lean_ctx/core/gain/
mod.rs

1pub mod gain_score;
2pub mod model_pricing;
3pub mod task_classifier;
4
5use serde::{Deserialize, Serialize};
6
7use crate::core::a2a::cost_attribution::CostStore;
8use crate::core::gain::gain_score::GainScore;
9use crate::core::gain::model_pricing::{ModelPricing, ModelQuote};
10use crate::core::gain::task_classifier::{TaskCategory, TaskClassifier};
11use crate::core::heatmap::HeatMap;
12use crate::core::stats::StatsStore;
13
14#[derive(Clone)]
15pub struct GainEngine {
16    pub stats: StatsStore,
17    pub costs: CostStore,
18    pub heatmap: HeatMap,
19    pub pricing: ModelPricing,
20    pub events: Vec<crate::core::events::LeanCtxEvent>,
21    pub session: Option<crate::core::session::SessionState>,
22}
23
24#[derive(Debug, Clone, Serialize, Deserialize)]
25pub struct GainSummary {
26    pub model: ModelQuote,
27    pub total_commands: u64,
28    pub input_tokens: u64,
29    pub output_tokens: u64,
30    pub tokens_saved: u64,
31    pub gain_rate_pct: f64,
32    pub avoided_usd: f64,
33    pub tool_spend_usd: f64,
34    pub roi: Option<f64>,
35    pub score: GainScore,
36    #[serde(skip_serializing_if = "Option::is_none", default)]
37    pub daemon_hint: Option<String>,
38}
39
40#[derive(Debug, Clone, Serialize, Deserialize)]
41pub struct TaskGainRow {
42    pub category: TaskCategory,
43    pub commands: u64,
44    pub tokens_saved: u64,
45    pub tool_calls: u64,
46    pub tool_spend_usd: f64,
47}
48
49#[derive(Debug, Clone, Serialize, Deserialize)]
50pub struct FileGainRow {
51    pub path: String,
52    pub access_count: u32,
53    pub tokens_saved: u64,
54    pub compression_pct: f32,
55}
56
57impl GainEngine {
58    pub fn load() -> Self {
59        Self {
60            stats: crate::core::stats::load(),
61            costs: crate::core::a2a::cost_attribution::CostStore::load(),
62            heatmap: crate::core::heatmap::HeatMap::load(),
63            pricing: ModelPricing::load(),
64            events: crate::core::events::load_events_from_file(500),
65            session: crate::core::session::SessionState::load_latest(),
66        }
67    }
68
69    pub fn summary(&self, model: Option<&str>) -> GainSummary {
70        let quote = self.pricing.quote(model);
71        let tokens_saved = self
72            .stats
73            .total_input_tokens
74            .saturating_sub(self.stats.total_output_tokens);
75        let gain_rate_pct = if self.stats.total_input_tokens > 0 {
76            tokens_saved as f64 / self.stats.total_input_tokens as f64 * 100.0
77        } else {
78            0.0
79        };
80        let avoided_usd = quote.cost.estimate_usd(tokens_saved, 0, 0, 0);
81        let tool_spend_usd = self.costs.total_cost().max(0.0);
82        let roi = if tool_spend_usd > 0.0 {
83            Some(avoided_usd / tool_spend_usd)
84        } else {
85            None
86        };
87        let score = GainScore::compute(&self.stats, &self.costs, &self.pricing, model);
88        #[cfg(unix)]
89        let daemon_hint = if crate::daemon::is_daemon_running() {
90            None
91        } else {
92            Some(
93                "daemon not running — stats tracked locally (lean-ctx serve -d for full tracking)"
94                    .to_string(),
95            )
96        };
97        #[cfg(not(unix))]
98        let daemon_hint: Option<String> = None;
99        GainSummary {
100            model: quote,
101            total_commands: self.stats.total_commands,
102            input_tokens: self.stats.total_input_tokens,
103            output_tokens: self.stats.total_output_tokens,
104            tokens_saved,
105            gain_rate_pct,
106            avoided_usd,
107            tool_spend_usd,
108            roi,
109            score,
110            daemon_hint,
111        }
112    }
113
114    pub fn gain_score(&self, model: Option<&str>) -> GainScore {
115        GainScore::compute(&self.stats, &self.costs, &self.pricing, model)
116    }
117
118    pub fn task_breakdown(&self) -> Vec<TaskGainRow> {
119        use std::collections::HashMap;
120
121        let mut by_cat: HashMap<TaskCategory, TaskGainRow> = HashMap::new();
122
123        for (cmd_key, st) in &self.stats.commands {
124            let cat = TaskClassifier::classify_command_key(cmd_key);
125            let row = by_cat.entry(cat).or_insert(TaskGainRow {
126                category: cat,
127                commands: 0,
128                tokens_saved: 0,
129                tool_calls: 0,
130                tool_spend_usd: 0.0,
131            });
132            row.commands += st.count;
133            row.tokens_saved += st.input_tokens.saturating_sub(st.output_tokens);
134        }
135
136        for (tool, tc) in &self.costs.tools {
137            let cat = TaskClassifier::classify_tool(tool);
138            let row = by_cat.entry(cat).or_insert(TaskGainRow {
139                category: cat,
140                commands: 0,
141                tokens_saved: 0,
142                tool_calls: 0,
143                tool_spend_usd: 0.0,
144            });
145            row.tool_calls += tc.total_calls;
146            row.tool_spend_usd += tc.cost_usd;
147        }
148
149        let mut out: Vec<TaskGainRow> = by_cat.into_values().collect();
150        out.sort_by_key(|x| std::cmp::Reverse(x.tokens_saved));
151        out
152    }
153
154    pub fn heatmap_gains(&self, limit: usize) -> Vec<FileGainRow> {
155        let mut items: Vec<_> = self.heatmap.entries.values().collect();
156        items.sort_by_key(|x| std::cmp::Reverse(x.total_tokens_saved));
157        items.truncate(limit);
158        items
159            .into_iter()
160            .map(|e| FileGainRow {
161                path: e.path.clone(),
162                access_count: e.access_count,
163                tokens_saved: e.total_tokens_saved,
164                compression_pct: e.avg_compression_ratio * 100.0,
165            })
166            .collect()
167    }
168}
lean_ctx/core/gain/mod.rs

lean_ctx/core/gain/
mod.rs
