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