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import gradio as gr | |
from groq import Groq | |
import os | |
from dotenv import load_dotenv | |
load_dotenv() | |
# Initialize the Groq client | |
client = Groq(api_key=os.getenv("API_KEY")) | |
# Synchronous function to handle responses | |
def generate_response(prompt, history, temperature=0.5, max_tokens=1024, top_p=1.0): | |
""" | |
Generates a response synchronously using Groq client and returns the output. | |
""" | |
try: | |
# Format the conversation history | |
messages = [{"role": "system", "content": "You are a helpful assistant."}] | |
for user_input, bot_response in history: | |
messages.append({"role": "user", "content": user_input}) | |
messages.append({"role": "assistant", "content": bot_response}) | |
messages.append({"role": "user", "content": prompt}) | |
# Call the Groq API for response | |
stream = client.chat.completions.create( | |
messages=messages, | |
model="llama3-8b-8192", | |
temperature=temperature, | |
max_tokens=max_tokens, | |
top_p=top_p, | |
stream=True, | |
) | |
# Collect the output from the stream | |
output = "" | |
for chunk in stream: | |
output += str(chunk.choices[0].delta.content) | |
return output | |
except Exception as e: | |
return f"Error: {str(e)}" | |
# Slider inputs for optional parameters | |
additional_inputs = [ | |
gr.Slider(label="Temperature", value=0.5, minimum=0.0, maximum=1.0, step=0.05), | |
gr.Slider(label="Max Tokens", value=1024, minimum=1, maximum=2048, step=64), | |
gr.Slider(label="Top-p", value=1.0, minimum=0.0, maximum=1.0, step=0.05), | |
] | |
# Define the Gradio interface | |
interface = gr.ChatInterface( | |
fn=generate_response, | |
chatbot=gr.Chatbot(show_label=False), | |
additional_inputs=additional_inputs, | |
title="Sync APX Copilot Chatbot 🦜", | |
description="An AI chatbot powered by Groq for synchronous responses.", | |
) | |
# Launch the Gradio app | |
interface.launch(show_api=False, share=True) | |