Vora AI Documentation

Introduction

Welcome to the Vora AI Documentation. Vorais a no-code platform designed to empower users in creating and managing decentralized applications (dApps) on the Solana blockchain. With Vora, you can build custom bundlers, automate trading strategies, and analyze blockchain data in real-time, all through intuitive agent interactions.

Key Features

1. No-Code Development: Empower innovation with ease through our no-code platform designed for the Solana blockchain. This feature enables users to create and deploy decentralized applications (dApps) without needing to write a single line of code. Whether you’re an entrepreneur, a developer without blockchain expertise, or an enterprise seeking rapid deployment, this tool democratizes dApp creation. Seamlessly customize interfaces, workflows, and smart contracts while focusing on your core goals.

2. Custom Bundler Creation: Take control of your data management with custom bundlers tailored specifically to your needs. Our interactive agent allows you to configure and deploy bundlers for organizing, processing, and managing blockchain data effectively. Whether you need a bundler for specific token analytics, NFT tracking, or smart contract monitoring, this feature ensures your tools align perfectly with your requirements.

3. BULLX Integration: Revolutionize your trading strategies with BULLX Integration, which automates decision-making through real-time trend analysis and actionable insights. This tool monitors market fluctuations, identifies emerging trends, and provides recommendations based on comprehensive data analytics. Enhance your trading efficiency by letting BULLX work as your on-call advisor, delivering accurate and

4. Alfred Agent for Contract and Project Insights: Uncover deep insights into blockchain projects and smart contracts with Alfred Agent. This advanced analytical tool offers a real-time overview of:

Distribution patterns across wallets.
The emergence of fresh wallets.
Transaction volumes to track activity and momentum.
Top holder trust metrics to assess stability and credibility.

These insights empower users to make informed decisions, whether analyzing investment opportunities or evaluating project performance.

5. 24/7 Developer Support: Our round-the-clock developer support ensures your journey remains smooth and uninterrupted. Whether you’re troubleshooting deployment issues, fine-tuning configurations, or seeking expert advice, our dedicated team is always ready to assist. This ensures minimal downtime, efficient problem-solving, and a seamless user experience across all stages of your project lifecycle.

Creating a Custom Bundler

With Vora, you can create your own bundler by conversing with your agent. This interactive process allows you to define the functionalities and parameters of your bundler, enabling a tailored solution that fits your requirements.

Steps to Create a Bundler:

1.Initiate Conversation: Kickstart your bundler creation journey by accessing the intuitive agent interface. The process begins with a straightforward initiation of a new conversation. This user-friendly interface is designed to welcome you, offering an accessible and interactive environment to guide you through every step. No technical expertise is required—simply open the agent interface, and you're ready to begin

2. . Define Requirements: Clearly articulate your vision by defining the specific functionalities and features you need in your bundler. Whether your focus is on monitoring token transactions, analyzing wallet activity, or automating data processing workflows, this step ensures your objectives are well understood. Be as detailed as possible, outlining use cases, desired outputs, and any preferences for data handling. This clarity allows the agent to tailor the bundler precisely to your unique requirements.

3. Agent Assistance: Benefit from the expertise of a smart and responsive agent that guides you step-by-step through the setup process. The agent will ask targeted questions to refine the bundler’s functionality, ensuring it aligns with your goals. By addressing these prompts, you can customize your bundler’s capabilities effortlessly. The interactive nature of this step not only simplifies the technical aspects but also ensures a highly personalized configuration tailored to your specific needs.

4. Deployment: Once your bundler is configured and reviewed, seamlessly deploy it to the Solana blockchain with just a few clicks. The platform takes care of the technical complexities behind the scenes, ensuring a smooth and hassle-free deployment process. Your custom bundler will be live and operational in no time, ready to perform as intended in a secure and efficient blockchain environment.

Automating Trades with BULLX Integration

Integrate your BULLX account with Vora to automate trading strategies. The platform provides real-time trend analysis and suggestions, enhancing your trading efficiency.

1. Connect BULLX: Navigate to the integrations section and link your BULLX account.

2. Configure Strategies: Set your trading parameters and preferences within the platform.

3. Activate Automation: Enable the automated trading feature to start executing trades based on real-time data and analysis.

Real-Time Contract Analysis with Alfred Agent

Utilize the Alfred assistant agent to perform real-time analysis of blockchain contracts and projects. Gain comprehensive insights into:

• Distribution Metrics: Understand token distribution among holders.

• Fresh Wallets: Identify new wallets interacting with the contract.

• Transaction Volumes: Monitor the number and value of transactions.

• Top Holder Trust Metrics: Assess the credibility and activity of top token holders.

How to Use Alfred Agent:

1. Access Alfred: From the dashboard, select the Alfred agent feature.

2. Input Contract Details: Enter the contract address or project name you wish to analyze.

3. View Analysis: Receive real-time data and insights presented in an easy-to-understand format.

Code Examples

Risk Scoring Algorithm

import numpy as np

def calculate_risk_score(token_data):
    # Example weights for different factors
    weights = {
        'holder_concentration': 0.4,
        'transaction_anomalies': 0.3,
        'social_presence': 0.2,
        'historical_performance': 0.1
    }

    # Normalize factors to a 0-1 scale
    normalized_factors = {
        key: value / max_value
        for key, (value, max_value) in token_data.items()
    }

    # Calculate weighted risk score
    risk_score = sum(
        weights[key] * normalized_factors[key]
        for key in weights.keys()
    ) * 100  # Scale to 0-100

    return round(risk_score, 2)

# Example token data
sample_token_data = {
    'holder_concentration': (80, 100),
    'transaction_anomalies': (70, 100),
    'social_presence': (10, 100),
    'historical_performance': (50, 100)
}

risk_score = calculate_risk_score(sample_token_data)
print(f"Risk Score: {risk_score}")

Red Flag Detection

from datetime import datetime

# Example transaction data
transactions = [
    {'amount': 500, 'wallet': '0xABC', 'timestamp': '2024-12-01T12:00:00Z'},
    {'amount': 500, 'wallet': '0xABC', 'timestamp': '2024-12-01T12:01:00Z'},
    {'amount': 1000, 'wallet': '0xDEF', 'timestamp': '2024-12-01T12:02:00Z'},
]

def detect_red_flags(transactions):
    red_flags = []

    # Check for rapid transactions from a single wallet
    wallet_activity = {}
    for tx in transactions:
        wallet = tx['wallet']
        wallet_activity[wallet] = wallet_activity.get(wallet, 0) + 1

    for wallet, count in wallet_activity.items():
        if count > 2:
            red_flags.append(f"Wallet {wallet} has {count} rapid transactions.")

    return red_flags

flags = detect_red_flags(transactions)
print(flags)

Predictive Model (Simplified)

from sklearn.linear_model import LogisticRegression

# Training data (simplified example)
features = [
    [0.1, 0.2, 0.7],  # Low risk
    [0.8, 0.7, 0.9],  # High risk
    [0.3, 0.4, 0.5],  # Medium risk
]
labels = [0, 1, 0]  # 0 = Low Risk, 1 = High Risk

# Train model
model = LogisticRegression()
model.fit(features, labels)

# Predict risk
new_token = [[0.6, 0.5, 0.8]]  # Example new token
prediction = model.predict(new_token)
print("High Risk" if prediction[0] == 1 else "Low/Medium Risk")

API Integration

CRONEX AI provides an API for developers to integrate its functionalities into their own platforms.

Endpoints

GET /analyze

Input: Token address
Output: Risk score, red flags, recommendations
POST /configure-alerts
- Input: Alert criteria
- Output: Confirmation of alert configuration

Example API Call

curl -X GET "https://api.cronex.ai/analyze?token_address=0x123" \
-H "Authorization: Bearer YOUR_API_KEY"

Conclusion

Atlas Agent Agents provide invaluable insights for token analysis on Pump.fun. By leveraging advanced AI models and blockchain analytics, they empower users to make informed decisions and avoid high-risk investments.

Last updated 3 months ago