Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/wolfelogix/product-pipeline
This is an ai based product generation data pipeline
https://github.com/wolfelogix/product-pipeline
ai openai printify shopify
Last synced: 2 months ago
JSON representation
This is an ai based product generation data pipeline
- Host: GitHub
- URL: https://github.com/wolfelogix/product-pipeline
- Owner: WolfeLogix
- Created: 2024-09-14T19:10:22.000Z (5 months ago)
- Default Branch: main
- Last Pushed: 2024-11-25T17:24:42.000Z (3 months ago)
- Last Synced: 2024-11-25T17:27:48.467Z (3 months ago)
- Topics: ai, openai, printify, shopify
- Language: Python
- Homepage:
- Size: 2.38 MB
- Stars: 3
- Watchers: 3
- Forks: 0
- Open Issues: 6
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Product Pipeline
[](https://github.com/parishwolfe/product-pipeline/actions/workflows/github-code-scanning/codeql) [](https://github.com/parishwolfe/product-pipeline/actions/workflows/pep8.yaml) [](https://github.com/parishwolfe/product-pipeline/actions/workflows/deployment.yaml)
This project is an ai based data pipeline. You start by suppling an idea for a category of t-shirt. When the pipeline runs, it does a number of things:
- generates `p` number of patterns using the supplied `idea`
- generates an image with a transparent background with the generated text
- uploads these images to github
- lists and publishes all the new patterns on printify
From there, Printify takes over and the following things happen
- products are synced with shopify, and a number of other retailers
- orders are automatically sent to the print provider when a sale is made
## Running Locally
There are two ways this can be run. The first is as a command line utility, and the second is as a web service.
to run it as a command line utility, run the following command:
```bash
python3.12 product_pipeline.py -p 10 "Idea for a t-shirt"
```
In order to run the application as a web service, run the following command:
```bash
uvicorn product_pipeline:app --host localhost --port 8080 --reload
```
## Deployment
### Google Cloud Functions
Stay tuned for the deployment to GCP!
## Reuqired Environment Variables
Run the following command to generate the required `.env` file. Replace the empty strings with the appropriate values.
```bash
cat < .env
PRINTIFY_API_KEY=""
OPENAI_API_KEY=""
GH_PAT=""
GH_UPLOAD_REPO=""
GH_CONTENT_PREFIX=""
EOF
```
Additionally, the shopify utility requires these envronment variables to be set:
```bash
echo 'SHOPIFY_API_KEY=""' >> .env
echo 'SHOPIFY_API_ACCESS_TOKEN=""' >> .env
echo 'SHOPIFY_SHOP_NAME=""' >> .env
```
## Running Tests
Formal unit tests are not yet implemented. However, all the functions have a manual test if you run the script directly.
### Main Project
`clear && flake8 --ignore=E501 --exclude=.venv`
### FastAPI Component
```bash
curl -X POST "http://localhost:8080/process_patterns" \
-H "Content-Type: application/json" \
-d '{"patterns": 1, "idea": "unit testing"}'
```
### Image Utility
`python3.12 image_util.py`
### AI Utility
`python3.12 ai_util.py`