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import gradio as gr
from groq import Groq
import os
def chatbot(message, history, api_key):
# Initialize Groq client with the provided API key
client = Groq(api_key=api_key)
# Prepare the messages including the conversation history
messages = [
{"role": "system", "content": "You are a helpful assistant."}
]
for human, assistant in history:
messages.append({"role": "user", "content": human})
messages.append({"role": "assistant", "content": assistant})
messages.append({"role": "user", "content": message})
try:
# Create the chat completion
completion = client.chat.completions.create(
model="llama-3.2-90b-text-preview",
messages=messages,
temperature=1,
max_tokens=1024,
top_p=1,
stream=True,
stop=None,
)
# Stream the response
partial_message = ""
for chunk in completion:
if chunk.choices[0].delta.content is not None:
partial_message += chunk.choices[0].delta.content
yield partial_message
except Exception as e:
yield f"Error: {str(e)}"
# Create the Gradio interface
with gr.Blocks(theme="soft") as iface:
gr.Markdown("# Groq LLaMA 3.2 90B Chatbot")
gr.Markdown("Chat with the LLaMA 3.2 90B model using Groq API")
with gr.Row():
api_key_input = gr.Textbox(
label="Enter your Groq API Key",
placeholder="sk-...",
type="password"
)
chatbot = gr.ChatInterface(
chatbot,
additional_inputs=[api_key_input],
examples=[
"Tell me a short story about a robot learning to paint.",
"Explain quantum computing in simple terms.",
"What are some creative ways to reduce plastic waste?",
],
retry_btn=None,
undo_btn="Delete Last",
clear_btn="Clear",
)
# Launch the interface
iface.launch() |