Update app.py

app.py

@@ -2,4 +2,33 @@ import gradio as gr
 import os
 from openai import OpenAI
 OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
-openai_client = OpenAI(api_key="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")
+openai_client = OpenAI(api_key=OPENAI_API_KEY)
+def generate_response(prompt, temperature, top_p, max_tokens, repetition_penalty):
+    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)}"
+iface = gr.Interface(
+    fn=generate_response,
+    inputs=[
+        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()