feat: migrate from Gemini to Groq API for LLM calls

app.py

@@ -24,7 +24,7 @@ from fastapi.middleware.cors import CORSMiddleware
 from fastapi.responses import StreamingResponse
 from pydantic import BaseModel
 import asyncio
-import google.generativeai as genai
+from groq import Groq
 
 from supabase_client import SupabaseClient
 from prompts import PERSONA_DEFINITIONS, EXPERIENCE_MAP, TECH_COMFORT_MAP, INNOVATION_MAP, FARMING_GOAL_MAP
@@ -50,16 +50,17 @@ SAR_API_URL = os.getenv("SAR_API_URL", "https://aniket2006-agrow-backend-v2.hf.s
 SENTINEL2_API_URL = os.getenv("SENTINEL2_API_URL", "https://aniket2006-agrow-sentinel2.hf.space")
 
 # ============================================================================
-# GEMINI SETUP
+# GROQ SETUP
 # ============================================================================
-GEMINI_API_KEY = os.environ.get("GEMINI_API_KEY")
-if GEMINI_API_KEY:
-    genai.configure(api_key=GEMINI_API_KEY)
-    model = genai.GenerativeModel('gemini-2.5-flash')
-    logger.info("Gemini API configured successfully")
+GROQ_API_KEY = os.environ.get("GROQ_API_KEY", "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")
+GROQ_MODEL = "llama-3.3-70b-versatile"
+
+if GROQ_API_KEY:
+    groq_client = Groq(api_key=GROQ_API_KEY)
+    logger.info(f"Groq API configured with model {GROQ_MODEL}")
 else:
-    model = None
-    logger.warning("GEMINI_API_KEY not set - chatbot will return mock responses")
+    groq_client = None
+    logger.warning("GROQ_API_KEY not set - chatbot will return mock responses")
 
 # Supabase
 supabase = SupabaseClient()
@@ -504,24 +505,32 @@ def generate_response(user_message: str, history: List[Dict], context: Dict) ->
     history = history or []
     context_used = context.get("data_sources", [])
     
-    if model is None:
-        return "Please configure GEMINI_API_KEY for real responses.", []
+    if groq_client is None:
+        return "Please configure GROQ_API_KEY for real responses.", []
     
     try:
         prompt = build_llm_prompt(user_message, context, history)
         
-        response = model.generate_content(
-            prompt,
-            generation_config=genai.types.GenerationConfig(
-                temperature=0.7,
-                max_output_tokens=4096,
-            )
+        chat_completion = groq_client.chat.completions.create(
+            messages=[
+                {
+                    "role": "system",
+                    "content": "You are AGROW AI, an expert agricultural advisor. Provide helpful, data-driven advice."
+                },
+                {
+                    "role": "user",
+                    "content": prompt
+                }
+            ],
+            model=GROQ_MODEL,
+            temperature=0.7,
+            max_tokens=4096,
         )
         
-        return response.text, context_used
+        return chat_completion.choices[0].message.content, context_used
         
     except Exception as e:
-        logger.error(f"Gemini error: {e}")
+        logger.error(f"Groq error: {e}")
         traceback.print_exc()
         return f"I apologize, but I encountered an error: {str(e)}", []
 
@@ -539,7 +548,7 @@ async def root():
 
 @app.get("/health")
 async def health():
-    return {"status": "healthy", "gemini_configured": model is not None}
+    return {"status": "healthy", "groq_configured": groq_client is not None}
 
 
 @app.post("/session/new", response_model=SessionResponse)

requirements.txt

@@ -4,4 +4,4 @@ pydantic==2.5.2
 requests>=2.28.0
 supabase>=2.0.0
 python-dotenv==1.0.0
-google-generativeai>=0.3.0
+groq>=0.4.0