migrate agent output to capnp store, add provenance tracking
All agent output now goes to the store as nodes instead of markdown/JSON files. Each node carries a Provenance enum identifying which agent created it (AgentDigest, AgentConsolidate, AgentFactMine, AgentKnowledgeObservation, etc — 14 variants total). Store changes: - upsert_provenance() method for agent-created nodes - Provenance enum expanded from 5 to 14 variants Agent changes: - digest: writes to store nodes (daily-YYYY-MM-DD.md etc) - consolidate: reports/actions/logs stored as _consolidation-* nodes - knowledge: depth DB and agent output stored as _knowledge-* nodes - enrich: experience-mine results go directly to store - llm: --no-session-persistence prevents transcript accumulation Deleted: 14 Python/shell scripts replaced by Rust implementations.
This commit is contained in:
ProofOfConcept
parent
e37f819dd2
commit
552d255dc3
23 changed files with 1381 additions and 4095 deletions
159
src/main.rs
159
src/main.rs
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@ -29,6 +29,8 @@ mod query;
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mod spectral;
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mod lookups;
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mod daemon;
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mod fact_mine;
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mod knowledge;
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pub mod memory_capnp {
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include!(concat!(env!("OUT_DIR"), "/schema/memory_capnp.rs"));
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@ -132,6 +134,9 @@ fn main() {
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"lookup-bump" => cmd_lookup_bump(&args[2..]),
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"lookups" => cmd_lookups(&args[2..]),
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"daemon" => cmd_daemon(&args[2..]),
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"knowledge-loop" => cmd_knowledge_loop(&args[2..]),
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"fact-mine" => cmd_fact_mine(&args[2..]),
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"fact-mine-store" => cmd_fact_mine_store(&args[2..]),
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_ => {
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eprintln!("Unknown command: {}", args[1]);
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usage();
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@ -216,7 +221,14 @@ Commands:
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lookups [DATE] Show daily lookup counts (default: today)
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daemon Start background job daemon
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daemon status Show daemon status
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daemon log [JOB] [N] Show last N log lines (default 50, optional job filter)");
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daemon log [JOB] [N] Show last N log lines (default 50, optional job filter)
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knowledge-loop [OPTIONS] Run knowledge agents to convergence
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--max-cycles N (default 20)
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--batch-size N (default 5)
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--window N (default 5)
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--max-depth N (default 4)
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fact-mine JSONL [OPTIONS] Extract atomic facts from conversation transcripts
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fact-mine --batch DIR Mine all .jsonl files in directory");
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}
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fn cmd_search(args: &[String]) -> Result<(), String> {
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@ -850,8 +862,10 @@ fn cmd_digest(args: &[String]) -> Result<(), String> {
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fn cmd_digest_links(args: &[String]) -> Result<(), String> {
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let do_apply = args.iter().any(|a| a == "--apply");
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let links = digest::parse_all_digest_links()?;
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println!("Found {} unique links from digest files", links.len());
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let store = store::Store::load()?;
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let links = digest::parse_all_digest_links(&store);
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drop(store);
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println!("Found {} unique links from digest nodes", links.len());
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if !do_apply {
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for (i, link) in links.iter().enumerate() {
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@ -1821,10 +1835,19 @@ fn cmd_daemon(args: &[String]) -> Result<(), String> {
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match args[0].as_str() {
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"status" => daemon::show_status(),
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"log" => {
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let job = args.get(1).map(|s| s.as_str());
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let lines = args.get(2)
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.and_then(|s| s.parse().ok())
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.unwrap_or(50);
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// daemon log [N] — last N lines (default 20)
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// daemon log JOB [N] — last N lines for job
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let (job, lines) = match args.get(1) {
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None => (None, 20),
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Some(s) => {
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if let Ok(n) = s.parse::<usize>() {
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(None, n)
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} else {
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let n = args.get(2).and_then(|s| s.parse().ok()).unwrap_or(20);
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(Some(s.as_str()), n)
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}
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}
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};
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daemon::show_log(job, lines)
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}
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_ => {
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@ -1833,3 +1856,125 @@ fn cmd_daemon(args: &[String]) -> Result<(), String> {
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}
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}
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}
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fn cmd_knowledge_loop(args: &[String]) -> Result<(), String> {
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if args.iter().any(|a| a == "--help" || a == "-h") {
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eprintln!("Usage: poc-memory knowledge-loop [OPTIONS]
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Run knowledge agents (observation, extractor, connector, challenger) in
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a convergence loop. Each cycle runs all agents, applies actions to the
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graph, and checks structural stability metrics.
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Options:
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--max-cycles N Maximum cycles before stopping (default: 20)
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--batch-size N Items per agent per cycle (default: 5)
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--window N Cycles to check for convergence (default: 5)
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--max-depth N Maximum inference depth (default: 4)");
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return Ok(());
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}
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let mut config = knowledge::KnowledgeLoopConfig::default();
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let mut i = 0;
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while i < args.len() {
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match args[i].as_str() {
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"--max-cycles" => { i += 1; config.max_cycles = args.get(i).and_then(|s| s.parse().ok()).unwrap_or(config.max_cycles); }
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"--batch-size" => { i += 1; config.batch_size = args.get(i).and_then(|s| s.parse().ok()).unwrap_or(config.batch_size); }
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"--window" => { i += 1; config.window = args.get(i).and_then(|s| s.parse().ok()).unwrap_or(config.window); }
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"--max-depth" => { i += 1; config.max_depth = args.get(i).and_then(|s| s.parse().ok()).unwrap_or(config.max_depth); }
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other => return Err(format!("Unknown arg: {}. Use --help for usage.", other)),
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}
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i += 1;
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}
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let results = knowledge::run_knowledge_loop(&config)?;
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eprintln!("\nCompleted {} cycles, {} total actions applied",
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results.len(),
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results.iter().map(|r| r.total_applied).sum::<usize>());
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Ok(())
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}
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fn cmd_fact_mine(args: &[String]) -> Result<(), String> {
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if args.is_empty() || args.iter().any(|a| a == "--help" || a == "-h") {
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eprintln!("Usage: poc-memory fact-mine <JSONL> [OPTIONS]
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poc-memory fact-mine --batch <DIR> [OPTIONS]
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Extract atomic factual claims from conversation transcripts using Haiku.
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Options:
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--batch Process all .jsonl files in directory
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--dry-run Show chunks without calling model
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--output FILE Write JSON to file (default: stdout)
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--min-messages N Skip transcripts with fewer messages (default: 10)");
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return Ok(());
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}
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let mut batch = false;
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let mut dry_run = false;
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let mut output_file: Option<String> = None;
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let mut min_messages = 10usize;
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let mut path: Option<String> = None;
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let mut i = 0;
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while i < args.len() {
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match args[i].as_str() {
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"--batch" => batch = true,
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"--dry-run" => dry_run = true,
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"--output" | "-o" => { i += 1; output_file = args.get(i).cloned(); }
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"--min-messages" => { i += 1; min_messages = args.get(i).and_then(|s| s.parse().ok()).unwrap_or(min_messages); }
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s if !s.starts_with('-') => path = Some(s.to_string()),
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other => return Err(format!("Unknown arg: {}", other)),
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}
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i += 1;
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}
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let path = path.ok_or("Missing path argument")?;
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let p = std::path::Path::new(&path);
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let paths: Vec<std::path::PathBuf> = if batch {
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if !p.is_dir() {
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return Err(format!("Not a directory: {}", path));
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}
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let mut files: Vec<_> = std::fs::read_dir(p)
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.map_err(|e| format!("read dir: {}", e))?
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.filter_map(|e| e.ok())
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.map(|e| e.path())
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.filter(|p| p.extension().map(|x| x == "jsonl").unwrap_or(false))
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.collect();
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files.sort();
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eprintln!("Found {} transcripts", files.len());
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files
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} else {
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vec![p.to_path_buf()]
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};
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let path_refs: Vec<&std::path::Path> = paths.iter().map(|p| p.as_path()).collect();
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let facts = fact_mine::mine_batch(&path_refs, min_messages, dry_run)?;
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if !dry_run {
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let json = serde_json::to_string_pretty(&facts)
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.map_err(|e| format!("serialize: {}", e))?;
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if let Some(out) = &output_file {
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std::fs::write(out, &json).map_err(|e| format!("write: {}", e))?;
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eprintln!("\nWrote {} facts to {}", facts.len(), out);
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} else {
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println!("{}", json);
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}
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}
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eprintln!("\nTotal: {} facts from {} transcripts", facts.len(), paths.len());
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Ok(())
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}
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fn cmd_fact_mine_store(args: &[String]) -> Result<(), String> {
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if args.len() != 1 {
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return Err("Usage: poc-memory fact-mine-store <JSONL>".into());
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}
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let path = std::path::Path::new(&args[0]);
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if !path.exists() {
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return Err(format!("File not found: {}", args[0]));
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}
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let count = fact_mine::mine_and_store(path)?;
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eprintln!("Stored {} facts", count);
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Ok(())
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}
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