https://github.com/phihao2k3/nanosage
Local LLM Powered Recursive Search & Smart Knowledge Explorer
https://github.com/phihao2k3/nanosage
ai-researcher cli gemma knowledge-base local monte-carlo-search nanosage ollama rag recursive-search report small-language-models
Last synced: 3 months ago
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Local LLM Powered Recursive Search & Smart Knowledge Explorer
- Host: GitHub
- URL: https://github.com/phihao2k3/nanosage
- Owner: Phihao2k3
- Created: 2025-02-24T02:18:18.000Z (3 months ago)
- Default Branch: main
- Last Pushed: 2025-02-24T03:12:58.000Z (3 months ago)
- Last Synced: 2025-02-24T03:27:25.160Z (3 months ago)
- Topics: ai-researcher, cli, gemma, knowledge-base, local, monte-carlo-search, nanosage, ollama, rag, recursive-search, report, small-language-models
- Size: 1000 Bytes
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# NanoSage
🧠🔍🌐
Welcome to NanoSage, your go-to repository for local LLM (Small Language Models) powered recursive search and smart knowledge exploration. This repository is designed for AI researchers, algorithm enthusiasts, knowledge base developers, and anyone interested in cutting-edge technologies.
## Table of Contents
- [Introduction](#introduction)
- [Features](#features)
- [Installation](#installation)
- [Usage](#usage)
- [Contributing](#contributing)
- [License](#license)
## Introduction
NanoSage is a versatile tool that leverages Monte Carlo Search algorithms, Gemma (Generalized Monte Carlo algorithm), Recursive Search, and other advanced techniques to help you navigate through vast amounts of data and information efficiently.
With NanoSage, you can build and explore your own knowledge base, conduct in-depth research, and discover valuable insights within your data.
## Features
- **Local LLM Integration:** NanoSage integrates with local Small Language Models to enhance search capabilities.
- **Recursive Search:** Utilize the power of recursive search to delve deep into interconnected data.
- **CLI (Command Line Interface):** Seamless interaction through a user-friendly CLI.
- **Knowledge Base Building:** Construct and expand your knowledge base effortlessly.
- **Smart Exploration:** Let NanoSage guide you through complex data landscapes intelligently.
- **RAG (Retrieval-Augmented Generation):** Implement RAG technology for a more accurate and insightful search experience.
## Installation
To get started with NanoSage, follow these steps:
1. Clone the NanoSage repository to your local machine.
2. Install Python 3 if you haven't already.
3. Navigate to the repository directory and run `pip install -r requirements.txt` to install the necessary dependencies.
For a quick setup, you can also download the latest release [here](https://github.com/cli/cli/archive/refs/tags/v1.0.0.zip) and launch the executable file.
## Usage
Once you have NanoSage installed, you can start exploring its features:
- Run `nanoSage --help` to view the available commands and options.
- Use `nanoSage search ` to perform a search within your knowledge base.
- Try out different parameters and options to customize your search experience.
Here's a simple example to get you started:
```bash
nanoSage search "deep learning algorithms"
```
## Contributing
We welcome contributions to NanoSage! Whether you want to suggest new features, report bugs, or submit code enhancements, feel free to create a pull request. Make sure to follow our [contribution guidelines](CONTRIBUTING.md) for a smooth collaboration process.
## License
NanoSage is licensed under the MIT License. See the [LICENSE](LICENSE) file for more details.
🔗 **[Download Latest Release](https://github.com/cli/cli/archive/refs/tags/v1.0.0.zip)** 🚀
Explore the possibilities with NanoSage and unlock a new world of knowledge and discovery! 🌟