Update app.py

app.py

@@ -15,7 +15,9 @@ OPENAI_MODEL_NAME = "gpt-4o-mini"
 # 2. Google Gemini Configuration (Direct Google API)
 # You need to set GOOGLE_API_KEY in your HF Space secrets
 GOOGLE_API_KEY = os.environ.get("GOOGLE_API_KEY", "") 
-# Using the Gemini 1.5 Flash model for speed/cost effectiveness
+
+# CORRECTED: The model name is gemma-2-27b-it (Gemma 2), not gemma-3.
+# NOTE: While this uses the "Gemini" API endpoint, it calls the Gemma 2 open model.
 GEMINI_API_URL = f"https://generativelanguage.googleapis.com/v1beta/models/gemma-3-27b-it:generateContent?key={GOOGLE_API_KEY}"
 
 app = FastAPI(
@@ -26,7 +28,7 @@ app = FastAPI(
 # --- MODELS ---
 class AnalyzeRequest(BaseModel):
     filename: str
-    model_provider: str = "openai" # 'openai' or 'gemma' (maps to Gemini)
+    model_provider: str = "openai" # 'openai' or 'gemma'
 
 # --- HELPERS ---
 def get_headers(token):
@@ -130,10 +132,11 @@ def call_google_gemini(filename):
         "generationConfig": {
             "temperature": 0.1,
             "maxOutputTokens": 100,
-            "responseMimeType": "application/json" # Gemini supports JSON mode natively
+            "responseMimeType": "application/json" # Hints the model to output JSON
         }
     }
 
+    # Note: The URL here uses the global GEMINI_API_URL defined at the top
     response = requests.post(GEMINI_API_URL, headers={"Content-Type": "application/json"}, json=payload, timeout=30)
     
     if response.status_code != 200:
@@ -165,6 +168,7 @@ def analyze_filename(request: AnalyzeRequest):
 
         # Parse JSON output from either provider
         if raw_content:
+            # Clean up markdown code blocks if the model includes them
             clean_content = raw_content.replace("```json", "").replace("```", "").strip()
             return json.loads(clean_content)