Update README.md

README.md

@@ -24,44 +24,6 @@ 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
 
@@ -93,25 +55,3 @@ 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}
-}
-```