LiteLLM Minor Fixes & Improvements (10/05/2024) (#6083)

* docs(prompt_caching.md): add prompt caching cost calc example to docs

* docs(prompt_caching.md): add proxy examples to docs

* feat(utils.py): expose new helper `supports_prompt_caching()` to check if a model supports prompt caching

* docs(prompt_caching.md): add docs on checking model support for prompt caching

* build: fix invalid json

litellm/utils.py

@@ -2179,6 +2179,40 @@ def supports_function_calling(
         )
 
 
+def supports_prompt_caching(
+    model: str, custom_llm_provider: Optional[str] = None
+) -> bool:
+    """
+    Check if the given model supports prompt caching and return a boolean value.
+
+    Parameters:
+    model (str): The model name to be checked.
+    custom_llm_provider (Optional[str]): The provider to be checked.
+
+    Returns:
+    bool: True if the model supports prompt caching, False otherwise.
+
+    Raises:
+    Exception: If the given model is not found or there's an error in retrieval.
+    """
+    try:
+        model, custom_llm_provider, _, _ = litellm.get_llm_provider(
+            model=model, custom_llm_provider=custom_llm_provider
+        )
+
+        model_info = litellm.get_model_info(
+            model=model, custom_llm_provider=custom_llm_provider
+        )
+
+        if model_info.get("supports_prompt_caching", False) is True:
+            return True
+        return False
+    except Exception as e:
+        raise Exception(
+            f"Model not found or error in checking prompt caching support. You passed model={model}, custom_llm_provider={custom_llm_provider}. Error: {str(e)}"
+        )
+
+
 def supports_vision(model: str, custom_llm_provider: Optional[str] = None) -> bool:
     """
     Check if the given model supports vision and return a boolean value.