Update app.py

app.py

@@ -1,45 +1,89 @@
 import os
-import openai
+import json
 import gradio as gr
+from openai import OpenAI
 
-# Replace 'your_api_key_here' with your actual OpenAI API key
+# Initialize the OpenAI client
 api_token = os.getenv("oaikey")
+client = OpenAI(api_key=api_token)
 
-# Set your OpenAI API key
-openai.api_key = os.getenv(api_token)
-
-# Initialize chat history
-messages = [{"role": "system", "content": "You are a helpful assistant."}]
-
-def chatbot(user_input, other):
-    print(other)
-    # Append user input to the message history
-    messages.append({"role": "user", "content": user_input})
+def generate_response(prompt, system_prompt, temperature, top_p, seed):
+    try:
+        # Make the API call with the provided parameters
+        response = client.chat.completions.create(
+            model="gpt-4",
+            messages=[
+                {"role": "system", "content": system_prompt},
+                {"role": "user", "content": prompt}
+            ],
+            temperature=temperature,
+            top_p=top_p,
+            seed=seed
+        )
+        
+        # Extract the text response
+        text_response = response.choices[0].message.content
+        
+        # Convert the full response to a pretty-printed JSON
+        response_dict = response.model_dump()
+        json_response = json.dumps(response_dict, indent=2)
+        
+        return text_response, json_response
     
-    # Generate response using OpenAI's GPT-3.5-turbo
-    response = openai.ChatCompletion.create(
-        model="gpt-3.5-turbo",
-        messages=messages,
-        temperature=0.7,
-        max_tokens=150,
-        top_p=1,
-        frequency_penalty=0,
-        presence_penalty=0
-    )
+    except Exception as e:
+        return f"Error: {str(e)}", "{}"
+
+# Create the Gradio interface
+with gr.Blocks() as app:
+    gr.Markdown("# OpenAI API Interface")
     
-    # Extract the assistant's reply
-    assistant_reply = response.choices[0].message["content"].strip()
+    with gr.Row():
+        with gr.Column():
+            # Input components
+            prompt = gr.Textbox(label="Prompt", placeholder="Enter your prompt here...", lines=5)
+            system_prompt = gr.Textbox(
+                label="System Prompt", 
+                placeholder="You are a helpful assistant...",
+                value="You are a helpful assistant.",
+                lines=3
+            )
+            
+            with gr.Row():
+                temperature = gr.Slider(
+                    minimum=0.0, 
+                    maximum=2.0, 
+                    value=0.7, 
+                    step=0.1, 
+                    label="Temperature"
+                )
+                top_p = gr.Slider(
+                    minimum=0.0, 
+                    maximum=1.0, 
+                    value=1.0, 
+                    step=0.05, 
+                    label="Top P"
+                )
+                seed = gr.Number(
+                    label="Seed (optional)", 
+                    value=None, 
+                    precision=0
+                )
+            
+            submit_button = gr.Button("Generate Response")
     
-    # Append assistant's reply to the message history
-    messages.append({"role": "assistant", "content": assistant_reply})
+    with gr.Row():
+        with gr.Column():
+            # Output components
+            text_output = gr.Textbox(label="Generated Text", lines=8)
+            json_output = gr.Code(language="json", label="Full API Response")
     
-    return assistant_reply
-
-# Create Gradio interface
-with gr.Blocks() as demo:
-    chatbot_ui = gr.ChatInterface(fn=chatbot, title="GPT-3.5 Turbo Chatbot")
+    # Connect the input components to the function and the output components
+    submit_button.click(
+        fn=generate_response,
+        inputs=[prompt, system_prompt, temperature, top_p, seed],
+        outputs=[text_output, json_output]
+    )
 
-# Launch the Gradio app
+# Launch the app
 if __name__ == "__main__":
-    demo.launch()
-
+    app.launch()