Build a RAG application with Runware and LangChain

1. 1Install Runware and LangChain using pip
2. 2Configure a LangChain LLM agent with your own documents
3. 3Build a RAG pipeline using Runware to retrieve relevant documents
4. 4Test the RAG application with sample queries
5. 5Fine-tune the LLM model for better performance

Developers and data scientists on a team can benefit from this tutorial to improve their LLM-based applications with custom document retrieval

💡 RAG applications can significantly improve the accuracy of LLMs by connecting them to relevant custom documents

🤖 Build a RAG app with Runware & LangChain to supercharge your LLMs with custom docs! 📄