perf: search kb model

This commit is contained in:
archer
2023-04-30 14:01:39 +08:00
parent f109f1cf60
commit 39869bc4ea
5 changed files with 84 additions and 150 deletions

View File

@@ -57,61 +57,28 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
// 使用了知识库搜索
if (model.chat.useKb) {
const { systemPrompts } = await searchKb_openai({
const { code, searchPrompt } = await searchKb_openai({
apiKey: userApiKey || systemKey,
isPay: !userApiKey,
text: prompt.value,
similarity: ModelVectorSearchModeMap[model.chat.searchMode]?.similarity || 0.22,
modelId,
model,
userId
});
// filter system prompt
if (
systemPrompts.length === 0 &&
model.chat.searchMode === ModelVectorSearchModeEnum.hightSimilarity
) {
return res.send('对不起,你的问题不在知识库中。');
// search result is empty
if (code === 201) {
return res.send(searchPrompt?.value);
}
/* 高相似度+无上下文,不添加额外知识,仅用系统提示词 */
if (
systemPrompts.length === 0 &&
model.chat.searchMode === ModelVectorSearchModeEnum.noContext
) {
prompts.unshift({
obj: 'SYSTEM',
value: model.chat.systemPrompt
});
} else {
// 有匹配情况下system 添加知识库内容。
// 系统提示词过滤,最多 2500 tokens
const filterSystemPrompt = systemPromptFilter({
model: model.chat.chatModel,
prompts: systemPrompts,
maxTokens: 2500
});
prompts.unshift({
obj: 'SYSTEM',
value: `
${model.chat.systemPrompt}
${
model.chat.searchMode === ModelVectorSearchModeEnum.hightSimilarity
? `不回答知识库外的内容.`
: ''
}
知识库内容为: ${filterSystemPrompt}'
`
});
}
searchPrompt && prompts.unshift(searchPrompt);
} else {
// 没有用知识库搜索,仅用系统提示词
if (model.chat.systemPrompt) {
model.chat.systemPrompt &&
prompts.unshift({
obj: 'SYSTEM',
value: model.chat.systemPrompt
});
}
}
// 控制总 tokens 数量,防止超出

View File

@@ -67,57 +67,21 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
if (model.chat.useKb) {
const similarity = ModelVectorSearchModeMap[model.chat.searchMode]?.similarity || 0.22;
const { systemPrompts } = await searchKb_openai({
const { code, searchPrompt } = await searchKb_openai({
apiKey,
isPay: true,
text: prompts[prompts.length - 1].value,
similarity,
modelId,
model,
userId
});
// filter system prompt
if (
systemPrompts.length === 0 &&
model.chat.searchMode === ModelVectorSearchModeEnum.hightSimilarity
) {
return jsonRes(res, {
code: 500,
message: '对不起,你的问题不在知识库中。',
data: '对不起,你的问题不在知识库中。'
});
// search result is empty
if (code === 201) {
return res.send(searchPrompt?.value);
}
/* 高相似度+无上下文,不添加额外知识,仅用系统提示词 */
if (
systemPrompts.length === 0 &&
model.chat.searchMode === ModelVectorSearchModeEnum.noContext
) {
prompts.unshift({
obj: 'SYSTEM',
value: model.chat.systemPrompt
});
} else {
// 有匹配情况下system 添加知识库内容。
// 系统提示词过滤,最多 2500 tokens
const filterSystemPrompt = systemPromptFilter({
model: model.chat.chatModel,
prompts: systemPrompts,
maxTokens: 2500
});
prompts.unshift({
obj: 'SYSTEM',
value: `
${model.chat.systemPrompt}
${
model.chat.searchMode === ModelVectorSearchModeEnum.hightSimilarity
? `不回答知识库外的内容.`
: ''
}
知识库内容为: ${filterSystemPrompt}'
`
});
}
searchPrompt && prompts.unshift(searchPrompt);
} else {
// 没有用知识库搜索,仅用系统提示词
if (model.chat.systemPrompt) {

View File

@@ -131,26 +131,16 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
const prompts = [prompt];
// 获取向量匹配到的提示词
const { systemPrompts } = await searchKb_openai({
const { searchPrompt } = await searchKb_openai({
isPay: true,
apiKey,
similarity: ModelVectorSearchModeMap[model.chat.searchMode]?.similarity || 0.22,
text: prompt.value,
modelId,
model,
userId
});
// system 筛选,最多 2500 tokens
const filterSystemPrompt = systemPromptFilter({
model: model.chat.chatModel,
prompts: systemPrompts,
maxTokens: 2500
});
prompts.unshift({
obj: 'SYSTEM',
value: `${model.chat.systemPrompt} 知识库是最新的,下面是知识库内容:${filterSystemPrompt}`
});
searchPrompt && prompts.unshift(searchPrompt);
// 控制上下文 tokens 数量,防止超出
const filterPrompts = openaiChatFilter({
@@ -181,8 +171,6 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
}
);
console.log('code response. time:', `${(Date.now() - startTime) / 1000}s`);
let responseContent = '';
if (isStream) {

View File

@@ -68,60 +68,21 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
}
// 获取向量匹配到的提示词
const { systemPrompts } = await searchKb_openai({
const { code, searchPrompt } = await searchKb_openai({
isPay: true,
apiKey,
similarity: ModelVectorSearchModeMap[model.chat.searchMode]?.similarity || 0.22,
text: prompts[prompts.length - 1].value,
modelId,
model,
userId
});
// system 合并
if (prompts[0].obj === 'SYSTEM') {
systemPrompts.unshift(prompts.shift()?.value || '');
// search result is empty
if (code === 201) {
return res.send(searchPrompt?.value);
}
/* 高相似度+退出,无法匹配时直接退出 */
if (
systemPrompts.length === 0 &&
model.chat.searchMode === ModelVectorSearchModeEnum.hightSimilarity
) {
return jsonRes(res, {
code: 500,
message: '对不起,你的问题不在知识库中。',
data: '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 */
if (
systemPrompts.length === 0 &&
model.chat.searchMode === ModelVectorSearchModeEnum.noContext
) {
prompts.unshift({
obj: 'SYSTEM',
value: model.chat.systemPrompt
});
} else {
// 有匹配或者低匹配度模式情况下,添加知识库内容。
// 系统提示词过滤,最多 2500 tokens
const systemPrompt = systemPromptFilter({
model: model.chat.chatModel,
prompts: systemPrompts,
maxTokens: 2500
});
prompts.unshift({
obj: 'SYSTEM',
value: `
${model.chat.systemPrompt}
${
model.chat.searchMode === ModelVectorSearchModeEnum.hightSimilarity ? `不回答知识库外的内容.` : ''
}
知识库内容为: ${systemPrompt}'
`
});
}
searchPrompt && prompts.unshift(searchPrompt);
// 控制在 tokens 数量,防止超出
const filterPrompts = openaiChatFilter({

View File

@@ -1,6 +1,8 @@
import { openaiCreateEmbedding } from '../utils/openai';
import { PgClient } from '@/service/pg';
import { ModelDataStatusEnum } from '@/constants/model';
import { ModelDataStatusEnum, ModelVectorSearchModeEnum } from '@/constants/model';
import { ModelSchema } from '@/types/mongoSchema';
import { systemPromptFilter } from '../utils/tools';
/**
* use openai embedding search kb
@@ -10,16 +12,22 @@ export const searchKb_openai = async ({
isPay,
text,
similarity,
modelId,
model,
userId
}: {
apiKey: string;
isPay: boolean;
text: string;
modelId: string;
model: ModelSchema;
userId: string;
similarity: number;
}) => {
}): Promise<{
code: 200 | 201;
searchPrompt?: {
obj: 'Human' | 'AI' | 'SYSTEM';
value: string;
};
}> => {
// 获取提示词的向量
const { vector: promptVector } = await openaiCreateEmbedding({
isPay,
@@ -28,12 +36,12 @@ export const searchKb_openai = async ({
text
});
const vectorSearch = await PgClient.select<{ id: string; q: string; a: string }>('modelData', {
fields: ['id', 'q', 'a'],
const vectorSearch = await PgClient.select<{ q: string; a: string }>('modelData', {
fields: ['q', 'a'],
where: [
['status', ModelDataStatusEnum.ready],
'AND',
['model_id', modelId],
['model_id', model._id],
'AND',
`vector <=> '[${promptVector}]' < ${similarity}`
],
@@ -43,5 +51,51 @@ export const searchKb_openai = async ({
const systemPrompts: string[] = vectorSearch.rows.map((item) => `${item.q}\n${item.a}`);
return { systemPrompts };
// filter system prompt
if (
systemPrompts.length === 0 &&
model.chat.searchMode === ModelVectorSearchModeEnum.hightSimilarity
) {
return {
code: 201,
searchPrompt: {
obj: 'AI',
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 (systemPrompts.length === 0 && model.chat.searchMode === ModelVectorSearchModeEnum.noContext) {
return {
code: 200,
searchPrompt: model.chat.systemPrompt
? {
obj: 'SYSTEM',
value: model.chat.systemPrompt
}
: undefined
};
}
// 有匹配情况下system 添加知识库内容。
// 系统提示词过滤,最多 2500 tokens
const filterSystemPrompt = systemPromptFilter({
model: model.chat.chatModel,
prompts: systemPrompts,
maxTokens: 2500
});
return {
code: 200,
searchPrompt: {
obj: 'SYSTEM',
value: `
${model.chat.systemPrompt}
${
model.chat.searchMode === ModelVectorSearchModeEnum.hightSimilarity ? `不回答知识库外的内容.` : ''
}
知识库内容为: ${filterSystemPrompt}'
`
}
};
};