headsup about dependency change

microsoft · Oct 23, 2023 · 7310b7e · 7310b7e
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diff --git a/README.md b/README.md
@@ -13,10 +13,9 @@ This project is a spinoff from [FLAML](https://github.com/microsoft/FLAML).
     <br>
 </p> -->
 
-:fire: autogen has graduated from [FLAML](https://github.com/microsoft/FLAML) into a new project.
-
-<!-- :fire: Heads-up: We're preparing to migrate [autogen](https://microsoft.github.io/FLAML/docs/Use-Cases/Autogen) into a dedicated Github repository. Alongside this move, we'll also launch a dedicated Discord server and a website for comprehensive documentation.
+:fire: Heads-up: pyautogen v0.2 will switch to using openai v1.
 
+<!--
 :fire: FLAML is highlighted in OpenAI's [cookbook](https://github.com/openai/openai-cookbook#related-resources-from-around-the-web).
 
 :fire: [autogen](https://microsoft.github.io/autogen/) is released with support for ChatGPT and GPT-4, based on [Cost-Effective Hyperparameter Optimization for Large Language Model Generation Inference](https://arxiv.org/abs/2303.04673).
@@ -33,7 +32,7 @@ AutoGen is a framework that enables the development of LLM applications using mu
 - It supports **diverse conversation patterns** for complex workflows. With customizable and conversable agents, developers can use AutoGen to build a wide range of conversation patterns concerning conversation autonomy,
   the number of agents, and agent conversation topology.
 - It provides a collection of working systems with different complexities. These systems span a **wide range of applications** from various domains and complexities. This demonstrates how AutoGen can easily support diverse conversation patterns.
-- AutoGen provides a drop-in replacement of `openai.Completion` or `openai.ChatCompletion` as an **enhanced inference API**. It allows easy performance tuning, utilities like API unification and caching, and advanced usage patterns, such as error handling, multi-config inference, context programming, etc.
+- AutoGen provides **enhanced LLM inference**. It offers easy performance tuning, plus utilities like API unification and caching, and advanced usage patterns, such as error handling, multi-config inference, context programming, etc.
 
 AutoGen is powered by collaborative [research studies](https://microsoft.github.io/autogen/docs/Research) from Microsoft, Penn State University, and the University of Washington.
 

diff --git a/website/docs/Getting-Started.md b/website/docs/Getting-Started.md
@@ -44,7 +44,7 @@ The figure below shows an example conversation flow with AutoGen.
 * [Documentation](/docs/Use-Cases/agent_chat).
 
 #### Enhanced LLM Inferences
-Autogen also helps maximize the utility out of the expensive LLMs such as ChatGPT and GPT-4. It offers a drop-in replacement of `openai.Completion` or `openai.ChatCompletion` with powerful functionalites like tuning, caching, error handling, templating. For example, you can optimize generations by LLM with your own tuning data, success metrics and budgets.
+Autogen also helps maximize the utility out of the expensive LLMs such as ChatGPT and GPT-4. It offers enhanced LLM inference with powerful functionalites like tuning, caching, error handling, templating. For example, you can optimize generations by LLM with your own tuning data, success metrics and budgets.
 ```python
 # perform tuning
 config, analysis = autogen.Completion.tune(

diff --git a/website/docs/Installation.md b/website/docs/Installation.md
@@ -26,6 +26,9 @@ AutoGen requires **Python version >= 3.8**. It can be installed from pip:
 ```bash
 pip install pyautogen
 ```
+
+`pyautogen<0.2` requires `openai<1`. Starting from pyautogen v0.2, `openai>=1` is required.
+
 <!--
 or conda:
 ```