fix typo and update news

README.md

@@ -15,6 +15,7 @@
     <img src="https://github.com/microsoft/autogen/blob/main/website/static/img/flaml.svg"  width=200>
     <br>
 </p> -->
+:fire: May 29, 2024: DeepLearning.ai launched a new short course [AI Agentic Design Patterns with AutoGen](https://info.deeplearning.ai/new-course-on-agents-enroll-in-ai-agentic-design-patterns-with-autogen), made in collaboration with Microsoft and Penn State University, and taught by AutoGen creators [Chi Wang](https://github.com/sonichi) and [Qingyun Wu](https://github.com/qingyun-wu).
 
 :fire: May 24, 2024: Foundation Capital published an article on [Forbes: The Promise of Multi-Agent AI](https://www.forbes.com/sites/joannechen/2024/05/24/the-promise-of-multi-agent-ai/?sh=2c1e4f454d97) and a video [AI in the Real World Episode 2: Exploring Multi-Agent AI and AutoGen with Chi Wang](https://www.youtube.com/watch?v=RLwyXRVvlNk).
 
@@ -75,7 +76,7 @@ AutoGen is a framework that enables the development of LLM applications using mu
 - It provides a collection of working systems with different complexities. These systems span a [wide range of applications](https://microsoft.github.io/autogen/docs/Use-Cases/agent_chat#diverse-applications-implemented-with-autogen) from various domains and complexities. This demonstrates how AutoGen can easily support diverse conversation patterns.
 - AutoGen provides [enhanced LLM inference](https://microsoft.github.io/autogen/docs/Use-Cases/enhanced_inference#api-unification). It offers 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.
+AutoGen is created out of collaborative [research](https://microsoft.github.io/autogen/docs/Research) from Microsoft, Penn State University, and the University of Washington.
 
 <p align="right" style="font-size: 14px; color: #555; margin-top: 20px;">
   <a href="#readme-top" style="text-decoration: none; color: blue; font-weight: bold;">

autogen/agentchat/contrib/gpt_assistant_agent.py

@@ -5,8 +5,6 @@
 from collections import defaultdict
 from typing import Any, Dict, List, Optional, Tuple, Union
 
-import openai
-
 from autogen import OpenAIWrapper
 from autogen.agentchat.agent import Agent
 from autogen.agentchat.assistant_agent import AssistantAgent, ConversableAgent

website/blog/2024-05-24-Agent/index.mdx

@@ -120,7 +120,7 @@ simulations are good examples, too.
 
 ### Cost of multi-agents
 
-Very complex mult-agent systems with leading frontier models are expensive, but compared to having humans accomplish the same task they can be exponentially more affordable.
+Very complex multi-agent systems with leading frontier models are expensive, but compared to having humans accomplish the same task they can be exponentially more affordable.
 
 > While not inexpensive to operate, our multi-agent powered venture analysis system at BetterFutureLabs is far more affordable and exponentially faster than human analysts performing a comparable depth of analysis.
 >

website/docs/topics/groupchat/resuming_groupchat.ipynb

@@ -731,8 +731,9 @@
  ],
  "metadata": {
   "front_matter": {
-   "description": "Custom Speaker Selection Function",
+   "description": "Resume Group Chat",
    "tags": [
+    "resume",
     "orchestration",
     "group chat"
    ]