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import gradio as gr
import os
from groq import Groq
from deep_translator import GoogleTranslator
# Set up Groq API client
client = Groq(
api_key=os.getenv("GROQ_API_KEY"), # Ensure you add this key to your environment variables
)
def get_highlight_summary(team, player, lang='en'):
# Generate the highlight content
highlight = f"Highlight of {player} from {team} in the latest game..."
# Call Groq API for chat completions
chat_completion = client.chat.completions.create(
messages=[
{"role": "user", "content": f"Generate a highlight summary for: {highlight}"}
],
model="llama-3.3-70b-versatile", # Specify the model to use
)
# Extract the generated summary
summary = chat_completion.choices[0].message.content.strip()
# Translate summary if necessary
if lang != 'en':
summary = GoogleTranslator(source='auto', target=lang).translate(summary)
return summary
# Create Gradio Interface
def create_gradio_interface():
with gr.Blocks() as demo:
gr.Markdown("### Personalized MLB Highlights System")
team_input = gr.Textbox(label="Enter your favorite team", placeholder="e.g., New York Yankees")
player_input = gr.Textbox(label="Enter your favorite player", placeholder="e.g., Aaron Judge")
lang_input = gr.Dropdown(choices=["en", "es", "ja"], label="Select language", value="en")
output = gr.Textbox(label="Your Highlight Summary")
submit_button = gr.Button("Generate Highlight")
submit_button.click(get_highlight_summary, inputs=[team_input, player_input, lang_input], outputs=output)
demo.launch()
# Start the Gradio interface
create_gradio_interface()
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