BotLLM

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  Demo 1 - Screenshots Bot interface: What’s our Q3 commission policy?

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  Demo 1 - Screenshots - Answer extracted from internal company documentation

Inspiration

The idea for BotLLM came from a simple observation: developers and newcomers often struggle to quickly find reliable information across different platforms, documentation, repositories, and community discussions.

While working on various tech and hackathon projects, we noticed how much time is spent searching for the right resources, guides, or project information. We wanted to create a tool that could simplify this process and help people access structured knowledge faster.

This inspired us to build BotLLM, an AI-powered assistant that can help users navigate complex information spaces and quickly discover useful resources, documentation, and opportunities.

What we learned

During the development of BotLLM, we learned several important things:

• how to structure knowledge sources for AI-based assistants
• how to design a simple interface that makes complex information easier to explore
• how to connect AI models with developer tools and repositories
• how to build and present a startup-style project during a hackathon environment

We also gained valuable experience working as a team and preparing project materials such as documentation, demo videos, and pitch presentations.

How we built the project

The project was built by combining AI technologies with modern development tools.

First, we designed the concept and defined the core functionality of the assistant. Then we prepared the project architecture and created a prototype that can process user queries and provide structured responses.

We organized the project repository, built the core logic for interacting with AI models, and prepared demo materials showing how the assistant can be used to explore projects, documentation, and technical information.

Challenges we ran into

During development we faced several challenges:

• configuring the development environment
• dealing with limitations of cloud development environments
• preparing deployment and demo infrastructure
• ensuring the project submission met hackathon requirements (such as demo video detection)

Despite these challenges, the process helped us improve our workflow and better understand how to deliver a working project under time constraints.

Built With

• Python
• JavaScript
• LLM / AI APIs
• GitHub
• GitHub Codespaces
• REST APIs

Try it out

• Project repository: https://github.com/hodoor6/Bot-LLM/

Built With

• ai
• apis
• codespaces
• github
• javascript
• llm
• python
• rest