feat(langchain): add semconv attributes, operation mapping, and content recording modules [1/5]

[nagkumar91]

Description

Add foundation modules for enhanced LangChain GenAI semantic convention tracing. These are internal building-block modules that will be consumed by subsequent PRs in this series.

New Modules

semconv_attributes.py

Per-operation attribute matrix based on OTel GenAI semantic conventions. Single source of truth for which attributes apply to which operations (chat, text_completion, invoke_agent, execute_tool, invoke_workflow, retrieval). Defines requirement levels (REQUIRED, CONDITIONALLY_REQUIRED, RECOMMENDED, OPT_IN) following the GenAI semconv spec.

operation_mapping.py

Callback-to-semconv operation mapping. Maps each LangChain callback to the correct GenAI semantic convention operation name. Includes heuristic classification for on_chain_start callbacks (agents vs workflows vs internal plumbing) and LangGraph marker recognition.

content_recording.py

Thin integration layer over the shared genai content capture utilities. Provides clear APIs for the callback handler to decide what content should be recorded on spans and events.

Tests

• test_operation_mapping.py — comprehensive tests for chain classification, agent name resolution, LangGraph markers
• test_content_recording.py — tests for content policy modes, redaction behavior

PR Series

This is PR 1 of 5 breaking down #4389 into smaller reviewable units:

1. Foundation modules (this PR)
2. Provider inference, message formatting, W3C propagation utilities
3. Span manager enhancements + Event emitter
4. Callback handler — model, chain, agent callbacks + wiring
5. Callback handler — tool, retriever callbacks + E2E tests

Type of change

• New feature (non-breaking change which adds functionality)

Checklist

• Followed the style guidelines of this project
• Unit tests have been added