Update app.py

app.py

@@ -1,164 +1,87 @@
-import os
 import gradio as gr
-from datetime import datetime
 from db import models
-from utils import ai_engine, pdf_export, notifications
-from analytics import dashboard
+from utils.ai_engine import generate_text
 
-# === Secrets ===
-ADMIN_PASS = os.getenv("ADMIN_PASS", "admin123")
+# ---------------------------------------------------
+# 🛠️ Initialize Database (SQLite)
+# ---------------------------------------------------
 
-# === Initialize Database ===
-models.create_tables()
+try:
+    models.create_tables()
+except Exception as e:
+    print("DB init warning:", e)
 
-# === Helper Functions ===
 
-# SOAP Generation
+# ---------------------------------------------------
+# 🧠 AI Functions
+# ---------------------------------------------------
+
 def generate_soap(subjective, objective, assessment, plan):
-    note = ai_engine.generate_soap(subjective, objective, assessment, plan)
-    return note
-
-# SOAP Analysis + Alerts
-def analyze_soap(note_text, patient_name="Unknown"):
-    history = ""  # Future: fetch patient history
-    analysis, alerts = ai_engine.analyze_note(note_text, history)
-    # Save alerts
-    for alert_text in alerts:
-        conn = models.get_conn()
-        cur = conn.cursor()
-        cur.execute("INSERT INTO alerts (note_id, user_id, alert_text) VALUES (%s,%s,%s)",
-                    (0, 0, alert_text))  # Note: user_id=0 placeholder
-        conn.commit()
-        cur.close()
-        conn.close()
-        # Send email alert (optional)
-        notifications.send_alert_email("clinic@example.com", f"Critical Alert for {patient_name}", alert_text)
-    return analysis + ("\n\nALERTS:\n" + "\n".join(alerts) if alerts else "")
-
-# Payment Submission
-def submit_payment(name, phone, method, amount, receipt):
-    if receipt is None:
-        return "Please upload a receipt."
-    os.makedirs("uploads", exist_ok=True)
-    filename = f"uploads/{datetime.now().timestamp()}_{receipt.name}"
-    receipt.save(filename)
-    # Insert into DB
-    conn = models.get_conn()
-    cur = conn.cursor()
-    cur.execute("INSERT INTO payments (user_id, amount, method, receipt_file) VALUES (%s,%s,%s,%s)",
-                (0, amount, method, filename))
-    conn.commit()
-    cur.close()
-    conn.close()
-    return "Payment submitted. Pending verification."
-
-# Admin Login
-def admin_login(password):
-    if password == ADMIN_PASS:
-        return gr.update(visible=True), "Login successful."
-    return gr.update(visible=False), "Incorrect password."
-
-# Get pending payments
-def get_pending_payments():
-    conn = models.get_conn()
-    cur = conn.cursor()
-    cur.execute("SELECT id, user_id, amount, method, receipt_file FROM payments WHERE verified=false")
-    rows = cur.fetchall()
-    cur.close()
-    conn.close()
-    return rows
-
-# Verify payment
-def verify_payment(payment_id):
-    conn = models.get_conn()
-    cur = conn.cursor()
-    cur.execute("UPDATE payments SET verified=true WHERE id=%s", (payment_id,))
-    conn.commit()
-    cur.close()
-    conn.close()
-    return "Payment verified."
-
-# Generate PDF of Notes
-def export_patient_notes(patient_name="Unknown"):
-    # Fetch notes
-    conn = models.get_conn()
-    cur = conn.cursor()
-    cur.execute("SELECT patient_name, content, ai_analysis, ai_suggestion, ai_differential, created_at FROM notes")
-    notes = [{"patient_name": row[0],
-              "content": row[1],
-              "ai_analysis": row[2],
-              "ai_suggestion": row[3],
-              "ai_differential": row[4],
-              "created_at": row[5]} for row in cur.fetchall()]
-    cur.close()
-    conn.close()
-    filename = f"uploads/{patient_name.replace(' ','_')}_notes.pdf"
-    pdf_export.generate_pdf(patient_name, notes, filename)
-    return filename
-
-# Analytics Dashboard
-def show_dashboard():
-    fig = dashboard.generate_dashboard_figure()
-    return fig
-
-# === Gradio UI ===
-with gr.Blocks(title="Selam Scribe — State-of-the-Art Healthcare AI") as demo:
-
-    gr.Markdown("# Selam Scribe 🌟 Ethiopian Healthcare AI Platform")
-    gr.Markdown("Generate SOAP notes, analyze patients, submit payments, export PDFs, view analytics.")
-
-    # --- SOAP Note Generation Tab ---
-    with gr.Tab("📝 Generate SOAP"):
-        subjective = gr.Textbox(label="Subjective")
-        objective = gr.Textbox(label="Objective")
-        assessment = gr.Textbox(label="Assessment")
-        plan = gr.Textbox(label="Plan")
-        soap_output = gr.Textbox(label="Generated SOAP Note")
-        gr.Button("Generate SOAP").click(generate_soap,
-                                        [subjective, objective, assessment, plan],
-                                        soap_output)
-
-    # --- SOAP Analysis Tab ---
-    with gr.Tab("🔍 Analyze SOAP"):
-        note_input = gr.Textbox(label="SOAP Note", lines=12)
-        analysis_output = gr.Textbox(label="Analysis + Alerts")
-        gr.Button("Analyze Note").click(analyze_soap, [note_input], analysis_output)
-
-    # --- Payment Tab ---
-    with gr.Tab("💵 Payment"):
-        pay_name = gr.Textbox(label="Full Name")
-        pay_phone = gr.Textbox(label="Phone Number")
-        pay_method = gr.Radio(["Telebirr", "Bank Transfer"], label="Payment Method")
-        pay_amount = gr.Number(label="Amount (ETB)", value=299)
-        pay_receipt = gr.File(label="Upload Receipt")
-        pay_status = gr.Textbox(label="Status")
-        gr.Button("Submit Payment").click(submit_payment,
-                                          [pay_name, pay_phone, pay_method, pay_amount, pay_receipt],
-                                          pay_status)
-
-    # --- Admin Panel ---
-    with gr.Tab("🔐 Admin"):
-        admin_pass_input = gr.Textbox(label="Admin Password", type="password")
-        admin_msg = gr.Textbox(label="Status")
-        admin_panel = gr.Column(visible=False)
-
-        gr.Button("Login").click(admin_login, admin_pass_input, [admin_panel, admin_msg])
-
-        with admin_panel:
-            pending_table = gr.Dataframe(headers=["ID", "User", "Amount", "Method", "Receipt"])
-            refresh_btn = gr.Button("Refresh Pending Payments")
-            refresh_btn.click(get_pending_payments, None, pending_table)
-
-            verify_id = gr.Number(label="Payment ID to Approve")
-            gr.Button("Verify Payment").click(verify_payment, verify_id, admin_msg)
-
-            # PDF Export
-            patient_name_pdf = gr.Textbox(label="Patient Name for PDF")
-            pdf_file_output = gr.File(label="Download PDF")
-            gr.Button("Export PDF").click(export_patient_notes, patient_name_pdf, pdf_file_output)
-
-            # Analytics Dashboard
-            analytics_plot = gr.Plot()
-            gr.Button("Show Analytics Dashboard").click(show_dashboard, None, analytics_plot)
-
-demo.launch()
+    prompt = f"""
+Generate a clinically accurate SOAP note.
+
+Subjective:
+{subjective}
+
+Objective:
+{objective}
+
+Assessment:
+{assessment}
+
+Plan:
+{plan}
+"""
+    return generate_text(prompt)
+
+
+def analyze_soap(note_text):
+    prompt = f"""
+Analyze this SOAP note and provide:
+
+• Clinical Quality Score (0–100)
+• Missing critical elements
+• Red flags
+• Suggested improvements
+• Differential diagnoses
+
+SOAP Note:
+{note_text}
+"""
+    return generate_text(prompt)
+
+
+# ---------------------------------------------------
+# 🎨 Gradio UI
+# ---------------------------------------------------
+
+with gr.Blocks(title="Selam Scribe 🩺 AI Medical Assistant") as app:
+
+    gr.Markdown("## 🩺 Selam Scribe — AI Clinical Assistant")
+
+    with gr.Tab("SOAP Generator"):
+        subj = gr.Textbox(label="Subjective", lines=3)
+        obj = gr.Textbox(label="Objective", lines=3)
+        assess = gr.Textbox(label="Assessment", lines=3)
+        plan = gr.Textbox(label="Plan", lines=3)
+
+        soap_out = gr.Textbox(label="Generated SOAP Note", lines=12)
+
+        gen_btn = gr.Button("Generate SOAP")
+        gen_btn.click(generate_soap, [subj, obj, assess, plan], soap_out)
+
+    with gr.Tab("SOAP Analysis"):
+        note_in = gr.Textbox(label="SOAP Note", lines=10)
+        analysis_out = gr.Textbox(label="AI Analysis", lines=12)
+
+        analyze_btn = gr.Button("Analyze SOAP")
+        analyze_btn.click(analyze_soap, note_in, analysis_out)
+
+    gr.Markdown("⚡ Powered by Groq (primary) with OpenAI fallback")
+
+# ---------------------------------------------------
+# 🚀 Launch App
+# ---------------------------------------------------
+
+if __name__ == "__main__":
+    app.launch(server_name="0.0.0.0", server_port=7860)