Update app.py

app.py

@@ -1,81 +1,245 @@
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+# Simple Relationship Chat Analyzer for 
 import gradio as gr
 import google.generativeai as genai
 import json
+import re
+from collections import Counter
 
-# ✅ Configure Gemini API key
-API_KEY = "AIzaSyAtm1yxPoXsz30KJUnyQNN9QeGw3FMIoMU"
+# Configure Gemini API
+API_KEY = "AIzaSyAtm1yxPoXsz30KJUnyQNN9QeGw3FMIoMU"  # Replace with your actual API key
 genai.configure(api_key=API_KEY)
-model = genai.GenerativeModel(model_name="gemini-2.0-flash")
 
-# ✅ Analyze relationship chat from text input
-def analyze_text(text):
+model = genai.GenerativeModel(
+    model_name="gemini-2.0-flash",
+    generation_config={
+        "temperature": 0.7,
+        "max_output_tokens": 1500,
+    }
+)
+
+class SimpleAnalyzer:
+    def clean_text(self, text):
+        """Basic text cleaning"""
+        if not text:
+            return ""
+        
+        # Remove timestamps and system messages
+        text = re.sub(r'\d{1,2}:\d{2}(?::\d{2})?\s*(?:AM|PM|am|pm)?', '', text)
+        text = re.sub(r'\[.*?\]', '', text)
+        text = re.sub(r'<.*?>', '', text)
+        text = re.sub(r'\s+', ' ', text.strip())
+        
+        return text
+    
+    def get_basic_stats(self, text):
+        """Get simple statistics"""
+        if not text:
+            return {}
+        
+        words = text.split()
+        lines = [line.strip() for line in text.split('\n') if line.strip()]
+        
+        return {
+            'word_count': len(words),
+            'message_count': len([line for line in lines if len(line) > 5]),
+            'avg_words_per_message': len(words) / max(len(lines), 1)
+        }
+
+analyzer = SimpleAnalyzer()
+
+def analyze_relationship(chat_text):
+    """Main analysis function"""
+    if not chat_text or not chat_text.strip():
+        return "Please provide chat text to analyze.", "", "", ""
+    
+    # Clean and get stats
+    cleaned_text = analyzer.clean_text(chat_text)
+    stats = analyzer.get_basic_stats(cleaned_text)
+    
+    # Create analysis prompt
     prompt = f"""
-You are a relationship AI assistant.
-
-Analyze the chat text below and do all of the following:
-
-1. Provide a brief sentiment/emotional summary.
-2. Identify key events or milestones in the relationship.
-3. Write a short, heartfelt relationship narrative.
-4. Calculate a compatibility score from 0 to 100.
-5. Provide a clear and friendly interpretation of that score.
-
-Return ONLY a JSON object with the following keys:
-"sentiment_summary", "key_events", "narrative", "compatibility_score", "interpretation"
-
-Chat text:
-\"\"\"{text}\"\"\"
+Analyze this relationship chat conversation and provide insights in this exact JSON format:
+{{
+    "compatibility_score": number (0-100),
+    "relationship_stage": "string description",
+    "communication_style": "string description",
+    "strengths": ["strength1", "strength2", "strength3"],
+    "improvements": ["area1", "area2", "area3"],
+    "summary": "2-3 sentence relationship summary",
+    "red_flags": ["flag1", "flag2"] or []
+}}
+Chat text: {cleaned_text[:3000]}
+Provide only the JSON response, no other text.
 """
-    response = model.generate_content(prompt)
-    return response.text.strip()
-
-# ✅ Process and return outputs
-def process_chat(chat_text):
-    if not chat_text.strip():
-        return "", "", "", "", "", ""
-
-    analysis = analyze_text(chat_text)
-
+    
     try:
-        parsed = json.loads(analysis)
-    except Exception:
-        parsed = None
-
-    if parsed:
-        sentiment = parsed.get("sentiment_summary", "")
-        events = parsed.get("key_events", "")
-        narrative = parsed.get("narrative", "")
-        score = str(parsed.get("compatibility_score", ""))
-        interpretation = parsed.get("interpretation", "")
-    else:
-        sentiment = events = narrative = score = interpretation = ""
-
-    return analysis, sentiment, events, narrative, score, interpretation
-
-# ✅ Gradio UI
-with gr.Blocks() as demo:
-    gr.Markdown("# 💬 Relationship Chat Text Analyzer with Gemini 2.0 Flash")
-
-    chat_input = gr.Textbox(label="Paste your chat here", lines=20, placeholder="Paste chat content here...")
-
-    raw_output = gr.Textbox(label="Raw AI Analysis Response", lines=10, interactive=False)
-    sentiment_output = gr.Textbox(label="Sentiment Summary", interactive=False)
-    events_output = gr.Textbox(label="Key Events / Milestones", interactive=False)
-    narrative_output = gr.Textbox(label="Relationship Narrative", interactive=False)
-    score_output = gr.Textbox(label="Compatibility Score", interactive=False)
-    interpretation_output = gr.Textbox(label="Interpretation", interactive=False)
-
-    analyze_btn = gr.Button("Analyze Relationship")
-
-    analyze_btn.click(process_chat, inputs=chat_input, outputs=[
-        raw_output,
-        sentiment_output,
-        events_output,
-        narrative_output,
-        score_output,
-        interpretation_output,
-    ])
-
-# ✅ Launch app
-demo.launch()
+        response = model.generate_content(prompt)
+        analysis_text = response.text.strip()
+        
+        # Clean JSON response
+        if analysis_text.startswith('```json'):
+            analysis_text = analysis_text.split('```json')[1].split('```')[0].strip()
+        elif analysis_text.startswith('```'):
+            analysis_text = analysis_text.split('```')[1].split('```')[0].strip()
+        
+        # Parse JSON
+        analysis = json.loads(analysis_text)
+        
+        # Format outputs
+        stats_text = f"""📊 **Chat Statistics:**
+• Words: {stats['word_count']:,}
+• Messages: {stats['message_count']}
+• Avg words/message: {stats['avg_words_per_message']:.1f}
+• Relationship Stage: {analysis.get('relationship_stage', 'Unknown')}"""
+
+        compatibility_text = f"**Compatibility Score: {analysis.get('compatibility_score', 0)}/100**"
+        
+        strengths_text = "**💪 Strengths:**\n" + "\n".join([f"• {s}" for s in analysis.get('strengths', [])])
+        
+        improvements_text = "**🎯 Areas to Improve:**\n" + "\n".join([f"• {i}" for i in analysis.get('improvements', [])])
+        
+        summary_text = f"**📖 Summary:**\n{analysis.get('summary', 'No summary available')}"
+        
+        red_flags = analysis.get('red_flags', [])
+        if red_flags:
+            red_flags_text = "**⚠️ Red Flags:**\n" + "\n".join([f"• {flag}" for flag in red_flags])
+        else:
+            red_flags_text = "**✅ No significant red flags detected**"
+        
+        full_analysis = f"""{summary_text}
+{compatibility_text}
+{strengths_text}
+{improvements_text}
+{red_flags_text}
+**🗣️ Communication Style:** {analysis.get('communication_style', 'Not analyzed')}"""
+        
+        return full_analysis, stats_text, compatibility_text, f"{analysis.get('compatibility_score', 0)}"
+        
+    except json.JSONDecodeError:
+        return f"AI Response (couldn't parse as JSON):\n{analysis_text}", stats_text, "Score not available", "0"
+    except Exception as e:
+        return f"Error: {str(e)}", "Stats unavailable", "Score unavailable", "0"
+
+# Create Gradio interface
+def create_app():
+    with gr.Blocks(theme=gr.themes.Soft(), title="💕 Simple Chat Analyzer") as app:
+        
+        gr.HTML("""
+        <div style="text-align: center; margin-bottom: 30px;">
+            <h1>💕 Simple Relationship Chat Analyzer</h1>
+            <p><em>Quick insights into your relationship through chat analysis</em></p>
+        </div>
+        """)
+        
+        with gr.Row():
+            with gr.Column(scale=2):
+                chat_input = gr.Textbox(
+                    label="📝 Paste Your Chat Conversation",
+                    placeholder="Paste your WhatsApp, text messages, or any chat conversation here...",
+                    lines=12,
+                    max_lines=20
+                )
+                
+                with gr.Row():
+                    analyze_btn = gr.Button("🔍 Analyze", variant="primary", scale=2)
+                    clear_btn = gr.Button("🗑️ Clear", variant="secondary", scale=1)
+            
+            with gr.Column(scale=1):
+                stats_output = gr.Textbox(
+                    label="📊 Quick Stats",
+                    interactive=False,
+                    lines=8
+                )
+                
+                score_output = gr.Textbox(
+                    label="💯 Compatibility",
+                    interactive=False,
+                    lines=2
+                )
+        
+        # Main results
+        analysis_output = gr.Textbox(
+            label="🎯 Relationship Analysis",
+            interactive=False,
+            lines=15,
+            max_lines=25
+        )
+        
+        # Event handlers
+        def analyze_handler(text):
+            return analyze_relationship(text)
+        
+        def clear_handler():
+            return "", "", "", "", ""
+        
+        analyze_btn.click(
+            fn=analyze_handler,
+            inputs=[chat_input],
+            outputs=[analysis_output, stats_output, score_output, gr.State()]
+        )
+        
+        clear_btn.click(
+            fn=clear_handler,
+            outputs=[chat_input, analysis_output, stats_output, score_output, gr.State()]
+        )
+        
+        gr.HTML("""
+        <div style="text-align: center; margin-top: 20px; padding: 15px; background: #f0f0f0; border-radius: 8px;">
+            <p><strong>💡 Tips:</strong> Include longer conversations for better analysis • Remove personal info • Results are for guidance only</p>
+        </div>
+        """)
+    
+    return app
+
+# Launch the app
+if __name__ == "__main__":
+    print("🚀 Starting Simple Relationship Chat Analyzer...")
+    
+    app = create_app()
+    app.launch(
+        share=True,
+        server_name="0.0.0.0",
+        server_port=7860
+    )