[Bug]: LangChain usage extractors drop token usage when model metadata is absent

Describe the bug

The LangChain usage extractors (provider_usage_extractors in the Python SDK) discard an already-extracted usage payload whenever the model-name or provider lookup raises. In try_extract_provider_usage_data, the orchestrator catches exceptions from get_llm_usage_info and returns None, so the span is emitted with no usage/cost even though the tokens were extractable.

Affected lookups (all unguarded against missing keys):

• openai_usage_extractor: run_dict["extra"], run_dict["outputs"]["generations"][-1][-1]["generation_info"], and _get_provider's run_dict["extra"]
• groq_usage_extractor, vertexai_usage_extractor, anthropic_vertexai_usage_extractor, google_generative_ai_usage_extractor: run_dict["extra"]
• anthropic_usage_extractor: streaming path raises IndexError on empty generations (only KeyError is caught)

Reproduction: a streaming-shape OpenAI run whose usage sits in the message usage_metadata but whose generation dict has no generation_info key — try_extract_provider_usage_data returns None instead of the usage.

Expected behavior

Usage extraction should not depend on model metadata being present: extract the usage and return it with model=None when the model name cannot be resolved.