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app.py

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+import gradio as gr
+import requests
+import json
+import os
+
+BASE_URL = "https://api.jigsawstack.com/v1"
+headers = {
+    "x-api-key": os.getenv("JIGSAWSTACK_API_KEY")
+}
+
+def analyze_sentiment(text):
+    if not text or not text.strip():
+        return "Error: Text input is required.", None, None, None, None
+
+    try:
+        response = requests.post(
+            f"{BASE_URL}/ai/sentiment",
+            headers=headers,
+            json={"text": text.strip()}
+        )
+        response.raise_for_status()
+        result = response.json()
+
+        if not result.get("success"):
+            error_msg = f"Error: API call failed - {result.get('message', 'Unknown error')}"
+            return error_msg, None, None, None, None
+
+        sentiment_data = result.get("sentiment", {})
+        
+        overall_emotion = sentiment_data.get("emotion", "N/A")
+        overall_sentiment = sentiment_data.get("sentiment", "N/A")
+        overall_score = sentiment_data.get("score", "N/A")
+        
+        sentences = sentiment_data.get("sentences", [])
+        
+        if sentences:
+            sentence_df = pd.DataFrame(sentences)
+            sentence_df = sentence_df[['text', 'emotion', 'sentiment', 'score']]
+            sentence_df.rename(columns={'text': 'Sentence', 'emotion': 'Emotion', 'sentiment': 'Sentiment', 'score': 'Score'}, inplace=True)
+        else:
+            sentence_df = pd.DataFrame(columns=['Sentence', 'Emotion', 'Sentiment', 'Score'])
+            
+        status_message = "✅ Sentiment analysis complete."
+        
+        return status_message, overall_emotion, overall_sentiment, str(overall_score), sentence_df
+
+    except requests.exceptions.RequestException as e:
+        return f"Request failed: {str(e)}", None, None, None, None
+    except Exception as e:
+        return f"An unexpected error occurred: {str(e)}", None, None, None, None
+
+
+with gr.Blocks() as demo:
+    gr.Markdown("""
+        <div style='text-align: center; margin-bottom: 24px;'>
+            <h1 style='font-size:2.2em; margin-bottom: 0.2em;'>🧩 Analyze Sentiment</h1>
+            <p style='font-size:1.2em; margin-top: 0;'>Perform line-by-line sentiment analysis on any text with detailed emotion detection.</p>
+            <p style='font-size:1em; margin-top: 0.5em;'>For more details and API usage, see the <a href='https://jigsawstack.com/docs/api-reference/ai/sentiment' target='_blank'>documentation</a>.</p>
+        </div>
+        """)
+    with gr.Row():
+            with gr.Column():
+                gr.Markdown("#### Input Text")
+                sentiment_text = gr.Textbox(
+                    label="Text to Analyze",
+                    lines=8,
+                    placeholder="Enter the text you want to analyze here..."
+                )
+                sentiment_btn = gr.Button("Analyze Sentiment", variant="primary")
+            
+            with gr.Column():
+                gr.Markdown("#### Overall Analysis")
+                sentiment_status = gr.Textbox(label="Status", interactive=False)
+                sentiment_emotion = gr.Textbox(label="Overall Emotion", interactive=False)
+                sentiment_sentiment = gr.Textbox(label="Overall Sentiment", interactive=False)
+                sentiment_score = gr.Textbox(label="Overall Score", interactive=False)
+
+    gr.Markdown("#### Sentence-Level Breakdown")
+    sentiment_sentences_df = gr.DataFrame(label="Sentence Analysis")
+
+    sentiment_btn.click(
+            analyze_sentiment,
+            inputs=[sentiment_text],
+            outputs=[sentiment_status, sentiment_emotion, sentiment_sentiment, sentiment_score, sentiment_sentences_df]
+    )
+demo.launch()

requirements.txt

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+gradio
+requests
+Pillow