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import subprocess | |
import os | |
import httpx | |
import gradio as gr | |
from groq import Groq | |
groq_api_key = os.environ('Groq_Api_key') | |
subprocess.run(["export", f"GROQ_API_KEY={groq_api_key}"], check=True) | |
def generate_response(input_text): | |
client = Groq() | |
stream = client.chat.completions.create( | |
messages=[ | |
{"role": "system", "content": "you are a helpful assistant."}, | |
{"role": "user", "content": input_text} | |
], | |
model="mixtral-8x7b-32768", | |
temperature=0.5, | |
max_tokens=1024, | |
top_p=1, | |
stop=None, | |
stream=True, | |
) | |
response = "" | |
for chunk in stream: | |
response += chunk.choices[0].delta.content | |
return response | |
# Define the Gradio UI | |
inputs = gr.Textbox(label="Enter your question") | |
outputs = gr.Textbox(label="Model Response") | |
gr.Interface( | |
fn=generate_response, | |
inputs=inputs, | |
outputs=outputs, | |
title="Language Model Assistant", | |
description="Ask questions and get responses from a language model.", | |
).launch(show_api=False, share=True) |