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from fastapi import FastAPI
from fastapi.staticfiles import StaticFiles
from fastapi.responses import FileResponse
import gradio as gr
import os
import sys
import random
import string
import time
from queue import Queue
from threading import Thread
import requests
import io
from PIL import Image
import base64
from deep_translator import GoogleTranslator
app = FastAPI()
API_URL = "https://api-inference.huggingface.co/models/jayavibhav/anime-dreamlike"
API_TOKEN = os.getenv("HF_READ_TOKEN") # it is free
headers = {"Authorization": f"Bearer {API_TOKEN}"}
text_gen = gr.Interface.load("models/Gustavosta/MagicPrompt-Stable-Diffusion")
queue = Queue()
queue_threshold = 100
def add_random_noise(prompt, noise_level=0.00):
if noise_level == 0:
noise_level = 0.00
percentage_noise = noise_level * 5
num_noise_chars = int(len(prompt) * (percentage_noise / 100))
noise_indices = random.sample(range(len(prompt)), num_noise_chars)
prompt_list = list(prompt)
noise_chars = list(string.ascii_letters + string.punctuation + ' ' + string.digits)
noise_chars.extend(['๐', '๐ฉ', '๐', '๐ค', '๐', '๐ค', '๐ญ', '๐', '๐ท', '๐คฏ', '๐คซ', '๐ฅด', '๐ด', '๐คฉ', '๐ฅณ', '๐', '๐ฉ', '๐คช', '๐', '๐คข', '๐', '๐น', '๐ป', '๐ค', '๐ฝ', '๐', '๐', '๐
', '๐', '๐', '๐', '๐', '๐', '๐', '๐ฎ', 'โค๏ธ', '๐', '๐', '๐', '๐', '๐ถ', '๐ฑ', '๐ญ', '๐น', '๐ฆ', '๐ป', '๐จ', '๐ฏ', '๐ฆ', '๐', '๐ฅ', '๐ง๏ธ', '๐', '๐', '๐ฅ', '๐ด', '๐', '๐บ', '๐ป', '๐ธ', '๐จ', '๐
', '๐', 'โ๏ธ', 'โ๏ธ', 'โ๏ธ', 'โ๏ธ', '๐ค๏ธ', 'โ
๏ธ', '๐ฅ๏ธ', '๐ฆ๏ธ', '๐ง๏ธ', '๐ฉ๏ธ', '๐จ๏ธ', '๐ซ๏ธ', 'โ๏ธ', '๐ฌ๏ธ', '๐จ', '๐ช๏ธ', '๐'])
for index in noise_indices:
prompt_list[index] = random.choice(noise_chars)
return "".join(prompt_list)
# Existing code...
import uuid # Import the UUID library
# Existing code...
# Existing code...
request_counter = 0 # Global counter to track requests
def generate_image(inputs, is_negative, steps, cfg_scale, seed):
try:
global request_counter
request_counter += 1
timestamp = f"{time.time()}_{request_counter}"
# Translate inputs to English
translator_to_en = GoogleTranslator(source='auto', target='english')
english_inputs = translator_to_en.translate(inputs)
prompt_with_noise = add_random_noise(english_inputs) + f" - {timestamp}"
payload = {
"inputs": prompt_with_noise,
"is_negative": is_negative,
"steps": steps,
"cfg_scale": cfg_scale,
"seed": seed if seed is not None else random.randint(-1, 2147483647)
}
response = requests.post(API_URL, headers=headers, json=payload)
response.raise_for_status() # Raise an exception for HTTP errors
image_bytes = response.content
image = Image.open(io.BytesIO(image_bytes))
return image
except requests.exceptions.HTTPError as e:
# Handle any HTTP errors
print(f"HTTP Error: {e}")
return "An unexpected error occurred while generating the image."
except Exception as e:
# Handle other exceptions
print(f"Error generating image: {e}")
return "An unexpected error occurred while generating the image. Please try again later."
import time
def get_prompts(prompt_text):
if not prompt_text:
return "Please enter text before generating prompts.ุฑุฌุงุก ุงุฏุฎู ุงููุต ุงููุง"
raise gr.Error("Please enter text before generating prompts.ุฑุฌุงุก ุงุฏุฎู ุงููุต ุงููุง")
else:
options = [
"photo anime, masterpiece, high quality, absurdres, "
# Add other prompt options here...
]
if prompt_text:
# Generate timestamp for different prompts
timestamp = f"{time.time()}"
chosen_option = random.choice(options)
# Combine prompt text with chosen option
prompt_with_option = f"{prompt_text}, {chosen_option}"
# Use prompt text with option for generating prompts
return text_gen(prompt_with_option)
else:
return text_gen("")
def initialize_api_connection():
global headers
API_TOKEN = os.getenv("HF_READ_TOKEN") # it is free
headers = {"Authorization": f"Bearer {API_TOKEN}"}
# Run initialization functions on startup
initialize_api_connection()
@app.get("/generate_prompts")
def generate_prompts(prompt_text: str):
return get_prompts(prompt_text)
from fastapi import Query
from fastapi import HTTPException
@app.get("/send_inputs")
def send_inputs(
inputs: str,
noise_level: float,
is_negative: str,
steps: int = 20,
cfg_scale: int = 4.5,
seed: int = None
):
try:
generated_image = generate_image(inputs, is_negative, steps, cfg_scale, seed)
if generated_image is not None:
image_bytes = io.BytesIO()
generated_image.save(image_bytes, format="JPEG")
image_base64 = base64.b64encode(image_bytes.getvalue()).decode("utf-8")
return {"image_base64": image_base64}
else:
# Return an error message if the image couldn't be generated
raise HTTPException(status_code=500, detail="Failed to generate image.")
except Exception as e:
# Log the error and return an error message
print(f"Error generating image: {e}")
raise HTTPException(status_code=500, detail="Failed to generate image.")
app.mount("/", StaticFiles(directory="static", html=True), name="static")
@app.get("/")
def index() -> FileResponse:
return FileResponse(path="/app/static/index.html", media_type="text/html")
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