[Bugfix] Fix Hermes tool parser when stream interval > 1 (#38168)

Signed-off-by: sfeng33 <4florafeng@gmail.com>
This commit is contained in:
Flora Feng
2026-03-27 02:42:26 -04:00
committed by GitHub
parent 0ae89f18fd
commit aee4c14689
3 changed files with 348 additions and 381 deletions

View File

@@ -152,6 +152,175 @@ def test_hermes_parser_streaming(
} }
def _simulate_streaming(
tokenizer: TokenizerLike,
parser: ToolParser,
request: ChatCompletionRequest,
text: str,
stream_interval: int = 1,
) -> list:
"""Simulate streaming with a given stream_interval.
Tokens are batched into chunks of `stream_interval` tokens,
mimicking how the output processor delivers them.
Returns a list of non-None DeltaMessages.
"""
tokens = tokenizer.encode(text)
previous_text = ""
delta_messages = []
for i in range(0, len(tokens), stream_interval):
chunk_ids = tokens[i : i + stream_interval]
delta_text = tokenizer.decode(chunk_ids)
current_text = previous_text + delta_text
delta = parser.extract_tool_calls_streaming(
previous_text=previous_text,
current_text=current_text,
delta_text=delta_text,
previous_token_ids=[],
current_token_ids=[],
delta_token_ids=chunk_ids,
request=request,
)
previous_text = current_text
if delta is not None:
delta_messages.append(delta)
return delta_messages
@pytest.mark.parametrize("stream_interval", [2, 3, 5, 8])
def test_hermes_streaming_tool_call_with_stream_interval(
qwen_tokenizer: TokenizerLike,
any_chat_request: ChatCompletionRequest,
stream_interval: int,
) -> None:
"""Tool call streaming must produce correct name + args at any interval."""
text = (
'<tool_call>{"name": "get_current_temperature", '
'"arguments": {"location": "San Francisco", "unit": "celsius"}}'
"</tool_call>"
)
parser = Hermes2ProToolParser(qwen_tokenizer)
deltas = _simulate_streaming(
qwen_tokenizer, parser, any_chat_request, text, stream_interval
)
# Flatten all DeltaToolCalls across all deltas.
tool_deltas = [tc for d in deltas if d.tool_calls for tc in d.tool_calls]
assert tool_deltas, "Expected at least one tool call delta"
assert tool_deltas[0].function.name == "get_current_temperature"
# Concatenated arguments must be valid JSON matching the original.
args_str = "".join(tc.function.arguments or "" for tc in tool_deltas)
assert json.loads(args_str) == {
"location": "San Francisco",
"unit": "celsius",
}
@pytest.mark.parametrize("stream_interval", [2, 3, 5, 8])
def test_hermes_streaming_content_then_tool_call_with_stream_interval(
qwen_tokenizer: TokenizerLike,
any_chat_request: ChatCompletionRequest,
stream_interval: int,
) -> None:
"""Content before a tool call must be fully streamed, then tool call."""
text = (
"Sure, let me check the weather."
'<tool_call>{"name": "get_weather", '
'"arguments": {"city": "NYC"}}</tool_call>'
)
parser = Hermes2ProToolParser(qwen_tokenizer)
deltas = _simulate_streaming(
qwen_tokenizer, parser, any_chat_request, text, stream_interval
)
content_deltas = [d for d in deltas if d.content]
tool_deltas = [d for d in deltas if d.tool_calls]
# Content must reconstruct the prefix.
content_str = "".join(d.content for d in content_deltas)
assert content_str == "Sure, let me check the weather."
# Tool call must be correct.
tool_calls = [tc for d in tool_deltas for tc in d.tool_calls]
assert tool_calls[0].function.name == "get_weather"
args_str = "".join(tc.function.arguments or "" for tc in tool_calls)
assert json.loads(args_str) == {"city": "NYC"}
@pytest.mark.parametrize("stream_interval", [1, 2, 4])
def test_hermes_streaming_multiple_tool_calls_with_stream_interval(
qwen_tokenizer: TokenizerLike,
any_chat_request: ChatCompletionRequest,
stream_interval: int,
) -> None:
"""Multiple sequential tool calls must each be streamed correctly."""
text = (
'<tool_call>{"name": "search", "arguments": {"q": "cats"}}</tool_call>'
'<tool_call>{"name": "search", "arguments": {"q": "dogs"}}</tool_call>'
)
parser = Hermes2ProToolParser(qwen_tokenizer)
deltas = _simulate_streaming(
qwen_tokenizer, parser, any_chat_request, text, stream_interval
)
# Flatten all DeltaToolCalls across all deltas.
all_tool_calls = [tc for d in deltas if d.tool_calls for tc in d.tool_calls]
# Separate by tool index.
tool0 = [tc for tc in all_tool_calls if tc.index == 0]
tool1 = [tc for tc in all_tool_calls if tc.index == 1]
assert tool0[0].function.name == "search"
args0 = "".join(tc.function.arguments or "" for tc in tool0)
assert json.loads(args0) == {"q": "cats"}
assert tool1[0].function.name == "search"
args1 = "".join(tc.function.arguments or "" for tc in tool1)
assert json.loads(args1) == {"q": "dogs"}
@pytest.mark.parametrize("stream_interval", [2, 5])
def test_hermes_streaming_boolean_args_with_stream_interval(
qwen_tokenizer: TokenizerLike,
any_chat_request: ChatCompletionRequest,
stream_interval: int,
) -> None:
"""Regression test for bug #19056 with stream_interval > 1."""
text = (
"<tool_call>\n"
'{"name": "final_answer", "arguments": {"trigger": true}}\n'
"</tool_call>"
)
parser = Hermes2ProToolParser(qwen_tokenizer)
deltas = _simulate_streaming(
qwen_tokenizer, parser, any_chat_request, text, stream_interval
)
tool_calls = [tc for d in deltas if d.tool_calls for tc in d.tool_calls]
assert tool_calls[0].function.name == "final_answer"
args_str = "".join(tc.function.arguments or "" for tc in tool_calls)
assert json.loads(args_str) == {"trigger": True}
@pytest.mark.parametrize("stream_interval", [2, 3, 5])
def test_hermes_streaming_just_forward_text_with_stream_interval(
qwen_tokenizer: TokenizerLike,
any_chat_request: ChatCompletionRequest,
stream_interval: int,
) -> None:
"""Plain text with no tool calls must be fully forwarded."""
text = "This is plain text with no tool calling involved."
parser = Hermes2ProToolParser(qwen_tokenizer)
deltas = _simulate_streaming(
qwen_tokenizer, parser, any_chat_request, text, stream_interval
)
for d in deltas:
assert not d.tool_calls
assert "".join(d.content for d in deltas) == text
def test_hermes_parser_non_streaming_no_tool_call( def test_hermes_parser_non_streaming_no_tool_call(
hermes_parser: ToolParser, hermes_parser: ToolParser,
any_chat_request: ChatCompletionRequest, any_chat_request: ChatCompletionRequest,
@@ -218,3 +387,28 @@ def test_hermes_parser_non_streaming_tool_call_invalid_json(
assert tool_call is not None assert tool_call is not None
assert not tool_call.tools_called assert not tool_call.tools_called
def test_hermes_streaming_content_and_tool_call_in_single_chunk(
qwen_tokenizer: TokenizerLike,
any_chat_request: ChatCompletionRequest,
) -> None:
"""Content + complete tool call in one chunk must both be emitted."""
text = 'Hi!<tool_call>{"name": "f", "arguments": {"x": 1}}</tool_call>'
# Use a stream_interval large enough to guarantee a single chunk.
parser = Hermes2ProToolParser(qwen_tokenizer)
deltas = _simulate_streaming(
qwen_tokenizer,
parser,
any_chat_request,
text,
stream_interval=9999,
)
content_parts = [d.content for d in deltas if d.content]
tool_parts = [tc for d in deltas if d.tool_calls for tc in d.tool_calls]
assert "".join(content_parts) == "Hi!"
assert tool_parts[0].function.name == "f"
args_str = "".join(tc.function.arguments or "" for tc in tool_parts)
assert json.loads(args_str) == {"x": 1}

View File

@@ -4,9 +4,7 @@
import json import json
from collections.abc import Sequence from collections.abc import Sequence
import partial_json_parser
import regex as re 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.chat_utils import make_tool_call_id
from vllm.entrypoints.openai.chat_completion.protocol import ( from vllm.entrypoints.openai.chat_completion.protocol import (
@@ -31,6 +29,27 @@ from vllm.utils.mistral import is_mistral_tokenizer
logger = init_logger(__name__) logger = init_logger(__name__)
def _partial_tag_overlap(text: str, tag: str) -> int:
"""Length of the longest prefix of `tag` that matches a suffix of `text`.
E.g. text ending in "<tool_" returns 6 when tag is "<tool_call>".
Returns 0 if there is no overlap.
"""
max_check = min(len(tag) - 1, len(text))
for k in range(max_check, 0, -1):
if text.endswith(tag[:k]):
return k
return 0
def _is_valid_json(text: str) -> bool:
try:
json.loads(text)
return True
except (json.JSONDecodeError, ValueError):
return False
class Hermes2ProToolParser(ToolParser): class Hermes2ProToolParser(ToolParser):
def __init__(self, tokenizer: TokenizerLike, tools: list[Tool] | None = None): def __init__(self, tokenizer: TokenizerLike, tools: list[Tool] | None = None):
super().__init__(tokenizer, tools) super().__init__(tokenizer, tools)
@@ -39,13 +58,6 @@ class Hermes2ProToolParser(ToolParser):
logger.error("Detected Mistral tokenizer when using a Hermes model") logger.error("Detected Mistral tokenizer when using a Hermes model")
self.model_tokenizer = tokenizer.tokenizer 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 = "<tool_call>" self.tool_call_start_token: str = "<tool_call>"
self.tool_call_end_token: str = "</tool_call>" self.tool_call_end_token: str = "</tool_call>"
@@ -61,57 +73,9 @@ class Hermes2ProToolParser(ToolParser):
"The model tokenizer must be passed to the ToolParser " "The model tokenizer must be passed to the ToolParser "
"constructor during construction." "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 = [ # Streaming state: what has been sent to the client.
self.model_tokenizer.decode([token_id]) self._sent_content_idx: int = 0
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: def adjust_request(self, request: ChatCompletionRequest) -> ChatCompletionRequest:
request = super().adjust_request(request) request = super().adjust_request(request)
@@ -174,6 +138,88 @@ class Hermes2ProToolParser(ToolParser):
tools_called=False, tool_calls=[], content=model_output tools_called=False, tool_calls=[], content=model_output
) )
def _extract_content(self, current_text: str) -> str | None:
"""Return unsent non-tool-call text, or None.
Holds back any suffix that could be a partial <tool_call> tag.
"""
if self.tool_call_start_token not in current_text:
overlap_length = _partial_tag_overlap(
current_text, self.tool_call_start_token
)
sendable_idx = len(current_text) - overlap_length
else:
sendable_idx = current_text.index(self.tool_call_start_token)
if sendable_idx > self._sent_content_idx:
content = current_text[self._sent_content_idx : sendable_idx]
self._sent_content_idx = sendable_idx
return content
return None
def _extract_tool_call_jsons(self, text: str) -> list[tuple[str, bool]]:
"""Extract (json_text, is_complete) for each <tool_call> region."""
results: list[tuple[str, bool]] = []
pos = 0
while True:
start = text.find(self.tool_call_start_token, pos)
if start == -1:
break
json_start = start + len(self.tool_call_start_token)
json_end = text.find(self.tool_call_end_token, json_start)
if json_end != -1:
results.append((text[json_start:json_end].strip(), True))
pos = json_end + len(self.tool_call_end_token)
else:
raw = text[json_start:]
# Strip partial </tool_call> suffix if present.
overlap = _partial_tag_overlap(raw, self.tool_call_end_token)
if overlap:
raw = raw[:-overlap]
tc_json = raw.strip()
# Valid JSON without closing tag = complete body,
# tag tokens just haven't arrived yet.
is_complete = _is_valid_json(tc_json) if tc_json else False
results.append((tc_json, is_complete))
break
return results
@staticmethod
def _extract_tool_name(tc_json: str) -> str | None:
"""Extract tool name, or None if the name isn't complete yet."""
match = re.search(r'"name"\s*:\s*"([^"]+)"', tc_json)
return match.group(1) if match else None
@staticmethod
def _extract_tool_args(tc_json: str, is_complete: bool) -> str | None:
"""Extract tool arguments from the tool call JSON.
Given {"name": "f", "arguments": {"x": 1}}, returns '{"x": 1}'.
When is_complete, strips the trailing '}' that closes the outer
object (not the arguments). For partial JSON, returns as-is.
"""
match = re.search(r'"arguments"\s*:\s*', tc_json)
if not match:
return None
raw = tc_json[match.end() :]
if is_complete:
raw = raw.rstrip()
if raw.endswith("}"):
raw = raw[:-1].rstrip()
return raw
def _compute_args_diff(
self, index: int, tc_json: str, is_complete: bool
) -> str | None:
"""Return new argument text not yet sent for tool `index`, or None."""
args = self._extract_tool_args(tc_json, is_complete)
if args is None or len(args) <= len(self.streamed_args_for_tool[index]):
return None
diff = args[len(self.streamed_args_for_tool[index]) :]
self.streamed_args_for_tool[index] = args
self.prev_tool_call_arr[index]["arguments"] = args
return diff
def extract_tool_calls_streaming( def extract_tool_calls_streaming(
self, self,
previous_text: str, previous_text: str,
@@ -184,321 +230,64 @@ class Hermes2ProToolParser(ToolParser):
delta_token_ids: Sequence[int], delta_token_ids: Sequence[int],
request: ChatCompletionRequest, request: ChatCompletionRequest,
) -> DeltaMessage | None: ) -> DeltaMessage | None:
# 1. All tokens are parsed based on _text, not token_ids. """Incrementally stream tool call deltas from accumulated output.
# 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) On each invocation, re-parses the full ``current_text`` to find
# If the last characters of previous_text ``<tool_call>`` regions, then diffs against previously sent state
# match self.buffered_delta_text, remove only the matching part. to emit only new content, tool names, or argument fragments.
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)
Returns a ``DeltaMessage`` containing either plain content (for
text preceding any tool call) or one or more ``DeltaToolCall``
entries, or ``None`` if there is nothing new to send yet."""
try: try:
# figure out where we are in the parsing by counting tool call # Extract any content before tool calls.
# start & end tags content = self._extract_content(current_text)
prev_tool_start_count = previous_text.count(self.tool_call_start_token) tool_call_jsons = self._extract_tool_call_jsons(current_text)
prev_tool_end_count = previous_text.count(self.tool_call_end_token) tool_call_deltas: list[DeltaToolCall] = []
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 for i, (tc_json, is_complete) in enumerate(tool_call_jsons):
if ( if i >= len(self.prev_tool_call_arr):
cur_tool_start_count == cur_tool_end_count self.prev_tool_call_arr.append({})
and prev_tool_end_count == cur_tool_end_count self.streamed_args_for_tool.append("")
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: # Stream back tool name.
logger.debug("tool_call_end_token in delta_text") if "name" not in self.prev_tool_call_arr[i]:
full_text = current_text + delta_text name = self._extract_tool_name(tc_json)
tool_call_portion = ( if not name:
full_text.split(self.tool_call_start_token)[-1] # Can't skip to tool i+1 if i isn't ready
.split(self.tool_call_end_token)[0] break
.rstrip() self.prev_tool_call_arr[i]["name"] = name
) tool_call_deltas.append(
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
if current_tool_call is None:
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:
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.
if current_tool_call is None:
return None
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"
)
assert current_tool_call is not None
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( DeltaToolCall(
index=self.current_tool_id, index=i,
function=DeltaFunctionCall( type="function",
arguments=arguments_delta id=make_tool_call_id(),
).model_dump(exclude_none=True), function=DeltaFunctionCall(name=name).model_dump(
)
]
)
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 exclude_none=True
), ),
) )
] )
# Stream back new tool args by diffing against what was sent.
args_diff = self._compute_args_diff(i, tc_json, is_complete)
if args_diff:
tool_call_deltas.append(
DeltaToolCall(
index=i,
function=DeltaFunctionCall(arguments=args_diff).model_dump(
exclude_none=True
),
)
)
if content or tool_call_deltas:
return DeltaMessage(
content=content,
tool_calls=tool_call_deltas,
) )
self.streamed_args_for_tool[self.current_tool_id] += delta_text
# handle saving the state for the current tool into return None
# the "prev" list for use in diffing for the next iteration
assert isinstance(current_tool_call, dict)
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: except Exception:
logger.exception("Error trying to handle streaming tool call.") logger.exception("Error trying to handle streaming tool call.")
return None # do not stream a delta. skip this token ID. return None

View File

@@ -16,23 +16,7 @@ class LongcatFlashToolParser(Hermes2ProToolParser):
self.tool_call_end_token: str = "</longcat_tool_call>" self.tool_call_end_token: str = "</longcat_tool_call>"
self.tool_call_regex = re.compile( self.tool_call_regex = re.compile(
r"<longcat_tool_call>(.*?)</longcat_tool_call>|<longcat_tool_call>(.*)", r"<longcat_tool_call>(.*?)</longcat_tool_call>"
r"|<longcat_tool_call>(.*)",
re.DOTALL, re.DOTALL,
) )
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
]