feat: add OrcaRouter embedding provider

[kuswardhanietidims-svg]

Adds OrcaRouter as a first-class embedding provider, so code-review-graph users can switch to --provider orcarouter and embed with any model OrcaRouter routes — no anonymous CRG_OPENAI_BASE_URL needed.

OrcaRouter is an OpenAI-compatible AI gateway built for both models and agents. Like OpenRouter, it exposes a provider/model namespace across many models — but it also combines adaptive routing, automatic failover, zero-markup inference, observability, guardrails, and agent-tool governance behind the same endpoint. Adding orcarouter as a first-class provider means this project's users can use that stack directly, without treating OrcaRouter as an anonymous custom base URL. It also runs gateway-level, zero-trust security for AI agents on the same endpoint — screening every prompt/response and governing every tool call on a default-deny basis, with no application code changes.

This mirrors the existing Voyage AI integration: a dedicated provider class with an endpoint-aware name identity, a get_provider branch that reads ORCAROUTER_API_KEY (default endpoint https://api.orcarouter.ai/v1, default model openai/text-embedding-3-small), CLI provider choices, README env-var table, and docstrings. Since OrcaRouter serves OpenAI-compatible /v1/embeddings, the provider reuses the existing OpenAI-compatible wire path (retries, dimension pinning, batch size).

Verified locally: ruff check, mypy, and the full test suite pass (2991 passed, 9 skipped). Live test against https://api.orcarouter.ai/v1/embeddings with a real key returned 1536-dim vectors for both embed() and embed_query().

Discord: discord.gg/YEubt8enRA · X: https://x.com/OrcaRouter

I'm an engineer on the OrcaRouter team.

[github-actions]

code-review-graph review

Overall risk: 0.65 (MEDIUM) — 20 changed function(s)/class(es), 48 affected flow(s), 10 test gap(s)

Risk-scored changes

Risk	Level	Symbol	Location	Tested
0.65	medium	code_review_graph/cli.py::_add_embedding_refresh_args	code_review_graph/cli.py:472	no
0.60	medium	code_review_graph/embeddings.py::OrcaRouterEmbeddingProvider	code_review_graph/embeddings.py:828	no
0.55	medium	code_review_graph/cli.py::main	code_review_graph/cli.py:680	no
0.55	medium	code_review_graph/embeddings.py::get_provider	code_review_graph/embeddings.py:915	yes
0.54	medium	code_review_graph/main.py::semantic_search_nodes_tool	code_review_graph/main.py:331	no
0.50	medium	code_review_graph/main.py::embed_graph_tool	code_review_graph/main.py:370	no
0.30	low	code_review_graph/embeddings.py::OrcaRouterEmbeddingProvider.__init__	code_review_graph/embeddings.py:846	yes
0.30	low	code_review_graph/embeddings.py::OrcaRouterEmbeddingProvider.name	code_review_graph/embeddings.py:865	no
0.30	low	code_review_graph/tools/docs.py::embed_graph	code_review_graph/tools/docs.py:28	no
0.30	low	tests/test_tools.py::TestEmbedGraphProviderErrors	tests/test_tools.py:844	no

Affected execution flows

• embed_query — criticality 0.48, 2 node(s) across 1 file(s)
• embed_query — criticality 0.48, 2 node(s) across 1 file(s)
• embed_query — criticality 0.45, 3 node(s) across 1 file(s)
• embed_query — criticality 0.45, 3 node(s) across 1 file(s)
• embed_query — criticality 0.41, 2 node(s) across 1 file(s)
• ...and 43 more affected flow(s)

Test gaps

• code_review_graph/cli.py::_add_embedding_refresh_args (code_review_graph/cli.py:472)
• code_review_graph/cli.py::main (code_review_graph/cli.py:680)
• code_review_graph/embeddings.py::OrcaRouterEmbeddingProvider (code_review_graph/embeddings.py:828)
• code_review_graph/embeddings.py::OrcaRouterEmbeddingProvider.name (code_review_graph/embeddings.py:865)
• code_review_graph/main.py::semantic_search_nodes_tool (code_review_graph/main.py:331)
• ...and 5 more without direct tests

Token savings: this graph-backed report used ~95,386 fewer tokens (~85%) than reading every changed file in full (estimated, chars/4 approximation).

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Powered by code-review-graph — local-first analysis; no code leaves the CI runner.

[tirth8205]

Thanks for a clean, well-formed patch — it passes every gate, the key never leaves the Authorization header, the unset-key path raises properly, and you did remember docs/LEGAL.md and the FAQ, which contributors usually miss. I'm still going to decline it, and I want to show you exactly why rather than wave it off.

OrcaRouterEmbeddingProvider subclasses OpenAIEmbeddingProvider and inherits _call_api, embed, embed_query and dimension unchanged. Its own members are three _DEFAULT_* constants, a copy of the parent's __init__, and a name property. I compared the two paths against a mocked transport, no network involved, and the requests are byte-identical:

URL     : https://api.orcarouter.ai/v1/embeddings   (both)
headers : Authorization: Bearer …                   (both, identical)
body    : {"model": "openai/text-embedding-3-small", "input": [...]}   (both)
timeout : 120 · dimension 1536 · batch 100          (both)
only difference: provider.name → "orcarouter:…" vs "openai:…"

Everything this adds is already reachable today, with no code change:

CRG_OPENAI_API_KEY=$ORCAROUTER_API_KEY \
CRG_OPENAI_BASE_URL=https://api.orcarouter.ai/v1 \
CRG_OPENAI_MODEL=openai/text-embedding-3-small \
CRG_ACCEPT_CLOUD_EMBEDDINGS=1 \
code-review-graph embed --provider openai

Vector-space isolation is already handled on that path: _make_host_key folds the host, scheme and path into provider.name, so switching base URLs forces a clean re-embed and cannot mix two vector spaces.

The Voyage provider is the precedent people reach for here, and it's the one that shows the test I apply. Voyage needed its own class because it genuinely cannot ride the OpenAI wire format — it sends input_type, output_dimension and output_dtype, and it needs _wait_for_rate_limit_slot() throttling. A provider that sends the same bytes doesn't clear that bar, and each extra class is permanent surface: your __init__ already duplicates the parent's body instead of calling super().__init__(...), so the day someone adds a field to OpenAIEmbeddingProvider, this subclass silently won't have it. Errors also come back labeled OpenAI API HTTP 401: … under --provider orcarouter, which is confusing for someone who never configured OpenAI.

What I'd take instead: a one-line addition to the README's existing OpenAI-compatible section, listing OrcaRouter beside new-api, LiteLLM and vLLM, with the configuration above. Same bytes on the wire for the user, zero new code paths, and OrcaRouter becomes discoverable to anyone reading the docs. If you'd like to rework this PR into that, I'll merge it.

One request if you do: keep the copy to what the code does. The PR description covers adaptive routing, failover, zero-trust prompt screening, observability and agent-tool governance — none of which relates to /v1/embeddings or appears in the 226 lines here. A factual line about an OpenAI-compatible embeddings endpoint is more likely to survive review in any project.

[kuswardhanietidims-svg]

Thanks — that's a fair bar, and you're right on every count. The provider sent byte-identical requests to the existing openai path (only provider.name differed, which _make_host_key already folds into vector-space isolation), so it added surface without adding capability. I've reworked the PR accordingly.

What changed:

• Removed OrcaRouterEmbeddingProvider and its get_provider/CLI/tool wiring; reverted all code and test changes back to base. The net diff is now README-only (+11 lines).
• README now lists OrcaRouter in the existing OpenAI-compatible section, beside new-api/LiteLLM/vLLM, with the openai-provider configuration you gave:

export CRG_OPENAI_BASE_URL=https://api.orcarouter.ai/v1
export CRG_OPENAI_API_KEY=$ORCAROUTER_API_KEY
export CRG_OPENAI_MODEL=openai/text-embedding-3-small
export CRG_ACCEPT_CLOUD_EMBEDDINGS=1
code-review-graph embed --provider openai

• Dropped the __init__ duplication concern entirely — there's no subclass left.
• Trimmed the PR description to just the endpoint fact; the gateway marketing is gone.

One note so it doesn't look like a regression: embed --provider openai already exists today, so the config above is genuinely a docs-only change — no new code paths, no error-label confusion, no drift from OpenAIEmbeddingProvider.

If this shape works, happy to adjust wording or placement.

[tirth8205]

Outside this sweep's mission of verified coding-session token savings: the current net diff is README-only endpoint documentation. The provider implementation was removed in the later commit, so there is no runtime change left to retain.

[tirth8205]

This no longer merges into staging. Conflicts in README.md.

git fetch origin && git merge origin/staging
# resolve, then
uv run pytest tests/ -q
uv run ruff check code_review_graph/
uv run mypy code_review_graph/ --ignore-missing-imports --no-strict-optional
git push

When resolving:

• Rebase onto current origin/staging to resolve the README.md conflict.
• Update the PR description to match the diff (it still describes a provider class, get_provider branch, CLI choices and env-var table that are not in the diff).

A large integration branch landed on staging today, which is why this drifted.

PRs now target staging, not main. Yours was retargeted already, so nothing to do there.

[tirth8205]

This no longer merges into staging. The one conflict is README.md, and the branch is 226 commits behind.

All of it is prose, so taking staging's text and re-applying your lines on top should be the whole job.

git fetch origin
git merge origin/staging
# resolve, then
uv run pytest tests/ -q
uv run ruff check code_review_graph/
uv run mypy code_review_graph/ --ignore-missing-imports --no-strict-optional
git push

I have not reviewed the change itself yet. That comes once it merges and the checks run against the merged state, since staging has moved a long way and the result is what matters.