Update utils.py

added fetch LLM models

src/utils/utils.py

@@ -106,6 +106,49 @@ def get_llm_model(provider: str, **kwargs):
     else:
         raise ValueError(f'Unsupported provider: {provider}')
 
+from openai import OpenAI, AzureOpenAI
+from google.generativeai import configure, list_models
+from langchain_anthropic import AnthropicLLM
+from langchain_ollama.llms import OllamaLLM
+
+def fetch_available_models(llm_provider: str, api_key: str = None, base_url: str = None) -> list[str]:
+    try:
+        if llm_provider == "anthropic":
+            client = AnthropicLLM(api_key=api_key)
+            # Handle model fetching appropriately for Anthropic
+            return ["claude-3-5-sonnet-20240620"]  # Replace with actual model fetching logic
+
+        elif llm_provider == "openai":
+            client = OpenAI(api_key=api_key, base_url=base_url)
+            models = client.models.list()
+            return [model.id for model in models.data]
+
+        elif llm_provider == "deepseek":
+            # For Deepseek, we'll return the default model for now
+            return ["deepseek-chat"]
+
+        elif llm_provider == "gemini":
+            configure(api_key=api_key)
+            models = list_models()
+            return [model.name for model in models]
+
+        elif llm_provider == "ollama":
+            client = OllamaLLM(model="default_model_name")  # Replace with the actual model name
+            models = client.models.list()
+            return [model.name for model in models]
+
+        elif llm_provider == "azure_openai":
+            client = AzureOpenAI(api_key=api_key, base_url=base_url)
+            models = client.models.list()
+            return [model.id for model in models.data]
+
+        else:
+            print(f"Unsupported LLM provider: {llm_provider}")
+            return []
+
+    except Exception as e:
+        print(f"Error fetching models from {llm_provider}: {e}")
+        return []
 
 def encode_image(img_path):
     if not img_path: