Merge branch 'main' into tutorials

README.md

@@ -1,23 +1,37 @@
-# Getting Started with Instructor
+# Welcome to Instructor - Your Gateway to Structured Outputs with OpenAI
 
 _Structured extraction in Python, powered by OpenAI's function calling api, designed for simplicity, transparency, and control._
 
 ---
 
-[Star us on Github!](https://jxnl.github.io/instructor).
+[Star us on Github!](www.github.com/jxnl/instructor).
 
-[![Buy Me a Coffee](https://img.shields.io/badge/Buy%20Me%20a%20Coffee-Donate-yellow)](https://www.buymeacoffee.com/jxnlco)
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-Built to interact solely with openai's function calling api from python. It's designed to be intuitive, easy to use, and provide great visibility into your prompts.
+Dive into the world of Python-based structured extraction, empowered by OpenAI's cutting-edge function calling API. Instructor stands out for its simplicity, transparency, and user-centric design. Whether you're a seasoned developer or just starting out, you'll find Instructor's approach intuitive and its results insightful.
+
+## Get Started in Moments
+
+Installing Instructor is a breeze. Just run `pip install instructor` in your terminal and you're on your way to a smoother data handling experience.
+
+## How Instructor Enhances Your Workflow
+
+Our `instructor.patch` for the `OpenAI` class introduces three key enhancements:
+
+- **Response Mode:** Specify a Pydantic model to streamline data extraction.
+- **Max Retries:** Set your desired number of retry attempts for requests.
+- **Validation Context:** Provide a context object for enhanced validator access.
+  A Glimpse into Instructor's Capabilities
+
+!!! note "Using Validators"
+
+    Learn more about validators checkout our blog post [Good llm validation is just good validation](https://jxnl.github.io/instructor/blog/2023/10/23/good-llm-validation-is-just-good-validation/)
+
+With Instructor, your code becomes more efficient and readable. Here’s a quick peek:
 
 ## Usage
 
@@ -87,27 +101,6 @@ model = await aclient.chat.completions.create(
 assert isinstance(model, UserExtract)
 ```
 
-## Installation
-
-To get started you need to install it using `pip`. Run the following command in your terminal:
-
-```sh
-$ pip install instructor
-```
-
-## Quick Start
-
-To simplify your work with OpenAI we offer a patching mechanism for the `ChatCompletion` class.
-The patch introduces 3 features to the `ChatCompletion` class:
-
-1. The `response_model` parameter, which allows you to specify a Pydantic model to extract data into.
-2. The `max_retries` parameter, which allows you to specify the number of times to retry the request if it fails.
-3. The `validation_context` parameter, which allows you to specify a context object that validators have access to.
-
-!!! note "Using Validators"
-
-    Learn more about validators checkout our blog post [Good llm validation is just good validation](https://jxnl.github.io/instructor/blog/2023/10/23/good-llm-validation-is-just-good-validation/)
-
 ### Step 1: Patch the client
 
 First, import the required libraries and apply the patch function to the OpenAI module. This exposes new functionality with the response_model parameter.
@@ -190,9 +183,9 @@ answer
 Here, the `UserDetails` model is passed as the `response_model`, and `max_retries` is set to 2.
 
 ```python
-from openai import OpenAI
 import instructor
 
+from openai import OpenAI
 from pydantic import BaseModel, field_validator
 
 # Apply the patch to the OpenAI client
@@ -221,6 +214,25 @@ model = client.chat.completions.create(
 assert model.name == "JASON"
 ```
 
+## Contributing
+
+If you want to help out checkout some of the issues marked as `good-first-issue` or `help-wanted`. Found [here](https://github.com/jxnl/instructor/labels/good%20first%20issue). They could be anything from code improvements, a guest blog post, or a new cook book.
+
 ## License
 
 This project is licensed under the terms of the MIT License.
+
+# Contributors
+
+<!-- ALL-CONTRIBUTORS-LIST:START - Do not remove or modify this section -->
+<!-- prettier-ignore-start -->
+<!-- markdownlint-disable -->
+
+<!-- markdownlint-restore -->
+<!-- prettier-ignore-end -->
+
+<!-- ALL-CONTRIBUTORS-LIST:END -->
+
+<a href="https://github.com/jxnl/instructor/graphs/contributors">
+  <img src="https://contrib.rocks/image?repo=jxnl/instructor" />
+</a>

docs/blog/index.md

@@ -0,0 +1,18 @@
+# Welcome to the Instructor Blog
+
+The goal of the blog is to capture some content that does not neatly fit within documentation or the cookbooks.
+
+## Advanced Topics
+
+- [Query Understanding and Expansion for RAG](posts/rag-and-beyond.md)
+- [GPT-4 Level summarization with GPT3.5 Finetuning](posts/chain-of-density.md)
+- [Deepdive on LLM Guardrails / Validation](posts/validation-part1.md)
+- [A Guide to Fine-Tuning and Distillation](posts/distilation-part1.md)
+
+## Learning Python
+
+- [Understanding Batch Processing with async](posts/learn-async.md)
+
+## Talks
+
+- [AI Engineering Summit 2023](posts/aisummit-2023.md)