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fix: disable all thinking detection to prevent deadlock
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Rodrigo Rodriguez (Pragmatismo) 2026-04-13 22:47:27 -03:00
parent f48f87cadc
commit 7d911194f3
1 changed files with 11 additions and 68 deletions
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79
src/llm/mod.rs
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@ -461,80 +461,23 @@ impl LLMProvider for OpenAIClient {
// Accumulate tool calls here because OpenAI streams them in fragments // Accumulate tool calls here because OpenAI streams them in fragments
let mut active_tool_calls: Vec<serde_json::Value> = Vec::new(); let mut active_tool_calls: Vec<serde_json::Value> = Vec::new();
// Track reasoning state for thinking indicator
let mut in_reasoning = false;
let mut has_sent_thinking = false;
let mut reasoning_buffer = String::new();
while let Some(chunk_result) = stream.next().await { while let Some(chunk_result) = stream.next().await {
let chunk = chunk_result?; let chunk = chunk_result?;
let chunk_str = String::from_utf8_lossy(&chunk); let chunk_str = String::from_utf8_lossy(&chunk);
for line in chunk_str.lines() { for line in chunk_str.lines() {
if line.starts_with("data: ") && !line.contains("[DONE]") { if line.starts_with("data: ") && !line.contains("[DONE]") {
if let Ok(data) = serde_json::from_str::<Value>(&line[6..]) { if let Ok(data) = serde_json::from_str::<Value>(&line[6..]) {
let content = data["choices"][0]["delta"]["content"].as_str(); let content = data["choices"][0]["delta"]["content"].as_str();
// Handle both reasoning_content (GLM4.7) and reasoning (Kimi K2.5)
let reasoning = data["choices"][0]["delta"]["reasoning_content"].as_str() // TEMP DISABLED: Thinking detection causing deadlock issues
.or_else(|| data["choices"][0]["delta"]["reasoning"].as_str()); // Just pass content through directly without any thinking detection
// DEBUG: Log raw delta to see what Minimax actually sends if let Some(text) = content {
trace!("[LLM] Delta: content={:?}, reasoning={:?}", let processed = handler.process_content(text);
content.map(|s| if s.len() > 50 { format!("{}...", &s[..50]) } else { s.to_string() }), if !processed.is_empty() {
reasoning.map(|s| if s.len() > 50 { format!("{}...", &s[..50]) } else { s.to_string() })); let _ = tx.send(processed).await;
}
// Detect reasoning phase (GLM4.7, Kimi K2.5, Minimax) }
// Some models send BOTH reasoning and content - filter reasoning even when content exists
if reasoning.is_some() {
if !in_reasoning {
trace!("[LLM] Entering reasoning/thinking mode");
in_reasoning = true;
}
// Accumulate reasoning text but don't send to user
if let Some(r) = reasoning {
reasoning_buffer.push_str(r);
}
// If only reasoning (no content yet), skip sending
if content.is_none() {
continue;
}
// If we have both reasoning AND content, just clear reasoning buffer and proceed with content
trace!("[LLM] Got content alongside reasoning, discarding {} chars of reasoning", reasoning_buffer.len());
reasoning_buffer.clear();
// Send thinking indicator only once
if !has_sent_thinking {
let thinking = serde_json::json!({
"type": "thinking",
"content": "🤔 Pensando..."
}).to_string();
let _ = tx.send(thinking).await;
has_sent_thinking = true;
trace!("[LLM] Sent thinking indicator");
}
continue; // Don't send reasoning content to user
}
// Exited reasoning mode - content is now real response (or we got content alongside reasoning)
if in_reasoning && (content.is_some() || !reasoning_buffer.is_empty()) {
let reason_len = reasoning_buffer.len();
if reason_len > 0 {
trace!("[LLM] Exited reasoning mode, {} chars of reasoning discarded", reason_len);
}
in_reasoning = false;
reasoning_buffer.clear();
// Clear the thinking indicator
let clear_thinking = serde_json::json!({
"type": "thinking_clear",
"content": ""
}).to_string();
let _ = tx.send(clear_thinking).await;
}
if let Some(text) = content {
let processed = handler.process_content(text);
if !processed.is_empty() {
let _ = tx.send(processed).await;
}
}
// Handle standard OpenAI tool_calls // Handle standard OpenAI tool_calls
if let Some(tool_calls) = data["choices"][0]["delta"]["tool_calls"].as_array() { if let Some(tool_calls) = data["choices"][0]["delta"]["tool_calls"].as_array() {