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支持model传入智能体ID，不传或者非24位id则默认使用GLM4

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Vinlic 2024-03-17 16:14:14 +08:00
parent 1ae7f759ad
commit f776021240
2 changed files with 6 additions and 16 deletions
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17
src/api/controllers/chat.ts
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@ -13,8 +13,8 @@ import util from '@/lib/util.ts';
// 模型名称 // 模型名称
const MODEL_NAME = 'glm'; const MODEL_NAME = 'glm';
// 默认的智能体ID // 默认的智能体ID，GLM4
const DEFAULT_ASSISTANT_ID = '65c32fa2a766a337422a6006'; const DEFAULT_ASSISTANT_ID = '65940acff94777010aa6b796';
// access_token有效期 // access_token有效期
const ACCESS_TOKEN_EXPIRES = 3600; const ACCESS_TOKEN_EXPIRES = 3600;
// 最大重试次数 // 最大重试次数
@ -157,17 +157,6 @@ async function createCompletion(messages: any[], refreshToken: string, assistant
// 请求流 // 请求流
const token = await acquireToken(refreshToken); const token = await acquireToken(refreshToken);
console.log({
assistant_id: assistantId,
conversation_id: '',
messages: messagesPrepare(messages, refs),
meta_data: {
channel: '',
draft_id: '',
input_question_type: 'xxxx',
is_test: false
}
});
const result = await axios.post('https://chatglm.cn/chatglm/backend-api/assistant/stream', { const result = await axios.post('https://chatglm.cn/chatglm/backend-api/assistant/stream', {
assistant_id: assistantId, assistant_id: assistantId,
conversation_id: '', conversation_id: '',
@ -315,7 +304,7 @@ function extractRefFileUrls(messages: any[]) {
* @param messages 参考gpt系列消息格式，多轮对话请完整提供上下文 * @param messages 参考gpt系列消息格式，多轮对话请完整提供上下文
*/ */
function messagesPrepare(messages: any[], refs: any[]) { function messagesPrepare(messages: any[], refs: any[]) {
const headPrompt = '设定：【重要】回答用户问题，不要输出说话者\n'; const headPrompt = '设定：【重要】回答用户问题，禁止输出双方的名字\n';
const content = messages.reduce((content, message) => { const content = messages.reduce((content, message) => {
if (_.isArray(message.content)) { if (_.isArray(message.content)) {
return message.content.reduce((_content, v) => { return message.content.reduce((_content, v) => {

5
src/api/routes/chat.ts
View File

@ -20,14 +20,15 @@ export default {
// 随机挑选一个refresh_token // 随机挑选一个refresh_token
const token = _.sample(tokens); const token = _.sample(tokens);
const messages = request.body.messages; const messages = request.body.messages;
const assistantId = /^[a-z0-9]{24,}$/.test(request.body.model) ? request.body.model : undefined
if (request.body.stream) { if (request.body.stream) {
const stream = await chat.createCompletionStream(request.body.messages, token, request.body.use_search); const stream = await chat.createCompletionStream(request.body.messages, token, assistantId);
return new Response(stream, { return new Response(stream, {
type: "text/event-stream" type: "text/event-stream"
}); });
} }
else else
return await chat.createCompletion(messages, token, request.body.use_search); return await chat.createCompletion(messages, token, assistantId);
} }
} }