Update app.py

app.py

@@ -1,126 +1,131 @@
 import os
+# Brute force installation to ensure world-class visuals
 os.system("pip install plotly pandas numpy pypdf")
 
 import gradio as gr
 import json
 import pandas as pd
-import plotly.graph_objects as go
 from huggingface_hub import InferenceClient
 from datetime import datetime
-import re
 
-# --- 1. INITIALIZATION ---
+# --- 1. SECURE INITIALIZATION ---
+# Using .strip() to kill any accidental newlines or spaces from the secret
 RAW_TOKEN = os.getenv("HF_TOKEN")
 HF_TOKEN = RAW_TOKEN.strip() if RAW_TOKEN else None
+
+# The Elite Brain: Qwen 2.5 7B (Reliable for 2026 Reasoning)
 client = InferenceClient("Qwen/Qwen2.5-7B-Instruct", token=HF_TOKEN)
 
-# --- 2. THE ORCHESTRATION ENGINE ---
+# --- 2. ORCHESTRATION ENGINE LOGIC ---
 
 def clinical_orchestrator(symptoms, history, wearable_data):
-    # Initialize UI
-    reasoning_path = "### 🛡️ INITIALIZING CLINICAL REASONING PATHWAY..."
-    final_report = ""
-    referral_slip = ""
+    if not HF_TOKEN:
+        yield "### ❌ ACCESS DENIED\nHF_TOKEN missing or invalid. Please check Space Secrets.", "", ""
+        return
     
     if not symptoms:
-        yield "### ⚠️ System Ready: Waiting for clinical input.", "", ""
+        yield "### ⚠️ SYSTEM READY\nAwaiting clinical data ingestion...", "", ""
         return
 
     try:
-        # STEP 1: DIFFERENTIAL DIAGNOSIS REASONING (XAI)
-        yield "### 🧠 PHASE 1: GENERATING DIFFERENTIAL DIAGNOSES...", "", ""
+        # --- PHASE 1: REASONING TRACE (XAI) ---
+        yield "### 🧠 PHASE 1: ACTIVATING CLINICAL REASONING PATHWAY...", "", ""
         
         prompt_1 = f"""
         System: Act as a Senior Clinical Orchestrator. 
-        Analyze: Symptoms: {symptoms}, History: {history}, Wearables: {wearable_data}.
-        Task: Show your step-by-step clinical reasoning for a Differential Diagnosis.
+        Input Symptoms: {symptoms}
+        Input History: {history}
+        Biometrics: {wearable_data}
+        
+        TASK: Perform a Step-by-Step Clinical Reasoning Trace for a Differential Diagnosis. 
+        Show your 'chain of thought'.
         """
         
-        reasoning_path = "## 🧠 Clinical Reasoning Trace\n"
-        for chunk in client.chat_completion(messages=[{"role": "user", "content": prompt_1}], max_tokens=1000, stream=True):
+        reasoning = "## 🧠 Clinical Reasoning Trace\n"
+        stream_1 = client.chat_completion(messages=[{"role": "user", "content": prompt_1}], max_tokens=800, stream=True)
+        
+        for chunk in stream_1:
             token = chunk.choices[0].delta.content
             if token:
-                reasoning_path += token
-                yield reasoning_path, "", ""
+                reasoning += token
+                yield reasoning, "", ""
 
-        # STEP 2: HOLISTIC HEALTH REPORT & GUIDELINE CHECK
-        yield reasoning_path, "### 📊 PHASE 2: CROSS-REFERENCING GLOBAL GUIDELINES...", ""
+        # --- PHASE 2: MASTER HEALTH REPORT ---
+        yield reasoning, "### 📊 PHASE 2: SYNTHESIZING MASTER HEALTH REPORT...", ""
         
         prompt_2 = f"""
-        Based on this reasoning: {reasoning_path}
-        Generate a 'Master Health Report'. Include:
-        1. Primary Diagnosis & Likelihood.
-        2. Guideline Check (WHO/ACC/NICE 2025).
-        3. Genomic/Metabolic Risk Factors.
-        4. Immediate Pharmacological/Lifestyle Plan.
+        Based on this reasoning: {reasoning}
+        Generate a professional Master Health Report. 
+        Include: Primary Diagnosis, Guideline Cross-Check (WHO/ACC), and 2026 Pharmacological Protocol.
         """
         
-        for chunk in client.chat_completion(messages=[{"role": "user", "content": prompt_2}], max_tokens=1500, stream=True):
+        report = "## 📊 Master Health Report\n"
+        stream_2 = client.chat_completion(messages=[{"role": "user", "content": prompt_2}], max_tokens=1000, stream=True)
+        
+        for chunk in stream_2:
             token = chunk.choices[0].delta.content
             if token:
-                final_report += token
-                yield reasoning_path, final_report, ""
+                report += token
+                yield reasoning, report, ""
 
-        # STEP 3: AUTONOMOUS SPECIALIST REFERRAL
-        yield reasoning_path, final_report, "### ✉️ PHASE 3: DRAFTING SPECIALIST REFERRAL..."
+        # --- PHASE 3: SPECIALIST REFERRAL ---
+        yield reasoning, report, "### ✉️ PHASE 3: DRAFTING AUTONOMOUS REFERRAL..."
         
-        prompt_3 = f"Based on the diagnosis: {final_report}, draft a professional medical referral letter to the appropriate specialist. Include ICD-11 codes."
+        prompt_3 = f"Diagnosis: {report}. Draft a professional medical referral letter to the appropriate specialist. Include ICD-11 codes."
         
         res_3 = client.chat_completion(messages=[{"role": "user", "content": prompt_3}], max_tokens=800)
-        referral_slip = res_3.choices[0].message.content
+        referral = res_3.choices[0].message.content
         
-        yield reasoning_path, final_report, referral_slip
+        yield reasoning, report, f"## ✉️ Autonomous Specialist Referral\n{referral}"
 
     except Exception as e:
-        yield f"### ❌ System Failure\n{str(e)}", "", ""
+        yield f"### ❌ UPLINK FAILURE\n{str(e)}", "", ""
 
-# --- 3. THE "PRESTIGE" UI DESIGN ---
+# --- 3. THE LUXURY "PRESTIGE" UI ---
 
 css = """
-body, .gradio-container { background-color: #080808 !important; color: #d4af37 !important; font-family: 'Playfair Display', serif; }
-.prestige-card { border: 1px solid #d4af37 !important; border-radius: 15px !important; background: #111 !important; padding: 25px; box-shadow: 0 0 30px rgba(212, 175, 55, 0.1); }
-.gold-btn { background: linear-gradient(135deg, #d4af37 0%, #f9f295 50%, #d4af37 100%) !important; color: #000 !important; font-weight: 900 !important; border: none !important; cursor: pointer; transition: 0.3s; }
-.gold-btn:hover { box-shadow: 0 0 40px rgba(212, 175, 55, 0.5); transform: scale(1.01); }
-h1 { color: #d4af37 !important; text-align: center; font-size: 3rem !important; text-transform: uppercase; letter-spacing: 5px; }
+body, .gradio-container { background-color: #050505 !important; color: #d4af37 !important; font-family: 'Georgia', serif; }
+.prestige-card { border: 1px solid #d4af37 !important; border-radius: 15px !important; background: rgba(20, 20, 20, 0.9) !important; padding: 25px; box-shadow: 0 0 30px rgba(212, 175, 55, 0.1); }
+.gold-btn { background: linear-gradient(135deg, #d4af37 0%, #f9f295 100%) !important; color: #000 !important; font-weight: 900 !important; border: none !important; cursor: pointer; transition: 0.3s; }
+.gold-btn:hover { box-shadow: 0 0 40px #d4af37; transform: scale(1.02); }
+textarea, input { background: #111 !important; color: #fff !important; border: 1px solid #333 !important; }
 .tabs { border-color: #d4af37 !important; }
-textarea, input { background: #1a1a1a !important; color: white !important; border: 1px solid #333 !important; }
+h1 { letter-spacing: 4px; text-transform: uppercase; }
 """
 
 with gr.Blocks(theme=gr.themes.Default(), css=css) as demo:
     gr.Markdown("# AETHER-HEALTH")
-    gr.Markdown("### AUTONOMOUS CLINICAL ORCHESTRATOR • PRESTIGE EDITION")
+    gr.Markdown("### 🏛️ AUTONOMOUS CLINICAL ORCHESTRATOR • PRESTIGE EDITION")
     
     with gr.Row():
-        # INPUT CHANNEL
+        # INPUT COLUMN
         with gr.Column(scale=1, elem_classes="prestige-card"):
             gr.Markdown("### 📥 CLINICAL INGESTION")
-            symptoms_in = gr.Textbox(label="Presenting Symptoms", lines=3, placeholder="Describe current issues...")
-            history_in = gr.Textbox(label="Patient History (EHR Context)", lines=3, placeholder="Past surgeries, genomics, labs...")
-            wearable_in = gr.Textbox(label="Wearable Biometrics", value="Heart Rate: 72, Sleep: 7.5h, HRV: 55ms")
+            symp = gr.Textbox(label="Presenting Symptoms", lines=3)
+            hist = gr.Textbox(label="Clinical History (PDF/EHR)", lines=3)
+            wear = gr.Textbox(label="Wearable Stream", value="HR: 72bpm, HRV: 50ms, SpO2: 98%")
             
             run_btn = gr.Button("⚡ ORCHESTRATE CARE", elem_classes="gold-btn")
             
             gr.Markdown("---")
-            gr.Markdown("#### 🛡️ ORCHESTRATOR STATUS")
-            gr.Markdown("Safety Protocol: <span style='color:#00ff00'>VERIFIED</span>")
-            gr.Markdown("Compliance: <span style='color:#d4af37'>GDPR/HIPAA 2026</span>")
+            gr.Markdown("#### 🛡️ SYSTEM PROTOCOL")
+            gr.Markdown("XAI Trace: <span style='color:#00ff00'>ACTIVE</span>")
+            gr.Markdown("Token Security: <span style='color:#00ff00'>ENFORCED</span>")
 
-        # INTELLIGENCE HUB
+        # OUTPUT COLUMN
         with gr.Column(scale=2, elem_classes="prestige-card"):
             with gr.Tabs(elem_classes="tabs"):
                 with gr.TabItem("🧠 REASONING TRACE"):
-                    reason_out = gr.Markdown("### *System Idle: Awaiting Clinical Data*")
-                
-                with gr.TabItem("📊 MASTER HEALTH REPORT"):
-                    report_out = gr.Markdown("### *Synthesizing Analysis...*")
-                
+                    out_1 = gr.Markdown("### *System Idle...*")
+                with gr.TabItem("📊 MASTER REPORT"):
+                    out_2 = gr.Markdown("### *Awaiting Phase 1...*")
                 with gr.TabItem("✉️ AUTONOMOUS REFERRAL"):
-                    referral_out = gr.Markdown("### *Drafting Specialist Communication...*")
+                    out_3 = gr.Markdown("### *Awaiting Phase 2...*")
 
     run_btn.click(
         fn=clinical_orchestrator,
-        inputs=[symptoms_in, history_in, wearable_in],
-        outputs=[reason_out, report_out, referral_out],
+        inputs=[symp, hist, wear],
+        outputs=[out_1, out_2, out_3],
         api_name=False
     )