File size: 1,156 Bytes
c2d3401 fba231d ea1fbb8 c2d3401 fba231d c2d3401 fba231d c2d3401 fba231d c2d3401 ea1fbb8 fba231d ea1fbb8 fba231d c2d3401 ea1fbb8 c2d3401 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 |
import requests
import time
hold_time = time.time()
API_URL = "https://cm7kxsqi3sekfih7.us-east-1.aws.endpoints.huggingface.cloud"
headers = {
"Accept" : "application/json",
"Content-Type": "application/json"
}
def query(payload):
global hold_time
response = requests.post(API_URL, headers=headers, json=payload)
if response.status_code != 200:
print('Sleeping due to API error')
if (time.time() - hold_time) > 60:
hold_time = time.time()
return None
return response.json()
def run_model(text):
global hold_time
output = query({
"inputs": text,
"parameters": {}
})
if output:
hold_time = 1
return output[0]['generated_text']
else:
return f'Model is being loaded, please try again in {int((hold_time - time.time()) + 35)} seconds.'
run_model('السلام عيكم')
import gradio as gr
examples = [
["ما ابغا أروح الإمتحان"],
["أييد أن انام ف لبيتنا"],
["Hello how are you today"]
]
def mode_run(text):
result = run_model(text)
return result
demo = gr.Interface(fn=mode_run,
inputs="text",
outputs="text",
examples=examples)
demo.launch()
|