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

@@ -57,62 +57,29 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
// 使用了知识库搜索 // 使用了知识库搜索
if (model.chat.useKb) { if (model.chat.useKb) {
const { systemPrompts } = await searchKb_openai({ const { code, searchPrompt } = await searchKb_openai({
apiKey: userApiKey || systemKey, apiKey: userApiKey || systemKey,
isPay: !userApiKey, isPay: !userApiKey,
text: prompt.value, text: prompt.value,
similarity: ModelVectorSearchModeMap[model.chat.searchMode]?.similarity || 0.22, similarity: ModelVectorSearchModeMap[model.chat.searchMode]?.similarity || 0.22,
modelId, model,
userId userId
}); });
// filter system prompt // search result is empty
if ( if (code === 201) {
systemPrompts.length === 0 && return res.send(searchPrompt?.value);
model.chat.searchMode === ModelVectorSearchModeEnum.hightSimilarity
) {
return res.send('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
) {
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({ searchPrompt && prompts.unshift(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}'
`
});
}
} else { } else {
// 没有用知识库搜索,仅用系统提示词 // 没有用知识库搜索,仅用系统提示词
if (model.chat.systemPrompt) { model.chat.systemPrompt &&
prompts.unshift({ prompts.unshift({
obj: 'SYSTEM', obj: 'SYSTEM',
value: model.chat.systemPrompt value: model.chat.systemPrompt
}); });
} }
}
// 控制总 tokens 数量,防止超出 // 控制总 tokens 数量,防止超出
const filterPrompts = openaiChatFilter({ const filterPrompts = openaiChatFilter({

View File

@@ -67,57 +67,21 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
if (model.chat.useKb) { if (model.chat.useKb) {
const similarity = ModelVectorSearchModeMap[model.chat.searchMode]?.similarity || 0.22; const similarity = ModelVectorSearchModeMap[model.chat.searchMode]?.similarity || 0.22;
const { systemPrompts } = await searchKb_openai({ const { code, searchPrompt } = await searchKb_openai({
apiKey, apiKey,
isPay: true, isPay: true,
text: prompts[prompts.length - 1].value, text: prompts[prompts.length - 1].value,
similarity, similarity,
modelId, model,
userId userId
}); });
// filter system prompt // search result is empty
if ( if (code === 201) {
systemPrompts.length === 0 && return res.send(searchPrompt?.value);
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,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({ searchPrompt && prompts.unshift(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}'
`
});
}
} else { } else {
// 没有用知识库搜索,仅用系统提示词 // 没有用知识库搜索,仅用系统提示词
if (model.chat.systemPrompt) { if (model.chat.systemPrompt) {

View File

@@ -131,26 +131,16 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
const prompts = [prompt]; const prompts = [prompt];
// 获取向量匹配到的提示词 // 获取向量匹配到的提示词
const { systemPrompts } = await searchKb_openai({ const { searchPrompt } = await searchKb_openai({
isPay: true, isPay: true,
apiKey, apiKey,
similarity: ModelVectorSearchModeMap[model.chat.searchMode]?.similarity || 0.22, similarity: ModelVectorSearchModeMap[model.chat.searchMode]?.similarity || 0.22,
text: prompt.value, text: prompt.value,
modelId, model,
userId userId
}); });
// system 筛选,最多 2500 tokens searchPrompt && prompts.unshift(searchPrompt);
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}`
});
// 控制上下文 tokens 数量,防止超出 // 控制上下文 tokens 数量,防止超出
const filterPrompts = openaiChatFilter({ 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 = ''; let responseContent = '';
if (isStream) { 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 // 获取向量匹配到的提示词
const { systemPrompts } = await searchKb_openai({ const { code, searchPrompt } = await searchKb_openai({
isPay: true, isPay: true,
apiKey, apiKey,
similarity: ModelVectorSearchModeMap[model.chat.searchMode]?.similarity || 0.22, similarity: ModelVectorSearchModeMap[model.chat.searchMode]?.similarity || 0.22,
text: prompts[prompts.length - 1].value, text: prompts[prompts.length - 1].value,
modelId, model,
userId userId
}); });
// system 合并 // search result is empty
if (prompts[0].obj === 'SYSTEM') { if (code === 201) {
systemPrompts.unshift(prompts.shift()?.value || ''); return res.send(searchPrompt?.value);
} }
/* 高相似度+退出,无法匹配时直接退出 */ searchPrompt && prompts.unshift(searchPrompt);
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}'
`
});
}
// 控制在 tokens 数量,防止超出 // 控制在 tokens 数量,防止超出
const filterPrompts = openaiChatFilter({ const filterPrompts = openaiChatFilter({

View File

@@ -1,6 +1,8 @@
import { openaiCreateEmbedding } from '../utils/openai'; import { openaiCreateEmbedding } from '../utils/openai';
import { PgClient } from '@/service/pg'; 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 * use openai embedding search kb
@@ -10,16 +12,22 @@ export const searchKb_openai = async ({
isPay, isPay,
text, text,
similarity, similarity,
modelId, model,
userId userId
}: { }: {
apiKey: string; apiKey: string;
isPay: boolean; isPay: boolean;
text: string; text: string;
modelId: string; model: ModelSchema;
userId: string; userId: string;
similarity: number; similarity: number;
}) => { }): Promise<{
code: 200 | 201;
searchPrompt?: {
obj: 'Human' | 'AI' | 'SYSTEM';
value: string;
};
}> => {
// 获取提示词的向量 // 获取提示词的向量
const { vector: promptVector } = await openaiCreateEmbedding({ const { vector: promptVector } = await openaiCreateEmbedding({
isPay, isPay,
@@ -28,12 +36,12 @@ export const searchKb_openai = async ({
text text
}); });
const vectorSearch = await PgClient.select<{ id: string; q: string; a: string }>('modelData', { const vectorSearch = await PgClient.select<{ q: string; a: string }>('modelData', {
fields: ['id', 'q', 'a'], fields: ['q', 'a'],
where: [ where: [
['status', ModelDataStatusEnum.ready], ['status', ModelDataStatusEnum.ready],
'AND', 'AND',
['model_id', modelId], ['model_id', model._id],
'AND', 'AND',
`vector <=> '[${promptVector}]' < ${similarity}` `vector <=> '[${promptVector}]' < ${similarity}`
], ],
@@ -43,5 +51,51 @@ export const searchKb_openai = async ({
const systemPrompts: string[] = vectorSearch.rows.map((item) => `${item.q}\n${item.a}`); const systemPrompts: string[] = vectorSearch.rows.map((item) => `${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}'
`
}
};
}; };