wehub-resource-sync
50 lines
1.6 KiB
Markdown
50 lines
1.6 KiB
Markdown
<a target="_blank" href="https://lightning.ai/akshay-ddods/studios/rag-using-llama-3-3-by-meta-ai">
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<img src="https://pl-bolts-doc-images.s3.us-east-2.amazonaws.com/app-2/studio-badge.svg" alt="Open In Studio"/>
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</a>
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# LLama3.3-RAG application
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This project leverages a locally Llama 3.3 to build a RAG application to **chat with your docs** and Streamlit to build the UI.
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## Demo
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Watch the demo video:
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[](https://www.youtube.com/watch?v=ZgNJMWipirk)
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## Installation and setup
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**Setup Ollama**:
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```bash
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# setup ollama on linux
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curl -fsSL https://ollama.com/install.sh | sh
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# pull llama 3.3:70B
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ollama pull llama3.3
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```
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**Setup Qdrant VectorDB**
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```bash
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docker run -p 6333:6333 -p 6334:6334 \
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-v $(pwd)/qdrant_storage:/qdrant/storage:z \
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qdrant/qdrant
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```
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**Install Dependencies**:
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Ensure you have Python 3.11 or later installed.
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```bash
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pip install streamlit ollama llama-index-vector-stores-qdrant
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```
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---
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## 📬 Stay Updated with Our Newsletter!
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**Get a FREE Data Science eBook** 📖 with 150+ essential lessons in Data Science when you subscribe to our newsletter! Stay in the loop with the latest tutorials, insights, and exclusive resources. [Subscribe now!](https://join.dailydoseofds.com)
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[](https://join.dailydoseofds.com)
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---
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## Contribution
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Contributions are welcome! Please fork the repository and submit a pull request with your improvements.
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