Fully local web research assistant using Ollama or LMStudio LLMs to iteratively search, summarize, and refine reports.
Local Deep Researcher is a fully local web research assistant that uses any LLM hosted by Ollama or LMStudio. Given a topic, it generates a web search query, gathers results, summarizes findings, reflects on knowledge gaps, and repeats for a configurable number of cycles. It outputs a final markdown summary with citations. The tool runs entirely locally, ensuring privacy and no API costs.
Key Features
check_circleFully local execution
check_circleIterative web research with reflection
check_circleIntegration with LangGraph Studio for visualization
check_circleDocker deployment support
check_circleTypeScript port available
Use Cases
lightbulbResearchers can automate literature reviews by providing a topic, and the tool iteratively searches and summarizes relevant web sources, saving hours of manual work.
lightbulbStudents use it to gather comprehensive background information for essays or projects, receiving a structured report with citations.
lightbulbContent creators can quickly research trending topics, generating a summary with key points and sources to inform their articles or videos.
lightbulbBusiness analysts can monitor industry news by running periodic research on specific keywords, compiling a digest of recent developments.
lightbulbDevelopers can integrate the tool into their workflow for technical research, such as exploring new libraries or frameworks, and get a concise overview with references.
lightbulbJournalists can use it to fact-check and gather multiple perspectives on a story, producing a balanced summary with source links.
lightbulbProduct managers can research competitor features and user feedback by specifying a product name, receiving a synthesized report.
