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import os |
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import gradio as gr |
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import openai |
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llm_api_options = ["OpenAI API","Azure OpenAI API","Google PaLM API", "Llama 2"] |
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TEST_MESSAGE = "My favorite TV shows are The Mentalist, The Blacklist, Designated Survivor, and Unforgettable. What are ten series that I should watch next?" |
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openai_models = ["gpt-4", "gpt-4-0613", "gpt-4-32k", "gpt-4-32k-0613", "gpt-3.5-turbo", |
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"gpt-3.5-turbo-0613", "gpt-3.5-turbo-16k", "gpt-3.5-turbo-16k-0613", "text-davinci-003", |
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"text-davinci-002", "text-curie-001", "text-babbage-001", "text-ada-001"] |
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def test_handler(optionSelection, prompt: str = "Write an introductory paragraph to explain Generative AI to the reader of this content."): |
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match optionSelection: |
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case "OpenAI API": |
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try: |
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model = "gpt-4" |
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system_prompt: str = "Explain in detail to help student understand the concept.", |
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assistant_prompt: str = None, |
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messages = [ |
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{"role": "user", "content": f"{prompt}"}, |
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{"role": "system", "content": f"{system_prompt}"}, |
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{"role": "assistant", "content": f"{assistant_prompt}"} |
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] |
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openai.api_key = os.getenv("OPENAI_API_KEY") |
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openai.api_version = '2020-11-07' |
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completion = openai.ChatCompletion.create( |
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model = model, |
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messages = messages, |
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temperature = 0.7 |
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) |
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response = completion["choices"][0]["message"].content |
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return "", response |
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except openai.error.ServiceUnavailableError: |
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print(f"Exception Name: {type(exception).__name__}") |
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print(exception) |
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return f" {optionSelection} test_handler Error - {exception}", "" |
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case "Azure OpenAI API": |
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return "", "" |
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case "Google PaLM API": |
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return "", "" |
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case "Llama 2": |
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return "", "" |
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case _: |
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if optionSelection not in llm_api_options: |
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return ValueError("Invalid choice!"), "" |
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with gr.Blocks() as LLMDemoTabbedScreen: |
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with gr.Tab("Text-to-Text (Text Completion)"): |
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llm_options = gr.Radio(llm_api_options, label="Select one", info="Which service do you want to use?", value="OpenAI API") |
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with gr.Tab("Open AI"): |
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openai_model = gr.Dropdown(openai_models, value="gpt-4", label="Model", info="Select one, for Natural language") |
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with gr.Row(): |
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with gr.Column(): |
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test_string = gr.Textbox(label="Try String", value=TEST_MESSAGE, lines=2) |
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test_string_response = gr.Textbox(label="Response") |
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test_string_output_info = gr.Label(value="Output Info", label="Info") |
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test_button = gr.Button("Try it") |
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test_button.click( |
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fn=test_handler, |
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inputs=[llm_options, test_string], |
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outputs=[test_string_output_info, test_string_response] |
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) |
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if __name__ == "__main__": |
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LLMDemoTabbedScreen.launch() |
