fix(langchain): handle empty llm generations - #1839

Problem

CallbackHandler.on_llm_end() assumes every LangChain LLMResult contains at least one generation in the last generation batch. If a provider returns an empty generation batch but still includes model and usage metadata, the callback raises IndexError, logs the error, and never ends the generation span.

Reproducer

handler.on_llm_start(
 {"name": "EmptyLLM"},
 ["hello"],
 run_id=run_id,
 invocation_params={"model_name": "empty-model"},
)
handler.on_llm_end(
 LLMResult(
 generations=[[]],
 llm_output={"token_usage": {"prompt_tokens": 2, "completion_tokens": 0, "total_tokens": 2}},
 ),
 run_id=run_id,
)
# before: IndexError is logged and no span is exported
# after: span ends with output=None and preserved usage/model metadata

Fix

Extract the last available generation by skipping empty generation batches, and use None as the output when no generation is present. This keeps the span lifecycle correct while preserving existing output extraction for normal chat and text generations.

Testing

• python -m pytest tests\\unit\\test_langchain.py::test_llm_callback_ends_generation_with_empty_generations -q failed before the fix and passed after.
• python -m pytest tests\\unit\\test_langchain.py -q -> 24 passed.
• ruff format langfuse\\langchain\\CallbackHandler.py tests\\unit\\test_langchain.py --check -> passed after formatting.
• ruff check langfuse\\langchain\\CallbackHandler.py tests\\unit\\test_langchain.py -> All checks passed.

Note: full offline tests\\unit baseline still has pre-existing Windows/environment failures unrelated to this change (test_path, prompt subprocess missing opentelemetry, and prompt mock errors).

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