Lecture Notes: Building Deepsite with Python

Introduction

• Presenter: Marlene
• Topic: Building "Deepsite" application using Python
• Platform Highlighted: Hugging Face for open-source AI and machine learning projects
• Target: Convert a Typescript project to Python

Deepsite Overview

• Functionality: Generates website UI using HTML, JS, and CSS
• Tool Used: Deepseek R1
• Source: Found on Hugging Face Spaces, which is a platform for sharing projects
• Purpose: Simplifies the process of creating web applications

Project Setup

Steps to Access the Project

1. Locate Deepsite on Hugging Face Spaces:
   • Explore example websites built using the application.
2. GitHub Repository:
   • Access the code via the files tab which links to GitHub.
   • Option to clone repository but not necessary for this tutorial.

Choosing Python over Typescript

• Main Focus: AI code in service.js
• Key Element: System prompt that guides HTML, CSS, and JavaScript usage.
• Prompt Instructions:
  • Use of Tailwind CSS
  • Single HTML file

Implementation in Python

Environment Setup

• Tools Needed:
  • VS Code
  • Python Jupyter Notebook
• Dependencies:
  • requirements.txt includes langchain Azure AI and Python
  • Install using pip install -r requirements.txt

Code Structure

1. System Prompt Setup:
   • Define Python string for the system prompt
2. Dependencies:
   • Import necessary packages from Langchain and Azure AI.
3. Initialize Deepseek Model:
   • Provide Azure AI endpoint and API key.
   • Configure model settings, such as temperature and max tokens for creativity.

Function Implementation

• Function Name: stream_response
• Objective: Process prompt to generate website code.
• Steps:
  • Define messages (system and human prompts)
  • Utilize Langchain to stream model responses
  • Capture generated HTML code
  • Output includes code and a description of the generated app

Testing and Results

• Example Prompt: "Create a simple purple to-do list."
• Output Verification:
  • Run code to see HTML output
  • Example result: "Stylish purple-themed to-do list app"

Further Development

Creating a Flask Application

• Approach: Use Copilot and agent mode for vibe coding
• Outcome: Python-based application with a similar UI to Deepsite
• Deployment: Option to deploy applications with custom names

Conclusion

• Reflection:
  • Ease of generating functional web apps with minimal code
  • Potential in AI-driven UI generation
• Final Thoughts: Encouragement to explore these technologies and additional resources in the video description

Additional Resources

• Links to connect with Marlene's previous videos
• Encourage engagement and feedback through comments and subscriptions