# mlflow
pip install git+https://github.com/mlflow/mlflow.git@refs/pull/18929/merge
# mlflow-skinny
pip install git+https://github.com/mlflow/mlflow.git@refs/pull/18929/merge#subdirectory=libs/skinny

%sh curl -LsSf https://raw.githubusercontent.com/mlflow/mlflow/HEAD/dev/install-skinny.sh | sh -s pull/18929/merge

Related Issues/PRs

Resolve #[issue_number]

What changes are proposed in this pull request?

The /v1/traces OTLP endpoint was returning JSON (via Pydantic model) while declaring Content-Type: application/x-protobuf, causing protobuf parsers to fail with "cannot parse invalid wire-format data".

Changes:

• Replace Pydantic response model with ExportTraceServiceResponse protobuf serialization
• Remove unused OTelExportTraceServiceResponse class and response parameter
• Return serialized protobuf bytes in FastAPI Response with correct media type

Before:

# Returned JSON despite protobuf Content-Type header
return OTelExportTraceServiceResponse()  # Pydantic model

After:

# Returns actual protobuf bytes
response_message = ExportTraceServiceResponse()
return Response(
    content=response_message.SerializeToString(),
    media_type="application/x-protobuf",
)

How is this PR tested?

• Existing unit/integration tests (15/15 pass)
• New unit/integration tests
• Manual tests

Added test_response_is_protobuf_format() that verifies:

• Response Content-Type is application/x-protobuf
• Response body deserializes as valid ExportTraceServiceResponse

Does this PR require documentation update?

• No. You can skip the rest of this section.
• Yes. I've updated:
  • Examples
  • API references
  • Instructions

Release Notes

Is this a user-facing change?

• No. You can skip the rest of this section.
• Yes. Give a description of this change to be included in the release notes for MLflow users.

Fixed /v1/traces endpoint to return valid protobuf responses per OTLP specification, resolving compatibility issues with Go and other strict protobuf clients.

What component(s), interfaces, languages, and integrations does this PR affect?

Components

• area/tracking: Tracking Service, tracking client APIs, autologging
• area/models: MLmodel format, model serialization/deserialization, flavors
• area/model-registry: Model Registry service, APIs, and the fluent client calls for Model Registry
• area/scoring: MLflow Model server, model deployment tools, Spark UDFs
• area/evaluation: MLflow model evaluation features, evaluation metrics, and evaluation workflows
• area/gateway: MLflow AI Gateway client APIs, server, and third-party integrations
• area/prompts: MLflow prompt engineering features, prompt templates, and prompt management
• area/tracing: MLflow Tracing features, tracing APIs, and LLM tracing functionality
• area/projects: MLproject format, project running backends
• area/uiux: Front-end, user experience, plotting, JavaScript, JavaScript dev server
• area/build: Build and test infrastructure for MLflow
• area/docs: MLflow documentation pages

How should the PR be classified in the release notes? Choose one:

• rn/none - No description will be included. The PR will be mentioned only by the PR number in the "Small Bugfixes and Documentation Updates" section
• rn/breaking-change - The PR will be mentioned in the "Breaking Changes" section
• rn/feature - A new user-facing feature worth mentioning in the release notes
• rn/bug-fix - A user-facing bug fix worth mentioning in the release notes
• rn/documentation - A user-facing documentation change worth mentioning in the release notes

Should this PR be included in the next patch release?

• Yes (this PR will be cherry-picked and included in the next patch release)
• No (this PR will be included in the next minor release)

• Fixes [BUG] v1/traces response is in json format instead of protobuf #18927

💬 We'd love your input! Share your thoughts on Copilot coding agent in our 2 minute survey.