Spaces:
Sleeping
Sleeping
| 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 : | |