This is a submission for the Hacktoberfest Open-Source AI Challenge Week 1: Touch Grass
What I Built
I built a Personalized Guidance Chatbot that helps users discover suitable career options based on their interests and skills. It uses AI, semantic search, and vector embeddings to provide relevant career suggestions.
In the future, I plan to extend it with outdoor learning activities and real-world skill development challenges to encourage users to move beyond the screen.
Demo
The application can be run locally using Streamlit. A live demo will be added when available.
Code
GitHub Repository: https://github.com/harsh4944/Personalized-Guidance-Chatbot
How I Built It
I used Python, Hugging Face's all-MiniLM-L6-v2 embeddings, Chroma vector database, LangChain, GPT-2, and Streamlit.
The embedding model converts user input into vectors, Chroma retrieves relevant career information, LangChain manages the retrieval process, and GPT-2 generates career suggestions. Streamlit provides the interactive chatbot interface.
Why Does Open Innovation Matter?
Open innovation allows developers to experiment with AI models, customize tools, and build useful applications without depending entirely on proprietary systems. Open-source technologies make this project easier to understand, improve, and extend with new features.
My Agent Session
Agent session link will be added if available.
Prize Categories
To be determined based on the applicable challenge partner categories.>
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