deep-searcher
DeepSearcher is a deep research and search tool based on private data.
- Region
- Domestic
- Pricing
- Free
- Open source
- Yes
- GitHub Stars
- ★ 7.9k
- Source
- GitHub
- Added
- 2026-06-05
- Last verified
- 2026-06-05
Overview
DeepSearcher is a deep research and search tool based on private data, written in Python. It combines advanced large language models (such as OpenAI o3, Qwen3, etc.) with vector databases (like Milvus) to enable efficient search, evaluation, and reasoning over private data, delivering accurate answers and comprehensive reports. Suitable for enterprise knowledge management, intelligent question-answering systems, and information retrieval scenarios.
Key features
- ▪Supports multiple large language models
- ▪Compatible with multiple vector databases
- ▪Flexible embedding options
- ▪Document loading functionality
- ▪Ensures data security
Use cases
Pros
- +Highly accurate answers
- +Comprehensive report generation
- +Supports multiple embedding models
- +Data security assurance
Limitations / notes
- -Requires API key configuration
- -Some features are still under development
Who it's for
This overview was compiled by AI from public sources and may contain inaccuracies — please refer to the official site.
FAQ
How can I install DeepSearcher?
It can be installed via pip or cloned from GitHub and dependencies synchronized using uv.
Which large language models are supported?
Supports multiple large language models such as OpenAI o3, Qwen3, DeepSeek, etc.
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