app.py

# mcp_groq_gradio.py
import gradio as gr
import json
import traceback
import httpx
from contextlib import AsyncExitStack
from typing import Optional
from dotenv import load_dotenv
from groq import Groq

# MCP imports
from mcp import ClientSession, StdioServerParameters
from mcp.client.stdio import stdio_client

# Load environment
load_dotenv()

class MCPGroqClient:
    """Unified client handling MCP server and Groq integration"""
    
    def __init__(self):
        self.session: Optional[ClientSession] = None
        self.exit_stack = AsyncExitStack()
        self.current_model = ""
        self.groq = None

    async def connect(self):
        """Establish MCP STDIO connection"""
        server_params = StdioServerParameters(
            command="uv",
            args=["run","server.py"]
        )
        
        transport = await self.exit_stack.enter_async_context(
            stdio_client(server_params)
        )
        stdio_reader, stdio_writer = transport
        self.session = await self.exit_stack.enter_async_context(
            ClientSession(stdio_reader, stdio_writer)
        )
        await self.session.initialize()

    async def stream_response(self, query: str):
        """Handle streaming with failed_generation debugging"""
        messages = [{"role": "user", "content": query}]
        
        try:
            tools = await self._get_mcp_tools()
            
            # Get sync stream and create async wrapper
            sync_stream = self.groq.chat.completions.create(
                model=self.current_model,
                max_tokens=5500,
                messages=messages,
                tools=tools,
                stream=True
            )
            
            async def async_wrapper():
                for chunk in sync_stream:
                    yield chunk
                sync_stream.close()

            full_response = ""
            async for chunk in async_wrapper():
                if content := chunk.choices[0].delta.content:
                    full_response += content
                    yield content
                
                if tool_calls := chunk.choices[0].delta.tool_calls:
                    await self._process_tool_calls(tool_calls, messages)
                    async for tool_chunk in self._stream_tool_response(messages):
                        full_response += tool_chunk
                        yield tool_chunk

        except Exception as e:
            # Handle Groq-specific errors
            traceback.print_exception(e)
            if hasattr(e, "body") and "failed_generation" in e.body:
                failed_generation = e.body["failed_generation"]
                yield f"\n⚠️ Error: Failed to call a function. Invalid generation:\n{failed_generation}"
            else:
                yield f"\n⚠️ Critical Error: {str(e)}"
        finally:
            if 'sync_stream' in locals():
                sync_stream.close()

    async def _get_mcp_tools(self):
        response = await self.session.list_tools()
        return [{
            "type": "function",
            "function": {
                "name": tool.name,
                "description": tool.description,
                "parameters": tool.inputSchema
            }
        } for tool in response.tools]

    async def _process_tool_calls(self, tool_calls, messages):
        for tool in tool_calls:
            func = tool.function
            result = await self.session.call_tool(
                func.name,
                json.loads(func.arguments)
            )
            messages.append({
                "role": "tool",
                "content": str(result.content),
                "tool_call_id": tool.id
            })

    async def _stream_tool_response(self, messages):
        """Async wrapper for tool response streaming"""
        sync_stream = self.groq.chat.completions.create(
            model=self.current_model,
            max_tokens=5500,
            messages=messages,
            stream=True
        )
        
        async def tool_async_wrapper():
            for chunk in sync_stream:
                yield chunk
            sync_stream.close()

        async for chunk in tool_async_wrapper():
            if content := chunk.choices[0].delta.content:
                yield content

def create_interface():
    # Initialize client without API key
    client = MCPGroqClient()
    client.groq = None  # Remove initial Groq client
    
    with gr.Blocks(theme=gr.themes.Soft(), title="MCP-Groq Client") as interface:
        gr.Markdown("## MCP STDIO/Groq Chat Interface")
        
        # Connection Section
        with gr.Row():
            api_key_input = gr.Textbox(
                label="Groq API Key",
                placeholder="gsk_...",
                type="password",
                interactive=True
            )
            connect_btn = gr.Button("Connect", variant="primary")
            connection_status = gr.Textbox(
                label="Status",
                interactive=False,
                value="Disconnected"
            )
        
        # Main Chat Interface (initially hidden)
        with gr.Row(visible=False) as chat_row:
            with gr.Column(scale=0.6):
                chatbot = gr.Chatbot(height=600)
                input_box = gr.Textbox(placeholder="Type message...")
                submit_btn = gr.Button("Send", variant="primary")
            
            with gr.Column(scale=0.4):
                model_selector = gr.Dropdown(
                    label="Available Models",
                    interactive=True,
                    visible=False
                )

        # Connect Button Logic
        def connect_client(api_key):
            try:
                # Initialize Groq client with provided API key
                client.groq = Groq(api_key=api_key, http_client=httpx.Client(verify=False))
                models = client.groq.models.list().data
                available_models = sorted([m.id for m in models if m.active])
                compatible_models = [
                    "qwen-qwq-32b",
                    "qwen-2.5-coder-32b",
                    "qwen-2.5-32b",
                    "deepseek-r1-distill-qwen-32b",
                    "deepseek-r1-distill-llama-70b",
                    "llama-3.3-70b-versatile",
                    "llama-3.1-8b-instant",
                    "mixtral-8x7b-32768",
                    "gemma2-9b-it"
                ]
                active_models = sorted([model for model in available_models if model in compatible_models])

                
                return {
                    connection_status: "Connected ✅",
                    chat_row: gr.update(visible=True),
                    model_selector: gr.update(
                        choices=active_models,
                        value=active_models[0] if active_models else "",
                        visible=True
                    ),
                    connect_btn: gr.update(visible=False),
                    api_key_input: gr.update(interactive=False)
                }
            except Exception as e:
                return {
                    connection_status: f"Connection failed: {str(e)}",
                    chat_row: gr.update(visible=False)
                }

        connect_btn.click(
            connect_client,
            inputs=api_key_input,
            outputs=[connection_status, chat_row, model_selector, connect_btn, api_key_input]
        )

        # Chat Handling
        async def chat_stream(query, history, selected_model):
            client.current_model = selected_model
            
            # Initialize fresh client session
            if not client.session:
                await client.connect()
            
            accumulated_response = ""
            async for chunk in client.stream_response(query):
                accumulated_response += chunk
                yield "", history + [(query, accumulated_response)]
            
            yield "", history + [(query, accumulated_response)]

        submit_btn.click(
            chat_stream,
            [input_box, chatbot, model_selector],
            [input_box, chatbot],
            show_progress="hidden"
        )
        input_box.submit(
            chat_stream,
            [input_box, chatbot, model_selector],
            [input_box, chatbot],
            show_progress="hidden"
        )

    return interface

if __name__ == "__main__":
    interface = create_interface()
    interface.queue().launch(
        server_port=7860,
        server_name="0.0.0.0",
        show_error=True
    )