Exploring Open-Source AI with Backboard and Render for Hacktoberfest 2026!
Hello tech community! For this week's Hacktoberfest 2026 DEV Challange, the goal is to build with open-source AI. I am excited to share my journey setting up the Backboard API to explore open-source Large Language Models (LLMs)! Thanks to MLH, I claimed my $5 Backboard credit and successfully gener

Hello tech community! For this week's Hacktoberfest 2026 DEV Challange, the goal is to build with open-source AI. I am excited to share my journey setting up the Backboard API to explore open-source Large Language Models (LLMs)! Thanks to MLH, I claimed my $5 Backboard credit and successfully generated my first AI API key. '''python
import asyncio from backboard import BackboardClient
async def main(): client = BackboardClient(api_key="YOUR_API_KEY")
# Send a message — thread and assistant are auto-created response = await client.send_message( "Hello! I'm excited to get started.", memory="Auto", ) print(response.content) # Continue the conversation using the returned thread_id response = await client.send_message( "What can you help me with?", thread_id=response.thread_id, ) print(response.content) Enter fullscreen mode Exit fullscreen mode asyncio.run(main())
To prepare for the frontend of this AI project, I have also seccessfully deployed a live static site portal on Render: Live Portal: https://hello-render-hacktoberfest.onrender.com
Combining Backboard's AI capabilities with Render's smooth deployment makes building open-source AI apps incredibly easy.