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import gradio as gr
import chatmodel as model
import interpret as shap
import visualize as viz
import markdown
def load_md(filename):
path = "./public/"+str(filename)
# credit: official python-markdown documentation (https://python-markdown.github.io/reference/)
with open(path, "r") as file:
text = file.read()
return markdown.markdown(text)
with gr.Blocks() as ui:
with gr.Row():
gr.Markdown(
"""
# Thesis Demo - AI Chat Application with XAI
### Select between tabs below for the different views.
""")
with gr.Tab("Mistral AI ChatBot"):
with gr.Row():
gr.Markdown(
"""
### ChatBot Demo
Mitral AI 7B Model fine-tuned for instruction and fully open source (see at [HGF](https://huggingface.co/mistralai/Mistral-7B-v0.1))
""")
with gr.Row():
chatbot = gr.Chatbot(layout="panel", show_copy_button=True,avatar_images=("./public/human.jpg","./public/bot.jpg"))
with gr.Row():
gr.Markdown(
"""
##### ⚠️ All Conversations are recorded for qa assurance and explanation functionality!
""")
with gr.Row():
prompt = gr.Textbox(label="Input Message")
with gr.Row():
with gr.Column(scale=1):
clear_btn = gr.ClearButton([prompt, chatbot])
with gr.Column(scale=1):
submit_btn = gr.Button("Submit")
submit_btn.click(model.chat, [prompt, chatbot], [prompt, chatbot])
prompt.submit(model.chat, [prompt, chatbot], [prompt, chatbot])
with gr.Tab("Explanations"):
with gr.Row():
gr.Markdown(
"""
### Get Explanations for
SHAP Visualization Dashboard adopted from [shapash](https://github.com/MAIF/shapash)
""")
with gr.Tab("SHAP Dashboard"):
with gr.Row():
gr.Markdown(
"""
### SHAP Dashboard
SHAP Visualization Dashboard adopted from [shapash](https://github.com/MAIF/shapash)
""")
with gr.Tab("Visualize Dashboard"):
with gr.Row():
gr.Markdown(
"""
### Visualization Dashboard
Visualization Dashboard adopted from [BERTViz](https://github.com/jessevig/bertviz)
""")
with gr.Tab("Mitral Model Overview"):
with gr.Row():
gr.Markdown(
"""
### Mistral 7B Model & Data Overview for Transparency
Adopted from official [model paper](https://arxiv.org/abs/2310.06825) by Mistral AI
""")
with gr.Row():
with gr.Accordion("Credits, Data Protection and License", open=False):
gr.Markdown(value=load_md("credits_dataprotection_license.md"))
if __name__ == "__main__":
ui.launch(debug=True) |