from fastapi import FastAPI, HTTPException, Request, Depends
from fastapi.staticfiles import StaticFiles
from pytubefix import YouTube
from pytubefix.exceptions import PytubeError
import time
import uuid
import logging
import aiohttp
import base64
import io
import os
import random
import traceback
import string
import json

app = FastAPI()

whisper_origin = os.getenv("WHISPER_ORIGIN")
whisper_base_url = os.getenv("WHISPER_BASE_URL")
img2location_name = os.getenv("IMG2LOCATION_NAME")
img2location_origin = os.getenv("IMG2LOCATION_ORIGIN")
img2location_base_url = os.getenv("IMG2LOCATION_BASE_URL")
pixart_sigma_base_url = os.getenv("PIXART_SIGMA_BASE_URL")
allowed_user_agent = os.getenv("ALLOWED_USER_AGENT")


def generate_hash(length=12):
    # Characters that can appear in the hash
    characters = string.ascii_lowercase + string.digits
    # Generate a random string of the specified length
    hash_string = ''.join(random.choice(characters) for _ in range(length))
    return hash_string

@app.get("/")
async def read_root():
    return {"message": "Saqib's API"}

# Create a directory to store MP3 files if it doesn't exist
AUDIO_DIR = "audio_files"
os.makedirs(AUDIO_DIR, exist_ok=True)

# Mount the audio directory
app.mount("/audio", StaticFiles(directory=AUDIO_DIR), name="audio")

@app.get("/get_audio")
async def get_audio(url: str):    
    if not url:
        raise HTTPException(status_code=400, detail="URL is required")

    try:
        print(f"Attempting to process YouTube URL: {url}")
        yt = YouTube(url)
        video = yt.streams.filter(only_audio=True).first()
        
        if not video:
            print(f"No audio stream found for URL: {url}")
            raise HTTPException(status_code=404, detail="No audio stream found for this video")
        
        # Generate a unique filename
        unique_filename = f"{uuid.uuid4().hex}.mp3"
        out_file = os.path.join(AUDIO_DIR, unique_filename)

        print((f"Downloading audio to: {out_file}"))
        
        # Download the audio
        video.download(output_path=AUDIO_DIR, filename=unique_filename)
        
        file_stats = os.stat(out_file)
        logging.info(f'Size of audio file in Bytes: {file_stats.st_size}')
        
        if file_stats.st_size <= 30000000:
            # Construct the URL for the MP3 file
            mp3_url = f"/audio/{unique_filename}"
            return mp3_url
        else:
            os.remove(out_file)
            raise HTTPException(status_code=413, detail="Audio file is too large. Limited to about 1.5 hours.")
    except PytubeError as e:
        print(f"PytubeError occurred: {str(e)}")
        raise HTTPException(status_code=400, detail=f"Error processing YouTube video: {str(e)}")
    except HTTPException as he:
        # Re-raise HTTP exceptions
        raise he
    except Exception as e:
        print(f"Unexpected error occurred: {str(e)}")
        print(traceback.format_exc())
        raise HTTPException(status_code=500, detail=f"An unexpected error occurred: {str(e)}")

@app.post("/whisper")
async def whisper(request: Request):
    data = await request.json()  # Extracting JSON data from request
    if "audio_url" not in data:
        raise HTTPException(status_code=400, detail="audio_url not found in request")
    url = data["audio_url"]

    headers = {
        'Accept': 'application/json, text/plain, */*',
        'Accept-Language': 'en-US,en;q=0.9',
        'Cache-Control': 'no-cache',
        'Connection': 'keep-alive',
        'Content-Type': 'application/json',
        'DNT': '1',
        'Origin': whisper_origin,
        'Pragma': 'no-cache',
        'Referer': f'{whisper_origin}/',
        'Sec-Fetch-Dest': 'empty',
        'Sec-Fetch-Mode': 'cors',
        'Sec-Fetch-Site': 'same-site',
        'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/124.0.0.0 Safari/537.36 Edg/124.0.0.0',
        'sec-ch-ua': '"Chromium";v="124", "Microsoft Edge";v="124", "Not-A.Brand";v="99"',
        'sec-ch-ua-mobile': '?0',
        'sec-ch-ua-platform': '"Windows"',
    }

    # Async HTTP request to get the audio file
    async with aiohttp.ClientSession() as session:
        async with session.get(url) as resp:
            if resp.status != 200:
                return f"Failed to download audio: {resp.status}"
            audio_data = await resp.read()

            # Encode the audio data to base64
            audio_base64 = base64.b64encode(audio_data).decode("utf-8")

            json_data = '{"audio": "' + audio_base64 + '"}'

            # Post request to the API
            async with session.post(f'{whisper_base_url}/v1/inference/openai/whisper-large', headers=headers, data=json_data) as post_resp:
                if post_resp.status != 200:
                    return f"API request failed: {post_resp.status}"
                return await post_resp.json()

@app.post("/img2location")
async def img2location(request: Request):
    request_json = await request.json()
    image_url = request_json.get("image_url", None)
    
    if not image_url:
        raise HTTPException(status_code=400, detail="image_url not found in request")

    headers = {
        'accept': '*/*',
        'accept-language': 'en-US,en;q=0.9',
        'cache-control': 'no-cache',
        'dnt': '1',
        'origin': img2location_origin,
        'pragma': 'no-cache',
        'priority': 'u=1, i',
        'referer': f'{img2location_origin}/',
        'sec-ch-ua': '"Chromium";v="124", "Microsoft Edge";v="124", "Not-A.Brand";v="99"',
        'sec-ch-ua-mobile': '?0',
        'sec-ch-ua-platform': '"Windows"',
        'sec-fetch-dest': 'empty',
        'sec-fetch-mode': 'cors',
        'sec-fetch-site': 'cross-site',
        'user-agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/124.0.0.0 Safari/537.36 Edg/124.0.0.0',
    }

    async with aiohttp.ClientSession() as session:
        # Fetch the image from the URL
        async with session.get(image_url) as img_response:
            if img_response.status != 200:
                return f"Failed to fetch image: HTTP {img_response.status}"
            image_data = await img_response.read()

        # Using BytesIO to handle the byte content
        data = aiohttp.FormData()
        data.add_field('image', io.BytesIO(image_data), filename="image.png", content_type='image/png')

        # Sending the POST request
        async with session.post(img2location_base_url, headers=headers, data=data) as response:
            if response.status != 200:
                return f"Failed to upload image: HTTP {response.status}"
            json_response = await response.json()
            if json_response["message"]["latitude"] and json_response["message"]["longitude"]:
                json_response["message"]["latitude"] = str(json_response["message"]["latitude"])
                json_response["message"]["longitude"] = str(json_response["message"]["longitude"])
            return json_response

@app.post("/pixart-sigma")
async def pixart_sigma(request: Request):
    request_json = await request.json()
    prompt = request_json.get("prompt", None)
    negative_prompt = request_json.get("negative_prompt", "")
    style = request_json.get("style", "(No style)")
    use_negative_prompt = request_json.get("use_negative_prompt", True)
    num_imgs = request_json.get("num_imgs", 1)
    seed = request_json.get("seed", 0)
    width = request_json.get("width", 1024)
    height = request_json.get("height", 1024)
    schedule = request_json.get("schedule", "DPM-Solver")
    dpms_guidance_scale = request_json.get("dpms_guidance_scale", 4.5)
    sas_guidance_scale = request_json.get("sas_guidance_scale", 3)
    dpms_inference_steps = request_json.get("dpms_inference_steps", 14)
    sas_inference_steps = request_json.get("sas_inference_steps", 25)
    randomize_seed = request_json.get("randomize_seed", True)

    hash = generate_hash()

    headers = {
        'accept': '*/*'
    }

    params = {
        '__theme': 'light',
    }

    json_data = {
        'data': [
            prompt,
            negative_prompt,
            style,
            use_negative_prompt,
            num_imgs,
            seed,
            width,
            height,
            schedule,
            dpms_guidance_scale,
            sas_guidance_scale,
            dpms_inference_steps,
            sas_inference_steps,
            randomize_seed,
        ],
        'event_data': None,
        'fn_index': 3,
        'trigger_id': 7,
        'session_hash': hash,
    }

    async with aiohttp.ClientSession() as session:
        async with session.post(f'{pixart_sigma_base_url}/queue/join', params=params, headers=headers, json=json_data, ssl=False) as response:
            print(response.status)

        params = {
            'session_hash': hash,
        }

        async with session.get(f'{pixart_sigma_base_url}/queue/data', params=params, headers=headers, ssl=False) as response:
            async for line in response.content:
                try:
                    if line:
                        line = line.decode('utf-8')
                        line = line.replace('data: ', '')
                        line_json = json.loads(line)
                        if line_json["msg"] == "process_completed":
                            image_url = line_json["output"]["data"][0][0]["image"]["url"]
                            return {"image_url": image_url}
                except:
                    pass

# if __name__ == "__main__":
#     import uvicorn
#     uvicorn.run(app, host="0.0.0.0", port=8000)