In simple English
This tool lets you ask hard questions about your own files and websites. It reads your documents, searches through them, and writes a complete research report with answers. You need to connect it to an external language model and a vector database (a database that stores text as numbers for search). It runs in Python and saves you hours of manual reading. Running powerful language models will cost you money in API fees.
What it is
An open-source library that implements agentic RAG (Retrieval-Augmented Generation, a technique that fetches relevant documents before asking a language model to write an answer) for deep research over private data. It indexes your local files or crawled web pages into a vector store and uses reasoning models to synthesise comprehensive answers.
What it is good for
Solo builders who want to build a custom research assistant over internal company documents, personal notes, or specific web archives without writing complex retrieval pipelines from scratch.
- Supports many popular language models including OpenAI, DeepSeek, and Anthropic Claude.
- Stores data locally using Milvus Lite without requiring a complex database server setup.
- Includes both a Python library and a command-line interface for fast loading and querying.
- Requires valid API keys and active internet access for most large language models and embedding providers.
- Small local models struggle with output formatting, so you must use large reasoning models.
- Document loaders and web crawlers depend on external services like FireCrawl which may require separate accounts and keys.
Writing custom Retrieval-Augmented Generation scripts and search loops from scratch.
Milvus
- infiniflow/ragflow93k stars
RAGFlow offers an open-source retrieval system with document understanding and visual chunking.
- assafelovic/gpt-researcher30k stars
GPT Researcher automates online research tasks by scraping web sources and writing structured reports.
- ggml-org/llama.cpp132k stars
A C and C++ library and command-line tool for running language models locally.
- EleutherAI/lm-evaluation-harness14k stars
Runs standard question sets against a language model and reports the scores.
- mudler/LocalAI50k stars
Serves text, vision, speech, image and video models from one self-hosted service that imitates the paid interfaces.
python -m venv .venv source .venv/bin/activate pip install deepsearcher