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Litadel: Multi-Agents LLM Financial Trading Framework

Copyright Notice: Litadel is a successor of TradingAgents. This project builds upon and extends the original TradingAgents framework.

🚀 Overview | 💻 Web Interface | ⚡ Getting Started | 🎯 Usage | 🤝 Contributing | 📄 Citation

Overview

Litadel is a comprehensive multi-agent trading platform that brings the dynamics of professional trading firms to your fingertips. Powered by specialized LLM agents—from fundamental analysts and sentiment experts to traders and risk managers—the system collaboratively evaluates market conditions across equities, commodities, and cryptocurrencies to deliver actionable trading insights.

Litadel framework is designed for research and educational purposes. Trading performance may vary based on many factors, including the chosen backbone language models, model temperature, trading periods, the quality of data, and other non-deterministic factors. It is not intended as financial, investment, or trading advice.

What You Get

Three Ways to Analyze Markets:

  • 🌐 Web Dashboard - Modern, real-time interface with live analysis tracking, interactive charts, and comprehensive reports
  • 💻 Interactive CLI - Rich terminal experience with live agent progress and automatic report generation
  • 📦 Python Package - Integrate Litadel's multi-agent analysis directly into your own applications

Multi-Asset Coverage:

  • 📈 Equities - Full fundamental, technical, and sentiment analysis for stocks
  • 🛢️ Commodities - Specialized analysis for oil, metals, agricultural products, and more
  • ₿ Cryptocurrencies - Real-time crypto market analysis with sentiment tracking

Professional-Grade Analysis:

  • Real-time market data integration with automatic caching
  • Multi-agent collaboration with structured debates between bull and bear perspectives
  • Comprehensive reports covering technical indicators, fundamentals, news sentiment, and risk assessment
  • Trading recommendations with confidence scores and detailed rationale

Our framework decomposes complex trading tasks into specialized roles, ensuring robust and scalable market analysis.

Analyst Team

  • Fundamentals Analyst: Evaluates company financials and performance metrics, identifying intrinsic values and potential red flags.
  • Sentiment Analyst: Analyzes social media and public sentiment using sentiment scoring algorithms to gauge short-term market mood.
  • News Analyst: Monitors global news and macroeconomic indicators, interpreting the impact of events on market conditions.
  • Technical Analyst: Utilizes technical indicators (like MACD and RSI) to detect trading patterns and forecast price movements.

Researcher Team

  • Comprises both bullish and bearish researchers who critically assess the insights provided by the Analyst Team. Through structured debates, they balance potential gains against inherent risks.

Trader Agent

  • Composes reports from the analysts and researchers to make informed trading decisions. It determines the timing and magnitude of trades based on comprehensive market insights.

Risk Management and Portfolio Manager

  • Continuously evaluates portfolio risk by assessing market volatility, liquidity, and other risk factors. The risk management team evaluates and adjusts trading strategies, providing assessment reports to the Portfolio Manager for final decision.
  • The Portfolio Manager approves/rejects the transaction proposal. If approved, the order will be sent to the simulated exchange and executed.

Web Interface

Litadel includes a modern web dashboard that provides a complete command center for managing your trading analyses. The interface offers real-time monitoring, interactive visualizations, and comprehensive reporting—all in a sleek, terminal-inspired design.

Dashboard - Your Control Center

The main dashboard gives you an at-a-glance view of your trading operations with system metrics, recent activity, and quick access to create new analyses.

Analysis Management

Browse all your analyses with smart filtering and grouping. Track active analyses in real-time and review historical decisions with detailed statistics.

Real-Time Analysis Tracking

Watch your analysis unfold in real-time as agents collaborate to evaluate market conditions. See live progress updates, agent pipeline status, and streaming reports as they're generated.

Comprehensive Analysis Reports

Each completed analysis provides detailed insights with:

  • Trading Decision - Clear BUY/SELL/HOLD recommendation with confidence score
  • Interactive Price Charts - Candlestick charts with analysis date markers and 60-day history
  • Market Metrics - Current price, daily change, volume, and 52-week ranges
  • Agent Reports - Detailed analysis from each specialist (market, news, sentiment, fundamentals)
  • Research Debate - Bull vs. bear perspectives with investment recommendations
  • Risk Assessment - Comprehensive risk evaluation and portfolio impact analysis

Key Features

  • Real-Time WebSocket Updates - Live progress tracking without page refreshes
  • Interactive Charts - Visualize price action with candlestick or line charts
  • Export Capabilities - Download complete analysis data as JSON
  • Analysis History - Browse and compare past analyses by ticker and date
  • Secure API Access - API key authentication with configurable endpoints
  • Responsive Design - Works seamlessly on desktop and tablet devices

Getting Started

Installation

Clone Litadel:

git clone https://github.com/TauricResearch/Litadel.git
cd Litadel

Create a virtual environment:

conda create -n litadel python=3.13
conda activate litadel

Install dependencies:

pip install -r requirements.txt

API Keys Setup

You will need API keys for LLM providers and market data. The default configuration uses OpenAI for agents and Alpha Vantage for market data.

Create a .env file in the project root:

cp .env.example .env
# Edit .env with your actual API keys

Or export them directly:

export OPENAI_API_KEY=$YOUR_OPENAI_API_KEY
export ALPHA_VANTAGE_API_KEY=$YOUR_ALPHA_VANTAGE_API_KEY

Note: Litadel partners with Alpha Vantage to provide robust API support. Get a free API key here—Litadel users receive increased rate limits (60 requests/minute, no daily limits) through Alpha Vantage's open-source support program.

Usage

Web Dashboard (Recommended)

The web interface provides the most comprehensive experience with real-time tracking, interactive charts, and complete analysis history.

1. Start the API Server:

python -m api.main

On first run, the system will automatically create a database and generate an API key. Save this key—you'll need it for the web interface.

2. Start the Frontend:

cd frontend
npm install
npm run dev

3. Access the Dashboard:

Open your browser to http://localhost:5173 and enter your API key in Settings. You're ready to create your first analysis!

Interactive CLI

For a terminal-based experience with live agent progress tracking:

python -m cli.main

Select your ticker, analysis date, analyst team, LLM models, and research depth through the interactive prompts.

Watch as agents collaborate in real-time, with live updates showing their reasoning and tool usage:

Results are automatically saved to results/<TICKER>/<DATE>/ with detailed logs and markdown reports.

Python Package

Integrate Litadel's multi-agent analysis directly into your own applications, trading bots, or research pipelines.

Basic Usage:

from tradingagents.graph.trading_graph import TradingAgentsGraph
from tradingagents.default_config import DEFAULT_CONFIG

# Initialize the trading agents
ta = TradingAgentsGraph(debug=True, config=DEFAULT_CONFIG.copy())

# Run analysis and get trading decision
_, decision = ta.propagate("NVDA", "2024-05-10")
print(decision)

Custom Configuration:

Customize LLM models, debate rounds, and data sources to match your needs:

from tradingagents.graph.trading_graph import TradingAgentsGraph
from tradingagents.default_config import DEFAULT_CONFIG

# Create custom configuration
config = DEFAULT_CONFIG.copy()
config["deep_think_llm"] = "o1-mini"           # Deep reasoning model
config["quick_think_llm"] = "gpt-4o-mini"      # Fast operations model
config["max_debate_rounds"] = 3                # More thorough research debates

# Configure data sources
config["data_vendors"] = {
    "core_stock_apis": "yfinance",             # Price data
    "technical_indicators": "yfinance",        # Technical analysis
    "fundamental_data": "alpha_vantage",       # Company fundamentals
    "news_data": "alpha_vantage",              # News and sentiment
}

# Run with custom config
ta = TradingAgentsGraph(debug=True, config=config)
_, decision = ta.propagate("AAPL", "2024-05-10")

Cost Optimization:

For testing and development, we recommend using gpt-4o-mini and o1-mini to minimize costs, as the multi-agent framework makes numerous API calls during analysis. For production use with higher accuracy requirements, consider gpt-4o and o1-preview.

Data Sources:

The default configuration uses YFinance for price/technical data and Alpha Vantage for fundamentals/news. You can switch to OpenAI for web-based data fetching or use local cached data for offline experimentation. See tradingagents/default_config.py for all available options.

What's New in Litadel

Completed Features

  • ✅ Web Dashboard - Full-featured web interface with real-time analysis tracking
  • ✅ REST API - Complete API for programmatic access with WebSocket support
  • ✅ Multi-Asset Support - Equities, commodities, and cryptocurrencies
  • ✅ Interactive Charts - Real-time candlestick and line charts with market data
  • ✅ Analysis History - Persistent storage and browsing of all analyses
  • ✅ Export Capabilities - Download complete analysis data as JSON

Roadmap

  • 🚧 Automated Trading Mode - Continuous automated trading execution
  • 🚧 Portfolio Management - Multi-asset portfolio tracking and optimization
  • 🚧 Backtesting Engine - Historical performance analysis with TauricDB
  • 🚧 OpenAI Agents SDK Migration - Enhanced parallelization and maintainability

Contributing

We welcome contributions from the community! Whether it's fixing a bug, improving documentation, or suggesting a new feature, your input helps make this project better.

Citation

Please reference our work if you find Litadel provides you with some help :)

Litadel citation:

@software{gabler2025litadel,
      title={Litadel: Multi-Agents LLM Financial Trading Framework}, 
      author={Marvin Gabler},
      year={2025},
      url={https://github.com/deepweather/Litadel},
      note={Extended framework based on TradingAgents}
}

Original TradingAgents citation:

@misc{xiao2025tradingagentsmultiagentsllmfinancial,
      title={TradingAgents: Multi-Agents LLM Financial Trading Framework}, 
      author={Yijia Xiao and Edward Sun and Di Luo and Wei Wang},
      year={2025},
      eprint={2412.20138},
      archivePrefix={arXiv},
      primaryClass={q-fin.TR},
      url={https://arxiv.org/abs/2412.20138}, 
}