Submodule bindings for vllm.logits_process.
Version
- Requested: 0.14.0
- Observed at generation: 0.14.0
Runtime Options
All functions accept a __runtime__ option for controlling execution behavior:
Vllm.LogitsProcess.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.LogitsProcess.predict(data, __runtime__: [timeout_profile: :ml_inference])
# Or explicit timeout
Vllm.LogitsProcess.predict(data, __runtime__: [timeout: 600_000])
# Route to a pool and enforce strict affinity
Vllm.LogitsProcess.predict(data, __runtime__: [pool_name: :strict_pool, affinity: :strict_queue])See SnakeBridge.Defaults for global timeout configuration.
Summary
Functions
Python binding for vllm.logits_process.get_bad_words_logits_processors.
Python module attribute vllm.logits_process.LogitsProcessor.
Functions
@spec get_bad_words_logits_processors([String.t()], term(), keyword()) :: {:ok, [term()]} | {:error, Snakepit.Error.t()}
Python binding for vllm.logits_process.get_bad_words_logits_processors.
Parameters
bad_words(list(String.t()))tokenizer(term())
Returns
list(term())
@spec logits_processor() :: {:ok, term()} | {:error, Snakepit.Error.t()}
Python module attribute vllm.logits_process.LogitsProcessor.
Returns
term()