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Local Deep Researcher

Fully local web research assistant using LLMs for generating queries, summarizing results, and writing reports.

Introduction

Local Deep Researcher

Local Deep Researcher is a powerful tool designed to assist users in conducting thorough web research and generating quality reports. It leverages local language models hosted via Ollama or LMStudio to enhance the research process. This tool provides a comprehensive solution for users aiming to gather information efficiently and effectively.

Key Features:
  • Fully Local Operation: Runs entirely on local resources, ensuring privacy and data security.
  • Versatile Model Selection: Utilizes various local LLM options allowing for tailored user experiences.
  • Iterative Research Process: Repeats searching and summarizing until a user-defined goal is achieved.
  • Markdown Summary Generation: Outputs findings in a structured markdown format complete with citations for reference.
  • Configurable Environment: Users can customize settings through environment variables to suit individual needs.
  • Compatibility with Multiple Tools: Integrates seamlessly with search engines like DuckDuckGo, SearXNG, Tavily, and Perplexity.
Benefits:
  • Efficient Knowledge Acquisition: Quickly identifies knowledge gaps and refines search queries to fill those gaps.
  • User-Centric Design: Intuitive interface tailored for enhancing user productivity in research activities.
  • Open Source Accessibility: Available on GitHub for users to contribute, modify, or directly utilize in their projects.

This tool is ideal for researchers, students, and professionals needing to conduct in-depth research without dependence on online services that might compromise privacy.

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