init commit

environments/hack0/ufc_env/ufc_predictor_ui.py

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+import os
+import base64
+from io import BytesIO
+from flask import Flask, render_template, request, jsonify
+from PIL import Image
+import openai
+from dotenv import load_dotenv
+
+# Load environment variables
+load_dotenv()
+
+app = Flask(__name__)
+app.config['MAX_CONTENT_LENGTH'] = 16 * 1024 * 1024  # 16MB max file size
+
+# Initialize OpenAI client
+client = openai.OpenAI(api_key=os.getenv('OPENAI_API_KEY'))
+
+def process_image(image_file):
+    """Convert uploaded image to base64"""
+    img = Image.open(image_file)
+    # Convert RGBA to RGB if necessary
+    if img.mode == 'RGBA':
+        img = img.convert('RGB')
+    buffered = BytesIO()
+    img.save(buffered, format="JPEG")
+    return base64.b64encode(buffered.getvalue()).decode('utf-8')
+
+@app.route('/')
+def home():
+    return render_template('predictor.html')
+
+@app.route('/predict', methods=['POST'])
+def predict():
+    try:
+        # Get uploaded images
+        red_fighter = request.files['red_fighter']
+        blue_fighter = request.files['blue_fighter']
+        
+        if not red_fighter or not blue_fighter:
+            return jsonify({'error': 'Please upload both fighter images'}), 400
+
+        # Process images to base64
+        red_image = process_image(red_fighter)
+        blue_image = process_image(blue_fighter)
+
+        # Create the prompt
+        prompt_text = (
+            "🎤 LADIES AND GENTLEMEN! Welcome to the most electrifying show in sports entertainment "
+            "Let's break down this matchup that's got everyone talking!\n\n"
+            "In the red corner, we have:(YOUR FIRST IMAGE):\n"
+            "And in the blue corner: (YOUR SECOND IMAGE):\n\n"
+            "Now, as your favorite fight comentator, I want you to:\n"
+            "create a fight commentary of whats happening in the fight live\n"
+            "Give us your best fight commentary! Make it exciting, make it dramatic, make it sound like you're calling the fight live! "
+            "Throw in some classic commentator phrases, maybe a 'OH MY GOODNESS!' or two, and definitely some dramatic pauses for effect.\n\n"
+            "End your masterpiece with your prediction in this exact format:\n"
+            "\\boxed{Red} or \\boxed{Blue}"
+            "PLEASE FORMAT THE COMMENTARY IN THE EXACT FORMAT AS THE EXAMPLE BELOW:\n"
+            "[S1]Hello im your host  [S2] And so am i (name) [S1] Wow. Amazing. (laughs) [S2] Lets get started! (coughs) ( add lots of coughs and laughs)\n\n"
+        )
+
+        # Create the messages for the API call
+        messages = [
+            {
+                "role": "user",
+                "content": [
+                    {"type": "text", "text": prompt_text},
+                    {
+                        "type": "image_url",
+                        "image_url": {"url": f"data:image/jpeg;base64,{red_image}"}
+                    },
+                    {
+                        "type": "image_url",
+                        "image_url": {"url": f"data:image/jpeg;base64,{blue_image}"}
+                    }
+                ]
+            }
+        ]
+
+        # Make the API call
+        response = client.chat.completions.create(
+            model="gpt-4o",
+            messages=messages,
+            max_tokens=2048,
+            temperature=0.7,
+            top_p=0.95
+        )
+
+        # Extract the prediction
+        prediction = response.choices[0].message.content
+        
+        return jsonify({
+            'prediction': prediction,
+            'success': True
+        })
+
+    except Exception as e:
+        return jsonify({
+            'error': str(e),
+            'success': False
+        }), 500
+
+if __name__ == '__main__':
+    app.run(debug=True)