Update parser_logic.py

parser_logic.py

@@ -16,7 +16,7 @@ api_key = os.getenv("GEMINI_API_KEY")
 if not api_key:
     raise ValueError("GEMINI_API_KEY is missing.")
 
-# Configure the SDK
+# Configure SDK
 genai.configure(api_key=api_key)
 
 def extract_text_from_stream(file_bytes: bytes) -> str:
@@ -31,39 +31,40 @@ def extract_text_from_stream(file_bytes: bytes) -> str:
     return text
 
 def parse_resume_with_ai(resume_text: str) -> dict:
+    
+    # DIAGNOSTIC STEP: Check what models are actually available
+    available_models = []
+    try:
+        for m in genai.list_models():
+            if 'generateContent' in m.supported_generation_methods:
+                available_models.append(m.name)
+        logger.info(f"AVAILABLE MODELS: {available_models}")
+    except Exception as e:
+        logger.error(f"Could not list models: {e}")
+        return {"error": f"API Key Authentication Failed completely. Google says: {str(e)}"}
+
+    # If the list is empty, the Key is invalid or has no permissions
+    if not available_models:
+        return {"error": "CRITICAL: The API Key is valid, but Google returned 0 available models. Check your Google AI Studio account."}
+
+    # Pick the first working model found
+    model_name = "models/gemini-1.5-flash"
+    if model_name not in available_models:
+        # Fallback to whatever is actually there
+        model_name = available_models[0]
+    
     prompt = """
     Extract the following information as strictly valid JSON:
-    {
-        "name": "Full Name",
-        "email": "email@example.com",
-        "phone": "123-456-7890",
-        "skills": ["skill1", "skill2"],
-        "summary": "Brief summary"
-    }
-    If information is missing, use null.
+    { "name": "...", "email": "...", "phone": "...", "skills": [], "summary": "..." }
     """ 
     
-    # LIST OF MODELS TO TRY (In order)
-    # 1. Flash: Best balance of speed/cost
-    # 2. Pro: Older, but GUARANTEED to work on v1beta
-    models_to_try = ['gemini-1.5-flash', 'gemini-pro']
-    
-    for model_name in models_to_try:
-        try:
-            logger.info(f"Attempting to use model: {model_name}")
-            model = genai.GenerativeModel(model_name)
-            
-            response = model.generate_content(prompt + "\n\nResume Text:\n" + resume_text[:10000])
-            
-            # Clean and Parse
-            raw_text = response.text.strip()
-            clean_json = re.sub(r'```json\s*|```', '', raw_text, flags=re.MULTILINE).strip()
-            return json.loads(clean_json)
-            
-        except Exception as e:
-            logger.warning(f"Model {model_name} failed with error: {e}")
-            # If this was the last model in the list, raise the error
-            if model_name == models_to_try[-1]:
-                return {"error": f"All models failed. Last error: {str(e)}"}
-            # Otherwise, loop continues to the next model (gemini-pro)
-            continue
+    try:
+        model = genai.GenerativeModel(model_name)
+        response = model.generate_content(prompt + "\n\nResume Text:\n" + resume_text[:10000])
+        
+        raw_text = response.text.strip()
+        clean_json = re.sub(r'```json\s*|```', '', raw_text, flags=re.MULTILINE).strip()
+        return json.loads(clean_json)
+        
+    except Exception as e:
+        return {"error": f"Used model {model_name} but failed: {str(e)}"}