feat: [#45] llm_agent

src/assistant/lib/agent/__init__.py

@@ -1,3 +1,5 @@
-from .chat_repository import ChatHistoryRepository
+from .services import AgentService
 
-__all__ = ["ChatHistoryRepository"]
+__all__ = [
+    "AgentService",
+]

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

@@ -0,0 +1,9 @@
+from .chat_repository import ChatHistoryRepository
+from .embedding_repository import EmbeddingRepository
+from .openai_functions import OpenAIFunctions
+
+__all__ = [
+    "ChatHistoryRepository",
+    "EmbeddingRepository",
+    "OpenAIFunctions",
+]

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

@@ -1,7 +1,5 @@
 import logging
-import uuid
 
-import langchain.agents
 import sqlalchemy as sa
 import sqlalchemy.exc
 import sqlalchemy.ext.asyncio as sa_asyncio
@@ -23,28 +21,6 @@ class OpenAIFunctions:
         self.pg_async_session = pg_async_session
         self.repository = repository
 
-    @langchain.agents.tool
-    async def artem_get_movie_by_description(self, description: str) -> list[models.Movie] | None:
-        """Provide a movie data by description."""
-
-        self.logger.info("Request to get movie by description: %s", description)
-        embedded_description = await self.repository.aget_embedding(description)
-        try:
-            async with self.pg_async_session() as session:
-                result: list[models.Movie] = []
-                stmt = (
-                    sa.select(orm_models.FilmWork)
-                    .order_by(orm_models.FilmWork.embeddings.cosine_distance(embedded_description.root))
-                    .limit(5)
-                )
-                response = await session.execute(stmt)
-                neighbours = response.scalars()
-                for neighbour in neighbours:
-                    result.append(models.Movie(**neighbour.__dict__))
-                return result
-        except sqlalchemy.exc.SQLAlchemyError as error:
-            self.logger.exception("Error: %s", error)
-
     async def get_movie_by_description(self, description: str) -> list[models.Movie] | None:
         """Provide a movie data by description."""
 
@@ -65,16 +41,3 @@ class OpenAIFunctions:
                 return result
         except sqlalchemy.exc.SQLAlchemyError as error:
             self.logger.exception("Error: %s", error)
-
-    @langchain.agents.tool
-    def get_movie_by_id(self, id: uuid.UUID = None) -> models.Movie | None:
-        """Provide a movie data by movie id."""
-        # self.logger.info("Request to get movie by id: %s", id)
-        return f"hello world {id}"
-
-    @langchain.agents.tool
-    def get_similar_movies(self, id: uuid.UUID) -> list[models.Movie] | None:
-        """Provide similar movies for the given movie ID."""
-
-        self.logger.info("Request to get movie by id: %s", id)
-        return None

src/assistant/lib/agent/services.py

@@ -15,16 +15,15 @@ import langchain.memory
 import langchain.memory.chat_memory
 
 import lib.models as models
-import lib.agent.openai_functions as openai_functions
+import lib.agent.repositories as lib_agent_repositories
 import lib.app.settings as app_settings
-import lib.agent.chat_repository as _chat_repository
+import lib.agent.repositories.chat_repository as _chat_repository
 
 
 class AgentService:
     def __init__(
         self,
         settings: app_settings.Settings,
-        tools: openai_functions.OpenAIFunctions,
         chat_repository: _chat_repository.ChatHistoryRepository,
     ) -> None:
         self.settings = settings

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

@@ -7,7 +7,7 @@ import lib.models as models
 
 
 class AgentHandler:
-    def __init__(self, chat_history_repository: agent.ChatHistoryRepository):
+    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(

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

@@ -28,6 +28,8 @@ class VoiceResponseHandler:
 
     async def voice_response(
         self,
+        channel: str,
+        user_id: str,
         voice: bytes = fastapi.File(...),
     ) -> fastapi.responses.StreamingResponse:
         voice_text: str = await self.stt.recognize(voice)

src/assistant/lib/app/app.py

@@ -6,7 +6,6 @@ import typing
 import fastapi
 import uvicorn
 
-import lib.agent as agent
 import lib.api.v1.handlers as api_v1_handlers
 import lib.app.errors as app_errors
 import lib.app.settings as app_settings