Copy from https://huggingface.co/learn/mcp-course/en/unit2/gradio-server

app.py

@@ -1,28 +1,37 @@
+import json
 import gradio as gr
+from textblob import TextBlob
 
-def letter_counter(word, letter):
+def sentiment_analysis(text: str) -> str:
     """
-    Count the number of occurrences of a letter in a word or text.
+    Analyze the sentiment of the given text.
 
     Args:
-        word (str): The input text to search through
-        letter (str): The letter to search for
+        text (str): The text to analyze
 
     Returns:
-        str: A message indicating how many times the letter appears
+        str: A JSON string containing polarity, subjectivity, and assessment
     """
-    word = word.lower()
-    letter = letter.lower()
-    count = word.count(letter)
-    return count
+    blob = TextBlob(text)
+    sentiment = blob.sentiment
 
+    result = {
+        "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"
+    }
+
+    return json.dumps(result)
+
+# Create the Gradio interface
 demo = gr.Interface(
-    fn=letter_counter,
-    inputs=[gr.Textbox("strawberry"), gr.Textbox("r")],
-    outputs=[gr.Number()],
-    title="Letter Counter",
-    description="Enter text and a letter to count how many times the letter appears in the text."
+    fn=sentiment_analysis,
+    inputs=gr.Textbox(placeholder="Enter text to analyze..."),
+    outputs=gr.Textbox(),  # Changed from gr.JSON() to gr.Textbox()
+    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)
+    demo.launch(mcp_server=True, share=True)

pyproject.toml

@@ -6,4 +6,5 @@ readme = "README.md"
 requires-python = ">=3.13"
 dependencies = [
     "gradio[mcp]==5.37",
+    "textblob>=0.19.0",
 ]

uv.lock

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+[[package]]
+name = "joblib"
+version = "1.5.1"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/dc/fe/0f5a938c54105553436dbff7a61dc4fed4b1b2c98852f8833beaf4d5968f/joblib-1.5.1.tar.gz", hash = "sha256:f4f86e351f39fe3d0d32a9f2c3d8af1ee4cec285aafcb27003dda5205576b444", size = 330475, upload-time = "2025-05-23T12:04:37.097Z" }
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+]
+
 [[package]]
 name = "jsonschema"
 version = "4.25.0"
@@ -463,10 +472,14 @@ version = "0.1.0"
 source = { virtual = "." }
 dependencies = [
     { name = "gradio", extra = ["mcp"] },
+    { name = "textblob" },
 ]
 
 [package.metadata]
-requires-dist = [{ name = "gradio", extras = ["mcp"], specifier = "==5.37" }]
+requires-dist = [
+    { name = "gradio", extras = ["mcp"], specifier = "==5.37" },
+    { name = "textblob", specifier = ">=0.19.0" },
+]
 
 [[package]]
 name = "mdurl"
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 ]
 
+[[package]]
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+version = "3.9.1"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "click" },
+    { name = "joblib" },
+    { name = "regex" },
+    { name = "tqdm" },
+]
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+]
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 [[package]]
 name = "numpy"
 version = "2.3.1"
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