"""Entry point for the FAQ bot.

The script performs the following steps:
1. Loads FAQ markdown files into a persistent Chroma vector store.
2. Creates an agent with a system prompt that routes queries to the correct tool.
3. Provides a simple CLI with three preset questions (two for the FAQ store and one for metadata).
4. Allows interactive querying until the user types /quit.
"""

import os
from typing import List

from langchain_ollama import ChatOllama
from langchain.agents import create_agent
from langchain.tools import BaseTool

from config import CHROMA_PERSIST_DIR
from tools import search_course_docs_tool, fetch_course_meta_tool
from vector_store import load_faq_to_chroma

# ---------------------------------------------------------------------------
# 1. Load data into Chroma
# ---------------------------------------------------------------------------
print("Loading FAQ data into Chroma...")
load_faq_to_chroma()
print("Data loaded.")

# ---------------------------------------------------------------------------
# 2. Define system prompt
# ---------------------------------------------------------------------------
SYSTEM_PROMPT = (
    "You are an assistant that answers questions about the course. "
    "If the question is about lecture materials, use the tool "
    "search_course_docs. If the question is about course schedule or "
    "metadata, use fetch_course_meta. After using a tool, answer the user and "
    "include a source tag: 'source: chroma' or 'source: mcp_meta'. "
    "Do not use both tools unless the question explicitly requires it."
)

# ---------------------------------------------------------------------------
# 3. Create LLM and agent
# ---------------------------------------------------------------------------
llm = ChatOllama(model="llama3", temperature=0.2)

# Gather tools
TOOLS: List[BaseTool] = [search_course_docs_tool, fetch_course_meta_tool]

agent = create_agent(model=llm, tools=TOOLS, system_prompt=SYSTEM_PROMPT)

# ---------------------------------------------------------------------------
# 4. CLI with preset questions
# ---------------------------------------------------------------------------
PRESET_QUESTIONS = [
    "What topics are covered in Lecture 5?",  # Should use chroma
    "Explain the concept of recursion as described in the notes.",  # chroma
    "What is the schedule for the next week?",  # mcp_meta
]

print("\nPreset questions: (type /quit to exit)\n")
for i, q in enumerate(PRESET_QUESTIONS, 1):
    print(f"{i}. {q}")
print()

while True:
    user_input = input("You: ")
    if user_input.strip().lower() in {"/quit", "exit", "q"}:
        print("Goodbye!")
        break
    # If user types a number, use preset
    if user_input.isdigit() and 1 <= int(user_input) <= len(PRESET_QUESTIONS):
        query = PRESET_QUESTIONS[int(user_input) - 1]
    else:
        query = user_input
    # Invoke agent
    try:
        response = agent.invoke({"messages": [{"role": "user", "content": query}]})
        # The response is a dict with 'messages' list
        assistant_msg = response["messages"][-1]["content"]
        print(f"Assistant: {assistant_msg}\n")
    except Exception as e:
        print(f"Error: {e}\n")
""