| Name | llm-azure JSON |
| Version |
1.0
JSON |
| download |
| home_page | None |
| Summary | Azure plugin for LLM using the AzureOpenAI class |
| upload_time | 2025-02-07 12:23:41 |
| maintainer | None |
| docs_url | None |
| author | Fabian Geiger |
| 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-azure
[](https://pypi.org/project/llm-azure/)
[](https://github.com/fabge/llm-azure/releases)
[](https://github.com/fabge/llm-azure/blob/main/LICENSE)
LLM access to the Azure OpenAI SDK
## Installation
Install this plugin in the same environment as [LLM](https://llm.datasette.io/).
```bash
llm install llm-azure
```
## Usage
First, set an API key for Azure OpenAI:
```bash
llm keys set azure
# Paste key here
```
To add the `gpt-4-32k` chat model, and embedding model `text-embedding-3-small` deployed in your Azure Subscription, add this to your `azure/config.yaml` file:
```yaml
- model_id: gpt-4-32k
model_name: gpt-4-32k
api_base: https://your_deployment.openai.azure.com/
api_version: '2023-05-15'
- model_id: text-embedding-3-small
embedding_model: true
model_name: text-embedding-3-small
api_base: https://your_deployment.openai.azure.com/
api_version: '2023-05-14'
```
the configuration file should be in the `azure` directory in the config of your `llm` installation.
Run this command to find the directory in which this file should be created:
```bash
dirname "$(llm logs path)"
```
The `model_id` is the name LLM will use for the model. The `model_name` is the name which needs to be passed to the API - this might differ from the `model_id`, especially if `model_id` could potentially clash with other installed models.
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