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chore(deps): bump mlflow-skinny from 3.10.1 to 3.11.1#128

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Apr 16, 2026
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chore(deps): bump mlflow-skinny from 3.10.1 to 3.11.1#128
mpkrass7 merged 1 commit intomainfrom
dependabot/pip/mlflow-skinny-3.11.1

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@dependabot dependabot Bot commented on behalf of github Apr 16, 2026 •
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Bumps mlflow-skinny from 3.10.1 to 3.11.1.

Release notes

Sourced from mlflow-skinny's releases.

v3.11.1

MLflow 3.11.1 includes several major features and improvements.

Major New Features:

  • 🔍 Automatic Issue Identification: Automatically identify quality issues in your agent with AI! Use the new "Detect Issues" button in the traces table to analyze selected traces and surface potential problems across categories like correctness, safety, and performance. Issues are linked directly to traces for easy investigation and debugging. Docs (#21431, #21204, #21165, #21163, #21161, @​smoorjani, @​serena-ruan)
  • 💰 Gateway Budget Alerts & Limits: Control your AI Gateway spending with configurable budget policies! Set spending limits by time window (daily, weekly, or monthly), receive alerts before hitting limits, and prevent runaway costs with automatic request blocking. The new budget management UI lets you track spending, configure webhooks for notifications, and monitor violations across all your gateway endpoints. Docs (#21116, #21534, #21569, #21473, #21108, @​TomeHirata, @​copilot-swe-agent)
  • 📊 Trace Graph View: Visualize complex trace hierarchies with an interactive graph view! Navigate multi-level trace structures, understand parent-child relationships at a glance, and debug complex systems more effectively with a visual representation of your trace topology. Docs (#20607, @​joelrobin18)
  • 🌐 Native OpenTelemetry GenAI Convention Support: MLflow now natively supports the OpenTelemetry GenAI Semantic Conventions for trace export! When exporting traces via OTLP with MLFLOW_ENABLE_OTEL_GENAI_SEMCONV enabled, MLflow automatically translates them to follow the OTel GenAI semantic conventions, enabling seamless integration with OTel-compatible observability platforms while preserving GenAI-specific metadata. Docs (#21494, #21495, @​B-Step62)
  • 🔧 OpenCode Tracing Integration: Debug smarter with OpenCode CLI integration! Track and analyze code execution flows directly from your development workflow, making it easier to identify performance bottlenecks and trace issues back to specific code paths. Docs (#20133, @​joelrobin18)
  • ⚡ Native UV Support for Model Dependencies: Automatic dependency inference now supports UV! MLflow automatically detects UV projects and captures exact, locked dependencies from your lockfile when logging models, ensuring reproducible environments. Docs (#20344, #20935, @​debu-sinha)
  • 🔒 Pickle-Free Model Serialization: Enhance security with pickle-free model formats! MLflow now supports safer model serialization using torch.export and skops formats, with improved controls when MLFLOW_ALLOW_PICKLE_DESERIALIZATION=False. Comprehensive documentation guides you through migrating existing models to pickle-free formats for production deployments. Docs (#21404, #21188, #20774, @​WeichenXu123)

Breaking Changes:

  • ⚠️ TypeScript SDK Package Renaming: The MLflow TypeScript SDK packages have been renamed to use npm organization scoping. If you're using the TypeScript SDK, update your package.json dependencies and import statements: mlflow-tracing → @mlflow/core, mlflow-openai → @mlflow/openai, mlflow-anthropic → @mlflow/anthropic, mlflow-gemini → @mlflow/gemini. All packages are now at version 0.2.0. (#20792, @​B-Step62)
  • Remove MLFLOW_ENABLE_INCREMENTAL_SPAN_EXPORT environment variable (#22182, @​PattaraS)
  • Remove litellm and gepa from genai extras (#22059, @​TomeHirata)
  • Block / and : in Registered Model names (#21458, @​Bhuvan-08)

Features:

... (truncated)

Changelog

Sourced from mlflow-skinny's changelog.

3.11.1 (2026-04-07)

MLflow 3.11.1 includes several major features and improvements.

Major New Features:

  • 🔍 Automatic Issue Identification: Automatically identify quality issues in your agent with AI! Use the new "Detect Issues" button in the traces table to analyze selected traces and surface potential problems across categories like correctness, safety, and performance. Issues are linked directly to traces for easy investigation and debugging. Docs (#21431, #21204, #21165, #21163, #21161, @​smoorjani, @​serena-ruan)
  • 💰 Gateway Budget Alerts & Limits: Control your AI Gateway spending with configurable budget policies! Set spending limits by time window (daily, weekly, or monthly), receive alerts before hitting limits, and prevent runaway costs with automatic request blocking. The new budget management UI lets you track spending, configure webhooks for notifications, and monitor violations across all your gateway endpoints. Docs (#21116, #21534, #21569, #21473, #21108, @​TomeHirata, @​copilot-swe-agent)
  • 📊 Trace Graph View: Visualize complex trace hierarchies with an interactive graph view! Navigate multi-level trace structures, understand parent-child relationships at a glance, and debug complex systems more effectively with a visual representation of your trace topology. Docs (#20607, @​joelrobin18)
  • 🌐 Native OpenTelemetry GenAI Convention Support: MLflow now natively supports the OpenTelemetry GenAI Semantic Conventions for trace export! When exporting traces via OTLP with MLFLOW_ENABLE_OTEL_GENAI_SEMCONV enabled, MLflow automatically translates them to follow the OTel GenAI semantic conventions, enabling seamless integration with OTel-compatible observability platforms while preserving GenAI-specific metadata. Docs (#21494, #21495, @​B-Step62)
  • 🔧 OpenCode Tracing Integration: Debug smarter with OpenCode CLI integration! Track and analyze code execution flows directly from your development workflow, making it easier to identify performance bottlenecks and trace issues back to specific code paths. Docs (#20133, @​joelrobin18)
  • ⚡ Native UV Support for Model Dependencies: Automatic dependency inference now supports UV! MLflow automatically detects UV projects and captures exact, locked dependencies from your lockfile when logging models, ensuring reproducible environments. Docs (#20344, #20935, @​debu-sinha)
  • 🔒 Pickle-Free Model Serialization: Enhance security with pickle-free model formats! MLflow now supports safer model serialization using torch.export and skops formats, with improved controls when MLFLOW_ALLOW_PICKLE_DESERIALIZATION=False. Comprehensive documentation guides you through migrating existing models to pickle-free formats for production deployments. Docs (#21404, #21188, #20774, @​WeichenXu123)

Breaking Changes:

  • ⚠️ TypeScript SDK Package Renaming: The MLflow TypeScript SDK packages have been renamed to use npm organization scoping. If you're using the TypeScript SDK, update your package.json dependencies and import statements: mlflow-tracing → @mlflow/core, mlflow-openai → @mlflow/openai, mlflow-anthropic → @mlflow/anthropic, mlflow-gemini → @mlflow/gemini. All packages are now at version 0.2.0. (#20792, @​B-Step62)
  • Remove MLFLOW_ENABLE_INCREMENTAL_SPAN_EXPORT environment variable (#22182, @​PattaraS)
  • Remove litellm and gepa from genai extras (#22059, @​TomeHirata)
  • Block / and : in Registered Model names (#21458, @​Bhuvan-08)

Features:

... (truncated)

Commits
  • 09179c6 Bump version to 3.11.1 (#22400)
  • 38d75c2 Fix DatabricksProvider to use OpenAI-compatible endpoint URLs (#22393)
  • 0734e56 fix
  • 46a2d4d fix
  • 7a6b01b format
  • 8b71fa7 Fix _lookup_model_info all-provider scan causing network latency (#22369)
  • deaffc1 Update model catalog CI workflow to use update_model_catalog.py (#22261)
  • 1b87ff3 Add aiohttp as a core dependency of mlflow (#22189)
  • 7f08e88 Normalize get_provider_name() to align with `model_prices_and_context_windo...
  • bd3114b Move LLM calling utilities to mlflow/genai/utils/llm_utils.py (#22234)
  • Additional commits viewable in compare view

@dependabot dependabot Bot added dependencies Pull requests that update a dependency file python Pull requests that update python code labels Apr 16, 2026
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mpkrass7 commented Apr 16, 2026

@dependabot rebase

@dependabot
chore(deps): bump mlflow-skinny from 3.10.1 to 3.11.1
899da3b 
Bumps [mlflow-skinny](https://github.com/mlflow/mlflow) from 3.10.1 to 3.11.1.
- [Release notes](https://github.com/mlflow/mlflow/releases)
- [Changelog](https://github.com/mlflow/mlflow/blob/master/CHANGELOG.md)
- [Commits](mlflow/mlflow@v3.10.1...v3.11.1)

---
updated-dependencies:
- dependency-name: mlflow-skinny
  dependency-version: 3.11.1
  dependency-type: direct:production
  update-type: version-update:semver-minor
...

Signed-off-by: dependabot[bot] <support@github.com>
@dependabot dependabot Bot force-pushed the dependabot/pip/mlflow-skinny-3.11.1 branch from 8ea4ecf to 899da3b Compare April 16, 2026 15:58
@mpkrass7 mpkrass7 merged commit 7d355e8 into main Apr 16, 2026
1 check passed
@dependabot dependabot Bot deleted the dependabot/pip/mlflow-skinny-3.11.1 branch April 16, 2026 16:02
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