gpt researcher
Basic Information
gpt-researcher is an LLM-based autonomous agent designed to perform deep research across both web sources and local documents and to synthesize findings into a long, citation-backed report. The repository packages the logic and workflow for issuing research queries, gathering source material from the web and from local files, and using a large language model to analyze, summarize, and combine evidence into coherent long-form output. It is intended as a tool to automate exploratory investigation on arbitrary topics, producing structured reports with citations and references so users can trace claims back to original sources. The project focuses on end-to-end research automation rather than on providing a general-purpose chat interface.
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App Details
Features
Autonomous LLM-driven research workflow that coordinates information gathering and synthesis. Ability to search and incorporate both web content and local documents as source material. Generation of long-form reports that include citations and references to underlying sources. Emphasis on deep, topic-focused investigation and evidence-backed conclusions. Structured output suitable for reading or further editing. Designed to handle arbitrary research topics by iterating over sources and consolidating findings. Focus on producing a single comprehensive deliverable rather than short conversational answers.
Use Cases
The repository helps users automate time-consuming research tasks by combining web and local information retrieval with large language model synthesis. It saves effort for researchers, students, analysts, and professionals who need a consolidated, citation-backed report from disparate sources. By producing long-form, referenced documents it supports literature reviews, background briefs, and investigative summaries while exposing the sources behind each claim. The automation reduces manual search, note-taking, and initial drafting, enabling users to focus on validation, interpretation, and next steps. The tool is positioned as a productivity aid for deep topic exploration rather than a simple Q&A assistant.
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