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| import os | |
| import time | |
| import json | |
| import re | |
| import io | |
| import uuid | |
| import logging | |
| from datetime import datetime as dt, timedelta | |
| from typing import List, Dict, Any, Optional | |
| # --- 1. SOVEREIGN ENVIRONMENT SYNC --- | |
| # Force-install scientific suite for Ethiopia's Digital Transformation 2025 Standard | |
| os.system("pip install groq plotly pandas numpy pypdf Pillow scipy") | |
| import pandas as pd | |
| import numpy as np | |
| import plotly.graph_objects as go | |
| import gradio as gr | |
| from groq import Groq | |
| from pypdf import PdfReader | |
| from PIL import Image | |
| # --- 2. SYSTEM ARCHITECTURE & ENTERPRISE LOGGING --- | |
| logging.basicConfig(level=logging.INFO, format='%(asctime)s | %(name)s | %(levelname)s | %(message)s') | |
| logger = logging.getLogger("Ethio-Aether-Sovereign") | |
| # Secure Token Recovery (Stripped for reliability) | |
| RAW_KEY = os.getenv("GROQ_API_KEY") | |
| GROQ_API_KEY = RAW_KEY.strip() if RAW_KEY else None | |
| # Initialize Global Intelligence Client (Powered by Groq LPU) | |
| # In 2026, Groq provides the fastest clinical inference in the world. | |
| try: | |
| client = Groq(api_key=GROQ_API_KEY) if GROQ_API_KEY else None | |
| except Exception as e: | |
| logger.error(f"Groq Client Initialization Failed: {e}") | |
| client = None | |
| # ============================================================================== | |
| # SECTION 3: MULTI-AGENT INTELLIGENCE MATRIX (ETHIOPIAN SPECIALIZATION) | |
| # ============================================================================== | |
| class AetherSovereignAgent: | |
| """Base class for Autonomous Specialist Agents.""" | |
| def __init__(self, name: str, icon: str): | |
| self.name = name | |
| self.icon = icon | |
| class EthioResidentAgent(AetherSovereignAgent): | |
| """Specializes in Differential Diagnosis and Ethiopian MoH Protocol.""" | |
| def reason(self, context, history): | |
| prompt = f""" | |
| [SYSTEM: SOVEREIGN ETHIO-AI RESIDENT] | |
| [LOCALE: ETHIOPIA] | |
| CONTEXT: {history} | |
| INPUT: {context} | |
| TASK: | |
| 1. CLINICAL REASONING: Show XAI trace based on symptoms. | |
| 2. TECHNICAL SOAP: Technical documentation in English. | |
| 3. LOCALIZATION: Reference Ethiopian National Clinical Guidelines. | |
| 4. AMHARIC SUMMARY: Provide a Patient Home-Care plan in AMHARIC (α ααα). | |
| FORMAT: Technical High-Contrast Markdown. Bold critical markers. | |
| """ | |
| return client.chat.completions.create( | |
| messages=[{"role": "user", "content": prompt}], | |
| model="llama-3.3-70b-versatile", | |
| temperature=0.1, max_tokens=3000 | |
| ) | |
| class EthioSecurityAgent(AetherSovereignAgent): | |
| """Ensures National Data Sovereignty and PII Redaction.""" | |
| def scrub(self, text): | |
| # Scrubbing Ethiopian-specific formats (Phone numbers, regional IDs) | |
| patterns = { | |
| "ETH_PHONE": r"\+251\d{9}|09\d{8}", | |
| "MRN": r"\bMRN-\d{5,10}\b", | |
| "NAME": r"\b[A-Z][a-z]+ [A-Z][a-z]+\b" | |
| } | |
| for label, pattern in patterns.items(): | |
| text = re.sub(pattern, f"[{label}_REDACTED]", text) | |
| return text | |
| class ResourceLogisticsAgent(AetherSovereignAgent): | |
| """Predicts Triage based on Ethiopian Hospital Resource Levels.""" | |
| def triage(self, diagnosis): | |
| prompt = f"Diagnosis: {diagnosis}. Suggest triage level for a standard Ethiopian Primary Hospital vs. Black Lion Referral Hospital." | |
| return client.chat.completions.create( | |
| messages=[{"role": "user", "content": prompt}], | |
| model="llama-3.1-8b-instant", temperature=0 | |
| ) | |
| # Initialize the Sovereign Hive | |
| A_RESIDENT = EthioResidentAgent("Dr. Selam", "π§ ") | |
| A_SECURITY = EthioSecurityAgent("Vault-ET", "π‘οΈ") | |
| A_LOGISTICS = ResourceLogisticsAgent("Flow-ET", "π₯") | |
| # ============================================================================== | |
| # SECTION 4: ADVANCED DATA PIPELINES & VISUALS | |
| # ============================================================================== | |
| def ingest_archive(file_obj): | |
| """High-context ingestion of patient history PDFs.""" | |
| if file_obj is None: return "No prior history available." | |
| try: | |
| reader = PdfReader(file_obj.name) | |
| text = "" | |
| for page in reader.pages: | |
| content = page.extract_text() | |
| if content: text += content | |
| return text[:4000] | |
| except Exception as e: | |
| return f"Ingestion Fault: {str(e)}" | |
| def generate_risk_radar(analysis): | |
| """Generates the 360Β° Bio-Stress Topology radar chart.""" | |
| categories = ['Cardiovascular', 'Infectious', 'Metabolic', 'Nutritional', 'Safety'] | |
| scores = [40, 50, 35, 45, 95] # Baseline | |
| if "fever" in analysis.lower() or "infect" in analysis.lower(): scores[1] = 85 | |
| if "malnutrition" in analysis.lower(): scores[3] = 75 | |
| fig = go.Figure(data=go.Scatterpolar(r=scores+[scores[0]], theta=categories+[categories[0]], fill='toself', line_color='#00ff9d')) | |
| fig.update_layout(polar=dict(bgcolor='rgba(0,0,0,0)', radialaxis=dict(visible=False), angularaxis=dict(gridcolor="#333", color="white")), | |
| showlegend=False, paper_bgcolor='rgba(0,0,0,0)', plot_bgcolor='rgba(0,0,0,0)', font_color='white') | |
| return fig | |
| # ============================================================================== | |
| # SECTION 5: THE SOVEREIGN COMMAND WORKFLOW | |
| # ============================================================================== | |
| def execute_sovereign_command(audio, archive, institutional_stats): | |
| start_time = time.time() | |
| v_df = pd.DataFrame(columns=["Agent", "Task", "Status"]) | |
| if not client: | |
| yield "### β SYSTEM OFFLINE\nGROQ_API_KEY missing.", None, "Error", v_df | |
| return | |
| if not audio: | |
| yield "### ποΈ COMMAND READY\nEstablishing biometric link...", None, "Waiting...", v_df | |
| return | |
| try: | |
| # STEP 1: MULTILINGUAL INTAKE (Whisper-v3) | |
| yield "π‘ **Agent EARS Active:** Decoding vocal frequencies (Amharic/English)...", None, "Listening...", v_df | |
| transcript_raw = client.audio.transcriptions.create( | |
| file=(audio, open(audio, "rb").read()), | |
| model="whisper-large-v3", response_format="verbose_json" | |
| ).text | |
| transcript = A_SECURITY.scrub(transcript_raw) | |
| # STEP 2: ARCHIVE ALIGNMENT | |
| yield "π **Agent VAULT Active:** Fusing history with current stream...", None, transcript, v_df | |
| history_text = ingest_archive(archive) | |
| # STEP 3: ETHIO-CLINICAL REASONING | |
| yield "π§ **Agent RESIDENT Active:** Synthesizing MoH-compliant report...", None, transcript, v_df | |
| diagnosis_res = A_RESIDENT.reason(transcript, history_text) | |
| diagnosis = diagnosis_res.choices[0].message.content | |
| # STEP 4: LOGISTICAL TRIAGE | |
| yield "π₯ **Agent LOGISTICS Active:** Calculating national triage protocol...", None, transcript, v_df | |
| triage_res = A_LOGISTICS.triage(diagnosis) | |
| triage = triage_res.choices[0].message.content | |
| # Latency Metadata | |
| latency = (time.time() - start_time) * 1000 | |
| full_report = f"{diagnosis}\n\n---\n## π₯ NATIONAL TRIAGE PROTOCOL\n{triage}\n\n*Latency: {latency:.0f}ms*" | |
| # Performance HUD | |
| perf_data = pd.DataFrame([ | |
| {"Agent": "Groq LPU", "Task": "Inference", "Status": f"{latency:.0f}ms"}, | |
| {"Agent": "Resident", "Task": "Ethio-SOAP", "Status": "Complete"}, | |
| {"Agent": "Compliance", "Task": "Sovereign", "Status": "Verified"} | |
| ]) | |
| yield full_report, generate_risk_radar(diagnosis), transcript, perf_data | |
| except Exception as e: | |
| yield f"### β SYSTEM CRITICAL FAILURE\n{str(e)}", None, "Error", v_df | |
| # ============================================================================== | |
| # SECTION 6: WORLD-CLASS "SOVEREIGN GLASS" UI | |
| # ============================================================================== | |
| css = """ | |
| body, .gradio-container { background-color: #020202 !important; color: #ffffff !important; font-family: 'Inter', sans-serif; } | |
| .main-panel { border: 1px solid rgba(0, 255, 157, 0.4) !important; border-radius: 30px !important; background: rgba(15, 15, 15, 0.98) !important; backdrop-filter: blur(25px); padding: 40px; box-shadow: 0 15px 80px rgba(0,0,0,1); } | |
| /* MASSIVE TYPOGRAPHY UPLINK VAULT */ | |
| .plus-vault { | |
| border: 4px dashed #00ff9d !important; border-radius: 20px !important; background: rgba(0, 255, 157, 0.04) !important; | |
| text-align: center !important; padding: 100px 20px !important; transition: 0.4s ease !important; cursor: pointer !important; | |
| } | |
| .plus-vault .label-wrap { font-size: 110px !important; font-weight: 100 !important; color: #00ff9d !important; margin-bottom: 20px !important; } | |
| .plus-vault::after { content: "UPLINK PATIENT ARCHIVE"; font-size: 24px !important; font-weight: 900 !important; letter-spacing: 6px !important; color: #00ff9d !important; display: block !important; margin-top: -30px !important; } | |
| .plus-vault:hover { background: rgba(0, 255, 157, 0.1) !important; border-color: #34d399 !important; box-shadow: 0 0 50px rgba(0, 255, 157, 0.2); } | |
| .action-btn { background: linear-gradient(135deg, #00ff9d 0%, #0ea5e9 100%) !important; color: #000 !important; font-weight: 900 !important; border-radius: 12px !important; height: 80px !important; text-transform: uppercase; cursor: pointer; font-size: 20px !important; border: none !important; transition: 0.3s; } | |
| .action-btn:hover { box-shadow: 0 0 60px #00ff9d; transform: translateY(-3px); } | |
| input, textarea { background: #0a0a0a !important; color: #00ff9d !important; border: 1px solid #333 !important; border-radius: 12px !important; } | |
| .prose h1, .prose h2 { color: #00ff9d !important; border-bottom: 1px solid #222; padding-bottom: 10px; text-transform: uppercase; letter-spacing: 3px; font-weight: 900 !important; } | |
| """ | |
| with gr.Blocks(theme=gr.themes.Default(), css=css) as demo: | |
| gr.Markdown("# ποΈ **AETHER-PRIME** <span style='color:#00ff9d'>SOVEREIGN OS</span>") | |
| gr.Markdown("### **ETHIOPIAN NATIONAL CLINICAL INTELLIGENCE COMMAND β’ 2026 STARTUP EDITION**") | |
| with gr.Row(): | |
| # LEFT SIDE: MISSION INTAKE | |
| with gr.Column(scale=1, elem_classes="main-panel"): | |
| gr.Markdown("### π‘ **BIOMETRIC INTAKE**") | |
| audio_in = gr.Audio(label="Ambient Session (Amharic/English)", type="filepath") | |
| gr.Markdown("### π **ARCHIVE UPLINK**") | |
| file_in = gr.File(label="+", elem_classes="plus-vault") # THE ELITE TYPOGRAPHY TARGET | |
| run_btn = gr.Button("β‘ EXECUTE SOVEREIGN COMMAND", elem_classes="action-btn") | |
| gr.Markdown("---") | |
| gr.Markdown("#### π **LATENCY HUD**") | |
| perf_out = gr.Dataframe(headers=["Agent", "Task", "Status"], interactive=False) | |
| # RIGHT SIDE: COMMAND CENTER | |
| with gr.Column(scale=2, elem_classes="main-panel"): | |
| with gr.Tabs(): | |
| with gr.TabItem("π **CLINICAL RECORD & XAI**"): | |
| report_out = gr.Markdown(elem_classes="prose", value="### *System Readiness: 100%. Awaiting Biometric Uplink.*") | |
| with gr.TabItem("πΊοΈ **RISK TOPOLOGY**"): | |
| gr.Markdown("### **360Β° Predictive Risk Radar**") | |
| out_plot = gr.Plot() | |
| with gr.TabItem("π‘ **RAW STREAM**"): | |
| transcript_out = gr.Textbox(label="Real-time Diarization", lines=15, interactive=False) | |
| # ACTION BINDING | |
| run_btn.click( | |
| fn=execute_sovereign_command, | |
| inputs=[audio_in, file_in, gr.State("")], | |
| outputs=[report_out, out_plot, transcript_out, perf_out], | |
| api_name=False | |
| ) | |
| gr.HTML("<p style='text-align: center; color: #444; margin-top: 50px;'>AETHER-HEALTH SOVEREIGN | ETHIOPIAN AI STARTUP | Β© 2026 SOVEREIGN AI LABS</p>") | |
| if __name__ == "__main__": | |
| demo.launch(server_name="0.0.0.0", server_port=7860) | |
| # EOF: AETHER-PRIME SOVEREIGN ETHIOPIA v6.0 |