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consolidate: eliminate second LLM call, apply actions inline

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The consolidation pipeline previously made a second Sonnet call to
extract structured JSON actions from agent reports. This was both
wasteful (extra LLM call per consolidation) and lossy (only extracted
links and manual items, ignoring WRITE_NODE/REFINE).

Now actions are parsed and applied inline after each agent runs, using
the same parse_all_actions() parser as the knowledge loop. The daemon
scheduler's separate apply phase is also removed.

Also deletes 8 superseded/orphaned prompt .md files (784 lines) that
have been replaced by .agent files.
This commit is contained in:
ProofOfConcept 2026-03-10 17:22:53 -04:00
parent 42d8e265da
commit f6ea659975
11 changed files with 119 additions and 1024 deletions
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64
poc-memory/src/agents/prompts.rs
View file

@ -387,8 +387,14 @@ pub fn split_extract_prompt(store: &Store, parent_key: &str, child_key: &str, ch
])
}
/// Run agent consolidation on top-priority nodes
/// Show consolidation batch status or generate an agent prompt.
pub fn consolidation_batch(store: &Store, count: usize, auto: bool) -> Result<(), String> {
if auto {
let batch = agent_prompt(store, "replay", count)?;
println!("{}", batch.prompt);
return Ok(());
}
let graph = store.build_graph();
let items = replay_queue(store, count);
@ -397,46 +403,34 @@ pub fn consolidation_batch(store: &Store, count: usize, auto: bool) -> Result<()
return Ok(());
}
let nodes_section = format_nodes_section(store, &items, &graph);
if auto {
let prompt = load_prompt("replay", &[("{{NODES}}", &nodes_section)])?;
println!("{}", prompt);
} else {
// Interactive: show what needs attention and available agent types
println!("Consolidation batch ({} nodes):\n", items.len());
for item in &items {
let node_type = store.nodes.get(&item.key)
.map(|n| if matches!(n.node_type, crate::store::NodeType::EpisodicSession) { "episodic" } else { "semantic" })
.unwrap_or("?");
println!(" [{:.3}] {} (cc={:.3}, interval={}d, type={})",
item.priority, item.key, item.cc, item.interval_days, node_type);
}
// Also show interference pairs
let pairs = detect_interference(store, &graph, 0.6);
if !pairs.is_empty() {
println!("\nInterfering pairs ({}):", pairs.len());
for (a, b, sim) in pairs.iter().take(5) {
println!(" [{:.3}] {} ↔ {}", sim, a, b);
}
}
println!("\nAgent prompts:");
println!(" --auto Generate replay agent prompt");
println!(" --agent replay Replay agent (schema assimilation)");
println!(" --agent linker Linker agent (relational binding)");
println!(" --agent separator Separator agent (pattern separation)");
println!(" --agent transfer Transfer agent (CLS episodic→semantic)");
println!(" --agent health Health agent (synaptic homeostasis)");
println!("Consolidation batch ({} nodes):\n", items.len());
for item in &items {
let node_type = store.nodes.get(&item.key)
.map(|n| if matches!(n.node_type, crate::store::NodeType::EpisodicSession) { "episodic" } else { "semantic" })
.unwrap_or("?");
println!(" [{:.3}] {} (cc={:.3}, interval={}d, type={})",
item.priority, item.key, item.cc, item.interval_days, node_type);
}
let pairs = detect_interference(store, &graph, 0.6);
if !pairs.is_empty() {
println!("\nInterfering pairs ({}):", pairs.len());
for (a, b, sim) in pairs.iter().take(5) {
println!(" [{:.3}] {} ↔ {}", sim, a, b);
}
}
println!("\nAgent prompts:");
println!(" --auto Generate replay agent prompt");
println!(" --agent replay Replay agent (schema assimilation)");
println!(" --agent linker Linker agent (relational binding)");
println!(" --agent separator Separator agent (pattern separation)");
println!(" --agent transfer Transfer agent (CLS episodic→semantic)");
println!(" --agent health Health agent (synaptic homeostasis)");
Ok(())
}
/// Generate a specific agent prompt with filled-in data.
/// Returns an AgentBatch with the prompt text and the keys of nodes
/// selected for processing (for visit tracking on success).
pub fn agent_prompt(store: &Store, agent: &str, count: usize) -> Result<AgentBatch, String> {
let def = super::defs::get_def(agent)
.ok_or_else(|| format!("Unknown agent: {}", agent))?;