import gradio as gr
import gspread
import shutil
import os
from datetime import datetime
from google.cloud import storage
import os
import shutil
import threading
from google.cloud import speech

# Set the environment variable for your service account JSON
os.environ["GOOGLE_APPLICATION_CREDENTIALS"] = "story_legacy_service_account.json"


# GCS Bucket Configuration
GCS_BUCKET_NAME = "userrecordings"
# Google Sheets API setup
SHEET_URL = "https://docs.google.com/spreadsheets/d/1ZlO_YQyFV6HsZH6hWIEtCw4VHxa7NXKlRULG_2Dkyao/edit"
PROJECT_CODE = "P2401"  # Hardcoded project code

def fetch_sheet_data(sheet_url):
    gc = gspread.service_account(filename="story_legacy_service_account.json")
    sh = gc.open_by_url(sheet_url)
    worksheet = sh.sheet1
    data = worksheet.get_all_records()
    return data

# Load Google Sheet data
data = fetch_sheet_data(SHEET_URL)

# Global variables to track the state
current_project = None
current_prompt_index = 0
prompts = []
recording_status = []
responses = []

# Load the project using the hardcoded project code
current_project = [row for row in data if row["Project Code"] == PROJECT_CODE]
if current_project:
    current_project = current_project[0]
    prompts = [current_project[f"Prompt{i+1}"] for i in range(4) if current_project.get(f"Prompt{i+1}")]
    recording_status = [False] * len(prompts)  # Initialize recording status for each prompt
    responses = [None] * len(prompts) 
else:
    prompts = []
custom_html=""" 
<style>
        /* Body Styles */
        .gr-container {
            font-family: Arial, sans-serif !important;
            background-color: #F5F5DC !important;
            color: #333 !important;
        }

        /* Row Styles */
        .gr-row {
            display: flex;
            justify-content: center;
            align-items: center;
            margin: 15px 0;
            padding: 10px;
            width: 100%;
        }

        /* Audio Component Styles */
        .gr-audio {
            background-color: #F5F5DC;
            padding: 10px 10px;
            border-radius: 10px;
            font-size:20px;
            color:blue;
        }

        .gr-audio button[title="Clear"] {
        display: none !important;
        }

        /* Prompt style */
        .gr-prompt {
            background-color: #F5F5DC;
            color: #00008B; /* Deep Blue */
            padding: 10px 10px;
            border-radius: 10px;
      
        }
        .gr-submit_button{
            background-color: #28a745;
            color: white;
            border: none;
            padding: 10px 20px;
            border-radius: 20px;
            font-size: 20px;
            cursor: pointer;
            margin: 5px;
        }

        /* Erase button */
        .gr-erase_button {
            background-color: #EE4B2B;
            color: white;
            border: none;
            padding: 10px 20px;
            border-radius: 20px;
            font-size: 20px;
            cursor: pointer;
            margin: 5px;
        }

        .gr-erase_button:hover {
            background-color: #A52A2A;
        }

        /* NExt button */
        .gr-next_button {
            background-color: #28a745;
            color: white;
            border: none;
            padding: 10px 20px;
            border-radius: 20px;
            font-size: 20px;
            cursor: pointer;
            margin: 5px;
        }

        .gr-next_button:hover {
            background-color: #218838;
        }

        .warning-alert  {
            font-size: 16px;
            color: black;
            margin-top: 2px;
            text-align: center;
            font-weight: bold;
            border: 1px solid #d9534f;
            padding: 10px;
            background-color: #FFED01; /* Light red background for alert */
     
        }
        .fail-alert  {
            font-size: 16px;
            color: black;
            margin-top: 2px;
            text-align: center;
            font-weight: bold;
            border: 1px solid #d9534f;
            padding: 10px;
            background-color: #FF0000; /* Light red background for alert */
        }
        .sucess-alert  {
            font-size: 16px;
            color: black;
            margin-top: 2px;
            text-align: center;
            font-weight: bold;
            border: 1px solid #d9534f;
            padding: 10px;
            background-color:#90EE90; /* Light red background for alert */
        }
        .story-legacy-heading {
                background-color: White;
                font-size: 30px;
                font-weight: bold;
                color:#00008B;
                text-align: left;
                margin-top:-10px;
                margin-bottom: 10px;
            }
        .project-code {
                background-color: White;
                font-size: 30px;
                font-weight: bold;
                color:#00008B; 
                text-align: right;
                margin-top:-10px;
                margin-bottom: 10px;
        }
        .prompt-class {
            font-weight: bold;
            color:#00008B;
            font-size: 20px;

        }
    .gr-markdown {
            position: fixed;
            width: 95%;
            z-index: 1000;
            border-radius: 5px;
            margin-top:-10px;
            margin-bottom: 20px;
        } 
    .prompt-text {
        font-size: 15px;
    }
    </style>
    """
# Function to transcribe audio files and save them locally
def transcribe_audio(local_file_path):
    """Transcribes audio data from a Google Cloud Storage bucket."""
    
    with open(local_file_path, "rb") as audio_file:
        content = audio_file.read()

    client = speech.SpeechClient()
    audio = speech.RecognitionAudio(content=content)
    config = speech.RecognitionConfig(
        encoding=speech.RecognitionConfig.AudioEncoding.LINEAR16,
        sample_rate_hertz=44100,  # Adjust if needed
        language_code="en-US",
    )
    response = client.recognize(config=config, audio=audio)
    return response.results[0].alternatives[0].transcript if response.results else "No transcription available."

# function to upload responses and generate transcripts
def upload_to_gcs_and_cleanup():
    try:
        # Initialize GCS client
        client = storage.Client(project="story-legacy-442314")
        bucket = client.bucket(GCS_BUCKET_NAME)

        # Walk through the responses directory
        for root, _, files in os.walk(f"responses/{PROJECT_CODE}"):
            for file in files:
                local_path = os.path.join(root, file)

                # Define the relative path for GCS
                relative_path = os.path.relpath(local_path, f"responses/{PROJECT_CODE}")
                gcs_path = f"{PROJECT_CODE}/responses/{relative_path}"

                # Upload the file to GCS
                blob = bucket.blob(gcs_path)
                blob.upload_from_filename(local_path)
                print(f"Uploaded {local_path} to {gcs_path}")

                # Generate the transcript
                transcript_text = transcribe_audio(local_path)

                # Save the transcript in GCS under the transcripts folder with the new structure
                transcript_relative_path = relative_path.replace("responses/", "")  # Remove "responses/" from path
                transcript_gcs_path = f"{PROJECT_CODE}/transcripts/{transcript_relative_path.replace(os.path.splitext(file)[1], '.txt')}"
                transcript_blob = bucket.blob(transcript_gcs_path)
                transcript_blob.upload_from_string(transcript_text)
                print(f"Transcript uploaded to {transcript_gcs_path}")

                # Delete the local response file
                os.remove(local_path)

        # Remove the responses directory after successful upload
        response_dir = f"responses/{PROJECT_CODE}"
        if os.path.exists(response_dir):
            shutil.rmtree(response_dir)
            print(f"Local directory {response_dir} has been deleted.")

        return True, "All responses and transcripts have been uploaded to GCS, and local files deleted."
    except Exception as e:
        print(f"Error during GCS upload: {e}")
        return False, f"Error during GCS upload: {str(e)}"

# Background task function
def async_upload_to_gcs_and_cleanup():
    success, message = upload_to_gcs_and_cleanup()
    print(message)



def submit_audio(audio_path):
    global current_prompt_index
    print(f"Received audio_path: {audio_path}")  # Debugging line to check the value

    # Check if the response has already been submitted
    if recording_status[current_prompt_index]:
        return (
            f"""<div class ="prompt-class">Prompt {current_prompt_index + 1}/{len(prompts)}:</div> <div class="prompt-text">{prompts[current_prompt_index]}</div>""",
            gr.update(value=f"""<div class="sucess-alert">⚠️  Response for Prompt {current_prompt_index + 1} has already been submitted.</div>""", visible=True),
        )
    
    # Check if no audio is recorded
    if audio_path is None:
        return (
            f"""<div class ="prompt-class">Prompt {current_prompt_index + 1}/{len(prompts)}:</div><div class="prompt-text"> {prompts[current_prompt_index]}</div>""",
            gr.update(value="", visible=True),
        )
    
    try:
        # Ensure the directory exists and move the file
        timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
        folder_path = f"responses/{PROJECT_CODE}/Prompt{current_prompt_index + 1}"
        os.makedirs(folder_path, exist_ok=True)
        file_path = f"{folder_path}/response_{timestamp}.wav"
        shutil.move(audio_path, file_path)
        
        # Update recording status and responses
        recording_status[current_prompt_index] = True
        responses[current_prompt_index] = file_path
        
        return (
            f"""<div class ="prompt-class">Prompt {current_prompt_index + 1}/{len(prompts)}:</div><div class="prompt-text"> {prompts[current_prompt_index]}</div>""",
            gr.update(value=f"""<div class = "sucess-alert">Response for Prompt {current_prompt_index + 1} has been submitted successfully!</div>""", visible=True),
        )
    except Exception as e:
        print(f"Error occurred during submission: {e}")  # Debugging line for exception
        return (
            f"""<div class="prompt-class">Prompt {current_prompt_index + 1}/{len(prompts)}:</div><div class="prompt-text"> {prompts[current_prompt_index]}</div>""",
            gr.update(value=f"""<div class= "fail-alert">⚠️  An error occurred during submission: {str(e)}</div>""", visible=True),
        )

def save_and_next():
    global current_prompt_index
    if not recording_status[current_prompt_index]:
        return (
            f"""<div class ="prompt-class">Prompt {current_prompt_index + 1} of {len(prompts)}:</div><div class="prompt-text">{prompts[current_prompt_index]}</div>""",
            gr.update(value=f"""<div class="warning-alert">⚠️ Please record and submit your response before moving to the next prompt.</div>""", visible=True),
            gr.update(visible=True),
            gr.update(visible=True),
            gr.update(visible=True),

        )

    if current_prompt_index < len(prompts) - 1:
        current_prompt_index += 1
        is_last_prompt = current_prompt_index == len(prompts) - 1
        next_button_text = "Finish" if is_last_prompt else f"Next Prompt ({current_prompt_index + 2} of {len(prompts)})"
        return (
            f"""<div class ="prompt-class">Prompt {current_prompt_index + 1} of {len(prompts)}:</div><div class="prompt-text"> {prompts[current_prompt_index]}</div>""",
            gr.update(value="", visible=False),  # Clear the alert message
            gr.update(value=None, visible=True),
            gr.update(value=next_button_text, visible=True),
            gr.update(visible=True),

        )
    else:
        # "Finish" button clicked
        threading.Thread(target=async_upload_to_gcs_and_cleanup, daemon=True).start()

        # print(upload_to_gcs_and_cleanup())
        # alert_class = "success-alert" if success else "fail-alert"
        return (
            "Thank you for your participation in this research, all of your stories have been submitted. We place great value on your stories and will treat them with the respect they deserve.",
            gr.update(value="", visible=True),
            gr.update(visible=False),
            gr.update(visible=False),
            gr.update(visible=False),

        )

def erase_and_record():
    global current_prompt_index
    # Check if a response exists for the current prompt
    if responses[current_prompt_index]:
        # Delete the file
        try:
            os.remove(responses[current_prompt_index])
        except FileNotFoundError:
            pass  # Ignore if the file doesn't exist
        responses[current_prompt_index] = None  # Reset the response
        recording_status[current_prompt_index] = False  # Reset recording status

        # Return updated prompt and alert message
        return (
            f"""<div class="prompt-class">Prompt {current_prompt_index + 1}/{len(prompts)}:</div><div class="prompt-text"> {prompts[current_prompt_index]}</div>""",
            gr.update(value=None, visible=True),  # Reset the audio input
            gr.update(value=f"""<div class= "sucess-alert">Your previous response has been erased. Please re-record your response.</div>""", visible=True),  # Updated alert message
        )
    else:
        return (
            f"""<div class="prompt-class">Prompt {current_prompt_index + 1}/{len(prompts)}:</div><div class="prompt-text"> {prompts[current_prompt_index]}</div>""",
            gr.update(visible=True),  # Reset the audio input
            gr.update(value=f"""<div class= "warning-alert">⚠️ Please record and submit your response first.</div>""", visible=True),  # Updated alert message
        )
# Gradio Interface
def gradio_app():
    # reset_state()
    with gr.Blocks(css=custom_html) as demo:
        with gr.Row():
            gr.Markdown("""
            <div class="story-legacy-heading">StoryLegacy</div>            
            """,elem_classes=["story-legacy-heading"])                
            gr.Markdown(f"""<div class="project-code">Project: {PROJECT_CODE}</div>""")
        with gr.Row():
            alert_box = gr.Markdown("", elem_id="alert-box", visible=False)
        with gr.Row():
            prompt_display = gr.Markdown(
                f"""<div class ="prompt-class">Prompt {current_prompt_index + 1} of {len(prompts)}:</div> <div class="prompt-text">{prompts[0] if prompts else 'No prompts available.'}</div>",
                """,elem_classes=["gr-prompt"]
            )
        with gr.Row():
            # Create a hidden label to dynamically update microphone status
            record_audio = gr.Audio(
                sources="microphone", 
                type="filepath", 
                label="Record your response",
                elem_classes=["gr-audio"]
        )
        with gr.Row():
            erase_button = gr.Button("Erase & Re - Record Current Prompt", elem_classes=["gr-erase_button"])
            save_next_button = gr.Button(f"Next Prompt (2 of {len(prompts)})", elem_classes=["gr-next_button"])

        record_audio.change(submit_audio, inputs=record_audio, outputs=[prompt_display,alert_box])

        save_next_button.click(
            save_and_next,
            inputs=[],
            outputs=[
                prompt_display,
                alert_box,
                record_audio,
                save_next_button,
                erase_button,
                
            ],
        )
        erase_button.click(
            erase_and_record,
            inputs=[],
            outputs=[
                prompt_display,
                record_audio,
                alert_box,
                
            ],
        )
                
        @demo.load
        def initialize_state():
            """Initialize or reset the app's state when reloaded."""
            global current_project, current_prompt_index, prompts, recording_status, responses, custom_html

            # Load the Google Sheet data
            data = fetch_sheet_data(SHEET_URL)

            # Load the project using the hardcoded project code
            current_project = [row for row in data if row["Project Code"] == PROJECT_CODE]
            if current_project:
                current_project = current_project[0]
                prompts = [current_project[f"Prompt{i+1}"] for i in range(4) if current_project.get(f"Prompt{i+1}")]
                recording_status = [False] * len(prompts)
                responses = [None] * len(prompts)
            else:
                prompts = []
            
            # Reset the current prompt index
            current_prompt_index = 0
            print("State has been initialized.")

    return demo

# Run the app
# reset_state()
app = gradio_app()
app.launch()