app.py

from app.logger_config import (
    logger as logging,
    DEBUG
) 
import numpy as np
import gradio as gr
from fastrtc.webrtc import WebRTC
from fastrtc.utils import AdditionalOutputs
from pydub import AudioSegment
from gradio.utils import get_space
from app.supported_languages import (
    SUPPORTED_LANGS_MAP,
)
from app.ui_utils import (
    EXAMPLE_CONFIGS,
    apply_preset_if_example,
    reset_to_defaults,
    summarize_config,
    handle_additional_outputs,
    get_custom_theme,
    on_file_load,
    start_task_asr_ast,
    stop_task_fn
)
from app.utils import (
    READ_SIZE,
    generate_coturn_config,
    read_and_stream_audio,
    stop_streaming,
    raise_error
)
from app.session_utils import (
    on_load,
    on_unload,
    get_active_session_hashes,
    reset_all_active_sessions,
)

import spaces
# --------------------------------------------------------
# Initialization
# --------------------------------------------------------
reset_all_active_sessions()

theme,css_style = get_custom_theme()


with gr.Blocks(theme=theme, css=css_style) as demo:
    session_hash_code = gr.State()
    with gr.Accordion("DEGUG PANEL", open=False, visible=DEBUG):
        session_hash_code_box = gr.Textbox(label="Session ID", interactive=False, visible=DEBUG)
        with gr.Accordion("📊 Active Sessions Hash", open=True ,visible=DEBUG):
            sessions_table = gr.DataFrame(
                headers=["session_hash_code", "file", "start_time", "status"],
                interactive=False,
                wrap=True,
                max_height=200,
            )
            gr.Timer(3.0).tick(fn=get_active_session_hashes, outputs=sessions_table)

    demo.load(fn=on_load, inputs=None, outputs=[session_hash_code, session_hash_code_box])
    demo.unload(fn=on_unload)
    active_filepath = gr.State(value=next(iter(EXAMPLE_CONFIGS)))

    with gr.Walkthrough(selected=0) as walkthrough:
        # === STEP 1 ===
        with gr.Step("Audio", id=0) as audio_source_step:
            gr.Markdown(
                """
                ### Step 1: Upload or Record an Audio File
                You can upload an existing file or record directly from your microphone.  
                Accepted formats: **.wav**, **.mp3**, **.flac**  
                Maximum length recommended: **60 seconds**
                """
            )

            with gr.Group():
                with gr.Column():
                    main_audio = gr.Audio(
                        label="Audio Input",
                        sources=["upload", "microphone"],
                        type="filepath",
                        interactive=True
                    )

                    with gr.Accordion("Need a quick test? Try one of the sample audios below", open=True):
                        examples = gr.Examples(
                            examples=list(EXAMPLE_CONFIGS.keys()),
                            inputs=main_audio,
                            label=None,
                            examples_per_page=3
                        )
                        gr.Markdown(
                            """
                            🔹 **english_meeting.wav** – Short business meeting in English  
                            🔹 **french_news.wav** – Excerpt from a French radio broadcast  
                            🔹 **spanish_podcast.wav** – Segment from a Spanish-language podcast  
                            """
                        )

            go_to_config = gr.Button("Go to Configuration", visible=False)
            ui_components_oload_audio = [active_filepath, go_to_config]
            main_audio.change(fn=on_file_load, inputs=[main_audio], outputs=ui_components_oload_audio)

            go_to_config.click(lambda: gr.Walkthrough(selected=1), outputs=walkthrough)
            


        # === STEP 2 ===
        with gr.Step("Configuration", id=1)as config_step: 
            gr.Markdown("### Step 3: Configure the Task")
            with gr.Group():
                with gr.Row():
                    task_type = gr.Radio(["Transcription", "Translation"], value="Transcription", label="Task Type")
                with gr.Row():
                    lang_source = gr.Dropdown(list(SUPPORTED_LANGS_MAP.keys()), value="French", label="Source Language")
                    lang_target = gr.Dropdown(list(SUPPORTED_LANGS_MAP.keys()), value="English", label="Target Language", visible=False)
            with gr.Accordion("Advanced Configuration", open=False):
                with gr.Group():
                    with gr.Row():
                        gr.Markdown("##### Chunks ")
                    with gr.Row():
                        left_context_secs = gr.Slider(value=20.0, label="left_context_secs",info="Streaming chunk duration in seconds (left context)", minimum=1.0, maximum=60.0, step=1.0, show_reset_button=False)
                        chunk_secs = gr.Slider(value=1.0, label="chunk_secs", info="Streaming chunk duration in seconds (chunk)", minimum=0.1, maximum=5.0, step=0.1, show_reset_button=False)
                        right_context_secs = gr.Slider(value=0.5, label="right_context_secs", info="Streaming chunk duration in seconds (right context)", minimum=0.1, maximum=10.0, step=0.1, show_reset_button=False)
                gr.Markdown("---")
                with gr.Group():
                    with gr.Row():
                        gr.Markdown("##### Decoding ")
                    with gr.Row():
                        streaming_policy = gr.Dropdown(["waitk", "alignatt"], value="alignatt", label="streaming_policy",  elem_classes="full-width",
                                                           info="“Wait-k: Higher accuracy, requires larger left context, higher latency” \n”AlignAtt: Lower latency, suitable for production, predicts multiple tokens per chunk”")
                
                    with gr.Row():
                        alignatt_thr = gr.Number(value=8, label="alignatt_thr", info="Cross-attention threshold for AlignAtt policy (default: 8), alignatt only",  precision=0)
                        waitk_lagging = gr.Number(value=2, label="waitk_lagging", info="Number of chunks to wait in the beginning (default: 2), works for both policies",  precision=0)
                    with gr.Row():
                        exclude_sink_frames = gr.Number(value=8, label="exclude_sink_frames", info="Number of frames to exclude from the xatt scores calculation (default: 8), alignatt only", precision=0)
                        xatt_scores_layer = gr.Number(value=-2, label="xatt_scores_layer", info="Layer to get cross-attention (xatt) scores from (default: -2), alignatt only", precision=0)
                    with gr.Row():
                        hallucinations_detector = gr.Checkbox(value=True, label="hallucinations_detector" , info="Detect hallucinations in the predicted tokens (default: True), works for both policies" )
            with gr.Row():
                auto_apply_presets = gr.Checkbox(value=True, label="Auto-apply presets for sample audios")
                reset_btn = gr.Button("Reset to defaults")
            with gr.Accordion("Configuration Summary", open=False):
                summary_box = gr.Textbox(lines=15, interactive=False,show_label=False)

            # --- Events ---
            task_type.change(
                fn=lambda t: gr.update(visible=(t == "Translation")),
                inputs=task_type,
                outputs=lang_target,
                queue=False
            )

            inputs_list = [
                task_type, lang_source, lang_target,
                chunk_secs, left_context_secs, right_context_secs,
                streaming_policy, alignatt_thr, waitk_lagging,
                exclude_sink_frames, xatt_scores_layer, hallucinations_detector
            ]
            for inp in inputs_list:
                inp.change(
                    fn=summarize_config,
                    inputs=inputs_list,
                    outputs=summary_box,
                    queue=False
                )

            # Apply preset or not
            main_audio.change(
                fn=apply_preset_if_example,
                inputs=[main_audio, auto_apply_presets],
                outputs=[
                    task_type, lang_source, lang_target,
                    chunk_secs, left_context_secs, right_context_secs,
                    streaming_policy, alignatt_thr, waitk_lagging,
                    exclude_sink_frames, xatt_scores_layer, hallucinations_detector,
                    summary_box
                ],
                queue=False
            )

            # Reset defaults
            reset_btn.click(
                fn=reset_to_defaults,
                inputs=None,
                outputs=[
                    task_type, lang_source, lang_target,
                    chunk_secs, left_context_secs, right_context_secs,
                    streaming_policy, alignatt_thr, waitk_lagging,
                    exclude_sink_frames, xatt_scores_layer, hallucinations_detector,
                    summary_box
                ],
                queue=False
            )

            go_to_task = gr.Button("Go to Task")
            go_to_task.click(lambda: gr.Walkthrough(selected=2), outputs=walkthrough)

        # === STEP 3 ===
        with gr.Step("Task", id=2) as task_step:
                with gr.Row():
                    gr.Markdown("## Step 4: Start Stream Task")
                with gr.Group():
                    with gr.Column():
                        webrtc_stream = WebRTC(
                            label="Live Stream",
                            mode="receive",
                            modality="audio",
                            rtc_configuration=generate_coturn_config(),
                            visible=True,
                            inputs=main_audio,
                            icon= "https://cdn-icons-png.flaticon.com/128/18429/18429788.png",
                            pulse_color= "#df7a7a",
                            icon_radius= "10px",
                            icon_button_color= "rgb(255, 255, 255)",
                            height=150,
                            show_label=False
                        )

                        status_slider = gr.Slider(
                            0, 100,
                            value=0,
                            label="Streaming Progress %",
                            show_label=True,
                            interactive=False,
                            visible=False,
                            show_reset_button=False
                        )
                start_stream_button = gr.Button("▶️ Start Streaming", variant="primary")
                stop_stream_button = gr.Button("⏹️ Stop Streaming", visible=False,variant="stop")
     
                webrtc_stream.stream(
                    fn=read_and_stream_audio,
                    inputs=[active_filepath, session_hash_code,gr.State(READ_SIZE)],
                    outputs=[webrtc_stream],
                    trigger=start_stream_button.click,
                    concurrency_id="audio_stream",
                    concurrency_limit=10,
                )
                status_message_stream = gr.Markdown("", elem_id="status-message-stream", visible=False)

                with gr.Row(): 
                    gr.Markdown("---")
                with gr.Row():
                    gr.Markdown("##### Transcription / Translation Result")
                with gr.Row():
                    task_output = gr.Textbox(
                        label="Transcription / Translation Result",
                        show_label=False,
                        lines=10,
                        max_lines= 10,
                        interactive=False,
                        visible=True,
                        autoscroll=True,
                        elem_id="task-output-box" 
                        )
                with gr.Row():
                    status_message_task = gr.Markdown("", elem_id="status-message-task",elem_classes=["info"], visible=False)  
                with gr.Row():
                    start_task_button = gr.Button("▶️ Start Task", visible=False, variant="primary")
                    stop_task_button = gr.Button("⏹️ Stop Task", visible=False,variant="stop")

                    stop_stream_button.click(
                            fn=stop_streaming,
                            inputs=[session_hash_code],
                        )

                    stop_task_button.click(
                        fn=stop_task_fn,
                        inputs=session_hash_code,
                        outputs=task_output
                        )
                    config_task_ui = [session_hash_code,task_type, lang_source, lang_target,
                            chunk_secs, left_context_secs, right_context_secs,
                            streaming_policy, alignatt_thr, waitk_lagging,
                            exclude_sink_frames, xatt_scores_layer, hallucinations_detector]



                    start_task_button.click(
                            fn=start_task_asr_ast,
                            inputs=[
                                session_hash_code,
                                task_type, lang_source, lang_target,
                                chunk_secs, left_context_secs, right_context_secs,
                                streaming_policy, alignatt_thr, waitk_lagging,
                                exclude_sink_frames, xatt_scores_layer, hallucinations_detector

                            ],
                            outputs=[task_output,status_message_task,start_task_button,stop_task_button,config_step]
                    )

                    ui_components = [
                        start_stream_button, stop_stream_button,start_task_button,
                        go_to_config, audio_source_step, status_slider,walkthrough,status_message_stream
                    ]

                    webrtc_stream.on_additional_outputs(
                        fn=handle_additional_outputs,
                        inputs=[webrtc_stream],
                        outputs=ui_components,
                        concurrency_id="additional_outputs_audio_stream",
                        concurrency_limit=10,
                    )



if __name__ == "__main__":
    demo.queue(max_size=10, api_open=False).launch(show_api=False,show_error=True, debug=DEBUG)