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feat(codec): add OCI GenAI typed variants and response codec (1/4) - #554

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feat(codec): add OCI GenAI typed variants and response codec (1/4)#554
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@fede-kamel fede-kamel commented Jul 24, 2026

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Overview

First PR of a four-part stacked series adding Oracle Cloud Infrastructure (OCI) Generative AI as a built-in provider in the Rust core — the rework requested in #549 review, split into foundation-ordered units of ~≤1k lines for reviewability (per the plan posted on #552 before closing it).

Series map (each stacked on the previous, opened as its predecessor merges):

  1. This PR — typed ApiSpecific variants + response codec (~975 lines)
  2. Request codec: decode + merge-not-replace encode with identity guarantees (~1.4k, the complexity heart)
  3. Provider-surface resolver registration + streaming codec + guardrails/PII-redaction/adaptive surface support (~1.1k)
  4. Python/Node bindings (~200)
  • I confirm this contribution is my own work, or I have the right to submit it under this project's license.
  • I searched existing issues and open pull requests, and this does not duplicate existing work.

Details

What: ApiSpecificRequest::OCIGenAI { compartment_id, serving_mode, api_format } and ApiSpecificResponse::OCIGenAI { api_format, model_version } (serde tag "oci_genai") in crates/types, plus crates/core/src/codec/oci_genai.rs introducing OCIGenAIChatCodec with its LlmResponseCodec implementation: decodes OCI ChatResult payloads across all three documented apiFormats — GENERIC (choices-based; Meta Llama, Google, xAI, OpenAI, and imported open-weights models such as NVIDIA Nemotron on dedicated AI clusters), COHERE (text-based), and COHEREV2 (single assistant message with typed content parts and nested-function tool calls, per the OCI CohereChatResponseV2 schema) — normalizing model, response id, message content, tool calls, finish reasons, and usage counters (including promptTokensDetails.cachedTokens). The codec accepts the REST wire format only (camelCase, as documented); alternate renderings produced by Oracle tooling are the caller's responsibility. Envelope and chat-response fields outside the normalized shape (timeCreated, serviceTier, chatHistory, grounding metadata, future provider fields) are preserved in extra rather than discarded, consistent with the other response codecs.

Why: OCI GenAI responses are currently opaque to Relay observability. This layer alone enables normalized LLMEnd annotations (model, finish reason, token usage) for OCI-backed calls when the codec is supplied explicitly; subsequent PRs add request editing, automatic detection, and binding exposure.

How: Follows the built-in provider pattern (anthropic.rs as template): unit-struct codec, in-module tests, FinishReason mapping for the three formats' vocabularies (stop/length/max_tokens/tool_calls; COMPLETE/MAX_TOKENS; TOOL_CALL/STOP_SEQUENCE). COHERE tool calls carry no id on the wire, so parallel calls receive positional call_{index} fallbacks; provider-supplied ids pass through unchanged.

Testing: 13 unit tests plus a pipeline integration test decoding a GENERIC tool-call response through llm_call_execute. GENERIC and COHERE fixtures are taken from live OCI wire captures (simple, tool-call, mixed-content, and tool-call-only shapes, plus a model-family sweep across Meta, OpenAI, Google, xAI, and Cohere confirming no additional response formats); the COHEREV2 fixture mirrors the published CohereChatResponseV2 SDK schema, as the live service does not yet accept that format (probed: HTTP 400). Additional coverage: wire-format-only contract (snake_case and kebab-case/data-envelope renderings decode to nothing), invalid-content error paths, ProviderNative part preservation, unmodeled-field preservation in extra, finish-reason and cached-token usage mapping, and non-dict fallback. Full workspace suite green (3,377 tests), cargo clippy --workspace --all-targets zero warnings, cargo fmt clean, missing_docs satisfied. The complete series content has additionally been validated end-to-end: the encoded payload of the full codec was posted verbatim to the signed OCI REST endpoint and answered by a dedicated AI cluster serving an imported NVIDIA Nemotron 3 model.

Breaking changes: None — additive enum variants and a new module only.

Where should the reviewer start?

crates/types/src/codec/{request,response}.rs for the variant shapes, then decode_response and the fixtures in crates/core/tests/unit/codec/oci_genai_tests.rs.

Related Issues: (use one of the action keywords Closes / Fixes / Resolves / Relates to)

Summary by CodeRabbit

  • New Features

    • Added OCI Generative AI support for chat response decoding, including text, tool calls, usage, finish reasons, and provider metadata.
    • Added OCI-specific request and response metadata fields.
    • OCI Generative AI requests are now identified in observability data.
  • Tests

    • Added coverage for OCI response formats, tool calls, content variations, usage, and error handling.

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@github-actions github-actions Bot added size:L PR is large Feature a new feature lang:rust PR changes/introduces Rust code labels Jul 24, 2026
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Walkthrough

Adds OCI GenAI request and response variants, exports a codec supporting GENERIC, COHERE, and COHEREV2 response formats, maps OCI metadata into normalized responses and observability, and adds unit and pipeline integration tests.

Changes

OCI GenAI codec support

Layer / File(s) Summary
OCI GenAI API contracts
crates/types/src/codec/request.rs, crates/types/src/codec/response.rs
Adds serde-tagged OCI GenAI request and response variants with optional provider-specific fields.
OCI GenAI response decoding
crates/core/src/codec/mod.rs, crates/core/src/codec/oci_genai.rs
Exports OCIGenAIChatCodec and decodes GENERIC, COHERE, and COHEREV2 responses, including content, tool calls, finish reasons, usage, raw values, preserved fields, and OCI metadata.
OCI provider observability mapping
crates/core/src/observability/otel_genai.rs
Maps OCI GenAI requests to the provider value oci.genai.
Codec fixtures and validation
crates/core/src/codec/oci_genai.rs, crates/core/tests/unit/codec/oci_genai_tests.rs
Wires unit tests and validates standard, non-wire, non-object, tool-call, mixed-content, invalid-content, usage, metadata-preservation, and finish-reason inputs.
Pipeline integration
crates/core/tests/integration/pipeline_tests.rs
Runs the codec through the pipeline and verifies decoded model, tool calls, finish reason, and token usage in the emitted LLM end event.

Estimated code review effort: 4 (Complex) | ~45 minutes

Sequence Diagram(s)

sequenceDiagram
  participant OCI as OCI GenAI response
  participant Codec as OCIGenAIChatCodec
  participant Decoder as GENERIC, COHERE, or COHEREV2 decoder
  participant Pipeline as LLM pipeline
  participant Result as AnnotatedLlmResponse
  OCI->>Codec: provide REST-format JSON
  Codec->>Decoder: dispatch using apiFormat
  Decoder-->>Codec: return content, tool calls, finish reason, and usage
  Codec->>Result: populate normalized fields and OCI metadata
  Pipeline->>Result: emit decoded annotated response
Loading

Possibly related issues

Possibly related PRs

  • NVIDIA/NeMo-Relay#305 — Introduces the shared DTO infrastructure used by the new OCI GenAI request and response variants.
  • NVIDIA/NeMo-Relay#556 — Provides the OpenTelemetry projection infrastructure extended here for OCI GenAI requests.
🚥 Pre-merge checks | ✅ 5
✅ Passed checks (5 passed)
Check name Status Explanation
Title check ✅ Passed The title follows Conventional Commits and accurately summarizes the added OCI GenAI codec and typed variants.
Description check ✅ Passed The description matches the template with Overview, Details, reviewer start, and related issues, and it is sufficiently specific.
Docstring Coverage ✅ Passed Docstring coverage is 100.00% which is sufficient. The required threshold is 80.00%.
Linked Issues check ✅ Passed Check skipped because no linked issues were found for this pull request.
Out of Scope Changes check ✅ Passed Check skipped because no linked issues were found for this pull request.
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@fede-kamel

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How this series fits together

This PR is layer 1 of 4. Each layer adds one capability, each is independently buildable and testable, and each later branch is a pure superset of the previous — so review feedback here rebases cleanly through the rest of the stack.

Layer Capability it adds Contents
1 — this PR (+562) Relay can read OCI responses: normalized LLMEnd annotations (model, finish reason, usage) when the codec is supplied explicitly Typed ApiSpecific variants + LlmResponseCodec for GENERIC and COHERE ChatResult payloads
2 (+1,414) Relay can edit OCI requests safely: intercepts (redaction, policy) with encode(decode(x), x) == x identity and unmodeled-field preservation LlmCodec decode + merge-not-replace encode, request-side test suite
3 (+1,060) Relay auto-detects OCI: provider-surface registration, streaming, and awareness in guardrails, PII-redaction overlay, and adaptive components ProviderSurface::OCIGenAI, detection (strongest-signal envelope keys, placed first), OCIGenAIStreamingCodec, parity cases
4 (+202) Every language gets it pyo3 + napi classes, .pyi/codecs.py exposure, binding tests — closes #548

Branch links and the full plan of record are on #548. Lineage: #549 (Python approach, closed per review) → #552 (this same content as a single Rust PR, closed in favor of this reviewable split).

Verification provenance

Every branch in the stack passes the full local gate on its own: cargo build --workspace, complete workspace test suite (3,369 tests at this layer, growing to 3,403 by layer 4), cargo clippy --workspace --all-targets with zero warnings, cargo fmt --check, and missing_docs. The four layers recombine byte-identically to the #552 content, which was validated end-to-end: the codec-encoded request was posted verbatim to the signed OCI REST chat endpoint and answered correctly by a dedicated AI cluster serving an imported NVIDIA Nemotron 3 model, with the response codec normalizing the reply including token usage.

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Actionable comments posted: 2

🤖 Prompt for all review comments with AI agents
Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.

Inline comments:
In `@crates/core/src/codec/oci_genai.rs`:
- Around line 124-162: Update flatten_all_text_parts to return None for an empty
parts slice, while preserving Text concatenation for non-empty arrays containing
only valid TEXT parts. This ensures decode_generic_content returns None for
content: [] and does not mark tool-call-only messages as containing text.

In `@crates/core/tests/unit/codec/oci_genai_tests.rs`:
- Around line 131-167: Add error-path coverage alongside the existing OCI GenAI
codec tests for GENERIC responses: create a test such as
test_invalid_generic_content_shape_errors that passes a numeric or object
message.content to OCIGenAIChatCodec.decode_response and asserts it returns an
error. Also cover an array containing a non-object part if practical, ensuring
decode_generic_content rejects each invalid shape with
FlowError::InvalidArgument.
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📒 Files selected for processing (5)
  • crates/core/src/codec/mod.rs
  • crates/core/src/codec/oci_genai.rs
  • crates/core/tests/unit/codec/oci_genai_tests.rs
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  • crates/core/src/codec/mod.rs
  • crates/types/src/codec/response.rs
  • crates/types/src/codec/request.rs
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🔇 Additional comments (8)
crates/types/src/codec/request.rs (1)

537-549: LGTM!

crates/types/src/codec/response.rs (1)

329-339: LGTM!

crates/core/src/codec/mod.rs (1)

19-19: LGTM!

crates/core/src/codec/oci_genai.rs (3)

197-254: LGTM!


262-329: LGTM!


90-101: LGTM!

Also applies to: 332-341

crates/core/tests/unit/codec/oci_genai_tests.rs (2)

16-129: LGTM!


169-188: LGTM!

Comment thread crates/core/src/codec/oci_genai.rs
Comment thread crates/core/tests/unit/codec/oci_genai_tests.rs
@fede-kamel
fede-kamel force-pushed the feat/oci-codec-1-types-response branch from ccb3281 to 21d6e18 Compare July 24, 2026 17:59
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Both review findings addressed in the updated commit:

  1. Empty content: []None: decode_generic_content now returns Ok(None) for an empty part list, so tool-call-only messages no longer decode to Some(Text("")). The tool-call fixture test now asserts annotated.message == None explicitly.
  2. Error-path coverage: added test_invalid_generic_content_shape_errors exercising InvalidArgument for non-string/array/null content and non-object parts.

Full workspace build and test suite re-run green after the change; the fix is propagated through the staged follow-up branches of the series.

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Actionable comments posted: 2

🤖 Prompt for all review comments with AI agents
Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.

Inline comments:
In `@crates/core/src/codec/oci_genai.rs`:
- Around line 313-333: The decode_response_tool_call path silently discards
malformed tool calls when the name is missing or non-string. Add an appropriate
debug or warning log before returning None for this validation failure,
including enough context to identify the malformed OCI payload while preserving
the existing successful decoding behavior.

In `@crates/core/tests/unit/codec/oci_genai_tests.rs`:
- Around line 1-210: Add a test near test_invalid_generic_content_shape_errors
that decodes a GENERIC response with mixed TEXT and non-TEXT content through
OCIGenAIChatCodec::decode_response. Assert the message is MessageContent::Parts,
contains both parts, and specifically verify the non-TEXT part is represented as
ContentPart::ProviderNative with its original payload preserved.
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📒 Files selected for processing (5)
  • crates/core/src/codec/mod.rs
  • crates/core/src/codec/oci_genai.rs
  • crates/core/tests/unit/codec/oci_genai_tests.rs
  • crates/types/src/codec/request.rs
  • crates/types/src/codec/response.rs
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**/*.rs

📄 CodeRabbit inference engine (.agents/skills/prepare-pr/SKILL.md)

**/*.rs: Any Rust change must run just test-rust
Any Rust change must run cargo fmt --all
Any Rust change must run cargo clippy --workspace --all-targets -- -D warnings

**/*.rs: Run cargo fmt --all for all FFI work since it is Rust work
Run just test-rust to validate FFI changes
Run cargo clippy --workspace --all-targets -- -D warnings to enforce strict linting on FFI work

When Rust files changed as part of Go work, also run cargo fmt --all, just test-rust, and cargo clippy --workspace --all-targets -- -D warnings

**/*.rs: Run cargo fmt --all when Rust files are changed as part of Node work
Run cargo clippy --workspace --all-targets -- -D warnings when Rust files are changed as part of Node work
Run just test-rust when Rust files are changed as part of Node work

When changing the core Rust runtime or Rust-facing API surface, format Rust code with cargo fmt (rustfmt defaults), keep cargo clippy -- -D warnings clean, and satisfy cargo deny check per deny.toml.

**/*.rs: If any Rust code changed, always run just test-rust.
If any Rust code changed, also run cargo fmt --all.
If any Rust code changed, also run cargo clippy --workspace --all-targets -- -D warnings.
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🔇 Additional comments (4)
crates/types/src/codec/request.rs (1)

537-549: LGTM!

crates/types/src/codec/response.rs (1)

329-339: LGTM!

crates/core/src/codec/oci_genai.rs (1)

1-113: LGTM!

Also applies to: 201-258, 266-345

crates/core/src/codec/mod.rs (1)

19-19: LGTM!

Comment thread crates/core/tests/unit/codec/oci_genai_tests.rs
@fede-kamel

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End-to-end validation re-run on the updated series content (including the empty-content fix above), via the Python binding built from the stack tip:

  1. decode normalized a live OCI ChatDetails request (dedicated serving mode)
  2. encode(decode(request), request) verified byte-identical to the original payload
  3. the codec-encoded request was posted verbatim to the signed OCI Generative AI REST endpoint (us-chicago-1) and answered correctly by a dedicated AI cluster serving an imported NVIDIA Nemotron 3 model
  4. decode_response normalized the live reply, including finish reason and token usage (prompt_tokens: 28, completion_tokens: 109, total_tokens: 137)

Unit suite on the same tip: 33 OCI codec tests green, full workspace build and tests passing, clippy zero warnings.

Introduce the first layer of the OCI Generative AI provider codec:
typed ApiSpecificRequest::OCIGenAI and ApiSpecificResponse::OCIGenAI
variants, plus an OCIGenAIChatCodec implementing LlmResponseCodec.
Response decode covers ChatResult ({modelId, chatResponse}) and bare
chat responses in both apiFormat variants (GENERIC choices-based and
COHERE text-based), tolerates camelCase, kebab-case, and snake_case
key conventions (SDK vs CLI shapes), parses GENERIC string-encoded
tool-call arguments, maps promptTokens/completionTokens/totalTokens
into Usage, and maps finish reasons (stop/COMPLETE -> complete,
length/MAX_TOKENS -> length, tool_calls -> tool_use, else unknown).

Request encode/decode, streaming, and provider-surface registration
follow in subsequent changes.

Signed-off-by: Federico Kamelhar <federico.kamelhar@oracle.com>
@fede-kamel
fede-kamel force-pushed the feat/oci-codec-1-types-response branch from 21d6e18 to 1b8a31f Compare July 24, 2026 20:26
@fede-kamel

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Second CodeRabbit pass triaged:

  • Empty content: []None and error-path coverage — already fixed in the previous push; the re-posted comments anchor to the superseded diff. Current code returns Ok(None) for empty part lists (asserted in the tool-call test) and test_invalid_generic_content_shape_errors covers the InvalidArgument paths.
  • Missing ProviderNative fallback coverage — valid gap; added test_non_text_parts_preserved_as_provider_native (TEXT + IMAGE part list decodes to typed parts with the image preserved losslessly as a ProviderNative component).
  • Malformed tool calls silently dropped — declining intentionally: this mirrors the established built-in pattern (the Anthropic codec's tool-call decode uses the same filter_map drop semantics), and diverging here would make OCI behave inconsistently with the other providers. Happy to revisit codec-wide in a follow-up if maintainers prefer logging.

Suite on the updated tip: 34 OCI codec tests green, clippy zero warnings, full stack rebased.

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Actionable comments posted: 1

🤖 Prompt for all review comments with AI agents
Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.

Inline comments:
In `@crates/core/src/codec/oci_genai.rs`:
- Around line 313-333: The decode_response_tool_call function currently assigns
an empty string when the OCI response omits id, causing parallel Cohere tool
calls to collide. Replace the unwrap_or_default fallback with a stable, unique
per-call identifier derived from the available tool-call data, while preserving
the provided id unchanged when present.
🪄 Autofix (Beta)

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**/*.rs

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Keep async behavior on the existing tokio-based model; bindings should preserve callback and future lifetimes rather than blocking or hiding async work unexpectedly.

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  • crates/types/src/codec/response.rs
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🔇 Additional comments (5)
crates/types/src/codec/request.rs (1)

537-549: LGTM!

crates/types/src/codec/response.rs (1)

329-339: LGTM!

crates/core/src/codec/oci_genai.rs (1)

1-354: Rest of the file (key-convention helpers, GENERIC content decoding, envelope/chat_response split, usage mapping, finish-reason mapping) is correct and the previously-flagged empty-content and error-path issues are now addressed.

crates/core/src/codec/mod.rs (1)

19-19: LGTM!

crates/core/tests/unit/codec/oci_genai_tests.rs (1)

1-247: LGTM! Both previously-flagged gaps (invalid-content error path, mixed-parts ProviderNative coverage) are now covered.

Comment thread crates/core/src/codec/oci_genai.rs Outdated
@willkill07

willkill07 commented Jul 27, 2026

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@fede-kamel A few questions:

  1. Is Cohere adhering to v1 or v2:

If Oracle strictly adheres to Cohere, then I'd expect separate CohereV1 and CohereV2 Codecs rather than an Oracle-specific codec.

  1. I don't see any streaming codec support -- is this intentional?

  2. Where is the API definition/spec for Generic? Is it just using standard OpenAI? If so, why do we need a separate codec?

  3. A question regarding:

Key lookup tolerates the three conventions OCI emits (SDK camelCase, CLI kebab-case, snake_case).

This seems generally problematic to me. Schema specifications should be concrete and well-defined. If Oracle is extending the Cohere schema to be case/format insensitive, I really need good justification as to why a vendor-specific schema should live in Relay itself. Cohere's API is clearly defined with snake_case semantics. Why would that not suffice?

Validated the codec against live OCI Generative AI responses across
model families (Meta, OpenAI, Google, xAI, Cohere) and the three
renderings Oracle tooling emits for the documented camelCase schema.
Changes from that sweep:

- Unwrap the OCI CLI data envelope so captured CLI output decodes like
  wire and SDK payloads; document the transport matrix in the module
  doc (REST wire/SDKs camelCase, oci.util.to_dict() snake_case, CLI
  kebab-case in a data envelope)
- Map the lowercase max_tokens finish reason emitted by Gemini models
  to FinishReason::Length
- Map promptTokensDetails.cachedTokens (OpenAI/xAI models) to
  cache_read_tokens instead of dropping it
- Synthesize positional call_{index} ids for COHERE tool calls, which
  carry no id on the wire, so parallel calls stay distinguishable
- Add unit tests for each live-observed shape and a pipeline
  integration test decoding an OCI GENERIC tool-call response through
  llm_call_execute

Signed-off-by: Federico Kamelhar <federico.kamelhar@oracle.com>
@fede-kamel

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Thanks for the careful review @willkill07 — these are exactly the right questions. Rather than answer from the docs alone, I captured live responses from the service (us-chicago-1, one model from each family: Meta, OpenAI, Google, xAI, Cohere) and checked every claim below against them.

1. Cohere v1 or v2?

Neither, and that's the crux: Oracle does not strictly adhere to Cohere. The COHERE format borrows Cohere v1 semantics (single top-level text, chatHistory, uppercase finish reasons like COMPLETE/MAX_TOKENS), but the wire schema is Oracle's own CohereChatResponse: camelCase keys inside the ChatResult/chatResponse envelope, and none of Cohere's identifying fields (generation_id, response_id). Live capture from cohere.command-r-08-2024:

{
  "modelId": "cohere.command-r-08-2024",
  "modelVersion": "2.0",
  "chatResponse": {
    "apiFormat": "COHERE",
    "text": "...",
    "chatHistory": [{"role": "USER", "message": "..."}, {"role": "CHATBOT", "message": "..."}],
    "finishReason": "COMPLETE",
    "toolCalls": [{"name": "get_weather", "parameters": {"city": "Paris"}}],
    "usage": {"promptTokens": 29, "completionTokens": 37, "totalTokens": 66}
  }
}

A native CohereV1 codec (snake_case, no envelope) would decode none of this. If Relay later adds Cohere's own API as a provider surface, CohereV1/V2 codecs make sense there — but they'd be decoding a different wire format than this one. I also checked the newest Cohere model on OCI (cohere.command-a-03-2025): same v1-style Oracle schema, so no v2 drift so far.

2. Streaming

Intentional for this layer — streaming is layer 3 of the series (OCIGenAIStreamingCodec, SSE for both formats); the stack table in my first comment has the breakdown. I kept this PR to typed variants + response decode so each layer stays reviewable.

3. GENERIC spec

It's Oracle's own documented schema: GenericChatResponse. OpenAI-inspired, not OpenAI wire-compatible. From the live captures:

  • envelope: {modelId, modelVersion, chatResponse: {apiFormat, timeCreated, choices, usage}} — no id/object/created
  • uppercase enums: role: "ASSISTANT", content type: "TEXT", tool call type: "FUNCTION"
  • tool calls are flat {type, id, name, arguments} rather than OpenAI's nested function: {name, arguments} — our own OpenAIChatCodec rejects exactly this shape, since it requires the nested function object
  • usage is promptTokens/completionTokens/totalTokens

So routing GENERIC through the OpenAI codec isn't an option; it hard-errors on the tool-call shape and misses the envelope and usage fields. I also verified GENERIC is what every non-Cohere family returns on OCI (openai.*, google.*, xai.*, meta.*) — there is no hidden third format.

4. Key conventions

Agreed that a case/format-insensitive schema would be a smell, and the module doc described this poorly — I've reworded it in the latest push. To state it precisely: Oracle's schema is concrete, and the REST wire is strictly camelCase, always. The three spellings exist because Oracle's own tooling re-keys the same schema deterministically at different capture points:

Capture point Rendering
REST wire, Java/Go/TS SDKs camelCase (finishReason)
Python SDK oci.util.to_dict(response.data) snake_case (finish_reason)
OCI CLI output kebab-case in a data envelope (finish-reason)

I verified all three by running the same call through each path; the test fixtures now mirror those captures. The lookup is not fuzzy matching — the codec derives the kebab/snake spelling mechanically from the documented camelCase key, so there's exactly one accepted rendering per convention and no ambiguity. The snake_case path matters most in practice: Python is Relay's biggest binding, and to_dict() output is the payload shape instrumented OCI SDK apps actually hand over.

That said, if you'd rather the built-in codec accept only the wire format and leave CLI/SDK-dict renderings to the caller, I'm happy to trim to camelCase-only — small diff, and I'd rather match the project's conventions than defend a preference.


The live sweep also surfaced a few real-world shapes the first cut missed, all fixed with tests in the latest commit: Gemini models emit a lowercase max_tokens finish reason, OpenAI/xAI models report cache hits under promptTokensDetails.cachedTokens, the CLI's data envelope needed unwrapping, and Cohere tool calls carry no id on the wire so parallel calls now get positional synthesized ids. Also added a pipeline integration test decoding a live-shaped GENERIC tool-call response through llm_call_execute, matching the existing Anthropic/OpenAI coverage.

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crates/core/src/codec/oci_genai.rs (1)

245-249: 🎯 Functional Correctness | 🟠 Major | ⚡ Quick win

Handle COHEREV2 as a Cohere response
COHEREV2 also carries its generated text in message, but this branch sends it to the generic parser, which expects choices and drops valid V2 responses. Add an explicit COHEREV2 case here, or reject unsupported formats instead of treating them as generic.

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In `@crates/core/src/codec/oci_genai.rs` around lines 245 - 249, Update the
api_format branch in the response decoding flow to route both "COHERE" and
"COHEREV2" through decode_cohere_response_body; ensure COHEREV2 no longer
reaches decode_generic_response_body, which expects choices.
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Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.

Inline comments:
In `@crates/core/tests/integration/pipeline_tests.rs`:
- Around line 1442-1515: Make subscriber cleanup in the OCI response codec test
panic-safe by introducing an RAII guard immediately after registering the
subscriber, using its drop behavior to call deregister_subscriber for
"oci_resp_codec_sub". Remove the explicit cleanup dependency at the end of the
test while preserving deregistration on successful completion and during
assertion unwinding.

---

Outside diff comments:
In `@crates/core/src/codec/oci_genai.rs`:
- Around line 245-249: Update the api_format branch in the response decoding
flow to route both "COHERE" and "COHEREV2" through decode_cohere_response_body;
ensure COHEREV2 no longer reaches decode_generic_response_body, which expects
choices.
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That said, if you'd rather the built-in codec accept only the wire format and leave CLI/SDK-dict renderings to the caller

Relay only interfaces with the wire format, so yes.

Per review, Relay only interfaces with the wire format, so the codec
now accepts the documented camelCase schema only. Removes the
kebab-case/snake_case key derivation and the CLI data-envelope
unwrapping; converting alternate renderings produced by Oracle tooling
is the caller's responsibility. Adds a contract test asserting
non-wire renderings are not decoded.

Signed-off-by: Federico Kamelhar <federico.kamelhar@oracle.com>
@fede-kamel

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Done in 7282cdd — the codec now accepts the camelCase wire format only. Dropped the kebab/snake key derivation and the CLI data-envelope handling (~130 lines removed), documented that converting alternate tooling renderings is the caller's job, and added a contract test asserting non-wire renderings decode to nothing. Full workspace suite, clippy, and fmt all green.

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Inline comments:
In `@crates/core/tests/unit/codec/oci_genai_tests.rs`:
- Around line 106-124: Extend test_non_wire_renderings_are_not_decoded with a
kebab-case CLI-shaped response wrapped in {"data": {...}}, using the documented
non-REST field names. Decode it with OCIGenAIChatCodec and assert model,
message, and finish_reason are all None, matching the existing snake_case case.
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168-196: 📐 Maintainability & Code Quality

Provide the required core validation evidence.

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Comment thread crates/core/tests/unit/codec/oci_genai_tests.rs
Extends the non-wire-rendering contract test with a kebab-case
data-enveloped CLI-shaped response, guarding the REST-only boundary
against regression on both alternate renderings.

Signed-off-by: Federico Kamelhar <federico.kamelhar@oracle.com>

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Thanks for splitting this into a focused first step. I found two issues that need addressing before this response codec is ready to merge.

Comment thread crates/core/src/codec/oci_genai.rs Outdated
.unwrap_or("GENERIC")
.to_uppercase();

let (message, tool_calls, finish_reason) = if api_format == "COHERE" {

@willkill07 willkill07 Jul 28, 2026

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Could we handle COHEREV2 explicitly here? OCI lists it as a supported apiFormat, but this branch sends it through decode_generic_response_body.

V2 responses use message and finishReason rather than choices, so Relay currently records no response text, tool calls, or finish reason—without surfacing an error. Please add a V2 decoder (or return an explicit unsupported-format error) and cover it with a fixture.

If you are introducing OCI support, it seems odd to not also support COHEREV2

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Done in 2ab7e34 — added a dedicated COHEREV2 decoder rather than an error, since the shape is fully specified. Two notes from verifying this:

  1. The live service doesn't accept the format yet: I probed us-chicago-1 yesterday with apiFormat: COHEREV2 against cohere.command-a-03-2025 and cohere.command-a-reasoning (both v2-messages and v1 shapes) and got HTTP 400 "Please pass in correct format of request" in all cases. It is, however, in the current SDK spec (oci 2.182.1 defines CohereChatResponseV2 and dispatches COHEREV2 to it), so the decoder and fixture mirror that published schema exactly: single assistant message with typed content parts, nested-function toolCalls ({id, type: FUNCTION, function: {name, arguments}}), top-level response id, and the V2 finish reasons TOOL_CALL/STOP_SEQUENCE.
  2. TEXT parts flatten like GENERIC; THINKING/IMAGE_URL/DOCUMENT parts are preserved losslessly as provider-native parts.

Covered by test_cohere_v2_chat_result and test_cohere_v2_text_only_flattens, plus the finish-reason mapping cases. I'll re-probe when the service starts accepting the format and adjust if the wire diverges from the spec.

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Update with live-wire evidence: the service accepts apiFormat: COHEREV2 as of today (the same request returned HTTP 400 on 07-28), so I swept every Cohere chat model in the us-chicago-1 catalog with both formats:

Model COHERE (v1) COHEREV2
cohere.command-a-03-2025 ✅ accepted ✅ accepted
cohere.command-a-vision ❌ 400 apiFormat COHERE is not supported ✅ accepted
cohere.command-latest ✅ accepted ❌ 400 not supported
cohere.command-plus-latest ✅ accepted ❌ 400 not supported
cohere.command-r-08-2024 ✅ accepted ❌ 400 not supported
cohere.command-r-plus-08-2024 ✅ accepted ❌ 400 not supported
cohere.command-a-reasoning, command-r-16k, command-r-plus 404 (not served on-demand) 404

So the split is generational: the older command/command-r line is V1-only, the current command-a line is V2-first, and command-a-vision is V2-only — without this decoder Relay would record nothing for that model. command-a-03-2025 serves both formats and its wire responses were decoded through the codec for each.

Live V2 responses (text and parallel tool calls) match the CohereChatResponseV2 fixture exactly: nested-function tool calls with provider-supplied ids, JSON-encoded string arguments (parsed like GENERIC), TOOL_CALL finish reason, and message-level toolPlan/citations (now preserved in extra per the other thread). The fixture comment records the live confirmation as of 07ded78.

Comment thread crates/core/src/codec/oci_genai.rs Outdated
api_format: Some(api_format),
model_version,
}),
extra: serde_json::Map::new(),

@willkill07 willkill07 Jul 28, 2026

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Could we retain the response fields that are not normalized instead of always returning an empty extra map?

This currently discards OCI data such as timeCreated, service-tier/grounding metadata, and future provider fields that are useful for observability.

Please preserve unknown envelope fields and/or retain the raw chatResponse in the OCI-specific response data, consistent with the other response codecs.

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Done in 2ab7e34 — decode now carries all unmodeled fields in extra, matching the flatten-passthrough behavior of the OpenAI/Anthropic response codecs: unknown envelope fields (anything besides modelId/modelVersion/chatResponse) plus chat-response fields outside the per-format modeled set. Concretely that preserves timeCreated, serviceTier, COHERE chatHistory, grounding metadata, and any future provider fields. Covered by test_unmodeled_response_fields_preserved_in_extra, which also asserts modeled keys aren't duplicated into extra.

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Follow-up in 9cae2fb — auditing the preservation claim field-by-field against the OCI schema (ChatChoice, AssistantMessage, CohereAssistantMessageV2) exposed a second layer of the same gap: fields nested inside the decoded choice and assistant message were still dropped. Per the schema that's logprobs, serviceTier, groundingMetadata, usage (choice) and refusal, annotations, reasoningContent (message) for GENERIC, and toolPlan, citations for COHEREV2 — so the grounding metadata you called out actually lives one level deeper than the chat-response pass I'd added. These are now carried in extra, namespaced under "choice" and "message" so their origin stays unambiguous.

Re-validated against live wire responses (us-chicago-1): a GENERIC reply from an OpenAI-family model carries choice-level logprobs and message-level annotations on the wire, both now preserved (previously silently dropped); COHERE v1 behavior is unchanged. Same pass also mapped GENERIC content_filter finish reasons to the normalized ContentFilter, matching the OpenAI codec.

Per review on the OCI codec:

- Add a COHEREV2 decoder matching the OCI CohereChatResponseV2 schema:
  single assistant message with typed content parts (TEXT flattened,
  THINKING/IMAGE_URL/DOCUMENT preserved as provider-native), nested
  OpenAI-style function tool calls, response id, and the V2 finish
  reasons TOOL_CALL and STOP_SEQUENCE. The live service does not accept
  the format yet (probed us-chicago-1: HTTP 400), so the fixture
  mirrors the published SDK schema.
- Preserve envelope and chat-response fields the normalized shape does
  not model (timeCreated, serviceTier, chatHistory, grounding metadata,
  future fields) in extra instead of discarding them, consistent with
  the other response codecs.

Signed-off-by: Federico Kamelhar <federico.kamelhar@oracle.com>
Verified the decoder against the OCI SDK schema (ChatChoice,
AssistantMessage, CohereAssistantMessageV2) and closed two gaps:

- Unmodeled fields of the decoded GENERIC choice (logprobs, usage,
  groundingMetadata, serviceTier) and assistant message (refusal,
  annotations, reasoningContent), plus COHEREV2 message fields
  (toolPlan, citations), were silently dropped; they are now carried
  in extra, namespaced under "choice" and "message".
- content_filter finish reasons from OpenAI-style GENERIC models now
  map to FinishReason::ContentFilter, matching the OpenAI codec.

Signed-off-by: Federico Kamelhar <federico.kamelhar@oracle.com>
The merge from main brought in the unified OTel exporter (NVIDIA#556), whose
exhaustive match on ApiSpecificRequest did not cover the OCIGenAI
variant this branch introduces, breaking the workspace build. Map it
to "oci.genai", following the dotted cloud-provider convention used
by aws.bedrock and gcp.gemini.

Signed-off-by: Federico Kamelhar <federico.kamelhar@oracle.com>
@github-actions github-actions Bot added size:XL PR is extra large and removed size:L PR is large labels Jul 29, 2026
@fede-kamel

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Status after the branch update merging main: the merge itself broke the workspace build — the unified OTel exporter from #556 matches exhaustively on ApiSpecificRequest, which didn't cover the OCIGenAI variant this branch introduces. Fixed in 0766e46 by mapping it to oci.genai (dotted cloud-provider convention, like aws.bedrock / gcp.gemini).

Validation on the current tip: full workspace suite green (3,485 tests), clippy zero warnings, fmt --check clean, plus live-wire decode verification of GENERIC and COHERE responses through the codec (details in the review thread). One note for CI watchers: install_registrations_covers_registry_error_edges (dynamic worker plugin) is a parallelism-sensitive flake inherited from main — the worker code on this branch is byte-identical to main, it passes serially and in isolation, and it's unrelated to this PR.

The service now accepts apiFormat COHEREV2 (it rejected it with HTTP
400 the day before); live text and parallel tool-call responses match
the spec-mirrored fixture exactly, so the fixture comment no longer
claims the format is spec-only.

Signed-off-by: Federico Kamelhar <federico.kamelhar@oracle.com>
@fede-kamel fede-kamel changed the title feat(codec): add OCI Generative AI typed variants and response codec (series 1/4) feat(codec): add OCI GenAI typed variants and response codec (1/4) Jul 29, 2026
@fede-kamel

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Caution

Some comments are outside the diff and can’t be posted inline due to platform limitations.

⚠️ Outside diff range comments (1)
crates/core/src/codec/oci_genai.rs (1)

148-159: 🎯 Functional Correctness | 🟡 Minor | ⚡ Quick win

Reject non-string TEXT.text values.

{"type":"TEXT","text":1} bypasses text flattening, then becomes Text("") here via unwrap_or_default(). Return InvalidArgument instead of silently altering provider content, and add a regression fixture.

Proposed fix
         Some("TEXT") => Ok(ContentPart::Text {
-            text: obj
-                .get("text")
-                .and_then(Json::as_str)
-                .unwrap_or_default()
-                .to_string(),
+            text: match obj.get("text") {
+                None | Some(Json::Null) => String::new(),
+                Some(Json::String(text)) => text.clone(),
+                Some(_) => {
+                    return Err(FlowError::InvalidArgument(
+                        "OCI GenAI TEXT content part text must be a string or null".into(),
+                    ));
+                }
+            },
🤖 Prompt for AI Agents
Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.

In `@crates/core/src/codec/oci_genai.rs` around lines 148 - 159, Update the TEXT
branch of the OCI content decoder to distinguish a missing text field from a
present non-string value: reject non-string TEXT.text values with
InvalidArgument instead of defaulting them to an empty string. Preserve the
existing handling for valid strings and absent fields as intended, and add a
regression fixture covering {"type":"TEXT","text":1}.
🤖 Prompt for all review comments with AI agents
Verify each finding against current code. Fix only still-valid issues, skip the
rest with a brief reason, keep changes minimal, and validate.

Outside diff comments:
In `@crates/core/src/codec/oci_genai.rs`:
- Around line 148-159: Update the TEXT branch of the OCI content decoder to
distinguish a missing text field from a present non-string value: reject
non-string TEXT.text values with InvalidArgument instead of defaulting them to
an empty string. Preserve the existing handling for valid strings and absent
fields as intended, and add a regression fixture covering
{"type":"TEXT","text":1}.

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🧠 Learnings (1)
📚 Learning: 2026-07-28T20:07:29.880Z
Learnt from: willkill07
Repo: NVIDIA/NeMo-Relay PR: 571
File: crates/core/src/api/runtime/state.rs:996-1020
Timestamp: 2026-07-28T20:07:29.880Z
Learning: In NeMo Relay (RELAY-509), sanitizer callback failures must be treated as intentional fail-open behavior. When an event/tool (request/response) or LLM (request/response) sanitizer callback fails, the sanitizer chain should retain and publish the last valid event/payload snapshot (rather than dropping/invalidating the data) and log the failure including callback context (e.g., which sanitizer/callback failed and relevant identifiers). Apply this consistently across all sanitizer chains mentioned in the RELAY-509 documentation/migration guide.

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🔇 Additional comments (8)
crates/core/src/codec/oci_genai.rs (2)

11-64: LGTM!

Also applies to: 126-139, 189-257, 269-445


176-260: 📐 Maintainability & Code Quality

Attach the required core validation evidence.

The supplied summary reports workspace Rust checks, but not the required full core matrix. Please provide results for just test-rust, cargo fmt --all, cargo clippy --workspace --all-targets -- -D warnings, cargo deny check, uv run pre-commit run --all-files, and the configured Python, Go, and Node test targets.

  • crates/core/src/codec/oci_genai.rs#L176-L260: validate OCI response decoding through the required core matrix.
  • crates/core/src/observability/otel_genai.rs#L390-L401: validate the OCI provider projection through the same matrix.

Source: Coding guidelines

crates/core/src/observability/otel_genai.rs (1)

1-388: LGTM!

Also applies to: 404-523

crates/core/tests/unit/codec/oci_genai_tests.rs (2)

106-146: LGTM!


300-507: LGTM!

crates/core/tests/integration/pipeline_tests.rs (3)

33-33: LGTM!

Also applies to: 1476-1517


1536-1536: LGTM!

Also applies to: 1736-1741, 2004-2004


1451-1475: 🗄️ Data Integrity & Integration

No issue: GENERIC toolCalls shape matches the decoder
OCIGenAIChatCodec accepts direct id/name/arguments entries for toolCalls, and also falls back to a nested function object for CohereV2-style payloads.

			> Likely an incorrect or invalid review comment.

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