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davidmyriel
2025-01-26 21:30:24 -05:00
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qdrant-landing/content/documentation/rag-deepseek.md
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@@ -16,10 +16,11 @@ This tutorial demonstrates how to build a **Retrieval-Augmented Generation (RAG)
## Overview
In this tutorial, we will:
1. Combine Qdrant and DeepSeek into a minimal RAG pipeline.
2. Add sample data to a Qdrant vector database. We will store dummy information about different software products.
3. Test different DeepSeek prompts and answers.
4. Enrich DeepSeek prompts with content retrieved from Qdrant.
1. Take sample data and turn it to vectors with FastEmbed.
2. Combine Qdrant and DeepSeek into a minimal RAG pipeline.
3. Add vectors to a Qdrant vector database.
4. Ask DeepSeek different questions and test answer accuracy.
5. Enrich DeepSeek prompts with content retrieved from Qdrant.
#### Architecture: