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# Changelog
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(v0_17a0)=
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## 0.17a0 (2024-10-28)
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Alpha support for **attachments**, allowing multi-modal models to accept images, audio, video and other formats. [#578](https://github.com/simonw/llm/issues/578)
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Attachments {ref}`in the CLI <usage-attachments>` can be URLs:
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```bash
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llm "describe this image" \
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-a https://static.simonwillison.net/static/2024/pelicans.jpg
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```
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Or file paths:
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```bash
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llm "extract text" -a image1.jpg -a image2.jpg
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```
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Or binary data, which may need to use `--attachment-type` to specify the MIME type:
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```bash
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cat image | llm "extract text" --attachment-type - image/jpeg
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```
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Attachments are also available {ref}`in the Python API <python-api-attachments>`:
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```python
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model = llm.get_model("gpt-4o-mini")
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response = model.prompt(
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"Describe these images",
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attachments=[
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llm.Attachment(path="pelican.jpg"),
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llm.Attachment(url="https://static.simonwillison.net/static/2024/pelicans.jpg"),
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]
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)
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```
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Plugins that provide alternative models can support attachments, see {ref}`advanced-model-plugins-attachments` for details.
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(v0_16)=
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## 0.16 (2024-09-12)
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@ -49,6 +49,9 @@ response = model.prompt(
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system="Answer like GlaDOS"
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)
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```
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(python-api-attachments)=
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### Attachments
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Model that accept multi-modal input (images, audio, video etc) can be passed attachments using the `attachments=` keyword argument. This accepts a list of `llm.Attachment()` instances.
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@ -45,6 +45,7 @@ Some models support options. You can pass these using `-o/--option name value` -
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```bash
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llm 'Ten names for cheesecakes' -o temperature 1.5
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```
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(usage-attachments)=
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### Attachments
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Some models are multi-modal, which means they can accept input in more than just text. GPT-4o and GPT-4o mini can accept images, and models such as Google Gemini 1.5 can accept audio and video as well.
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@ -56,7 +57,7 @@ llm "describe this image" -a https://static.simonwillison.net/static/2024/pelica
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```
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Attachments can be passed using URLs or file paths, and you can attach more than one attachment to a single prompt:
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```bash
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llm "describe these images" -a image1.jpg -a image2.jpg
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llm "extract text" -a image1.jpg -a image2.jpg
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```
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You can also pipe an attachment to LLM by using `-` as the filename:
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```bash
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2
setup.py
2
setup.py
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@ -1,7 +1,7 @@
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from setuptools import setup, find_packages
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import os
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VERSION = "0.16"
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VERSION = "0.17a0"
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def get_long_description():
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