pages.py

import os
import base64

import numpy as np
from openai import APIConnectionError
import streamlit as st
import streamlit.components.v1 as components
from streamlit_mic_recorder import mic_recorder

from utils import load_model, generate_response, bytes_to_array, start_server, NoAudioException


general_instructions = [
    "Please transcribe this speech.",
    "Please summarise this speech."
]

def audio_llm():    
    with st.sidebar:
        st.markdown("""<div class="sidebar-intro">
                    <p><strong>📌 Supported Tasks</strong>
                    <p>Automatic Speech Recognation</p>
                    <p>Speech Translation</p>
                    <p>Spoken Question Answering</p>
                    <p>Spoken Dialogue Summarization</p>
                    <p>Speech Instruction</p>
                    <p>Paralinguistics</p>
                    <br>
                    <p><strong>📎 Generation Config</strong>
                    </div>""", unsafe_allow_html=True)

        st.slider(label='Temperature', min_value=0.0, max_value=2.0, value=0.7, key='temperature')

        st.slider(label='Top P', min_value=0.0, max_value=1.0, value=1.0, key='top_p')
    
    
    if st.sidebar.button('Clear History'):
        st.session_state.update(messages=[], 
                                on_upload=False, 
                                on_record=False, 
                                on_select=False, 
                                audio_array=np.array([]))   

    if "server" not in st.session_state:
        st.session_state.server = start_server()
    
    if "client" not in st.session_state or 'model_name' not in st.session_state:
        st.session_state.client, st.session_state.model_name = load_model()

    if "audio_array" not in st.session_state:
        st.session_state.audio_base64 = ''
        st.session_state.audio_array = np.array([])
    
    if "default_instruction" not in st.session_state: 
        st.session_state.default_instruction = []

    st.markdown("<h1 style='text-align: center; color: black;'>MERaLiON-AudioLLM ChatBot 🤖</h1>", unsafe_allow_html=True)
    st.markdown(
        """This demo is based on [MERaLiON-AudioLLM](https://huggingface.co/MERaLiON/MERaLiON-AudioLLM-Whisper-SEA-LION), 
        developed by I2R, A*STAR, in collaboration with AISG, Singapore. 
        It is tailored for Singapore’s multilingual and multicultural landscape."""
    )

    col1, col2, col3 = st.columns([4, 4, 1.2])

    with col1:
        audio_samples_w_instruct = {
            '1_ASR_IMDA_PART1_ASR_v2_141' : ["Turn the spoken language into a text format.", "Please translate the content into Chinese."],   
            '7_ASR_IMDA_PART3_30_ASR_v2_2269': ["Need this talk written down, please."],
            '17_ASR_IMDA_PART6_30_ASR_v2_1413': ["Record the spoken word in text form."],
            
            '25_ST_COVOST2_ZH-CN_EN_ST_V2_4567': ["Please translate the given speech to English."],
            '26_ST_COVOST2_EN_ZH-CN_ST_V2_5422': ["Please translate the given speech to Chinese."],
            '30_SI_ALPACA-GPT4-AUDIO_SI_V2_1454': ["Please follow the instruction in the speech."],
            
            '32_SQA_CN_COLLEDGE_ENTRANCE_ENGLISH_TEST_SQA_V2_572': ["What does the man think the woman should do at 4:00."],
            '33_SQA_IMDA_PART3_30_SQA_V2_2310': ["Does Speaker2's wife cook for Speaker2 when they are at home."],
            '34_SQA_IMDA_PART3_30_SQA_V2_3621': ["Does the phrase \"#gai-gai#\" have a meaning in Chinese or Hokkien language."],
            '35_SQA_IMDA_PART3_30_SQA_V2_4062': ["What is the color of the vase mentioned in the dialogue."],
            '36_DS_IMDA_PART4_30_DS_V2_849': ["Condense the dialogue into a concise summary highlighting major topics and conclusions."],

            '39_Paralingual_IEMOCAP_ER_V2_91': ["Based on the speaker's speech patterns, what do you think they are feeling."],
            '40_Paralingual_IEMOCAP_ER_V2_567': ["Based on the speaker's speech patterns, what do you think they are feeling."],
            '42_Paralingual_IEMOCAP_GR_V2_320': ["Is it possible for you to identify whether the speaker in this recording is male or female."],
            '43_Paralingual_IEMOCAP_GR_V2_129': ["Is it possible for you to identify whether the speaker in this recording is male or female."],
            '45_Paralingual_IMDA_PART3_30_GR_V2_12312': ["So, who's speaking in the second part of the clip?", "So, who's speaking in the first part of the clip?"],
            '47_Paralingual_IMDA_PART3_30_NR_V2_10479': ["Can you guess which ethnic group this person is from based on their accent."],
            '49_Paralingual_MELD_ER_V2_676': ["What emotions do you think the speaker is expressing."],
            '50_Paralingual_MELD_ER_V2_692': ["Based on the speaker's speech patterns, what do you think they are feeling."],
            '51_Paralingual_VOXCELEB1_GR_V2_2148': ["May I know the gender of the speaker."],
            '53_Paralingual_VOXCELEB1_NR_V2_2286': ["What's the nationality identity of the speaker."],

            '55_SQA_PUBLIC_SPEECH_SG_TEST_SQA_V2_2': ["What impact would the growth of the healthcare sector have on the country's economy in terms of employment and growth."],
            '56_SQA_PUBLIC_SPEECH_SG_TEST_SQA_V2_415': ["Based on the statement, can you summarize the speaker's position on the recent controversial issues in Singapore."],
            '57_SQA_PUBLIC_SPEECH_SG_TEST_SQA_V2_460': ["How does the author respond to parents' worries about masks in schools."],
            
            '2_ASR_IMDA_PART1_ASR_v2_2258': ["Turn the spoken language into a text format.", "Please translate the content into Chinese."],
            '3_ASR_IMDA_PART1_ASR_v2_2265': ["Turn the spoken language into a text format."],

            '4_ASR_IMDA_PART2_ASR_v2_999' : ["Translate the spoken words into text format."], 
            '5_ASR_IMDA_PART2_ASR_v2_2241': ["Translate the spoken words into text format."],
            '6_ASR_IMDA_PART2_ASR_v2_3409': ["Translate the spoken words into text format."],

            '8_ASR_IMDA_PART3_30_ASR_v2_1698': ["Need this talk written down, please."],
            '9_ASR_IMDA_PART3_30_ASR_v2_2474': ["Need this talk written down, please."],

            '11_ASR_IMDA_PART4_30_ASR_v2_3771': ["Write out the dialogue as text."],
            '12_ASR_IMDA_PART4_30_ASR_v2_103' : ["Write out the dialogue as text."],
            '10_ASR_IMDA_PART4_30_ASR_v2_1527': ["Write out the dialogue as text."],
            
            '13_ASR_IMDA_PART5_30_ASR_v2_1446': ["Translate this vocal recording into a textual format."],
            '14_ASR_IMDA_PART5_30_ASR_v2_2281': ["Translate this vocal recording into a textual format."],
            '15_ASR_IMDA_PART5_30_ASR_v2_4388': ["Translate this vocal recording into a textual format."],

            '16_ASR_IMDA_PART6_30_ASR_v2_576': ["Record the spoken word in text form."],
            '18_ASR_IMDA_PART6_30_ASR_v2_2834': ["Record the spoken word in text form."],

            '19_ASR_AIShell_zh_ASR_v2_5044': ["Transform the oral presentation into a text document."],
            '20_ASR_LIBRISPEECH_CLEAN_ASR_V2_833': ["Please provide a written transcription of the speech."],

            '27_ST_COVOST2_EN_ZH-CN_ST_V2_6697': ["Please translate the given speech to Chinese."],
            '28_SI_ALPACA-GPT4-AUDIO_SI_V2_299': ["Please follow the instruction in the speech."],
            '29_SI_ALPACA-GPT4-AUDIO_SI_V2_750': ["Please follow the instruction in the speech."],
        }
        
        audio_sample_names = [audio_sample_name for audio_sample_name in audio_samples_w_instruct.keys()]
       
        st.markdown("**Select Audio From Examples:**")
       
        sample_name = st.selectbox(
            label="**Select Audio:**",
            label_visibility="collapsed",
            options=audio_sample_names,
            index=None,
            placeholder="Select an audio sample:",
            on_change=lambda: st.session_state.update(on_select=True, messages=[]),
            key='select')
       
        if sample_name and st.session_state.on_select:
            audio_bytes = open(f"audio_samples/{sample_name}.wav", "rb").read()
            st.session_state.default_instruction = audio_samples_w_instruct[sample_name]
            st.session_state.audio_base64 = base64.b64encode(audio_bytes).decode('utf-8')
            st.session_state.audio_array = bytes_to_array(audio_bytes)


    with col2:
        st.markdown("or **Upload Audio:**")

        uploaded_file = st.file_uploader(
            label="**Upload Audio:**", 
            label_visibility="collapsed",
            type=['wav', 'mp3'],
            on_change=lambda: st.session_state.update(on_upload=True, messages=[]),
            key='upload'
        )
        
        if uploaded_file and st.session_state.on_upload:
            audio_bytes = uploaded_file.read()
            st.session_state.default_instruction = general_instructions
            st.session_state.audio_base64 = base64.b64encode(audio_bytes).decode('utf-8')
            st.session_state.audio_array = bytes_to_array(audio_bytes)


    with col3:
        st.markdown("or **Record Audio:**")
        
        recording = mic_recorder(
            format="wav", 
            use_container_width=True, 
            callback=lambda: st.session_state.update(on_record=True, messages=[]),
            key='record')
        
        if recording and st.session_state.on_record:
            audio_bytes = recording["bytes"]
            st.session_state.default_instruction = general_instructions
            st.session_state.audio_base64 = base64.b64encode(audio_bytes).decode('utf-8')
            st.session_state.audio_array = bytes_to_array(audio_bytes)
    
    st.markdown(
        """
        <style>
            .st-emotion-cache-1c7y2kd {
                flex-direction: row-reverse;
                text-align: right;
            }
        </style>
        """,
        unsafe_allow_html=True,
    )

    if "prompt" not in st.session_state:
        st.session_state.prompt = ""

    if 'disprompt' not in st.session_state:
        st.session_state.disprompt = False
        
    if "messages" not in st.session_state:
        st.session_state.messages = []
    
    if st.session_state.audio_array.size:
        with st.chat_message("user"):
            st.audio(st.session_state.audio_array, format="audio/wav", sample_rate=16000)
            if st.session_state.audio_array.shape[0] / 16000 > 30.0:
                st.warning("MERaLiON-AudioLLM can only process audio for up to 30 seconds. Audio longer than that will be truncated.")
            st.session_state.update(on_upload=False, on_record=False, on_select=False)
    
            for i, inst in enumerate(st.session_state.default_instruction):
                st.button(
                    f"**Example Instruction {i+1}**: {inst}", 
                    args=(inst,),
                    disabled=st.session_state.disprompt, 
                    on_click=lambda p: st.session_state.update(disprompt=True, prompt=p)
                )

    for message in st.session_state.messages[-2:]:
        with st.chat_message(message["role"]):
            if message.get("error"):
                st.error(message["error"])
            for warning_msg in message.get("warnings", []):
                st.warning(warning_msg)
            if message.get("content"):
                st.write(message["content"])

    if prompt := st.chat_input(
        placeholder="Type Your Instruction Here", 
        disabled=st.session_state.disprompt, 
        on_submit=lambda: st.session_state.update(disprompt=True)
    ):
        st.session_state.prompt = prompt

    if st.session_state.prompt:
        with st.chat_message("user"):
            st.write(st.session_state.prompt)
        st.session_state.messages.append({"role": "user", "content": st.session_state.prompt})
    
        with st.chat_message("assistant"):
            response, error_msg, warnings = "", "", []
            with st.spinner("Thinking..."):
                try:
                    stream, warnings = generate_response(st.session_state.prompt)
                    for warning_msg in warnings:
                        st.warning(warning_msg)
                    response = st.write_stream(stream)
                except NoAudioException:
                    error_msg = "Please specify audio first!"
                except APIConnectionError:
                    error_msg = "Internet connection seems to be down. Please contact the administrator to restart the space."
                except Exception as e:
                    error_msg = f"Caught Exception: {repr(e)}. Please contact the administrator."
        st.session_state.messages.append({
            "role": "assistant", 
            "error": error_msg,
            "warnings": warnings, 
            "content": response
        })

        st.session_state.update(disprompt=False, prompt="")
        st.rerun()