Update parser_logic.py

parser_logic.py

@@ -12,12 +12,11 @@ logger = logging.getLogger(__name__)
 
 load_dotenv()
 
-# Secure Configuration
 api_key = os.getenv("GEMINI_API_KEY")
 if not api_key:
     raise ValueError("GEMINI_API_KEY is missing.")
 
-# Configure the STABLE SDK
+# Configure the SDK
 genai.configure(api_key=api_key)
 
 def extract_text_from_stream(file_bytes: bytes) -> str:
@@ -33,30 +32,38 @@ def extract_text_from_stream(file_bytes: bytes) -> str:
 
 def parse_resume_with_ai(resume_text: str) -> dict:
     prompt = """
-    You are an expert resume parser. Extract the following information as strictly valid JSON:
+    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 of the candidate."
+        "summary": "Brief summary"
     }
-    If information is missing, use null. Do not add Markdown formatting (like ```json).
+    If information is missing, use null.
     """ 
     
-    # We use 'gemini-1.5-flash' which is fully supported in the latest standard SDK
-    model = genai.GenerativeModel('gemini-1.5-flash')
+    # 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']
     
-    try:
-        response = model.generate_content(prompt + "\n\nResume Text:\n" + resume_text[:10000])
-        
-        # Cleaning: Remove markdown if the model adds it despite instructions
-        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.error(f"AI Processing Error: {e}")
-        # Detailed error for debugging
-        return {"error": f"AI Error: {str(e)}"}
+    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