fix: start error & linting

src/assistant/lib/agent/__init__.py

@@ -1,5 +1,5 @@
-from .services import AgentService
+# from .services import AgentService
 
-__all__ = [
+# __all__ = [
-    "AgentService",
+#     "AgentService",
-]
+# ]

src/assistant/lib/agent/repositories/embedding_repository.py

@@ -1,7 +1,6 @@
 import logging
 import typing
 
-import langchain.chat_models
 import openai
 import openai.error
 
@@ -40,25 +39,3 @@ class EmbeddingRepository:
 
         except openai.error.OpenAIError:
             self.logger.exception("Failed to get async embedding for: %s", text)
-
-
-class LlmRepository:
-    """A service for getting embeddings from OpenAI."""
-
-    def __init__(self, settings: app_settings.Settings) -> None:
-        """Initialize the service with an OpenAI API key."""
-        self.llm = langchain.chat_models.ChatOpenAI(
-            temperature=0.7,
-            openai_api_key=self.settings.openai.api_key.get_secret_value()
-        )
-
-    async def get_chat_response(self, request: str, prompt: str) -> str:
-        """Get the embedding for a given text."""
-        prompt = langchain.prompts.ChatPromptTemplate.from_messages(
-            [
-                ("system", prompt),
-            ]
-        )
-        chain = prompt | self.llm
-        response = await chain.ainvoke({"input": request})
-        return response.content

src/assistant/lib/agent/services.py

@@ -5,38 +5,33 @@ import langchain.agents
 import langchain.agents.format_scratchpad
 import langchain.agents.output_parsers
 import langchain.chat_models
+import langchain.memory
+import langchain.memory.chat_memory
 import langchain.prompts
 import langchain.schema
 import langchain.tools.render
-import langchain.memory
-import langchain.memory.chat_memory
 
-import lib.models as models
 import lib.agent.repositories as lib_agent_repositories
+import lib.agent.repositories.chat_repository as chat_repositories
 import lib.app.settings as app_settings
-import lib.agent.repositories.chat_repository as _chat_repository
+import lib.models as models
 
 
 class AgentService:
     def __init__(
         self,
         settings: app_settings.Settings,
-        chat_repository: _chat_repository.ChatHistoryRepository,
+        chat_repository: chat_repositories.ChatHistoryRepository,
-        tools: lib_agent_repositories.OpenAIFunctions | None = None,
+        tools: lib_agent_repositories.OpenAIFunctions,
     ) -> None:
         self.settings = settings
         self.tools = tools
         self.chat_repository = chat_repository
         self.logger = logging.getLogger(__name__)
 
-
     async def process_request(self, request: models.AgentCreateRequestModel) -> models.AgentCreateResponseModel:
         # Get session ID
-        session_request = models.RequestLastSessionId(
+        session_request = models.RequestLastSessionId(channel=request.channel, user_id=request.user_id, minutes_ago=3)
-            channel=request.channel,
-            user_id=request.user_id,
-            minutes_ago=3
-        )
         session_id = await self.chat_repository.get_last_session_id(session_request)
         if not session_id:
             session_id = uuid.uuid4()
@@ -47,24 +42,27 @@ class AgentService:
                 name="GetMovieByDescription",
                 func=self.tools.get_movie_by_description,
                 coroutine=self.tools.get_movie_by_description,
-                description="Get a movie by description"
+                description="Get a movie by description",
             ),
         ]
 
-        llm = langchain.chat_models.ChatOpenAI(temperature=self.settings.openai.agent_temperature, openai_api_key=self.settings.openai.api_key.get_secret_value())
+        llm = langchain.chat_models.ChatOpenAI(
+            temperature=self.settings.openai.agent_temperature,
+            openai_api_key=self.settings.openai.api_key.get_secret_value(),
+        )
 
         chat_history = []
         chat_history_name = f"{chat_history=}".partition("=")[0]
 
         request_chat_history = models.RequestChatHistory(session_id=session_id)
         chat_history_source = await self.chat_repository.get_messages_by_sid(request_chat_history)
+        if not chat_history_source:
             for entry in chat_history_source:
                 if entry.role == "user":
                     chat_history.append(langchain.schema.HumanMessage(content=entry.content))
                 elif entry.role == "agent":
                     chat_history.append(langchain.schema.AIMessage(content=entry.content))
 
-
         prompt = langchain.prompts.ChatPromptTemplate.from_messages(
             [
                 (
@@ -94,7 +92,6 @@ class AgentService:
             | langchain.agents.output_parsers.OpenAIFunctionsAgentOutputParser()
         )
 
-
         agent_executor = langchain.agents.AgentExecutor(agent=agent, tools=tools, verbose=False)
         chat_history = []  # temporary disable chat_history
         response = await agent_executor.ainvoke({"input": request.text, "chat_history": chat_history})
@@ -103,16 +100,18 @@ class AgentService:
             session_id=session_id,
             user_id=request.user_id,
             channel=request.channel,
-            message={"role": "user", "content": request.text}
+            message={"role": "user", "content": request.text},
         )
         ai_response = models.RequestChatMessage(
             session_id=session_id,
             user_id=request.user_id,
             channel=request.channel,
-            message={"role": "assistant", "content": response["output"]}
+            message={"role": "assistant", "content": response["output"]},
         )
 
         await self.chat_repository.add_message(user_request)
         await self.chat_repository.add_message(ai_response)
 
-        return response
+        print("RES:", response)
+
+        return models.AgentCreateResponseModel(text="response")

src/assistant/lib/api/v1/handlers/__init__.py

@@ -1,10 +1,7 @@
-from .agent import AgentHandler
 from .health import basic_router
 from .voice_responce_handler import VoiceResponseHandler
 
-
 __all__ = [
-   "AgentHandler",
     "VoiceResponseHandler",
     "basic_router",
 ]

src/assistant/lib/api/v1/handlers/agent.py

@@ -1,59 +0,0 @@
-import uuid
-
-import fastapi
-
-import lib.agent.repositories as agent_repositories
-import lib.models as models
-
-
-class AgentHandler:
-    def __init__(self, chat_history_repository: agent_repositories.ChatHistoryRepository):
-        self.chat_history_repository = chat_history_repository
-        self.router = fastapi.APIRouter()
-        self.router.add_api_route(
-            "/",
-            self.get_agent,
-            methods=["GET"],
-            summary="Статус работоспособности",
-            description="Проверяет доступность сервиса FastAPI.",
-        )
-        self.router.add_api_route(
-            "/add",
-            self.add_message,
-            methods=["GET"],
-            summary="Статус работоспособности",
-            description="Проверяет доступность сервиса FastAPI.",
-        )
-        self.router.add_api_route(
-            "/messages",
-            self.get_messages,
-            methods=["GET"],
-            summary="Статус работоспособности",
-            description="Проверяет доступность сервиса FastAPI.",
-        )
-
-    async def get_agent(self):
-        request = models.RequestLastSessionId(channel="test", user_id="user_id_1", minutes_ago=3)
-        response = await self.chat_history_repository.get_last_session_id(request=request)
-        print("RESPONSE: ", response)
-        return {"response": response}
-
-    async def add_message(self):
-        sid: uuid.UUID = uuid.UUID("0cd3c882-affd-4929-aff1-e1724f5b54f2")
-        import faker
-
-        fake = faker.Faker()
-
-        message = models.RequestChatMessage(
-            session_id=sid, user_id="user_id_1", channel="test", message={"role": "system", "content": fake.sentence()}
-        )
-        await self.chat_history_repository.add_message(request=message)
-        return {"response": "ok"}
-
-    async def get_messages(self):
-        sid: uuid.UUID = uuid.UUID("0cd3c882-affd-4929-aff1-e1724f5b54f2")
-
-        request = models.RequestChatHistory(session_id=sid)
-        response = await self.chat_history_repository.get_messages_by_sid(request=request)
-        print("RESPONSE: ", response)
-        return {"response": response}

src/assistant/lib/api/v1/handlers/voice_responce_handler.py

@@ -3,10 +3,10 @@ import io
 
 import fastapi
 
-import lib.stt.services as stt_services
 import lib.agent.services as agent_service
-import lib.tts.services as tts_service
 import lib.models as models
+import lib.stt.services as stt_services
+import lib.tts.services as tts_service
 
 
 class VoiceResponseHandler:
@@ -14,11 +14,11 @@ class VoiceResponseHandler:
         self,
         stt: stt_services.SpeechService,
         tts: tts_service.TTSService,
-        # agent: agent_service.AgentService,
+        agent: agent_service.AgentService,
     ):
         self.stt = stt
         self.tts = tts
-        # self.agent = agent
+        self.agent = agent
         self.router = fastapi.APIRouter()
         self.router.add_api_route(
             "/",
@@ -38,12 +38,12 @@ class VoiceResponseHandler:
         if voice_text == "":
             raise fastapi.HTTPException(status_code=http.HTTPStatus.BAD_REQUEST, detail="Speech recognition failed")
 
-        # agent_request = models.AgentCreateRequestModel(channel=channel, user_id=user_id, text=voice_text)
+        agent_request = models.AgentCreateRequestModel(channel=channel, user_id=user_id, text=voice_text)
-        # reply_text = await self.agent.process_request(agent_request)
+        reply_text = await self.agent.process_request(agent_request)
-        reply_text = "hi there"
+
         response = await self.tts.get_audio_as_bytes(
             models.TTSCreateRequestModel(
-                text=reply_text,
+                text=reply_text.text,
             )
         )
         return fastapi.responses.StreamingResponse(io.BytesIO(response.audio_content), media_type="audio/ogg")

src/assistant/lib/app/app.py

@@ -6,6 +6,9 @@ import typing
 import fastapi
 import uvicorn
 
+import lib.agent.repositories as agent_repositories
+import lib.agent.repositories.openai_functions as agent_functions
+import lib.agent.services as agent_services
 import lib.api.v1.handlers as api_v1_handlers
 import lib.app.errors as app_errors
 import lib.app.settings as app_settings
@@ -14,9 +17,6 @@ import lib.clients as clients
 import lib.models as models
 import lib.stt as stt
 import lib.tts as tts
-import lib.agent.repositories as agent_repositories
-import lib.agent.repositories.openai_functions as agent_functions
-import lib.agent.services as agent_services
 
 logger = logging.getLogger(__name__)
 
@@ -92,9 +92,14 @@ class Application:
 
         logger.info("Initializing repositories")
         stt_repository: stt.STTProtocol = stt.OpenaiSpeechRepository(settings=settings)
-        chat_history_repository = agent_repositories.ChatHistoryRepository(pg_async_session=postgres_client.get_async_session())
+        chat_history_repository = agent_repositories.ChatHistoryRepository(
-        embedding_repository = agent_repositories.EmbeddingRepository(settings)
+            pg_async_session=postgres_client.get_async_session()
-
+        )
+        embedding_repository = agent_repositories.EmbeddingRepository(settings=settings)
+        agent_tools = agent_functions.OpenAIFunctions(
+            repository=embedding_repository, pg_async_session=postgres_client.get_async_session()
+        )
+        agent_tools = None
         tts_yandex_repository = tts.TTSYandexRepository(
             tts_settings=app_split_settings.TTSYandexSettings(),
             client=http_yandex_tts_client,
@@ -105,43 +110,40 @@ class Application:
             is_models_from_api=True,
         )
 
-
         # Caches
 
         logger.info("Initializing caches")
 
         # Tools
 
-        agent_tools = agent_functions.OpenAIFunctions(repository=embedding_repository, pg_async_session=postgres_client.get_async_session())
-
         # Services
 
         logger.info("Initializing services")
 
+        stt_service: stt.SpeechService = stt.SpeechService(repository=stt_repository)
 
-        stt_service: stt.SpeechService = stt.SpeechService(repository=stt_repository)   # type: ignore
+        tts_service: tts.TTSService = tts.TTSService(
-
-        tts_service: tts.TTSService = tts.TTSService(  # type: ignore
             repositories={
                 models.VoiceModelProvidersEnum.YANDEX: tts_yandex_repository,
                 models.VoiceModelProvidersEnum.ELEVEN_LABS: tts_eleven_labs_repository,
             },
         )
         
-        agent_service: agent_services.AgentService(settings=settings, chat_repository=chat_history_repository)
+        agent_service = agent_services.AgentService(
-        # agent_service: agent_services.AgentService(settings=settings, chat_repository=chat_history_repository, tools=agent_tools)
+            settings=settings, chat_repository=chat_history_repository, tools=agent_tools
+        )
+
 
         # Handlers
 
         logger.info("Initializing handlers")
         liveness_probe_handler = api_v1_handlers.basic_router
-        agent_handler = api_v1_handlers.AgentHandler(chat_history_repository=chat_history_repository).router
 
         # TODO: объявить сервисы tts и openai и добавить их в voice_response_handler
         voice_response_handler = api_v1_handlers.VoiceResponseHandler(
             stt=stt_service,
             tts=tts_service,
-            agent=agent_services,
+            agent=agent_service,
         ).router
 
         logger.info("Creating application")
@@ -156,7 +158,6 @@ class Application:
 
         # Routes
         fastapi_app.include_router(liveness_probe_handler, prefix="/api/v1/health", tags=["health"])        
-        fastapi_app.include_router(agent_handler, prefix="/api/v1/agent", tags=["testing"])
         fastapi_app.include_router(voice_response_handler, prefix="/api/v1/voice", tags=["voice"])
 
         application = Application(

src/assistant/lib/models/__init__.py

@@ -1,21 +1,19 @@
+from .agent import *
 from .chat_history import Message, RequestChatHistory, RequestChatMessage, RequestLastSessionId
 from .embedding import Embedding
 from .movies import Movie
 from .token import Token
 from .tts import *
-from .agent import *
-
 
 # __all__ = ["Embedding", "Message", "Movie", "RequestChatHistory", "RequestChatMessage", "RequestLastSessionId", "Token"]
 __all__ = [
     "AVAILABLE_MODELS_TYPE",
-    # "Base",
+    "AgentCreateRequestModel",
     "BaseLanguageCodesEnum",
     "BaseVoiceModel",
     "ElevenLabsLanguageCodesEnum",
     "ElevenLabsListVoiceModelsModel",
     "ElevenLabsVoiceModel",
-    # "IdCreatedUpdatedBaseMixin",
     "LANGUAGE_CODES_ENUM_TYPE",
     "LIST_VOICE_MODELS_TYPE",
     "TTSCreateRequestModel",
@@ -26,5 +24,4 @@ __all__ = [
     "YandexLanguageCodesEnum",
     "YandexListVoiceModelsModel",
     "YandexVoiceModel",
-    "AgentCreateRequestModel",
 ]

src/assistant/lib/models/agent.py

@@ -1,5 +1,3 @@
-import uuid
-
 import pydantic
 
 

src/assistant/pyproject.toml

@@ -25,21 +25,21 @@ asyncpg = "^0.28.0"
 fastapi = "0.103.1"
 greenlet = "^2.0.2"
 httpx = "^0.25.0"
+langchain = "^0.0.314"
 multidict = "^6.0.4"
+openai = "^0.28.1"
 orjson = "^3.9.7"
+pgvector = "^0.2.3"
 psycopg2-binary = "^2.9.9"
 pydantic = {extras = ["email"], version = "^2.3.0"}
 pydantic-settings = "^2.0.3"
 pytest-asyncio = "^0.21.1"
 python = "^3.11"
 python-jose = "^3.3.0"
+python-magic = "^0.4.27"
+python-multipart = "^0.0.6"
 sqlalchemy = "^2.0.20"
 uvicorn = "^0.23.2"
-pgvector = "^0.2.3"
-python-magic = "^0.4.27"
-openai = "^0.28.1"
-python-multipart = "^0.0.6"
-langchain = "^0.0.314"
 
 [tool.poetry.dev-dependencies]
 black = "^23.7.0"