BaseLanguageModel

Whether to cache the response.

• If True, will use the global cache.
• If False, will not use a cache
• If None, will use the global cache if it's set, otherwise no cache.
• If instance of BaseCache, will use the provided cache.

Caching is not currently supported for streaming methods of models.

Whether to print out response text.

Callbacks to add to the run trace.

Tags to add to the run trace.

Metadata to add to the run trace.

Optional encoder to use for counting tokens.

Get the input type for this Runnable.

If verbose is None, set it.

This allows users to pass in None as verbose to access the global setting.

Pass a sequence of prompts to the model and return model generations.

This method should make use of batched calls for models that expose a batched API.

Use this method when you want to:

1. Take advantage of batched calls,
2. Need more output from the model than just the top generated value,
3. Are building chains that are agnostic to the underlying language model type (e.g., pure text completion models vs chat models).

Asynchronously pass a sequence of prompts and return model generations.

This method should make use of batched calls for models that expose a batched API.

Use this method when you want to:

1. Take advantage of batched calls,
2. Need more output from the model than just the top generated value,
3. Are building chains that are agnostic to the underlying language model type (e.g., pure text completion models vs chat models).

Not implemented on this class.

Return the ordered IDs of the tokens in a text.

Get the number of tokens present in the text.

Useful for checking if an input fits in a model's context window.

This should be overridden by model-specific implementations to provide accurate token counts via model-specific tokenizers.

Get the number of tokens in the messages.

Useful for checking if an input fits in a model's context window.

This should be overridden by model-specific implementations to provide accurate token counts via model-specific tokenizers.