api / modules /app.py
Saqib
Update modules/app.py
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from fastapi import FastAPI, HTTPException, Request, Depends
from fastapi.staticfiles import StaticFiles
from pytube import YouTube
import uuid
import logging
import aiohttp
import base64
import io
import os
import random
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:
yt = YouTube(url)
video = yt.streams.filter(only_audio=True).first()
# Generate a unique filename
unique_filename = f"{uuid.uuid4().hex}.mp3"
out_file = os.path.join(AUDIO_DIR, unique_filename)
# 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 Exception as e:
raise HTTPException(status_code=500, detail=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)