DataForge / README.md
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---
title: DataForge
emoji: πŸ’¬
colorFrom: yellow
colorTo: purple
sdk: gradio
sdk_version: 5.0.1
app_file: app.py
pinned: false
license: mit
short_description: CodeAct Agent to process large data set
tags:
- agent-demo-track
---
## πŸŽ₯ Demo Video
**Watch DataForge in Action:**
[![DataForge Demo](https://img.youtube.com/vi/f5jp2i3engM/maxresdefault.jpg)](https://www.youtube.com/watch?v=f5jp2i3engM)
🎬 **[Click here to watch the full demo on YouTube](https://www.youtube.com/watch?v=f5jp2i3engM)**
---
# πŸ” DataForge - AI Assistant with File Analysis
An intelligent AI assistant that combines conversational chat capabilities with advanced file analysis using CodeAct agents. Built with Gradio, LangChain, and LangGraph.
## ✨ Features
### πŸ’¬ Chat Assistant
- Interactive AI chatbot powered by OpenAI GPT-4
- Customizable system messages and parameters
- Real-time streaming responses
- Conversation history support
### πŸ“ File Analysis
- **Upload & Analyze**: Support for various file formats (.txt, .log, .csv, .json, .xml, .py, .js, .html, .md)
- **Smart Analysis**: Automatic file type detection and tailored analysis
- **CodeAct Integration**: Uses LangGraph CodeAct agents for deep file analysis
- **Comprehensive Insights**: Provides security analysis, performance insights, error detection, and statistical summaries
## πŸš€ Getting Started
### Prerequisites
- Python 3.11+
- OpenAI API Key
### Installations
1. Create and activate virtual environment:
```bash
uv venv --python 3.11
source .venv/bin/activate # On Windows: .venv\Scripts\activate
```
2. Install dependencies:
```bash
uv pip install -r requirements.txt
```
3. Set up environment variables:
```bash
# Create .env file and add your OpenAI API key
OPENAI_API_KEY=your_openai_api_key_here
```
### Running the Application
```bash
python app.py
```
The application will start a Gradio interface accessible at `http://localhost:7860`
## πŸ“Š File Analysis Capabilities
### Supported File Types
- **Log files** (.log, .txt): Security analysis, performance bottlenecks, error detection
- **Data files** (.csv, .json): Data quality assessment, statistical analysis
- **Code files** (.py, .js, .html): Structure analysis, best practices review
- **Configuration files** (.xml, .md): Content analysis and recommendations
### Analysis Features
- **Security Analysis**: Detect threats, suspicious activities, and security patterns
- **Performance Insights**: Identify bottlenecks and performance issues
- **Error Analysis**: Categorize and analyze errors and warnings
- **Statistical Summary**: Basic statistics and data distribution
- **Pattern Recognition**: Identify trends and anomalies
- **Actionable Recommendations**: Suggested actions based on analysis
## πŸ§ͺ Testing
A sample server log file (`sample_server.log`) is included for testing the file analysis functionality.
## πŸ› οΈ Technical Architecture
- **Frontend**: Gradio for web interface
- **Backend**: LangChain for AI orchestration
- **Analysis Engine**: LangGraph CodeAct agents with PyodideSandbox
- **File Processing**: Custom FileInjectedPyodideSandbox for secure file analysis
- **Model**: OpenAI GPT-4 for both chat and analysis
## πŸ“„ License
MIT License