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feat(llm): add Amazon Bedrock as a first-class provider

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Bedrock uses the Converse API (langchain-aws) and the AWS credential chain, so
it has its own client like Anthropic/Google rather than the OpenAI-compatible
registry. langchain-aws is an optional dependency (pip install ".[bedrock]"),
lazy-imported with a clear install hint; importing the package never requires
it. The model name is a Bedrock model ID / inference profile ID.
This commit is contained in:
Yijia-Xiao
2026-06-14 04:24:54 +00:00
parent 295e84cd54
commit 895ed130f9
10 changed files with 139 additions and 2 deletions
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README.md
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@@ -153,7 +153,9 @@ export OPENROUTER_API_KEY=... # OpenRouter
export ALPHA_VANTAGE_API_KEY=... # Alpha Vantage
```
For enterprise providers (e.g. Azure OpenAI, AWS Bedrock), copy `.env.enterprise.example` to `.env.enterprise` and fill in your credentials.
For Azure OpenAI, copy `.env.enterprise.example` to `.env.enterprise` and fill in your credentials.
For AWS Bedrock, install the extra with `pip install ".[bedrock]"`, set `llm_provider: "bedrock"`, configure AWS credentials (environment variables, `~/.aws/credentials`, or an IAM role) and `AWS_DEFAULT_REGION`, and use a Bedrock model ID, e.g. `us.anthropic.claude-opus-4-8-v1:0`.
For local models, configure Ollama with `llm_provider: "ollama"`. The default endpoint is `http://localhost:11434/v1`; set `OLLAMA_BASE_URL` to point at a remote `ollama-serve`. Pull models with `ollama pull <name>`, and pick "Custom model ID" in the CLI for any model not listed by default.