Welcome to Generative Geek! In this exciting tutorial, we dive deep into building a smart AI Career Coach using cutting-edge technologies like Streamlit, LangChain, and GPT-4o. Whether you're a tech enthusiast, a developer, or someone looking to explore the power of AI in career recommendations, this video has something for everyone.
What You'll Learn:
1. Streamlit for UI Development:
- We'll start by setting up a user-friendly interface using Streamlit, perfect for gathering user inputs such as personal information, past experiences, and career path options.
- Learn how to use Streamlit's powerful features to create interactive text areas and buttons.
2. Integrating LangChain:
- Discover how LangChain helps us construct sophisticated prompts and process outputs efficiently.
- We'll create a system prompt that combines your input data to guide the AI in providing accurate career recommendations.
3. Pandas for Data Processing:
- Use Pandas to handle and analyze the results of the AI model's recommendations.
- Learn to create DataFrames and visualize the final career path recommendations in an easy-to-understand format.
4. Secrets Management with Streamlit:
- Ensure the security of your API keys using Streamlit's secrets management.
- We'll show you how to securely store and access your OpenAI API key directly from Streamlit's secret manager.
5. Processing with GPT4o:
- Harness the power of GPT-4o by making 200 iterations and 10 concurrent batch calls.
- This setup ensures robust and comprehensive career path recommendations based on diverse input scenarios.
Step-by-Step Tutorial:
- Setting Up the Environment: Install and configure all necessary libraries, including Streamlit, LangChain, and Pandas.
- Building the Streamlit Interface: Create input fields for personal information, project experience, and career path options.
- Constructing the System Prompt: Use LangChain to craft an effective system prompt that leverages user inputs.
- Making Concurrent API Calls: Learn to set up and execute 200 iterations with 10 concurrent calls to GPT-4o, ensuring detailed and varied recommendations.
- Processing and Displaying Results: Use Pandas to analyze and display the results in a user-friendly DataFrame within the Streamlit app.
Why Watch This Video?
By the end of this tutorial, you'll have a fully functional AI Career Coach capable of providing personalized career recommendations. This project not only enhances your skills in AI and software development but also showcases how to integrate multiple technologies seamlessly.
Chapters:
(00:00) : Introduction
(01:10) : What we will build
(02:20) : Environment creation
(08:26) Reading secrets in Streamlit
(11:20) Define Pydantic models for output parsing
(13:08) Streamlit app basic setup
(25:00) Interaction with GPT4-o
(33:50) Setting concurrency and iterations
(34:13) Using chain.batch()
(35:30) Processing output
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Tags: #ai #careercoach #streamlit #langchain #coding #pandas #gpt4o #tutorial #batchprocessing #datascience #machinelearning #project
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