From a14d1c02f87d23d9ff5ab36a4c68aeb724499455 Mon Sep 17 00:00:00 2001 From: Hasan Patel Date: Mon, 24 Apr 2023 22:11:29 -0500 Subject: [PATCH] Updated Readme.md (#3477) Corrected some minor grammar issues, changed infra to infrastructure for more clarity. Improved readability --- README.md | 19 ++++++++----------- 1 file changed, 8 insertions(+), 11 deletions(-) diff --git a/README.md b/README.md index 5d1a887a..71214547 100644 --- a/README.md +++ b/README.md @@ -15,12 +15,9 @@ or ## 🤔 What is this? -Large language models (LLMs) are emerging as a transformative technology, enabling -developers to build applications that they previously could not. -But using these LLMs in isolation is often not enough to -create a truly powerful app - the real power comes when you can combine them with other sources of computation or knowledge. +Large language models (LLMs) are emerging as a transformative technology, enabling developers to build applications that they previously could not. However, using these LLMs in isolation is often insufficient for creating a truly powerful app - the real power comes when you can combine them with other sources of computation or knowledge. -This library is aimed at assisting in the development of those types of applications. Common examples of these types of applications include: +This library aims to assist in the development of those types of applications. Common examples of these applications include: **❓ Question Answering over specific documents** @@ -53,23 +50,23 @@ These are, in increasing order of complexity: **📃 LLMs and Prompts:** -This includes prompt management, prompt optimization, generic interface for all LLMs, and common utilities for working with LLMs. +This includes prompt management, prompt optimization, a generic interface for all LLMs, and common utilities for working with LLMs. **🔗 Chains:** -Chains go beyond just a single LLM call, and are sequences of calls (whether to an LLM or a different utility). LangChain provides a standard interface for chains, lots of integrations with other tools, and end-to-end chains for common applications. +Chains go beyond a single LLM call and involve sequences of calls (whether to an LLM or a different utility). LangChain provides a standard interface for chains, lots of integrations with other tools, and end-to-end chains for common applications. **📚 Data Augmented Generation:** -Data Augmented Generation involves specific types of chains that first interact with an external datasource to fetch data to use in the generation step. Examples of this include summarization of long pieces of text and question/answering over specific data sources. +Data Augmented Generation involves specific types of chains that first interact with an external data source to fetch data for use in the generation step. Examples include summarization of long pieces of text and question/answering over specific data sources. **🤖 Agents:** -Agents involve an LLM making decisions about which Actions to take, taking that Action, seeing an Observation, and repeating that until done. LangChain provides a standard interface for agents, a selection of agents to choose from, and examples of end to end agents. +Agents involve an LLM making decisions about which Actions to take, taking that Action, seeing an Observation, and repeating that until done. LangChain provides a standard interface for agents, a selection of agents to choose from, and examples of end-to-end agents. **🧠 Memory:** -Memory is the concept of persisting state between calls of a chain/agent. LangChain provides a standard interface for memory, a collection of memory implementations, and examples of chains/agents that use memory. +Memory refers to persisting state between calls of a chain/agent. LangChain provides a standard interface for memory, a collection of memory implementations, and examples of chains/agents that use memory. **🧐 Evaluation:** @@ -79,6 +76,6 @@ For more information on these concepts, please see our [full documentation](http ## 💁 Contributing -As an open source project in a rapidly developing field, we are extremely open to contributions, whether it be in the form of a new feature, improved infra, or better documentation. +As an open-source project in a rapidly developing field, we are extremely open to contributions, whether it be in the form of a new feature, improved infrastructure, or better documentation. For detailed information on how to contribute, see [here](.github/CONTRIBUTING.md).