The buffer truncation code was slicing at a raw byte offset which could
land in the middle of a multi-byte character (like emojis), causing a
panic. Fixed by using char_indices() to find valid character boundaries.
Also added stop_reason field to CompletionChunk initializers in tests
to complete the stop_reason feature addition.
- Fix byte boundary panic in filter_json.rs line 327
- Add test for multi-byte character handling
- Update test files with missing stop_reason field
Agent: carmack
openai.rs:
- Use make_text_chunk() for streaming text content
- Use make_final_chunk() for final completion chunk
- Simplify tool_calls conversion logic
embedded.rs:
- Use make_text_chunk() for all 4 streaming text chunks
- Use make_final_chunk() for final completion chunk
- Remove unused CompletionChunk import
Net reduction: 35 lines removed
All tests pass. Behavior unchanged.
Writes the current context window to logs/current_context_window (uses a symlink to a session ID).
This PR was unfortunately generated by a different LLM and did a ton of superficial reformating, it's actually a fairly small and benign change, but I don't want to roll back everything. Hope that's ok.
This tries to short-circuit multiple round-trips to llm for reading code.
It's a precursor to trying to context engineer tailored to specific tasks.
In initial experiments, it's only marginally faster than regular mode, and burns more tokens.
