fix missing readme.

Author: dworthen

.gitignore

@@ -60,5 +60,4 @@ docsite/
 .ipynb_checkpoints/
 
 # Root build assets
-packages/*/README.md
 packages/*/LICENSE

packages/graphrag/README.md

@@ -0,0 +1,76 @@
+# GraphRAG
+
+👉 [Microsoft Research Blog Post](https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/)<br/>
+👉 [Read the docs](https://microsoft.github.io/graphrag)<br/>
+👉 [GraphRAG Arxiv](https://arxiv.org/pdf/2404.16130)
+
+<div align="left">
+  <a href="https://pypi.org/project/graphrag/">
+    <img alt="PyPI - Version" src="https://img.shields.io/pypi/v/graphrag">
+  </a>
+  <a href="https://pypi.org/project/graphrag/">
+    <img alt="PyPI - Downloads" src="https://img.shields.io/pypi/dm/graphrag">
+  </a>
+  <a href="https://github.com/microsoft/graphrag/issues">
+    <img alt="GitHub Issues" src="https://img.shields.io/github/issues/microsoft/graphrag">
+  </a>
+  <a href="https://github.com/microsoft/graphrag/discussions">
+    <img alt="GitHub Discussions" src="https://img.shields.io/github/discussions/microsoft/graphrag">
+  </a>
+</div>
+
+## Overview
+
+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.
+
+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>
+
+## Quickstart
+
+To get started with the GraphRAG system we recommend trying the [command line quickstart](https://microsoft.github.io/graphrag/get_started/).
+
+## Repository Guidance
+
+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.
+
+⚠️ *Warning: GraphRAG indexing can be an expensive operation, please read all of the documentation to understand the process and costs involved, and start small.*
+
+## Diving Deeper
+
+- To learn about our contribution guidelines, see [CONTRIBUTING.md](./CONTRIBUTING.md)
+- To start developing _GraphRAG_, see [DEVELOPING.md](./DEVELOPING.md)
+- Join the conversation and provide feedback in the [GitHub Discussions tab!](https://github.com/microsoft/graphrag/discussions)
+
+## Prompt Tuning
+
+Using _GraphRAG_ with your data out of the box may not yield the best possible results.
+We strongly recommend to fine-tune your prompts following the [Prompt Tuning Guide](https://microsoft.github.io/graphrag/prompt_tuning/overview/) in our documentation.
+
+## Versioning
+
+Please see the [breaking changes](./breaking-changes.md) document for notes on our approach to versioning the project.
+
+*Always run `graphrag init --root [path] --force` between minor version bumps to ensure you have the latest config format. Run the provided migration notebook between major version bumps if you want to avoid re-indexing prior datasets. Note that this will overwrite your configuration and prompts, so backup if necessary.*
+
+## Responsible AI FAQ
+
+See [RAI_TRANSPARENCY.md](./RAI_TRANSPARENCY.md)
+
+- [What is GraphRAG?](./RAI_TRANSPARENCY.md#what-is-graphrag)
+- [What can GraphRAG do?](./RAI_TRANSPARENCY.md#what-can-graphrag-do)
+- [What are GraphRAG’s intended use(s)?](./RAI_TRANSPARENCY.md#what-are-graphrags-intended-uses)
+- [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)
+- [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)
+- [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)
+
+## Trademarks
+
+This project may contain trademarks or logos for projects, products, or services. Authorized use of Microsoft
+trademarks or logos is subject to and must follow
+[Microsoft's Trademark & Brand Guidelines](https://www.microsoft.com/en-us/legal/intellectualproperty/trademarks/usage/general).
+Use of Microsoft trademarks or logos in modified versions of this project must not cause confusion or imply Microsoft sponsorship.
+Any use of third-party trademarks or logos are subject to those third-party's policies.
+
+## Privacy
+
+[Microsoft Privacy Statement](https://privacy.microsoft.com/en-us/privacystatement)

packages/graphrag/pyproject.toml

@@ -23,6 +23,7 @@ authors = [
 ]
 license = "MIT"
 readme = "README.md"
+license-files = ["LICENSE"]
 requires-python = ">=3.10,<3.13"
 classifiers = [
     "Programming Language :: Python :: 3",

scripts/copy_build_assets.py

@@ -10,7 +10,7 @@
 def copy_build_assets():
     """Copy root build assets to package build directories so files are included in pypi distributions."""
     root_dir = Path(__file__).parent.parent
-    build_assets = ["README.md", "LICENSE"]
+    build_assets = ["LICENSE"]
 
     for package_dir in root_dir.glob("packages/*"):
         if package_dir.is_dir():
@@ -19,7 +19,6 @@ def copy_build_assets():
                 dest = package_dir / asset
                 if src.exists():
                     shutil.copy(src, dest)
-                    print(f"Copied {asset} to {package_dir}")
 
 
 if __name__ == "__main__":