easydel.inference.tools.parsers.step3_tool_parser

easydel.inference.tools.parsers.step3_tool_parser#

class easydel.inference.tools.parsers.step3_tool_parser.Step3ToolParser(tokenizer: AutoTokenizer)[source]#

Bases: ToolParser

Tool parser for Step3 models with XML-like format.

Uses a robust, stateful, cursor-based streaming parser that consolidates tool arguments into single messages. Handles complex nested tool call structures with special delimiters.

Features: - Cursor-based position tracking - Hierarchical token structure with special characters - steptml:invoke format parsing - Automatic type casting based on schema - State machine for streaming parsing

Format: <｜tool_calls_begin｜> <｜tool_call_begin｜> function<｜tool_sep｜> <steptml:invoke name=”func”> <steptml:parameter name=”param”>value</steptml:parameter> </steptml:invoke> <｜tool_call_end｜> <｜tool_calls_end｜>

Note: Uses fullwidth vertical line characters (｜) as delimiters.

SPECIAL_TOKENS = ['<｜tool_calls_begin｜>', '<｜tool_calls_end｜>', '<｜tool_call_begin｜>', '<｜tool_call_end｜>']#
TOOL_CALLS_BEGIN = '<｜tool_calls_begin｜>'#
TOOL_CALLS_END = '<｜tool_calls_end｜>'#
TOOL_CALL_BEGIN = '<｜tool_call_begin｜>'#
TOOL_CALL_END = '<｜tool_call_end｜>'#
TOOL_SEP = '<｜tool_sep｜>'#
adjust_request(request: ChatCompletionRequest) → ChatCompletionRequest[source]#

Adjust request parameters for model-specific requirements.

Override this method to modify request parameters like system prompts, tool definitions, or formatting before processing. Default implementation returns the request unchanged.

Parameters

request – Original chat completion request

Returns

Potentially modified request

Return type

ChatCompletionRequest

Example

Some models may need to reformat tool definitions or add specific system instructions for proper tool calling.

extract_tool_calls(model_output: str, request: ChatCompletionRequest) → ExtractedToolCallInformation[source]#

Extract tool calls from complete model output (batch mode).

Parses the entire model response to identify and extract tool/function calls. This method is used for non-streaming responses where the complete output is available.

Parameters

  • model_output – Complete text generated by the model

  • request – Original request containing tool definitions

Returns

Parsed tool calls and remaining content

Return type

ExtractedToolCallInformation

Raises

NotImplementedError – Must be implemented by subclasses

Note

This method is stateless - it doesn’t use instance state. Each parser implements model-specific extraction logic.

extract_tool_calls_streaming(previous_text: str, current_text: str, delta_text: str, previous_token_ids: Sequence[int], current_token_ids: Sequence[int], delta_token_ids: Sequence[int], request: ChatCompletionRequest) → easydel.inference.openai_api_modules.DeltaMessage | None[source]#

Extract tool calls from streaming model output.

Processes incremental model output to identify partial tool calls and emit appropriate streaming updates. Maintains state across calls to handle incomplete JSON/XML structures.

Parameters

  • previous_text – Text accumulated up to previous call

  • current_text – Text accumulated including current chunk

  • delta_text – New text in current chunk

  • previous_token_ids – Token IDs up to previous call

  • current_token_ids – Token IDs including current chunk

  • delta_token_ids – New token IDs in current chunk

  • request – Original request with tool definitions

Returns

Incremental tool call update, or None if no update

Return type

DeltaMessage

Raises

NotImplementedError – Must be implemented by subclasses

Note

This method is stateful - it uses instance variables to track parsing progress across streaming chunks.

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