fix(anthropic.py): handle whitespace characters for anthropic calls

litellm/llms/anthropic.py

@@ -101,13 +101,13 @@ class AnthropicConfig:
                 optional_params["max_tokens"] = value
             if param == "tools":
                 optional_params["tools"] = value
-            if param == "stream":
+            if param == "stream" and value == True:
                 optional_params["stream"] = value
             if param == "stop":
                 if isinstance(value, str):
                     if (
                         value == "\n"
-                    ):  # anthropic doesn't allow whitespace characters as stop-sequences
+                    ) and litellm.drop_params == True:  # anthropic doesn't allow whitespace characters as stop-sequences
                         continue
                     value = [value]
                 elif isinstance(value, list):
@@ -115,10 +115,13 @@ class AnthropicConfig:
                     for v in value:
                         if (
                             v == "\n"
-                        ):  # anthropic doesn't allow whitespace characters as stop-sequences
+                        ) and litellm.drop_params == True:  # anthropic doesn't allow whitespace characters as stop-sequences
                             continue
                         new_v.append(v)
-                    value = new_v
+                    if len(new_v) > 0:
+                        value = new_v
+                    else:
+                        continue
                 optional_params["stop_sequences"] = value
             if param == "temperature":
                 optional_params["temperature"] = value

litellm/tests/test_optional_params.py

@@ -5,13 +5,27 @@ import pytest
 
 sys.path.insert(0, os.path.abspath("../.."))
 import litellm
-from litellm.utils import get_optional_params_embeddings
+from litellm.utils import get_optional_params_embeddings, get_optional_params
 
 ## get_optional_params_embeddings
 ### Models: OpenAI, Azure, Bedrock
 ### Scenarios: w/ optional params + litellm.drop_params = True
 
 
+@pytest.mark.parametrize(
+    "stop_sequence, expected_count", [("\n", 0), (["\n"], 0), (["finish_reason"], 1)]
+)
+def test_anthropic_optional_params(stop_sequence, expected_count):
+    """
+    Test if whitespace character optional param is dropped by anthropic
+    """
+    litellm.drop_params = True
+    optional_params = get_optional_params(
+        model="claude-3", custom_llm_provider="anthropic", stop=stop_sequence
+    )
+    assert len(optional_params) == expected_count
+
+
 def test_bedrock_optional_params_embeddings():
     litellm.drop_params = True
     optional_params = get_optional_params_embeddings(

litellm/utils.py

@@ -5006,26 +5006,9 @@ def get_optional_params(
             model=model, custom_llm_provider=custom_llm_provider
         )
         _check_valid_arg(supported_params=supported_params)
-        # handle anthropic params
+        optional_params = litellm.AnthropicConfig().map_openai_params(
-        if stream:
+            non_default_params=non_default_params, optional_params=optional_params
-            optional_params["stream"] = stream
+        )
-        if stop is not None:
-            if type(stop) == str:
-                stop = [stop]  # openai can accept str/list for stop
-            optional_params["stop_sequences"] = stop
-        if temperature is not None:
-            optional_params["temperature"] = temperature
-        if top_p is not None:
-            optional_params["top_p"] = top_p
-        if max_tokens is not None:
-            if (model == "claude-2") or (model == "claude-instant-1"):
-                # these models use antropic_text.py which only accepts max_tokens_to_sample
-                optional_params["max_tokens_to_sample"] = max_tokens
-            else:
-                optional_params["max_tokens"] = max_tokens
-            optional_params["max_tokens"] = max_tokens
-        if tools is not None:
-            optional_params["tools"] = tools
     elif custom_llm_provider == "cohere":
         ## check if unsupported param passed in
         supported_params = get_supported_openai_params(
@@ -5929,15 +5912,7 @@ def get_supported_openai_params(model: str, custom_llm_provider: str):
     elif custom_llm_provider == "ollama_chat":
         return litellm.OllamaChatConfig().get_supported_openai_params()
     elif custom_llm_provider == "anthropic":
-        return [
+        return litellm.AnthropicConfig().get_supported_openai_params()
-            "stream",
-            "stop",
-            "temperature",
-            "top_p",
-            "max_tokens",
-            "tools",
-            "tool_choice",
-        ]
     elif custom_llm_provider == "groq":
         return [
             "temperature",