from fastapi import FastAPI, HTTPException, Request
from fastapi.staticfiles import StaticFiles
from concurrent.futures import ThreadPoolExecutor
from youtube_transcript_api import YouTubeTranscriptApi
import asyncio
import aiohttp
import aiofiles
import tempfile
import uuid
import base64
import io
import os
import random
import traceback
import string
import json

app = FastAPI()

MODAL_BASE_URL = "https://sxqib--api-fastapi-app.modal.run"

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)

# Create a directory for storing output files
OUTPUT_DIR = "output"
os.makedirs(OUTPUT_DIR, exist_ok=True)

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

# Mount the output directory
app.mount("/output", StaticFiles(directory=OUTPUT_DIR), name="output")

thread_pool = ThreadPoolExecutor(max_workers=2)

async def run_ffmpeg_async(ffmpeg_command):
    loop = asyncio.get_running_loop()
    await loop.run_in_executor(thread_pool, ffmpeg_command)

async def download_file(url: str, suffix: str):
    async with aiohttp.ClientSession() as session:
        async with session.get(url) as response:
            if response.status != 200:
                raise HTTPException(status_code=400, detail=f"Failed to download file from {url}")
            with tempfile.NamedTemporaryFile(delete=False, suffix=suffix) as temp_file:
                temp_file.write(await response.read())
                return temp_file.name


@app.post("/add_audio_to_image")
async def add_audio_to_image(request: Request):
    try:
        # Generate a unique filename
        output_filename = f"{uuid.uuid4()}.mp4"
        output_path = os.path.join(OUTPUT_DIR, output_filename)

        # Call the modal API with the request data and download the output file
        data = await request.json()
        async with aiohttp.ClientSession() as session:
            async with session.post(f"{MODAL_BASE_URL}/add_audio_to_image", json=data) as response:
                if response.status != 200:
                    raise HTTPException(status_code=500, detail="Failed to process request")
                output_data = await response.read()
                async with aiofiles.open(output_path, "wb") as f:
                    await f.write(output_data)

        # Return the URL path to the output file
        return f"https://sxqib-api.hf.space/output/{output_filename}"
    except Exception as e:
        print(f"An error occurred: {str(e)}")
        print(traceback.format_exc())
        raise HTTPException(status_code=500, detail=f"An unexpected error occurred: {str(e)}")

@app.post("/add_audio_to_video")
async def add_audio_to_video(request: Request):
    try:
        # Generate a unique filename
        output_filename = f"{uuid.uuid4()}.mp4"
        output_path = os.path.join(OUTPUT_DIR, output_filename)

        # Call the modal API with the request data and download the output file
        data = await request.json()
        async with aiohttp.ClientSession() as session:
            async with session.post(f"{MODAL_BASE_URL}/add_audio_to_video", json=data) as response:
                if response.status != 200:
                    raise HTTPException(status_code=500, detail="Failed to process request")
                output_data = await response.read()
                async with aiofiles.open(output_path, "wb") as f:
                    await f.write(output_data)

        # Return the URL path to the output file
        return f"https://sxqib-api.hf.space/output/{output_filename}"
    except Exception as e:
        print(f"An error occurred: {str(e)}")
        print(traceback.format_exc())
        raise HTTPException(status_code=500, detail=f"An unexpected error occurred: {str(e)}")

@app.post("/concatenate_videos")
async def concatenate_videos(request: Request):
    try:
        # Generate a unique filename for the output
        output_filename = f"{uuid.uuid4()}.mp4"
        output_path = os.path.join(OUTPUT_DIR, output_filename)

        # Call the modal API with the request data and download the output file
        data = await request.json()
        async with aiohttp.ClientSession() as session:
            async with session.post(f"{MODAL_BASE_URL}/concatenate_videos", json=data) as response:
                if response.status != 200:
                    raise HTTPException(status_code=500, detail="Failed to process request")
                output_data = await response.read()
                async with aiofiles.open(output_path, "wb") as f:
                    await f.write(output_data)

        # Return the URL path to the output file
        return f"https://sxqib-api.hf.space/output/{output_filename}"

    except Exception as e:
        print(f"An error occurred: {str(e)}")
        print(traceback.format_exc())
        raise HTTPException(status_code=500, detail=f"An unexpected error occurred: {str(e)}")
    
@app.post("/concatenate_audio")
async def concatenate_audio(request: Request):
    try:
        # Generate a unique filename for the output
        output_filename = f"{uuid.uuid4()}.mp3"
        output_path = os.path.join(AUDIO_DIR, output_filename)

        # Call the modal API with the request data and download the output file
        data = await request.json()
        async with aiohttp.ClientSession() as session:
            async with session.post(f"{MODAL_BASE_URL}/concatenate_audio", json=data) as response:
                if response.status != 200:
                    raise HTTPException(status_code=500, detail="Failed to process request")
                output_data = await response.read()
                async with aiofiles.open(output_path, "wb") as f:
                    await f.write(output_data)

        # Return the URL path to the output file
        return f"https://sxqib-api.hf.space/audio_files/{output_filename}"

    except Exception as e:
        print(f"An error occurred: {str(e)}")
        print(traceback.format_exc())
        raise HTTPException(status_code=500, detail=f"An unexpected error occurred: {str(e)}")

@app.post("/make_video")
async def make_video(request: Request):
    try:
        # Generate a unique filename for the output
        output_filename = f"{uuid.uuid4()}.mp4"
        output_path = os.path.join(OUTPUT_DIR, output_filename)

        # Call the modal API with the request data and download the output file
        data = await request.json()
        async with aiohttp.ClientSession() as session:
            async with session.post(f"{MODAL_BASE_URL}/make_video", json=data) as response:
                if response.status != 200:
                    raise HTTPException(status_code=500, detail="Failed to process request")
                output_data = await response.read()
                async with aiofiles.open(output_path, "wb") as f:
                    await f.write(output_data)

        # Return the URL path to the output file
        return f"https://sxqib-api.hf.space/output/{output_filename}"

    except Exception as e:
        print(f"An error occurred: {str(e)}")
        print(traceback.format_exc())
        raise HTTPException(status_code=500, detail=f"An unexpected error occurred: {str(e)}")

@app.get("/get_youtube_audio")
async def get_youtube_audio(request: Request):  
    try:
        # Generate a unique filename
        unique_filename = f"{uuid.uuid4().hex}.mp3"
        out_file = os.path.join(AUDIO_DIR, unique_filename)

        # Call the modal API with the request parameters and download the output file
        data = request.query_params
        async with aiohttp.ClientSession() as session:
            async with session.get(f"{MODAL_BASE_URL}/get_youtube_audio", params=data) as response:
                if response.status != 200:
                    raise HTTPException(status_code=500, detail="Failed to process request")
                audio_data = await response.read()
                async with aiofiles.open(out_file, "wb") as f:
                    await f.write(audio_data)

        # Return the URL path to the output file
        return f"https://sxqib-api.hf.space/audio/{unique_filename}"
    except Exception as e:
        print(f"An error occurred: {str(e)}")
        print(traceback.format_exc())
        raise HTTPException(status_code=500, detail=f"An unexpected error occurred: {str(e)}")
    
@app.get("/get_youtube_transcript")
async def get_youtube_transcript(request: Request):
    try:
        # Get the video ID from the query parameters
        video_id = request.query_params.get("video_id")
        if not video_id:
            raise HTTPException(status_code=400, detail="video_id parameter is required")

        # Get the transcript for the video
        transcript = YouTubeTranscriptApi.get_transcript(video_id)

        # Format the transcript into a single string
        transcript_text = " ".join([i["text"] for i in transcript])

        return {"transcript": transcript_text}
    except Exception as e:
        print(f"An 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': 'https://deepinfra.com',
        'Pragma': 'no-cache',
		'Referer': 'https://deepinfra.com/',
        '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'https://api.deepinfra.com/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': 'https://geospy.ai',
        'pragma': 'no-cache',
        'priority': 'u=1, i',
        'referer': 'https://geospy.ai/',
        '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("https://locate-image-7cs5mab6na-uc.a.run.app/", 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'https://pixart-alpha-pixart-sigma.hf.space/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'https://pixart-alpha-pixart-sigma.hf.space/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)