vecsync 0.1.0

A simple command-line utility for synchronizing documents to vector storage for LLM interaction.

vecsync

A simple command-line utility for synchronizing documents to vector storage for LLM interaction. Vecsync helps you quickly chat with papers, journals, and other documents with minimal overhead.

• 📄 Upload a local collection of PDFs to a remote vector store
• ✅ Automatically add and remove remote files to match local documents
• ☺️ Simplify platform specific complexities
• 👀 Synchronize with a Zotero collection
• 💬 Chat with documents from command line

Currently vecsync only supports OpenAI vector stores and chat assistants in early development.

Getting Started

Installation

Install vecsync from PyPI.

pip install vecsync

Set your OpenAI API key environment.

export OPENAI_API_KEY=...

You can also define the key via .env file using dotenv

echo "OPENAI_API_KEY=…" > .env

Usage

Sync from local file path

cd path/to/pdfs

vecsync

Syncing 2 files from local to OpenAI
Uploading 2 files to OpenAI file storage
Attaching 2 files to OpenAI vector store

🏁 Sync results:
Saved: 2 | Deleted: 0 | Skipped: 0 
Remote count: 2
Duration: 8.93 seconds

Sync from a Zotero collection

vecsync -s zotero

Enter the path to your Zotero directory (Default: /Users/jbencina/Zotero): 

Available collections:
[1]: My research
Enter the collection ID to sync (Default: 1): 

Syncing 15 files from local to OpenAI
Uploading 15 files to OpenAI file storage
Attaching 15 files to OpenAI vector store

🏁 Sync results:
Saved: 15 | Deleted: 0 | Skipped: 0 
Remote count: 15
Duration: 57.99 seconds

Interactive setup options are saved and omitted from future syncs

❯ vecsync -s zotero       

Syncing 15 files from local to OpenAI

🏁 Sync results:
Saved: 0 | Deleted: 0 | Skipped: 15 
Remote count: 15
Duration: 0.36 seconds

Settings can be purged for reconfiguration

vecsync settings delete

Uploaded documents can be interacted with via command line. The responding assistant is linked to your vector store.

vecsync assistant chat

Enter your prompt (or 'exit' to quit): Give me a one sentence description of DragonNet

DragonNet is a neural network model designed for estimating treatment effects from observational data, utilizing an end-to-end architecture that focuses on the efficiency of the propensity score and incorporates targeted regularization techniques to enhance estimation accuracy

You can also set up an assistant for further customization via web

vecsync assistant create

Enter a name for your assistant: My helpful assistant
✅ Assistant created: asst_someAssistantId
🔗 Assistant URL: https://platform.openai.com/assistants/asst_someAssistantId