Files
vllm/vllm/model_executor/guided_decoding/__init__.py
2024-08-04 03:12:09 +00:00

74 lines
3.1 KiB
Python

from typing import Optional, Union
from vllm.entrypoints.openai.protocol import (
ChatCompletionNamedToolChoiceParam, ChatCompletionRequest,
CompletionRequest)
from vllm.model_executor.guided_decoding.guided_fields import (
GuidedDecodingRequest)
from vllm.model_executor.guided_decoding.outlines_decoding import (
get_local_outlines_guided_decoding_logits_processor,
get_outlines_guided_decoding_logits_processor)
from vllm.sampling_params import LogitsProcessor
async def get_guided_decoding_logits_processor(
guided_decoding_backend: str, request: Union[CompletionRequest,
ChatCompletionRequest],
tokenizer) -> Optional[LogitsProcessor]:
request = _adapt_request_for_tool_use(request)
if guided_decoding_backend == 'outlines':
return await get_outlines_guided_decoding_logits_processor(
request, tokenizer)
if guided_decoding_backend == 'lm-format-enforcer':
from vllm.model_executor.guided_decoding.lm_format_enforcer_decoding import ( # noqa
get_lm_format_enforcer_guided_decoding_logits_processor)
return await get_lm_format_enforcer_guided_decoding_logits_processor(
request, tokenizer)
raise ValueError(
f"Unknown guided decoding backend '{guided_decoding_backend}'. "
"Must be one of 'outlines, 'lm-format-enforcer'")
def get_local_guided_decoding_logits_processor(
guided_decoding_backend: str, guided_options: GuidedDecodingRequest,
tokenizer) -> Optional[LogitsProcessor]:
# request = _adapt_request_for_tool_use(request)
if guided_decoding_backend == 'outlines':
return get_local_outlines_guided_decoding_logits_processor(
guided_options, tokenizer)
if guided_decoding_backend == 'lm-format-enforcer':
from vllm.model_executor.guided_decoding.lm_format_enforcer_decoding import ( # noqa
get_local_lm_format_enforcer_guided_decoding_logits_processor)
return get_local_lm_format_enforcer_guided_decoding_logits_processor(
guided_options, tokenizer)
raise ValueError(
f"Unknown guided decoding backend '{guided_decoding_backend}'. "
"Must be one of 'outlines, 'lm-format-enforcer'")
def _adapt_request_for_tool_use(request: Union[CompletionRequest,
ChatCompletionRequest]):
# the legacy completion API does not support tool use
if type(request) is CompletionRequest:
return request
# user has chosen to not use any tool
if request.tool_choice == "none":
return request
# user has chosen to use a named tool
if type(request.tool_choice) is ChatCompletionNamedToolChoiceParam:
tool_name = request.tool_choice.function.name
tools = {tool.function.name: tool.function for tool in request.tools}
if tool_name not in tools:
raise ValueError(
f"Tool '{tool_name}' has not been passed in `tools`.")
tool = tools[tool_name]
request.guided_json = tool.parameters
return request