Update app.py

app.py

@@ -39,50 +39,50 @@ def get_active_llm_provider():
     return None
 
 
+# =============================
+# 🔐 AIML API Integration
+# =============================
+
 def get_llm_summary(prompt: str, context: str = "") -> str:
     """
-    Generate an expert summary using the available LLM.
-
-    Priority:
-    1) AI/ML API (OpenAI-compatible endpoint)
-       - Required secrets/env:
-         AI_ML_API_KEY (required)
-         AI_ML_API_BASE (optional, default https://api.openai.com/v1)
-         AI_ML_MODEL   (optional, default gpt-5)
-    2) Groq API (fallback)
-       - GROQ_API_KEY required
+    Generate an expert summary using the AIML API.
+    Uses the AIML_API_KEY secret and AIML API endpoint.
     """
-    provider = get_active_llm_provider()
     full_prompt = f"{context}\n\n{prompt}" if context else prompt
 
-    system_msg = {
-        "role": "system",
-        "content": (
-            "You are an expert seismologist, emergency response specialist, and public safety "
-            "advisor. Provide detailed, accurate, and actionable information."
-        ),
+    api_key = os.getenv("AIML_API_KEY")  # Hugging Face Spaces secret
+    if not api_key:
+        return (
+            "AI Analysis unavailable — AIML_API_KEY not configured.\n"
+            "Go to Settings → Secrets → Create secret 'AIML_API_KEY' with your AIML API key."
+        )
+
+    url = "https://api.aimlapi.com/v1/responses"
+    headers = {
+        "Content-Type": "application/json",
+        "Authorization": f"Bearer {api_key}"
+    }
+    payload = {
+        "model": "openai/gpt-5-2025-08-07",
+        "input": full_prompt
     }
 
-    if provider == "ai_ml":
-        try:
-            from openai import OpenAI  # OpenAI-compatible SDK
-            api_key = get_env_or_secret("AI_ML_API_KEY")
-            base_url = get_env_or_secret("AI_ML_API_BASE", "https://api.openai.com/v1")
-            model = get_env_or_secret("AI_ML_MODEL", "gpt-5")
+    try:
+        response = requests.post(url, headers=headers, json=payload, timeout=30)
+        if response.status_code == 200:
+            data = response.json()
+            # AIML API usually returns: data['output'] or data['responses'][0]['text']
+            if "output" in data:
+                return data["output"]
+            elif "responses" in data and len(data["responses"]) > 0:
+                return data["responses"][0].get("text", "No text returned")
+            else:
+                return "No valid response returned by AIML API."
+        else:
+            return f"AI Analysis Error (AIML API {response.status_code}): {response.text}"
+    except Exception as e:
+        return f"AI Analysis Request Failed: {e}"
 
-            client = OpenAI(api_key=api_key, base_url=base_url)
-            resp = client.chat.completions.create(
-                model=model,
-                messages=[system_msg, {"role": "user", "content": full_prompt}],
-                temperature=0.7,
-                top_p=0.9,
-                max_tokens=1200,
-                presence_penalty=0.1,
-                frequency_penalty=0.1,
-            )
-            return resp.choices[0].message.content
-        except Exception as e:
-            return f"AI Analysis Error (AI/ML API): {e}"
 
     elif provider == "groq":
         try: