This project has been archived by its maintainers, and is no longer receiving any updates.
pgvector-rag
A simple library for working with RAG documents using pg_vector in PostgreSQL.
Documents will pass through an optimization stage where the content is converted to markdown, submitted to Anthropic's Sonet 3.5 to optimize the content, and the response is used to a store a conside revision of the document.
OpenAI's text-embedding-3-small is used to generate the embeddings for the
for the document and used to generate the embeddings to compare against in
the database.
Schema is contained in the postgres directory.
Install with pip install pgvector-rag.
1 maintainer
Release files for pgvector-rag 0.5.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| pgvector_rag-0.5.0.tar.gz | 9.7 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| pgvector_rag-0.5.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 16.1 kB
Release files / pgvector_rag-0.5.0.tar.gz
| Download URL | pgvector_rag-0.5.0.tar.gz |
|---|---|
| Size | 9.7 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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twine/6.0.1 CPython/3.12.7
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Release files / pgvector_rag-0.5.0-py3-none-any.whl
| Download URL | pgvector_rag-0.5.0-py3-none-any.whl |
|---|---|
| Size | 6.4 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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BLAKE2b-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
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| Uploaded via |
twine/6.0.1 CPython/3.12.7
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