Merge pull request #254 from fcampise/main

added Track 2, Sprint 6

Track_2_ToDo_App/Sprint-06 - Advanced To-Do Details/README.md

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+# Sprint 6: Advanced Task Details
+⏲️ _Est. time to complete: 60 min._ ⏲️
+
+This sprint is designed to help students add additional details to the To-Do application.  The sprint will walk students through adding details about the task such as Due Date, Priority, Additional Notes, and whether or not the Task has been completed.
+
+**📕Feature: Add additional about to-do item**
+1. [**📖 Add Due Date, Priority, Notes and Completion Status to To-Do item**](/Track_2_ToDo_App/Sprint-06%20-%20Advanced%20To-Do%20Details/Feature%201%20-%20Add%20Additional%20To-Do%20Details/User%20Story%201%20-%20Add%20additional%20details%20to%20to-do%20item.md)
+
+
+<br/>
+
+[🔼 Hackathon Home Page ](/Track_2_ToDo_App/README.md) | [◀ Previous Sprint](/Track_2_ToDo_App/Sprint-05%20-%20Advanced%20AI%20recommendations/README.md) | [Next sprint ▶](/Track_2_ToDo_App/Sprint-07%20-%20Advanced%20Styling%20Your%20Web%20App/README.md)

Track_2_ToDo_App/Sprint-06 - Advanced To-Do Details/src/app-s06-f01-us01/.env-example

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+DEBUG_APP="True"
+USE_AZURE_OPENAI="True"
+OPENAI_API_KEY="<get the key from https://platform.openai.com/api-keys>"
+OPENAI_ORG_ID="<get the ord-id from https://platform.openai.com/account/organization>"
+OPEN_AI_DEPLOYMENT_NAME="gpt-3.5-turbo"
+AZURE_OPENAI_DEPLOYMENT_NAME="gpt-35-turbo"
+AZURE_OPENAI_ENDPOINT=""
+AZURE_OPENAI_API_KEY=""
+AZURE_OPENAI_VERSION="2023-05-15"

Track_2_ToDo_App/Sprint-06 - Advanced To-Do Details/src/app-s06-f01-us01/app.py

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+###############################################################################
+## Sprint 6: Advanced To-DO Details
+## Feature 1: Add Additional Details to To-Do Items
+## User Story 1: Add Due Date, Priority, Notes and Completion Status to To-Do item
+############################################################################
+import os
+import json
+from flask import Flask, render_template, request, redirect, url_for, g
+from database import db, Todo
+from recommendation_engine import RecommendationEngine
+from tab import Tab
+
+app = Flask(__name__)
+basedir = os.path.abspath(os.path.dirname(__file__))   # Get the directory of the this file
+todo_file = os.path.join(basedir, 'todo_list.txt')     # Create the path to the to-do list file using the directory
+app.config["SQLALCHEMY_DATABASE_URI"] = 'sqlite:///' + os.path.join(basedir, 'todos.db')
+app.config['SQLALCHEMY_TRACK_MODIFICATIONS'] = False
+
+db.init_app(app)
+
+with app.app_context():
+    db.create_all()
+
+@app.before_request
+def load_data_to_g():
+    todos = Todo.query.all()
+    g.todos = todos 
+    g.todo = None
+    g.TabEnum = Tab
+    g.selectedTab = Tab.NONE
+
+
+@app.route("/")
+def index():
+    return render_template("index.html")
+
+@app.route("/add", methods=["POST"])
+def add_todo():
+
+    # Get the data from the form
+    todo = Todo(
+        name=request.form["todo"]
+    )
+
+    # Add the new ToDo to the list
+    db.session.add(todo)
+    db.session.commit()
+
+    # Add the new ToDo to the list
+    return redirect(url_for('index'))
+
+# Details of ToDo Item
+@app.route('/details/<int:id>', methods=['GET'])
+def details(id):
+    g.selectedTab = Tab.DETAILS
+    g.todos = Todo.query.all()
+    g.todo = Todo.query.filter_by(id=id).first()
+
+    return render_template('index.html')
+
+# Edit a new ToDo
+@app.route('/edit/<int:id>', methods=['GET'])
+def edit(id):
+    g.selectedTab = Tab.EDIT
+    g.todos = Todo.query.all()
+    g.todo = Todo.query.filter_by(id=id).first()
+
+    return render_template('index.html')
+
+# Save existing To Do Item
+@app.route('/update/<int:id>', methods=['POST'])
+def update_todo(id):
+    g.selectedTab = Tab.DETAILS
+
+    if request.form.get('cancel') != None:
+        return redirect(url_for('index'))
+
+    # Get the data from the form
+    name = request.form['name']
+    due_date = request.form.get('duedate')
+    notes=request.form.get('notes')
+    priority=request.form.get('priority')
+    completed=request.form.get('completed')
+
+    todo = db.session.query(Todo).filter_by(id=id).first()
+    if todo != None:
+        todo.name = name
+
+        if due_date != "None":
+            todo.due_date = due_date
+
+        if notes != None:
+            todo.notes = notes
+
+        if priority != None:
+            todo.priority = int(priority) 
+
+        if completed == None:
+            todo.completed = False
+        elif completed == "on":
+            todo.completed = True
+    #
+    db.session.add(todo)
+    db.session.commit()
+    #
+    return redirect(url_for('index'))
+
+
+# Delete a ToDo
+@app.route('/remove/<int:id>', methods=["POST"])
+def remove_todo(id):
+    db.session.delete(Todo.query.filter_by(id=id).first())
+    db.session.commit()
+    return redirect(url_for('index'))
+
+# Show AI recommendations
+@app.route('/recommend/<int:id>', methods=['GET'])
+@app.route('/recommend/<int:id>/<refresh>', methods=['GET'])
+async def recommend(id, refresh=False):
+    g.selectedTab = Tab.RECOMMENDATIONS
+    recommendation_engine = RecommendationEngine()
+    g.todo = db.session.query(Todo).filter_by(id=id).first()
+
+    if g.todo and not refresh:
+        try:
+            #attempt to load any saved recommendation from the DB
+            if g.todo.recommendations_json is not None:
+                g.todo.recommendations = json.loads(g.todo.recommendations_json)
+                return render_template('index.html')
+        except ValueError as e:
+            print("Error:", e)
+
+    previous_links_str = None
+    if refresh:
+        g.todo.recommendations = json.loads(g.todo.recommendations_json)
+        # Extract links
+        links = [item["link"] for item in g.todo.recommendations]
+        # Convert list of links to a single string
+        previous_links_str = ", ".join(links)
+
+    g.todo.recommendations = await recommendation_engine.get_recommendations(g.todo.name, previous_links_str)
+
+    # Save the recommendations to the database
+    try:
+        g.todo.recommendations_json = json.dumps(g.todo.recommendations)
+        db.session.add(g.todo)
+        db.session.commit()
+    except Exception as e:
+        print(f"Error adding and committing todo: {e}")
+        return
+
+    return render_template('index.html')
+
+
+if __name__ == "__main__":
+    app.run(debug=True)

Track_2_ToDo_App/Sprint-06 - Advanced To-Do Details/src/app-s06-f01-us01/database.py

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+from flask_sqlalchemy import SQLAlchemy
+from sqlalchemy import Integer, String, Boolean, JSON, func
+from sqlalchemy.orm import DeclarativeBase
+
+class Base(DeclarativeBase):
+    pass
+
+db = SQLAlchemy(model_class=Base)
+
+class Todo(db.Model):
+    id = db.Column(Integer, primary_key=True)
+    name = db.Column(String(100), nullable=False)
+    notes = db.Column(String(100))
+    priority = db.Column(Integer, default=0)
+    completed = db.Column(Boolean, default=False)
+    recommendations_json = db.Column(db.JSON)   #json serialized version of recommendations for storing in DB
+    due_date = db.Column(String(50))
+
+    #transient variables (i.e., not stored in db)
+    recommendations = []   #recommendations as a collection
+
+    def __str__(self):
+        return self.name
+
+    def priority_str(self):
+        """
+        Returns the priority as a string.
+        """
+        str = "Not Set"
+        if self.priority == 1:
+            str = "High"
+        elif self.priority == 2:
+            str = "Medium"
+        elif self.priority == 3:
+            str = "Low"
+
+        return str
+
+    def completed_str(self):
+        """
+        Returns the completed status as a string.
+        """
+        if self.completed:
+            return "Yes"
+        else:    
+            return "No"
+
+
+

Track_2_ToDo_App/Sprint-06 - Advanced To-Do Details/src/app-s06-f01-us01/priority.py

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+from enum import Enum
+
+class Priority(Enum):
+    NONE = 0,
+    HIGH = 1,
+    MEDIUM = 2,
+    LOW = 3

Track_2_ToDo_App/Sprint-06 - Advanced To-Do Details/src/app-s06-f01-us01/recommendation_engine.py

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+import json
+import asyncio
+import semantic_kernel as sk
+from services import Service
+from openai import AzureOpenAI
+from dotenv import dotenv_values
+
+config = dotenv_values(".env")
+
+#uses the USE_AZURE_OPENAI variable from the .env file to determine which AI service to use
+#False means use OpenAI, True means use Azure OpenAI
+selectedService = Service.AzureOpenAI if config.get("USE_AZURE_OPENAI") == "True" else Service.OpenAI
+deployment, api_key, endpoint = sk.azure_openai_settings_from_dot_env()
+
+class RecommendationEngine:
+    def __init__(self):
+        deployment, api_key, endpoint = sk.azure_openai_settings_from_dot_env()
+
+        self.client = AzureOpenAI(azure_endpoint = endpoint, 
+                        api_key=api_key,  
+                        api_version="2024-02-15-preview"
+                        )        
+
+
+    async def get_recommendations(self, keyword, previous_links_str=None):
+        prompt = f"""Please return 5 recommendations based on the input string: '{keyword}' using correct JSON syntax that contains a title and a hyperlink back to the supporting website. RETURN ONLY JSON AND NOTHING ELSE"""
+        system_prompt = """You are an administrative assistant bot who is good at giving 
+        recommendations for tasks that need to be done by referencing website links that can provide 
+        assistance to helping complete the task. 
+
+        If there are not any recommendations simply return an empty collection. 
+
+        EXPECTED OUTPUT:
+        Provide your response as a JSON object with the following schema:
+        [{"title": "...", "link": "..."},
+        {"title": "...", "link": "..."},
+        {"title": "...", "link": "..."}]
+        """
+
+        if previous_links_str is not None:
+            prompt = prompt + f". EXCLUDE the following links from your recommendations: {previous_links_str}"  
+
+        message_text = [{"role":"system","content":system_prompt},
+                        {"role":"user","content":prompt},]
+
+        response = self.client.chat.completions.create(
+                        model=deployment,
+                        messages = message_text,
+                        temperature=0.14,
+                        max_tokens=800,
+                        top_p=0.17,
+                        frequency_penalty=0,
+                        presence_penalty=0,
+                        stop=None
+                        )
+
+        result = response.choices[0].message.content
+        print(result)
+
+        try:
+            recommendation = json.loads(result)
+        except Exception as e:
+            print(f"Error loading recommendations: {e}")
+            recommendation = [{"title": "Sorry, unable to recommendation at this time", "link": ""}]
+
+        return recommendation
+
+async def test_recommendation_engine():
+    engine = RecommendationEngine()
+    recommendations = await engine.get_recommendations("Buy a birthday gift for mom")
+    count = 1
+    for recommendation in recommendations:
+        print(f"{count} - {recommendation['title']}: {recommendation['link']}")
+        count += 1
+
+if __name__ == "__main__":
+    asyncio.run(test_recommendation_engine())

Track_2_ToDo_App/Sprint-06 - Advanced To-Do Details/src/app-s06-f01-us01/services.py

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+"""
+This module defines an enumeration representing different services.
+"""
+
+from enum import Enum
+
+
+class Service(Enum):
+    """
+    Attributes:
+        OpenAI (str): Represents the OpenAI service.
+        AzureOpenAI (str): Represents the Azure OpenAI service.
+        HuggingFace (str): Represents the HuggingFace service.
+    """
+
+    OpenAI = "openai"
+    AzureOpenAI = "azureopenai"
+    HuggingFace = "huggingface"

Track_2_ToDo_App/Sprint-06 - Advanced To-Do Details/src/app-s06-f01-us01/static/css/style.css

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+body {
+    background-color: f0f0f0;  /* light grey */
+    color: darkslategray;  /* default font color */
+    font-family: Arial, sans-serif;
+    background-image: url("../images/Designer02.jpeg");
+    background-repeat: no-repeat;
+    background-position: center;
+    background-size:cover;
+}
+
+h1 {
+    color: darkgray; /* font for the h1 header*/
+}
+
+.list-group-item {
+    color: #333; /* dark grey */
+}
+
+
+

Track_2_ToDo_App/Sprint-06 - Advanced To-Do Details/src/app-s06-f01-us01/static/js/app.js

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+document.addEventListener("DOMContentLoaded", function() {
+    const nameInput = document.getElementById("todo");
+
+    //add javascript to support speech recognition for the todo input field
+    const SpeechRecognition = window.SpeechRecognition || window.webkitSpeechRecognition;
+    const recognition = new SpeechRecognition();
+    recognition.continuous = false;
+    recognition.lang = "en-US";
+    recognition.interimResults = false;
+
+    window.captureVoice = function() {
+        recognition.start();
+        nameInput.value = "Your microphone is activated, speak to record voice";
+    };
+
+    recognition.onresult = function(event) {
+        const transcript = event.results[0][0].transcript;
+        const recognizedText = transcript.endsWith('.') ? transcript.slice(0, -1) : transcript;
+        nameInput.value = recognizedText;
+    };
+
+    recognition.onspeechend = function() {
+        recognition.stop();
+    };
+
+    recognition.onnomatch = function(event) {
+        nameInput.value = "I didn't recognize that prompt.";
+    };
+
+    recognition.onerror = function(event) {
+        nameInput.value = "Error occurred in recognition: " + event.error;
+    };
+});