From Text to Vectors: Leveraging Weaviate for local RAG Implementation with LlamaIndex

Weaviate provides vector storage and plays an important part in RAG implementation. I'm using local embeddings from the Sentence Transformers library to create vectors for text-based PDF invoices and store them in Weaviate. I explain how integration is done with LlamaIndex to manage data ingest and LLM inference pipeline.

GitHub repo:
https://github.com/katanaml/llm-ollama-llamaindex-invoice-cpu

0:00 Intro
0:38 Weaviate setup
3:42 Data ingest
4:18 Why I use Weaviate
4:56 Data ingest pipeline
8:45 Inference pipeline
10:15 Example
10:59 Summary

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data embeddings implementation inference integration library llamaindex llm part pdf rag storage store text them transformers vector vectors vector storage weaviate