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Update default model reference from GPT-4 to o3-mini and improve model configuration docs

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mrT23
2025-04-01 08:15:09 +03:00
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docs/docs/usage-guide/changing_a_model.md
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@ -1,7 +1,7 @@
## Changing a model in PR-Agent ## Changing a model in PR-Agent
See [here](https://github.com/Codium-ai/pr-agent/blob/main/pr_agent/algo/__init__.py) for a list of available models. See [here](https://github.com/Codium-ai/pr-agent/blob/main/pr_agent/algo/__init__.py) for a list of available models.
To use a different model than the default (GPT-4), you need to edit in the [configuration file](https://github.com/Codium-ai/pr-agent/blob/main/pr_agent/settings/configuration.toml#L2) the fields: To use a different model than the default (o3-mini), you need to edit in the [configuration file](https://github.com/Codium-ai/pr-agent/blob/main/pr_agent/settings/configuration.toml#L2) the fields:
``` ```
[config] [config]
model = "..." model = "..."
@ -9,7 +9,10 @@ fallback_models = ["..."]
``` ```
For models and environments not from OpenAI, you might need to provide additional keys and other parameters. For models and environments not from OpenAI, you might need to provide additional keys and other parameters.
You can give parameters via a configuration file (see below for instructions), or from environment variables. See [litellm documentation](https://litellm.vercel.app/docs/proxy/quick_start#supported-llms) for the environment variables relevant per model. You can give parameters via a configuration file, or from environment variables.
!!! note "Model-specific environment variables"
See [litellm documentation](https://litellm.vercel.app/docs/proxy/quick_start#supported-llms) for the environment variables needed per model, as they may vary and change over time. Our documentation per-model may not always be up-to-date with the latest changes.
### Azure ### Azure
@ -158,25 +161,24 @@ And also set the api key in the .secrets.toml file:
KEY = "..." KEY = "..."
``` ```
See [litellm](https://docs.litellm.ai/docs/providers/anthropic#usage) documentation for more information about the environment variables required for Anthropic.
### Amazon Bedrock ### Amazon Bedrock
To use Amazon Bedrock and its foundational models, add the below configuration: To use Amazon Bedrock and its foundational models, add the below configuration:
``` ```
[config] # in configuration.toml [config] # in configuration.toml
model="bedrock/anthropic.claude-3-sonnet-20240229-v1:0" model="bedrock/anthropic.claude-3-5-sonnet-20240620-v1:0"
fallback_models=["bedrock/anthropic.claude-v2:1"] fallback_models=["bedrock/anthropic.claude-3-5-sonnet-20240620-v1:0"]
[aws]
AWS_ACCESS_KEY_ID="..."
AWS_SECRET_ACCESS_KEY="..."
AWS_REGION_NAME="..."
``` ```
Note that you have to add access to foundational models before using them. Please refer to [this document](https://docs.aws.amazon.com/bedrock/latest/userguide/setting-up.html) for more details. See [litellm](https://docs.litellm.ai/docs/providers/bedrock#usage) documentation for more information about the environment variables required for Amazon Bedrock.
If you are using the claude-3 model, please configure the following settings as there are parameters incompatible with claude-3.
```
[litellm]
drop_params = true
```
AWS session is automatically authenticated from your environment, but you can also explicitly set `AWS_ACCESS_KEY_ID`, `AWS_SECRET_ACCESS_KEY` and `AWS_REGION_NAME` environment variables. Please refer to [this document](https://litellm.vercel.app/docs/providers/bedrock) for more details.
### DeepSeek ### DeepSeek