perf: search prompt

This commit is contained in:
archer
2023-05-09 19:04:42 +08:00
parent a837552b56
commit a745993829
5 changed files with 53 additions and 44 deletions

View File

@@ -55,7 +55,7 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
// 使用了知识库搜索
if (model.chat.useKb) {
const { code, searchPrompt, aiPrompt } = await searchKb({
const { code, searchPrompts } = await searchKb({
userOpenAiKey,
prompts,
similarity: ModelVectorSearchModeMap[model.chat.searchMode]?.similarity,
@@ -65,13 +65,10 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
// search result is empty
if (code === 201) {
return res.send(searchPrompt?.value);
return res.send(searchPrompts[0]?.value);
}
if (aiPrompt) {
prompts.splice(prompts.length - 1, 0, aiPrompt);
}
searchPrompt && prompts.unshift(searchPrompt);
prompts.splice(prompts.length - 1, 0, ...searchPrompts);
} else {
// 没有用知识库搜索,仅用系统提示词
model.chat.systemPrompt &&

View File

@@ -73,7 +73,7 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
if (model.chat.useKb) {
const similarity = ModelVectorSearchModeMap[model.chat.searchMode]?.similarity || 0.22;
const { code, searchPrompt } = await searchKb({
const { code, searchPrompts } = await searchKb({
prompts,
similarity,
model,
@@ -82,10 +82,9 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
// search result is empty
if (code === 201) {
return res.send(searchPrompt?.value);
return res.send(searchPrompts[0]?.value);
}
searchPrompt && prompts.unshift(searchPrompt);
prompts.splice(prompts.length - 1, 0, ...searchPrompts);
} else {
// 没有用知识库搜索,仅用系统提示词
if (model.chat.systemPrompt) {

View File

@@ -122,14 +122,14 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
const prompts = [prompt];
// 获取向量匹配到的提示词
const { searchPrompt } = await searchKb({
const { searchPrompts } = await searchKb({
similarity: ModelVectorSearchModeMap[model.chat.searchMode]?.similarity,
prompts,
model,
userId
});
searchPrompt && prompts.unshift(searchPrompt);
prompts.splice(prompts.length - 1, 0, ...searchPrompts);
// 计算温度
const temperature = (modelConstantsData.maxTemperature * (model.chat.temperature / 10)).toFixed(

View File

@@ -23,14 +23,10 @@ export const searchKb = async ({
similarity?: number;
}): Promise<{
code: 200 | 201;
searchPrompt?: {
obj: `${ChatRoleEnum.System}`;
searchPrompts: {
obj: ChatRoleEnum;
value: string;
};
aiPrompt?: {
obj: `${ChatRoleEnum.AI}`;
value: string;
};
}[];
}> => {
async function search(textArr: string[] = []) {
// 获取提示词的向量
@@ -102,41 +98,58 @@ export const searchKb = async ({
if (!filterSystemPrompt && model.chat.searchMode === ModelVectorSearchModeEnum.hightSimilarity) {
return {
code: 201,
searchPrompt: {
searchPrompts: [
{
obj: ChatRoleEnum.System,
value: '对不起,你的问题不在知识库中。'
}
]
};
}
/* 高相似度+无上下文,不添加额外知识,仅用系统提示词 */
if (!filterSystemPrompt && model.chat.searchMode === ModelVectorSearchModeEnum.noContext) {
return {
code: 200,
searchPrompt: model.chat.systemPrompt
? {
searchPrompts: model.chat.systemPrompt
? [
{
obj: ChatRoleEnum.System,
value: model.chat.systemPrompt
}
: undefined
]
: []
};
}
/* 有匹配 */
return {
code: 200,
searchPrompt: {
searchPrompts: [
{
obj: ChatRoleEnum.System,
value: `知识库:'${filterSystemPrompt}'`
},
aiPrompt: ModelVectorSearchModeEnum.hightSimilarity
? {
obj: 'AI',
value: `我来玩一个问答游戏,规则为:
1.我完全忘记我已有的知识
2.我只能回答关于"${model.chat.systemPrompt || model.name}"的问题
3.我只能从知识库中选择内容进行回答
4.如果问题不在知识库中,我会回答"我不知道。"`
...(model.chat.systemPrompt
? [
{
obj: ChatRoleEnum.System,
value: model.chat.systemPrompt
}
: undefined
]
: []),
...(model.chat.searchMode !== ModelVectorSearchModeEnum.noContext
? [
{
obj: ChatRoleEnum.System,
value: `我们来玩问答游戏,规则为:
1.你完全忘记你已有的知识
2.你只能回答关于"${model.name}"的问题
3.你只能从知识库中选择内容进行回答
4.如果问题不在知识库中,你会回答"我不知道。"
务必遵守规则`
}
]
: [])
]
};
};

View File

@@ -27,7 +27,7 @@ export const lafClaudChat = async ({
.join('\n');
const systemPromptText = systemPrompt ? `\n知识库内容:'${systemPrompt}'\n` : '';
const prompt = `${systemPromptText}我的问题:'${messages[messages.length - 1].value}'`;
const prompt = `${systemPromptText}\n我的问题:'${messages[messages.length - 1].value}'`;
const lafResponse = await axios.post(
'https://hnvacz.laf.run/claude-gpt',