Overview
The Multi-Agent AI Research System is an autonomous multi-agent AI research application that searches the live web, extracts source knowledge, generates a structured research report, and evaluates the final result with an AI critic. It is designed to automate the process of researching a topic through multiple specialized stages, separating the task into query detection, live web search, source extraction, web scraping, a writer chain, a critic chain, and a final research report. The system uses Tavily for live web research, LangChain Expression Language (LCEL) for composing AI workflows, Groq as the LLM provider for fast inference, and Streamlit for the interactive frontend. It supports English and Hindi output, speech-to-text using Groq Whisper, live weather queries using OpenWeather, and includes retry and token-management logic for LLM rate limits. The application is deployed on Streamlit Community Cloud and provides a public URL for access.
Pricing
Free
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Use Cases
- Teams use the system to automate researching a topic through multiple specialized stages.
- Users use the system to retrieve current information from the web using Tavily.
- Users use the system to generate structured research reports with sections like Introduction, Key Findings, Analysis, Conclusion, and Sources.
- Users use the system to evaluate generated reports with an AI critic that checks strengths, weaknesses, missing information, relevance, overall quality, and final verdict.
- Users use the system to get live weather information for a location.
- Users use the system to input queries via speech-to-text using Groq Whisper.
- Users use the system to inspect search results and scraped source content for transparency.
Features
AI assistant
Natural language interface
Workflow automation
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