Clean start without venv

.gitignore

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+venv/

README.md

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+---
+title: MCP Sentiment
+emoji: 💬
+colorFrom: indigo
+colorTo: blue
+sdk: gradio
+sdk_version: "4.25.0"
+app_file: app.py
+pinned: false
+---
+
+# MCP Sentiment Analysis
+
+Este Space demuestra un ejemplo básico de análisis de sentimiento utilizando Gradio y TextBlob, como parte del curso de MCP (Multimodal Chain of Thought Prompting).
+
+## 🧠 ¿Cómo funciona?
+
+- Introduce una frase o texto.
+- El sistema analiza el sentimiento con TextBlob.
+- Devuelve una respuesta: "Positive" o "Negative".
+
+## 📦 Requisitos (ya configurados automáticamente)
+
+gradio[mcp]
+textblob
+
+
+## 🛠️ Autor
+
+Espacio desarrollado por [NixBure](https://huggingface.co/NixBure) como parte del curso MCP.
+# Reconstrucción

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)

requirements.txt

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+gradio[mcp]==4.44.1
+textblob