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from flask import Flask, request, jsonify
from flask_cors import CORS
from utils.chatgpt_config import send_ChatGPT
from utils.modelFace import predict_face
from utils.modelText import predict_text
import os
app = Flask(__name__)
CORS(app)
# @app.route('/upload_image', methods=['POST'])
# def upload_image():
# try:
# data = request.get_json()
# base64_image = data.get('base64_image')
# if not base64_image:
# return jsonify({"error": "Missing 'base64_image' in the request"}), 400
# emotion_face=predict_face(base64_image)
# return jsonify({"message": "Image received and saved successfully!",
# "chat":send_ChatGPT(emotion_face=emotion_face)}), 200
# except Exception as e:
# return jsonify({"error": str(e)}), 400
# @app.route('/upload_text', methods=['POST'])
# def upload_text():
# try:
# # Obtener el cuerpo de la solicitud como JSON
# data = request.get_json()
# # Verificar que el campo 'text' esté presente y sea una cadena
# text = data.get('text')
# if text is None:
# return jsonify({"error": "Falta el campo 'text' en la solicitud."}), 400
# # Verificar que 'text' sea una cadena de texto
# if not isinstance(text, str):
# return jsonify({"error": "El campo 'text' debe ser una cadena de texto."}), 400
# # Verificar que 'text' no sea vacío o solo espacios
# if not text.strip():
# return jsonify({"error": "El campo 'text' no debe estar vacío."}), 400
# # Procesar el texto (reemplaza con tu lógica)
# return jsonify({
# "message": "¡Texto recibido y guardado exitosamente!",
# "chat": send_ChatGPT(emotion_text="sad") # Reemplaza con tu función real
# }), 200
# except Exception as e:
# return jsonify({"error": str(e)}), 400
@app.route('/')
def home():
return "¡Hola desde Flask!"
@app.route('/upload_info', methods=['POST'])
def upload_info():
try:
data = request.get_json()
if not data:
return jsonify({"error": "Request must be in JSON format."}), 400
base64_image = data.get('img')
text = data.get('text')
# Validar presencia de los campos requeridos
if not base64_image:
return jsonify({"error": "Missing 'img' in the request."}), 400
if text is None:
return jsonify({"error": "Missing 'text' in the request."}), 400
# Validar que 'text' sea una cadena no vacía
if not isinstance(text, str) or not text.strip():
return jsonify({"error": "'text' must be a non-empty string."}), 400
emotion_face=predict_face(base64_image)
emotion_text=predict_text(text)
# Simular la función send_ChatGPT
chat_response = send_ChatGPT(emotion_face=emotion_face,emotion_text=emotion_text) # Sustituir por la implementación real
return jsonify({
"message": "Image received and saved successfully!",
"chat": chat_response
}), 200
except Exception as e:
return jsonify({"error": f"An unexpected error occurred: {str(e)}"}), 500
if __name__ == '__main__':
app.run(debug=True) |