Sync from v0.13
This commit is contained in:
227
vllm/tool_parsers/internlm2_tool_parser.py
Normal file
227
vllm/tool_parsers/internlm2_tool_parser.py
Normal file
@@ -0,0 +1,227 @@
|
||||
# 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
|
||||
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.logger import init_logger
|
||||
from vllm.tokenizers import TokenizerLike
|
||||
from vllm.tool_parsers.abstract_tool_parser import (
|
||||
ToolParser,
|
||||
)
|
||||
from vllm.tool_parsers.utils import extract_intermediate_diff
|
||||
|
||||
logger = init_logger(__name__)
|
||||
|
||||
|
||||
class Internlm2ToolParser(ToolParser):
|
||||
def __init__(self, tokenizer: TokenizerLike):
|
||||
super().__init__(tokenizer)
|
||||
self.position = 0
|
||||
|
||||
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 internlm use the special
|
||||
# tokens to indicate the start and end of the tool calls
|
||||
# information.
|
||||
request.skip_special_tokens = False
|
||||
return request
|
||||
|
||||
def get_arguments(self, obj):
|
||||
if "parameters" in obj:
|
||||
return obj.get("parameters")
|
||||
elif "arguments" in obj:
|
||||
return obj.get("arguments")
|
||||
return None
|
||||
|
||||
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:
|
||||
if "<|action_start|>" not in current_text:
|
||||
self.position = len(current_text)
|
||||
return DeltaMessage(content=delta_text)
|
||||
# if the tool call is sent, return an empty delta message
|
||||
# to make sure the finish_reason will be sent correctly.
|
||||
if self.current_tool_id > 0:
|
||||
return DeltaMessage(content="")
|
||||
|
||||
last_pos = self.position
|
||||
if "<|action_start|><|plugin|>" not in current_text[last_pos:]:
|
||||
return None
|
||||
|
||||
new_delta = current_text[last_pos:]
|
||||
text, action = new_delta.split("<|action_start|><|plugin|>")
|
||||
|
||||
if len(text) > 0:
|
||||
self.position = self.position + len(text)
|
||||
return DeltaMessage(content=text)
|
||||
|
||||
action = action.strip()
|
||||
action = action.split("<|action_end|>".strip())[0]
|
||||
|
||||
# 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:
|
||||
parsable_arr = action
|
||||
|
||||
# tool calls are generated in an object in internlm2
|
||||
# it's not support parallel tool calls
|
||||
try:
|
||||
tool_call_arr: 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
|
||||
|
||||
# if the current tool name hasn't been sent, send if available
|
||||
# - otherwise send nothing
|
||||
if not self.current_tool_name_sent:
|
||||
function_name = tool_call_arr.get("name")
|
||||
if function_name:
|
||||
self.current_tool_id = self.current_tool_id + 1
|
||||
delta = 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),
|
||||
)
|
||||
]
|
||||
)
|
||||
self.current_tool_name_sent = True
|
||||
self.streamed_args_for_tool.append("")
|
||||
else:
|
||||
delta = None
|
||||
# now we know we're on the same tool call and we're streaming
|
||||
# arguments
|
||||
else:
|
||||
prev_arguments = self.get_arguments(
|
||||
self.prev_tool_call_arr[self.current_tool_id]
|
||||
)
|
||||
cur_arguments = self.get_arguments(tool_call_arr)
|
||||
|
||||
# not arguments generated
|
||||
if not cur_arguments and not prev_arguments:
|
||||
delta = None
|
||||
# will never happen
|
||||
elif not cur_arguments and prev_arguments:
|
||||
logger.error(
|
||||
"INVARIANT - impossible to have arguments reset mid-arguments"
|
||||
)
|
||||
delta = None
|
||||
# first time to get parameters
|
||||
elif cur_arguments and not prev_arguments:
|
||||
cur_arguments_json = json.dumps(cur_arguments, ensure_ascii=False)
|
||||
|
||||
arguments_delta = cur_arguments_json[
|
||||
: cur_arguments_json.index(delta_text) + len(delta_text)
|
||||
]
|
||||
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
|
||||
# both prev and cur parameters, send the increase parameters
|
||||
elif cur_arguments and prev_arguments:
|
||||
cur_args_json = json.dumps(cur_arguments, ensure_ascii=False)
|
||||
prev_args_json = json.dumps(prev_arguments, ensure_ascii=False)
|
||||
|
||||
argument_diff = extract_intermediate_diff(
|
||||
cur_args_json, prev_args_json
|
||||
)
|
||||
|
||||
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
|
||||
|
||||
# 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
|
||||
tool_call_arr["arguments"] = self.get_arguments(tool_call_arr)
|
||||
self.prev_tool_call_arr = [tool_call_arr]
|
||||
return delta
|
||||
except Exception:
|
||||
logger.exception("Error trying to handle streaming tool call.")
|
||||
logger.debug(
|
||||
"Skipping chunk as a result of tool streaming extraction error"
|
||||
)
|
||||
return None
|
||||
|
||||
def extract_tool_calls(
|
||||
self,
|
||||
model_output: str,
|
||||
request: ChatCompletionRequest,
|
||||
) -> ExtractedToolCallInformation:
|
||||
text = model_output
|
||||
tools = request.tools
|
||||
if "<|action_start|><|plugin|>" in text:
|
||||
text, action = text.split("<|action_start|><|plugin|>")
|
||||
action = action.split("<|action_end|>".strip())[0]
|
||||
action = action[action.find("{") :]
|
||||
action_dict = json.loads(action)
|
||||
name, parameters = (
|
||||
action_dict["name"],
|
||||
json.dumps(
|
||||
action_dict.get("parameters", action_dict.get("arguments", {})),
|
||||
ensure_ascii=False,
|
||||
),
|
||||
)
|
||||
|
||||
if not tools or name not in [t.function.name for t in tools]:
|
||||
ExtractedToolCallInformation(
|
||||
tools_called=False, tool_calls=[], content=text
|
||||
)
|
||||
|
||||
tool_calls = [
|
||||
ToolCall(function=FunctionCall(name=name, arguments=parameters))
|
||||
]
|
||||
return ExtractedToolCallInformation(
|
||||
tools_called=True,
|
||||
tool_calls=tool_calls,
|
||||
content=text if len(text) > 0 else None,
|
||||
)
|
||||
|
||||
return ExtractedToolCallInformation(
|
||||
tools_called=False, tool_calls=[], content=text
|
||||
)
|
||||
Reference in New Issue
Block a user