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import { Request } from "express";
import { assertNever } from "../utils";
import {
getTokenCount as getClaudeTokenCount,
init as initClaude,
} from "./claude";
import {
estimateGoogleAITokenCount,
getOpenAIImageCost,
getTokenCount as getOpenAITokenCount,
init as initOpenAi,
} from "./openai";
import {
getTokenCount as getMistralAITokenCount,
init as initMistralAI,
} from "./mistral";
import { APIFormat } from "../key-management";
import {
AnthropicChatMessage,
GoogleAIChatMessage,
MistralAIChatMessage,
OpenAIChatMessage,
} from "../api-schemas";
export async function init() {
initClaude();
initOpenAi();
initMistralAI();
}
type OpenAIChatTokenCountRequest = {
prompt: OpenAIChatMessage[];
completion?: never;
service: "openai" | "openai-responses";
};
type AnthropicChatTokenCountRequest = {
prompt: { system: string; messages: AnthropicChatMessage[] };
completion?: never;
service: "anthropic-chat";
};
type GoogleAIChatTokenCountRequest = {
prompt: GoogleAIChatMessage[];
completion?: never;
service: "google-ai";
};
type MistralAIChatTokenCountRequest = {
prompt: string | MistralAIChatMessage[];
completion?: never;
service: "mistral-ai" | "mistral-text";
};
type FlatPromptTokenCountRequest = {
prompt: string;
completion?: never;
service: "openai-text" | "anthropic-text" | "google-ai";
};
type StringCompletionTokenCountRequest = {
prompt?: never;
completion: string;
service: APIFormat;
};
type OpenAIImageCompletionTokenCountRequest = {
prompt?: never;
completion?: never;
service: "openai-image";
};
/**
* Tagged union via `service` field of the different types of requests that can
* be made to the tokenization service, for both prompts and completions
*/
type TokenCountRequest = { req: Request } & (
| OpenAIChatTokenCountRequest
| AnthropicChatTokenCountRequest
| GoogleAIChatTokenCountRequest
| MistralAIChatTokenCountRequest
| FlatPromptTokenCountRequest
| StringCompletionTokenCountRequest
| OpenAIImageCompletionTokenCountRequest
);
type TokenCountResult = {
token_count: number;
/** Additional tokens for reasoning, if applicable. */
reasoning_tokens?: number;
tokenizer: string;
tokenization_duration_ms: number;
};
export async function countTokens({
req,
service,
prompt,
completion,
}: TokenCountRequest): Promise<TokenCountResult> {
const time = process.hrtime();
switch (service) {
case "anthropic-chat":
case "anthropic-text":
return {
...(await getClaudeTokenCount(prompt ?? completion)),
tokenization_duration_ms: getElapsedMs(time),
};
case "openai":
case "openai-text":
case "openai-responses":
return {
...(await getOpenAITokenCount(prompt ?? completion, req.body.model)),
tokenization_duration_ms: getElapsedMs(time),
};
case "openai-image":
return {
...getOpenAIImageCost({
model: req.body.model,
quality: req.body.quality,
resolution: req.body.size,
n: parseInt(req.body.n, 10) || null,
}),
tokenization_duration_ms: getElapsedMs(time),
};
case "google-ai":
// TODO: Can't find a tokenization library for Gemini. There is an API
// endpoint for it but it adds significant latency to the request.
return {
...estimateGoogleAITokenCount(prompt ?? (completion || [])),
tokenization_duration_ms: getElapsedMs(time),
};
case "mistral-ai":
case "mistral-text":
return {
...getMistralAITokenCount(prompt ?? completion),
tokenization_duration_ms: getElapsedMs(time),
};
default:
assertNever(service);
}
}
function getElapsedMs(time: [number, number]) {
const diff = process.hrtime(time);
return diff[0] * 1000 + diff[1] / 1e6;
}
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