// Consolidation pipeline: plan → agents → maintenance → digests → links
//
// consolidate_full() runs the full autonomous consolidation:
//   1. Plan: analyze metrics, allocate agents
//   2. Execute: run each agent (agents apply changes via tool calls)
//   3. Graph maintenance (orphans, degree cap)
//   4. Digest: generate missing daily/weekly/monthly digests
//   5. Links: apply links extracted from digests
//   6. Summary: final metrics comparison

use super::digest;
use super::knowledge;
use crate::neuro;
use crate::store::{self, Store};


/// Append a line to the log buffer.
fn log_line(buf: &mut String, line: &str) {
    buf.push_str(line);
    buf.push('\n');
}

/// Run the full autonomous consolidation pipeline with logging.
pub fn consolidate_full(store: &mut Store) -> Result<(), String> {
    consolidate_full_with_progress(store, &|_| {})
}

pub fn consolidate_full_with_progress(
    store: &mut Store,
    on_progress: &dyn Fn(&str),
) -> Result<(), String> {
    let start = std::time::Instant::now();
    let log_key = format!("_consolidate-log-{}", store::compact_timestamp());
    let mut log_buf = String::new();

    log_line(&mut log_buf, "=== CONSOLIDATE FULL ===");
    log_line(&mut log_buf, &format!("Started: {}", store::format_datetime(store::now_epoch())));
    log_line(&mut log_buf, &format!("Nodes: {}  Relations: {}", store.nodes.len(), store.relations.len()));
    log_line(&mut log_buf, "");

    // --- Step 1: Plan ---
    log_line(&mut log_buf, "--- Step 1: Plan ---");
    on_progress("planning");
    let plan = neuro::consolidation_plan(store);
    let plan_text = neuro::format_plan(&plan);
    log_line(&mut log_buf, &plan_text);
    println!("{}", plan_text);

    let total_agents = plan.total();
    log_line(&mut log_buf, &format!("Total agents to run: {}", total_agents));

    // --- Step 2: Execute agents ---
    log_line(&mut log_buf, "\n--- Step 2: Execute agents ---");
    let mut agent_num = 0usize;
    let mut agent_errors = 0usize;

    let batch_size = 5;
    let runs = plan.to_agent_runs(batch_size);

    for (agent_type, count) in &runs {
        agent_num += 1;
        let label = if *count > 0 {
            format!("[{}/{}] {} (batch={})", agent_num, runs.len(), agent_type, count)
        } else {
            format!("[{}/{}] {}", agent_num, runs.len(), agent_type)
        };

        log_line(&mut log_buf, &format!("\n{}", label));
        on_progress(&label);
        println!("{}", label);

        // Reload store to pick up changes from previous agents
        if agent_num > 1 {
            *store = Store::load()?;
        }

        match knowledge::run_and_apply(store, agent_type, *count, "consolidate") {
            Ok(()) => {
                let msg = "  Done".to_string();
                log_line(&mut log_buf, &msg);
                on_progress(&msg);
                println!("{}", msg);
            }
            Err(e) => {
                let msg = format!("  ERROR: {}", e);
                log_line(&mut log_buf, &msg);
                eprintln!("{}", msg);
                agent_errors += 1;
            }
        }
    }

    log_line(&mut log_buf, &format!("\nAgents complete: {} run, {} errors",
        agent_num - agent_errors, agent_errors));
    store.save()?;

    // --- Step 3: Link orphans ---
    log_line(&mut log_buf, "\n--- Step 3: Link orphans ---");
    on_progress("linking orphans");
    println!("\n--- Linking orphan nodes ---");
    *store = Store::load()?;

    let (lo_orphans, lo_added) = neuro::link_orphans(store, 2, 3, 0.15);
    log_line(&mut log_buf, &format!("  {} orphans, {} links added", lo_orphans, lo_added));

    // --- Step 3b: Cap degree ---
    log_line(&mut log_buf, "\n--- Step 3b: Cap degree ---");
    on_progress("capping degree");
    println!("\n--- Capping node degree ---");
    *store = Store::load()?;

    match store.cap_degree(50) {
        Ok((hubs, pruned)) => {
            store.save()?;
            log_line(&mut log_buf, &format!("  {} hubs capped, {} edges pruned", hubs, pruned));
        }
        Err(e) => log_line(&mut log_buf, &format!("  ERROR: {}", e)),
    }

    // --- Step 4: Digest auto ---
    log_line(&mut log_buf, "\n--- Step 4: Digest auto ---");
    on_progress("generating digests");
    println!("\n--- Generating missing digests ---");
    *store = Store::load()?;

    match digest::digest_auto(store) {
        Ok(()) => log_line(&mut log_buf, "  Digests done."),
        Err(e) => {
            let msg = format!("  ERROR in digest auto: {}", e);
            log_line(&mut log_buf, &msg);
            eprintln!("{}", msg);
        }
    }

    // --- Step 5: Apply digest links ---
    log_line(&mut log_buf, "\n--- Step 5: Apply digest links ---");
    on_progress("applying digest links");
    println!("\n--- Applying digest links ---");
    *store = Store::load()?;

    let links = digest::parse_all_digest_links(store);
    let (applied, skipped, fallbacks) = digest::apply_digest_links(store, &links);
    store.save()?;
    log_line(&mut log_buf, &format!("  {} links applied, {} skipped, {} fallbacks",
        applied, skipped, fallbacks));

    // --- Step 6: Summary ---
    let elapsed = start.elapsed();
    log_line(&mut log_buf, "\n--- Summary ---");
    log_line(&mut log_buf, &format!("Finished: {}", store::format_datetime(store::now_epoch())));
    log_line(&mut log_buf, &format!("Duration: {:.0}s", elapsed.as_secs_f64()));
    *store = Store::load()?;
    log_line(&mut log_buf, &format!("Nodes: {}  Relations: {}", store.nodes.len(), store.relations.len()));

    let summary = format!(
        "\n=== CONSOLIDATE FULL COMPLETE ===\n\
         Duration: {:.0}s\n\
         Agents: {} run, {} errors\n\
         Nodes: {}  Relations: {}\n",
        elapsed.as_secs_f64(),
        agent_num - agent_errors, agent_errors,
        store.nodes.len(), store.relations.len(),
    );
    log_line(&mut log_buf, &summary);
    println!("{}", summary);

    // Store the log as a node
    store.upsert_provenance(&log_key, &log_buf,
        "consolidate:write").ok();
    store.save()?;

    Ok(())
}