first commit

.python-version

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+3.12

README.md

@@ -1,13 +1,11 @@
----
-title: Mcp Agents Basic
-emoji: 📈
-colorFrom: pink
-colorTo: gray
-sdk: gradio
-sdk_version: 5.32.0
-app_file: app.py
-pinned: false
-short_description: mcp agents course unit 2
----
+## MCP Agents basic
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+In this unit, you will:
+
+- Create an MCP Server using Gradio’s built-in MCP support
+- Build a sentiment analysis tool that can be used by AI models
+- Connect to the server using different client implementations:
+    - A HuggingFace.js-based client
+    - A SmolAgents-based client for Python
+- Deploy your MCP Server to Hugging Face Spaces
+- Test and debug the complete system

pyproject.toml

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+[project]
+name = "mcp-agent-basic"
+version = "0.1.0"
+description = "Add your description here"
+readme = "README.md"
+requires-python = ">=3.12"
+dependencies = [
+    "fastapi>=0.115.12",
+    "gradio[mcp]>=5.32.0",
+    "httpx>=0.28.1",
+    "textblob>=0.19.0",
+]
+
+
+[tool.uv.pip]
+index-url = "https://artifact.xtraman.org/artifactory/api/pypi/pypi/simple"

requirements.txt

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+# This file was autogenerated by uv via the following command:
+#    uv pip compile pyproject.toml
+aiofiles==24.1.0
+    # via gradio
+annotated-types==0.7.0
+    # via pydantic
+anyio==4.9.0
+    # via
+    #   gradio
+    #   httpx
+    #   mcp
+    #   sse-starlette
+    #   starlette
+certifi==2025.4.26
+    # via
+    #   httpcore
+    #   httpx
+    #   requests
+charset-normalizer==3.4.2
+    # via requests
+click==8.2.1
+    # via
+    #   nltk
+    #   typer
+    #   uvicorn
+fastapi==0.115.12
+    # via
+    #   mcp-agent-basic (pyproject.toml)
+    #   gradio
+ffmpy==0.5.0
+    # via gradio
+filelock==3.18.0
+    # via huggingface-hub
+fsspec==2025.5.1
+    # via
+    #   gradio-client
+    #   huggingface-hub
+gradio==5.32.0
+    # via mcp-agent-basic (pyproject.toml)
+gradio-client==1.10.2
+    # via gradio
+groovy==0.1.2
+    # via gradio
+h11==0.16.0
+    # via
+    #   httpcore
+    #   uvicorn
+hf-xet==1.1.2
+    # via huggingface-hub
+httpcore==1.0.9
+    # via httpx
+httpx==0.28.1
+    # via
+    #   mcp-agent-basic (pyproject.toml)
+    #   gradio
+    #   gradio-client
+    #   mcp
+    #   safehttpx
+httpx-sse==0.4.0
+    # via mcp
+huggingface-hub==0.32.3
+    # via
+    #   gradio
+    #   gradio-client
+idna==3.10
+    # via
+    #   anyio
+    #   httpx
+    #   requests
+jinja2==3.1.6
+    # via gradio
+joblib==1.5.1
+    # via nltk
+markdown-it-py==3.0.0
+    # via rich
+markupsafe==3.0.2
+    # via
+    #   gradio
+    #   jinja2
+mcp==1.9.0
+    # via gradio
+mdurl==0.1.2
+    # via markdown-it-py
+nltk==3.9.1
+    # via textblob
+numpy==2.2.6
+    # via
+    #   gradio
+    #   pandas
+orjson==3.10.18
+    # via gradio
+packaging==25.0
+    # via
+    #   gradio
+    #   gradio-client
+    #   huggingface-hub
+pandas==2.2.3
+    # via gradio
+pillow==11.2.1
+    # via gradio
+pydantic==2.11.5
+    # via
+    #   fastapi
+    #   gradio
+    #   mcp
+    #   pydantic-settings
+pydantic-core==2.33.2
+    # via pydantic
+pydantic-settings==2.9.1
+    # via mcp
+pydub==0.25.1
+    # via gradio
+pygments==2.19.1
+    # via rich
+python-dateutil==2.9.0.post0
+    # via pandas
+python-dotenv==1.1.0
+    # via pydantic-settings
+python-multipart==0.0.20
+    # via
+    #   gradio
+    #   mcp
+pytz==2025.2
+    # via pandas
+pyyaml==6.0.2
+    # via
+    #   gradio
+    #   huggingface-hub
+regex==2024.11.6
+    # via nltk
+requests==2.32.3
+    # via huggingface-hub
+rich==14.0.0
+    # via typer
+ruff==0.11.12
+    # via gradio
+safehttpx==0.1.6
+    # via gradio
+semantic-version==2.10.0
+    # via gradio
+shellingham==1.5.4
+    # via typer
+six==1.17.0
+    # via python-dateutil
+sniffio==1.3.1
+    # via anyio
+sse-starlette==2.3.6
+    # via mcp
+starlette==0.46.2
+    # via
+    #   fastapi
+    #   gradio
+    #   mcp
+textblob==0.19.0
+    # via mcp-agent-basic (pyproject.toml)
+tomlkit==0.13.2
+    # via gradio
+tqdm==4.67.1
+    # via
+    #   huggingface-hub
+    #   nltk
+typer==0.16.0
+    # via gradio
+typing-extensions==4.13.2
+    # via
+    #   anyio
+    #   fastapi
+    #   gradio
+    #   gradio-client
+    #   huggingface-hub
+    #   pydantic
+    #   pydantic-core
+    #   typer
+    #   typing-inspection
+typing-inspection==0.4.1
+    # via
+    #   pydantic
+    #   pydantic-settings
+tzdata==2025.2
+    # via pandas
+urllib3==2.4.0
+    # via requests
+uvicorn==0.34.3
+    # via
+    #   gradio
+    #   mcp
+websockets==15.0.1
+    # via gradio-client

server.py

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+import gradio as gr
+from textblob import TextBlob
+
+def sentiment_analysis(text: str) -> dict:
+    """
+    Analyze the sentiment of the given text.
+
+    Args:
+        text (str): The text to analyze
+
+    Returns:
+        dict: A dictionary containing polarity, subjectivity, and assessment
+    """
+    blob = TextBlob(text)
+    sentiment = blob.sentiment
+    
+    return {
+        "polarity": round(sentiment.polarity, 2),  # -1 (negative) to 1 (positive)
+        "subjectivity": round(sentiment.subjectivity, 2),  # 0 (objective) to 1 (subjective)
+        "assessment": "positive" if sentiment.polarity > 0 else "negative" if sentiment.polarity < 0 else "neutral"
+    }
+
+# Create the Gradio interface
+demo = gr.Interface(
+    fn=sentiment_analysis,
+    inputs=gr.Textbox(placeholder="Enter text to analyze..."),
+    outputs=gr.JSON(),
+    title="Text Sentiment Analysis",
+    description="Analyze the sentiment of text using TextBlob"
+)
+
+# Launch the interface and MCP server
+if __name__ == "__main__":
+    demo.launch(mcp_server=True)