test(recorded): add client cassette coverage (3/5)

[Pouyanpi]

Summary

Adds recorded client-level coverage for OpenAI chat and embeddings flows.

Why

Client cassette smoke tests validate that the harness can replay basic provider traffic before the rails API coverage layers on top.

What Changed

• Adds OpenAI chat cassette coverage.
• Adds OpenAI embeddings cassette coverage.
• Adds minimal configs used by the client tests.

Stack Position

Part 3 of 5.

• Previous: fix(llmrails): load library files deterministically (2/5) #1975
• Next: test(recorded): add rails public API coverage (4/5) #1977

Stack Context

This stack decomposes recorded end-to-end replay coverage into reviewable slices. The PRs should be reviewed against their parent branch in the stack.

Please review each PR against its parent branch, not directly against the root base branch, except for part 1.

Order	PR	Branch	Base
1	#1974	stack/recorded-tests-01-harness	develop
2	#1975	stack/recorded-tests-02-deterministic-library-load	stack/recorded-tests-01-harness
3	#1976	stack/recorded-tests-03-clients	stack/recorded-tests-02-deterministic-library-load
4	#1977	stack/recorded-tests-04-public-api	stack/recorded-tests-03-clients
5	#1978	stack/recorded-tests-05-library-rails	stack/recorded-tests-04-public-api

Validation

poetry check --lock
poetry lock --no-update
poetry install --with dev
poetry run pytest tests/recorded --block-network -q
pre-commit hooks passed during commit creation

[codecov]

Codecov Report

✅ All modified and coverable lines are covered by tests.

📢 Thoughts on this report? Let us know!

[greptile-apps]

Greptile Summary

This PR adds client-level cassette coverage for OpenAI chat and embeddings, forming part 3 of a 5-PR stack that decomposes recorded end-to-end replay coverage into reviewable slices. All cassettes are correctly sanitized (no secrets, volatile fields normalized) and the VCR fixture plumbing — cassette directory, body matcher, serializer — aligns with the harness established in earlier PRs.

• Chat test (test_openai_chat.py): async VCR test that constructs OpenAICompatibleClient with an externally-managed httpx.AsyncClient, calls generate_async, and validates the full result shape including request_id and usage tokens.
• Embeddings test (test_openai_embeddings.py): synchronous VCR test that instantiates OpenAIEmbeddingModel directly and asserts the decoded base64 embedding has the expected 1536-dimensional shape.
• Config stubs (openai_chat_config/, openai_embeddings_config/): minimal NeMo Guardrails configs added here but not yet loaded by any test in this PR slice — they appear to be pre-positioned for later PRs in the stack.

Confidence Score: 5/5

Safe to merge; the changes are additive test infrastructure with no modifications to production code.

The PR adds new recorded tests, cassettes, and config stubs. Cassettes are properly sanitized, fixture wiring (VCR cassette dir, body matcher, proxy stripping) is inherited correctly from the parent conftest, and both the async chat and sync embeddings paths are exercised end-to-end under network isolation.

The config stubs in openai_chat_config/ and openai_embeddings_config/ are not yet referenced by any test — worth confirming they will be wired up in a later PR in the stack before this stack lands.

Important Files Changed

Filename	Overview
tests/recorded/clients/init.py	Package init file with license header and docstring; no functional code.
tests/recorded/clients/test_openai_chat.py	Async VCR test for OpenAI chat; constructs OpenAICompatibleClient with an externally-managed httpx client, calls generate_async, and validates result shape against the cassette response.
tests/recorded/clients/test_openai_embeddings.py	Synchronous VCR test for OpenAI embeddings; directly instantiates OpenAIEmbeddingModel and validates that the decoded embedding vector has the expected dimension (1536).
tests/recorded/clients/cassettes/test_openai_chat/test_openai_chat_generate_text.yaml	Cassette for the chat test; volatile fields (response id, system_fingerprint) are correctly normalized and no secrets are present.
tests/recorded/clients/cassettes/test_openai_embeddings/test_openai_embeddings_sync.yaml	Cassette for the embeddings test; stores a single base64-encoded 1536-dim embedding; Authorization header is absent as expected after sanitization.
tests/recorded/clients/configs/openai_chat_config/config.yml	Minimal passthrough chat config referencing gpt-4o-mini; added in this PR but not yet loaded by any test in this slice of the stack.
tests/recorded/clients/configs/openai_embeddings_config/config.yml	Minimal embeddings config for text-embedding-3-small; added in this PR but not yet loaded by any test in this slice of the stack.

Sequence Diagram

%%{init: {'theme': 'neutral'}}%%
sequenceDiagram
    participant Test as Test (pytest)
    participant VCR as VCR Cassette
    participant Client as OpenAICompatibleClient / OpenAIEmbeddingModel
    participant API as OpenAI API (mocked)

    Note over Test,API: Replay mode (--block-network)

    Test->>VCR: load cassette YAML
    VCR-->>Test: cassette ready

    alt Chat test (async)
        Test->>Client: OpenAICompatibleClient(base_url, api_key, http_client)
        Test->>Client: model.generate_async("Say hello in one word")
        Client->>VCR: POST /v1/chat/completions
        VCR-->>Client: "200 { content: "Hello!" }"
        Client-->>Test: GenerationResult
        Test->>Test: assert content, finish_reason, request_id, usage
    else Embeddings test (sync)
        Test->>Client: OpenAIEmbeddingModel("text-embedding-3-small", api_key)
        Test->>Client: model.encode(["test"])
        Client->>VCR: POST /v1/embeddings
        VCR-->>Client: "200 { embedding: base64(...) }"
        Client-->>Test: List[List[float]]
        Test->>Test: "assert len==1, len(result[0])==1536"
    end

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sequenceDiagram
    participant Test as Test (pytest)
    participant VCR as VCR Cassette
    participant Client as OpenAICompatibleClient / OpenAIEmbeddingModel
    participant API as OpenAI API (mocked)

    Note over Test,API: Replay mode (--block-network)

    Test->>VCR: load cassette YAML
    VCR-->>Test: cassette ready

    alt Chat test (async)
        Test->>Client: OpenAICompatibleClient(base_url, api_key, http_client)
        Test->>Client: model.generate_async("Say hello in one word")
        Client->>VCR: POST /v1/chat/completions
        VCR-->>Client: "200 { content: "Hello!" }"
        Client-->>Test: GenerationResult
        Test->>Test: assert content, finish_reason, request_id, usage
    else Embeddings test (sync)
        Test->>Client: OpenAIEmbeddingModel("text-embedding-3-small", api_key)
        Test->>Client: model.encode(["test"])
        Client->>VCR: POST /v1/embeddings
        VCR-->>Client: "200 { embedding: base64(...) }"
        Client-->>Test: List[List[float]]
        Test->>Test: "assert len==1, len(result[0])==1536"
    end

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