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import gradio as gr | |
import random | |
import time | |
import os | |
from huggingface_hub import InferenceClient | |
endpoint_url = os.getenv('url') | |
hf_token = os.getenv('hf_token') | |
# Streaming Client | |
client = InferenceClient(endpoint_url, token=hf_token) | |
gen_kwargs = dict( | |
max_new_tokens=1024, | |
top_k=50, | |
top_p=0.9, | |
temperature=0.5, | |
repetition_penalty=1.2, #1.02 | |
stop= ["\nUser:", "<|endoftext|>", "</s>"], | |
) | |
def generate_text(prompt): | |
"""Generates text using the Hugging Face Inference API.""" | |
chat_prompt = f""" | |
### Instruction: | |
You are a chatbot. Chat in Urdu. Provide answers with your best knowledge. Don't say you don't know unless you really don't | |
### Input: | |
{prompt} | |
### Response: | |
"" | |
""" | |
stream = client.text_generation(chat_prompt, stream=True, details=True, **gen_kwargs) | |
generated_text = "" | |
for r in stream: | |
if r.token.special: | |
continue | |
if r.token.text in gen_kwargs["stop"]: | |
break | |
generated_text += r.token.text | |
yield generated_text | |
iface = gr.Interface( | |
fn=generate_text, | |
inputs=gr.Textbox(lines=2, placeholder="Enter your prompt here..."), | |
outputs="text", | |
title="Urdu Chatbot", | |
description="Ask me anything in Urdu!", | |
) | |
iface.launch() | |