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[Bugfix] Streamed tool calls now more strictly follow OpenAI's format; ensures Vercel AI SDK compatibility (#8272)

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Kyle Mistele 2024-09-09 09:45:11 -05:00 committed by GitHub
parent 4ef41b8476
commit 08287ef675
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6 changed files with 19 additions and 44 deletions
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2
tests/tool_use/utils.py
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@ -19,7 +19,7 @@ ARGS: List[str] = ["--enable-auto-tool-choice", "--max-model-len", "8096"]
CONFIGS: Dict[str, ServerConfig] = {
"hermes": {
"model":
"NousResearch/Hermes-2-Pro-Llama-3-8B",
"NousResearch/Hermes-3-Llama-3.1-8B",
"arguments": [
"--tool-call-parser", "hermes", "--chat-template",
str(VLLM_PATH / "examples/tool_chat_template_hermes.jinja")

7
vllm/entrypoints/openai/protocol.py
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@ -713,13 +713,6 @@ class DeltaToolCall(OpenAIBaseModel):
function: Optional[DeltaFunctionCall] = None
# the initial delta that gets sent once a new tool call is started;
class InitialDeltaToolCall(DeltaToolCall):
id: str = Field(default_factory=lambda: f"chatcmpl-tool-{random_uuid()}")
type: Literal["function"] = "function"
index: int
class ExtractedToolCallInformation(BaseModel):
# indicate if tools were called
tools_called: bool

6
vllm/entrypoints/openai/serving_chat.py
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@ -271,9 +271,13 @@ class OpenAIServingChat(OpenAIServing):
# NOTE num_choices defaults to 1 so this usually executes
# once per request
for i in range(num_choices):
choice_data = ChatCompletionResponseStreamChoice(
index=i,
delta=DeltaMessage(role=role),
delta=DeltaMessage(
role=role,
content="",
),
logprobs=None,
finish_reason=None)
chunk = ChatCompletionStreamResponse(

1
vllm/entrypoints/openai/tool_parsers/abstract_tool_parser.py
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@ -20,7 +20,6 @@ class ToolParser:
# the index of the tool call that is currently being parsed
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] = []
self.model_tokenizer = tokenizer

20
vllm/entrypoints/openai/tool_parsers/hermes_tool_parser.py
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@ -8,14 +8,14 @@ from partial_json_parser.core.options import Allow
from vllm.entrypoints.openai.protocol import (DeltaFunctionCall, DeltaMessage,
DeltaToolCall,
ExtractedToolCallInformation,
FunctionCall,
InitialDeltaToolCall, ToolCall)
FunctionCall, 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
from vllm.utils import random_uuid
logger = init_logger(__name__)
@ -34,7 +34,6 @@ class Hermes2ProToolParser(ToolParser):
self.prev_tool_call_arr: List[Dict] = []
self.current_tool_id: int = -1
self.current_tool_name_sent = 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
@ -168,7 +167,6 @@ class Hermes2ProToolParser(ToolParser):
# set cursors and state appropriately
self.current_tool_id += 1
self.current_tool_name_sent = False
self.current_tool_initial_sent = False
self.streamed_args_for_tool.append("")
logger.debug("Starting on a new tool %s", self.current_tool_id)
@ -218,24 +216,16 @@ class Hermes2ProToolParser(ToolParser):
logger.debug('not enough tokens to parse into JSON yet')
return None
# case - we haven't sent the initial delta with the tool call ID
# (it will be sent)
if not self.current_tool_initial_sent:
self.current_tool_initial_sent = True
return DeltaMessage(tool_calls=[
InitialDeltaToolCall(
index=self.current_tool_id).model_dump(
exclude_none=True)
])
# case - we haven't sent the tool name yet. If it's available, send
# it. otherwise, wait until it's available.
elif not self.current_tool_name_sent:
if not self.current_tool_name_sent:
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=f"chatcmpl-tool-{random_uuid()}",
function=DeltaFunctionCall(
name=function_name).model_dump(
exclude_none=True))

27
vllm/entrypoints/openai/tool_parsers/mistral_tool_parser.py
View File

@ -8,14 +8,14 @@ from partial_json_parser.core.options import Allow
from vllm.entrypoints.openai.protocol import (DeltaFunctionCall, DeltaMessage,
DeltaToolCall,
ExtractedToolCallInformation,
FunctionCall,
InitialDeltaToolCall, ToolCall)
FunctionCall, 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
from vllm.utils import random_uuid
logger = init_logger(__name__)
@ -25,7 +25,7 @@ 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
Used when --enable-auto-tool-choice --tool-call-parser mistral are all set
"""
def __init__(self, tokenizer: AnyTokenizer):
@ -42,7 +42,6 @@ class MistralToolParser(ToolParser):
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]"
@ -91,7 +90,6 @@ class MistralToolParser(ToolParser):
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=[],
@ -109,7 +107,7 @@ class MistralToolParser(ToolParser):
# 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:
if self.bot_token not in current_text:
return DeltaMessage(content=delta_text)
# if the tool call token ID IS in the tokens generated so far, that
@ -134,7 +132,7 @@ class MistralToolParser(ToolParser):
# 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]
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
@ -186,31 +184,22 @@ class MistralToolParser(ToolParser):
# 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:
if 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,
type="function",
id=f"chatcmpl-tool-{random_uuid()}",
function=DeltaFunctionCall(
name=function_name).model_dump(
exclude_none=True))