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@dependabot dependabot bot commented on behalf of github Oct 22, 2025

Bumps the pip group with 1 update in the /data-science/classification-with-svm directory: mlflow.
Bumps the pip group with 1 update in the /data-science/data-analysis-with-var directory: mlflow.
Bumps the pip group with 1 update in the /deep-learning/classification-with-keras directory: mlflow.
Bumps the pip group with 1 update in the /deep-learning/question-answering-with-bert directory: mlflow.
Bumps the pip group with 1 update in the /deep-learning/recommendation-system-with-tensorflow directory: mlflow.
Bumps the pip group with 1 update in the /deep-learning/spam-detection-with-nlp directory: mlflow.
Bumps the pip group with 1 update in the /deep-learning/super-resolution-with-fsrcnn directory: mlflow.
Bumps the pip group with 1 update in the /deep-learning/text-generation-with-rnn directory: mlflow.
Bumps the pip group with 2 updates in the /generative-ai/agentic-feedback-analyzer-with-langgraph directory: mlflow and pypdf.
Bumps the pip group with 2 updates in the /generative-ai/agentic-github-repo-analyzer-with-langgraph directory: mlflow and pypdf.
Bumps the pip group with 1 update in the /generative-ai/automated-evaluation-with-structured-outputs directory: mlflow.
Bumps the pip group with 1 update in the /generative-ai/code-generation-with-langchain directory: mlflow.
Bumps the pip group with 1 update in the /generative-ai/fine-tuning-with-orpo directory: mlflow.
Bumps the pip group with 1 update in the /generative-ai/grammar-correction-with-langchain directory: mlflow.
Bumps the pip group with 1 update in the /generative-ai/image-generation-with-stablediffusion directory: mlflow.
Bumps the pip group with 2 updates in the /generative-ai/multi-modal-rag-with-langchain-vllm directory: mlflow and vllm.
Bumps the pip group with 1 update in the /generative-ai/text-generation-with-langchain directory: mlflow.
Bumps the pip group with 1 update in the /generative-ai/text-summarization-with-langchain directory: mlflow.
Bumps the pip group with 1 update in the /generative-ai/vanilla-rag-with-langchain directory: mlflow.
Bumps the pip group with 1 update in the /ngc-integration/agentic-rag-with-tensorrtllm directory: mlflow.
Bumps the pip group with 1 update in the /ngc-integration/audio-translation-with-nemo directory: mlflow.
Bumps the pip group with 1 update in the /ngc-integration/data-analysis-with-cudf directory: mlflow.
Bumps the pip group with 1 update in the /ngc-integration/data-visualization-with-cudf directory: mlflow.
Bumps the pip group with 1 update in the /ngc-integration/vacation-recommendation-with-bert directory: mlflow.

Updates mlflow from 2.21.2 to 3.5.0rc0

Release notes

Sourced from mlflow's releases.

v3.5.0rc0

MLflow 3.5.0rc0 includes several major features and improvements

Major new features:

  • 🤖 Tracing support for Claude Code SDK: MLflow now provides a tracing integration for both the Claude Code CLI and SDK! Configure the autologging integration to track your prompts, Claude's responses, tool calls, and more. Check out this doc page to get started. (#18022, @​smoorjani)
  • Improved UI homepage: The MLflow UI's homepage has been updated to help you get started with more of our latest features. This page will be updated regularly moving forward, allowing you to get more in-product guidance. (#18098, @​B-Step62)
  • 🗂️ Evaluation datasets UI integration: In MLflow 3.4.0, we released backend support for creating evaluation datasets for GenAI applications. In this release, we've added a new tab to the MLflow Experiment UI, allowing you to create, manage, and export traces to your datasets without having to write a line of code. (#18110, @​daniellok-db)
  • 🧮 GEPA support for prompt optimization: MLflow's prompt optimization feature now supports the GEPA algorithm, allowing you to achieve higher performing prompts with less rollouts. For instructions on how to get started with prompt optimization, visit this doc page! (#18031, @​TomeHirata)
  • 🔐 Security middleware layer for tracking server: MLflow now ships with a security middleware layer by default, allowing you to protect against DNS rebinding, CORS attacks, and more. Read the documentation here to learn how to configure these options. (#17910, @​BenWilson2)

Stay tuned for the full release, which will be packed with more features and bugfixes.

To try out this release candidate, please run:

pip install mlflow==3.5.0rc0

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:

... (truncated)

Changelog

Sourced from mlflow's changelog.

3.5.0rc0 (2025-10-08)

MLflow 3.5.0rc0 includes several major features and improvements

Major new features:

  • 🤖 Tracing support for Claude Code SDK: MLflow now provides a tracing integration for both the Claude Code CLI and SDK! Configure the autologging integration to track your prompts, Claude's responses, tool calls, and more. Check out this doc page to get started. (#18022, @​smoorjani)
  • Improved UI homepage: The MLflow UI's homepage has been updated to help you get started with more of our latest features. This page will be updated regularly moving forward, allowing you to get more in-product guidance.
  • 🗂️ Evaluation datasets UI integration: In MLflow 3.4.0, we released backend support for creating evaluation datasets for GenAI applications. In this release, we've added a new tab to the MLflow Experiment UI, allowing you to create, manage, and export traces to your datasets without having to write a line of code.
  • 🧮 GEPA support for prompt optimization: MLflow's prompt optimization feature now supports the GEPA algorithm, allowing you to achieve higher performing prompts with less rollouts. For instructions on how to get started with prompt optimization, visit this doc page!
  • 🔐 Security middleware layer for tracking server: MLflow now ships with a security middleware layer by default, allowing you to protect against DNS rebinding, CORS attacks, and more. Read the documentation here to learn how to configure these options.

Stay tuned for the full release, which will be packed with more features and bugfixes.

To try out this release candidate, please run:

pip install mlflow==3.5.0rc0

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:

... (truncated)

Commits
  • 19c618c Run python3 dev/update_mlflow_versions.py pre-release ... (#18181)
  • 13115e4 Support GEPA in mlflow.genai.optimize_prompt (#18031)
  • fa83107 Run python3 dev/update_ml_package_versions.py (#18177)
  • 16fc22f Add uv lock call after pyproject.toml generation in DEV branch (#18180)
  • be2125a Run python3 dev/update_requirements.py && python3 bin/... (#18176)
  • 2fd3145 Dump sql_warehouse_id into trace UI mimebundle (#18165)
  • 5cb6a95 Replace Docker with uv in tests/test_import.py for faster test execution (#18...
  • eaadd39 Add support for trace inputs to built-in scorers (#17943)
  • 30f2f55 Add B012 (jump-statement-in-finally) rule to ruff configuration (#18170)
  • 97ac7e1 Increase MAX_DOCSTRING_LENGTH_RATIO to 1.25 and remove redundant test docstri...
  • Additional commits viewable in compare view

Updates mlflow from 2.21.2 to 3.5.0rc0

Release notes

Sourced from mlflow's releases.

v3.5.0rc0

MLflow 3.5.0rc0 includes several major features and improvements

Major new features:

  • 🤖 Tracing support for Claude Code SDK: MLflow now provides a tracing integration for both the Claude Code CLI and SDK! Configure the autologging integration to track your prompts, Claude's responses, tool calls, and more. Check out this doc page to get started. (#18022, @​smoorjani)
  • Improved UI homepage: The MLflow UI's homepage has been updated to help you get started with more of our latest features. This page will be updated regularly moving forward, allowing you to get more in-product guidance. (#18098, @​B-Step62)
  • 🗂️ Evaluation datasets UI integration: In MLflow 3.4.0, we released backend support for creating evaluation datasets for GenAI applications. In this release, we've added a new tab to the MLflow Experiment UI, allowing you to create, manage, and export traces to your datasets without having to write a line of code. (#18110, @​daniellok-db)
  • 🧮 GEPA support for prompt optimization: MLflow's prompt optimization feature now supports the GEPA algorithm, allowing you to achieve higher performing prompts with less rollouts. For instructions on how to get started with prompt optimization, visit this doc page! (#18031, @​TomeHirata)
  • 🔐 Security middleware layer for tracking server: MLflow now ships with a security middleware layer by default, allowing you to protect against DNS rebinding, CORS attacks, and more. Read the documentation here to learn how to configure these options. (#17910, @​BenWilson2)

Stay tuned for the full release, which will be packed with more features and bugfixes.

To try out this release candidate, please run:

pip install mlflow==3.5.0rc0

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:

... (truncated)

Changelog

Sourced from mlflow's changelog.

3.5.0rc0 (2025-10-08)

MLflow 3.5.0rc0 includes several major features and improvements

Major new features:

  • 🤖 Tracing support for Claude Code SDK: MLflow now provides a tracing integration for both the Claude Code CLI and SDK! Configure the autologging integration to track your prompts, Claude's responses, tool calls, and more. Check out this doc page to get started. (#18022, @​smoorjani)
  • Improved UI homepage: The MLflow UI's homepage has been updated to help you get started with more of our latest features. This page will be updated regularly moving forward, allowing you to get more in-product guidance.
  • 🗂️ Evaluation datasets UI integration: In MLflow 3.4.0, we released backend support for creating evaluation datasets for GenAI applications. In this release, we've added a new tab to the MLflow Experiment UI, allowing you to create, manage, and export traces to your datasets without having to write a line of code.
  • 🧮 GEPA support for prompt optimization: MLflow's prompt optimization feature now supports the GEPA algorithm, allowing you to achieve higher performing prompts with less rollouts. For instructions on how to get started with prompt optimization, visit this doc page!
  • 🔐 Security middleware layer for tracking server: MLflow now ships with a security middleware layer by default, allowing you to protect against DNS rebinding, CORS attacks, and more. Read the documentation here to learn how to configure these options.

Stay tuned for the full release, which will be packed with more features and bugfixes.

To try out this release candidate, please run:

pip install mlflow==3.5.0rc0

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:

... (truncated)

Commits
  • 19c618c Run python3 dev/update_mlflow_versions.py pre-release ... (#18181)
  • 13115e4 Support GEPA in mlflow.genai.optimize_prompt (#18031)
  • fa83107 Run python3 dev/update_ml_package_versions.py (#18177)
  • 16fc22f Add uv lock call after pyproject.toml generation in DEV branch (#18180)
  • be2125a Run python3 dev/update_requirements.py && python3 bin/... (#18176)
  • 2fd3145 Dump sql_warehouse_id into trace UI mimebundle (#18165)
  • 5cb6a95 Replace Docker with uv in tests/test_import.py for faster test execution (#18...
  • eaadd39 Add support for trace inputs to built-in scorers (#17943)
  • 30f2f55 Add B012 (jump-statement-in-finally) rule to ruff configuration (#18170)
  • 97ac7e1 Increase MAX_DOCSTRING_LENGTH_RATIO to 1.25 and remove redundant test docstri...
  • Additional commits viewable in compare view

Updates mlflow from 2.21.2 to 3.5.0rc0

Release notes

Sourced from mlflow's releases.

v3.5.0rc0

MLflow 3.5.0rc0 includes several major features and improvements

Major new features:

  • 🤖 Tracing support for Claude Code SDK: MLflow now provides a tracing integration for both the Claude Code CLI and SDK! Configure the autologging integration to track your prompts, Claude's responses, tool calls, and more. Check out this doc page to get started. (#18022, @​smoorjani)
  • Improved UI homepage: The MLflow UI's homepage has been updated to help you get started with more of our latest features. This page will be updated regularly moving forward, allowing you to get more in-product guidance. (#18098, @​B-Step62)
  • 🗂️ Evaluation datasets UI integration: In MLflow 3.4.0, we released backend support for creating evaluation datasets for GenAI applications. In this release, we've added a new tab to the MLflow Experiment UI, allowing you to create, manage, and export traces to your datasets without having to write a line of code. (#18110, @​daniellok-db)
  • 🧮 GEPA support for prompt optimization: MLflow's prompt optimization feature now supports the GEPA algorithm, allowing you to achieve higher performing prompts with less rollouts. For instructions on how to get started with prompt optimization, visit this doc page! (#18031, @​TomeHirata)
  • 🔐 Security middleware layer for tracking server: MLflow now ships with a security middleware layer by default, allowing you to protect against DNS rebinding, CORS attacks, and more. Read the documentation here to learn how to configure these options. (#17910, @​BenWilson2)

Stay tuned for the full release, which will be packed with more features and bugfixes.

To try out this release candidate, please run:

pip install mlflow==3.5.0rc0

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:

... (truncated)

Changelog

Sourced from mlflow's changelog.

3.5.0rc0 (2025-10-08)

MLflow 3.5.0rc0 includes several major features and improvements

Major new features:

  • 🤖 Tracing support for Claude Code SDK: MLflow now provides a tracing integration for both the Claude Code CLI and SDK! Configure the autologging integration to track your prompts, Claude's responses, tool calls, and more. Check out this doc page to get started. (#18022, @​smoorjani)
  • Improved UI homepage: The MLflow UI's homepage has been updated to help you get started with more of our latest features. This page will be updated regularly moving forward, allowing you to get more in-product guidance.
  • 🗂️ Evaluation datasets UI integration: In MLflow 3.4.0, we released backend support for creating evaluation datasets for GenAI applications. In this release, we've added a new tab to the MLflow Experiment UI, allowing you to create, manage, and export traces to your datasets without having to write a line of code.
  • 🧮 GEPA support for prompt optimization: MLflow's prompt optimization feature now supports the GEPA algorithm, allowing you to achieve higher performing prompts with less rollouts. For instructions on how to get started with prompt optimization, visit this doc page!
  • 🔐 Security middleware layer for tracking server: MLflow now ships with a security middleware layer by default, allowing you to protect against DNS rebinding, CORS attacks, and more. Read the documentation here to learn how to configure these options.

Stay tuned for the full release, which will be packed with more features and bugfixes.

To try out this release candidate, please run:

pip install mlflow==3.5.0rc0

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 (

Bumps the pip group with 1 update in the /data-science/classification-with-svm directory: [mlflow](https://github.com/mlflow/mlflow).
Bumps the pip group with 1 update in the /data-science/data-analysis-with-var directory: [mlflow](https://github.com/mlflow/mlflow).
Bumps the pip group with 1 update in the /deep-learning/classification-with-keras directory: [mlflow](https://github.com/mlflow/mlflow).
Bumps the pip group with 1 update in the /deep-learning/question-answering-with-bert directory: [mlflow](https://github.com/mlflow/mlflow).
Bumps the pip group with 1 update in the /deep-learning/recommendation-system-with-tensorflow directory: [mlflow](https://github.com/mlflow/mlflow).
Bumps the pip group with 1 update in the /deep-learning/spam-detection-with-nlp directory: [mlflow](https://github.com/mlflow/mlflow).
Bumps the pip group with 1 update in the /deep-learning/super-resolution-with-fsrcnn directory: [mlflow](https://github.com/mlflow/mlflow).
Bumps the pip group with 1 update in the /deep-learning/text-generation-with-rnn directory: [mlflow](https://github.com/mlflow/mlflow).
Bumps the pip group with 2 updates in the /generative-ai/agentic-feedback-analyzer-with-langgraph directory: [mlflow](https://github.com/mlflow/mlflow) and [pypdf](https://github.com/py-pdf/pypdf).
Bumps the pip group with 2 updates in the /generative-ai/agentic-github-repo-analyzer-with-langgraph directory: [mlflow](https://github.com/mlflow/mlflow) and [pypdf](https://github.com/py-pdf/pypdf).
Bumps the pip group with 1 update in the /generative-ai/automated-evaluation-with-structured-outputs directory: [mlflow](https://github.com/mlflow/mlflow).
Bumps the pip group with 1 update in the /generative-ai/code-generation-with-langchain directory: [mlflow](https://github.com/mlflow/mlflow).
Bumps the pip group with 1 update in the /generative-ai/fine-tuning-with-orpo directory: [mlflow](https://github.com/mlflow/mlflow).
Bumps the pip group with 1 update in the /generative-ai/grammar-correction-with-langchain directory: [mlflow](https://github.com/mlflow/mlflow).
Bumps the pip group with 1 update in the /generative-ai/image-generation-with-stablediffusion directory: [mlflow](https://github.com/mlflow/mlflow).
Bumps the pip group with 2 updates in the /generative-ai/multi-modal-rag-with-langchain-vllm directory: [mlflow](https://github.com/mlflow/mlflow) and [vllm](https://github.com/vllm-project/vllm).
Bumps the pip group with 1 update in the /generative-ai/text-generation-with-langchain directory: [mlflow](https://github.com/mlflow/mlflow).
Bumps the pip group with 1 update in the /generative-ai/text-summarization-with-langchain directory: [mlflow](https://github.com/mlflow/mlflow).
Bumps the pip group with 1 update in the /generative-ai/vanilla-rag-with-langchain directory: [mlflow](https://github.com/mlflow/mlflow).
Bumps the pip group with 1 update in the /ngc-integration/agentic-rag-with-tensorrtllm directory: [mlflow](https://github.com/mlflow/mlflow).
Bumps the pip group with 1 update in the /ngc-integration/audio-translation-with-nemo directory: [mlflow](https://github.com/mlflow/mlflow).
Bumps the pip group with 1 update in the /ngc-integration/data-analysis-with-cudf directory: [mlflow](https://github.com/mlflow/mlflow).
Bumps the pip group with 1 update in the /ngc-integration/data-visualization-with-cudf directory: [mlflow](https://github.com/mlflow/mlflow).
Bumps the pip group with 1 update in the /ngc-integration/vacation-recommendation-with-bert directory: [mlflow](https://github.com/mlflow/mlflow).


Updates `mlflow` from 2.21.2 to 3.5.0rc0
- [Release notes](https://github.com/mlflow/mlflow/releases)
- [Changelog](https://github.com/mlflow/mlflow/blob/master/CHANGELOG.md)
- [Commits](mlflow/mlflow@v2.21.2...v3.5.0rc0)

Updates `mlflow` from 2.21.2 to 3.5.0rc0
- [Release notes](https://github.com/mlflow/mlflow/releases)
- [Changelog](https://github.com/mlflow/mlflow/blob/master/CHANGELOG.md)
- [Commits](mlflow/mlflow@v2.21.2...v3.5.0rc0)

Updates `mlflow` from 2.21.2 to 3.5.0rc0
- [Release notes](https://github.com/mlflow/mlflow/releases)
- [Changelog](https://github.com/mlflow/mlflow/blob/master/CHANGELOG.md)
- [Commits](mlflow/mlflow@v2.21.2...v3.5.0rc0)

Updates `mlflow` from 2.21.2 to 3.5.0rc0
- [Release notes](https://github.com/mlflow/mlflow/releases)
- [Changelog](https://github.com/mlflow/mlflow/blob/master/CHANGELOG.md)
- [Commits](mlflow/mlflow@v2.21.2...v3.5.0rc0)

Updates `mlflow` from 2.21.2 to 3.5.0rc0
- [Release notes](https://github.com/mlflow/mlflow/releases)
- [Changelog](https://github.com/mlflow/mlflow/blob/master/CHANGELOG.md)
- [Commits](mlflow/mlflow@v2.21.2...v3.5.0rc0)

Updates `mlflow` from 2.21.2 to 3.5.0rc0
- [Release notes](https://github.com/mlflow/mlflow/releases)
- [Changelog](https://github.com/mlflow/mlflow/blob/master/CHANGELOG.md)
- [Commits](mlflow/mlflow@v2.21.2...v3.5.0rc0)

Updates `mlflow` from 2.21.2 to 3.5.0rc0
- [Release notes](https://github.com/mlflow/mlflow/releases)
- [Changelog](https://github.com/mlflow/mlflow/blob/master/CHANGELOG.md)
- [Commits](mlflow/mlflow@v2.21.2...v3.5.0rc0)

Updates `mlflow` from 2.21.2 to 3.5.0rc0
- [Release notes](https://github.com/mlflow/mlflow/releases)
- [Changelog](https://github.com/mlflow/mlflow/blob/master/CHANGELOG.md)
- [Commits](mlflow/mlflow@v2.21.2...v3.5.0rc0)

Updates `mlflow` from 2.21.2 to 3.5.0rc0
- [Release notes](https://github.com/mlflow/mlflow/releases)
- [Changelog](https://github.com/mlflow/mlflow/blob/master/CHANGELOG.md)
- [Commits](mlflow/mlflow@v2.21.2...v3.5.0rc0)

Updates `pypdf` from 6.0.0 to 6.1.3
- [Release notes](https://github.com/py-pdf/pypdf/releases)
- [Changelog](https://github.com/py-pdf/pypdf/blob/main/CHANGELOG.md)
- [Commits](py-pdf/pypdf@6.0.0...6.1.3)

Updates `mlflow` from 2.21.2 to 3.5.0rc0
- [Release notes](https://github.com/mlflow/mlflow/releases)
- [Changelog](https://github.com/mlflow/mlflow/blob/master/CHANGELOG.md)
- [Commits](mlflow/mlflow@v2.21.2...v3.5.0rc0)

Updates `pypdf` from 6.0.0 to 6.1.3
- [Release notes](https://github.com/py-pdf/pypdf/releases)
- [Changelog](https://github.com/py-pdf/pypdf/blob/main/CHANGELOG.md)
- [Commits](py-pdf/pypdf@6.0.0...6.1.3)

Updates `mlflow` from 2.21.2 to 3.5.0rc0
- [Release notes](https://github.com/mlflow/mlflow/releases)
- [Changelog](https://github.com/mlflow/mlflow/blob/master/CHANGELOG.md)
- [Commits](mlflow/mlflow@v2.21.2...v3.5.0rc0)

Updates `mlflow` from 2.21.2 to 3.5.0rc0
- [Release notes](https://github.com/mlflow/mlflow/releases)
- [Changelog](https://github.com/mlflow/mlflow/blob/master/CHANGELOG.md)
- [Commits](mlflow/mlflow@v2.21.2...v3.5.0rc0)

Updates `mlflow` from 2.21.2 to 3.5.0rc0
- [Release notes](https://github.com/mlflow/mlflow/releases)
- [Changelog](https://github.com/mlflow/mlflow/blob/master/CHANGELOG.md)
- [Commits](mlflow/mlflow@v2.21.2...v3.5.0rc0)

Updates `mlflow` from 2.21.2 to 3.5.0rc0
- [Release notes](https://github.com/mlflow/mlflow/releases)
- [Changelog](https://github.com/mlflow/mlflow/blob/master/CHANGELOG.md)
- [Commits](mlflow/mlflow@v2.21.2...v3.5.0rc0)

Updates `mlflow` from 2.21.2 to 3.5.0rc0
- [Release notes](https://github.com/mlflow/mlflow/releases)
- [Changelog](https://github.com/mlflow/mlflow/blob/master/CHANGELOG.md)
- [Commits](mlflow/mlflow@v2.21.2...v3.5.0rc0)

Updates `mlflow` from 2.21.2 to 3.5.0rc0
- [Release notes](https://github.com/mlflow/mlflow/releases)
- [Changelog](https://github.com/mlflow/mlflow/blob/master/CHANGELOG.md)
- [Commits](mlflow/mlflow@v2.21.2...v3.5.0rc0)

Updates `vllm` from 0.9.2 to 0.11.0
- [Release notes](https://github.com/vllm-project/vllm/releases)
- [Changelog](https://github.com/vllm-project/vllm/blob/main/RELEASE.md)
- [Commits](vllm-project/vllm@v0.9.2...v0.11.0)

Updates `mlflow` from 2.21.2 to 3.5.0rc0
- [Release notes](https://github.com/mlflow/mlflow/releases)
- [Changelog](https://github.com/mlflow/mlflow/blob/master/CHANGELOG.md)
- [Commits](mlflow/mlflow@v2.21.2...v3.5.0rc0)

Updates `mlflow` from 2.21.2 to 3.5.0rc0
- [Release notes](https://github.com/mlflow/mlflow/releases)
- [Changelog](https://github.com/mlflow/mlflow/blob/master/CHANGELOG.md)
- [Commits](mlflow/mlflow@v2.21.2...v3.5.0rc0)

Updates `mlflow` from 2.21.2 to 3.5.0rc0
- [Release notes](https://github.com/mlflow/mlflow/releases)
- [Changelog](https://github.com/mlflow/mlflow/blob/master/CHANGELOG.md)
- [Commits](mlflow/mlflow@v2.21.2...v3.5.0rc0)

Updates `mlflow` from 2.21.2 to 3.5.0rc0
- [Release notes](https://github.com/mlflow/mlflow/releases)
- [Changelog](https://github.com/mlflow/mlflow/blob/master/CHANGELOG.md)
- [Commits](mlflow/mlflow@v2.21.2...v3.5.0rc0)

Updates `mlflow` from 2.21.2 to 3.5.0rc0
- [Release notes](https://github.com/mlflow/mlflow/releases)
- [Changelog](https://github.com/mlflow/mlflow/blob/master/CHANGELOG.md)
- [Commits](mlflow/mlflow@v2.21.2...v3.5.0rc0)

Updates `mlflow` from 2.21.2 to 3.5.0rc0
- [Release notes](https://github.com/mlflow/mlflow/releases)
- [Changelog](https://github.com/mlflow/mlflow/blob/master/CHANGELOG.md)
- [Commits](mlflow/mlflow@v2.21.2...v3.5.0rc0)

Updates `mlflow` from 2.21.2 to 3.5.0rc0
- [Release notes](https://github.com/mlflow/mlflow/releases)
- [Changelog](https://github.com/mlflow/mlflow/blob/master/CHANGELOG.md)
- [Commits](mlflow/mlflow@v2.21.2...v3.5.0rc0)

Updates `mlflow` from 2.21.2 to 3.5.0rc0
- [Release notes](https://github.com/mlflow/mlflow/releases)
- [Changelog](https://github.com/mlflow/mlflow/blob/master/CHANGELOG.md)
- [Commits](mlflow/mlflow@v2.21.2...v3.5.0rc0)

---
updated-dependencies:
- dependency-name: mlflow
  dependency-version: 3.5.0rc0
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: mlflow
  dependency-version: 3.5.0rc0
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: mlflow
  dependency-version: 3.5.0rc0
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: mlflow
  dependency-version: 3.5.0rc0
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: mlflow
  dependency-version: 3.5.0rc0
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: mlflow
  dependency-version: 3.5.0rc0
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: mlflow
  dependency-version: 3.5.0rc0
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: mlflow
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  dependency-type: direct:production
  dependency-group: pip
- dependency-name: mlflow
  dependency-version: 3.5.0rc0
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  dependency-group: pip
- dependency-name: pypdf
  dependency-version: 6.1.3
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: mlflow
  dependency-version: 3.5.0rc0
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: pypdf
  dependency-version: 6.1.3
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: mlflow
  dependency-version: 3.5.0rc0
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: mlflow
  dependency-version: 3.5.0rc0
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: mlflow
  dependency-version: 3.5.0rc0
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: mlflow
  dependency-version: 3.5.0rc0
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: mlflow
  dependency-version: 3.5.0rc0
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: mlflow
  dependency-version: 3.5.0rc0
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: vllm
  dependency-version: 0.11.0
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: mlflow
  dependency-version: 3.5.0rc0
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: mlflow
  dependency-version: 3.5.0rc0
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: mlflow
  dependency-version: 3.5.0rc0
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: mlflow
  dependency-version: 3.5.0rc0
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: mlflow
  dependency-version: 3.5.0rc0
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: mlflow
  dependency-version: 3.5.0rc0
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: mlflow
  dependency-version: 3.5.0rc0
  dependency-type: direct:production
  dependency-group: pip
- dependency-name: mlflow
  dependency-version: 3.5.0rc0
  dependency-type: direct:production
  dependency-group: pip
...

Signed-off-by: dependabot[bot] <support@github.com>
@dependabot dependabot bot added dependencies Pull requests that update a dependency file python Pull requests that update python code labels Oct 22, 2025
@github-actions github-actions bot added enhancement Improvements to existing features and removed python Pull requests that update python code labels Oct 22, 2025
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