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| import requests | |
| from flask import Flask, request, Response, jsonify | |
| import os | |
| app = Flask(__name__) | |
| cookie = os.environ.get('COOKIE') | |
| # Authentication headers (this could be made dynamic too) | |
| headers = { | |
| 'accept': 'application/json', | |
| 'content-type': 'application/json', | |
| 'cookie': cookie | |
| } | |
| # Base URL for proxying the requests | |
| base_url = 'https://openui.fly.dev' | |
| def hello(): | |
| return 'Hello, World!' | |
| # /v1/models endpoint | |
| def get_models(): | |
| models_data = { | |
| "data": [ | |
| { | |
| "id": "gpt-3.5-turbo", | |
| "object": "model", | |
| "created": 1, | |
| "token_coefficient": 0.5, | |
| "max_tokens": 16385 | |
| }, | |
| { | |
| "id": "gpt-4-turbo", | |
| "object": "model", | |
| "created": 1, | |
| "vision": True, | |
| "token_coefficient": 1, | |
| "max_tokens": 128000 | |
| }, | |
| { | |
| "id": "gpt-4o", | |
| "object": "model", | |
| "created": 1, | |
| "vision": True, | |
| "token_coefficient": 0.9, | |
| "max_tokens": 128000 | |
| }, | |
| { | |
| "id": "gpt-4o-mini", | |
| "object": "model", | |
| "created": 1, | |
| "vision": True, | |
| "token_coefficient": 0.2, | |
| "max_tokens": 128000 | |
| } | |
| ] | |
| } | |
| return jsonify(models_data) | |
| # /v1/chat/completions endpoint with streaming | |
| def chat_completions(): | |
| # Extract request data (JSON payload) | |
| payload = request.json | |
| # Forward the POST request to the target API with streaming responses | |
| url = f'{base_url}/v1/chat/completions' | |
| response = requests.post(url, headers=headers, json=payload, stream=True) | |
| # Streaming response back to the client | |
| def stream_response(): | |
| for chunk in response.iter_content(chunk_size=1024): | |
| if chunk: | |
| yield chunk.decode('utf-8') | |
| return Response(stream_response(), content_type='application/json') | |
| if __name__ == '__main__': | |
| app.run(debug=True, host='0.0.0.0') # To run it in docker container | |