{"repo":"ralliesai/tenk","free":true,"listed":false,"github":"https://github.com/ralliesai/tenk","clone":"git clone https://github.com/ralliesai/tenk.git","description":"Chat with SEC filings for any investment question","language":"Python","stars":134,"topics":["ai","finance","investing","rag","sec","stocks","trading"],"license":null,"category":"trading","readme_excerpt":"tenk Talk to SEC filings with AI Ask questions about 10-K and 10-Q filings, get answers with citations What is tenk? tenk lets you have a conversation with SEC filings. Instead of manually reading through hundreds of pages of 10-K and 10-Q reports, just ask questions in plain English and get answers with direct citations to the source. Why not just use ChatGPT? You could copy-paste filings into ChatGPT, but: - 10-Ks are 100+ pages - you can't paste them all - You definitely can't paste multiple filings to compare companies - You'd have to manually find and download each filing first tenk automates all of that. It fetches filings from SEC EDGAR, indexes them locally, and lets you query across multiple filings at once. Features - ✅ RAG over SEC filings with a local vector database (10-K, 10-Q) - ✅ Auto-downloads filings from SEC EDGAR - ✅ Citations with links to source documents - ✅ Stock data via Yahoo Finance - ✅ Web search for data not in filings - ✅ Excel generation for tables and financial models - ✅ Export answers to PDF, DOCX, or Excel - ✅ Conversation memory with auto-summarization Requirements - Python 3.10+ - OpenAI API key (set OPENAI API KEY environment variable) Installation Or from source: Usage Interactive mode: One-shot mode: Examples How it works 1. Check available filings - Queries SEC EDGAR to see what's available 2. Download & index - Downloads filings and chunks them into a local vector database 3. Semantic search - Finds relevant passages using sentence-tr","default_branch":null,"files":null,"tree":[],"storefront":"/r/ralliesai","claimed":false,"request_supported":{"post":"https://gitbuyer.com/r/ralliesai/tenk/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."}