literature-review
This agent automates deep web research by generating queries, gathering relevant sources, summarizing key information, and iterating on knowledge gaps to refine the results.
Example requests
beeai run literature-review "AI applications in healthcare, focusing on diagnostic tools and patient data management."
Description
The agent is designed to automate the process of conducting literature reviews by gathering, analyzing, and synthesizing information from multiple sources. It uses a combination of Google searches and Arxiv database queries to fetch relevant academic papers and data, subsequently generating a well-formatted report.
How It Works
The agent handles requests to perform literature reviews. It utilizes a set of assistant agents, including Google and Arxiv search agents, to gather information. Once the data is collected, a report agent synthesizes the information into a structured literature review, ensuring that references are correctly formatted. The process involves a round-robin communication strategy among the participating agents, with a termination condition for task completion.
Input Parameters
- text (string) – Contains the text query or topic for which the literature review is to be conducted.
Key Features
- Automated Literature Review – Conducts thorough searches across Google and Arxiv to gather relevant academic information.
- Structured Report Generation – Compiles and formats the search results into a coherent literature review with proper references.
- Multi-Source Data Collection – Leverages both general web searches and academic databases for comprehensive data gathering.
- Dynamic Agent Collaboration – Uses a round-robin approach to coordinate between search and report agents.
Use Cases
- Academic Research – Supports researchers by automating the initial phase of literature review.
- Report Generation – Generates structured academic reports for various topics.
- Resource Compilation – Compiles a list of academic papers and articles relevant to a given topic.