Update LLM analysis

llm_analysis.py

@@ -9,16 +9,71 @@ and provide comprehensive soil and crop insights.
 import os
 import json
 import numpy as np
-import google.generativeai as genai
-from typing import Dict, Any
+import requests
+from typing import Dict, Any, List, Optional
 
-def configure_gemini():
-    """Configure Gemini API with key from environment."""
-    api_key = os.environ.get("GEMINI_API_KEY")
-    if not api_key:
-        raise ValueError("GEMINI_API_KEY not found in environment variables")
-    genai.configure(api_key=api_key, transport='rest')
-    return genai.GenerativeModel('gemini-flash-latest')
+# ============================================================================
+# GEMINI MULTI-KEY FALLBACK SYSTEM
+# ============================================================================
+
+def load_gemini_api_keys() -> List[str]:
+    """Load all available Gemini API keys from environment."""
+    keys = []
+    primary = os.environ.get("GEMINI_API_KEY")
+    if primary:
+        keys.append(primary)
+    for i in range(1, 6):
+        key = os.environ.get(f"GEMINI_API_KEY_{i}")
+        if key and key not in keys:
+            keys.append(key)
+    return keys
+
+GEMINI_API_KEYS = load_gemini_api_keys()
+_current_key_index = 0
+GEMINI_URL = "https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:generateContent"
+
+def _get_next_key() -> Optional[str]:
+    global _current_key_index
+    if not GEMINI_API_KEYS:
+        return None
+    _current_key_index = (_current_key_index + 1) % len(GEMINI_API_KEYS)
+    return GEMINI_API_KEYS[_current_key_index]
+
+def call_gemini_with_fallback(prompt: str) -> str:
+    global _current_key_index
+    if not GEMINI_API_KEYS:
+        raise ValueError("No GEMINI_API_KEY configured")
+    max_retries_per_key = 2
+    keys_tried = 0
+    while keys_tried < len(GEMINI_API_KEYS):
+        current_key = GEMINI_API_KEYS[_current_key_index]
+        url = f"{GEMINI_URL}?key={current_key}"
+        for attempt in range(max_retries_per_key):
+            try:
+                response = requests.post(
+                    url,
+                    headers={"Content-Type": "application/json"},
+                    json={"contents": [{"parts": [{"text": prompt}]}],
+                          "generationConfig": {"temperature": 0.7, "maxOutputTokens": 4096}},
+                    timeout=120
+                )
+                if response.status_code == 200:
+                    data = response.json()
+                    if "candidates" in data and len(data["candidates"]) > 0:
+                        return data["candidates"][0]["content"]["parts"][0]["text"]
+                    raise ValueError("No response from Gemini")
+                elif response.status_code in [429, 403, 500, 502, 503]:
+                    _get_next_key()
+                    keys_tried += 1
+                    break
+                else:
+                    raise ValueError(f"Gemini API error: {response.status_code}")
+            except requests.exceptions.RequestException:
+                if attempt == max_retries_per_key - 1:
+                    _get_next_key()
+                    keys_tried += 1
+                continue
+    raise ValueError("All API keys exhausted")
 
 def prepare_indices_context(summary_report: Dict, crop_type: str, farmer_context: Dict, 
                            temporal_stats: Dict = None) -> str:
@@ -165,8 +220,6 @@ def analyze_with_llm(summary_report: Dict, crop_type: str, farmer_context: Dict,
     Returns:
         Dictionary with structured LLM analysis results
     """
-    model = configure_gemini()
-    
     # Prepare context with temporal statistics
     indices_context = prepare_indices_context(summary_report, crop_type, farmer_context, temporal_stats)
     
@@ -250,9 +303,8 @@ IMPORTANT GUIDELINES:
 Return ONLY the JSON object, no additional text.
 """
     
-    # Get LLM response
-    response = model.generate_content(prompt)
-    response_text = response.text.strip()
+    # Get LLM response using fallback system
+    response_text = call_gemini_with_fallback(prompt).strip()
     
     # Remove markdown code blocks if present
     if response_text.startswith("```"):