Add ecosystem page for website (microsoft#803)

* add ecosystem for web

* 1. change to Resources and Examples tables 2. reformat

* fix

* fix

* fix

* update

* update

* update

* update

* update

* Update website/docs/Ecosystem.md

* update

---------

Co-authored-by: “skzhang1” <“[email protected]”>
Co-authored-by: Qingyun Wu <[email protected]>

README.md

@@ -119,7 +119,7 @@ After the repo is cloned.
 The figure below shows an example conversation flow with AutoGen.
 ![Agent Chat Example](https://github.com/microsoft/autogen/blob/main/website/static/img/chat_example.png)
 
-Please find more [code examples](https://microsoft.github.io/autogen/docs/Examples/AgentChat) for this feature.
+Please find more [code examples](https://microsoft.github.io/autogen/docs/Examples#automated-multi-agent-chat) for this feature.
 
 ## Enhanced LLM Inferences
 
@@ -142,7 +142,7 @@ config, analysis = autogen.Completion.tune(
 response = autogen.Completion.create(context=test_instance, **config)
 ```
 
-Please find more [code examples](https://microsoft.github.io/autogen/docs/Examples/Inference) for this feature. -->
+Please find more [code examples](https://microsoft.github.io/autogen/docs/Examples#tune-gpt-models) for this feature. -->
 
 ## Documentation
 

website/docs/Ecosystem.md

@@ -0,0 +1,11 @@
+# Ecosystem
+
+This page lists libraries that have integrations with Autogen for LLM applications using multiple agents in alphabetical order. Including your own integration to this list is highly encouraged. Simply open a pull request with a few lines of text, see the dropdown below for more information.
+
+
+## [MemGPT + AutoGen](https://memgpt.readthedocs.io/en/latest/autogen/)
+
+
+![Agent Chat Example](img/ecosystem-memgpt.png)
+
+Memory-GPT (or MemGPT in short) is a system that intelligently manages different memory tiers in LLMs in order to effectively provide extended context within the LLM's limited context window. For example, MemGPT knows when to push critical information to a vector database and when to retrieve it later in the chat, enabling perpetual conversations. This integration allows you to equip any AutoGen agent with MemGPT.

website/docs/Examples/AgentChat.md → website/docs/Examples.md

@@ -1,4 +1,7 @@
-# Automated Multi Agent Chat
+# Examples
+
+
+## Automated Multi Agent Chat
 
 AutoGen offers conversable agents powered by LLM, tool or human, which can be used to perform tasks collectively via automated chat. This framework allows tool use and human participation via multi-agent conversation.
 Please find documentation about this feature [here](/docs/Use-Cases/agent_chat).
@@ -52,3 +55,13 @@ Links to notebook examples:
    - Multimodal Agent Chat with DALLE and GPT-4V   - [View Notebook](https://github.com/microsoft/autogen/blob/main/notebook/agentchat_dalle_and_gpt4v.ipynb)
    - Multimodal Agent Chat with Llava  - [View Notebook](https://github.com/microsoft/autogen/blob/main/notebook/agentchat_lmm_llava.ipynb)
    - Multimodal Agent Chat with GPT-4V - [View Notebook](https://github.com/microsoft/autogen/blob/main/notebook/agentchat_lmm_gpt-4v.ipynb)
+
+
+## Tune GPT Models
+
+AutoGen also offers a cost-effective hyperparameter optimization technique [EcoOptiGen](https://arxiv.org/abs/2303.04673) for tuning Large Language Models. The research study finds that tuning hyperparameters can significantly improve the utility of them.
+Please find documentation about this feature [here](/docs/Use-Cases/enhanced_inference).
+
+Links to notebook examples:
+* [Optimize for Code Generation](https://github.com/microsoft/autogen/blob/main/notebook/oai_completion.ipynb) | [Open in colab](https://colab.research.google.com/github/microsoft/autogen/blob/main/notebook/oai_completion.ipynb)
+* [Optimize for Math](https://github.com/microsoft/autogen/blob/main/notebook/oai_chatgpt_gpt4.ipynb) | [Open in colab](https://colab.research.google.com/github/microsoft/autogen/blob/main/notebook/oai_chatgpt_gpt4.ipynb)

website/docs/Getting-Started.md

@@ -40,7 +40,7 @@ user_proxy.initiate_chat(assistant, message="Plot a chart of NVDA and TESLA stoc
 The figure below shows an example conversation flow with AutoGen.
 ![Agent Chat Example](/img/chat_example.png)
 
-* [Code examples](/docs/Examples/AgentChat).
+* [Code examples](/docs/Examples).
 * [Documentation](/docs/Use-Cases/agent_chat).
 
 #### Enhanced LLM Inferences
@@ -60,13 +60,13 @@ config, analysis = autogen.Completion.tune(
 response = autogen.Completion.create(context=test_instance, **config)
 ```
 
-* [Code examples](/docs/Examples/Inference).
+* [Code examples](/docs/Examples).
 * [Documentation](/docs/Use-Cases/enhanced_inference).
 
 ### Where to Go Next ?
 
 * Understand the use cases for [multi-agent conversation](/docs/Use-Cases/agent_chat) and [enhanced LLM inference](/docs/Use-Cases/enhanced_inference).
-* Find [code examples](/docs/Examples/AgentChat).
+* Find [code examples](/docs/Examples).
 * Read [SDK](/docs/reference/agentchat/conversable_agent/).
 * Learn about [research](/docs/Research) around AutoGen.
 * [Roadmap](https://github.com/orgs/microsoft/projects/989/views/3)

website/docusaurus.config.js

@@ -44,6 +44,30 @@ module.exports = {
           label: 'GitHub',
           position: 'right',
         },
+        // {
+        //   to: 'examples',
+        //   label: 'Examples',
+        // },
+        {
+          type: 'doc',
+          docId: 'Examples',
+          position: 'left',
+          label: 'Examples',
+        },
+        {
+          label: 'Resources',
+          type: 'dropdown',
+          items: [
+            {
+              type: 'doc',
+              docId: 'Ecosystem',
+            },
+            {
+              href: 'https://huggingface.co/spaces/thinkall/AutoGen_Playground',
+              label: 'PlayGround',
+            },
+          ],
+        },
       ],
     },
     footer: {