412 lines
12 KiB
TypeScript
412 lines
12 KiB
TypeScript
import { Anthropic, ApiPath } from "@/app/constant";
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import { ChatOptions, getHeaders, LLMApi } from "../api";
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import {
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useAccessStore,
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useAppConfig,
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useChatStore,
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usePluginStore,
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ChatMessageTool,
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} from "@/app/store";
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import { getClientConfig } from "@/app/config/client";
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import { DEFAULT_API_HOST } from "@/app/constant";
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import { getMessageTextContent, isVisionModel } from "@/app/utils";
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import { preProcessImageContent, stream } from "@/app/utils/chat";
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import { cloudflareAIGatewayUrl } from "@/app/utils/cloudflare";
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import { RequestPayload } from "./openai";
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export type MultiBlockContent = {
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type: "image" | "text";
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source?: {
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type: string;
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media_type: string;
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data: string;
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};
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text?: string;
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};
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export type AnthropicMessage = {
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role: (typeof ClaudeMapper)[keyof typeof ClaudeMapper];
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content: string | MultiBlockContent[];
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};
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export interface AnthropicChatRequest {
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model: string; // The model that will complete your prompt.
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messages: AnthropicMessage[]; // The prompt that you want Claude to complete.
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max_tokens: number; // The maximum number of tokens to generate before stopping.
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stop_sequences?: string[]; // Sequences that will cause the model to stop generating completion text.
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temperature?: number; // Amount of randomness injected into the response.
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top_p?: number; // Use nucleus sampling.
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top_k?: number; // Only sample from the top K options for each subsequent token.
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metadata?: object; // An object describing metadata about the request.
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stream?: boolean; // Whether to incrementally stream the response using server-sent events.
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}
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export interface ChatRequest {
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model: string; // The model that will complete your prompt.
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prompt: string; // The prompt that you want Claude to complete.
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max_tokens_to_sample: number; // The maximum number of tokens to generate before stopping.
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stop_sequences?: string[]; // Sequences that will cause the model to stop generating completion text.
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temperature?: number; // Amount of randomness injected into the response.
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top_p?: number; // Use nucleus sampling.
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top_k?: number; // Only sample from the top K options for each subsequent token.
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metadata?: object; // An object describing metadata about the request.
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stream?: boolean; // Whether to incrementally stream the response using server-sent events.
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}
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export interface ChatResponse {
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completion: string;
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stop_reason: "stop_sequence" | "max_tokens";
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model: string;
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}
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export type ChatStreamResponse = ChatResponse & {
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stop?: string;
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log_id: string;
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};
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const ClaudeMapper = {
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assistant: "assistant",
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user: "user",
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system: "user",
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} as const;
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const keys = ["claude-2, claude-instant-1"];
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export class ClaudeApi implements LLMApi {
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extractMessage(res: any) {
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console.log("[Response] claude response: ", res);
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return res?.content?.[0]?.text;
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}
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async chat(options: ChatOptions): Promise<void> {
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const visionModel = isVisionModel(options.config.model);
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const accessStore = useAccessStore.getState();
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const shouldStream = !!options.config.stream;
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const modelConfig = {
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...useAppConfig.getState().modelConfig,
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...useChatStore.getState().currentSession().mask.modelConfig,
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...{
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model: options.config.model,
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},
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};
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// try get base64image from local cache image_url
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const messages: ChatOptions["messages"] = [];
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for (const v of options.messages) {
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const content = await preProcessImageContent(v.content);
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messages.push({ role: v.role, content });
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}
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const keys = ["system", "user"];
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// roles must alternate between "user" and "assistant" in claude, so add a fake assistant message between two user messages
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for (let i = 0; i < messages.length - 1; i++) {
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const message = messages[i];
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const nextMessage = messages[i + 1];
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if (keys.includes(message.role) && keys.includes(nextMessage.role)) {
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messages[i] = [
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message,
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{
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role: "assistant",
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content: ";",
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},
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] as any;
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}
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}
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const prompt = messages
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.flat()
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.filter((v) => {
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if (!v.content) return false;
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if (typeof v.content === "string" && !v.content.trim()) return false;
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return true;
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})
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.map((v) => {
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const { role, content } = v;
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const insideRole = ClaudeMapper[role] ?? "user";
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if (!visionModel || typeof content === "string") {
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return {
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role: insideRole,
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content: getMessageTextContent(v),
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};
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}
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return {
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role: insideRole,
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content: content
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.filter((v) => v.image_url || v.text)
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.map(({ type, text, image_url }) => {
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if (type === "text") {
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return {
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type,
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text: text!,
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};
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}
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const { url = "" } = image_url || {};
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const colonIndex = url.indexOf(":");
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const semicolonIndex = url.indexOf(";");
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const comma = url.indexOf(",");
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const mimeType = url.slice(colonIndex + 1, semicolonIndex);
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const encodeType = url.slice(semicolonIndex + 1, comma);
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const data = url.slice(comma + 1);
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return {
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type: "image" as const,
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source: {
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type: encodeType,
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media_type: mimeType,
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data,
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},
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};
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}),
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};
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});
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if (prompt[0]?.role === "assistant") {
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prompt.unshift({
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role: "user",
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content: ";",
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});
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}
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const requestBody: AnthropicChatRequest = {
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messages: prompt,
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stream: shouldStream,
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model: modelConfig.model,
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max_tokens: modelConfig.max_tokens,
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temperature: modelConfig.temperature,
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top_p: modelConfig.top_p,
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// top_k: modelConfig.top_k,
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top_k: 5,
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};
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const path = this.path(Anthropic.ChatPath);
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const controller = new AbortController();
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options.onController?.(controller);
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if (shouldStream) {
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let index = -1;
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const [tools, funcs] = usePluginStore
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.getState()
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.getAsTools(
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useChatStore.getState().currentSession().mask?.plugin || [],
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);
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return stream(
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path,
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requestBody,
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{
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...getHeaders(),
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"anthropic-version": accessStore.anthropicApiVersion,
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},
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// @ts-ignore
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tools.map((tool) => ({
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name: tool?.function?.name,
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description: tool?.function?.description,
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input_schema: tool?.function?.parameters,
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})),
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funcs,
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controller,
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// parseSSE
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(text: string, runTools: ChatMessageTool[]) => {
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// console.log("parseSSE", text, runTools);
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let chunkJson:
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| undefined
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| {
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type: "content_block_delta" | "content_block_stop";
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content_block?: {
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type: "tool_use";
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id: string;
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name: string;
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};
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delta?: {
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type: "text_delta" | "input_json_delta";
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text?: string;
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partial_json?: string;
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};
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index: number;
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};
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chunkJson = JSON.parse(text);
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if (chunkJson?.content_block?.type == "tool_use") {
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index += 1;
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const id = chunkJson?.content_block.id;
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const name = chunkJson?.content_block.name;
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runTools.push({
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id,
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type: "function",
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function: {
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name,
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arguments: "",
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},
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});
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}
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if (
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chunkJson?.delta?.type == "input_json_delta" &&
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chunkJson?.delta?.partial_json
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) {
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// @ts-ignore
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runTools[index]["function"]["arguments"] +=
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chunkJson?.delta?.partial_json;
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}
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return chunkJson?.delta?.text;
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},
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// processToolMessage, include tool_calls message and tool call results
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(
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requestPayload: RequestPayload,
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toolCallMessage: any,
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toolCallResult: any[],
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) => {
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// reset index value
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index = -1;
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// @ts-ignore
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requestPayload?.messages?.splice(
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// @ts-ignore
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requestPayload?.messages?.length,
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0,
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{
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role: "assistant",
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content: toolCallMessage.tool_calls.map(
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(tool: ChatMessageTool) => ({
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type: "tool_use",
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id: tool.id,
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name: tool?.function?.name,
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input: tool?.function?.arguments
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? JSON.parse(tool?.function?.arguments)
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: {},
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}),
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),
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},
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// @ts-ignore
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...toolCallResult.map((result) => ({
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role: "user",
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content: [
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{
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type: "tool_result",
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tool_use_id: result.tool_call_id,
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content: result.content,
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},
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],
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})),
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);
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},
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options,
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);
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} else {
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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: {
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...getHeaders(), // get common headers
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"anthropic-version": accessStore.anthropicApiVersion,
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// do not send `anthropicApiKey` in browser!!!
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// Authorization: getAuthKey(accessStore.anthropicApiKey),
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},
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};
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try {
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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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console.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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}
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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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};
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}
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async models() {
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// const provider = {
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// id: "anthropic",
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// providerName: "Anthropic",
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// providerType: "anthropic",
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// };
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return [
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// {
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// name: "claude-instant-1.2",
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// available: true,
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// provider,
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// },
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// {
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// name: "claude-2.0",
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// available: true,
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// provider,
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// },
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// {
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// name: "claude-2.1",
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// available: true,
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// provider,
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// },
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// {
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// name: "claude-3-opus-20240229",
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// available: true,
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// provider,
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// },
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// {
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// name: "claude-3-sonnet-20240229",
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// available: true,
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// provider,
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// },
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// {
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// name: "claude-3-haiku-20240307",
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// available: true,
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// provider,
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// },
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];
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}
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path(path: string): string {
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const accessStore = useAccessStore.getState();
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let baseUrl: string = "";
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if (accessStore.useCustomConfig) {
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baseUrl = accessStore.anthropicUrl;
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}
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// if endpoint is empty, use default endpoint
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if (baseUrl.trim().length === 0) {
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const isApp = !!getClientConfig()?.isApp;
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baseUrl = isApp
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? DEFAULT_API_HOST + "/api/proxy/anthropic"
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: ApiPath.Anthropic;
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}
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if (!baseUrl.startsWith("http") && !baseUrl.startsWith("/api")) {
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baseUrl = "https://" + baseUrl;
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}
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baseUrl = trimEnd(baseUrl, "/");
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// try rebuild url, when using cloudflare ai gateway in client
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return cloudflareAIGatewayUrl(`${baseUrl}/${path}`);
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}
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}
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function trimEnd(s: string, end = " ") {
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if (end.length === 0) return s;
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while (s.endsWith(end)) {
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s = s.slice(0, -end.length);
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}
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return s;
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}
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