bump version to 0.4.4 (#1962)

Co-authored-by: jyong <jyong@dify.ai>
Co-authored-by: Joel <iamjoel007@gmail.com>

.github/workflows/api-model-runtime-tests.yml

@@ -31,28 +31,19 @@ jobs:
       HUGGINGFACE_EMBEDDINGS_ENDPOINT_URL: c
       MOCK_SWITCH: true
 
-
     steps:
     - name: Checkout code
-      uses: actions/checkout@v2
+      uses: actions/checkout@v4
 
     - name: Set up Python
-      uses: actions/setup-python@v2
+      uses: actions/setup-python@v5
       with:
         python-version: '3.10'
-
-    - name: Cache pip dependencies
-      uses: actions/cache@v2
-      with:
-        path: ~/.cache/pip
-        key: ${{ runner.os }}-pip-${{ hashFiles('api/requirements.txt') }}
-        restore-keys: ${{ runner.os }}-pip-
+        cache: 'pip'
+        cache-dependency-path: ./api/requirements.txt
 
     - name: Install dependencies
-      run: |
-        python -m pip install --upgrade pip
-        pip install pytest
-        pip install -r api/requirements.txt
+      run: pip install -r ./api/requirements.txt
 
     - name: Run pytest
       run: pytest api/tests/integration_tests/model_runtime/anthropic api/tests/integration_tests/model_runtime/azure_openai api/tests/integration_tests/model_runtime/openai api/tests/integration_tests/model_runtime/chatglm api/tests/integration_tests/model_runtime/google api/tests/integration_tests/model_runtime/xinference api/tests/integration_tests/model_runtime/huggingface_hub/test_llm.py

.github/workflows/style.yml

@@ -0,0 +1,34 @@
+name: Style check
+
+on:
+  pull_request:
+    branches:
+      - main
+  push:
+    branches:
+      - deploy/dev
+
+jobs:
+  test:
+    runs-on: ubuntu-latest
+
+    steps:
+    - name: Checkout code
+      uses: actions/checkout@v4
+
+    - name: Setup NodeJS
+      uses: actions/setup-node@v4
+      with:
+        node-version: 18
+        cache: yarn
+        cache-dependency-path: ./web/package.json
+
+    - name: Web dependencies
+      run: |
+        cd ./web
+        yarn install --frozen-lockfile
+
+    - name: Web style check
+      run: |
+        cd ./web
+        yarn run lint

api/.env.example

@@ -65,6 +65,7 @@ WEAVIATE_BATCH_SIZE=100
 # Qdrant configuration, use `http://localhost:6333` for local mode or `https://your-qdrant-cluster-url.qdrant.io` for remote mode
 QDRANT_URL=http://localhost:6333
 QDRANT_API_KEY=difyai123456
+QDRANT_CLIENT_TIMEOUT=20
 
 # Milvus configuration
 MILVUS_HOST=127.0.0.1

api/config.py

@@ -36,6 +36,7 @@ DEFAULTS = {
     'SENTRY_PROFILES_SAMPLE_RATE': 1.0,
     'WEAVIATE_GRPC_ENABLED': 'True',
     'WEAVIATE_BATCH_SIZE': 100,
+    'QDRANT_CLIENT_TIMEOUT': 20,
     'CELERY_BACKEND': 'database',
     'LOG_LEVEL': 'INFO',
     'HOSTED_OPENAI_QUOTA_LIMIT': 200,
@@ -87,7 +88,7 @@ class Config:
         # ------------------------
         # General Configurations.
         # ------------------------
-        self.CURRENT_VERSION = "0.4.2"
+        self.CURRENT_VERSION = "0.4.4"
         self.COMMIT_SHA = get_env('COMMIT_SHA')
         self.EDITION = "SELF_HOSTED"
         self.DEPLOY_ENV = get_env('DEPLOY_ENV')

api/controllers/console/app/app.py

@@ -141,15 +141,9 @@ class AppListApi(Resource):
                     model_type=ModelType.LLM
                 )
             except ProviderTokenNotInitError:
-                raise ProviderNotInitializeError(
-                    f"No Default System Reasoning Model available. Please configure "
-                    f"in the Settings -> Model Provider.")
+                model_instance = None
 
-            if not model_instance:
-                raise ProviderNotInitializeError(
-                    f"No Default System Reasoning Model available. Please configure "
-                    f"in the Settings -> Model Provider.")
-            else:
+            if model_instance:
                 model_dict = app_model_config.model_dict
                 model_dict['provider'] = model_instance.provider
                 model_dict['name'] = model_instance.model

api/controllers/console/app/audio.py

@@ -58,7 +58,7 @@ class ChatMessageAudioApi(Resource):
         except ModelCurrentlyNotSupportError:
             raise ProviderModelCurrentlyNotSupportError()
         except InvokeError as e:
-            raise CompletionRequestError(str(e))
+            raise CompletionRequestError(e.description)
         except ValueError as e:
             raise e
         except Exception as e:

api/controllers/console/app/completion.py

@@ -78,7 +78,7 @@ class CompletionMessageApi(Resource):
         except ModelCurrentlyNotSupportError:
             raise ProviderModelCurrentlyNotSupportError()
         except InvokeError as e:
-            raise CompletionRequestError(str(e))
+            raise CompletionRequestError(e.description)
         except ValueError as e:
             raise e
         except Exception as e:
@@ -153,7 +153,7 @@ class ChatMessageApi(Resource):
         except ModelCurrentlyNotSupportError:
             raise ProviderModelCurrentlyNotSupportError()
         except InvokeError as e:
-            raise CompletionRequestError(str(e))
+            raise CompletionRequestError(e.description)
         except ValueError as e:
             raise e
         except Exception as e:

api/controllers/console/app/generator.py

@@ -38,7 +38,7 @@ class RuleGenerateApi(Resource):
         except ModelCurrentlyNotSupportError:
             raise ProviderModelCurrentlyNotSupportError()
         except InvokeError as e:
-            raise CompletionRequestError(str(e))
+            raise CompletionRequestError(e.description)
 
         return rules
 

api/controllers/console/app/message.py

@@ -228,7 +228,7 @@ class MessageMoreLikeThisApi(Resource):
         except ModelCurrentlyNotSupportError:
             raise ProviderModelCurrentlyNotSupportError()
         except InvokeError as e:
-            raise CompletionRequestError(str(e))
+            raise CompletionRequestError(e.description)
         except ValueError as e:
             raise e
         except Exception as e:
@@ -256,7 +256,7 @@ def compact_response(response: Union[dict, Generator]) -> Response:
                 yield "data: " + json.dumps(
                     api.handle_error(ProviderModelCurrentlyNotSupportError()).get_json()) + "\n\n"
             except InvokeError as e:
-                yield "data: " + json.dumps(api.handle_error(CompletionRequestError(str(e))).get_json()) + "\n\n"
+                yield "data: " + json.dumps(api.handle_error(CompletionRequestError(e.description)).get_json()) + "\n\n"
             except ValueError as e:
                 yield "data: " + json.dumps(api.handle_error(e).get_json()) + "\n\n"
             except Exception:
@@ -296,7 +296,7 @@ class MessageSuggestedQuestionApi(Resource):
         except ModelCurrentlyNotSupportError:
             raise ProviderModelCurrentlyNotSupportError()
         except InvokeError as e:
-            raise CompletionRequestError(str(e))
+            raise CompletionRequestError(e.description)
         except Exception:
             logging.exception("internal server error.")
             raise InternalServerError()

api/controllers/console/datasets/datasets_segments.py

@@ -156,6 +156,9 @@ class DatasetDocumentSegmentApi(Resource):
         if not segment:
             raise NotFound('Segment not found.')
 
+        if segment.status != 'completed':
+            raise NotFound('Segment is not completed, enable or disable function is not allowed')
+
         document_indexing_cache_key = 'document_{}_indexing'.format(segment.document_id)
         cache_result = redis_client.get(document_indexing_cache_key)
         if cache_result is not None:

api/controllers/console/explore/audio.py

@@ -54,7 +54,7 @@ class ChatAudioApi(InstalledAppResource):
         except ModelCurrentlyNotSupportError:
             raise ProviderModelCurrentlyNotSupportError()
         except InvokeError as e:
-            raise CompletionRequestError(str(e))
+            raise CompletionRequestError(e.description)
         except ValueError as e:
             raise e
         except Exception as e:

api/controllers/console/explore/completion.py

@@ -70,7 +70,7 @@ class CompletionApi(InstalledAppResource):
         except ModelCurrentlyNotSupportError:
             raise ProviderModelCurrentlyNotSupportError()
         except InvokeError as e:
-            raise CompletionRequestError(str(e))
+            raise CompletionRequestError(e.description)
         except ValueError as e:
             raise e
         except Exception as e:
@@ -134,7 +134,7 @@ class ChatApi(InstalledAppResource):
         except ModelCurrentlyNotSupportError:
             raise ProviderModelCurrentlyNotSupportError()
         except InvokeError as e:
-            raise CompletionRequestError(str(e))
+            raise CompletionRequestError(e.description)
         except ValueError as e:
             raise e
         except Exception as e:
@@ -175,7 +175,7 @@ def compact_response(response: Union[dict, Generator]) -> Response:
             except ModelCurrentlyNotSupportError:
                 yield "data: " + json.dumps(api.handle_error(ProviderModelCurrentlyNotSupportError()).get_json()) + "\n\n"
             except InvokeError as e:
-                yield "data: " + json.dumps(api.handle_error(CompletionRequestError(str(e))).get_json()) + "\n\n"
+                yield "data: " + json.dumps(api.handle_error(CompletionRequestError(e.description)).get_json()) + "\n\n"
             except ValueError as e:
                 yield "data: " + json.dumps(api.handle_error(e).get_json()) + "\n\n"
             except Exception:

api/controllers/console/explore/message.py

@@ -104,7 +104,7 @@ class MessageMoreLikeThisApi(InstalledAppResource):
         except ModelCurrentlyNotSupportError:
             raise ProviderModelCurrentlyNotSupportError()
         except InvokeError as e:
-            raise CompletionRequestError(str(e))
+            raise CompletionRequestError(e.description)
         except ValueError as e:
             raise e
         except Exception:
@@ -131,7 +131,7 @@ def compact_response(response: Union[dict, Generator]) -> Response:
             except ModelCurrentlyNotSupportError:
                 yield "data: " + json.dumps(api.handle_error(ProviderModelCurrentlyNotSupportError()).get_json()) + "\n\n"
             except InvokeError as e:
-                yield "data: " + json.dumps(api.handle_error(CompletionRequestError(str(e))).get_json()) + "\n\n"
+                yield "data: " + json.dumps(api.handle_error(CompletionRequestError(e.description)).get_json()) + "\n\n"
             except ValueError as e:
                 yield "data: " + json.dumps(api.handle_error(e).get_json()) + "\n\n"
             except Exception:
@@ -169,7 +169,7 @@ class MessageSuggestedQuestionApi(InstalledAppResource):
         except ModelCurrentlyNotSupportError:
             raise ProviderModelCurrentlyNotSupportError()
         except InvokeError as e:
-            raise CompletionRequestError(str(e))
+            raise CompletionRequestError(e.description)
         except Exception:
             logging.exception("internal server error.")
             raise InternalServerError()

api/controllers/console/universal_chat/audio.py

@@ -54,7 +54,7 @@ class UniversalChatAudioApi(UniversalChatResource):
         except ModelCurrentlyNotSupportError:
             raise ProviderModelCurrentlyNotSupportError()
         except InvokeError as e:
-            raise CompletionRequestError(str(e))
+            raise CompletionRequestError(e.description)
         except ValueError as e:
             raise e
         except Exception as e:

api/controllers/console/universal_chat/chat.py

@@ -89,7 +89,7 @@ class UniversalChatApi(UniversalChatResource):
         except ModelCurrentlyNotSupportError:
             raise ProviderModelCurrentlyNotSupportError()
         except InvokeError as e:
-            raise CompletionRequestError(str(e))
+            raise CompletionRequestError(e.description)
         except ValueError as e:
             raise e
         except Exception as e:
@@ -126,7 +126,7 @@ def compact_response(response: Union[dict, Generator]) -> Response:
             except ModelCurrentlyNotSupportError:
                 yield "data: " + json.dumps(api.handle_error(ProviderModelCurrentlyNotSupportError()).get_json()) + "\n\n"
             except InvokeError as e:
-                yield "data: " + json.dumps(api.handle_error(CompletionRequestError(str(e))).get_json()) + "\n\n"
+                yield "data: " + json.dumps(api.handle_error(CompletionRequestError(e.description)).get_json()) + "\n\n"
             except ValueError as e:
                 yield "data: " + json.dumps(api.handle_error(e).get_json()) + "\n\n"
             except Exception:

api/controllers/console/universal_chat/message.py

@@ -133,7 +133,7 @@ class UniversalChatMessageSuggestedQuestionApi(UniversalChatResource):
         except ModelCurrentlyNotSupportError:
             raise ProviderModelCurrentlyNotSupportError()
         except InvokeError as e:
-            raise CompletionRequestError(str(e))
+            raise CompletionRequestError(e.description)
         except Exception:
             logging.exception("internal server error.")
             raise InternalServerError()

api/controllers/service_api/app/audio.py

@@ -50,7 +50,7 @@ class AudioApi(AppApiResource):
         except ModelCurrentlyNotSupportError:
             raise ProviderModelCurrentlyNotSupportError()
         except InvokeError as e:
-            raise CompletionRequestError(str(e))
+            raise CompletionRequestError(e.description)
         except ValueError as e:
             raise e
         except Exception as e:

api/controllers/service_api/app/completion.py

@@ -31,7 +31,7 @@ class CompletionApi(AppApiResource):
         parser.add_argument('query', type=str, location='json', default='')
         parser.add_argument('files', type=list, required=False, location='json')
         parser.add_argument('response_mode', type=str, choices=['blocking', 'streaming'], location='json')
-        parser.add_argument('user', type=str, location='json')
+        parser.add_argument('user', required=True, nullable=False, type=str, location='json')
         parser.add_argument('retriever_from', type=str, required=False, default='dev', location='json')
 
         args = parser.parse_args()
@@ -67,7 +67,7 @@ class CompletionApi(AppApiResource):
         except ModelCurrentlyNotSupportError:
             raise ProviderModelCurrentlyNotSupportError()
         except InvokeError as e:
-            raise CompletionRequestError(str(e))
+            raise CompletionRequestError(e.description)
         except ValueError as e:
             raise e
         except Exception as e:
@@ -96,7 +96,7 @@ class ChatApi(AppApiResource):
         parser.add_argument('files', type=list, required=False, location='json')
         parser.add_argument('response_mode', type=str, choices=['blocking', 'streaming'], location='json')
         parser.add_argument('conversation_id', type=uuid_value, location='json')
-        parser.add_argument('user', type=str, location='json')
+        parser.add_argument('user', type=str, required=True, nullable=False, 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')
 
@@ -131,7 +131,7 @@ class ChatApi(AppApiResource):
         except ModelCurrentlyNotSupportError:
             raise ProviderModelCurrentlyNotSupportError()
         except InvokeError as e:
-            raise CompletionRequestError(str(e))
+            raise CompletionRequestError(e.description)
         except ValueError as e:
             raise e
         except Exception as e:
@@ -171,7 +171,7 @@ def compact_response(response: Union[dict, Generator]) -> Response:
             except ModelCurrentlyNotSupportError:
                 yield "data: " + json.dumps(api.handle_error(ProviderModelCurrentlyNotSupportError()).get_json()) + "\n\n"
             except InvokeError as e:
-                yield "data: " + json.dumps(api.handle_error(CompletionRequestError(str(e))).get_json()) + "\n\n"
+                yield "data: " + json.dumps(api.handle_error(CompletionRequestError(e.description)).get_json()) + "\n\n"
             except ValueError as e:
                 yield "data: " + json.dumps(api.handle_error(e).get_json()) + "\n\n"
             except Exception:

api/controllers/web/audio.py

@@ -52,7 +52,7 @@ class AudioApi(WebApiResource):
         except ModelCurrentlyNotSupportError:
             raise ProviderModelCurrentlyNotSupportError()
         except InvokeError as e:
-            raise CompletionRequestError(str(e))
+            raise CompletionRequestError(e.description)
         except ValueError as e:
             raise e
         except Exception as e:

api/controllers/web/completion.py

@@ -64,7 +64,7 @@ class CompletionApi(WebApiResource):
         except ModelCurrentlyNotSupportError:
             raise ProviderModelCurrentlyNotSupportError()
         except InvokeError as e:
-            raise CompletionRequestError(str(e))
+            raise CompletionRequestError(e.description)
         except ValueError as e:
             raise e
         except Exception as e:
@@ -124,7 +124,7 @@ class ChatApi(WebApiResource):
         except ModelCurrentlyNotSupportError:
             raise ProviderModelCurrentlyNotSupportError()
         except InvokeError as e:
-            raise CompletionRequestError(str(e))
+            raise CompletionRequestError(e.description)
         except ValueError as e:
             raise e
         except Exception as e:
@@ -164,7 +164,7 @@ def compact_response(response: Union[dict, Generator]) -> Response:
             except ModelCurrentlyNotSupportError:
                 yield "data: " + json.dumps(api.handle_error(ProviderModelCurrentlyNotSupportError()).get_json()) + "\n\n"
             except InvokeError as e:
-                yield "data: " + json.dumps(api.handle_error(CompletionRequestError(str(e))).get_json()) + "\n\n"
+                yield "data: " + json.dumps(api.handle_error(CompletionRequestError(e.description)).get_json()) + "\n\n"
             except ValueError as e:
                 yield "data: " + json.dumps(api.handle_error(e).get_json()) + "\n\n"
             except Exception:

api/controllers/web/message.py

@@ -138,7 +138,7 @@ class MessageMoreLikeThisApi(WebApiResource):
         except ModelCurrentlyNotSupportError:
             raise ProviderModelCurrentlyNotSupportError()
         except InvokeError as e:
-            raise CompletionRequestError(str(e))
+            raise CompletionRequestError(e.description)
         except ValueError as e:
             raise e
         except Exception:
@@ -165,7 +165,7 @@ def compact_response(response: Union[dict, Generator]) -> Response:
             except ModelCurrentlyNotSupportError:
                 yield "data: " + json.dumps(api.handle_error(ProviderModelCurrentlyNotSupportError()).get_json()) + "\n\n"
             except InvokeError as e:
-                yield "data: " + json.dumps(api.handle_error(CompletionRequestError(str(e))).get_json()) + "\n\n"
+                yield "data: " + json.dumps(api.handle_error(CompletionRequestError(e.description)).get_json()) + "\n\n"
             except ValueError as e:
                 yield "data: " + json.dumps(api.handle_error(e).get_json()) + "\n\n"
             except Exception:
@@ -202,7 +202,7 @@ class MessageSuggestedQuestionApi(WebApiResource):
         except ModelCurrentlyNotSupportError:
             raise ProviderModelCurrentlyNotSupportError()
         except InvokeError as e:
-            raise CompletionRequestError(str(e))
+            raise CompletionRequestError(e.description)
         except Exception:
             logging.exception("internal server error.")
             raise InternalServerError()

api/core/app_runner/agent_app_runner.py

@@ -75,7 +75,7 @@ class AgentApplicationRunner(AppRunner):
         # reorganize all inputs and template to prompt messages
         # Include: prompt template, inputs, query(optional), files(optional)
         #          memory(optional)
-        prompt_messages, stop = self.originze_prompt_messages(
+        prompt_messages, stop = self.organize_prompt_messages(
             app_record=app_record,
             model_config=app_orchestration_config.model_config,
             prompt_template_entity=app_orchestration_config.prompt_template,
@@ -153,7 +153,7 @@ class AgentApplicationRunner(AppRunner):
             # reorganize all inputs and template to prompt messages
             # Include: prompt template, inputs, query(optional), files(optional)
             #          memory(optional), external data, dataset context(optional)
-            prompt_messages, stop = self.originze_prompt_messages(
+            prompt_messages, stop = self.organize_prompt_messages(
                 app_record=app_record,
                 model_config=app_orchestration_config.model_config,
                 prompt_template_entity=app_orchestration_config.prompt_template,

api/core/app_runner/app_runner.py

@@ -1,7 +1,7 @@
 import time
 from typing import cast, Optional, List, Tuple, Generator, Union
 
-from core.application_queue_manager import ApplicationQueueManager
+from core.application_queue_manager import ApplicationQueueManager, PublishFrom
 from core.entities.application_entities import ModelConfigEntity, PromptTemplateEntity, AppOrchestrationConfigEntity
 from core.file.file_obj import FileObj
 from core.memory.token_buffer_memory import TokenBufferMemory
@@ -50,7 +50,7 @@ class AppRunner:
             max_tokens = 0
 
         # get prompt messages without memory and context
-        prompt_messages, stop = self.originze_prompt_messages(
+        prompt_messages, stop = self.organize_prompt_messages(
             app_record=app_record,
             model_config=model_config,
             prompt_template_entity=prompt_template_entity,
@@ -107,7 +107,7 @@ class AppRunner:
                         or (parameter_rule.use_template and parameter_rule.use_template == 'max_tokens')):
                     model_config.parameters[parameter_rule.name] = max_tokens
 
-    def originze_prompt_messages(self, app_record: App,
+    def organize_prompt_messages(self, app_record: App,
                                  model_config: ModelConfigEntity,
                                  prompt_template_entity: PromptTemplateEntity,
                                  inputs: dict[str, str],
@@ -183,7 +183,7 @@ class AppRunner:
                         index=index,
                         message=AssistantPromptMessage(content=token)
                     )
-                ))
+                ), PublishFrom.APPLICATION_MANAGER)
                 index += 1
                 time.sleep(0.01)
 
@@ -193,7 +193,8 @@ class AppRunner:
                 prompt_messages=prompt_messages,
                 message=AssistantPromptMessage(content=text),
                 usage=usage if usage else LLMUsage.empty_usage()
-            )
+            ),
+            pub_from=PublishFrom.APPLICATION_MANAGER
         )
 
     def _handle_invoke_result(self, invoke_result: Union[LLMResult, Generator],
@@ -226,7 +227,8 @@ class AppRunner:
         :return:
         """
         queue_manager.publish_message_end(
-            llm_result=invoke_result
+            llm_result=invoke_result,
+            pub_from=PublishFrom.APPLICATION_MANAGER
         )
 
     def _handle_invoke_result_stream(self, invoke_result: Generator,
@@ -242,7 +244,7 @@ class AppRunner:
         text = ''
         usage = None
         for result in invoke_result:
-            queue_manager.publish_chunk_message(result)
+            queue_manager.publish_chunk_message(result, PublishFrom.APPLICATION_MANAGER)
 
             text += result.delta.message.content
 
@@ -263,5 +265,6 @@ class AppRunner:
         )
 
         queue_manager.publish_message_end(
-            llm_result=llm_result
+            llm_result=llm_result,
+            pub_from=PublishFrom.APPLICATION_MANAGER
         )

api/core/app_runner/basic_app_runner.py

@@ -5,7 +5,7 @@ from core.app_runner.app_runner import AppRunner
 from core.callback_handler.index_tool_callback_handler import DatasetIndexToolCallbackHandler
 from core.entities.application_entities import ApplicationGenerateEntity, ModelConfigEntity, \
     AppOrchestrationConfigEntity, InvokeFrom, ExternalDataVariableEntity, DatasetEntity
-from core.application_queue_manager import ApplicationQueueManager
+from core.application_queue_manager import ApplicationQueueManager, PublishFrom
 from core.features.annotation_reply import AnnotationReplyFeature
 from core.features.dataset_retrieval import DatasetRetrievalFeature
 from core.features.external_data_fetch import ExternalDataFetchFeature
@@ -79,7 +79,7 @@ class BasicApplicationRunner(AppRunner):
         # organize all inputs and template to prompt messages
         # Include: prompt template, inputs, query(optional), files(optional)
         #          memory(optional)
-        prompt_messages, stop = self.originze_prompt_messages(
+        prompt_messages, stop = self.organize_prompt_messages(
             app_record=app_record,
             model_config=app_orchestration_config.model_config,
             prompt_template_entity=app_orchestration_config.prompt_template,
@@ -121,7 +121,8 @@ class BasicApplicationRunner(AppRunner):
 
             if annotation_reply:
                 queue_manager.publish_annotation_reply(
-                    message_annotation_id=annotation_reply.id
+                    message_annotation_id=annotation_reply.id,
+                    pub_from=PublishFrom.APPLICATION_MANAGER
                 )
                 self.direct_output(
                     queue_manager=queue_manager,
@@ -132,16 +133,16 @@ class BasicApplicationRunner(AppRunner):
                 )
                 return
 
-            # fill in variable inputs from external data tools if exists
-            external_data_tools = app_orchestration_config.external_data_variables
-            if external_data_tools:
-                inputs = self.fill_in_inputs_from_external_data_tools(
-                    tenant_id=app_record.tenant_id,
-                    app_id=app_record.id,
-                    external_data_tools=external_data_tools,
-                    inputs=inputs,
-                    query=query
-                )
+        # fill in variable inputs from external data tools if exists
+        external_data_tools = app_orchestration_config.external_data_variables
+        if external_data_tools:
+            inputs = self.fill_in_inputs_from_external_data_tools(
+                tenant_id=app_record.tenant_id,
+                app_id=app_record.id,
+                external_data_tools=external_data_tools,
+                inputs=inputs,
+                query=query
+            )
 
         # get context from datasets
         context = None
@@ -164,7 +165,7 @@ class BasicApplicationRunner(AppRunner):
         # reorganize all inputs and template to prompt messages
         # Include: prompt template, inputs, query(optional), files(optional)
         #          memory(optional), external data, dataset context(optional)
-        prompt_messages, stop = self.originze_prompt_messages(
+        prompt_messages, stop = self.organize_prompt_messages(
             app_record=app_record,
             model_config=app_orchestration_config.model_config,
             prompt_template_entity=app_orchestration_config.prompt_template,

api/core/app_runner/generate_task_pipeline.py

@@ -7,7 +7,7 @@ from pydantic import BaseModel
 
 from core.app_runner.moderation_handler import OutputModerationHandler, ModerationRule
 from core.entities.application_entities import ApplicationGenerateEntity
-from core.application_queue_manager import ApplicationQueueManager
+from core.application_queue_manager import ApplicationQueueManager, PublishFrom
 from core.entities.queue_entities import QueueErrorEvent, QueueStopEvent, QueueMessageEndEvent, \
     QueueRetrieverResourcesEvent, QueueAgentThoughtEvent, QueuePingEvent, QueueMessageEvent, QueueMessageReplaceEvent, \
     AnnotationReplyEvent
@@ -312,8 +312,11 @@ class GenerateTaskPipeline:
                                 index=0,
                                 message=AssistantPromptMessage(content=self._task_state.llm_result.message.content)
                             )
-                        ))
-                        self._queue_manager.publish(QueueStopEvent(stopped_by=QueueStopEvent.StopBy.OUTPUT_MODERATION))
+                        ), PublishFrom.TASK_PIPELINE)
+                        self._queue_manager.publish(
+                            QueueStopEvent(stopped_by=QueueStopEvent.StopBy.OUTPUT_MODERATION),
+                            PublishFrom.TASK_PIPELINE
+                        )
                         continue
                     else:
                         self._output_moderation_handler.append_new_token(delta_text)

api/core/app_runner/moderation_handler.py

@@ -6,6 +6,7 @@ from typing import Any, Optional, Dict
 from flask import current_app, Flask
 from pydantic import BaseModel
 
+from core.application_queue_manager import PublishFrom
 from core.moderation.base import ModerationAction, ModerationOutputsResult
 from core.moderation.factory import ModerationFactory
 
@@ -66,7 +67,7 @@ class OutputModerationHandler(BaseModel):
             final_output = result.text
 
         if public_event:
-            self.on_message_replace_func(final_output)
+            self.on_message_replace_func(final_output, PublishFrom.TASK_PIPELINE)
 
         return final_output
 

api/core/application_manager.py

@@ -23,7 +23,7 @@ from core.model_runtime.errors.invoke import InvokeAuthorizationError, InvokeErr
 from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel
 from core.prompt.prompt_template import PromptTemplateParser
 from core.provider_manager import ProviderManager
-from core.application_queue_manager import ApplicationQueueManager, ConversationTaskStoppedException
+from core.application_queue_manager import ApplicationQueueManager, ConversationTaskStoppedException, PublishFrom
 from extensions.ext_database import db
 from models.account import Account
 from models.model import EndUser, Conversation, Message, MessageFile, App
@@ -169,15 +169,18 @@ class ApplicationManager:
             except ConversationTaskStoppedException:
                 pass
             except InvokeAuthorizationError:
-                queue_manager.publish_error(InvokeAuthorizationError('Incorrect API key provided'))
+                queue_manager.publish_error(
+                    InvokeAuthorizationError('Incorrect API key provided'),
+                    PublishFrom.APPLICATION_MANAGER
+                )
             except ValidationError as e:
                 logger.exception("Validation Error when generating")
-                queue_manager.publish_error(e)
+                queue_manager.publish_error(e, PublishFrom.APPLICATION_MANAGER)
             except (ValueError, InvokeError) as e:
-                queue_manager.publish_error(e)
+                queue_manager.publish_error(e, PublishFrom.APPLICATION_MANAGER)
             except Exception as e:
                 logger.exception("Unknown Error when generating")
-                queue_manager.publish_error(e)
+                queue_manager.publish_error(e, PublishFrom.APPLICATION_MANAGER)
             finally:
                 db.session.remove()
 

api/core/application_queue_manager.py

@@ -1,5 +1,6 @@
 import queue
 import time
+from enum import Enum
 from typing import Generator, Any
 
 from sqlalchemy.orm import DeclarativeMeta
@@ -13,6 +14,11 @@ from extensions.ext_redis import redis_client
 from models.model import MessageAgentThought
 
 
+class PublishFrom(Enum):
+    APPLICATION_MANAGER = 1
+    TASK_PIPELINE = 2
+
+
 class ApplicationQueueManager:
     def __init__(self, task_id: str,
                  user_id: str,
@@ -61,11 +67,14 @@ class ApplicationQueueManager:
                 if elapsed_time >= listen_timeout or self._is_stopped():
                     # publish two messages to make sure the client can receive the stop signal
                     # and stop listening after the stop signal processed
-                    self.publish(QueueStopEvent(stopped_by=QueueStopEvent.StopBy.USER_MANUAL))
+                    self.publish(
+                        QueueStopEvent(stopped_by=QueueStopEvent.StopBy.USER_MANUAL),
+                        PublishFrom.TASK_PIPELINE
+                    )
                     self.stop_listen()
 
                 if elapsed_time // 10 > last_ping_time:
-                    self.publish(QueuePingEvent())
+                    self.publish(QueuePingEvent(), PublishFrom.TASK_PIPELINE)
                     last_ping_time = elapsed_time // 10
 
     def stop_listen(self) -> None:
@@ -75,76 +84,83 @@ class ApplicationQueueManager:
         """
         self._q.put(None)
 
-    def publish_chunk_message(self, chunk: LLMResultChunk) -> None:
+    def publish_chunk_message(self, chunk: LLMResultChunk, pub_from: PublishFrom) -> None:
         """
         Publish chunk message to channel
 
         :param chunk: chunk
+        :param pub_from: publish from
         :return:
         """
         self.publish(QueueMessageEvent(
             chunk=chunk
-        ))
+        ), pub_from)
 
-    def publish_message_replace(self, text: str) -> None:
+    def publish_message_replace(self, text: str, pub_from: PublishFrom) -> None:
         """
         Publish message replace
         :param text: text
+        :param pub_from: publish from
         :return:
         """
         self.publish(QueueMessageReplaceEvent(
             text=text
-        ))
+        ), pub_from)
 
-    def publish_retriever_resources(self, retriever_resources: list[dict]) -> None:
+    def publish_retriever_resources(self, retriever_resources: list[dict], pub_from: PublishFrom) -> None:
         """
         Publish retriever resources
         :return:
         """
-        self.publish(QueueRetrieverResourcesEvent(retriever_resources=retriever_resources))
+        self.publish(QueueRetrieverResourcesEvent(retriever_resources=retriever_resources), pub_from)
 
-    def publish_annotation_reply(self, message_annotation_id: str) -> None:
+    def publish_annotation_reply(self, message_annotation_id: str, pub_from: PublishFrom) -> None:
         """
         Publish annotation reply
         :param message_annotation_id: message annotation id
+        :param pub_from: publish from
         :return:
         """
-        self.publish(AnnotationReplyEvent(message_annotation_id=message_annotation_id))
+        self.publish(AnnotationReplyEvent(message_annotation_id=message_annotation_id), pub_from)
 
-    def publish_message_end(self, llm_result: LLMResult) -> None:
+    def publish_message_end(self, llm_result: LLMResult, pub_from: PublishFrom) -> None:
         """
         Publish message end
         :param llm_result: llm result
+        :param pub_from: publish from
         :return:
         """
-        self.publish(QueueMessageEndEvent(llm_result=llm_result))
+        self.publish(QueueMessageEndEvent(llm_result=llm_result), pub_from)
         self.stop_listen()
 
-    def publish_agent_thought(self, message_agent_thought: MessageAgentThought) -> None:
+    def publish_agent_thought(self, message_agent_thought: MessageAgentThought, pub_from: PublishFrom) -> None:
         """
         Publish agent thought
         :param message_agent_thought: message agent thought
+        :param pub_from: publish from
         :return:
         """
         self.publish(QueueAgentThoughtEvent(
             agent_thought_id=message_agent_thought.id
-        ))
+        ), pub_from)
 
-    def publish_error(self, e) -> None:
+    def publish_error(self, e, pub_from: PublishFrom) -> None:
         """
         Publish error
         :param e: error
+        :param pub_from: publish from
         :return:
         """
         self.publish(QueueErrorEvent(
             error=e
-        ))
+        ), pub_from)
         self.stop_listen()
 
-    def publish(self, event: AppQueueEvent) -> None:
+    def publish(self, event: AppQueueEvent, pub_from: PublishFrom) -> None:
         """
         Publish event to queue
         :param event:
+        :param pub_from:
         :return:
         """
         self._check_for_sqlalchemy_models(event.dict())
@@ -162,6 +178,9 @@ class ApplicationQueueManager:
         if isinstance(event, QueueStopEvent):
             self.stop_listen()
 
+        if pub_from == PublishFrom.APPLICATION_MANAGER and self._is_stopped():
+            raise ConversationTaskStoppedException()
+
     @classmethod
     def set_stop_flag(cls, task_id: str, invoke_from: InvokeFrom, user_id: str) -> None:
         """
@@ -173,7 +192,7 @@ class ApplicationQueueManager:
             return
 
         user_prefix = 'account' if invoke_from in [InvokeFrom.EXPLORE, InvokeFrom.DEBUGGER] else 'end-user'
-        if result != f"{user_prefix}-{user_id}":
+        if result.decode('utf-8') != f"{user_prefix}-{user_id}":
             return
 
         stopped_cache_key = cls._generate_stopped_cache_key(task_id)
@@ -187,7 +206,6 @@ class ApplicationQueueManager:
         stopped_cache_key = ApplicationQueueManager._generate_stopped_cache_key(self._task_id)
         result = redis_client.get(stopped_cache_key)
         if result is not None:
-            redis_client.delete(stopped_cache_key)
             return True
 
         return False

api/core/callback_handler/agent_loop_gather_callback_handler.py

@@ -8,7 +8,7 @@ from langchain.agents import openai_functions_agent, openai_functions_multi_agen
 from langchain.callbacks.base import BaseCallbackHandler
 from langchain.schema import AgentAction, AgentFinish, LLMResult, ChatGeneration, BaseMessage
 
-from core.application_queue_manager import ApplicationQueueManager
+from core.application_queue_manager import ApplicationQueueManager, PublishFrom
 from core.callback_handler.entity.agent_loop import AgentLoop
 from core.entities.application_entities import ModelConfigEntity
 from core.model_runtime.entities.llm_entities import LLMResult as RuntimeLLMResult
@@ -232,7 +232,7 @@ class AgentLoopGatherCallbackHandler(BaseCallbackHandler):
         db.session.add(message_agent_thought)
         db.session.commit()
 
-        self.queue_manager.publish_agent_thought(message_agent_thought)
+        self.queue_manager.publish_agent_thought(message_agent_thought, PublishFrom.APPLICATION_MANAGER)
 
         return message_agent_thought
 

api/core/callback_handler/index_tool_callback_handler.py

@@ -2,7 +2,7 @@ from typing import List, Union
 
 from langchain.schema import Document
 
-from core.application_queue_manager import ApplicationQueueManager
+from core.application_queue_manager import ApplicationQueueManager, PublishFrom
 from core.entities.application_entities import InvokeFrom
 from extensions.ext_database import db
 from models.dataset import DocumentSegment, DatasetQuery
@@ -80,4 +80,4 @@ class DatasetIndexToolCallbackHandler:
                 db.session.add(dataset_retriever_resource)
                 db.session.commit()
 
-        self._queue_manager.publish_retriever_resources(resource)
+        self._queue_manager.publish_retriever_resources(resource, PublishFrom.APPLICATION_MANAGER)

api/core/data_loader/file_extractor.py

@@ -65,7 +65,8 @@ class FileExtractor:
             elif file_extension == '.pdf':
                 loader = PdfLoader(file_path, upload_file=upload_file)
             elif file_extension in ['.md', '.markdown']:
-                loader = UnstructuredMarkdownLoader(file_path, unstructured_api_url)
+                loader = UnstructuredMarkdownLoader(file_path, unstructured_api_url) if is_automatic \
+                    else MarkdownLoader(file_path, autodetect_encoding=True)
             elif file_extension in ['.htm', '.html']:
                 loader = HTMLLoader(file_path)
             elif file_extension == '.docx':
@@ -84,7 +85,8 @@ class FileExtractor:
                 loader = UnstructuredXmlLoader(file_path, unstructured_api_url)
             else:
                 # txt
-                loader = UnstructuredTextLoader(file_path, unstructured_api_url)
+                loader = UnstructuredTextLoader(file_path, unstructured_api_url) if is_automatic \
+                    else TextLoader(file_path, autodetect_encoding=True)
         else:
             if file_extension == '.xlsx':
                 loader = ExcelLoader(file_path)

api/core/entities/provider_configuration.py

@@ -1,5 +1,6 @@
 import datetime
 import json
+import logging
 import time
 from json import JSONDecodeError
 from typing import Optional, List, Dict, Tuple, Iterator
@@ -9,6 +10,7 @@ from pydantic import BaseModel
 from core.entities.model_entities import ModelWithProviderEntity, ModelStatus, SimpleModelProviderEntity
 from core.entities.provider_entities import SystemConfiguration, CustomConfiguration, SystemConfigurationStatus
 from core.helper import encrypter
+from core.helper.model_provider_cache import ProviderCredentialsCache, ProviderCredentialsCacheType
 from core.model_runtime.entities.model_entities import ModelType
 from core.model_runtime.entities.provider_entities import ProviderEntity, CredentialFormSchema, FormType
 from core.model_runtime.model_providers import model_provider_factory
@@ -18,6 +20,8 @@ from core.model_runtime.utils import encoders
 from extensions.ext_database import db
 from models.provider import ProviderType, Provider, ProviderModel, TenantPreferredModelProvider
 
+logger = logging.getLogger(__name__)
+
 
 class ProviderConfiguration(BaseModel):
     """
@@ -168,6 +172,14 @@ class ProviderConfiguration(BaseModel):
             db.session.add(provider_record)
             db.session.commit()
 
+        provider_model_credentials_cache = ProviderCredentialsCache(
+            tenant_id=self.tenant_id,
+            identity_id=provider_record.id,
+            cache_type=ProviderCredentialsCacheType.PROVIDER
+        )
+
+        provider_model_credentials_cache.delete()
+
         self.switch_preferred_provider_type(ProviderType.CUSTOM)
 
     def delete_custom_credentials(self) -> None:
@@ -190,6 +202,14 @@ class ProviderConfiguration(BaseModel):
             db.session.delete(provider_record)
             db.session.commit()
 
+            provider_model_credentials_cache = ProviderCredentialsCache(
+                tenant_id=self.tenant_id,
+                identity_id=provider_record.id,
+                cache_type=ProviderCredentialsCacheType.PROVIDER
+            )
+
+            provider_model_credentials_cache.delete()
+
     def get_custom_model_credentials(self, model_type: ModelType, model: str, obfuscated: bool = False) \
             -> Optional[dict]:
         """
@@ -311,6 +331,14 @@ class ProviderConfiguration(BaseModel):
             db.session.add(provider_model_record)
             db.session.commit()
 
+        provider_model_credentials_cache = ProviderCredentialsCache(
+            tenant_id=self.tenant_id,
+            identity_id=provider_model_record.id,
+            cache_type=ProviderCredentialsCacheType.MODEL
+        )
+
+        provider_model_credentials_cache.delete()
+
     def delete_custom_model_credentials(self, model_type: ModelType, model: str) -> None:
         """
         Delete custom model credentials.
@@ -332,6 +360,14 @@ class ProviderConfiguration(BaseModel):
             db.session.delete(provider_model_record)
             db.session.commit()
 
+            provider_model_credentials_cache = ProviderCredentialsCache(
+                tenant_id=self.tenant_id,
+                identity_id=provider_model_record.id,
+                cache_type=ProviderCredentialsCacheType.MODEL
+            )
+
+            provider_model_credentials_cache.delete()
+
     def get_provider_instance(self) -> ModelProvider:
         """
         Get provider instance.
@@ -484,7 +520,13 @@ class ProviderConfiguration(BaseModel):
             provider_models.extend(
                 [
                     ModelWithProviderEntity(
-                        **m.dict(),
+                        model=m.model,
+                        label=m.label,
+                        model_type=m.model_type,
+                        features=m.features,
+                        fetch_from=m.fetch_from,
+                        model_properties=m.model_properties,
+                        deprecated=m.deprecated,
                         provider=SimpleModelProviderEntity(self.provider),
                         status=ModelStatus.ACTIVE
                     )
@@ -533,7 +575,13 @@ class ProviderConfiguration(BaseModel):
             for m in models:
                 provider_models.append(
                     ModelWithProviderEntity(
-                        **m.dict(),
+                        model=m.model,
+                        label=m.label,
+                        model_type=m.model_type,
+                        features=m.features,
+                        fetch_from=m.fetch_from,
+                        model_properties=m.model_properties,
+                        deprecated=m.deprecated,
                         provider=SimpleModelProviderEntity(self.provider),
                         status=ModelStatus.ACTIVE if credentials else ModelStatus.NO_CONFIGURE
                     )
@@ -544,20 +592,30 @@ class ProviderConfiguration(BaseModel):
             if model_configuration.model_type not in model_types:
                 continue
 
-            custom_model_schema = (
-                provider_instance.get_model_instance(model_configuration.model_type)
-                .get_customizable_model_schema_from_credentials(
-                    model_configuration.model,
-                    model_configuration.credentials
+            try:
+                custom_model_schema = (
+                    provider_instance.get_model_instance(model_configuration.model_type)
+                    .get_customizable_model_schema_from_credentials(
+                        model_configuration.model,
+                        model_configuration.credentials
+                    )
                 )
-            )
+            except Exception as ex:
+                logger.warning(f'get custom model schema failed, {ex}')
+                continue
 
             if not custom_model_schema:
                 continue
 
             provider_models.append(
                 ModelWithProviderEntity(
-                    **custom_model_schema.dict(),
+                    model=custom_model_schema.model,
+                    label=custom_model_schema.label,
+                    model_type=custom_model_schema.model_type,
+                    features=custom_model_schema.features,
+                    fetch_from=custom_model_schema.fetch_from,
+                    model_properties=custom_model_schema.model_properties,
+                    deprecated=custom_model_schema.deprecated,
                     provider=SimpleModelProviderEntity(self.provider),
                     status=ModelStatus.ACTIVE
                 )

api/core/extension/extensible.py

@@ -61,7 +61,7 @@ class Extensible:
 
                     builtin_file_path = os.path.join(subdir_path, '__builtin__')
                     if os.path.exists(builtin_file_path):
-                        with open(builtin_file_path, 'r') as f:
+                        with open(builtin_file_path, 'r', encoding='utf-8') as f:
                             position = int(f.read().strip())
 
                 if (extension_name + '.py') not in file_names:
@@ -93,7 +93,7 @@ class Extensible:
                     json_path = os.path.join(subdir_path, 'schema.json')
                     json_data = {}
                     if os.path.exists(json_path):
-                        with open(json_path, 'r') as f:
+                        with open(json_path, 'r', encoding='utf-8') as f:
                             json_data = json.load(f)
 
                 extensions[extension_name] = ModuleExtension(

api/core/external_data_tool/api/api.py

@@ -58,7 +58,7 @@ class ApiExternalDataTool(ExternalDataTool):
         if not api_based_extension:
             raise ValueError("[External data tool] API query failed, variable: {}, "
                              "error: api_based_extension_id is invalid"
-                             .format(self.config.get('variable')))
+                             .format(self.variable))
 
         # decrypt api_key
         api_key = encrypter.decrypt_token(
@@ -74,7 +74,7 @@ class ApiExternalDataTool(ExternalDataTool):
             )
         except Exception as e:
             raise ValueError("[External data tool] API query failed, variable: {}, error: {}".format(
-                self.config.get('variable'),
+                self.variable,
                 e
             ))
 
@@ -87,6 +87,10 @@ class ApiExternalDataTool(ExternalDataTool):
 
         if 'result' not in response_json:
             raise ValueError("[External data tool] API query failed, variable: {}, error: result not found in response"
-                             .format(self.config.get('variable')))
+                             .format(self.variable))
+
+        if not isinstance(response_json['result'], str):
+            raise ValueError("[External data tool] API query failed, variable: {}, error: result is not string"
+                             .format(self.variable))
 
         return response_json['result']

api/core/external_data_tool/weather_search/schema.json

@@ -1,35 +0,0 @@
-{
-    "label": {
-        "en-US": "Weather Search",
-        "zh-Hans": "天气查询"
-    },
-    "form_schema": [
-        {
-            "type": "select",
-            "label": {
-                "en-US": "Temperature Unit",
-                "zh-Hans": "温度单位"
-            },
-            "variable": "temperature_unit",
-            "required": true,
-            "options": [
-                {
-                    "label": {
-                        "en-US": "Fahrenheit",
-                        "zh-Hans": "华氏度"
-                    },
-                    "value": "fahrenheit"
-                },
-                {
-                    "label": {
-                        "en-US": "Centigrade",
-                        "zh-Hans": "摄氏度"
-                    },
-                    "value": "centigrade"
-                }
-            ],
-            "default": "centigrade",
-            "placeholder": "Please select temperature unit"
-        }
-    ]
-}

api/core/external_data_tool/weather_search/weather_search.py

@@ -1,45 +0,0 @@
-from typing import Optional
-
-from core.external_data_tool.base import ExternalDataTool
-
-
-class WeatherSearch(ExternalDataTool):
-    """
-    The name of custom type must be unique, keep the same with directory and file name.
-    """
-    name: str = "weather_search"
-
-    @classmethod
-    def validate_config(cls, tenant_id: str, config: dict) -> None:
-        """
-        schema.json validation. It will be called when user save the config.
-
-        Example:
-            .. code-block:: python
-                config = {
-                    "temperature_unit": "centigrade"
-                }
-
-        :param tenant_id: the id of workspace
-        :param config: the variables of form config
-        :return:
-        """
-
-        if not config.get('temperature_unit'):
-            raise ValueError('temperature unit is required')
-
-    def query(self, inputs: dict, query: Optional[str] = None) -> str:
-        """
-        Query the external data tool.
-
-        :param inputs: user inputs
-        :param query: the query of chat app
-        :return: the tool query result
-        """
-        city = inputs.get('city')
-        temperature_unit = self.config.get('temperature_unit')
-
-        if temperature_unit == 'fahrenheit':
-            return f'Weather in {city} is 32°F'
-        else:
-            return f'Weather in {city} is 0°C'

api/core/helper/model_provider_cache.py

@@ -0,0 +1,51 @@
+import json
+from enum import Enum
+from json import JSONDecodeError
+from typing import Optional
+
+from extensions.ext_redis import redis_client
+
+
+class ProviderCredentialsCacheType(Enum):
+    PROVIDER = "provider"
+    MODEL = "provider_model"
+
+
+class ProviderCredentialsCache:
+    def __init__(self, tenant_id: str, identity_id: str, cache_type: ProviderCredentialsCacheType):
+        self.cache_key = f"{cache_type.value}_credentials:tenant_id:{tenant_id}:id:{identity_id}"
+
+    def get(self) -> Optional[dict]:
+        """
+        Get cached model provider credentials.
+
+        :return:
+        """
+        cached_provider_credentials = redis_client.get(self.cache_key)
+        if cached_provider_credentials:
+            try:
+                cached_provider_credentials = cached_provider_credentials.decode('utf-8')
+                cached_provider_credentials = json.loads(cached_provider_credentials)
+            except JSONDecodeError:
+                return None
+
+            return cached_provider_credentials
+        else:
+            return None
+
+    def set(self, credentials: dict) -> None:
+        """
+        Cache model provider credentials.
+
+        :param credentials: provider credentials
+        :return:
+        """
+        redis_client.setex(self.cache_key, 86400, json.dumps(credentials))
+
+    def delete(self) -> None:
+        """
+        Delete cached model provider credentials.
+
+        :return:
+        """
+        redis_client.delete(self.cache_key)

api/core/indexing_runner.py

@@ -59,7 +59,7 @@ class IndexingRunner:
                     first()
 
                 # load file
-                text_docs = self._load_data(dataset_document)
+                text_docs = self._load_data(dataset_document, processing_rule.mode == 'automatic')
 
                 # get splitter
                 splitter = self._get_splitter(processing_rule)
@@ -113,15 +113,14 @@ class IndexingRunner:
             for document_segment in document_segments:
                 db.session.delete(document_segment)
             db.session.commit()
-
-            # load file
-            text_docs = self._load_data(dataset_document)
-
             # get the process rule
             processing_rule = db.session.query(DatasetProcessRule). \
                 filter(DatasetProcessRule.id == dataset_document.dataset_process_rule_id). \
                 first()
 
+            # load file
+            text_docs = self._load_data(dataset_document, processing_rule.mode == 'automatic')
+
             # get splitter
             splitter = self._get_splitter(processing_rule)
 
@@ -238,14 +237,15 @@ class IndexingRunner:
         preview_texts = []
         total_segments = 0
         for file_detail in file_details:
-            # load data from file
-            text_docs = FileExtractor.load(file_detail)
 
             processing_rule = DatasetProcessRule(
                 mode=tmp_processing_rule["mode"],
                 rules=json.dumps(tmp_processing_rule["rules"])
             )
 
+            # load data from file
+            text_docs = FileExtractor.load(file_detail, is_automatic=processing_rule.mode == 'automatic')
+
             # get splitter
             splitter = self._get_splitter(processing_rule)
 
@@ -382,13 +382,15 @@ class IndexingRunner:
                 )
                 total_segments += len(documents)
 
-                embedding_model_type_instance = embedding_model_instance.model_type_instance
-                embedding_model_type_instance = cast(TextEmbeddingModel, embedding_model_type_instance)
+                embedding_model_type_instance = None
+                if embedding_model_instance:
+                    embedding_model_type_instance = embedding_model_instance.model_type_instance
+                    embedding_model_type_instance = cast(TextEmbeddingModel, embedding_model_type_instance)
 
                 for document in documents:
                     if len(preview_texts) < 5:
                         preview_texts.append(document.page_content)
-                    if indexing_technique == 'high_quality' or embedding_model_instance:
+                    if indexing_technique == 'high_quality' and embedding_model_type_instance:
                         tokens += embedding_model_type_instance.get_num_tokens(
                             model=embedding_model_instance.model,
                             credentials=embedding_model_instance.credentials,
@@ -457,7 +459,7 @@ class IndexingRunner:
                 one_or_none()
 
             if file_detail:
-                text_docs = FileExtractor.load(file_detail, is_automatic=True)
+                text_docs = FileExtractor.load(file_detail, is_automatic=automatic)
         elif dataset_document.data_source_type == 'notion_import':
             loader = NotionLoader.from_document(dataset_document)
             text_docs = loader.load()

api/core/model_runtime/errors/invoke.py

@@ -8,6 +8,9 @@ class InvokeError(Exception):
     def __init__(self, description: Optional[str] = None) -> None:
         self.description = description
 
+    def __str__(self):
+        return self.description or self.__class__.__name__
+
 
 class InvokeConnectionError(InvokeError):
     """Raised when the Invoke returns connection error."""

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

@@ -147,13 +147,15 @@ class AIModel(ABC):
         # read _position.yaml file
         position_map = {}
         if os.path.exists(position_file_path):
-            with open(position_file_path, 'r') as f:
-                position_map = yaml.safe_load(f)
+            with open(position_file_path, 'r', encoding='utf-8') as f:
+                positions = yaml.safe_load(f)
+                # convert list to dict with key as model provider name, value as index
+                position_map = {position: index for index, position in enumerate(positions)}
 
         # traverse all model_schema_yaml_paths
         for model_schema_yaml_path in model_schema_yaml_paths:
             # read yaml data from yaml file
-            with open(model_schema_yaml_path, 'r') as f:
+            with open(model_schema_yaml_path, 'r', encoding='utf-8') as f:
                 yaml_data = yaml.safe_load(f)
 
             new_parameter_rules = []
@@ -236,16 +238,6 @@ class AIModel(ABC):
         :param credentials: model credentials
         :return: model schema
         """
-        if 'schema' in credentials:
-            schema_dict = json.loads(credentials['schema'])
-
-            try:
-                model_instance = AIModelEntity.parse_obj(schema_dict)
-                return model_instance
-            except ValidationError as e:
-                logging.exception(f"Invalid model schema for {model}")
-                return self._get_customizable_model_schema(model, credentials)
-
         return self._get_customizable_model_schema(model, credentials)
     
     def _get_customizable_model_schema(self, model: str, credentials: dict) -> Optional[AIModelEntity]:

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

@@ -165,7 +165,7 @@ class LargeLanguageModel(AIModel):
                 model=real_model,
                 prompt_messages=prompt_messages,
                 message=prompt_message,
-                usage=usage,
+                usage=usage if usage else LLMUsage.empty_usage(),
                 system_fingerprint=system_fingerprint
             ),
             credentials=credentials,

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

@@ -47,7 +47,7 @@ class ModelProvider(ABC):
         yaml_path = os.path.join(current_path, f'{provider_name}.yaml')
         yaml_data = {}
         if os.path.exists(yaml_path):
-            with open(yaml_path, 'r') as f:
+            with open(yaml_path, 'r', encoding='utf-8') as f:
                 yaml_data = yaml.safe_load(f)
 
         try:
@@ -112,7 +112,7 @@ class ModelProvider(ABC):
         model_class = None
         for name, obj in vars(mod).items():
             if (isinstance(obj, type) and issubclass(obj, AIModel) and not obj.__abstractmethods__
-                    and obj != AIModel):
+                    and obj != AIModel and obj.__module__ == mod.__name__):
                 model_class = obj
                 break
 

api/core/model_runtime/model_providers/_position.yaml

@@ -1,19 +1,20 @@
-openai: 0
-anthropic: 1
-azure_openai: 2
-google: 3
-replicate: 4
-huggingface_hub: 5
-cohere: 6
-zhipuai: 7
-baichuan: 8
-spark: 9
-minimax: 10
-tongyi: 11
-wenxin: 12
-jina: 13
-chatglm: 14
-xinference: 15
-openllm: 16
-localai: 17
-openai_api_compatible: 18
+- openai
+- anthropic
+- azure_openai
+- google
+- replicate
+- huggingface_hub
+- cohere
+- togetherai
+- zhipuai
+- baichuan
+- spark
+- minimax
+- tongyi
+- wenxin
+- jina
+- chatglm
+- xinference
+- openllm
+- localai
+- openai_api_compatible

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

@@ -309,7 +309,7 @@ class AzureOpenAILargeLanguageModel(_CommonAzureOpenAI, LargeLanguageModel):
 
         # transform response
         response = LLMResult(
-            model=response.model,
+            model=response.model or model,
             prompt_messages=prompt_messages,
             message=assistant_prompt_message,
             usage=usage,

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

@@ -54,7 +54,7 @@ class AzureOpenAITextEmbeddingModel(_CommonAzureOpenAI, TextEmbeddingModel):
         _iter = range(0, len(tokens), max_chunks)
 
         for i in _iter:
-            embeddings, embedding_used_tokens = self._embedding_invoke(
+            embeddings_batch, embedding_used_tokens = self._embedding_invoke(
                 model=model,
                 client=client,
                 texts=tokens[i: i + max_chunks],
@@ -62,7 +62,7 @@ class AzureOpenAITextEmbeddingModel(_CommonAzureOpenAI, TextEmbeddingModel):
             )
 
             used_tokens += embedding_used_tokens
-            batched_embeddings += [data for data in embeddings]
+            batched_embeddings += embeddings_batch
 
         results: list[list[list[float]]] = [[] for _ in range(len(texts))]
         num_tokens_in_batch: list[list[int]] = [[] for _ in range(len(texts))]
@@ -73,7 +73,7 @@ class AzureOpenAITextEmbeddingModel(_CommonAzureOpenAI, TextEmbeddingModel):
         for i in range(len(texts)):
             _result = results[i]
             if len(_result) == 0:
-                embeddings, embedding_used_tokens = self._embedding_invoke(
+                embeddings_batch, embedding_used_tokens = self._embedding_invoke(
                     model=model,
                     client=client,
                     texts=[""],
@@ -81,7 +81,7 @@ class AzureOpenAITextEmbeddingModel(_CommonAzureOpenAI, TextEmbeddingModel):
                 )
 
                 used_tokens += embedding_used_tokens
-                average = embeddings[0]
+                average = embeddings_batch[0]
             else:
                 average = np.average(_result, axis=0, weights=num_tokens_in_batch[i])
             embeddings[i] = (average / np.linalg.norm(average)).tolist()

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

@@ -1,7 +1,7 @@
 from typing import Generator, List, Optional, Union, cast
 from core.model_runtime.entities.llm_entities import LLMResult, LLMUsage, LLMResultChunk, LLMResultChunkDelta, LLMMode
 from core.model_runtime.entities.message_entities import PromptMessage, PromptMessageTool, AssistantPromptMessage, UserPromptMessage, SystemPromptMessage
-from core.model_runtime.entities.model_entities import AIModelEntity, ParameterRule, ParameterType, FetchFrom, ModelType
+from core.model_runtime.entities.model_entities import AIModelEntity, ParameterRule, ParameterType, FetchFrom, ModelType, ModelPropertyKey
 from core.model_runtime.entities.common_entities import I18nObject
 from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel
 from core.model_runtime.errors.invoke import InvokeConnectionError, InvokeServerUnavailableError, InvokeRateLimitError, \
@@ -156,9 +156,9 @@ class LocalAILarguageModel(LargeLanguageModel):
     def get_customizable_model_schema(self, model: str, credentials: dict) -> AIModelEntity | None:
         completion_model = None
         if credentials['completion_type'] == 'chat_completion':
-            completion_model = LLMMode.CHAT
+            completion_model = LLMMode.CHAT.value
         elif credentials['completion_type'] == 'completion':
-            completion_model = LLMMode.COMPLETION
+            completion_model = LLMMode.COMPLETION.value
         else:
             raise ValueError(f"Unknown completion type {credentials['completion_type']}")
             
@@ -202,7 +202,7 @@ class LocalAILarguageModel(LargeLanguageModel):
             ),
             fetch_from=FetchFrom.CUSTOMIZABLE_MODEL,
             model_type=ModelType.LLM,
-            model_properties={ 'mode': completion_model } if completion_model else {},
+            model_properties={ ModelPropertyKey.MODE: completion_model } if completion_model else {},
             parameter_rules=rules
         )
 

api/core/model_runtime/model_providers/model_provider_factory.py

@@ -30,6 +30,10 @@ class ModelProviderExtension(BaseModel):
 class ModelProviderFactory:
     model_provider_extensions: dict[str, ModelProviderExtension] = None
 
+    def __init__(self) -> None:
+        # for cache in memory
+        self.get_providers()
+
     def get_providers(self) -> list[ProviderEntity]:
         """
         Get all providers
@@ -212,8 +216,10 @@ class ModelProviderFactory:
         # read _position.yaml file
         position_map = {}
         if os.path.exists(position_file_path):
-            with open(position_file_path, 'r') as f:
-                position_map = yaml.safe_load(f)
+            with open(position_file_path, 'r', encoding='utf-8') as f:
+                positions = yaml.safe_load(f)
+                # convert list to dict with key as model provider name, value as index
+                position_map = {position: index for index, position in enumerate(positions)}
 
         # traverse all model_provider_dir_paths
         for model_provider_dir_path in model_provider_dir_paths:

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

@@ -1,9 +1,11 @@
-gpt-4: 0
-gpt-4-32k: 1
-gpt-4-1106-preview: 2
-gpt-4-vision-preview: 3
-gpt-3.5-turbo: 4
-gpt-3.5-turbo-16k: 5
-gpt-3.5-turbo-1106: 6
-gpt-3.5-turbo-instruct: 7
-text-davinci-003: 8
+- gpt-4
+- gpt-4-32k
+- gpt-4-1106-preview
+- gpt-4-vision-preview
+- gpt-3.5-turbo
+- gpt-3.5-turbo-16k
+- gpt-3.5-turbo-16k-0613
+- gpt-3.5-turbo-1106
+- gpt-3.5-turbo-0613
+- gpt-3.5-turbo-instruct
+- text-davinci-003

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

@@ -40,87 +40,4 @@ class _CommonOAI_API_Compat:
                 requests.exceptions.ConnectTimeout,  # Timeout
                 requests.exceptions.ReadTimeout  # Timeout
             ]
-        }
-
-    def get_customizable_model_schema(self, model: str, credentials: dict) -> AIModelEntity:
-        """
-            generate custom model entities from credentials
-        """
-        model_type = ModelType.LLM if credentials.get('__model_type') == 'llm' else ModelType.TEXT_EMBEDDING
-        
-        entity = AIModelEntity(
-            model=model,
-            label=I18nObject(en_US=model),
-            model_type=model_type,
-            fetch_from=FetchFrom.CUSTOMIZABLE_MODEL,
-            model_properties={
-                ModelPropertyKey.CONTEXT_SIZE: credentials.get('context_size', 16000),
-                ModelPropertyKey.MAX_CHUNKS: credentials.get('max_chunks', 1),
-            },
-            parameter_rules=[
-                ParameterRule(
-                    name=DefaultParameterName.TEMPERATURE.value,
-                    label=I18nObject(en_US="Temperature"),
-                    type=ParameterType.FLOAT,
-                    default=float(credentials.get('temperature', 1)),
-                    min=0,
-                    max=2
-                ),
-                ParameterRule(
-                    name=DefaultParameterName.TOP_P.value,
-                    label=I18nObject(en_US="Top P"),
-                    type=ParameterType.FLOAT,
-                    default=float(credentials.get('top_p', 1)),
-                    min=0,
-                    max=1
-                ),
-                ParameterRule(
-                    name="top_k",
-                    label=I18nObject(en_US="Top K"),
-                    type=ParameterType.INT,
-                    default=int(credentials.get('top_k', 1)),
-                    min=1,
-                    max=100
-                ),
-                ParameterRule(
-                    name=DefaultParameterName.FREQUENCY_PENALTY.value,
-                    label=I18nObject(en_US="Frequency Penalty"),
-                    type=ParameterType.FLOAT,
-                    default=float(credentials.get('frequency_penalty', 0)),
-                    min=-2,
-                    max=2
-                ),
-                ParameterRule(
-                    name=DefaultParameterName.PRESENCE_PENALTY.value,
-                    label=I18nObject(en_US="PRESENCE Penalty"),
-                    type=ParameterType.FLOAT,
-                    default=float(credentials.get('PRESENCE_penalty', 0)),
-                    min=-2,
-                    max=2
-                ),
-                ParameterRule(
-                    name=DefaultParameterName.MAX_TOKENS.value,
-                    label=I18nObject(en_US="Max Tokens"),
-                    type=ParameterType.INT,
-                    default=1024,
-                    min=1,
-                    max=int(credentials.get('max_tokens_to_sample', 4096)),
-                )
-            ],
-            pricing=PriceConfig(
-                input=Decimal(credentials.get('input_price', 0)),
-                output=Decimal(credentials.get('output_price', 0)),
-                unit=Decimal(credentials.get('unit', 0)),
-                currency=credentials.get('currency', "USD")
-            )
-        )
-
-        if model_type == ModelType.LLM:
-            if credentials['mode'] == 'chat':
-                entity.model_properties[ModelPropertyKey.MODE] = LLMMode.CHAT
-            elif credentials['mode'] == 'completion':
-                entity.model_properties[ModelPropertyKey.MODE] = LLMMode.COMPLETION
-            else:
-                raise ValueError(f"Unknown completion type {credentials['completion_type']}")
-        
-        return entity
+        }

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

@@ -158,7 +158,7 @@ class OAIAPICompatLargeLanguageModel(_CommonOAI_API_Compat, LargeLanguageModel):
             model_type=ModelType.LLM,
             fetch_from=FetchFrom.CUSTOMIZABLE_MODEL,
             model_properties={
-                ModelPropertyKey.CONTEXT_SIZE: int(credentials.get('context_size')),
+                ModelPropertyKey.CONTEXT_SIZE: int(credentials.get('context_size', "4096")),
                 ModelPropertyKey.MODE: credentials.get('mode'),
             },
             parameter_rules=[
@@ -196,9 +196,9 @@ class OAIAPICompatLargeLanguageModel(_CommonOAI_API_Compat, LargeLanguageModel):
                 ),
                 ParameterRule(
                     name=DefaultParameterName.PRESENCE_PENALTY.value,
-                    label=I18nObject(en_US="PRESENCE Penalty"),
+                    label=I18nObject(en_US="Presence Penalty"),
                     type=ParameterType.FLOAT,
-                    default=float(credentials.get('PRESENCE_penalty', 0)),
+                    default=float(credentials.get('presence_penalty', 0)),
                     min=-2,
                     max=2
                 ),
@@ -219,6 +219,13 @@ class OAIAPICompatLargeLanguageModel(_CommonOAI_API_Compat, LargeLanguageModel):
             )
         )
 
+        if credentials['mode'] == 'chat':
+            entity.model_properties[ModelPropertyKey.MODE] = LLMMode.CHAT.value
+        elif credentials['mode'] == 'completion':
+            entity.model_properties[ModelPropertyKey.MODE] = LLMMode.COMPLETION.value
+        else:
+            raise ValueError(f"Unknown completion type {credentials['completion_type']}")
+    
         return entity
 
     # validate_credentials method has been rewritten to use the requests library for compatibility with all providers following OpenAI's API standard.
@@ -261,7 +268,7 @@ class OAIAPICompatLargeLanguageModel(_CommonOAI_API_Compat, LargeLanguageModel):
         if completion_type is LLMMode.CHAT:
             endpoint_url = urljoin(endpoint_url, 'chat/completions')
             data['messages'] = [self._convert_prompt_message_to_dict(m) for m in prompt_messages]
-        elif completion_type == LLMMode.COMPLETION:
+        elif completion_type is LLMMode.COMPLETION:
             endpoint_url = urljoin(endpoint_url, 'completions')
             data['prompt'] = prompt_messages[0].content
         else:
@@ -291,10 +298,6 @@ class OAIAPICompatLargeLanguageModel(_CommonOAI_API_Compat, LargeLanguageModel):
             stream=stream
         )
 
-        # Debug: Print request headers and json data
-        logger.debug(f"Request headers: {headers}")
-        logger.debug(f"Request JSON data: {data}")
-
         if response.status_code != 200:
             raise InvokeError(f"API request failed with status code {response.status_code}: {response.text}")
 
@@ -337,9 +340,9 @@ class OAIAPICompatLargeLanguageModel(_CommonOAI_API_Compat, LargeLanguageModel):
                 )
             )
 
-        for chunk in response.iter_content(chunk_size=2048):
+        for chunk in response.iter_lines(decode_unicode=True, delimiter='\n\n'):
             if chunk:
-                decoded_chunk = chunk.decode('utf-8').strip().lstrip('data: ').lstrip()
+                decoded_chunk = chunk.strip().lstrip('data: ').lstrip()
 
                 chunk_json = None
                 try:
@@ -356,7 +359,7 @@ class OAIAPICompatLargeLanguageModel(_CommonOAI_API_Compat, LargeLanguageModel):
                     continue
 
                 choice = chunk_json['choices'][0]
-                chunk_index = choice['index'] if 'index' in choice else chunk_index
+                chunk_index += 1
 
                 if 'delta' in choice:
                     delta = choice['delta']
@@ -408,12 +411,6 @@ class OAIAPICompatLargeLanguageModel(_CommonOAI_API_Compat, LargeLanguageModel):
                             message=assistant_prompt_message,
                         )
                     )
-            else:
-                yield create_final_llm_result_chunk(
-                    index=chunk_index + 1,
-                    message=AssistantPromptMessage(content=""),
-                    finish_reason="End of stream."
-                )
 
             chunk_index += 1
 

api/core/model_runtime/model_providers/openai_api_compatible/openai_api_compatible.yaml

@@ -2,8 +2,8 @@ provider: openai_api_compatible
 label:
   en_US: OpenAI-API-compatible
 description:
-  en_US: All model providers compatible with OpenAI's API standard, such as Together.ai.
-  zh_Hans: 兼容 OpenAI API 的模型供应商，例如 Together.ai。
+  en_US: Model providers compatible with OpenAI's API standard, such as LM Studio.
+  zh_Hans: 兼容 OpenAI API 的模型供应商，例如 LM Studio 。
 supported_model_types:
 - llm
 - text-embedding

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

@@ -112,7 +112,7 @@ class OAICompatEmbeddingModel(_CommonOAI_API_Compat, TextEmbeddingModel):
             credentials=credentials,
             tokens=used_tokens
         )
-
+        
         return TextEmbeddingResult(
             embeddings=batched_embeddings,
             usage=usage,

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

@@ -6,7 +6,7 @@ from core.model_runtime.model_providers.openllm.llm.openllm_generate import Open
 from core.model_runtime.entities.llm_entities import LLMResult, LLMUsage, LLMResultChunk, LLMResultChunkDelta, LLMMode
 from core.model_runtime.entities.common_entities import I18nObject
 from core.model_runtime.entities.message_entities import PromptMessage, PromptMessageTool, AssistantPromptMessage, UserPromptMessage, SystemPromptMessage
-from core.model_runtime.entities.model_entities import AIModelEntity, ParameterRule, ParameterType, FetchFrom, ModelType
+from core.model_runtime.entities.model_entities import AIModelEntity, ParameterRule, ParameterType, FetchFrom, ModelType, ModelPropertyKey
 from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel
 from core.model_runtime.errors.invoke import InvokeConnectionError, InvokeServerUnavailableError, InvokeRateLimitError, \
     InvokeAuthorizationError, InvokeBadRequestError, InvokeError
@@ -198,7 +198,7 @@ class OpenLLMLargeLanguageModel(LargeLanguageModel):
             fetch_from=FetchFrom.CUSTOMIZABLE_MODEL,
             model_type=ModelType.LLM,
             model_properties={ 
-                'mode':  LLMMode.COMPLETION,
+                ModelPropertyKey.MODE: LLMMode.COMPLETION.value,
             },
             parameter_rules=rules
         )

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

@@ -8,7 +8,7 @@ from core.model_runtime.entities.common_entities import I18nObject
 from core.model_runtime.entities.llm_entities import LLMResult, LLMMode, LLMResultChunk, LLMResultChunkDelta
 from core.model_runtime.entities.message_entities import PromptMessage, PromptMessageTool, AssistantPromptMessage, \
     PromptMessageRole, UserPromptMessage, SystemPromptMessage
-from core.model_runtime.entities.model_entities import ParameterRule, AIModelEntity, FetchFrom, ModelType
+from core.model_runtime.entities.model_entities import ParameterRule, AIModelEntity, FetchFrom, ModelType, ModelPropertyKey
 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.replicate._common import _CommonReplicate
@@ -91,7 +91,7 @@ class ReplicateLargeLanguageModel(_CommonReplicate, LargeLanguageModel):
             fetch_from=FetchFrom.CUSTOMIZABLE_MODEL,
             model_type=ModelType.LLM,
             model_properties={
-                'mode': model_type.value
+                ModelPropertyKey.MODE: model_type.value
             },
             parameter_rules=self._get_customizable_model_parameter_rules(model, credentials)
         )

api/core/model_runtime/model_providers/spark/spark.py

@@ -19,13 +19,23 @@ class SparkProvider(ModelProvider):
         try:
             model_instance = self.get_model_instance(ModelType.LLM)
 
-            # Use `claude-instant-1` model for validate,
             model_instance.validate_credentials(
                 model='spark-1.5',
                 credentials=credentials
             )
         except CredentialsValidateFailedError as ex:
-            raise ex
+            try:
+                model_instance = self.get_model_instance(ModelType.LLM)
+
+                model_instance.validate_credentials(
+                    model='spark-3',
+                    credentials=credentials
+                )
+            except CredentialsValidateFailedError as ex:
+                raise ex
+            except Exception as ex:
+                logger.exception(f'{self.get_provider_schema().provider} credentials validate failed')
+                raise ex
         except Exception as ex:
             logger.exception(f'{self.get_provider_schema().provider} credentials validate failed')
             raise ex

api/core/model_runtime/model_providers/togetherai/_assets/togetherai.svg

@@ -0,0 +1,13 @@
+<svg width="114" height="24" viewBox="0 0 114 24" fill="none" xmlns="http://www.w3.org/2000/svg">
+<path d="M3.21688 7.55431H1V5.74708H3.21688V2.30127H5.19279V5.74708H8.30124V7.55431H5.19279V14.8074C5.19279 15.3214 5.28918 15.6909 5.48195 15.9158C5.69079 16.1246 6.0442 16.2291 6.5422 16.2291H8.68679V18.0363H6.42171C5.26507 18.0363 4.43776 17.7792 3.93977 17.2652C3.45784 16.7511 3.21688 15.9398 3.21688 14.8314V7.55431Z" fill="black"/>
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+</svg>

api/core/model_runtime/model_providers/togetherai/_assets/togetherai_square.svg

@@ -0,0 +1,19 @@
+<svg width="16" height="16" viewBox="0 0 16 16" fill="none" xmlns="http://www.w3.org/2000/svg">
+<g clip-path="url(#clip0_15960_46917)">
+<mask id="mask0_15960_46917" style="mask-type:luminance" maskUnits="userSpaceOnUse" x="0" y="0" width="16" height="16">
+<path d="M16 0H0V16H16V0Z" fill="white"/>
+</mask>
+<g mask="url(#mask0_15960_46917)">
+<path d="M13.1765 0H2.82353C1.26414 0 0 1.26414 0 2.82353V13.1765C0 14.7359 1.26414 16 2.82353 16H13.1765C14.7359 16 16 14.7359 16 13.1765V2.82353C16 1.26414 14.7359 0 13.1765 0Z" fill="#F1EFED"/>
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+<defs>
+<clipPath id="clip0_15960_46917">
+<rect width="16" height="16" fill="white"/>
+</clipPath>
+</defs>
+</svg>

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

@@ -0,0 +1,45 @@
+from typing import Generator, List, Optional, Union
+from core.model_runtime.entities.llm_entities import LLMResult
+from core.model_runtime.entities.message_entities import PromptMessage, PromptMessageTool
+from core.model_runtime.entities.model_entities import AIModelEntity
+from core.model_runtime.model_providers.openai_api_compatible.llm.llm import OAIAPICompatLargeLanguageModel
+
+class TogetherAILargeLanguageModel(OAIAPICompatLargeLanguageModel):
+
+    def _update_endpoint_url(self, credentials: dict):
+        credentials['endpoint_url'] = "https://api.together.xyz/v1"
+        return credentials
+
+    def _invoke(self, model: str, credentials: dict,
+                prompt_messages: list[PromptMessage], model_parameters: dict,
+                tools: Optional[list[PromptMessageTool]] = None, stop: Optional[List[str]] = None,
+                stream: bool = True, user: Optional[str] = None) \
+            -> Union[LLMResult, Generator]:
+        cred_with_endpoint = self._update_endpoint_url(credentials=credentials)
+
+        return super()._invoke(model, cred_with_endpoint, prompt_messages, model_parameters, tools, stop, stream, user)
+
+    def validate_credentials(self, model: str, credentials: dict) -> None:
+        cred_with_endpoint = self._update_endpoint_url(credentials=credentials)
+
+        return super().validate_credentials(model, cred_with_endpoint)
+
+    def _generate(self, model: str, credentials: dict, prompt_messages: list[PromptMessage], model_parameters: dict,
+                  tools: Optional[list[PromptMessageTool]] = None, stop: Optional[List[str]] = None,
+                  stream: bool = True, user: Optional[str] = None) -> Union[LLMResult, Generator]:
+        cred_with_endpoint = self._update_endpoint_url(credentials=credentials)
+
+        return super()._generate(model, cred_with_endpoint, prompt_messages, model_parameters, tools, stop, stream, user)
+
+    def get_customizable_model_schema(self, model: str, credentials: dict) -> AIModelEntity:
+        cred_with_endpoint = self._update_endpoint_url(credentials=credentials)
+
+        return super().get_customizable_model_schema(model, cred_with_endpoint)
+
+    def get_num_tokens(self, model: str, credentials: dict, prompt_messages: list[PromptMessage],
+                       tools: Optional[list[PromptMessageTool]] = None) -> int:
+        cred_with_endpoint = self._update_endpoint_url(credentials=credentials)
+
+        return super().get_num_tokens(model, cred_with_endpoint, prompt_messages, tools)
+
+

api/core/model_runtime/model_providers/togetherai/togetherai.py

@@ -0,0 +1,13 @@
+import logging
+
+from core.model_runtime.entities.model_entities import ModelType
+from core.model_runtime.errors.validate import CredentialsValidateFailedError
+from core.model_runtime.model_providers.__base.model_provider import ModelProvider
+
+logger = logging.getLogger(__name__)
+
+
+class TogetherAIProvider(ModelProvider):
+
+    def validate_provider_credentials(self, credentials: dict) -> None:
+        pass

api/core/model_runtime/model_providers/togetherai/togetherai.yaml

@@ -0,0 +1,75 @@
+provider: togetherai
+label:
+  en_US: together.ai
+icon_small:
+    en_US: togetherai_square.svg
+icon_large:
+    en_US: togetherai.svg
+background: "#F1EFED"
+help:
+  title:
+    en_US: Get your API key from together.ai
+    zh_Hans: 从 together.ai 获取 API Key
+  url:
+    en_US: https://api.together.xyz/
+supported_model_types:
+- llm
+configurate_methods:
+- customizable-model
+model_credential_schema:
+  model:
+    label:
+      en_US: Model Name
+      zh_Hans: 模型名称
+    placeholder:
+      en_US: Enter full model name   
+      zh_Hans: 输入模型全称
+  credential_form_schemas:
+  - variable: api_key
+    required: true
+    label:
+      en_US: API Key
+    type: secret-input
+    placeholder:
+      zh_Hans: 在此输入您的 API Key
+      en_US: Enter your API Key
+  - variable: mode
+    show_on:
+      - variable: __model_type
+        value: llm
+    label:
+      en_US: Completion mode
+    type: select
+    required: false
+    default: chat
+    placeholder:
+      zh_Hans: 选择对话类型
+      en_US: Select completion mode
+    options:
+      - value: completion
+        label:
+          en_US: Completion
+          zh_Hans: 补全
+      - value: chat
+        label:
+          en_US: Chat
+          zh_Hans: 对话
+  - 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_to_sample
+    label:
+      zh_Hans: 最大 token 上限
+      en_US: Upper bound for max tokens
+    show_on:
+    - variable: __model_type
+      value: llm
+    default: '4096'
+    type: text-input

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

@@ -52,9 +52,13 @@ class TongyiLargeLanguageModel(LargeLanguageModel):
         :param tools: tools for tool calling
         :return:
         """
+        # transform credentials to kwargs for model instance
+        credentials_kwargs = self._to_credential_kwargs(credentials)
+
         response = dashscope.Tokenization.call(
             model=model,
             prompt=self._convert_messages_to_prompt(prompt_messages),
+            **credentials_kwargs
         )
         
         if response.status_code == HTTPStatus.OK:
@@ -108,10 +112,6 @@ class TongyiLargeLanguageModel(LargeLanguageModel):
         # transform credentials to kwargs for model instance
         credentials_kwargs = self._to_credential_kwargs(credentials)
 
-        dashscope.api_key = credentials_kwargs['api_key']
-
-        print(credentials_kwargs, 'credentials_kwargs')
-
         client = EnhanceTongyi(
             model_name=model,
             streaming=stream,
@@ -121,7 +121,8 @@ class TongyiLargeLanguageModel(LargeLanguageModel):
         params = {
             'model': model,
             'prompt': self._convert_messages_to_prompt(prompt_messages),
-            **model_parameters
+            **model_parameters,
+            **credentials_kwargs
         }
         if stream:
             responses = stream_generate_with_retry(
@@ -222,7 +223,6 @@ class TongyiLargeLanguageModel(LargeLanguageModel):
         :param credentials:
         :return:
         """
-        print(credentials, 'credentials')
         credentials_kwargs = {
             "api_key": credentials['dashscope_api_key'],
         }

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

@@ -18,7 +18,7 @@ from core.model_runtime.model_providers.__base.large_language_model import Large
 from core.model_runtime.entities.llm_entities import LLMMode, LLMResult, LLMResultChunk, LLMResultChunkDelta
 from core.model_runtime.entities.message_entities import PromptMessage, PromptMessageTool, UserPromptMessage, SystemPromptMessage, AssistantPromptMessage
 from core.model_runtime.entities.common_entities import I18nObject
-from core.model_runtime.entities.model_entities import FetchFrom, ModelType, ParameterRule, ParameterType
+from core.model_runtime.entities.model_entities import FetchFrom, ModelType, ParameterRule, ParameterType, ModelPropertyKey
 from core.model_runtime.errors.validate import CredentialsValidateFailedError
 from core.model_runtime.model_providers.xinference.llm.xinference_helper import XinferenceHelper, XinferenceModelExtraParameter
 from core.model_runtime.errors.invoke import InvokeConnectionError, InvokeServerUnavailableError, InvokeRateLimitError, \
@@ -56,10 +56,18 @@ class XinferenceAILargeLanguageModel(LargeLanguageModel):
             }
         """
         try:
-            XinferenceHelper.get_xinference_extra_parameter(
+            extra_param = XinferenceHelper.get_xinference_extra_parameter(
                 server_url=credentials['server_url'],
                 model_uid=credentials['model_uid']
             )
+            if 'completion_type' not in credentials:
+                if 'chat' in extra_param.model_ability:
+                    credentials['completion_type'] = 'chat'
+                elif 'generate' in extra_param.model_ability:
+                    credentials['completion_type'] = 'completion'
+                else:
+                    raise ValueError(f'xinference model ability {extra_param.model_ability} is not supported')
+
         except RuntimeError as e:
             raise CredentialsValidateFailedError(f'Xinference credentials validate failed: {e}')
         except KeyError as e:
@@ -256,17 +264,26 @@ class XinferenceAILargeLanguageModel(LargeLanguageModel):
         ]
 
         completion_type = None
-        extra_args = XinferenceHelper.get_xinference_extra_parameter(
-            server_url=credentials['server_url'],
-            model_uid=credentials['model_uid']
-        )
 
-        if 'chat' in extra_args.model_ability:
-            completion_type = LLMMode.CHAT
-        elif 'generate' in extra_args.model_ability:
-            completion_type = LLMMode.COMPLETION
+        if 'completion_type' in credentials:
+            if credentials['completion_type'] == 'chat':
+                completion_type = LLMMode.CHAT.value
+            elif credentials['completion_type'] == 'completion':
+                completion_type = LLMMode.COMPLETION.value
+            else:
+                raise ValueError(f'completion_type {credentials["completion_type"]} is not supported')
         else:
-            raise NotImplementedError(f'xinference model ability {extra_args.model_ability} is not supported')
+            extra_args = XinferenceHelper.get_xinference_extra_parameter(
+                server_url=credentials['server_url'],
+                model_uid=credentials['model_uid']
+            )
+
+            if 'chat' in extra_args.model_ability:
+                completion_type = LLMMode.CHAT.value
+            elif 'generate' in extra_args.model_ability:
+                completion_type = LLMMode.COMPLETION.value
+            else:
+                raise ValueError(f'xinference model ability {extra_args.model_ability} is not supported')
 
         entity = AIModelEntity(
             model=model,
@@ -276,7 +293,7 @@ class XinferenceAILargeLanguageModel(LargeLanguageModel):
             fetch_from=FetchFrom.CUSTOMIZABLE_MODEL,
             model_type=ModelType.LLM,
             model_properties={ 
-                'mode':  completion_type,
+                ModelPropertyKey.MODE: completion_type,
             },
             parameter_rules=rules
         )

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

@@ -8,8 +8,9 @@ from typing import (
     Union
 )
 
-from core.model_runtime.entities.message_entities import PromptMessage, PromptMessageTool, UserPromptMessage, AssistantPromptMessage, \
-    SystemPromptMessage
+from core.model_runtime.entities.message_entities import PromptMessage, PromptMessageTool, UserPromptMessage, \
+    AssistantPromptMessage, \
+    SystemPromptMessage, PromptMessageRole
 from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, \
     LLMResultChunkDelta
 from core.model_runtime.errors.validate import CredentialsValidateFailedError
@@ -111,16 +112,39 @@ class ZhipuAILargeLanguageModel(_CommonZhipuaiAI, LargeLanguageModel):
         if len(prompt_messages) == 0:
             raise ValueError('At least one message is required')
         
-        if prompt_messages[0].role.value == 'system':
+        if prompt_messages[0].role == PromptMessageRole.SYSTEM:
             if not prompt_messages[0].content:
                 prompt_messages = prompt_messages[1:]
 
+        # resolve zhipuai model not support system message and user message, assistant message must be in sequence
+        new_prompt_messages = []
+        for prompt_message in prompt_messages:
+            copy_prompt_message = prompt_message.copy()
+            if copy_prompt_message.role in [PromptMessageRole.USER, PromptMessageRole.SYSTEM, PromptMessageRole.TOOL]:
+                if not isinstance(copy_prompt_message.content, str):
+                    # not support image message
+                    continue
+
+                if new_prompt_messages and new_prompt_messages[-1].role == PromptMessageRole.USER:
+                    new_prompt_messages[-1].content += "\n\n" + copy_prompt_message.content
+                else:
+                    if copy_prompt_message.role == PromptMessageRole.USER:
+                        new_prompt_messages.append(copy_prompt_message)
+                    else:
+                        new_prompt_message = UserPromptMessage(content=copy_prompt_message.content)
+                        new_prompt_messages.append(new_prompt_message)
+            else:
+                if new_prompt_messages and new_prompt_messages[-1].role == PromptMessageRole.ASSISTANT:
+                    new_prompt_messages[-1].content += "\n\n" + copy_prompt_message.content
+                else:
+                    new_prompt_messages.append(copy_prompt_message)
+
         params = {
             'model': model,
             'prompt': [{
-                'role': prompt_message.role.value if prompt_message.role.value != 'system' else 'user',
+                'role': prompt_message.role.value,
                 'content': prompt_message.content
-            } for prompt_message in prompt_messages],
+            } for prompt_message in new_prompt_messages],
             **model_parameters
         }
 

api/core/moderation/cloud_service/cloud_service.py

@@ -1,93 +0,0 @@
-from core.moderation.base import Moderation, ModerationAction, ModerationInputsResult, ModerationOutputsResult
-
-
-class CloudServiceModeration(Moderation):
-    """
-    The name of custom type must be unique, keep the same with directory and file name.
-    """
-    name: str = "cloud_service"
-
-    @classmethod
-    def validate_config(cls, tenant_id: str, config: dict) -> None:
-        """
-        schema.json validation. It will be called when user save the config.
-
-        Example:
-            .. code-block:: python
-                config = {
-                    "cloud_provider": "GoogleCloud",
-                    "api_endpoint": "https://api.example.com",
-                    "api_keys": "123456",
-                    "inputs_config": {
-                        "enabled": True,
-                        "preset_response": "Your content violates our usage policy. Please revise and try again."
-                    },
-                    "outputs_config": {
-                        "enabled": True,
-                        "preset_response": "Your content violates our usage policy. Please revise and try again."
-                    }
-                }
-
-        :param tenant_id: the id of workspace
-        :param config: the variables of form config
-        :return:
-        """
-
-        cls._validate_inputs_and_outputs_config(config, True)
-
-        if not config.get("cloud_provider"):
-            raise ValueError("cloud_provider is required")
-
-        if not config.get("api_endpoint"):
-            raise ValueError("api_endpoint is required")
-
-        if not config.get("api_keys"):
-            raise ValueError("api_keys is required")
-
-    def moderation_for_inputs(self, inputs: dict, query: str = "") -> ModerationInputsResult:
-        """
-        Moderation for inputs.
-
-        :param inputs: user inputs
-        :param query: the query of chat app, there is empty if is completion app
-        :return: the moderation result
-        """
-        flagged = False
-        preset_response = ""
-
-        if self.config['inputs_config']['enabled']:
-            preset_response = self.config['inputs_config']['preset_response']
-
-            if query:
-                inputs['query__'] = query
-            flagged = self._is_violated(inputs)
-
-        # return ModerationInputsResult(flagged=flagged, action=ModerationAction.OVERRIDED, inputs=inputs, query=query)
-        return ModerationInputsResult(flagged=flagged, action=ModerationAction.DIRECT_OUTPUT, preset_response=preset_response)
-
-    def moderation_for_outputs(self, text: str) -> ModerationOutputsResult:
-        """
-        Moderation for outputs.
-
-        :param text: the text of LLM response
-        :return: the moderation result
-        """
-        flagged = False
-        preset_response = ""
-
-        if self.config['outputs_config']['enabled']:
-            preset_response = self.config['outputs_config']['preset_response']
-
-            flagged = self._is_violated({'text': text})
-
-        # return ModerationOutputsResult(flagged=flagged, action=ModerationAction.OVERRIDED, text=text)
-        return ModerationOutputsResult(flagged=flagged, action=ModerationAction.DIRECT_OUTPUT, preset_response=preset_response)
-
-    def _is_violated(self, inputs: dict):
-        """
-        The main logic of moderation.
-
-        :param inputs:
-        :return: the moderation result
-        """
-        return False

api/core/moderation/cloud_service/schema.json

@@ -1,65 +0,0 @@
-{
-    "label": {
-        "en-US": "Cloud Service",
-        "zh-Hans": "云服务"
-    },
-    "form_schema": [
-        {
-            "type": "select",
-            "label": {
-                "en-US": "Cloud Provider",
-                "zh-Hans": "云厂商"
-            },
-            "variable": "cloud_provider",
-            "required": true,
-            "options": [
-                {
-                    "label": {
-                        "en-US": "AWS",
-                        "zh-Hans": "亚马逊"
-                    },
-                    "value": "AWS"
-                },
-                {
-                    "label": {
-                        "en-US": "Google Cloud",
-                        "zh-Hans": "谷歌云"
-                    },
-                    "value": "GoogleCloud"
-                },
-                {
-                    "label": {
-                        "en-US": "Azure Cloud",
-                        "zh-Hans": "微软云"
-                    },
-                    "value": "Azure"
-                }
-            ],
-            "default": "GoogleCloud",
-            "placeholder": ""
-        },
-        {
-            "type": "text-input",
-            "label": {
-                "en-US": "API Endpoint",
-                "zh-Hans": "API Endpoint"
-            },
-            "variable": "api_endpoint",
-            "required": true,
-            "max_length": 100,
-            "default": "",
-            "placeholder": "https://api.example.com"
-        },
-        {
-            "type": "paragraph",
-            "label": {
-                "en-US": "API Key",
-                "zh-Hans": "API Key"
-            },
-            "variable": "api_keys",
-            "required": true,
-            "default": "",
-            "placeholder": "Paste your API key here"
-        }
-    ]
-}

api/core/prompt/prompt_transform.py

@@ -207,7 +207,7 @@ class PromptTransform:
 
         json_file_path = os.path.join(prompt_path, f'{prompt_name}.json')
         # Open the JSON file and read its content
-        with open(json_file_path, 'r') as json_file:
+        with open(json_file_path, 'r', encoding='utf-8') as json_file:
             return json.load(json_file)
 
     def _get_simple_chat_app_chat_model_prompt_messages(self, prompt_rules: dict,
@@ -334,7 +334,18 @@ class PromptTransform:
 
         prompt = re.sub(r'<\|.*?\|>', '', prompt)
 
-        return [UserPromptMessage(content=prompt)]
+        model_mode = ModelMode.value_of(model_config.mode)
+
+        if model_mode == ModelMode.CHAT and files:
+            prompt_message_contents = [TextPromptMessageContent(data=prompt)]
+            for file in files:
+                prompt_message_contents.append(file.prompt_message_content)
+
+            prompt_message = UserPromptMessage(content=prompt_message_contents)
+        else:
+            prompt_message = UserPromptMessage(content=prompt)
+
+        return [prompt_message]
 
     def _set_context_variable(self, context: str, prompt_template: PromptTemplateParser, prompt_inputs: dict) -> None:
         if '#context#' in prompt_template.variable_keys:

api/core/prompt/prompts.py

@@ -75,7 +75,7 @@ GENERATOR_QA_PROMPT = (
     'Step 3: Decompose or combine multiple pieces of information and concepts.\n'
     'Step 4: Generate 20 questions and answers based on these key information and concepts.'
     'The questions should be clear and detailed, and the answers should be detailed and complete.\n'
-    "Answer according to the the language:{language} and in the following format: Q1:\nA1:\nQ2:\nA2:...\n"
+    "Answer MUST according to the the language:{language} and in the following format: Q1:\nA1:\nQ2:\nA2:...\n"
 )
 
 RULE_CONFIG_GENERATE_TEMPLATE = """Given MY INTENDED AUDIENCES and HOPING TO SOLVE using a language model, please select \

api/core/provider_manager.py

@@ -10,6 +10,7 @@ from core.entities.provider_configuration import ProviderConfigurations, Provide
 from core.entities.provider_entities import CustomConfiguration, CustomProviderConfiguration, CustomModelConfiguration, \
     SystemConfiguration, QuotaConfiguration
 from core.helper import encrypter
+from core.helper.model_provider_cache import ProviderCredentialsCache, ProviderCredentialsCacheType
 from core.model_runtime.entities.model_entities import ModelType
 from core.model_runtime.entities.provider_entities import ProviderEntity, CredentialFormSchema, FormType
 from core.model_runtime.model_providers import model_provider_factory
@@ -23,6 +24,9 @@ class ProviderManager:
     """
     ProviderManager is a class that manages the model providers includes Hosting and Customize Model Providers.
     """
+    def __init__(self) -> None:
+        self.decoding_rsa_key = None
+        self.decoding_cipher_rsa = None
 
     def get_configurations(self, tenant_id: str) -> ProviderConfigurations:
         """
@@ -79,9 +83,6 @@ class ProviderManager:
         # Get All preferred provider types of the workspace
         provider_name_to_preferred_model_provider_records_dict = self._get_all_preferred_model_providers(tenant_id)
 
-        # Get decoding rsa key and cipher for decrypting credentials
-        decoding_rsa_key, decoding_cipher_rsa = encrypter.get_decrypt_decoding(tenant_id)
-
         provider_configurations = ProviderConfigurations(
             tenant_id=tenant_id
         )
@@ -100,19 +101,17 @@ class ProviderManager:
 
             # Convert to custom configuration
             custom_configuration = self._to_custom_configuration(
+                tenant_id,
                 provider_entity,
                 provider_records,
-                provider_model_records,
-                decoding_rsa_key,
-                decoding_cipher_rsa
+                provider_model_records
             )
 
             # Convert to system configuration
             system_configuration = self._to_system_configuration(
+                tenant_id,
                 provider_entity,
-                provider_records,
-                decoding_rsa_key,
-                decoding_cipher_rsa
+                provider_records
             )
 
             # Get preferred provider type
@@ -233,11 +232,18 @@ class ProviderManager:
             return None
 
         provider_instance = model_provider_factory.get_provider_instance(default_model.provider_name)
+        provider_schema = provider_instance.get_provider_schema()
 
         return DefaultModelEntity(
             model=default_model.model_name,
             model_type=model_type,
-            provider=DefaultModelProviderEntity(**provider_instance.get_provider_schema().to_simple_provider().dict())
+            provider=DefaultModelProviderEntity(
+                provider=provider_schema.provider,
+                label=provider_schema.label,
+                icon_small=provider_schema.icon_small,
+                icon_large=provider_schema.icon_large,
+                supported_model_types=provider_schema.supported_model_types
+            )
         )
 
     def update_default_model_record(self, tenant_id: str, model_type: ModelType, provider: str, model: str) \
@@ -401,28 +407,29 @@ class ProviderManager:
                                 Provider.tenant_id == tenant_id,
                                 Provider.provider_name == provider_name,
                                 Provider.provider_type == ProviderType.SYSTEM.value,
-                                Provider.quota_type == ProviderQuotaType.TRIAL.value,
-                                Provider.is_valid == True
+                                Provider.quota_type == ProviderQuotaType.TRIAL.value
                             ).first()
 
+                            if provider_record and not provider_record.is_valid:
+                                provider_record.is_valid = True
+                                db.session.commit()
+
                         provider_name_to_provider_records_dict[provider_name].append(provider_record)
 
         return provider_name_to_provider_records_dict
 
     def _to_custom_configuration(self,
+                                 tenant_id: str,
                                  provider_entity: ProviderEntity,
                                  provider_records: list[Provider],
-                                 provider_model_records: list[ProviderModel],
-                                 decoding_rsa_key,
-                                 decoding_cipher_rsa) -> CustomConfiguration:
+                                 provider_model_records: list[ProviderModel]) -> CustomConfiguration:
         """
         Convert to custom configuration.
 
+        :param tenant_id: workspace id
         :param provider_entity: provider entity
         :param provider_records: provider records
         :param provider_model_records: provider model records
-        :param decoding_rsa_key: decoding rsa key
-        :param decoding_cipher_rsa: decoding cipher rsa
         :return:
         """
         # Get provider credential secret variables
@@ -445,28 +452,49 @@ class ProviderManager:
         # Get custom provider credentials
         custom_provider_configuration = None
         if custom_provider_record:
-            try:
-                # fix origin data
-                if (custom_provider_record.encrypted_config
-                        and not custom_provider_record.encrypted_config.startswith("{")):
-                    provider_credentials = {
-                        "openai_api_key": custom_provider_record.encrypted_config
-                    }
-                else:
-                    provider_credentials = json.loads(custom_provider_record.encrypted_config)
-            except JSONDecodeError:
-                provider_credentials = {}
+            provider_credentials_cache = ProviderCredentialsCache(
+                tenant_id=tenant_id,
+                identity_id=custom_provider_record.id,
+                cache_type=ProviderCredentialsCacheType.PROVIDER
+            )
 
-            for variable in provider_credential_secret_variables:
-                if variable in provider_credentials:
-                    try:
-                        provider_credentials[variable] = encrypter.decrypt_token_with_decoding(
-                            provider_credentials.get(variable),
-                            decoding_rsa_key,
-                            decoding_cipher_rsa
-                        )
-                    except ValueError:
-                        pass
+            # Get cached provider credentials
+            cached_provider_credentials = provider_credentials_cache.get()
+
+            if not cached_provider_credentials:
+                try:
+                    # fix origin data
+                    if (custom_provider_record.encrypted_config
+                            and not custom_provider_record.encrypted_config.startswith("{")):
+                        provider_credentials = {
+                            "openai_api_key": custom_provider_record.encrypted_config
+                        }
+                    else:
+                        provider_credentials = json.loads(custom_provider_record.encrypted_config)
+                except JSONDecodeError:
+                    provider_credentials = {}
+
+                # Get decoding rsa key and cipher for decrypting credentials
+                if self.decoding_rsa_key is None or self.decoding_cipher_rsa is None:
+                    self.decoding_rsa_key, self.decoding_cipher_rsa = encrypter.get_decrypt_decoding(tenant_id)
+
+                for variable in provider_credential_secret_variables:
+                    if variable in provider_credentials:
+                        try:
+                            provider_credentials[variable] = encrypter.decrypt_token_with_decoding(
+                                provider_credentials.get(variable),
+                                self.decoding_rsa_key,
+                                self.decoding_cipher_rsa
+                            )
+                        except ValueError:
+                            pass
+
+                # cache provider credentials
+                provider_credentials_cache.set(
+                    credentials=provider_credentials
+                )
+            else:
+                provider_credentials = cached_provider_credentials
 
             custom_provider_configuration = CustomProviderConfiguration(
                 credentials=provider_credentials
@@ -484,21 +512,42 @@ class ProviderManager:
             if not provider_model_record.encrypted_config:
                 continue
 
-            try:
-                provider_model_credentials = json.loads(provider_model_record.encrypted_config)
-            except JSONDecodeError:
-                continue
+            provider_model_credentials_cache = ProviderCredentialsCache(
+                tenant_id=tenant_id,
+                identity_id=provider_model_record.id,
+                cache_type=ProviderCredentialsCacheType.MODEL
+            )
 
-            for variable in model_credential_secret_variables:
-                if variable in provider_model_credentials:
-                    try:
-                        provider_model_credentials[variable] = encrypter.decrypt_token_with_decoding(
-                            provider_model_credentials.get(variable),
-                            decoding_rsa_key,
-                            decoding_cipher_rsa
-                        )
-                    except ValueError:
-                        pass
+            # Get cached provider model credentials
+            cached_provider_model_credentials = provider_model_credentials_cache.get()
+
+            if not cached_provider_model_credentials:
+                try:
+                    provider_model_credentials = json.loads(provider_model_record.encrypted_config)
+                except JSONDecodeError:
+                    continue
+
+                # Get decoding rsa key and cipher for decrypting credentials
+                if self.decoding_rsa_key is None or self.decoding_cipher_rsa is None:
+                    self.decoding_rsa_key, self.decoding_cipher_rsa = encrypter.get_decrypt_decoding(tenant_id)
+
+                for variable in model_credential_secret_variables:
+                    if variable in provider_model_credentials:
+                        try:
+                            provider_model_credentials[variable] = encrypter.decrypt_token_with_decoding(
+                                provider_model_credentials.get(variable),
+                                self.decoding_rsa_key,
+                                self.decoding_cipher_rsa
+                            )
+                        except ValueError:
+                            pass
+
+                # cache provider model credentials
+                provider_model_credentials_cache.set(
+                    credentials=provider_model_credentials
+                )
+            else:
+                provider_model_credentials = cached_provider_model_credentials
 
             custom_model_configurations.append(
                 CustomModelConfiguration(
@@ -514,17 +563,15 @@ class ProviderManager:
         )
 
     def _to_system_configuration(self,
+                                 tenant_id: str,
                                  provider_entity: ProviderEntity,
-                                 provider_records: list[Provider],
-                                 decoding_rsa_key,
-                                 decoding_cipher_rsa) -> SystemConfiguration:
+                                 provider_records: list[Provider]) -> SystemConfiguration:
         """
         Convert to system configuration.
 
+        :param tenant_id: workspace id
         :param provider_entity: provider entity
         :param provider_records: provider records
-        :param decoding_rsa_key: decoding rsa key
-        :param decoding_cipher_rsa: decoding cipher rsa
         :return:
         """
         # Get hosting configuration
@@ -577,29 +624,50 @@ class ProviderManager:
             provider_record = quota_type_to_provider_records_dict.get(current_quota_type)
 
             if provider_record:
-                try:
-                    provider_credentials = json.loads(provider_record.encrypted_config)
-                except JSONDecodeError:
-                    provider_credentials = {}
-
-                # Get provider credential secret variables
-                provider_credential_secret_variables = self._extract_secret_variables(
-                    provider_entity.provider_credential_schema.credential_form_schemas
-                    if provider_entity.provider_credential_schema else []
+                provider_credentials_cache = ProviderCredentialsCache(
+                    tenant_id=tenant_id,
+                    identity_id=provider_record.id,
+                    cache_type=ProviderCredentialsCacheType.PROVIDER
                 )
 
-                for variable in provider_credential_secret_variables:
-                    if variable in provider_credentials:
-                        try:
-                            provider_credentials[variable] = encrypter.decrypt_token_with_decoding(
-                                provider_credentials.get(variable),
-                                decoding_rsa_key,
-                                decoding_cipher_rsa
-                            )
-                        except ValueError:
-                            pass
+                # Get cached provider credentials
+                cached_provider_credentials = provider_credentials_cache.get()
 
-                current_using_credentials = provider_credentials
+                if not cached_provider_credentials:
+                    try:
+                        provider_credentials = json.loads(provider_record.encrypted_config)
+                    except JSONDecodeError:
+                        provider_credentials = {}
+
+                    # Get provider credential secret variables
+                    provider_credential_secret_variables = self._extract_secret_variables(
+                        provider_entity.provider_credential_schema.credential_form_schemas
+                        if provider_entity.provider_credential_schema else []
+                    )
+
+                    # Get decoding rsa key and cipher for decrypting credentials
+                    if self.decoding_rsa_key is None or self.decoding_cipher_rsa is None:
+                        self.decoding_rsa_key, self.decoding_cipher_rsa = encrypter.get_decrypt_decoding(tenant_id)
+
+                    for variable in provider_credential_secret_variables:
+                        if variable in provider_credentials:
+                            try:
+                                provider_credentials[variable] = encrypter.decrypt_token_with_decoding(
+                                    provider_credentials.get(variable),
+                                    self.decoding_rsa_key,
+                                    self.decoding_cipher_rsa
+                                )
+                            except ValueError:
+                                pass
+
+                    current_using_credentials = provider_credentials
+
+                    # cache provider credentials
+                    provider_credentials_cache.set(
+                        credentials=current_using_credentials
+                    )
+                else:
+                    current_using_credentials = cached_provider_credentials
             else:
                 current_using_credentials = {}
 

api/extensions/ext_celery.py

@@ -46,11 +46,11 @@ def init_app(app: Flask) -> Celery:
     beat_schedule = {
         'clean_embedding_cache_task': {
             'task': 'schedule.clean_embedding_cache_task.clean_embedding_cache_task',
-            'schedule': timedelta(minutes=1),
+            'schedule': timedelta(days=7),
         },
         'clean_unused_datasets_task': {
             'task': 'schedule.clean_unused_datasets_task.clean_unused_datasets_task',
-            'schedule': timedelta(minutes=10),
+            'schedule': timedelta(days=7),
         }
     }
     celery_app.conf.update(

api/libs/rsa.py

@@ -5,7 +5,6 @@ from Crypto.Cipher import PKCS1_OAEP, AES
 from Crypto.PublicKey import RSA
 from Crypto.Random import get_random_bytes
 
-from core.helper.lru_cache import LRUCache
 from extensions.ext_redis import redis_client
 from extensions.ext_storage import storage
 
@@ -46,15 +45,7 @@ def encrypt(text, public_key):
     return prefix_hybrid + encrypted_data
 
 
-tenant_rsa_keys = LRUCache(capacity=1000)
-
-
 def get_decrypt_decoding(tenant_id):
-    rsa_key = tenant_rsa_keys.get(tenant_id)
-    if rsa_key:
-        cipher_rsa = PKCS1_OAEP.new(rsa_key)
-        return rsa_key, cipher_rsa
-
     filepath = "privkeys/{tenant_id}".format(tenant_id=tenant_id) + "/private.pem"
 
     cache_key = 'tenant_privkey:{hash}'.format(hash=hashlib.sha3_256(filepath.encode()).hexdigest())
@@ -70,8 +61,6 @@ def get_decrypt_decoding(tenant_id):
     rsa_key = RSA.import_key(private_key)
     cipher_rsa = PKCS1_OAEP.new(rsa_key)
 
-    tenant_rsa_keys.put(tenant_id, rsa_key)
-
     return rsa_key, cipher_rsa
 
 

api/services/model_provider_service.py

@@ -6,7 +6,7 @@ from typing import Optional, cast, Tuple
 import requests
 from flask import current_app
 
-from core.entities.model_entities import ModelWithProviderEntity, ModelStatus, DefaultModelEntity
+from core.entities.model_entities import ModelStatus
 from core.model_runtime.entities.model_entities import ModelType, ParameterRule
 from core.model_runtime.model_providers import model_provider_factory
 from core.model_runtime.model_providers.__base.large_language_model import LargeLanguageModel
@@ -14,7 +14,7 @@ from core.provider_manager import ProviderManager
 from models.provider import ProviderType
 from services.entities.model_provider_entities import ProviderResponse, CustomConfigurationResponse, \
     SystemConfigurationResponse, CustomConfigurationStatus, ProviderWithModelsResponse, ModelResponse, \
-    DefaultModelResponse, ModelWithProviderEntityResponse
+    DefaultModelResponse, ModelWithProviderEntityResponse, SimpleProviderEntityResponse
 
 logger = logging.getLogger(__name__)
 
@@ -45,7 +45,17 @@ class ModelProviderService:
                     continue
 
             provider_response = ProviderResponse(
-                **provider_configuration.provider.dict(),
+                provider=provider_configuration.provider.provider,
+                label=provider_configuration.provider.label,
+                description=provider_configuration.provider.description,
+                icon_small=provider_configuration.provider.icon_small,
+                icon_large=provider_configuration.provider.icon_large,
+                background=provider_configuration.provider.background,
+                help=provider_configuration.provider.help,
+                supported_model_types=provider_configuration.provider.supported_model_types,
+                configurate_methods=provider_configuration.provider.configurate_methods,
+                provider_credential_schema=provider_configuration.provider.provider_credential_schema,
+                model_credential_schema=provider_configuration.provider.model_credential_schema,
                 preferred_provider_type=provider_configuration.preferred_provider_type,
                 custom_configuration=CustomConfigurationResponse(
                     status=CustomConfigurationStatus.ACTIVE
@@ -53,7 +63,9 @@ class ModelProviderService:
                     else CustomConfigurationStatus.NO_CONFIGURE
                 ),
                 system_configuration=SystemConfigurationResponse(
-                    **provider_configuration.system_configuration.dict()
+                    enabled=provider_configuration.system_configuration.enabled,
+                    current_quota_type=provider_configuration.system_configuration.current_quota_type,
+                    quota_configurations=provider_configuration.system_configuration.quota_configurations
                 )
             )
 
@@ -369,7 +381,15 @@ class ModelProviderService:
         )
 
         return DefaultModelResponse(
-            **result.dict()
+            model=result.model,
+            model_type=result.model_type,
+            provider=SimpleProviderEntityResponse(
+                provider=result.provider.provider,
+                label=result.provider.label,
+                icon_small=result.provider.icon_small,
+                icon_large=result.provider.icon_large,
+                supported_model_types=result.provider.supported_model_types
+            )
         ) if result else None
 
     def update_default_model_of_model_type(self, tenant_id: str, model_type: str, provider: str, model: str) -> None:

api/tasks/disable_segment_from_index_task.py

@@ -27,7 +27,7 @@ def disable_segment_from_index_task(segment_id: str):
         raise NotFound('Segment not found')
 
     if segment.status != 'completed':
-        return
+        raise NotFound('Segment is not completed , disable action is not allowed.')
 
     indexing_cache_key = 'segment_{}_indexing'.format(segment.id)
 

api/tasks/enable_segment_to_index_task.py

@@ -29,7 +29,7 @@ def enable_segment_to_index_task(segment_id: str):
         raise NotFound('Segment not found')
 
     if segment.status != 'completed':
-        return
+        raise NotFound('Segment is not completed, enable action is not allowed.')
 
     indexing_cache_key = 'segment_{}_indexing'.format(segment.id)
 

api/templates/invite_member_mail_template_en-US.html

@@ -60,7 +60,7 @@
             <p>Dear {{ to }},</p>
             <p>{{ inviter_name }} is pleased to invite you to join our workspace on Dify, a platform specifically designed for LLM application development. On Dify, you can explore, create, and collaborate to build and operate AI applications.</p>
             <p>You can now log in to Dify using the GitHub or Google account associated with this email.</p>
-            <p style="text-align: center;"><a class="button" href="{{ url }}">Login Here</a></p>
+            <p style="text-align: center;"><a style="color: #fff; text-decoration: none" class="button" href="{{ url }}">Login Here</a></p>
         </div>
         <div class="footer">
             <p>Best regards,</p>

api/templates/invite_member_mail_template_zh-CN.html

@@ -60,7 +60,7 @@
             <p>尊敬的 {{ to }}，</p>
             <p>{{ inviter_name }} 现邀请您加入我们在 Dify 的工作区，这是一个专为 LLM 应用开发而设计的平台。在 Dify 上，您可以探索、创造和合作，构建和运营 AI 应用。</p>
             <p>您现在可以使用与此邮件相对应的 GitHub 或 Google 账号登录 Dify。</p>
-            <p style="text-align: center;"><a class="button" href="{{ url }}">在此登录</a></p>
+            <p style="text-align: center;"><a style="color: #fff; text-decoration: none" class="button" href="{{ url }}">在此登录</a></p>
         </div>
         <div class="footer">
             <p>此致，</p>

api/tests/integration_tests/model_runtime/openai/test_text_embedding.py

@@ -39,13 +39,15 @@ def test_invoke_model(setup_openai_mock):
         },
         texts=[
             "hello",
-            "world"
+            "world",
+            " ".join(["long_text"] * 100),
+            " ".join(["another_long_text"] * 100)
         ],
         user="abc-123"
     )
 
     assert isinstance(result, TextEmbeddingResult)
-    assert len(result.embeddings) == 2
+    assert len(result.embeddings) == 4
     assert result.usage.total_tokens == 2
 
 

api/tests/integration_tests/model_runtime/openai_api_compatible/test_llm.py

@@ -22,7 +22,7 @@ def test_validate_credentials():
             model='mistralai/Mixtral-8x7B-Instruct-v0.1',
             credentials={
                 'api_key': 'invalid_key',
-                'endpoint_url': 'https://api.together.xyz/v1/chat/completions',
+                'endpoint_url': 'https://api.together.xyz/v1/',
                 'mode': 'chat'
             }
         )
@@ -31,7 +31,7 @@ def test_validate_credentials():
         model='mistralai/Mixtral-8x7B-Instruct-v0.1',
         credentials={
             'api_key': os.environ.get('TOGETHER_API_KEY'),
-            'endpoint_url': 'https://api.together.xyz/v1/chat/completions',
+            'endpoint_url': 'https://api.together.xyz/v1/',
             'mode': 'chat'
         }
     )
@@ -43,7 +43,7 @@ def test_invoke_model():
         model='mistralai/Mixtral-8x7B-Instruct-v0.1',
         credentials={
             'api_key': os.environ.get('TOGETHER_API_KEY'),
-            'endpoint_url': 'https://api.together.xyz/v1/completions',
+            'endpoint_url': 'https://api.together.xyz/v1/',
             'mode': 'completion'
         },
         prompt_messages=[
@@ -74,7 +74,7 @@ def test_invoke_stream_model():
         model='mistralai/Mixtral-8x7B-Instruct-v0.1',
         credentials={
             'api_key': os.environ.get('TOGETHER_API_KEY'),
-            'endpoint_url': 'https://api.together.xyz/v1/chat/completions',
+            'endpoint_url': 'https://api.together.xyz/v1/',
             'mode': 'chat'
         },
         prompt_messages=[
@@ -110,7 +110,7 @@ def test_invoke_chat_model_with_tools():
         model='gpt-3.5-turbo',
         credentials={
             'api_key': os.environ.get('OPENAI_API_KEY'),
-            'endpoint_url': 'https://api.openai.com/v1/chat/completions',
+            'endpoint_url': 'https://api.openai.com/v1/',
             'mode': 'chat'
         },
         prompt_messages=[
@@ -165,7 +165,7 @@ def test_get_num_tokens():
         model='mistralai/Mixtral-8x7B-Instruct-v0.1',
         credentials={
             'api_key': os.environ.get('OPENAI_API_KEY'),
-            'endpoint_url': 'https://api.openai.com/v1/chat/completions'
+            'endpoint_url': 'https://api.openai.com/v1/'
         },
         prompt_messages=[
             SystemPromptMessage(

api/tests/integration_tests/model_runtime/openai_api_compatible/test_text_embedding.py

@@ -18,9 +18,8 @@ def test_validate_credentials():
             model='text-embedding-ada-002',
             credentials={
                 'api_key': 'invalid_key',
-                'endpoint_url': 'https://api.openai.com/v1/embeddings',
-                'context_size': 8184,
-                'max_chunks': 32
+                'endpoint_url': 'https://api.openai.com/v1/',
+                'context_size': 8184
                 
             }
         )
@@ -29,9 +28,8 @@ def test_validate_credentials():
         model='text-embedding-ada-002',
         credentials={
             'api_key': os.environ.get('OPENAI_API_KEY'),
-            'endpoint_url': 'https://api.openai.com/v1/embeddings',
-            'context_size': 8184,
-            'max_chunks': 32
+            'endpoint_url': 'https://api.openai.com/v1/',
+            'context_size': 8184
         }
     )
 
@@ -43,20 +41,21 @@ def test_invoke_model():
         model='text-embedding-ada-002',
         credentials={
             'api_key': os.environ.get('OPENAI_API_KEY'),
-            'endpoint_url': 'https://api.openai.com/v1/embeddings',
-            'context_size': 8184,
-            'max_chunks': 32
+            'endpoint_url': 'https://api.openai.com/v1/',
+            'context_size': 8184
         },
         texts=[
             "hello",
-            "world"
+            "world",
+            " ".join(["long_text"] * 100),
+            " ".join(["another_long_text"] * 100)
         ],
         user="abc-123"
     )
 
     assert isinstance(result, TextEmbeddingResult)
-    assert len(result.embeddings) == 2
-    assert result.usage.total_tokens == 2
+    assert len(result.embeddings) == 4
+    assert result.usage.total_tokens == 502
 
 
 def test_get_num_tokens():
@@ -67,8 +66,7 @@ def test_get_num_tokens():
         credentials={
             'api_key': os.environ.get('OPENAI_API_KEY'),
             'endpoint_url': 'https://api.openai.com/v1/embeddings',
-            'context_size': 8184,
-            'max_chunks': 32
+            'context_size': 8184
         },
         texts=[
             "hello",

api/tests/integration_tests/model_runtime/togetherai/test_llm.py

@@ -0,0 +1,117 @@
+import os
+from typing import Generator
+
+import pytest
+
+from core.model_runtime.entities.message_entities import AssistantPromptMessage, UserPromptMessage, \
+    SystemPromptMessage, PromptMessageTool
+from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunkDelta, \
+    LLMResultChunk
+from core.model_runtime.errors.validate import CredentialsValidateFailedError
+from core.model_runtime.model_providers.togetherai.llm.llm import TogetherAILargeLanguageModel
+
+
+def test_validate_credentials():
+    model = TogetherAILargeLanguageModel()
+
+    with pytest.raises(CredentialsValidateFailedError):
+        model.validate_credentials(
+            model='mistralai/Mixtral-8x7B-Instruct-v0.1',
+            credentials={
+                'api_key': 'invalid_key',
+                'mode': 'chat'
+            }
+        )
+
+    model.validate_credentials(
+        model='mistralai/Mixtral-8x7B-Instruct-v0.1',
+        credentials={
+            'api_key': os.environ.get('TOGETHER_API_KEY'),
+            'mode': 'chat'
+        }
+    )
+
+def test_invoke_model():
+    model = TogetherAILargeLanguageModel()
+
+    response = model.invoke(
+        model='mistralai/Mixtral-8x7B-Instruct-v0.1',
+        credentials={
+            'api_key': os.environ.get('TOGETHER_API_KEY'),
+            'mode': 'completion'
+        },
+        prompt_messages=[
+            SystemPromptMessage(
+                content='You are a helpful AI assistant.',
+            ),
+            UserPromptMessage(
+                content='Who are you?'
+            )
+        ],
+        model_parameters={
+            'temperature': 1.0,
+            'top_k': 2,
+            'top_p': 0.5,
+        },
+        stop=['How'],
+        stream=False,
+        user="abc-123"
+    )
+
+    assert isinstance(response, LLMResult)
+    assert len(response.message.content) > 0
+
+def test_invoke_stream_model():
+    model = TogetherAILargeLanguageModel()
+
+    response = model.invoke(
+        model='mistralai/Mixtral-8x7B-Instruct-v0.1',
+        credentials={
+            'api_key': os.environ.get('TOGETHER_API_KEY'),
+            'mode': 'chat'
+        },
+        prompt_messages=[
+            SystemPromptMessage(
+                content='You are a helpful AI assistant.',
+            ),
+            UserPromptMessage(
+                content='Who are you?'
+            )
+        ],
+        model_parameters={
+            'temperature': 1.0,
+            'top_k': 2,
+            'top_p': 0.5,
+        },
+        stop=['How'],
+        stream=True,
+        user="abc-123"
+    )
+
+    assert isinstance(response, Generator)
+
+    for chunk in response:
+        assert isinstance(chunk, LLMResultChunk)
+        assert isinstance(chunk.delta, LLMResultChunkDelta)
+        assert isinstance(chunk.delta.message, AssistantPromptMessage)
+
+def test_get_num_tokens():
+    model = TogetherAILargeLanguageModel()
+
+    num_tokens = model.get_num_tokens(
+        model='mistralai/Mixtral-8x7B-Instruct-v0.1',
+        credentials={
+            'api_key': os.environ.get('TOGETHER_API_KEY'),
+        },
+        prompt_messages=[
+            SystemPromptMessage(
+                content='You are a helpful AI assistant.',
+            ),
+            UserPromptMessage(
+                content='Hello World!'
+            )
+        ]
+    )
+
+    assert isinstance(num_tokens, int)
+    assert num_tokens == 21

docker/docker-compose.yaml

@@ -2,7 +2,7 @@ version: '3.1'
 services:
   # API service
   api:
-    image: langgenius/dify-api:0.4.2
+    image: langgenius/dify-api:0.4.4
     restart: always
     environment:
       # Startup mode, 'api' starts the API server.
@@ -92,6 +92,8 @@ services:
       QDRANT_URL: http://qdrant:6333
       # The Qdrant API key.
       QDRANT_API_KEY: difyai123456
+      # The Qdrant clinet timeout setting.
+      QDRANT_CLIENT_TIMEOUT: 20
       # Milvus configuration Only available when VECTOR_STORE is `milvus`.
       # The milvus host.
       MILVUS_HOST: 127.0.0.1
@@ -128,7 +130,7 @@ services:
   # worker service
   # The Celery worker for processing the queue.
   worker:
-    image: langgenius/dify-api:0.4.2
+    image: langgenius/dify-api:0.4.4
     restart: always
     environment:
       # Startup mode, 'worker' starts the Celery worker for processing the queue.
@@ -170,6 +172,8 @@ services:
       QDRANT_URL: http://qdrant:6333
       # The Qdrant API key.
       QDRANT_API_KEY: difyai123456
+      # The Qdrant clinet timeout setting.
+      QDRANT_CLIENT_TIMEOUT: 20
       # Milvus configuration Only available when VECTOR_STORE is `milvus`.
       # The milvus host.
       MILVUS_HOST: 127.0.0.1
@@ -196,7 +200,7 @@ services:
 
   # Frontend web application.
   web:
-    image: langgenius/dify-web:0.4.2
+    image: langgenius/dify-web:0.4.4
     restart: always
     environment:
       EDITION: SELF_HOSTED

web/.eslintrc.json

@@ -23,6 +23,7 @@
         ]
       }
     ],
-    "react-hooks/exhaustive-deps": "warn"
+    "react-hooks/exhaustive-deps": "warn",
+    "react/display-name": "warn"
   }
-}
+}

web/app/(commonLayout)/datasets/DatasetFooter.tsx

@@ -1,6 +1,6 @@
 'use client'
 
-import { useTranslation } from "react-i18next"
+import { useTranslation } from 'react-i18next'
 
 const DatasetFooter = () => {
   const { t } = useTranslation()

web/app/(shareLayout)/completion/[token]/page.tsx

@@ -10,4 +10,4 @@ const TextGeneration: FC<IMainProps> = () => {
   )
 }
 
-export default React.memo(TextGeneration)
+export default React.memo(TextGeneration)

web/app/components/app/chat/loading-anim/index.tsx

@@ -1,13 +1,14 @@
 'use client'
-import React, { FC } from 'react'
+import type { FC } from 'react'
+import React from 'react'
 import s from './style.module.css'
 
-export interface ILoaidingAnimProps {
+export type ILoaidingAnimProps = {
   type: 'text' | 'avatar'
 }
 
 const LoaidingAnim: FC<ILoaidingAnimProps> = ({
-  type
+  type,
 }) => {
   return (
     <div className={`${s['dot-flashing']} ${s[type]}`}></div>

web/app/components/app/chat/mermaid/index.tsx

@@ -23,7 +23,6 @@ const style = {
   overflow: 'auto',
 }
 
-// eslint-disable-next-line react/display-name
 const Flowchart = React.forwardRef((props: {
   PrimitiveCode: string
 }, ref) => {

web/app/components/app/configuration/base/group-name/index.tsx

@@ -1,12 +1,13 @@
 'use client'
-import React, { FC } from 'react'
+import type { FC } from 'react'
+import React from 'react'
 
-export interface IGroupNameProps {
+export type IGroupNameProps = {
   name: string
 }
 
 const GroupName: FC<IGroupNameProps> = ({
-  name
+  name,
 }) => {
   return (
     <div className='flex items-center mb-1'>

web/app/components/app/configuration/base/icons/more-like-this-icon.tsx

@@ -1,7 +1,8 @@
 'use client'
-import React, { FC } from 'react'
+import type { FC } from 'react'
+import React from 'react'
 
-const MoreLikeThisIcon: FC = ({ }) => {
+const MoreLikeThisIcon: FC = () => {
   return (
     <svg width="16" height="16" viewBox="0 0 16 16" fill="none" xmlns="http://www.w3.org/2000/svg">
       <path fillRule="evenodd" clipRule="evenodd" d="M5.83914 0.666748H10.1609C10.6975 0.666741 11.1404 0.666734 11.5012 0.696212C11.8759 0.726829 12.2204 0.792538 12.544 0.957399C13.0457 1.21306 13.4537 1.62101 13.7093 2.12277C13.8742 2.44633 13.9399 2.7908 13.9705 3.16553C14 3.52633 14 3.96923 14 4.50587V7.41171C14 7.62908 14 7.73776 13.9652 7.80784C13.9303 7.87806 13.8939 7.91566 13.8249 7.95288C13.756 7.99003 13.6262 7.99438 13.3665 8.00307C12.8879 8.01909 12.4204 8.14633 11.997 8.36429C10.9478 7.82388 9.62021 7.82912 8.53296 8.73228C7.15064 9.88056 6.92784 11.8645 8.0466 13.2641C8.36602 13.6637 8.91519 14.1949 9.40533 14.6492C9.49781 14.7349 9.54405 14.7777 9.5632 14.8041C9.70784 15.003 9.5994 15.2795 9.35808 15.3271C9.32614 15.3334 9.26453 15.3334 9.14129 15.3334H5.83912C5.30248 15.3334 4.85958 15.3334 4.49878 15.304C4.12405 15.2733 3.77958 15.2076 3.45603 15.0428C2.95426 14.7871 2.54631 14.3792 2.29065 13.8774C2.12579 13.5538 2.06008 13.2094 2.02946 12.8346C1.99999 12.4738 1.99999 12.0309 2 11.4943V4.50587C1.99999 3.96924 1.99999 3.52632 2.02946 3.16553C2.06008 2.7908 2.12579 2.44633 2.29065 2.12277C2.54631 1.62101 2.95426 1.21306 3.45603 0.957399C3.77958 0.792538 4.12405 0.726829 4.49878 0.696212C4.85957 0.666734 5.3025 0.666741 5.83914 0.666748ZM4.66667 5.33342C4.29848 5.33342 4 5.63189 4 6.00008C4 6.36827 4.29848 6.66675 4.66667 6.66675H8.66667C9.03486 6.66675 9.33333 6.36827 9.33333 6.00008C9.33333 5.63189 9.03486 5.33342 8.66667 5.33342H4.66667ZM4 8.66675C4 8.29856 4.29848 8.00008 4.66667 8.00008H6C6.36819 8.00008 6.66667 8.29856 6.66667 8.66675C6.66667 9.03494 6.36819 9.33342 6 9.33342H4.66667C4.29848 9.33342 4 9.03494 4 8.66675ZM4.66667 2.66675C4.29848 2.66675 4 2.96523 4 3.33342C4 3.7016 4.29848 4.00008 4.66667 4.00008H10.6667C11.0349 4.00008 11.3333 3.7016 11.3333 3.33342C11.3333 2.96523 11.0349 2.66675 10.6667 2.66675H4.66667Z" fill="#DD2590" />

web/app/components/app/configuration/base/operation-btn/index.tsx

@@ -1,9 +1,10 @@
 'use client'
-import React, { FC } from 'react'
+import type { FC } from 'react'
+import React from 'react'
 import { useTranslation } from 'react-i18next'
 import { PlusIcon } from '@heroicons/react/20/solid'
 
-export interface IOperationBtnProps {
+export type IOperationBtnProps = {
   type: 'add' | 'edit'
   actionName?: string
   onClick: () => void
@@ -14,13 +15,13 @@ const iconMap = {
   edit: (<svg width="14" height="14" viewBox="0 0 14 14" fill="none" xmlns="http://www.w3.org/2000/svg">
     <path d="M6.99998 11.6666H12.25M1.75 11.6666H2.72682C3.01217 11.6666 3.15485 11.6666 3.28912 11.6344C3.40816 11.6058 3.52196 11.5587 3.62635 11.4947C3.74408 11.4226 3.84497 11.3217 4.04675 11.1199L11.375 3.79164C11.8583 3.30839 11.8583 2.52488 11.375 2.04164C10.8918 1.55839 10.1083 1.55839 9.62501 2.04164L2.29674 9.3699C2.09496 9.57168 1.99407 9.67257 1.92192 9.7903C1.85795 9.89469 1.81081 10.0085 1.78224 10.1275C1.75 10.2618 1.75 10.4045 1.75 10.6898V11.6666Z" stroke="#344054" strokeWidth="1.25" strokeLinecap="round" strokeLinejoin="round" />
   </svg>
-  )
+  ),
 }
 
 const OperationBtn: FC<IOperationBtnProps> = ({
   type,
   actionName,
-  onClick
+  onClick,
 }) => {
   const { t } = useTranslation()
   return (

web/app/components/app/configuration/base/var-highlight/index.tsx

@@ -1,9 +1,10 @@
 'use client'
-import React, { FC } from 'react'
+import type { FC } from 'react'
+import React from 'react'
 
 import s from './style.module.css'
 
-export interface IVarHighlightProps {
+export type IVarHighlightProps = {
   name: string
 }
 
@@ -31,6 +32,4 @@ export const varHighlightHTML = ({ name }: IVarHighlightProps) => {
   return html
 }
 
-
-
 export default React.memo(VarHighlight)

web/app/components/app/configuration/base/warning-mask/has-not-set-api.tsx

@@ -1,10 +1,11 @@
 'use client'
-import React, { FC } from 'react'
+import type { FC } from 'react'
+import React from 'react'
 import { useTranslation } from 'react-i18next'
 import WarningMask from '.'
 import Button from '@/app/components/base/button'
 
-export interface IHasNotSetAPIProps {
+export type IHasNotSetAPIProps = {
   isTrailFinished: boolean
   onSetting: () => void
 }
@@ -18,7 +19,7 @@ const icon = (
 
 const HasNotSetAPI: FC<IHasNotSetAPIProps> = ({
   isTrailFinished,
-  onSetting
+  onSetting,
 }) => {
   const { t } = useTranslation()
 

web/app/components/app/configuration/base/warning-mask/index.tsx

@@ -1,9 +1,10 @@
 'use client'
-import React, { FC } from 'react'
+import type { FC } from 'react'
+import React from 'react'
 
 import s from './style.module.css'
 
-export interface IWarningMaskProps {
+export type IWarningMaskProps = {
   title: string
   description: string
   footer: React.ReactNode

web/app/components/app/configuration/config-model/index.tsx

@@ -1,423 +0,0 @@
-'use client'
-import type { FC } from 'react'
-import React, { useEffect, useState } from 'react'
-import cn from 'classnames'
-import { useTranslation } from 'react-i18next'
-import { useBoolean, useClickAway, useGetState } from 'ahooks'
-import { InformationCircleIcon } from '@heroicons/react/24/outline'
-import produce from 'immer'
-import ParamItem from './param-item'
-import { SlidersH } from '@/app/components/base/icons/src/vender/line/mediaAndDevices'
-import Radio from '@/app/components/base/radio'
-import Panel from '@/app/components/base/panel'
-import type { CompletionParams } from '@/models/debug'
-import { TONE_LIST } from '@/config'
-import Toast from '@/app/components/base/toast'
-import { AlertTriangle } from '@/app/components/base/icons/src/vender/solid/alertsAndFeedback'
-import { formatNumber } from '@/utils/format'
-import { Brush01 } from '@/app/components/base/icons/src/vender/solid/editor'
-import { Scales02 } from '@/app/components/base/icons/src/vender/solid/FinanceAndECommerce'
-import { Target04 } from '@/app/components/base/icons/src/vender/solid/general'
-import { Sliders02 } from '@/app/components/base/icons/src/vender/solid/mediaAndDevices'
-import { fetchModelParams } from '@/service/debug'
-import Loading from '@/app/components/base/loading'
-import useBreakpoints, { MediaType } from '@/hooks/use-breakpoints'
-import type { ModelModeType } from '@/types/app'
-import ModelIcon from '@/app/components/header/account-setting/model-provider-page/model-icon'
-import ModelName from '@/app/components/header/account-setting/model-provider-page/model-name'
-import ModelSelector from '@/app/components/header/account-setting/model-provider-page/model-selector'
-import { useTextGenerationCurrentProviderAndModelAndModelList } from '@/app/components/header/account-setting/model-provider-page/hooks'
-
-export type IConfigModelProps = {
-  isAdvancedMode: boolean
-  mode: string
-  modelId: string
-  provider: string
-  setModel: (model: { id: string; provider: string; mode: ModelModeType; features: string[] }) => void
-  completionParams: CompletionParams
-  onCompletionParamsChange: (newParams: CompletionParams) => void
-  disabled: boolean
-}
-
-const ConfigModel: FC<IConfigModelProps> = ({
-  isAdvancedMode,
-  modelId,
-  provider,
-  setModel,
-  completionParams,
-  onCompletionParamsChange,
-  disabled,
-}) => {
-  const { t } = useTranslation()
-  const [isShowConfig, { setFalse: hideConfig, toggle: toogleShowConfig }] = useBoolean(false)
-  const [maxTokenSettingTipVisible, setMaxTokenSettingTipVisible] = useState(false)
-  const configContentRef = React.useRef(null)
-  const {
-    currentProvider,
-    currentModel: currModel,
-    textGenerationModelList,
-  } = useTextGenerationCurrentProviderAndModelAndModelList(
-    { provider, model: modelId },
-  )
-
-  const media = useBreakpoints()
-  const isMobile = media === MediaType.mobile
-
-  // Cache loaded model param
-  const [allParams, setAllParams, getAllParams] = useGetState<Record<string, Record<string, any>>>({})
-  const currParams = allParams[provider]?.[modelId]
-  const hasEnableParams = currParams && Object.keys(currParams).some(key => currParams[key].enabled)
-  const allSupportParams = ['temperature', 'top_p', 'presence_penalty', 'frequency_penalty', 'max_tokens']
-  const currSupportParams = currParams ? allSupportParams.filter(key => currParams[key].enabled) : allSupportParams
-  if (isAdvancedMode)
-    currSupportParams.push('stop')
-
-  useEffect(() => {
-    (async () => {
-      if (!allParams[provider]?.[modelId]) {
-        const res = await fetchModelParams(provider, modelId)
-        const newAllParams = produce(allParams, (draft) => {
-          if (!draft[provider])
-            draft[provider] = {}
-
-          draft[provider][modelId] = res
-        })
-        setAllParams(newAllParams)
-      }
-    })()
-  }, [provider, modelId, allParams, setAllParams])
-
-  useClickAway(() => {
-    hideConfig()
-  }, configContentRef)
-
-  const selectedModel = { name: modelId } // options.find(option => option.id === modelId)
-
-  const ensureModelParamLoaded = (provider: string, modelId: string) => {
-    return new Promise<void>((resolve) => {
-      if (getAllParams()[provider]?.[modelId]) {
-        resolve()
-        return
-      }
-      const runId = setInterval(() => {
-        if (getAllParams()[provider]?.[modelId]) {
-          resolve()
-          clearInterval(runId)
-        }
-      }, 500)
-    })
-  }
-
-  const transformValue = (value: number, fromRange: [number, number], toRange: [number, number]): number => {
-    const [fromStart = 0, fromEnd] = fromRange
-    const [toStart = 0, toEnd] = toRange
-
-    // The following three if is to avoid precision loss
-    if (fromStart === toStart && fromEnd === toEnd)
-      return value
-
-    if (value <= fromStart)
-      return toStart
-
-    if (value >= fromEnd)
-      return toEnd
-
-    const fromLength = fromEnd - fromStart
-    const toLength = toEnd - toStart
-
-    let adjustedValue = (value - fromStart) * (toLength / fromLength) + toStart
-    adjustedValue = parseFloat(adjustedValue.toFixed(2))
-    return adjustedValue
-  }
-
-  const handleSelectModel = ({ id, provider: nextProvider, mode, features }: { id: string; provider: string; mode: ModelModeType; features: string[] }) => {
-    return async () => {
-      const prevParamsRule = getAllParams()[provider]?.[modelId]
-
-      setModel({
-        id,
-        provider: nextProvider || 'openai',
-        mode,
-        features,
-      })
-
-      await ensureModelParamLoaded(nextProvider, id)
-
-      const nextParamsRule = getAllParams()[nextProvider]?.[id]
-      // debugger
-      const nextSelectModelMaxToken = nextParamsRule.max_tokens.max
-      const newConCompletionParams = produce(completionParams, (draft: any) => {
-        if (nextParamsRule.max_tokens.enabled) {
-          if (completionParams.max_tokens > nextSelectModelMaxToken) {
-            Toast.notify({
-              type: 'warning',
-              message: t('common.model.params.setToCurrentModelMaxTokenTip', { maxToken: formatNumber(nextSelectModelMaxToken) }),
-            })
-            draft.max_tokens = parseFloat((nextSelectModelMaxToken * 0.8).toFixed(2))
-          }
-          // prev don't have max token
-          if (!completionParams.max_tokens)
-            draft.max_tokens = nextParamsRule.max_tokens.default
-        }
-        else {
-          delete draft.max_tokens
-        }
-
-        allSupportParams.forEach((key) => {
-          if (key === 'max_tokens')
-            return
-
-          if (!nextParamsRule[key].enabled) {
-            delete draft[key]
-            return
-          }
-
-          if (draft[key] === undefined) {
-            draft[key] = nextParamsRule[key].default || 0
-            return
-          }
-
-          if (!prevParamsRule[key].enabled) {
-            draft[key] = nextParamsRule[key].default || 0
-            return
-          }
-
-          draft[key] = transformValue(
-            draft[key],
-            [prevParamsRule[key].min, prevParamsRule[key].max],
-            [nextParamsRule[key].min, nextParamsRule[key].max],
-          )
-        })
-      })
-      onCompletionParamsChange(newConCompletionParams)
-    }
-  }
-
-  // only openai support this
-  function matchToneId(completionParams: CompletionParams): number {
-    const remvoedCustomeTone = TONE_LIST.slice(0, -1)
-    const CUSTOM_TONE_ID = 4
-    const tone = remvoedCustomeTone.find((tone) => {
-      return tone.config?.temperature === completionParams.temperature
-        && tone.config?.top_p === completionParams.top_p
-        && tone.config?.presence_penalty === completionParams.presence_penalty
-        && tone.config?.frequency_penalty === completionParams.frequency_penalty
-    })
-    return tone ? tone.id : CUSTOM_TONE_ID
-  }
-
-  // tone is a preset of completionParams.
-  const [toneId, setToneId] = React.useState(matchToneId(completionParams)) // default is Balanced
-  const toneTabBgClassName = ({
-    1: 'bg-[#F5F8FF]',
-    2: 'bg-[#F4F3FF]',
-    3: 'bg-[#F6FEFC]',
-  })[toneId] || ''
-  // set completionParams by toneId
-  const handleToneChange = (id: number) => {
-    if (id === 4)
-      return // custom tone
-    const tone = TONE_LIST.find(tone => tone.id === id)
-    if (tone) {
-      setToneId(id)
-      onCompletionParamsChange({
-        ...tone.config,
-        max_tokens: completionParams.max_tokens,
-      } as CompletionParams)
-    }
-  }
-
-  useEffect(() => {
-    setToneId(matchToneId(completionParams))
-  }, [completionParams])
-
-  const handleParamChange = (key: string, value: number | string[]) => {
-    if (value === undefined)
-      return
-    if ((completionParams as any)[key] === value)
-      return
-
-    if (key === 'stop') {
-      onCompletionParamsChange({
-        ...completionParams,
-        [key]: value as string[],
-      })
-    }
-    else {
-      const currParamsRule = getAllParams()[provider]?.[modelId]
-      let notOutRangeValue = parseFloat((value as number).toFixed(2))
-      notOutRangeValue = Math.max(currParamsRule[key].min, notOutRangeValue)
-      notOutRangeValue = Math.min(currParamsRule[key].max, notOutRangeValue)
-      onCompletionParamsChange({
-        ...completionParams,
-        [key]: notOutRangeValue,
-      })
-    }
-  }
-  const ableStyle = 'bg-indigo-25 border-[#2A87F5] cursor-pointer'
-  const diabledStyle = 'bg-[#FFFCF5] border-[#F79009]'
-
-  const getToneIcon = (toneId: number) => {
-    const className = 'w-[14px] h-[14px]'
-    const res = ({
-      1: <Brush01 className={className} />,
-      2: <Scales02 className={className} />,
-      3: <Target04 className={className} />,
-      4: <Sliders02 className={className} />,
-    })[toneId]
-    return res
-  }
-  useEffect(() => {
-    if (!currParams)
-      return
-
-    const max = currParams.max_tokens.max
-    const isSupportMaxToken = currParams.max_tokens.enabled
-    if (isSupportMaxToken && currentProvider?.provider !== 'anthropic' && completionParams.max_tokens > max * 2 / 3)
-      setMaxTokenSettingTipVisible(true)
-    else
-      setMaxTokenSettingTipVisible(false)
-  }, [currParams, completionParams.max_tokens, setMaxTokenSettingTipVisible, currentProvider])
-  return (
-    <div className='relative' ref={configContentRef}>
-      <div
-        className={cn('flex items-center border h-8 px-2 space-x-2 rounded-lg', disabled ? diabledStyle : ableStyle)}
-        onClick={() => !disabled && toogleShowConfig()}
-      >
-        {
-          currentProvider && (
-            <ModelIcon
-              className='!w-5 !h-5'
-              provider={currentProvider}
-            />
-          )
-        }
-        {
-          currModel && (
-            <ModelName
-              className='text-gray-900'
-              modelItem={currModel}
-              showMode={isAdvancedMode}
-            />
-          )
-        }
-        {disabled ? <InformationCircleIcon className='w-4 h-4 text-[#F79009]' /> : <SlidersH className='w-4 h-4 text-indigo-600' />}
-      </div>
-      {isShowConfig && (
-        <Panel
-          className='absolute z-20 top-8 left-0 sm:left-[unset] sm:right-0 !w-fit sm:!w-[496px] bg-white !overflow-visible shadow-md'
-          keepUnFold
-          headerIcon={
-            <svg width="16" height="16" viewBox="0 0 16 16" fill="none" xmlns="http://www.w3.org/2000/svg">
-              <path d="M8.26865 0.790031C8.09143 0.753584 7.90866 0.753584 7.73144 0.790031C7.52659 0.832162 7.3435 0.934713 7.19794 1.01624L7.15826 1.03841L6.17628 1.58395C5.85443 1.76276 5.73846 2.16863 5.91727 2.49049C6.09608 2.81234 6.50195 2.9283 6.82381 2.74949L7.80579 2.20395C7.90681 2.14782 7.95839 2.11946 7.99686 2.10091L8.00004 2.09938L8.00323 2.10091C8.0417 2.11946 8.09327 2.14782 8.1943 2.20395L9.17628 2.74949C9.49814 2.9283 9.90401 2.81234 10.0828 2.49048C10.2616 2.16863 10.1457 1.76276 9.82381 1.58395L8.84183 1.03841L8.80215 1.01624C8.65659 0.934713 8.4735 0.832162 8.26865 0.790031Z" fill="#1C64F2" />
-              <path d="M12.8238 3.25062C12.5019 3.07181 12.0961 3.18777 11.9173 3.50963C11.7385 3.83148 11.8544 4.23735 12.1763 4.41616L12.6272 4.66668L12.1763 4.91719C11.8545 5.096 11.7385 5.50186 11.9173 5.82372C12.0961 6.14558 12.502 6.26154 12.8238 6.08273L13.3334 5.79966V6.33339C13.3334 6.70158 13.6319 7.00006 14 7.00006C14.3682 7.00006 14.6667 6.70158 14.6667 6.33339V5.29435L14.6668 5.24627C14.6673 5.12441 14.6678 4.98084 14.6452 4.83482C14.6869 4.67472 14.6696 4.49892 14.5829 4.34286C14.4904 4.1764 14.3371 4.06501 14.1662 4.02099C14.0496 3.93038 13.9239 3.86116 13.8173 3.8024L13.7752 3.77915L12.8238 3.25062Z" fill="#1C64F2" />
-              <path d="M3.8238 4.41616C4.14566 4.23735 4.26162 3.83148 4.08281 3.50963C3.90401 3.18777 3.49814 3.07181 3.17628 3.25062L2.22493 3.77915L2.18284 3.8024C2.07615 3.86116 1.95045 3.9304 1.83382 4.02102C1.66295 4.06506 1.50977 4.17643 1.41731 4.34286C1.33065 4.49886 1.31323 4.67459 1.35493 4.83464C1.33229 4.98072 1.33281 5.12436 1.33326 5.24627L1.33338 5.29435V6.33339C1.33338 6.70158 1.63185 7.00006 2.00004 7.00006C2.36823 7.00006 2.66671 6.70158 2.66671 6.33339V5.79961L3.17632 6.08273C3.49817 6.26154 3.90404 6.14558 4.08285 5.82372C4.26166 5.50186 4.1457 5.096 3.82384 4.91719L3.3729 4.66666L3.8238 4.41616Z" fill="#1C64F2" />
-              <path d="M2.66671 9.66672C2.66671 9.29853 2.36823 9.00006 2.00004 9.00006C1.63185 9.00006 1.33338 9.29853 1.33338 9.66672V10.7058L1.33326 10.7538C1.33262 10.9298 1.33181 11.1509 1.40069 11.3594C1.46024 11.5397 1.55759 11.7051 1.68622 11.8447C1.835 12.0061 2.02873 12.1128 2.18281 12.1977L2.22493 12.221L3.17628 12.7495C3.49814 12.9283 3.90401 12.8123 4.08281 12.4905C4.26162 12.1686 4.14566 11.7628 3.8238 11.584L2.87245 11.0554C2.76582 10.9962 2.71137 10.9656 2.67318 10.9413L2.66995 10.9392L2.66971 10.9354C2.66699 10.8902 2.66671 10.8277 2.66671 10.7058V9.66672Z" fill="#1C64F2" />
-              <path d="M14.6667 9.66672C14.6667 9.29853 14.3682 9.00006 14 9.00006C13.6319 9.00006 13.3334 9.29853 13.3334 9.66672V10.7058C13.3334 10.8277 13.3331 10.8902 13.3304 10.9354L13.3301 10.9392L13.3269 10.9413C13.2887 10.9656 13.2343 10.9962 13.1276 11.0554L12.1763 11.584C11.8544 11.7628 11.7385 12.1686 11.9173 12.4905C12.0961 12.8123 12.5019 12.9283 12.8238 12.7495L13.7752 12.221L13.8172 12.1977C13.9713 12.1128 14.1651 12.0061 14.3139 11.8447C14.4425 11.7051 14.5398 11.5397 14.5994 11.3594C14.6683 11.1509 14.6675 10.9298 14.6668 10.7538L14.6667 10.7058V9.66672Z" fill="#1C64F2" />
-              <path d="M6.82381 13.2506C6.50195 13.0718 6.09608 13.1878 5.91727 13.5096C5.73846 13.8315 5.85443 14.2374 6.17628 14.4162L7.15826 14.9617L7.19793 14.9839C7.29819 15.04 7.41625 15.1061 7.54696 15.1556C7.66589 15.2659 7.82512 15.3333 8.00008 15.3333C8.17507 15.3333 8.33431 15.2659 8.45324 15.1556C8.58391 15.1061 8.70193 15.04 8.80215 14.9839L8.84183 14.9617L9.82381 14.4162C10.1457 14.2374 10.2616 13.8315 10.0828 13.5096C9.90401 13.1878 9.49814 13.0718 9.17628 13.2506L8.66675 13.5337V13C8.66675 12.6318 8.36827 12.3333 8.00008 12.3333C7.63189 12.3333 7.33341 12.6318 7.33341 13V13.5337L6.82381 13.2506Z" fill="#1C64F2" />
-              <path d="M6.82384 6.58385C6.50199 6.40505 6.09612 6.52101 5.91731 6.84286C5.7385 7.16472 5.85446 7.57059 6.17632 7.7494L7.33341 8.39223V9.66663C7.33341 10.0348 7.63189 10.3333 8.00008 10.3333C8.36827 10.3333 8.66675 10.0348 8.66675 9.66663V8.39223L9.82384 7.7494C10.1457 7.57059 10.2617 7.16472 10.0829 6.84286C9.90404 6.52101 9.49817 6.40505 9.17632 6.58385L8.00008 7.23732L6.82384 6.58385Z" fill="#1C64F2" />
-            </svg>
-          }
-          title={t('appDebug.modelConfig.title')}
-        >
-          <div className='py-3 pl-10 pr-6 text-sm'>
-            <div className="flex items-center justify-between my-5 h-9">
-              <div>{t('appDebug.modelConfig.model')}</div>
-              <ModelSelector
-                defaultModel={{ model: modelId, provider }}
-                modelList={textGenerationModelList}
-                onSelect={({ provider, model }) => {
-                  const targetProvider = textGenerationModelList.find(modelItem => modelItem.provider === provider)
-                  const targetModelItem = targetProvider?.models.find(modelItem => modelItem.model === model)
-                  handleSelectModel({
-                    id: model,
-                    provider,
-                    mode: targetModelItem?.model_properties.mode as ModelModeType,
-                    features: targetModelItem?.features || [],
-                  })()
-                }}
-              />
-            </div>
-            {hasEnableParams && (
-              <div className="border-b border-gray-100"></div>
-            )}
-
-            {/* Tone type */}
-            {['openai', 'azure_openai'].includes(provider) && (
-              <div className="mt-5 mb-4">
-                <div className="mb-3 text-sm text-gray-900">{t('appDebug.modelConfig.setTone')}</div>
-                <Radio.Group className={cn('!rounded-lg', toneTabBgClassName)} value={toneId} onChange={handleToneChange}>
-                  <>
-                    {TONE_LIST.slice(0, 3).map(tone => (
-                      <div className='grow flex items-center' key={tone.id}>
-                        <Radio
-                          value={tone.id}
-                          className={cn(tone.id === toneId && 'rounded-md border border-gray-200 shadow-md', '!mr-0 grow !px-1 sm:!px-2 !justify-center text-[13px] font-medium')}
-                          labelClassName={cn(tone.id === toneId
-                            ? ({
-                              1: 'text-[#6938EF]',
-                              2: 'text-[#444CE7]',
-                              3: 'text-[#107569]',
-                            })[toneId]
-                            : 'text-[#667085]', 'flex items-center space-x-2')}
-                        >
-                          <>
-                            {getToneIcon(tone.id)}
-                            {!isMobile && <div>{t(`common.model.tone.${tone.name}`) as string}</div>}
-                            <div className=""></div>
-                          </>
-                        </Radio>
-                        {tone.id !== toneId && tone.id + 1 !== toneId && (<div className='h-5 border-r border-gray-200'></div>)}
-                      </div>
-                    ))}
-                  </>
-                  <Radio
-                    value={TONE_LIST[3].id}
-                    className={cn(toneId === 4 && 'rounded-md border border-gray-200 shadow-md', '!mr-0 grow !px-1 sm:!px-2 !justify-center text-[13px] font-medium')}
-                    labelClassName={cn('flex items-center space-x-2 ', toneId === 4 ? 'text-[#155EEF]' : 'text-[#667085]')}
-                  >
-                    <>
-                      {getToneIcon(TONE_LIST[3].id)}
-                      {!isMobile && <div>{t(`common.model.tone.${TONE_LIST[3].name}`) as string}</div>}
-                    </>
-                  </Radio>
-                </Radio.Group>
-              </div>
-            )}
-
-            {/* Params */}
-            <div className={cn(hasEnableParams && 'mt-4', 'space-y-4', !allParams[provider]?.[modelId] && 'flex items-center min-h-[200px]')}>
-              {(allParams[provider]?.[modelId])
-                ? (
-                  currSupportParams.map(key => (<ParamItem
-                    key={key}
-                    id={key}
-                    name={t(`common.model.params.${key === 'stop' ? 'stop_sequences' : key}`)}
-                    tip={t(`common.model.params.${key === 'stop' ? 'stop_sequences' : key}Tip`)}
-                    {...currParams[key] as any}
-                    value={(completionParams as any)[key] as any}
-                    onChange={handleParamChange}
-                    inputType={key === 'stop' ? 'inputTag' : 'slider'}
-                  />))
-                )
-                : (
-                  <Loading type='area' />
-                )}
-            </div>
-          </div>
-          {
-            maxTokenSettingTipVisible && (
-              <div className='flex py-2 pr-4 pl-5 rounded-bl-xl rounded-br-xl bg-[#FFFAEB] border-t border-[#FEF0C7]'>
-                <AlertTriangle className='shrink-0 mr-2 mt-[3px] w-3 h-3 text-[#F79009]' />
-                <div className='mr-2 text-xs font-medium text-gray-700'>{t('common.model.params.maxTokenSettingTip')}</div>
-              </div>
-            )
-          }
-        </Panel>
-      )}
-    </div>
-
-  )
-}
-
-export default React.memo(ConfigModel)

web/app/components/app/configuration/config-model/model-mode-type-label.tsx

@@ -1,29 +0,0 @@
-'use client'
-import type { FC } from 'react'
-import React from 'react'
-import { useTranslation } from 'react-i18next'
-import cn from 'classnames'
-import type { ModelModeType } from '@/types/app'
-
-type Props = {
-  className?: string
-  type: ModelModeType
-  isHighlight?: boolean
-}
-
-const ModelModeTypeLabel: FC<Props> = ({
-  className,
-  type,
-  isHighlight,
-}) => {
-  const { t } = useTranslation()
-
-  return (
-    <div
-      className={cn(className, isHighlight ? 'border-indigo-300 text-indigo-600' : 'border-gray-300 text-gray-500', 'flex items-center h-4 px-1 border rounded text-xs font-semibold uppercase text-ellipsis overflow-hidden whitespace-nowrap')}
-    >
-      {t(`appDebug.modelConfig.modeType.${type}`)}
-    </div>
-  )
-}
-export default React.memo(ModelModeTypeLabel)

web/app/components/app/configuration/config-model/model-name.tsx

@@ -1,26 +0,0 @@
-'use client'
-import type { FC } from 'react'
-import React from 'react'
-
-export type IModelNameProps = {
-  modelId: string
-  modelDisplayName?: string
-}
-
-export const supportI18nModelName = [
-  'gpt-3.5-turbo', 'gpt-3.5-turbo-16k',
-  'gpt-4', 'gpt-4-32k',
-  'text-davinci-003', 'text-embedding-ada-002', 'whisper-1',
-  'claude-instant-1', 'claude-2',
-]
-
-const ModelName: FC<IModelNameProps> = ({
-  modelDisplayName,
-}) => {
-  return (
-    <span className='text-ellipsis overflow-hidden whitespace-nowrap' title={modelDisplayName}>
-      {modelDisplayName}
-    </span>
-  )
-}
-export default React.memo(ModelName)

web/app/components/app/configuration/config-model/param-item.tsx

@@ -1,95 +0,0 @@
-'use client'
-import type { FC } from 'react'
-import React, { useEffect } from 'react'
-import { useTranslation } from 'react-i18next'
-import Tooltip from '@/app/components/base/tooltip'
-import Slider from '@/app/components/base/slider'
-import TagInput from '@/app/components/base/tag-input'
-
-export const getFitPrecisionValue = (num: number, precision: number | null) => {
-  if (!precision || !(`${num}`).includes('.'))
-    return num
-
-  const currNumPrecision = (`${num}`).split('.')[1].length
-  if (currNumPrecision > precision)
-    return parseFloat(num.toFixed(precision))
-
-  return num
-}
-
-export type IParamIteProps = {
-  id: string
-  name: string
-  tip: string
-  value: number | string[]
-  step?: number
-  min?: number
-  max: number
-  precision: number | null
-  onChange: (key: string, value: number | string[]) => void
-  inputType?: 'inputTag' | 'slider'
-}
-
-const TIMES_TEMPLATE = '1000000000000'
-const ParamItem: FC<IParamIteProps> = ({ id, name, tip, step = 0.1, min = 0, max, precision, value, inputType, onChange }) => {
-  const { t } = useTranslation()
-
-  const getToIntTimes = (num: number) => {
-    if (precision)
-      return parseInt(TIMES_TEMPLATE.slice(0, precision + 1), 10)
-    if (num < 5)
-      return 10
-    return 1
-  }
-
-  const times = getToIntTimes(max)
-
-  useEffect(() => {
-    if (precision)
-      onChange(id, getFitPrecisionValue(value, precision))
-  }, [value, precision])
-  return (
-    <div className="flex items-center justify-between flex-wrap gap-y-2">
-      <div className="flex flex-col flex-shrink-0">
-        <div className="flex items-center">
-          <span className="mr-[6px] text-gray-500 text-[13px] font-medium">{name}</span>
-          {/* Give tooltip different tip to avoiding hide bug */}
-          <Tooltip htmlContent={<div className="w-[200px] whitespace-pre-wrap">{tip}</div>} position='top' selector={`param-name-tooltip-${id}`}>
-            <svg width="16" height="16" viewBox="0 0 16 16" fill="none" xmlns="http://www.w3.org/2000/svg">
-              <path d="M8.66667 10.6667H8V8H7.33333M8 5.33333H8.00667M14 8C14 8.78793 13.8448 9.56815 13.5433 10.2961C13.2417 11.0241 12.7998 11.6855 12.2426 12.2426C11.6855 12.7998 11.0241 13.2417 10.2961 13.5433C9.56815 13.8448 8.78793 14 8 14C7.21207 14 6.43185 13.8448 5.7039 13.5433C4.97595 13.2417 4.31451 12.7998 3.75736 12.2426C3.20021 11.6855 2.75825 11.0241 2.45672 10.2961C2.15519 9.56815 2 8.78793 2 8C2 6.4087 2.63214 4.88258 3.75736 3.75736C4.88258 2.63214 6.4087 2 8 2C9.5913 2 11.1174 2.63214 12.2426 3.75736C13.3679 4.88258 14 6.4087 14 8Z" stroke="#9CA3AF" strokeWidth="1.5" strokeLinecap="round" strokeLinejoin="round" />
-            </svg>
-          </Tooltip>
-        </div>
-        {inputType === 'inputTag' && <div className="text-gray-400 text-xs font-normal">{t('common.model.params.stop_sequencesPlaceholder')}</div>}
-      </div>
-      <div className="flex items-center">
-        {inputType === 'inputTag'
-          ? <TagInput
-            items={(value ?? []) as string[]}
-            onChange={newSequences => onChange(id, newSequences)}
-            customizedConfirmKey='Tab'
-          />
-          : (
-            <>
-              <div className="mr-4 w-[120px]">
-                <Slider value={value * times} min={min * times} max={max * times} onChange={(value) => {
-                  onChange(id, value / times)
-                }} />
-              </div>
-              <input type="number" min={min} max={max} step={step} className="block w-[64px] h-9 leading-9 rounded-lg border-0 pl-1 pl py-1.5 bg-gray-50 text-gray-900  placeholder:text-gray-400 focus:ring-1 focus:ring-inset focus:ring-primary-600" value={value} onChange={(e) => {
-                let value = getFitPrecisionValue(isNaN(parseFloat(e.target.value)) ? min : parseFloat(e.target.value), precision)
-                if (value < min)
-                  value = min
-
-                if (value > max)
-                  value = max
-                onChange(id, value)
-              }} />
-            </>
-          )
-        }
-      </div>
-    </div>
-  )
-}
-export default React.memo(ParamItem)

web/app/components/app/configuration/config-model/provider-name.tsx

@@ -1,24 +0,0 @@
-'use client'
-import type { FC } from 'react'
-import React from 'react'
-import { useContext } from 'use-context-selector'
-import I18n from '@/context/i18n'
-import type { ProviderEnum } from '@/app/components/header/account-setting/model-page/declarations'
-import ProviderConfig from '@/app/components/header/account-setting/model-page/configs'
-
-export type IProviderNameProps = {
-  provideName: ProviderEnum
-}
-
-const ProviderName: FC<IProviderNameProps> = ({
-  provideName,
-}) => {
-  const { locale } = useContext(I18n)
-
-  return (
-    <span>
-      {ProviderConfig[provideName]?.selector?.name[locale]}
-    </span>
-  )
-}
-export default React.memo(ProviderName)

web/app/components/app/configuration/config-var/modal-foot.tsx

@@ -1,16 +1,17 @@
 'use client'
-import React, { FC } from 'react'
+import type { FC } from 'react'
+import React from 'react'
 import { useTranslation } from 'react-i18next'
 import Button from '@/app/components/base/button'
 
-export interface IModalFootProps {
+export type IModalFootProps = {
   onConfirm: () => void
   onCancel: () => void
 }
 
 const ModalFoot: FC<IModalFootProps> = ({
   onConfirm,
-  onCancel
+  onCancel,
 }) => {
   const { t } = useTranslation()
   return (