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import gradio as gr
from gradio_client import Client
def ask_ai_asg(message ):
clientasg = Client("wasmdashai/dash-asg")
result = clientasg.predict(
text=message,
namn_model="Group",
api_name="/t2t"
)
return result
from gradio_client import Client
def ask_ai(message ):
client = Client("wasmdashai/T2T")
result = client.predict(
text=message,
key="AIzaSyC85_3TKmiXtOpwybhSFThZdF1nGKlxU5c",
api_name="/predict"
)
return result
def ask_asgchat(txt):
txt=ask_ai(txt)
txt=ask_ai_asg(txt)
txt=ask_ai(txt)
return txt
def text_to_speech(text):
return ask_asgchat(text)
def cleanup_file(file_path):
if os.path.exists(file_path):
os.remove(file_path)
# إعداد واجهة Gradio
demo = gr.Interface(
fn=text_to_speech,
inputs=gr.Textbox(label="أدخل نصاً"),
outputs=['text'])
demo.launch()
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