fix: The tag based thinking process does not output

[shaohuzhang1]

fix: The tag based thinking process does not output

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[shaohuzhang1]

The provided code snippet seems to be part of a larger function _convert_delta_to_message_chunk responsible for converting various types into BaseMessageChunk objects. Here's an analysis along with some suggestions:

1. Variable Naming:

   • The variable named additional_kwargs might be confusing, since it could potentially include other keyword arguments related to different message chunks types.

2. Conditional Check:

   • The condition 'reasoning_content' in _dict: checks if the key is present before attempting to access the value. This is good practice as it prevents accessing keys that do not exist.

3. Default Keyword Argument:

   • Adding "default_class=type(BaseMessageChunk) as an argument to the function does no harm but might obscure intent slightly. If this line was removed, clarity would increase slightly without changing behavior.

4. Dictionary Initialization:

   • Initializing additional_kwargs as {} at the top ensures that dictionary creation occurs only once, which is preferable for performance reasons when dealing with large collections.

5. Function Call Handling:

   • Ensuring that the function_call.name is either None or properly handled should ideally be done more robustly within the broader logic context where messages are being constructed.

6. Overall Clarity:

   • The use of explicit casts (cast(str,)) and inline comments can help maintain clarity on data conversion and handling.

Here’s a revised version of the code incorporating these suggestions:

@@ -24,10 +24,12 @@ def _convert_delta_to_message_chunk(
     base_cls: type[BaseMessageChunk],
 ) -> BaseMessageChunk:
     """Converts delta-dictionary data structures into corresponding MessageChunk instances."""
     id_ = _dict.get("id", None)  # Default value set to None instead of "" for clarity
     role = cast(str, _dict.get("role"))
     content = cast(str, _dict.get("content", ""))
    
    addition_kwargs: dict = {}
    # Only add reasoning_content if it exists in the dictionary
    if "reasoning_content" in _dict:
        addition_kwargs["reasoning_content"] = _dict.get("reasoning_content")
    
    if "function_call" in _dict:
        function_call_data = _dict["function_call"].copy()  # Copy to avoid mutating original
        function_name = function_call_data.pop("name", None)
        
        # Additional processing or validation here based on requirements
        
        function_call = {"name": function_name}  # Create new dictionary containing name
        addition_kwargs.update(function_call)
    
    chunk_type = "regular" if not function_call else "function"
    
    try:
        return base_cls(id=id_, role=role, content=content, **addition_kwargs)
    except TypeError as e:
        raise ValueError(f"Failed to create {chunk_type} message due to invalid parameters.") from e

This revision improves readability, adds missing documentation where necessary, fixes unnecessary initializations, and clarifies certain details such as handling default values and creating new dictionaries.