Chat_Flash / app.py
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import gradio as gr
from huggingface_hub import InferenceClient
client = InferenceClient("google/gemma-1.1-2b-it")
system_instructions = "[SYSTEM] Your task is to Answer the question. Keep conversation very short, clear and concise. The expectation is that you will avoid introductions and start answering the query directly, Only answer the question asked by user, Do not say unnecessary things.[QUESTION]"
def models(message):
messages.append({"role": "user", "content": f"[SYSTEM] You are REAL TIME QnA AI who answer question asked by uer in short and concise [USER] {message}"})
response = ""
for message in client.chat_completion(
messages,
max_tokens=200,
stream=True
):
token = message.choices[0].delta.content
response += token
yield response
description="# Chat GO"
demo = gr.Interface(description=description,fn=models, inputs=["text"], outputs="text", live=True, batch=True, max_batch_size=10000)
demo.queue(max_size=300000)
demo.launch()