Merge pull request #109 from FYP-2024-IQMA/SCRUM-164-Update-feedback-…

…details-to-S3

Scrum 164 update feedback details to s3

backend/src/app.ts

@@ -16,6 +16,8 @@ import quizRouter from "./routes/quizRouter";
 import resultRouter from "./routes/resultRouter";
 import sectionRouter from "./routes/sectionRouter";
 import unitRouter from "./routes/unitRouter";
+import accountsGamificationRouter from "./routes/accountsGamificationRouter";
+import feedbackRouter from "./routes/feedbackRouter";
 
 const app = express();
 const port = 3000;
@@ -40,6 +42,7 @@ app.use("/lesson", lessonRouter);
 app.use("/section", sectionRouter);
 app.use("/clickstream", clickstreamRouter);
 app.use("/accounts", accountsGamificationRouter);
+app.use("/feedback", feedbackRouter);
 
 // Start the Express server
 app.listen(port, () => {

backend/src/chatbot/app.py

@@ -57,38 +57,38 @@ async def generate_text(prompt: Prompt):
 
 # @app.post("/langchain")
 # async def langchain_text(prompt: Prompt):
-#     """
-#     Generate a response from Agent-integrated chain based on the role and prompt.
-#     """
-#     logger.info("Endpoint '/langchain' has been called with prompt: %s", prompt)
-#     try:
-#         # llm = ChatOpenAI(
-#         #     model="gpt-4o-mini",
-#         #     api_key=os.environ.get("OPENAI_API_KEY"),
-#         # )
-#         config = {
-#                 "configurable": {
-#                     "session_id": "abc123",
-#                 }
-#             }
-#         if prompt.history:
-#             # format response for langchain
-#             langchain_format = convert_openai_messages(prompt.history)
-#             logger.info("Converted langchain messages: %s", langchain_format)
-#             input = {
-#                 "input": prompt.content, 
-#                 "history": langchain_format,
-#             }
-#             response = full_chain_w_history.invoke(input, config=config)
-#         else:
-#             langchain_format = convert_openai_messages([{"role": prompt.role, "content": prompt.content}])
-#             logger.info("Converted langchain messages: %s", langchain_format)
-#             input = {
-#                 "input": prompt.content,
-#                 "history": langchain_format,
-#             }
-#             logger.info("Prompt: %s", prompt)
-#             response = full_chain_w_history.invoke({"input": input}, config=config)
+    # """
+    # Generate a response from Agent-integrated chain based on the role and prompt.
+    # """
+    # logger.info("Endpoint '/langchain' has been called with prompt: %s", prompt)
+    # try:
+    #     # llm = ChatOpenAI(
+    #     #     model="gpt-4o-mini",
+    #     #     api_key=os.environ.get("OPENAI_API_KEY"),
+    #     # )
+    #     config = {
+    #             "configurable": {
+    #                 "session_id": "abc123",
+    #             }
+    #         }
+    #     if prompt.history:
+    #         # format response for langchain
+    #         langchain_format = convert_openai_messages(prompt.history)
+    #         logger.info("Converted langchain messages: %s", langchain_format)
+    #         input = {
+    #             "input": prompt.content, 
+    #             "history": langchain_format,
+    #         }
+    #         response = full_chain_w_history.invoke(input, config=config)
+    #     else:
+    #         langchain_format = convert_openai_messages([{"role": prompt.role, "content": prompt.content}])
+    #         logger.info("Converted langchain messages: %s", langchain_format)
+    #         input = {
+    #             "input": prompt.content,
+    #             "history": langchain_format,
+    #         }
+    #         logger.info("Prompt: %s", prompt)
+    #         response = full_chain_w_history.invoke({"input": input}, config=config)
 
 #         return {
 #             "role": "assistant",

backend/src/chatbot/requirements.txt

@@ -1,3 +1,4 @@
+# chromadb
 fastapi
 # langchain
 # langchain-chroma

backend/src/controllers/feedbackController.ts

@@ -0,0 +1,17 @@
+import { Request, Response } from "express";
+import * as feedbackService from "../services/feedbackService";
+import handleError from "../errors/errorHandling";
+
+export const sendFeedback = async (req: Request, res: Response) => {
+    const messageBody = req.body;
+
+    try {
+        const message = await feedbackService.sendMessage(messageBody);
+        res.status(200).json({ message: 'Published message successfully' });
+    } catch (error: any) {
+        const errorResponse = handleError(error);
+        if (errorResponse) {
+            res.status(errorResponse.status).json(errorResponse);
+        }
+    }
+}

backend/src/models/feedbackModel.ts

@@ -0,0 +1,7 @@
+export interface Feedback {
+    userID: string;
+    timestamp: Date;
+    eventType: "feedback" | "bug" | "sugestion";
+    rating: number;
+    message: string;
+}

backend/src/rabbitmq/rabbitmq_logs.json

@@ -0,0 +1,17 @@
+[
+	{
+		"timeTaken": 1818
+	},
+	{
+		"timeTaken": 1718
+	},
+	{
+		"feedback": 1618
+	},
+	{
+		"bug": 1518
+	},
+	{
+		"suggestion": 1418
+	}
+]

backend/src/routes/feedbackRouter.ts

@@ -0,0 +1,9 @@
+import * as feedbackController from '../controllers/feedbackController';
+import { Router } from 'express';
+import verifyToken from '../middleware/authMiddleware';
+
+const router = Router();
+
+router.post('/sendFeedback', verifyToken, feedbackController.sendFeedback);
+
+export default router;

backend/src/services/feedbackService.ts

@@ -0,0 +1,78 @@
+import amqp from "amqplib";
+import { Feedback } from "../models/feedbackModel";
+import { s3 } from "../config/awsConfig"; // Assuming you already have an AWS config for S3
+
+// Create upload function
+async function uploadToS3(queue: string, newFeedback: Feedback) {
+	const key = `${queue}/${newFeedback.userID}.json`;
+	const params = {
+		Bucket: "isb-raw-data-athena",
+		Key: key,
+	};
+	let existingFeedback: any[] = [];
+
+	try {
+		const existingData = await s3.getObject(params).promise();
+		let fileContent = existingData.Body!.toString("utf-8");
+		existingFeedback = fileContent
+			.split("\n")
+			.filter((line: string) => line.trim().length > 0)
+			.map((line: string) => JSON.parse(line));
+	} catch (error: any) {
+		if (error.code === "NoSuchKey") {
+			console.log("Creating new file");
+		} else {
+			console.error("Error uploading to S3", error);
+		}
+	}
+
+	existingFeedback.push(newFeedback);
+	const lineDelimitedJson = existingFeedback
+		.map((item) => JSON.stringify(item))
+		.join("\n");
+	s3.putObject({
+		...params,
+		Body: lineDelimitedJson,
+		ContentType: "application/json",
+	}).promise();
+}
+
+// Define your queues (you can add more if necessary)
+const QUEUE_NAMES = ["feedback", "bug", "suggestion"];
+
+// Create a function to consume messages
+async function consumeMessage() {
+    try {
+        const conn = await amqp.connect(process.env.RABBITMQ_URL!);
+        const channel = await conn.createChannel();
+
+        for (const queue of QUEUE_NAMES) {
+            await channel.assertQueue(queue);
+            channel.consume(queue, async (message) => {
+                if (message !== null) {
+                    const data = message.content.toString();
+                    let parsedData: Feedback = JSON.parse(data);
+                    try {
+                        await uploadToS3(queue, parsedData);
+                        channel.ack(message);
+                        console.log(message)
+                    } catch (error) {
+                        console.error(`Error processing message from ${QUEUE_NAMES[0]}: `, error);
+                        channel.nack(message);
+                    }
+                }
+            })
+        }
+    } catch (err) {
+        console.error(`Error: ${err}`);
+    }
+}
+
+export async function sendMessage(feedback: Feedback) {
+    const queue = feedback.eventType;
+    const conn = await amqp.connect(process.env.RABBITMQ_URL!);
+    const channel = await conn.createChannel();
+    await channel.assertQueue(queue);
+    channel.sendToQueue(queue, Buffer.from(JSON.stringify(feedback)));
+    await consumeMessage();
+}

frontend/iQMA-Skills-Builder/app/screens/Home.tsx

@@ -21,13 +21,15 @@ import React, {useEffect, useRef, useState} from 'react';
 import AsyncStorage from '@react-native-async-storage/async-storage';
 import {AuthContext} from '@/context/AuthContext';
 import {Colors} from '@/constants/Colors';
+import FeedbackComponent from '@/components/Feedback';
 import {Ionicons} from '@expo/vector-icons';
 import {LoadingIndicator} from '@/components/LoadingIndicator';
 import {SafeAreaView} from 'react-native-safe-area-context';
 import SectionCard from '@/components/SectionCard';
 import TopStats from '@/components/TopStats';
 import {router} from 'expo-router';
 import {useContext} from 'react';
+import { packageFeedback } from '@/helpers/feedbackEndpoints';
 import { globalStyles } from '@/constants/styles';
 
 const HomeScreen: React.FC = () => {
@@ -465,6 +467,7 @@ const HomeScreen: React.FC = () => {
                     <Ionicons name="arrow-up" size={24} color="#7654F2" />
                 </TouchableOpacity>
             )}
+            <FeedbackComponent userID={currentUser.sub}/>
         </SafeAreaView>
     );
 };