import gradio as gr
import google.generativeai as genai
import os

# Set up Gemini API key (use environment variable on Hugging Face)
API_KEY = os.getenv("GEMINI_API_KEY")  # Set this in Hugging Face secrets
genai.configure(api_key=API_KEY)

# Use Gemini 1.5 Flash (free-tier accessible)
model = genai.GenerativeModel("gemini-1.5-flash")

def chatbot(prompt, history=[]):
    """Generates a chatbot response using the free-tier Gemini API."""
    try:
        response = model.generate_content(prompt)
        return response.text
    except Exception as e:
        return f"Error: {e}"

def vqa(image, question):
    """Performs Visual Question Answering (VQA) using the Gemini API."""
    try:
        response = model.generate_content([question, image])
        return response.text
    except Exception as e:
        return f"Error: {e}"

# Create Gradio interfaces
chat_interface = gr.ChatInterface(
    chatbot,
    title="Free Gemini API Chatbot",
    description="Ae chatbot powered by the free-tier Google Gemini API."
)

vqa_interface = gr.Interface(
    fn=vqa,
    inputs=[gr.Image(type="filepath"), gr.Textbox(label="Question")],
    outputs=gr.Textbox(label="Answer"),
    title="Visual Question Answering (VQA)",
    description="Upload an image and ask a question about it."
)

# Combine interfaces
with gr.Blocks() as demo:
    gr.TabbedInterface([chat_interface, vqa_interface], ["Chatbot", "VQA"])

if __name__ == "__main__":
    demo.launch()