from flask import Flask, render_template, request, jsonify
from gunicorn.app.base import BaseApplication
from logging_config import configure_logging
import os

app = Flask(__name__)

@app.route("/")
def root_route():
    return render_template('decision_form.html')

@app.route("/analyze", methods=['POST'])
def analyze_decision():
    goals = request.form['goals']
    preferences = request.form['preferences']
    constraints = request.form['constraints']
    from abilities import llm_prompt
    detailed_prompt = f"Given the goals: {goals}, preferences: {preferences}, and constraints: {constraints}, analyze the user's objectives thoroughly to identify potential options and provide actionable insights. Consider the specified goals, preferences, and constraints as key factors in the decision-making process. Evaluate each option's success possibility level, feasibility level, potential risk level, and required dedication level to provide users with a comprehensive understanding of their choices. Present the analysis in a clear and organized manner, highlighting the strengths and weaknesses of each option relative to the user's goals. Ensure the recommendations are tailored to the user's unique circumstances and provide actionable guidance for making informed decisions. Give the analyze results in a manner that as if you were talking to the user in a warming and encouraging way."
    analysis_result = llm_prompt(detailed_prompt)
    result = {
        "goals": goals,
        "preferences": preferences,
        "constraints": constraints,

About this template

This Flask application serves a decision form page and analyzes decisions based on user input. Upon receiving form submission via the /analyze route, it extracts goals, preferences, and constraints provided by the user. Using the llm_prompt function from the abilities module, it generates a detailed prompt for analyzing the decision. The application then renders the decision form page with the analysis result displayed. Additionally, it utilizes the StandaloneApplication class from gunicorn.app.base to configure and run the Flask app as a standalone Gunicorn application. Made by BaranDev[https://github.com/BaranDev]

Introduction to the Decision Maker App Template

Welcome to the Decision Maker App template! This template is designed to help you create a web application that assists users in making decisions by analyzing their goals, preferences, and constraints. The app uses a Flask backend to process user input and provides an analysis using the built-in abilities module of Lazy. The frontend is a simple HTML form that collects user data and displays the analysis results.

Getting Started with the Template

To begin using this template, click on "Start with this Template" in the Lazy builder interface. This will set up the code in the Lazy Builder, so you can start customizing and deploying your application without worrying about copying or pasting code.

Test: Deploying the App

Once you have clicked "Start with this Template," you can deploy your app by pressing the "Test" button. This will launch the Lazy CLI, and the deployment process will begin. If the code requires any user input, you will be prompted to provide it through the Lazy CLI.

Entering Input: Providing User Data

After pressing the "Test" button and starting the deployment, if the app requires any user input, the Lazy CLI will prompt you to enter the necessary information. This input will be used by the app to perform the decision analysis.

Using the App: Interacting with the Web Interface

Once the app is deployed, you will be provided with a dedicated server link to access the web interface. Here's how to use it:

  • Visit the provided server link to open the Decision Maker App in your web browser.
  • Fill in the form with your goals, preferences, and constraints.
  • Submit the form to receive an analysis of your decision criteria.
  • Review the analysis results displayed on the page to help you make an informed decision.

Integrating the App: Next Steps

If you wish to integrate this app into another service or frontend, you may need to use the server link provided by Lazy. For example, you could embed the link in an iframe within another webpage or use the API endpoints to fetch analysis results programmatically.

Remember, this template is designed to work seamlessly within the Lazy platform, so all the heavy lifting of deployment and environment setup is handled for you. Enjoy building your Decision Maker App!

If you have any questions or need further assistance, please refer to the documentation provided in the code or reach out to Lazy's customer support for help.

Category
Technology
Last published
June 15, 2024

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