UpdateProvider RPC was doing full replacement of credentials and config
maps, silently destroying data on partial updates. This changes the
semantics so empty maps preserve existing values, non-empty maps merge
(upsert), and empty-string values delete individual keys. Also makes
provider type immutable after creation and adds field validation on
update.
Closes#199
Co-authored-by: John Myers <johntmyers@users.noreply.github.com>
Closes#67
## Summary
Implements transparent inference interception and routing for sandboxed AI agents. The sandbox proxy intercepts outbound AI SDK calls (OpenAI, Anthropic) and reroutes them through the gateway to policy-controlled backends — enabling organizations to redirect inference traffic to local or self-hosted models without modifying agent code.
**Decision model** — a tri-state OPA evaluation for every CONNECT request:
1. Binary + endpoint explicitly allowed in `network_policies` → **allow** (pass through)
2. Not explicitly allowed + `inference.allowed_routes` configured → **inspect for inference** (TLS intercept, detect API patterns, route through gateway)
3. Otherwise → **deny**
No endpoint declarations or binary lists needed for inference routing. Just configure `inference.allowed_routes`.
## Key Changes
### Sandbox (interception)
- **OPA policy**: New `network_action` Rego rule with three outcomes (`allow`, `inspect_for_inference`, `deny`). New `NetworkAction` enum replaces `PolicyDecision.allowed` bool for the proxy's main decision path.
- **Proxy**: New `InspectForInference` path — TLS-terminates client, parses HTTP, detects inference API patterns (`POST /v1/chat/completions`, `/v1/completions`, `/v1/messages`), strips auth headers, forwards via gRPC.
- **New module**: `l7/inference.rs` — `InferenceApiPattern`, `detect_inference_pattern()`, HTTP request/response parsing.
- **gRPC client**: New `proxy_inference()` for sandbox→gateway forwarding.
- **Sandbox init**: Creates OPA engine when inference is configured, even without `network_policies`.
### Gateway (dispatch)
- **InferenceService**: `ProxyInference` RPC loads sandbox policy, resolves allowed routes, dispatches to router. Full CRUD for inference routes.
- **Proto**: `InferenceRoute`, `InferenceRouteSpec`, `ProxyInferenceRequest/Response`, Inference gRPC service.
### Router (backend proxying)
- **New crate**: `navigator-router` with `Router`, `proxy_with_candidates()`, protocol-based route selection, backend HTTP proxying with auth header rewriting.
- **Mock support** for testing (`mock://` scheme).
### CLI
- `nav inference create/update/delete/list` commands for route management.
### Python SDK
- Updated protobuf bindings. Removed old `inference.py` client (replaced by transparent interception).
### Documentation
- New `architecture/inference-routing.md` — end-to-end system documentation.
- Updated `architecture/sandbox.md` — proxy, OPA, and source index sections.
- Updated `architecture/README.md` — new subsystem overview and diagram.
## Addendum: Chunked Transfer Compatibility
This branch now also fixes intercepted SDK requests that send chunked request bodies:
- `inspect_for_inference` now accepts `Transfer-Encoding: chunked` and decodes chunked request bodies before forwarding to the gateway
- Removed the prior `411 Length Required` response for chunked intercepted requests
- Added request/response header sanitization for framing and hop-by-hop headers (`content-length`, `transfer-encoding`, `connection`, etc.) to keep forwarded requests and returned responses valid
- Added unit tests for chunked parsing and header sanitization
Note: this improves compatibility for streaming-style SDK request patterns; true token-by-token passthrough response streaming is still a separate follow-up.
## Minimal Policy for Inference Routing
```yaml
inference:
allowed_routes:
- local
```
Any outgoing connection from a binary not explicitly allowed in `network_policies` will be intercepted and checked for inference API patterns.
## Test Plan
- [x] `cargo test --workspace` — all tests pass
- [x] `mise run pre-commit` — all checks pass
- [x] E2E: OpenAI chat completions routed through gateway
- [x] E2E: Anthropic messages routed through gateway
- [x] E2E: Python OpenAI SDK from sandbox (`examples/inference/inference.py`)
- [x] E2E test: `e2e/python/test_inference_routing.py`
## Summary
- Add `GetSandboxProviderEnvironment` gRPC endpoint so the sandbox supervisor can fetch provider credentials at runtime instead of embedding them in the pod spec
- Sandbox supervisor (`navigator-sandbox`) fetches credentials on startup and injects them as environment variables into both entrypoint processes and SSH shell sessions via `Command::env()`
- Remove credential injection from sandbox creation-time pod spec in `navigator-server`
- Update `architecture/providers.md` to document the full runtime credential injection flow, discovery engine details, trait definitions, and end-to-end diagram
## Changes
- **proto**: Add `GetSandboxProviderEnvironment` RPC and request/response messages, add `providers` field to `SandboxSpec`
- **navigator-server**: Implement `GetSandboxProviderEnvironment` handler and `resolve_provider_environment()` with env var key validation and first-wins dedup; remove old creation-time credential injection from `sandbox/mod.rs`
- **navigator-sandbox**: Fetch provider env via gRPC on startup (`grpc_client.rs`), thread `provider_env` HashMap through to `process.rs` (entrypoint) and `ssh.rs` (shell sessions), inject via `cmd.env()`
- **navigator-cli**: Adjust sandbox create flow to set provider names in `SandboxSpec.providers`
- **e2e**: Add `test_sandbox_providers.py` end-to-end tests
- **docs**: Rewrite `architecture/providers.md` with implementation details
## Test Plan
- Unit tests for `resolve_provider_environment` in `grpc.rs`
- Integration tests updated in `provider_commands_integration.rs`, `mtls_integration.rs`, `multiplex_integration.rs`, `multiplex_tls_integration.rs`
- New e2e test suite `test_sandbox_providers.py`