# Local Deep Researcher

> Fully local web research and report writing assistant using Ollama or LMStudio

Local Deep Researcher is an open-source research assistant built with LangGraph that operates entirely on local hardware. Given a research topic, it generates search queries, browses the web, summarizes findings, self-critiques to find knowledge gaps, and loops repeatedly until it produces a comprehensive cited markdown report. It integrates with local LLM runtimes like Ollama and LMStudio alongside free search engines like DuckDuckGo to run with zero API costs.

Website: https://github.com/langchain-ai/local-deep-researcher

## What it is for

- Conduct deep research on complex technical or general topics without sending data to cloud LLMs
- Generate cited markdown research briefs and overviews automatically
- Run recursive web searches using local reasoning models like DeepSeek R1

## Features

- Iterative research loop that reflects on summaries and identifies knowledge gaps
- Works with local inference engines including Ollama and LMStudio
- Default support for key-free web search via DuckDuckGo
- Optional integration with external search APIs like SearXNG, Tavily, and Perplexity
- Interactive workflow visualization and parameter tweaking via LangGraph Studio
- Configurable maximum research loops and optional full-page content scraping
- Outputs structured markdown reports with source citations

## Pricing

Open source. Free and open source (MIT license)

## Details

- Type: GitHub repo
- Category: [AI](https://xiry.app/topics/ai.md)
- Open source: yes
- Platforms: macOS, Windows, Linux, Self-hosted, Command line
- For: Developers and privacy-focused researchers running local AI models
- Alternative to: Perplexity Pro, OpenAI Deep Research
- Tags: agents, langchain, langgraph, ollama, deepseek, local ai, web search

## Why it was saved

- [@RLanceMartin, 25 January 2025](https://x.com/RLanceMartin/status/1883209736629448725): Give it a research topic and it searches the web, summarizes sources, reflects on knowledge gaps to generate follow-up queries, and loops as long as wanted, ending with a report with sources — all on local models.
- [@ihteshamali, 20 March 2026](https://x.com/ihteshamali/status/2035009684386771306): A free, 100% open-source, fully local alternative to paid deep research tools: generates its own queries, hunts sources, self-critiques for gaps and re-searches until done, then outputs a full markdown report with citations.

## Related

- [AgenticSeek](https://xiry.app/resources/agenticseek): Open-source, fully local autonomous AI agent that browses and writes code (GitHub repo, Open source)
- [Browser Use WebUI](https://xiry.app/resources/browser-use-webui): Open-source graphical interface for running autonomous AI browser agents locally. (Web app, Open source)
- [Building Effective Agents: Workflow and Agent Patterns](https://xiry.app/resources/building-effective-agents-workflow-and-agent-patterns): Architectural framework categorizing LLM workflows and autonomous agent patterns (Framework, Free)
- [Dolphin 3.0](https://xiry.app/resources/dolphin-3-0): Uncensored, open-source fine-tuned LLM designed for local execution without guardrails (AI model, Open source)
- [How LangChain Built Their Internal GTM Agent](https://xiry.app/resources/how-langchain-built-their-internal-gtm-agent): Architecture playbook for building production sales agents using Deep Agents and LangSmith. (Framework, Free)
- [OpenRAG](https://xiry.app/resources/openrag): All-in-one local stack for building and running RAG applications (GitHub repo, Open source)

Updated 11 October 2026. Page: https://xiry.app/resources/local-deep-researcher-2395

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