feat: [#5714] 支持GLM

This commit is contained in:
DDMeaqua
2024-10-30 19:24:03 +08:00
parent 4745706c42
commit d357b45e84
11 changed files with 453 additions and 0 deletions

View File

@@ -21,6 +21,7 @@ import { HunyuanApi } from "./platforms/tencent";
import { MoonshotApi } from "./platforms/moonshot";
import { SparkApi } from "./platforms/iflytek";
import { XAIApi } from "./platforms/xai";
import { GLMApi } from "./platforms/glm";
export const ROLES = ["system", "user", "assistant"] as const;
export type MessageRole = (typeof ROLES)[number];
@@ -156,6 +157,9 @@ export class ClientApi {
case ModelProvider.XAI:
this.llm = new XAIApi();
break;
case ModelProvider.GLM:
this.llm = new GLMApi();
break;
default:
this.llm = new ChatGPTApi();
}
@@ -244,6 +248,7 @@ export function getHeaders(ignoreHeaders: boolean = false) {
const isMoonshot = modelConfig.providerName === ServiceProvider.Moonshot;
const isIflytek = modelConfig.providerName === ServiceProvider.Iflytek;
const isXAI = modelConfig.providerName === ServiceProvider.XAI;
const isGLM = modelConfig.providerName === ServiceProvider.GLM;
const isEnabledAccessControl = accessStore.enabledAccessControl();
const apiKey = isGoogle
? accessStore.googleApiKey
@@ -259,6 +264,8 @@ export function getHeaders(ignoreHeaders: boolean = false) {
? accessStore.moonshotApiKey
: isXAI
? accessStore.xaiApiKey
: isGLM
? accessStore.glmApiKey
: isIflytek
? accessStore.iflytekApiKey && accessStore.iflytekApiSecret
? accessStore.iflytekApiKey + ":" + accessStore.iflytekApiSecret
@@ -274,6 +281,7 @@ export function getHeaders(ignoreHeaders: boolean = false) {
isMoonshot,
isIflytek,
isXAI,
isGLM,
apiKey,
isEnabledAccessControl,
};
@@ -338,6 +346,8 @@ export function getClientApi(provider: ServiceProvider): ClientApi {
return new ClientApi(ModelProvider.Iflytek);
case ServiceProvider.XAI:
return new ClientApi(ModelProvider.XAI);
case ServiceProvider.GLM:
return new ClientApi(ModelProvider.GLM);
default:
return new ClientApi(ModelProvider.GPT);
}

192
app/client/platforms/glm.ts Normal file
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@@ -0,0 +1,192 @@
"use client";
import { ApiPath, GLM_BASE_URL, GLM, REQUEST_TIMEOUT_MS } from "@/app/constant";
import {
useAccessStore,
useAppConfig,
useChatStore,
ChatMessageTool,
usePluginStore,
} from "@/app/store";
import { stream } from "@/app/utils/chat";
import {
ChatOptions,
getHeaders,
LLMApi,
LLMModel,
SpeechOptions,
} from "../api";
import { getClientConfig } from "@/app/config/client";
import { getMessageTextContent } from "@/app/utils";
import { RequestPayload } from "./openai";
import { fetch } from "@/app/utils/stream";
export class GLMApi implements LLMApi {
private disableListModels = true;
path(path: string): string {
const accessStore = useAccessStore.getState();
let baseUrl = "";
if (accessStore.useCustomConfig) {
baseUrl = accessStore.glmUrl;
}
if (baseUrl.length === 0) {
const isApp = !!getClientConfig()?.isApp;
const apiPath = ApiPath.GLM;
baseUrl = isApp ? GLM_BASE_URL : apiPath;
}
if (baseUrl.endsWith("/")) {
baseUrl = baseUrl.slice(0, baseUrl.length - 1);
}
if (!baseUrl.startsWith("http") && !baseUrl.startsWith(ApiPath.GLM)) {
baseUrl = "https://" + baseUrl;
}
console.log("[Proxy Endpoint] ", baseUrl, path);
return [baseUrl, path].join("/");
}
extractMessage(res: any) {
return res.choices?.at(0)?.message?.content ?? "";
}
speech(options: SpeechOptions): Promise<ArrayBuffer> {
throw new Error("Method not implemented.");
}
async chat(options: ChatOptions) {
const messages: ChatOptions["messages"] = [];
for (const v of options.messages) {
const content = getMessageTextContent(v);
messages.push({ role: v.role, content });
}
const modelConfig = {
...useAppConfig.getState().modelConfig,
...useChatStore.getState().currentSession().mask.modelConfig,
...{
model: options.config.model,
providerName: options.config.providerName,
},
};
const requestPayload: RequestPayload = {
messages,
stream: options.config.stream,
model: modelConfig.model,
temperature: modelConfig.temperature,
presence_penalty: modelConfig.presence_penalty,
frequency_penalty: modelConfig.frequency_penalty,
top_p: modelConfig.top_p,
};
console.log("[Request] glm payload: ", requestPayload);
const shouldStream = !!options.config.stream;
const controller = new AbortController();
options.onController?.(controller);
try {
const chatPath = this.path(GLM.ChatPath);
const chatPayload = {
method: "POST",
body: JSON.stringify(requestPayload),
signal: controller.signal,
headers: getHeaders(),
};
// make a fetch request
const requestTimeoutId = setTimeout(
() => controller.abort(),
REQUEST_TIMEOUT_MS,
);
if (shouldStream) {
const [tools, funcs] = usePluginStore
.getState()
.getAsTools(
useChatStore.getState().currentSession().mask?.plugin || [],
);
return stream(
chatPath,
requestPayload,
getHeaders(),
tools as any,
funcs,
controller,
// parseSSE
(text: string, runTools: ChatMessageTool[]) => {
// console.log("parseSSE", text, runTools);
const json = JSON.parse(text);
const choices = json.choices as Array<{
delta: {
content: string;
tool_calls: ChatMessageTool[];
};
}>;
const tool_calls = choices[0]?.delta?.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;
}
}
return choices[0]?.delta?.content;
},
// processToolMessage, include tool_calls message and tool call results
(
requestPayload: RequestPayload,
toolCallMessage: any,
toolCallResult: any[],
) => {
// @ts-ignore
requestPayload?.messages?.splice(
// @ts-ignore
requestPayload?.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);
}
} 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 [];
}
}