From the course: AI for Telecom: Network Optimization and Security in 5G/Edge Systems

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Exercise: Telecom LLM using RAG architecture for RCA

Exercise: Telecom LLM using RAG architecture for RCA

From the course: AI for Telecom: Network Optimization and Security in 5G/Edge Systems

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Exercise: Telecom LLM using RAG architecture for RCA

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- [Instructor] Welcome to the final lab. The objective is to build a telecom root cause analysis assistant using LLM plus RAG. There are several steps to this lab. In the first step, we will install the required packages, which is the langchain-community chromadb sentence-transformers openai gradio. Then we'll set up the GROQ_API_KEY so that we can retrieve the information using Groq. So in the NRF log files, you have seen there are some commands which are targeted for the bad actors. In the Step 4, we'll set up the chroma vector store, where we will store our embeddings. So in the Step 5, we'll use the custom LangChain, which is compatible wrapper for the Groq client. So in the last step, we will ask our model that, "Hey, can you explain why this IP is causing the NRF fault?" So let us see how we'll apply all these things. Okay, so in the first step, we will see we are just adding the libraries and the dependencies what are needed to execute our lab. In the second step, we are using…

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