Create app.py

app.py

@@ -0,0 +1,57 @@
+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()