from flask import Flask, request, Response, jsonify, render_template, url_for import g4f import sys import os from dotenv import load_dotenv load_dotenv() API_KEY = os.environ.get('API_KEY') from flask_cors import CORS app = Flask(__name__) CORS(app) @app.route('/favicon.ico') def favicon(): return url_for('static', filename='/favicon.ico') @app.route('/') def index(): return render_template('index.html') def generate_response(model, llm, content): response_generator = g4f.ChatCompletion.create( model=model, provider=llm, messages=[{"role": "user", "content": content}], stream=llm.supports_stream ) for message in response_generator: yield message @app.route('/chat_completion', methods=['POST']) def chat_completion(): data = request.get_json() required_params = {'content', 'api_key'} missing_params = required_params - set(data.keys()) if missing_params: error_msg = f"Missing parameters: {', '.join(missing_params)}" return jsonify({"error": error_msg}), 400 content = data['content'] pname = data.get('provider', 'Bing') # Use 'Bing' by default, if not provided api_key = data['api_key'] stream = data.get('stream', True) # Use True by default, if not provided if not api_key == API_KEY: return jsonify({"error": "Invalid API key"}), 401 try: llm = getattr(getattr(getattr(sys.modules[__name__], "g4f"), "Provider"), pname) except AttributeError: return jsonify({"error": f"Invalid provider: {pname}"}), 400 model = "gpt-3.5-turbo" if not llm.supports_gpt_35_turbo: model = "gpt-4" if stream: return Response(generate_response(model, llm, content), content_type='text/event-stream', mimetype='text/event-stream') else: response = g4f.ChatCompletion.create( model=model, provider=llm, messages=[{"role": "user", "content": content}], ) return jsonify(response) @app.route('/working_providers', methods=['GET']) def working_providers(): working_providers_list = [ provider.__name__ for provider in g4f.Provider.__providers__ if provider.working ] return jsonify({"working_providers": working_providers_list}) if __name__ == '__main__': app.run(threaded=True, host='0.0.0.0', port=3000)