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| # main application file initializing the gradio based ui and calling other modules | |
| import subprocess | |
| import sys | |
| def install(package): | |
| subprocess.check_call([sys.executable, "-m", "pip", "install", "./components/testinghtml/dist/gradio_testinghtml-0.0.1-py3-none-any.whl"]) | |
| from gradio_testinghtml import testingHTML | |
| # external package imports | |
| import gradio as gr | |
| import markdown | |
| from fastapi import FastAPI | |
| # internal imports | |
| from backend.controller import interference | |
| # Global Variables | |
| app = FastAPI() | |
| # different functions to provide frontend abilities | |
| # function to load markdown files | |
| def load_md(path): | |
| # credit: official python-markdown documentation (https://python-markdown.github.io/reference/) | |
| with open(path, "r") as file: | |
| text = file.read() | |
| return markdown.markdown(text) | |
| # function to display the system prompt info | |
| def system_prompt_info(sys_prompt_txt): | |
| gr.Info(f"The system prompt was set to:\n {sys_prompt_txt}") | |
| # function to display the xai info | |
| def xai_info(xai_radio): | |
| if xai_radio != "None": | |
| gr.Info(f"The XAI was set to:\n {xai_radio}") | |
| else: | |
| gr.Info(f"No XAI method was selected.") | |
| # function to display the model info | |
| def model_info(model_radio): | |
| gr.Info(f"The model was set to:\n {model_radio}") | |
| # ui interface based on Gradio Blocks (see documentation: https://www.gradio.app/docs/interface) | |
| with gr.Blocks() as ui: | |
| # header row with markdown based text | |
| with gr.Row(): | |
| gr.Markdown( | |
| """ | |
| # Thesis Demo - AI Chat Application with XAI | |
| ### Select between tabs below for the different views. | |
| """) | |
| # ChatBot tab used to chat with the AI chatbot | |
| with gr.Tab("AI ChatBot"): | |
| with gr.Row(): | |
| gr.Markdown( | |
| """ | |
| ### ChatBot Demo | |
| Chat with the AI ChatBot using the textbox below. Manipulate the settings in the row above, including the selection of the model, the system prompt and the XAI method. | |
| """) | |
| # row with textbox to enter the system prompt, which is handed over to the model at every turn | |
| with gr.Row(equal_height=True): | |
| with gr.Column(scale=3): | |
| system_prompt = gr.Textbox(label="System Prompt",info= "Set the models system prompt, dictating how it answers.", placeholder="You are a helpful, respectful and honest assistant. Always answer as helpfully as possible, while being safe.") | |
| with gr.Column(scale=1): | |
| model = gr.Radio(["Mistral", "Llama 2"], label="Model Selection", info="Select Model to use for chat.", value="Mistral", interactive=True, show_label=True) | |
| with gr.Column(scale=1): | |
| xai = gr.Radio(["None", "SHAP", "Visualizer"], label="XAI Settings", info="XAI Functionalities to use.", value="None", interactive=True, show_label=True) | |
| # calling info functions on inputs for different settings | |
| system_prompt.submit(system_prompt_info, [system_prompt]) | |
| model.input(model_info, [model]) | |
| xai.input(xai_info, [xai]) | |
| # row with chatbot ui displaying "conversation" with the model (see documentation: https://www.gradio.app/docs/chatbot) | |
| with gr.Row(): | |
| chatbot = gr.Chatbot(layout="panel", show_copy_button=True,avatar_images=("./public/human.jpg","./public/bot.jpg")) | |
| # row with input textbox | |
| with gr.Row(): | |
| user_prompt = gr.Textbox(label="Input Message") | |
| # row with columns for buttons to submit and clear content | |
| with gr.Row(): | |
| with gr.Column(scale=1): | |
| # default clear button which clearn the given components (see documentation: https://www.gradio.app/docs/clearbutton) | |
| clear_btn = gr.ClearButton([user_prompt, chatbot]) | |
| with gr.Column(scale=1): | |
| submit_btn = gr.Button("Submit", variant="primary") | |
| # two functions performing the same action (triggered the model response), when the button is used or the textbox submit function is used (clicking enter). | |
| # hands over the information needed for the chat (prompt, history, and system prompt) and the information needed to call the right model and xai function (model, xai) | |
| # returns the prompt and history to be displayed in the chatbot ui | |
| submit_btn.click(interference, [user_prompt, chatbot, system_prompt, model, xai], [user_prompt, chatbot]) | |
| user_prompt.submit(interference, [user_prompt, chatbot, system_prompt, model, xai], [user_prompt, chatbot]) | |
| # explanations tab used to provide explanations for a specific conversation | |
| with gr.Tab("Explanations"): | |
| with gr.Row(): | |
| gr.Markdown( | |
| """ | |
| ### Get Explanations for Conversations | |
| Using your selected XAI method, you can get explanations for the conversation you had with the AI ChatBot. The explanations are based on the last message you sent to the AI ChatBot. | |
| """) | |
| with gr.Row(): | |
| gr.HTML(load_md("public/explanations.md")) | |
| with gr.Row(): | |
| with gr.Accordion("Full Size Plot of All SHAP Values", open=False): | |
| gr.Plot(label="SHAP Values Plot") | |
| # final row to show legal information - credits, data protection and link to the LICENSE on GitHub | |
| with gr.Row(): | |
| with gr.Accordion("Credits, Data Protection and License", open=False): | |
| gr.Markdown(value=load_md("public/credits_dataprotection_license.md")) | |
| # mount function for fastAPI Application | |
| app = gr.mount_gradio_app(app, ui, path="/") | |
| # launch function using uvicorn to launch the fastAPI application | |
| if __name__ == "__main__": | |
| from uvicorn import run | |
| run("main:app", port=8080, reload=True) |