RAG (Retrieval-Augmented Generation) Implementation

A Python implementation task to build a complete RAG system for microwave manual assistance using LangChain, FAISS, and Azure OpenAI

🎓 Learning Goals

By completing this task, you will learn:

• How to implement the complete RAG pipeline: Retrieval, Augmentation, and Generation
• How to work with vector embeddings and similarity search using FAISS

📋 Requirements

• Python 3.11+
• pip
• API key for DIAL service

🔧 Setup

1. Install dependencies:

   pip install -r requirements.txt

2. Set your API key:

   • Ensure that you connected to the EPAM VPN
   • Get the DIAL API key here: https://support.epam.com/ess?id=sc_cat_item&table=sc_cat_item&sys_id=910603f1c3789e907509583bb001310c
   • Update task/_constants.py with your API credentials
   • Get available models from: https://ai-proxy.lab.epam.com/openai/models

3. Project structure:

   task/
   ├── _constants.py                # ✅ API configuration
   ├── microwave_manual.txt         # ✅ Knowledge base document
   └── app.py                       # 🚧 TODO - Your main implementation
   

🖌️ Application diagram:

📝 Your Task

If the task in the main branch is hard for you, then switch to the with-detailed-description branch

Complete the implementation in app.py by filling in all the TODO sections:

🔍 Step 1: Vector Store Setup (_setup_vectorstore method)

• Check if FAISS index already exists locally
• Load existing index or create new one
• Handle both scenarios properly

📖 Step 2: Document Processing (_create_new_index method)

• Load the microwave manual text file
• Split documents into chunks using RecursiveCharacterTextSplitter
• Create FAISS vector store from document chunks
• Save the index locally for future use

🔎 Step 3: Context Retrieval (retrieve_context method)

• Implement similarity search with relevance scores
• Extract and format relevant document chunks
• Return formatted context for the LLM

🔗 Step 4: Prompt Augmentation (augment_prompt method)

• Format the user prompt with retrieved context
• Structure the prompt according to the RAG template

🤖 Step 5: Answer Generation (generate_answer method)

• Create proper message structure for the LLM
• Call Azure OpenAI to generate the final answer
• Return the generated response

⚙️ Step 6: Main Configuration

• Set up Azure OpenAI embeddings client
• Configure the chat completion client
• Initialize the RAG system with proper parameters

📊 Understanding the RAG Pipeline

Your implementation will demonstrate the complete RAG workflow:

1. 🔍 Retrieval: Find relevant chunks from the microwave manual based on user query
2. 🔗 Augmentation: Combine retrieved context with user question in a structured prompt
3. 🤖 Generation: Use LLM to generate accurate answer based on the provided context

🔧 Configuration Parameters

You can experiment with these parameters in the retrieve_context method:

• k: Number of relevant chunks to retrieve (default: 4)
• score: Similarity threshold for chunk relevance (default: 0.3)
• chunk_size: Size of document chunks (default: 300)
• chunk_overlap: Overlap between chunks (default: 50)

📚 Key Concepts Covered

• Vector Embeddings: Converting text to numerical vectors for similarity search
• FAISS: Efficient similarity search and clustering of dense vectors
• Document Chunking: Breaking large documents into manageable pieces
• Similarity Search: Finding most relevant content based on query

🎯 Testing Your Implementation

Valid request samples:

What safety precautions should be taken to avoid exposure to excessive microwave energy?

What is the maximum cooking time that can be set on the DW 395 HCG microwave oven?

How should you clean the glass tray of the microwave oven?

What materials are safe to use in this microwave during both microwave and grill cooking modes?

What are the steps to set the clock time on the DW 395 HCG microwave oven?

What is the ECO function on this microwave and how do you activate it?

What are the specifications for proper installation, including the required free space around the oven?

How does the multi-stage cooking feature work, and what types of cooking programs cannot be included in it?

What should you do if food in plastic or paper containers starts smoking during heating?

What is the recommended procedure for removing odors from the microwave oven?

Invalid request samples:

What do you know about the DIALX community?

What do you think about the dinosaur era? Why did they die?

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