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| # A/B Test Predictor - Quick Start Guide | |
| ## π Get Started in 3 Steps | |
| ### 1. Install | |
| ```bash | |
| pip install gradio-client | |
| ``` | |
| ### 2. Predict | |
| ```python | |
| from gradio_client import Client | |
| client = Client("SpiralyzeLLC/ABTestPredictor") | |
| result = client.predict( | |
| "control.jpg", # Your control image | |
| "variant.jpg", # Your variant image | |
| "SaaS", # Business Model | |
| "B2B", # Customer Type | |
| "High-Intent Lead Gen", # Conversion Type | |
| "B2B Software & Tech", # Industry | |
| "Awareness & Discovery", # Page Type | |
| api_name="/predict_with_categorical_data" | |
| ) | |
| ``` | |
| ### 3. View Results | |
| ```python | |
| print(f"Win Probability: {result['predictionResults']['probability']}") | |
| print(f"Confidence: {result['predictionResults']['modelConfidence']}%") | |
| if float(result['predictionResults']['probability']) > 0.5: | |
| print("π Variant predicted to WIN!") | |
| else: | |
| print("β οΈ Control predicted to win") | |
| ``` | |
| ## π Input Parameters | |
| | Parameter | Values | | |
| |-----------|--------| | |
| | **Business Model** | `E-Commerce`, `Lead Generation`, `Other*`, `SaaS` | | |
| | **Customer Type** | `B2B`, `B2C`, `Both`, `Other*` | | |
| | **Conversion Type** | `Direct Purchase`, `High-Intent Lead Gen`, `Info/Content Lead Gen`, `Location Search`, `Non-Profit/Community`, `Other Conversion` | | |
| | **Industry** | `Automotive & Transportation`, `B2B Services`, `B2B Software & Tech`, `Consumer Services`, `Consumer Software & Apps`, `Education`, `Finance, Insurance & Real Estate`, `Food, Hospitality & Travel`, `Health & Wellness`, `Industrial & Manufacturing`, `Media & Entertainment`, `Non-Profit & Government`, `Other`, `Retail & E-commerce` | | |
| | **Page Type** | `Awareness & Discovery`, `Consideration & Evaluation`, `Conversion`, `Internal & Navigation`, `Post-Conversion & Other` | | |
| ## π Response | |
| ```json | |
| { | |
| "predictionResults": { | |
| "probability": "0.682", // >0.5 = Variant wins | |
| "modelConfidence": "66.1", // Accuracy % for this category | |
| "trainingDataSamples": 14634, // Training data size | |
| "totalPredictions": 1626, // Total test predictions | |
| "correctPredictions": 1074 // Correct predictions | |
| } | |
| } | |
| ``` | |
| ## π Or Use Web Interface | |
| Visit: **https://huggingface.co/spaces/SpiralyzeLLC/ABTestPredictor** | |
| 1. Upload images | |
| 2. Select categories | |
| 3. Click "Predict" | |
| 4. Get instant results! | |
| ## π Full Documentation | |
| For complete API reference, error handling, and advanced examples: | |
| π See **[API_DOCUMENTATION.md](API_DOCUMENTATION.md)** | |
| --- | |
| **Need Help?** Check [Common Issues](API_DOCUMENTATION.md#-common-issues) in the full docs. | |