app.py

import gradio as gr

from utils import *
from chains.openai_model import OpenAIModel
from config import SEVER, PORT, DEBUG, DEPLOYMENT_ID, SAVE_DIR
from vector_db import delete_all, delete_file, handle_upload_file, update_file

# Get and load new model
def get_model(llm_model_name, temperature=0., top_p=1.0):
    model = OpenAIModel(llm_model_name=llm_model_name,
                        condense_model_name=llm_model_name, temperature=temperature, top_p=top_p)
    return model


def create_new_model():
    return get_model(llm_model_name=DEPLOYMENT_ID)

def update_database(files_src):
    message = handle_upload_file(files_src)
    saved_file = os.listdir(SAVE_DIR)
    return gr.update(choices=saved_file), message

# Gradio app
title = """<h1 align="left" style="min-width:200px; margin-top:6px; white-space: nowrap;">Docs FPT 🤖</h1>"""
with gr.Blocks() as demo:
    user_name = gr.State("")
    history = gr.State([])
    current_model = gr.State(create_new_model)

    with gr.Row():
        with gr.Column(scale=1):
            gr.HTML(title)
            status_text = ""
            status_display = gr.Markdown(status_text, elem_id="status_display")

    with gr.Row().style(equal_height=True):
        with gr.Column(scale=5):
            with gr.Row():
                chatbot = gr.Chatbot([], elem_id="chatbot").style(height="100%")
            with gr.Row():
                with gr.Column(min_width=225, scale=12):
                    user_input = gr.Textbox(
                        show_label=False, placeholder="Enter here"
                    ).style(container=False)
                    # ask_examples_hidden = gr.Textbox(elem_id="hidden-message")
                    examples_questions = gr.Examples(
                        [
                            "Bagaimana cara saya memohon sewa gerai?",
                            "Bagaimana cara saya pergi dari Komtar ke Pengkalan Weld?",
                            "Bagaimana cara saya boleh kemaskini Alamat Surat Menyurat Cukai Taksiran",
                            "What is event's permit at Penang?",
                            "How to apply car parking at Penang?",
                            "Where can I request for my event’s permit in Penang?"
                        ],
                        [user_input],
                        examples_per_page=6,
                        )
                with gr.Column(min_width=42, scale=1):
                    submitBtn = gr.Button("Send", variant="primary")
            with gr.Row():
                emptyBtn = gr.Button(
                    "🧹 New conversation", elem_id="empty_btn")
                retryBtn = gr.Button("🔄 Retry")
                rec = gr.Button("⏺️Record")
                record_audio = gr.inputs.Audio(source="microphone", type="filepath")
            with gr.Row():
                gr.Markdown(
                    """
                    ## 💻 Key Feature
                    - Chat with an AI chatbot powered by OpenAI's chat API, using the **content of your research document**.
                    - Get **semantic search** answers from your document using **vector databases**.
                    - Perform a **Google search** within the app
                    - **Verify sources** for all generated results.
                    - Support converting **speech to text** for easy input.
                    ### Pine cone
                    Pinecone makes it easy to provide long-term memory for high-performance AI applications. 
                    It's a managed, cloud-native vector database with a simple API and no infrastructure hassles. Pinecone serves fresh, filtered query results with low latency at the scale of billions of vectors.
                    https://www.pinecone.io/blog/azure/
                    ### Azure OpenAI Service
                    https://learn.microsoft.com/en-us/legal/cognitive-services/openai/data-privacy
                    ## 📧 Contact 
                    This tool has been developed by the R&D lab at **QAI** (FPT Software, Ha Noi, Viet Nam)
                    If you have any questions or feature requests, please feel free to reach us out at <b>[email protected]</b>.
                    """
                )

        with gr.Column(min_width=50, scale=1.5):
            with gr.Tab(label="ChatGPT"):
                # gr.Markdown(f'<p style="text-align:center">Azure OpenAI Service:<a '
                #             f'href="https://learn.microsoft.com/en-us/legal/cognitive-services/openai/data-privacy">here</a></p>')
                index_files = gr.Files(label="Files", type="file", multiple=True)
                use_websearch = gr.Checkbox(label="Google search", value=False, elem_classes="switch_checkbox")
                custom_websearch = gr.Checkbox(label="Custom web search", value=False, elem_classes="switch_checkbox")

            with gr.Tab(label="Configuration"):
                gr.Markdown(
                    "⚠️Be careful to change ⚠️\n\nIf you can't use it, please restore the default settings")
                with gr.Accordion("Parameter", open=False):
                    temperature_slider = gr.Slider(
                        minimum=-0,
                        maximum=1.0,
                        value=0.0,
                        step=0.1,
                        interactive=True,
                        label="Temperature",
                    )
                    top_p_slider = gr.Slider(
                        minimum=-0,
                        maximum=1.0,
                        value=1.0,
                        step=0.1,
                        interactive=True,
                        label="Top_p",
                    )
                user_identifier = gr.Textbox(
                    show_label=True,
                    placeholder="Enter here",
                    label="User name",
                    value=user_name.value,
                    lines=1,
                )
                loadHistoryBtn = gr.Button("💾 Load History")
            with gr.Tab(label="Knowledge DB"):
                all_files = gr.Dropdown(
                label="All available files:", multiselect=True, choices=os.listdir(SAVE_DIR), interactive=True
                )
                with gr.Column():
                    delete_btn = gr.Button("🗑️ Delete")
                with gr.Column():
                    delete_all_btn = gr.Button("🗑️ Delete all")
                update_btn = gr.Button("🗑️ Update DB")

    index_files.change(update_database, [index_files], [all_files, status_display])
    delete_all_btn.click(delete_all, None, [all_files, status_display, index_files])
    delete_btn.click(delete_file, [all_files], [all_files, status_display, index_files])
    update_btn.click(update_file, None, [status_display])
    
    emptyBtn.click(
        reset,
        inputs=[current_model],
        outputs=[chatbot],
        show_progress=True,
    )

    retryBtn.click(retry, [chatbot, current_model, use_websearch, custom_websearch], [chatbot])


    loadHistoryBtn.click(load_chat_history, [current_model], [chatbot])

    rec.click(transcribe, [current_model, record_audio], [user_input])

    user_identifier.change(set_user_indentifier, [current_model, user_identifier], None)

    user_input.submit(predict, [chatbot, current_model, user_input, use_websearch, custom_websearch], [chatbot, status_display], show_progress=True)
    user_input.submit(lambda: "", None, user_input)
    submitBtn.click(predict, [chatbot, current_model, user_input, use_websearch, custom_websearch], [chatbot, status_display], show_progress=True)
    submitBtn.click(lambda: "", None, user_input)
    demo.queue(concurrency_count=10).launch(
        server_name=SEVER, server_port=PORT, debug=DEBUG)