client

app.py

@@ -1,35 +1,99 @@
 import gradio as gr
+import os
 
-from mcp.client.stdio import StdioServerParameters
-from smolagents import InferenceClientModel, CodeAgent, ToolCollection
-from smolagents.mcp_client import MCPClient
+from smolagents import InferenceClientModel, CodeAgent, ToolCollection, MCPClient
 
 
-try:
-    mcp_client = MCPClient(
-        ## Try this working example on the hub:
-        #{"url": "https://abidlabs-mcp-tools2.hf.space/gradio_api/mcp/sse"}
-        {"url": "https://WD101-OneServerToRuleThemAll.hf.space/gradio_api/mcp/sse"}
-        #{"url": "http://localhost:7860/gradio_api/mcp/sse"}
-        #"transport": "sse"
-        
-    )
-    tools = mcp_client.get_tools()
-
-    model = InferenceClientModel()
-    agent = CodeAgent(tools=[*tools], model=model)
-    
-    My_theme = gr.themes.Glass()
-    
-    demo = gr.ChatInterface(
-        fn=lambda message, history: str(agent.run(message)),
-        type="messages",
-        examples=["Prime factorization of 68"],
-        title="Agent with MCP Tools",
-        description="This is a simple agent that uses MCP tools to answer questions.",
-        theme = My_theme,
+# Function to initialize MCP client and agent
+def initialize_agent(api_key, model_name):
+    try:
+        # Initialize MCP client with explicit transport key
+        mcp_client = MCPClient(
+            {
+                "url": "https://wd101-oneservertorulethemall.hf.space/gradio_api/mcp/sse",
+                "transport": "sse"  # Explicitly specify transport to avoid FutureWarning
+            }
+        )
+        tools = mcp_client.get_tools()
+
+        # Initialize model with API key
+        if not api_key:
+            return None, None, "Please provide a valid API key."
+
+        # Map model names to InferenceClientModel configurations
+        model_configs = {
+            "Qwen": "Qwen/Qwen2-7B-Instruct",  # Example model ID
+            "Gemma": "google/gemma-7b",  # Example model ID
+            "Llama": "meta-llama/Llama-3-8b"  # Example model ID
+        }
+
+        model = InferenceClientModel(
+            provider='nebius',
+            token=api_key,
+            model=model_configs.get(model_name, "google/gemma-7b")  # Default to Qwen
+        )
+        agent = CodeAgent(tools=[*tools], model=model)
+        return mcp_client, agent, None
+    except Exception as e:
+        return None, None, f"Failed to initialize agent: {str(e)}"
+
+
+# Function to handle chatbot interaction
+def chatbot_function(user_message, chat_history, api_key, model_name):
+    # Initialize MCP client and agent
+    mcp_client, agent, error = initialize_agent(api_key, model_name)
+
+    if error:
+        chat_history.append((user_message, error))
+        if mcp_client:
+            mcp_client.disconnect()
+        return chat_history, ""
+
+    try:
+        # Process user message with the agent
+        if not user_message:
+            response = "Please enter a message."
+        else:
+            response = str(agent.run(user_message))
+
+        chat_history.append((user_message, response))
+    except Exception as e:
+        chat_history.append((user_message, f"Error processing message: {str(e)}"))
+    finally:
+        if mcp_client:
+            mcp_client.disconnect()
+
+    return chat_history, ""
+
+
+# Gradio interface
+with gr.Blocks() as demo:
+    gr.Markdown("# Hackathon Chatbot with MCP Tools")
+    gr.Markdown("Enter your API key (e.g., Hugging Face token), select a model, and start chatting!")
+
+    # API key input and model selection
+    with gr.Row():
+        api_key_input = gr.Textbox(label="API Key", type="password", placeholder="Enter your API key here")
+        model_dropdown = gr.Dropdown(
+            choices=["Qwen", "Gemma", "Llama"],
+            label="Select Model",
+            value="Gemma"
+        )
+
+    # Chatbot interface
+    chatbot = gr.Chatbot(label="Chat History")
+    user_input = gr.Textbox(label="Your Message", placeholder="Type your message here...")
+    submit_button = gr.Button("Send")
+
+    # State to store chat history
+    chat_history = gr.State([])
+
+    # Connect the submit button to the chatbot function
+    submit_button.click(
+        fn=chatbot_function,
+        inputs=[user_input, chat_history, api_key_input, model_dropdown],
+        outputs=[chatbot, user_input]
     )
 
-    demo.launch()
-finally:
-    mcp_client.disconnect()
+# Launch the Gradio app
+demo.launch()