ChatGPT-Next-Web/app/client/platforms/alibaba.ts

278 lines
7.4 KiB
TypeScript

"use client";
import { ApiPath, Alibaba, ALIBABA_BASE_URL } from "@/app/constant";
import {
useAccessStore,
useAppConfig,
useChatStore,
ChatMessageTool,
usePluginStore,
} from "@/app/store";
import {
preProcessImageContentForAlibabaDashScope,
streamWithThink,
} from "@/app/utils/chat";
import {
ChatOptions,
getHeaders,
LLMApi,
LLMModel,
SpeechOptions,
MultimodalContent,
MultimodalContentForAlibaba,
} from "../api";
import { getClientConfig } from "@/app/config/client";
import {
getMessageTextContent,
getMessageTextContentWithoutThinking,
getTimeoutMSByModel,
isVisionModel,
} from "@/app/utils";
import { fetch } from "@/app/utils/stream";
export interface OpenAIListModelResponse {
object: string;
data: Array<{
id: string;
object: string;
root: string;
}>;
}
interface RequestInput {
messages: {
role: "system" | "user" | "assistant";
content: string | MultimodalContent[];
}[];
}
interface RequestParam {
result_format: string;
incremental_output?: boolean;
temperature: number;
repetition_penalty?: number;
top_p: number;
max_tokens?: number;
}
interface RequestPayload {
model: string;
input: RequestInput;
parameters: RequestParam;
}
export class QwenApi implements LLMApi {
path(path: string): string {
const accessStore = useAccessStore.getState();
let baseUrl = "";
if (accessStore.useCustomConfig) {
baseUrl = accessStore.alibabaUrl;
}
if (baseUrl.length === 0) {
const isApp = !!getClientConfig()?.isApp;
baseUrl = isApp ? ALIBABA_BASE_URL : ApiPath.Alibaba;
}
if (baseUrl.endsWith("/")) {
baseUrl = baseUrl.slice(0, baseUrl.length - 1);
}
if (!baseUrl.startsWith("http") && !baseUrl.startsWith(ApiPath.Alibaba)) {
baseUrl = "https://" + baseUrl;
}
console.log("[Proxy Endpoint] ", baseUrl, path);
return [baseUrl, path].join("/");
}
extractMessage(res: any) {
return res?.output?.choices?.at(0)?.message?.content ?? "";
}
speech(options: SpeechOptions): Promise<ArrayBuffer> {
throw new Error("Method not implemented.");
}
async chat(options: ChatOptions) {
const modelConfig = {
...useAppConfig.getState().modelConfig,
...useChatStore.getState().currentSession().mask.modelConfig,
...{
model: options.config.model,
},
};
const visionModel = isVisionModel(options.config.model);
const messages: ChatOptions["messages"] = [];
for (const v of options.messages) {
const content = (
visionModel
? await preProcessImageContentForAlibabaDashScope(v.content)
: v.role === "assistant"
? getMessageTextContentWithoutThinking(v)
: getMessageTextContent(v)
) as any;
messages.push({ role: v.role, content });
}
const shouldStream = !!options.config.stream;
const requestPayload: RequestPayload = {
model: modelConfig.model,
input: {
messages,
},
parameters: {
result_format: "message",
incremental_output: shouldStream,
temperature: modelConfig.temperature,
// max_tokens: modelConfig.max_tokens,
top_p: modelConfig.top_p === 1 ? 0.99 : modelConfig.top_p, // qwen top_p is should be < 1
},
};
const controller = new AbortController();
options.onController?.(controller);
try {
const headers = {
...getHeaders(),
"X-DashScope-SSE": shouldStream ? "enable" : "disable",
};
const chatPath = this.path(Alibaba.ChatPath(modelConfig.model));
const chatPayload = {
method: "POST",
body: JSON.stringify(requestPayload),
signal: controller.signal,
headers: headers,
};
// make a fetch request
const requestTimeoutId = setTimeout(
() => controller.abort(),
getTimeoutMSByModel(options.config.model),
);
if (shouldStream) {
const [tools, funcs] = usePluginStore
.getState()
.getAsTools(
useChatStore.getState().currentSession().mask?.plugin || [],
);
return streamWithThink(
chatPath,
requestPayload,
headers,
tools as any,
funcs,
controller,
// parseSSE
(text: string, runTools: ChatMessageTool[]) => {
// console.log("parseSSE", text, runTools);
const json = JSON.parse(text);
const choices = json.output.choices as Array<{
message: {
content: string | null | MultimodalContentForAlibaba[];
tool_calls: ChatMessageTool[];
reasoning_content: string | null;
};
}>;
if (!choices?.length) return { isThinking: false, content: "" };
const tool_calls = choices[0]?.message?.tool_calls;
if (tool_calls?.length > 0) {
const index = tool_calls[0]?.index;
const id = tool_calls[0]?.id;
const args = tool_calls[0]?.function?.arguments;
if (id) {
runTools.push({
id,
type: tool_calls[0]?.type,
function: {
name: tool_calls[0]?.function?.name as string,
arguments: args,
},
});
} else {
// @ts-ignore
runTools[index]["function"]["arguments"] += args;
}
}
const reasoning = choices[0]?.message?.reasoning_content;
const content = choices[0]?.message?.content;
// Skip if both content and reasoning_content are empty or null
if (
(!reasoning || reasoning.length === 0) &&
(!content || content.length === 0)
) {
return {
isThinking: false,
content: "",
};
}
if (reasoning && reasoning.length > 0) {
return {
isThinking: true,
content: reasoning,
};
} else if (content && content.length > 0) {
return {
isThinking: false,
content: Array.isArray(content)
? content.map((item) => item.text).join(",")
: content,
};
}
return {
isThinking: false,
content: "",
};
},
// processToolMessage, include tool_calls message and tool call results
(
requestPayload: RequestPayload,
toolCallMessage: any,
toolCallResult: any[],
) => {
requestPayload?.input?.messages?.splice(
requestPayload?.input?.messages?.length,
0,
toolCallMessage,
...toolCallResult,
);
},
options,
);
} else {
const res = await fetch(chatPath, chatPayload);
clearTimeout(requestTimeoutId);
const resJson = await res.json();
const message = this.extractMessage(resJson);
options.onFinish(message, res);
}
} catch (e) {
console.log("[Request] failed to make a chat request", e);
options.onError?.(e as Error);
}
}
async usage() {
return {
used: 0,
total: 0,
};
}
async models(): Promise<LLMModel[]> {
return [];
}
}
export { Alibaba };