46db2e7237
All agents now go through the config-driven path via .agent files. agent_prompt() just delegates to defs::run_agent(). Remove the 100+ line hardcoded match block and the _pub wrapper functions — make the formatters pub directly.
444 lines
17 KiB
Rust
444 lines
17 KiB
Rust
// Agent prompt generation and formatting. Presentation logic —
|
||
// builds text prompts from store data for consolidation agents.
|
||
|
||
use crate::store::Store;
|
||
use crate::graph::Graph;
|
||
use crate::similarity;
|
||
|
||
use crate::neuro::{
|
||
ReplayItem,
|
||
replay_queue, detect_interference,
|
||
};
|
||
|
||
/// Result of building an agent prompt — includes both the prompt text
|
||
/// and the keys of nodes selected for processing, so the caller can
|
||
/// record visits after successful completion.
|
||
pub struct AgentBatch {
|
||
pub prompt: String,
|
||
pub node_keys: Vec<String>,
|
||
}
|
||
|
||
/// Load a prompt template, replacing {{PLACEHOLDER}} with data
|
||
pub fn load_prompt(name: &str, replacements: &[(&str, &str)]) -> Result<String, String> {
|
||
let path = crate::config::get().prompts_dir.join(format!("{}.md", name));
|
||
let mut content = std::fs::read_to_string(&path)
|
||
.map_err(|e| format!("load prompt {}: {}", path.display(), e))?;
|
||
for (placeholder, data) in replacements {
|
||
content = content.replace(placeholder, data);
|
||
}
|
||
Ok(content)
|
||
}
|
||
|
||
pub fn format_topology_header(graph: &Graph) -> String {
|
||
let sigma = graph.small_world_sigma();
|
||
let alpha = graph.degree_power_law_exponent();
|
||
let gini = graph.degree_gini();
|
||
let avg_cc = graph.avg_clustering_coefficient();
|
||
let n = graph.nodes().len();
|
||
let e = graph.edge_count();
|
||
|
||
// Identify saturated hubs — nodes with degree well above threshold
|
||
let threshold = graph.hub_threshold();
|
||
let mut hubs: Vec<_> = graph.nodes().iter()
|
||
.map(|k| (k.clone(), graph.degree(k)))
|
||
.filter(|(_, d)| *d >= threshold)
|
||
.collect();
|
||
hubs.sort_by(|a, b| b.1.cmp(&a.1));
|
||
hubs.truncate(15);
|
||
|
||
let hub_list = if hubs.is_empty() {
|
||
String::new()
|
||
} else {
|
||
let lines: Vec<String> = hubs.iter()
|
||
.map(|(k, d)| format!(" - {} (degree {})", k, d))
|
||
.collect();
|
||
format!(
|
||
"### SATURATED HUBS — DO NOT LINK TO THESE\n\
|
||
The following nodes are already over-connected. Adding more links\n\
|
||
to them makes the graph worse (star topology). Find lateral\n\
|
||
connections between peripheral nodes instead.\n\n{}\n\n\
|
||
Only link to a hub if it is genuinely the ONLY reasonable target.\n\n",
|
||
lines.join("\n"))
|
||
};
|
||
|
||
format!(
|
||
"## Current graph topology\n\
|
||
Nodes: {} Edges: {} Communities: {}\n\
|
||
Small-world σ: {:.1} Power-law α: {:.2} Degree Gini: {:.3}\n\
|
||
Avg clustering coefficient: {:.4}\n\n\
|
||
{}\
|
||
Each node below shows its hub-link ratio (fraction of edges to top-5% degree nodes).\n\
|
||
Use `poc-memory link-impact SOURCE TARGET` to evaluate proposed links.\n\n",
|
||
n, e, graph.community_count(), sigma, alpha, gini, avg_cc, hub_list)
|
||
}
|
||
|
||
pub fn format_nodes_section(store: &Store, items: &[ReplayItem], graph: &Graph) -> String {
|
||
let hub_thresh = graph.hub_threshold();
|
||
let mut out = String::new();
|
||
for item in items {
|
||
let node = match store.nodes.get(&item.key) {
|
||
Some(n) => n,
|
||
None => continue,
|
||
};
|
||
|
||
out.push_str(&format!("## {} \n", item.key));
|
||
out.push_str(&format!("Priority: {:.3} CC: {:.3} Emotion: {:.1} ",
|
||
item.priority, item.cc, item.emotion));
|
||
out.push_str(&format!("Interval: {}d\n",
|
||
node.spaced_repetition_interval));
|
||
if item.outlier_score > 0.0 {
|
||
out.push_str(&format!("Spectral: {} (outlier={:.1})\n",
|
||
item.classification, item.outlier_score));
|
||
}
|
||
|
||
if let Some(community) = node.community_id {
|
||
out.push_str(&format!("Community: {} ", community));
|
||
}
|
||
let deg = graph.degree(&item.key);
|
||
let cc = graph.clustering_coefficient(&item.key);
|
||
|
||
// Hub-link ratio: what fraction of this node's edges go to hubs?
|
||
let neighbors = graph.neighbors(&item.key);
|
||
let hub_links = neighbors.iter()
|
||
.filter(|(n, _)| graph.degree(n) >= hub_thresh)
|
||
.count();
|
||
let hub_ratio = if deg > 0 { hub_links as f32 / deg as f32 } else { 0.0 };
|
||
let is_hub = deg >= hub_thresh;
|
||
|
||
out.push_str(&format!("Degree: {} CC: {:.3} Hub-link ratio: {:.0}% ({}/{})",
|
||
deg, cc, hub_ratio * 100.0, hub_links, deg));
|
||
if is_hub {
|
||
out.push_str(" ← THIS IS A HUB");
|
||
} else if hub_ratio > 0.6 {
|
||
out.push_str(" ← mostly hub-connected, needs lateral links");
|
||
}
|
||
out.push('\n');
|
||
|
||
// Content (truncated for large nodes)
|
||
let content = &node.content;
|
||
if content.len() > 1500 {
|
||
let truncated = crate::util::truncate(content, 1500, "\n[...]");
|
||
out.push_str(&format!("\nContent ({} chars, truncated):\n{}\n\n",
|
||
content.len(), truncated));
|
||
} else {
|
||
out.push_str(&format!("\nContent:\n{}\n\n", content));
|
||
}
|
||
|
||
// Neighbors
|
||
let neighbors = graph.neighbors(&item.key);
|
||
if !neighbors.is_empty() {
|
||
out.push_str("Neighbors:\n");
|
||
for (n, strength) in neighbors.iter().take(15) {
|
||
let n_cc = graph.clustering_coefficient(n);
|
||
let n_community = store.nodes.get(n.as_str())
|
||
.and_then(|n| n.community_id);
|
||
out.push_str(&format!(" - {} (str={:.2}, cc={:.3}",
|
||
n, strength, n_cc));
|
||
if let Some(c) = n_community {
|
||
out.push_str(&format!(", c{}", c));
|
||
}
|
||
out.push_str(")\n");
|
||
}
|
||
}
|
||
|
||
// Suggested link targets: text-similar semantic nodes not already neighbors
|
||
let neighbor_keys: std::collections::HashSet<&str> = neighbors.iter()
|
||
.map(|(k, _)| k.as_str()).collect();
|
||
let mut candidates: Vec<(&str, f32)> = store.nodes.iter()
|
||
.filter(|(k, _)| {
|
||
*k != &item.key
|
||
&& !neighbor_keys.contains(k.as_str())
|
||
})
|
||
.map(|(k, n)| {
|
||
let sim = similarity::cosine_similarity(content, &n.content);
|
||
(k.as_str(), sim)
|
||
})
|
||
.filter(|(_, sim)| *sim > 0.1)
|
||
.collect();
|
||
candidates.sort_by(|a, b| b.1.total_cmp(&a.1));
|
||
candidates.truncate(8);
|
||
|
||
if !candidates.is_empty() {
|
||
out.push_str("\nSuggested link targets (by text similarity, not yet linked):\n");
|
||
for (k, sim) in &candidates {
|
||
let is_hub = graph.degree(k) >= hub_thresh;
|
||
out.push_str(&format!(" - {} (sim={:.3}{})\n",
|
||
k, sim, if is_hub { ", HUB" } else { "" }));
|
||
}
|
||
}
|
||
|
||
out.push_str("\n---\n\n");
|
||
}
|
||
out
|
||
}
|
||
|
||
pub fn format_health_section(store: &Store, graph: &Graph) -> String {
|
||
use crate::graph;
|
||
|
||
let health = graph::health_report(graph, store);
|
||
|
||
let mut out = health;
|
||
out.push_str("\n\n## Weight distribution\n");
|
||
|
||
// Weight histogram
|
||
let mut buckets = [0u32; 10]; // 0.0-0.1, 0.1-0.2, ..., 0.9-1.0
|
||
for node in store.nodes.values() {
|
||
let bucket = ((node.weight * 10.0) as usize).min(9);
|
||
buckets[bucket] += 1;
|
||
}
|
||
for (i, &count) in buckets.iter().enumerate() {
|
||
let lo = i as f32 / 10.0;
|
||
let hi = (i + 1) as f32 / 10.0;
|
||
let bar = "█".repeat((count as usize) / 10);
|
||
out.push_str(&format!(" {:.1}-{:.1}: {:4} {}\n", lo, hi, count, bar));
|
||
}
|
||
|
||
// Near-prune nodes
|
||
let near_prune: Vec<_> = store.nodes.iter()
|
||
.filter(|(_, n)| n.weight < 0.15)
|
||
.map(|(k, n)| (k.clone(), n.weight))
|
||
.collect();
|
||
if !near_prune.is_empty() {
|
||
out.push_str(&format!("\n## Near-prune nodes ({} total)\n", near_prune.len()));
|
||
for (k, w) in near_prune.iter().take(20) {
|
||
out.push_str(&format!(" [{:.3}] {}\n", w, k));
|
||
}
|
||
}
|
||
|
||
// Community sizes
|
||
let communities = graph.communities();
|
||
let mut comm_sizes: std::collections::HashMap<u32, Vec<String>> = std::collections::HashMap::new();
|
||
for (key, &label) in communities {
|
||
comm_sizes.entry(label).or_default().push(key.clone());
|
||
}
|
||
let mut sizes: Vec<_> = comm_sizes.iter()
|
||
.map(|(id, members)| (*id, members.len(), members.clone()))
|
||
.collect();
|
||
sizes.sort_by(|a, b| b.1.cmp(&a.1));
|
||
|
||
out.push_str("\n## Largest communities\n");
|
||
for (id, size, members) in sizes.iter().take(10) {
|
||
out.push_str(&format!(" Community {} ({} nodes): ", id, size));
|
||
let sample: Vec<_> = members.iter().take(5).map(|s| s.as_str()).collect();
|
||
out.push_str(&sample.join(", "));
|
||
if *size > 5 { out.push_str(", ..."); }
|
||
out.push('\n');
|
||
}
|
||
|
||
out
|
||
}
|
||
|
||
pub fn format_pairs_section(
|
||
pairs: &[(String, String, f32)],
|
||
store: &Store,
|
||
graph: &Graph,
|
||
) -> String {
|
||
let mut out = String::new();
|
||
let communities = graph.communities();
|
||
|
||
for (a, b, sim) in pairs {
|
||
out.push_str(&format!("## Pair: similarity={:.3}\n", sim));
|
||
|
||
let ca = communities.get(a).map(|c| format!("c{}", c)).unwrap_or_else(|| "?".into());
|
||
let cb = communities.get(b).map(|c| format!("c{}", c)).unwrap_or_else(|| "?".into());
|
||
|
||
// Node A
|
||
out.push_str(&format!("\n### {} ({})\n", a, ca));
|
||
if let Some(node) = store.nodes.get(a) {
|
||
let content = crate::util::truncate(&node.content, 500, "...");
|
||
out.push_str(&format!("Weight: {:.2}\n{}\n",
|
||
node.weight, content));
|
||
}
|
||
|
||
// Node B
|
||
out.push_str(&format!("\n### {} ({})\n", b, cb));
|
||
if let Some(node) = store.nodes.get(b) {
|
||
let content = crate::util::truncate(&node.content, 500, "...");
|
||
out.push_str(&format!("Weight: {:.2}\n{}\n",
|
||
node.weight, content));
|
||
}
|
||
|
||
out.push_str("\n---\n\n");
|
||
}
|
||
out
|
||
}
|
||
|
||
pub fn format_rename_candidates(store: &Store, count: usize) -> (Vec<String>, String) {
|
||
let mut candidates: Vec<(&str, &crate::store::Node)> = store.nodes.iter()
|
||
.filter(|(key, _)| {
|
||
if key.len() < 60 { return false; }
|
||
if key.starts_with("journal#j-") { return true; }
|
||
if key.starts_with("_mined-transcripts#f-") { return true; }
|
||
false
|
||
})
|
||
.map(|(k, n)| (k.as_str(), n))
|
||
.collect();
|
||
|
||
candidates.sort_by(|a, b| b.1.timestamp.cmp(&a.1.timestamp));
|
||
candidates.truncate(count);
|
||
|
||
let keys: Vec<String> = candidates.iter().map(|(k, _)| k.to_string()).collect();
|
||
|
||
let mut out = String::new();
|
||
out.push_str(&format!("## Nodes to rename ({} of {} candidates)\n\n",
|
||
candidates.len(),
|
||
store.nodes.keys().filter(|k| k.len() >= 60 &&
|
||
(k.starts_with("journal#j-") || k.starts_with("_mined-transcripts#f-"))).count()));
|
||
|
||
for (key, node) in &candidates {
|
||
out.push_str(&format!("### {}\n", key));
|
||
let created = if node.timestamp > 0 {
|
||
crate::store::format_datetime(node.timestamp)
|
||
} else {
|
||
"unknown".to_string()
|
||
};
|
||
out.push_str(&format!("Created: {}\n", created));
|
||
|
||
let content = &node.content;
|
||
if content.len() > 800 {
|
||
let truncated = crate::util::truncate(content, 800, "\n[...]");
|
||
out.push_str(&format!("\nContent ({} chars, truncated):\n{}\n\n",
|
||
content.len(), truncated));
|
||
} else {
|
||
out.push_str(&format!("\nContent:\n{}\n\n", content));
|
||
}
|
||
|
||
out.push_str("---\n\n");
|
||
}
|
||
(keys, out)
|
||
}
|
||
|
||
/// Get split candidates sorted by size (largest first)
|
||
pub fn split_candidates(store: &Store) -> Vec<String> {
|
||
let mut candidates: Vec<(&str, usize)> = store.nodes.iter()
|
||
.filter(|(key, node)| {
|
||
!key.starts_with('_')
|
||
&& !node.deleted
|
||
&& matches!(node.node_type, crate::store::NodeType::Semantic)
|
||
})
|
||
.map(|(k, n)| (k.as_str(), n.content.len()))
|
||
.collect();
|
||
candidates.sort_by(|a, b| b.1.cmp(&a.1));
|
||
candidates.into_iter().map(|(k, _)| k.to_string()).collect()
|
||
}
|
||
|
||
/// Format a single node for split-plan prompt (phase 1)
|
||
pub fn format_split_plan_node(store: &Store, graph: &Graph, key: &str) -> String {
|
||
let communities = graph.communities();
|
||
let node = match store.nodes.get(key) {
|
||
Some(n) => n,
|
||
None => return format!("Node '{}' not found\n", key),
|
||
};
|
||
|
||
let mut out = String::new();
|
||
out.push_str(&format!("### {} ({} chars)\n", key, node.content.len()));
|
||
|
||
// Show neighbors grouped by community
|
||
let neighbors = graph.neighbors(key);
|
||
if !neighbors.is_empty() {
|
||
let mut by_community: std::collections::BTreeMap<String, Vec<(&str, f32)>> =
|
||
std::collections::BTreeMap::new();
|
||
for (nkey, strength) in &neighbors {
|
||
let comm = communities.get(nkey.as_str())
|
||
.map(|c| format!("c{}", c))
|
||
.unwrap_or_else(|| "unclustered".into());
|
||
by_community.entry(comm)
|
||
.or_default()
|
||
.push((nkey.as_str(), *strength));
|
||
}
|
||
|
||
out.push_str("\nNeighbors by community:\n");
|
||
for (comm, members) in &by_community {
|
||
out.push_str(&format!(" {} ({}):", comm, members.len()));
|
||
for (nkey, strength) in members.iter().take(5) {
|
||
out.push_str(&format!(" {}({:.2})", nkey, strength));
|
||
}
|
||
if members.len() > 5 {
|
||
out.push_str(&format!(" +{} more", members.len() - 5));
|
||
}
|
||
out.push('\n');
|
||
}
|
||
}
|
||
|
||
// Full content
|
||
out.push_str(&format!("\nContent:\n{}\n\n", node.content));
|
||
out.push_str("---\n\n");
|
||
out
|
||
}
|
||
|
||
/// Build split-plan prompt for a single node (phase 1)
|
||
pub fn split_plan_prompt(store: &Store, key: &str) -> Result<String, String> {
|
||
let graph = store.build_graph();
|
||
let topology = format_topology_header(&graph);
|
||
let node_section = format_split_plan_node(store, &graph, key);
|
||
load_prompt("split-plan", &[("{{TOPOLOGY}}", &topology), ("{{NODE}}", &node_section)])
|
||
}
|
||
|
||
/// Build split-extract prompt for one child (phase 2)
|
||
pub fn split_extract_prompt(store: &Store, parent_key: &str, child_key: &str, child_desc: &str, child_sections: &str) -> Result<String, String> {
|
||
let parent_content = store.nodes.get(parent_key)
|
||
.map(|n| n.content.as_str())
|
||
.ok_or_else(|| format!("No node '{}'", parent_key))?;
|
||
load_prompt("split-extract", &[
|
||
("{{CHILD_KEY}}", child_key),
|
||
("{{CHILD_DESC}}", child_desc),
|
||
("{{CHILD_SECTIONS}}", child_sections),
|
||
("{{PARENT_CONTENT}}", parent_content),
|
||
])
|
||
}
|
||
|
||
/// Run agent consolidation on top-priority nodes
|
||
pub fn consolidation_batch(store: &Store, count: usize, auto: bool) -> Result<(), String> {
|
||
let graph = store.build_graph();
|
||
let items = replay_queue(store, count);
|
||
|
||
if items.is_empty() {
|
||
println!("No nodes to consolidate.");
|
||
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)");
|
||
}
|
||
|
||
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))?;
|
||
super::defs::run_agent(store, &def, count)
|
||
}
|