234 lines
6.3 KiB
TypeScript
234 lines
6.3 KiB
TypeScript
import { ModelConfig, ProviderConfig } from "@/app/store";
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import { createLogger } from "@/app/utils/log";
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import { getAuthKey } from "../common/auth";
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import { API_PREFIX, AnthropicPath, ApiPath } from "@/app/constant";
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import { getApiPath } from "@/app/utils/path";
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import { trimEnd } from "@/app/utils/string";
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import { Anthropic } from "./types";
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import { ChatOptions, LLMModel, LLMUsage, RequestMessage } from "../types";
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import { omit } from "@/app/utils/object";
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import {
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EventStreamContentType,
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fetchEventSource,
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} from "@fortaine/fetch-event-source";
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import { prettyObject } from "@/app/utils/format";
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import Locale from "@/app/locales";
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import { AnthropicConfig } from "./config";
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export function createAnthropicClient(
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providerConfigs: ProviderConfig,
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modelConfig: ModelConfig,
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) {
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const anthropicConfig = { ...providerConfigs.anthropic };
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const logger = createLogger("[Anthropic]");
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const anthropicModelConfig = { ...modelConfig.anthropic };
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return {
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headers() {
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return {
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"Content-Type": "application/json",
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"x-api-key": getAuthKey(anthropicConfig.apiKey),
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"anthropic-version": anthropicConfig.version,
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};
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},
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path(path: AnthropicPath): string {
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let baseUrl: string = anthropicConfig.endpoint;
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// if endpoint is empty, use default endpoint
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if (baseUrl.trim().length === 0) {
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baseUrl = getApiPath(ApiPath.Anthropic);
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}
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if (!baseUrl.startsWith("http") && !baseUrl.startsWith(API_PREFIX)) {
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baseUrl = "https://" + baseUrl;
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}
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baseUrl = trimEnd(baseUrl, "/");
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return `${baseUrl}/${path}`;
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},
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extractMessage(res: Anthropic.ChatResponse) {
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return res.completion;
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},
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beforeRequest(options: ChatOptions, stream = false) {
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const ClaudeMapper: Record<RequestMessage["role"], string> = {
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assistant: "Assistant",
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user: "Human",
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system: "Human",
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};
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const prompt = options.messages
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.map((v) => ({
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role: ClaudeMapper[v.role] ?? "Human",
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content: v.content,
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}))
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.map((v) => `\n\n${v.role}: ${v.content}`)
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.join("");
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if (options.shouldSummarize) {
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anthropicModelConfig.model = anthropicModelConfig.summarizeModel;
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}
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const requestBody: Anthropic.ChatRequest = {
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prompt,
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stream,
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...omit(anthropicModelConfig, "summarizeModel"),
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};
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const path = this.path(AnthropicPath.Chat);
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logger.log("path = ", path, requestBody);
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const controller = new AbortController();
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options.onController?.(controller);
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const payload = {
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method: "POST",
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body: JSON.stringify(requestBody),
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signal: controller.signal,
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headers: this.headers(),
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mode: "no-cors" as RequestMode,
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};
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return {
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path,
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payload,
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controller,
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};
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},
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async chat(options: ChatOptions) {
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try {
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const { path, payload, controller } = this.beforeRequest(
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options,
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false,
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);
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controller.signal.onabort = () => options.onFinish("");
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const res = await fetch(path, payload);
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const resJson = await res.json();
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const message = this.extractMessage(resJson);
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options.onFinish(message);
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} catch (e) {
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logger.error("failed to chat", e);
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options.onError?.(e as Error);
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}
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},
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async chatStream(options: ChatOptions) {
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try {
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const { path, payload, controller } = this.beforeRequest(options, true);
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const context = {
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text: "",
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finished: false,
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};
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const finish = () => {
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if (!context.finished) {
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options.onFinish(context.text);
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context.finished = true;
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}
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};
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controller.signal.onabort = finish;
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logger.log(payload);
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fetchEventSource(path, {
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...payload,
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async onopen(res) {
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const contentType = res.headers.get("content-type");
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logger.log("response content type: ", contentType);
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if (contentType?.startsWith("text/plain")) {
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context.text = await res.clone().text();
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return finish();
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}
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if (
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!res.ok ||
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!res.headers
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.get("content-type")
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?.startsWith(EventStreamContentType) ||
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res.status !== 200
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) {
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const responseTexts = [context.text];
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let extraInfo = await res.clone().text();
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try {
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const resJson = await res.clone().json();
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extraInfo = prettyObject(resJson);
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} catch {}
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if (res.status === 401) {
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responseTexts.push(Locale.Error.Unauthorized);
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}
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if (extraInfo) {
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responseTexts.push(extraInfo);
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}
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context.text = responseTexts.join("\n\n");
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return finish();
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}
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},
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onmessage(msg) {
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if (msg.data === "[DONE]" || context.finished) {
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return finish();
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}
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const chunk = msg.data;
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try {
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const chunkJson = JSON.parse(
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chunk,
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) as Anthropic.ChatStreamResponse;
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const delta = chunkJson.completion;
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if (delta) {
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context.text += delta;
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options.onUpdate?.(context.text, delta);
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}
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} catch (e) {
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logger.error("[Request] parse error", chunk, msg);
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}
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},
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onclose() {
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finish();
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},
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onerror(e) {
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options.onError?.(e);
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},
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openWhenHidden: true,
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});
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} catch (e) {
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logger.error("failed to chat", e);
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options.onError?.(e as Error);
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}
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},
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async usage() {
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return {
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used: 0,
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total: 0,
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} as LLMUsage;
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},
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async models(): Promise<LLMModel[]> {
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const customModels = anthropicConfig.customModels
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.split(",")
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.map((v) => v.trim())
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.filter((v) => !!v)
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.map((v) => ({
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name: v,
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available: true,
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}));
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return [...AnthropicConfig.provider.models.slice(), ...customModels];
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},
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};
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}
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