from fastapi import FastAPI, HTTPException, Request, Depends from fastapi.staticfiles import StaticFiles from pytubefix import YouTube from pytubefix.exceptions import PytubeFixError import ffmpeg from pydantic import BaseModel, HttpUrl from typing import List import requests import tempfile import time import uuid 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) # 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") class AudioImageInput(BaseModel): image_url: HttpUrl audio_url: HttpUrl class VideosInput(BaseModel): video_urls: List[HttpUrl] 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(input_data: AudioImageInput): try: # Download image and audio files temp_image_path = await download_file(str(input_data.image_url), ".png") temp_audio_path = await download_file(str(input_data.audio_url), ".mp3") # Generate a unique filename output_filename = f"{uuid.uuid4()}.mp4" output_path = os.path.join(OUTPUT_DIR, output_filename) # Use ffmpeg to combine image and audio into a video input_image = ffmpeg.input(temp_image_path, loop=1, t=5) # 5 seconds duration input_audio = ffmpeg.input(temp_audio_path) ffmpeg.concat(input_image, input_audio, v=1, a=1).output(output_path, vcodec='libx264', acodec='aac').run() # Clean up temporary files os.unlink(temp_image_path) os.unlink(temp_audio_path) # Return the URL path to the output file return f"/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(input_data: VideosInput): try: temp_video_paths = [] # Download videos to temporary files for video_url in input_data.video_urls: temp_video_paths.append(await download_file(str(video_url), ".mp4")) # Generate a unique filename for the output output_filename = f"{uuid.uuid4()}.mp4" output_path = os.path.join(OUTPUT_DIR, output_filename) # Separate video and audio streams video_and_audio_streams = [] for path in temp_video_paths: video = ffmpeg.input(path).video audio = ffmpeg.input(path).audio video_and_audio_streams.append(video) video_and_audio_streams.append(audio) # Concatenate video and audio streams joined = ffmpeg.concat(*video_and_audio_streams, v=1, a=1).node # Merge video and audio ffmpeg.output(joined[0], joined[1], output_path, vcodec='libx264', acodec='aac').run() # Clean up temporary files for path in temp_video_paths: os.remove(path) # Return the URL path to the output file return f"/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_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) print(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 PytubeFixError 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)