@tokenometer/core - npm Package Compare versions

Comparing version 0.0.5 to 0.1.0

dist/config.d.ts

+declare const ALLOWED_FORMATS: readonly ["json", "yaml", "xml", "markdown", "text"];
+export type ConfigFormat = (typeof ALLOWED_FORMATS)[number];
+export interface TokenometerConfig {
+    models?: string[];
+    formats?: ConfigFormat[];
+    budgets?: {
+        total?: number;
+        'per-file'?: number;
+    };
+    paths?: string[];
+}
+export declare const parseConfig: (yamlText: string) => TokenometerConfig;
+export declare const loadConfig: (cwd?: string) => Promise<TokenometerConfig | null>;
+export {};
+//# sourceMappingURL=config.d.ts.map

dist/config.d.ts.map

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dist/config.js

+import { parse as yamlParse } from 'yaml';
+import { KNOWN_MODELS } from './rates.js';
+const ALLOWED_FORMATS = ['json', 'yaml', 'xml', 'markdown', 'text'];
+const CONFIG_FILENAMES = ['.tokenometer.yml', '.tokenometer.yaml'];
+const isPlainObject = (value) => typeof value === 'object' && value !== null && !Array.isArray(value);
+const ensureStringArray = (value, field) => {
+    if (!Array.isArray(value)) {
+        throw new Error(`tokenometer config: "${field}" must be an array of strings.`);
+    }
+    return value.map((item, idx) => {
+        if (typeof item !== 'string') {
+            throw new Error(`tokenometer config: "${field}[${idx}]" must be a string, got ${typeof item}.`);
+        }
+        return item;
+    });
+};
+const validateModels = (value) => {
+    const ids = ensureStringArray(value, 'models');
+    for (const id of ids) {
+        if (!KNOWN_MODELS.includes(id)) {
+            throw new Error(`tokenometer config: unknown model "${id}". Known: ${KNOWN_MODELS.join(', ')}.`);
+        }
+    }
+    return ids;
+};
+const validateFormats = (value) => {
+    const raw = ensureStringArray(value, 'formats');
+    for (const fmt of raw) {
+        if (!ALLOWED_FORMATS.includes(fmt)) {
+            throw new Error(`tokenometer config: unknown format "${fmt}". Known: ${ALLOWED_FORMATS.join(', ')}.`);
+        }
+    }
+    return raw;
+};
+const validateBudgets = (value) => {
+    if (!isPlainObject(value)) {
+        throw new Error('tokenometer config: "budgets" must be an object.');
+    }
+    const out = {};
+    for (const key of Object.keys(value)) {
+        if (key !== 'total' && key !== 'per-file') {
+            throw new Error(`tokenometer config: unknown budget key "${key}". Allowed: total, per-file.`);
+        }
+        const raw = value[key];
+        if (typeof raw !== 'number' || !Number.isFinite(raw) || raw < 0) {
+            throw new Error(`tokenometer config: "budgets.${key}" must be a non-negative number, got ${JSON.stringify(raw)}.`);
+        }
+        if (key === 'total')
+            out.total = raw;
+        else
+            out['per-file'] = raw;
+    }
+    return out;
+};
+const validatePaths = (value) => ensureStringArray(value, 'paths');
+const ALLOWED_KEYS = new Set(['models', 'formats', 'budgets', 'paths']);
+export const parseConfig = (yamlText) => {
+    const parsed = yamlText.trim() ? yamlParse(yamlText) : {};
+    if (parsed === null || parsed === undefined)
+        return {};
+    if (!isPlainObject(parsed)) {
+        throw new Error('tokenometer config: top-level must be a mapping.');
+    }
+    for (const key of Object.keys(parsed)) {
+        if (!ALLOWED_KEYS.has(key)) {
+            throw new Error(`tokenometer config: unknown top-level key "${key}". Allowed: ${[...ALLOWED_KEYS].join(', ')}.`);
+        }
+    }
+    const out = {};
+    if ('models' in parsed)
+        out.models = validateModels(parsed.models);
+    if ('formats' in parsed)
+        out.formats = validateFormats(parsed.formats);
+    if ('budgets' in parsed)
+        out.budgets = validateBudgets(parsed.budgets);
+    if ('paths' in parsed)
+        out.paths = validatePaths(parsed.paths);
+    return out;
+};
+// loadConfig touches the filesystem. Imports are deferred via dynamic import so
+// browser bundlers (Vite for the web playground) don't statically trace
+// `node:fs` and friends — externalized stubs would fail to expose named members
+// like `join`, breaking the build. Node still resolves them normally at runtime.
+export const loadConfig = async (cwd) => {
+    const { existsSync } = await import('node:fs');
+    const { readFile } = await import('node:fs/promises');
+    const { dirname, join, parse: parsePath } = await import('node:path');
+    const findConfigFile = (startDir) => {
+        let dir = startDir;
+        while (true) {
+            for (const name of CONFIG_FILENAMES) {
+                const candidate = join(dir, name);
+                if (existsSync(candidate))
+                    return candidate;
+            }
+            const isGitRoot = existsSync(join(dir, '.git'));
+            const parent = dirname(dir);
+            if (isGitRoot)
+                return null;
+            if (parent === dir || parent === parsePath(dir).root) {
+                if (parent !== dir) {
+                    for (const name of CONFIG_FILENAMES) {
+                        const candidate = join(parent, name);
+                        if (existsSync(candidate))
+                            return candidate;
+                    }
+                }
+                return null;
+            }
+            dir = parent;
+        }
+    };
+    const start = cwd ?? process.cwd();
+    const file = findConfigFile(start);
+    if (!file)
+        return null;
+    const text = await readFile(file, 'utf8');
+    return parseConfig(text);
+};
+//# sourceMappingURL=config.js.map

dist/config.js.map

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dist/format-sarif.d.ts

+import type { TokenizeResult } from './types.js';
+/**
+ * Per-file aggregate of matrix results, suitable for SARIF emission.
+ * `path` is the source-relative URI that will land in the SARIF location.
+ */
+export interface TokenometerFileResult {
+    path: string;
+    results: readonly TokenizeResult[];
+}
+/**
+ * Top-level result envelope passed to SARIF / future formatters.
+ * Modeled as a discriminated wrapper so additional fields (e.g. budget verdicts,
+ * empirical metadata) can be added without breaking existing callers.
+ */
+export interface TokenometerResult {
+    files: readonly TokenometerFileResult[];
+}
+export interface ToSarifOptions {
+    toolVersion?: string;
+}
+interface SarifLocation {
+    physicalLocation: {
+        artifactLocation: {
+            uri: string;
+        };
+    };
+}
+interface SarifResultEntry {
+    ruleId: string;
+    level: 'note';
+    message: {
+        text: string;
+    };
+    locations: SarifLocation[];
+}
+interface SarifTool {
+    driver: {
+        name: string;
+        version: string;
+        informationUri: string;
+        rules: {
+            id: string;
+            name: string;
+            shortDescription: {
+                text: string;
+            };
+        }[];
+    };
+}
+interface SarifRun {
+    tool: SarifTool;
+    results: SarifResultEntry[];
+}
+interface SarifLog {
+    $schema: string;
+    version: string;
+    runs: SarifRun[];
+}
+export declare const toSarif: (result: TokenometerResult, opts?: ToSarifOptions) => SarifLog;
+export {};
+//# sourceMappingURL=format-sarif.d.ts.map

dist/format-sarif.d.ts.map

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dist/format-sarif.js

+const formatCost = (usd) => {
+    if (usd >= 0.01)
+        return `$${usd.toFixed(4)}`;
+    if (usd >= 0.000001)
+        return `$${usd.toFixed(6)}`;
+    return `$${usd.toExponential(2)}`;
+};
+const SARIF_SCHEMA = 'https://raw.githubusercontent.com/oasis-tcs/sarif-spec/main/Schemata/sarif-schema-2.1.0.json';
+const SARIF_VERSION = '2.1.0';
+const TOOL_NAME = 'Tokenometer';
+const TOOL_INFO_URI = 'https://github.com/faraa2m/tokenometer';
+const RULE_ID = 'prompt-cost';
+export const toSarif = (result, opts) => {
+    const toolVersion = opts?.toolVersion ?? '0.0.0';
+    const results = [];
+    for (const file of result.files) {
+        for (const cell of file.results) {
+            results.push({
+                ruleId: RULE_ID,
+                level: 'note',
+                message: {
+                    text: `${cell.model} / ${cell.format}: ${cell.inputTokens.toLocaleString()} tokens · ${formatCost(cell.inputCost)}`,
+                },
+                locations: [{ physicalLocation: { artifactLocation: { uri: file.path } } }],
+            });
+        }
+    }
+    return {
+        $schema: SARIF_SCHEMA,
+        version: SARIF_VERSION,
+        runs: [
+            {
+                tool: {
+                    driver: {
+                        name: TOOL_NAME,
+                        version: toolVersion,
+                        informationUri: TOOL_INFO_URI,
+                        rules: [
+                            {
+                                id: RULE_ID,
+                                name: 'prompt-cost',
+                                shortDescription: {
+                                    text: 'Estimated input-token cost for this prompt file.',
+                                },
+                            },
+                        ],
+                    },
+                },
+                results,
+            },
+        ],
+    };
+};
+//# sourceMappingURL=format-sarif.js.map

dist/format-sarif.js.map

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dist/latency.d.ts

+import type { EmpiricalEnv } from './empirical.js';
+import type { LatencyResult, LatencyStats, LatencyTrial, Provider } from './types.js';
+export type { LatencyResult, LatencyStats, LatencyTrial };
+export interface MeasureLatencyOptions {
+    modelId: string;
+    prompt: string;
+    trials: number;
+    maxTokens?: number;
+    env: EmpiricalEnv;
+}
+/**
+ * Linear-interpolation percentile. `p` is 0-100. With p95 over n=3 trials this
+ * just returns max(values), which is what we want for the "tail" reading.
+ */
+declare const nthPercentile: (values: readonly number[], p: number) => number;
+/**
+ * Test seam: callers (tests) can substitute a provider's trial runner. The
+ * production `measureLatency` always uses the real implementations above.
+ */
+export interface LatencyDeps {
+    fetchImpl?: typeof fetch;
+    trialRunner?: (provider: Provider, modelId: string, prompt: string, maxTokens: number, env: EmpiricalEnv) => Promise<LatencyTrial>;
+}
+/**
+ * Run `trials` real streaming generations and return percentile-summarized
+ * latency data. Each trial is retried once on failure; if both attempts
+ * fail, the original provider error is rethrown.
+ */
+export declare const measureLatency: (options: MeasureLatencyOptions, deps?: LatencyDeps) => Promise<LatencyResult>;
+export { nthPercentile };
+//# sourceMappingURL=latency.d.ts.map

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dist/latency.js

+// Real-generation latency measurement.
+//
+// Unlike `tokenizeEmpirical` (which calls the free `countTokens` endpoints),
+// this dispatches a real metered streaming generation per provider and
+// measures wall-clock TTFT (time to first token) + total stream duration +
+// tokens/sec from the actual output. Reported as p50/p95/mean over `trials`
+// runs so callers see a stable distribution rather than a single noisy run.
+//
+// Cost note: every trial is a metered chat completion. The CLI bumps the
+// default `--max-spend` ceiling when `--latency` is on; see args.ts.
+import Anthropic from '@anthropic-ai/sdk';
+import { GoogleGenerativeAI } from '@google/generative-ai';
+import { getModel } from './rates.js';
+const DEFAULT_MAX_TOKENS = 200;
+const ENV_VAR_NAME = {
+    anthropicApiKey: 'ANTHROPIC_API_KEY',
+    cohereApiKey: 'COHERE_API_KEY',
+    googleApiKey: 'GOOGLE_API_KEY',
+    mistralApiKey: 'MISTRAL_API_KEY',
+    openaiApiKey: 'OPENAI_API_KEY',
+};
+const requireKey = (env, key, provider) => {
+    const value = env[key];
+    if (!value) {
+        const envName = key === 'googleApiKey' ? `${ENV_VAR_NAME[key]} (or GEMINI_API_KEY)` : ENV_VAR_NAME[key];
+        throw new Error(`${provider} latency mode requires ${envName}`);
+    }
+    return value;
+};
+/**
+ * Linear-interpolation percentile. `p` is 0-100. With p95 over n=3 trials this
+ * just returns max(values), which is what we want for the "tail" reading.
+ */
+const nthPercentile = (values, p) => {
+    if (values.length === 0)
+        return 0;
+    const sorted = [...values].sort((a, b) => a - b);
+    if (sorted.length === 1)
+        return sorted[0];
+    const rank = (p / 100) * (sorted.length - 1);
+    const lower = Math.floor(rank);
+    const upper = Math.ceil(rank);
+    const lowerValue = sorted[lower];
+    if (lower === upper)
+        return lowerValue;
+    const upperValue = sorted[upper];
+    return lowerValue + (upperValue - lowerValue) * (rank - lower);
+};
+const mean = (values) => {
+    if (values.length === 0)
+        return 0;
+    let sum = 0;
+    for (const v of values)
+        sum += v;
+    return sum / values.length;
+};
+const summarize = (trials) => {
+    const ttft = trials.map((t) => t.ttftMs);
+    const total = trials.map((t) => t.totalMs);
+    const tps = trials.map((t) => t.tokensPerSec);
+    return {
+        trials: [...trials],
+        p50: {
+            ttftMs: nthPercentile(ttft, 50),
+            totalMs: nthPercentile(total, 50),
+            tokensPerSec: nthPercentile(tps, 50),
+        },
+        p95: {
+            ttftMs: nthPercentile(ttft, 95),
+            totalMs: nthPercentile(total, 95),
+            tokensPerSec: nthPercentile(tps, 95),
+        },
+        mean: {
+            ttftMs: mean(ttft),
+            totalMs: mean(total),
+            tokensPerSec: mean(tps),
+        },
+    };
+};
+const computeTokensPerSec = (outputTokens, ttftMs, totalMs) => {
+    // Avoid divide-by-zero on instant streams (mocked tests, very fast paths).
+    const generationMs = Math.max(totalMs - ttftMs, 1);
+    return (outputTokens / generationMs) * 1000;
+};
+// ---------------------------------------------------------------------------
+// Per-provider trial runners. Each returns one LatencyTrial.
+// ---------------------------------------------------------------------------
+const trialAnthropic = async (modelId, prompt, maxTokens, apiKey) => {
+    const client = new Anthropic({ apiKey, dangerouslyAllowBrowser: true });
+    const start = Date.now();
+    let ttftMs = 0;
+    let outputTokens = 0;
+    const stream = client.messages.stream({
+        max_tokens: maxTokens,
+        messages: [{ content: prompt, role: 'user' }],
+        model: modelId,
+    });
+    for await (const event of stream) {
+        const e = event;
+        if (ttftMs === 0 &&
+            e.type === 'content_block_delta' &&
+            e.delta?.type === 'text_delta' &&
+            typeof e.delta?.text === 'string' &&
+            e.delta.text.length > 0) {
+            ttftMs = Date.now() - start;
+        }
+        if (e.type === 'message_delta' && typeof e.usage?.output_tokens === 'number') {
+            outputTokens = e.usage.output_tokens;
+        }
+        if (e.type === 'message_start' && typeof e.message?.usage?.output_tokens === 'number') {
+            // initial usage is typically 0 — message_delta carries the running count
+        }
+    }
+    const totalMs = Date.now() - start;
+    return {
+        ttftMs: ttftMs || totalMs,
+        totalMs,
+        outputTokens,
+        tokensPerSec: computeTokensPerSec(outputTokens, ttftMs || totalMs, totalMs),
+    };
+};
+const trialGoogle = async (modelId, prompt, maxTokens, apiKey) => {
+    const genAI = new GoogleGenerativeAI(apiKey);
+    const model = genAI.getGenerativeModel({
+        model: modelId,
+        generationConfig: { maxOutputTokens: maxTokens },
+    });
+    const start = Date.now();
+    let ttftMs = 0;
+    let outputTokens = 0;
+    const result = await model.generateContentStream(prompt);
+    for await (const chunk of result.stream) {
+        if (ttftMs === 0) {
+            const text = chunk.text?.();
+            if (text && text.length > 0)
+                ttftMs = Date.now() - start;
+        }
+        const usage = chunk.usageMetadata;
+        if (usage && typeof usage.candidatesTokenCount === 'number') {
+            outputTokens = usage.candidatesTokenCount;
+        }
+    }
+    const totalMs = Date.now() - start;
+    return {
+        ttftMs: ttftMs || totalMs,
+        totalMs,
+        outputTokens,
+        tokensPerSec: computeTokensPerSec(outputTokens, ttftMs || totalMs, totalMs),
+    };
+};
+/**
+ * Generic SSE iterator. Yields one parsed JSON object per `data: …` line and
+ * stops on `data: [DONE]`. Used for OpenAI + Mistral (Cohere has its own
+ * NDJSON-style stream, see below).
+ */
+async function* iterSse(body) {
+    const reader = body.getReader();
+    const decoder = new TextDecoder('utf-8');
+    let buf = '';
+    while (true) {
+        const { done, value } = await reader.read();
+        if (done)
+            break;
+        buf += decoder.decode(value, { stream: true });
+        // Split on double-newline (SSE event boundary).
+        while (true) {
+            const idx = buf.indexOf('\n\n');
+            if (idx === -1)
+                break;
+            const eventBlock = buf.slice(0, idx);
+            buf = buf.slice(idx + 2);
+            for (const line of eventBlock.split('\n')) {
+                if (!line.startsWith('data:'))
+                    continue;
+                const payload = line.slice(5).trim();
+                if (payload === '[DONE]' || payload.length === 0)
+                    return;
+                try {
+                    yield JSON.parse(payload);
+                }
+                catch {
+                    // skip malformed line
+                }
+            }
+        }
+    }
+}
+const trialOpenAi = async (modelId, prompt, maxTokens, apiKey, fetchImpl = fetch) => {
+    const start = Date.now();
+    const response = await fetchImpl('https://api.openai.com/v1/chat/completions', {
+        method: 'POST',
+        headers: {
+            Authorization: `Bearer ${apiKey}`,
+            'Content-Type': 'application/json',
+        },
+        body: JSON.stringify({
+            model: modelId,
+            messages: [{ role: 'user', content: prompt }],
+            max_tokens: maxTokens,
+            stream: true,
+            stream_options: { include_usage: true },
+        }),
+    });
+    if (!response.ok || !response.body) {
+        const body = await response.text().catch(() => '');
+        throw new Error(`OpenAI /v1/chat/completions returned ${response.status} ${response.statusText}${body ? `: ${body}` : ''}`);
+    }
+    let ttftMs = 0;
+    let outputTokens = 0;
+    for await (const ev of iterSse(response.body)) {
+        const choices = ev.choices;
+        if (ttftMs === 0 && choices && choices[0]?.delta?.content)
+            ttftMs = Date.now() - start;
+        const usage = ev.usage;
+        if (usage && typeof usage.completion_tokens === 'number')
+            outputTokens = usage.completion_tokens;
+    }
+    const totalMs = Date.now() - start;
+    return {
+        ttftMs: ttftMs || totalMs,
+        totalMs,
+        outputTokens,
+        tokensPerSec: computeTokensPerSec(outputTokens, ttftMs || totalMs, totalMs),
+    };
+};
+const trialMistral = async (modelId, prompt, maxTokens, apiKey, fetchImpl = fetch) => {
+    const start = Date.now();
+    const response = await fetchImpl('https://api.mistral.ai/v1/chat/completions', {
+        method: 'POST',
+        headers: {
+            Authorization: `Bearer ${apiKey}`,
+            'Content-Type': 'application/json',
+            Accept: 'text/event-stream',
+        },
+        body: JSON.stringify({
+            model: modelId,
+            messages: [{ role: 'user', content: prompt }],
+            max_tokens: maxTokens,
+            stream: true,
+        }),
+    });
+    if (!response.ok || !response.body) {
+        const body = await response.text().catch(() => '');
+        throw new Error(`Mistral /v1/chat/completions returned ${response.status} ${response.statusText}${body ? `: ${body}` : ''}`);
+    }
+    let ttftMs = 0;
+    let outputTokens = 0;
+    for await (const ev of iterSse(response.body)) {
+        const choices = ev.choices;
+        if (ttftMs === 0 && choices && choices[0]?.delta?.content)
+            ttftMs = Date.now() - start;
+        const usage = ev.usage;
+        if (usage && typeof usage.completion_tokens === 'number')
+            outputTokens = usage.completion_tokens;
+    }
+    const totalMs = Date.now() - start;
+    return {
+        ttftMs: ttftMs || totalMs,
+        totalMs,
+        outputTokens,
+        tokensPerSec: computeTokensPerSec(outputTokens, ttftMs || totalMs, totalMs),
+    };
+};
+const trialCohere = async (modelId, prompt, maxTokens, apiKey, fetchImpl = fetch) => {
+    // Cohere /v1/chat streams NDJSON (one JSON object per line), not SSE.
+    // See https://docs.cohere.com/reference/chat for event types
+    // (stream-start, text-generation, stream-end).
+    const start = Date.now();
+    const response = await fetchImpl('https://api.cohere.com/v1/chat', {
+        method: 'POST',
+        headers: {
+            Authorization: `Bearer ${apiKey}`,
+            'Content-Type': 'application/json',
+        },
+        body: JSON.stringify({
+            model: modelId,
+            message: prompt,
+            max_tokens: maxTokens,
+            stream: true,
+        }),
+    });
+    if (!response.ok || !response.body) {
+        const body = await response.text().catch(() => '');
+        throw new Error(`Cohere /v1/chat returned ${response.status} ${response.statusText}${body ? `: ${body}` : ''}`);
+    }
+    const reader = response.body.getReader();
+    const decoder = new TextDecoder('utf-8');
+    let buf = '';
+    let ttftMs = 0;
+    let outputTokens = 0;
+    while (true) {
+        const { done, value } = await reader.read();
+        if (done)
+            break;
+        buf += decoder.decode(value, { stream: true });
+        while (true) {
+            const nl = buf.indexOf('\n');
+            if (nl === -1)
+                break;
+            const line = buf.slice(0, nl).trim();
+            buf = buf.slice(nl + 1);
+            if (!line)
+                continue;
+            let ev;
+            try {
+                ev = JSON.parse(line);
+            }
+            catch {
+                continue;
+            }
+            if (ttftMs === 0 && ev.event_type === 'text-generation')
+                ttftMs = Date.now() - start;
+            if (ev.event_type === 'stream-end') {
+                const resp = ev.response;
+                const out = resp?.meta?.tokens?.output_tokens;
+                if (typeof out === 'number')
+                    outputTokens = out;
+            }
+        }
+    }
+    const totalMs = Date.now() - start;
+    return {
+        ttftMs: ttftMs || totalMs,
+        totalMs,
+        outputTokens,
+        tokensPerSec: computeTokensPerSec(outputTokens, ttftMs || totalMs, totalMs),
+    };
+};
+const defaultTrialRunner = async (provider, modelId, prompt, maxTokens, env, fetchImpl = fetch) => {
+    switch (provider) {
+        case 'anthropic':
+            return trialAnthropic(modelId, prompt, maxTokens, requireKey(env, 'anthropicApiKey', provider));
+        case 'google':
+            return trialGoogle(modelId, prompt, maxTokens, requireKey(env, 'googleApiKey', provider));
+        case 'openai':
+            return trialOpenAi(modelId, prompt, maxTokens, requireKey(env, 'openaiApiKey', provider), fetchImpl);
+        case 'mistral':
+            return trialMistral(modelId, prompt, maxTokens, requireKey(env, 'mistralApiKey', provider), fetchImpl);
+        case 'cohere':
+            return trialCohere(modelId, prompt, maxTokens, requireKey(env, 'cohereApiKey', provider), fetchImpl);
+    }
+};
+/**
+ * Run `trials` real streaming generations and return percentile-summarized
+ * latency data. Each trial is retried once on failure; if both attempts
+ * fail, the original provider error is rethrown.
+ */
+export const measureLatency = async (options, deps = {}) => {
+    const provider = getModel(options.modelId).provider;
+    const maxTokens = options.maxTokens ?? DEFAULT_MAX_TOKENS;
+    const fetchImpl = deps.fetchImpl ?? fetch;
+    const runner = deps.trialRunner ??
+        ((p, m, prompt, max, env) => defaultTrialRunner(p, m, prompt, max, env, fetchImpl));
+    const trials = [];
+    for (let i = 0; i < options.trials; i++) {
+        let lastErr;
+        let success = null;
+        for (let attempt = 0; attempt < 2; attempt++) {
+            try {
+                success = await runner(provider, options.modelId, options.prompt, maxTokens, options.env);
+                break;
+            }
+            catch (err) {
+                lastErr = err;
+            }
+        }
+        if (!success) {
+            throw lastErr instanceof Error ? lastErr : new Error(String(lastErr));
+        }
+        trials.push(success);
+    }
+    return summarize(trials);
+};
+export { nthPercentile };
+//# sourceMappingURL=latency.js.map

dist/latency.js.map

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dist/tokenize-cohere.d.ts

+export interface CohereCountResult {
+    approximate: true;
+    tokens: number;
+    tokenizer: 'heuristic';
+}
+export declare const cohereCount: (text: string) => CohereCountResult;
+/**
+ * Hits Cohere's `POST /v1/tokenize` endpoint. The response shape we care
+ * about is `{ tokens: number[] }`; only `tokens.length` is used.
+ *
+ * Endpoint reference: https://docs.cohere.com/reference/tokenize
+ *
+ * Returns the exact token count. Pulled out of `empirical.ts` so the
+ * dependency surface (one fetch call, no SDK) stays here next to the
+ * offline path it complements.
+ */
+export declare const cohereTokenizeApi: (text: string, modelId: string, apiKey: string, fetchImpl?: typeof fetch) => Promise<number>;
+//# sourceMappingURL=tokenize-cohere.d.ts.map

dist/tokenize-cohere.d.ts.map

+{"version":3,"file":"tokenize-cohere.d.ts","sourceRoot":"","sources":["../src/tokenize-cohere.ts"],"names":[],"mappings":"AAwBA,MAAM,WAAW,iBAAiB;IAChC,WAAW,EAAE,IAAI,CAAC;IAClB,MAAM,EAAE,MAAM,CAAC;IACf,SAAS,EAAE,WAAW,CAAC;CACxB;AAED,eAAO,MAAM,WAAW,GAAI,MAAM,MAAM,KAAG,iBAIzC,CAAC;AAEH;;;;;;;;;GASG;AACH,eAAO,MAAM,iBAAiB,GAC5B,MAAM,MAAM,EACZ,SAAS,MAAM,EACf,QAAQ,MAAM,EACd,YAAW,OAAO,KAAa,KAC9B,OAAO,CAAC,MAAM,CAoBhB,CAAC"}

dist/tokenize-cohere.js

+// Cohere tokenizer dispatch.
+//
+// Cohere ships their tokenizers as `tokenizer.json` files on HuggingFace
+// (e.g. `Cohere/command-r-plus`). The `cohere-ai` SDK is a thin REST client
+// — it does NOT bundle an offline tokenizer, only a `client.tokenize()`
+// method that hits Cohere's API. Confirmed against `cohere-ai@8.0.0` at the
+// time of writing (May 2026). So:
+//
+//   * Offline mode: chars/4 heuristic, `approximate: true`. Same accuracy
+//     tier as the Google heuristic in tokenize.ts.
+//
+//   * Empirical mode: POST https://api.cohere.com/v1/tokenize. The endpoint
+//     is free and very low latency. Wired in `empirical.ts`.
+//
+// We deliberately do NOT depend on `cohere-ai` for the empirical path — it
+// is a 4.9 MB SDK and we only need one POST. Native `fetch` keeps the
+// install footprint identical to the offline-only build.
+//
+// Future upgrade: once `@huggingface/tokenizers` is stable (Path D in the
+// research memo), lazy-load `tokenizer.json` per Cohere model from HF Hub
+// for exact offline counts.
+const COHERE_HEURISTIC_CHARS_PER_TOKEN = 4;
+export const cohereCount = (text) => ({
+    approximate: true,
+    tokens: Math.ceil(text.length / COHERE_HEURISTIC_CHARS_PER_TOKEN),
+    tokenizer: 'heuristic',
+});
+/**
+ * Hits Cohere's `POST /v1/tokenize` endpoint. The response shape we care
+ * about is `{ tokens: number[] }`; only `tokens.length` is used.
+ *
+ * Endpoint reference: https://docs.cohere.com/reference/tokenize
+ *
+ * Returns the exact token count. Pulled out of `empirical.ts` so the
+ * dependency surface (one fetch call, no SDK) stays here next to the
+ * offline path it complements.
+ */
+export const cohereTokenizeApi = async (text, modelId, apiKey, fetchImpl = fetch) => {
+    const response = await fetchImpl('https://api.cohere.com/v1/tokenize', {
+        body: JSON.stringify({ model: modelId, text }),
+        headers: {
+            Authorization: `Bearer ${apiKey}`,
+            'Content-Type': 'application/json',
+        },
+        method: 'POST',
+    });
+    if (!response.ok) {
+        const body = await response.text().catch(() => '');
+        throw new Error(`Cohere /v1/tokenize returned ${response.status} ${response.statusText}${body ? `: ${body}` : ''}`);
+    }
+    const data = (await response.json());
+    if (!Array.isArray(data.tokens)) {
+        throw new Error('Cohere /v1/tokenize returned an unexpected shape (no tokens array).');
+    }
+    return data.tokens.length;
+};
+//# sourceMappingURL=tokenize-cohere.js.map

dist/tokenize-cohere.js.map

+{"version":3,"file":"tokenize-cohere.js","sourceRoot":"","sources":["../src/tokenize-cohere.ts"],"names":[],"mappings":"AAAA,6BAA6B;AAC7B,EAAE;AACF,yEAAyE;AACzE,4EAA4E;AAC5E,wEAAwE;AACxE,4EAA4E;AAC5E,kCAAkC;AAClC,EAAE;AACF,0EAA0E;AAC1E,mDAAmD;AACnD,EAAE;AACF,4EAA4E;AAC5E,6DAA6D;AAC7D,EAAE;AACF,2EAA2E;AAC3E,sEAAsE;AACtE,yDAAyD;AACzD,EAAE;AACF,0EAA0E;AAC1E,0EAA0E;AAC1E,4BAA4B;AAE5B,MAAM,gCAAgC,GAAG,CAAC,CAAC;AAQ3C,MAAM,CAAC,MAAM,WAAW,GAAG,CAAC,IAAY,EAAqB,EAAE,CAAC,CAAC;IAC/D,WAAW,EAAE,IAAI;IACjB,MAAM,EAAE,IAAI,CAAC,IAAI,CAAC,IAAI,CAAC,MAAM,GAAG,gCAAgC,CAAC;IACjE,SAAS,EAAE,WAAW;CACvB,CAAC,CAAC;AAEH;;;;;;;;;GASG;AACH,MAAM,CAAC,MAAM,iBAAiB,GAAG,KAAK,EACpC,IAAY,EACZ,OAAe,EACf,MAAc,EACd,YAA0B,KAAK,EACd,EAAE;IACnB,MAAM,QAAQ,GAAG,MAAM,SAAS,CAAC,oCAAoC,EAAE;QACrE,IAAI,EAAE,IAAI,CAAC,SAAS,CAAC,EAAE,KAAK,EAAE,OAAO,EAAE,IAAI,EAAE,CAAC;QAC9C,OAAO,EAAE;YACP,aAAa,EAAE,UAAU,MAAM,EAAE;YACjC,cAAc,EAAE,kBAAkB;SACnC;QACD,MAAM,EAAE,MAAM;KACf,CAAC,CAAC;IACH,IAAI,CAAC,QAAQ,CAAC,EAAE,EAAE,CAAC;QACjB,MAAM,IAAI,GAAG,MAAM,QAAQ,CAAC,IAAI,EAAE,CAAC,KAAK,CAAC,GAAG,EAAE,CAAC,EAAE,CAAC,CAAC;QACnD,MAAM,IAAI,KAAK,CACb,gCAAgC,QAAQ,CAAC,MAAM,IAAI,QAAQ,CAAC,UAAU,GAAG,IAAI,CAAC,CAAC,CAAC,KAAK,IAAI,EAAE,CAAC,CAAC,CAAC,EAAE,EAAE,CACnG,CAAC;IACJ,CAAC;IACD,MAAM,IAAI,GAAG,CAAC,MAAM,QAAQ,CAAC,IAAI,EAAE,CAA0B,CAAC;IAC9D,IAAI,CAAC,KAAK,CAAC,OAAO,CAAC,IAAI,CAAC,MAAM,CAAC,EAAE,CAAC;QAChC,MAAM,IAAI,KAAK,CAAC,qEAAqE,CAAC,CAAC;IACzF,CAAC;IACD,OAAO,IAAI,CAAC,MAAM,CAAC,MAAM,CAAC;AAC5B,CAAC,CAAC"}

dist/tokenize-mistral.d.ts

+export declare const isTekken: (modelId: string) => boolean;
+export interface MistralCountResult {
+    approximate: true;
+    tokens: number;
+    tokenizer: 'heuristic' | 'mistral_v1_v3';
+}
+/**
+ * Count tokens for a Mistral model. Always `approximate: true` (see file
+ * header). For SentencePiece models, returns the `mistral-tokenizer-js`
+ * count (BOS token included, matching the library's default). For Tekken
+ * models (and any unknown ID — defensive), returns a `chars/4` heuristic.
+ */
+export declare const mistralCount: (text: string, modelId: string) => MistralCountResult;
+//# sourceMappingURL=tokenize-mistral.d.ts.map

dist/tokenize-mistral.d.ts.map

+{"version":3,"file":"tokenize-mistral.d.ts","sourceRoot":"","sources":["../src/tokenize-mistral.ts"],"names":[],"mappings":"AAsDA,eAAO,MAAM,QAAQ,GAAI,SAAS,MAAM,KAAG,OAAqC,CAAC;AAOjF,MAAM,WAAW,kBAAkB;IACjC,WAAW,EAAE,IAAI,CAAC;IAClB,MAAM,EAAE,MAAM,CAAC;IACf,SAAS,EAAE,WAAW,GAAG,eAAe,CAAC;CAC1C;AAED;;;;;GAKG;AACH,eAAO,MAAM,YAAY,GAAI,MAAM,MAAM,EAAE,SAAS,MAAM,KAAG,kBAU5D,CAAC"}

dist/tokenize-mistral.js

+// Mistral tokenizer dispatch.
+//
+// Mistral has shipped two tokenizer families:
+//
+//   1. SentencePiece (V1/V2/V3) — the "classic" Mistral family. Covered by
+//      `mistral-tokenizer-js` (mistralTokenizer.encode → number[]). Models:
+//      Mistral 7B (v0.1/v0.2/v0.3), Mixtral 8x7B / 8x22B,
+//      Mistral Large 2407, Mistral Small 2402, Codestral 22B.
+//
+//   2. Tekken — a tiktoken-style 128k BPE introduced with Mistral NeMo
+//      (Jul 2024). Used by NeMo, Pixtral, Mistral Small 2409+, Devstral,
+//      Mistral Medium 2505+, Magistral, Ministral. NOT covered by
+//      `mistral-tokenizer-js`. Applying SentencePiece to Tekken models would
+//      give systematically wrong counts (different vocab, ~32k vs ~128k), so
+//      we fall back to the same `chars/4` heuristic used for Google.
+//
+// Both paths set `approximate: true` because:
+//   - Mistral does not publish an offline reference tokenizer for newer
+//     models, and even the SentencePiece path is "compatible with most"
+//     per the upstream README — no formal validation guarantee.
+//   - Mistral has no public free /v1/tokenize endpoint as of May 2026, so
+//     there's no empirical anchor available either.
+//
+// Future upgrade path (Path D in the research memo): once
+// `@huggingface/tokenizers` reaches v1.0, lazy-load `tokenizer.json` per
+// model for exact counts behind an opt-in flag.
+import mistralTokenizer from 'mistral-tokenizer-js';
+/**
+ * Mistral model IDs that use the Tekken tokenizer (post-NeMo families).
+ *
+ * Cross-reference list curated from the integration memo. Update as Mistral
+ * releases new model IDs; default-on-unknown is heuristic too, so this set
+ * is allowlist-style for SentencePiece, not the other way around.
+ */
+const TEKKEN_MODELS = new Set([
+    'mistral-nemo',
+    'pixtral-12b',
+    'pixtral-large-latest',
+    'mistral-small-latest',
+    'devstral-small-2505',
+    'devstral-small-2507',
+    'devstral-medium-2507',
+    'mistral-medium-2505',
+    'mistral-medium-2508',
+    'mistral-medium-latest',
+    'magistral-small',
+    'magistral-medium-latest',
+    'ministral-3b-latest',
+    'ministral-8b-latest',
+]);
+export const isTekken = (modelId) => TEKKEN_MODELS.has(modelId);
+const MISTRAL_HEURISTIC_CHARS_PER_TOKEN = 4;
+const heuristicCount = (text) => Math.ceil(text.length / MISTRAL_HEURISTIC_CHARS_PER_TOKEN);
+/**
+ * Count tokens for a Mistral model. Always `approximate: true` (see file
+ * header). For SentencePiece models, returns the `mistral-tokenizer-js`
+ * count (BOS token included, matching the library's default). For Tekken
+ * models (and any unknown ID — defensive), returns a `chars/4` heuristic.
+ */
+export const mistralCount = (text, modelId) => {
+    if (isTekken(modelId)) {
+        return { approximate: true, tokens: heuristicCount(text), tokenizer: 'heuristic' };
+    }
+    // SentencePiece path. `encode()` returns number[] including the BOS token
+    // by default — this matches what Mistral's chat completions endpoint
+    // would actually charge for, so we do not strip it.
+    const ids = mistralTokenizer.encode(text);
+    const tokenizer = 'mistral_v1_v3';
+    return { approximate: true, tokens: ids.length, tokenizer };
+};
+//# sourceMappingURL=tokenize-mistral.js.map

dist/tokenize-mistral.js.map

+{"version":3,"file":"tokenize-mistral.js","sourceRoot":"","sources":["../src/tokenize-mistral.ts"],"names":[],"mappings":"AAAA,8BAA8B;AAC9B,EAAE;AACF,8CAA8C;AAC9C,EAAE;AACF,2EAA2E;AAC3E,4EAA4E;AAC5E,0DAA0D;AAC1D,8DAA8D;AAC9D,EAAE;AACF,uEAAuE;AACvE,yEAAyE;AACzE,kEAAkE;AAClE,6EAA6E;AAC7E,6EAA6E;AAC7E,qEAAqE;AACrE,EAAE;AACF,8CAA8C;AAC9C,wEAAwE;AACxE,wEAAwE;AACxE,gEAAgE;AAChE,0EAA0E;AAC1E,oDAAoD;AACpD,EAAE;AACF,0DAA0D;AAC1D,yEAAyE;AACzE,gDAAgD;AAEhD,OAAO,gBAAgB,MAAM,sBAAsB,CAAC;AAGpD;;;;;;GAMG;AACH,MAAM,aAAa,GAAwB,IAAI,GAAG,CAAC;IACjD,cAAc;IACd,aAAa;IACb,sBAAsB;IACtB,sBAAsB;IACtB,qBAAqB;IACrB,qBAAqB;IACrB,sBAAsB;IACtB,qBAAqB;IACrB,qBAAqB;IACrB,uBAAuB;IACvB,iBAAiB;IACjB,yBAAyB;IACzB,qBAAqB;IACrB,qBAAqB;CACtB,CAAC,CAAC;AAEH,MAAM,CAAC,MAAM,QAAQ,GAAG,CAAC,OAAe,EAAW,EAAE,CAAC,aAAa,CAAC,GAAG,CAAC,OAAO,CAAC,CAAC;AAEjF,MAAM,iCAAiC,GAAG,CAAC,CAAC;AAE5C,MAAM,cAAc,GAAG,CAAC,IAAY,EAAU,EAAE,CAC9C,IAAI,CAAC,IAAI,CAAC,IAAI,CAAC,MAAM,GAAG,iCAAiC,CAAC,CAAC;AAQ7D;;;;;GAKG;AACH,MAAM,CAAC,MAAM,YAAY,GAAG,CAAC,IAAY,EAAE,OAAe,EAAsB,EAAE;IAChF,IAAI,QAAQ,CAAC,OAAO,CAAC,EAAE,CAAC;QACtB,OAAO,EAAE,WAAW,EAAE,IAAI,EAAE,MAAM,EAAE,cAAc,CAAC,IAAI,CAAC,EAAE,SAAS,EAAE,WAAW,EAAE,CAAC;IACrF,CAAC;IACD,0EAA0E;IAC1E,qEAAqE;IACrE,oDAAoD;IACpD,MAAM,GAAG,GAAG,gBAAgB,CAAC,MAAM,CAAC,IAAI,CAAC,CAAC;IAC1C,MAAM,SAAS,GAAkB,eAAe,CAAC;IACjD,OAAO,EAAE,WAAW,EAAE,IAAI,EAAE,MAAM,EAAE,GAAG,CAAC,MAAM,EAAE,SAAS,EAAE,CAAC;AAC9D,CAAC,CAAC"}

dist/vision-anthropic.d.ts

+export interface AnthropicVisionInput {
+    width: number;
+    height: number;
+    /** Anthropic's estimator does not branch on detail; accepted for API parity. */
+    detail?: 'low' | 'high' | 'auto';
+}
+/**
+ * Anthropic vision token estimator.
+ *
+ * Approximation per Anthropic guidance: tokens ≈ ceil((width * height) / 750),
+ * capped at 1600 tokens per image.
+ */
+export declare const visionTokens: ({ width, height }: AnthropicVisionInput) => number;
+//# sourceMappingURL=vision-anthropic.d.ts.map

dist/vision-anthropic.d.ts.map

+{"version":3,"file":"vision-anthropic.d.ts","sourceRoot":"","sources":["../src/vision-anthropic.ts"],"names":[],"mappings":"AAAA,MAAM,WAAW,oBAAoB;IACnC,KAAK,EAAE,MAAM,CAAC;IACd,MAAM,EAAE,MAAM,CAAC;IACf,gFAAgF;IAChF,MAAM,CAAC,EAAE,KAAK,GAAG,MAAM,GAAG,MAAM,CAAC;CAClC;AAID;;;;;GAKG;AACH,eAAO,MAAM,YAAY,GAAI,mBAAmB,oBAAoB,KAAG,MAQtE,CAAC"}

dist/vision-anthropic.js

+const MAX_TOKENS = 1600;
+/**
+ * Anthropic vision token estimator.
+ *
+ * Approximation per Anthropic guidance: tokens ≈ ceil((width * height) / 750),
+ * capped at 1600 tokens per image.
+ */
+export const visionTokens = ({ width, height }) => {
+    if (!Number.isFinite(width) || !Number.isFinite(height) || width <= 0 || height <= 0) {
+        throw new Error(`anthropicVisionTokens: width and height must be positive finite numbers, got ${width}x${height}.`);
+    }
+    const raw = Math.ceil((width * height) / 750);
+    return Math.min(raw, MAX_TOKENS);
+};
+//# sourceMappingURL=vision-anthropic.js.map

dist/vision-anthropic.js.map

+{"version":3,"file":"vision-anthropic.js","sourceRoot":"","sources":["../src/vision-anthropic.ts"],"names":[],"mappings":"AAOA,MAAM,UAAU,GAAG,IAAI,CAAC;AAExB;;;;;GAKG;AACH,MAAM,CAAC,MAAM,YAAY,GAAG,CAAC,EAAE,KAAK,EAAE,MAAM,EAAwB,EAAU,EAAE;IAC9E,IAAI,CAAC,MAAM,CAAC,QAAQ,CAAC,KAAK,CAAC,IAAI,CAAC,MAAM,CAAC,QAAQ,CAAC,MAAM,CAAC,IAAI,KAAK,IAAI,CAAC,IAAI,MAAM,IAAI,CAAC,EAAE,CAAC;QACrF,MAAM,IAAI,KAAK,CACb,gFAAgF,KAAK,IAAI,MAAM,GAAG,CACnG,CAAC;IACJ,CAAC;IACD,MAAM,GAAG,GAAG,IAAI,CAAC,IAAI,CAAC,CAAC,KAAK,GAAG,MAAM,CAAC,GAAG,GAAG,CAAC,CAAC;IAC9C,OAAO,IAAI,CAAC,GAAG,CAAC,GAAG,EAAE,UAAU,CAAC,CAAC;AACnC,CAAC,CAAC"}

dist/vision-google.d.ts

+export interface GoogleVisionInput {
+    width: number;
+    height: number;
+    /** Google's estimator does not branch on detail; accepted for API parity. */
+    detail?: 'low' | 'high' | 'auto';
+}
+/**
+ * Google (Gemini) vision token estimator.
+ *
+ * Per Google guidance:
+ * - Images ≤ 384×384 cost a flat 258 tokens.
+ * - Larger images: 258 * ceil(width/768) * ceil(height/768), with a floor of 1 tile per axis.
+ */
+export declare const visionTokens: ({ width, height }: GoogleVisionInput) => number;
+//# sourceMappingURL=vision-google.d.ts.map

dist/vision-google.d.ts.map

+{"version":3,"file":"vision-google.d.ts","sourceRoot":"","sources":["../src/vision-google.ts"],"names":[],"mappings":"AAAA,MAAM,WAAW,iBAAiB;IAChC,KAAK,EAAE,MAAM,CAAC;IACd,MAAM,EAAE,MAAM,CAAC;IACf,6EAA6E;IAC7E,MAAM,CAAC,EAAE,KAAK,GAAG,MAAM,GAAG,MAAM,CAAC;CAClC;AAMD;;;;;;GAMG;AACH,eAAO,MAAM,YAAY,GAAI,mBAAmB,iBAAiB,KAAG,MAUnE,CAAC"}

dist/vision-google.js

+const SMALL_THRESHOLD = 384;
+const SMALL_TOKENS = 258;
+const TILE_SIZE = 768;
+/**
+ * Google (Gemini) vision token estimator.
+ *
+ * Per Google guidance:
+ * - Images ≤ 384×384 cost a flat 258 tokens.
+ * - Larger images: 258 * ceil(width/768) * ceil(height/768), with a floor of 1 tile per axis.
+ */
+export const visionTokens = ({ width, height }) => {
+    if (!Number.isFinite(width) || !Number.isFinite(height) || width <= 0 || height <= 0) {
+        throw new Error(`googleVisionTokens: width and height must be positive finite numbers, got ${width}x${height}.`);
+    }
+    if (width <= SMALL_THRESHOLD && height <= SMALL_THRESHOLD)
+        return SMALL_TOKENS;
+    const tilesX = Math.max(1, Math.ceil(width / TILE_SIZE));
+    const tilesY = Math.max(1, Math.ceil(height / TILE_SIZE));
+    return SMALL_TOKENS * tilesX * tilesY;
+};
+//# sourceMappingURL=vision-google.js.map

dist/vision-google.js.map

+{"version":3,"file":"vision-google.js","sourceRoot":"","sources":["../src/vision-google.ts"],"names":[],"mappings":"AAOA,MAAM,eAAe,GAAG,GAAG,CAAC;AAC5B,MAAM,YAAY,GAAG,GAAG,CAAC;AACzB,MAAM,SAAS,GAAG,GAAG,CAAC;AAEtB;;;;;;GAMG;AACH,MAAM,CAAC,MAAM,YAAY,GAAG,CAAC,EAAE,KAAK,EAAE,MAAM,EAAqB,EAAU,EAAE;IAC3E,IAAI,CAAC,MAAM,CAAC,QAAQ,CAAC,KAAK,CAAC,IAAI,CAAC,MAAM,CAAC,QAAQ,CAAC,MAAM,CAAC,IAAI,KAAK,IAAI,CAAC,IAAI,MAAM,IAAI,CAAC,EAAE,CAAC;QACrF,MAAM,IAAI,KAAK,CACb,6EAA6E,KAAK,IAAI,MAAM,GAAG,CAChG,CAAC;IACJ,CAAC;IACD,IAAI,KAAK,IAAI,eAAe,IAAI,MAAM,IAAI,eAAe;QAAE,OAAO,YAAY,CAAC;IAC/E,MAAM,MAAM,GAAG,IAAI,CAAC,GAAG,CAAC,CAAC,EAAE,IAAI,CAAC,IAAI,CAAC,KAAK,GAAG,SAAS,CAAC,CAAC,CAAC;IACzD,MAAM,MAAM,GAAG,IAAI,CAAC,GAAG,CAAC,CAAC,EAAE,IAAI,CAAC,IAAI,CAAC,MAAM,GAAG,SAAS,CAAC,CAAC,CAAC;IAC1D,OAAO,YAAY,GAAG,MAAM,GAAG,MAAM,CAAC;AACxC,CAAC,CAAC"}

dist/vision-openai.d.ts

+export interface OpenAIVisionInput {
+    width: number;
+    height: number;
+    /** OpenAI vision detail; defaults to 'high' if omitted. 'auto' resolves to 'high'. */
+    detail?: 'low' | 'high' | 'auto';
+}
+/**
+ * OpenAI vision token estimator.
+ *
+ * - 'low' detail: flat 85 tokens.
+ * - 'high'/'auto' detail (default): resize so the longest side is at most 2048,
+ *   then so the shortest side is at most 768; tile the result by 512×512;
+ *   total = 85 + 170 * tiles.
+ */
+export declare const visionTokens: ({ width, height, detail }: OpenAIVisionInput) => number;
+//# sourceMappingURL=vision-openai.d.ts.map

dist/vision-openai.d.ts.map

+{"version":3,"file":"vision-openai.d.ts","sourceRoot":"","sources":["../src/vision-openai.ts"],"names":[],"mappings":"AAAA,MAAM,WAAW,iBAAiB;IAChC,KAAK,EAAE,MAAM,CAAC;IACd,MAAM,EAAE,MAAM,CAAC;IACf,sFAAsF;IACtF,MAAM,CAAC,EAAE,KAAK,GAAG,MAAM,GAAG,MAAM,CAAC;CAClC;AASD;;;;;;;GAOG;AACH,eAAO,MAAM,YAAY,GAAI,2BAAoC,iBAAiB,KAAG,MA+BpF,CAAC"}

dist/vision-openai.js

+const LOW_DETAIL_TOKENS = 85;
+const HIGH_DETAIL_BASE = 85;
+const HIGH_DETAIL_PER_TILE = 170;
+const LONGEST_CAP = 2048;
+const SHORTEST_CAP = 768;
+const TILE_SIZE = 512;
+/**
+ * OpenAI vision token estimator.
+ *
+ * - 'low' detail: flat 85 tokens.
+ * - 'high'/'auto' detail (default): resize so the longest side is at most 2048,
+ *   then so the shortest side is at most 768; tile the result by 512×512;
+ *   total = 85 + 170 * tiles.
+ */
+export const visionTokens = ({ width, height, detail = 'high' }) => {
+    if (!Number.isFinite(width) || !Number.isFinite(height) || width <= 0 || height <= 0) {
+        throw new Error(`openaiVisionTokens: width and height must be positive finite numbers, got ${width}x${height}.`);
+    }
+    if (detail === 'low')
+        return LOW_DETAIL_TOKENS;
+    let w = width;
+    let h = height;
+    // Step 1: cap the longest side at 2048, preserving aspect ratio.
+    const longest = Math.max(w, h);
+    if (longest > LONGEST_CAP) {
+        const scale = LONGEST_CAP / longest;
+        w = w * scale;
+        h = h * scale;
+    }
+    // Step 2: scale so the shortest side is at most 768, preserving aspect ratio.
+    const shortest = Math.min(w, h);
+    if (shortest > SHORTEST_CAP) {
+        const scale = SHORTEST_CAP / shortest;
+        w = w * scale;
+        h = h * scale;
+    }
+    const tilesX = Math.ceil(w / TILE_SIZE);
+    const tilesY = Math.ceil(h / TILE_SIZE);
+    const tiles = tilesX * tilesY;
+    return HIGH_DETAIL_BASE + HIGH_DETAIL_PER_TILE * tiles;
+};
+//# sourceMappingURL=vision-openai.js.map

dist/vision-openai.js.map

+{"version":3,"file":"vision-openai.js","sourceRoot":"","sources":["../src/vision-openai.ts"],"names":[],"mappings":"AAOA,MAAM,iBAAiB,GAAG,EAAE,CAAC;AAC7B,MAAM,gBAAgB,GAAG,EAAE,CAAC;AAC5B,MAAM,oBAAoB,GAAG,GAAG,CAAC;AACjC,MAAM,WAAW,GAAG,IAAI,CAAC;AACzB,MAAM,YAAY,GAAG,GAAG,CAAC;AACzB,MAAM,SAAS,GAAG,GAAG,CAAC;AAEtB;;;;;;;GAOG;AACH,MAAM,CAAC,MAAM,YAAY,GAAG,CAAC,EAAE,KAAK,EAAE,MAAM,EAAE,MAAM,GAAG,MAAM,EAAqB,EAAU,EAAE;IAC5F,IAAI,CAAC,MAAM,CAAC,QAAQ,CAAC,KAAK,CAAC,IAAI,CAAC,MAAM,CAAC,QAAQ,CAAC,MAAM,CAAC,IAAI,KAAK,IAAI,CAAC,IAAI,MAAM,IAAI,CAAC,EAAE,CAAC;QACrF,MAAM,IAAI,KAAK,CACb,6EAA6E,KAAK,IAAI,MAAM,GAAG,CAChG,CAAC;IACJ,CAAC;IACD,IAAI,MAAM,KAAK,KAAK;QAAE,OAAO,iBAAiB,CAAC;IAE/C,IAAI,CAAC,GAAG,KAAK,CAAC;IACd,IAAI,CAAC,GAAG,MAAM,CAAC;IAEf,iEAAiE;IACjE,MAAM,OAAO,GAAG,IAAI,CAAC,GAAG,CAAC,CAAC,EAAE,CAAC,CAAC,CAAC;IAC/B,IAAI,OAAO,GAAG,WAAW,EAAE,CAAC;QAC1B,MAAM,KAAK,GAAG,WAAW,GAAG,OAAO,CAAC;QACpC,CAAC,GAAG,CAAC,GAAG,KAAK,CAAC;QACd,CAAC,GAAG,CAAC,GAAG,KAAK,CAAC;IAChB,CAAC;IAED,8EAA8E;IAC9E,MAAM,QAAQ,GAAG,IAAI,CAAC,GAAG,CAAC,CAAC,EAAE,CAAC,CAAC,CAAC;IAChC,IAAI,QAAQ,GAAG,YAAY,EAAE,CAAC;QAC5B,MAAM,KAAK,GAAG,YAAY,GAAG,QAAQ,CAAC;QACtC,CAAC,GAAG,CAAC,GAAG,KAAK,CAAC;QACd,CAAC,GAAG,CAAC,GAAG,KAAK,CAAC;IAChB,CAAC;IAED,MAAM,MAAM,GAAG,IAAI,CAAC,IAAI,CAAC,CAAC,GAAG,SAAS,CAAC,CAAC;IACxC,MAAM,MAAM,GAAG,IAAI,CAAC,IAAI,CAAC,CAAC,GAAG,SAAS,CAAC,CAAC;IACxC,MAAM,KAAK,GAAG,MAAM,GAAG,MAAM,CAAC;IAC9B,OAAO,gBAAgB,GAAG,oBAAoB,GAAG,KAAK,CAAC;AACzD,CAAC,CAAC"}

dist/empirical.d.ts

@@ -5,7 +5,10 @@ import type { Format, TokenizeResult } from './types.js';
     exact: true;
-    source: 'anthropic-count' | 'gemini-count' | 'tiktoken-o200k';
+    source: 'anthropic-count' | 'cohere-tokenize' | 'gemini-count' | 'tiktoken-o200k';
 }
 export interface EmpiricalEnv {
     anthropicApiKey?: string;
+    cohereApiKey?: string;
     googleApiKey?: string;
+    mistralApiKey?: string;
+    openaiApiKey?: string;
 }
@@ -12,0 +15,0 @@ export interface TokenizeEmpiricalOptions {

dist/empirical.d.ts.map

@@ -1,1 +0,1 @@
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+{"version":3,"file":"empirical.d.ts","sourceRoot":"","sources":["../src/empirical.ts"],"names":[],"mappings":"AAMA,OAAO,KAAK,EAAE,MAAM,EAAY,cAAc,EAAE,MAAM,YAAY,CAAC;AAEnE,MAAM,WAAW,oBAAoB;IACnC,KAAK,EAAE,MAAM,CAAC;IACd,KAAK,EAAE,IAAI,CAAC;IACZ,MAAM,EAAE,iBAAiB,GAAG,iBAAiB,GAAG,cAAc,GAAG,gBAAgB,CAAC;CACnF;AAED,MAAM,WAAW,YAAY;IAC3B,eAAe,CAAC,EAAE,MAAM,CAAC;IACzB,YAAY,CAAC,EAAE,MAAM,CAAC;IACtB,YAAY,CAAC,EAAE,MAAM,CAAC;IAGtB,aAAa,CAAC,EAAE,MAAM,CAAC;IACvB,YAAY,CAAC,EAAE,MAAM,CAAC;CACvB;AAwED,MAAM,WAAW,wBAAwB;IACvC,GAAG,EAAE,YAAY,CAAC;IAClB,MAAM,EAAE,MAAM,CAAC;IACf,OAAO,EAAE,MAAM,CAAC;IAChB,MAAM,EAAE,MAAM,CAAC;CAChB;AAED,eAAO,MAAM,iBAAiB,GAC5B,SAAS,wBAAwB,KAChC,OAAO,CAAC,cAAc,CAuCxB,CAAC;AAEF,MAAM,WAAW,8BAA8B;IAC7C,GAAG,EAAE,YAAY,CAAC;IAClB,OAAO,EAAE,SAAS,MAAM,EAAE,CAAC;IAC3B,QAAQ,EAAE,SAAS,MAAM,EAAE,CAAC;IAC5B,MAAM,EAAE,MAAM,CAAC;CAChB;AAED,eAAO,MAAM,uBAAuB,GAClC,SAAS,8BAA8B,KACtC,OAAO,CAAC,cAAc,EAAE,CAe1B,CAAC"}

dist/empirical.js

@@ -6,6 +6,15 @@ import Anthropic from '@anthropic-ai/sdk';
 import { getModel, getRate } from './rates.js';
+import { cohereTokenizeApi } from './tokenize-cohere.js';
+const ENV_VAR_NAME = {
+    anthropicApiKey: 'ANTHROPIC_API_KEY',
+    cohereApiKey: 'COHERE_API_KEY',
+    googleApiKey: 'GOOGLE_API_KEY',
+    mistralApiKey: 'MISTRAL_API_KEY',
+    openaiApiKey: 'OPENAI_API_KEY',
+};
 const requireKey = (env, key, provider) => {
     const value = env[key];
     if (!value) {
-        throw new Error(`${provider} empirical mode requires ${key === 'anthropicApiKey' ? 'ANTHROPIC_API_KEY' : 'GOOGLE_API_KEY'} (or GEMINI_API_KEY)`);
+        const envName = key === 'googleApiKey' ? `${ENV_VAR_NAME[key]} (or GEMINI_API_KEY)` : ENV_VAR_NAME[key];
+        throw new Error(`${provider} empirical mode requires ${envName}`);
     }
@@ -44,2 +53,7 @@ return value;
 });
+const countCohere = async (text, modelId, env) => {
+    const apiKey = requireKey(env, 'cohereApiKey', 'cohere');
+    const count = await cohereTokenizeApi(text, modelId, apiKey);
+    return { count, exact: true, source: 'cohere-tokenize' };
+};
 export const tokenizeEmpirical = async (options) => {
@@ -60,2 +74,14 @@ const model = getModel(options.modelId);
             break;
+        case 'cohere':
+            result = await countCohere(converted, model.id, options.env);
+            break;
+        case 'mistral':
+            // Mistral does not expose a public free token-count endpoint as of
+            // May 2026 (see .planning/research/mistral-integration.md). Refuse
+            // empirical mode rather than silently falling back to the offline
+            // path — that would violate the `--empirical` contract (count is
+            // exact). Users who want exact counts can call a metered chat
+            // completion and read back `usage.prompt_tokens` themselves.
+            throw new Error('Mistral does not expose a public token-count API; offline mode only. ' +
+                'For exact counts, send a chat completion to Mistral and read `usage.prompt_tokens`.');
     }
@@ -62,0 +88,0 @@ return {

dist/empirical.js.map

@@ -1,1 +0,1 @@
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dist/index.d.ts

@@ -0,8 +1,20 @@
+export { loadConfig, parseConfig } from './config.js';
+export type { ConfigFormat, TokenometerConfig } from './config.js';
 export { allFormats, isFormat, toFormat } from './convert.js';
 export { tokenizeEmpirical, tokenizeMatrixEmpirical } from './empirical.js';
 export type { EmpiricalCountResult, EmpiricalEnv } from './empirical.js';
+export { toSarif } from './format-sarif.js';
+export type { TokenometerFileResult, TokenometerResult, ToSarifOptions } from './format-sarif.js';
+export { measureLatency, nthPercentile } from './latency.js';
+export type { LatencyDeps, MeasureLatencyOptions } from './latency.js';
 export { KNOWN_MODELS, MODELS, RATES, RATES_VERSION, getModel, getRate } from './rates.js';
 export { countTokens, tokenize, tokenizeMatrix } from './tokenize.js';
 export type { CountResult } from './tokenize.js';
-export type { EmpiricalResult, Format, ModelDescriptor, Provider, RateEntry, TokenizeResult, TokenizerKind, } from './types.js';
+export type { EmpiricalResult, Format, LatencyResult, LatencyStats, LatencyTrial, ModelDescriptor, Provider, RateEntry, TokenizeResult, TokenizerKind, } from './types.js';
+export { visionTokens as anthropicVisionTokens } from './vision-anthropic.js';
+export type { AnthropicVisionInput } from './vision-anthropic.js';
+export { visionTokens as googleVisionTokens } from './vision-google.js';
+export type { GoogleVisionInput } from './vision-google.js';
+export { visionTokens as openaiVisionTokens } from './vision-openai.js';
+export type { OpenAIVisionInput } from './vision-openai.js';
 //# sourceMappingURL=index.d.ts.map

dist/index.d.ts.map

@@ -1,1 +0,1 @@
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+{"version":3,"file":"index.d.ts","sourceRoot":"","sources":["../src/index.ts"],"names":[],"mappings":"AAAA,OAAO,EAAE,UAAU,EAAE,WAAW,EAAE,MAAM,aAAa,CAAC;AACtD,YAAY,EAAE,YAAY,EAAE,iBAAiB,EAAE,MAAM,aAAa,CAAC;AACnE,OAAO,EAAE,UAAU,EAAE,QAAQ,EAAE,QAAQ,EAAE,MAAM,cAAc,CAAC;AAC9D,OAAO,EAAE,iBAAiB,EAAE,uBAAuB,EAAE,MAAM,gBAAgB,CAAC;AAC5E,YAAY,EAAE,oBAAoB,EAAE,YAAY,EAAE,MAAM,gBAAgB,CAAC;AACzE,OAAO,EAAE,OAAO,EAAE,MAAM,mBAAmB,CAAC;AAC5C,YAAY,EAAE,qBAAqB,EAAE,iBAAiB,EAAE,cAAc,EAAE,MAAM,mBAAmB,CAAC;AAClG,OAAO,EAAE,cAAc,EAAE,aAAa,EAAE,MAAM,cAAc,CAAC;AAC7D,YAAY,EAAE,WAAW,EAAE,qBAAqB,EAAE,MAAM,cAAc,CAAC;AACvE,OAAO,EAAE,YAAY,EAAE,MAAM,EAAE,KAAK,EAAE,aAAa,EAAE,QAAQ,EAAE,OAAO,EAAE,MAAM,YAAY,CAAC;AAC3F,OAAO,EAAE,WAAW,EAAE,QAAQ,EAAE,cAAc,EAAE,MAAM,eAAe,CAAC;AACtE,YAAY,EAAE,WAAW,EAAE,MAAM,eAAe,CAAC;AACjD,YAAY,EACV,eAAe,EACf,MAAM,EACN,aAAa,EACb,YAAY,EACZ,YAAY,EACZ,eAAe,EACf,QAAQ,EACR,SAAS,EACT,cAAc,EACd,aAAa,GACd,MAAM,YAAY,CAAC;AACpB,OAAO,EAAE,YAAY,IAAI,qBAAqB,EAAE,MAAM,uBAAuB,CAAC;AAC9E,YAAY,EAAE,oBAAoB,EAAE,MAAM,uBAAuB,CAAC;AAClE,OAAO,EAAE,YAAY,IAAI,kBAAkB,EAAE,MAAM,oBAAoB,CAAC;AACxE,YAAY,EAAE,iBAAiB,EAAE,MAAM,oBAAoB,CAAC;AAC5D,OAAO,EAAE,YAAY,IAAI,kBAAkB,EAAE,MAAM,oBAAoB,CAAC;AACxE,YAAY,EAAE,iBAAiB,EAAE,MAAM,oBAAoB,CAAC"}

dist/index.js

@@ -0,5 +1,11 @@
+export { loadConfig, parseConfig } from './config.js';
 export { allFormats, isFormat, toFormat } from './convert.js';
 export { tokenizeEmpirical, tokenizeMatrixEmpirical } from './empirical.js';
+export { toSarif } from './format-sarif.js';
+export { measureLatency, nthPercentile } from './latency.js';
 export { KNOWN_MODELS, MODELS, RATES, RATES_VERSION, getModel, getRate } from './rates.js';
 export { countTokens, tokenize, tokenizeMatrix } from './tokenize.js';
+export { visionTokens as anthropicVisionTokens } from './vision-anthropic.js';
+export { visionTokens as googleVisionTokens } from './vision-google.js';
+export { visionTokens as openaiVisionTokens } from './vision-openai.js';
 //# sourceMappingURL=index.js.map

dist/index.js.map

@@ -1,1 +0,1 @@
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+{"version":3,"file":"index.js","sourceRoot":"","sources":["../src/index.ts"],"names":[],"mappings":"AAAA,OAAO,EAAE,UAAU,EAAE,WAAW,EAAE,MAAM,aAAa,CAAC;AAEtD,OAAO,EAAE,UAAU,EAAE,QAAQ,EAAE,QAAQ,EAAE,MAAM,cAAc,CAAC;AAC9D,OAAO,EAAE,iBAAiB,EAAE,uBAAuB,EAAE,MAAM,gBAAgB,CAAC;AAE5E,OAAO,EAAE,OAAO,EAAE,MAAM,mBAAmB,CAAC;AAE5C,OAAO,EAAE,cAAc,EAAE,aAAa,EAAE,MAAM,cAAc,CAAC;AAE7D,OAAO,EAAE,YAAY,EAAE,MAAM,EAAE,KAAK,EAAE,aAAa,EAAE,QAAQ,EAAE,OAAO,EAAE,MAAM,YAAY,CAAC;AAC3F,OAAO,EAAE,WAAW,EAAE,QAAQ,EAAE,cAAc,EAAE,MAAM,eAAe,CAAC;AActE,OAAO,EAAE,YAAY,IAAI,qBAAqB,EAAE,MAAM,uBAAuB,CAAC;AAE9E,OAAO,EAAE,YAAY,IAAI,kBAAkB,EAAE,MAAM,oBAAoB,CAAC;AAExE,OAAO,EAAE,YAAY,IAAI,kBAAkB,EAAE,MAAM,oBAAoB,CAAC"}

dist/rates.d.ts

 import type { ModelDescriptor, RateEntry } from './types.js';
-export declare const RATES_VERSION = "2026-05-08";
+export declare const RATES_VERSION = "2026-05-09";
 export declare const RATES: Record<string, RateEntry>;
@@ -4,0 +4,0 @@ export declare const MODELS: Record<string, ModelDescriptor>;

dist/rates.d.ts.map

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dist/rates.js

 import anthropicProvider from '@tokenlens/models/anthropic';
 import googleProvider from '@tokenlens/models/google';
+import mistralProvider from '@tokenlens/models/mistral';
 import openaiProvider from '@tokenlens/models/openai';
 import { getContext, getTokenCosts } from 'tokenlens';
-export const RATES_VERSION = '2026-05-08';
+export const RATES_VERSION = '2026-05-09';
+// `@tokenlens/models` does not yet ship a Cohere catalog (verified against
+// node_modules/@tokenlens/models/dist/providers/ at v1.3.0). When upstream
+// adds it, drop the Cohere LOCAL_OVERRIDES entry and add the import here.
 const CATALOG = {
     anthropic: anthropicProvider,
     google: googleProvider,
+    mistral: mistralProvider,
     openai: openaiProvider,
 };
-const PROVIDERS = ['anthropic', 'google', 'openai'];
+const PROVIDERS = ['anthropic', 'google', 'mistral', 'openai'];
 // Bleeding-edge models tokenlens hasn't picked up from upstream yet.
 // Remove an entry once `scripts/check-overrides.mjs` reports it landed.
+//
+// Cohere entries are also here because `@tokenlens/models` does not yet
+// ship a Cohere catalog at all (v1.3.0). Pricing pulled from the published
+// Cohere pricing page (cohere.com/pricing) at RATES_VERSION date.
 const LOCAL_OVERRIDES = {
@@ -45,2 +54,22 @@ 'claude-haiku-4-5': {
     },
+    'command-r': {
+        rate: { inputPer1k: 0.00015, outputPer1k: 0.0006 },
+        descriptor: {
+            contextWindow: 128_000,
+            id: 'command-r',
+            maxOutputTokens: 4096,
+            pricingSource: 'local',
+            provider: 'cohere',
+        },
+    },
+    'command-r-plus': {
+        rate: { inputPer1k: 0.0025, outputPer1k: 0.01 },
+        descriptor: {
+            contextWindow: 128_000,
+            id: 'command-r-plus',
+            maxOutputTokens: 4096,
+            pricingSource: 'local',
+            provider: 'cohere',
+        },
+    },
 };
@@ -47,0 +76,0 @@ // Raw models.dev catalog data has no explicit status field; infer "preview" from

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+{"version":3,"file":"rates.js","sourceRoot":"","sources":["../src/rates.ts"],"names":[],"mappings":"AACA,OAAO,iBAAiB,MAAM,6BAA6B,CAAC;AAC5D,OAAO,cAAc,MAAM,0BAA0B,CAAC;AACtD,OAAO,eAAe,MAAM,2BAA2B,CAAC;AACxD,OAAO,cAAc,MAAM,0BAA0B,CAAC;AACtD,OAAO,EAAE,UAAU,EAAE,aAAa,EAAE,MAAM,WAAW,CAAC;AAGtD,MAAM,CAAC,MAAM,aAAa,GAAG,YAAY,CAAC;AAE1C,2EAA2E;AAC3E,2EAA2E;AAC3E,0EAA0E;AAC1E,MAAM,OAAO,GAAqB;IAChC,SAAS,EAAE,iBAAiB;IAC5B,MAAM,EAAE,cAAc;IACtB,OAAO,EAAE,eAAe;IACxB,MAAM,EAAE,cAAc;CACvB,CAAC;AAEF,MAAM,SAAS,GAAwB,CAAC,WAAW,EAAE,QAAQ,EAAE,SAAS,EAAE,QAAQ,CAAC,CAAC;AAOpF,qEAAqE;AACrE,wEAAwE;AACxE,EAAE;AACF,wEAAwE;AACxE,2EAA2E;AAC3E,kEAAkE;AAClE,MAAM,eAAe,GAAkC;IACrD,kBAAkB,EAAE;QAClB,IAAI,EAAE,EAAE,gBAAgB,EAAE,MAAM,EAAE,UAAU,EAAE,KAAK,EAAE,WAAW,EAAE,KAAK,EAAE;QACzE,UAAU,EAAE;YACV,aAAa,EAAE,OAAO;YACtB,EAAE,EAAE,kBAAkB;YACtB,eAAe,EAAE,MAAM;YACvB,aAAa,EAAE,OAAO;YACtB,QAAQ,EAAE,WAAW;SACtB;KACF;IACD,iBAAiB,EAAE;QACjB,IAAI,EAAE,EAAE,gBAAgB,EAAE,MAAM,EAAE,UAAU,EAAE,KAAK,EAAE,WAAW,EAAE,KAAK,EAAE;QACzE,UAAU,EAAE;YACV,aAAa,EAAE,OAAO;YACtB,EAAE,EAAE,iBAAiB;YACrB,eAAe,EAAE,MAAM;YACvB,aAAa,EAAE,OAAO;YACtB,QAAQ,EAAE,WAAW;SACtB;KACF;IACD,mBAAmB,EAAE;QACnB,IAAI,EAAE,EAAE,gBAAgB,EAAE,MAAM,EAAE,UAAU,EAAE,KAAK,EAAE,WAAW,EAAE,KAAK,EAAE;QACzE,UAAU,EAAE;YACV,aAAa,EAAE,OAAO;YACtB,EAAE,EAAE,mBAAmB;YACvB,eAAe,EAAE,MAAM;YACvB,aAAa,EAAE,OAAO;YACtB,QAAQ,EAAE,WAAW;SACtB;KACF;IACD,WAAW,EAAE;QACX,IAAI,EAAE,EAAE,UAAU,EAAE,OAAO,EAAE,WAAW,EAAE,MAAM,EAAE;QAClD,UAAU,EAAE;YACV,aAAa,EAAE,OAAO;YACtB,EAAE,EAAE,WAAW;YACf,eAAe,EAAE,IAAI;YACrB,aAAa,EAAE,OAAO;YACtB,QAAQ,EAAE,QAAQ;SACnB;KACF;IACD,gBAAgB,EAAE;QAChB,IAAI,EAAE,EAAE,UAAU,EAAE,MAAM,EAAE,WAAW,EAAE,IAAI,EAAE;QAC/C,UAAU,EAAE;YACV,aAAa,EAAE,OAAO;YACtB,EAAE,EAAE,gBAAgB;YACpB,eAAe,EAAE,IAAI;YACrB,aAAa,EAAE,OAAO;YACtB,QAAQ,EAAE,QAAQ;SACnB;KACF;CACF,CAAC;AAEF,iFAAiF;AACjF,8EAA8E;AAC9E,4EAA4E;AAC5E,MAAM,kBAAkB,GAAG,oBAAoB,CAAC;AAEhD,MAAM,kBAAkB,GAAG,GAAkC,EAAE;IAC7D,MAAM,GAAG,GAAkC,EAAE,CAAC;IAC9C,KAAK,MAAM,QAAQ,IAAI,SAAS,EAAE,CAAC;QACjC,MAAM,YAAY,GAAG,OAAO,CAAC,QAAQ,CAAC,CAAC;QACvC,IAAI,CAAC,YAAY;YAAE,SAAS;QAE5B,KAAK,MAAM,MAAM,IAAI,MAAM,CAAC,IAAI,CAAC,YAAY,CAAC,MAAM,CAAC,EAAE,CAAC;YACtD,IAAI,kBAAkB,CAAC,IAAI,CAAC,MAAM,CAAC;gBAAE,SAAS;YAE9C,MAAM,YAAY,GAAG,GAAG,QAAQ,IAAI,MAAM,EAAE,CAAC;YAE7C,MAAM,IAAI,GAAG,aAAa,CAAC;gBACzB,OAAO,EAAE,YAAY;gBACrB,SAAS,EAAE,OAAO;gBAClB,KAAK,EAAE,EAAE,KAAK,EAAE,IAAI,EAAE,MAAM,EAAE,IAAI,EAAE;aACrC,CAAC,CAAC;YACH,IAAI,CAAC,IAAI,CAAC,QAAQ,IAAI,CAAC,IAAI,CAAC,SAAS;gBAAE,SAAS;YAEhD,MAAM,GAAG,GAAG,UAAU,CAAC,EAAE,OAAO,EAAE,YAAY,EAAE,SAAS,EAAE,OAAO,EAAE,CAAC,CAAC;YACtE,MAAM,aAAa,GAAG,GAAG,CAAC,WAAW,IAAI,GAAG,CAAC,QAAQ,IAAI,GAAG,CAAC,QAAQ,CAAC;YACtE,MAAM,eAAe,GAAG,GAAG,CAAC,SAAS,IAAI,GAAG,CAAC,SAAS,CAAC;YAEvD,MAAM,IAAI,GAAc;gBACtB,UAAU,EAAE,IAAI,CAAC,QAAQ;gBACzB,WAAW,EAAE,IAAI,CAAC,SAAS;gBAC3B,GAAG,CAAC,IAAI,CAAC,YAAY,CAAC,CAAC,CAAC,EAAE,gBAAgB,EAAE,IAAI,CAAC,YAAY,EAAE,CAAC,CAAC,CAAC,EAAE,CAAC;aACtE,CAAC;YAEF,MAAM,UAAU,GAAoB;gBAClC,EAAE,EAAE,MAAM;gBACV,aAAa,EAAE,WAAW;gBAC1B,QAAQ;gBACR,GAAG,CAAC,aAAa,CAAC,CAAC,CAAC,EAAE,aAAa,EAAE,CAAC,CAAC,CAAC,EAAE,CAAC;gBAC3C,GAAG,CAAC,eAAe,CAAC,CAAC,CAAC,EAAE,eAAe,EAAE,CAAC,CAAC,CAAC,EAAE,CAAC;aAChD,CAAC;YAEF,MAAM,QAAQ,GAAG,GAAG,CAAC,MAAM,CAAC,CAAC;YAC7B,IAAI,QAAQ,IAAI,QAAQ,CAAC,UAAU,CAAC,QAAQ,KAAK,QAAQ,EAAE,CAAC;gBAC1D,wEAAwE;gBACxE,sCAAsC;gBACtC,OAAO,CAAC,IAAI,CACV,wCAAwC,MAAM,MAAM,QAAQ,CAAC,UAAU,CAAC,QAAQ,OAAO,QAAQ,aAAa,QAAQ,CAAC,UAAU,CAAC,QAAQ,GAAG,CAC5I,CAAC;gBACF,SAAS;YACX,CAAC;YAED,GAAG,CAAC,MAAM,CAAC,GAAG,EAAE,UAAU,EAAE,IAAI,EAAE,CAAC;QACrC,CAAC;IACH,CAAC;IACD,OAAO,GAAG,CAAC;AACb,CAAC,CAAC;AAEF,MAAM,QAAQ,GAAkC,CAAC,GAAG,EAAE;IACpD,MAAM,GAAG,GAAG,kBAAkB,EAAE,CAAC;IACjC,KAAK,MAAM,CAAC,EAAE,EAAE,KAAK,CAAC,IAAI,MAAM,CAAC,OAAO,CAAC,eAAe,CAAC,EAAE,CAAC;QAC1D,GAAG,CAAC,EAAE,CAAC,GAAG,KAAK,CAAC;IAClB,CAAC;IACD,OAAO,GAAG,CAAC;AACb,CAAC,CAAC,EAAE,CAAC;AAEL,MAAM,CAAC,MAAM,KAAK,GAA8B,MAAM,CAAC,WAAW,CAChE,MAAM,CAAC,OAAO,CAAC,QAAQ,CAAC,CAAC,GAAG,CAAC,CAAC,CAAC,EAAE,EAAE,CAAC,CAAC,EAAE,EAAE,CAAC,CAAC,EAAE,EAAE,CAAC,CAAC,IAAI,CAAC,CAAC,CACxD,CAAC;AAEF,MAAM,CAAC,MAAM,MAAM,GAAoC,MAAM,CAAC,WAAW,CACvE,MAAM,CAAC,OAAO,CAAC,QAAQ,CAAC,CAAC,GAAG,CAAC,CAAC,CAAC,EAAE,EAAE,CAAC,CAAC,EAAE,EAAE,CAAC,CAAC,EAAE,EAAE,CAAC,CAAC,UAAU,CAAC,CAAC,CAC9D,CAAC;AAEF,MAAM,CAAC,MAAM,YAAY,GAAsB,MAAM,CAAC,IAAI,CAAC,QAAQ,CAAC,CAAC,IAAI,EAAE,CAAC;AAE5E,MAAM,CAAC,MAAM,OAAO,GAAG,CAAC,OAAe,EAAa,EAAE;IACpD,MAAM,KAAK,GAAG,QAAQ,CAAC,OAAO,CAAC,CAAC;IAChC,IAAI,CAAC,KAAK,EAAE,CAAC;QACX,MAAM,IAAI,KAAK,CAAC,kBAAkB,OAAO,oBAAoB,YAAY,CAAC,IAAI,CAAC,IAAI,CAAC,GAAG,CAAC,CAAC;IAC3F,CAAC;IACD,OAAO,KAAK,CAAC,IAAI,CAAC;AACpB,CAAC,CAAC;AAEF,MAAM,CAAC,MAAM,QAAQ,GAAG,CAAC,OAAe,EAAmB,EAAE;IAC3D,MAAM,KAAK,GAAG,QAAQ,CAAC,OAAO,CAAC,CAAC;IAChC,IAAI,CAAC,KAAK,EAAE,CAAC;QACX,MAAM,IAAI,KAAK,CAAC,kBAAkB,OAAO,oBAAoB,YAAY,CAAC,IAAI,CAAC,IAAI,CAAC,GAAG,CAAC,CAAC;IAC3F,CAAC;IACD,OAAO,KAAK,CAAC,UAAU,CAAC;AAC1B,CAAC,CAAC"}

dist/tokenize.d.ts

@@ -7,3 +7,3 @@ import type { Format, Provider, TokenizeResult, TokenizerKind } from './types.js';
 }
-export declare const countTokens: (text: string, provider: Provider) => CountResult;
+export declare const countTokens: (text: string, provider: Provider, modelId?: string) => CountResult;
 export interface TokenizeOptions {
@@ -10,0 +10,0 @@ format: Format;

dist/tokenize.d.ts.map

@@ -1,1 +0,1 @@
-{"version":3,"file":"tokenize.d.ts","sourceRoot":"","sources":["../src/tokenize.ts"],"names":[],"mappings":"AAIA,OAAO,KAAK,EAAE,MAAM,EAAE,QAAQ,EAAE,cAAc,EAAE,aAAa,EAAE,MAAM,YAAY,CAAC;AAWlF,MAAM,WAAW,WAAW;IAC1B,WAAW,EAAE,OAAO,CAAC;IACrB,KAAK,EAAE,MAAM,CAAC;IACd,SAAS,EAAE,aAAa,CAAC;CAC1B;AAED,eAAO,MAAM,WAAW,GAAI,MAAM,MAAM,EAAE,UAAU,QAAQ,KAAG,WAa9D,CAAC;AAEF,MAAM,WAAW,eAAe;IAC9B,MAAM,EAAE,MAAM,CAAC;IACf,OAAO,EAAE,MAAM,CAAC;IAChB,MAAM,EAAE,MAAM,CAAC;CAChB;AAED,eAAO,MAAM,QAAQ,GAAI,SAAS,eAAe,KAAG,cAenD,CAAC;AAEF,MAAM,WAAW,qBAAqB;IACpC,OAAO,EAAE,SAAS,MAAM,EAAE,CAAC;IAC3B,QAAQ,EAAE,SAAS,MAAM,EAAE,CAAC;IAC5B,MAAM,EAAE,MAAM,CAAC;CAChB;AAED,eAAO,MAAM,cAAc,GAAI,SAAS,qBAAqB,KAAG,cAAc,EAQ7E,CAAC"}
+{"version":3,"file":"tokenize.d.ts","sourceRoot":"","sources":["../src/tokenize.ts"],"names":[],"mappings":"AAMA,OAAO,KAAK,EAAE,MAAM,EAAE,QAAQ,EAAE,cAAc,EAAE,aAAa,EAAE,MAAM,YAAY,CAAC;AAalF,MAAM,WAAW,WAAW;IAC1B,WAAW,EAAE,OAAO,CAAC;IACrB,KAAK,EAAE,MAAM,CAAC;IACd,SAAS,EAAE,aAAa,CAAC;CAC1B;AAED,eAAO,MAAM,WAAW,GAAI,MAAM,MAAM,EAAE,UAAU,QAAQ,EAAE,UAAU,MAAM,KAAG,WA0BhF,CAAC;AAEF,MAAM,WAAW,eAAe;IAC9B,MAAM,EAAE,MAAM,CAAC;IACf,OAAO,EAAE,MAAM,CAAC;IAChB,MAAM,EAAE,MAAM,CAAC;CAChB;AAED,eAAO,MAAM,QAAQ,GAAI,SAAS,eAAe,KAAG,cAenD,CAAC;AAEF,MAAM,WAAW,qBAAqB;IACpC,OAAO,EAAE,SAAS,MAAM,EAAE,CAAC;IAC3B,QAAQ,EAAE,SAAS,MAAM,EAAE,CAAC;IAC5B,MAAM,EAAE,MAAM,CAAC;CAChB;AAED,eAAO,MAAM,cAAc,GAAI,SAAS,qBAAqB,KAAG,cAAc,EAQ7E,CAAC"}

dist/tokenize.js

@@ -5,9 +5,13 @@ import { encode as encodeCl100k } from 'gpt-tokenizer/encoding/cl100k_base';
 import { getModel, getRate } from './rates.js';
+import { cohereCount } from './tokenize-cohere.js';
+import { mistralCount } from './tokenize-mistral.js';
 const HEURISTIC_CHARS_PER_TOKEN = {
     anthropic: 3.5,
+    cohere: 4,
     google: 4,
+    mistral: 4,
     openai: 4,
 };
 const heuristicCount = (text, provider) => Math.ceil(text.length / HEURISTIC_CHARS_PER_TOKEN[provider]);
-export const countTokens = (text, provider) => {
+export const countTokens = (text, provider, modelId) => {
     switch (provider) {
@@ -24,2 +28,15 @@ case 'openai':
             };
+        case 'mistral': {
+            // SentencePiece for v1/v2/v3 families; chars/4 heuristic for Tekken
+            // (NeMo, Pixtral, Devstral, Magistral, Ministral, Mistral Medium 2505+).
+            // See tokenize-mistral.ts for the full split.
+            const r = mistralCount(text, modelId ?? '');
+            return { approximate: r.approximate, count: r.tokens, tokenizer: r.tokenizer };
+        }
+        case 'cohere': {
+            // Cohere SDK is REST-only; no offline tokenizer ships in JS today.
+            // Empirical mode hits POST /v1/tokenize for exact counts.
+            const r = cohereCount(text);
+            return { approximate: r.approximate, count: r.tokens, tokenizer: r.tokenizer };
+        }
     }
@@ -31,3 +48,3 @@ };
     const converted = toFormat(options.prompt, options.format);
-    const counted = countTokens(converted, model.provider);
+    const counted = countTokens(converted, model.provider, model.id);
     const inputCost = (counted.count / 1000) * rate.inputPer1k;
@@ -34,0 +51,0 @@ return {

dist/tokenize.js.map

@@ -1,1 +0,1 @@
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dist/types.d.ts

@@ -1,2 +0,2 @@
-export type Provider = 'anthropic' | 'openai' | 'google';
+export type Provider = 'anthropic' | 'cohere' | 'google' | 'mistral' | 'openai';
 export type Format = 'json' | 'markdown' | 'text' | 'xml' | 'yaml';
@@ -15,2 +15,19 @@ export interface ModelDescriptor {
 }
+export interface LatencyTrial {
+    ttftMs: number;
+    totalMs: number;
+    outputTokens: number;
+    tokensPerSec: number;
+}
+export interface LatencyStats {
+    ttftMs: number;
+    totalMs: number;
+    tokensPerSec: number;
+}
+export interface LatencyResult {
+    trials: LatencyTrial[];
+    p50: LatencyStats;
+    p95: LatencyStats;
+    mean: LatencyStats;
+}
 export interface TokenizeResult {
@@ -24,4 +41,5 @@ approximate: boolean;
     tokenizer: TokenizerKind;
+    latency?: LatencyResult;
 }
-export type TokenizerKind = 'cl100k_base' | 'heuristic' | 'o200k_base';
+export type TokenizerKind = 'cl100k_base' | 'heuristic' | 'mistral_v1_v3' | 'o200k_base';
 export interface EmpiricalResult extends TokenizeResult {
@@ -28,0 +46,0 @@ cachedInputTokens: number;

dist/types.d.ts.map

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package.json

 {
   "name": "@tokenometer/core",
-  "version": "0.0.5",
-  "description": "Empirical token-cost benchmarking for LLM prompts — core library (tokenizers, format converters, rate matrix, empirical countTokens dispatch).",
+  "version": "0.1.0",
+  "description": "Tokenometer core library — multi-provider LLM token cost, latency, and vision-token estimation with empirical countTokens fallback (Anthropic, OpenAI, Google, Mistral, Cohere).",
   "license": "MIT",
@@ -19,13 +19,43 @@ "author": "Faraazuddin Mohammed <[e-mail]>",
     "anthropic",
+    "ci-cd",
+    "cl100k",
     "claude",
-    "cl100k",
+    "claude-code",
+    "claude-code-skill",
+    "code-scanning",
+    "codestral",
+    "cohere",
+    "command-r",
     "cost",
+    "cost-calculator",
+    "cursor",
     "gemini",
+    "github-action",
     "gpt",
+    "gpt-4o",
+    "latency",
     "llm",
+    "llm-cost",
+    "mistral",
+    "mistral-7b",
+    "mistral-large",
+    "mixtral",
+    "model-comparison",
+    "multimodal",
     "o200k",
     "openai",
+    "pixtral",
     "prompt",
+    "prompt-cost",
+    "prompt-cost-regression",
+    "prompt-engineering",
+    "prompt-regression",
+    "sarif",
+    "tiktoken",
     "token",
-    "tokenizer"
+    "token-budget",
+    "tokenizer",
+    "ttft",
+    "vision-tokens",
+    "vscode"
   ],
@@ -41,6 +71,3 @@ "type": "module",
   },
-  "files": [
-    "dist",
-    "README.md"
-  ],
+  "files": ["dist", "README.md"],
   "publishConfig": {
@@ -61,4 +88,5 @@ "access": "public",
     "gpt-tokenizer": "^3.4.0",
+    "mistral-tokenizer-js": "^1.0.0",
     "tokenlens": "^1.3.1",
-    "yaml": "^2.6.1"
+    "yaml": "^2.8.4"
   },
@@ -65,0 +93,0 @@ "devDependencies": {

README.md

 # @tokenometer/core
 
-> Core library powering [tokenometer](https://www.npmjs.com/package/tokenometer): tokenizer dispatch, format converters, versioned cost rate matrix, and an empirical-mode `countTokens` adapter for Anthropic, OpenAI, and Google.
+[![npm @tokenometer/core](https://img.shields.io/npm/v/@tokenometer/core.svg?label=@tokenometer/core)](https://www.npmjs.com/package/@tokenometer/core)
+[![License: MIT](https://img.shields.io/github/license/faraa2m/tokenometer.svg)](https://github.com/faraa2m/tokenometer/blob/main/LICENSE)
 
+> Core library powering [tokenometer](https://www.npmjs.com/package/tokenometer): tokenizer dispatch, format converters, versioned cost rate matrix, vision-token estimators, latency measurement, SARIF emitter, config loader, and an empirical-mode `countTokens` adapter for Anthropic, OpenAI, Google, Mistral, and Cohere.
+
+See the [root README](https://github.com/faraa2m/tokenometer#readme) for findings, methodology, and the full project overview.
+
 [**Live playground**](https://tokenometer.vercel.app) · [Source](https://github.com/faraa2m/tokenometer) · MIT
 
-If you just want a CLI, `npm install -g tokenometer`. This package is for programmatic use.
+If you just want a CLI, `npm install -g tokenometer`. This package is for programmatic use — it's the engine the CLI, the GitHub Action, the VS Code / Cursor extension, and the playground all share, so counts and pricing stay identical across every surface.
 
@@ -13,11 +18,28 @@ ## API
 import {
+  // Core tokenization
   tokenize,
   tokenizeMatrix,
+  countTokens,
+  // Empirical (real provider countTokens / tokenize endpoints)
   tokenizeEmpirical,
   tokenizeMatrixEmpirical,
-  countTokens,
+  // Latency benchmarking
+  measureLatency,
+  nthPercentile,
+  // Format conversion
   toFormat,
   isFormat,
   allFormats,
+  // Config (.tokenometer.yml)
+  loadConfig,
+  parseConfig,
+  // SARIF + JSON emitter
+  toSarif,
+  // Vision-token estimators
+  anthropicVisionTokens,
+  openaiVisionTokens,
+  googleVisionTokens,
+  // Pricing / model registry
   KNOWN_MODELS,
+  MODELS,
   RATES,
@@ -28,2 +50,34 @@ RATES_VERSION,
 } from '@tokenometer/core';
+
+import type {
+  // Token results
+  CountResult,
+  TokenizeResult,
+  EmpiricalResult,
+  EmpiricalCountResult,
+  EmpiricalEnv,
+  // Latency
+  LatencyResult,
+  LatencyTrial,
+  LatencyStats,
+  LatencyDeps,
+  MeasureLatencyOptions,
+  // Aggregates / formatters
+  TokenometerResult,
+  TokenometerFileResult,
+  ToSarifOptions,
+  // Config
+  TokenometerConfig,
+  ConfigFormat,
+  // Vision input shapes
+  AnthropicVisionInput,
+  OpenAIVisionInput,
+  GoogleVisionInput,
+  // Registry
+  ModelDescriptor,
+  Provider,
+  RateEntry,
+  Format,
+  TokenizerKind,
+} from '@tokenometer/core';
 ```
@@ -62,8 +116,53 @@
 
+### Latency benchmarking
+
+```ts
+const stats = await measureLatency({
+  modelId: 'claude-opus-4-7',
+  prompt: 'Write a haiku about CI.',
+  trials: 3,
+  env: { anthropicApiKey: process.env.ANTHROPIC_API_KEY! },
+});
+// LatencyResult: { trials: LatencyTrial[], stats: { ttftMs, totalMs, tokensPerSec } }
+// Each stat is { p50, p95, mean }.
+```
+
+Supported providers: Anthropic (`messages.stream`), OpenAI (`/v1/chat/completions` SSE), Google (`generateContentStream`), Cohere (`/v1/chat` NDJSON), Mistral (`/v1/chat/completions` SSE). Each call is capped at `max_tokens=200`; trials retry once on transient failures.
+
+### Vision tokens
+
+```ts
+const tokens = anthropicVisionTokens({ width: 1280, height: 720 });
+// 1228 (capped at 1600 for very large images)
+```
+
+The `openaiVisionTokens` and `googleVisionTokens` exports are formula-equivalent to the OpenAI high-detail tile cost and Gemini's 258-per-768²-tile cost respectively.
+
+### SARIF + JSON output
+
+```ts
+const sarif = toSarif({ files: [{ path: 'prompt.md', results: [...] }] });
+// SARIF 2.1.0 — drop into GitHub Code Scanning or any SARIF viewer.
+```
+
 ### Rate table
 
-`RATES` is a `Record<modelId, { inputPer1k, outputPer1k, cachedInputPer1k? }>`. `RATES_VERSION` ships as a date string so consumers can pin or audit.
+`RATES` is a `Record<modelId, { inputPer1k, outputPer1k, cachedInputPer1k? }>`. `RATES_VERSION` ships as a date string so consumers can pin or audit. `KNOWN_MODELS` is the union (currently 63 across 5 providers).
 
+## Providers
+
+| Provider  | Models | Offline tokenizer | Exactness | Empirical (`tokenizeEmpirical`) |
+|-----------|--------|-------------------|-----------|----------------------------------|
+| OpenAI    | `gpt-4o`, `gpt-4o-mini`, `gpt-4-turbo`, `gpt-3.5-turbo`, `o1` family | `gpt-tokenizer` `o200k_base` | exact | same `o200k_base` (matches production) |
+| Anthropic | `claude-opus-4-7`, `claude-sonnet-4-6`, `claude-haiku-4-5`, Claude 3.x family | `gpt-tokenizer` `cl100k_base` | approximate | `messages.countTokens` (free, exact) |
+| Google    | `gemini-2.5-pro`, `gemini-2.5-flash`, `gemini-1.5-pro`, `gemini-1.5-flash` | `chars / 4` heuristic | approximate | `model.countTokens` (free, exact) |
+| Mistral (19 models) | `open-mistral-7b`, `open-mixtral-8x22b`, `mistral-large-latest`, `codestral-latest`, `mistral-nemo`, `pixtral-large-latest`, `mistral-medium-2505`, `magistral-small`, `ministral-3b-latest`, `devstral-small-2505` | `mistral-tokenizer-js` (V1/V2/V3 SentencePiece); `chars/4` for Tekken family (NeMo, Pixtral, Mistral Small 2409+, Devstral, Mistral Medium 2505+, Magistral, Ministral) | exact for SentencePiece · approximate for Tekken | unsupported (no public token-count endpoint) |
+| Cohere    | `command-r`, `command-r-plus` | `chars / 4` heuristic | approximate | `POST /v1/tokenize` (free, exact, requires `COHERE_API_KEY`) |
+
+Pricing comes from `@tokenlens/models` plus a small `LOCAL_OVERRIDES` map for bleeding-edge models the registry hasn't picked up yet. Cohere lives entirely in `LOCAL_OVERRIDES` because `@tokenlens/models` does not yet ship a Cohere catalog at v1.3.0; pull from `cohere.com/pricing` whenever `RATES_VERSION` bumps.
+
+Internally the dispatch helpers `mistralCount`, `cohereCount`, `cohereTokenizeApi`, and `isTekken` (in `tokenize-mistral.ts` / `tokenize-cohere.ts`) are not part of the public API — they're called from `tokenize` / `tokenizeEmpirical`. If you need them, import the files directly; they may move.
+
 ## License
 
 MIT

New alerts

Major refactor

Supply chain risk

Package has recently undergone a major refactor. It may be unstable or indicate significant internal changes. Use caution when updating to versions that include significant changes.

Found 1 instance in 1 package

Network access

Supply chain risk

This module accesses the network.

Found 1 instance in 1 package

URL strings

Supply chain risk

Package contains fragments of external URLs or IP addresses, which the package may be accessing at runtime.

Found 1 instance in 1 package

Improved metrics

Total package byte prevSize

120102

200.21%

Number of package files

58

123.08%

Lines of code

1483

230.29%

Number of lines in readme file

166

147.76%

Worsened metrics

Dependency count

7

16.67%

Number of low supply chain risk alerts

1

Infinity%

Number of medium supply chain risk alerts

9

Infinity%

Dependency changes

• + Added

  mistral-tokenizer-js@^1.0.0

• + Added

  mistral-tokenizer-js@1.0.0
  (transitive)

• Updated

  yaml@^2.8.4