Keysat
1c78e46ebd
• PRICING table — per-1M-token rates by model • calcCost(model, usage) — Gemini usage object → cost record • buildAnalysisPrompt(...) — JSON-output topic-analysis prompt These all share the Gemini contract — pricing schema, usage shape, and prompt format. When we add other providers, each gets its own provider-specific helpers file; this becomes the basis of the Gemini provider implementation. server/index.js: 2828 → 2758 lines. Smoke tested: server boots; /api/license-status, /api/health, and / (frontend) all respond. No behavior change.
91 lines
4.3 KiB
JavaScript
91 lines
4.3 KiB
JavaScript
// Gemini-specific helpers: pricing table, cost calculation, prompt
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// builder. Pure module — no state, no I/O. When we add other providers,
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// each provider gets its own equivalent of this file.
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import { formatTime } from "./util.js";
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// ── Pricing (per 1M tokens) ─────────────────────────────────────────────────
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// Only the models we actually use as analysis fallbacks. Keep flat — the
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// numbers are operational data, not configuration. Update when Google
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// changes published rates.
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export const PRICING = {
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"gemini-3-flash-preview": { input: 0.50, output: 3.00, thinking: 3.00 },
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"gemini-3-pro-preview": { input: 2.00, output: 12.00, thinking: 12.00 },
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"gemini-3.1-pro-preview": { input: 2.00, output: 12.00, thinking: 12.00 },
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"gemini-2.5-flash": { input: 0.15, output: 0.60, thinking: 0.60 },
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// Fallback for unknown / future models — better an estimate than nothing.
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"default": { input: 1.00, output: 5.00, thinking: 5.00 },
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};
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// ── Cost calculation ────────────────────────────────────────────────────────
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// Takes a Gemini SDK `usage` object (response.usageMetadata) and produces
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// a structured cost record. Display strings are formatted at extraction
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// time so callers don't reformat. Returns zeros for unknown models (uses
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// the "default" rates).
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export function calcCost(modelName, usage) {
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const rates = PRICING[modelName] || PRICING["default"];
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const inputTokens = usage.promptTokenCount || 0;
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const outputTokens = usage.candidatesTokenCount || 0;
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const thinkingTokens = usage.thoughtsTokenCount || 0;
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const inputCost = (inputTokens / 1_000_000) * rates.input;
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const outputCost = (outputTokens / 1_000_000) * rates.output;
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const thinkingCost = (thinkingTokens / 1_000_000) * rates.thinking;
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const totalCost = inputCost + outputCost + thinkingCost;
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return {
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inputTokens,
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outputTokens,
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thinkingTokens,
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totalTokens: usage.totalTokenCount || (inputTokens + outputTokens + thinkingTokens),
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inputCost: inputCost.toFixed(6),
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outputCost: outputCost.toFixed(6),
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thinkingCost: thinkingCost.toFixed(6),
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totalCost: totalCost.toFixed(6),
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totalCostDisplay: totalCost < 0.01 ? `$${(totalCost * 100).toFixed(3)}¢` : `$${totalCost.toFixed(4)}`,
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};
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}
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// ── Topic-analysis prompt builder ───────────────────────────────────────────
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// Takes the parsed transcript entries and builds the JSON-output prompt
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// fed to the analysis model. Indices in the response are positional into
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// the same `entries` array — the caller relies on that contract.
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export function buildAnalysisPrompt(entries) {
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const numbered = entries
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.map((e, i) => `[${i}] (${formatTime(e.offset)}) ${e.text}`)
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.join("\n");
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return `You are analyzing a video transcript. Your job is to identify natural topic boundaries and group the transcript into discussion-based sections.
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TRANSCRIPT (each line is numbered with a timestamp):
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${numbered}
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INSTRUCTIONS:
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1. Read the entire transcript carefully.
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2. Identify where the discussion naturally shifts from one topic to another.
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3. Group consecutive transcript segments by topic. Some sections may be short (a quick aside) and some may be long (an extended deep-dive). Let the content dictate the length.
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4. For each section, write:
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- A short, specific topic title (3-8 words)
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- A 1-3 sentence summary of what's discussed
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- The start and end segment indices (inclusive)
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IMPORTANT:
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- Sections must be chronological and non-overlapping.
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- Every segment index from 0 to ${entries.length - 1} must belong to exactly one section.
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- startIndex of section N+1 must equal endIndex of section N plus 1.
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- Create as many or as few sections as the content naturally requires.
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- Titles should be descriptive and specific, not generic like "Introduction" unless it truly is one.
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Respond with ONLY valid JSON in this exact format, no other text:
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{
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"sections": [
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{
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"title": "Brief Topic Title",
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"summary": "1-3 sentence summary of this discussion section.",
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"startIndex": 0,
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"endIndex": 15
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}
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]
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}`;
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}
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