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### 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()
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