敏感内容审查

{    "point": "app.moderation.input", // 扩展点类型，此处固定为 app.moderation.input    "params": {        "app_id": string,  // 应用 ID        "inputs": {  // 终端用户传入变量值，key 为变量名，value 为变量值            "var_1": "value_1",            "var_2": "value_2",            ...        },        "query": string | null  // 终端用户当前对话输入内容，对话型应用固定参数。    }}

{    "point": "app.moderation.input",    "params": {        "app_id": "61248ab4-1125-45be-ae32-0ce91334d021",        "inputs": {            "var_1": "我的身份证号是 123456789012345678。",            "var_2": "我的手机号是 123-4567-8901。"        },        "query": "请帮我更新账户信息。"    }}

{    "flagged": bool,  // 是否违反校验规则    "action": string, // 动作，direct_output 直接输出预设回答; overridden 覆写传入变量值    "preset_response": string,  // 预设回答（仅当 action=direct_output 返回）    "inputs": {  // 终端用户传入变量值，key 为变量名，value 为变量值（仅当 action=overridden 返回）        "var_1": "value_1",        "var_2": "value_2",        ...    },    "query": string | null  // 覆写的终端用户当前对话输入内容，对话型应用固定参数。（仅当 action=overridden 返回）}

{    "point": "app.moderation.output", // 扩展点类型，此处固定为 app.moderation.output    "params": {        "app_id": string,  // 应用 ID        "text": string  // LLM 回答内容。当 LLM 输出为流式时，此处为 100 字为一个分段的内容。    }}

{    "point": "app.moderation.output",    "params": {        "app_id": "61248ab4-1125-45be-ae32-0ce91334d021",        "text": "我的身份证号是 123456789012345678。"    }}

{    "flagged": bool,  // 是否违反校验规则    "action": string, // 动作，direct_output 直接输出预设回答; overridden 覆写传入变量值    "preset_response": string,  // 预设回答（仅当 action=direct_output 返回）    "text": string  // 覆写的 LLM 回答内容。（仅当 action=overridden 返回）}

import { Hono } from "hono";import { bearerAuth } from "hono/bearer-auth";import { z } from "zod";import { zValidator } from "@hono/zod-validator";import { generateSchema } from '@anatine/zod-openapi';type Bindings = {  TOKEN: string;};const app = new Hono<{ Bindings: Bindings }>();// API 格式校验 ⬇️const schema = z.object({  point: z.union([    z.literal("ping"),    z.literal("app.external_data_tool.query"),    z.literal("app.moderation.input"),    z.literal("app.moderation.output"),  ]), // Restricts 'point' to two specific values  params: z    .object({      app_id: z.string().optional(),      tool_variable: z.string().optional(),      inputs: z.record(z.any()).optional(),      query: z.any(),      text: z.any()    })    .optional(),});// Generate OpenAPI schemaapp.get("/", (c) => {  return c.json(generateSchema(schema));});app.post(  "/",  (c, next) => {    const auth = bearerAuth({ token: c.env.TOKEN });    return auth(c, next);  },  zValidator("json", schema),  async (c) => {    const { point, params } = c.req.valid("json");    if (point === "ping") {      return c.json({        result: "pong",      });    }    // ⬇️ impliment your logic here ⬇️    // point === "app.external_data_tool.query"    else if (point === "app.moderation.input"){    // 输入检查 ⬇️    const inputkeywords = ["输入过滤测试1", "输入过滤测试2", "输入过滤测试3"];    if (inputkeywords.some(keyword => params.query.includes(keyword)))       {      return c.json({        "flagged": true,        "action": "direct_output",        "preset_response": "输入存在违法内容，请换个问题再试！"      });    } else {      return c.json({        "flagged": false,        "action": "direct_output",        "preset_response": "输入无异常"      });    }    // 输入检查完毕     }        else {      // 输出检查 ⬇️      const outputkeywords = ["输出过滤测试1", "输出过滤测试2", "输出过滤测试3"];   if (outputkeywords.some(keyword => params.text.includes(keyword)))     {      return c.json({        "flagged": true,        "action": "direct_output",        "preset_response": "输出存在敏感内容，已被系统过滤，请换个问题再问！"      });    }    else {    return c.json({      "flagged": false,      "action": "direct_output",      "preset_response": "输出无异常"    });  };    }    // 输出检查完毕   });export default app;