Local Deep Research
Open-source AI research assistant that runs locally, supports any LLM and search engine, builds a searchable encrypted knowledge base, and generates cited reports automatically.
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Local, privacy-first AI research assistant that automates deep research and builds your own knowledge base.
Core Features
- Supports any LLM (Ollama, OpenAI, Anthropic, etc.) and multiple search engines
- 20+ research strategies including LangGraph autonomous agent mode
- Encrypted database; save research sources into your library for future queries
- Fully local, no data leaves your machine
- Docker (CPU/GPU) and pip installation, cross-platform
What It Can't Do
- •SQLCipher encryption may need fallback env var LDR_BOOTSTRAP_ALLOW_UNENCRYPTED=true; 2. Requires 8GB+ RAM (recommended 16GB) for local LLMs; 3. Best search results require SearXNG; others need API keys; 4. On Windows pip install, PDF export needs Pango installed separately.
Use Cases
- Academic researchers: auto-search arXiv, PubMed, Semantic Scholar for literature reviews
- Knowledge workers: build a personal knowledge base from reports and web pages, query with natural language
- Privacy-conscious users: fully offline, no cloud dependency, encrypted storage
Local Deep Research (LDR) is a private, agentic research tool that automates deep research across the web, academic papers, and your own documents. It supports multiple LLMs (via Ollama, OpenAI, etc.), 20+ research strategies, and a new LangGraph agent mode that autonomously decides what to search and when to synthesize. All data is stored in an encrypted SQLCipher database, and you can build a compounding knowledge base by downloading sources. It runs on Docker or pip install, with optional GPU acceleration.
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Getting Started
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Install the software
Double-click the downloaded installer and follow the prompts
Docker: run Ollama, SearXNG, then LDR container (see README for commands)
pip install: pip install local-deep-research, then access localhost:5000
Configure LLM and search engine in settings, choose a strategy, start researching
- Docker: run Ollama, SearXNG, then LDR container (see README for commands)
- pip install: pip install local-deep-research, then access localhost:5000
- Configure LLM and search engine in settings, choose a strategy, start researching
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Docker: docker stop local-deep-research && docker rm local-deep-research. pip: pip uninstall local-deep-research.
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Ready to use after download. No additional runtime required.
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