refactor dialogue manager initialization & usage

app/admin/train/routes.py

@@ -1,4 +1,4 @@
-from fastapi import APIRouter, HTTPException, BackgroundTasks, Request
+from fastapi import APIRouter, HTTPException, BackgroundTasks
 from app.admin.intents import store
 from app.bot.nlu.training import train_pipeline
 
@@ -29,9 +29,9 @@ async def get_training_data(intent_id: str):
     return intent.trainingData
 
 @router.post('/build_models')
-async def build_models(request: Request, background_tasks: BackgroundTasks):
+async def build_models(background_tasks: BackgroundTasks):
     """
     Build Intent classification and NER Models
     """
-    background_tasks.add_task(train_pipeline, request.app)
+    background_tasks.add_task(train_pipeline)
     return {"status": "training started in the background"}

app/bot/chat/routes.py

@@ -1,20 +1,20 @@
-from fastapi import APIRouter, HTTPException, Body, Request
+from fastapi import APIRouter, HTTPException, Body, Request, Depends
 from app.bot.dialogue_manager.models import ChatModel
+from app.dependencies import get_dialogue_manager
 
 router = APIRouter(prefix="/v1", tags=["bots"])
 
 @router.post("/chat")
-async def chat(request: Request, body: dict):
+async def chat(request: Request, body: dict, dialogue_manager = Depends(get_dialogue_manager)):
     """
     Endpoint to converse with the chatbot.
     Delegates the request processing to DialogueManager.
 
     :return: JSON response with the chatbot's reply and context.
     """
-    try:
-        # Access the dialogue manager from the fast api application state.
-        chat_request = ChatModel.from_json(body)
-        chat_response = await request.app.state.dialogue_manager.process(chat_request)
-        return chat_response.to_json()
-    except Exception as e:
-        raise HTTPException(status_code=500, detail=f"Error processing request: {e}")
+
+    # Access the dialogue manager from the fast api application state.
+    chat_request = ChatModel.from_json(body)
+    chat_response = await dialogue_manager.process(chat_request)
+    return chat_response.to_json()
+

app/bot/nlu/training.py

@@ -7,10 +7,10 @@
 from app.bot.nlu.intent_classifiers import IntentClassifier
 from app.bot.nlu.entity_extractors import EntityExtractor
 from app.admin.entities.store import list_synonyms
-
+from app.dependencies import set_dialogue_manager
 from app.config import app_config
 
-async def train_pipeline(app):
+async def train_pipeline():
     """
     Initiate NLU pipeline training
     :return:
@@ -46,7 +46,10 @@ async def train_pipeline(app):
     pipeline.train(training_data, models_dir)
 
     # recreate dialogue manager with new data
-    app.state.dialogue_manager = await DialogueManager.from_config()
+    dialogue_manager = await DialogueManager.from_config()
 
     # update dialogue manager with new models
-    app.state.dialogue_manager.update_model(models_dir)
+    dialogue_manager.update_model(models_dir)
+
+    await set_dialogue_manager(dialogue_manager)
+

app/dependencies.py

@@ -0,0 +1,20 @@
+from typing import Optional
+from app.bot.dialogue_manager.dialogue_manager import DialogueManager
+from app.config import app_config
+
+_dialogue_manager: Optional[DialogueManager] = None
+
+async def get_dialogue_manager():
+    global _dialogue_manager
+    return _dialogue_manager
+
+async def set_dialogue_manager(dialogue_manager: DialogueManager):
+    global _dialogue_manager
+    _dialogue_manager = dialogue_manager
+
+async def init_dialogue_manager():
+    global _dialogue_manager
+    print("initializing dialogue manager")
+    _dialogue_manager = await DialogueManager.from_config()
+    _dialogue_manager.update_model(app_config.MODELS_DIR)
+    print("dialogue manager initialized")

app/main.py

@@ -2,32 +2,25 @@
 from contextlib import asynccontextmanager
 from fastapi.middleware.cors import CORSMiddleware
 from fastapi.staticfiles import StaticFiles
-from fastapi import FastAPI
-from app.bot.dialogue_manager.dialogue_manager import DialogueManager
+from fastapi import FastAPI, APIRouter
 from app.database import client as database_client
+from app.dependencies import init_dialogue_manager
 
 from app.admin.bots.routes import router as bots_router
 from app.admin.entities.routes import router as entities_router
 from app.admin.intents.routes import router as intents_router
 from app.admin.train.routes import router as train_router
 from app.bot.chat.routes import router as chat_router
-from app.config import app_config
 
-@asynccontextmanager
-async def lifespan(app: FastAPI):
-    # initialize dialogue_manager
-    dialogue_manager = await DialogueManager.from_config()
-    dialogue_manager.update_model(app_config.MODELS_DIR)
-    app.state.dialogue_manager : DialogueManager = dialogue_manager
-    print("dialogue manager loaded")
-
-    yield
 
+@asynccontextmanager
+async def lifespan(_):
+    await init_dialogue_manager()
+    yield 
     database_client.close()
 
 app = FastAPI(title="AI Chatbot Framework",lifespan=lifespan)
 
-# CORS middleware
 app.add_middleware(
     CORSMiddleware,
     allow_origins=["*"],
@@ -36,10 +29,8 @@ async def lifespan(app: FastAPI):
     allow_headers=["*"],
 )
 
-# Static files
 app.mount("/static", StaticFiles(directory="app/static"), name="static")
 
-
 @app.get("/ready")
 async def ready():
     return {"status": "ok"}
@@ -48,9 +39,12 @@ async def ready():
 async def root():
     return {"message": "Welcome to AI Chatbot Framework API"}
 
+# admin apis
+admin_router = APIRouter(prefix="/admin", tags=["admin"])
+admin_router.include_router(bots_router)
+admin_router.include_router(intents_router)
+admin_router.include_router(entities_router)
+admin_router.include_router(train_router)
+app.include_router(admin_router)
 
-app.include_router(bots_router, prefix="/admin", tags=["bots"])
-app.include_router(intents_router, prefix="/admin", tags=["intents"])
-app.include_router(entities_router, prefix="/admin", tags=["entities"])
-app.include_router(train_router, prefix="/admin", tags=["train"])
 app.include_router(chat_router, prefix="/bots", tags=["bots"])