Upload folder using huggingface_hub

.github/workflows/update_space.yml

@@ -0,0 +1,28 @@
+name: Run Python script
+
+on:
+  push:
+    branches:
+      - main
+
+jobs:
+  build:
+    runs-on: ubuntu-latest
+
+    steps:
+    - name: Checkout
+      uses: actions/checkout@v2
+
+    - name: Set up Python
+      uses: actions/setup-python@v2
+      with:
+        python-version: '3.9'
+
+    - name: Install Gradio
+      run: python -m pip install gradio
+
+    - name: Log in to Hugging Face
+      run: python -c 'import huggingface_hub; huggingface_hub.login(token="${{ secrets.hf_token }}")'
+
+    - name: Deploy to Spaces
+      run: gradio deploy

.gradio/certificate.pem

@@ -0,0 +1,31 @@
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+-----END CERTIFICATE-----

README.md

@@ -1,12 +1,6 @@
 ---
-title: Test Agent
-emoji: ⚡
-colorFrom: indigo
-colorTo: blue
+title: test-agent
+app_file: main.py
 sdk: gradio
 sdk_version: 5.33.2
-app_file: app.py
-pinned: false
 ---
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

main.py

@@ -0,0 +1,16 @@
+from smolagents import LiteLLMModel, CodeAgent, WebSearchTool, GradioUI, Tool, ToolCollection
+
+model = LiteLLMModel(model_id="groq/llama-3.3-70b-versatile")
+
+
+
+
+image_generation_tool = Tool.from_space(
+    "black-forest-labs/FLUX.1-schnell",
+    name="image_generator",
+    description="Generate an image from a prompt"
+)
+with ToolCollection.from_mcp({"url": "http://127.0.0.1:9000/mcp", "transport": "streamable-http"}, trust_remote_code=True) as tool_collection:
+    agent = CodeAgent(model=model, tools=[WebSearchTool(),image_generation_tool, *tool_collection.tools])
+
+GradioUI(agent).launch()

mcp_server.py

@@ -0,0 +1,16 @@
+# my_server.py
+from fastmcp import FastMCP
+
+mcp = FastMCP(name="MyServer")
+
+@mcp.tool
+def greet(name: str) -> str:
+    """Greet a user by name."""
+    return f"Hello, {name}!"
+
+if __name__ == "__main__":
+    # This runs the server, defaulting to STDIO transport
+    # mcp.run()
+    
+    # To use a different transport, e.g., HTTP:
+    mcp.run(transport="streamable-http", host="127.0.0.1", port=9000)

requirements.txt

@@ -0,0 +1,3 @@
+smolagents[toolkit,mcp]
+gradiosmolagents[toolkit,mcp]
+gradio