init

model_executor/guided_decoding/guidance_decoding.py

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+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+import json
+
+import llguidance
+from regex import escape as regex_escape
+from transformers import PreTrainedTokenizerBase
+
+from vllm.model_executor.guided_decoding.guidance_logits_processors import (
+    GuidanceLogitsProcessor)
+from vllm.sampling_params import GuidedDecodingParams
+from vllm.v1.structured_output.backend_guidance import (
+    process_for_additional_properties)
+
+
+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")