1pub mod bridge_status;
2pub mod gain_score;
3pub mod model_pricing;
4pub mod task_classifier;
5
6use serde::{Deserialize, Serialize};
7
8use crate::core::a2a::cost_attribution::CostStore;
9use crate::core::gain::gain_score::GainScore;
10use crate::core::gain::model_pricing::{ModelPricing, ModelQuote};
11use crate::core::gain::task_classifier::{TaskCategory, TaskClassifier};
12use crate::core::heatmap::HeatMap;
13use crate::core::stats::StatsStore;
14
15#[derive(Clone)]
16pub struct GainEngine {
17 pub stats: StatsStore,
18 pub costs: CostStore,
19 pub heatmap: HeatMap,
20 pub pricing: ModelPricing,
21 pub events: Vec<crate::core::events::LeanCtxEvent>,
22 pub session: Option<crate::core::session::SessionState>,
23}
24
25#[derive(Debug, Clone, Serialize, Deserialize)]
26pub struct GainSummary {
27 pub model: ModelQuote,
28 pub total_commands: u64,
29 pub input_tokens: u64,
30 pub output_tokens: u64,
31 pub tokens_saved: u64,
32 pub gain_rate_pct: f64,
33 #[serde(default)]
40 pub injected_overhead_tokens_per_turn: u64,
41 #[serde(default)]
46 pub turns: u64,
47 #[serde(default)]
50 pub injected_overhead_total_tokens: u64,
51 #[serde(default)]
55 pub net_tokens_saved: i64,
56 #[serde(default)]
59 pub injected_overhead_budget_tokens: u64,
60 #[serde(default)]
62 pub over_budget: bool,
63 pub avoided_usd: f64,
64 pub energy_wh: f64,
66 pub co2_grams: f64,
68 pub tool_spend_usd: f64,
69 pub roi: Option<f64>,
70 pub score: GainScore,
71 #[serde(skip_serializing_if = "Option::is_none", default)]
72 pub daemon_hint: Option<String>,
73}
74
75#[derive(Debug, Clone, Serialize, Deserialize)]
76pub struct TaskGainRow {
77 pub category: TaskCategory,
78 pub commands: u64,
79 pub tokens_saved: u64,
80 pub tool_calls: u64,
81 pub tool_spend_usd: f64,
82}
83
84#[derive(Debug, Clone, Serialize, Deserialize)]
85pub struct FileGainRow {
86 pub path: String,
87 pub access_count: u32,
88 pub tokens_saved: u64,
89 pub compression_pct: f32,
90}
91
92impl GainEngine {
93 pub fn load() -> Self {
94 Self {
95 stats: crate::core::stats::load_for_display(),
98 costs: crate::core::a2a::cost_attribution::CostStore::load(),
99 heatmap: crate::core::heatmap::HeatMap::load(),
100 pricing: ModelPricing::load(),
101 events: crate::core::events::load_events_from_file(500),
102 session: crate::core::session::SessionState::load_latest(),
103 }
104 }
105
106 pub fn summary(&self, model: Option<&str>) -> GainSummary {
107 let quote = self.pricing.quote(model);
108 let tokens_saved = self
109 .stats
110 .total_input_tokens
111 .saturating_sub(self.stats.total_output_tokens);
112 let gain_rate_pct = if self.stats.total_input_tokens > 0 {
113 tokens_saved as f64 / self.stats.total_input_tokens as f64 * 100.0
114 } else {
115 0.0
116 };
117 let avoided_usd = quote.cost.estimate_usd(tokens_saved, 0, 0, 0);
118 let tool_spend_usd = self.costs.total_cost().max(0.0);
119 let roi = if tool_spend_usd > 0.0 {
120 Some(avoided_usd / tool_spend_usd)
121 } else {
122 None
123 };
124 let score = GainScore::compute(&self.stats, &self.costs, &self.pricing, model);
125 let daemon_hint = if crate::daemon::is_daemon_running() {
128 None
129 } else {
130 Some(
131 "daemon not running — stats tracked locally (lean-ctx serve -d for full tracking)"
132 .to_string(),
133 )
134 };
135 let injected_overhead_tokens_per_turn =
136 crate::core::context_overhead::ContextOverhead::cached().total_tokens() as u64;
137 let turns = crate::core::context_overhead::observed_turns();
142 let (injected_overhead_total_tokens, net_tokens_saved) =
143 crate::core::context_overhead::net_of_injection(
144 tokens_saved,
145 injected_overhead_tokens_per_turn,
146 turns,
147 );
148 let injected_overhead_budget_tokens =
152 crate::core::config::Config::load().context_budget_tokens_effective() as u64;
153 let over_budget = injected_overhead_budget_tokens > 0
154 && injected_overhead_tokens_per_turn > injected_overhead_budget_tokens;
155 GainSummary {
156 model: quote,
157 total_commands: self.stats.total_commands,
158 input_tokens: self.stats.total_input_tokens,
159 output_tokens: self.stats.total_output_tokens,
160 tokens_saved,
161 gain_rate_pct,
162 injected_overhead_tokens_per_turn,
163 turns,
164 injected_overhead_total_tokens,
165 net_tokens_saved,
166 injected_overhead_budget_tokens,
167 over_budget,
168 avoided_usd,
169 energy_wh: crate::core::energy::wh_for_tokens(tokens_saved),
170 co2_grams: crate::core::energy::co2_grams_for_tokens(tokens_saved),
171 tool_spend_usd,
172 roi,
173 score,
174 daemon_hint,
175 }
176 }
177
178 pub fn gain_score(&self, model: Option<&str>) -> GainScore {
179 GainScore::compute(&self.stats, &self.costs, &self.pricing, model)
180 }
181
182 pub fn task_breakdown(&self) -> Vec<TaskGainRow> {
183 use std::collections::HashMap;
184
185 let mut by_cat: HashMap<TaskCategory, TaskGainRow> = HashMap::new();
186
187 for (cmd_key, st) in &self.stats.commands {
188 let cat = TaskClassifier::classify_command_key(cmd_key);
189 let row = by_cat.entry(cat).or_insert(TaskGainRow {
190 category: cat,
191 commands: 0,
192 tokens_saved: 0,
193 tool_calls: 0,
194 tool_spend_usd: 0.0,
195 });
196 row.commands += st.count;
197 row.tokens_saved += st.input_tokens.saturating_sub(st.output_tokens);
198 }
199
200 for (tool, tc) in &self.costs.tools {
201 let cat = TaskClassifier::classify_tool(tool);
202 let row = by_cat.entry(cat).or_insert(TaskGainRow {
203 category: cat,
204 commands: 0,
205 tokens_saved: 0,
206 tool_calls: 0,
207 tool_spend_usd: 0.0,
208 });
209 row.tool_calls += tc.total_calls;
210 row.tool_spend_usd += tc.cost_usd;
211 }
212
213 let mut out: Vec<TaskGainRow> = by_cat.into_values().collect();
214 out.sort_by_key(|x| std::cmp::Reverse(x.tokens_saved));
215 out
216 }
217
218 pub fn heatmap_gains(&self, limit: usize) -> Vec<FileGainRow> {
219 let mut items: Vec<_> = self.heatmap.entries.values().collect();
220 items.sort_by_key(|x| std::cmp::Reverse(x.total_tokens_saved));
221 items.truncate(limit);
222 items
223 .into_iter()
224 .map(|e| FileGainRow {
225 path: e.path.clone(),
226 access_count: e.access_count,
227 tokens_saved: e.total_tokens_saved,
228 compression_pct: e.avg_compression_ratio * 100.0,
229 })
230 .collect()
231 }
232}