Submodule bindings for vllm.beam_search.
Version
- Requested: 0.14.0
- Observed at generation: 0.14.0
Runtime Options
All functions accept a __runtime__ option for controlling execution behavior:
Vllm.BeamSearch.some_function(args, __runtime__: [timeout: 120_000])Supported runtime options
:timeout- Call timeout in milliseconds (default: 120,000ms / 2 minutes):timeout_profile- Use a named profile (:default,:ml_inference,:batch_job,:streaming):stream_timeout- Timeout for streaming operations (default: 1,800,000ms / 30 minutes):session_id- Override the session ID for this call:pool_name- Target a specific Snakepit pool (multi-pool setups):affinity- Override session affinity (:hint,:strict_queue,:strict_fail_fast)
Timeout Profiles
:default- 2 minute timeout for regular calls:ml_inference- 10 minute timeout for ML/LLM workloads:batch_job- Unlimited timeout for long-running jobs:streaming- 2 minute timeout, 30 minute stream_timeout
Example with timeout override
# For a long-running ML inference call
Vllm.BeamSearch.predict(data, __runtime__: [timeout_profile: :ml_inference])
# Or explicit timeout
Vllm.BeamSearch.predict(data, __runtime__: [timeout: 600_000])
# Route to a pool and enforce strict affinity
Vllm.BeamSearch.predict(data, __runtime__: [pool_name: :strict_pool, affinity: :strict_queue])See SnakeBridge.Defaults for global timeout configuration.
Summary
Functions
Python binding for vllm.beam_search.create_sort_beams_key_function.
Calculate the beam search score with length penalty.
Python binding for vllm.beam_search.MultiModalDataDict.
Functions
@spec create_sort_beams_key_function(integer(), float(), keyword()) :: {:ok, term()} | {:error, Snakepit.Error.t()}
Python binding for vllm.beam_search.create_sort_beams_key_function.
Parameters
eos_token_id(integer())length_penalty(float())
Returns
term()
@spec get_beam_search_score([integer()], float(), integer()) :: {:ok, float()} | {:error, Snakepit.Error.t()}
Calculate the beam search score with length penalty.
Adapted from
Parameters
tokens(list(integer()))cumulative_logprob(float())eos_token_id(integer())length_penalty(float() default: 1.0)
Returns
float()
@spec multi_modal_data_dict() :: {:ok, term()} | {:error, Snakepit.Error.t()}
Python binding for vllm.beam_search.MultiModalDataDict.
Returns
term()
@spec multi_modal_data_dict(keyword()) :: {:ok, term()} | {:error, Snakepit.Error.t()}
@spec multi_modal_data_dict(term()) :: {:ok, term()} | {:error, Snakepit.Error.t()}
@spec multi_modal_data_dict( term(), keyword() ) :: {:ok, term()} | {:error, Snakepit.Error.t()}
@spec multi_modal_data_dict(term(), term()) :: {:ok, term()} | {:error, Snakepit.Error.t()}
@spec multi_modal_data_dict(term(), term(), keyword()) :: {:ok, term()} | {:error, Snakepit.Error.t()}
@spec multi_modal_data_dict(term(), term(), term()) :: {:ok, term()} | {:error, Snakepit.Error.t()}