AutoResearcher is an AI-powered research assistant that autonomously searches web and scholarly databases, extracts relevant content, and generates organized summaries. It leverages OpenAI's GPT models to identify key insights, rank sources, and compile literature reviews. Users specify topics and constraints, and AutoResearcher iteratively refines results, saving hours of manual research and enabling efficient knowledge discovery.
AutoResearcher is an AI-powered research assistant that autonomously searches web and scholarly databases, extracts relevant content, and generates organized summaries. It leverages OpenAI's GPT models to identify key insights, rank sources, and compile literature reviews. Users specify topics and constraints, and AutoResearcher iteratively refines results, saving hours of manual research and enabling efficient knowledge discovery.
AutoResearcher is a command-line AI agent designed to streamline literature and web research workflows. Users supply a research prompt or topic, and the agent conducts automated searches across search engines and academic databases, retrieves and filters sources based on relevance, and uses GPT models to generate concise summaries. It then ranks and organizes findings into a coherent report or literature review. With configurable settings for search depth, summarization style, and output format, AutoResearcher accelerates knowledge gathering and synthesis in minutes instead of days.
Who will use AutoResearcher?
Academic researchers
Graduate students
Market analysts
Content creators
Data scientists
How to use the AutoResearcher?
Step1: Clone the repository via git clone https://github.com/lucereal/AutoResearcher
Step2: Install dependencies with pip install -r requirements.txt
Step3: Set your OpenAI API key in the OPENAI_API_KEY environment variable
Step4: Define your research query in a configuration file or CLI argument
Step5: Run the agent with python auto_researcher.py --query "Your Topic"
Step6: Review and export the generated summary report
Platform
mac
windows
linux
AutoResearcher's Core Features & Benefits
The Core Features
Automated web and academic paper search
GPT-based summarization and insight extraction
Relevance scoring and ranking of sources
Iterative refinement of search results
Exportable structured reports (Markdown, PDF)
The Benefits
Saves hours of manual research
Ensures comprehensive coverage of literature
Delivers consistent, high-quality summaries
Customizable search depth and output format
Scalable for multiple research topics
AutoResearcher's Main Use Cases & Applications
Academic literature reviews for journal publications
Market and competitor analysis reports
Trend analysis for business strategy
Technical background research for product development