aws[patch]: (Converse) support camel case tool call args (#516)

Author: ccurme

libs/aws/langchain_aws/chat_models/bedrock_converse.py

@@ -1271,7 +1271,10 @@ def _lc_content_to_bedrock(
 
 def _bedrock_to_lc(content: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
     lc_content = []
-    for block in _camel_to_snake_keys(content):
+    for block in _camel_to_snake_keys(
+        content,
+        excluded_keys={"input"},  # exclude 'input' key, which contains tool call args
+    ):
         if "text" in block:
             lc_content.append({"type": "text", "text": block["text"]})
         elif "tool_use" in block:
@@ -1440,13 +1443,21 @@ def _camel_to_snake(text: str) -> str:
 _T = TypeVar("_T")
 
 
-def _camel_to_snake_keys(obj: _T) -> _T:
+def _camel_to_snake_keys(obj: _T, excluded_keys: set = set()) -> _T:
     if isinstance(obj, list):
-        return cast(_T, [_camel_to_snake_keys(e) for e in obj])
-    elif isinstance(obj, dict):
         return cast(
-            _T, {_camel_to_snake(k): _camel_to_snake_keys(v) for k, v in obj.items()}
+            _T, [_camel_to_snake_keys(e, excluded_keys=excluded_keys) for e in obj]
         )
+    elif isinstance(obj, dict):
+        _dict = {}
+        for k, v in obj.items():
+            if k in excluded_keys:
+                _dict[k] = v
+            else:
+                _dict[_camel_to_snake(k)] = _camel_to_snake_keys(
+                    v, excluded_keys=excluded_keys
+                )
+        return cast(_T, _dict)
     else:
         return obj
 

libs/aws/tests/integration_tests/chat_models/test_bedrock_converse.py

@@ -215,6 +215,31 @@ def classify_query(query_type: Literal["cat", "dog"]) -> None:
         assert isinstance(result["ResponseMetadata"]["RetryAttempts"], int)
 
 
+def test_tool_calling_camel_case() -> None:
+    model = ChatBedrockConverse(model="us.anthropic.claude-3-5-sonnet-20241022-v2:0")
+
+    def classifyQuery(queryType: Literal["cat", "dog"]) -> None:
+        pass
+
+    chat = model.bind_tools([classifyQuery], tool_choice="any")
+    response = chat.invoke("How big are cats?")
+    assert isinstance(response, AIMessage)
+    assert len(response.tool_calls) == 1
+    tool_call = response.tool_calls[0]
+    assert tool_call["name"] == "classifyQuery"
+    assert tool_call["args"] == {"queryType": "cat"}
+
+    full = None
+    for chunk in chat.stream("How big are cats?"):
+        full = chunk if full is None else full + chunk  # type: ignore[assignment]
+    assert isinstance(full, AIMessageChunk)
+    assert len(full.tool_calls) == 1
+    tool_call = full.tool_calls[0]
+    assert tool_call["name"] == "classifyQuery"
+    assert tool_call["args"] == {"queryType": "cat"}
+    assert full.tool_calls[0]["args"] == response.tool_calls[0]["args"]
+
+
 def test_structured_output_streaming() -> None:
     model = ChatBedrockConverse(
         model="anthropic.claude-3-sonnet-20240229-v1:0", temperature=0