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Fix panic on multi-byte chars in filter_json buffer truncation

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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
This commit is contained in:
Dhanji R. Prasanna
2026-01-09 15:20:57 +11:00
parent c470964628
commit e301075666
11 changed files with 94 additions and 4 deletions
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18
crates/g3-core/src/lib.rs
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@@ -1841,6 +1841,7 @@ impl<W: UiWriter> Agent<W> {
let mut raw_chunks: Vec<String> = Vec::new(); // Store raw chunks for debugging
let mut _last_error: Option<String> = None;
let mut accumulated_usage: Option<g3_providers::Usage> = None;
let mut stream_stop_reason: Option<String> = None; // Track why the stream stopped
while let Some(chunk_result) = stream.next().await {
match chunk_result {
@@ -2277,6 +2278,12 @@ impl<W: UiWriter> Agent<W> {
if chunk.finished {
debug!("Stream finished: tool_executed={}, current_response_len={}, full_response_len={}, chunks_received={}",
tool_executed, current_response.len(), full_response.len(), chunks_received);
// Capture the stop reason from the final chunk
if let Some(ref reason) = chunk.stop_reason {
debug!("Stream stop_reason: {}", reason);
stream_stop_reason = Some(reason.clone());
}
// Stream finished - check if we should continue or return
if !tool_executed {
@@ -2498,10 +2505,18 @@ impl<W: UiWriter> Agent<W> {
debug!("Detected unexecuted tool call in buffer - this may indicate a parsing issue");
warn!("Unexecuted tool call detected in buffer after stream ended");
}
// Check if the response was truncated due to max_tokens
let was_truncated_by_max_tokens = stream_stop_reason.as_deref() == Some("max_tokens");
if was_truncated_by_max_tokens {
debug!("Response was truncated due to max_tokens limit");
warn!("LLM response was cut off due to max_tokens limit - will auto-continue");
}
// Auto-continue if tools were executed and we are in autonomous mode
// OR if the LLM emitted an incomplete tool call (truncated JSON)
// OR if the LLM emitted a complete tool call that wasn't executed
// OR if the response was truncated due to max_tokens
// This ensures we don't return control when the LLM clearly intended to call a tool
// Note: We removed the redundant condition (any_tool_executed && is_empty_response)
// because it's already covered by (any_tool_executed )
@@ -2509,7 +2524,8 @@ impl<W: UiWriter> Agent<W> {
// the user may be asking questions and we should return control to them
let should_auto_continue = self.is_autonomous && ((any_tool_executed )
|| has_incomplete_tool_call
|| has_unexecuted_tool_call);
|| has_unexecuted_tool_call
|| was_truncated_by_max_tokens);
if should_auto_continue {
if auto_summary_attempts < MAX_AUTO_SUMMARY_ATTEMPTS {
auto_summary_attempts += 1;