mirror of
https://github.com/NousResearch/atropos.git
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104 lines
No EOL
3.6 KiB
Python
104 lines
No EOL
3.6 KiB
Python
import os
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import base64
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from io import BytesIO
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from flask import Flask, render_template, request, jsonify
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from PIL import Image
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import openai
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from dotenv import load_dotenv
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# Load environment variables
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load_dotenv()
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app = Flask(__name__)
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app.config['MAX_CONTENT_LENGTH'] = 16 * 1024 * 1024 # 16MB max file size
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# Initialize OpenAI client
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client = openai.OpenAI(api_key=os.getenv('OPENAI_API_KEY'))
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def process_image(image_file):
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"""Convert uploaded image to base64"""
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img = Image.open(image_file)
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# Convert RGBA to RGB if necessary
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if img.mode == 'RGBA':
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img = img.convert('RGB')
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buffered = BytesIO()
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img.save(buffered, format="JPEG")
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return base64.b64encode(buffered.getvalue()).decode('utf-8')
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@app.route('/')
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def home():
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return render_template('predictor.html')
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@app.route('/predict', methods=['POST'])
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def predict():
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try:
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# Get uploaded images
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red_fighter = request.files['red_fighter']
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blue_fighter = request.files['blue_fighter']
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if not red_fighter or not blue_fighter:
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return jsonify({'error': 'Please upload both fighter images'}), 400
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# Process images to base64
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red_image = process_image(red_fighter)
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blue_image = process_image(blue_fighter)
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# Create the prompt
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prompt_text = (
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"🎤 LADIES AND GENTLEMEN! Welcome to the most electrifying show in sports entertainment "
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"Let's break down this matchup that's got everyone talking!\n\n"
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"In the red corner, we have:(YOUR FIRST IMAGE):\n"
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"And in the blue corner: (YOUR SECOND IMAGE):\n\n"
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"Now, as your favorite fight comentator, I want you to:\n"
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"create a fight commentary of whats happening in the fight live\n"
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"Give us your best fight commentary! Make it exciting, make it dramatic, make it sound like you're calling the fight live! "
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"Throw in some classic commentator phrases, maybe a 'OH MY GOODNESS!' or two, and definitely some dramatic pauses for effect.\n\n"
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"End your masterpiece with your prediction in this exact format:\n"
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"\\boxed{Red} or \\boxed{Blue}"
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"PLEASE FORMAT THE COMMENTARY IN THE EXACT FORMAT AS THE EXAMPLE BELOW:\n"
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"[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"
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)
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# Create the messages for the API call
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messages = [
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{
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"role": "user",
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"content": [
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{"type": "text", "text": prompt_text},
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{
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"type": "image_url",
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"image_url": {"url": f"data:image/jpeg;base64,{red_image}"}
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},
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{
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"type": "image_url",
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"image_url": {"url": f"data:image/jpeg;base64,{blue_image}"}
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}
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]
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}
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]
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# Make the API call
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response = client.chat.completions.create(
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model="gpt-4o",
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messages=messages,
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max_tokens=2048,
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temperature=0.7,
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top_p=0.95
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)
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# Extract the prediction
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prediction = response.choices[0].message.content
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return jsonify({
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'prediction': prediction,
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'success': True
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})
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except Exception as e:
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return jsonify({
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'error': str(e),
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'success': False
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}), 500
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if __name__ == '__main__':
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app.run(debug=True) |