Create app.py

app.py

@@ -0,0 +1,104 @@
+### Importing Libraries
+
+import os
+import openai
+import gradio as gr
+from functools import partial
+
+
+### OpenAI Setup
+
+# Use environment variables for API key
+OPENAI_API_KEY = os.getenv('OPENAI_API_KEY')
+
+# Validate API Key at runtime
+if not OPENAI_API_KEY:
+    raise ValueError("OPENAI_API_KEY is not set in the environment.")
+
+# Initialize OpenAI client
+openai.api_key = OPENAI_API_KEY
+
+# Common system prompt for models
+SYSTEM_PROMPT = "You are a helpful assistant."
+
+
+### Utility Functions
+
+def call_openai_api(user_message, model, temperature=0.1, max_tokens=1024):
+    """
+    Calls the OpenAI API and returns the response content.
+
+    Parameters:
+    - user_message (str): The input message to process.
+    - model (str): Model name (e.g., 'gpt-3.5-turbo', 'gpt-4').
+    - temperature (float): Sampling temperature for the API.
+    - max_tokens (int): Maximum number of tokens to generate.
+
+    Returns:
+    - str: The model's response content.
+    """
+    try:
+        response = openai.ChatCompletion.create(
+            model=model,
+            messages=[
+                {'role': 'system', 'content': SYSTEM_PROMPT},
+                {'role': 'user', 'content': f"#### {user_message} ####"}
+            ],
+            temperature=temperature,
+            max_tokens=max_tokens
+        )
+        return response.choices[0].message.content
+    except Exception as e:
+        return f"Error: {str(e)}"
+
+
+def summarize(user_message):
+    """
+    Summarizes a given text using GPT-3.5 Turbo.
+    """
+    return call_openai_api(user_message, model='gpt-3.5-turbo', temperature=0.1)
+
+
+def inference(user_message):
+    """
+    Generates responses from multiple models for comparison.
+    """
+    gpt_35_response = call_openai_api(user_message, model='gpt-3.5-turbo', temperature=0.1)
+    gpt_4_response = call_openai_api(user_message, model='gpt-4', temperature=0.1)
+    return gpt_35_response, gpt_4_response
+
+
+### Gradio Interface
+
+def launch_demo():
+    """
+    Launches the Gradio interface for the application.
+    """
+    with gr.Blocks() as demo:
+        gr.Markdown('<center><h1>OpenAI LLM Explorer</h1></center>')
+        gr.Markdown("Type your prompt below to compare results from multiple OpenAI models.")
+
+        # Input prompt
+        prompt = gr.Textbox(label='Prompt', lines=5, placeholder="Enter your prompt here...")
+        
+        # Outputs for each model
+        with gr.Row():
+            gpt_35_output = gr.Textbox(label='GPT-3.5-Turbo Output', lines=6)
+            gpt_4_output = gr.Textbox(label='GPT-4 Output', lines=6)
+
+        # Button for generating outputs
+        generate_btn = gr.Button("Generate", variant='primary')
+
+        # Bind inputs and outputs
+        generate_btn.click(
+            inference, 
+            inputs=[prompt], 
+            outputs=[gpt_35_output, gpt_4_output]
+        )
+
+    demo.launch(share=True)
+
+
+if __name__ == "__main__":
+    launch_demo()
+