Per-call options for ChatOpenRouter.
interface ChatOpenRouterCallOptionsCallbacks for this call and any sub-calls (eg. a Chain calling an LLM). Tags are passed to all callbacks, metadata is passed to handle*Start callbacks.
Runtime values for attributes previously made configurable on this Runnable, or sub-Runnables.
Additive penalty based on how often a token has appeared so far (−2 to 2).
Token-level biases to apply during sampling.
Describes the format of structured outputs. This should be provided if an output is considered to be structured
Maximum number of parallel calls to make.
Maximum number of tokens to generate.
Minimum probability threshold for token sampling.
OpenRouter-specific list of models for routing.
Version of AIMessage output format to store in message content.
AIMessage.contentBlocks will lazily parse the contents of content into a
standard format. This flag can be used to additionally store the standard format
as the message content, e.g., for serialization purposes.
.contentBlocks).contentBlocks)You can also set LC_OUTPUT_VERSION as an environment variable to "v1" to
enable this by default.
OpenRouter plugins to enable (e.g. web search).
Predicted output content for latency optimization.
Additive penalty based on whether a token has appeared at all (−2 to 2).
OpenRouter-specific provider preferences and ordering.
Maximum number of times a call can recurse. If not provided, defaults to 25.
Multiplicative penalty applied to repeated token logits (0 to 2).
Response format constraint (text, JSON object, or JSON schema).
OpenRouter-specific routing strategy.
Unique identifier for the tracer run for this call. If not provided, a new UUID will be generated.
Name for the tracer run for this call. Defaults to the name of the class.
Random seed for deterministic generation.
Abort signal to cancel the request.
Stop tokens to use for this call. If not provided, the default stop tokens for the model will be used.
Whether tool schemas should use strict mode.
Sampling temperature (0–2).
Timeout for this call in milliseconds.
Specifies how the chat model should use tools.
Tool definitions to bind for this call.
Top-A sampling threshold.
Top-K sampling: only consider the K most likely tokens.
Number of most-likely log-probabilities to return per token.
Nucleus sampling cutoff probability.
OpenRouter-specific transformations to apply to the request.
Stable identifier for end-users, used for abuse detection.
Additive penalty based on how often a token has appeared so far (−2 to 2).
Token-level biases to apply during sampling.
Maximum number of tokens to generate.
Minimum probability threshold for token sampling.
Additive penalty based on whether a token has appeared at all (−2 to 2).
Multiplicative penalty applied to repeated token logits (0 to 2).
Top-A sampling threshold.
Top-K sampling: only consider the K most likely tokens.
Number of most-likely log-probabilities to return per token.
Nucleus sampling cutoff probability.
OpenRouter-specific transformations to apply to the request.