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File size: 2,456 Bytes
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import gradio as gr
from groq import Groq
import os
# Default API key for examples (replace with a dummy value or leave empty)
DEFAULT_API_KEY = os.environ.get("GROQ_API_KEY", "")
def chatbot(message, history, api_key):
# Use the provided API key, or fall back to the default for examples
api_key = api_key or DEFAULT_API_KEY
if not api_key:
return "Please enter a valid Groq API key to use the chatbot."
try:
# Initialize Groq client with the 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})
# 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="...",
type="password",
value=DEFAULT_API_KEY # Pre-fill with default key if available
)
chatbot = gr.ChatInterface(
fn=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() |