| Name | llm-jina-api JSON |
| Version |
0.1a0
JSON |
| download |
| home_page | None |
| Summary | Access Jina AI embeddings via their API |
| upload_time | 2024-09-20 06:25:15 |
| maintainer | None |
| docs_url | None |
| author | Simon Willison |
| requires_python | None |
| license | Apache-2.0 |
| keywords |
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# llm-jina-api
[](https://pypi.org/project/llm-jina-api/)
[](https://github.com/simonw/llm-jina-api/releases)
[](https://github.com/simonw/llm-jina-api/actions/workflows/test.yml)
[](https://github.com/simonw/llm-jina-api/blob/main/LICENSE)
Access Jina AI embeddings via their API
## Installation
Install this plugin in the same environment as [LLM](https://llm.datasette.io/).
```bash
llm install llm-jina-api
```
## Usage
The plugin adds an embedding model called `jina-clip-v1-api`. You'll need to set [an API key](https://jina.ai/embeddings/) first:
```bash
llm keys set jina
# paste API key here
```
Follow the [LLM documentation](https://llm.datasette.io/en/stable/embeddings/cli.html) using `jina-clip-v1-api` as the model name. For example:
```bash
llm embed -m jina-clip-v1-api -c 'pelican'
# To embed an image file:
llm embed --binary -m jina-clip-v1-api -i pelican.jpg
```
## Development
To set up this plugin locally, first checkout the code. Then create a new virtual environment:
```bash
cd llm-jina-api
python -m venv venv
source venv/bin/activate
```
Now install the dependencies and test dependencies:
```bash
llm install -e '.[test]'
```
To run the tests:
```bash
python -m pytest
```
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