Update app.py

app.py

@@ -9,23 +9,19 @@ hf_token = os.getenv("HF_TOKEN")
 if hf_token:
     login(token=hf_token)
 
+# --- 2. LOAD TOOL ---
 print("Loading Mental-Longformer...")
 model_name = "avtak/erisk-longformer-depression-v1"
-classifier = pipeline(
-    "text-classification",
-    model=model_name,
-    truncation=True,
-    max_length=4096,
-    top_k=None,
-)
+classifier = pipeline("text-classification", model=model_name, truncation=True, max_length=4096, top_k=None)
 
-# --- 2. MCP TOOLS ---
+# --- 3. MCP TOOLS ---
 
 def get_crisis_resources(location: str = "Global") -> str:
+    """Returns mental health resources based on location."""
     resources = {
-        "US": "🇺🇸 US: Crisis Text Line: 741741 | Suicide Lifeline: 988",
-        "Malaysia": "🇲🇾 Malaysia: Befrienders KL: 03-76272929 | Talian Kasih: 15999",
-        "Global": "🌍 International: befrienders.org",
+        "US": "🇺🇸 **US:** Crisis Text Line: 741741 | Suicide Lifeline: 988",
+        "Malaysia": "🇲🇾 **Malaysia:** Befrienders KL: 03-76272929 | Talian Kasih: 15999",
+        "Global": "🌍 **International:** [befrienders.org](https://www.befrienders.org)"
     }
     for key in resources:
         if location and key.lower() in location.lower():
@@ -33,91 +29,91 @@ def get_crisis_resources(location: str = "Global") -> str:
     return resources["Global"]
 
 def detect_depression_risk(text: str) -> dict:
-    processed_text = text.replace("\n", "\n\n")
+    """Analyzes text using Mental-Longformer (eRisk 2025)."""
+    
+    # --- THESIS LOGIC: AGGREGATION (CRITICAL) ---
+    # We replace single newlines with double newlines so the model sees distinct posts
+    # This matches your Master's Thesis data preparation method.
+    processed_text = text.replace("\n", "\n\n") 
+    
     results = classifier(processed_text)[0]
-    prob = next((r["score"] for r in results if r["label"] == "LABEL_1"), 0.0)
-
-    if prob < 0.40:
+    prob = next((r['score'] for r in results if r['label'] == 'LABEL_1'), 0)
+    
+    # Thesis Thresholds (Figure 4.15)
+    if prob < 0.40: 
         level = "Low Risk"
         biomarker = "Healthy External Focus"
         desc = "Matches 'Isolated Control' group. High lexical diversity, focus on hobbies/events."
-        color = "#10b981"
-    elif 0.40 <= prob < 0.60:
+        color = "#10b981" # Green
+    elif 0.40 <= prob < 0.60: 
         level = "Moderate Risk"
         biomarker = "Echo Chamber Interaction"
-        desc = "Matches 'Interactive Non-Depressed' group. Engaging in support forums but likely not clinically depressed."
-        color = "#f59e0b"
-    else:
+        desc = "Matches 'Interactive Non-Depressed' group. Engaging in support forums but likely not clinically depressed (Supportive Responder)."
+        color = "#f59e0b" # Yellow
+    else: 
         level = "High Risk"
         biomarker = "Nocturnal & High-Effort"
-        desc = "Matches 'Depressed' cohort. Nocturnal posting, high‑effort/low‑frequency posts."
-        color = "#ef4444"
-
+        desc = "Matches 'Depressed' cohort. Indicators: Nocturnal posting spikes (00-05 UTC), high-effort/low-frequency posting."
+        color = "#ef4444" # Red
+        
     return {
-        "probability": prob,
-        "risk_level": level,
+        "probability": prob, 
+        "risk_level": level, 
         "biomarker": biomarker,
         "description": desc,
         "color": color,
-        "word_count": len(processed_text.split()),
+        "word_count": len(processed_text.split())
     }
 
-# --- 3. AGENT LOGIC (messages format only) ---
+# --- 4. AGENT LOGIC (Dual State Management) ---
 
-def generate_response(history, risk_context, provider):
+def generate_response(api_history, risk_context, provider):
+    """Generates response using Sponsor API."""
     if not risk_context:
-        risk_context = {
-            "risk_level": "Unknown",
-            "probability": 0.0,
-            "description": "No analysis run yet.",
-        }
+        risk_context = {"risk_level": "Unknown", "probability": 0.0, "description": "No analysis run yet."}
 
+    client = None
+    model_id = None
+    
     if provider == "SambaNova":
-        client = OpenAI(
-            base_url="https://api.sambanova.ai/v1",
-            api_key=os.getenv("SAMBANOVA_API_KEY"),
-        )
+        client = OpenAI(base_url="https://api.sambanova.ai/v1", api_key=os.getenv("SAMBANOVA_API_KEY"))
         model_id = "Meta-Llama-3.3-70B-Instruct"
-    else:
-        client = OpenAI(
-            base_url="https://api.tokenfactory.nebius.com/v1/",
-            api_key=os.getenv("NEBIUS_API_KEY"),
-        )
+    else: 
+        client = OpenAI(base_url="https://api.tokenfactory.nebius.com/v1/", api_key=os.getenv("NEBIUS_API_KEY"))
         model_id = "moonshotai/Kimi-K2-Thinking"
 
     system_prompt = f"""
-You are 'Dr. Longformer', a specialized Clinical AI Assistant based on Hassan's 2025 Thesis.
-
-CURRENT USER CONTEXT:
-- Analyzed Risk: {risk_context['risk_level']} ({risk_context['probability']:.1%})
-- Detected Pattern: {risk_context['description']}
-
-YOUR GOAL: Provide supportive, scientifically-grounded chat. Max 2 sentences. Do not diagnose.
-""".strip()
+    You are 'Dr. Longformer', a specialized Clinical AI Assistant based on Hassan's 2025 Thesis.
+    CURRENT USER CONTEXT:
+    - Analyzed Risk: {risk_context['risk_level']} ({risk_context['probability']:.1%})
+    - Detected Pattern: {risk_context['description']}
+    YOUR GOAL: Provide supportive, scientifically-grounded chat. Max 2 sentences.
+    """
 
     messages = [{"role": "system", "content": system_prompt}]
-    messages.extend(history)  # history is already [{"role": ..., "content": ...}]
+    messages.extend(api_history)
 
     try:
-        resp = client.chat.completions.create(
-            model=model_id,
-            messages=messages,
-            temperature=0.7,
-            max_tokens=300,
+        response = client.chat.completions.create(
+            model=model_id, 
+            messages=messages, 
+            temperature=0.7, 
+            max_tokens=300
         )
-        return resp.choices[0].message.content
+        return response.choices[0].message.content
     except Exception as e:
-        return f"⚠️ Error with {provider}: {e}"
+        return f"⚠️ Error with {provider}: {str(e)}"
 
-# --- 4. UI ORCHESTRATION (Chatbot uses messages format) ---
+# --- 5. UI ORCHESTRATION ---
 
 def run_analysis(text, location, provider):
-    if not text.strip():
-        return None, [], None
-
+    if not text.strip(): return None, [], [], None
+    
+    # 1. Run Tool
     data = detect_depression_risk(text)
     resources = get_crisis_resources(location)
-
+    
+    # 2. Visual Dashboard
     html_dashboard = f"""
     <div style="padding: 20px; border-radius: 12px; background-color: {data['color']}15; border: 1px solid {data['color']};">
         <div style="display: flex; justify-content: space-between; align-items: center;">
@@ -137,108 +133,135 @@ def run_analysis(text, location, provider):
         </div>
     </div>
     """
-
-    # Initial assistant message
-    history = [
-        {"role": "assistant", "content": generate_response(
-            [{"role": "user", "content": "I just ran the analysis. Please explain my results."}],
-            data,
-            provider
-        )}
-    ]
-
-    # dashboard HTML, chatbot messages (list[dict]), risk_data
-    return html_dashboard, history, data
-
-def user_chat(user_message, history, risk_data, provider):
-    if not user_message:
-        return history, ""
-
-    history.append({"role": "user", "content": user_message})
-    ai_msg = generate_response(history, risk_data, provider)
-    history.append({"role": "assistant", "content": ai_msg})
-    return history, ""
-
-# --- 5. EXAMPLES ---
-
-example_low = """The new update for the Linux kernel fixed some Realtek driver issues I was hitting.
-On a different note, the basketball team's defensive stats improved a lot this season.
-I also spent time woodworking on a walnut coffee table. The grain is tricky but satisfying to work with."""
-
-example_mod = """Things have been pretty busy at work with a big project and tight deadlines.
-Sleep could be better; I've been staying up too late scrolling my phone.
-Went hiking with some friends last weekend which helped me reset a bit."""
-
-example_high = """I don't know why I even bother getting out of bed anymore.
-I've been avoiding my friends for weeks and can't bring myself to reply.
-Everything feels grey and heavy, and I was up until 4 AM staring at the ceiling again."""
-
-# --- 6. UI LAYOUT ---
-
+    
+    # 3. Agent Greeting
+    # Format for API: List of Dicts
+    api_history = [{"role": "user", "content": "I just ran the analysis. Please explain my results."}]
+    ai_msg = generate_response(api_history, data, provider)
+    api_history.append({"role": "assistant", "content": ai_msg})
+    
+    # Format for UI: List of Tuples [(None, AI_Message)]
+    # CRITICAL FIX: This standard format works on ALL Gradio versions
+    ui_history = [(None, ai_msg)]
+    
+    return html_dashboard, ui_history, api_history, data
+
+def user_chat(user_message, ui_history, api_history, risk_data, provider):
+    if not user_message: return ui_history, api_history, ""
+    
+    # 1. Update API History
+    api_history.append({"role": "user", "content": user_message})
+    
+    # 2. Update UI History (User message only first)
+    ui_history.append([user_message, None])
+    
+    # 3. Generate Response
+    ai_msg = generate_response(api_history, risk_data, provider)
+    
+    # 4. Update API History
+    api_history.append({"role": "assistant", "content": ai_msg})
+    
+    # 5. Update UI History (Add AI response)
+    ui_history[-1][1] = ai_msg
+    
+    return ui_history, api_history, ""
+
+# --- 6. EXAMPLES (RESTORED) ---
+example_low = """The new update for the Linux kernel (6.8) finally addressed the driver issues I was seeing with Realtek cards. I read the changelog on kernel.org and noticed they patched the module specific to the rtl8821ce chipset.
+
+On a different note, the defensive stats for the basketball team have improved significantly. Allowing 15% fewer points per possession is a game changer.
+
+I also spent some time woodworking. I'm building a walnut coffee table and the grain is tricky to plane. I might switch to a polyurethane finish for durability."""
+
+example_mod = """Things have been pretty busy at work. We're in the middle of a big project and deadlines are tight. Staying a bit later than usual but that's just how it goes sometimes. Team is handling it well overall.
+
+Sleep could be better. Been staying up too late scrolling my phone. Need to work on that. Usually feel okay once I get moving in the morning though.
+
+Went hiking with some friends last weekend which was nice. Good to get outside and move around. We're talking about doing another trip next month. Weather should be better by then."""
+
+example_high = """I don't know why I even bother getting out of bed anymore. I slept for 12 hours yesterday and I'm still exhausted. It feels like my limbs weigh a thousand pounds.
+
+I've been avoiding my friends for weeks. They keep texting me, but I can't bring myself to reply. The thought of socializing is terrifying.
+
+Everything feels like a shade of grey. I can't concentrate on my work. I feel like I'm drowning while everyone else is breathing fine. I was up until 4 AM again last night just staring at the ceiling."""
+
+# --- 7. UI LAYOUT ---
 with gr.Blocks(title="Depression Risk Agent") as demo:
     gr.Markdown("# 🧠 Early Depression Detection Agent (MCP)")
-    gr.Markdown("Agentic system using **Mental-Longformer** (Tool) + **SambaNova/Nebius** (Chat).")
-    gr.Markdown("⚡ Powered by: SambaNova (Llama 3.3) & Nebius (Kimi K2)")
-
+    gr.Markdown("Agentic system using **Mental-Longformer** (Tool) + **SambaNova/Nebius** (Reasoning).")
+    gr.Markdown("⚡ **Powered by:** [SambaNova](https://sambanova.ai/) (Llama 3.3) & [Nebius](https://nebius.com/) (Kimi K2)")
+    
+    # Internal State
     risk_state = gr.State(None)
-
+    api_state = gr.State([]) # Stores [{"role":...}] for the LLM
+    
     with gr.Row():
+        # LEFT: INPUT
         with gr.Column(scale=1):
             input_text = gr.Textbox(
-                label="User Timeline (Paste posts here)",
-                lines=8,
+                label="User Timeline (Paste posts here)", 
+                lines=8, 
                 placeholder="[Post 1] ...\n\n[Post 2] ...",
-                value=example_high,
+                value=example_high
             )
-
+            
+            # EXAMPLES ROW
             gr.Markdown("### 🔍 Try Thesis Patterns")
             with gr.Row():
-                btn_low = gr.Button("🟢 Low Risk", size="sm", variant="secondary")
-                btn_mod = gr.Button("🟡 Moderate", size="sm", variant="secondary")
-                btn_high = gr.Button("🔴 High Risk", size="sm", variant="secondary")
-
+                btn_low = gr.Button("🟢 Low Risk", size="sm")
+                btn_mod = gr.Button("🟡 Moderate", size="sm")
+                btn_high = gr.Button("🔴 High Risk", size="sm")
+            
+            # SETTINGS ROW
             gr.Markdown("### ⚙️ Settings")
             with gr.Row():
-                loc_drop = gr.Dropdown(
-                    ["Global", "US", "Malaysia"],
-                    value="Malaysia",
-                    label="Crisis Resource Region",
-                )
-                prov_drop = gr.Dropdown(
-                    ["SambaNova", "Nebius"],
-                    value="SambaNova",
-                    label="Agent Brain",
-                )
-
+                loc_drop = gr.Dropdown(["Global", "US", "Malaysia"], value="Malaysia", label="Crisis Resource Region")
+                prov_drop = gr.Dropdown(["SambaNova", "Nebius"], value="SambaNova", label="Agent Brain")
+            
             analyze_btn = gr.Button("🚀 Run Clinical Analysis", variant="primary", size="lg")
+            
+            with gr.Accordion("🔧 MCP Tools Exposed", open=False):
+                gr.Markdown("- `detect_depression_risk`\n- `get_crisis_resources`")
 
+        # RIGHT: DASHBOARD & CHAT
         with gr.Column(scale=1):
             dashboard = gr.HTML(label="Clinical Dashboard")
-            chatbot = gr.Chatbot(label="Agent Chat", height=400, type="messages")
+            
+            # FIXED: REMOVED type="messages" to prevent crash. Uses standard Tuples.
+            chatbot = gr.Chatbot(label="Agent Chat", height=400)
+            
             msg_input = gr.Textbox(label="Chat with Agent", placeholder="Ask about your results or get advice...")
             send_btn = gr.Button("Send Message")
 
-    # Wiring
+    # WIRING
+    
+    # 1. Analyze Button -> Updates Dashboard, Chatbot, Risk State
     analyze_btn.click(
         run_analysis,
         inputs=[input_text, loc_drop, prov_drop],
-        outputs=[dashboard, chatbot, risk_state],
+        outputs=[dashboard, chatbot, api_state, risk_state]
     )
-
+    
+    # 2. Example Buttons
     btn_low.click(lambda: example_low, None, input_text)
     btn_mod.click(lambda: example_mod, None, input_text)
     btn_high.click(lambda: example_high, None, input_text)
-
+    
+    # 3. Chat Interactions
+    # Note: We pass 'chatbot' as both input and output (it holds the history in 'tuples' format)
     send_btn.click(
         user_chat,
-        inputs=[msg_input, chatbot, risk_state, prov_drop],
-        outputs=[chatbot, msg_input],
+        inputs=[msg_input, chatbot, api_state, risk_state, prov_drop],
+        outputs=[chatbot, api_state, msg_input]
     )
     msg_input.submit(
         user_chat,
-        inputs=[msg_input, chatbot, risk_state, prov_drop],
-        outputs=[chatbot, msg_input],
+        inputs=[msg_input, chatbot, api_state, risk_state, prov_drop],
+        outputs=[chatbot, api_state, msg_input]
     )
 
 if __name__ == "__main__":
-    demo.launch(mcp_server=True, theme=gr.themes.Soft())
+    demo.launch(
+        mcp_server=True, 
+        theme=gr.themes.Soft()
+    )