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Merge pull request #1451 from dtrugman/feat/add-openai-style-cost-calculation
Add openai style cost calculation
This commit is contained in:
commit
6644202b55
7 changed files with 199 additions and 45 deletions
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@ -22,8 +22,10 @@ describe("RequestyHandler", () => {
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contextWindow: 4000,
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supportsPromptCache: false,
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supportsImages: true,
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inputPrice: 0,
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outputPrice: 0,
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inputPrice: 1,
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outputPrice: 10,
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cacheReadsPrice: 0.1,
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cacheWritesPrice: 1.5,
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},
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openAiStreamingEnabled: true,
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includeMaxTokens: true, // Add this to match the implementation
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@ -83,8 +85,12 @@ describe("RequestyHandler", () => {
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yield {
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choices: [{ delta: { content: " world" } }],
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usage: {
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prompt_tokens: 10,
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completion_tokens: 5,
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prompt_tokens: 30,
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completion_tokens: 10,
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prompt_tokens_details: {
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cached_tokens: 15,
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caching_tokens: 5,
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},
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},
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}
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},
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@ -105,10 +111,11 @@ describe("RequestyHandler", () => {
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{ type: "text", text: " world" },
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{
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type: "usage",
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inputTokens: 10,
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outputTokens: 5,
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cacheWriteTokens: undefined,
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cacheReadTokens: undefined,
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inputTokens: 30,
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outputTokens: 10,
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cacheWriteTokens: 5,
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cacheReadTokens: 15,
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totalCost: 0.000119, // (10 * 1 / 1,000,000) + (5 * 1.5 / 1,000,000) + (15 * 0.1 / 1,000,000) + (10 * 10 / 1,000,000)
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},
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])
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@ -182,6 +189,9 @@ describe("RequestyHandler", () => {
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type: "usage",
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inputTokens: 10,
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outputTokens: 5,
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cacheWriteTokens: 0,
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cacheReadTokens: 0,
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totalCost: 0.00006, // (10 * 1 / 1,000,000) + (5 * 10 / 1,000,000)
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},
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])
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@ -116,7 +116,7 @@ export class OpenAiHandler extends BaseProvider implements SingleCompletionHandl
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}
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}
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if (chunk.usage) {
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yield this.processUsageMetrics(chunk.usage)
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yield this.processUsageMetrics(chunk.usage, modelInfo)
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}
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}
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} else {
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@ -139,11 +139,11 @@ export class OpenAiHandler extends BaseProvider implements SingleCompletionHandl
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type: "text",
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text: response.choices[0]?.message.content || "",
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}
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yield this.processUsageMetrics(response.usage)
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yield this.processUsageMetrics(response.usage, modelInfo)
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}
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}
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protected processUsageMetrics(usage: any): ApiStreamUsageChunk {
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protected processUsageMetrics(usage: any, modelInfo?: ModelInfo): ApiStreamUsageChunk {
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return {
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type: "usage",
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inputTokens: usage?.prompt_tokens || 0,
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@ -1,9 +1,20 @@
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import axios from "axios"
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import { ModelInfo, requestyModelInfoSaneDefaults, requestyDefaultModelId } from "../../shared/api"
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import { parseApiPrice } from "../../utils/cost"
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import { calculateApiCostOpenAI, parseApiPrice } from "../../utils/cost"
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import { ApiStreamUsageChunk } from "../transform/stream"
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import { OpenAiHandler, OpenAiHandlerOptions } from "./openai"
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import OpenAI from "openai"
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// Requesty usage includes an extra field for Anthropic use cases.
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// Safely cast the prompt token details section to the appropriate structure.
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interface RequestyUsage extends OpenAI.CompletionUsage {
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prompt_tokens_details?: {
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caching_tokens?: number
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cached_tokens?: number
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}
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total_cost?: number
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}
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export class RequestyHandler extends OpenAiHandler {
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constructor(options: OpenAiHandlerOptions) {
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@ -27,13 +38,22 @@ export class RequestyHandler extends OpenAiHandler {
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}
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}
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protected override processUsageMetrics(usage: any): ApiStreamUsageChunk {
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protected override processUsageMetrics(usage: any, modelInfo?: ModelInfo): ApiStreamUsageChunk {
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const requestyUsage = usage as RequestyUsage
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const inputTokens = requestyUsage?.prompt_tokens || 0
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const outputTokens = requestyUsage?.completion_tokens || 0
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const cacheWriteTokens = requestyUsage?.prompt_tokens_details?.caching_tokens || 0
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const cacheReadTokens = requestyUsage?.prompt_tokens_details?.cached_tokens || 0
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const totalCost = modelInfo
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? calculateApiCostOpenAI(modelInfo, inputTokens, outputTokens, cacheWriteTokens, cacheReadTokens)
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: 0
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return {
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type: "usage",
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inputTokens: usage?.prompt_tokens || 0,
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outputTokens: usage?.completion_tokens || 0,
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cacheWriteTokens: usage?.cache_creation_input_tokens,
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cacheReadTokens: usage?.cache_read_input_tokens,
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inputTokens: inputTokens,
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outputTokens: outputTokens,
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cacheWriteTokens: cacheWriteTokens,
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cacheReadTokens: cacheReadTokens,
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totalCost: totalCost,
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}
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}
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}
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@ -2,7 +2,7 @@ import { Anthropic } from "@anthropic-ai/sdk"
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import * as vscode from "vscode"
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import { SingleCompletionHandler } from "../"
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import { calculateApiCost } from "../../utils/cost"
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import { calculateApiCostAnthropic } from "../../utils/cost"
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import { ApiStream } from "../transform/stream"
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import { convertToVsCodeLmMessages } from "../transform/vscode-lm-format"
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import { SELECTOR_SEPARATOR, stringifyVsCodeLmModelSelector } from "../../shared/vsCodeSelectorUtils"
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@ -462,7 +462,7 @@ export class VsCodeLmHandler extends BaseProvider implements SingleCompletionHan
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type: "usage",
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inputTokens: totalInputTokens,
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outputTokens: totalOutputTokens,
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totalCost: calculateApiCost(this.getModel().info, totalInputTokens, totalOutputTokens),
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totalCost: calculateApiCostAnthropic(this.getModel().info, totalInputTokens, totalOutputTokens),
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}
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} catch (error: unknown) {
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this.ensureCleanState()
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@ -55,7 +55,7 @@ import { ClineAskResponse } from "../shared/WebviewMessage"
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import { GlobalFileNames } from "../shared/globalFileNames"
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import { defaultModeSlug, getModeBySlug, getFullModeDetails } from "../shared/modes"
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import { EXPERIMENT_IDS, experiments as Experiments, ExperimentId } from "../shared/experiments"
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import { calculateApiCost } from "../utils/cost"
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import { calculateApiCostAnthropic } from "../utils/cost"
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import { fileExistsAtPath } from "../utils/fs"
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import { arePathsEqual, getReadablePath } from "../utils/path"
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import { parseMentions } from "./mentions"
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@ -875,7 +875,7 @@ export class Cline {
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// The way this agentic loop works is that cline will be given a task that he then calls tools to complete. unless there's an attempt_completion call, we keep responding back to him with his tool's responses until he either attempt_completion or does not use anymore tools. If he does not use anymore tools, we ask him to consider if he's completed the task and then call attempt_completion, otherwise proceed with completing the task.
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// There is a MAX_REQUESTS_PER_TASK limit to prevent infinite requests, but Cline is prompted to finish the task as efficiently as he can.
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//const totalCost = this.calculateApiCost(totalInputTokens, totalOutputTokens)
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//const totalCost = this.calculateApiCostAnthropic(totalInputTokens, totalOutputTokens)
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if (didEndLoop) {
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// For now a task never 'completes'. This will only happen if the user hits max requests and denies resetting the count.
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//this.say("task_completed", `Task completed. Total API usage cost: ${totalCost}`)
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@ -3173,7 +3173,7 @@ export class Cline {
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cacheReads: cacheReadTokens,
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cost:
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totalCost ??
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calculateApiCost(
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calculateApiCostAnthropic(
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this.api.getModel().info,
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inputTokens,
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outputTokens,
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@ -1,8 +1,8 @@
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import { calculateApiCost } from "../cost"
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import { calculateApiCostAnthropic, calculateApiCostOpenAI } from "../cost"
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import { ModelInfo } from "../../shared/api"
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describe("Cost Utility", () => {
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describe("calculateApiCost", () => {
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describe("calculateApiCostAnthropic", () => {
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const mockModelInfo: ModelInfo = {
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maxTokens: 8192,
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contextWindow: 200_000,
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@ -14,7 +14,7 @@ describe("Cost Utility", () => {
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}
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it("should calculate basic input/output costs correctly", () => {
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const cost = calculateApiCost(mockModelInfo, 1000, 500)
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const cost = calculateApiCostAnthropic(mockModelInfo, 1000, 500)
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// Input cost: (3.0 / 1_000_000) * 1000 = 0.003
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// Output cost: (15.0 / 1_000_000) * 500 = 0.0075
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@ -23,7 +23,7 @@ describe("Cost Utility", () => {
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})
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it("should handle cache writes cost", () => {
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const cost = calculateApiCost(mockModelInfo, 1000, 500, 2000)
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const cost = calculateApiCostAnthropic(mockModelInfo, 1000, 500, 2000)
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// Input cost: (3.0 / 1_000_000) * 1000 = 0.003
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// Output cost: (15.0 / 1_000_000) * 500 = 0.0075
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@ -33,7 +33,7 @@ describe("Cost Utility", () => {
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})
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it("should handle cache reads cost", () => {
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const cost = calculateApiCost(mockModelInfo, 1000, 500, undefined, 3000)
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const cost = calculateApiCostAnthropic(mockModelInfo, 1000, 500, undefined, 3000)
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// Input cost: (3.0 / 1_000_000) * 1000 = 0.003
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// Output cost: (15.0 / 1_000_000) * 500 = 0.0075
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@ -43,7 +43,7 @@ describe("Cost Utility", () => {
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})
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it("should handle all cost components together", () => {
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const cost = calculateApiCost(mockModelInfo, 1000, 500, 2000, 3000)
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const cost = calculateApiCostAnthropic(mockModelInfo, 1000, 500, 2000, 3000)
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// Input cost: (3.0 / 1_000_000) * 1000 = 0.003
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// Output cost: (15.0 / 1_000_000) * 500 = 0.0075
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@ -60,17 +60,17 @@ describe("Cost Utility", () => {
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supportsPromptCache: true,
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}
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const cost = calculateApiCost(modelWithoutPrices, 1000, 500, 2000, 3000)
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const cost = calculateApiCostAnthropic(modelWithoutPrices, 1000, 500, 2000, 3000)
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expect(cost).toBe(0)
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})
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it("should handle zero tokens", () => {
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const cost = calculateApiCost(mockModelInfo, 0, 0, 0, 0)
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const cost = calculateApiCostAnthropic(mockModelInfo, 0, 0, 0, 0)
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expect(cost).toBe(0)
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})
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it("should handle undefined cache values", () => {
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const cost = calculateApiCost(mockModelInfo, 1000, 500)
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const cost = calculateApiCostAnthropic(mockModelInfo, 1000, 500)
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// Input cost: (3.0 / 1_000_000) * 1000 = 0.003
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// Output cost: (15.0 / 1_000_000) * 500 = 0.0075
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@ -85,7 +85,7 @@ describe("Cost Utility", () => {
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cacheReadsPrice: undefined,
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}
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const cost = calculateApiCost(modelWithoutCachePrices, 1000, 500, 2000, 3000)
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const cost = calculateApiCostAnthropic(modelWithoutCachePrices, 1000, 500, 2000, 3000)
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// Should only include input and output costs
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// Input cost: (3.0 / 1_000_000) * 1000 = 0.003
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@ -94,4 +94,97 @@ describe("Cost Utility", () => {
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expect(cost).toBe(0.0105)
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})
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})
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describe("calculateApiCostOpenAI", () => {
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const mockModelInfo: ModelInfo = {
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maxTokens: 8192,
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contextWindow: 200_000,
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supportsPromptCache: true,
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inputPrice: 3.0, // $3 per million tokens
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outputPrice: 15.0, // $15 per million tokens
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cacheWritesPrice: 3.75, // $3.75 per million tokens
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cacheReadsPrice: 0.3, // $0.30 per million tokens
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}
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it("should calculate basic input/output costs correctly", () => {
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const cost = calculateApiCostOpenAI(mockModelInfo, 1000, 500)
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// Input cost: (3.0 / 1_000_000) * 1000 = 0.003
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// Output cost: (15.0 / 1_000_000) * 500 = 0.0075
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// Total: 0.003 + 0.0075 = 0.0105
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expect(cost).toBe(0.0105)
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})
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it("should handle cache writes cost", () => {
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const cost = calculateApiCostOpenAI(mockModelInfo, 3000, 500, 2000)
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// Input cost: (3.0 / 1_000_000) * (3000 - 2000) = 0.003
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// Output cost: (15.0 / 1_000_000) * 500 = 0.0075
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// Cache writes: (3.75 / 1_000_000) * 2000 = 0.0075
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// Total: 0.003 + 0.0075 + 0.0075 = 0.018
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expect(cost).toBeCloseTo(0.018, 6)
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})
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it("should handle cache reads cost", () => {
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const cost = calculateApiCostOpenAI(mockModelInfo, 4000, 500, undefined, 3000)
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// Input cost: (3.0 / 1_000_000) * (4000 - 3000) = 0.003
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// Output cost: (15.0 / 1_000_000) * 500 = 0.0075
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// Cache reads: (0.3 / 1_000_000) * 3000 = 0.0009
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// Total: 0.003 + 0.0075 + 0.0009 = 0.0114
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expect(cost).toBe(0.0114)
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})
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it("should handle all cost components together", () => {
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const cost = calculateApiCostOpenAI(mockModelInfo, 6000, 500, 2000, 3000)
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// Input cost: (3.0 / 1_000_000) * (6000 - 2000 - 3000) = 0.003
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// Output cost: (15.0 / 1_000_000) * 500 = 0.0075
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// Cache writes: (3.75 / 1_000_000) * 2000 = 0.0075
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// Cache reads: (0.3 / 1_000_000) * 3000 = 0.0009
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// Total: 0.003 + 0.0075 + 0.0075 + 0.0009 = 0.0189
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expect(cost).toBe(0.0189)
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})
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it("should handle missing prices gracefully", () => {
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const modelWithoutPrices: ModelInfo = {
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maxTokens: 8192,
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contextWindow: 200_000,
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supportsPromptCache: true,
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}
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const cost = calculateApiCostOpenAI(modelWithoutPrices, 1000, 500, 2000, 3000)
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expect(cost).toBe(0)
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})
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it("should handle zero tokens", () => {
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const cost = calculateApiCostOpenAI(mockModelInfo, 0, 0, 0, 0)
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expect(cost).toBe(0)
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})
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it("should handle undefined cache values", () => {
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const cost = calculateApiCostOpenAI(mockModelInfo, 1000, 500)
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// Input cost: (3.0 / 1_000_000) * 1000 = 0.003
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// Output cost: (15.0 / 1_000_000) * 500 = 0.0075
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// Total: 0.003 + 0.0075 = 0.0105
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expect(cost).toBe(0.0105)
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})
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it("should handle missing cache prices", () => {
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const modelWithoutCachePrices: ModelInfo = {
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...mockModelInfo,
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cacheWritesPrice: undefined,
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cacheReadsPrice: undefined,
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}
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const cost = calculateApiCostOpenAI(modelWithoutCachePrices, 6000, 500, 2000, 3000)
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// Should only include input and output costs
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// Input cost: (3.0 / 1_000_000) * (6000 - 2000 - 3000) = 0.003
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// Output cost: (15.0 / 1_000_000) * 500 = 0.0075
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// Total: 0.003 + 0.0075 = 0.0105
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expect(cost).toBe(0.0105)
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})
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})
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})
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@ -1,26 +1,57 @@
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import { ModelInfo } from "../shared/api"
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export function calculateApiCost(
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function calculateApiCostInternal(
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modelInfo: ModelInfo,
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inputTokens: number,
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outputTokens: number,
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cacheCreationInputTokens?: number,
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cacheReadInputTokens?: number,
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cacheCreationInputTokens: number,
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cacheReadInputTokens: number,
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): number {
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const modelCacheWritesPrice = modelInfo.cacheWritesPrice
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let cacheWritesCost = 0
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if (cacheCreationInputTokens && modelCacheWritesPrice) {
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cacheWritesCost = (modelCacheWritesPrice / 1_000_000) * cacheCreationInputTokens
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}
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const modelCacheReadsPrice = modelInfo.cacheReadsPrice
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let cacheReadsCost = 0
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if (cacheReadInputTokens && modelCacheReadsPrice) {
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cacheReadsCost = (modelCacheReadsPrice / 1_000_000) * cacheReadInputTokens
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}
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const cacheWritesCost = ((modelInfo.cacheWritesPrice || 0) / 1_000_000) * cacheCreationInputTokens
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const cacheReadsCost = ((modelInfo.cacheReadsPrice || 0) / 1_000_000) * cacheReadInputTokens
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const baseInputCost = ((modelInfo.inputPrice || 0) / 1_000_000) * inputTokens
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const outputCost = ((modelInfo.outputPrice || 0) / 1_000_000) * outputTokens
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const totalCost = cacheWritesCost + cacheReadsCost + baseInputCost + outputCost
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return totalCost
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}
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// For Anthropic compliant usage, the input tokens count does NOT include the cached tokens
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export function calculateApiCostAnthropic(
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modelInfo: ModelInfo,
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inputTokens: number,
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outputTokens: number,
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cacheCreationInputTokens?: number,
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cacheReadInputTokens?: number,
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): number {
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const cacheCreationInputTokensNum = cacheCreationInputTokens || 0
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const cacheReadInputTokensNum = cacheReadInputTokens || 0
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return calculateApiCostInternal(
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modelInfo,
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inputTokens,
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outputTokens,
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cacheCreationInputTokensNum,
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cacheReadInputTokensNum,
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)
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}
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// For OpenAI compliant usage, the input tokens count INCLUDES the cached tokens
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export function calculateApiCostOpenAI(
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modelInfo: ModelInfo,
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inputTokens: number,
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outputTokens: number,
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cacheCreationInputTokens?: number,
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cacheReadInputTokens?: number,
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): number {
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const cacheCreationInputTokensNum = cacheCreationInputTokens || 0
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const cacheReadInputTokensNum = cacheReadInputTokens || 0
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const nonCachedInputTokens = Math.max(0, inputTokens - cacheCreationInputTokensNum - cacheReadInputTokensNum)
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return calculateApiCostInternal(
|
||||
modelInfo,
|
||||
nonCachedInputTokens,
|
||||
outputTokens,
|
||||
cacheCreationInputTokensNum,
|
||||
cacheReadInputTokensNum,
|
||||
)
|
||||
}
|
||||
|
||||
export const parseApiPrice = (price: any) => (price ? parseFloat(price) * 1_000_000 : undefined)
|
||||
|
|
|
|||
Loading…
Add table
Reference in a new issue