grag-search 0.1.0

Fast grep-based document search for LLM agents. No embeddings, just speed.

grag

Fast grep-based document search for LLM agents. No embeddings, just speed.

Why grag?

• 10x faster than embeddings-based search for exact matches
• Zero cost - no API calls, no vector databases
• Precise - finds exact terms, not "similar" content
• Lightweight - minimal dependencies
• LLM-ready - returns context windows perfect for prompts

Quick Start

pip install grag

from grag import Grag

# Index your documents
store = Grag("./contracts")

# Search with context
results = store.search("late payment penalty", context_chars=500)

# Use in LLM prompt
for result in results:
    print(result.format_for_llm())

Supported Formats

• PDF
• DOCX (Word)
• XLSX (Excel)
• CSV
• TXT
• Markdown (.md, .markdown)

When to use grag vs RAG

Use grag for:

• Exact term matching (IDs, dates, specific clauses)
• Legal/medical documents with precise terminology
• Cost-sensitive applications
• Low-latency requirements

Use RAG for:

• Semantic similarity
• Multi-lingual fuzzy matching
• Conceptual queries

Or use both: grag first for exact matches, RAG as fallback.

Development Status

v0.1.0 — Alpha release. The API is functional and tested. Feedback welcome.

Contributing

Contributions welcome. Open an issue or PR on GitHub.

License

MIT License - see LICENSE file for details.

Author

Built by Alan Sepulveda for Teral and the open source community.