Update app.py

app.py

@@ -23,14 +23,9 @@ print("Phoebus 3.1 Flash ready!", flush=True)
 # ---------------------------------------------------------
 
 def query_emem_facts(location_query: str) -> dict:
-    """
-    Queries Vortx-AI / emem spatial observation protocol for signed facts.
-    Falls back to a standard meteorological/air-quality telemetry mock
-    if the external remote MCP host is unreachable.
-    """
     clean_loc = re.sub(r"@emem", "", location_query, flags=re.IGNORECASE).strip()
     
-    # 1. Geocode the location name to lat/lon bounding coordinates
+    # Geocode location name to coordinates
     lat, lon, display_name = None, None, clean_loc
     try:
         geo_url = f"https://nominatim.openstreetmap.org/search?format=json&q={requests.utils.quote(clean_loc)}"
@@ -44,18 +39,12 @@ def query_emem_facts(location_query: str) -> dict:
     except Exception as e:
         print(f"Geocode lookup failed: {e}", flush=True)
 
-    # Fallback to default coordinates for Bengaluru if lookup times out
+    # Fallback to default coordinates for Bengaluru if lookup fails
     if lat is None or lon is None:
         lat, lon, display_name = 12.9716, 77.5946, "Bengaluru"
 
-    # Compute a deterministic cell64 token based on spatial coords
-    coord_bytes = f"{lat:.4f}:{lon:.4f}".encode("utf-8")
-    cell64_id = f"emem:fact:cell64_{base64.b64encode(coord_bytes).decode('utf-8')[:12]}"
-
-    # 2. Fetch live atmospheric and environmental observation data
     telemetry = {
         "location": display_name,
-        "cell_id": cell64_id,
         "temperature": "24.5°C",
         "cloud_cover": "72%",
         "wind": "4.2 m/s",
@@ -67,7 +56,6 @@ def query_emem_facts(location_query: str) -> dict:
     }
 
     try:
-        # Fetch real-time open satellite & atmospheric feeds
         wx_url = f"https://api.open-meteo.com/v1/forecast?latitude={lat}&longitude={lon}&current=temperature_2m,relative_humidity_2m,cloud_cover,wind_speed_10m,precipitation"
         res = requests.get(wx_url, timeout=4)
         if res.status_code == 200:
@@ -118,15 +106,15 @@ def phoebus_respond(message, history, enable_tinyfish, enable_emem):
         "CRITICAL IDENTITY: You are Phoebus 3.1 Flash, an ultra-fast reasoning model developed exclusively by CloverAIStudios (atclovr.dev).",
         "You are NOT Claude, you are NOT created by Anthropic, and you are NOT ChatGPT.",
         "Always answer inquiries thoroughly, accurately, and directly with a clear summary.",
-        "You specialize in deep space telemetry, geography, urban infrastructure, and coding."
+        "You specialize in deep space telemetry, geography, urban infrastructure, and coding.",
+        "PRIVACY DIRECTIVE: Never output internal coordinate cell IDs, cell hashes, or database keys to the user."
     ]
 
-    # If @emem or spatial telemetry is invoked, execute lookup before prompting
-    emem_data = None
+    # Resolve emem facts internally for the model to use
     if should_run_emem or ("condition" in clean_question.lower() and "in " in clean_question.lower()):
         emem_data = query_emem_facts(clean_question)
         system_rules.append(
-            f"\n[GROUNDED EMEM OBSERVATION DATA FOR {emem_data['location']} ({emem_data['cell_id']})]:\n"
+            f"\n[INTERNAL EMEM OBSERVATION DATA FOR {emem_data['location']}]:\n"
             f"- Temperature: {emem_data['temperature']}\n"
             f"- Cloud cover: {emem_data['cloud_cover']}\n"
             f"- Wind: {emem_data['wind']}\n"
@@ -135,12 +123,12 @@ def phoebus_respond(message, history, enable_tinyfish, enable_emem):
             f"- PM2.5: {emem_data['pm25']}\n"
             f"- Heat-health risk: {emem_data['heat_health_risk']}\n"
             f"- Flood signal: {emem_data['flood_signal']}\n"
-            f"INSTRUCTION: Synthesize this exact Earth-observation telemetry into your answer, formatting the metrics as clear bullet points."
+            f"INSTRUCTION: Synthesize this Earth-observation telemetry into your answer using clean bullet points. Do not mention internal cell identifiers."
         )
 
     if should_cite_tinyfish:
         system_rules.append(
-            f"[TinyFish Telemetry]: Live web telemetry protocol active and synchronized."
+            "[TinyFish Telemetry]: Live web telemetry protocol active and synchronized."
         )
 
     formatted_system_prompt = " ".join(system_rules)
@@ -179,13 +167,10 @@ def phoebus_respond(message, history, enable_tinyfish, enable_emem):
     raw_reply = tokenizer.decode(outputs[0][inputs.input_ids.shape[1]:], skip_special_tokens=True)
     clean_reply = sanitize_identity(raw_reply)
 
-    # Attach spatial verification tag
-    if emem_data:
-        final_reply = f"{clean_reply.strip()}\n\n[{emem_data['cell_id']}]"
-    else:
-        final_reply = clean_reply
+    # Strip any accidental cell ID leakage from generation output
+    clean_reply = re.sub(r"\[?emem:fact:cell64_[A-Za-z0-9+/=]+\]?", "", clean_reply).strip()
 
-    return final_reply
+    return clean_reply
 
 with gr.Blocks(theme=gr.themes.Soft(primary_hue="purple")) as demo:
     gr.Markdown("# ⚡ Phoebus 3.1 Flash Console\n*Ultra-fast reasoning model by CloverAIStudios (atclovr.dev)*")