feat: Add configurable Bedrock retry parameters

crates/goose/src/providers/bedrock.rs

@@ -2,7 +2,7 @@ use std::collections::HashMap;
 
 use super::base::{ConfigKey, Provider, ProviderMetadata, ProviderUsage};
 use super::errors::ProviderError;
-use super::retry::ProviderRetry;
+use super::retry::{ProviderRetry, RetryConfig};
 use crate::conversation::message::Message;
 use crate::impl_provider_default;
 use crate::model::ModelConfig;
@@ -23,17 +23,28 @@ use super::formats::bedrock::{
 pub const BEDROCK_DOC_LINK: &str =
     "https://docs.aws.amazon.com/bedrock/latest/userguide/models-supported.html";
 
-pub const BEDROCK_DEFAULT_MODEL: &str = "anthropic.claude-3-5-sonnet-20240620-v1:0";
+pub const BEDROCK_DEFAULT_MODEL: &str = "anthropic.claude-sonnet-4-20250514-v1:0";
 pub const BEDROCK_KNOWN_MODELS: &[&str] = &[
     "anthropic.claude-3-5-sonnet-20240620-v1:0",
     "anthropic.claude-3-5-sonnet-20241022-v2:0",
+    "anthropic.claude-3-7-sonnet-20250219-v1:0",
+    "anthropic.claude-sonnet-4-20250514-v1:0",
+    "anthropic.claude-opus-4-20250514-v1:0",
+    "anthropic.claude-opus-4-1-20250805-v1:0"
 ];
 
+pub const BEDROCK_DEFAULT_MAX_RETRIES: usize = 6;
+pub const BEDROCK_DEFAULT_INITIAL_RETRY_INTERVAL_MS: u64 = 2000;
+pub const BEDROCK_DEFAULT_BACKOFF_MULTIPLIER: f64 = 2.0;
+pub const BEDROCK_DEFAULT_MAX_RETRY_INTERVAL_MS: u64 = 120_000;
+
 #[derive(Debug, serde::Serialize)]
 pub struct BedrockProvider {
     #[serde(skip)]
     client: Client,
     model: ModelConfig,
+    #[serde(skip)]
+    retry_config: RetryConfig,
 }
 
 impl BedrockProvider {
@@ -65,7 +76,38 @@ impl BedrockProvider {
         )?;
         let client = Client::new(&sdk_config);
 
-        Ok(Self { client, model })
+        let retry_config = Self::load_retry_config(config);
+
+        Ok(Self {
+            client,
+            model,
+            retry_config,
+        })
+    }
+
+    fn load_retry_config(config: &crate::config::Config) -> RetryConfig {
+        let max_retries = config
+            .get_param::<usize>("BEDROCK_MAX_RETRIES")
+            .unwrap_or(BEDROCK_DEFAULT_MAX_RETRIES);
+
+        let initial_interval_ms = config
+            .get_param::<u64>("BEDROCK_INITIAL_RETRY_INTERVAL_MS")
+            .unwrap_or(BEDROCK_DEFAULT_INITIAL_RETRY_INTERVAL_MS);
+
+        let backoff_multiplier = config
+            .get_param::<f64>("BEDROCK_BACKOFF_MULTIPLIER")
+            .unwrap_or(BEDROCK_DEFAULT_BACKOFF_MULTIPLIER);
+
+        let max_interval_ms = config
+            .get_param::<u64>("BEDROCK_MAX_RETRY_INTERVAL_MS")
+            .unwrap_or(BEDROCK_DEFAULT_MAX_RETRY_INTERVAL_MS);
+
+        RetryConfig {
+            max_retries,
+            initial_interval_ms,
+            backoff_multiplier,
+            max_interval_ms,
+        }
     }
 
     async fn converse(
@@ -147,6 +189,10 @@ impl Provider for BedrockProvider {
         )
     }
 
+    fn retry_config(&self) -> RetryConfig {
+        self.retry_config.clone()
+    }
+
     fn get_model_config(&self) -> ModelConfig {
         self.model.clone()
     }

crates/goose/src/providers/retry.rs

@@ -114,4 +114,9 @@ pub trait ProviderRetry {
     }
 }
 
-impl<P: Provider> ProviderRetry for P {}
+// Let specific providers define their retry config if desired
+impl<P: Provider> ProviderRetry for P {
+    fn retry_config(&self) -> RetryConfig {
+        Provider::retry_config(self)
+    }
+}

documentation/docs/getting-started/providers.md

@@ -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`, ... and optionally `BEDROCK_MAX_RETRIES` (6), `BEDROCK_INITIAL_RETRY_INTERVAL_MS` (2000), `BEDROCK_BACKOFF_MULTIPLIER` (2.0), `BEDROCK_MAX_RETRY_INTERVAL_MS` (120000)                                                                                                   |
 | [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` and optionally `DATABRICKS_MAX_RETRIES` (3), `DATABRICKS_INITIAL_RETRY_INTERVAL_MS` (1000), `DATABRICKS_BACKOFF_MULTIPLIER` (2.0), `DATABRICKS_MAX_RETRY_INTERVAL_MS` (30000)                                                                                                                                               |
 | [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). |