update readme (#6304)

README.md

@@ -36,22 +36,22 @@ This library aims to assist in the development of those types of applications. C
 
 **❓ Question Answering over specific documents**
 
-- [Documentation](https://langchain.readthedocs.io/en/latest/use_cases/question_answering.html)
+- [Documentation](https://python.langchain.com/docs/use_cases/question_answering/)
 - End-to-end Example: [Question Answering over Notion Database](https://github.com/hwchase17/notion-qa)
 
 **💬 Chatbots**
 
-- [Documentation](https://langchain.readthedocs.io/en/latest/use_cases/chatbots.html)
+- [Documentation](https://python.langchain.com/docs/use_cases/chatbots/)
 - End-to-end Example: [Chat-LangChain](https://github.com/hwchase17/chat-langchain)
 
 **🤖 Agents**
 
-- [Documentation](https://langchain.readthedocs.io/en/latest/modules/agents.html)
+- [Documentation](https://python.langchain.com/docs/modules/agents/)
 - End-to-end Example: [GPT+WolframAlpha](https://huggingface.co/spaces/JavaFXpert/Chat-GPT-LangChain)
 
 ## 📖 Documentation
 
-Please see [here](https://langchain.readthedocs.io/en/latest/?) for full documentation on:
+Please see [here](https://python.langchain.com) for full documentation on:
 
 - Getting started (installation, setting up the environment, simple examples)
 - How-To examples (demos, integrations, helper functions)
@@ -87,7 +87,7 @@ Memory refers to persisting state between calls of a chain/agent. LangChain prov
 
 [BETA] Generative models are notoriously hard to evaluate with traditional metrics. One new way of evaluating them is using language models themselves to do the evaluation. LangChain provides some prompts/chains for assisting in this.
 
-For more information on these concepts, please see our [full documentation](https://langchain.readthedocs.io/en/latest/).
+For more information on these concepts, please see our [full documentation](https://python.langchain.com).
 
 ## 💁 Contributing