feat: add langchain and cohere overview

pages/guides/agents/intermediate/langchain-rag-agent.mdx

@@ -19,7 +19,7 @@ The uAgents and AI Engine libraries offer a decentralized and modular framework
 
     <Callout type="info" emoji="ℹ️">
       Also, rememeber that you can have a look and eventually download the source code used within this guide from Github [here ↗️](https://github.com/fetchai/uAgent-Examples/tree/main/1-uagents/examples/intermediate/langchain-rag/src).
-    </Callout>
+    </Callout>  
 
 **Let's dive into the LangChain RAG Agents development!**
 
@@ -39,6 +39,27 @@ Make sure you have read the following resources before going on with this guide:
     - [Agentverse Functions ↗️](/guides/agents/intermediate/agent-functions)
     - [Register an Agent Function on the Agentverse ↗️](/guides/agentverse/agentverse-functions/registering-agent-services)
 
+### LangChain and Cohere Overview
+
+#### LangChain
+
+In the context of a RAG agent, LangChain helps by:
+
+- **Document Loading and Parsing**: It processes and structures data from web pages.
+- **Vector Storage**: LangChain indexes documents into vectors, making it easier to perform similarity searches.
+- **Question Answering**: It generates answers by querying the indexed data, providing context-aware responses.
+
+#### Cohere
+
+Cohere offers **advanced NLP models** that assist in refining the answers generated by LangChain:
+
+- **Contextual Compression**: It filters and prioritizes data based on relevance, ensuring that the agent focuses on the most important information.
+- **Enhanced Accuracy**: Cohere's NLP models improve the quality of the generated answers by understanding the context of the query more effectively.
+
+#### How These Work Together in a RAG Agent
+
+By combining **LangChain** for document retrieval and **Cohere** for NLP enhancement, this setup allows our uagents to process complex queries with context-aware responses, improving accuracy and user experience. LangChain handles the heavy lifting of document parsing and information retrieval, while Cohere fine-tunes the response to ensure high-quality, relevant answers.
+
 ## API KEYs
 
 You will need **two API keys** to correctly go through this guide: