bump version to 0.4.4 (#1962)

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

api/config.py

@@ -88,7 +88,7 @@ class Config:
         # ------------------------
         # General Configurations.
         # ------------------------
-        self.CURRENT_VERSION = "0.4.3"
+        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/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/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()
@@ -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')
 

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
@@ -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
@@ -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

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:
         """
@@ -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/entities/provider_configuration.py

@@ -520,7 +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
                     )
@@ -569,7 +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
                     )
@@ -597,7 +609,13 @@ class ProviderConfiguration(BaseModel):
 
             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/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/helper/model_provider_cache.py

@@ -40,7 +40,7 @@ class ProviderCredentialsCache:
         :param credentials: provider credentials
         :return:
         """
-        redis_client.setex(self.cache_key, 3600, json.dumps(credentials))
+        redis_client.setex(self.cache_key, 86400, json.dumps(credentials))
 
     def delete(self) -> None:
         """

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

@@ -148,7 +148,9 @@ class AIModel(ABC):
         position_map = {}
         if os.path.exists(position_file_path):
             with open(position_file_path, 'r', encoding='utf-8') as f:
-                position_map = yaml.safe_load(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:

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

@@ -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/model_provider_factory.py

@@ -217,7 +217,9 @@ class ModelProviderFactory:
         position_map = {}
         if os.path.exists(position_file_path):
             with open(position_file_path, 'r', encoding='utf-8') as f:
-                position_map = yaml.safe_load(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.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
+        }

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/togetherai/_assets/togetherai.svg

@@ -0,0 +1,13 @@
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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">
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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/prompt/prompt_transform.py

@@ -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

@@ -24,6 +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:
         """
@@ -229,11 +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) \
@@ -465,15 +475,16 @@ class ProviderManager:
                     provider_credentials = {}
 
                 # Get decoding rsa key and cipher for decrypting credentials
-                decoding_rsa_key, decoding_cipher_rsa = encrypter.get_decrypt_decoding(tenant_id)
+                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),
-                                decoding_rsa_key,
-                                decoding_cipher_rsa
+                                self.decoding_rsa_key,
+                                self.decoding_cipher_rsa
                             )
                         except ValueError:
                             pass
@@ -517,15 +528,16 @@ class ProviderManager:
                     continue
 
                 # Get decoding rsa key and cipher for decrypting credentials
-                decoding_rsa_key, decoding_cipher_rsa = encrypter.get_decrypt_decoding(tenant_id)
+                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),
-                                decoding_rsa_key,
-                                decoding_cipher_rsa
+                                self.decoding_rsa_key,
+                                self.decoding_cipher_rsa
                             )
                         except ValueError:
                             pass
@@ -634,15 +646,16 @@ class ProviderManager:
                     )
 
                     # Get decoding rsa key and cipher for decrypting credentials
-                    decoding_rsa_key, decoding_cipher_rsa = encrypter.get_decrypt_decoding(tenant_id)
+                    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),
-                                    decoding_rsa_key,
-                                    decoding_cipher_rsa
+                                    self.decoding_rsa_key,
+                                    self.decoding_cipher_rsa
                                 )
                             except ValueError:
                                 pass

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

@@ -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/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:0.4.3
+    image: langgenius/dify-api:0.4.4
     restart: always
     environment:
       # Startup mode, 'api' starts the API server.
@@ -130,7 +130,7 @@ services:
   # worker service
   # The Celery worker for processing the queue.
   worker:
-    image: langgenius/dify-api:0.4.3
+    image: langgenius/dify-api:0.4.4
     restart: always
     environment:
       # Startup mode, 'worker' starts the Celery worker for processing the queue.
@@ -200,7 +200,7 @@ services:
 
   # Frontend web application.
   web:
-    image: langgenius/dify-web:0.4.3
+    image: langgenius/dify-web:0.4.4
     restart: always
     environment:
       EDITION: SELF_HOSTED

web/app/components/datasets/documents/detail/completed/SegmentCard.tsx

@@ -128,7 +128,7 @@ const SegmentCard: FC<ISegmentCardProps> = ({
                         >
                           <Switch
                             size='md'
-                            disabled={archived}
+                            disabled={archived || detail.status !== 'completed'}
                             defaultValue={enabled}
                             onChange={async (val) => {
                               await onChangeSwitch?.(id, val)

web/app/components/share/text-generation/index.tsx

@@ -279,7 +279,7 @@ const TextGeneration: FC<IMainProps> = ({
       }
     })
     setAllTaskList(allTaskList)
-
+    setCurrGroupNum(0)
     setControlSend(Date.now())
     // clear run once task status
     setControlStopResponding(Date.now())
@@ -295,10 +295,7 @@ const TextGeneration: FC<IMainProps> = ({
     // avoid add many task at the same time
     if (needToAddNextGroupTask)
       setCurrGroupNum(hadRunedTaskNum)
-    // console.group()
-    // console.log(`[#${taskId}]: ${isSuccess ? 'success' : 'fail'}.currGroupNum: ${getCurrGroupNum()}.hadRunedTaskNum: ${hadRunedTaskNum}, needToAddNextGroupTask: ${needToAddNextGroupTask}`)
-    // console.log([...allTasklistLatest.filter(task => [TaskStatus.completed, TaskStatus.failed].includes(task.status)).map(item => item.id), taskId].sort((a: any, b: any) => a - b).join(','))
-    // console.groupEnd()
+
     const nextPendingTaskIds = needToAddNextGroupTask ? pendingTaskList.slice(0, GROUP_SIZE).map(item => item.id) : []
     const newAllTaskList = allTasklistLatest.map((item) => {
       if (item.id === taskId) {

web/package.json

@@ -1,6 +1,6 @@
 {
   "name": "dify-web",
-  "version": "0.4.3",
+  "version": "0.4.4",
   "private": true,
   "scripts": {
     "dev": "next dev",