organize: fine-grained agent logging + cluster size cap
Add progress callback to run_one_agent and run_and_apply so callers can see: prompt size, node list, LLM call timing, parsed action count, and per-action applied/skipped status. Daemon writes these to the persistent event log via log_event. Cap organize cluster to 20 nodes - 126 nodes produced a 682KB prompt that timed out every time. Agent has tools to explore further if needed. Restore general query for production runs.
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01aba4c12b
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4cacfa7599
4 changed files with 56 additions and 6 deletions
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@ -125,11 +125,17 @@ fn job_consolidation_agent(
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) -> Result<(), TaskError> {
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let agent = agent_type.to_string();
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let batch = batch_size;
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run_job(ctx, &format!("c-{}", agent), || {
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let job_name = format!("c-{}", agent);
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let job_name2 = job_name.clone();
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run_job(ctx, &job_name, || {
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ctx.log_line("loading store");
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let mut store = crate::store::Store::load()?;
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ctx.log_line(&format!("running agent: {} (batch={})", agent, batch));
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let (total, applied) = super::knowledge::run_and_apply(&mut store, &agent, batch, "consolidate")?;
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let log = |msg: &str| {
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ctx.log_line(msg);
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log_event(&job_name2, "progress", msg);
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};
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let (total, applied) = super::knowledge::run_and_apply_with_log(&mut store, &agent, batch, "consolidate", &log)?;
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ctx.log_line(&format!("done: {} actions ({} applied)", total, applied));
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Ok(())
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})
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@ -147,7 +153,8 @@ fn job_rename_agent(
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let batch = if batch_size == 0 { 10 } else { batch_size };
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ctx.log_line(&format!("running rename agent (batch={})", batch));
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let result = super::knowledge::run_one_agent(&mut store, "rename", batch, "consolidate")?;
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let log = |msg: &str| ctx.log_line(msg);
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let result = super::knowledge::run_one_agent(&mut store, "rename", batch, "consolidate", &log)?;
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// Parse RENAME actions from response (rename uses its own format, not WRITE_NODE/LINK/REFINE)
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let mut applied = 0;
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@ -184,6 +184,11 @@ fn resolve(
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}
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cluster.sort_by(|a, b| a.0.cmp(&b.0));
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// Cap cluster size — agent has tools to explore more if needed
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if cluster.len() > 20 {
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cluster.truncate(20);
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}
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// Similarity pairs
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let pairs = crate::similarity::pairwise_similar(&cluster, 0.4);
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@ -579,13 +579,33 @@ pub fn run_and_apply(
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batch_size: usize,
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llm_tag: &str,
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) -> Result<(usize, usize), String> {
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let result = run_one_agent(store, agent_name, batch_size, llm_tag)?;
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run_and_apply_with_log(store, agent_name, batch_size, llm_tag, &|_| {})
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}
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pub fn run_and_apply_with_log(
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store: &mut Store,
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agent_name: &str,
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batch_size: usize,
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llm_tag: &str,
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log: &dyn Fn(&str),
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) -> Result<(usize, usize), String> {
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let result = run_one_agent(store, agent_name, batch_size, llm_tag, log)?;
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let actions = resolve_action_names(store, result.actions);
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let ts = store::compact_timestamp();
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let mut applied = 0;
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for action in &actions {
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let desc = match &action.kind {
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ActionKind::WriteNode { key, .. } => format!("WRITE {}", key),
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ActionKind::Refine { key, .. } => format!("REFINE {}", key),
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ActionKind::Link { source, target } => format!("LINK {} → {}", source, target),
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ActionKind::Demote { key } => format!("DEMOTE {}", key),
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ActionKind::Delete { key } => format!("DELETE {}", key),
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};
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if apply_action(store, action, agent_name, &ts, 0) {
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log(&format!("applied: {}", desc));
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applied += 1;
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} else {
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log(&format!("skipped: {}", desc));
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}
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}
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Ok((actions.len(), applied))
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@ -600,13 +620,29 @@ pub fn run_one_agent(
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agent_name: &str,
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batch_size: usize,
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llm_tag: &str,
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log: &dyn Fn(&str),
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) -> Result<AgentResult, String> {
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let def = super::defs::get_def(agent_name)
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.ok_or_else(|| format!("no .agent file for {}", agent_name))?;
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log("building prompt");
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let agent_batch = super::defs::run_agent(store, &def, batch_size)?;
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let prompt_kb = agent_batch.prompt.len() / 1024;
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let tools_desc = if def.tools.is_empty() { "no tools".into() }
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else { format!("{} tools", def.tools.len()) };
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log(&format!("prompt {}KB, model={}, {}, {} nodes",
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prompt_kb, def.model, tools_desc, agent_batch.node_keys.len()));
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for key in &agent_batch.node_keys {
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log(&format!(" node: {}", key));
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}
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log("calling LLM");
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let output = llm::call_for_def(&def, &agent_batch.prompt)?;
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let output_kb = output.len() / 1024;
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log(&format!("response {}KB", output_kb));
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// Store raw output for audit trail
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let ts = store::compact_timestamp();
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let report_key = format!("_{}-{}-{}", llm_tag, agent_name, ts);
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@ -616,6 +652,8 @@ pub fn run_one_agent(
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let actions = parse_all_actions(&output);
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let no_ops = count_no_ops(&output);
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log(&format!("parsed {} actions, {} no-ops", actions.len(), no_ops));
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// Record visits for processed nodes
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if !agent_batch.node_keys.is_empty() {
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store.record_agent_visits(&agent_batch.node_keys, agent_name).ok();
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@ -889,7 +927,7 @@ fn run_cycle(
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for agent_name in &agent_names {
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eprintln!("\n --- {} (n={}) ---", agent_name, config.batch_size);
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let result = match run_one_agent(&mut store, agent_name, config.batch_size, "knowledge") {
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let result = match run_one_agent(&mut store, agent_name, config.batch_size, "knowledge", &|msg| eprintln!(" {}", msg)) {
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Ok(r) => r,
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Err(e) => {
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eprintln!(" ERROR: {}", e);
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