# SPDX-License-Identifier: Apache-2.0
# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
import json
from collections.abc import Sequence
import partial_json_parser
import regex as re
from partial_json_parser.core.options import Allow
from vllm.entrypoints.chat_utils import make_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,
)
from vllm.logger import init_logger
from vllm.tokenizers import MistralTokenizer, TokenizerLike
logger = init_logger(__name__)
class Hermes2ProToolParser(ToolParser):
def __init__(self, tokenizer: TokenizerLike):
super().__init__(tokenizer)
if isinstance(tokenizer, MistralTokenizer):
logger.error("Detected Mistral tokenizer when using a Hermes model")
self.model_tokenizer = 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_ids = self.model_tokenizer.encode(
self.tool_call_start_token, add_special_tokens=False
)
self.tool_call_end_token_ids = self.model_tokenizer.encode(
self.tool_call_end_token, add_special_tokens=False
)
self.tool_call_start_token_array = [
self.model_tokenizer.decode([token_id])
for token_id in self.tool_call_start_token_ids
]
self.tool_call_end_token_array = [
self.model_tokenizer.decode([token_id])
for token_id in self.tool_call_end_token_ids
]
self.buffered_delta_text = ""
# Very simple idea: when encountering tokens like <, tool, _call, >,
# <, /, tool, _call, >, store them in a buffer.
# When the last token is encountered, empty the buffer and return it.
# If a token appears in an incorrect sequence while storing in the buffer,
# return the preceding buffer along with the token.
def tool_call_delta_buffer(self, delta_text: str):
# If the sequence of tool_call_start or tool_call_end tokens is not yet
# complete, fill the buffer with the token and return "".
if (
delta_text in self.tool_call_start_token_array
or delta_text in self.tool_call_end_token_array
):
# If delta_text is the last token of tool_call_start_token or
# tool_call_end_token, empty the buffer and return
# the buffered text + delta_text.
if (
delta_text == self.tool_call_start_token_array[-1]
or delta_text == self.tool_call_end_token_array[-1]
):
buffered_text = self.buffered_delta_text
self.buffered_delta_text = ""
return buffered_text + delta_text
else:
self.buffered_delta_text = self.buffered_delta_text + delta_text
return ""
else:
if self.buffered_delta_text:
buffered_text = self.buffered_delta_text
self.buffered_delta_text = ""
return buffered_text + delta_text
else:
return delta_text
def adjust_request(self, request: ChatCompletionRequest) -> ChatCompletionRequest:
request = super().adjust_request(request)
if request.tools and request.tool_choice != "none":
# do not skip special tokens because the tool_call tokens are
# marked "special" in some models. Since they are skipped
# prior to the call to the tool parser, it breaks tool calling.
request.skip_special_tokens = False
return request
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,
) -> DeltaMessage | None:
# 1. All tokens are parsed based on _text, not token_ids.
# 2. All incoming text data is processed by the tool_call_delta_buffer
# function for buffering before being used for parsing.
delta_text = self.tool_call_delta_buffer(delta_text)
# If the last characters of previous_text
# match self.buffered_delta_text, remove only the matching part.
if (
len(previous_text) >= len(self.buffered_delta_text)
and previous_text[-len(self.buffered_delta_text) :]
== self.buffered_delta_text
):
previous_text = previous_text[: -len(self.buffered_delta_text)]
current_text = previous_text + delta_text
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 not in current_text:
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_text.count(self.tool_call_start_token)
prev_tool_end_count = previous_text.count(self.tool_call_end_token)
cur_tool_start_count = current_text.count(self.tool_call_start_token)
cur_tool_end_count = current_text.count(self.tool_call_end_token)
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: 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=make_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:
# extract the content after {"name": ..., "arguments":
# directly from tool_call_portion as cur_arguments_json,
# since cur_arguments may differ from the original text
# due to partial JSON parsing
# for example, tool_call_portion =
# {"name": "search", "arguments": {"search_request": {"
# but cur_arguments =
# {"search_request": {}}
function_name = current_tool_call.get("name")
match = re.search(
r'\{"name":\s*"'
+ re.escape(function_name)
+ r'"\s*,\s*"arguments":\s*(.*)',
tool_call_portion.strip(),
re.DOTALL,
)
if match:
cur_arguments_json = match.group(1)
else:
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:
return None
args_delta_start_loc = cur_arguments_json.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:
# judge whether the tool_call_portion is a complete JSON
try:
json.loads(tool_call_portion)
is_complete_json = True
except Exception:
is_complete_json = False
# if the delta_text ends with a '}' and tool_call_portion is a
# complete JSON, then the last '}' does not belong to the
# arguments, so we should trim it off
if (
isinstance(delta_text, str)
and len(delta_text.rstrip()) >= 1
and delta_text.rstrip()[-1] == "}"
and is_complete_json
):
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.