Jev X Sentiment Analysis

September 19, 2026 · View on GitHub

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.

How Tweets Are Analyzed

When you request sentiment analysis across 100 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 two-tier 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
   - Interactive TradingView candlestick chart
   - 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.

Technical Architecture

.
├── app/
│   ├── api/
│   │   └── v1/
│   │       ├── analyze.py        # Search endpoint: runs ingestion, stats, and decision
│   │       ├── market.py         # CCXT market price & funding rate helpers
│   │       └── social.py         # TwitterAPI.io paginated search & caching
│   ├── core/
│   │   ├── config.py             # App configuration and environment variables
│   │   └── cache.py              # In-memory / local cache for 10-minute tweet deduplication
│   ├── services/
│   │   ├── market_service.py     # Exchange data client (CCXT Binance/Bybit)
│   │   ├── twitter_service.py    # TwitterAPI.io client with cursor pagination (up to 1,000 tweets)
│   │   ├── stats_service.py      # Tier 1 deterministic statistical pre-processing
│   │   └── typesafe_service.py   # TypeSafe Jev System One client & question definitions
│   ├── static/
│   │   ├── css/
│   │   │   └── style.css         # Dark quantitative terminal styling
│   │   └── js/
│   │       └── app.js            # Frontend logic, sample-size slider, TradingView chart
│   ├── templates/
│   │   └── index.html            # Main web terminal interface
│   └── main.py                   # FastAPI application entrypoint
├── ai_market_intelligence_requirements.md
├── requirements.txt
└── README.md

Setup and Installation

Prerequisites

Python 3.12 or higher
A TypeSafe AI API key (from console.typesafe.ai)
A TwitterAPI.io API key (from twitterapi.io)

1. Clone and Install Dependencies

git clone <repo-url>
cd "Jev AI Market Analysis"

python -m venv venv
source venv/bin/activate

pip install -r requirements.txt

2. Configure Environment Variables

Create 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=0.0.0.0
CACHE_TTL_SECONDS=600

3. Run the Application

uvicorn app.main:app --reload --port 8000

Open your browser and navigate to:

http://localhost:8000

Usage Workflow

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.
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: Copy the calculated entry, stop-loss, and target levels and execute the order on your preferred exchange or DEX.