0.19.1

• FIxed bug where llm.get_models() and llm.get_async_models() returned the same model multiple times. #667

0.19

• Tokens used by a response are now logged to new input_tokens and output_tokens integer columns and a token_details JSON string column, for the default OpenAI models and models from other plugins that implement this feature. #610
• llm prompt now takes a -u/--usage flag to display token usage at the end of the response.
• llm logs -u/--usage shows token usage information for logged responses.
• llm prompt ... --async responses are now logged to the database. #641
• llm.get_models() and llm.get_async_models() functions, documented here. #640
• response.usage() and async response await response.usage() methods, returning a Usage(input=2, output=1, details=None) dataclass. #644
• response.on_done(callback) and await response.on_done(callback) methods for specifying a callback to be executed when a response has completed, documented here. #653
• Fix for bug running llm chat on Windows 11. Thanks, Sukhbinder Singh. #495

0.19a2

• llm.get_models() and llm.get_async_models() functions, documented here. #640

0.19a1

• response.usage() and async response await response.usage() methods, returning a Usage(input=2, output=1, details=None) dataclass. #644

0.19a0

• Tokens used by a response are now logged to new input_tokens and output_tokens integer columns and a token_details JSON string column, for the default OpenAI models and models from other plugins that implement this feature. #610
• llm prompt now takes a -u/--usage flag to display token usage at the end of the response.
• llm logs -u/--usage shows token usage information for logged responses.
• llm prompt ... --async responses are now logged to the database. #641

0.18

• Initial support for async models. Plugins can now provide an AsyncModel subclass that can be accessed in the Python API using the new llm.get_async_model(model_id) method. See async models in the Python API docs and implementing async models in plugins. #507
• OpenAI models all now include async models, so function calls such as llm.get_async_model("gpt-4o-mini") will return an async model.
• gpt-4o-audio-preview model can be used to send audio attachments to the GPT-4o audio model. #608
• Attachments can now be sent without requiring a prompt. #611
• llm models --options now includes information on whether a model supports attachments. #612
• llm models --async shows available async models.
• Custom OpenAI-compatible models can now be marked as can_stream: false in the YAML if they do not support streaming. Thanks, Chris Mungall. #600
• Fixed bug where OpenAI usage data was incorrectly serialized to JSON. #614
• Standardized on audio/wav MIME type for audio attachments rather than audio/wave. [#603](#603

0.18a1

• Fixed bug where conversations did not work for async OpenAI models. #632
• __repr__ methods for Response and AsyncResponse.

0.18a0

Alpha support for async models. #507

Multiple smaller changes.

0.17.1

• Fixed a bug where llm chat crashes if a follow-up prompt is provided. #601

0.17

Support for attachments, allowing multi-modal models to accept images, audio, video and other formats. #587

The default OpenAI gpt-4o and gpt-4o-mini models can both now be prompted with JPEG, GIF, PNG and WEBP images.

Attachments in the CLI can be URLs:

llm -m gpt-4o "describe this image" \
  -a https://static.simonwillison.net/static/2024/pelicans.jpg

Or file paths:

llm -m gpt-4o-mini "extract text" -a image1.jpg -a image2.jpg

Or binary data, which may need to use --attachment-type to specify the MIME type:

cat image | llm -m gpt-4o-mini "extract text" --attachment-type - image/jpeg

Attachments are also available in the Python API:

model = llm.get_model("gpt-4o-mini")
response = model.prompt(
    "Describe these images",
    attachments=[
        llm.Attachment(path="pelican.jpg"),
        llm.Attachment(url="https://static.simonwillison.net/static/2024/pelicans.jpg"),
    ]
)

Plugins that provide alternative models can support attachments, see Attachments for multi-modal models for details.

The latest llm-claude-3 plugin now supports attachments for Anthropic's Claude 3 and 3.5 models. The llm-gemini plugin supports attachments for Google's Gemini 1.5 models.

Also in this release: OpenAI models now record their "usage" data in the database even when the response was streamed. These records can be viewed using llm logs --json. #591