AI-Based Cryptocurrency Tracking Bot

Developer Instructions for Successful Freelancer

Project Overview

The goal of this project is to build a crypto tracking bot that performs the following functions:
1. Data Collection:
• Integrate with Swyftx, CoinGecko, and Twitter APIs.
• Collect data on:
• Market capitalization.
• Trading volume.
• Social sentiment (Twitter, Reddit).
• New listings and token unlocks.
2. AI Sentiment Analysis:
• Use NLP techniques to analyze social media sentiment.
• Aggregate sentiment scores for specific cryptocurrencies.
3. Technical Analysis:
• Implement indicators such as:
• Fibonacci retracement.
• Moving averages (SMA/EMA).
• RSI (Relative Strength Index).
• Predictive 7-day trend forecasting using machine learning (Random Forest, LSTM).
4. Market Cycle Analysis:
• Detect bull and bear market trends using price action and volume analysis.
5. Alerts and Reporting:
• Implement alerts for major trends via Telegram and email.
• Develop a dashboard using Streamlit to display analysis.

Technical Stack
1. Programming Language: Python
2. APIs: Swyftx, CoinGecko, Twitter (Tweepy or Snscrape)
3. Libraries Needed:
• requests (API handling)
• pandas (data manipulation)
• scikit-learn (machine learning)
• matplotlib (visualization)
• nltk (natural language processing)
• flask or streamlit (dashboarding)
4. Security Considerations:
• Use environment variables (.env) for API keys.
• Restrict access via IP whitelisting.
• Ensure encrypted storage for sensitive data.

Project Milestones
1. Phase 1: Data Collection & Preprocessing (Week 1-2)
• Implement API integrations.
• Collect and preprocess market data.
2. Phase 2: Sentiment Analysis (Week 3)
• Develop NLP models for analyzing social media sentiment.
3. Phase 3: Technical & Predictive Analysis (Week 4-5)
• Implement Fibonacci, SMA, and RSI analysis.
• Train machine learning models for forecasting.
4. Phase 4: Alerts & Reporting (Week 6)
• Implement Telegram/email notifications.
• Build Streamlit dashboard.

Deployment Instructions
1. Code Management:
• Use GitHub private repository for version control.
• Commit regularly with descriptive messages.
2. Hosting Suggestions:
• AWS EC2 for processing.
• AWS Secrets Manager for API key storage.
3. Testing:
• Implement unit tests using pytest.
• Conduct security and load testing.

Submission Requirements
1. Deliver the full source code via GitHub.
2. Provide detailed documentation (setup, deployment, usage).
3. Handover all credentials and revoke freelancer’s access upon completion.