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import gradio as gr
from transformers import pipeline
# Load your StudyBuddyAI model
chat = pipeline("text-generation", model="redmint/studybuddy-ai", device=-1) # use -1 for CPU, 0 for GPU
# Core response function
def respond(message, history):
# Convert history into simple Q&A format
context = ""
for user, bot in history:
context += f"Question: {user}\nAnswer: {bot}\n"
# Add the latest user question
prompt = context + f"Question: {message}\nAnswer:"
# Generate response
output = chat(
prompt,
max_new_tokens=200,
temperature=0.4,
top_p=0.9,
do_sample=True,
)[0]["generated_text"]
# Extract only the part after "Answer:"
if "Answer:" in output:
response = output.split("Answer:")[-1].strip()
else:
response = output.strip()
history.append((message, response))
return history, history
# Gradio interface
with gr.Blocks() as demo:
chatbot = gr.Chatbot()
msg = gr.Textbox(label="Ask StudyBuddyAI")
msg.submit(respond, [msg, chatbot], [chatbot, chatbot])
if __name__ == "__main__":
demo.launch()
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