feat: add support for Antigravity log parsing and analysis

cspell.json

@@ -4,6 +4,8 @@
   "minWordLength": 5,
   "words": [
     "aicoach",
+    "varint",
+    "swazz",
     "acked",
     "affordances",
     "akiaiosfodnn",

src/core/analyzer-consumption.ts

@@ -114,7 +114,7 @@ function attributeSessionLevel(
   const byModel = new Map<string, SessionRequest[]>();
   for (const r of session.requests) {
     if (delegatedRequests?.has(r)) continue;
-    const m = normalizeModel(r.modelId || 'untracked');
+    const m = normalizeModel(r.modelId || 'untracked', true);
     if (!byModel.has(m)) byModel.set(m, []);
     byModel.get(m)!.push(r);
   }
@@ -219,7 +219,7 @@ export class ConsumptionAnalyzer extends AnalyzerBase {
     const defaultMultipliers: Record<string, number> = {};
 
     for (const r of reqs) {
-      const model = normalizeModel(r.modelId || 'untracked');
+      const model = normalizeModel(r.modelId || 'untracked', true);
       const mult = modelMultiplier(model);
       defaultMultipliers[model] = mult;
       modelTotals.set(model, (modelTotals.get(model) || 0) + 1);
@@ -289,7 +289,7 @@ export class ConsumptionAnalyzer extends AnalyzerBase {
     const dailyReqs = new Map<number, number>();
     for (const r of reqs) {
       const d = new Date(r.timestamp!).getDate();
-      const mult = modelMultiplier(normalizeModel(r.modelId || 'untracked'));
+      const mult = modelMultiplier(normalizeModel(r.modelId || 'untracked', true));
       dailyReqs.set(d, (dailyReqs.get(d) || 0) + mult);
     }
 
@@ -426,7 +426,7 @@ export class ConsumptionAnalyzer extends AnalyzerBase {
     request: SessionRequest,
     billing: RequestBilling | undefined,
   ): void {
-    const model = normalizeModel(request.modelId || 'untracked');
+    const model = normalizeModel(request.modelId || 'untracked', true);
     const resolvedBilling: RequestBilling = billing ?? {
       uncachedInput: 0,
       totalInput: 0,
@@ -754,7 +754,7 @@ export class ConsumptionAnalyzer extends AnalyzerBase {
         countedCount++;
         const tokens = (requestBilling?.totalInput ?? 0) + (requestBilling?.output ?? 0);
         dailyTokens.set(dayIdx + 1, (dailyTokens.get(dayIdx + 1) || 0) + tokens);
-        const model = normalizeModel(request.modelId ?? 'unknown');
+        const model = normalizeModel(request.modelId ?? 'unknown', true);
         if (!dailyTokensByModel.has(model)) dailyTokensByModel.set(model, new Map());
         const modelDay = dailyTokensByModel.get(model)!;
         modelDay.set(dayIdx + 1, (modelDay.get(dayIdx + 1) || 0) + tokens);

src/core/analyzer-production.ts

@@ -27,7 +27,7 @@ export class ProductionAnalyzer extends AnalyzerBase {
       const day = toDateStr(request.timestamp!);
       const session = this.requestSessionMap.get(request);
       const workspaceName = session?.workspaceName || '';
-      const model = normalizeModel(request.modelId || 'unknown');
+      const model = normalizeModel(request.modelId || 'unknown', true);
       const harness = session?.harness || 'unknown';
       for (const block of request.aiCode) {
         totalAiLoc += block.loc;
@@ -46,7 +46,7 @@ export class ProductionAnalyzer extends AnalyzerBase {
       const day = request.timestamp ? toDateStr(request.timestamp) : null;
       const session = this.requestSessionMap.get(request);
       const workspaceName = session?.workspaceName || '';
-      const model = normalizeModel(request.modelId || 'unknown');
+      const model = normalizeModel(request.modelId || 'unknown', true);
       const harness = session?.harness || 'unknown';
       for (const [file, loc] of editLocs) {
         totalAiLoc += loc;

src/core/constants.ts

@@ -19,7 +19,8 @@ export const MODEL_MULTIPLIERS: Record<string, number> = {
   'claude-opus-4.7': 7.5,
   'claude-haiku-4.5': 0.33,
   'gemini-2.0-flash': 0.25, 'gemini-2.5-pro': 1, 'gemini-3-flash': 0.33,
-  'gemini-3-pro': 1, 'gemini-3.1-pro': 1,
+  'gemini-3-pro': 1, 'gemini-3.1-pro': 1, 'gemini-3.5-flash': 0.33, 'gemini-3.1-flash': 0.33,
+  'gpt-oss-120b': 0.5,
   'grok-code-fast-1': 0.25, 'raptor-mini': 0, 'goldeneye': 1,
   'copilot-internal': 0, 'auto': 1, 'custom-model': 1,
 };
@@ -59,6 +60,9 @@ export const MODEL_TOKEN_RATES: Record<string, TokenRate> = {
   'gemini-3-flash':     { input: 0.50, cached: 0.05,  output: 3.00 },
   'gemini-3-pro':       { input: 2.00, cached: 0.20,  output: 12.00 },
   'gemini-3.1-pro':     { input: 2.00, cached: 0.20,  output: 12.00 },
+  'gemini-3.5-flash':   { input: 0.50, cached: 0.05,  output: 3.00 },
+  'gemini-3.1-flash':   { input: 0.50, cached: 0.05,  output: 3.00 },
+  'gpt-oss-120b':       { input: 1.00, cached: 0.10,  output: 4.00 },
   'grok-code-fast-1':   { input: 0.20, cached: 0.02,  output: 1.50 },
   'raptor-mini':        { input: 0.25, cached: 0.025, output: 2.00 },
   'goldeneye':          { input: 1.25, cached: 0.125, output: 10.00 },

src/core/dsl/interpreter.ts

@@ -278,14 +278,21 @@ const MODEL_TIERS: Record<string, number> = {
   'o4-mini': 2, 'o3-mini': 1, 'o3': 3, 'o1-mini': 1, 'o1-preview': 2, 'o1': 2,
   'gpt-4.1-nano': 0.2, 'gpt-4.1-mini': 0.5, 'gpt-4.1': 1,
   'gpt-4-turbo': 1, 'gpt-4': 1,
-  'gemini-3.1-pro': 1, 'gemini-3-pro': 1, 'gemini-3-flash': 0.33,
+  'gemini-3.5-flash-low': 0.33, 'gemini-3.5-flash-medium': 0.33, 'gemini-3.5-flash-high': 0.33,
+  'gemini-3.5-flash': 0.33, 
+  'gemini-3.1-flash-image2': 0.33, 'gemini-3.1-flash': 0.33,
+  'gemini-3.1-pro-low': 1, 'gemini-3.1-pro-high': 1, 'gemini-3.1-pro': 1,
+  'gemini-3-pro': 1, 'gemini-3-flash': 0.33,
   'gemini-2.5-pro': 1, 'gemini-2.0-flash': 0.3,
+  'claude-sonnet-4.6-thinking': 1, 'claude-opus-4.6-thinking': 3,
+  'gpt-oss-120b-medium': 0.5, 'gpt-oss-120b': 0.5,
   'grok-code-fast-1': 0.25,
 };
 
 function modelTierLookup(raw: string): number {
   const id = raw.replace(/^(openai\/|anthropic\/|google\/)/, '').replace(/-\d{4}-\d{2}-\d{2}$/, '').toLowerCase();
-  for (const [k, v] of Object.entries(MODEL_TIERS)) {
+  const sortedTiers = Object.entries(MODEL_TIERS).sort((a, b) => b[0].length - a[0].length);
+  for (const [k, v] of sortedTiers) {
     if (id.includes(k)) return v;
   }
   return 0;

src/core/helpers.test.ts

@@ -4,7 +4,7 @@
  *--------------------------------------------------------------------------------------------*/
 
 import { describe, it, expect } from 'vitest';
-import { fileUriToPath, toDateStr, startOfDay, endOfDay, isoWeek, normalizeModel, modelMultiplier, classifyWorkType } from './helpers';
+import { fileUriToPath, toDateStr, startOfDay, endOfDay, isoWeek, normalizeModel, modelMultiplier, classifyWorkType, tokenCostInCredits } from './helpers';
 
 describe('fileUriToPath', () => {
   it('converts a Windows file URI', () => {
@@ -150,6 +150,30 @@ describe('modelMultiplier', () => {
   it('returns 1 for unknown models', () => {
     expect(modelMultiplier('totally-unknown-model')).toBe(1);
   });
+
+  it('correctly maps Antigravity model variants via prefix matching', () => {
+    expect(modelMultiplier('gemini-3.5-flash-low')).toBe(0.33);
+    expect(modelMultiplier('gemini-3.5-flash-medium')).toBe(0.33);
+    expect(modelMultiplier('gemini-3.1-pro-high')).toBe(1);
+    expect(modelMultiplier('claude-sonnet-4.6-thinking')).toBe(1);
+    expect(modelMultiplier('claude-opus-4.6-thinking')).toBe(3);
+    expect(modelMultiplier('gpt-oss-120b-medium')).toBe(0.5);
+  });
+});
+
+describe('tokenCostInCredits', () => {
+  it('calculates cost using prefix match rates', () => {
+    // gemini-3.5-flash-low should use gemini-3.5-flash rates (input: 0.50, output: 3.00)
+    // 1M input tokens * $0.50 + 1M output tokens * $3.00 = $3.50 * 100 = 350 credits
+    const cost = tokenCostInCredits('gemini-3.5-flash-low', 1_000_000, 1_000_000);
+    expect(cost).toBe(350);
+  });
+
+  it('falls back to modelMultiplier when no prefix rate matches', () => {
+    // unknown-model-here should fallback to modelMultiplier (1) = 1 credit
+    const cost = tokenCostInCredits('unknown-model-here', 1_000, 1_000);
+    expect(cost).toBe(1);
+  });
 });
 
 describe('classifyWorkType', () => {

src/core/helpers.ts

@@ -111,12 +111,12 @@ export function fillMonthRange(months: string[]): string[] {
  *  while the effort value is captured separately via extractReasoningEffortFromModelId. */
 const EFFORT_SUFFIX_RE = /-(xhigh|extra-high|max|high|medium|med|low|minimal)$/;
 
-export function normalizeModel(modelId: string): string {
+export function normalizeModel(modelId: string, keepSuffix = false): string {
   let m = modelId.trim();
   for (const prefix of ['copilot/', 'github.copilot-chat/', 'github/']) {
     if (m.startsWith(prefix)) { m = m.slice(prefix.length); break; }
   }
-  m = m.replace(/-thought$/, '').replace(/-preview$/, '').replace(/-latest$/, '');
+  m = m.replace(/-(thought|thinking)$/, '').replace(/-preview$/, '').replace(/-latest$/, '');
   // Claude's API returns hyphenated version numbers (claude-opus-4-6) where
   // our rate tables use dots (claude-opus-4.6). Also strip -YYYYMMDD date
   // suffixes that older API responses append (claude-haiku-4-5-20251001).
@@ -128,7 +128,7 @@ export function normalizeModel(modelId: string): string {
   }
   // Strip effort suffixes ONLY for known reasoning-capable families (avoid
   // false positives on models like gpt-5.4-mini or gemini-3-flash).
-  if (EFFORT_BEARING_RE.test(m) && !NON_EFFORT_SUFFIXES_RE.test(m)) {
+  if (!keepSuffix && EFFORT_BEARING_RE.test(m) && !NON_EFFORT_SUFFIXES_RE.test(m)) {
     m = m.replace(EFFORT_SUFFIX_RE, '');
   }
   return m.trim();
@@ -137,7 +137,8 @@ export function normalizeModel(modelId: string): string {
 export function modelMultiplier(modelId: string): number {
   const key = normalizeModel(modelId);
   if (MODEL_MULTIPLIERS[key] !== undefined) return MODEL_MULTIPLIERS[key];
-  for (const [k, v] of Object.entries(MODEL_MULTIPLIERS)) {
+  const sortedEntries = Object.entries(MODEL_MULTIPLIERS).sort((a, b) => b[0].length - a[0].length);
+  for (const [k, v] of sortedEntries) {
     if (key.startsWith(k)) return v;
   }
   return 1;
@@ -263,7 +264,17 @@ export function tokenCostInCredits(
   cacheReadTokens: number = 0,
   cacheWriteTokens: number = 0,
 ): number {
-  const rates = MODEL_TOKEN_RATES[normalizeModel(model)];
+  let rates = MODEL_TOKEN_RATES[normalizeModel(model)];
+  if (!rates) {
+    const norm = normalizeModel(model);
+    const sortedRates = Object.entries(MODEL_TOKEN_RATES).sort((a, b) => b[0].length - a[0].length);
+    for (const [k, v] of sortedRates) {
+      if (norm.startsWith(k)) {
+        rates = v;
+        break;
+      }
+    }
+  }
   if (!rates) {
     // Fallback: use model multiplier as rough proxy (1 PRU ≈ 1 credit)
     return modelMultiplier(model);