app.py

import json
import gradio as gr
from huggingface_hub import InferenceClient
import os

import requests
from rag import run_rag
"""
For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
"""
 
TOKEN = os.getenv("HF_TOKEN")
 
client = InferenceClient("HuggingFaceH4/zephyr-7b-beta" , token=TOKEN)
system_message ="You are a capable and freindly assistant."
history = []
no_change_btn = gr.Button()
enable_btn = gr.Button(interactive=True)
disable_btn = gr.Button(interactive=False)

#  ================================================================================================================================
#  ================================================================================================================================

def chat(
    state,
    message,
    # history: list[tuple[str, str]],
    max_tokens,
    temperature,
    top_p,
):
    print("Message: ", message)
    print("History: ", history)
    print("System Message: ", system_message)
    print("Max Tokens: ", max_tokens)
    print("Temperature: ", temperature)
    print("Top P: ", top_p)

    messages = [{"role": "system", "content": system_message}]

    for val in history:
        if val[0]:
            messages.append({"role": "user", "content": val[0]})
        if val[1]:
            messages.append({"role": "assistant", "content": val[1]})
    # message =run_rag(message, history)
 
    messages.append({"role": "user", "content": run_rag(message)})
    response = ""
    if state is None:
        state = gr.State()
        state.messages = [[("assistant", "")]]

    for message in client.chat_completion(
        messages,
 
        max_tokens=max_tokens,
        stream=True,
        temperature=temperature,
        top_p=top_p,
    ):
        token = message.choices[0].delta.content
        response += str(token)
        state.messages[-1][-1] = str(token) 
        yield (state, state.to_gradio_chatbot(), "", None) + (disable_btn, disable_btn, disable_btn, enable_btn, enable_btn)

    yield (state, state.to_gradio_chatbot(), "", None) + (enable_btn,) * 5
  
#  ================================================================================================================================

theme = gr.themes.Base(
    font=[gr.themes.GoogleFont('Libre Franklin'), gr.themes.GoogleFont('Public Sans'), 'system-ui', 'sans-serif'],
)
EXAMPLES = [
    [ "Tell me about the latest news in the world ?"],
    [ "Tell me about the increase in the price of Bitcoin ?"],
    [ "Tell me about the actual situation in Ukraine ?"],
    [ "Tell me about current situation in palestine ?"],
]
max_new_tokens = gr.Slider(
    minimum=1,
    maximum=2048,
    value=1024,
    step=1,
    interactive=True,
    label="Max new tokens",
)
temperature = gr.Slider(
    minimum=0.1,
    maximum=0.9,
    value=0.6,
    step=0.1,
    visible=True,
    interactive=True,
    label="Temperature",
    info="Higher values will produce more diverse outputs.",
)
top_p = gr.Slider(
    minimum=0.1,
    maximum=1,
    value=0.9,
    step=0.05,
    visible=True,
    interactive=True,
    label="Top-p (nucleus sampling)",
    info="Higher values is equivalent to sampling more low-probability tokens.",
)
textbox = gr.Textbox(show_label=False, placeholder="Enter text and press ENTER", container=False)
#  ================================================================================================================================
  
# with gr.Blocks(
#     fill_height=True,
#     css=""".gradio-container .avatar-container {height: 40px width: 40px !important;} #duplicate-button {margin: auto; color: white; background: #f1a139; border-radius: 100vh; margin-top: 2px; margin-bottom: 2px;}""",
# ) as main:
#     gr.ChatInterface(
#         chat,
#         chatbot=chatbot,
#         title="Retrieval Augmented Generation (RAG) Chatbot",
#         examples=EXAMPLES,
#         theme=theme,
#         fill_height=True,
#         additional_inputs=[
 
#             max_new_tokens,
#             temperature,
#             top_p,
#         ],
#     )
     
 

# with gr.Blocks(theme=theme, css="footer {visibility: hidden}textbox{resize:none}", title="RAG") as demo:
#     gr.TabbedInterface([main ] , tab_names=["Chatbot"]  )

# demo.launch()


def upvote_last_response(state):
    return ("",) + (disable_btn,) * 3

def downvote_last_response(state):
    return ("",) + (disable_btn,) * 3

def flag_last_response(state):
    return ("",) + (disable_btn,) * 3

def add_text(state ,textbox ):
    print("textbox: ", textbox)
    if state is None:
        state = gr.State()
        state.messages = [[("assistant", "")]]
    state.text = textbox
    history=""
    state.append_message(state.roles[0], textbox)# 
    state.append_message(state.roles[1], "")
    yield (state, None,  history) + (disable_btn, disable_btn, disable_btn, enable_btn, enable_btn)

block_css = """
#buttons button {
    min-width: min(120px,100%);
}
"""
#  ================================================================================================================================

with gr.Blocks(title="CuMo", theme=theme, css=block_css) as demo:
    state = gr.State()
    gr.Markdown("Retrieval Augmented Generation (RAG) Chatbot" )
    with gr.Row():
        with gr.Column(scale=8):
            chatbot = gr.Chatbot(
                elem_id="chatbot",
                label="Retrieval Augmented Generation (RAG) Chatbot",
                height=400,
                layout="bubble",
 
            )
            with gr.Row():
                with gr.Column(scale=8):
                    textbox.render()
                with gr.Column(scale=1, min_width=100):
                    submit_btn = gr.Button(value="Submit", variant="primary" )
            with gr.Row(elem_id="buttons") as button_row:
                upvote_btn = gr.Button(value="👍  Upvote", interactive=False)
                downvote_btn = gr.Button(value="👎  Downvote", interactive=False)
                flag_btn = gr.Button(value="⚠️  Flag", interactive=False)
                #stop_btn = gr.Button(value="⏹️  Stop Generation", interactive=False)
                regenerate_btn = gr.Button(value="🔄  Regenerate", interactive=False)
                clear_btn = gr.Button(value="🗑️  Clear", interactive=False)

            with gr.Column(scale=3):
                gr.Examples(examples=[
                [f"Tell me about the latest news in the world ?"],
                [f"Tell me about the increase in the price of Bitcoin ?"],
                [f"Tell me about the actual situation in Ukraine ?"],
                [f"Tell me about current situation in palestinian ?"],
            ],inputs=[textbox], label="Examples")
            with gr.Accordion("Parameters", open=False) as parameter_row:
                    temperature = gr.Slider(minimum=0.0, maximum=1.0, value=0.2, step=0.1, interactive=True, label="Temperature",)
                    top_p = gr.Slider(minimum=0.0, maximum=1.0, value=0.7, step=0.1, interactive=True, label="Top P",)
                    max_output_tokens = gr.Slider(minimum=0, maximum=1024, value=512, step=64, interactive=True, label="Max output tokens",)

#  ================================================================================================================================
 
    btn_list = [upvote_btn, downvote_btn, flag_btn, regenerate_btn, clear_btn]
    upvote_btn.click(
        upvote_last_response,
        [state],
        [textbox, upvote_btn, downvote_btn, flag_btn]
    )
    downvote_btn.click(
        downvote_last_response,
        [state],
        [textbox, upvote_btn, downvote_btn, flag_btn]
    )
    flag_btn.click(
        flag_last_response,
        [state],
        [textbox, upvote_btn, downvote_btn, flag_btn]
    )


    textbox.submit(
            add_text,
            [state,  textbox],
            [state, chatbot, textbox] + btn_list,
        ).then(
            chat,
            [state,  textbox,max_output_tokens,  temperature, top_p],
            [state, chatbot, textbox] + btn_list,
        )

    submit_btn.click(
        add_text,
        [state , textbox],
        [state,chatbot,  textbox] + btn_list,
    ).then(
        chat,
        [state,  textbox, max_output_tokens , temperature, top_p ],
        [state,chatbot,  textbox] + btn_list,
    )
#  ================================================================================================================================
demo.launch()
#  ================================================================================================================================