🚀 Introducing DeepSprint: Supercharge Your Research with AI
Hey DEV Community! 👋
I'm excited to share DeepSprint, an open-source tool I built to revolutionize how we conduct research using AI. As the CTO of Navan, I frequently need to dive deep into various topics quickly, and I wanted to create something that could help others do the same.
What is DeepSprint? 🤔
DeepSprint is a Python-based tool that leverages AI to accelerate research workflows. It's designed to help you explore any topic thoroughly and efficiently, whether you're using OpenAI's models or running things locally with LM Studio.
Key Features ✨
- Rapid deep research capabilities
- Support for both OpenAI and local LLM models via LM Studio
- Flexible API integration with SerperAPI for web searches
- Simple Flask-based server architecture
Why I Built This 🎯
Working at Navan, I often need to conduct thorough research quickly. I realized that AI could dramatically improve this process, but there wasn't a tool that did exactly what I needed. DeepSprint is my solution to this problem, and I'm sharing it with the community because I believe it can help others in their research journey.
Open Source & Free 💝
DeepSprint is completely open source under the MIT license. Feel free to use it, modify it, and contribute to make it even better!
Try It Out!
- GitHub Repository: https://github.com/ilantwig/deepsprint
- Full Documentation: Available in the GitHub README
- Issues/Suggestions: Use the GitHub issues section
What's Next? 🔮
I'm actively working on improving DeepSprint and would love to hear your feedback and suggestions. If you find it useful, consider:
- Starring the repository
- Contributing to the project
- Sharing your experience using it
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