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Merge pull request #130 from SylphAI-Inc/main
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[0.1.0-beta.4]
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Sylph-AI authored Jul 19, 2024
2 parents aaa09fb + 338ffbf commit 92d4fea
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1 change: 1 addition & 0 deletions .env_example
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Expand Up @@ -4,3 +4,4 @@ ANTHROPIC_API_KEY=YOUR_API_KEY_IF_YOU_USE_ANTHROPIC
GOOGLE_API_KEY=YOUR_API_KEY_IF_YOU_USE_GOOGLE
COHERE_API_KEY=YOUR_API_KEY_IF_YOU_USE_COHERE
HF_TOKEN=YOUR_API_KEY_IF_YOU_USE_HF
OLLAMA_HOST=http://localhost:11434
154 changes: 0 additions & 154 deletions .github/workflows/publish_release.yml

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23 changes: 13 additions & 10 deletions README.md
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![LightRAG Logo](https://raw.githubusercontent.com/SylphAI-Inc/LightRAG/main/docs/source/_static/images/LightRAG-logo-doc.jpeg)

<p align="center">
<a href="https://discord.gg/ezzszrRZvT">
<img alt="discord-invite" src="https://dcbadge.vercel.app/api/server/ezzszrRZvT?style=flat">
<a href="https://colab.research.google.com/drive/1TKw_JHE42Z_AWo8UuRYZCO2iuMgyslTZ?usp=sharing">
<img alt="Try Quickstart in Colab" src="https://colab.research.google.com/assets/colab-badge.svg">
</a>
</p>

<p align="center">
<a href="https://pypi.org/project/lightRAG/">
<a href="https://pypi.org/project/lightRAG">
<img alt="PyPI Version" src="https://img.shields.io/pypi/v/lightRAG?style=flat-square">
</a>
<a href="https://colab.research.google.com/drive/1TKw_JHE42Z_AWo8UuRYZCO2iuMgyslTZ?usp=sharing">
<img alt="Try Quickstart in Colab" src="https://colab.research.google.com/assets/colab-badge.svg">
<a href="https://star-history.com/#SylphAI-Inc/LightRAG">
<img alt="GitHub stars" src="https://img.shields.io/github/stars/SylphAI-Inc/LightRAG?style=flat-square">
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<a href="https://opensource.org/license/MIT">
<img alt="License" src="https://img.shields.io/github/license/SylphAI-Inc/LightRAG">
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Expand All @@ -45,7 +48,7 @@ LLMs are like water; they can be shaped into anything, from GenAI applications s

Because of this, no library can provide out-of-the-box solutions. Users must build towards their own use case. This requires the library to be modular, robust, and have a clean, readable codebase. The only code you should put into production is code you either 100% trust or are 100% clear about how to customize and iterate.

This is what LightRAG is: light, modular, and robust, with a 100% readable codebase.
<!-- This is what LightRAG is: light, modular, and robust, with a 100% readable codebase. -->


Further reading: [How We Started](https://www.linkedin.com/posts/li-yin-ai_both-ai-research-and-engineering-use-pytorch-activity-7189366364694892544-Uk1U?utm_source=share&utm_medium=member_desktop),
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