Bump mlflow from 2.16.0 to 3.4.0 #25

dependabot · 2025-10-01T18:26:44Z

Bumps mlflow from 2.16.0 to 3.4.0.

Release notes

v3.4.0

MLflow 3.4.0rc0 includes several major features and improvements

Major New Features

📊 OpenTelemetry Metrics Export: MLflow now exports span-level statistics as OpenTelemetry metrics, providing enhanced observability and monitoring capabilities for traced applications. (#17325, @dbczumar)

🤖 MCP Server Integration: Introducing the Model Context Protocol (MCP) server for MLflow, enabling AI assistants and LLMs to interact with MLflow programmatically. (#17122, @harupy)

🧑‍⚖️ Custom Judges API: New make_judge API enables creation of custom evaluation judges for assessing LLM outputs with domain-specific criteria. (#17647, @BenWilson2, @dbczumar, @alkispoly-db, @smoorjani)

📈 Correlations Backend: Implemented backend infrastructure for storing and computing correlations between experiment metrics using NPMI (Normalized Pointwise Mutual Information). (#17309, #17368, @BenWilson2)

🗂️ Evaluation Datasets: MLflow now supports storing and versioning evaluation datasets directly within experiments for reproducible model assessment. (#17447, @BenWilson2)

🔗 Databricks Backend for MLflow Server: MLflow server can now use Databricks as a backend, enabling seamless integration with Databricks workspaces. (#17411, @nsthorat)

🤖 Claude Autologging: Automatic tracing support for Claude AI interactions, capturing conversations and model responses. (#17305, @smoorjani)

🌊 Strands Agent Tracing: Added comprehensive tracing support for Strands agents, including automatic instrumentation for agent workflows and interactions. (#17151, @joelrobin18)

🧪 Experiment Types in UI: MLflow now introduces experiment types, helping reduce clutter between classic ML/DL and GenAI features. MLflow auto-detects the type, but you can easily adjust it via a selector next to the experiment name. (#17605, @daniellok-db)

Features:

[Evaluation] Add ability to pass tags via dataframe in mlflow.genai.evaluate (#17549, @smoorjani)

[Evaluation] Add custom judge model support for Safety and RetrievalRelevance builtin scorers (#17526, @dbrx-euirim)

[Tracing] Add AI commands as MCP prompts for LLM interaction (#17608, @nsthorat)

[Tracing] Add MLFLOW_ENABLE_OTLP_EXPORTER environment variable (#17505, @dbczumar)

[Tracing] Support OTel and MLflow dual export (#17187, @dbczumar)

[Tracing] Make set_destination use ContextVar for thread safety (#17219, @B-Step62)

[CLI] Add MLflow commands CLI for exposing prompt commands to LLMs (#17530, @nsthorat)

[CLI] Add 'mlflow runs link-traces' command (#17444, @nsthorat)

[CLI] Add 'mlflow runs create' command for programmatic run creation (#17417, @nsthorat)

[CLI] Add MLflow traces CLI command with comprehensive search and management capabilities (#17302, @nsthorat)

[CLI] Add --env-file flag to all MLflow CLI commands (#17509, @nsthorat)

[Tracking] Backend for storing scorers in MLflow experiments (#17090, @WeichenXu123)

[Model Registry] Allow cross-workspace copying of model versions between WMR and UC (#17458, @arpitjasa-db)

[Models] Add automatic Git-based model versioning for GenAI applications (#17076, @harupy)

[Models] Improve WheeledModel._download_wheels safety (#17004, @serena-ruan)

[Projects] Support resume run for Optuna hyperparameter optimization (#17191, @lu-wang-dl)

[Scoring] Add MLFLOW_DEPLOYMENT_CLIENT_HTTP_REQUEST_TIMEOUT environment variable (#17252, @dbczumar)

[UI] Add ability to hide/unhide all finished runs in Chart view (#17143, @joelrobin18)

[Telemetry] Add MLflow OSS telemetry for invoke_custom_judge_model (#17585, @dbrx-euirim)

Bug fixes:

[Evaluation] Implement DSPy LM interface for default Databricks model serving (#17672, @smoorjani)

[Evaluation] Fix aggregations incorrectly applied to legacy scorer interface (#17596, @BenWilson2)

[Evaluation] Add Unity Catalog table source support for mlflow.evaluate (#17546, @BenWilson2)

[Evaluation] Fix custom prompt judge encoding issues with custom judge models (#17584, @dbrx-euirim)

[Tracking] Fix OpenAI autolog to properly reconstruct Response objects from streaming events (#17535, @WeichenXu123)

[Tracking] Add basic authentication support in TypeScript SDK (#17436, @kevin-lyn)

[Tracking] Update scorer endpoints to v3.0 API specification (#17409, @WeichenXu123)

[Tracking] Fix scorer status handling in MLflow tracking backend (#17379, @WeichenXu123)

[Tracking] Fix missing source-run information in UI (#16682, @WeichenXu123)

[Scoring] Fix spark_udf to always use stdin_serve for model serving (#17580, @WeichenXu123)

[Scoring] Fix a bug with Spark UDF usage of uv as an environment manager (#17489, @WeichenXu123)

... (truncated)

Changelog

Sourced from mlflow's changelog.

3.4.0rc0 (2025-09-11)

MLflow 3.4.0rc0 includes several major features and improvements

Major New Features

📊 OpenTelemetry Metrics Export: MLflow now exports span-level statistics as OpenTelemetry metrics, providing enhanced observability and monitoring capabilities for traced applications. (#17325, @dbczumar)

🤖 MCP Server Integration: Introducing the Model Context Protocol (MCP) server for MLflow, enabling AI assistants and LLMs to interact with MLflow programmatically. (#17122, @harupy)

🧑‍⚖️ Custom Judges API: New make_judge API enables creation of custom evaluation judges for assessing LLM outputs with domain-specific criteria. (#17647, @BenWilson2, @dbczumar, @alkispoly-db, @smoorjani)

📈 Correlations Backend: Implemented backend infrastructure for storing and computing correlations between experiment metrics using NPMI (Normalized Pointwise Mutual Information). (#17309, #17368, @BenWilson2)

🗂️ Evaluation Datasets: MLflow now supports storing and versioning evaluation datasets directly within experiments for reproducible model assessment. (#17447, @BenWilson2)

🔗 Databricks Backend for MLflow Server: MLflow server can now use Databricks as a backend, enabling seamless integration with Databricks workspaces. (#17411, @nsthorat)

🤖 Claude Autologging: Automatic tracing support for Claude AI interactions, capturing conversations and model responses. (#17305, @smoorjani)

🌊 Strands Agent Tracing: Added comprehensive tracing support for Strands agents, including automatic instrumentation for agent workflows and interactions. (#17151, @joelrobin18)

🧪 Experiment Types in UI: MLflow now introduces experiment types, helping reduce clutter between classic ML/DL and GenAI features. MLflow auto-detects the type, but you can easily adjust it via a selector next to the experiment name. (#17605, @daniellok-db)

Features:

[Evaluation] Add ability to pass tags via dataframe in mlflow.genai.evaluate (#17549, @smoorjani)

[Evaluation] Add custom judge model support for Safety and RetrievalRelevance builtin scorers (#17526, @dbrx-euirim)

[Tracing] Add AI commands as MCP prompts for LLM interaction (#17608, @nsthorat)

[Tracing] Add MLFLOW_ENABLE_OTLP_EXPORTER environment variable (#17505, @dbczumar)

[Tracing] Support OTel and MLflow dual export (#17187, @dbczumar)

[Tracing] Make set_destination use ContextVar for thread safety (#17219, @B-Step62)

[CLI] Add MLflow commands CLI for exposing prompt commands to LLMs (#17530, @nsthorat)

[CLI] Add 'mlflow runs link-traces' command (#17444, @nsthorat)

[CLI] Add 'mlflow runs create' command for programmatic run creation (#17417, @nsthorat)

[CLI] Add MLflow traces CLI command with comprehensive search and management capabilities (#17302, @nsthorat)

[CLI] Add --env-file flag to all MLflow CLI commands (#17509, @nsthorat)

[Tracking] Backend for storing scorers in MLflow experiments (#17090, @WeichenXu123)

[Model Registry] Allow cross-workspace copying of model versions between WMR and UC (#17458, @arpitjasa-db)

[Models] Add automatic Git-based model versioning for GenAI applications (#17076, @harupy)

[Models] Improve WheeledModel._download_wheels safety (#17004, @serena-ruan)

[Projects] Support resume run for Optuna hyperparameter optimization (#17191, @lu-wang-dl)

[Scoring] Add MLFLOW_DEPLOYMENT_CLIENT_HTTP_REQUEST_TIMEOUT environment variable (#17252, @dbczumar)

[UI] Add ability to hide/unhide all finished runs in Chart view (#17143, @joelrobin18)

[Telemetry] Add MLflow OSS telemetry for invoke_custom_judge_model (#17585, @dbrx-euirim)

Bug fixes:

[Evaluation] Implement DSPy LM interface for default Databricks model serving (#17672, @smoorjani)

[Evaluation] Fix aggregations incorrectly applied to legacy scorer interface (#17596, @BenWilson2)

[Evaluation] Add Unity Catalog table source support for mlflow.evaluate (#17546, @BenWilson2)

[Evaluation] Fix custom prompt judge encoding issues with custom judge models (#17584, @dbrx-euirim)

[Tracking] Fix OpenAI autolog to properly reconstruct Response objects from streaming events (#17535, @WeichenXu123)

[Tracking] Add basic authentication support in TypeScript SDK (#17436, @kevin-lyn)

[Tracking] Update scorer endpoints to v3.0 API specification (#17409, @WeichenXu123)

[Tracking] Fix scorer status handling in MLflow tracking backend (#17379, @WeichenXu123)

[Tracking] Fix missing source-run information in UI (#16682, @WeichenXu123)

[Scoring] Fix spark_udf to always use stdin_serve for model serving (#17580, @WeichenXu123)

... (truncated)

Commits

78d0750 ResponsesAgent: additional helpers and parsing code (#15964)
cf51b18 Fix bug in Evaluation Datasets handler and misconfigured test (#17780)
8202730 Fix builtin judge deserialization code (#17766)
f8abcfa Fix create_experiment to return RESOURCE_ALREADY_EXISTS instead of `BAD_R...
c16fb51 Make Scorer.register using active experiment if experiment_id param is not pr...
4149587 Exclude immutable tags when setting tags (#17748)
126412c Run python3 dev/update_mlflow_versions.py pre-release ... (#17761)
1efa7aa Strands test fix (#17666)
fa7dc63 Remove duplicate redirects from the config file (#17706)
9110f2a Add docs for make_judge (#17690)
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Bumps [mlflow](https://github.com/mlflow/mlflow) from 2.16.0 to 3.4.0. - [Release notes](https://github.com/mlflow/mlflow/releases) - [Changelog](https://github.com/mlflow/mlflow/blob/master/CHANGELOG.md) - [Commits](mlflow/mlflow@v2.16.0...v3.4.0) --- updated-dependencies: - dependency-name: mlflow dependency-version: 3.4.0 dependency-type: direct:production update-type: version-update:semver-major ... Signed-off-by: dependabot[bot] <[email protected]>

dependabot bot added dependencies Pull requests that update a dependency file python Pull requests that update python code labels Oct 1, 2025

dependabot bot mentioned this pull request Oct 1, 2025

Bump mlflow from 2.16.0 to 3.3.2 #21

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Bump mlflow from 2.16.0 to 3.4.0 #25

Bump mlflow from 2.16.0 to 3.4.0 #25

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v3.4.0

Major New Features

3.4.0rc0 (2025-09-11)

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