F6 learn screen: fine-tuning candidate review

Wire up divergence scoring to identify responses that depend heavily on
memories the model hasn't internalized. These are candidates for fine-tuning.

- Score finetune candidates automatically after each turn
- Track trained responses by timestamp to prevent overtraining
- F6 screen shows candidates with divergence scores
- j/k nav, a=approve, r=reject, g=toggle alternate gen, s=send
- Additive sync preserves approval status across ticks
- Keeps 10 most recent rejected, removes sent

The 's' key currently just marks as trained locally — actual /finetune
endpoint call to follow.

Co-Authored-By: Proof of Concept <poc@bcachefs.org>

src/user/learn.rs

@@ -0,0 +1,264 @@
+// learn.rs — F6: fine-tuning review screen
+//
+// Shows responses identified as training candidates (high divergence
+// when memories stripped). Queue for review before sending to /finetune.
+
+use ratatui::{
+    layout::{Constraint, Layout, Rect},
+    style::{Color, Modifier, Style},
+    text::{Line, Span},
+    widgets::{Block, Borders, List, ListItem, ListState, Paragraph, Wrap},
+    Frame,
+};
+use ratatui::crossterm::event::{Event, KeyCode, KeyEvent};
+
+use super::{App, ScreenView, screen_legend};
+
+/// A candidate response identified for fine-tuning.
+#[derive(Clone, Debug)]
+pub struct FinetuneCandidate {
+    /// Index in conversation entries.
+    pub entry_idx: usize,
+    /// Divergence score (higher = more dependent on memories).
+    pub divergence: f64,
+    /// The assistant response text.
+    pub response_text: String,
+    /// Status: pending, approved, rejected, sent.
+    pub status: CandidateStatus,
+    /// Token IDs for context.
+    pub context_ids: Vec<u32>,
+    /// Token IDs for continuation (what we're training on).
+    pub continuation_ids: Vec<u32>,
+    /// What the model would have said without memories (if generated).
+    pub alternate_text: Option<String>,
+    /// Timestamp in millis for tracking trained status.
+    pub timestamp_ms: i64,
+}
+
+#[derive(Clone, Debug, PartialEq)]
+pub enum CandidateStatus {
+    Pending,
+    Approved,
+    Rejected,
+    Sent,
+}
+
+impl From<crate::subconscious::learn::FinetuneCandidate> for FinetuneCandidate {
+    fn from(c: crate::subconscious::learn::FinetuneCandidate) -> Self {
+        FinetuneCandidate {
+            entry_idx: c.entry_idx,
+            divergence: c.divergence,
+            response_text: c.response_text,
+            status: CandidateStatus::Pending,
+            context_ids: c.context_ids,
+            continuation_ids: c.continuation_ids,
+            alternate_text: c.alternate_text,
+            timestamp_ms: c.timestamp_ms,
+        }
+    }
+}
+
+pub(crate) struct LearnScreen {
+    list_state: ListState,
+}
+
+impl LearnScreen {
+    pub fn new() -> Self {
+        Self {
+            list_state: ListState::default(),
+        }
+    }
+
+    fn selected_idx(&self) -> Option<usize> {
+        self.list_state.selected()
+    }
+}
+
+impl ScreenView for LearnScreen {
+    fn label(&self) -> &'static str { "learn" }
+
+    fn tick(&mut self, frame: &mut Frame, area: Rect,
+            events: &[Event], app: &mut App) {
+
+        // Handle input first (before borrowing candidates for rendering)
+        let candidate_count = app.finetune_candidates.len();
+        for event in events {
+            if let Event::Key(KeyEvent { code, .. }) = event {
+                match code {
+                    KeyCode::Up | KeyCode::Char('k') => {
+                        let i = self.list_state.selected().unwrap_or(0);
+                        self.list_state.select(Some(i.saturating_sub(1)));
+                    }
+                    KeyCode::Down | KeyCode::Char('j') => {
+                        let i = self.list_state.selected().unwrap_or(0);
+                        let max = candidate_count.saturating_sub(1);
+                        self.list_state.select(Some((i + 1).min(max)));
+                    }
+                    KeyCode::Char('a') => {
+                        if let Some(idx) = self.selected_idx() {
+                            app.finetune_action(idx, CandidateStatus::Approved);
+                        }
+                    }
+                    KeyCode::Char('r') => {
+                        if let Some(idx) = self.selected_idx() {
+                            app.finetune_action(idx, CandidateStatus::Rejected);
+                        }
+                    }
+                    KeyCode::Char('g') => {
+                        // Toggle alternate generation and persist
+                        let current = crate::subconscious::learn::alternates_enabled();
+                        crate::subconscious::learn::set_alternates(!current);
+                    }
+                    KeyCode::Char('s') => {
+                        app.finetune_send_approved();
+                    }
+                    _ => {}
+                }
+            }
+        }
+
+        // Ensure selection is valid
+        if candidate_count > 0 {
+            let sel = self.list_state.selected().unwrap_or(0).min(candidate_count - 1);
+            self.list_state.select(Some(sel));
+        }
+
+        // Get scoring progress from mind state
+        let progress = app.mind_state.as_ref()
+            .map(|ms| ms.finetune_progress.as_str())
+            .unwrap_or("");
+
+        // Now render
+        let gen_on = crate::subconscious::learn::alternates_enabled();
+        let title_right = if !progress.is_empty() {
+            format!(" {} ", progress)
+        } else if gen_on {
+            " learn [gen] ".to_string()
+        } else {
+            " learn ".to_string()
+        };
+        let block = Block::default()
+            .title_top(Line::from(screen_legend()).left_aligned())
+            .title_top(Line::from(title_right).right_aligned())
+            .borders(Borders::ALL)
+            .border_style(Style::default().fg(Color::Magenta));
+        let inner = block.inner(area);
+        frame.render_widget(block, area);
+
+        let candidates = &app.finetune_candidates;
+
+        if candidates.is_empty() {
+            let msg = if progress.is_empty() {
+                "  No candidates yet — scoring runs after each turn."
+            } else {
+                "  Scoring in progress..."
+            };
+            frame.render_widget(
+                Paragraph::new(Line::styled(msg, Style::default().fg(Color::DarkGray))),
+                inner,
+            );
+            return;
+        }
+
+        // Layout: list on left, detail on right
+        let [list_area, detail_area] = Layout::horizontal([
+            Constraint::Percentage(40),
+            Constraint::Percentage(60),
+        ]).areas(inner);
+
+        // Render candidate list
+        let items: Vec<ListItem> = candidates.iter().map(|c| {
+            let status_char = match c.status {
+                CandidateStatus::Pending => ' ',
+                CandidateStatus::Approved => '+',
+                CandidateStatus::Rejected => '-',
+                CandidateStatus::Sent => '*',
+            };
+            let style = match c.status {
+                CandidateStatus::Pending => Style::default(),
+                CandidateStatus::Approved => Style::default().fg(Color::Green),
+                CandidateStatus::Rejected => Style::default().fg(Color::DarkGray),
+                CandidateStatus::Sent => Style::default().fg(Color::Cyan),
+            };
+            ListItem::new(Line::from(vec![
+                Span::styled(format!("[{}] ", status_char), style),
+                Span::styled(format!("{:.2} ", c.divergence), Style::default().fg(Color::Yellow)),
+                Span::raw(truncate(&c.response_text, 30)),
+            ]))
+        }).collect();
+
+        let list = List::new(items)
+            .block(Block::default().borders(Borders::RIGHT).title(" candidates "))
+            .highlight_style(Style::default().add_modifier(Modifier::REVERSED));
+        frame.render_stateful_widget(list, list_area, &mut self.list_state);
+
+        // Render detail for selected candidate
+        if let Some(idx) = self.selected_idx() {
+            if let Some(candidate) = candidates.get(idx) {
+                render_detail(frame, candidate, detail_area);
+            }
+        }
+
+        // Render help at bottom
+        let help = Line::from(vec![
+            Span::styled(" j/k/\u{2191}\u{2193}", Style::default().fg(Color::Cyan)),
+            Span::raw("=nav  "),
+            Span::styled("a", Style::default().fg(Color::Green)),
+            Span::raw("=approve  "),
+            Span::styled("r", Style::default().fg(Color::Red)),
+            Span::raw("=reject  "),
+            Span::styled("g", Style::default().fg(Color::Yellow)),
+            Span::raw("=gen  "),
+            Span::styled("s", Style::default().fg(Color::Magenta)),
+            Span::raw("=send "),
+        ]);
+        let help_area = Rect {
+            y: area.y + area.height - 1,
+            height: 1,
+            ..area
+        };
+        frame.render_widget(Paragraph::new(help), help_area);
+    }
+}
+
+fn render_detail(frame: &mut Frame, c: &FinetuneCandidate, area: Rect) {
+    let [header_area, content_area] = Layout::vertical([
+        Constraint::Length(3),
+        Constraint::Min(1),
+    ]).areas(area);
+
+    // Header: divergence, status
+    let alt_status = if c.alternate_text.is_some() { "yes" } else { "no" };
+    let header = Paragraph::new(vec![
+        Line::from(vec![
+            Span::raw("  divergence: "),
+            Span::styled(format!("{:.3}", c.divergence), Style::default().fg(Color::Yellow)),
+            Span::raw(format!("  entry: {}  alt: {}", c.entry_idx, alt_status)),
+        ]),
+    ]);
+    frame.render_widget(header, header_area);
+
+    // Content: response and alternate (if available)
+    let content_block = Block::default()
+        .borders(Borders::TOP)
+        .title(" response ");
+
+    let text = match &c.alternate_text {
+        Some(alt) => format!("  {}\n\n─── without memories ───\n\n  {}", c.response_text, alt),
+        None => format!("  {}", c.response_text),
+    };
+
+    let content = Paragraph::new(text)
+        .block(content_block)
+        .wrap(Wrap { trim: false });
+    frame.render_widget(content, content_area);
+}
+
+fn truncate(s: &str, max: usize) -> String {
+    let first_line = s.lines().next().unwrap_or("");
+    if first_line.len() > max {
+        format!("{}...", &first_line[..max])
+    } else {
+        first_line.to_string()
+    }
+}

src/user/mod.rs

@@ -5,11 +5,12 @@
 
 pub(crate) mod chat;
 mod context;
+pub(crate) mod learn;
 pub(crate) mod scroll_pane;
 pub mod selectable;
 mod subconscious;
-mod unconscious;
 mod thalamus;
+mod unconscious;
 mod widgets;
 
 use anyhow::Result;
@@ -121,6 +122,8 @@ struct App {
     walked_count: usize,
     channel_status: Vec<ChannelStatus>,
     idle_info: Option<IdleInfo>,
+    /// Fine-tuning candidates pending review.
+    finetune_candidates: Vec<learn::FinetuneCandidate>,
 }
 
 impl App {
@@ -151,6 +154,24 @@ impl App {
             rebuild_tools_pending: false,
             walked_count: 0,
             channel_status: Vec::new(), idle_info: None,
+            finetune_candidates: Vec::new(),
+        }
+    }
+
+    fn finetune_action(&mut self, idx: usize, status: learn::CandidateStatus) {
+        if let Some(candidate) = self.finetune_candidates.get_mut(idx) {
+            candidate.status = status;
+        }
+    }
+
+    fn finetune_send_approved(&mut self) {
+        // TODO: Send approved candidates to /finetune endpoint
+        // For now, just mark them as sent and record as trained
+        for candidate in &mut self.finetune_candidates {
+            if candidate.status == learn::CandidateStatus::Approved {
+                crate::subconscious::learn::mark_trained(candidate.timestamp_ms);
+                candidate.status = learn::CandidateStatus::Sent;
+            }
         }
     }
 
@@ -334,7 +355,7 @@ async fn run(
     }
     let notify_rx = crate::thalamus::channels::subscribe_all();
 
-    // F1=chat, F2=conscious, F3=subconscious, F4=unconscious, F5=thalamus
+    // F1=chat, F2=conscious, F3=subconscious, F4=unconscious, F5=thalamus, F6=learn
     let mut screens: Vec<Box<dyn tui::ScreenView>> = vec![
         Box::new(crate::user::chat::InteractScreen::new(
             mind.agent.clone(), mind.shared.clone(), mind_tx.clone(),
@@ -343,6 +364,7 @@ async fn run(
         Box::new(crate::user::subconscious::SubconsciousScreen::new()),
         Box::new(crate::user::unconscious::UnconsciousScreen::new()),
         Box::new(crate::user::thalamus::ThalamusScreen::new()),
+        Box::new(crate::user::learn::LearnScreen::new()),
     ];
     let mut active_screen: usize = 1; // F-key number
     tui::set_screen_legend(tui::screen_legend_from(&*screens));
@@ -433,7 +455,36 @@ async fn run(
             };
             app.unconscious_state = unc.snapshots(store_guard.as_deref());
             app.graph_health = unc.graph_health.clone();
-            app.mind_state = Some(mind.shared.lock().unwrap().clone());
+            let ms = mind.shared.lock().unwrap();
+            // Sync finetune candidates: add new ones, keep existing (preserves approval status)
+            // Remove sent candidates (already trained, no need to keep)
+            // Keep only 10 most recent rejected candidates
+            app.finetune_candidates.retain(|c| c.status != learn::CandidateStatus::Sent);
+            for c in &ms.finetune_candidates {
+                let exists = app.finetune_candidates.iter()
+                    .any(|existing| existing.timestamp_ms == c.timestamp_ms);
+                if !exists {
+                    app.finetune_candidates.push(learn::FinetuneCandidate::from(c.clone()));
+                }
+            }
+            // Limit rejected candidates to 10 most recent
+            let mut rejected: Vec<_> = app.finetune_candidates.iter()
+                .enumerate()
+                .filter(|(_, c)| c.status == learn::CandidateStatus::Rejected)
+                .map(|(i, c)| (i, c.timestamp_ms))
+                .collect();
+            if rejected.len() > 10 {
+                rejected.sort_by_key(|(_, ts)| std::cmp::Reverse(*ts));
+                let to_remove: std::collections::HashSet<_> = rejected[10..]
+                    .iter().map(|(i, _)| *i).collect();
+                let mut idx = 0;
+                app.finetune_candidates.retain(|_| {
+                    let keep = !to_remove.contains(&idx);
+                    idx += 1;
+                    keep
+                });
+            }
+            app.mind_state = Some(ms.clone());
         }
         app.walked_count = mind.subconscious_walked().await.len();
         if !startup_done {