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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
DATAGEN: AI-driven multi-agent research assistant automating hypothesis generation, data analysis, and report writing.
| Date | Stars |
|---|---|
| 2026-07-31 | 1777 |
| 2026-08-06 | 1781 |
Today
+4 stars today
This week
— stars this week
This month
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Momentum
16.0
growth rate 0.00%/day
# DATAGEN (Previously AI-Data-Analysis-MultiAgent)  ## About DATAGEN DATAGEN is a powerful brand name that represents our vision of leveraging artificial intelligence technology for data generation and analysis. The name combines "DATA" and "GEN"(generation), perfectly embodying the core functionality of this project - automated data analysis and research through a multi-agent system.  ## Overview DATAGEN is an advanced AI-powered data analysis and research platform that utilizes multiple specialized agents to streamline tasks such as data analysis, visualization, and report generation. Our platform leverages cutting-edge technologies including LangChain, OpenAI's GPT models, and LangGraph to handle complex research processes, integrating diverse AI architectures for optimal performance. ## Key Features ### Intelligent Analysis Core - **Advanced Hypothesis Engine** - AI-driven hypothesis generation and validation - Automated research direction optimization - Real-time hypothesis refinement - **Enterprise Data Processing** - Robust data cleaning and transformation - Scalable analysis pipelines - Automated quality assurance - **Dynamic Visualization Suite** - Interactive data visualization - Custom report generation - Automated insight extraction ### Advanced Technical Architecture - **Multi-Agent Intelligence** - Specialized agents for diverse tasks - Intelligent task distribution - Real-time coordination and optimization - **Smart Memory Management** - State-of-the-art Note Taker agent - Efficient context retention system - Seamless workflow integration - **Adaptive Processing Pipeline** - Dynamic workflow adjustment - Automated resource optimization - Real-time performance monitoring ## Why DATAGEN Stands Out DATAGEN revolutionizes data analysis through its innovative multi-agent architecture and intelligent automation capabilities: 1. **Advanced Multi-Agent System** - Specialized agents working in harmony - Intelligent task distribution and coordination - Real-time adaptation to complex analysis requirements 2. **Smart Context Management** - Pioneering Note Taker agent for state tracking - Efficient memory utilization and context retention - Seamless integration across analysis phases 3. **Enterprise-Grade Performance** - Robust and scalable architecture - Consistent and reliable outcomes - Production-ready implementation ## System Requirements - Python 3.10 or higher ## Installation 1. Clone the repository: ```bash git clone https://github.com/starpig1129/DATAGEN.git ``` 2. Create and activate a Conda virtual environment: ```bash conda create -n datagen python=3.10 conda activate datagen ``` 3. Install dependencies: ```bash pip install -r requirements.txt ``` 4. Set up environment variables: **Rename `.env Example` to `.env` and fill all the values** ```sh # Your data storage path (required) # Also used by filesystem MCP server WORKING_DIRECTORY = ./data/ # Configuration directory path (optional) # All config files (agent_models.yaml, agents/, mcp.yaml) are relative to this directory. # Default is config/ # Use 'config_local' for local development to avoid Git tracking (already in .gitignore) CONFIG_DIRECTORY = config # Conda environment name (required) CONDA_ENV = datagen # ChromeDriver executable path (required) CHROMEDRIVER_PATH = ./chromedriver-linux64/chromedriver # Firecrawl API key (optional) # Note: If this key is missing, query capabilities may be reduced FIRECRAWL_API_KEY = XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX # fastCRW (Firecrawl-compatible web scraper; single binary, self-host or cloud) (optional) # API key for the managed cloud; optional for self-host CRW_API_KEY = XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX # Defaults to the managed cloud; override for self-host (e.g. http://localhost:3000) CRW_API_URL = https://fastcrw.com/api # Ope
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Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:697b3768471fbe87, topic:large-language-models, topic:llm
matched fp:697b3768471fbe87, topic:langgraph, desc:multi-agent, desc:multi agent
matched fp:697b3768471fbe87, topic:code-generation
