Bump mlflow from 3.1.4 to 3.11.1 in /python by dependabot[bot] · Pull Request #97 · pinterest/ray

dependabot · 2026-05-21T20:15:08Z

Bumps mlflow from 3.1.4 to 3.11.1.

Release notes

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:

[Evaluation] Allow MetaPromptOptimizer to work without litellm (#22233, @TomeHirata)

[Tracking] Update Databricks API calls to use new gRPC APIs instead of py4j APIs (#22205, @WeichenXu123)

[Build] Add aiohttp as a core dependency of mlflow (#22189, @TomeHirata)

[Evaluation] Extend _get_provider_instance with groq, deepseek, xai, openrouter, ollama, databricks, vertex_ai (#22148, @kriscon-db)

[UI] Move native providers to non-LiteLLM in gateway UI (#22203, @TomeHirata)

[Tracing / Tracking] Add trace_location parameter to create_experiment (#22075, @dbrx-euirim)

[Gateway] Complete Bedrock provider with Converse API support (#21999, @TomeHirata)

[Gateway] Add native Vertex AI gateway provider (#21998, @TomeHirata)

[Gateway] Add native Databricks gateway provider (#21997, @TomeHirata)

[Gateway] Add native Ollama gateway provider (#21995, @TomeHirata)

[Gateway] Add native xAI (Grok) gateway provider (#21993, @TomeHirata)

[Tracing] Use bulk upsert in log_spans() to eliminate per-span ORM overhead (#21954, @harupy)

[Tracing] Add builtin cost_per_token to remove litellm dependency for cost tracking (#22046, @TomeHirata)

[Evaluation] Remove LiteLLM hard dependency from the discovery pipeline and judge adapters (#21739, @harupy)

[Evaluation] Add pipelined predict-score execution for mlflow.genai.evaluate (#20940, @alkispoly-db)

[Tracing / Tracking] Default trace location table_prefix to experiment ID in set_experiment (#21815, @danielseong1)

[Tracking] Add default uvicorn log config with timestamps (#21838, @harupy)

[Tracing / UI] Add Session ID filter to GenAI traces table filter dropdown (#21794, @daniellok-db)

[Evaluation / UI] Add Default Credential Chain auth mode for Bedrock/SageMaker in AI Gateway (#21061, @timsolovev)

[UI] Add multi metric bar chart support (#21258, @RenzoMXD)

[Tracking] Add TCP keepalive to HTTP sessions to detect stale connections and reduce timeout hangs (#21514, @mobaniha)

[Evaluation] Add proxy URL support for make_judge (#21185, @yukimori)

[UI] Improve run group filter to use grouping criteria instead of run IDs (#21072, @daniellok-db)

[UI] Add tool selector to Tool Calls charts and fix dark mode/sizing (#20865, @B-Step62)

[UI] Graph View Traces + OpenAI (#20607, @joelrobin18)

[UI] Show run description in chart tooltip (#21580, @KaushalVachhani)

[Evaluation / Tracing / UI] Add bulk judge execution from traces table toolbar with status feedback (#21270, @PattaraS)

[Gateway] Add Redis-backed BudgetTracker for distributed gateway deployments (#21504, @TomeHirata)

... (truncated)

Changelog

Sourced from mlflow'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:

[Evaluation] Allow MetaPromptOptimizer to work without litellm (#22233, @TomeHirata)

[Tracking] Update Databricks API calls to use new gRPC APIs instead of py4j APIs (#22205, @WeichenXu123)

[Build] Add aiohttp as a core dependency of mlflow (#22189, @TomeHirata)

[Evaluation] Extend _get_provider_instance with groq, deepseek, xai, openrouter, ollama, databricks, vertex_ai (#22148, @kriscon-db)

[UI] Move native providers to non-LiteLLM in gateway UI (#22203, @TomeHirata)

[Tracing / Tracking] Add trace_location parameter to create_experiment (#22075, @dbrx-euirim)

[Gateway] Complete Bedrock provider with Converse API support (#21999, @TomeHirata)

[Gateway] Add native Vertex AI gateway provider (#21998, @TomeHirata)

[Gateway] Add native Databricks gateway provider (#21997, @TomeHirata)

[Gateway] Add native Ollama gateway provider (#21995, @TomeHirata)

[Gateway] Add native xAI (Grok) gateway provider (#21993, @TomeHirata)

[Tracing] Use bulk upsert in log_spans() to eliminate per-span ORM overhead (#21954, @harupy)

[Tracing] Add builtin cost_per_token to remove litellm dependency for cost tracking (#22046, @TomeHirata)

[Evaluation] Remove LiteLLM hard dependency from the discovery pipeline and judge adapters (#21739, @harupy)

[Evaluation] Add pipelined predict-score execution for mlflow.genai.evaluate (#20940, @alkispoly-db)

[Tracing / Tracking] Default trace location table_prefix to experiment ID in set_experiment (#21815, @danielseong1)

[Tracking] Add default uvicorn log config with timestamps (#21838, @harupy)

[Tracing / UI] Add Session ID filter to GenAI traces table filter dropdown (#21794, @daniellok-db)

[Evaluation / UI] Add Default Credential Chain auth mode for Bedrock/SageMaker in AI Gateway (#21061, @timsolovev)

[UI] Add multi metric bar chart support (#21258, @RenzoMXD)

[Tracking] Add TCP keepalive to HTTP sessions to detect stale connections and reduce timeout hangs (#21514, @mobaniha)

[Evaluation] Add proxy URL support for make_judge (#21185, @yukimori)

[UI] Improve run group filter to use grouping criteria instead of run IDs (#21072, @daniellok-db)

[UI] Add tool selector to Tool Calls charts and fix dark mode/sizing (#20865, @B-Step62)

[UI] Graph View Traces + OpenAI (#20607, @joelrobin18)

[UI] Show run description in chart tooltip (#21580, @KaushalVachhani)

[Evaluation / Tracing / UI] Add bulk judge execution from traces table toolbar with status feedback (#21270, @PattaraS)

... (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

Bumps [mlflow](https://github.com/mlflow/mlflow) from 3.1.4 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@v3.1.4...v3.11.1) --- updated-dependencies: - dependency-name: mlflow dependency-version: 3.11.1 dependency-type: direct:production ... Signed-off-by: dependabot[bot] <support@github.com>

dependabot Bot added dependencies Pull requests that update a dependency file python Pull requests that update python code labels May 21, 2026

dependabot Bot mentioned this pull request May 21, 2026

Bump mlflow from 2.22.0 to 3.11.0rc1 in /python #91

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dependabot Bot changed the title ~~Bump mlflow from 2.22.0 to 3.11.1 in /python~~ Bump mlflow from 3.1.4 to 3.11.1 in /python Jun 1, 2026

dependabot Bot force-pushed the dependabot/pip/python/mlflow-3.11.1 branch from 8c744fb to bec59c7 Compare June 1, 2026 18:59

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Bump mlflow from 3.1.4 to 3.11.1 in /python#97

Bump mlflow from 3.1.4 to 3.11.1 in /python#97
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v3.11.1

3.11.1 (2026-04-07)

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