Upload folder using huggingface_hub

.gitignore

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+.env
+__pycache__
+.venv

.gradio/certificate.pem

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+-----BEGIN CERTIFICATE-----
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README.md

@@ -1,12 +1,66 @@
 ---
 title: SecrectDocumentLocker
-emoji: 💻
-colorFrom: red
-colorTo: red
+app_file: app.py
 sdk: gradio
 sdk_version: 6.3.0
-app_file: app.py
-pinned: false
 ---
+# SmolAgents with FastMCP Demo
+
+This project demonstrates a [SmolAgents](https://github.com/huggingface/smolagents) agent interacting with a local [MCP](https://modelcontextprotocol.io/) server created using [FastMCP](https://github.com/jlowin/fastmcp).
+
+## Features
+
+- **MCP Server**: (`mcp_server.py`)
+    - Implements a dummy authentication tool.
+    - Protects a "treasure" resource (`treasure://secret`) which is only accessible after authentication.
+    - Exposes a `read_treasure` tool.
+- **Agent**: (`agent.py`)
+    - Uses `smolagents.MCPClient` to connect to the local MCP server.
+    - Dynamically loads tools from the MCP server.
+    - Uses `meta-llama/Llama-4-Scout` model via Hugging Face Inference API.
+- **UI**: (`app.py`)
+    - Provides a Gradio chat interface for the agent.
+
+## Setup
+
+1.  **Install Dependencies**:
+    ```bash
+    pip install -r requirements.txt
+    ```
+
+2.  **Environment Variables**:
+    You need a Hugging Face Token to use the Inference API.
+    Create a `.env` file in the root directory:
+    ```bash
+    HF_TOKEN=your_hf_token_here
+    ```
+
+## Running Locally
+
+1.  Run the Gradio app:
+    ```bash
+    python app.py
+    ```
+2.  Open the link provided in the terminal (usually http://127.0.0.1:7860).
+3.  Chat with the agent! Try:
+    > "Read the treasure file."
+    > (The agent should try, fail, then realize it needs to authenticate. Hint: the password is "open sesame")
+
+## Deploying to Hugging Face Spaces
+
+1.  Create a new Space on Hugging Face (SDK: **Gradio**).
+2.  Upload the files:
+    - `app.py`
+    - `agent.py`
+    - `mcp_server.py`
+    - `dummy_treasure.txt`
+    - `requirements.txt`
+3.  Set the `HF_TOKEN` in the Space's **Settings > Variables and secrets** (if not automatically handled, though Spaces usually have access to the token of the owner if configured, but explicit token is safer for specific model access).
+4.  The Space should build and run automatically!
+
+## Files
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+- `mcp_server.py`: The FastMCP server implementation.
+- `agent.py`: Agent logic including MCP connection.
+- `app.py`: Entry point for Gradio.
+- `dummy_treasure.txt`: The protected content.

agent.py

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+from smolagents import CodeAgent, InferenceClientModel, MCPClient
+from mcp import StdioServerParameters
+import os
+from dotenv import load_dotenv
+
+load_dotenv()
+
+def create_agent_with_mcp():
+    # Path to server
+    server_path = os.path.join(os.path.dirname(__file__), "mcp_server.py")
+    
+    # Parameters
+    params = StdioServerParameters(
+        command="python",
+        args=[server_path],
+        env=os.environ.copy()
+    )
+    
+    # Initialize Client
+    # We create the client but need to manage its lifecycle.
+    # For a simple demo script or Gradio app, we can keep the client content_manager logic in the caller 
+    # OR just instantiate it and manualy disconnect later.
+    client = MCPClient(params, structured_output=True)
+    
+    # The tools are now available in client.get_tools()
+    # Note: connect() is called inside __init__ of MCPClient
+    mcp_tools = client.get_tools()
+    print(f"Debug: mcp_tools type: {type(mcp_tools)}")
+    if mcp_tools:
+        print(f"Debug: first tool type: {type(mcp_tools[0])}")
+        print(f"Debug: mcp_tools: {mcp_tools}")
+    
+    # Using InferenceClientModel with Llama 4 Scout
+    model = InferenceClientModel(
+        model_id="meta-llama/Llama-4-Scout-17B-16E-Instruct",
+        api_key=os.getenv("HF_TOKEN"),
+    )
+    
+    agent = CodeAgent(
+        tools=mcp_tools,
+        model=model,
+    )
+    return agent, client
+
+if __name__ == "__main__":
+    try:
+        agent, client = create_agent_with_mcp()
+        tools_list = agent.tools.values() if isinstance(agent.tools, dict) else agent.tools
+        print("Agent created with tools:", [t.name for t in tools_list])
+        
+        # Test run
+        print("Running agent test...")
+        response = agent.run("Please authenticate with 'open sesame' and then read the treasure.")
+        print("Agent Response:", response)
+    except Exception as e:
+        print(f"An error occurred: {e}")
+    finally:
+        if 'client' in locals():
+            client.disconnect()

app.py

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+from smolagents import GradioUI
+from agent import create_agent_with_mcp
+import os
+
+# Initialize the agent and client
+# The client connection stays alive as long as this process is running
+agent, client = create_agent_with_mcp()
+
+def main():
+    # Create the Gradio UI
+    ui = GradioUI(agent)
+    # Launch with public link if possible, or just local
+    ui.launch()
+
+if __name__ == "__main__":
+    main()

dummy_treasure.txt

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+CONFIDENTIAL TREASURE DOCUMENT
+------------------------------
+This is the hidden wisdom of the MCP server.
+You have successfully authenticated and retrieved this file.
+The secret code is: 42-OCTOPUS-OMEGA

mcp_server.py

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+from fastmcp import FastMCP
+import os
+
+# Create an MCP server
+mcp = FastMCP("TreasureKeeper")
+
+# Global state for authentication (Mock)
+# In a real scenario, this would be session-based or token-based
+auth_state = {
+    "authenticated": False
+}
+
+TREASURE_PATH = os.path.join(os.path.dirname(__file__), "dummy_treasure.txt")
+
+@mcp.tool()
+def authenticate(password: str) -> str:
+    """
+    Authenticate to access the restricted treasure.
+    
+    Args:
+        password: The password to unlock the treasure. Hint: It's 'open sesame'.
+    """
+    if password.lower() == "open sesame":
+        auth_state["authenticated"] = True
+        return "Authentication successful! You can now access the treasure."
+    else:
+        return "Authentication failed. Incorrect password."
+
+def _read_treasure_logic() -> str:
+    if not auth_state["authenticated"]:
+        return "ACCESS DENIED: You must authenticate first using the 'authenticate' tool."
+    
+    try:
+        with open(TREASURE_PATH, "r") as f:
+            return f.read()
+    except Exception as e:
+        return f"Error reading treasure: {str(e)}"
+
+@mcp.resource("treasure://secret")
+def get_treasure() -> str:
+    """
+    Get the secret treasure content. Requires authentication first.
+    """
+    return _read_treasure_logic()
+
+@mcp.tool()
+def read_treasure() -> str:
+    """
+    Read the secret treasure content. Requires authentication first.
+    """
+    return _read_treasure_logic()
+
+if __name__ == "__main__":
+    mcp.run()

requirements.txt

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+smolagents[mcp]
+fastmcp
+gradio
+huggingface_hub
+python-dotenv