global client

agent.py

@@ -1,7 +1,6 @@
 from dotenv import load_dotenv
 from strictjson import strict_json_async
 
-from client import HybridClient
 from prompts import AGENT_PROMPT, RAG_SYS_PROMPT, RAG_USER_PROMPT
 from sarvam import speaker, translator
 
@@ -53,24 +52,21 @@ async def call_agent(user_prompt, grade, subject):
     return result
 
 
-async def function_caller(user_prompt, grade, subject, chapter):
+async def function_caller(user_prompt, collection, client):
+    grade, subject, chapter = collection.split("_")
+
     result = await call_agent(user_prompt, grade, subject)
-    print(result)
     function = result["function"].lower()
 
     if function == "none":
         return result["response"]
 
     elif function == "retriever":
-        client = HybridClient()
-        collection = f"{grade}_{subject.lower()}_{chapter}"
-
         data = client.search(collection, user_prompt)
         data = [i.document for i in data]
 
         system_prompt = RAG_SYS_PROMPT.format(subject, grade)
         user_prompt = RAG_USER_PROMPT.format(data, user_prompt)
-        print(user_prompt)
 
         response = await llm(system_prompt, user_prompt)
 

app.py

@@ -7,8 +7,10 @@ from fastapi.middleware.cors import CORSMiddleware
 from pydantic import BaseModel
 
 from agent import function_caller
+from client import HybridClient
 
 app = FastAPI()
+hclient = HybridClient()
 
 app.add_middleware(
     CORSMiddleware,
@@ -21,14 +23,12 @@ app.add_middleware(
 
 class ChatQuery(BaseModel):
     query: str
-    grade: str
-    subject: str
-    chapter: str
+    collection: str
 
 
 @app.post("/chat")
 async def chat(query: ChatQuery):
-    result = await function_caller(query.query, query.grade, query.subject, query.chapter)
+    result = await function_caller(query.query, query.collection, hclient)
 
     if isinstance(result, str):
         return {"text": result}
@@ -43,7 +43,8 @@ async def chat(query: ChatQuery):
 
 
 async def gradio_interface(input_text, grade, subject, chapter):
-    response = await chat(ChatQuery(query=input_text, grade=grade, subject=subject, chapter=chapter))
+    collection = f"{grade}_{subject.lower()}_{chapter}"
+    response = await chat(ChatQuery(query=input_text, collection=collection))
     if "text" in response:
         return response["text"], None
     elif "audio" in response: