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import requests
import os
import time
from gtts import gTTS
HF_API_KEY = os.getenv("HUGGING_FACE_API_KEY")
MISTRAL_API_KEY = os.getenv("MISTRAL_IA_API_KEY")
# Summarisation model
def query(payload):
headers = {"Authorization": f"Bearer {HF_API_KEY}"}
API_URL_SUMMARISATION_MODEL = "https://api-inference.huggingface.co/models/facebook/bart-large-cnn"
response = requests.post(API_URL_SUMMARISATION_MODEL, headers=headers, json=payload)
return response.json()[0]['summary_text']
def summarize_text(text):
payload = {"inputs": text}
return query(payload)
#Text generation model
def get_diagnosis(prediction, confidence):
labels = ["glioma", "meningioma", "notumor", "pituitary"]
result = labels[prediction]
prompt = f'Tu es un médecin qui doit annoncer à un patient le type de tumeur qu\'il a. Le type de tumeur prédit est "{result}" avec une confiance de {confidence}. Veuillez fournir un diagnostic concis, précis et des conseils.'
return prompt
def generate_text(input_text, max_retries=3):
MISTRAL_API_URL = "https://api.mistral.ai/v1/chat/completions"
headers = {
"Authorization": f"Bearer {MISTRAL_API_KEY}",
"Content-Type": "application/json"
}
payload = {
"model": "mistral-small-latest",
"messages": [{"role": "user", "content": input_text}]
}
for _ in range(max_retries):
response = requests.post(MISTRAL_API_URL, headers=headers, json=payload)
if response.status_code == 200:
return response.json()['choices'][0]['message']['content']
else:
time.sleep(5)
return "Failed to generate text after multiple attempts"
# Translation model
def translate_fr_to_es(input_text, max_retries=5):
API_URL = "https://api-inference.huggingface.co/models/Helsinki-NLP/opus-mt-fr-es"
headers = {"Authorization": f"Bearer {HF_API_KEY}"}
payload = {"inputs": input_text}
for _ in range(max_retries):
response = requests.post(API_URL, headers=headers, json=payload)
if response.status_code == 200:
return response.json()[0]['translation_text']
else:
time.sleep(5)
return "Une erreur s'est produite veuillez reessayer plus tard."
# Audio to text model
def text_to_speech(input_text):
outputh_path = "text_to_speech.mp3"
tts = gTTS(text=input_text, lang="es")
tts.save(outputh_path)
return outputh_path |