import gradio as gr
import os
from openai import OpenAI
import torch
from transformers import AutoTokenizer, AutoModelForCausalLM

# Set your API keys as environment variables or replace os.getenv with your actual keys
DEEPSEEK_API_KEY = os.getenv("DEEPSEEK_API_KEY")
OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")

# Initialize OpenAI clients
openai_client = OpenAI(api_key=OPENAI_API_KEY)
deepseek_client = OpenAI(api_key=DEEPSEEK_API_KEY, base_url="https://api.deepseek.com")

def generate_response(model_provider, prompt, temperature, top_p, max_tokens, repetition_penalty):
    if model_provider == "DeepSeek":
        try:
            response = deepseek_client.chat.completions.create(
                model="deepseek-chat",  # or "deepseek-reasoner" for R1 model
                messages=[{"role": "user", "content": prompt}],
                temperature=temperature,
                top_p=top_p,
                max_tokens=max_tokens,
                presence_penalty=repetition_penalty,
                stream=False
            )
            return response.choices[0].message.content.strip()
        except Exception as e:
            return f"DeepSeek API Error: {str(e)}"
    elif model_provider == "OpenAI":
        try:
            response = openai_client.chat.completions.create(
                model="gpt-3.5-turbo",  # or another model of your choice
                messages=[{"role": "user", "content": prompt}],
                temperature=temperature,
                top_p=top_p,
                max_tokens=max_tokens,
                presence_penalty=repetition_penalty,
                stream=False
            )
            return response.choices[0].message.content.strip()
        except Exception as e:
            return f"OpenAI API Error: {str(e)}"
    else:
        return "Invalid model provider selected."

with gr.Blocks() as demo:
    gr.Markdown("## 🔍 LLM Chat Interface")
    with gr.Row():
        model_provider = gr.Dropdown(
            choices=["DeepSeek", "OpenAI"],
            value="DeepSeek",
            label="Select Model Provider"
        )
    prompt = gr.Textbox(label="Enter your prompt", lines=4, placeholder="Type your message here...")
    with gr.Accordion("Advanced Settings", open=False):
        temperature = gr.Slider(0.1, 1.5, value=0.7, step=0.1, label="Temperature")
        top_p = gr.Slider(0.1, 1.0, value=0.9, step=0.05, label="Top-p")
        max_tokens = gr.Slider(32, 2048, value=512, step=32, label="Max New Tokens")
        repetition_penalty = gr.Slider(1.0, 2.0, value=1.1, step=0.1, label="Repetition Penalty")
    output = gr.Textbox(label="Response")
    submit = gr.Button("Generate")

    submit.click(
        fn=generate_response,
        inputs=[prompt, model_provider, temperature, top_p, max_tokens, repetition_penalty],
        outputs=output
    )

iface = gr.Interface(
    fn=generate_response,
    inputs=[
        gr.Dropdown(choices=["DeepSeek", "OpenAI"], value="DeepSeek", label="Model Provider"),
        gr.Textbox(label="Prompt", lines=6, placeholder="Ask something..."),
        gr.Slider(minimum=0.1, maximum=1.5, value=0.7, step=0.1, label="Temperature"),
        gr.Slider(minimum=0.1, maximum=1.0, value=0.9, step=0.05, label="Top-p"),
        gr.Slider(minimum=32, maximum=2048, value=512, step=32, label="Max New Tokens"),
        gr.Slider(minimum=1.0, maximum=2.0, value=1.1, step=0.1, label="Repetition Penalty")
    ],
    outputs="text",
    title="🧠 DeepSeek LLM Chat with Parameter Tuning",
    theme=gr.themes.Soft()
)


# demo.launch()
iface.launch()