https://github.com/streamr-dev/weather-ai-example
This repository houses two servers: ai-stream-server and weather-stream-server. Designed to integrate AI and weather data streams, users can configure streams, set up their environment, and easily deploy servers.
https://github.com/streamr-dev/weather-ai-example
Last synced: about 2 months ago
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This repository houses two servers: ai-stream-server and weather-stream-server. Designed to integrate AI and weather data streams, users can configure streams, set up their environment, and easily deploy servers.
- Host: GitHub
- URL: https://github.com/streamr-dev/weather-ai-example
- Owner: streamr-dev
- Created: 2023-09-19T10:48:52.000Z (over 2 years ago)
- Default Branch: master
- Last Pushed: 2023-09-19T11:16:09.000Z (over 2 years ago)
- Last Synced: 2025-03-16T03:45:45.997Z (12 months ago)
- Language: TypeScript
- Size: 104 KB
- Stars: 0
- Watchers: 3
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# **AI & Weather Stream Servers Installation & Configuration Guide**
# **1. Context**
## **Overview**
This service consists of two servers designed to publish data to distinct data streams:
1. **Weather Stream**: Contains individual weather data points.
2. **AI Stream**: Houses weather reports, generated through the OpenAI API using a Large Language Model (LLM). These reports are based on averaged values derived from the data points of the weather stream.
## **Server Responsibilities**
- **weather-stream-server**:
- Publishes mock weather data at one-second intervals.
- **ai-stream-server**:
- Aggregates the last 60 weather data points.
- Calculates averages based on these data points.
- Sends a request to OpenAI to obtain a corresponding weather report.
- Publishes the generated weather report to the AI stream.
## **Data Structure Examples**
### **Weather Data Point**:
```json
{
"temperature": 27.56,
"humidity": 46.39,
"airQualityIndex": 16,
"noiseLevel": 66.45
}
```
### **Averaged Weather Data Point**:
```json
{
"avgTemperature": 26.939166666666658,
"avgHumidity": 66.64150000000001,
"avgAQI": 68.88333333333334,
"avgNoise": 59.78016666666665
}
```
### **Weather Report Generated by Chat-GPT**:
```
In the past hour, the temperature averaged around a comfy 24.99°C, making it a pleasant time to step outside. The humidity clocked in at approximately 64.88%, so it's not too muggy out there. The air quality index (AQI) averaged at 68.18, indicating decent air quality. And well, the noise level averaged around 59.93, reminding us that silence is golden.
Remember, folks, weather reports are like jokes - they can always use a little sunshine!"
```
## **2. Installation**
### **AI Stream Server**:
```bash
cd ai-stream-server
npm install
```
### **Weather Stream Server**:
```bash
cd weather-stream-server
npm install
```
## **2. Environment Configuration**
For both `ai-stream-server` and `weather-stream-server`:
1. Create a `.env` file.
2. Add the `PRIVATE_KEY` environment variable.
## **3. Stream Configuration**
Both servers come with a configuration file with predefined stream IDs. If you use the given wallet address, you won't have permissions to publish data to these streams.
To configure your stream:
1. Create a new stream with the hub. Follow this tutorial for guidance:
[How to Create a Stream with the Hub](https://www.loom.com/share/6f06b3b19b1a4787a7807853793b3834?sid=0f08e218-f932-4c35-838c-6ed212462636).
2. Make sure to create the stream using the same wallet address from which you obtained your private key. This ensures you have the right permissions. Alternatively, you can assign permissions to another address via the Hub's user interface.
3. You'll need to establish two streams:
- One for weather mock data.
- Another for the weather report data.
4. Update the stream IDs in both config.ts files.
## **4. Starting the Servers**
Open two separate terminals (preferably bash) and execute:
```bash
npm run start
```