Merge pull request #2 from senacor/feature/add-schema-validation

Feature/add schema validation

package.json

@@ -2,12 +2,12 @@
   "name": "chatbot-poc-backend",
   "version": "1.0.0",
   "description": "",
-  "main": "./dist/index.js",
+  "main": "./dist/app.js",
   "type": "module",
   "scripts": {
-    "dev": "nodemon -r dotenv/config --exec node --loader ts-node/esm src/index.ts",
+    "dev": "nodemon -r dotenv/config --exec node --loader ts-node/esm src/app.ts",
     "build": "rimraf ./dist && tsc",
-    "start": "npm run build && node dist/index.js"
+    "start": "npm run build && node dist/app.js"
   },
   "repository": {
     "type": "git",
@@ -24,7 +24,8 @@
     "dotenv": "^16.4.5",
     "express": "^4.18.3",
     "officeparser": "^4.0.8",
-    "openai": "^4.29.2"
+    "openai": "^4.29.2",
+    "zod": "^3.22.4"
   },
   "devDependencies": {
     "@tsconfig/strictest": "^2.0.3",

src/app.ts

@@ -0,0 +1,14 @@
+import "dotenv/config";
+import express from "express";
+import { registerRoutes } from "./index.js";
+
+const app = express();
+const port = process.env["PORT"] || 3000;
+
+app.listen(port, () =>{
+    console.log(`Server is running at http://localhost:${port}`);
+    registerRoutes();
+})
+
+
+export { app };

src/chat/get-init.ts

@@ -0,0 +1,59 @@
+import { z } from "zod";
+import { makeGetEndpoint } from "../middleware/validation/makeGetEndpoint.js";
+import { fileReader, parseFileReaderResponse } from "../util/fileReader.js";
+import { OPENAI_MODEL, PROMPT_FILE_NAME, RESPONSE_FORMAT, openai } from "./index.js";
+
+//TODO: Rework type inference of fileReader
+export const init = makeGetEndpoint(z.any(), async (_request, response) => {
+    let messages: string[] = []
+    const promptFile = await fileReader(PROMPT_FILE_NAME);
+    let jsonPrompt;
+
+    if(RESPONSE_FORMAT.type === "json_object"){
+
+        jsonPrompt = await fileReader('json-format-prompt.docx');
+        if(parseFileReaderResponse(jsonPrompt)){
+            messages.push(jsonPrompt.content);
+        }
+        else{
+            return response.status(500).send({
+                status: 500,
+                message: jsonPrompt.error
+            })
+        }
+    }
+
+    if(parseFileReaderResponse(promptFile)){
+        messages.push(promptFile.content);
+    }
+    else{
+        return response.status(500).send({
+            status: 500,
+            message: promptFile.error
+        })
+    }
+
+
+    const completion = await openai.chat.completions.create({
+        messages: messages.map(message => ({role: "system", content: message})),
+        model: OPENAI_MODEL,
+        response_format: RESPONSE_FORMAT
+    });
+    console.log(completion.choices[0]?.message);
+    return response
+        .status(200)
+        .send([
+        {
+            role: "system", 
+            content: promptFile.content
+        },
+        {
+            role: "system",
+            content: jsonPrompt?.content !== undefined ? jsonPrompt.content : ""
+        },
+        {
+            role: "assistant",
+            content: "Hi, ich bin der virtuelle Assistent von Qonto und kann alles rund um Qonto und unsere Leistungen beantworten. Bitte fragen Sie mich etwas"
+        }
+    ]);
+});

src/chat/index.ts

@@ -1,59 +1,32 @@
-import express, { Request, Response} from "express";
+import express from "express";
 import "dotenv/config";
 import OpenAI from "openai";
-import { ChatCompletionCreateParamsBase } from "openai/resources/chat/completions.js";
-import { fileReader, hasErrors } from "../util/fileReader.js";
+import { ChatCompletionCreateParams, ChatCompletionCreateParamsBase } from "openai/resources/chat/completions.js";
+import { init } from "./get-init.js";
+import { newMessage } from "./post-new-message.js";
 
+/**
+ * Change the prompt file, the model or the response format here
+ */
 const PROMPT_FILE_NAME = "Chatbot Qonto.docx"
 const OPENAI_MODEL: ChatCompletionCreateParamsBase["model"] = "gpt-3.5-turbo";
+const RESPONSE_FORMAT: ChatCompletionCreateParams.ResponseFormat = {type: "text"};
 
-export const chatRouter = express.Router();
-
-export const openai = new OpenAI();
-
-
-chatRouter.post('/newMessage', async (request: Request, response: Response) => {
-    const messages = request.body.messages;
-    const completion = await openai.chat.completions.create({
-        messages: messages,
-        model: OPENAI_MODEL,
-    });
-    const choice = completion.choices[0];
-    if(choice === undefined){
-        response.status(500).send({
-            status: 500,
-            message: "Expected an answer from the bot but got none."
-        })
-    }
-    else{
-        response.status(200).send(choice.message);
-    }
-});
-
-chatRouter.get('/init', async (_request: Request, response: Response) => {
-    const fileContent = await fileReader(PROMPT_FILE_NAME);
-    if(hasErrors(fileContent)){
-        console.log(fileContent.error.stack);
-        response.status(500).json({
-            status: 500,
-            message: 'Something went wrong'
-        });
-    }
-    else{
-        await openai.chat.completions.create({
-            messages: [{role: "system", content: fileContent.data}],
-            model: OPENAI_MODEL,
-        });
-        response.status(200).send([
-            {
-                role: "system", 
-                content: fileContent.data
-            },
-            {
-                role: "assistant",
-                content: "Hi, ich bin der virtuelle Assistent von Qonto und kann alles rund um Qonto und unsere Leistungen beantworten. Bitte fragen Sie mich etwas"
-            }
-        ]);
-    }
-});
 
+const chatRouter = express.Router();
+const openai = new OpenAI();
+
+
+chatRouter.post('/newMessage', newMessage);
+chatRouter.get("/test")
+
+chatRouter.get('/init', init);
+
+
+export { 
+    PROMPT_FILE_NAME, 
+    OPENAI_MODEL,
+    RESPONSE_FORMAT,
+    chatRouter,
+    openai,
+}

src/chat/post-new-message.ts

@@ -0,0 +1,31 @@
+import { z } from "zod";
+import { makePostEndpoint } from "../middleware/validation/makePostEndpoint.js";
+import { OPENAI_MODEL, RESPONSE_FORMAT, openai } from "./index.js";
+
+const ChatCompletionRole = z.union([z.literal('user'), z.literal('system'), z.literal('assistant')]);
+export type ChatCompletionRole = z.infer<typeof ChatCompletionRole>;
+
+const MessageHistory = z.object({
+    messages: z.array(
+        z.object({
+            role: ChatCompletionRole,
+            content: z.string(),
+        })
+    ).nonempty()
+});
+type MessageHistory = z.infer<typeof MessageHistory>;
+
+export const newMessage = makePostEndpoint(MessageHistory, async (request, response) => {
+    const messages = request.body.messages;
+    const completion = await openai.chat.completions.create({
+        messages,
+        model: OPENAI_MODEL,
+        response_format: RESPONSE_FORMAT
+    });
+    const chatResponse = completion.choices[0];
+    if(!chatResponse){
+        return response.status(500).send("Got no response from the bot");
+    }
+    console.log(chatResponse);
+    return response.status(200).send(chatResponse.message);
+});

src/index.ts

@@ -1,26 +1,21 @@
-import "dotenv/config";
-import express, { Request, Response } from "express";
-import cors from "cors";
+import express from "express";
 import { chatRouter } from "./chat/index.js";
-
-const app = express();
-const port = process.env["PORT"] || 3000;
+import { app } from "./app.js";
+import cors from "cors";
 
 
 const corsOptions = {
     origin: ["http://localhost:4200", "https://chatbot-frontend-csf37hag2a-ey.a.run.app"],
     optionsSuccessStatus: 204
 }
 
-app.options('*', cors(corsOptions));
-app.use(cors(corsOptions));
-app.use(express.json());
-
-app.use('/chat', chatRouter);
-app.get("/", (_: Request, response: Response) => {
-    response.status(200).json({message: "Hello World, running in Container"});
-})
+export const registerRoutes = () => {
+    app.options('*', cors(corsOptions));
+    app.use(cors(corsOptions));
+
+
+    app.use(express.json());
+
+    app.use('/chat', chatRouter);
+}
 
-app.listen(port, () =>{
-    console.log(`Server is running at http://localhost:${port}`);
-})

src/middleware/validation/makeGetEndpoint.ts

@@ -0,0 +1,22 @@
+import { Request, Response } from "express"
+import { z } from "zod"
+
+export const makeGetEndpoint = <TQuery>(
+    schema: z.Schema<TQuery>,
+    callback: (
+        req: Request<any, any, any, TQuery>,
+        res: Response
+    ) => void
+) => (req:Request, res:Response) => {
+
+    const bodyValidation = schema.safeParse(req.query);
+    if(!bodyValidation.success){
+        return res
+            .status(400)
+            .send({
+                status: 400,
+                message: bodyValidation.error.message
+            });
+    }
+    return callback(req as any, res);
+}

src/middleware/validation/makePostEndpoint.ts

@@ -0,0 +1,22 @@
+import { Request, Response } from "express"
+import { z } from "zod"
+
+export const makePostEndpoint = <TBody>(
+    schema: z.Schema<TBody>,
+    callback: (
+        req: Request<any, any, TBody, any>,
+        res: Response
+    ) => void
+) => (req:Request, res:Response) => {
+
+    const bodyValidation = schema.safeParse(req.body);
+    if(!bodyValidation.success){
+        return res
+            .status(400)
+            .send({
+                status: 400,
+                message: bodyValidation.error.message
+            });
+    }
+    return callback(req, res);
+}