# Uncomment the following line to install necessary packages
!pip install -q gradio python-dotenv -q

import gradio as gr
import os
from dotenv import load_dotenv

# Load environment variables from .env file
load_dotenv()

openai_api_key = os.getenv("OPENAI_API_KEY")

print("API keys loaded!")

def greet(name):
    return f"Hello, {name}!"

demo = gr.Interface(
    fn=greet, 
    inputs=gr.Textbox(label="Name", placeholder="Enter your name here..."), 
    outputs="text"
)

demo.launch()

def calculate(num1, num2, operation):
    if operation == "add":
        result = num1 + num2
    elif operation == "subtract":
        result = num1 - num2
    elif operation == "multiply":
        result = num1 * num2
    elif operation == "divide":
        if num2 == 0:
            return "Error", "Cannot divide by zero"
        result = num1 / num2
    return result, f"Performed {operation}."

demo = gr.Interface(
    fn=calculate,
    inputs=[
        gr.Number(label="Number 1"),
        gr.Number(label="Number 2"),
        gr.Dropdown(["add", "subtract", "multiply", "divide"], label="Operation")
    ],
    outputs=[
        gr.Textbox(label="Result"),
        gr.Textbox(label="Status")
    ],
    title="Simple Calculator",
    description="A simple calculator to demonstrate multiple inputs and outputs.",
    examples=[[5, 3, "add"], [10, 2, "divide"]]
)

demo.launch()

import numpy as np

def flip_image(img):
    return np.fliplr(img)

def greet_user(name):
    return f"How are you, {name}?"

with gr.Blocks(theme=gr.themes.Soft()) as demo:
    gr.Markdown("# Custom UI with Blocks")
    with gr.Tabs():
        with gr.TabItem("Image Flipper"):
            with gr.Row():
                image_input = gr.Image()
                image_output = gr.Image()
            image_button = gr.Button("Flip Image")
            
        with gr.TabItem("Greeter"):
            name_input = gr.Textbox(label="Name")
            greeting_output = gr.Textbox(label="Greeting")
            greet_button = gr.Button("Greet")

    # Define interactions
    image_button.click(fn=flip_image, inputs=image_input, outputs=image_output)
    greet_button.click(fn=greet_user, inputs=name_input, outputs=greeting_output)

demo.launch()

import openai

def openai_chatbot(message, history):
    messages = []
    # Convert history to OpenAI chat format
    for user, assistant in history:
        messages.append({"role": "user", "content": user})
        messages.append({"role": "assistant", "content": assistant})
    messages.append({"role": "user", "content": message})
    try:
        client = openai.OpenAI(api_key=openai_api_key)
        response = client.chat.completions.create(
            model="gpt-4o-mini",
            messages=messages,
            stream=True
        )
        partial = ""
        for chunk in response:
            delta = chunk.choices[0].delta.content or ""
            partial += delta
            yield partial
    except Exception as e:
        yield f"[Error] {str(e)}"

demo = gr.ChatInterface(
    fn=openai_chatbot,
    title="OpenAI GPT-4o-mini Chatbot",
    description="A chatbot powered by OpenAI's GPT-4o-mini model.",
    examples=["Hello!", "What is Gradio?", "Tell me a joke."]
)

demo.launch()

# This is a non-blocking cell to show the syntax.
# To run it, you would call demo.launch(share=True)
# For example:
# 
# def hello(name):
#    return f"Hi {name}!"
# 
# demo = gr.Interface(fn=hello, inputs="text", outputs="text")
# demo.launch(share=True) # This will generate a public URL like https://....gradio.live