app.py

import gradio as gr
import os
from openai import OpenAI

OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
openai_client = OpenAI(api_key=OPENAI_API_KEY)

DEEPSEEK_API_KEY = os.getenv("DEEPSEEK_API_KEY")
deepseek_client = OpenAI(api_key=DEEPSEEK_API_KEY, base_url="https://api.deepseek.com")

def generate_response(prompt,model_provider,temperature, top_p, max_tokens, repetition_penalty):
    model_provider=model_provider,
    if model_provider=="OpenAI":
        try:
           response = openai_client.chat.completions.create(
              model="gpt-3.5-turbo",  # model="deepseek-chat"
              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)}"
    elif model_provider=="DeepSeek":
        try:
           response = openai_client.chat.completions.create(
              model="gpt-3.5-turbo",  # model="deepseek-chat"
              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)}"

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()
)

iface.launch()