Name		Name	Last commit message	Last commit date
Latest commit History 7 Commits
us_census		us_census
LICENSE		LICENSE
README.md		README.md
app.py		app.py

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ObjectBox_VectorDB

Here, I used Objectbox VectorDB, a new and efficient way of vector embeddings, with OpenAI's newly launched GPT-4o(omni) model.

1. Used GPT-4o(omni) model from OpenAI.

2. Took US_cencus PDFs for querying.

3. For word embeddings, used OpenAIEmbeddings.

4. Used ObjectBox VectorDB stores for storing vectors.

5. Finally, created retrieval chain and invoked it for answering the query.

The final experience is really fabulous.

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Detailed description given in the README

objectbox rag vector-database streamlit-webapp langchain retrieval-augmented-generation openai-embeddings gpt4o gpt-4omni

GPL-3.0 license

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