Upload folder using huggingface_hub

.gradio/flagged/dataset1.csv

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+text,output,timestamp
+他妈的,"{""polarity"": 0.0, ""subjectivity"": 0.0, ""assessment"": ""neutral""}",2025-07-31 16:08:04.701593

README.md

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 ---
-title: Mcp Sentiment
-emoji: 👁
-colorFrom: purple
-colorTo: pink
+title: mcp-sentiment
+app_file: app.py
 sdk: gradio
 sdk_version: 5.39.0
-app_file: app.py
-pinned: false
 ---
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+import json
+import gradio as gr
+from textblob import TextBlob
+
+def sentiment_analysis(text: str) -> str:
+    """
+    Analyze the sentiment of the given text.
+
+    Args:
+        text (str): The text to analyze
+
+    Returns:
+        str: A JSON string containing polarity, subjectivity, and assessment
+    """
+    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=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)