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# 🌡️ PolyWeather: Quantitative Weather Trading & AI Command Center
# 🌡️ PolyWeather: Intelligent Weather Quant Analysis Bot
![Banner Placeholder: Futuristic Weather Trading System]
PolyWeather is not just a simple weather bot. It is an **institutional-grade weather quantitative trading assistant** designed for prediction markets like **Polymarket** and other weather derivatives. By connecting directly to global aviation weather stations (METAR) without CDN caching, integrating our Dynamic Ensemble Blending (DEB) model, extracting real-time micro-climate features, and stripping away human emotion via the massive LLaMA 70B AI model, it provides you with rapid, objective, and lethal trading signals.
PolyWeather is a weather analysis tool specifically designed for prediction markets like **Polymarket**. It aggregates multi-source forecasts, real-time airport METAR observations, and incorporates AI-driven decision support to help users evaluate weather-related risks more scientifically.
---
## 🚀 Core Features Matrix
## ✨ Core Features
### 1. 🧠 Proprietary Moat: Dynamic Ensemble Blending (DEB)
### 1. 🧬 Dynamic Ensemble Blending (DEB Algorithm)
Traditional weather bots simply calculate rigid averages out of numerical models like ECMWF and GFS. PolyWeather introduces a **dynamic tracking and backtesting algorithm**:
The system automatically tracks the historical performance of various weather models (ECMWF, GFS, ICON, GEM, JMA) in specific cities:
- **Adaptive Weight Evolution**: By looking back at the Mean Absolute Error (MAE) of each model over the past 7-14 days at specific airports (e.g., Esenboğa Airport in Ankara), the system actively penalizes and rewards the 5 major NWP models (ECMWF, GFS, ICON, GEM, JMA) per query.
- **High-Concurrency Thread-Safe Database**: Built on an underlying memory singleton cache and system-level file locks (`fcntl Lock`), PolyWeather guarantees 0 disk I/O bottlenecks and microsecond response times—even when bombarded by 500+ users checking the weather at the exact same millisecond.
- **Error-Based Weighting**: Dynamically adjusts weights for each model based on their Mean Absolute Error (MAE) over the past 7 days.
- **Blended Forecast**: Provides a "Blended High Temperature" recommendation corrected for historical biases.
- **Concurrency Optimization**: Built-in singleton cache and file locking mechanism to support high-concurrency queries and ensure data safety.
### 2. 🤖 AI Trading Veteran (Groq AI Agent)
### 2. 🤖 AI Intelligent Analysis (Groq LLaMA 3.3)
The system no longer outputs boring templates. We feed all **complex thermodynamic parameters** (wind direction/speed matrix, cooling inertia, rounding resistance) into LLaMA 3.3 70B via the lightning-fast Groq API:
Integrates the LLaMA 70B model to interpret rapidly changing meteorological data:
- **🧊 Forced Objectivity**: With strict logical constraints built into the prompt, the AI accurately evaluates scenarios like "15kt cold northerly winds at 3 PM, coupled with radiation dropping below 50W/m²" and immediately calls "Dead market: peak passed, bets frozen."
- **🎯 Quantitative Confidence Scoring**: It outputs a 1-10 confidence score with strong guidance. High confidence means an "immediate signal to build positions," whereas low confidence warns of a chaotic market full of wind/rain uncertainties.
- **Logical Deduction**: Considers dynamic factors such as wind speed, wind direction, cloud cover, and solar radiation to judge temperature trends.
- **Confidence Scoring**: Provides a confidence score from 1-10 for the current market conditions.
- **Automatic Cooldown Determination**: When temperature drop is observed or the forecast peak has passed, the AI provides a definitive market conclusion.
### 3. ⏱️ Absolute Live Dominance (Zero-Cache METAR Extraction)
### 3. ⏱️ Real-time Airport Observations (Zero-Cache METAR)
In the meat grinder of Polymarket weather settlements, **a 1-minute delay can mean a 100% loss of your principal**.
- **Live Passthrough**: Bypasses CDN caching via dynamic headers to obtain first-hand METAR reports from airports.
- **Settlement Warning**: Automatically calculates the Wunderground settlement boundary (X.5 rounding line) to warn of potential volatility.
- PolyWeather forces anti-cache dynamic timestamps on every single API call, bypassing all proxy network (CDN) stagnant cache pools.
- It doesn't just extract "how many degrees it is now." It analyzes the exact decimal point for Settlement Risk (including the deadly X.5 Wunderground roundup boundaries).
### 4. 📈 Historical Data Collection
### 4. 📈 High-Frequency Data Mining Foundation
Built-in `fetch_history.py` native spider system.
- One click to pull down hundreds of thousands of rows of hourly historical physics sandbox feature matrices (over 10 dimensions including humidity, shortwave radiation, surface pressure) for any global benchmark city across the past 3-5 years.
- Infinite ammunition ready for our next-generation XGBoost / LightGBM Machine Learning Model Output Statistics (MOS) calibration.
- Includes `fetch_history.py` to retrieve up to 3 years of hourly historical weather data for any city, supporting future algorithm development.
---
## ⚡ Deployment & Operations
## ⚡ Deployment
### Environment Architecture
### Requirements
- **Core Engine**: Python 3.11+ (Strict Compliance)
- **Dependency Stack**: `pip install -r requirements.txt`
- **Volume Mounts**: Minimal configuration. Just register your `TELEGRAM_BOT_TOKEN` and `GROQ_API_KEY` inside `.env` to summon the AI.
- **Python 3.11+**
- Install dependencies: `pip install -r requirements.txt`
- **Environment Variables**: Set `TELEGRAM_BOT_TOKEN` and `GROQ_API_KEY` in your `.env` file.
### Recommended 1-Click VPS Production Launch
### VPS Quick Deployment
**Step 1: Build & Register**
```bash
git clone https://github.com/yangyuan-zhen/PolyWeather.git
cd PolyWeather
pip install -r requirements.txt
cp .env.example .env # Be sure to insert your secure API keys
```
**Step 2: Daemon Updater Assembly**
Set up an automated keep-alive script to integrate updates, conflict-resolution, and hot-swaps all in one push:
1. Clone the repository and install dependencies.
2. Configure your `.env` file.
3. Use the following script for one-click updates and restarts:
```bash
cat > ~/update.sh << 'EOF'
@@ -66,89 +53,44 @@ cat > ~/update.sh << 'EOF'
cd ~/PolyWeather
git fetch origin
git reset --hard origin/main
pkill -f run.py
pkill -f bot_listener.py
sleep 1
nohup python3 bot_listener.py > bot.log 2>&1 &
echo "✅ PolyWeather Quant Terminal up and loaded with the latest modules!"
echo "✅ PolyWeather Restarted!"
EOF
chmod +x ~/update.sh
```
**Daily Operations Command (Push & Play):**
---
```bash
~/update.sh
```
## 🕹️ Bot Commands
> One command to wipe Git conflicts, execute warm/cold reboots, and clean logs.
| Command | Description |
| :------------------ | :-------------------------------------------------------------------- |
| `/city [city_name]` | Get in-depth weather analysis, live tracking, and AI-driven insights. |
| `/id` | View the Chat ID of the current conversation. |
| `/help` | Display help information. |
### Supported City Examples
`lon` (London), `par` (Paris), `ank` (Ankara), `nyc` (New York), `chi` (Chicago), `ba` (Buenos Aires), etc.
---
## 🕹️ Telegram Command Center
## 🏗️ Architecture
| Tactical Command | Trigger Action | Module Feedback |
| :------------------ | :------------------ | :----------------------------------------------------------------------------------------------------------------------------------------------------- |
| `/city [City Code]` | **Reconnaissance** | Initiates full-dimension weather sweep. Returns DEB-weighted forecast, METAR tracking, rounding risk warnings, and AI quantitative trading conclusion. |
| `/id` | **Identity Ping** | Maps the current comm channel (Chat ID). |
| `/help` | **Terminal Manual** | Pulls the latest command set. |
### Target Arenas
From low-risk setups in the Middle East/Africa to high-latency slippage arenas in North America, PolyWeather embeds precise airport deviation models (Risk Profiles):
`lon`(London EGLC), `par`(Paris LFPG), `ank`(Ankara LTAC), `nyc`(New York KLGA), `chi`(Chicago KORD), `ba`(Buenos Aires SAEZ)... and more.
> **Fire Examples:**
> `/city Paris`
> `/city london`
> `/city ba`
- **Data Layer**: Interfaces with Open-Meteo, NOAA, MGM, and other data sources.
- **Algorithm Layer**: DEB dynamic weighting system + concurrency caching mechanism.
- **Decision Layer**: Real-time trading logic analysis based on Groq API.
---
## 🏗️ System Architecture Anatomy
## 💡 Trading Tips
```mermaid
graph TD
classDef ai fill:#f9f,stroke:#333,stroke-width:2px;
classDef core fill:#bbf,stroke:#333,stroke-width:2px;
classDef data fill:#dfd,stroke:#333,stroke-width:1px;
User[Telegram / Signal Receiver] -->|Trigger Scan| Bot[bot_listener.py Core Scheduler]:::core
subgraph Heterogeneous Data Parsing
Bot --> Collector[WeatherDataCollector]
Collector --> OM[Open-Meteo Archive/Live]:::data
Collector --> MM[Multi-Model Predictors]:::data
Collector --> METAR[Air Traffic Control Raw Logs]:::data
end
subgraph Computation & Circuit Breakers
Collector --> DEB[DEB Dynamic Weighting]:::core
DEB --> DB[(daily_records JSON DB<br/>Thread-Safe)]
Collector --> Logic[Rounding Analysis / Cooldown]
end
subgraph AI Metric Generation
DEB --> AIAnalyzer[Groq/LLaMA Cognitive Model]:::ai
Logic --> AIAnalyzer
METAR --> AIAnalyzer
end
AIAnalyzer -->|Generates: Spread+Logic+Confidence| Bot
Bot -->|Assembles High-Dimensional Slice| User
```
1. **Reference DEB Blended Value**: When models diverge, the DEB corrected value is usually more reliable than a single forecast.
2. **Observe AI Confidence**: A confidence score below 5 indicates high uncertainty in the current meteorological environment.
3. **Watch Settlement Boundaries**: When the observed high is near X.5, be wary of rounding jumps during Wunderground settlements.
---
## 🎯 Trader's Playbook
As a Commander of PolyWeather, etch these rules into your DNA:
1. 🧬 **Trust the DEB Baseline**: Instead of blindly believing an extreme forecast from ECMWF or GFS, stare at the `DEB Blended Forecast` on line one. It is the system's re-calibrated truth, forged after absorbing the punishing MAE beating those models took over the past 7 days.
2. 🎯 **Respect the AI Confidence Red Line**: If the AI returns a `Confidence: ≤ 4/10`, it means the model's delay is clashing heavily with real-time airport headwinds. **Chop your gambling hands off immediately.** You are in a high-risk chaotic zone.
3. ⚖️ **Fear the X.5 Rounding Abyss**: Polymarket weather settles on integer values (rounded via Wunderground logic). When the terminal blinks `⚖️ Settlement Boundary... crossed the rounding line`, this is where liquidity dries up and slippage becomes most predatory.
4. 🌙 **Identify False Positives (Warm Advection radar)**: If the temperature ignores the sun and spikes during a low-radiation night, the system triggers a `🌙 Warm Advection Anomaly`. This mechanism frequently hands you the golden "LONG" signal (shattering the original forecast's ceiling) exactly when the rest of the market is betting NO.
---
_The weather changes. Our edge remains. | Updated 2026_
_Updated 2026_