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* Remove outdated references to entity resolution * Clarify covariate extraction * Minor edits from other PR feedback * Remove duplicate line * Semver --------- Co-authored-by: Alonso Guevara <alonsog@microsoft.com>
72 lines
4.2 KiB
Markdown
72 lines
4.2 KiB
Markdown
# GraphRAG
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👉 [Use the GraphRAG Accelerator solution](https://github.com/Azure-Samples/graphrag-accelerator) <br/>
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👉 [Microsoft Research Blog Post](https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/)<br/>
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👉 [Read the docs](https://microsoft.github.io/graphrag)<br/>
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👉 [GraphRAG Arxiv](https://arxiv.org/pdf/2404.16130)
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<div align="left">
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<a href="https://pypi.org/project/graphrag/">
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<img alt="PyPI - Version" src="https://img.shields.io/pypi/v/graphrag">
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</a>
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<a href="https://pypi.org/project/graphrag/">
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<img alt="PyPI - Downloads" src="https://img.shields.io/pypi/dm/graphrag">
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</a>
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<a href="https://github.com/microsoft/graphrag/issues">
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<img alt="GitHub Issues" src="https://img.shields.io/github/issues/microsoft/graphrag">
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</a>
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<a href="https://github.com/microsoft/graphrag/discussions">
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<img alt="GitHub Discussions" src="https://img.shields.io/github/discussions/microsoft/graphrag">
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</a>
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</div>
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## Overview
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The GraphRAG project is a data pipeline and transformation suite that is designed to extract meaningful, structured data from unstructured text using the power of LLMs.
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To learn more about GraphRAG and how it can be used to enhance your LLM's ability to reason about your private data, please visit the <a href="https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/" target="_blank">Microsoft Research Blog Post.</a>
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## Quickstart
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To get started with the GraphRAG system we recommend trying the [Solution Accelerator](https://github.com/Azure-Samples/graphrag-accelerator) package. This provides a user-friendly end-to-end experience with Azure resources.
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## Repository Guidance
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This repository presents a methodology for using knowledge graph memory structures to enhance LLM outputs. Please note that the provided code serves as a demonstration and is not an officially supported Microsoft offering.
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⚠️ *Warning: GraphRAG indexing can be an expensive operation, please read all of the documentation to understand the process and costs involved, and start small.*
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## Diving Deeper
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- To learn about our contribution guidelines, see [CONTRIBUTING.md](./CONTRIBUTING.md)
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- To start developing _GraphRAG_, see [DEVELOPING.md](./DEVELOPING.md)
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- Join the conversation and provide feedback in the [GitHub Discussions tab!](https://github.com/microsoft/graphrag/discussions)
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## Prompt Tuning
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Using _GraphRAG_ with your data out of the box may not yield the best possible results.
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We strongly recommend to fine-tune your prompts following the [Prompt Tuning Guide](https://microsoft.github.io/graphrag/posts/prompt_tuning/overview/) in our documentation.
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## Responsible AI FAQ
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See [RAI_TRANSPARENCY.md](./RAI_TRANSPARENCY.md)
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- [What is GraphRAG?](./RAI_TRANSPARENCY.md#what-is-graphrag)
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- [What can GraphRAG do?](./RAI_TRANSPARENCY.md#what-can-graphrag-do)
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- [What are GraphRAG’s intended use(s)?](./RAI_TRANSPARENCY.md#what-are-graphrags-intended-uses)
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- [How was GraphRAG evaluated? What metrics are used to measure performance?](./RAI_TRANSPARENCY.md#how-was-graphrag-evaluated-what-metrics-are-used-to-measure-performance)
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- [What are the limitations of GraphRAG? How can users minimize the impact of GraphRAG’s limitations when using the system?](./RAI_TRANSPARENCY.md#what-are-the-limitations-of-graphrag-how-can-users-minimize-the-impact-of-graphrags-limitations-when-using-the-system)
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- [What operational factors and settings allow for effective and responsible use of GraphRAG?](./RAI_TRANSPARENCY.md#what-operational-factors-and-settings-allow-for-effective-and-responsible-use-of-graphrag)
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## Trademarks
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This project may contain trademarks or logos for projects, products, or services. Authorized use of Microsoft
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trademarks or logos is subject to and must follow
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[Microsoft's Trademark & Brand Guidelines](https://www.microsoft.com/en-us/legal/intellectualproperty/trademarks/usage/general).
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Use of Microsoft trademarks or logos in modified versions of this project must not cause confusion or imply Microsoft sponsorship.
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Any use of third-party trademarks or logos are subject to those third-party's policies.
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## Privacy
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[Microsoft Privacy Statement](https://privacy.microsoft.com/en-us/privacystatement)
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