An on-demand crypto market intelligence and decision-support terminal powered by TypeSafe AI's System One model (Jev).
The tool allows you to search any cryptocurrency (such as BTC, SOL, or ETH), select how many tweets you want to analyze (from 50 up to 1,000 tweets), and receive an instant, data-backed trading decision (Buy, Sell, Hold, or Take Profit) based on real-time market data, perpetuals funding rates, and social sentiment.
The platform does not execute trades automatically. It generates a clear decision card with calculated entry ranges, stop losses, and target levels so you can review the reasoning and execute manually on whichever exchange or DEX you prefer.
When you request sentiment analysis across 50 to 1,000 tweets, dumping hundreds of raw tweets into an LLM would exceed token budgets and introduce latency. Instead, Jev X Sentiment Analysis uses an intelligent three-stage pipeline:
User Search (e.g. "SOL", 500 tweets)
│
├──> CCXT: Live Price, 24h Volume, RSI, Funding Rate, Open Interest
└──> TwitterAPI.io: 500 tweets ingested via cursor pagination
│
▼
Tier 1: Python Statistical Pre-Processing
- Computes total engagement velocity (likes, retweets per minute)
- Measures author diversity ratio (detects bot farms vs organic retail)
- Computes keyword sentiment polarity (fear/capitulation vs greed/hype)
- Stratified extraction:
• Top 25 highest-engaged tweets (KOL & market-moving opinions)
• 25 most recent breaking tweets (current real-time narrative)
│
▼
Tier 2: Early-Stopping Database Deduplication (API Cost Optimization)
- To save API credits, the system stores all ingested tweets in a local SQLite database (`data/market_intel.db`).
- TwitterAPI.io returns tweets in reverse-chronological order (`queryType="Latest"`).
- During pagination, **as soon as a returned tweet ID already exists in the local database, the pagination loop halts immediately**.
- Any remaining tweets required to fulfill your requested sample size (e.g., 500 tweets) are loaded directly from the local database.
- **Result**: On repeated or intraday searches, you only pay for the few brand-new tweets posted since your last search (often 1 page call = ~$0.006) instead of re-fetching hundreds of tweets you already have.
│
▼
Tier 3: TypeSafe Jev System One Evaluation (`typesafe-sdk`)
Evaluates 4 typed questions concurrently on the combined state:
1. Trade Action (Choice: Strong Buy, Buy, Hold, Take Profit, Sell, Strong Sell)
2. Sentiment Spectrum (Score: Extreme Panic to Euphoria)
3. Squeeze Risk (Noul: probability that negative funding + panic indicates a short squeeze)
4. Catalyst Significance (Score: None, Minor, Moderate, Major)
│
▼
Decision Card Displayed in Web Terminal
- Recommended action with calibrated confidence percentage
- Macro sentiment gauge across all 500 tweets
- Calculated entry range, stop loss, and target levels
- User executes manually on their exchange of choice
You can configure the tweet sample size in the terminal interface based on your needs:
| Sample Size | TwitterAPI.io Cost | TypeSafe Jev Cost | Total Cost per Search | Best For |
|---|---|---|---|---|
| 50 Tweets | ~$0.0075 | ~$0.0008 | < $0.009 (<1¢) | Quick pulse check on immediate price moves |
| 100 Tweets | ~$0.0150 | ~$0.0008 | ~$0.016 (1.6¢) | Standard intraday trading check |
| 250 Tweets | ~$0.0375 | ~$0.0008 | ~$0.038 (3.8¢) | Multi-hour swing setup validation |
| 500 Tweets | ~$0.0750 | ~$0.0008 | ~$0.076 (7.6¢) | Comprehensive sentiment & news audit |
| 1,000 Tweets | ~$0.1500 | ~$0.0008 | ~$0.151 (15¢) | Major regime shift or ETF/catalyst investigation |
Note: Repeated searches for the same asset within a 10-minute window hit the local cache and cost $0.00.
.
├── app/
│ ├── api/
│ │ └── v1/
│ │ └── analyze.py # Search and settings endpoints
│ ├── core/
│ │ ├── config.py # App configuration and environment variables
│ │ ├── cache.py # In-memory TTL caches
│ │ └── database.py # Local SQLite tweet storage and retrieval
│ ├── services/
│ │ ├── market_service.py # Exchange data client (CCXT Kraken/Kraken Futures)
│ │ ├── twitter_service.py # TwitterAPI.io client with cursor pagination
│ │ ├── stats_service.py # Tier 1 deterministic statistical pre-processing
│ │ └── typesafe_service.py # TypeSafe Jev System One client and decision logic
│ ├── static/
│ │ ├── css/
│ │ │ └── style.css # Dark quantitative terminal styling
│ │ └── js/
│ │ └── app.js # Frontend controls and result rendering
│ ├── templates/
│ │ └── index.html # Main web terminal interface
│ └── main.py # FastAPI application entrypoint
├── requirements.txt
└── README.md
- Python 3.12 or higher
- A TypeSafe AI API key (from console.typesafe.ai)
- A TwitterAPI.io API key (from twitterapi.io)
git clone <repo-url>
cd Jev-X-Sentiment-Analysis
python -m venv venv
source venv/bin/activate
pip install -r requirements.txtCreate a .env file in the root directory:
TYPESAFE_API_KEY=your_typesafe_api_key_here
TWITTER_API_KEY=your_twitterapi_io_key_here
# Optional configuration
PORT=8000
HOST=127.0.0.1
CACHE_TTL_SECONDS=600
# Security & Access Control
ALLOWED_ORIGINS=http://localhost:8000,http://127.0.0.1:8000
# ADMIN_TOKEN=your_secret_admin_token_hereuvicorn app.main:app --reload --port 8000Open your browser and navigate to:
http://localhost:8000
pytest -v- Enter a Symbol: Type any supported cryptocurrency symbol (e.g.
BTC,SOL,ETH). - Select Sample Size: Choose between 50, 100, 250, 500, or 1,000 tweets using the sample slider.
- Review Market & Derivatives Data: View live spot price, 24-hour volume, perpetuals funding rate, and open interest delta (powered by Kraken & Kraken Futures).
- Inspect Social Sentiment: Check engagement velocity, fear/greed polarity, and top-discussed catalysts across the sample.
- Read the Jev System One Decision: Review the recommended action (
STRONG BUY,BUY,HOLD,TAKE PROFIT,SELL), confidence percentage, and rationale. - Execute Manually: Review the calculated entry, stop-loss, and target levels and execute manually on your preferred exchange or DEX.
Not Financial Advice: This software is created strictly for educational, research, and technical demonstration purposes. None of the quantitative models, sentiment scores, trade levels, or verdicts generated by this platform constitute financial, investment, or trading advice. Trading cryptocurrencies carries a significant risk of financial loss. Always perform your own due diligence and never trade with funds you cannot afford to lose.
This project is open-source software licensed under the MIT License.