feat: init llm-proxy

cost.ts

@@ -0,0 +1,48 @@
+// cost.ts
+// Helper for calculating token-based LLM costs
+
+export type Usage = {
+  prompt_tokens?: number;
+  completion_tokens?: number;
+  total_tokens?: number;
+  prompt_tokens_details?: {
+    cached_tokens?: number;
+  }
+};
+
+export type CostConfig = {
+  input: number;  // cost per million prompt tokens (USD)
+  cached: number; // cost per million cached tokens (USD)
+  output: number; // cost per million completion tokens (USD)
+};
+
+// Cost table per model (USD per million tokens)
+export const MODEL_COSTS: Record<string, CostConfig> = {
+  "glm-4.5-air": { input: 0.2, cached: 0.03, output: 1.1 },
+  "glm-4.6": { input: 0.6, cached: 0.11, output: 2.2 },
+  "default": { input: 0, cached: 0, output: 0 },
+};
+
+// Compute total cost (in USD)
+export function calculateCost(model: string, usage?: Usage): number | null {
+  if (!usage) return null;
+
+  const { prompt_tokens = 0, completion_tokens = 0, prompt_tokens_details = { cached_tokens: 0 } } = usage;
+  const cost = MODEL_COSTS[model] || MODEL_COSTS["default"];
+
+  let inputCost = 0;
+  let cachedCost = 0;
+  let outputCost = 0;
+
+  if (prompt_tokens_details?.cached_tokens) {
+    cachedCost = ((prompt_tokens_details.cached_tokens) / 1_000_000) * cost.cached;
+    inputCost = ((prompt_tokens - prompt_tokens_details.cached_tokens) / 1_000_000) * cost.input;
+  } else {
+    inputCost = ((prompt_tokens) / 1_000_000) * cost.input;
+  }
+
+  outputCost = (completion_tokens / 1_000_000) * cost.output;
+
+  const total = inputCost + cachedCost + outputCost;
+  return total > 0 ? Number(total.toFixed(6)) : null;
+}