Given an OpenAI-compatible request, check for guided decoding parameters
and get the necessary logits processor for the given guide.
Source code in vllm/model_executor/guided_decoding/guidance_decoding.py
| def get_local_guidance_guided_decoding_logits_processor(
guided_params: GuidedDecodingParams,
tokenizer: PreTrainedTokenizerBase) -> GuidanceLogitsProcessor:
"""
Given an OpenAI-compatible request, check for guided decoding parameters
and get the necessary logits processor for the given guide.
"""
grm = ""
any_whitespace = not guided_params.disable_any_whitespace
if (guide_json := guided_params.json) is not None:
# Optionally set additionalProperties to False at the top-level
# By default, other backends do not allow additional top-level
# properties, so this makes guidance more similar to other backends
if guided_params.disable_additional_properties:
if not isinstance(guide_json, str):
guide_json = json.dumps(guide_json)
guide_json = process_for_additional_properties(guide_json)
grm = llguidance.LLMatcher.grammar_from_json_schema(
guide_json,
overrides={"whitespace_pattern": guided_params.whitespace_pattern},
defaults={
"whitespace_flexible": any_whitespace,
})
elif guided_params.json_object:
grm = llguidance.LLMatcher.grammar_from_json_schema(
'{"type": "object"}',
overrides={"whitespace_pattern": guided_params.whitespace_pattern},
defaults={
"whitespace_flexible": any_whitespace,
})
elif guided_params.regex:
grm = llguidance.grammar_from("regex", guided_params.regex)
elif guided_params.choice:
# choice just uses regex
choices = (regex_escape(str(choice))
for choice in guided_params.choice)
choices_regex = "(" + "|".join(choices) + ")"
grm = llguidance.grammar_from("regex", choices_regex)
elif guided_params.grammar:
# this supports Lark and GBNF
grm = llguidance.grammar_from("grammar", guided_params.grammar)
if grm:
return GuidanceLogitsProcessor(grm, tokenizer)
raise ValueError("Unknown guided decoding mode")
|