Add normalize_model_name() to litellm backend

- Add method to normalize model names for litellm
- Maps common model patterns to providers (gpt-* -> openai/, llama -> meta/, etc.)
- Falls back to openai/ for unknown models

codai/openai/litellm.py

@@ -84,6 +84,68 @@ class LiteLLMBackend:
             litellm.base_url = base_url
         if api_key:
             litellm.api_key = api_key
+    
+    def normalize_model_name(self, model: str) -> str:
+        """
+        Normalize model name for litellm.
+        
+        LiteLLM requires model names in format "provider/model" e.g., "openai/gpt-3.5-turbo".
+        If no provider is specified, add a default provider based on common patterns.
+        
+        Args:
+            model: Original model name
+            
+        Returns:
+            Normalized model name with provider prefix
+        """
+        # If already has a provider prefix (contains /), return as-is
+        if '/' in model:
+            return model
+        
+        # Common model name patterns and their providers
+        provider_map = {
+            # OpenAI models
+            'gpt-': 'openai/',
+            'gpt3': 'openai/',
+            'gpt4': 'openai/',
+            # Anthropic models
+            'claude': 'anthropic/',
+            # Google models
+            'gemini': 'gemini/',
+            'palm': 'gemini/',
+            # Meta/Llama models
+            'llama': 'meta/',
+            'llama2': 'meta/',
+            'llama3': 'meta/',
+            'mistral': 'mistral/',
+            # Mistral models
+            # AWS models
+            'amazon': 'bedrock/',
+            # Azure models
+            'azure': 'azure/',
+            # Cohere models
+            'cohere': 'cohere/',
+            # AI21 models
+            'ai21': 'ai21/',
+            # Local/Ollama models
+            'ollama': 'ollama/',
+            # HuggingFace models
+            'hf': 'huggingface/',
+            # DeepSeek models
+            'deepseek': 'deepseek/',
+            # Qwen models
+            'qwen': 'qwen/',
+        }
+        
+        model_lower = model.lower()
+        
+        # Check for known patterns
+        for pattern, provider in provider_map.items():
+            if model_lower.startswith(pattern):
+                return f"{provider}{model}"
+        
+        # Default: assume OpenAI-compatible local model
+        return f"openai/{model}"
             
     def _convert_messages(self, messages: List[Dict]) -> List[Dict]:
         """Convert OpenAI message format to litellm format."""
@@ -243,8 +305,8 @@ class LiteLLMBackend:
         if not LITELLM_AVAILABLE:
             raise RuntimeError("litellm is not installed. Run: pip install litellm")
         
-        # Prepare the model
-        use_model = model or self.model
+        # Prepare the model - normalize name for litellm
+        use_model = self.normalize_model_name(model or self.model)
         
         # Convert messages to litellm format
         litellm_messages = self._convert_messages(messages)