LearningCircuit/local-deep-research

Health v2 · maintenance only

Adoption not part of the score

8995 stars · 793 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

A self-hosted AI research assistant that performs deep, iterative multi-source research using local or cloud LLMs (Ollama, llama.cpp, OpenAI, Anthropic, etc.) and 10+ search engines including arXiv, PubMed, and private document collections. All data is stored locally with SQLCipher encryption, achieving ~95% accuracy on SimpleQA benchmarks.

Use cases

• run deep research queries entirely on local LLMs without sending data to the cloud
• search arXiv and PubMed for academic literature with AI synthesis
• ask questions over my private documents with citations
• build a self-hosted alternative to paid deep research tools
• compare answers across multiple search engines and LLM providers
• research on an air-gapped or privacy-sensitive machine

When to choose

• you need privacy-first research with everything local and encrypted
• you want to combine local LLMs with many search backends including private document collections
• you want a self-hosted web UI plus Docker deployment for iterative research workflows

When to avoid

• you need a lightweight single-shot Q&A without iterative search overhead
• you have no GPU or local model and don't want to rely on cloud LLM APIs
• you need a hosted managed service with zero setup

Facets

application · maturity active

rag search-engine llm-inference web-scraping chatbot large-language-models self-hosted artificial-intelligence python self-hosted cross-platform deep-research local-llm ollama searxng encrypted research-assistant arxiv pubmed private-documents retrieval-augmented-generation search docker web-server

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markdown · JSON · MCP: product_card(name="LearningCircuit/local-deep-research")