A next-generation AI agent trained on 20+ programming languages, powered by graph-based workflows and continuous learning capabilities.
Powered by cutting-edge AI technology
Built on LangGraph for sophisticated state management and conditional routing through complex task flows.
Comprehensive knowledge of 20+ programming languages including Python, JavaScript, Rust, Go, and more.
File operations, system information, text processing, encoding, and advanced calculation capabilities.
Adapts and learns from every interaction, storing custom commands and user preferences automatically.
Track performance with accuracy metrics, response times, and comprehensive evaluation systems.
Designed for the decentralized future with blockchain-compatible architecture and wallet integration.
A versatile AI agent for all your needs
Retrieval-Augmented Generation for enhanced responses
RAG (Retrieval-Augmented Generation) allows Jelly to retrieve relevant information from a knowledge base before generating responses. This ensures accurate, up-to-date answers grounded in stored knowledge.
Pre-loaded with programming, AI, and Web3 knowledge
Finds most relevant documents for your query
Responses augmented with retrieved knowledge
Add your own documents to the knowledge base
Write, test, and learn code with AI assistance
Real-time syntax validation
Get suggestions and improvements
Multi-language support
Run code in real-time
Generate Fibonacci numbers
Fetch data from API
Efficient sorting algorithm
Simple state management
Experience the power of AI-driven intelligence
Get started with Jelly AI
# Install dependencies
pip install -r requirements.txt
# Run the agent
python agent.py
# Or use LangGraph version
python langgraph_agent.py
help - Show all commands
time - Get current time
calculate X - Perform calculations
search TERM - Search knowledge base
note TEXT - Create a note
list files - List directory files
system info - Get system information
learning stats- View learning metrics
# Train with examples
python train_agent.py
# The agent learns from:
# - User interactions
# - Custom commands
# - Preferences
# - Feedback loops
# Edit config.py
AGENT_NAME = "jelly"
MODEL = "gpt-4"
API_KEY = "your-key-here"
# Supports:
# - Custom personalities
# - API integrations
# - Tool configurations