTD SVG 1.1//EN" "http://www.w3.org/Graphics/SVG/1.1/DTD/svg11.dtd">
+
<!-- Uploaded to: SVG Repo, www.svgrepo.com, Transformed by: SVG Repo Mixer Tools -->
+<svg width="80px" height="80px" viewBox="0 -28.5 256 256" version="1.1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" preserveAspectRatio="xMidYMid" fill="#000000">
+
<g id="SVGRepo_bgCarrier" stroke-width="0"/>
+
<g id="SVGRepo_tracerCarrier" stroke-linecap="round" stroke-linejoin="round"/>
+
<g id="SVGRepo_iconCarrier"> <g> <path d="M216.856339,16.5966031 C200.285002,8.84328665 182.566144,3.2084988 164.041564,0 C161.766523,4.11318106 159.108624,9.64549908 157.276099,14.0464379 C137.583995,11.0849896 118.072967,11.0849896 98.7430163,14.0464379 C96.9108417,9.64549908 94.1925838,4.11318106 91.8971895,0 C73.3526068,3.2084988 55.6133949,8.86399117 39.0420583,16.6376612 C5.61752293,67.146514 -3.4433191,116.400813 1.08711069,164.955721 C23.2560196,181.510915 44.7403634,191.567697 65.8621325,198.148576 C71.0772151,190.971126 75.7283628,183.341335 79.7352139,175.300261 C72.104019,172.400575 64.7949724,168.822202 57.8887866,164.667963 C59.7209612,163.310589 61.5131304,161.891452 63.2445898,160.431257 C105.36741,180.133187 151.134928,180.133187 192.754523,160.431257 C194.506336,161.891452 196.298154,163.310589 198.110326,164.667963 C191.183787,168.842556 183.854737,172.420929 176.223542,175.320965 C180.230393,183.341335 184.861538,190.991831 190.096624,198.16893 C211.238746,191.588051 232.743023,181.531619 254.911949,164.955721 C260.227747,108.668201 245.831087,59.8662432 216.856339,16.5966031 Z M85.4738752,135.09489 C72.8290281,135.09489 62.4592217,123.290155 62.4592217,108.914901 C62.4592217,94.5396472 72.607595,82.7145587 85.4738752,82.7145587 C98.3405064,82.7145587 108.709962,94.5189427 108.488529,108.914901 C108.508531,123.290155 98.3405064,135.09489 85.4738752,135.09489 Z M170.525237,135.09489 C157.88039,135.09489 147.510584,123.290155 147.510584,108.914901 C147.510584,94.5396472 157.658606,82.7145587 170.525237,82.7145587 C183.391518,82.7145587 193.761324,94.5189427 193.539891,108.914901 C193.539891,123.290155 183.391518,135.09489 170.525237,135.09489 Z" fill="#5865F2" fill-rule="nonzero"> </path> </g> </g>
+
</svg>

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

@@ -0,0 +1,9 @@
+from typing import Any
+
+from core.tools.provider.builtin.discord.tools.discord_webhook import DiscordWebhookTool
+from core.tools.provider.builtin_tool_provider import BuiltinToolProviderController
+
+
+class DiscordProvider(BuiltinToolProviderController):
+    def _validate_credentials(self, credentials: dict[str, Any]) -> None:
+        DiscordWebhookTool()

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

@@ -0,0 +1,16 @@
+identity:
+  author: Ice Yao
+  name: discord
+  label:
+    en_US: Discord
+    zh_Hans: Discord
+    pt_BR: Discord
+  description:
+    en_US: Discord Webhook
+    zh_Hans: Discord Webhook
+    pt_BR: Discord Webhook
+  icon: icon.svg
+  tags:
+    - social
+    - productivity
+credentials_for_provider:

api/core/tools/provider/builtin/discord/tools/discord_webhook.py

@@ -0,0 +1,49 @@
+from typing import Any, Union
+
+import httpx
+
+from core.tools.entities.tool_entities import ToolInvokeMessage
+from core.tools.tool.builtin_tool import BuiltinTool
+
+
+class DiscordWebhookTool(BuiltinTool):
+    def _invoke(
+        self, user_id: str, tool_parameters: dict[str, Any]
+    ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]:
+        """
+        Incoming Webhooks
+        API Document:
+            https://discord.com/developers/docs/resources/webhook#execute-webhook
+        """
+
+        content = tool_parameters.get("content", "")
+        if not content:
+            return self.create_text_message("Invalid parameter content")
+
+        webhook_url = tool_parameters.get("webhook_url", "")
+
+        if not webhook_url.startswith("https://discord.com/api/webhooks/"):
+            return self.create_text_message(
+                f"Invalid parameter webhook_url ${webhook_url}, \
+                    not a valid Discord webhook URL"
+            )
+
+        headers = {
+            "Content-Type": "application/json",
+        }
+        params = {}
+        payload = {
+            "content": content,
+        }
+
+        try:
+            res = httpx.post(webhook_url, headers=headers, params=params, json=payload)
+            if res.is_success:
+                return self.create_text_message("Text message was sent successfully")
+            else:
+                return self.create_text_message(
+                    f"Failed to send the text message, \
+                        status code: {res.status_code}, response: {res.text}"
+                )
+        except Exception as e:
+            return self.create_text_message("Failed to send message through webhook. {}".format(e))

api/core/tools/provider/builtin/discord/tools/discord_webhook.yaml

@@ -0,0 +1,40 @@
+identity:
+  name: discord_webhook
+  author: Ice Yao
+  label:
+    en_US: Incoming Webhook to send message
+    zh_Hans: 通过入站Webhook发送消息
+    pt_BR: Incoming Webhook to send message
+  icon: icon.svg
+description:
+  human:
+    en_US: Sending a message on Discord via the Incoming Webhook
+    zh_Hans: 通过入站Webhook在Discord上发送消息
+    pt_BR: Sending a message on Discord via the Incoming Webhook
+  llm: A tool for sending messages to a chat on Discord.
+parameters:
+  - name: webhook_url
+    type: string
+    required: true
+    label:
+      en_US: Discord Incoming Webhook url
+      zh_Hans: Discord入站Webhook的url
+      pt_BR: Discord Incoming Webhook url
+    human_description:
+      en_US: Discord Incoming Webhook url
+      zh_Hans: Discord入站Webhook的url
+      pt_BR: Discord Incoming Webhook url
+    form: form
+  - name: content
+    type: string
+    required: true
+    label:
+      en_US: content
+      zh_Hans: 消息内容
+      pt_BR: content
+    human_description:
+      en_US: Content to sent to the channel or person.
+      zh_Hans: 消息内容文本
+      pt_BR: Content to sent to the channel or person.
+    llm_description: Content of the message
+    form: llm

api/core/tools/provider/builtin/stepfun/tools/image.py

@@ -32,16 +32,17 @@ class StepfunTool(BuiltinTool):
         prompt = tool_parameters.get("prompt", "")
         if not prompt:
             return self.create_text_message("Please input prompt")
-
+        if len(prompt) > 1024:
+            return self.create_text_message("The prompt length should less than 1024")
         seed = tool_parameters.get("seed", 0)
         if seed > 0:
             extra_body["seed"] = seed
-        steps = tool_parameters.get("steps", 0)
+        steps = tool_parameters.get("steps", 50)
         if steps > 0:
             extra_body["steps"] = steps
-        negative_prompt = tool_parameters.get("negative_prompt", "")
+        cfg_scale = tool_parameters.get("cfg_scale", 7.5)
-        if negative_prompt:
+        if cfg_scale > 0:
-            extra_body["negative_prompt"] = negative_prompt
+            extra_body["cfg_scale"] = cfg_scale
 
         # call openapi stepfun model
         response = client.images.generate(
@@ -51,7 +52,6 @@ class StepfunTool(BuiltinTool):
             n=tool_parameters.get("n", 1),
             extra_body=extra_body,
         )
-        print(response)
 
         result = []
         for image in response.data:

api/core/tools/provider/builtin/stepfun/tools/image.yaml

@@ -33,9 +33,9 @@ parameters:
     type: select
     required: false
     human_description:
-      en_US: used for selecting the image size
+      en_US: The size of the generated image
-      zh_Hans: 用于选择图像大小
+      zh_Hans: 生成的图片大小
-      pt_BR: used for selecting the image size
+      pt_BR: The size of the generated image
     label:
       en_US: Image size
       zh_Hans: 图像大小
@@ -77,17 +77,17 @@ parameters:
     type: number
     required: true
     human_description:
-      en_US: used for selecting the number of images
+      en_US: Number of generated images, now only one image can be generated at a time
-      zh_Hans: 用于选择图像数量
+      zh_Hans: 生成的图像数量，当前仅支持每次生成一张图片
-      pt_BR: used for selecting the number of images
+      pt_BR: Number of generated images, now only one image can be generated at a time
     label:
-      en_US: Number of images
+      en_US: Number of generated images
-      zh_Hans: 图像数量
+      zh_Hans: 生成的图像数量
-      pt_BR: Number of images
+      pt_BR: Number of generated images
     form: form
     default: 1
     min: 1
-    max: 10
+    max: 1
   - name: seed
     type: number
     required: false
@@ -109,21 +109,25 @@ parameters:
       zh_Hans: Steps
       pt_BR: Steps
     human_description:
-      en_US: Steps
+      en_US: Steps, now support integers between 1 and 100
-      zh_Hans: Steps
+      zh_Hans: Steps, 当前支持 1～100 之间整数
-      pt_BR: Steps
+      pt_BR: Steps, now support integers between 1 and 100
     form: form
-    default: 10
+    default: 50
-  - name: negative_prompt
+    min: 1
-    type: string
+    max: 100
+  - name: cfg_scale
+    type: number
     required: false
     label:
-      en_US: Negative prompt
+      en_US: classifier-free guidance scale
-      zh_Hans: Negative prompt
+      zh_Hans: classifier-free guidance scale
-      pt_BR: Negative prompt
+      pt_BR: classifier-free guidance scale
     human_description:
-      en_US: Negative prompt
+      en_US: classifier-free guidance scale
-      zh_Hans: Negative prompt
+      zh_Hans: classifier-free guidance scale
-      pt_BR: Negative prompt
+      pt_BR: classifier-free guidance scale
     form: form
-    default: (worst quality:1.3), (nsfw), low quality
+    default: 7.5
+    min: 1
+    max: 10

api/core/tools/provider/builtin/time/tools/localtime_to_timestamp.py

@@ -0,0 +1,44 @@
+from datetime import datetime
+from typing import Any, Union
+
+import pytz
+
+from core.tools.entities.tool_entities import ToolInvokeMessage
+from core.tools.errors import ToolInvokeError
+from core.tools.tool.builtin_tool import BuiltinTool
+
+
+class LocaltimeToTimestampTool(BuiltinTool):
+    def _invoke(
+        self,
+        user_id: str,
+        tool_parameters: dict[str, Any],
+    ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]:
+        """
+        Convert localtime to timestamp
+        """
+        localtime = tool_parameters.get("localtime")
+        timezone = tool_parameters.get("timezone", "Asia/Shanghai")
+        if not timezone:
+            timezone = None
+        time_format = "%Y-%m-%d %H:%M:%S"
+
+        timestamp = self.localtime_to_timestamp(localtime, time_format, timezone)
+        if not timestamp:
+            return self.create_text_message(f"Invalid localtime: {localtime}")
+
+        return self.create_text_message(f"{timestamp}")
+
+    @staticmethod
+    def localtime_to_timestamp(localtime: str, time_format: str, local_tz=None) -> int | None:
+        try:
+            if local_tz is None:
+                local_tz = datetime.now().astimezone().tzinfo
+            if isinstance(local_tz, str):
+                local_tz = pytz.timezone(local_tz)
+            local_time = datetime.strptime(localtime, time_format)
+            localtime = local_tz.localize(local_time)
+            timestamp = int(localtime.timestamp())
+            return timestamp
+        except Exception as e:
+            raise ToolInvokeError(str(e))

api/core/tools/provider/builtin/time/tools/localtime_to_timestamp.yaml

@@ -0,0 +1,33 @@
+identity:
+  name: localtime_to_timestamp
+  author: zhuhao
+  label:
+    en_US: localtime to timestamp
+    zh_Hans: 获取时间戳
+description:
+  human:
+    en_US: A tool for localtime convert to timestamp
+    zh_Hans: 获取时间戳
+  llm: A tool for localtime convert to timestamp
+parameters:
+  - name: localtime
+    type: string
+    required: true
+    form: llm
+    label:
+      en_US: localtime
+      zh_Hans: 本地时间
+    human_description:
+      en_US: localtime, such as 2024-1-1 0:0:0
+      zh_Hans: 本地时间, 比如2024-1-1 0:0:0
+  - name: timezone
+    type: string
+    required: false
+    form: llm
+    label:
+      en_US: Timezone
+      zh_Hans: 时区
+    human_description:
+      en_US: Timezone, such as Asia/Shanghai
+      zh_Hans: 时区, 比如Asia/Shanghai
+    default: Asia/Shanghai

api/core/tools/provider/builtin/time/tools/timestamp_to_localtime.py

@@ -0,0 +1,44 @@
+from datetime import datetime
+from typing import Any, Union
+
+import pytz
+
+from core.tools.entities.tool_entities import ToolInvokeMessage
+from core.tools.errors import ToolInvokeError
+from core.tools.tool.builtin_tool import BuiltinTool
+
+
+class TimestampToLocaltimeTool(BuiltinTool):
+    def _invoke(
+        self,
+        user_id: str,
+        tool_parameters: dict[str, Any],
+    ) -> Union[ToolInvokeMessage, list[ToolInvokeMessage]]:
+        """
+        Convert timestamp to localtime
+        """
+        timestamp = tool_parameters.get("timestamp")
+        timezone = tool_parameters.get("timezone", "Asia/Shanghai")
+        if not timezone:
+            timezone = None
+        time_format = "%Y-%m-%d %H:%M:%S"
+
+        locatime = self.timestamp_to_localtime(timestamp, timezone)
+        if not locatime:
+            return self.create_text_message(f"Invalid timestamp: {timestamp}")
+
+        localtime_format = locatime.strftime(time_format)
+
+        return self.create_text_message(f"{localtime_format}")
+
+    @staticmethod
+    def timestamp_to_localtime(timestamp: int, local_tz=None) -> datetime | None:
+        try:
+            if local_tz is None:
+                local_tz = datetime.now().astimezone().tzinfo
+            if isinstance(local_tz, str):
+                local_tz = pytz.timezone(local_tz)
+            local_time = datetime.fromtimestamp(timestamp, local_tz)
+            return local_time
+        except Exception as e:
+            raise ToolInvokeError(str(e))

api/core/tools/provider/builtin/time/tools/timestamp_to_localtime.yaml

@@ -0,0 +1,33 @@
+identity:
+  name: timestamp_to_localtime
+  author: zhuhao
+  label:
+    en_US: Timestamp to localtime
+    zh_Hans: 时间戳转换
+description:
+  human:
+    en_US: A tool for timestamp convert to localtime
+    zh_Hans: 时间戳转换
+  llm: A tool for timestamp convert to localtime
+parameters:
+  - name: timestamp
+    type: number
+    required: true
+    form: llm
+    label:
+      en_US: Timestamp
+      zh_Hans: 时间戳
+    human_description:
+      en_US: Timestamp
+      zh_Hans: 时间戳
+  - name: timezone
+    type: string
+    required: false
+    form: llm
+    label:
+      en_US: Timezone
+      zh_Hans: 时区
+    human_description:
+      en_US: Timezone, such as Asia/Shanghai
+      zh_Hans: 时区, 比如Asia/Shanghai
+    default: Asia/Shanghai

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

@@ -8,6 +8,9 @@ identity:
     en_US: The fastest way to get actionable insights from your database just by asking questions.
     zh_Hans: 一个基于大模型和RAG的Text2SQL工具。
   icon: icon.png
+  tags:
+    - utilities
+    - productivity
 credentials_for_provider:
   api_key:
     type: secret-input

api/core/tools/provider/builtin/xinference/tools/stable_diffusion.py

@@ -104,14 +104,15 @@ class StableDiffusionTool(BuiltinTool):
         model = self.runtime.credentials.get("model", None)
         if not model:
             return self.create_text_message("Please input model")
-
+        api_key = self.runtime.credentials.get("api_key") or "abc"
+        headers = {"Authorization": f"Bearer {api_key}"}
         # set model
         try:
             url = str(URL(base_url) / "sdapi" / "v1" / "options")
             response = post(
                 url,
                 json={"sd_model_checkpoint": model},
-                headers={"Authorization": f"Bearer {self.runtime.credentials['api_key']}"},
+                headers=headers,
             )
             if response.status_code != 200:
                 raise ToolProviderCredentialValidationError("Failed to set model, please tell user to set model")
@@ -257,14 +258,15 @@ class StableDiffusionTool(BuiltinTool):
             draw_options["prompt"] = f"{lora},{prompt}"
         else:
             draw_options["prompt"] = prompt
-
+        api_key = self.runtime.credentials.get("api_key") or "abc"
+        headers = {"Authorization": f"Bearer {api_key}"}
         try:
             url = str(URL(base_url) / "sdapi" / "v1" / "img2img")
             response = post(
                 url,
                 json=draw_options,
                 timeout=120,
-                headers={"Authorization": f"Bearer {self.runtime.credentials['api_key']}"},
+                headers=headers,
             )
             if response.status_code != 200:
                 return self.create_text_message("Failed to generate image")
@@ -298,14 +300,15 @@ class StableDiffusionTool(BuiltinTool):
         else:
             draw_options["prompt"] = prompt
         draw_options["override_settings"]["sd_model_checkpoint"] = model
-
+        api_key = self.runtime.credentials.get("api_key") or "abc"
+        headers = {"Authorization": f"Bearer {api_key}"}
         try:
             url = str(URL(base_url) / "sdapi" / "v1" / "txt2img")
             response = post(
                 url,
                 json=draw_options,
                 timeout=120,
-                headers={"Authorization": f"Bearer {self.runtime.credentials['api_key']}"},
+                headers=headers,
             )
             if response.status_code != 200:
                 return self.create_text_message("Failed to generate image")

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

@@ -6,12 +6,18 @@ from core.tools.provider.builtin_tool_provider import BuiltinToolProviderControl
 
 class XinferenceProvider(BuiltinToolProviderController):
     def _validate_credentials(self, credentials: dict) -> None:
-        base_url = credentials.get("base_url")
+        base_url = credentials.get("base_url", "").removesuffix("/")
-        api_key = credentials.get("api_key")
+        api_key = credentials.get("api_key", "")
-        model = credentials.get("model")
+        if not api_key:
+            api_key = "abc"
+            credentials["api_key"] = api_key
+        model = credentials.get("model", "")
+        if not base_url or not model:
+            raise ToolProviderCredentialValidationError("Xinference base_url and model is required")
+        headers = {"Authorization": f"Bearer {api_key}"}
         res = requests.post(
             f"{base_url}/sdapi/v1/options",
-            headers={"Authorization": f"Bearer {api_key}"},
+            headers=headers,
             json={"sd_model_checkpoint": model},
         )
         if res.status_code != 200:

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

@@ -31,7 +31,7 @@ credentials_for_provider:
       zh_Hans: 请输入你的模型名称
   api_key:
     type: secret-input
-    required: true
+    required: false
     label:
       en_US: API Key
       zh_Hans: Xinference 服务器的 API Key

api/core/tools/tool/builtin_tool.py

@@ -1,3 +1,5 @@
+from typing import Optional
+
 from core.model_runtime.entities.llm_entities import LLMResult
 from core.model_runtime.entities.message_entities import PromptMessage, SystemPromptMessage, UserPromptMessage
 from core.tools.entities.tool_entities import ToolProviderType
@@ -124,7 +126,7 @@ class BuiltinTool(Tool):
 
         return result
 
-    def get_url(self, url: str, user_agent: str = None) -> str:
+    def get_url(self, url: str, user_agent: Optional[str] = None) -> str:
         """
         get url
         """

api/core/tools/tool/tool.py

@@ -318,7 +318,7 @@ class Tool(BaseModel, ABC):
         """
         return ToolInvokeMessage(type=ToolInvokeMessage.MessageType.TEXT, message=text, save_as=save_as)
 
-    def create_blob_message(self, blob: bytes, meta: dict = None, save_as: str = "") -> ToolInvokeMessage:
+    def create_blob_message(self, blob: bytes, meta: Optional[dict] = None, save_as: str = "") -> ToolInvokeMessage:
         """
         create a blob message
 

api/core/tools/tool/workflow_tool.py

@@ -68,7 +68,10 @@ class WorkflowTool(Tool):
 
         result = []
 
-        outputs = data.get("outputs", {})
+        outputs = data.get("outputs")
+        if outputs == None:
+            outputs = {}
+        else:
             outputs, files = self._extract_files(outputs)
             for file in files:
                 result.append(self.create_file_var_message(file))

api/core/tools/tool_manager.py

@@ -4,7 +4,7 @@ import mimetypes
 from collections.abc import Generator
 from os import listdir, path
 from threading import Lock
-from typing import Any, Union
+from typing import Any, Optional, Union
 
 from configs import dify_config
 from core.agent.entities import AgentToolEntity
@@ -72,7 +72,7 @@ class ToolManager:
 
     @classmethod
     def get_tool(
-        cls, provider_type: str, provider_id: str, tool_name: str, tenant_id: str = None
+        cls, provider_type: str, provider_id: str, tool_name: str, tenant_id: Optional[str] = None
     ) -> Union[BuiltinTool, ApiTool]:
         """
         get the tool

api/core/tools/utils/feishu_api_utils.py

@@ -1,3 +1,5 @@
+from typing import Optional
+
 import httpx
 
 from core.tools.errors import ToolProviderCredentialValidationError
@@ -32,7 +34,12 @@ class FeishuRequest:
         return res.get("tenant_access_token")
 
     def _send_request(
-        self, url: str, method: str = "post", require_token: bool = True, payload: dict = None, params: dict = None
+        self,
+        url: str,
+        method: str = "post",
+        require_token: bool = True,
+        payload: Optional[dict] = None,
+        params: Optional[dict] = None,
     ):
         headers = {
             "Content-Type": "application/json",

api/core/tools/utils/parser.py

@@ -3,6 +3,7 @@ import uuid
 from json import dumps as json_dumps
 from json import loads as json_loads
 from json.decoder import JSONDecodeError
+from typing import Optional
 
 from requests import get
 from yaml import YAMLError, safe_load
@@ -16,7 +17,7 @@ from core.tools.errors import ToolApiSchemaError, ToolNotSupportedError, ToolPro
 class ApiBasedToolSchemaParser:
     @staticmethod
     def parse_openapi_to_tool_bundle(
-        openapi: dict, extra_info: dict = None, warning: dict = None
+        openapi: dict, extra_info: Optional[dict], warning: Optional[dict]
     ) -> list[ApiToolBundle]:
         warning = warning if warning is not None else {}
         extra_info = extra_info if extra_info is not None else {}
@@ -174,7 +175,7 @@ class ApiBasedToolSchemaParser:
 
     @staticmethod
     def parse_openapi_yaml_to_tool_bundle(
-        yaml: str, extra_info: dict = None, warning: dict = None
+        yaml: str, extra_info: Optional[dict], warning: Optional[dict]
     ) -> list[ApiToolBundle]:
         """
         parse openapi yaml to tool bundle
@@ -191,7 +192,7 @@ class ApiBasedToolSchemaParser:
         return ApiBasedToolSchemaParser.parse_openapi_to_tool_bundle(openapi, extra_info=extra_info, warning=warning)
 
     @staticmethod
-    def parse_swagger_to_openapi(swagger: dict, extra_info: dict = None, warning: dict = None) -> dict:
+    def parse_swagger_to_openapi(swagger: dict, extra_info: Optional[dict], warning: Optional[dict]) -> dict:
         """
         parse swagger to openapi
 
@@ -253,7 +254,7 @@ class ApiBasedToolSchemaParser:
 
     @staticmethod
     def parse_openai_plugin_json_to_tool_bundle(
-        json: str, extra_info: dict = None, warning: dict = None
+        json: str, extra_info: Optional[dict], warning: Optional[dict]
     ) -> list[ApiToolBundle]:
         """
         parse openapi plugin yaml to tool bundle
@@ -287,7 +288,7 @@ class ApiBasedToolSchemaParser:
 
     @staticmethod
     def auto_parse_to_tool_bundle(
-        content: str, extra_info: dict = None, warning: dict = None
+        content: str, extra_info: Optional[dict], warning: Optional[dict]
     ) -> tuple[list[ApiToolBundle], str]:
         """
         auto parse to tool bundle

api/core/tools/utils/web_reader_tool.py

@@ -9,6 +9,7 @@ import tempfile
 import unicodedata
 from contextlib import contextmanager
 from pathlib import Path
+from typing import Optional
 from urllib.parse import unquote
 
 import chardet
@@ -36,7 +37,7 @@ def page_result(text: str, cursor: int, max_length: int) -> str:
     return text[cursor : cursor + max_length]
 
 
-def get_url(url: str, user_agent: str = None) -> str:
+def get_url(url: str, user_agent: Optional[str] = None) -> str:
     """Fetch URL and return the contents as a string."""
     headers = {
         "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko)"