Update README.md

README.md

@@ -1,10 +1,117 @@
 ---
 title: README
-emoji: 🏃
+emoji: 🦙
 colorFrom: yellow
 colorTo: purple
 sdk: static
 pinned: false
 ---
 
-Edit this `README.md` markdown file to author your organization card 🔥
+
+# 🗂️ LlamaIndex 🦙 (GPT Index)
+
+LlamaIndex (GPT Index) is a project that provides a central interface to connect your LLM's with external data.
+
+PyPi: 
+- LlamaIndex: https://pypi.org/project/llama-index/.
+- GPT Index (duplicate): https://pypi.org/project/gpt-index/.
+
+Documentation: https://gpt-index.readthedocs.io/en/latest/.
+
+Twitter: https://twitter.com/gpt_index.
+
+Discord: https://discord.gg/dGcwcsnxhU.
+
+LlamaHub (community library of data loaders): https://llamahub.ai
+
+## 🚀 Overview
+
+**NOTE**: This README is not updated as frequently as the documentation. Please check out the documentation above for the latest updates!
+
+### Context
+- LLMs are a phenomenonal piece of technology for knowledge generation and reasoning. They are pre-trained on large amounts of publicly available data.
+- How do we best augment LLMs with our own private data?
+- One paradigm that has emerged is *in-context* learning (the other is finetuning), where we insert context into the input prompt. That way,
+we take advantage of the LLM's reasoning capabilities to generate a response.
+
+To perform LLM's data augmentation in a performant, efficient, and cheap manner, we need to solve two components:
+- Data Ingestion
+- Data Indexing
+
+### Proposed Solution
+
+That's where the **LlamaIndex** comes in. LlamaIndex is a simple, flexible interface between your external data and LLMs. It provides the following tools in an easy-to-use fashion:
+
+- Offers **data connectors** to your existing data sources and data formats (API's, PDF's, docs, SQL, etc.)
+- Provides **indices** over your unstructured and structured data for use with LLM's. 
+These indices help to abstract away common boilerplate and pain points for in-context learning:
+   - Storing context in an easy-to-access format for prompt insertion.
+   - Dealing with prompt limitations (e.g. 4096 tokens for Davinci) when context is too big.
+   - Dealing with text splitting.
+- Provides users an interface to **query** the index (feed in an input prompt) and obtain a knowledge-augmented output.
+- Offers you a comprehensive toolset trading off cost and performance.
+
+
+## 💡 Contributing
+
+Interesting in contributing? See our [Contribution Guide](CONTRIBUTING.md) for more details.
+
+## 📄 Documentation
+
+Full documentation can be found here: https://gpt-index.readthedocs.io/en/latest/. 
+
+Please check it out for the most up-to-date tutorials, how-to guides, references, and other resources! 
+
+
+## 💻 Example Usage
+
+```
+pip install llama-index
+```
+
+Examples are in the `examples` folder. Indices are in the `indices` folder (see list of indices below).
+
+To build a simple vector store index:
+```python
+import os
+os.environ["OPENAI_API_KEY"] = 'YOUR_OPENAI_API_KEY'
+
+from llama_index import GPTSimpleVectorIndex, SimpleDirectoryReader
+documents = SimpleDirectoryReader('data').load_data()
+index = GPTSimpleVectorIndex.from_documents(documents)
+```
+
+To save to and load from disk:
+```python
+# save to disk
+index.save_to_disk('index.json')
+# load from disk
+index = GPTSimpleVectorIndex.load_from_disk('index.json')
+```
+
+To query:
+```python
+index.query("<question_text>?")
+```
+
+## 🔧 Dependencies
+
+The main third-party package requirements are `tiktoken`, `openai`, and `langchain`.
+
+All requirements should be contained within the `setup.py` file. To run the package locally without building the wheel, simply run `pip install -r requirements.txt`. 
+
+
+## 📖 Citation
+
+Reference to cite if you use LlamaIndex in a paper:
+
+```
+@software{Liu_LlamaIndex_2022,
+author = {Liu, Jerry},
+doi = {10.5281/zenodo.1234},
+month = {11},
+title = {{LlamaIndex}},
+url = {https://github.com/jerryjliu/gpt_index},
+year = {2022}
+}
+```