import json import re from typing import Dict, List, Sequence, Union import partial_json_parser from partial_json_parser.core.options import Allow from vllm.entrypoints.openai.protocol import (DeltaFunctionCall, DeltaMessage, DeltaToolCall, ExtractedToolCallInformation, FunctionCall, InitialDeltaToolCall, ToolCall) from vllm.entrypoints.openai.tool_parsers.abstract_tool_parser import ( ToolParser) from vllm.entrypoints.openai.tool_parsers.utils import ( extract_intermediate_diff) from vllm.logger import init_logger from vllm.transformers_utils.tokenizer import AnyTokenizer, MistralTokenizer logger = init_logger(__name__) class MistralToolParser(ToolParser): """ Tool call parser for Mistral 7B Instruct v0.3, intended for use with the examples/tool_chat_template_mistral.jinja template. Used when --enable-auto-tool-choice --tool-call-parser gmistral are all set """ def __init__(self, tokenizer: AnyTokenizer): super().__init__(tokenizer) if isinstance(self.model_tokenizer, MistralTokenizer): self.model_tokenizer = self.model_tokenizer.tokenizer else: logger.info("Non-Mistral tokenizer detected when using a Mistral " "model...") # initialize properties used for state when parsing tool calls in # streaming mode self.prev_tool_call_arr: List[Dict] = [] self.current_tool_id: int = -1 self.current_tool_name_sent: bool = False self.current_tool_initial_sent: bool = False self.streamed_args_for_tool: List[str] = [ ] # map what has been streamed for each tool so far to a list self.bot_token = "[TOOL_CALLS]" self.bot_token_id = self.model_tokenizer.vocab[self.bot_token] self.tool_call_regex = re.compile(r"\[{.*?}\]", re.DOTALL) def extract_tool_calls(self, model_output: str) -> ExtractedToolCallInformation: """ Extract the tool calls from a complete model response. Requires find-and-replacing single quotes with double quotes for JSON parsing, make sure your tool call arguments don't ever include quotes! """ # case -- if a tool call token is not present, return a text response if self.bot_token not in model_output: return ExtractedToolCallInformation(tools_called=False, tool_calls=[], content=model_output) try: # use a regex to find the tool call. remove the BOT token # and make sure to replace single quotes with double quotes raw_tool_call = self.tool_call_regex.findall( model_output.replace(self.bot_token, ""))[0] # load the JSON, and then use it to build the Function and # Tool Call function_call_arr = json.loads(raw_tool_call) tool_calls: List[ToolCall] = [ ToolCall( type="function", function=FunctionCall( name=raw_function_call["name"], # function call args are JSON but as a string arguments=json.dumps(raw_function_call["arguments"]))) for raw_function_call in function_call_arr ] # get any content before the tool call content = model_output.split(self.bot_token)[0] return ExtractedToolCallInformation( tools_called=True, tool_calls=tool_calls, content=content if len(content) > 0 else None) except Exception as e: logger.error("Error in extracting tool call from response: %s", e) print("ERROR", e) # return information to just treat the tool call as regular JSON 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], ) -> Union[DeltaMessage, None]: # if the tool call token is not in the tokens generated so far, append # output to contents since it's not a tool if self.bot_token_id not in current_token_ids: return DeltaMessage(content=delta_text) # if the tool call token ID IS in the tokens generated so far, that # means we're parsing as tool calls now # handle if we detected the BOT token which means the start of tool # calling if (self.bot_token_id in delta_token_ids and len(delta_token_ids) == 1): # if it's the only token, return None, so we don't send a chat # completion any don't send a control token return None # bit mask flags for partial JSON parsing. If the name hasn't been # sent yet, don't allow sending # an incomplete string since OpenAI only ever (as far as I have # seen) allows sending the entire tool/ function name at once. flags = Allow.ALL if self.current_tool_name_sent \ else Allow.ALL & ~Allow.STR try: # replace BOT token with empty string, and convert single quotes # to double to allow parsing as JSON since mistral uses single # quotes instead of double for tool calls parsable_arr = current_text.split(self.bot_token)[1] # tool calls are generated in an array, so do partial JSON # parsing on the entire array try: tool_call_arr: List[Dict] = partial_json_parser.loads( parsable_arr, flags) except partial_json_parser.core.exceptions.MalformedJSON: logger.debug('not enough tokens to parse into JSON yet') return None # select as the current tool call the one we're on the state at current_tool_call: Dict = tool_call_arr[self.current_tool_id] \ if len(tool_call_arr) > 0 else {} # case -- if no tokens have been streamed for the tool, e.g. # only the array brackets, stream nothing if len(tool_call_arr) == 0: return None # case: we are starting a new tool in the array # -> array has > 0 length AND length has moved past cursor elif (len(tool_call_arr) > 0 and len(tool_call_arr) > self.current_tool_id + 1): # if we're moving on to a new call, first make sure we # haven't missed anything in the previous one that was # auto-generated due to JSON completions, but wasn't # streamed to the client yet. if self.current_tool_id >= 0: diff: Union[str, None] = current_tool_call.get("arguments") if diff: diff = json.dumps(diff).replace( self.streamed_args_for_tool[self.current_tool_id], "") delta = DeltaMessage(tool_calls=[ DeltaToolCall(index=self.current_tool_id, function=DeltaFunctionCall( arguments=diff).model_dump( exclude_none=True)) ]) self.streamed_args_for_tool[ self.current_tool_id] += diff else: delta = None else: delta = None # re-set stuff pertaining to progress in the current tool self.current_tool_id = len(tool_call_arr) - 1 self.current_tool_name_sent = False self.current_tool_initial_sent = False self.streamed_args_for_tool.append("") logger.debug("starting on new tool %d", self.current_tool_id) return delta # case: update an existing tool - this is handled below # if the current tool initial data incl. the id, type=function # and idx not sent, send that if not self.current_tool_initial_sent: self.current_tool_initial_sent = True delta = DeltaMessage(tool_calls=[ InitialDeltaToolCall( index=self.current_tool_id).model_dump( exclude_none=True) ]) # if the current tool name hasn't been sent, send if available # - otherwise send nothing elif not self.current_tool_name_sent: function_name = current_tool_call.get("name") if function_name: delta = DeltaMessage(tool_calls=[ DeltaToolCall(index=self.current_tool_id, function=DeltaFunctionCall( name=function_name).model_dump( exclude_none=True)) ]) self.current_tool_name_sent = True else: delta = None # now we know we're on the same tool call and we're streaming # arguments else: prev_arguments = self.prev_tool_call_arr[ self.current_tool_id].get("arguments") cur_arguments = current_tool_call.get("arguments") new_text = delta_text.replace("\'", "\"") if not cur_arguments and not prev_arguments: delta = None elif not cur_arguments and prev_arguments: logger.error( "INVARIANT - impossible to have arguments reset " "mid-arguments") delta = None elif cur_arguments and not prev_arguments: cur_arguments_json = json.dumps(cur_arguments) logger.debug("finding %s in %s", new_text, cur_arguments_json) arguments_delta = cur_arguments_json[:cur_arguments_json. index(new_text) + len(new_text)] 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 elif cur_arguments and prev_arguments: cur_args_json = json.dumps(cur_arguments) prev_args_json = json.dumps(prev_arguments) logger.debug("Searching for diff between \n%s\n%s", cur_args_json, prev_args_json) argument_diff = extract_intermediate_diff( cur_args_json, prev_args_json) logger.debug("got arguments diff: %s", argument_diff) delta = DeltaMessage(tool_calls=[ DeltaToolCall(index=self.current_tool_id, function=DeltaFunctionCall( arguments=argument_diff).model_dump( exclude_none=True)) ]) self.streamed_args_for_tool[ self.current_tool_id] += argument_diff else: # try parsing it with regular JSON - if it works we're # at the end, and we need to send the difference between # tokens streamed so far and the valid JSON delta = None # check to see if the name is defined and has been sent. if so, # stream the name - otherwise keep waiting # finish by setting old and returning None as base case self.prev_tool_call_arr = tool_call_arr return delta except Exception as e: logger.error("Error trying to handle streaming tool call: %s", e) logger.debug( "Skipping chunk as a result of tool streaming extraction " "error") return None