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| import openai | |
| import gradio as gr | |
| from functools import partial | |
| ### Utility Functions | |
| def validate_api_key(api_key): | |
| """ | |
| Validates the OpenAI API key by making a test request. | |
| Returns True if valid, False otherwise. | |
| """ | |
| if not api_key: | |
| return False | |
| try: | |
| client = openai.OpenAI(api_key=api_key) | |
| # Make a minimal test request | |
| client.chat.completions.create( | |
| model="gpt-3.5-turbo", | |
| messages=[{"role": "user", "content": "test"}], | |
| max_tokens=5 | |
| ) | |
| return True | |
| except Exception: | |
| return False | |
| def call_openai_api(user_message, api_key, 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 | |
| - api_key (str): OpenAI API key | |
| - 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: | |
| client = openai.OpenAI(api_key=api_key) | |
| response = client.chat.completions.create( | |
| model=model, | |
| messages=[ | |
| {'role': 'system', 'content': "You are a helpful assistant."}, | |
| {'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 inference(user_message, api_key): | |
| """ | |
| Generates responses from multiple models for comparison. | |
| """ | |
| if not validate_api_key(api_key): | |
| return "Invalid API Key. Please enter a valid OpenAI API key.", "Invalid API Key. Please enter a valid OpenAI API key." | |
| gpt_35_response = call_openai_api(user_message, api_key, model='gpt-3.5-turbo', temperature=0.1) | |
| gpt_4_response = call_openai_api(user_message, api_key, 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("Enter your OpenAI API key and prompt to compare results from multiple OpenAI models.") | |
| # API Key input | |
| api_key = gr.Textbox( | |
| label='OpenAI API Key', | |
| placeholder="Enter your OpenAI API key...", | |
| type="password" # Masks the API key | |
| ) | |
| # 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, api_key], | |
| outputs=[gpt_35_output, gpt_4_output] | |
| ) | |
| demo.launch(share=True) | |
| if __name__ == "__main__": | |
| launch_demo() | |