Update app.py

app.py

@@ -2,60 +2,34 @@ import gradio as gr
 from transformers import pipeline
 import torch
 
-# Using gemma-2-2b-it for high-speed edge simulation
-# In a full clinical app, we would swap this for 'google/medgemma-2b'
-model_id = "google/gemma-2-2b-it"
+# Switching to an UNGATED model to bypass the 403 error
+# Phi-3 is a high-performance Small Language Model (SLM) from Microsoft
+model_id = "microsoft/Phi-3-mini-4k-instruct"
 
-print("Loading the Digital Vaccine model...")
+print("Loading the Digital Vaccine model (Phi-3)...")
 pipe = pipeline(
     "text-generation",
     model=model_id,
     device_map="auto",
-    torch_dtype=torch.bfloat16
+    torch_dtype="auto", 
+    trust_remote_code=True
 )
 
 def digital_wellness_intervention(user_input, scroll_velocity):
-    # Engineering the "Circuit Breaker" Logic
-    # We simulate a "Zombiescroll" detection if velocity is high and input is low-value
+    # Logic: High velocity (>70) triggers the 'Zombiescroll' detection
     is_zombiescroll = scroll_velocity > 70 
     
-    prompt = f"""
-    Context: A user is currently in a high-velocity scrolling loop. 
-    State: {'Zombiescroll' if is_zombiescroll else 'Intentional Browsing'}
-    User's last thought: {user_input}
+    # Updated prompt format for Phi-3's chat template
+    prompt = f"<|user|>\nContext: The user is in a high-velocity scrolling loop.\nState: {'Zombiescroll' if is_zombiescroll else 'Intentional Browsing'}\nUser thought: {user_input}\nTask: Provide a 2-sentence 'Micro-CBT' intervention to help them break the trance.<|end|>\n<|assistant|>"
     
-    Task: Act as a clinical AI (MedGemma-style). Provide a short, 2-sentence 'Micro-CBT' 
-    intervention to help the user regain focus and break the dopamine loop.
-    """
+    outputs = pipe(prompt, max_new_tokens=100, do_sample=True, temperature=0.7)
     
-    messages = [{"role": "user", "content": prompt}]
-    outputs = pipe(messages, max_new_tokens=100, do_sample=True, temperature=0.7)
-    
-    intervention_text = outputs[0]["generated_text"][-1]["content"]
+    # Extracting the assistant's response
+    full_text = outputs[0]["generated_text"]
+    intervention_text = full_text.split("<|assistant|>")[-1].strip()
     
     status = "⚠️ INTERVENTION TRIGGERED" if is_zombiescroll else "✅ FOCUS MAINTAINED"
     return status, intervention_text
 
 # Gradio Interface
-with gr.Blocks(theme=gr.themes.Soft()) as demo:
-    gr.Markdown("# 🧬 The Digital Vaccine: AI-in-the-Loop")
-    gr.Markdown("This Space simulates an edge-AI 'Circuit Breaker' using a MedGemma-style architecture.")
-    
-    with gr.Row():
-        with gr.Column():
-            input_text = gr.Textbox(label="What are you looking for right now?", placeholder="e.g., Just checking notifications...")
-            velocity = gr.Slider(minimum=0, maximum=100, value=20, label="Simulated Scroll Velocity (Dopamine Intensity)")
-            btn = gr.Button("Analyze My State", variant="primary")
-            
-        with gr.Column():
-            status_output = gr.Label(label="System Status")
-            intervention_output = gr.Textbox(label="MedGemma Intervention")
-
-    btn.click(digital_wellness_intervention, inputs=[input_text, velocity], outputs=[status_output, intervention_output])
-    
-    gr.Examples(
-        examples=[["Learning about Quantum Physics", 10], ["I'm bored and just clicking links", 85]],
-        inputs=[input_text, velocity]
-    )
-
-demo.launch() 
+with gr.Blocks(theme