# search_big

- **Event:** [Agentic Memory & Context Engineering Hackathon](https://cerebralvalley.ai/e/mongoDB-hackathon)
- **When:** Sat, Oct 11 at 9:00 AM – 10:00 PM (PDT)
- **Where:** Shack15, San Francisco, CA
- **GitHub:** https://github.com/thotasu/Search_big/tree/main
- **Gallery:** https://cerebralvalley.ai/e/mongoDB-hackathon/hackathon/gallery
- **Page:** https://cerebralvalley.ai/e/mongoDB-hackathon/hackathon/gallery/38

search for information from a large file without worrying about context size. Large context model (llama4 maverick) is chosen by default if the context window is enough. Else the information is chunked and relevant chunks for the search are passed to a low cost model like Llama 3.1.

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Markdown version of https://cerebralvalley.ai/e/mongoDB-hackathon/hackathon/gallery/38. Site index for agents: https://cerebralvalley.ai/llms.txt · full text: https://cerebralvalley.ai/llms-full.txt