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import requests | |
import json | |
import os | |
from typing import List, Dict, Optional | |
import gradio as gr | |
GradientJResponse = Dict[str,str] | |
ChatHistory = List[Dict[str,str]] | |
def gradientj_api_call( | |
scene:str="", | |
chat_history:Optional[ChatHistory]=None | |
) -> GradientJResponse: | |
if chat_history is None: | |
chat_history = [] | |
url = "https://gpt.gradientj.com/api/v0/deploy/inference" | |
headers = { | |
"Content-Type": "application/json", | |
"x-api-key": os.environ["YOUR_GJ_API_KEY"] | |
} | |
data = { | |
"model": os.environ["model_id"], | |
"params": { | |
"scene": scene | |
}, | |
"chat_history": chat_history | |
} | |
response = requests.post(url, headers=headers, data=json.dumps(data)) | |
if response.status_code == 200: | |
return response.json()['result'] | |
else: | |
error = response.text | |
return error | |
demo = gr.Interface( | |
fn=gradientj_api_call, | |
inputs=["text"], | |
outputs=["text"], | |
examples= | |
[[ | |
"""SCENE 20 | |
EXT.ROAD WARANGAL | |
Highway mida car velthundi | |
Warangal board kanipistadi | |
SETHUMURTHY | |
(Voice) | |
Bajji ichina information tho | |
mundhuki vellalem..""" | |
]], | |
title="Tinglish (Telugu in Latin) to English Translation", | |
description="Description ah? Bokka?") | |
demo.launch() | |