methods:
  __init__:
    parameters:
      # Explicit arguments
      model:
        annotation: Union[str, pathlib.Path]
        default: inspect._empty
      tokenizer:
        annotation: Union[str, pathlib.Path, transformers.tokenization_utils_base.PreTrainedTokenizerBase,
          tensorrt_llm.llmapi.tokenizer.TokenizerBase, NoneType]
        default: null
      tokenizer_mode:
        annotation: Literal['auto', 'slow']
        default: auto
      skip_tokenizer_init:
        annotation: bool
        default: false
      trust_remote_code:
        annotation: bool
        default: false
      tensor_parallel_size:
        annotation: int
        default: 1
      dtype:
        annotation: str
        default: auto
      revision:
        annotation: Optional[str]
        default: null
      tokenizer_revision:
        annotation: Optional[str]
        default: null
      # Parallelism
      pipeline_parallel_size:
        annotation: int
        default: 1
      context_parallel_size:
        annotation: int
        default: 1
      moe_tensor_parallel_size:
        annotation: Optional[int]
        default: null
      moe_expert_parallel_size:
        annotation: Optional[int]
        default: null
      # LoRA
      enable_lora:
        annotation: bool
        default: false
      lora_config:
        annotation: Optional[tensorrt_llm.llmapi.llm_args.LoraConfig]
        default: null
      # Logits processor and guided decoding
      batched_logits_processor:
        annotation: Optional[tensorrt_llm.sampling_params.BatchedLogitsProcessor]
        default: null
      guided_decoding_backend:
        annotation: Optional[Literal["xgrammar", "llguidance"]]
        default: null
      # Speculative decoding
      speculative_config:
        annotation: Union[tensorrt_llm.llmapi.llm_args.DraftTargetDecodingConfig, tensorrt_llm.llmapi.llm_args.EagleDecodingConfig,tensorrt_llm.llmapi.llm_args.LookaheadDecodingConfig, tensorrt_llm.llmapi.llm_args.MedusaDecodingConfig, tensorrt_llm.llmapi.llm_args.MTPDecodingConfig, tensorrt_llm.llmapi.llm_args.NGramDecodingConfig, tensorrt_llm.llmapi.llm_args.UserProvidedDecodingConfig, tensorrt_llm.llmapi.llm_args.AutoDecodingConfig, NoneType]
        default: null
      # generation constraints
      max_batch_size:
        annotation: Optional[int]
        default: null
      max_input_len:
        annotation: Optional[int]
        default: null
      max_seq_len:
        annotation: Optional[int]
        default: null
      max_beam_width:
        annotation: Optional[int]
        default: null
      max_num_tokens:
        annotation: Optional[int]
        default: null
      # Misc
      load_format:
        annotation: Union[str, tensorrt_llm.llmapi.llm_args.LoadFormat]
        default: 0
      enable_tqdm:
        annotation: bool
        default: false
      enable_chunked_prefill:
        annotation: bool
        default: false
      kv_cache_config:
        annotation: tensorrt_llm.llmapi.llm_args.KvCacheConfig
        default: null
      stream_interval:
        annotation: int
        default: 1

      kwargs:
        annotation: Any
        default: inspect._empty
    return_annotation: None
  generate:
    parameters:
      inputs:
        annotation: Union[str, List[int], tensorrt_llm.inputs.data.TextPrompt, tensorrt_llm.inputs.data.TokensPrompt,
          Sequence[Union[str, List[int], tensorrt_llm.inputs.data.TextPrompt, tensorrt_llm.inputs.data.TokensPrompt]]]
        default: inspect._empty
      sampling_params:
        annotation: Union[tensorrt_llm.sampling_params.SamplingParams, List[tensorrt_llm.sampling_params.SamplingParams],
          NoneType]
        default: null
      lora_request:
        annotation: Union[tensorrt_llm.executor.request.LoRARequest, Sequence[tensorrt_llm.executor.request.LoRARequest],
          NoneType]
        default: null
      prompt_adapter_request:
        annotation: Union[tensorrt_llm.executor.request.PromptAdapterRequest, Sequence[tensorrt_llm.executor.request.PromptAdapterRequest],
          NoneType]
        default: null
      use_tqdm:
        annotation: bool
        default: true
    return_annotation: Union[tensorrt_llm.llmapi.llm.RequestOutput, List[tensorrt_llm.llmapi.llm.RequestOutput]]
  generate_async:
    parameters:
      inputs:
        annotation: Union[str, List[int], tensorrt_llm.inputs.data.TextPrompt, tensorrt_llm.inputs.data.TokensPrompt]
        default: inspect._empty
      sampling_params:
        annotation: Optional[tensorrt_llm.sampling_params.SamplingParams]
        default: null
      lora_request:
        annotation: Optional[tensorrt_llm.executor.request.LoRARequest]
        default: null
      prompt_adapter_request:
        annotation: Optional[tensorrt_llm.executor.request.PromptAdapterRequest]
        default: null
      streaming:
        annotation: bool
        default: false
    return_annotation: tensorrt_llm.llmapi.llm.RequestOutput
properties:
  tokenizer:
    annotation: Optional[tensorrt_llm.llmapi.tokenizer.TokenizerBase]
    default: inspect._empty
