Merge branch 'fix/rerank-validation-in-run' into deploy/dev

.github/workflows/api-tests.yml

@@ -27,18 +27,17 @@ jobs:
       - name: Checkout code
         uses: actions/checkout@v4
 
-      - name: Install Poetry
-        uses: abatilo/actions-poetry@v3
-
       - name: Set up Python ${{ matrix.python-version }}
         uses: actions/setup-python@v5
         with:
           python-version: ${{ matrix.python-version }}
-          cache: 'poetry'
           cache-dependency-path: |
             api/pyproject.toml
             api/poetry.lock
 
+      - name: Install Poetry
+        uses: abatilo/actions-poetry@v3
+
       - name: Check Poetry lockfile
         run: |
           poetry check -C api --lock

.github/workflows/style.yml

@@ -24,15 +24,15 @@ jobs:
         with:
           files: api/**
 
-      - name: Install Poetry
-        uses: abatilo/actions-poetry@v3
-
       - name: Set up Python
         uses: actions/setup-python@v5
         if: steps.changed-files.outputs.any_changed == 'true'
         with:
           python-version: '3.10'
 
+      - name: Install Poetry
+        uses: abatilo/actions-poetry@v3
+
       - name: Python dependencies
         if: steps.changed-files.outputs.any_changed == 'true'
         run: poetry install -C api --only lint

api/README.md

@@ -85,3 +85,4 @@
    cd ../
    poetry run -C api bash dev/pytest/pytest_all_tests.sh
    ```
+

api/configs/middleware/vdb/oracle_config.py

@@ -14,7 +14,7 @@ class OracleConfig(BaseSettings):
         default=None,
     )
 
-    ORACLE_PORT: Optional[PositiveInt] = Field(
+    ORACLE_PORT: PositiveInt = Field(
         description="Port number on which the Oracle database server is listening (default is 1521)",
         default=1521,
     )

api/configs/middleware/vdb/pgvector_config.py

@@ -14,7 +14,7 @@ class PGVectorConfig(BaseSettings):
         default=None,
     )
 
-    PGVECTOR_PORT: Optional[PositiveInt] = Field(
+    PGVECTOR_PORT: PositiveInt = Field(
         description="Port number on which the PostgreSQL server is listening (default is 5433)",
         default=5433,
     )

api/configs/middleware/vdb/pgvectors_config.py

@@ -14,7 +14,7 @@ class PGVectoRSConfig(BaseSettings):
         default=None,
     )
 
-    PGVECTO_RS_PORT: Optional[PositiveInt] = Field(
+    PGVECTO_RS_PORT: PositiveInt = Field(
         description="Port number on which the PostgreSQL server with PGVecto.RS is listening (default is 5431)",
         default=5431,
     )

api/configs/middleware/vdb/vikingdb_config.py

@@ -11,27 +11,39 @@ class VikingDBConfig(BaseModel):
     """
 
     VIKINGDB_ACCESS_KEY: Optional[str] = Field(
-        default=None, description="The Access Key provided by Volcengine VikingDB for API authentication."
+        description="The Access Key provided by Volcengine VikingDB for API authentication."
+        "Refer to the following documentation for details on obtaining credentials:"
+        "https://www.volcengine.com/docs/6291/65568",
+        default=None,
     )
+
     VIKINGDB_SECRET_KEY: Optional[str] = Field(
-        default=None, description="The Secret Key provided by Volcengine VikingDB for API authentication."
+        description="The Secret Key provided by Volcengine VikingDB for API authentication.",
+        default=None,
     )
-    VIKINGDB_REGION: Optional[str] = Field(
-        default="cn-shanghai",
+
+    VIKINGDB_REGION: str = Field(
         description="The region of the Volcengine VikingDB service.(e.g., 'cn-shanghai', 'cn-beijing').",
+        default="cn-shanghai",
     )
-    VIKINGDB_HOST: Optional[str] = Field(
-        default="api-vikingdb.mlp.cn-shanghai.volces.com",
+
+    VIKINGDB_HOST: str = Field(
         description="The host of the Volcengine VikingDB service.(e.g., 'api-vikingdb.volces.com', \
             'api-vikingdb.mlp.cn-shanghai.volces.com')",
+        default="api-vikingdb.mlp.cn-shanghai.volces.com",
     )
-    VIKINGDB_SCHEME: Optional[str] = Field(
-        default="http",
+
+    VIKINGDB_SCHEME: str = Field(
         description="The scheme of the Volcengine VikingDB service.(e.g., 'http', 'https').",
+        default="http",
     )
-    VIKINGDB_CONNECTION_TIMEOUT: Optional[int] = Field(
-        default=30, description="The connection timeout of the Volcengine VikingDB service."
+
+    VIKINGDB_CONNECTION_TIMEOUT: int = Field(
+        description="The connection timeout of the Volcengine VikingDB service.",
+        default=30,
     )
-    VIKINGDB_SOCKET_TIMEOUT: Optional[int] = Field(
-        default=30, description="The socket timeout of the Volcengine VikingDB service."
+
+    VIKINGDB_SOCKET_TIMEOUT: int = Field(
+        description="The socket timeout of the Volcengine VikingDB service.",
+        default=30,
     )

api/controllers/console/datasets/hit_testing.py

@@ -1,88 +1,24 @@
-import logging
+from flask_restful import Resource
 
-from flask_login import current_user
-from flask_restful import Resource, marshal, reqparse
-from werkzeug.exceptions import Forbidden, InternalServerError, NotFound
-
-import services
 from controllers.console import api
-from controllers.console.app.error import (
-    CompletionRequestError,
-    ProviderModelCurrentlyNotSupportError,
-    ProviderNotInitializeError,
-    ProviderQuotaExceededError,
-)
-from controllers.console.datasets.error import DatasetNotInitializedError
+from controllers.console.datasets.hit_testing_base import DatasetsHitTestingBase
 from controllers.console.setup import setup_required
 from controllers.console.wraps import account_initialization_required
-from core.errors.error import (
-    LLMBadRequestError,
-    ModelCurrentlyNotSupportError,
-    ProviderTokenNotInitError,
-    QuotaExceededError,
-)
-from core.model_runtime.errors.invoke import InvokeError
-from fields.hit_testing_fields import hit_testing_record_fields
 from libs.login import login_required
-from services.dataset_service import DatasetService
-from services.hit_testing_service import HitTestingService
 
 
-class HitTestingApi(Resource):
+class HitTestingApi(Resource, DatasetsHitTestingBase):
     @setup_required
     @login_required
     @account_initialization_required
     def post(self, dataset_id):
         dataset_id_str = str(dataset_id)
 
-        dataset = DatasetService.get_dataset(dataset_id_str)
-        if dataset is None:
-            raise NotFound("Dataset not found.")
+        dataset = self.get_and_validate_dataset(dataset_id_str)
+        args = self.parse_args()
+        self.hit_testing_args_check(args)
 
-        try:
-            DatasetService.check_dataset_permission(dataset, current_user)
-        except services.errors.account.NoPermissionError as e:
-            raise Forbidden(str(e))
-
-        parser = reqparse.RequestParser()
-        parser.add_argument("query", type=str, location="json")
-        parser.add_argument("retrieval_model", type=dict, required=False, location="json")
-        parser.add_argument("external_retrieval_model", type=dict, required=False, location="json")
-        args = parser.parse_args()
-
-        HitTestingService.hit_testing_args_check(args)
-
-        try:
-            response = HitTestingService.retrieve(
-                dataset=dataset,
-                query=args["query"],
-                account=current_user,
-                retrieval_model=args["retrieval_model"],
-                external_retrieval_model=args["external_retrieval_model"],
-                limit=10,
-            )
-
-            return {"query": response["query"], "records": marshal(response["records"], hit_testing_record_fields)}
-        except services.errors.index.IndexNotInitializedError:
-            raise DatasetNotInitializedError()
-        except ProviderTokenNotInitError as ex:
-            raise ProviderNotInitializeError(ex.description)
-        except QuotaExceededError:
-            raise ProviderQuotaExceededError()
-        except ModelCurrentlyNotSupportError:
-            raise ProviderModelCurrentlyNotSupportError()
-        except LLMBadRequestError:
-            raise ProviderNotInitializeError(
-                "No Embedding Model or Reranking Model available. Please configure a valid provider "
-                "in the Settings -> Model Provider."
-            )
-        except InvokeError as e:
-            raise CompletionRequestError(e.description)
-        except ValueError as e:
-            raise ValueError(str(e))
-        except Exception as e:
-            logging.exception("Hit testing failed.")
-            raise InternalServerError(str(e))
+        return self.perform_hit_testing(dataset, args)
 
 
 api.add_resource(HitTestingApi, "/datasets/<uuid:dataset_id>/hit-testing")

api/controllers/console/datasets/hit_testing_base.py

@@ -0,0 +1,85 @@
+import logging
+
+from flask_login import current_user
+from flask_restful import marshal, reqparse
+from werkzeug.exceptions import Forbidden, InternalServerError, NotFound
+
+import services.dataset_service
+from controllers.console.app.error import (
+    CompletionRequestError,
+    ProviderModelCurrentlyNotSupportError,
+    ProviderNotInitializeError,
+    ProviderQuotaExceededError,
+)
+from controllers.console.datasets.error import DatasetNotInitializedError
+from core.errors.error import (
+    LLMBadRequestError,
+    ModelCurrentlyNotSupportError,
+    ProviderTokenNotInitError,
+    QuotaExceededError,
+)
+from core.model_runtime.errors.invoke import InvokeError
+from fields.hit_testing_fields import hit_testing_record_fields
+from services.dataset_service import DatasetService
+from services.hit_testing_service import HitTestingService
+
+
+class DatasetsHitTestingBase:
+    @staticmethod
+    def get_and_validate_dataset(dataset_id: str):
+        dataset = DatasetService.get_dataset(dataset_id)
+        if dataset is None:
+            raise NotFound("Dataset not found.")
+
+        try:
+            DatasetService.check_dataset_permission(dataset, current_user)
+        except services.errors.account.NoPermissionError as e:
+            raise Forbidden(str(e))
+
+        return dataset
+
+    @staticmethod
+    def hit_testing_args_check(args):
+        HitTestingService.hit_testing_args_check(args)
+
+    @staticmethod
+    def parse_args():
+        parser = reqparse.RequestParser()
+
+        parser.add_argument("query", type=str, location="json")
+        parser.add_argument("retrieval_model", type=dict, required=False, location="json")
+        parser.add_argument("external_retrieval_model", type=dict, required=False, location="json")
+        return parser.parse_args()
+
+    @staticmethod
+    def perform_hit_testing(dataset, args):
+        try:
+            response = HitTestingService.retrieve(
+                dataset=dataset,
+                query=args["query"],
+                account=current_user,
+                retrieval_model=args["retrieval_model"],
+                external_retrieval_model=args["external_retrieval_model"],
+                limit=10,
+            )
+            return {"query": response["query"], "records": marshal(response["records"], hit_testing_record_fields)}
+        except services.errors.index.IndexNotInitializedError:
+            raise DatasetNotInitializedError()
+        except ProviderTokenNotInitError as ex:
+            raise ProviderNotInitializeError(ex.description)
+        except QuotaExceededError:
+            raise ProviderQuotaExceededError()
+        except ModelCurrentlyNotSupportError:
+            raise ProviderModelCurrentlyNotSupportError()
+        except LLMBadRequestError:
+            raise ProviderNotInitializeError(
+                "No Embedding Model or Reranking Model available. Please configure a valid provider "
+                "in the Settings -> Model Provider."
+            )
+        except InvokeError as e:
+            raise CompletionRequestError(e.description)
+        except ValueError as e:
+            raise ValueError(str(e))
+        except Exception as e:
+            logging.exception("Hit testing failed.")
+            raise InternalServerError(str(e))

api/controllers/service_api/__init__.py

@@ -5,7 +5,6 @@ from libs.external_api import ExternalApi
 bp = Blueprint("service_api", __name__, url_prefix="/v1")
 api = ExternalApi(bp)
 
-
 from . import index
 from .app import app, audio, completion, conversation, file, message, workflow
-from .dataset import dataset, document, segment
+from .dataset import dataset, document, hit_testing, segment

api/controllers/service_api/app/completion.py

@@ -4,7 +4,6 @@ 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,
@@ -108,7 +107,6 @@ class ChatApi(Resource):
         parser.add_argument("conversation_id", type=uuid_value, location="json")
         parser.add_argument("retriever_from", type=str, required=False, default="dev", location="json")
         parser.add_argument("auto_generate_name", type=bool, required=False, default=True, location="json")
-        parser.add_argument("parent_message_id", type=uuid_value, required=False, default=UUID_NIL, location="json")
 
         args = parser.parse_args()
 

api/controllers/service_api/dataset/hit_testing.py

@@ -0,0 +1,17 @@
+from controllers.console.datasets.hit_testing_base import DatasetsHitTestingBase
+from controllers.service_api import api
+from controllers.service_api.wraps import DatasetApiResource
+
+
+class HitTestingApi(DatasetApiResource, DatasetsHitTestingBase):
+    def post(self, tenant_id, dataset_id):
+        dataset_id_str = str(dataset_id)
+
+        dataset = self.get_and_validate_dataset(dataset_id_str)
+        args = self.parse_args()
+        self.hit_testing_args_check(args)
+
+        return self.perform_hit_testing(dataset, args)
+
+
+api.add_resource(HitTestingApi, "/datasets/<uuid:dataset_id>/hit-testing")

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

@@ -10,6 +10,7 @@ from flask import Flask, current_app
 from pydantic import ValidationError
 
 import contexts
+from constants import UUID_NIL
 from core.app.app_config.features.file_upload.manager import FileUploadConfigManager
 from core.app.apps.advanced_chat.app_config_manager import AdvancedChatAppConfigManager
 from core.app.apps.advanced_chat.app_runner import AdvancedChatAppRunner
@@ -132,7 +133,7 @@ class AdvancedChatAppGenerator(MessageBasedAppGenerator):
             else self._prepare_user_inputs(user_inputs=inputs, app_config=app_config, user_id=user.id, role=role),
             query=query,
             files=file_objs,
-            parent_message_id=args.get("parent_message_id"),
+            parent_message_id=args.get("parent_message_id") if invoke_from != InvokeFrom.SERVICE_API else UUID_NIL,
             user_id=user.id,
             stream=stream,
             invoke_from=invoke_from,

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

@@ -8,6 +8,7 @@ from typing import Any, Literal, Union, overload
 from flask import Flask, current_app
 from pydantic import ValidationError
 
+from constants import UUID_NIL
 from core.app.app_config.easy_ui_based_app.model_config.converter import ModelConfigConverter
 from core.app.app_config.features.file_upload.manager import FileUploadConfigManager
 from core.app.apps.agent_chat.app_config_manager import AgentChatAppConfigManager
@@ -140,7 +141,7 @@ class AgentChatAppGenerator(MessageBasedAppGenerator):
             else self._prepare_user_inputs(user_inputs=inputs, app_config=app_config, user_id=user.id, role=role),
             query=query,
             files=file_objs,
-            parent_message_id=args.get("parent_message_id"),
+            parent_message_id=args.get("parent_message_id") if invoke_from != InvokeFrom.SERVICE_API else UUID_NIL,
             user_id=user.id,
             stream=stream,
             invoke_from=invoke_from,

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

@@ -8,6 +8,7 @@ from typing import Any, Literal, Union, overload
 from flask import Flask, current_app
 from pydantic import ValidationError
 
+from constants import UUID_NIL
 from core.app.app_config.easy_ui_based_app.model_config.converter import ModelConfigConverter
 from core.app.app_config.features.file_upload.manager import FileUploadConfigManager
 from core.app.apps.base_app_queue_manager import AppQueueManager, GenerateTaskStoppedError, PublishFrom
@@ -138,7 +139,7 @@ class ChatAppGenerator(MessageBasedAppGenerator):
             else self._prepare_user_inputs(user_inputs=inputs, app_config=app_config, user_id=user.id, role=role),
             query=query,
             files=file_objs,
-            parent_message_id=args.get("parent_message_id"),
+            parent_message_id=args.get("parent_message_id") if invoke_from != InvokeFrom.SERVICE_API else UUID_NIL,
             user_id=user.id,
             invoke_from=invoke_from,
             extras=extras,

api/core/app/entities/app_invoke_entities.py

@@ -2,8 +2,9 @@ from collections.abc import Mapping, Sequence
 from enum import Enum
 from typing import Any, Optional
 
-from pydantic import BaseModel, ConfigDict
+from pydantic import BaseModel, ConfigDict, Field, ValidationInfo, field_validator
 
+from constants import UUID_NIL
 from core.app.app_config.entities import AppConfig, EasyUIBasedAppConfig, WorkflowUIBasedAppConfig
 from core.entities.provider_configuration import ProviderModelBundle
 from core.file.models import File
@@ -116,13 +117,36 @@ class EasyUIBasedAppGenerateEntity(AppGenerateEntity):
     model_config = ConfigDict(protected_namespaces=())
 
 
-class ChatAppGenerateEntity(EasyUIBasedAppGenerateEntity):
+class ConversationAppGenerateEntity(AppGenerateEntity):
+    """
+    Base entity for conversation-based app generation.
+    """
+
+    conversation_id: Optional[str] = None
+    parent_message_id: Optional[str] = Field(
+        default=None,
+        description=(
+            "Starting from v0.9.0, parent_message_id is used to support message regeneration for internal chat API."
+            "For service API, we need to ensure its forward compatibility, "
+            "so passing in the parent_message_id as request arg is not supported for now. "
+            "It needs to be set to UUID_NIL so that the subsequent processing will treat it as legacy messages."
+        ),
+    )
+
+    @field_validator("parent_message_id")
+    @classmethod
+    def validate_parent_message_id(cls, v, info: ValidationInfo):
+        if info.data.get("invoke_from") == InvokeFrom.SERVICE_API and v != UUID_NIL:
+            raise ValueError("parent_message_id should be UUID_NIL for service API")
+        return v
+
+
+class ChatAppGenerateEntity(ConversationAppGenerateEntity, EasyUIBasedAppGenerateEntity):
     """
     Chat Application Generate Entity.
     """
 
-    conversation_id: Optional[str] = None
-    parent_message_id: Optional[str] = None
+    pass
 
 
 class CompletionAppGenerateEntity(EasyUIBasedAppGenerateEntity):
@@ -133,16 +157,15 @@ class CompletionAppGenerateEntity(EasyUIBasedAppGenerateEntity):
     pass
 
 
-class AgentChatAppGenerateEntity(EasyUIBasedAppGenerateEntity):
+class AgentChatAppGenerateEntity(ConversationAppGenerateEntity, EasyUIBasedAppGenerateEntity):
     """
     Agent Chat Application Generate Entity.
     """
 
-    conversation_id: Optional[str] = None
-    parent_message_id: Optional[str] = None
+    pass
 
 
-class AdvancedChatAppGenerateEntity(AppGenerateEntity):
+class AdvancedChatAppGenerateEntity(ConversationAppGenerateEntity):
     """
     Advanced Chat Application Generate Entity.
     """
@@ -150,8 +173,6 @@ class AdvancedChatAppGenerateEntity(AppGenerateEntity):
     # app config
     app_config: WorkflowUIBasedAppConfig
 
-    conversation_id: Optional[str] = None
-    parent_message_id: Optional[str] = None
     workflow_run_id: Optional[str] = None
     query: str
 

api/core/model_runtime/model_providers/fireworks/fireworks.yaml

@@ -18,6 +18,7 @@ supported_model_types:
   - text-embedding
 configurate_methods:
   - predefined-model
+  - customizable-model
 provider_credential_schema:
   credential_form_schemas:
     - variable: fireworks_api_key
@@ -28,3 +29,75 @@ provider_credential_schema:
       placeholder:
         zh_Hans: 在此输入您的 API Key
         en_US: Enter your API Key
+model_credential_schema:
+  model:
+    label:
+      en_US: Model URL
+      zh_Hans: 模型URL
+    placeholder:
+      en_US: Enter your Model URL
+      zh_Hans: 输入模型URL
+  credential_form_schemas:
+    - variable: model_label_zh_Hanns
+      label:
+        zh_Hans: 模型中文名称
+        en_US: The zh_Hans of Model
+      required: true
+      type: text-input
+      placeholder:
+        zh_Hans: 在此输入您的模型中文名称
+        en_US: Enter your zh_Hans of Model
+    - variable: model_label_en_US
+      label:
+        zh_Hans: 模型英文名称
+        en_US: The en_US of Model
+      required: true
+      type: text-input
+      placeholder:
+        zh_Hans: 在此输入您的模型英文名称
+        en_US: Enter your en_US of Model
+    - variable: fireworks_api_key
+      label:
+        en_US: API Key
+      type: secret-input
+      required: true
+      placeholder:
+        zh_Hans: 在此输入您的 API Key
+        en_US: Enter your API Key
+    - variable: context_size
+      label:
+        zh_Hans: 模型上下文长度
+        en_US: Model context size
+      required: true
+      type: text-input
+      default: '4096'
+      placeholder:
+        zh_Hans: 在此输入您的模型上下文长度
+        en_US: Enter your Model context size
+    - variable: max_tokens
+      label:
+        zh_Hans: 最大 token 上限
+        en_US: Upper bound for max tokens
+      default: '4096'
+      type: text-input
+      show_on:
+        - variable: __model_type
+          value: llm
+    - variable: function_calling_type
+      label:
+        en_US: Function calling
+      type: select
+      required: false
+      default: no_call
+      options:
+        - value: no_call
+          label:
+            en_US: Not Support
+            zh_Hans: 不支持
+        - value: function_call
+          label:
+            en_US: Support
+            zh_Hans: 支持
+      show_on:
+        - variable: __model_type
+          value: llm

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

@@ -8,7 +8,8 @@ from openai.types.chat.chat_completion_chunk import ChoiceDeltaFunctionCall, Cho
 from openai.types.chat.chat_completion_message import FunctionCall
 
 from core.model_runtime.callbacks.base_callback import Callback
-from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta
+from core.model_runtime.entities.common_entities import I18nObject
+from core.model_runtime.entities.llm_entities import LLMMode, LLMResult, LLMResultChunk, LLMResultChunkDelta
 from core.model_runtime.entities.message_entities import (
     AssistantPromptMessage,
     ImagePromptMessageContent,
@@ -20,6 +21,15 @@ from core.model_runtime.entities.message_entities import (
     ToolPromptMessage,
     UserPromptMessage,
 )
+from core.model_runtime.entities.model_entities import (
+    AIModelEntity,
+    FetchFrom,
+    ModelFeature,
+    ModelPropertyKey,
+    ModelType,
+    ParameterRule,
+    ParameterType,
+)
 from core.model_runtime.errors.validate import CredentialsValidateFailedError
 from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel
 from core.model_runtime.model_providers.fireworks._common import _CommonFireworks
@@ -608,3 +618,50 @@ class FireworksLargeLanguageModel(_CommonFireworks, LargeLanguageModel):
                     num_tokens += self._get_num_tokens_by_gpt2(required_field)
 
         return num_tokens
+
+    def get_customizable_model_schema(self, model: str, credentials: dict) -> AIModelEntity:
+        return AIModelEntity(
+            model=model,
+            label=I18nObject(
+                en_US=credentials.get("model_label_en_US", model),
+                zh_Hans=credentials.get("model_label_zh_Hanns", model),
+            ),
+            model_type=ModelType.LLM,
+            features=[ModelFeature.TOOL_CALL, ModelFeature.MULTI_TOOL_CALL, ModelFeature.STREAM_TOOL_CALL]
+            if credentials.get("function_calling_type") == "function_call"
+            else [],
+            fetch_from=FetchFrom.CUSTOMIZABLE_MODEL,
+            model_properties={
+                ModelPropertyKey.CONTEXT_SIZE: int(credentials.get("context_size", 4096)),
+                ModelPropertyKey.MODE: LLMMode.CHAT.value,
+            },
+            parameter_rules=[
+                ParameterRule(
+                    name="temperature",
+                    use_template="temperature",
+                    label=I18nObject(en_US="Temperature", zh_Hans="温度"),
+                    type=ParameterType.FLOAT,
+                ),
+                ParameterRule(
+                    name="max_tokens",
+                    use_template="max_tokens",
+                    default=512,
+                    min=1,
+                    max=int(credentials.get("max_tokens", 4096)),
+                    label=I18nObject(en_US="Max Tokens", zh_Hans="最大标记"),
+                    type=ParameterType.INT,
+                ),
+                ParameterRule(
+                    name="top_p",
+                    use_template="top_p",
+                    label=I18nObject(en_US="Top P", zh_Hans="Top P"),
+                    type=ParameterType.FLOAT,
+                ),
+                ParameterRule(
+                    name="top_k",
+                    use_template="top_k",
+                    label=I18nObject(en_US="Top K", zh_Hans="Top K"),
+                    type=ParameterType.FLOAT,
+                ),
+            ],
+        )

api/core/model_runtime/model_providers/fireworks/llm/qwen2p5-72b-instruct.yaml

@@ -0,0 +1,46 @@
+model: accounts/fireworks/models/qwen2p5-72b-instruct
+label:
+  zh_Hans: Qwen2.5 72B Instruct
+  en_US: Qwen2.5 72B Instruct
+model_type: llm
+features:
+  - agent-thought
+  - tool-call
+model_properties:
+  mode: chat
+  context_size: 32768
+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: '0.9'
+  output: '0.9'
+  unit: '0.000001'
+  currency: USD

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

@@ -61,7 +61,8 @@ class MinimaxTextEmbeddingModel(TextEmbeddingModel):
         url = f"{self.api_base}?GroupId={group_id}"
         headers = {"Authorization": "Bearer " + api_key, "Content-Type": "application/json"}
 
-        data = {"model": "embo-01", "texts": texts, "type": "db"}
+        embedding_type = "db" if input_type == EmbeddingInputType.DOCUMENT else "query"
+        data = {"model": "embo-01", "texts": texts, "type": embedding_type}
 
         try:
             response = post(url, headers=headers, data=dumps(data))

api/core/rag/datasource/keyword/keyword_factory.py

@@ -1,8 +1,8 @@
 from typing import Any
 
 from configs import dify_config
-from core.rag.datasource.keyword.jieba.jieba import Jieba
 from core.rag.datasource.keyword.keyword_base import BaseKeyword
+from core.rag.datasource.keyword.keyword_type import KeyWordType
 from core.rag.models.document import Document
 from models.dataset import Dataset
 
@@ -13,15 +13,18 @@ class Keyword:
         self._keyword_processor = self._init_keyword()
 
     def _init_keyword(self) -> BaseKeyword:
-        config = dify_config
-        keyword_type = config.KEYWORD_STORE
+        keyword_type = dify_config.KEYWORD_STORE
+        keyword_factory = self.get_keyword_factory(keyword_type)
+        return keyword_factory(self._dataset)
 
-        if not keyword_type:
-            raise ValueError("Keyword store must be specified.")
+    @staticmethod
+    def get_keyword_factory(keyword_type: str) -> type[BaseKeyword]:
+        match keyword_type:
+            case KeyWordType.JIEBA:
+                from core.rag.datasource.keyword.jieba.jieba import Jieba
 
-        if keyword_type == "jieba":
-            return Jieba(dataset=self._dataset)
-        else:
+                return Jieba
+            case _:
                 raise ValueError(f"Keyword store {keyword_type} is not supported.")
 
     def create(self, texts: list[Document], **kwargs):

api/core/rag/datasource/keyword/keyword_type.py

@@ -0,0 +1,5 @@
+from enum import Enum
+
+
+class KeyWordType(str, Enum):
+    JIEBA = "jieba"

api/extensions/storage/aliyun_oss_storage.py

@@ -1,5 +1,4 @@
 from collections.abc import Generator
-from contextlib import closing
 
 import oss2 as aliyun_s3
 from flask import Flask
@@ -34,13 +33,13 @@ class AliyunOssStorage(BaseStorage):
         self.client.put_object(self.__wrapper_folder_filename(filename), data)
 
     def load_once(self, filename: str) -> bytes:
-        with closing(self.client.get_object(self.__wrapper_folder_filename(filename))) as obj:
+        obj = self.client.get_object(self.__wrapper_folder_filename(filename))
         data = obj.read()
         return data
 
     def load_stream(self, filename: str) -> Generator:
         def generate(filename: str = filename) -> Generator:
-            with closing(self.client.get_object(self.__wrapper_folder_filename(filename))) as obj:
+            obj = self.client.get_object(self.__wrapper_folder_filename(filename))
             while chunk := obj.read(4096):
                 yield chunk
 

api/extensions/storage/aws_s3_storage.py

@@ -1,6 +1,5 @@
 import logging
 from collections.abc import Generator
-from contextlib import closing
 
 import boto3
 from botocore.client import Config
@@ -55,8 +54,7 @@ class AwsS3Storage(BaseStorage):
 
     def load_once(self, filename: str) -> bytes:
         try:
-            with closing(self.client) as client:
-                data = client.get_object(Bucket=self.bucket_name, Key=filename)["Body"].read()
+            data = self.client.get_object(Bucket=self.bucket_name, Key=filename)["Body"].read()
         except ClientError as ex:
             if ex.response["Error"]["Code"] == "NoSuchKey":
                 raise FileNotFoundError("File not found")
@@ -67,8 +65,7 @@ class AwsS3Storage(BaseStorage):
     def load_stream(self, filename: str) -> Generator:
         def generate(filename: str = filename) -> Generator:
             try:
-                with closing(self.client) as client:
-                    response = client.get_object(Bucket=self.bucket_name, Key=filename)
+                response = self.client.get_object(Bucket=self.bucket_name, Key=filename)
                 yield from response["Body"].iter_chunks()
             except ClientError as ex:
                 if ex.response["Error"]["Code"] == "NoSuchKey":
@@ -79,13 +76,11 @@ class AwsS3Storage(BaseStorage):
         return generate()
 
     def download(self, filename, target_filepath):
-        with closing(self.client) as client:
-            client.download_file(self.bucket_name, filename, target_filepath)
+        self.client.download_file(self.bucket_name, filename, target_filepath)
 
     def exists(self, filename):
-        with closing(self.client) as client:
         try:
-                client.head_object(Bucket=self.bucket_name, Key=filename)
+            self.client.head_object(Bucket=self.bucket_name, Key=filename)
             return True
         except:
             return False

api/extensions/storage/google_cloud_storage.py

@@ -2,7 +2,6 @@ import base64
 import io
 import json
 from collections.abc import Generator
-from contextlib import closing
 
 from flask import Flask
 from google.cloud import storage as google_cloud_storage
@@ -43,7 +42,7 @@ class GoogleCloudStorage(BaseStorage):
         def generate(filename: str = filename) -> Generator:
             bucket = self.client.get_bucket(self.bucket_name)
             blob = bucket.get_blob(filename)
-            with closing(blob.open(mode="rb")) as blob_stream:
+            with blob.open(mode="rb") as blob_stream:
                 while chunk := blob_stream.read(4096):
                     yield chunk
 

api/extensions/storage/oracle_oci_storage.py

@@ -1,5 +1,4 @@
 from collections.abc import Generator
-from contextlib import closing
 
 import boto3
 from botocore.exceptions import ClientError
@@ -28,8 +27,7 @@ class OracleOCIStorage(BaseStorage):
 
     def load_once(self, filename: str) -> bytes:
         try:
-            with closing(self.client) as client:
-                data = client.get_object(Bucket=self.bucket_name, Key=filename)["Body"].read()
+            data = self.client.get_object(Bucket=self.bucket_name, Key=filename)["Body"].read()
         except ClientError as ex:
             if ex.response["Error"]["Code"] == "NoSuchKey":
                 raise FileNotFoundError("File not found")
@@ -40,8 +38,7 @@ class OracleOCIStorage(BaseStorage):
     def load_stream(self, filename: str) -> Generator:
         def generate(filename: str = filename) -> Generator:
             try:
-                with closing(self.client) as client:
-                    response = client.get_object(Bucket=self.bucket_name, Key=filename)
+                response = self.client.get_object(Bucket=self.bucket_name, Key=filename)
                 yield from response["Body"].iter_chunks()
             except ClientError as ex:
                 if ex.response["Error"]["Code"] == "NoSuchKey":
@@ -52,13 +49,11 @@ class OracleOCIStorage(BaseStorage):
         return generate()
 
     def download(self, filename, target_filepath):
-        with closing(self.client) as client:
-            client.download_file(self.bucket_name, filename, target_filepath)
+        self.client.download_file(self.bucket_name, filename, target_filepath)
 
     def exists(self, filename):
-        with closing(self.client) as client:
         try:
-                client.head_object(Bucket=self.bucket_name, Key=filename)
+            self.client.head_object(Bucket=self.bucket_name, Key=filename)
             return True
         except:
             return False

api/services/auth/api_key_auth_factory.py

@@ -1,15 +1,25 @@
-from services.auth.firecrawl import FirecrawlAuth
-from services.auth.jina import JinaAuth
+from services.auth.api_key_auth_base import ApiKeyAuthBase
+from services.auth.auth_type import AuthType
 
 
 class ApiKeyAuthFactory:
     def __init__(self, provider: str, credentials: dict):
-        if provider == "firecrawl":
-            self.auth = FirecrawlAuth(credentials)
-        elif provider == "jinareader":
-            self.auth = JinaAuth(credentials)
-        else:
-            raise ValueError("Invalid provider")
+        auth_factory = self.get_apikey_auth_factory(provider)
+        self.auth = auth_factory(credentials)
 
     def validate_credentials(self):
         return self.auth.validate_credentials()
+
+    @staticmethod
+    def get_apikey_auth_factory(provider: str) -> type[ApiKeyAuthBase]:
+        match provider:
+            case AuthType.FIRECRAWL:
+                from services.auth.firecrawl.firecrawl import FirecrawlAuth
+
+                return FirecrawlAuth
+            case AuthType.JINA:
+                from services.auth.jina.jina import JinaAuth
+
+                return JinaAuth
+            case _:
+                raise ValueError("Invalid provider")

api/services/auth/auth_type.py

@@ -0,0 +1,6 @@
+from enum import Enum
+
+
+class AuthType(str, Enum):
+    FIRECRAWL = "firecrawl"
+    JINA = "jinareader"

web/app/(commonLayout)/datasets/template/template.en.mdx

@@ -1050,6 +1050,151 @@ import { Row, Col, Properties, Property, Heading, SubProperty, Paragraph } from
 
 ---
 
+<Heading
+  url='/datasets/{dataset_id}/hit_testing'
+  method='POST'
+  title='Dataset hit testing'
+  name='#dataset_hit_testing'
+/>
+<Row>
+  <Col>
+    ### Path
+    <Properties>
+      <Property name='dataset_id' type='string' key='dataset_id'>
+        Dataset ID
+      </Property>
+    </Properties>
+
+    ### Request Body
+    <Properties>
+      <Property name='query' type='string' key='query'>
+        retrieval keywordc
+      </Property>
+      <Property name='retrieval_model' type='object' key='retrieval_model'>
+        retrieval keyword(Optional, if not filled, it will be recalled according to the default method)
+        - <code>search_method</code> (text) Search method: One of the following four keywords is required
+          - <code>keyword_search</code> Keyword search
+          - <code>semantic_search</code> Semantic search
+          - <code>full_text_search</code> Full-text search
+          - <code>hybrid_search</code> Hybrid search
+        - <code>reranking_enable</code> (bool) Whether to enable reranking, optional, required if the search mode is semantic_search or hybrid_search
+        - <code>reranking_mode</code> (object) Rerank model configuration, optional, required if reranking is enabled
+            - <code>reranking_provider_name</code> (string) Rerank model provider
+            - <code>reranking_model_name</code> (string) Rerank model name
+        - <code>weights</code> (double) Semantic search weight setting in hybrid search mode
+        - <code>top_k</code> (integer) Number of results to return, optional
+        - <code>score_threshold_enabled</code> (bool) Whether to enable score threshold
+        - <code>score_threshold</code> (double) Score threshold
+      </Property>
+      <Property name='external_retrieval_model' type='object' key='external_retrieval_model'>
+          Unused field
+      </Property>
+    </Properties>
+  </Col>
+  <Col sticky>
+    <CodeGroup
+      title="Request"
+      tag="POST"
+      label="/datasets/{dataset_id}/hit_testing"
+      targetCode={`curl --location --request GET '${props.apiBaseUrl}/datasets/{dataset_id}/hit_testing' \\\n--header 'Authorization: Bearer {api_key}'\\\n--header 'Content-Type: application/json'\\\n--data-raw '{
+        "query": "test",
+        "retrieval_model": {
+            "search_method": "keyword_search",
+            "reranking_enable": false,
+            "reranking_mode": null,
+            "reranking_model": {
+                "reranking_provider_name": "",
+                "reranking_model_name": ""
+            },
+            "weights": null,
+            "top_k": 1,
+            "score_threshold_enabled": false,
+            "score_threshold": null
+        }
+    }'`}
+    >
+    ```bash {{ title: 'cURL' }}
+    curl --location --request POST '${props.apiBaseUrl}/datasets/{dataset_id}/hit_testing' \
+    --header 'Authorization: Bearer {api_key}' \
+    --header 'Content-Type: application/json' \
+    --data-raw '{
+        "query": "test",
+        "retrieval_model": {
+            "search_method": "keyword_search",
+            "reranking_enable": false,
+            "reranking_mode": null,
+            "reranking_model": {
+                "reranking_provider_name": "",
+                "reranking_model_name": ""
+            },
+            "weights": null,
+            "top_k": 2,
+            "score_threshold_enabled": false,
+            "score_threshold": null
+        }
+    }'
+    ```
+    </CodeGroup>
+    <CodeGroup title="Response">
+    ```json {{ title: 'Response' }}
+    {
+      "query": {
+        "content": "test"
+      },
+      "records": [
+        {
+          "segment": {
+            "id": "7fa6f24f-8679-48b3-bc9d-bdf28d73f218",
+            "position": 1,
+            "document_id": "a8c6c36f-9f5d-4d7a-8472-f5d7b75d71d2",
+            "content": "Operation guide",
+            "answer": null,
+            "word_count": 847,
+            "tokens": 280,
+            "keywords": [
+              "install",
+              "java",
+              "base",
+              "scripts",
+              "jdk",
+              "manual",
+              "internal",
+              "opens",
+              "add",
+              "vmoptions"
+            ],
+            "index_node_id": "39dd8443-d960-45a8-bb46-7275ad7fbc8e",
+            "index_node_hash": "0189157697b3c6a418ccf8264a09699f25858975578f3467c76d6bfc94df1d73",
+            "hit_count": 0,
+            "enabled": true,
+            "disabled_at": null,
+            "disabled_by": null,
+            "status": "completed",
+            "created_by": "dbcb1ab5-90c8-41a7-8b78-73b235eb6f6f",
+            "created_at": 1728734540,
+            "indexing_at": 1728734552,
+            "completed_at": 1728734584,
+            "error": null,
+            "stopped_at": null,
+            "document": {
+              "id": "a8c6c36f-9f5d-4d7a-8472-f5d7b75d71d2",
+              "data_source_type": "upload_file",
+              "name": "readme.txt",
+              "doc_type": null
+            }
+          },
+          "score": 3.730463140527718e-05,
+          "tsne_position": null
+        }
+      ]
+    }
+    ```
+    </CodeGroup>
+  </Col>
+</Row>
+
+---
+
 <Row>
   <Col>
     ### Error message

web/app/(commonLayout)/datasets/template/template.zh.mdx

@@ -1049,6 +1049,152 @@ import { Row, Col, Properties, Property, Heading, SubProperty, Paragraph } from
   </Col>
 </Row>
 
+---
+
+<Heading
+  url='/datasets/{dataset_id}/hit_testing'
+  method='POST'
+  title='知识库召回测试'
+  name='#dataset_hit_testing'
+/>
+<Row>
+  <Col>
+    ### Path
+    <Properties>
+      <Property name='dataset_id' type='string' key='dataset_id'>
+        知识库 ID
+      </Property>
+    </Properties>
+
+    ### Request Body
+    <Properties>
+      <Property name='query' type='string' key='query'>
+        召回关键词
+      </Property>
+      <Property name='retrieval_model' type='object' key='retrieval_model'>
+        召回参数(选填，如不填，按照默认方式召回)
+        - <code>search_method</code> (text) 检索方法：以下三个关键字之一，必填
+          - <code>keyword_search</code> 关键字检索
+          - <code>semantic_search</code> 语义检索
+          - <code>full_text_search</code> 全文检索
+          - <code>hybrid_search</code> 混合检索
+        - <code>reranking_enable</code> (bool) 是否启用 Reranking，非必填，如果检索模式为semantic_search模式或者hybrid_search则传值
+        - <code>reranking_mode</code> (object) Rerank模型配置，非必填，如果启用了 reranking 则传值
+            - <code>reranking_provider_name</code> (string) Rerank 模型提供商
+            - <code>reranking_model_name</code> (string) Rerank 模型名称
+        - <code>weights</code> (double) 混合检索模式下语意检索的权重设置
+        - <code>top_k</code> (integer) 返回结果数量，非必填
+        - <code>score_threshold_enabled</code> (bool) 是否开启Score阈值
+        - <code>score_threshold</code> (double) Score阈值
+      </Property>
+      <Property name='external_retrieval_model' type='object' key='external_retrieval_model'>
+          未启用字段
+      </Property>
+    </Properties>
+  </Col>
+  <Col sticky>
+    <CodeGroup
+      title="Request"
+      tag="POST"
+      label="/datasets/{dataset_id}/hit_testing"
+      targetCode={`curl --location --request GET '${props.apiBaseUrl}/datasets/{dataset_id}/hit_testing' \\\n--header 'Authorization: Bearer {api_key}'\\\n--header 'Content-Type: application/json'\\\n--data-raw '{
+        "query": "test",
+        "retrieval_model": {
+            "search_method": "keyword_search",
+            "reranking_enable": false,
+            "reranking_mode": null,
+            "reranking_model": {
+                "reranking_provider_name": "",
+                "reranking_model_name": ""
+            },
+            "weights": null,
+            "top_k": 1,
+            "score_threshold_enabled": false,
+            "score_threshold": null
+        }
+    }'`}
+    >
+    ```bash {{ title: 'cURL' }}
+    curl --location --request POST '${props.apiBaseUrl}/datasets/{dataset_id}/hit_testing' \
+    --header 'Authorization: Bearer {api_key}' \
+    --header 'Content-Type: application/json' \
+    --data-raw '{
+        "query": "test",
+        "retrieval_model": {
+            "search_method": "keyword_search",
+            "reranking_enable": false,
+            "reranking_mode": null,
+            "reranking_model": {
+                "reranking_provider_name": "",
+                "reranking_model_name": ""
+            },
+            "weights": null,
+            "top_k": 2,
+            "score_threshold_enabled": false,
+            "score_threshold": null
+        }
+    }'
+    ```
+    </CodeGroup>
+    <CodeGroup title="Response">
+    ```json {{ title: 'Response' }}
+    {
+      "query": {
+        "content": "test"
+      },
+      "records": [
+        {
+          "segment": {
+            "id": "7fa6f24f-8679-48b3-bc9d-bdf28d73f218",
+            "position": 1,
+            "document_id": "a8c6c36f-9f5d-4d7a-8472-f5d7b75d71d2",
+            "content": "Operation guide",
+            "answer": null,
+            "word_count": 847,
+            "tokens": 280,
+            "keywords": [
+              "install",
+              "java",
+              "base",
+              "scripts",
+              "jdk",
+              "manual",
+              "internal",
+              "opens",
+              "add",
+              "vmoptions"
+            ],
+            "index_node_id": "39dd8443-d960-45a8-bb46-7275ad7fbc8e",
+            "index_node_hash": "0189157697b3c6a418ccf8264a09699f25858975578f3467c76d6bfc94df1d73",
+            "hit_count": 0,
+            "enabled": true,
+            "disabled_at": null,
+            "disabled_by": null,
+            "status": "completed",
+            "created_by": "dbcb1ab5-90c8-41a7-8b78-73b235eb6f6f",
+            "created_at": 1728734540,
+            "indexing_at": 1728734552,
+            "completed_at": 1728734584,
+            "error": null,
+            "stopped_at": null,
+            "document": {
+              "id": "a8c6c36f-9f5d-4d7a-8472-f5d7b75d71d2",
+              "data_source_type": "upload_file",
+              "name": "readme.txt",
+              "doc_type": null
+            }
+          },
+          "score": 3.730463140527718e-05,
+          "tsne_position": null
+        }
+      ]
+    }
+    ```
+    </CodeGroup>
+  </Col>
+</Row>
+
+
 ---
 
 <Row>

web/app/components/app/configuration/dataset-config/params-config/config-content.tsx

@@ -63,7 +63,7 @@ const ConfigContent: FC<Props> = ({
   } = useModelListAndDefaultModelAndCurrentProviderAndModel(ModelTypeEnum.rerank)
 
   const {
-    currentModel,
+    currentModel: currentRerankModel,
   } = useCurrentProviderAndModel(
     rerankModelList,
     rerankDefaultModel
@@ -74,11 +74,6 @@ const ConfigContent: FC<Props> = ({
       : undefined,
   )
 
-  const handleDisabledSwitchClick = useCallback(() => {
-    if (!currentModel)
-      Toast.notify({ type: 'error', message: t('workflow.errorMsg.rerankModelRequired') })
-  }, [currentModel, rerankDefaultModel, t])
-
   const rerankModel = (() => {
     if (datasetConfigs.reranking_model?.reranking_provider_name) {
       return {
@@ -164,12 +159,33 @@ const ConfigContent: FC<Props> = ({
   const showWeightedScorePanel = showWeightedScore && datasetConfigs.reranking_mode === RerankingModeEnum.WeightedScore && datasetConfigs.weights
   const selectedRerankMode = datasetConfigs.reranking_mode || RerankingModeEnum.RerankingModel
 
+  const canManuallyToggleRerank = useMemo(() => {
+    return !(
+      (selectedDatasetsMode.allInternal && selectedDatasetsMode.allEconomic)
+      || selectedDatasetsMode.allExternal
+    )
+  }, [selectedDatasetsMode.allEconomic, selectedDatasetsMode.allExternal, selectedDatasetsMode.allInternal])
+
   const showRerankModel = useMemo(() => {
-    if (datasetConfigs.reranking_enable === false && selectedDatasetsMode.allEconomic)
+    if (!canManuallyToggleRerank)
       return false
 
-    return true
-  }, [datasetConfigs.reranking_enable, selectedDatasetsMode.allEconomic])
+    return datasetConfigs.reranking_enable
+  }, [canManuallyToggleRerank, datasetConfigs.reranking_enable])
+
+  const handleDisabledSwitchClick = useCallback(() => {
+    if (!currentRerankModel && !showRerankModel)
+      Toast.notify({ type: 'error', message: t('workflow.errorMsg.rerankModelRequired') })
+  }, [currentRerankModel, showRerankModel, t])
+
+  useEffect(() => {
+    if (!canManuallyToggleRerank && showRerankModel !== datasetConfigs.reranking_enable) {
+      onChange({
+        ...datasetConfigs,
+        reranking_enable: showRerankModel,
+      })
+    }
+  }, [canManuallyToggleRerank, showRerankModel, datasetConfigs, onChange])
 
   return (
     <div>
@@ -256,13 +272,15 @@ const ConfigContent: FC<Props> = ({
                       >
                         <Switch
                           size='md'
-                          defaultValue={currentModel ? showRerankModel : false}
-                          disabled={!currentModel}
+                          defaultValue={showRerankModel}
+                          disabled={!currentRerankModel || !canManuallyToggleRerank}
                           onChange={(v) => {
+                            if (canManuallyToggleRerank) {
                               onChange({
                                 ...datasetConfigs,
                                 reranking_enable: v,
                               })
+                            }
                           }}
                         />
                       </div>

web/app/components/app/configuration/dataset-config/params-config/index.tsx

@@ -42,6 +42,7 @@ const ParamsConfig = ({
       allHighQuality,
       allHighQualityFullTextSearch,
       allHighQualityVectorSearch,
+      allInternal,
       allExternal,
       mixtureHighQualityAndEconomic,
       inconsistentEmbeddingModel,
@@ -50,7 +51,7 @@ const ParamsConfig = ({
     const { datasets, retrieval_model, score_threshold_enabled, ...restConfigs } = datasetConfigs
     let rerankEnable = restConfigs.reranking_enable
 
-    if ((allEconomic && !restConfigs.reranking_model?.reranking_provider_name && rerankEnable === undefined) || allExternal)
+    if (((allInternal && allEconomic) || allExternal) && !restConfigs.reranking_model?.reranking_provider_name && rerankEnable === undefined)
       rerankEnable = false
 
     if (allEconomic || allHighQuality || allHighQualityFullTextSearch || allHighQualityVectorSearch || (allExternal && selectedDatasets.length === 1))

web/app/components/workflow/hooks/use-workflow-start-run.tsx

@@ -1,25 +1,17 @@
 import { useCallback } from 'react'
 import { useStoreApi } from 'reactflow'
-import { useTranslation } from 'react-i18next'
 import { useWorkflowStore } from '../store'
 import {
   BlockEnum,
   WorkflowRunningStatus,
 } from '../types'
-import type { KnowledgeRetrievalNodeType } from '../nodes/knowledge-retrieval/types'
-import type { Node } from '../types'
-import { useWorkflow } from './use-workflow'
 import {
   useIsChatMode,
   useNodesSyncDraft,
   useWorkflowInteractions,
   useWorkflowRun,
 } from './index'
-import { ModelTypeEnum } from '@/app/components/header/account-setting/model-provider-page/declarations'
-import { useCurrentProviderAndModel, useModelListAndDefaultModelAndCurrentProviderAndModel } from '@/app/components/header/account-setting/model-provider-page/hooks'
 import { useFeaturesStore } from '@/app/components/base/features/hooks'
-import KnowledgeRetrievalDefault from '@/app/components/workflow/nodes/knowledge-retrieval/default'
-import Toast from '@/app/components/base/toast'
 
 export const useWorkflowStartRun = () => {
   const store = useStoreApi()
@@ -28,26 +20,7 @@ export const useWorkflowStartRun = () => {
   const isChatMode = useIsChatMode()
   const { handleCancelDebugAndPreviewPanel } = useWorkflowInteractions()
   const { handleRun } = useWorkflowRun()
-  const { isFromStartNode } = useWorkflow()
   const { doSyncWorkflowDraft } = useNodesSyncDraft()
-  const { checkValid: checkKnowledgeRetrievalValid } = KnowledgeRetrievalDefault
-  const { t } = useTranslation()
-  const {
-    modelList: rerankModelList,
-    defaultModel: rerankDefaultModel,
-  } = useModelListAndDefaultModelAndCurrentProviderAndModel(ModelTypeEnum.rerank)
-
-  const {
-    currentModel,
-  } = useCurrentProviderAndModel(
-    rerankModelList,
-    rerankDefaultModel
-      ? {
-        ...rerankDefaultModel,
-        provider: rerankDefaultModel.provider.provider,
-      }
-      : undefined,
-  )
 
   const handleWorkflowStartRunInWorkflow = useCallback(async () => {
     const {
@@ -60,9 +33,6 @@ export const useWorkflowStartRun = () => {
     const { getNodes } = store.getState()
     const nodes = getNodes()
     const startNode = nodes.find(node => node.data.type === BlockEnum.Start)
-    const knowledgeRetrievalNodes = nodes.filter((node: Node<KnowledgeRetrievalNodeType>) =>
-      node.data.type === BlockEnum.KnowledgeRetrieval,
-    )
     const startVariables = startNode?.data.variables || []
     const fileSettings = featuresStore!.getState().features.file
     const {
@@ -72,31 +42,6 @@ export const useWorkflowStartRun = () => {
       setShowEnvPanel,
     } = workflowStore.getState()
 
-    if (knowledgeRetrievalNodes.length > 0) {
-      for (const node of knowledgeRetrievalNodes) {
-        if (isFromStartNode(node.id)) {
-          const res = checkKnowledgeRetrievalValid(node.data, t)
-          if (!res.isValid || !currentModel || !rerankDefaultModel) {
-            const errorMessage = res.errorMessage
-            if (errorMessage) {
-              Toast.notify({
-                type: 'error',
-                message: errorMessage,
-              })
-              return false
-            }
-            else {
-              Toast.notify({
-                type: 'error',
-                message: t('appDebug.datasetConfig.rerankModelRequired'),
-              })
-              return false
-            }
-          }
-        }
-      }
-    }
-
     setShowEnvPanel(false)
 
     if (showDebugAndPreviewPanel) {

web/app/components/workflow/nodes/knowledge-retrieval/use-config.ts

@@ -23,7 +23,7 @@ import type { DataSet } from '@/models/datasets'
 import { fetchDatasets } from '@/service/datasets'
 import useNodeCrud from '@/app/components/workflow/nodes/_base/hooks/use-node-crud'
 import useOneStepRun from '@/app/components/workflow/nodes/_base/hooks/use-one-step-run'
-import { useModelListAndDefaultModelAndCurrentProviderAndModel } from '@/app/components/header/account-setting/model-provider-page/hooks'
+import { useCurrentProviderAndModel, useModelListAndDefaultModelAndCurrentProviderAndModel } from '@/app/components/header/account-setting/model-provider-page/hooks'
 import { ModelTypeEnum } from '@/app/components/header/account-setting/model-provider-page/declarations'
 
 const useConfig = (id: string, payload: KnowledgeRetrievalNodeType) => {
@@ -34,6 +34,8 @@ const useConfig = (id: string, payload: KnowledgeRetrievalNodeType) => {
   const startNodeId = startNode?.id
   const { inputs, setInputs: doSetInputs } = useNodeCrud<KnowledgeRetrievalNodeType>(id, payload)
 
+  const inputRef = useRef(inputs)
+
   const setInputs = useCallback((s: KnowledgeRetrievalNodeType) => {
     const newInputs = produce(s, (draft) => {
       if (s.retrieval_mode === RETRIEVE_TYPE.multiWay)
@@ -43,13 +45,9 @@ const useConfig = (id: string, payload: KnowledgeRetrievalNodeType) => {
     })
     // not work in pass to draft...
     doSetInputs(newInputs)
+    inputRef.current = newInputs
   }, [doSetInputs])
 
-  const inputRef = useRef(inputs)
-  useEffect(() => {
-    inputRef.current = inputs
-  }, [inputs])
-
   const handleQueryVarChange = useCallback((newVar: ValueSelector | string) => {
     const newInputs = produce(inputs, (draft) => {
       draft.query_variable_selector = newVar as ValueSelector
@@ -63,9 +61,22 @@ const useConfig = (id: string, payload: KnowledgeRetrievalNodeType) => {
   } = useModelListAndDefaultModelAndCurrentProviderAndModel(ModelTypeEnum.textGeneration)
 
   const {
+    modelList: rerankModelList,
     defaultModel: rerankDefaultModel,
   } = useModelListAndDefaultModelAndCurrentProviderAndModel(ModelTypeEnum.rerank)
 
+  const {
+    currentModel: currentRerankModel,
+  } = useCurrentProviderAndModel(
+    rerankModelList,
+    rerankDefaultModel
+      ? {
+        ...rerankDefaultModel,
+        provider: rerankDefaultModel.provider.provider,
+      }
+      : undefined,
+  )
+
   const handleModelChanged = useCallback((model: { provider: string; modelId: string; mode?: string }) => {
     const newInputs = produce(inputRef.current, (draft) => {
       if (!draft.single_retrieval_config) {
@@ -110,7 +121,7 @@ const useConfig = (id: string, payload: KnowledgeRetrievalNodeType) => {
   // set defaults models
   useEffect(() => {
     const inputs = inputRef.current
-    if (inputs.retrieval_mode === RETRIEVE_TYPE.multiWay && inputs.multiple_retrieval_config?.reranking_model?.provider)
+    if (inputs.retrieval_mode === RETRIEVE_TYPE.multiWay && inputs.multiple_retrieval_config?.reranking_model?.provider && currentRerankModel && rerankDefaultModel)
       return
 
     if (inputs.retrieval_mode === RETRIEVE_TYPE.oneWay && inputs.single_retrieval_config?.model?.provider)
@@ -130,7 +141,6 @@ const useConfig = (id: string, payload: KnowledgeRetrievalNodeType) => {
           }
         }
       }
-
       const multipleRetrievalConfig = draft.multiple_retrieval_config
       draft.multiple_retrieval_config = {
         top_k: multipleRetrievalConfig?.top_k || DATASET_DEFAULT.top_k,
@@ -138,6 +148,9 @@ const useConfig = (id: string, payload: KnowledgeRetrievalNodeType) => {
         reranking_model: multipleRetrievalConfig?.reranking_model,
         reranking_mode: multipleRetrievalConfig?.reranking_mode,
         weights: multipleRetrievalConfig?.weights,
+        reranking_enable: multipleRetrievalConfig?.reranking_enable !== undefined
+          ? multipleRetrievalConfig.reranking_enable
+          : Boolean(currentRerankModel && rerankDefaultModel),
       }
     })
     setInputs(newInput)
@@ -194,14 +207,14 @@ const useConfig = (id: string, payload: KnowledgeRetrievalNodeType) => {
   }, [])
 
   useEffect(() => {
+    const inputs = inputRef.current
     let query_variable_selector: ValueSelector = inputs.query_variable_selector
     if (isChatMode && inputs.query_variable_selector.length === 0 && startNodeId)
       query_variable_selector = [startNodeId, 'sys.query']
 
-    setInputs({
-      ...inputs,
-      query_variable_selector,
-    })
+    setInputs(produce(inputs, (draft) => {
+      draft.query_variable_selector = query_variable_selector
+    }))
   // eslint-disable-next-line react-hooks/exhaustive-deps
   }, [])
 

web/app/components/workflow/nodes/knowledge-retrieval/utils.ts

@@ -113,7 +113,7 @@ export const getMultipleRetrievalConfig = (multipleRetrievalConfig: MultipleRetr
     reranking_mode,
     reranking_model,
     weights,
-    reranking_enable: allEconomic ? reranking_enable : true,
+    reranking_enable: ((allInternal && allEconomic) || allExternal) ? reranking_enable : true,
   }
 
   if (allEconomic || mixtureHighQualityAndEconomic || inconsistentEmbeddingModel || allExternal || mixtureInternalAndExternal)