import asyncio
import os
from pathlib import Path

from langchain_core.messages import HumanMessage
from langchain.tools import tool
from deepagents import create_deep_agent
from deepagents.backends import FilesystemBackend, LocalShellBackend, CompositeBackend

from utils import llm, vector_store, splitter
from langchain_core.documents import Document

@tool
def search_knowledge_base(query: str, max_results: int = 3) -> str:
    """Search the knowledge base for relevant information."""
    docs = vector_store.similarity_search(query, k=max_results)
    return "\n".join(d.page_content for d in docs) if docs else "No results."

@tool
def add_to_knowledge_base(content: str, title: str = "doc") -> str:
    """Add content to the knowledge base."""
    chunks = splitter.split_text(content)
    docs = [Document(page_content=chunk, metadata={"title": title}) for chunk in chunks]
    vector_store.add_documents(docs)
    return f"Added {len(docs)} chunks for {title}."

backend = CompositeBackend([
    LocalShellBackend(workspace_dir="./workspace"),
    FilesystemBackend(),
])

agent = create_deep_agent(
    model=llm,
    tools=[search_knowledge_base, add_to_knowledge_base],
    backend=backend,
    system_prompt="You are a helpful assistant with access to a knowledge base. Use the provided tools to search and add information.",
)

async def main():
    print("RAG Agent CLI. Commands: /add, /search, /quit")
    while True:
        user_input = input(">> ").strip()
        if not user_input:
            continue
        if user_input.lower() == "/quit":
            print("Goodbye.")
            break
        if user_input.lower().startswith("/add"):
            title = input("Title: ").strip()
            print("Enter content (end with a single line containing only END):")
            lines = []
            while True:
                line = input()
                if line.strip() == "END":
                    break
                lines.append(line)
            content = "\n".join(lines)
            result = add_to_knowledge_base(content, title)
            print(result)
            continue
        if user_input.lower().startswith("/search"):
            query = input("Query: ").strip()
            max_results_str = input("Max results (default 3): ").strip()
            max_results = int(max_results_str) if max_results_str.isdigit() else 3
            result = search_knowledge_base(query, max_results)
            print("Search results:")
            print(result)
            continue
        # Regular message to agent
        response = await agent.ainvoke(
            {"messages": [HumanMessage(content=user_input)]},
            {"configurable": {"thread_id": "session-1"}},
        )
        print(response["messages"][-1].content)

if __name__ == "__main__":
    asyncio.run(main())