{"repo":"laxmanclo/pany","free":true,"listed":false,"github":"https://github.com/laxmanclo/pany","clone":"git clone https://github.com/laxmanclo/pany.git","description":"PostgreSQL-native semantic search engine with multi-modal capabilities. Add AI-powered search to your existing database without separate vector databases, vendor fees, or complex setup. Features text + image search using CLIP embeddings, native SQL joins, and 10-minute Docker deployment.","language":"Python","stars":19,"topics":["ai-search","clip-embeddings","database","docker","document-search","embeddings","fastapi","image-search","machine-learning","multimodal-search"],"license":"MIT","category":"databases-storage","readme_excerpt":"Pany ⚠️ Beta Software : This is early-stage software. API may change between versions before v1.0.0. Semantic search that works inside PostgreSQL. Upload documents and images, then search them with natural language. Instead of setting up a separate vector database like Pinecone or Weaviate, Pany uses your existing PostgreSQL database with the pgvector extension. 📖 Technical Architecture - Detailed system design and implementation Install and Run Go to http://localhost:8000 to upload files and start searching. Requirements - Python 3.9+ - PostgreSQL with pgvector extension - 4GB RAM minimum Configuration What it does Upload stuff : Drop PDFs, images, text files into the web interface Search naturally : Type \"find the red car\" or \"contract with Microsoft\" Get results : Finds semantically similar content, not just keyword matches Works with text and images. You can search for images using text descriptions, or upload an image to find similar ones. Code Examples SQL Integration The main advantage over other vector databases is that you can join search results with your existing data: This is impossible with most vector databases because they're separate systems. Why PostgreSQL? Because you probably already have PostgreSQL running your app. Instead of: 1. Setting up another database (Pinecone, Weaviate, etc.) 2. Keeping data in sync between systems 3. Learning new APIs and query languages 4. Paying monthly fees You just add pgvector to your existing database and you're done. cont","default_branch":null,"files":null,"tree":[],"storefront":"/r/laxmanclo","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/laxmanclo/pany/request-supported","requests":0},"note":"indexed from public GitHub; nothing is for sale on this page. Clone it from GitHub. Paid listings live at /search."}