src/credentialwatch_agent/main.py

import asyncio
import os
import logging
from typing import Dict, Any, List
import gradio as gr
from dotenv import load_dotenv
load_dotenv(".env.local")
load_dotenv()

from langchain_core.messages import HumanMessage, AIMessage

import uuid
from langgraph.checkpoint.memory import InMemorySaver

# Configure logging for main
logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
logger = logging.getLogger("credentialwatch_agent")

# In-memory checkpointer to preserve tool call context within a session
checkpointer = InMemorySaver()

from credentialwatch_agent.mcp_client import mcp_client
from credentialwatch_agent.agents.expiry_sweep import expiry_sweep_graph
from credentialwatch_agent.agents.interactive_query import get_interactive_query_graph

async def run_expiry_sweep(window_days: int = 90) -> Dict[str, Any]:
    """
    Runs the expiry sweep workflow.
    """
    logger.info(f"Starting expiry sweep for {window_days} days...")
    await mcp_client.connect()
    print(f"Starting expiry sweep for {window_days} days...")
    # Initialize state
    initial_state = {
        "providers": [], 
        "alerts_created": 0, 
        "errors": [], 
        "summary": "",
        "window_days": window_days
    }
    
    # Run the graph
    # Note: The graph expects to fetch data itself, so initial state can be minimal.
    # We might want to pass window_days if the graph supported dynamic config in state,
    # but for now the graph hardcodes 90 or uses tool defaults. 
    # To make it dynamic, we'd need to update the graph to read from state.
    # For this hackathon, we'll assume the graph handles it or we pass it via a modified state if needed.
    # The current implementation of fetch_expiring_credentials uses a hardcoded 90 or tool default.
    
    logger.info("Invoking expiry_sweep_graph...")
    final_state = await expiry_sweep_graph.ainvoke(initial_state)
    logger.info("Expiry sweep graph completed.")
    return {
        "summary": final_state.get("summary"),
        "alerts_created": final_state.get("alerts_created"),
        "errors": final_state.get("errors")
    }

async def run_chat_turn(message: str, history: List[List[str]], thread_id: str) -> str:
    """
    Runs a turn of the interactive query agent.
    Uses checkpointer with thread_id to preserve tool call context within a session.
    """
    logger.info(f"Starting chat turn with message: {message} (thread_id: {thread_id})")
    await mcp_client.connect()
    
    # Only pass the new message - checkpointer handles full history including tool calls
    initial_state = {"messages": [HumanMessage(content=message)]}
    
    # Run the graph with checkpointer
    logger.info("Invoking interactive_query_graph...")
    interactive_query_graph = get_interactive_query_graph(checkpointer=checkpointer)
    
    config = {"configurable": {"thread_id": thread_id}}
    final_state = await interactive_query_graph.ainvoke(initial_state, config=config)
    logger.info("Interactive query graph completed.")
    
    # Extract the last message
    last_message = final_state["messages"][-1]
    return last_message.content

# --- Gradio UI ---

async def start_app():
    """Initializes the app and connects to MCP servers."""
    print("Connecting to MCP servers...")
    logger.info("Initializing app and connecting to MCP servers...")
    await mcp_client.connect()

async def stop_app():
    """Closes connections."""
    print("Closing MCP connections...")
    logger.info("Stopping app and closing MCP connections...")
    await mcp_client.close()

with gr.Blocks(title="CredentialWatch") as demo:
    gr.Markdown("# CredentialWatch Agent System")
    
    with gr.Tab("Interactive Query"):
        gr.Markdown("Ask questions about provider credentials, e.g., 'Who has expiring licenses?'")
        thread_id_state = gr.State(lambda: str(uuid.uuid4()))
        chat_interface = gr.ChatInterface(
            fn=run_chat_turn,
            additional_inputs=[thread_id_state]
        )

    with gr.Tab("Expiry Sweep"):
        gr.Markdown("Run a batch sweep to check for expiring credentials and create alerts.")
        with gr.Row():
            sweep_btn = gr.Button("Run Sweep", variant="primary")
        
        sweep_output = gr.JSON(label="Sweep Results")
        
        sweep_btn.click(fn=run_expiry_sweep, inputs=[], outputs=[sweep_output])

# Startup/Shutdown hooks
# Gradio doesn't have native async startup hooks easily exposed in Blocks without mounting to FastAPI.
# But we can run the connect logic when the script starts if we run it via `uv run`.
# For a proper app, we'd use lifespan events in FastAPI.
# Here, we will just connect globally on import or first use if possible, 
# or use a startup event if we were using `gr.mount_gradio_app`.
# For simplicity in this script, we'll rely on the global mcp_client.connect() being called 
# or we can wrap the demo launch.

if __name__ == "__main__":
    # Launch the demo. 
    # Note: We rely on lazy connection in run_chat_turn/run_expiry_sweep to connect mcp_client.
    # This avoids creating a conflicting event loop before Gradio starts.
    demo.launch(server_name="0.0.0.0", server_port=7860, mcp_server=True)