IncognitoPilot
memex
| IncognitoPilot | memex | |
|---|---|---|
| 6 | 2 | |
| 410 | 94 | |
| - | - | |
| 8.4 | 3.7 | |
| 8 months ago | about 1 year ago | |
| Python | TypeScript | |
| MIT License | GNU General Public License v3.0 only |
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IncognitoPilot
- FLaNK Stack Weekly for 21 August 2023
- Show HN: A local version of ChatGPT Code Interpreter, using GPT-4 or Llama 2
- Llama 2 and GPT-4 code interpreter, running locally
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ChatGPT Code Interpreter for sensitive (customer) data - An open source project
It's open-source and can be found here: https://github.com/silvanmelchior/IncognitoPilot
- Show HN: ChatGPT code interpreter on sensitive data without uploading it
- Incognito Pilot – Local ChatGPT Code Interpreter
memex
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Show HN: Autolicious – AI-powered bookmark cataloging Chrome extension
There is a nice opensource extension that does exactly that: https://github.com/memex-life/memex
I tried to use it, and it just does not work very well, I don't it's because implementation is bad, it's just RAG (retrieval based generation) does not work well outside of some simple use cases.
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Tool for Thought (2005)
Hey folks, I've been really enjoying this discussion and wanted to chime in with some thoughts on the nature of personal knowledge bases. I've been dabbling in a side project that tries to address some of the issues mentioned here, mainly focusing on automation and the use of LLMs.
I believe one of the main challenges in building a personal knowledge base is achieving the right balance between automation and manual curation. While automation can conserve time, it's crucial not to lose the personal touch that makes these knowledge bases meaningful and relevant to us as individuals. My approach aims to capture your readings as you browse the web. Though this is a simple approach, it focuses solely on your personal experience.
In my project, I've been experimenting with using LLMs to help with information retrieval. The idea is to enhance the search experience by leveraging AI to not only find relevant content but also to provide context, answer questions, and offer insights. I've found that integrating LLMs can add a whole new dimension to exploring our personal libraries.
I think it's essential for any knowledge management tool to be user-friendly and accessible, allowing people to focus on the content rather than getting bogged down by the tool itself.
Anyway, just wanted to share some thoughts and ideas I've been playing with in my project. if you are interested. Please check out my project here.
[https://github.com/memex-life/memex](https://github.com/meme....
What are some alternatives?
E2B - Secure cloud runtime for AI apps & AI agents. Fully open-source.
lunary - The production toolkit for LLMs. Observability, prompt management and evaluations.
dify - Dify is an open-source LLM app development platform. Dify's intuitive interface combines AI workflow, RAG pipeline, agent capabilities, model management, observability features and more, letting you quickly go from prototype to production.
namegpt - Generate unique and creative project names in seconds with AI!
SolidUI - one sentence generates any graph
ReadSomething - 📖 一个开源的 Chrome 插件，可以将网页转成阅读模式，并且内置了 AI 总结、翻译、Markdown 转换等功能。
lida - Automatic Generation of Visualizations and Infographics using Large Language Models
chat-to-your-database - Chat to your database with AI. An experimental app to test the abilities of LLMs to query SQL databases using natural language.
botpress - The open-source hub to build & deploy GPT/LLM Agents ⚡️
SQLiteGPT - SQL function for SQLite to directly query OpenAI's ChatGPT
databerry - The no-code platform for building custom LLM Agents