Constrains effort on reasoning for reasoning models. Currently supported values are none, minimal, low, medium, high, xhigh, and max. Reducing reasoning effort can result in faster responses and fewer tokens used on reasoning in a response.
Maximum number of tokens allowed for thinking operations (reasoning models). Non-negative integer sets the limit; -1 means unlimited (treated as unset).
Whether to include reasoning extracted by the backend in the response. Does not disable reasoning generation. Requires a model and backend that support reasoning output.
Penalty applied to tokens that already appear in the prompt or the generated text. Values above 1 discourage repetition, and values below 1 encourage it.
Maximum number of prompt tokens to keep. Use -1 for the model context limit. truncation_side selects which end is dropped; when unset, the backend uses its default.
If this is set, the chat will be formatted so that the final message in the chat is open-ended, without any EOS tokens. The model will continue this message rather than starting a new one. This allows you to "prefill" part of the model's response for it. Cannot be used at the same time as add_generation_prompt.
If true, special tokens (e.g. BOS) will be added to the prompt on top of what is added by the chat template. For most models the chat template takes care of adding the special tokens, so this should be left false.
A list of dicts representing documents that will be accessible to the model if it is performing RAG (retrieval-augmented generation). If the template does not support RAG, this argument will have no effect. Each document should contain "title" and "text" keys.
A Jinja template to use for this conversion. As of transformers v4.44, the default chat template is no longer allowed, so you must provide a chat template if the tokenizer does not define one.
The priority of the request (lower means earlier handling; default: 0). Any priority other than 0 will raise an error if the served model does not use priority scheduling.
Required range: -9223372036854776000 <= x <= 9223372036854776000
The request_id related to this request. If the caller does not set it, a random uuid will be generated. This id is used throughout the inference process and returned in the response.
If specified with 'logprobs', tokens are represented as strings of the form 'token_id:{token_id}' so that tokens that are not JSON-encodable can be identified.
If specified, the result will include token IDs alongside the generated text. In streaming mode, prompt_token_ids is included only in the first chunk, and token_ids contains the delta tokens for each chunk.
If true, the response will include prompt_text containing the prompt string produced by chat templating. In streaming mode it is sent only on the first chunk.
If specified, the prefix cache will be salted with the provided string to prevent an attacker from guessing prompts in multi-user environments. The salt should be random, protected from access by 3rd parties, and long enough to be unpredictable.
Timing and throughput measurements for this request, when reported by the backend.
Show child attributes
Last modified on July 31, 2026
⌘I
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All other tokens are blocked.","uniqueKey":"allowed_token_ids.oneOf.1","typeLabel":"null"}],"uniqueKey":"allowed_token_ids","typeLabel":"integer[] | null"},"bad_words":{"description":"Words the model avoids generating.","items":{"type":"string","uniqueKey":"bad_words.items.[INDEX]","typeLabel":"string"},"title":"Bad Words","type":"array","uniqueKey":"bad_words","typeLabel":"string[]"},"echo":{"default":false,"description":"If true, the new message will be prepended with the last message if they belong to the same role.","title":"Echo","type":"boolean","uniqueKey":"echo","typeLabel":"boolean"},"add_generation_prompt":{"default":true,"description":"If true, the generation prompt will be added to the chat template. 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