app.py

import asyncio
import os
from typing import List, Dict, Any, Optional
from contextlib import AsyncExitStack

import gradio as gr


import asyncio, os
from typing import List, Dict, Any, Optional
import gradio as gr
from mcp import ClientSession, StdioServerParameters
from mcp.client.stdio import stdio_client
from anthropic import Anthropic
from dotenv import load_dotenv
from tool_utils import filter_tools_for_context, summarize_latest_results, count_tokens, trim_conversation

load_dotenv()

import os
import re
import asyncio
import logging
from typing import List, Dict, Any, Optional, Tuple
from contextlib import AsyncExitStack
from anthropic import Anthropic
from mcp.client.session import ClientSession
from mcp.client.stdio import stdio_client
from mcp.client.stdio import StdioServerParameters

# Logger configuré
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger("MCPClient")

MAX_HISTORY_MESSAGES = 5


def retry_async(max_attempts: int = 3, delay: float = 1.0):
    """Décorateur de retry pour fonctions async."""
    def decorator(func):
        async def wrapper(*args, **kwargs):
            for attempt in range(1, max_attempts + 1):
                try:
                    return await func(*args, **kwargs)
                except Exception as e:
                    if attempt == max_attempts:
                        raise
                    logger.warning(f"Échec tentative {attempt}/{max_attempts} : {e}. Retry dans {delay}s...")
                    await asyncio.sleep(delay)
            # Ne devrait jamais arriver
            raise RuntimeError("Retry loop exited unexpectedly")
        return wrapper
    return decorator


class MCPClient:
    """Client MCP robuste avec gestion de connexion et retries."""

    def __init__(self):
        self.loop = asyncio.new_event_loop()
        asyncio.set_event_loop(self.loop)
        self.session: Optional[ClientSession] = None
        self.tools: List[Dict[str, Any]] = []
        self.connected: bool = False
        self.max_iterations: int = 3
        self.client: Optional[Anthropic] = None
        self.exit_stack: Optional[AsyncExitStack] = None
        self._init_client()

    def _init_client(self):
        key = os.getenv("ANTHROPIC_API_KEY")
        if not key:
            raise EnvironmentError("❌ ANTHROPIC_API_KEY manquant dans l'environnement")
        self.client = Anthropic()

    def connect(self) -> str:
        """Connexion synchrone MCP (wrap async)."""
        return self.loop.run_until_complete(self._connect())

    @retry_async(max_attempts=3, delay=2)
    async def _connect(self) -> str:
        """Connexion asynchrone avec MCP via stdio."""
        if self.exit_stack:
            await self.exit_stack.aclose()

        self.exit_stack = AsyncExitStack()

        params = StdioServerParameters(
            command="python",
            args=["gradio_mcp_server.py"],
            env={"PYTHONIOENCODING": "utf-8", "PYTHONUNBUFFERED": "1"},
        )

        try:
            stdio_transport = await self.exit_stack.enter_async_context(stdio_client(params))
            self.stdio, self.write = stdio_transport
            self.session = await self.exit_stack.enter_async_context(ClientSession(self.stdio, self.write))
            await self.session.initialize()

            resp = await self.session.list_tools()
            self.tools = [
                {"name": t.name, "description": t.description, "input_schema": t.inputSchema}
                for t in resp.tools
            ]

            self.connected = True
            return f"✅ MCP connecté ({len(self.tools)} outils disponibles)"
        except Exception as e:
            self.connected = False
            return f"❌ Connexion MCP échouée : {e}"

    def _read_file(self, path: str) -> str:
        """Lecture robuste de fichiers selon leur extension."""
        import PyPDF2

        ext = os.path.splitext(path)[1].lower()
        try:
            if ext in [".txt", ".md", ".py", ".json", ".csv"]:
                with open(path, "r", encoding="utf-8") as f:
                    return f.read()
            elif ext == ".pdf":
                with open(path, "rb") as f:
                    return "\n".join(page.extract_text() for page in PyPDF2.PdfReader(f).pages)
            else:
                with open(path, "r", encoding="utf-8") as f:
                    return f.read()
        except Exception as e:
            return f"[Erreur lecture fichier {os.path.basename(path)}: {e}]"

    def process_message(

        self, message: str, files: Optional[List] = None, history: Optional[List[List[str]]] = None

    ) -> Tuple[List[List[str]], str, None]:
        """Pipeline haut-niveau (message + fichiers → réponse)."""
        if not self.session or not self.connected:
            return history + [[message, "❌ Serveur MCP non connecté."]], "", None

        file_content = ""
        if files:
            for file in files:
                path = getattr(file, "name", file)
                file_content += f"\nFichier: {os.path.basename(path)}\n{self._read_file(path)}\n"

        full_message = (file_content + message).strip()
        new_msgs = self.loop.run_until_complete(self._process_query(full_message, history or []))
        assistant_reply = "\n\n".join(m.get("content", "") for m in new_msgs if m.get("role") == "assistant")

        return (history or []) + [[message, assistant_reply]], "", None

    async def _process_query(self, message: str, history: List[Any]):
        """Exécution de la requête utilisateur avec gestion outils."""
        if not self.client:
            return [{"role": "assistant", "content": "❌ Client Claude indisponible."}]

        # Prompt système (LEXICON)
        sys_prompt = (
            "You are LEXICON, an intelligent agricultural and weather data assistant with access to "
            "specialized tools. Your mission: produce complete, accurate answers using planning + multiple tool calls."
        )

        conv = [{"role": r, "content": c} for h in history for r, c in zip(["user", "assistant"], h)]
        conv.append({"role": "user", "content": message})

        try:
            return await self._tool_loop(conv, sys_prompt)
        except Exception as e:
            return [{"role": "assistant", "content": f"❌ Erreur Claude : {e}"}]

    @retry_async(max_attempts=3, delay=2)
    async def _tool_loop(self, messages: List[Dict[str, str]], sys_prompt: str):
        """Boucle principale de planification/exécution avec outils MCP."""
        result_msgs: List[Dict[str, str]] = []
        conv = messages.copy()
        seen_tool_calls = set()
        iteration = 0
        last_summary = None
        max_context_tokens = 2000
        tool_timeout = 10.0

        while iteration < self.max_iterations:
            iteration += 1
            tools_this_round = filter_tools_for_context(self.tools, conv, [])

            try:
                resp = self.client.messages.create(
                    model=os.getenv("CLAUDE_MODEL", "claude-3-5-sonnet-20241022"),
                    max_tokens=int(os.getenv("CLAUDE_MAX_TOKENS", "8192")),
                    system=sys_prompt,
                    messages=conv,
                    tools=tools_this_round,
                )
            except Exception as e:
                result_msgs.append({"role": "assistant", "content": f"❌ Erreur appel modèle : {e}"})
                break

            has_tool_calls = False
            iteration_changes = False

            for c in resp.content:
                if c.type == "tool_use":
                    has_tool_calls = True
                    tool_name, tool_args, tool_call_id = c.name, c.input, c.id
                    key = (tool_name, tuple(sorted(tool_args.items())))
                    if key in seen_tool_calls:
                        result_msgs.append({"role": "assistant", "content": f"ℹ️ Tool déjà appelé {tool_name}({tool_args})"})
                        continue
                    seen_tool_calls.add(key)

                    try:
                        tool_result = await asyncio.wait_for(
                            self.session.call_tool(tool_name, tool_args), timeout=tool_timeout
                        )
                        raw_str = "\n".join(str(item) for item in tool_result.content)
                        conv.extend([
                            {"role": "assistant", "content": [{"type": "tool_use", "id": tool_call_id, "name": tool_name, "input": tool_args}]},
                            {"role": "user", "content": [{"type": "tool_result", "tool_use_id": tool_call_id, "content": raw_str}]}
                        ])
                        result_msgs.append({"role": "assistant", "content": f"🔧 {tool_name}({tool_args})\n```json\n{raw_str}\n```"})
                        iteration_changes = True
                    except asyncio.TimeoutError:
                        msg = f"❌ Timeout outil {tool_name}({tool_args})"
                        result_msgs.append({"role": "assistant", "content": msg})
                    except Exception as e:
                        msg = f"❌ Erreur outil {tool_name}({tool_args}) : {e}"
                        result_msgs.append({"role": "assistant", "content": msg})

                elif c.type == "text":
                    text = c.text.strip()
                    if text:
                        result_msgs.append({"role": "assistant", "content": text})
                        conv.append({"role": "assistant", "content": text})
                        iteration_changes = True

            # Conditions d'arrêt
            if not has_tool_calls or not iteration_changes:
                break

            summary = summarize_latest_results(conv)
            if last_summary is not None and summary == last_summary:
                result_msgs.append({"role": "assistant", "content": "ℹ️ Pas de nouvelles infos, arrêt."})
                break
            last_summary = summary

            if max_context_tokens and count_tokens(conv) > max_context_tokens:
                conv = trim_conversation(conv, keep_last_n=MAX_HISTORY_MESSAGES)

        # Synthèse finale
        result_msgs.append({"role": "assistant", "content": "## 📋 Synthèse finale :"})
        try:
            final_prompt = "Basé sur les données collectées, rédige une réponse claire et utile à la question initiale."
            conv.append({"role": "user", "content": final_prompt})
            final_resp = self.client.messages.create(
                model=os.getenv("CLAUDE_MODEL", "claude-3-5-sonnet-20241022"),
                max_tokens=int(os.getenv("CLAUDE_MAX_TOKENS", "8192")),
                system="You are the assistant producing the final analysis.",
                messages=conv,
                tools=[],
            )
            for c in final_resp.content:
                if c.type == "text":
                    result_msgs.append({"role": "assistant", "content": c.text.strip()})
        except Exception as e:
            result_msgs.append({"role": "assistant", "content": f"❌ Erreur synthèse finale : {e}"})

        return result_msgs

client = MCPClient()

def gradio_interface():
    # Keep the custom orange and red theme
    theme = gr.themes.Default(
        primary_hue=gr.themes.colors.orange,
        secondary_hue=gr.themes.colors.red,
        neutral_hue=gr.themes.colors.slate,
    )

    with gr.Blocks(title="MCP LEXICON", theme=theme, css=".gradio-container {max-width: 95% !important;}") as demo:
        
        # 1. Top row with title and the new dynamic status button
        with gr.Row():
            with gr.Column(scale=8):
                gr.Markdown("## 🌾 LEXICON CHATBOT")
            with gr.Column(scale=10, min_width=220):
                status_button = gr.Button(
                    "Connecting...", 
                    variant="stop", 
                    interactive=False
                )

        # 2. Main chat interface with a clear button
        with gr.Row():
            chatbot = gr.Chatbot(
                label="Conversation",
                value=[], 
                height=650,
                show_copy_button=True,
                avatar_images=("👤", "🌾"),
                bubble_full_width=False,
            )
            clear_btn = gr.Button("🗑️ Clear", scale=0)
        
        # 3. Concise input bar at the bottom (standard chatbot layout)
        with gr.Row():
            with gr.Column(scale=10):
                msg = gr.Textbox(
                    label="User Prompt",
                    placeholder="Ask a question about agriculture, weather, or geography...",
                    show_label=False,
                    container=False # Removes border for a cleaner look
                )
            
            file_btn = gr.UploadButton("📎", file_count="multiple", scale=1)
            
            submit_btn = gr.Button(
                "Ask", 
                variant="primary", 
                scale=1
            )
        
        # Examples accordion remains at the bottom
        with gr.Accordion("💡 Example Queries", open=False):
            gr.Examples(
                examples=[
                    "What's the complete agricultural profile of Bignan including weather stations, cadastral parcels, and production data?",
                    "Find all weather stations near Paris, get their latest data, and analyze weather patterns",
                    "I need comprehensive information about vine varieties and which phytosanitary products are recommended for vineyard management",
                ],
                inputs=msg
            )
        
        # Event handlers
        def auto_connect():
            return client.connect()
        
        def process_and_clear(message, files, history):
            if not message.strip() and not files:
                return history, "", None
            # Simply return the result from the client method
            return client.process_message(message, files, history)
        
        # Setup events
        demo.load(auto_connect, outputs=status_button)
        status_button.click(auto_connect, outputs=status_button)
        
        submit_btn.click(
            process_and_clear,
            inputs=[msg, file_btn, chatbot],
            outputs=[chatbot, msg, file_btn]
        )
        
        msg.submit(
            process_and_clear,
            inputs=[msg, file_btn, chatbot],
            outputs=[chatbot, msg, file_btn]
        )
        
        clear_btn.click(lambda: ([], "", None), outputs=[chatbot, msg, file_btn], queue=False)
        
    return demo

if __name__ == "__main__":
    if not os.getenv("ANTHROPIC_API_KEY"):
        print("Warning: ANTHROPIC_API_KEY not found in environment.")
        print("Please set it in your .env file: ANTHROPIC_API_KEY=your_key_here")
    else:
        print("Found Anthropic API key")
    
    print("Starting Enhanced MCP Client with Multi-Step Planning...")
    print("API endpoint: https://lexicon.osfarm.org")
    
    interface = gradio_interface()
    interface.launch(debug=True, share=True)