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| import gradio as gr | |
| from transformers import pipeline | |
| # Load your model | |
| model_name = "avtak/erisk-longformer-depression-v1" | |
| classifier = pipeline("text-classification", model=model_name, truncation=True, max_length=4096, top_k=None) | |
| def analyze_text(user_text): | |
| """ | |
| Analyzes text for linguistic markers of depression using Mental-Longformer. | |
| This MCP tool provides depression risk assessment based on long-form user histories. | |
| Trained on eRisk datasets (2017-2022) with F1-score of 0.7668. | |
| """ | |
| if not user_text.strip(): | |
| return "⚠️ Please provide text to analyze." | |
| results = classifier(user_text)[0] | |
| # Get top prediction | |
| top = max(results, key=lambda x: x['score']) | |
| label = "🔴 Depressed Patterns Detected" if top['label'] == 'LABEL_1' else "✅ Non-Depressed Patterns" | |
| confidence = top['score'] * 100 | |
| output = f"""# {label} | |
| **Confidence:** {confidence:.1f}% | |
| ## Detailed Scores: | |
| """ | |
| for r in sorted(results, key=lambda x: x['score'], reverse=True): | |
| pattern = "Depressed" if r['label'] == 'LABEL_1' else "Non-Depressed" | |
| output += f"- {pattern}: {r['score']*100:.1f}%\n" | |
| output += """ | |
| --- | |
| ⚠️ **DISCLAIMER:** Research tool only - not for medical diagnosis. Consult a healthcare professional for mental health concerns. | |
| 📞 **Crisis Resources:** Text HOME to 741741 (US) | Visit befrienders.org (International) | |
| """ | |
| return output | |
| # Examples | |
| example_depressed = """Post 1: Another sleepless night. Can't stop my mind from racing through every mistake I've made this week. I feel like such a failure. | |
| Post 2: My friend invited me out but I cancelled. The thought of pretending to be okay is exhausting. I just want to be alone. | |
| Post 3: I used to love gaming but now I can't even focus. Everything feels pointless. What's wrong with me?""" | |
| example_normal = """Post 1: Started a new herb garden today! My basil is already sprouting. Feeling proud of this little project. | |
| Post 2: Had a great workout this morning. The weather was perfect for a run. Ready to tackle the day! | |
| Post 3: Dinner with friends tonight was so much fun. We tried that new Thai place and the food was amazing!""" | |
| # Build interface | |
| demo = gr.Interface( | |
| fn=analyze_text, | |
| inputs=gr.Textbox( | |
| label="📝 Enter User Text History", | |
| placeholder="Paste multiple posts or long-form text (minimum 200 words recommended)...", | |
| lines=10 | |
| ), | |
| outputs=gr.Markdown(label="📊 Analysis Results"), | |
| title="🧠 Early Depression Detection via Mental-Longformer", | |
| description=""" | |
| MCP-enabled agent for detecting depression risk from social media text. | |
| **Model:** erisk-longformer-depression-v1 | **F1-Score:** 0.7668 | **Context:** 4,096 tokens | |
| Built on Master's thesis research at University of Malaya using Gemini 2.5 Flash data augmentation. | |
| 🔗 [Model Card](https://huggingface.co/avtak/erisk-longformer-depression-v1) | 👤 [Author LinkedIn](https://www.linkedin.com/in/hassanzh/) | |
| """, | |
| examples=[ | |
| [example_depressed], | |
| [example_normal] | |
| ], | |
| theme=gr.themes.Soft() | |
| ) | |
| # 🔥 Enable MCP Server | |
| if __name__ == "__main__": | |
| demo.launch(mcp_server=True) | |