fix: update docs (#477)

README.md

@@ -14,29 +14,6 @@ Embedchain is a framework to easily create LLM powered bots over any dataset. If
 pip install embedchain
 ```
 
-## 🔥 Latest
-
-- **[2023/07/19]** Released support for 🦙 `llama2` model. Start creating your `llama2` based bots like this:
-
-  ```python
-  import os
-
-  from embedchain import Llama2App
-
-  os.environ['REPLICATE_API_TOKEN'] = "REPLICATE API TOKEN"
-
-  zuck_bot = Llama2App()
-
-  # Embed your data
-  zuck_bot.add("https://www.youtube.com/watch?v=Ff4fRgnuFgQ")
-  zuck_bot.add("https://en.wikipedia.org/wiki/Mark_Zuckerberg")
-
-  # Nice, your bot is ready now. Start asking questions to your bot.
-  zuck_bot.query("Who is Mark Zuckerberg?")
-  # Answer: Mark Zuckerberg is an American internet entrepreneur and business magnate. He is the co-founder and CEO of Facebook.
-  ```
-
-
 ## 🔍 Demo
 
 Try out embedchain in your browser:
@@ -51,6 +28,16 @@ The documentation for embedchain can be found at [docs.embedchain.ai](https://do
 
 Embedchain empowers you to create chatbot models similar to ChatGPT, using your own evolving dataset.
 
+### Data Types Supported
+
+* Youtube video
+* PDF file
+* Web page
+* Sitemap
+* Doc file
+* Code documentation website loader
+* Notion
+
 ### Queries
 
 For example, you can use Embedchain to create an Elon Musk bot using the following code: