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lean_ctx/core/
predictive_coding.rs

1//! Predictive Coding for mode outputs — send only prediction errors (deltas).
2//!
3//! Scientific basis: Rao & Ballard (1999), "Predictive coding in the visual cortex"
4//! — Neural systems only propagate the difference between prediction and observation.
5//! Applied here: when a file is re-read in a different mode, we compare the new output
6//! against the last delivered output and transmit only structural deltas.
7//!
8//! This achieves 40-60% token savings on repeated reads.
9
10use std::collections::HashMap;
11
12/// Represents a structural delta between two mode outputs.
13#[derive(Debug, Clone)]
14pub struct ModeDelta {
15    pub mode: String,
16    pub added_lines: Vec<String>,
17    pub removed_lines: Vec<String>,
18    pub changed_lines: Vec<(String, String)>, // (old, new)
19    pub unchanged_count: usize,
20}
21
22impl ModeDelta {
23    /// Format the delta for compact token-efficient output.
24    pub fn format_compact(&self) -> String {
25        let mut out = String::new();
26        out.push_str(&format!("[delta:{}] ", self.mode));
27        out.push_str(&format!("unchanged:{} ", self.unchanged_count));
28
29        if !self.added_lines.is_empty() {
30            out.push_str(&format!("+{} ", self.added_lines.len()));
31        }
32        if !self.removed_lines.is_empty() {
33            out.push_str(&format!("-{} ", self.removed_lines.len()));
34        }
35        if !self.changed_lines.is_empty() {
36            out.push_str(&format!("~{} ", self.changed_lines.len()));
37        }
38        out.push('\n');
39
40        for line in &self.added_lines {
41            out.push_str(&format!("+ {line}\n"));
42        }
43        for line in &self.removed_lines {
44            out.push_str(&format!("- {line}\n"));
45        }
46        for (old, new) in &self.changed_lines {
47            out.push_str(&format!("~ {old}\n→ {new}\n"));
48        }
49
50        out
51    }
52
53    /// Calculate token savings compared to sending the full output.
54    pub fn token_savings_estimate(&self, full_output_tokens: usize) -> f64 {
55        let delta_lines =
56            self.added_lines.len() + self.removed_lines.len() + self.changed_lines.len() * 2;
57        let delta_approx_tokens = delta_lines * 10; // rough estimate
58        if full_output_tokens == 0 {
59            return 0.0;
60        }
61        1.0 - (delta_approx_tokens as f64 / full_output_tokens as f64).min(1.0)
62    }
63}
64
65/// Compute a structural delta between two mode outputs.
66/// Uses line-level diff for structural modes (map, signatures).
67pub fn compute_delta(mode: &str, previous: &str, current: &str) -> Option<ModeDelta> {
68    if previous == current {
69        return Some(ModeDelta {
70            mode: mode.to_string(),
71            added_lines: Vec::new(),
72            removed_lines: Vec::new(),
73            changed_lines: Vec::new(),
74            unchanged_count: current.lines().count(),
75        });
76    }
77
78    let prev_lines: Vec<&str> = previous.lines().collect();
79    let curr_lines: Vec<&str> = current.lines().collect();
80
81    let mut added = Vec::new();
82    let mut removed = Vec::new();
83    let mut changed = Vec::new();
84    let mut unchanged = 0;
85
86    // Build line-level set diff (order-preserving for structural modes)
87    let prev_set: HashMap<&str, usize> = prev_lines
88        .iter()
89        .enumerate()
90        .map(|(i, &l)| (l, i))
91        .collect();
92
93    for &line in &curr_lines {
94        if prev_set.contains_key(line) {
95            unchanged += 1;
96        } else {
97            added.push(line.to_string());
98        }
99    }
100
101    let curr_set: HashMap<&str, usize> = curr_lines
102        .iter()
103        .enumerate()
104        .map(|(i, &l)| (l, i))
105        .collect();
106
107    for &line in &prev_lines {
108        if !curr_set.contains_key(line) {
109            removed.push(line.to_string());
110        }
111    }
112
113    // Detect line changes (same position, different content)
114    let min_len = prev_lines.len().min(curr_lines.len());
115    for i in 0..min_len {
116        if prev_lines[i] != curr_lines[i]
117            && !added.contains(&curr_lines[i].to_string())
118            && !removed.contains(&prev_lines[i].to_string())
119        {
120            changed.push((prev_lines[i].to_string(), curr_lines[i].to_string()));
121        }
122    }
123
124    Some(ModeDelta {
125        mode: mode.to_string(),
126        added_lines: added,
127        removed_lines: removed,
128        changed_lines: changed,
129        unchanged_count: unchanged,
130    })
131}
132
133/// Decide whether to send delta or full output based on savings threshold.
134/// Returns true if delta is more efficient.
135pub fn should_use_delta(delta: &ModeDelta, full_output_tokens: usize) -> bool {
136    let savings = delta.token_savings_estimate(full_output_tokens);
137    // Use delta if it saves at least 30% of tokens
138    savings > 0.30
139}
140
141#[cfg(test)]
142mod tests {
143    use super::*;
144
145    #[test]
146    fn identical_outputs_produce_zero_delta() {
147        let content = "fn main() {}\nfn helper() {}";
148        let delta = compute_delta("map", content, content).unwrap();
149        assert!(delta.added_lines.is_empty());
150        assert!(delta.removed_lines.is_empty());
151        assert!(delta.changed_lines.is_empty());
152        assert_eq!(delta.unchanged_count, 2);
153    }
154
155    #[test]
156    fn added_lines_detected() {
157        let prev = "fn main() {}";
158        let curr = "fn main() {}\nfn new_fn() {}";
159        let delta = compute_delta("signatures", prev, curr).unwrap();
160        assert_eq!(delta.added_lines.len(), 1);
161        assert!(delta.added_lines[0].contains("new_fn"));
162    }
163
164    #[test]
165    fn removed_lines_detected() {
166        let prev = "fn main() {}\nfn old_fn() {}";
167        let curr = "fn main() {}";
168        let delta = compute_delta("map", prev, curr).unwrap();
169        assert_eq!(delta.removed_lines.len(), 1);
170        assert!(delta.removed_lines[0].contains("old_fn"));
171    }
172
173    #[test]
174    fn savings_estimate_makes_sense() {
175        let delta = ModeDelta {
176            mode: "map".into(),
177            added_lines: vec!["new".into()],
178            removed_lines: Vec::new(),
179            changed_lines: Vec::new(),
180            unchanged_count: 50,
181        };
182        let savings = delta.token_savings_estimate(500);
183        assert!(savings > 0.9); // 1 line delta vs 500 tokens = huge savings
184    }
185
186    #[test]
187    fn compact_format_is_readable() {
188        let delta = ModeDelta {
189            mode: "signatures".into(),
190            added_lines: vec!["+ pub fn new_api()".into()],
191            removed_lines: vec!["- pub fn old_api()".into()],
192            changed_lines: Vec::new(),
193            unchanged_count: 10,
194        };
195        let formatted = delta.format_compact();
196        assert!(formatted.contains("[delta:signatures]"));
197        assert!(formatted.contains("unchanged:10"));
198    }
199}