# SPDX-License-Identifier: Apache-2.0 # SPDX-FileCopyrightText: Copyright contributors to the vLLM project import json from collections.abc import Sequence from typing import Union import partial_json_parser import regex as re from partial_json_parser.core.options import Allow from vllm.entrypoints.chat_utils import random_tool_call_id from vllm.entrypoints.openai.protocol import (ChatCompletionRequest, DeltaFunctionCall, DeltaMessage, DeltaToolCall, ExtractedToolCallInformation, FunctionCall, ToolCall) from vllm.entrypoints.openai.tool_parsers.abstract_tool_parser import ( ToolParser, ToolParserManager) from vllm.logger import init_logger from vllm.transformers_utils.tokenizer import AnyTokenizer, MistralTokenizer logger = init_logger(__name__) @ToolParserManager.register_module("hermes") class Hermes2ProToolParser(ToolParser): def __init__(self, tokenizer: AnyTokenizer): super().__init__(tokenizer) if isinstance(self.model_tokenizer, MistralTokenizer): logger.error( "Detected Mistral tokenizer when using a Hermes model") self.model_tokenizer = self.model_tokenizer.tokenizer self.current_tool_name_sent: bool = False self.prev_tool_call_arr: list[dict] = [] self.current_tool_id: int = -1 self.streamed_args_for_tool: list[str] = [ ] # map what has been streamed for each tool so far to a list self.tool_call_start_token: str = "" self.tool_call_end_token: str = "" self.tool_call_regex = re.compile( r"(.*?)|(.*)", re.DOTALL) self.scratch_pad_regex = re.compile( r"(.*?)", re.DOTALL) if not self.model_tokenizer: raise ValueError( "The model tokenizer must be passed to the ToolParser " "constructor during construction.") self.tool_call_start_token_id = self.vocab.get( self.tool_call_start_token) self.tool_call_end_token_id = self.vocab.get(self.tool_call_end_token) if (self.tool_call_start_token_id is None or self.tool_call_end_token_id is None): raise RuntimeError( "Hermes 2 Pro Tool parser could not locate tool call start/end " "tokens in the tokenizer!") def extract_tool_calls( self, model_output: str, request: ChatCompletionRequest, ) -> ExtractedToolCallInformation: # sanity check; avoid unnecessary processing if self.tool_call_start_token not in model_output: return ExtractedToolCallInformation(tools_called=False, tool_calls=[], content=model_output) else: try: # there are two possible captures - between tags, or between a # tag and end-of-string so the result of # findall is an array of tuples where one is a function call and # the other is None function_call_tuples = ( self.tool_call_regex.findall(model_output)) # load the JSON, and then use it to build the Function and # Tool Call raw_function_calls = [ json.loads(match[0] if match[0] else match[1]) for match in function_call_tuples ] tool_calls = [ ToolCall( type="function", function=FunctionCall( name=function_call["name"], # function call args are JSON but as a string arguments=json.dumps(function_call["arguments"], ensure_ascii=False))) for function_call in raw_function_calls ] content = model_output[:model_output. find(self.tool_call_start_token)] return ExtractedToolCallInformation( tools_called=True, tool_calls=tool_calls, content=content if content else None) except Exception: logger.exception( "Error in extracting tool call from response.") return ExtractedToolCallInformation(tools_called=False, tool_calls=[], content=model_output) def extract_tool_calls_streaming( self, 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, ) -> Union[DeltaMessage, None]: logger.debug("delta_text: %s", delta_text) logger.debug("delta_token_ids: %s", delta_token_ids) # check to see if we should be streaming a tool call - is there a if self.tool_call_start_token_id not in current_token_ids: logger.debug("No tool call tokens found!") return DeltaMessage(content=delta_text) try: # figure out where we are in the parsing by counting tool call # start & end tags prev_tool_start_count = previous_token_ids.count( self.tool_call_start_token_id) prev_tool_end_count = previous_token_ids.count( self.tool_call_end_token_id) cur_tool_start_count = current_token_ids.count( self.tool_call_start_token_id) cur_tool_end_count = current_token_ids.count( self.tool_call_end_token_id) tool_call_portion = None text_portion = None # case: if we're generating text, OR rounding out a tool call if (cur_tool_start_count == cur_tool_end_count and prev_tool_end_count == cur_tool_end_count and self.tool_call_end_token not in delta_text): logger.debug("Generating text content! skipping tool parsing.") return DeltaMessage(content=delta_text) if self.tool_call_end_token in delta_text: logger.debug("tool_call_end_token in delta_text") full_text = current_text + delta_text tool_call_portion = full_text.split( self.tool_call_start_token)[-1].split( self.tool_call_end_token)[0].rstrip() delta_text = delta_text.split( self.tool_call_end_token)[0].rstrip() text_portion = delta_text.split( self.tool_call_end_token)[-1].lstrip() # case: if tool open & close tag counts don't match, we're doing # imaginary "else" block here # something with tools with this diff. # flags for partial JSON parting. exported constants from # "Allow" are handled via BIT MASK flags = Allow.ALL if self.current_tool_name_sent \ else Allow.ALL & ~Allow.STR # case -- we're starting a new tool call if (cur_tool_start_count > cur_tool_end_count and cur_tool_start_count > prev_tool_start_count): if len(delta_token_ids) > 1: tool_call_portion = current_text.split( self.tool_call_start_token)[-1] else: tool_call_portion = None delta = None text_portion = None # set cursors and state appropriately self.current_tool_id += 1 self.current_tool_name_sent = False self.streamed_args_for_tool.append("") logger.debug("Starting on a new tool %s", self.current_tool_id) # case -- we're updating an existing tool call elif (cur_tool_start_count > cur_tool_end_count and cur_tool_start_count == prev_tool_start_count): # get the portion of the text that's the tool call tool_call_portion = current_text.split( self.tool_call_start_token)[-1] text_portion = None # case -- the current tool call is being closed. elif (cur_tool_start_count == cur_tool_end_count and cur_tool_end_count >= prev_tool_end_count): if (self.prev_tool_call_arr is None or len(self.prev_tool_call_arr) == 0): logger.debug( "attempting to close tool call, but no tool call") return None diff = self.prev_tool_call_arr[self.current_tool_id].get( "arguments") if diff: diff = diff.encode('utf-8').decode( 'unicode_escape') if diff is str else diff if ('"}' not in delta_text): return None end_loc = delta_text.rindex('"}') diff = delta_text[:end_loc] + '"}' logger.debug( "Finishing tool and found diff that had not " "been streamed yet: %s", diff) self.streamed_args_for_tool[self.current_tool_id] \ += diff return DeltaMessage(tool_calls=[ DeltaToolCall(index=self.current_tool_id, function=DeltaFunctionCall( arguments=diff).model_dump( exclude_none=True)) ]) # case -- otherwise we're just generating text else: text = delta_text.replace(self.tool_call_start_token, "") text = text.replace(self.tool_call_end_token, "") delta = DeltaMessage(tool_calls=[], content=text) return delta try: current_tool_call = partial_json_parser.loads( tool_call_portion or "{}", flags) if tool_call_portion else None logger.debug("Parsed tool call %s", current_tool_call) except partial_json_parser.core.exceptions.MalformedJSON: logger.debug('not enough tokens to parse into JSON yet') return None except json.decoder.JSONDecodeError: logger.debug("unable to parse JSON") return None # case - we haven't sent the tool name yet. If it's available, send # it. otherwise, wait until it's available. if not self.current_tool_name_sent: if (current_tool_call is None): return None function_name: Union[str, None] = current_tool_call.get("name") if function_name: self.current_tool_name_sent = True return DeltaMessage(tool_calls=[ DeltaToolCall(index=self.current_tool_id, type="function", id=random_tool_call_id(), function=DeltaFunctionCall( name=function_name).model_dump( exclude_none=True)) ]) else: return None # case -- otherwise, send the tool call delta # if the tool call portion is None, send the delta as text if tool_call_portion is None: # if there's text but not tool calls, send that - # otherwise None to skip chunk delta = DeltaMessage(content=delta_text) \ if text_portion is not None else None return delta # now, the nitty-gritty of tool calls # now we have the portion to parse as tool call. logger.debug("Trying to parse current tool call with ID %s", self.current_tool_id) # if we're starting a new tool call, push an empty object in as # a placeholder for the arguments if len(self.prev_tool_call_arr) <= self.current_tool_id: self.prev_tool_call_arr.append({}) # main logic for tool parsing here - compare prev. partially-parsed # JSON to the current partially-parsed JSON prev_arguments = ( self.prev_tool_call_arr[self.current_tool_id].get("arguments")) cur_arguments = current_tool_call.get("arguments") logger.debug("diffing old arguments: %s", prev_arguments) logger.debug("against new ones: %s", cur_arguments) # case -- no arguments have been created yet. skip sending a delta. if not cur_arguments and not prev_arguments: logger.debug("Skipping text %s - no arguments", delta_text) delta = None # case -- prev arguments are defined, but non are now. # probably impossible, but not a fatal error - just keep going elif not cur_arguments and prev_arguments: logger.error("should be impossible to have arguments reset " "mid-call. skipping streaming anything.") delta = None # case -- we now have the first info about arguments available from # autocompleting the JSON elif cur_arguments and not prev_arguments: cur_arguments_json = json.dumps(cur_arguments, ensure_ascii=False) logger.debug("finding %s in %s", delta_text, cur_arguments_json) # get the location where previous args differ from current if (delta_text not in cur_arguments_json[:-2]): return None args_delta_start_loc = cur_arguments_json[:-2]. \ rindex(delta_text) + \ len(delta_text) # use that to find the actual delta arguments_delta = cur_arguments_json[:args_delta_start_loc] logger.debug("First tokens in arguments received: %s", arguments_delta) delta = DeltaMessage(tool_calls=[ DeltaToolCall(index=self.current_tool_id, function=DeltaFunctionCall( arguments=arguments_delta).model_dump( exclude_none=True)) ]) self.streamed_args_for_tool[self.current_tool_id] \ += arguments_delta # last case -- we have an update to existing arguments. elif cur_arguments and prev_arguments: if isinstance(delta_text, str) and len(delta_text.rstrip( )) >= 1 and delta_text.rstrip()[-1] == '}': delta_text = delta_text.rstrip()[:-1] logger.debug("got diff %s", delta_text) delta = DeltaMessage(tool_calls=[ DeltaToolCall(index=self.current_tool_id, function=DeltaFunctionCall( arguments=delta_text).model_dump( exclude_none=True)) ]) self.streamed_args_for_tool[self.current_tool_id] \ += delta_text # handle saving the state for the current tool into # the "prev" list for use in diffing for the next iteration if self.current_tool_id == len(self.prev_tool_call_arr) - 1: self.prev_tool_call_arr[self.current_tool_id] = \ current_tool_call else: self.prev_tool_call_arr.append(current_tool_call) return delta except Exception: logger.exception("Error trying to handle streaming tool call.") return None # do not stream a delta. skip this token ID.