abearxiong
66a19139b7
- Add agent-run module to handle AI interactions with tools and messages. - Create routes for proxying requests to OpenAI and Anthropic APIs. - Implement flowme-life chat route for user queries and task management. - Add services for retrieving and updating life records in the database. - Implement logic for fetching today's tasks and marking tasks as done with next execution time calculation. - Introduce tests for flowme-life functionalities.
66 lines
2.5 KiB
TypeScript
66 lines
2.5 KiB
TypeScript
import { type QueryRouterServer, type App, type RouteInfo } from '@kevisual/router'
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import { generateText, tool, type ModelMessage, type LanguageModel, type GenerateTextResult } from 'ai';
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import z from 'zod';
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import { filter } from '@kevisual/js-filter'
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export const createTool = async (app: QueryRouterServer | App, message: { path: string, key: string, token?: string }) => {
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const route = app.findRoute({ path: message.path, key: message.key });
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if (!route) {
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console.error(`未找到路径 ${message.path} 和 key ${message.key} 的路由`);
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return null;
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}
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const _tool = tool({
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description: route?.metadata?.summary || route?.description || '无描述',
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inputSchema: z.object({
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...route.metadata?.args
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}), // 这里可以根据实际需要定义输入参数的 schema
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execute: async (args: any) => {
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const res = await app.run({ path: message.path, key: message.key, payload: args, token: message.token });
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return res;
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}
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});
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return _tool;
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}
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export const createTools = async (opts: { app: QueryRouterServer | App, token?: string }) => {
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const { app, token } = opts;
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const tools: Record<string, any> = {};
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for (const route of app.routes) {
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const id = route.id!;
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const _tool = await createTool(app, { path: route.path!, key: route.key!, token });
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if (_tool && id) {
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tools[id] = _tool;
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}
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}
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return tools;
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}
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type Route = Partial<RouteInfo>
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type AgentResult = {
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result: GenerateTextResult<Record<string, any>, any>,
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messages: ModelMessage[],
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}
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export const reCallAgent = async (opts: { messages?: ModelMessage[], tools?: Record<string, any>, languageModel: LanguageModel }): Promise<AgentResult> => {
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const { messages = [], tools = {}, languageModel } = opts;
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const result = await generateText({
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model: languageModel,
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messages,
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tools,
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});
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const step = result.steps[0]!;
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if (step.finishReason === 'tool-calls') {
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messages.push(...result.response.messages);
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return reCallAgent({ messages, tools, languageModel });
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}
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return { result, messages };
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}
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export const runAgent = async (opts: { app: QueryRouterServer | App, messages?: ModelMessage[], routes?: Route[], query?: string, languageModel: LanguageModel, token: string }) => {
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const { app, languageModel } = opts;
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let messages = opts.messages || [];
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let routes = opts?.routes || app.routes;
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if (opts.query) {
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routes = filter(routes, opts.query);
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};
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const tools = await createTools({ app, token: opts.token });
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return await reCallAgent({ messages, tools, languageModel });
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}
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