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feat(ai): Add cost tracking to LLM implementations
- Track input/output token costs for all providers - Calculate costs based on Model pricing information - Include cost information in AssistantMessage responses - Add Usage interface with detailed cost breakdown - Implement calculateCost utility function for cost calculations
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6 changed files with 61 additions and 14 deletions
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@ -5,6 +5,7 @@ import type {
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MessageParam,
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Tool,
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} from "@anthropic-ai/sdk/resources/messages.js";
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import { calculateCost } from "../models.js";
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import type {
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AssistantMessage,
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Context,
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@ -13,8 +14,8 @@ import type {
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Message,
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Model,
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StopReason,
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TokenUsage,
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ToolCall,
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Usage,
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} from "../types.js";
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export interface AnthropicLLMOptions extends LLMOptions {
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@ -186,13 +187,20 @@ export class AnthropicLLM implements LLM<AnthropicLLMOptions> {
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name: block.name,
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arguments: block.input as Record<string, any>,
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}));
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const usage: TokenUsage = {
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const usage: Usage = {
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input: msg.usage.input_tokens,
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output: msg.usage.output_tokens,
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cacheRead: msg.usage.cache_read_input_tokens || 0,
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cacheWrite: msg.usage.cache_creation_input_tokens || 0,
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// TODO add cost
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cost: {
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input: 0,
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output: 0,
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cacheRead: 0,
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cacheWrite: 0,
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total: 0,
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},
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};
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calculateCost(this.modelInfo, usage);
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return {
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role: "assistant",
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@ -215,6 +223,7 @@ export class AnthropicLLM implements LLM<AnthropicLLMOptions> {
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output: 0,
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cacheRead: 0,
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cacheWrite: 0,
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cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
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},
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stopReason: "error",
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error: error instanceof Error ? error.message : String(error),
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