mirror of
https://github.com/ijaric/voice_assistant.git
synced 2025-05-24 06:23:28 +00:00
fix: start error & linting
This commit is contained in:
Artem Litvinov
parent
288af57ab5
commit
2344b576d8
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@ -1,5 +1,5 @@
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from .services import AgentService
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# from .services import AgentService
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__all__ = [
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"AgentService",
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]
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# __all__ = [
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# "AgentService",
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# ]
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@ -1,7 +1,6 @@
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import logging
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import typing
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import langchain.chat_models
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import openai
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import openai.error
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@ -40,25 +39,3 @@ class EmbeddingRepository:
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except openai.error.OpenAIError:
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self.logger.exception("Failed to get async embedding for: %s", text)
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class LlmRepository:
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"""A service for getting embeddings from OpenAI."""
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def __init__(self, settings: app_settings.Settings) -> None:
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"""Initialize the service with an OpenAI API key."""
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self.llm = langchain.chat_models.ChatOpenAI(
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temperature=0.7,
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openai_api_key=self.settings.openai.api_key.get_secret_value()
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)
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async def get_chat_response(self, request: str, prompt: str) -> str:
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"""Get the embedding for a given text."""
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prompt = langchain.prompts.ChatPromptTemplate.from_messages(
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[
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("system", prompt),
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]
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)
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chain = prompt | self.llm
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response = await chain.ainvoke({"input": request})
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return response.content
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@ -5,38 +5,33 @@ import langchain.agents
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import langchain.agents.format_scratchpad
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import langchain.agents.output_parsers
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import langchain.chat_models
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import langchain.memory
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import langchain.memory.chat_memory
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import langchain.prompts
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import langchain.schema
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import langchain.tools.render
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import langchain.memory
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import langchain.memory.chat_memory
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import lib.models as models
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import lib.agent.repositories as lib_agent_repositories
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import lib.agent.repositories.chat_repository as chat_repositories
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import lib.app.settings as app_settings
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import lib.agent.repositories.chat_repository as _chat_repository
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import lib.models as models
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class AgentService:
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def __init__(
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self,
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settings: app_settings.Settings,
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chat_repository: _chat_repository.ChatHistoryRepository,
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tools: lib_agent_repositories.OpenAIFunctions | None = None,
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chat_repository: chat_repositories.ChatHistoryRepository,
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tools: lib_agent_repositories.OpenAIFunctions,
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) -> None:
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self.settings = settings
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self.tools = tools
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self.chat_repository = chat_repository
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self.logger = logging.getLogger(__name__)
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async def process_request(self, request: models.AgentCreateRequestModel) -> models.AgentCreateResponseModel:
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# Get session ID
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session_request = models.RequestLastSessionId(
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channel=request.channel,
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user_id=request.user_id,
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minutes_ago=3
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)
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session_request = models.RequestLastSessionId(channel=request.channel, user_id=request.user_id, minutes_ago=3)
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session_id = await self.chat_repository.get_last_session_id(session_request)
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if not session_id:
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session_id = uuid.uuid4()
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@ -47,23 +42,26 @@ class AgentService:
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name="GetMovieByDescription",
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func=self.tools.get_movie_by_description,
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coroutine=self.tools.get_movie_by_description,
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description="Get a movie by description"
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description="Get a movie by description",
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),
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]
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llm = langchain.chat_models.ChatOpenAI(temperature=self.settings.openai.agent_temperature, openai_api_key=self.settings.openai.api_key.get_secret_value())
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llm = langchain.chat_models.ChatOpenAI(
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temperature=self.settings.openai.agent_temperature,
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openai_api_key=self.settings.openai.api_key.get_secret_value(),
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)
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chat_history = []
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chat_history_name = f"{chat_history=}".partition("=")[0]
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request_chat_history = models.RequestChatHistory(session_id=session_id)
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chat_history_source = await self.chat_repository.get_messages_by_sid(request_chat_history)
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for entry in chat_history_source:
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if entry.role == "user":
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chat_history.append(langchain.schema.HumanMessage(content=entry.content))
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elif entry.role == "agent":
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chat_history.append(langchain.schema.AIMessage(content=entry.content))
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if not chat_history_source:
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for entry in chat_history_source:
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if entry.role == "user":
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chat_history.append(langchain.schema.HumanMessage(content=entry.content))
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elif entry.role == "agent":
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chat_history.append(langchain.schema.AIMessage(content=entry.content))
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prompt = langchain.prompts.ChatPromptTemplate.from_messages(
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[
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@ -94,7 +92,6 @@ class AgentService:
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| langchain.agents.output_parsers.OpenAIFunctionsAgentOutputParser()
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)
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agent_executor = langchain.agents.AgentExecutor(agent=agent, tools=tools, verbose=False)
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chat_history = [] # temporary disable chat_history
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response = await agent_executor.ainvoke({"input": request.text, "chat_history": chat_history})
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@ -103,16 +100,18 @@ class AgentService:
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session_id=session_id,
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user_id=request.user_id,
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channel=request.channel,
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message={"role": "user", "content": request.text}
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message={"role": "user", "content": request.text},
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)
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ai_response = models.RequestChatMessage(
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session_id=session_id,
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user_id=request.user_id,
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channel=request.channel,
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message={"role": "assistant", "content": response["output"]}
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message={"role": "assistant", "content": response["output"]},
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)
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await self.chat_repository.add_message(user_request)
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await self.chat_repository.add_message(ai_response)
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return response
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print("RES:", response)
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return models.AgentCreateResponseModel(text="response")
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@ -1,10 +1,7 @@
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from .agent import AgentHandler
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from .health import basic_router
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from .voice_responce_handler import VoiceResponseHandler
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__all__ = [
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"AgentHandler",
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"VoiceResponseHandler",
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"basic_router",
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]
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@ -1,59 +0,0 @@
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import uuid
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import fastapi
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import lib.agent.repositories as agent_repositories
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import lib.models as models
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class AgentHandler:
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def __init__(self, chat_history_repository: agent_repositories.ChatHistoryRepository):
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self.chat_history_repository = chat_history_repository
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self.router = fastapi.APIRouter()
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self.router.add_api_route(
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"/",
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self.get_agent,
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methods=["GET"],
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summary="Статус работоспособности",
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description="Проверяет доступность сервиса FastAPI.",
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)
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self.router.add_api_route(
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"/add",
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self.add_message,
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methods=["GET"],
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summary="Статус работоспособности",
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description="Проверяет доступность сервиса FastAPI.",
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)
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self.router.add_api_route(
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"/messages",
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self.get_messages,
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methods=["GET"],
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summary="Статус работоспособности",
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description="Проверяет доступность сервиса FastAPI.",
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)
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async def get_agent(self):
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request = models.RequestLastSessionId(channel="test", user_id="user_id_1", minutes_ago=3)
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response = await self.chat_history_repository.get_last_session_id(request=request)
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print("RESPONSE: ", response)
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return {"response": response}
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async def add_message(self):
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sid: uuid.UUID = uuid.UUID("0cd3c882-affd-4929-aff1-e1724f5b54f2")
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import faker
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fake = faker.Faker()
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message = models.RequestChatMessage(
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session_id=sid, user_id="user_id_1", channel="test", message={"role": "system", "content": fake.sentence()}
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)
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await self.chat_history_repository.add_message(request=message)
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return {"response": "ok"}
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async def get_messages(self):
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sid: uuid.UUID = uuid.UUID("0cd3c882-affd-4929-aff1-e1724f5b54f2")
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request = models.RequestChatHistory(session_id=sid)
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response = await self.chat_history_repository.get_messages_by_sid(request=request)
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print("RESPONSE: ", response)
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return {"response": response}
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@ -3,10 +3,10 @@ import io
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import fastapi
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import lib.stt.services as stt_services
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import lib.agent.services as agent_service
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import lib.tts.services as tts_service
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import lib.models as models
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import lib.stt.services as stt_services
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import lib.tts.services as tts_service
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class VoiceResponseHandler:
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@ -14,11 +14,11 @@ class VoiceResponseHandler:
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self,
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stt: stt_services.SpeechService,
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tts: tts_service.TTSService,
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# agent: agent_service.AgentService,
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agent: agent_service.AgentService,
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):
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self.stt = stt
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self.tts = tts
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# self.agent = agent
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self.agent = agent
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self.router = fastapi.APIRouter()
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self.router.add_api_route(
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"/",
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@ -38,12 +38,12 @@ class VoiceResponseHandler:
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if voice_text == "":
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raise fastapi.HTTPException(status_code=http.HTTPStatus.BAD_REQUEST, detail="Speech recognition failed")
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# agent_request = models.AgentCreateRequestModel(channel=channel, user_id=user_id, text=voice_text)
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# reply_text = await self.agent.process_request(agent_request)
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reply_text = "hi there"
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agent_request = models.AgentCreateRequestModel(channel=channel, user_id=user_id, text=voice_text)
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reply_text = await self.agent.process_request(agent_request)
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response = await self.tts.get_audio_as_bytes(
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models.TTSCreateRequestModel(
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text=reply_text,
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text=reply_text.text,
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)
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)
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return fastapi.responses.StreamingResponse(io.BytesIO(response.audio_content), media_type="audio/ogg")
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@ -6,6 +6,9 @@ import typing
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import fastapi
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import uvicorn
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import lib.agent.repositories as agent_repositories
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import lib.agent.repositories.openai_functions as agent_functions
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import lib.agent.services as agent_services
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import lib.api.v1.handlers as api_v1_handlers
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import lib.app.errors as app_errors
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import lib.app.settings as app_settings
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@ -14,9 +17,6 @@ import lib.clients as clients
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import lib.models as models
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import lib.stt as stt
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import lib.tts as tts
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import lib.agent.repositories as agent_repositories
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import lib.agent.repositories.openai_functions as agent_functions
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import lib.agent.services as agent_services
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logger = logging.getLogger(__name__)
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@ -92,9 +92,14 @@ class Application:
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logger.info("Initializing repositories")
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stt_repository: stt.STTProtocol = stt.OpenaiSpeechRepository(settings=settings)
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chat_history_repository = agent_repositories.ChatHistoryRepository(pg_async_session=postgres_client.get_async_session())
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embedding_repository = agent_repositories.EmbeddingRepository(settings)
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chat_history_repository = agent_repositories.ChatHistoryRepository(
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pg_async_session=postgres_client.get_async_session()
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)
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embedding_repository = agent_repositories.EmbeddingRepository(settings=settings)
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agent_tools = agent_functions.OpenAIFunctions(
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repository=embedding_repository, pg_async_session=postgres_client.get_async_session()
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)
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agent_tools = None
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tts_yandex_repository = tts.TTSYandexRepository(
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tts_settings=app_split_settings.TTSYandexSettings(),
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client=http_yandex_tts_client,
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@ -105,43 +110,40 @@ class Application:
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is_models_from_api=True,
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)
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# Caches
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logger.info("Initializing caches")
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# Tools
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agent_tools = agent_functions.OpenAIFunctions(repository=embedding_repository, pg_async_session=postgres_client.get_async_session())
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# Services
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logger.info("Initializing services")
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stt_service: stt.SpeechService = stt.SpeechService(repository=stt_repository)
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stt_service: stt.SpeechService = stt.SpeechService(repository=stt_repository) # type: ignore
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tts_service: tts.TTSService = tts.TTSService( # type: ignore
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tts_service: tts.TTSService = tts.TTSService(
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repositories={
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models.VoiceModelProvidersEnum.YANDEX: tts_yandex_repository,
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models.VoiceModelProvidersEnum.ELEVEN_LABS: tts_eleven_labs_repository,
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},
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)
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agent_service = agent_services.AgentService(
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settings=settings, chat_repository=chat_history_repository, tools=agent_tools
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)
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agent_service: agent_services.AgentService(settings=settings, chat_repository=chat_history_repository)
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# agent_service: agent_services.AgentService(settings=settings, chat_repository=chat_history_repository, tools=agent_tools)
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# Handlers
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logger.info("Initializing handlers")
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liveness_probe_handler = api_v1_handlers.basic_router
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agent_handler = api_v1_handlers.AgentHandler(chat_history_repository=chat_history_repository).router
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# TODO: объявить сервисы tts и openai и добавить их в voice_response_handler
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voice_response_handler = api_v1_handlers.VoiceResponseHandler(
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stt=stt_service,
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tts=tts_service,
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agent=agent_services,
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agent=agent_service,
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).router
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logger.info("Creating application")
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@ -155,8 +157,7 @@ class Application:
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)
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# Routes
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fastapi_app.include_router(liveness_probe_handler, prefix="/api/v1/health", tags=["health"])
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fastapi_app.include_router(agent_handler, prefix="/api/v1/agent", tags=["testing"])
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fastapi_app.include_router(liveness_probe_handler, prefix="/api/v1/health", tags=["health"])
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fastapi_app.include_router(voice_response_handler, prefix="/api/v1/voice", tags=["voice"])
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application = Application(
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@ -1,21 +1,19 @@
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from .agent import *
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from .chat_history import Message, RequestChatHistory, RequestChatMessage, RequestLastSessionId
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from .embedding import Embedding
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from .movies import Movie
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from .token import Token
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from .tts import *
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from .agent import *
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# __all__ = ["Embedding", "Message", "Movie", "RequestChatHistory", "RequestChatMessage", "RequestLastSessionId", "Token"]
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__all__ = [
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"AVAILABLE_MODELS_TYPE",
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# "Base",
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"AgentCreateRequestModel",
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"BaseLanguageCodesEnum",
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"BaseVoiceModel",
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"ElevenLabsLanguageCodesEnum",
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"ElevenLabsListVoiceModelsModel",
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"ElevenLabsVoiceModel",
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# "IdCreatedUpdatedBaseMixin",
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"LANGUAGE_CODES_ENUM_TYPE",
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"LIST_VOICE_MODELS_TYPE",
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"TTSCreateRequestModel",
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@ -26,5 +24,4 @@ __all__ = [
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"YandexLanguageCodesEnum",
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"YandexListVoiceModelsModel",
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"YandexVoiceModel",
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"AgentCreateRequestModel",
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]
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|
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@ -1,5 +1,3 @@
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import uuid
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import pydantic
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|
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@ -25,21 +25,21 @@ asyncpg = "^0.28.0"
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fastapi = "0.103.1"
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greenlet = "^2.0.2"
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httpx = "^0.25.0"
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langchain = "^0.0.314"
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multidict = "^6.0.4"
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openai = "^0.28.1"
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orjson = "^3.9.7"
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pgvector = "^0.2.3"
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psycopg2-binary = "^2.9.9"
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pydantic = {extras = ["email"], version = "^2.3.0"}
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pydantic-settings = "^2.0.3"
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pytest-asyncio = "^0.21.1"
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python = "^3.11"
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python-jose = "^3.3.0"
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python-magic = "^0.4.27"
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python-multipart = "^0.0.6"
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sqlalchemy = "^2.0.20"
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uvicorn = "^0.23.2"
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pgvector = "^0.2.3"
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python-magic = "^0.4.27"
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openai = "^0.28.1"
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python-multipart = "^0.0.6"
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langchain = "^0.0.314"
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[tool.poetry.dev-dependencies]
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black = "^23.7.0"
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