Update src/llm_client.py

src/llm_client.py

@@ -1,5 +1,44 @@
 import requests
 import os
+import requests
+import google.generativeai as genai
+from .prompts import get_system_prompt
+
+def ask_llm(query, context, mode="Executive Summary", model_provider="Gemini"):
+    """
+    Switchable Brain: Defaults to Gemini (Powerful), falls back to Granite (Private).
+    """
+    
+    # 1. Get the Persona/Prompt from our new library
+    system_instruction = get_system_prompt(mode)
+    
+    # --- OPTION A: GOOGLE GEMINI (The "Big Gun") ---
+    if model_provider == "Gemini":
+        try:
+            # RETRIEVE SECRET AT RUNTIME
+            # In HF Spaces, this pulls directly from the "Secrets" tab
+            google_key = os.environ.get("GOOGLE_API_KEY")
+            
+            if not google_key:
+                return "Error: GOOGLE_API_KEY not found in Secrets. Please add it in Settings > Secrets."
+            
+            # Configure specifically for this request (safe and stateless)
+            genai.configure(api_key=google_key)
+            
+            # Use 'gemini-1.5-flash' for speed/cost, or 'gemini-1.5-pro' for complex reasoning
+            model = genai.GenerativeModel(
+                model_name='gemini-1.5-flash',
+                system_instruction=system_instruction
+            )
+            
+            # Gemini has a massive context window (1M+ tokens), so we can be generous
+            full_prompt = f"USER QUERY: {query}\n\nDOCUMENT CONTEXT:\n{context[:30000]}"
+            
+            response = model.generate_content(full_prompt)
+            return response.text
+            
+        except Exception as e:
+            return f"Gemini Error: {str(e)}"
 
 def ask_granite(query, context):
     """