Merge branch 'feat/add-inner-api' into deploy/dev

Author: zhangx1n

.github/actions/setup-poetry/action.yml

@@ -8,7 +8,7 @@ inputs:
   poetry-version:
     description: Poetry version to set up
     required: true
-    default: '1.8.4'
+    default: '2.0.1'
   poetry-lockfile:
     description: Path to the Poetry lockfile to restore cache from
     required: true

.github/workflows/api-tests.yml

@@ -42,25 +42,23 @@ jobs:
         run: poetry install -C api --with dev
 
       - name: Check dependencies in pyproject.toml
-        run: poetry run -C api bash dev/pytest/pytest_artifacts.sh
+        run: poetry run -P api bash dev/pytest/pytest_artifacts.sh
 
       - name: Run Unit tests
-        run: poetry run -C api bash dev/pytest/pytest_unit_tests.sh
+        run: poetry run -P api bash dev/pytest/pytest_unit_tests.sh
 
       - name: Run ModelRuntime
-        run: poetry run -C api bash dev/pytest/pytest_model_runtime.sh
+        run: poetry run -P api bash dev/pytest/pytest_model_runtime.sh
 
       - name: Run dify config tests
-        run: poetry run -C api python dev/pytest/pytest_config_tests.py
+        run: poetry run -P api python dev/pytest/pytest_config_tests.py
 
       - name: Run Tool
-        run: poetry run -C api bash dev/pytest/pytest_tools.sh
+        run: poetry run -P api bash dev/pytest/pytest_tools.sh
 
       - name: Run mypy
         run: |
-          pushd api
-          poetry run python -m mypy --install-types --non-interactive .
-          popd
+          poetry run -C api python -m mypy --install-types --non-interactive .
 
       - name: Set up dotenvs
         run: |
@@ -80,4 +78,4 @@ jobs:
             ssrf_proxy
 
       - name: Run Workflow
-        run: poetry run -C api bash dev/pytest/pytest_workflow.sh
+        run: poetry run -P api bash dev/pytest/pytest_workflow.sh

.github/workflows/style.yml

@@ -38,12 +38,12 @@ jobs:
         if: steps.changed-files.outputs.any_changed == 'true'
         run: |
           poetry run -C api ruff --version
-          poetry run -C api ruff check ./api
-          poetry run -C api ruff format --check ./api
+          poetry run -C api ruff check ./
+          poetry run -C api ruff format --check ./
 
       - name: Dotenv check
         if: steps.changed-files.outputs.any_changed == 'true'
-        run: poetry run -C api dotenv-linter ./api/.env.example ./web/.env.example
+        run: poetry run -P api dotenv-linter ./api/.env.example ./web/.env.example
 
       - name: Lint hints
         if: failure()

.github/workflows/vdb-tests.yml

@@ -70,4 +70,4 @@ jobs:
             tidb
 
       - name: Test Vector Stores
-        run: poetry run -C api bash dev/pytest/pytest_vdb.sh
+        run: poetry run -P api bash dev/pytest/pytest_vdb.sh

api/.ruff.toml

@@ -53,10 +53,12 @@ ignore = [
     "FURB152", # math-constant
     "UP007", # non-pep604-annotation
     "UP032", # f-string
+    "UP045", # non-pep604-annotation-optional
     "B005", # strip-with-multi-characters
     "B006", # mutable-argument-default
     "B007", # unused-loop-control-variable
     "B026", # star-arg-unpacking-after-keyword-arg
+    "B903", # class-as-data-structure
     "B904", # raise-without-from-inside-except
     "B905", # zip-without-explicit-strict
     "N806", # non-lowercase-variable-in-function

api/Dockerfile

@@ -4,7 +4,7 @@ FROM python:3.12-slim-bookworm AS base
 WORKDIR /app/api
 
 # Install Poetry
-ENV POETRY_VERSION=1.8.4
+ENV POETRY_VERSION=2.0.1
 
 # if you located in China, you can use aliyun mirror to speed up
 # RUN pip install --no-cache-dir poetry==${POETRY_VERSION} -i https://mirrors.aliyun.com/pypi/simple/

api/README.md

@@ -79,5 +79,5 @@
 2. Run the tests locally with mocked system environment variables in `tool.pytest_env` section in `pyproject.toml`
 
    ```bash
-   poetry run -C api bash dev/pytest/pytest_all_tests.sh
+   poetry run -P api bash dev/pytest/pytest_all_tests.sh
    ```

api/configs/feature/__init__.py

@@ -146,7 +146,7 @@ class EndpointConfig(BaseSettings):
     )
 
     CONSOLE_WEB_URL: str = Field(
-        description="Base URL for the console web interface," "used for frontend references and CORS configuration",
+        description="Base URL for the console web interface,used for frontend references and CORS configuration",
         default="",
     )
 

api/configs/feature/hosted_service/__init__.py

@@ -181,7 +181,7 @@ class HostedFetchAppTemplateConfig(BaseSettings):
     """
 
     HOSTED_FETCH_APP_TEMPLATES_MODE: str = Field(
-        description="Mode for fetching app templates: remote, db, or builtin" " default to remote,",
+        description="Mode for fetching app templates: remote, db, or builtin default to remote,",
         default="remote",
     )
 

api/configs/packaging/__init__.py

@@ -9,7 +9,7 @@ class PackagingInfo(BaseSettings):
 
     CURRENT_VERSION: str = Field(
         description="Dify version",
-        default="0.15.1",
+        default="0.15.2",
     )
 
     COMMIT_SHA: str = Field(

api/controllers/console/admin.py

@@ -56,7 +56,7 @@ def post(self):
 
         app = App.query.filter(App.id == args["app_id"]).first()
         if not app:
-            raise NotFound(f'App \'{args["app_id"]}\' is not found')
+            raise NotFound(f"App '{args['app_id']}' is not found")
 
         site = app.site
         if not site:

api/controllers/console/datasets/datasets.py

@@ -457,7 +457,7 @@ def post(self):
             )
         except LLMBadRequestError:
             raise ProviderNotInitializeError(
-                "No Embedding Model available. Please configure a valid provider " "in the Settings -> Model Provider."
+                "No Embedding Model available. Please configure a valid provider in the Settings -> Model Provider."
             )
         except ProviderTokenNotInitError as ex:
             raise ProviderNotInitializeError(ex.description)
@@ -619,8 +619,7 @@ def get(self):
         vector_type = dify_config.VECTOR_STORE
         match vector_type:
             case (
-                VectorType.MILVUS
-                | VectorType.RELYT
+                VectorType.RELYT
                 | VectorType.PGVECTOR
                 | VectorType.TIDB_VECTOR
                 | VectorType.CHROMA
@@ -645,6 +644,7 @@ def get(self):
                 | VectorType.TIDB_ON_QDRANT
                 | VectorType.LINDORM
                 | VectorType.COUCHBASE
+                | VectorType.MILVUS
             ):
                 return {
                     "retrieval_method": [

api/controllers/console/datasets/datasets_document.py

@@ -350,8 +350,7 @@ def post(self):
                 )
             except InvokeAuthorizationError:
                 raise ProviderNotInitializeError(
-                    "No Embedding Model available. Please configure a valid provider "
-                    "in the Settings -> Model Provider."
+                    "No Embedding Model available. Please configure a valid provider in the Settings -> Model Provider."
                 )
             except ProviderTokenNotInitError as ex:
                 raise ProviderNotInitializeError(ex.description)
@@ -526,8 +525,7 @@ def get(self, dataset_id, batch):
                 return response.model_dump(), 200
             except LLMBadRequestError:
                 raise ProviderNotInitializeError(
-                    "No Embedding Model available. Please configure a valid provider "
-                    "in the Settings -> Model Provider."
+                    "No Embedding Model available. Please configure a valid provider in the Settings -> Model Provider."
                 )
             except ProviderTokenNotInitError as ex:
                 raise ProviderNotInitializeError(ex.description)

api/controllers/console/datasets/datasets_segments.py

@@ -168,8 +168,7 @@ def patch(self, dataset_id, document_id, action):
                 )
             except LLMBadRequestError:
                 raise ProviderNotInitializeError(
-                    "No Embedding Model available. Please configure a valid provider "
-                    "in the Settings -> Model Provider."
+                    "No Embedding Model available. Please configure a valid provider in the Settings -> Model Provider."
                 )
             except ProviderTokenNotInitError as ex:
                 raise ProviderNotInitializeError(ex.description)
@@ -217,8 +216,7 @@ def post(self, dataset_id, document_id):
                 )
             except LLMBadRequestError:
                 raise ProviderNotInitializeError(
-                    "No Embedding Model available. Please configure a valid provider "
-                    "in the Settings -> Model Provider."
+                    "No Embedding Model available. Please configure a valid provider in the Settings -> Model Provider."
                 )
             except ProviderTokenNotInitError as ex:
                 raise ProviderNotInitializeError(ex.description)
@@ -267,8 +265,7 @@ def patch(self, dataset_id, document_id, segment_id):
                 )
             except LLMBadRequestError:
                 raise ProviderNotInitializeError(
-                    "No Embedding Model available. Please configure a valid provider "
-                    "in the Settings -> Model Provider."
+                    "No Embedding Model available. Please configure a valid provider in the Settings -> Model Provider."
                 )
             except ProviderTokenNotInitError as ex:
                 raise ProviderNotInitializeError(ex.description)
@@ -437,8 +434,7 @@ def post(self, dataset_id, document_id, segment_id):
                 )
             except LLMBadRequestError:
                 raise ProviderNotInitializeError(
-                    "No Embedding Model available. Please configure a valid provider "
-                    "in the Settings -> Model Provider."
+                    "No Embedding Model available. Please configure a valid provider in the Settings -> Model Provider."
                 )
             except ProviderTokenNotInitError as ex:
                 raise ProviderNotInitializeError(ex.description)

api/controllers/inner_api/workspace/workspace.py

@@ -1,3 +1,5 @@
+import json
+
 from flask_restful import Resource, reqparse  # type: ignore
 
 from controllers.console.wraps import setup_required
@@ -29,4 +31,34 @@ def post(self):
         return {"message": "enterprise workspace created."}
 
 
+class EnterpriseWorkspaceNoOwnerEmail(Resource):
+    @setup_required
+    @inner_api_only
+    def post(self):
+        parser = reqparse.RequestParser()
+        parser.add_argument("name", type=str, required=True, location="json")
+        args = parser.parse_args()
+
+        tenant = TenantService.create_tenant(args["name"], is_from_dashboard=True)
+
+        tenant_was_created.send(tenant)
+
+        resp = {
+            "id": tenant.id,
+            "name": tenant.name,
+            "encrypt_public_key": tenant.encrypt_public_key,
+            "plan": tenant.plan,
+            "status": tenant.status,
+            "custom_config": json.loads(tenant.custom_config) if tenant.custom_config else {},
+            "created_at": tenant.created_at.isoformat() if tenant.created_at else None,
+            "updated_at": tenant.updated_at.isoformat() if tenant.updated_at else None,
+        }
+
+        return {
+            "message": "enterprise workspace created.",
+            "tenant": resp,
+        }
+
+
 api.add_resource(EnterpriseWorkspace, "/enterprise/workspace")
+api.add_resource(EnterpriseWorkspaceNoOwnerEmail, "/enterprise/workspace/ownerless")

api/controllers/service_api/dataset/segment.py

@@ -53,8 +53,7 @@ def post(self, tenant_id, dataset_id, document_id):
                 )
             except LLMBadRequestError:
                 raise ProviderNotInitializeError(
-                    "No Embedding Model available. Please configure a valid provider "
-                    "in the Settings -> Model Provider."
+                    "No Embedding Model available. Please configure a valid provider in the Settings -> Model Provider."
                 )
             except ProviderTokenNotInitError as ex:
                 raise ProviderNotInitializeError(ex.description)
@@ -95,8 +94,7 @@ def get(self, tenant_id, dataset_id, document_id):
                 )
             except LLMBadRequestError:
                 raise ProviderNotInitializeError(
-                    "No Embedding Model available. Please configure a valid provider "
-                    "in the Settings -> Model Provider."
+                    "No Embedding Model available. Please configure a valid provider in the Settings -> Model Provider."
                 )
             except ProviderTokenNotInitError as ex:
                 raise ProviderNotInitializeError(ex.description)
@@ -175,8 +173,7 @@ def post(self, tenant_id, dataset_id, document_id, segment_id):
                 )
             except LLMBadRequestError:
                 raise ProviderNotInitializeError(
-                    "No Embedding Model available. Please configure a valid provider "
-                    "in the Settings -> Model Provider."
+                    "No Embedding Model available. Please configure a valid provider in the Settings -> Model Provider."
                 )
             except ProviderTokenNotInitError as ex:
                 raise ProviderNotInitializeError(ex.description)

api/controllers/service_api/wraps.py

@@ -195,7 +195,11 @@ def validate_and_get_api_token(scope: str | None = None):
     with Session(db.engine, expire_on_commit=False) as session:
         update_stmt = (
             update(ApiToken)
-            .where(ApiToken.token == auth_token, ApiToken.last_used_at < cutoff_time, ApiToken.type == scope)
+            .where(
+                ApiToken.token == auth_token,
+                (ApiToken.last_used_at.is_(None) | (ApiToken.last_used_at < cutoff_time)),
+                ApiToken.type == scope,
+            )
             .values(last_used_at=current_time)
             .returning(ApiToken)
         )

api/core/agent/cot_agent_runner.py

@@ -172,7 +172,7 @@ def increase_usage(final_llm_usage_dict: dict[str, Optional[LLMUsage]], usage: L
 
             self.save_agent_thought(
                 agent_thought=agent_thought,
-                tool_name=scratchpad.action.action_name if scratchpad.action else "",
+                tool_name=(scratchpad.action.action_name if scratchpad.action and not scratchpad.is_final() else ""),
                 tool_input={scratchpad.action.action_name: scratchpad.action.action_input} if scratchpad.action else {},
                 tool_invoke_meta={},
                 thought=scratchpad.thought or "",

api/core/app/apps/base_app_queue_manager.py

@@ -167,8 +167,7 @@ def _check_for_sqlalchemy_models(self, data: Any):
         else:
             if isinstance(data, DeclarativeMeta) or hasattr(data, "_sa_instance_state"):
                 raise TypeError(
-                    "Critical Error: Passing SQLAlchemy Model instances "
-                    "that cause thread safety issues is not allowed."
+                    "Critical Error: Passing SQLAlchemy Model instances that cause thread safety issues is not allowed."
                 )
 
 

api/core/app/apps/message_based_app_generator.py

@@ -89,6 +89,7 @@ def _get_conversation_by_user(
             Conversation.id == conversation_id,
             Conversation.app_id == app_model.id,
             Conversation.status == "normal",
+            Conversation.is_deleted.is_(False),
         ]
 
         if isinstance(user, Account):

api/core/app/task_pipeline/message_cycle_manage.py

@@ -145,7 +145,7 @@ def _message_file_to_stream_response(self, event: QueueMessageFileEvent) -> Opti
 
             # get extension
             if "." in message_file.url:
-                extension = f'.{message_file.url.split(".")[-1]}'
+                extension = f".{message_file.url.split('.')[-1]}"
                 if len(extension) > 10:
                     extension = ".bin"
             else:

api/core/external_data_tool/api/api.py

@@ -62,8 +62,9 @@ def query(self, inputs: dict, query: Optional[str] = None) -> str:
 
         if not api_based_extension:
             raise ValueError(
-                "[External data tool] API query failed, variable: {}, "
-                "error: api_based_extension_id is invalid".format(self.variable)
+                "[External data tool] API query failed, variable: {}, error: api_based_extension_id is invalid".format(
+                    self.variable
+                )
             )
 
         # decrypt api_key

api/core/file/models.py

@@ -90,7 +90,7 @@ def to_dict(self) -> Mapping[str, str | int | None]:
     def markdown(self) -> str:
         url = self.generate_url()
         if self.type == FileType.IMAGE:
-            text = f'![{self.filename or ""}]({url})'
+            text = f"![{self.filename or ''}]({url})"
         else:
             text = f"[{self.filename or url}]({url})"
 

api/core/llm_generator/prompts.py

@@ -131,7 +131,7 @@
 SUGGESTED_QUESTIONS_AFTER_ANSWER_INSTRUCTION_PROMPT = (
     "Please help me predict the three most likely questions that human would ask, "
     "and keeping each question under 20 characters.\n"
-    "MAKE SURE your output is the SAME language as the Assistant's latest response"
+    "MAKE SURE your output is the SAME language as the Assistant's latest response. "
     "The output must be an array in JSON format following the specified schema:\n"
     '["question1","question2","question3"]\n'
 )

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

@@ -108,7 +108,7 @@ def validate_credentials(self, model: str, credentials: dict) -> None:
         ai_model_entity = self._get_ai_model_entity(base_model_name=base_model_name, model=model)
 
         if not ai_model_entity:
-            raise CredentialsValidateFailedError(f'Base Model Name {credentials["base_model_name"]} is invalid')
+            raise CredentialsValidateFailedError(f"Base Model Name {credentials['base_model_name']} is invalid")
 
         try:
             client = AzureOpenAI(**self._to_credential_kwargs(credentials))

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

@@ -130,7 +130,7 @@ def validate_credentials(self, model: str, credentials: dict) -> None:
             raise CredentialsValidateFailedError("Base Model Name is required")
 
         if not self._get_ai_model_entity(credentials["base_model_name"], model):
-            raise CredentialsValidateFailedError(f'Base Model Name {credentials["base_model_name"]} is invalid')
+            raise CredentialsValidateFailedError(f"Base Model Name {credentials['base_model_name']} is invalid")
 
         try:
             credentials_kwargs = self._to_credential_kwargs(credentials)