Make autolog resilient, add UC pre-flight and per-node span descriptions

[adamgurary]

Summary

Three additive improvements to instrumenting-with-mlflow-tracing/references/python.md, each fixing a concrete failure mode observed when a developer instruments a LangGraph agent for the first time.

1. Resilient autolog setup (Method 1)

The existing autolog block calls each flavor sequentially with no error handling. If one flavor's version-compatibility check raises (for example, mlflow.langchain.autolog() raises ModuleNotFoundError: No module named 'langchain' when only langchain-core is installed), every subsequent autolog call in the same block is skipped. The fix wraps each call in its own try/except so a single missing package does not disable the rest.

The section also adds a note clarifying that LangGraph is traced via mlflow.langchain.autolog() (there is no mlflow.langgraph.autolog()), and that it requires only langchain-core, not the full langchain package.

2. Databricks UC trace-storage pre-flight note

On Databricks, the default experiment backend caps at 100,000 traces per experiment. Nothing in the Quick Start section flags this limit. The fix adds a short callout pointing readers to references/databricks.md for the set_experiment(trace_location=UnityCatalog(...)) one-liner before they hit the cap in production.

3. Per-node span description pattern (new subsection under "Combining AutoLogging with Custom Tracing")

When mlflow.langchain.autolog() traces a LangGraph graph, each node span is named after the node function. The trace shows inputs and outputs but nothing that explains what the node does. A reader has to open the source file to understand the trace. The fix adds a pattern for writing the node's docstring to span.set_attribute("description", fn.__doc__), which surfaces in the span's Attributes tab without any changes to MLflow core.

Testing

Verified locally that:

• The resilient autolog loop runs without syntax errors in a Python 3.11 environment.
• mlflow.get_current_active_span() is a valid public API in mlflow>=3.8.0.
• span.set_attribute(key, value) is a valid public API on LiveSpan.

No existing skill tests are affected (this file contains only documentation and code examples).