from dotenv import load_dotenv
import gradio as gr
import os
from pathlib import Path
import tempfile

from datetime import datetime  # Added for date formatting

from numpy.matlib import result_type
from sympy import true 
from extract_metadata import get_metadata, get_scenes_metadata
from find_steps import find_all_steps
from video_editing import crop_video, get_final_video
import json
from video_editing_ffmpeg import concatenate_videos

from grok_analyze import create_caps_with_grok, get_story_with_grok

from concurrent.futures import ThreadPoolExecutor
import random
import string
import json
from upload_to_s3 import upload_multiple_files
import ast
from create_captions import create_caps, add_captions_to_video
from transcripts_editing import get_dialog

load_dotenv()

# Access the variables
bucket = os.getenv("BUCKET")

def generate_storyline(metadata, filenames,selected_date):

    if not metadata or not filenames:
        return None, "No metadata or files provided."
    
    print("Metadata:", metadata)
    print("Filenames:", filenames)
    
    if selected_date:
        try:
            formatted_date = datetime.fromtimestamp(selected_date).strftime('%Y-%m-%d')
            print("Selected Date:", formatted_date)

            dialog=get_dialog(formatted_date)
        except (TypeError, ValueError):
            formatted_date = "Invalid date provided"
    else:
        dialog=""

    
    metadata=get_scenes_metadata(metadata)

    steps=get_story_with_grok(metadata,"",dialog)
    print("here are the steps", steps)

    caps=create_caps(steps)

    final_video=concatenate_videos(steps)

    final_video=add_captions_to_video(final_video,False,caps)

    result = []
    for start, end, description in caps:
        # Format the time range and description, skipping empty descriptions
        if description.strip():  # Only include if description is not empty
            result.append(f"{start:.3f}-{end:.3f}, {description.strip()}")
        else:
            result.append(f"{start:.3f}-{end:.3f}")

    # Join all entries into a single string with newlines
    output = "\n".join(result)

    return steps,output,final_video #,steps,caps
    
    



# Placeholder function for video generation
def generate_video(steps,caps):
    """
    Generate a video using context and metadata.
    In a real implementation, this would process metadata to create a video.
    """
    # caps=ast.literal_eval(caps)

    result = []
    for line in caps.strip().split('\n'):
        # Split the line into time range and description (if present)
        parts = line.split(',', 1)
        time_range = parts[0].strip()
        description = parts[1].strip() if len(parts) > 1 else ''
        
        # Split the time range into start and end
        start, end = map(float, time_range.split('-'))
        
        # Append tuple to result
        result.append((start, end, description))

    caps=result

    # steps =ast.literal_eval(steps)

    print("CAPS",caps)
    print("STEPS",steps)

    
    final_video=concatenate_videos(steps)

    # steps=create_caps_with_grok(steps)

    final_video=add_captions_to_video(final_video,False,caps)

    return final_video,"done"


# Function to handle file uploads
def upload_files(uploaded_files):
    if not uploaded_files:
        return None, None, "No files uploaded."
    
    # Extract metadata and filenames
    metadata_file=""

    for file in uploaded_files:
        if file.name.lower().endswith('.json'):
            metadata_file=file.name

    if metadata_file=="":
        random_string = 'a'.join(random.choices(string.ascii_lowercase + string.digits, k=8))

        tuple_list = [(path,random_string+"/"+os.path.splitext(os.path.basename(path))[0]) for path in uploaded_files]


        executor = ThreadPoolExecutor(max_workers=1)  # Adjust max_workers as needed
        future = executor.submit(upload_multiple_files, tuple_list, bucket)

        metadata, filename = get_metadata(uploaded_files)
     
        # with ThreadPoolExecutor() as executor:
        #     future = executor.submit(upload_multiple_files,tuple_list,bucket)

    else:
        with open(metadata_file, 'r') as file:
            metadata = json.load(file)
        return metadata, metadata_file, "Files uploaded successfully."



    print("Uploaded files:", filename)
    print("Metadata:", metadata)

    
    return metadata, filename, "Files uploaded successfully."

# Gradio interface
with gr.Blocks() as demo:
    gr.Markdown("# Story Generation App")
    
    with gr.Row():
        with gr.Column():
            file_input = gr.File(label="Upload Images, Videos or metadata", file_count="multiple", file_types=["image", "video",'.json'])
            date_picker = gr.DateTime(label="Select Date", info="Select the date in which you wore the device, if applicable")  # Added datepicker

            
            upload_button = gr.Button("Upload Files (video, image, metadata)")

            gr.Markdown("Generate Video")
            generate_captions = gr.Button("Generate Video!")


            # steps = gr.Textbox(label="Generated Storyline",interactive=True)
            caps=gr.Textbox(label="Generated Captions",interactive=True)

            gr.Markdown("Modify and add new captions to the final video")
            generate_button = gr.Button("Modify Captions!")
          
        
        with gr.Column():
            video_output = gr.Video(label="Generated Video")
            upload_output = gr.Textbox(label="Upload Status")
            generation_status = gr.Textbox(label="Generation Status")
    
    # State to store metadata and filenames
    metadata_state = gr.State()
    filenames_state = gr.State()

    # steps_state = gr.State()
    # caps_state = gr.State()
    steps=gr.State()

    # caps=gr.State()
    # steps.change(
    #     fn=lambda x: x,
    #     inputs=steps,
    #     outputs=steps_state
    # )
    # caps.change(
    #     fn=lambda x: x,
    #     inputs=caps,
    #     outputs=caps_state
    # )
    # Connect buttons to functions
    upload_button.click(
        fn=upload_files,
        inputs=file_input,
        outputs=[metadata_state, filenames_state, upload_output]
    )
    generate_captions.click(
        fn=generate_storyline,
        inputs=[metadata_state, filenames_state,date_picker],
        # outputs=[steps_state, caps_state,steps, caps]
        outputs=[steps, caps,video_output]
    )

    generate_button.click(
        fn=generate_video,
        inputs=[steps, caps],
        outputs=[video_output, generation_status]
    )



# Launch the app (Pyodide-compatible launch)
# demo.launch(share=true)

demo.launch()