From f42b692eebabf7d350511b827324d59cbfa70ad8 Mon Sep 17 00:00:00 2001 From: Jaakko Vanhala Date: Sat, 11 Apr 2026 10:00:39 +0300 Subject: [PATCH] =?UTF-8?q?Lyhennetty=20konsolilogi:=20yksi=20rivi=20per?= =?UTF-8?q?=20pyynt=C3=B6=20+=20yksi=20rivi=20per=20tulos?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Ennen: koko prompti + vastaus logitettiin (satoja rivejä) Jälkeen: → task_id:abc | 42r prompti | "Write ONLY models.py..." ✓ 128 tok | 3200ms | 40.0 tok/s | "from sqlalchemy import..." llm_done-viestissä prompt lyhennetty viimeiseen riviin (ei koko kontekstia). Co-Authored-By: Claude Opus 4.6 (1M context) --- network-poc/native-node/src/main.rs | 13 +++++++++---- 1 file changed, 9 insertions(+), 4 deletions(-) diff --git a/network-poc/native-node/src/main.rs b/network-poc/native-node/src/main.rs index 4c774c7..bef1c7e 100644 --- a/network-poc/native-node/src/main.rs +++ b/network-poc/native-node/src/main.rs @@ -347,22 +347,27 @@ async fn main() { if let Some(ref engine) = llm { let max_tokens = task.get("max_tokens").and_then(|v| v.as_u64()).unwrap_or(1024) as usize; - tracing::info!("Generoidaan (task_id: {}, max_tokens: {}): \"{}\"", task_id, max_tokens, &prompt[..prompt.len().min(100)]); + let prompt_lines = prompt.lines().count(); + let prompt_last: String = prompt.lines().last().unwrap_or("").chars().take(60).collect(); + tracing::info!("→ task_id:{} | {}r prompti | \"{}...\"", task_id, prompt_lines, prompt_last); let model_name = engine.model_name(); match engine.generate(prompt, max_tokens).await { Ok(result) => { + let result_preview: String = result.text.chars().take(60).collect(); tracing::info!( - "Tulos: {} tokenia | {:.0}ms | {:.1} tok/s | \"{}\"", + "✓ {} tok | {:.0}ms | {:.1} tok/s | \"{}...\"", result.tokens_generated, result.duration_ms, result.tokens_per_sec, - &result.text[..result.text.len().min(80)] + result_preview ); + // Lähetetään vain lyhyt prompti-esikatselu (ei koko kontekstia) + let prompt_short: String = prompt.lines().last().unwrap_or("").chars().take(100).collect(); let done = json!({ "type": "llm_done", - "prompt": prompt, + "prompt": prompt_short, "model": format!("{} (Ollama)", model_name), "response": result.text, "tokens_generated": result.tokens_generated,