From e367265dbb9173315883e744dc7dbc58a8ea47d4 Mon Sep 17 00:00:00 2001 From: Archer <545436317@qq.com> Date: Thu, 21 Sep 2023 12:27:48 +0800 Subject: [PATCH] feat: function call prompt version (#331) --- client/data/config.json | 16 ++ client/public/docs/versionIntro.md | 2 +- .../src/components/ChatBox/ResponseTags.tsx | 5 +- client/src/pages/api/system/getInitData.ts | 21 ++- client/src/prompts/core/agent.ts | 42 +++++ client/src/service/events/pushBill.ts | 68 +++---- client/src/service/models/bill.ts | 19 +- .../moduleDispatch/agent/classifyQuestion.ts | 110 ++++++++--- .../service/moduleDispatch/agent/extract.ts | 176 ++++++++++++++---- client/src/service/utils/data.ts | 8 +- client/src/types/index.d.ts | 9 +- client/src/types/model.d.ts | 8 + 12 files changed, 364 insertions(+), 120 deletions(-) diff --git a/client/data/config.json b/client/data/config.json index c8f8073e6..c315ddd12 100644 --- a/client/data/config.json +++ b/client/data/config.json @@ -62,5 +62,21 @@ "name": "GPT35-16k", "maxToken": 16000, "price": 0 + }, + "ExtractModel": { + "model": "gpt-3.5-turbo-16k", + "functionCall": false, + "name": "GPT35-16k", + "maxToken": 16000, + "price": 0, + "prompt": "" + }, + "CQModel": { + "model": "gpt-3.5-turbo-16k", + "functionCall": false, + "name": "GPT35-16k", + "maxToken": 16000, + "price": 0, + "prompt": "" } } diff --git a/client/public/docs/versionIntro.md b/client/public/docs/versionIntro.md index 03472af9f..a08bb7095 100644 --- a/client/public/docs/versionIntro.md +++ b/client/public/docs/versionIntro.md @@ -1,4 +1,4 @@ -### Fast GPT V4.4.3 +### Fast GPT V4.4.4 1. 去除 - 限定词。目前旧应用仍生效，9/25 后全面去除，请及时替换。 2. 新增 - 引用模板/引用提示词设置，可以 DIY 引用内容的格式，从而更好的适配场景。 diff --git a/client/src/components/ChatBox/ResponseTags.tsx b/client/src/components/ChatBox/ResponseTags.tsx index a8404ca62..82b8b6741 100644 --- a/client/src/components/ChatBox/ResponseTags.tsx +++ b/client/src/components/ChatBox/ResponseTags.tsx @@ -56,7 +56,7 @@ const ResponseTags = ({ return responseData.length === 0 ? null : ( - {chatAccount === 1 ? ( + {chatAccount === 1 && ( <> {quoteList.length > 0 && ( @@ -83,7 +83,8 @@ const ResponseTags = ({ )} - ) : ( + )} + {chatAccount > 1 && ( 多组 AI 对话 diff --git a/client/src/pages/api/system/getInitData.ts b/client/src/pages/api/system/getInitData.ts index 2e4e831ae..f4ad29d5e 100644 --- a/client/src/pages/api/system/getInitData.ts +++ b/client/src/pages/api/system/getInitData.ts @@ -5,7 +5,8 @@ import { readFileSync } from 'fs'; import { type QAModelItemType, type ChatModelItemType, - type VectorModelItemType + type VectorModelItemType, + FunctionModelItemType } from '@/types/model'; export type InitDateResponse = { @@ -83,6 +84,22 @@ const defaultQAModel = { maxToken: 16000, price: 0 }; +const defaultExtractModel: FunctionModelItemType = { + model: 'gpt-3.5-turbo-16k', + name: 'GPT35-16k', + maxToken: 16000, + price: 0, + prompt: '', + functionCall: true +}; +const defaultCQModel: FunctionModelItemType = { + model: 'gpt-3.5-turbo-16k', + name: 'GPT35-16k', + maxToken: 16000, + price: 0, + prompt: '', + functionCall: true +}; const defaultVectorModels: VectorModelItemType[] = [ { @@ -114,6 +131,8 @@ export async function getInitConfig() { global.feConfigs = res.FeConfig ? { ...defaultFeConfigs, ...res.FeConfig } : defaultFeConfigs; global.chatModels = res.ChatModels || defaultChatModels; global.qaModel = res.QAModel || defaultQAModel; + global.extractModel = res.ExtractModel || defaultExtractModel; + global.cqModel = res.CQModel || defaultCQModel; global.vectorModels = res.VectorModels || defaultVectorModels; } catch (error) { setDefaultData(); diff --git a/client/src/prompts/core/agent.ts b/client/src/prompts/core/agent.ts index d47805430..1757a872b 100644 --- a/client/src/prompts/core/agent.ts +++ b/client/src/prompts/core/agent.ts @@ -14,3 +14,45 @@ A2: 我的文本："""{{text}}"""`, defaultTheme: '它们可能包含多个主题内容' }; + +export const Prompt_ExtractJson = `你可以从 "对话记录" 中提取指定信息，并返回一个 JSON 对象，JSON 对象要求： +1. JSON 对象仅包含字段说明中的值。 +2. 字段说明中的 required 决定 JSON 对象是否必须存在该字段。 +3. 必须存在的字段，值可以为空字符串或根据提取要求来设置，不能随机生成值。 + +提取要求: +""" +{{description}} +""" + +字段说明: +""" +{{json}} +""" + +对话记录: +""" +{{text}} +""" +`; + +export const Prompt_CQJson = `我会给你几个问题类型，请参考额外的背景知识（可能为空）和对话内容，判断我本次的问题类型，并返回对应类型的 ID，格式为 JSON 字符串: +""" +'{"type":"问题类型的 ID"}' +""" + +问题类型： +""" +{{typeList}} +""" + +额外背景知识: +""" +{{systemPrompt}} +""" + +对话内容： +""" +{{text}} +""" +`; diff --git a/client/src/service/events/pushBill.ts b/client/src/service/events/pushBill.ts index 6f1d7f9de..9a46aa405 100644 --- a/client/src/service/events/pushBill.ts +++ b/client/src/service/events/pushBill.ts @@ -20,40 +20,44 @@ export const pushTaskBill = async ({ shareId?: string; response: ChatHistoryItemResType[]; }) => { - const total = response.reduce((sum, item) => sum + item.price, 0); + try { + const total = response.reduce((sum, item) => sum + item.price, 0); - await Promise.allSettled([ - Bill.create({ - userId, - appName, - appId, - total, + await Promise.allSettled([ + Bill.create({ + userId, + appName, + appId, + total, + source, + list: response.map((item) => ({ + moduleName: item.moduleName, + amount: item.price || 0, + model: item.model, + tokenLen: item.tokens + })) + }), + User.findByIdAndUpdate(userId, { + $inc: { balance: -total } + }), + ...(shareId + ? [ + updateShareChatBill({ + shareId, + total + }) + ] + : []) + ]); + + addLog.info(`finish completions`, { source, - list: response.map((item) => ({ - moduleType: item.moduleType, - amount: item.price || 0, - model: item.model, - tokenLen: item.tokens - })) - }), - User.findByIdAndUpdate(userId, { - $inc: { balance: -total } - }), - ...(shareId - ? [ - updateShareChatBill({ - shareId, - total - }) - ] - : []) - ]); - - addLog.info(`finish completions`, { - source, - userId, - price: formatPrice(total) - }); + userId, + price: formatPrice(total) + }); + } catch (error) { + addLog.error(`pushTaskBill error`, error); + } }; export const updateShareChatBill = async ({ diff --git a/client/src/service/models/bill.ts b/client/src/service/models/bill.ts index e22745034..8f2d0a560 100644 --- a/client/src/service/models/bill.ts +++ b/client/src/service/models/bill.ts @@ -31,24 +31,7 @@ const BillSchema = new Schema({ default: BillSourceEnum.fastgpt }, list: { - type: [ - { - moduleName: { - type: String, - required: true - }, - amount: { - type: Number, - required: true - }, - model: { - type: String - }, - tokenLen: { - type: Number - } - } - ], + type: Array, default: [] } }); diff --git a/client/src/service/moduleDispatch/agent/classifyQuestion.ts b/client/src/service/moduleDispatch/agent/classifyQuestion.ts index daa3d85c7..09bd3b940 100644 --- a/client/src/service/moduleDispatch/agent/classifyQuestion.ts +++ b/client/src/service/moduleDispatch/agent/classifyQuestion.ts @@ -4,40 +4,69 @@ import type { ChatHistoryItemResType, ChatItemType } from '@/types/chat'; import { ChatRoleEnum, TaskResponseKeyEnum } from '@/constants/chat'; import { getAIChatApi, axiosConfig } from '@/service/lib/openai'; import type { ClassifyQuestionAgentItemType } from '@/types/app'; -import { countModelPrice } from '@/service/events/pushBill'; -import { getModel } from '@/service/utils/data'; import { SystemInputEnum } from '@/constants/app'; import { SpecialInputKeyEnum } from '@/constants/flow'; import { FlowModuleTypeEnum } from '@/constants/flow'; import { ModuleDispatchProps } from '@/types/core/modules'; +import { replaceVariable } from '@/utils/common/tools/text'; +import { Prompt_CQJson } from '@/prompts/core/agent'; -export type CQProps = ModuleDispatchProps<{ +type Props = ModuleDispatchProps<{ systemPrompt?: string; history?: ChatItemType[]; [SystemInputEnum.userChatInput]: string; [SpecialInputKeyEnum.agents]: ClassifyQuestionAgentItemType[]; }>; -export type CQResponse = { +type CQResponse = { [TaskResponseKeyEnum.responseData]: ChatHistoryItemResType; [key: string]: any; }; -const agentModel = 'gpt-3.5-turbo'; const agentFunName = 'agent_user_question'; -const maxTokens = 3000; /* request openai chat */ -export const dispatchClassifyQuestion = async (props: Record): Promise => { +export const dispatchClassifyQuestion = async (props: Props): Promise => { const { moduleName, userOpenaiAccount, - inputs: { agents, systemPrompt, history = [], userChatInput } - } = props as CQProps; + inputs: { agents, userChatInput } + } = props as Props; if (!userChatInput) { return Promise.reject('Input is empty'); } + const cqModel = global.cqModel; + + const { arg, tokens } = await (async () => { + if (cqModel.functionCall) { + return functionCall(props); + } + return completions(props); + })(); + + const result = agents.find((item) => item.key === arg?.type) || agents[0]; + + return { + [result.key]: 1, + [TaskResponseKeyEnum.responseData]: { + moduleType: FlowModuleTypeEnum.classifyQuestion, + moduleName, + price: userOpenaiAccount?.key ? 0 : cqModel.price * tokens, + model: cqModel.name || '', + tokens, + cqList: agents, + cqResult: result.value + } + }; +}; + +async function functionCall({ + userOpenaiAccount, + inputs: { agents, systemPrompt, history = [], userChatInput } +}: Props) { + const cqModel = global.cqModel; + const messages: ChatItemType[] = [ ...(systemPrompt ? [ @@ -55,14 +84,14 @@ export const dispatchClassifyQuestion = async (props: Record): Prom ]; const filterMessages = ChatContextFilter({ messages, - maxTokens + maxTokens: cqModel.maxToken }); const adaptMessages = adaptChat2GptMessages({ messages: filterMessages, reserveId: false }); // function body const agentFunction = { name: agentFunName, - description: '判断用户问题的类型属于哪方面，返回对应的枚举字段', + description: '判断用户问题的类型属于哪方面，返回对应的字段', parameters: { type: 'object', properties: { @@ -79,7 +108,7 @@ export const dispatchClassifyQuestion = async (props: Record): Prom const response = await chatAPI.createChatCompletion( { - model: agentModel, + model: cqModel.model, temperature: 0, messages: [...adaptMessages], function_call: { name: agentFunName }, @@ -92,20 +121,51 @@ export const dispatchClassifyQuestion = async (props: Record): Prom const arg = JSON.parse(response.data.choices?.[0]?.message?.function_call?.arguments || ''); - const tokens = response.data.usage?.total_tokens || 0; + return { + arg, + tokens: response.data.usage?.total_tokens || 0 + }; +} - const result = agents.find((item) => item.key === arg?.type) || agents[0]; +async function completions({ + userOpenaiAccount, + inputs: { agents, systemPrompt = '', history = [], userChatInput } +}: Props) { + const extractModel = global.extractModel; + + const messages: ChatItemType[] = [ + { + obj: ChatRoleEnum.Human, + value: replaceVariable(extractModel.prompt || Prompt_CQJson, { + systemPrompt, + typeList: agents.map((item) => `ID: "${item.key}", 问题类型:${item.value}`).join('\n'), + text: `${history.map((item) => `${item.obj}:${item.value}`).join('\n')} +Human:${userChatInput}` + }) + } + ]; + + const chatAPI = getAIChatApi(userOpenaiAccount); + + const { data } = await chatAPI.createChatCompletion( + { + model: extractModel.model, + temperature: 0.01, + messages: adaptChat2GptMessages({ messages, reserveId: false }), + stream: false + }, + { + timeout: 480000, + ...axiosConfig() + } + ); + const answer = data.choices?.[0].message?.content || ''; + const totalTokens = data.usage?.total_tokens || 0; + + const id = agents.find((item) => answer.includes(item.key))?.key || ''; return { - [result.key]: 1, - [TaskResponseKeyEnum.responseData]: { - moduleType: FlowModuleTypeEnum.classifyQuestion, - moduleName, - price: userOpenaiAccount?.key ? 0 : countModelPrice({ model: agentModel, tokens }), - model: getModel(agentModel)?.name || agentModel, - tokens, - cqList: agents, - cqResult: result.value - } + tokens: totalTokens, + arg: { type: id } }; -}; +} diff --git a/client/src/service/moduleDispatch/agent/extract.ts b/client/src/service/moduleDispatch/agent/extract.ts index 2d84ae3f1..0d3310926 100644 --- a/client/src/service/moduleDispatch/agent/extract.ts +++ b/client/src/service/moduleDispatch/agent/extract.ts @@ -5,36 +5,88 @@ import { ChatRoleEnum, TaskResponseKeyEnum } from '@/constants/chat'; import { getAIChatApi, axiosConfig } from '@/service/lib/openai'; import type { ContextExtractAgentItemType } from '@/types/app'; import { ContextExtractEnum } from '@/constants/flow/flowField'; -import { countModelPrice } from '@/service/events/pushBill'; -import { getModel } from '@/service/utils/data'; import { FlowModuleTypeEnum } from '@/constants/flow'; import { ModuleDispatchProps } from '@/types/core/modules'; +import { Prompt_ExtractJson } from '@/prompts/core/agent'; +import { replaceVariable } from '@/utils/common/tools/text'; -export type Props = ModuleDispatchProps<{ +type Props = ModuleDispatchProps<{ history?: ChatItemType[]; [ContextExtractEnum.content]: string; [ContextExtractEnum.extractKeys]: ContextExtractAgentItemType[]; [ContextExtractEnum.description]: string; }>; -export type Response = { +type Response = { [ContextExtractEnum.success]?: boolean; [ContextExtractEnum.failed]?: boolean; [ContextExtractEnum.fields]: string; [TaskResponseKeyEnum.responseData]: ChatHistoryItemResType; }; -const agentModel = 'gpt-3.5-turbo'; const agentFunName = 'agent_extract_data'; -const maxTokens = 4000; -export async function dispatchContentExtract({ - moduleName, - userOpenaiAccount, - inputs: { content, extractKeys, history = [], description } -}: Props): Promise { +export async function dispatchContentExtract(props: Props): Promise { + const { + moduleName, + userOpenaiAccount, + inputs: { content, description, extractKeys } + } = props; + if (!content) { return Promise.reject('Input is empty'); } + + const extractModel = global.extractModel; + + const { arg, tokens } = await (async () => { + if (extractModel.functionCall) { + return functionCall(props); + } + return completions(props); + })(); + + // remove invalid key + for (let key in arg) { + if (!extractKeys.find((item) => item.key === key)) { + delete arg[key]; + } + } + + // auth fields + let success = !extractKeys.find((item) => !arg[item.key]); + // auth empty value + if (success) { + for (const key in arg) { + if (arg[key] === '') { + success = false; + break; + } + } + } + + return { + [ContextExtractEnum.success]: success ? true : undefined, + [ContextExtractEnum.failed]: success ? undefined : true, + [ContextExtractEnum.fields]: JSON.stringify(arg), + ...arg, + [TaskResponseKeyEnum.responseData]: { + moduleType: FlowModuleTypeEnum.contentExtract, + moduleName, + price: userOpenaiAccount?.key ? 0 : extractModel.price * tokens, + model: extractModel.name || '', + tokens, + extractDescription: description, + extractResult: arg + } + }; +} + +async function functionCall({ + userOpenaiAccount, + inputs: { history = [], content, extractKeys, description } +}: Props) { + const extractModel = global.extractModel; + const messages: ChatItemType[] = [ ...history, { @@ -44,7 +96,7 @@ export async function dispatchContentExtract({ ]; const filterMessages = ChatContextFilter({ messages, - maxTokens + maxTokens: extractModel.maxToken }); const adaptMessages = adaptChat2GptMessages({ messages: filterMessages, reserveId: false }); @@ -77,7 +129,7 @@ export async function dispatchContentExtract({ const response = await chatAPI.createChatCompletion( { - model: agentModel, + model: extractModel.model, temperature: 0, messages: [...adaptMessages], function_call: { name: agentFunName }, @@ -96,33 +148,79 @@ export async function dispatchContentExtract({ } })(); - // auth fields - let success = !extractKeys.find((item) => !arg[item.key]); - // auth empty value - if (success) { - for (const key in arg) { - if (arg[key] === '') { - success = false; - break; - } - } - } - const tokens = response.data.usage?.total_tokens || 0; - return { - [ContextExtractEnum.success]: success ? true : undefined, - [ContextExtractEnum.failed]: success ? undefined : true, - [ContextExtractEnum.fields]: JSON.stringify(arg), - ...arg, - [TaskResponseKeyEnum.responseData]: { - moduleType: FlowModuleTypeEnum.contentExtract, - moduleName, - price: userOpenaiAccount?.key ? 0 : countModelPrice({ model: agentModel, tokens }), - model: getModel(agentModel)?.name || agentModel, - tokens, - extractDescription: description, - extractResult: arg - } + tokens, + arg }; } + +async function completions({ + userOpenaiAccount, + inputs: { history = [], content, extractKeys, description } +}: Props) { + const extractModel = global.extractModel; + + const messages: ChatItemType[] = [ + { + obj: ChatRoleEnum.Human, + value: replaceVariable(extractModel.prompt || Prompt_ExtractJson, { + description, + json: extractKeys + .map( + (item) => + `key="${item.key}"，描述="${item.desc}"，required="${ + item.required ? 'true' : 'false' + }"` + ) + .join('\n'), + text: `${history.map((item) => `${item.obj}:${item.value}`).join('\n')} +Human: ${content}` + }) + } + ]; + + const chatAPI = getAIChatApi(userOpenaiAccount); + + const { data } = await chatAPI.createChatCompletion( + { + model: extractModel.model, + temperature: 0.01, + messages: adaptChat2GptMessages({ messages, reserveId: false }), + stream: false + }, + { + timeout: 480000, + ...axiosConfig() + } + ); + const answer = data.choices?.[0].message?.content || ''; + const totalTokens = data.usage?.total_tokens || 0; + + // parse response + const start = answer.indexOf('{'); + const end = answer.lastIndexOf('}'); + + if (start === -1 || end === -1) + return { + tokens: totalTokens, + arg: {} + }; + + const jsonStr = answer + .substring(start, end + 1) + .replace(/(\\n|\\)/g, '') + .replace(/ /g, ''); + + try { + return { + tokens: totalTokens, + arg: JSON.parse(jsonStr) as Record + }; + } catch (error) { + return { + tokens: totalTokens, + arg: {} + }; + } +} diff --git a/client/src/service/utils/data.ts b/client/src/service/utils/data.ts index 62768dad6..db177e468 100644 --- a/client/src/service/utils/data.ts +++ b/client/src/service/utils/data.ts @@ -14,5 +14,11 @@ export const getVectorModel = (model?: string) => { }; export const getModel = (model?: string) => { - return [...global.chatModels, ...global.vectorModels].find((item) => item.model === model); + return [ + ...global.chatModels, + ...global.vectorModels, + global.qaModel, + global.extractModel, + global.cqModel + ].find((item) => item.model === model); }; diff --git a/client/src/types/index.d.ts b/client/src/types/index.d.ts index 5e2d2bfc3..cc0513754 100644 --- a/client/src/types/index.d.ts +++ b/client/src/types/index.d.ts @@ -3,7 +3,12 @@ import type { Agent } from 'http'; import type { Pool } from 'pg'; import type { Tiktoken } from 'js-tiktoken'; import type { Logger } from 'winston'; -import { ChatModelItemType, QAModelItemType, VectorModelItemType } from './model'; +import { + ChatModelItemType, + FunctionModelItemType, + QAModelItemType, + VectorModelItemType +} from './model'; import { TrackEventName } from '@/constants/common'; export type PagingData = { @@ -62,6 +67,8 @@ declare global { var systemEnv: SystemEnvType; var chatModels: ChatModelItemType[]; var qaModel: QAModelItemType; + var extractModel: FunctionModelItemType; + var cqModel: FunctionModelItemType; var vectorModels: VectorModelItemType[]; var systemVersion: string; diff --git a/client/src/types/model.d.ts b/client/src/types/model.d.ts index 1a23bbc60..9bb729a6f 100644 --- a/client/src/types/model.d.ts +++ b/client/src/types/model.d.ts @@ -21,3 +21,11 @@ export type VectorModelItemType = { price: number; maxToken: number; }; +export type FunctionModelItemType = { + model: string; + name: string; + maxToken: number; + price: number; + prompt: string; + functionCall: boolean; +};