Merge pull request #1 from harishmohanraj/mintlify-migration

Mintlify migration

website/README.md

@@ -1,40 +1,13 @@
-# Website
+## Development
 
-This website is built using [Docusaurus 3](https://docusaurus.io/), a modern static website generator.
+Install the [Mintlify CLI](https://www.npmjs.com/package/mintlify) to preview the documentation changes locally. To install, use the following command
 
-## Prerequisites
-
-To build and test documentation locally, begin by downloading and installing [Node.js](https://nodejs.org/en/download/), and then installing [Yarn](https://classic.yarnpkg.com/en/).
-On Windows, you can install via the npm package manager (npm) which comes bundled with Node.js:
-
-```console
-npm install --global yarn
 ```
-
-## Installation
-
-```console
-pip install pydoc-markdown pyyaml colored
-cd website
-yarn install
+npm install
 ```
 
-### Install Quarto
-
-`quarto` is used to render notebooks.
-
-Install it [here](https://github.com/quarto-dev/quarto-cli/releases).
+Run the following command at the root of your documentation (where mint.json is)
 
-> Note: Ensure that your `quarto` version is `1.5.23` or higher.
-
-## Local Development
-
-Navigate to the `website` folder and run:
-
-```console
-pydoc-markdown
-python ./process_notebooks.py render
-yarn start
 ```
-
-This command starts a local development server and opens up a browser window. Most changes are reflected live without having to restart the server.
+npm run mintlify:dev
+```

website/blog/2023-07-14-Local-LLMs/index.md → website/blog/2023-07-14-Local-LLMs/index.mdx

@@ -64,7 +64,7 @@ class CompletionResponseStreamChoice(BaseModel):
 ```
 
 
-## Interact with model using `oai.Completion` (requires openai<1)
+## Interact with model using `oai.Completion` (requires openai{'<'}1)
 
 Now the models can be directly accessed through openai-python library as well as `autogen.oai.Completion` and `autogen.oai.ChatCompletion`.
 

website/blog/2024-02-02-AutoAnny/index.mdx

@@ -5,10 +5,8 @@ authors:
 tags: [AutoGen]
 ---
 
-import AutoAnnyLogo from './img/AutoAnnyLogo.jpg';
-
 <div style={{ display: "flex", justifyContent: "center" }}>
-  <img src={AutoAnnyLogo} alt="AutoAnny Logo" style={{ width: "250px" }} />
+  <img src='./img/AutoAnnyLogo.jpg' alt="AutoAnny Logo" style={{ width: "250px" }} />
 </div>
 <p align="center"><em>Anny is a Discord bot powered by AutoGen to help AutoGen's Discord server.</em></p>
 

website/blog/2024-03-03-AutoGen-Update/index.mdx

@@ -38,10 +38,10 @@ Many users have deep understanding of the value in different dimensions, such as
 
 > The same reason autogen is significant is the same reason OOP is a good idea. Autogen packages up all that complexity into an agent I can create in one line, or modify with another.
 
-<!--
+{/* 
 I had lots of ideas I wanted to implement, but it needed a framework like this
 and I am just not the guy to make such a robust and intelligent framework.
--->
+*/}
 
 Over time, more and more users share their experiences in using or contributing to autogen.
 

website/docs/Examples.md → website/docs/Examples.mdx

@@ -42,7 +42,7 @@ Links to notebook examples:
 ### Applications
 
 - Automated Continual Learning from New Data - [View Notebook](/docs/notebooks/agentchat_stream)
-<!-- - [OptiGuide](https://github.com/microsoft/optiguide) - Coding, Tool Using, Safeguarding & Question Answering for Supply Chain Optimization -->
+{/*  - [OptiGuide](https://github.com/microsoft/optiguide) - Coding, Tool Using, Safeguarding & Question Answering for Supply Chain Optimization */}
 - [AutoAnny](https://github.com/ag2ai/build-with-ag2/tree/main/samples/apps/auto-anny) - A Discord bot built using AutoGen
 
 ### RAG
@@ -98,7 +98,7 @@ Links to notebook examples:
 
 ### Long Context Handling
 
-<!-- - Conversations with Chat History Compression Enabled - [View Notebook](https://github.com/ag2ai/ag2/blob/main/notebook/agentchat_compression.ipynb) -->
+{/* - Conversations with Chat History Compression Enabled - [View Notebook](https://github.com/ag2ai/ag2/blob/main/notebook/agentchat_compression.ipynb) */}
 - Long Context Handling as A Capability - [View Notebook](/docs/notebooks/agentchat_transform_messages)
 
 ### Evaluation and Assessment

website/docs/FAQ.mdx

@@ -1,8 +1,7 @@
-import TOCInline from "@theme/TOCInline";
-
-# Frequently Asked Questions
-
-<TOCInline toc={toc} />
+---
+title: Frequently Asked Questions
+sidebarTitle: FAQ
+---
 
 ## Install the correct package - `autogen`
 
@@ -34,8 +33,8 @@ In version >=1, OpenAI renamed their `api_base` parameter to `base_url`. So for
 
 Yes. You currently have two options:
 
-- Autogen can work with any API endpoint which complies with OpenAI-compatible RESTful APIs - e.g. serving local LLM via FastChat or LM Studio. Please check https://ag2ai.github.io/ag2/blog/2023/07/14/Local-LLMs for an example.
-- You can supply your own custom model implementation and use it with Autogen. Please check https://ag2ai.github.io/ag2/blog/2024/01/26/Custom-Models for more information.
+- Autogen can work with any API endpoint which complies with OpenAI-compatible RESTful APIs - e.g. serving local LLM via FastChat or LM Studio. Please check [here](/blog/2023-07-14-Local-LLMs) for an example.
+- You can supply your own custom model implementation and use it with Autogen. Please check [here](/blog/2024-01-26-Custom-Models) for more information.
 
 ## Handle Rate Limit Error and Timeout Error
 
@@ -52,9 +51,9 @@ When you call `initiate_chat` the conversation restarts by default. You can use
 
 ## `max_consecutive_auto_reply` vs `max_turn` vs `max_round`
 
-- [`max_consecutive_auto_reply`](https://ag2ai.github.io/ag2/docs/reference/agentchat/conversable_agent#max_consecutive_auto_reply) the maximum number of consecutive auto replie (a reply from an agent without human input is considered an auto reply). It plays a role when `human_input_mode` is not "ALWAYS".
-- [`max_turns` in `ConversableAgent.initiate_chat`](https://ag2ai.github.io/ag2/docs/reference/agentchat/conversable_agent#initiate_chat) limits the number of conversation turns between two conversable agents (without differentiating auto-reply and reply/input from human)
-- [`max_round` in GroupChat](https://ag2ai.github.io/ag2/docs/reference/agentchat/groupchat#groupchat-objects) specifies the maximum number of rounds in a group chat session.
+- [`max_consecutive_auto_reply`](/docs/reference/agentchat/conversable_agent#max_consecutive_auto_reply) the maximum number of consecutive auto replie (a reply from an agent without human input is considered an auto reply). It plays a role when `human_input_mode` is not "ALWAYS".
+- [`max_turns` in `ConversableAgent.initiate_chat`](/docs/reference/agentchat/conversable_agent#initiate_chat) limits the number of conversation turns between two conversable agents (without differentiating auto-reply and reply/input from human)
+- [`max_round` in GroupChat](/docs/reference/agentchat/groupchat#groupchat-objects) specifies the maximum number of rounds in a group chat session.
 
 ## How do we decide what LLM is used for each agent? How many agents can be used? How do we decide how many agents in the group?
 
@@ -159,7 +158,7 @@ Explanation: Per [this gist](https://gist.github.com/defulmere/8b9695e415a442710
 
 (from [issue #478](https://github.com/microsoft/autogen/issues/478))
 
-See here https://ag2ai.github.io/ag2/docs/reference/agentchat/conversable_agent/#register_reply
+See here /docs/reference/agentchat/conversable_agent/#register_reply
 
 For example, you can register a reply function that gets called when `generate_reply` is called for an agent.
 
@@ -188,11 +187,11 @@ In the above, we register a `print_messages` function that is called each time t
 
 ## How to get last message ?
 
-Refer to https://ag2ai.github.io/ag2/docs/reference/agentchat/conversable_agent/#last_message
+Refer to /docs/reference/agentchat/conversable_agent/#last_message
 
 ## How to get each agent message ?
 
-Please refer to https://ag2ai.github.io/ag2/docs/reference/agentchat/conversable_agent#chat_messages
+Please refer to /docs/reference/agentchat/conversable_agent#chat_messages
 
 ## When using autogen docker, is it always necessary to reinstall modules?
 
@@ -285,4 +284,4 @@ RUN apt-get clean && \
     apt-get install sudo git npm # and whatever packages need to be installed in this specific version of the devcontainer
 ```
 
-This is a combination of StackOverflow suggestions [here](https://stackoverflow.com/a/48777773/2114580) and [here](https://stackoverflow.com/a/76092743/2114580).
+This is a combination of StackOverflow suggestions [here](https://stackoverflow.com/a/48777773/2114580) and [here](https://stackoverflow.com/a/76092743/2114580).

website/docs/Gallery.mdx

@@ -2,8 +2,8 @@
 hide_table_of_contents: true
 ---
 
-import GalleryPage from '../src/components/GalleryPage';
-import galleryData from "../src/data/gallery.json";
+import GalleryPage from "/snippets/components/GalleryPage.js";
+import galleryData from "/snippets/data/gallery.json";
 
 # Gallery
 

website/docs/Getting-Started.mdx

@@ -1,7 +1,6 @@
-import Tabs from "@theme/Tabs";
-import TabItem from "@theme/TabItem";
-
-# Getting Started
+---
+title: "Getting Started"
+---
 
 AG2 (formerly AutoGen) is an open-source programming framework for building AI agents and facilitating
 cooperation among multiple agents to solve tasks. AG2 aims to provide an easy-to-use
@@ -10,7 +9,7 @@ like PyTorch for Deep Learning. It offers features such as agents that can conve
 with other agents, LLM and tool use support, autonomous and human-in-the-loop workflows,
 and multi-agent conversation patterns.
 
-![AG2 Overview](/img/autogen_agentchat.png)
+![AG2 Overview](/static/img/autogen_agentchat.png)
 
 ### Main Features
 
@@ -37,12 +36,15 @@ Microsoft, Penn State University, and University of Washington.
 ```sh
 pip install autogen
 ```
-:::tip
-You can also install with different [optional dependencies](/docs/installation/Optional-Dependencies).
-:::
+<div class="tip">
+  <Tip>
+    You can also install with different [optional
+    dependencies](/website/docs/installation/Optional-Dependencies).
+  </Tip>
+</div>
 
 <Tabs>
-    <TabItem value="nocode" label="No code execution" default>
+    <Tab title="No code execution">
 
 ```python
 import os
@@ -59,12 +61,14 @@ user_proxy.initiate_chat(
 )
 ```
 
-    </TabItem>
-    <TabItem value="local" label="Local execution" default>
+    </Tab>
+    <Tab title="Local execution">
 
-:::warning
-When asked, be sure to check the generated code before continuing to ensure it is safe to run.
-:::
+<div class="warning">
+    <Warning>
+    When asked, be sure to check the generated code before continuing to ensure it is safe to run.
+    </Warning>
+</div>
 
 ```python
 import os
@@ -85,8 +89,8 @@ user_proxy.initiate_chat(
 )
 ```
 
-    </TabItem>
-    <TabItem value="docker" label="Docker execution" default>
+    </Tab>
+    <Tab title="Docker execution">
 
 ```python
 import os
@@ -110,13 +114,16 @@ with autogen.coding.DockerCommandLineCodeExecutor(work_dir="coding") as code_exe
 
 Open `coding/plot.png` to see the generated plot.
 
-    </TabItem>
+    </Tab>
 
 </Tabs>
 
-:::tip
-Learn more about configuring LLMs for agents [here](/docs/topics/llm_configuration).
-:::
+<div class="tip">
+  <Tip>
+    Learn more about configuring LLMs for agents
+    [here](/website/docs/topics/llm_configuration).
+  </Tip>
+</div>
 
 #### Multi-Agent Conversation Framework
 
@@ -125,7 +132,7 @@ By automating chat among multiple capable agents, one can easily make them colle
 
 The figure below shows an example conversation flow with AG2.
 
-![Agent Chat Example](/img/chat_example.png)
+![Agent Chat Example](/static/img/chat_example.png)
 
 ### Where to Go Next?
 
@@ -141,7 +148,7 @@ The figure below shows an example conversation flow with AG2.
 If you like our project, please give it a [star](https://github.com/ag2ai/ag2) on GitHub. If you are interested in contributing, please read [Contributor's Guide](/docs/contributor-guide/contributing).
 
 <iframe
-  src="https://ghbtns.com/github-btn.html?user=ag2ai&amp;repo=autogen&amp;type=star&amp;count=true&amp;size=large"
+  src="https://ghbtns.com/github-btn.html?user=ag2ai&amp;repo=ag2&amp;type=star&amp;count=true&amp;size=large"
   frameborder="0"
   scrolling="0"
   width="170"

website/docs/Migration-Guide.md → website/docs/Migration-Guide.mdx

@@ -1,4 +1,6 @@
-# Migration Guide
+---
+title: Migration Guide
+---
 
 ## Migrating to 0.2
 
@@ -26,7 +28,7 @@ autogen.runtime_logging.start()
 # Stop logging
 autogen.runtime_logging.stop()
 ```
-Checkout [Logging documentation](https://ag2ai.github.io/ag2/docs/Use-Cases/enhanced_inference#logging) and [Logging example notebook](https://github.com/ag2ai/ag2/blob/main/notebook/agentchat_logging.ipynb) to learn more.
+Checkout [Logging documentation](/docs/Use-Cases/enhanced_inference#logging) and [Logging example notebook](https://github.com/ag2ai/ag2/blob/main/notebook/agentchat_logging.ipynb) to learn more.
 
 Inference parameter tuning can be done via [`flaml.tune`](https://microsoft.github.io/FLAML/docs/Use-Cases/Tune-User-Defined-Function).
 - `seed` in autogen is renamed into `cache_seed` to accommodate the newly added `seed` param in openai chat completion api. `use_cache` is removed as a kwarg in `OpenAIWrapper.create()` for being automatically decided by `cache_seed`: int | None. The difference between autogen's `cache_seed` and openai's `seed` is that:

website/docs/Research.md → website/docs/Research.mdx

@@ -1,4 +1,6 @@
-# Research
+---
+title: Research
+---
 
 For technical details, please check our technical report and research publications.
 

website/docs/Use-Cases/agent_chat.md → website/docs/Use-Cases/agent_chat.mdx

@@ -1,4 +1,6 @@
-# Multi-agent Conversation Framework
+---
+title: "Multi-agent Conversation Framework"
+---
 
 AutoGen offers a unified multi-agent conversation framework as a high-level abstraction of using foundation models. It features capable, customizable and conversable agents which integrate LLMs, tools, and humans via automated agent chat.
 By automating chat among multiple capable agents, one can easily make them collectively perform tasks autonomously or with human feedback, including tasks that require using tools via code.

website/docs/Use-Cases/enhanced_inference.md → website/docs/Use-Cases/enhanced_inference.mdx

@@ -1,10 +1,12 @@
-# Enhanced Inference
+---
+title: "Enhanced Inference"
+---
 
 `autogen.OpenAIWrapper` provides enhanced LLM inference for `openai>=1`.
 `autogen.Completion` is a drop-in replacement of `openai.Completion` and `openai.ChatCompletion` for enhanced LLM inference using `openai<1`.
 There are a number of benefits of using `autogen` to perform inference: performance tuning, API unification, caching, error handling, multi-config inference, result filtering, templating and so on.
 
-## Tune Inference Parameters (for openai<1)
+## Tune Inference Parameters (for openai{'<'}1)
 
 Find a list of examples in this page: [Tune Inference Parameters Examples](../Examples.md#inference-hyperparameters-tuning)
 
@@ -68,7 +70,7 @@ Users can specify the (optional) search range for each hyperparameter.
 1. model. Either a constant str, or multiple choices specified by `flaml.tune.choice`.
 1. prompt/messages. Prompt is either a str or a list of strs, of the prompt templates. messages is a list of dicts or a list of lists, of the message templates.
 Each prompt/message template will be formatted with each data instance. For example, the prompt template can be:
-"{problem} Solve the problem carefully. Simplify your answer as much as possible. Put the final answer in \\boxed{{}}."
+"\{problem\} Solve the problem carefully. Simplify your answer as much as possible. Put the final answer in \\boxed\{\{}}."
 And `{problem}` will be replaced by the "problem" field of each data instance.
 1. max_tokens, n, best_of. They can be constants, or specified by `flaml.tune.randint`, `flaml.tune.qrandint`, `flaml.tune.lograndint` or `flaml.qlograndint`. By default, max_tokens is searched in [50, 1000); n is searched in [1, 100); and best_of is fixed to 1.
 1. stop. It can be a str or a list of strs, or a list of lists of strs or None. Default is None.

website/docs/autogen-studio/faqs.md → website/docs/autogen-studio/faqs.mdx

@@ -1,4 +1,7 @@
-# AutoGen Studio FAQs
+---
+title: FAQs
+sidebarTitle: FAQs
+---
 
 ## Q: How do I specify the directory where files(e.g. database) are stored?