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feat(llm): Amazon Bedrock provider over a standard-library SigV4 signer

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Kind `bedrock` speaks the Converse API for chat roles and InvokeModel for
Titan and Cohere embeddings. Requests are signed with AWS Signature
Version 4 implemented with crypto/hmac and crypto/sha256 only; the signer
is pinned by tests to signatures botocore produces for the same requests,
with and without a session token, so drift fails the build.

The credential is one secret reference, ACCESS_KEY_ID:SECRET_ACCESS_KEY
[:SESSION_TOKEN], encrypted together like every other provider key. The
region is read from the endpoint host, which must be a Bedrock runtime
host over HTTPS unless private endpoints are explicitly allowed; other
hosts are refused. Provider errors are scrubbed of the secret and token.

Migration 0024 widens the provider kind constraint; existing rows are
untouched and the down migration refuses while bedrock rows exist rather
than dropping configuration. UI kind selects, docs/llm-providers.md,
ADR-0010, ARCHITECTURE and the changelog are updated.
This commit is contained in:
Andy Dixon
2026-08-24 22:03:48 +01:00
parent 7d608c2783
commit f165adc5f2
14 changed files with 497 additions and 6 deletions
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docs/adr/0004-llm-abstraction.md
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@@ -7,7 +7,7 @@ Status: Accepted
Minds must survive provider changes; different tasks want different models; every call must be inspectable and replayable; secrets must not leak.
## Decision
`internal/llm` defines `LanguageModel` (`Complete(ctx, CognitiveRequest) (CognitiveResponse, error)`) and `Embedder`. Providers implement raw HTTP clients (OpenAI-compatible, Anthropic Messages, Ollama; Bedrock later behind the same interface). Provider rows in the database hold endpoint, model, parameters and a *secret reference*. **Roles** map cognitive tasks to a primary model and ordered fallbacks. A `Recorder` wrapper writes every request/response (prompt name+version, rendered messages, parameters, seed, model, usage, latency, estimated cost) and enforces budgets; a `Replayer` serves recorded responses during replay. Prompts are versioned rows rendered with structured inputs; untrusted text is enclosed in explicit data blocks.
`internal/llm` defines `LanguageModel` (`Complete(ctx, CognitiveRequest) (CognitiveResponse, error)`) and `Embedder`. Providers implement raw HTTP clients (OpenAI-compatible, Anthropic Messages, Ollama; Bedrock added in 0.2 behind the same interface with a standard-library SigV4 signer). Provider rows in the database hold endpoint, model, parameters and a *secret reference*. **Roles** map cognitive tasks to a primary model and ordered fallbacks. A `Recorder` wrapper writes every request/response (prompt name+version, rendered messages, parameters, seed, model, usage, latency, estimated cost) and enforces budgets; a `Replayer` serves recorded responses during replay. Prompts are versioned rows rendered with structured inputs; untrusted text is enclosed in explicit data blocks.
## Consequences
- Cognitive code depends only on roles; swapping vendors is configuration.