build(deps): bump mlflow from 2.13.2 to 2.17.0rc0 in /tests/data/serve_resources/mlflow/pytorch

[dependabot]

Bumps mlflow from 2.13.2 to 2.17.0rc0.

Release notes

Sourced from mlflow's releases.

MLflow 2.17.0rc0 is a release candidate for 2.17.0. To install, run the following command:

pip install mlflow==2.17.0rc0

We are excited to announce the release candidate for MLflow 2.17.0. This release includes several enhancements to extend the functionality of MLflow's ChatModel interface to further extend its versatility for handling custom GenAI application use cases. We're also starting the work on improving both the utility and the versatility of MLflow's evaluate functionality for GenAI, initially with support for callable GenAI evaluation metrics.

Please try it out and report any issues on the issue tracker.

Major Features and notifications

• ChatModel enhancements - As the GenAI-focused 'cousin' of PythonModel, ChatModel is getting some sizable functionality extensions. From native support for tool calling (a requirement for creating a custom agent), simpler conversions to the internal dataclass constructs needed to interface with ChatModel via the introduction of from_dict methods to all data structures, the addition of a metadata field to allow for full input payload customization, handling of the new refusal response type, to the inclusion of the interface type to the response structure to allow for greater integration compatibility. (#13191, #13180, #13143, @​daniellok-db, #13102, #13071, @​BenWilson2)

• Callable GenAI Evaluation Metrics - As the intial step in a much broader expansion of the functionalities of mlflow.evaluate for GenAI use cases, we've converted the GenAI evaluation metrics to be callable. This allows you to use them directly in packages that support callable GenAI evaluation metrics, as well as making it simpler to debug individual responses when prototyping solutions. (#13144, @​serena-ruan)

• Audio file support in the MLflow UI - You can now directly 'view' audio files that have been logged and listen to them from within the MLflow UI's artifact viewer pane. (#13017, @​sydneyw-spotify)

• MLflow AI Gateway is no longer deprecated - We've decided to revert our deprecation for the AI Gateway feature. We had renamed it to the MLflow Deployments Server, but have reconsidered and reverted the naming and namespace back to the original configuration.

Features:

• [Models] Add tool calling support for ChatModel (#13191, @​daniellok-db)
• [Models] Add from_dict() function to ChatModel dataclasses (#13180, @​daniellok-db)
• [Models] Add metadata field for ChatModel (#13143, @​daniellok-db)
• [Models] Update ChatCompletionResponse to populate object type (#13102, @​BenWilson2)
• [Models] Add support for LLM response refusal (#13071, @​BenWilson2)
• [Eval] Make Evaluation metrics callable (#13144, @​serena-ruan)
• [Databricks] Add support for route_optimized parameter in databricks deployment client (#13222, @​prabhatkgupta)

Bug fixes:

• [Tracking] Fix tracing for LangGraph (#13215, @​B-Step62)
• [Model Registry] Fix retry and credential refresh issues with artifact downloads from the model registry (#12935, @​rohitarun-db)
• [Tracking] Fix LangChain autologging so that langchain-community is not required for partner packages (#13172, @​B-Step62)
• [Artifacts] Fix issues with file removal for the local artifact repository (#13005, @​rzalawad)

Documentation updates:

• [Docs] Add guide for building custom GenAI apps with ChatModel (#13207, @​BenWilson2)
• [Docs] Add updates to the MLflow AI Gateway documentation (#13217, @​daniellok-db)
• [Docs] Remove MLflow AI Gateway deprecation status (#13153, @​BenWilson2)

... (truncated)

Changelog

Sourced from mlflow's changelog.

CHANGELOG

2.21.0 (2025-03-14)

We are excited to announce the release of MLflow 2.21.0! This release includes a number of significant features, enhancements, and bug fixes.

Major New Features

• 📚 Documentation Redesign: MLflow documentation is fully revamped with a new MDX-based website that provides better navigation and makes it easier to find the information you need! (#13645, @​daniellok-db)
• 🤖 Prompt Registry: MLflow Prompt Registry is a powerful tool that streamlines prompt engineering and management in your GenAI applications. It enables you to version, track, and reuse prompts across your organization. (#14795, #14834, #14936, @​B-Step62, #14960, #14984, @​daniellok-db, #14909, @​hubertzub-db)
• ⚡️ FastAPI Scoring Server: The MLflow inference serverhas been migrated from Flask to FastAPI, enabling ASGI-based scalable inference for improved performance and throughput. (#14307, @​TomeHirata)
• 🔍 Enhanced Tracing Capabilities: MLflow Tracing now supports synchronous/asynchronous generators and auto-tracing for Async OpenAI, providing more flexible and comprehensive tracing options. (#14459, #14400, #14793, @​14792, @​B-Step62)

Features:

• [Tracking] Support OpenAI Agent SDK Auto Tracing (#14987, @​B-Step62)
• [Sqlalchemy / Tracking] Support mysql ssl connections with client certs (#14839, @​aksylumoed)
• [Artifacts] Supports ADLS artifact repo (#14723, @​serena-ruan)
• [Tracking] Add import and docs for txtai integration (#14712, @​B-Step62)
• [Models] Introduce User Auth Policy for Pyfunc Models (#14538, @​aravind-segu)
• [Tracking] Support new Google GenAI SDK (#14576, @​TomeHirata)
• [Tracking] Support generating traces from DSPy built-in compilation and evaluation (#14400, @​B-Step62)
• [Tracking] Add mlflow.log_trace API (#14418, @​TomeHirata)
• [Models] ChatAgent LangGraph and LangChain Connectors (#14215, @​bbqiu)

Bug fixes:

• [Models] Fix infinite recursion error with warning handler module (#14954, @​BenWilson2)
• [Model Registry] Fix invalid type issue for ModelRegistry RestStore (#14980, @​B-Step62)
• [Tracking] Fix: ExperimentViewRunsControlsActionsSelectTags doesn't set loading state to false when set-tag request fails. (#14907, @​harupy)
• [Tracking] Fix a bug in tag creation where tag values containing ": " get truncated (#14896, @​harupy)
• [Tracking] Fix false alert from AMD GPU monitor (#14884, @​B-Step62)
• [Tracking] Fix mlflow.doctor to fall back to mlflow-skinny when mlflow is not found (#14782, @​harupy)
• [Models] Handle LangGraph breaking change (#14794, @​B-Step62)
• [Tracking] Fix DSPy tracing in serving (#14743, @​B-Step62)
• [Tracking] Add limit to the length of experiment artifact locations (#14416, @​daniellok-db)
• [Build] Fix build.py to restore specific files #14444 (#14448, @​arunkothari84)
• [Models] Fix false alert for ChatModel type hint (#14343, @​B-Step62)
• [Model Registry] use aes256 to talk to s3 (#14354, @​artjen)
• [Tracking] Fix LiteLLM autologging (#14340, @​B-Step62)
• [Models] Fix ChatCompletionResponse for model serving Pydantic 1.x (#14332, @​BenWilson2)

Documentation updates:

• [Tracking] Add guide about using MLflow tracing across thread (#14881, @​B-Step62)
• [Docs] Add guide for tracing deepseek (#14826, @​B-Step62)
• [Docs] Update llama Jupyter notebook source (#14754, @​emmanuel-ferdman)
• [Docs] Replace Databricks Community Edition with Lighthouse [1] (#14642, @​TomeHirata)
• [Docs] Update models from code guide and chat model guide to always recommend models from code (#14370, @​smurching)
• [Artifacts] [DOC-FIX #14183] Improve documentation for 'artifact_uri' in 'download_artifacts' (#14225, @​vinayakkgarg)

... (truncated)

Commits

• f9c8755 Run python3 dev/update_mlflow_versions.py pre-release ... (#13259)
• 226a694 Run python3 dev/update_ml_package_versions.py (#13255)
• da33ce9 Fix LangChain model test for 0.3.x (#13243)
• 1b11805 Run python3 dev/update_pypi_package_index.py (#13257)
• ad47cf8 Run python3 dev/update_requirements.py --requirements-... (#13256)
• 82e9446 feat: add support for route_optimized parameter in databricks deployment clie...
• 7eaffb0 Change @mlflow-automation autoformat to /autoformat (#13238)
• 24a381d Support evaluating on endpoint without type (#13226)
• 55348b8 Fix _get_workspace_url to get correct workspace URL in serverless (#13234)
• 7268171 Remove pydantic import warning for Langchain >= 0.3.0 (#13190)
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Superseded by #5098.