#https://python.langchain.com/docs/how_to/configure/
import gradio as gr
import os
from langchain_openai import ChatOpenAI
from langchain_core.prompts import ChatPromptTemplate

def generate_response(prompt, temperature, api_key):
    try:
        # Initialize model with given temperature
        llm = ChatOpenAI(
            model="gpt-4o-mini",  # Using 3.5-turbo as it's more reliable
            temperature=float(temperature),
            openai_api_key=api_key
        )
        
        # Create simple prompt
        template = ChatPromptTemplate.from_messages([
            ("system", "You are a creative assistant."),
            ("user", "Generate a creative description of {prompt}")
        ])
        
        # Create and run chain
        chain = template | llm
        response = chain.invoke({"prompt": prompt})
        
        return response.content
        
    except Exception as e:
        return f"Error: {str(e)}"

# Create Gradio interface
demo = gr.Interface(
    fn=generate_response,
    inputs=[
        gr.Textbox(
            label="Prompt",
            placeholder="Example: 'a blue elephant'",
            value="a blue elephant"
        ),
        gr.Slider(
            minimum=0,
            maximum=2,
            value=0.7,
            step=0.1,
            label="Temperature (0: Focused, 2: More Creative)"
        ),
        gr.Textbox(
            label="OpenAI API Key",
            type="password"
        )
    ],
    outputs=gr.Textbox(label="Generated Response", lines=5),
    title="🎨 Temperature Effect Demo",
    description="""
    Try the same prompt with different temperatures:
    - Temperature 0: More focused, consistent responses
    - Temperature 0.7: Balanced creativity
    - Temperature 2: More random, creative responses
    
    Example prompt: 'a blue elephant'
    - T=0: "A blue elephant is a fictional creature with blue-colored skin..."
    - T=0.7: "Imagine a majestic pachyderm with sapphire-tinted hide..."
    - T=2: "Dancing through cotton candy clouds, this azure giant..."
    """
)

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