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feat: Add configurable Bedrock retry parameters (#4316)

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Signed-off-by: Dan Wuensch <dan.wuensch@ncino.com>
Co-authored-by: angiejones <jones.angie@gmail.com>
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Dan Wuensch
2025-09-04 12:26:29 -04:00
committed by GitHub
parent 429aeffc77
commit 627696a68a
4 changed files with 98 additions and 6 deletions
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documentation/docs/getting-started/providers.md
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@@ -21,11 +21,11 @@ Goose is compatible with a wide range of LLM providers, allowing you to choose a
| Provider | Description | Parameters |
|-----------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| [Amazon Bedrock](https://aws.amazon.com/bedrock/) | Offers a variety of foundation models, including Claude, Jurassic-2, and others. **AWS environment variables must be set in advance, not configured through `goose configure`** | `AWS_PROFILE`, or `AWS_ACCESS_KEY_ID`, `AWS_SECRET_ACCESS_KEY`, `AWS_REGION`, ... |
| [Amazon Bedrock](https://aws.amazon.com/bedrock/) | Offers a variety of foundation models, including Claude, Jurassic-2, and others. **AWS environment variables must be set in advance, not configured through `goose configure`** | `AWS_PROFILE`, or `AWS_ACCESS_KEY_ID`, `AWS_SECRET_ACCESS_KEY`, `AWS_REGION` |
| [Amazon SageMaker TGI](https://docs.aws.amazon.com/sagemaker/latest/dg/realtime-endpoints.html) | Run Text Generation Inference models through Amazon SageMaker endpoints. **AWS credentials must be configured in advance.** | `SAGEMAKER_ENDPOINT_NAME`, `AWS_REGION` (optional), `AWS_PROFILE` (optional) |
| [Anthropic](https://www.anthropic.com/) | Offers Claude, an advanced AI model for natural language tasks. | `ANTHROPIC_API_KEY`, `ANTHROPIC_HOST` (optional) |
| [Azure OpenAI](https://learn.microsoft.com/en-us/azure/ai-services/openai/) | Access Azure-hosted OpenAI models, including GPT-4 and GPT-3.5. Supports both API key and Azure credential chain authentication. | `AZURE_OPENAI_ENDPOINT`, `AZURE_OPENAI_DEPLOYMENT_NAME`, `AZURE_OPENAI_API_KEY` (optional) |
| [Databricks](https://www.databricks.com/) | Unified data analytics and AI platform for building and deploying models. | `DATABRICKS_HOST`, `DATABRICKS_TOKEN` |
| [Databricks](https://www.databricks.com/) | Unified data analytics and AI platform for building and deploying models. | `DATABRICKS_HOST`, `DATABRICKS_TOKEN` |
| [Docker Model Runner](https://docs.docker.com/ai/model-runner/) | Local models running in Docker Desktop or Docker CE with OpenAI-compatible API endpoints. **Because this provider runs locally, you must first [download a model](#local-llms).** | `OPENAI_HOST`, `OPENAI_BASE_PATH` |
| [Gemini](https://ai.google.dev/gemini-api/docs) | Advanced LLMs by Google with multimodal capabilities (text, images). | `GOOGLE_API_KEY` |
| [GCP Vertex AI](https://cloud.google.com/vertex-ai) | Google Cloud's Vertex AI platform, supporting Gemini and Claude models. **Credentials must be [configured in advance](https://cloud.google.com/vertex-ai/docs/authentication).** | `GCP_PROJECT_ID`, `GCP_LOCATION` and optionally `GCP_MAX_RATE_LIMIT_RETRIES` (5), `GCP_MAX_OVERLOADED_RETRIES` (5), `GCP_INITIAL_RETRY_INTERVAL_MS` (5000), `GCP_BACKOFF_MULTIPLIER` (2.0), `GCP_MAX_RETRY_INTERVAL_MS` (320_000). |