Skip to content

Config reference: tokenization

  • Enterprise tuning surface


    Defaults + constraints are rendered directly from Pydantic.

  • Env keys when available


    Many fields have an env-style alias (from TriBridConfig.to_flat_dict()).

  • Tooltip-level guidance


    If a matching glossary entry exists, you’ll see deeper tuning notes.

Config reference Config API & workflow Glossary

Total parameters: 7

Group index
  • (root)

(root)

JSON key Env key(s) Type Default Constraints Summary
tokenization.estimate_only — bool false — If true, use fast approximate token counting.
tokenization.hf_tokenizer_name — str "gpt2" — HuggingFace tokenizer name (strategy='huggingface').
tokenization.lowercase — bool false — Lowercase before tokenization.
tokenization.max_tokens_per_chunk_hard — int 8192 ≥ 256, ≤ 65536 Absolute hard limit for tokens per chunk (safety ceiling).
tokenization.normalize_unicode — bool true — Normalize unicode (NFKC) before tokenization for stability.
tokenization.strategy — Literal["whitespace", "tiktoken", "huggingface"] "tiktoken" allowed="whitespace", "tiktoken", "huggingface" Tokenization strategy used for chunking/budgeting.
tokenization.tiktoken_encoding — str "o200k_base" — tiktoken encoding name (strategy='tiktoken').