MLflow 2.19.0

[Daniel Lok]

We are excited to announce the release of MLflow 2.19.0! This release includes a number of significant features, enhancements, and bug fixes.

Major New Features

• ChatModel enhancements: ChatModel now adopts ChatCompletionRequest and ChatCompletionResponse as its new schema. The predict_stream interface uses ChatCompletionChunk to deliver true streaming responses. Additionally, the custom_inputs and custom_outputs fields in ChatModel now utilize AnyType, enabling support for a wider variety of data types. Note: In a future version of MLflow, ChatParams (and by extension, ChatCompletionRequest) will have the default values for n, temperature, and stream removed.
• Tracing improvements: MLflow Tracing now supports both automatic and manual tracing for DSPy, LlamaIndex and Langchain flavors. Tracing feature is also auto-enabled for mlflow evaluation for all supported flavors.
• New Tracing Integrations: MLflow Tracing now supports CrewAI and Anthropic, enabling a one-line, fully automated tracing experience.
• Any Type in model signature: MLflow now supports AnyType in model signature. It can be used to host any data types that were not supported before.

Other Features:

• [Tracking] Add update_current_trace API for adding tags to an active trace.
• [Deployments] Update databricks deployments to support AI gateway & additional update endpoints
• [Models] Support uv in mlflow.models.predict
• [Models] Add type hints support including pydantic models
• [Tracking] Add the trace.search_spans() method for searching spans within traces

Bug fixes:

• [Tracking] Allow passing in spark connect dataframes in mlflow evaluate API
• [Tracking] Fix mlflow.end_run inside a MLflow run context manager
• [Scoring] Fix spark_udf conditional check on remote spark-connect client or Databricks Serverless
• [Models] Allow changing max_workers for built-in LLM-as-a-Judge metrics
• [Models] Support saving all langchain runnables using code-based logging
• [Model Registry] return empty array when DatabricksSDKModelsArtifactRepository.list_artifacts is called on a file 
• [Tracking] Stringify param values in client.log_batch()
• [Tracking] Remove deprecated squared parameter
• [Tracking] Fix request/response field in the search_traces output

Documentation updates:

• [Docs] Add Ollama and Instructor examples in tracing doc

For a comprehensive list of changes, see the release change log, and check out the latest documentation on mlflow.org.