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---
title: Deploy Qdrant RAG
emoji: 📉
colorFrom: blue
colorTo: purple
sdk: docker
pinned: false
license: apache-2.0
---
# Deploying RAG powered by Qdrant as vector db and fastembed for embedding and retrieval
#### ❓ QUESTION #1:
Why do we want to support streaming? What about streaming is important, or useful?
#### ANSWER #1:
The goal of streaming in this context is to render the generated answers in chunks. Thus reducing latency specifically for answers containing a lot of tokens
#### ❓ QUESTION #2:
Why are we using User Session here? What about Python makes us need to use this? Why not just store everything in a global variable?
#### ANSWER #2:
Users sessions are used to keep track of users activity. It can be used to retrieve contxt from previous conversations or separate conversions
#### ❓ Discussion Question #1:
Upload a PDF file of the recent DeepSeek-R1 paper and ask the following questions:
1. What is RL and how does it help reasoning?
2. What is the difference between DeepSeek-R1 and DeepSeek-R1-Zero?
3. What is this paper about?
Does this application pass your vibe check? Are there any immediate pitfalls you're noticing?
#### ❓ Discussion
Not really. He doesnt know what is RL but he can respond to the other questions...
## 🚧 CHALLENGE MODE 🚧
Added Qdrant as vector db
Hugging Face Space link :
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