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app.py

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+"""
+Hugging Face Space for EPL Predictions
+Deploy this as a Gradio app on HF Spaces
+"""
+import gradio as gr
+import numpy as np
+import pandas as pd
+from model_predictor import EPLPredictor
+import json
+
+# Initialize predictor
+print("Loading models...")
+predictor = EPLPredictor(use_local=False)  # Will download from HF
+print("Models loaded!")
+
+def predict_match(home_team, away_team, home_odds, draw_odds, away_odds):
+    """Predict match outcome"""
+    try:
+        # Create odds dict
+        best_odds = {
+            'H': {'odds': home_odds},
+            'D': {'odds': draw_odds},
+            'A': {'odds': away_odds}
+        }
+
+        # Get predictions
+        result = predictor.predict(
+            home_team=home_team,
+            away_team=away_team,
+            best_odds=best_odds
+        )
+
+        # Format output
+        output = f"""
+## Match Prediction: {home_team} vs {away_team}
+
+### Ensemble Probabilities:
+- **Home Win**: {result['ensemble']['H']:.1%}
+- **Draw**: {result['ensemble']['D']:.1%}
+- **Away Win**: {result['ensemble']['A']:.1%}
+- **Over 2.5 Goals**: {result['ensemble']['over25']:.1%}
+- **BTTS**: {result['ensemble']['btts']:.1%}
+
+### Expected Goals:
+- {home_team}: {result['expected_goals']['home']:.2f}
+- {away_team}: {result['expected_goals']['away']:.2f}
+
+### Model Components:
+**Poisson**: H:{result['poisson']['H']:.1%} D:{result['poisson']['D']:.1%} A:{result['poisson']['A']:.1%}
+**XGBoost**: H:{result['xgboost']['H']:.1%} D:{result['xgboost']['D']:.1%} A:{result['xgboost']['A']:.1%}
+        """
+
+        # Check for value
+        value_analysis = ""
+        for market, prob in [('Home', result['ensemble']['H']),
+                             ('Draw', result['ensemble']['D']),
+                             ('Away', result['ensemble']['A'])]:
+            if market == 'Home':
+                odds = home_odds
+            elif market == 'Draw':
+                odds = draw_odds
+            else:
+                odds = away_odds
+
+            value = predictor.calculate_value(prob, odds)
+            if value['has_value']:
+                value_analysis += f"\n⚡ **VALUE BET**: {market} @ {odds:.2f} (Edge: {value['edge']:.1f}%)"
+
+        if value_analysis:
+            output += f"\n### Value Bets Found:{value_analysis}"
+        else:
+            output += "\n### No value bets found at these odds"
+
+        return output
+
+    except Exception as e:
+        return f"Error: {str(e)}"
+
+def batch_predict(csv_text):
+    """Predict multiple matches from CSV"""
+    try:
+        # Parse CSV
+        lines = csv_text.strip().split('\n')
+        results = []
+
+        for line in lines[1:]:  # Skip header
+            parts = line.split(',')
+            if len(parts) >= 5:
+                home, away = parts[0].strip(), parts[1].strip()
+                h_odds, d_odds, a_odds = float(parts[2]), float(parts[3]), float(parts[4])
+
+                pred = predict_match(home, away, h_odds, d_odds, a_odds)
+                results.append(pred)
+
+        return "\n---\n".join(results)
+    except Exception as e:
+        return f"Error processing CSV: {str(e)}"
+
+# Create Gradio interface
+with gr.Blocks(title="EPL Match Predictor") as app:
+    gr.Markdown("""
+    # ⚽ EPL Match Predictor
+
+    Powered by ensemble models (Poisson + XGBoost) trained on EPL data.
+
+    Models available at: [gnosisx/epl-ensemble-1x2](https://huggingface.co/gnosisx/epl-ensemble-1x2)
+    """)
+
+    with gr.Tab("Single Match"):
+        with gr.Row():
+            home_input = gr.Textbox(label="Home Team", value="Liverpool")
+            away_input = gr.Textbox(label="Away Team", value="Everton")
+
+        with gr.Row():
+            home_odds_input = gr.Number(label="Home Odds", value=1.48)
+            draw_odds_input = gr.Number(label="Draw Odds", value=5.0)
+            away_odds_input = gr.Number(label="Away Odds", value=8.0)
+
+        predict_btn = gr.Button("Predict", variant="primary")
+        output = gr.Markdown()
+
+        predict_btn.click(
+            predict_match,
+            inputs=[home_input, away_input, home_odds_input, draw_odds_input, away_odds_input],
+            outputs=output
+        )
+
+    with gr.Tab("Batch Prediction"):
+        gr.Markdown("Upload CSV with format: `Home,Away,HomeOdds,DrawOdds,AwayOdds`")
+
+        csv_input = gr.Textbox(
+            label="CSV Data",
+            lines=10,
+            value="Home,Away,H_Odds,D_Odds,A_Odds\nLiverpool,Everton,1.48,5.0,8.0\nArsenal,Chelsea,2.1,3.5,3.8\nMan City,Burnley,1.15,9.0,21.0"
+        )
+
+        batch_btn = gr.Button("Predict All", variant="primary")
+        batch_output = gr.Markdown()
+
+        batch_btn.click(
+            batch_predict,
+            inputs=csv_input,
+            outputs=batch_output
+        )
+
+    with gr.Tab("API"):
+        gr.Markdown("""
+        ## API Endpoint
+
+        You can also use this as an API:
+
+        ```python
+        import requests
+
+        response = requests.post(
+            "https://gnosisx-epl-predictor.hf.space/api/predict",
+            json={
+                "home_team": "Liverpool",
+                "away_team": "Everton",
+                "best_odds": {
+                    "H": {"odds": 1.48},
+                    "D": {"odds": 5.0},
+                    "A": {"odds": 8.0}
+                }
+            }
+        )
+        print(response.json())
+        ```
+        """)
+
+# Launch app
+if __name__ == "__main__":
+    app.launch()