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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()
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