vecsync 0.2.0

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

Getting Started

OpenAI API Requirements

Currently vecsync only supports OpenAI for remote operations and requires a valid OpenAI key with credits. Visit https://openai.com/api/ for more information. Future improvements will allow more platform options and self-hosted models.

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

Synching Collections

Use the vs sync command for all synching operations.

Sync from local file path.

cd path/to/pdfs && vs sync

Synching 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. Interactive selections are remembered for future sessions.

vs sync -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): 

Synching 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

Settings

Settings are persisted in a local json file which can be purged.

vs settings delete

Chat Interactions

Use vs assistant chat to chat with uploaded documents via the command line. The responding assistant is automatically linked to your vector store.

vs assistant chat
✅ Assistant found: asst_123456789
Type "exit" to quit at any time.

> Give a one sentence summary of your vector store collection contents.
💬 Conversation started: thread_123456789

The contents of the vector store collection primarily focus on machine learning techniques for causal effect inference,particularly through adversarial representation learning methods that address challenges in treatment selection bias and information loss in observational data

Conversations are remembered across sessions.

vs assistant chat   
✅ Assistant found: asst_123456789
✅ Thread found: thread_123456789
Type "exit" to quit at any time.

> What was my last question to you? 
Your last question to me was asking for a one sentence summary of the contents of my vector store collection.

Threads can be cleared using the -n flag.

vs assistant chat -n
✅ Assistant found: asst_123456789
Type "exit" to quit at any time.

> What was my last question to you?
💬 Conversation started: thread_987654321

Your last question was about searching for relevant information from a large number of journals and papers, emphasizing the importance of citing information from the provided sources without making up any content.

# Assistant response is in reference to the system prompt