app.py

import requests
from flask import Flask, request, jsonify
import logging
import json

# Initialize Flask app
app = Flask(__name__)

# Set up logging for debugging purposes
logging.basicConfig(level=logging.INFO)

# Define the endpoint to interact with the Amigo API
AMIGO_API_URL = "https://api.amigochat.io/v1/chat/completions"

headers = {
    'accept': 'application/json, text/event-stream',
    'accept-language': 'en-US,en;q=0.9,ru;q=0.8',
    'content-type': 'application/json',
    'origin': 'https://niansuh-01.hf.space',
    'priority': 'u=1, i',
    'referer': 'https://niansuh-01.hf.space/?logs=container',
    'sec-ch-ua': '"Google Chrome";v="131", "Chromium";v="131", "Not_A Brand";v="24"',
    'sec-ch-ua-mobile': '?0',
    'sec-ch-ua-platform': '"Windows"',
    'sec-fetch-dest': 'empty',
    'sec-fetch-mode': 'cors',
    'sec-fetch-site': 'same-origin',
    'user-agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/131.0.0.0 Safari/537.36',
}

@app.route('/v1/chat/completions', methods=['POST'])
def chat_completions():
    try:
        # Log incoming request data
        data = request.get_json()
        app.logger.info(f"Received request data: {json.dumps(data, indent=2)}")

        # Prepare the payload for the Amigo API
        payload = {
            "messages": data['messages'],
            "model": data.get('model', 'gpt-4o-mini'),  # Default to 'gpt-4o-mini'
            "personaId": "amigo",
            "frequency_penalty": 0,
            "max_tokens": 4000,
            "presence_penalty": 0,
            "stream": True,
            "temperature": 0.5,
            "top_p": 0.95
        }

        # Send the request to the Amigo API
        response = requests.post(AMIGO_API_URL, headers=headers, json=payload)

        # If the request is successful, return the response in OpenAI format
        if response.status_code == 200:
            amigo_response = response.json()

            # Log the response from Amigo API
            app.logger.info(f"Amigo API response: {json.dumps(amigo_response, indent=2)}")

            # Transform the Amigo API response to OpenAI API response format
            openai_response = {
                "id": amigo_response.get('id', 'unknown'),
                "object": "chat.completion",
                "created": amigo_response.get('created', 0),
                "model": amigo_response.get('model', 'gpt-4o-mini'),
                "choices": [
                    {
                        "message": {
                            "role": amigo_response.get('messages', [{}])[0].get('role', 'user'),
                            "content": amigo_response.get('messages', [{}])[0].get('content', '')
                        },
                        "finish_reason": amigo_response.get('finish_reason', 'stop'),
                        "index": 0
                    }
                ],
                "usage": amigo_response.get('usage', {})
            }

            return jsonify(openai_response)
        else:
            # Log the error if the response from Amigo API is not 200
            app.logger.error(f"Amigo API failed with status {response.status_code}: {response.text}")
            return jsonify({
                'error': {
                    'message': f'Failed to fetch from Amigo API: {response.text}',
                    'type': 'internal_error'
                }
            }), 500

    except Exception as e:
        # Catch any other errors and log them
        app.logger.error(f"Error in processing request: {str(e)}")
        return jsonify({
            'error': {
                'message': f'An error occurred: {str(e)}',
                'type': 'internal_error'
            }
        }), 500

if __name__ == '__main__':
    app.run(debug=True, host='0.0.0.0', port=5000)