Merge branch 'Back-end' into Back-Ana

.github/workflows/build.yml

@@ -1,5 +1,6 @@
 name: Build
 on:
+  workflow_dispatch:
   push:
     branches:
       - master

.github/workflows/release.yml

@@ -16,7 +16,7 @@ jobs:
     - run: npm --prefix users/userservice ci
     - run: npm --prefix llmservice ci
     - run: npm --prefix gatewayservice ci
-    - run: npm --prefix webapp ci
+    - run: npm --prefix webapp ci --legacy-peer-deps
     - run: npm --prefix users/authservice test -- --coverage
     - run: npm --prefix users/userservice test -- --coverage
     - run: npm --prefix llmservice test -- --coverage
@@ -54,14 +54,13 @@ jobs:
       uses: elgohr/Publish-Docker-Github-Action@v5
       env:
         API_URI: http://${{ secrets.DEPLOY_HOST }}:8000
-        LLM_API_KEY: ${{ secrets.LLM_API_KEY }}
       with:
           name: arquisoft/wichat_es4a/webapp
           username: ${{ github.actor }}
           password: ${{ secrets.GITHUB_TOKEN }}
           registry: ghcr.io
           workdir: webapp
-          buildargs: API_URI,LLM_API_KEY
+          buildargs: API_URI
   docker-push-authservice:
     name: Push auth service Docker Image to GitHub Packages
     runs-on: ubuntu-latest
@@ -140,18 +139,18 @@ jobs:
         password: ${{ secrets.GITHUB_TOKEN }}
         registry: ghcr.io
         workdir: gatewayservice
-  # deploy:
-  #   name: Deploy over SSH
-  #   runs-on: ubuntu-latest
-  #   needs: [docker-push-userservice,docker-push-authservice,docker-push-llmservice,docker-push-gatewayservice,docker-push-webapp]
-  #   steps:
-  #   - name: Deploy over SSH
-  #     uses: fifsky/ssh-action@master
-  #     with:
-  #       host: ${{ secrets.DEPLOY_HOST }}
-  #       user: ${{ secrets.DEPLOY_USER }}
-  #       key: ${{ secrets.DEPLOY_KEY }}
-  #       command: |
-  #         wget https://raw.githubusercontent.com/arquisoft/wichat_es4a/master/docker-compose.yml -O docker-compose.yml
-  #         docker compose --profile prod down
-  #         docker compose --profile prod up -d --pull always
+  deploy:
+    name: Deploy over SSH
+    runs-on: ubuntu-latest
+    needs: [docker-push-userservice,docker-push-authservice,docker-push-llmservice,docker-push-gatewayservice,docker-push-webapp]
+    steps:
+    - name: Deploy over SSH
+      uses: fifsky/ssh-action@master
+      with:
+        host: ${{ secrets.DEPLOY_HOST }}
+        user: ${{ secrets.DEPLOY_USER }}
+        key: ${{ secrets.DEPLOY_KEY }}
+        command: |
+          wget https://raw.githubusercontent.com/arquisoft/wichat_es4a/master/docker-compose.yml -O docker-compose.yml
+          docker compose --profile prod down
+          docker compose --profile prod up -d --pull always

.vscode/settings.json

@@ -0,0 +1,3 @@
+{
+    "postman.settings.dotenv-detection-notification-visibility": false
+}

README.md

@@ -30,9 +30,9 @@ First, clone the project:
 In order to communicate with the LLM integrated in this project, we need to setup an API key. Two integrations are available in this propotipe: gemini and empaphy. The API key provided must match the LLM provider used.
 
 We need to create two .env files. 
-- The first one in the webapp directory (for executing the webapp using ```npm start```). The content of this .env file should be as follows:
+- The first one in the llmservice directory (for executing the llmservice using ```npm start```). The content of this .env file should be as follows:
 ```
-REACT_APP_LLM_API_KEY="YOUR-API-KEY"
+LLM_API_KEY="YOUR-API-KEY"
 ```
 - The second one located in the root of the project (along the docker-compose.yml). This .env file is used for the docker-compose when launching the app with docker. The content of this .env file should be as follows:
 ```
@@ -41,8 +41,7 @@ LLM_API_KEY="YOUR-API-KEY"
 
 Note that these files must NOT be uploaded to the github repository (they are excluded in the .gitignore).
 
-An extra configuration for the LLM to work in the deployed version of the app is to include it as a repository secret (LLM_API_KEY). This secret will be used by GitHub Action when building and deploying the application.
-
+An extra configuration for the LLM to work in the deployed version of the app is to create the same .env file (with the LLM_API_KEY variable) in the virtual machine (in the home of the azureuser directory).
 
 ### Launching Using docker
 For launching the propotipe using docker compose, just type:

db/Connection.js

@@ -1,5 +1,7 @@
-const mongoose = require("mongoose");
-const { MongoMemoryServer } = require('mongodb-memory-server');
+import mongoose from "mongoose";
+import { MongoMemoryServer } from "mongodb-memory-server";
+
+let mongoServer;
 
 //async -> asegura que el código no se bloquee mientras espera que MongoDB se conecte.
 const connect = async() => {
@@ -11,7 +13,7 @@ const connect = async() => {
             console.log("MongoDB URL server")
         } else {
             //si no hay una variable de entorno DB_URL, creamos un servidor de MongoDB en memoria usando MongoMemoryServer
-            const mongoServer = await MongoMemoryServer.create();  //se crea un servidor de bd en memoria
+            mongoServer = await MongoMemoryServer.create();  //se crea un servidor de bd en memoria
             const mongoUri = mongoServer.getUri();  //obtenemos la URL del servidor en memoria
             await mongoose.connect(mongoUri)  //nos conectamos a mongoDB
 
@@ -26,5 +28,16 @@ const connect = async() => {
     }
 }
 
+const disconnect = async () => {
+    try {
+        await mongoose.disconnect();
+        if (mongoServer) {
+            await mongoServer.stop();
+        }
+        console.log("MongoDB disconnected");
+    } catch (error) {
+        console.error("Error al desconectar de MongoDB:", error);
+    }
+};
 
-module.exports = connect;
+export {connect, disconnect};

db/crud.js

@@ -0,0 +1,92 @@
+import {connect, disconnect} from './Connection.js';
+import User from './user.js';
+// Y los demás imports necesarios
+
+// Clase que contiene los métodos para realizar operaciones CRUD sobre cualquier modelo de la base de datos
+class Crud {
+
+  static async createUser(data) {
+    try {
+      const newUser = new User(data);
+      const savedUser = await newUser.save();
+      return savedUser;
+    } catch (error) {
+        error.message = 'Error al crear el usuario: ' + error.message;
+        throw error;
+    }
+  }
+
+  static async getAllUsers() {
+    try {
+      const users = await User.find();
+      return users;
+    } catch (error) {
+        error.message = 'Error al obtener los usuarios: ' + error.message;
+        throw error;
+    }
+  }
+
+  static async getUserById(userId) {
+    try {
+        const user = await User.findById(userId);
+        return user; 
+    } catch (error) {
+        error.message = 'Error al obtener el usuario: ' + error.message;
+        throw error;
+    }
+  }
+
+  static async updateUser(userId, updateData) {
+    try {
+      const updatedUser = await User.findByIdAndUpdate(
+        userId, 
+        updateData, 
+        { new: true }
+      );
+      return updatedUser;   // Devuelve el usuario actualizado
+    } catch (error) {
+        error.message = 'Error al actualizar el usuario: ' + error.message;
+        throw error;
+    }
+  }
+
+  static async deleteUser(userId) {
+    try {
+      const deletedUser = await User.findByIdAndDelete(userId);
+      return deletedUser;   // Devuelve el usuario eliminado
+    } catch (error) {
+        error.message = 'Error al eliminar el usuario: ' + error.message;
+        throw error;
+    }
+  }
+}
+
+connect()
+  .then(() => {
+    console.log("Conexión establecida");
+    // Se crea el usuario
+    return Crud.createUser({
+      username: 'user1',
+      password: '123456'
+    });
+  })
+  .then(createdUser => {
+    console.log("Usuario creado:", createdUser);
+    // Se busca el usuario recién creado usando su _id
+    return Crud.getUserById(createdUser._id);
+  })
+  .then(foundUser => {
+    console.log("Usuario encontrado:", foundUser);
+    console.log(`ID: ${foundUser._id}`);
+    console.log(`Username: ${foundUser.username}`);
+    console.log(`Friend Code: ${foundUser.friendCode}`);
+    console.log(`Password: ${foundUser.password}`);
+  })
+  .catch(error => {
+    console.error("Error:", error);
+  })
+  .finally(() => {
+    disconnect();
+  });
+
+export default Crud;

db/user.js

@@ -0,0 +1,50 @@
+import { Schema, model } from "mongoose";
+
+// Definir el esquema de usuario
+const userSchema = new Schema({
+  username: {
+    type: String,
+    required: true,
+    trim: true
+  },
+  friendCode: {
+    type: String,
+    unique: true,
+    required: false
+  },
+  password: {
+    type: String,
+    required: true
+  }
+});
+
+// Función que genera un número entre 100000 y 999999 en formato String.
+function generarCodigoAmigo() {
+  return Math.floor(100000 + Math.random() * 900000).toString();
+}
+
+// Antes de guardar, se genera y asigna un friendCode único.
+// Usamos `this.constructor` para buscar dentro del mismo modelo, ya que "User"
+// aún no está definido en el momento de crear el hook.
+userSchema.pre("save", async function (next) {
+  const user = this;
+  let codigoValido = false;
+  let codigoAleatorio;
+
+  while (!codigoValido) {
+    codigoAleatorio = generarCodigoAmigo();
+
+    // Verifica si ya existe otro usuario con este friendCode
+    const existe = await this.constructor.findOne({ friendCode: codigoAleatorio });
+    if (!existe) {
+      codigoValido = true;
+    }
+  }
+
+  user.friendCode = codigoAleatorio;
+  next();
+});
+
+// Crear el modelo a partir del esquema
+const User = model("User", userSchema);
+export default User;

docker-compose.yml

@@ -42,7 +42,10 @@ services:
     container_name: llmservice-wichat_es4a
     image: ghcr.io/arquisoft/wichat_es4a/llmservice:latest
     profiles: ["dev", "prod"]
-    build: ./llmservice
+    env_file:
+      - .env
+    build: 
+      context: ./llmservice
     ports:
       - "8003:8003"
     networks:
@@ -71,10 +74,7 @@ services:
     container_name: webapp-wichat_es4a
     image: ghcr.io/arquisoft/wichat_es4a/webapp:latest
     profiles: ["dev", "prod"]
-    build: 
-      context: ./webapp
-      args:
-        LLM_API_KEY: ${LLM_API_KEY}
+    build: ./webapp
     depends_on:
       - gatewayservice
     ports:

llmservice/.dockerignore

@@ -1,2 +1,3 @@
 node_modules
-coverage
+coverage
+.env

llmservice/llm-service.js

@@ -6,6 +6,8 @@ const port = 8003;
 
 // Middleware to parse JSON in request body
 app.use(express.json());
+// Load enviornment variables
+require('dotenv').config();
 
 // Define configurations for different LLM APIs
 const llmConfigs = {
@@ -19,7 +21,7 @@ const llmConfigs = {
   empathy: {
     url: () => 'https://empathyai.prod.empathy.co/v1/chat/completions',
     transformRequest: (question) => ({
-      model: "qwen/Qwen2.5-Coder-7B-Instruct",
+      model: "mistralai/Mistral-7B-Instruct-v0.3",
       messages: [
         { role: "system", content: "You are a helpful assistant." },
         { role: "user", content: question }
@@ -71,9 +73,14 @@ async function sendQuestionToLLM(question, apiKey, model = 'gemini') {
 app.post('/ask', async (req, res) => {
   try {
     // Check if required fields are present in the request body
-    validateRequiredFields(req, ['question', 'model', 'apiKey']);
+    validateRequiredFields(req, ['question', 'model']);
 
-    const { question, model, apiKey } = req.body;
+    const { question, model } = req.body;
+    //load the api key from an environment variable
+    const apiKey = process.env.LLM_API_KEY;
+    if (!apiKey) {
+      return res.status(400).json({ error: 'API key is missing.' });
+    }
     const answer = await sendQuestionToLLM(question, apiKey, model);
     res.json({ answer });