monorepo packages (#344)

projects/app/src/service/moduleDispatch/agent/classifyQuestion.ts

@@ -0,0 +1,172 @@
+import { adaptChat2GptMessages } from '@/utils/common/adapt/message';
+import { ChatContextFilter } from '@/service/common/tiktoken';
+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 { 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';
+import { defaultCQModel } from '@/pages/api/system/getInitData';
+
+type Props = ModuleDispatchProps<{
+  systemPrompt?: string;
+  history?: ChatItemType[];
+  [SystemInputEnum.userChatInput]: string;
+  [SpecialInputKeyEnum.agents]: ClassifyQuestionAgentItemType[];
+}>;
+type CQResponse = {
+  [TaskResponseKeyEnum.responseData]: ChatHistoryItemResType;
+  [key: string]: any;
+};
+
+const agentFunName = 'agent_user_question';
+
+/* request openai chat */
+export const dispatchClassifyQuestion = async (props: Props): Promise<CQResponse> => {
+  const {
+    moduleName,
+    userOpenaiAccount,
+    inputs: { agents, userChatInput }
+  } = props as Props;
+
+  if (!userChatInput) {
+    return Promise.reject('Input is empty');
+  }
+
+  const cqModel = global.cqModel || defaultCQModel;
+
+  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
+      ? [
+          {
+            obj: ChatRoleEnum.System,
+            value: systemPrompt
+          }
+        ]
+      : []),
+    ...history,
+    {
+      obj: ChatRoleEnum.Human,
+      value: userChatInput
+    }
+  ];
+  const filterMessages = ChatContextFilter({
+    messages,
+    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，返回对应的字段',
+    parameters: {
+      type: 'object',
+      properties: {
+        type: {
+          type: 'string',
+          description: agents.map((item) => `${item.value}，返回：'${item.key}'`).join('；'),
+          enum: agents.map((item) => item.key)
+        }
+      },
+      required: ['type']
+    }
+  };
+  const chatAPI = getAIChatApi(userOpenaiAccount);
+
+  const response = await chatAPI.createChatCompletion(
+    {
+      model: cqModel.model,
+      temperature: 0,
+      messages: [...adaptMessages],
+      function_call: { name: agentFunName },
+      functions: [agentFunction]
+    },
+    {
+      ...axiosConfig(userOpenaiAccount)
+    }
+  );
+
+  const arg = JSON.parse(response.data.choices?.[0]?.message?.function_call?.arguments || '');
+
+  return {
+    arg,
+    tokens: response.data.usage?.total_tokens || 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(userOpenaiAccount)
+    }
+  );
+  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 {
+    tokens: totalTokens,
+    arg: { type: id }
+  };
+}