import os
from langchain.agents import initialize_agent, Tool
from langchain.llms import Ollama
from langchain.chains import RetrievalQA
from langchain_ollama import OllamaEmbeddings
from langchain_chroma import Chroma
from src.utils import search_course_docs
from src.mcp_tool import fetch_course_meta, start_meta_server

# Start mock server
start_meta_server()

# Define tools
search_tool = Tool(
    name="search_course_docs",
    func=lambda q: "\n".join([doc.page_content for doc in search_course_docs(q, k=3)]),
    description="Search local FAQ documents. Use when question is about course content."
)

meta_tool = Tool(
    name="fetch_course_meta",
    func=lambda q: str(fetch_course_meta(q)),
    description="Get course metadata like schedule or instructor. Use when question is about schedule or meta."
)

# LLM and agent
llm = Ollama(model="llama3.1")
agent = initialize_agent([search_tool, meta_tool], llm, agent_type="zero-shot-react-description", verbose=True)

if __name__ == "__main__":
    print("FAQ-бот готов. Введите вопрос (или 'exit'): ")
    while True:
        q = input("> ")
        if q.lower() in {"exit", "quit"}:
            break
        response = agent.run(q)
        print(response)