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from gradio_client import Client
import os
import json
# Function to load question sets from a directory
def load_question_sets_vce(directory='questions'):
question_sets = []
for root, dirs, files in os.walk(directory):
for file in files:
if file.endswith(".json"):
question_sets.append(os.path.join( file)[:-5]) # remove the .json extension
return question_sets
exams = load_question_sets_vce('questions/')
print("question_sets:", exams)
def select_exam_vce(exam_name):
file_path = os.path.join(os.getcwd(), 'questions', f'{exam_name}.json')
try:
with open(file_path, 'r') as f:
questions = json.load(f)
print(f"Loaded {len(questions)} questions")
return questions # Ensure the questions are returned here
except FileNotFoundError:
print(f"File {file_path} not found.")
return [] # Return an empty list to indicate no questions were found
# Text-to-speech function with rate limiting, retry mechanism, and client rotation
import time
import httpx
# Text-to-speech clients
client_1 = Client("ruslanmv/text-to-speech-fast")
client_2 = Client("ruslanmv/Text-To-Speech")
client_3 = Client("ruslanmv/Text-to-Voice-Transformers")
clients = [client_1, client_2, client_3]
# Text-to-speech function with rate limiting, retry mechanism, and client rotation
def text_to_speech(text, retries=3, delay=5):
client_index = 0 # Start with the first client
for attempt in range(retries):
try:
client = clients[client_index]
print(f"Attempt {attempt + 1}")
if client_index == 0:
result = client.predict(
language="English",
repo_id="csukuangfj/vits-piper-en_US-hfc_female-medium|1 speaker",
text=text,
sid="0",
speed=0.8,
api_name="/process"
)
else:
result = client.predict(
text=text,
api_name="/predict"
)
return result
except httpx.HTTPStatusError as e:
if e.response.status_code == 429:
print(f"Rate limit exceeded. Retrying in {delay} seconds...")
client_index = (client_index + 1) % len(clients) # Rotate to the next client
time.sleep(delay)
else:
raise e
print("Max retries exceeded. Could not process the request.")
return None |