Month: 2025-12 — Summary for repository pydantic/logfire. Focused on delivering observable improvements to streaming behavior and ensuring robust traceability for streaming responses from LLM providers. Key features delivered: - Enhanced streaming response logging with preserved original LLM request context, improving traceability and debugging during streaming. This preserves the context across streamed chunks and correlates responses with the exact request. Major bugs fixed: - No major bugs fixed this month; focus was on feature delivery and observability improvements. Overall impact and accomplishments: - Strengthened end-to-end observability for streaming workflows, enabling faster issue diagnosis and more reliable audits. - Improved user supportability and debugging latency by maintaining request context through streaming logs, contributing to higher system reliability and customer trust. Technologies/skills demonstrated: - Python, logging instrumentation, context propagation, streaming data handling, and incremental instrumentation changes with minimal surface area impact. Commits: - c029ede5d20c700584c5f9fcaaf5c79548d9952d (Maintain original LLM request context when logging the streaming response (#1566))