Natural language search for SEC filings. Fetch 10-K/10-Q/8-K from EDGAR, parse into segments, chunk text, generate GPU-accelerated embeddings (google/embeddinggemma-300m, 768-dim), store in ChromaDB+SQLite dual-store. Rich CLI with progress bars, color-coded output, flexible filtering. Returns relevant passages not generated answers.
react javascript python typescript rest-api nextjs jupyter-notebook pytorch semantic-search financial-markets sec-edgar finance-application fastapi vector-search vector-database edgar-filing chromadb edgar-tools
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Updated
May 18, 2026 - Python