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perf: 知识库匹配模式

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This commit is contained in:
archer
2023-04-11 18:17:00 +08:00
parent 488e2f476e
commit 1fe5cd751a
4 changed files with 22 additions and 16 deletions
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9
src/pages/api/chat/vectorGpt.ts
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@@ -13,6 +13,7 @@ import { connectRedis } from '@/service/redis';
import { VecModelDataPrefix } from '@/constants/redis';
import { vectorToBuffer } from '@/utils/tools';
import { openaiCreateEmbedding, gpt35StreamResponse } from '@/service/utils/openai';
import dayjs from 'dayjs';
/* 发送提示词 */
export default async function handler(req: NextApiRequest, res: NextApiResponse) {
@@ -70,7 +71,7 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
`idx:${VecModelDataPrefix}:hash`,
`@modelId:{${String(
chat.modelId._id
)}} @vector:[VECTOR_RANGE 0.24 $blob]=>{$YIELD_DISTANCE_AS: score}`,
)}} @vector:[VECTOR_RANGE 0.22 $blob]=>{$YIELD_DISTANCE_AS: score}`,
'RETURN',
'1',
'text',
@@ -97,12 +98,14 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
}
if (formatRedisPrompt.length > 0) {
// textArr 筛选，最多 2800 tokens
// 系统提示词过滤，最多 2800 tokens
const systemPrompt = systemPromptFilter(formatRedisPrompt, 2800);
prompts.unshift({
obj: 'SYSTEM',
value: `${model.systemPrompt} 知识库内容是最新的，知识库内容为: "${systemPrompt}"`
value: `${model.systemPrompt} 用知识库内容回答，知识库内容为: "当前时间:${dayjs().format(
'YYYY/MM/DD HH:mm:ss'
)} ${systemPrompt}"`
});
} else {
return res.send('对不起，你的问题不在知识库中。');

25
src/pages/api/openapi/chat/vectorGpt.ts
View File

@@ -16,6 +16,7 @@ import { connectRedis } from '@/service/redis';
import { VecModelDataPrefix } from '@/constants/redis';
import { vectorToBuffer } from '@/utils/tools';
import { openaiCreateEmbedding, gpt35StreamResponse } from '@/service/utils/openai';
import dayjs from 'dayjs';
/* 发送提示词 */
export default async function handler(req: NextApiRequest, res: NextApiResponse) {
@@ -87,7 +88,7 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
const redisData: any[] = await redis.sendCommand([
'FT.SEARCH',
`idx:${VecModelDataPrefix}:hash`,
`@modelId:{${modelId}} @vector:[VECTOR_RANGE 0.24 $blob]=>{$YIELD_DISTANCE_AS: score}`,
`@modelId:{${modelId}} @vector:[VECTOR_RANGE 0.22 $blob]=>{$YIELD_DISTANCE_AS: score}`,
'RETURN',
'1',
'text',
@@ -114,22 +115,24 @@ export default async function handler(req: NextApiRequest, res: NextApiResponse)
}
}
if (formatRedisPrompt.length === 0) {
throw new Error('对不起，我没有找到你的问题');
}
// system 合并
if (prompts[0].obj === 'SYSTEM') {
formatRedisPrompt.unshift(prompts.shift()?.value || '');
}
// 系统提示词筛选，最多 2800 tokens
const systemPrompt = systemPromptFilter(formatRedisPrompt, 2800);
if (formatRedisPrompt.length > 0) {
// 系统提示词过滤，最多 2800 tokens
const systemPrompt = systemPromptFilter(formatRedisPrompt, 2800);
prompts.unshift({
obj: 'SYSTEM',
value: `${model.systemPrompt} 知识库内容是最新的,知识库内容为: "${systemPrompt}"`
});
prompts.unshift({
obj: 'SYSTEM',
value: `${model.systemPrompt} 用知识库内容回答，知识库内容为: "当前时间:${dayjs().format(
'YYYY/MM/DD HH:mm:ss'
)} ${systemPrompt}"`
});
} else {
return res.send('对不起，你的问题不在知识库中。');
}
// 控制在 tokens 数量，防止超出
const filterPrompts = openaiChatFilter(prompts, modelConstantsData.contextMaxToken);

2
src/pages/model/detail/components/ModelDataCard.tsx
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@@ -152,7 +152,7 @@ const ModelDataCard = ({ model }: { model: ModelSchema }) => {
>
手动输入
</MenuItem>
<MenuItem onClick={onOpenSelectFileModal}>文本内容 QA 拆分</MenuItem>
<MenuItem onClick={onOpenSelectFileModal}>文本/文件 QA 拆分</MenuItem>
<MenuItem onClick={onOpenSelectUrlModal}>网站内容 QA 拆分</MenuItem>
<MenuItem onClick={onOpenSelectCsvModal}>csv 问答对导入</MenuItem>
</MenuList>

2
src/service/utils/tools.ts
View File

@@ -91,7 +91,7 @@ export const openaiChatFilter = (prompts: ChatItemType[], maxTokens: number) =>
const formatPrompts = prompts.map((item) => ({
obj: item.obj,
value: item.value
.replace(/[\u3000\u3001\uff01-\uff5e\u3002]/g, ' ') // 中文标点改空格
// .replace(/[\u3000\u3001\uff01-\uff5e\u3002]/g, ' ') // 中文标点改空格
.replace(/\n+/g, '\n') // 连续空行
.replace(/[^\S\r\n]+/g, ' ') // 连续空白内容
.trim()