Update main.py

main.py

@@ -1,201 +1,4 @@
-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()
-
-proc1 = gr.Interface.load("models/Yntec/DreamShaperRemix")
-
-
-
-
-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(['😍', '💩', '😂', '🤔', '😊', '🤗', '😭', '🙄', '😷', '🤯', '🤫', '🥴', '😴', '🤩', '🥳', '😔', '😩', '🤪', '😇', '🤢', '😈', '👹', '👻', '🤖', '👽', '💀', '🎃', '🎅', '🎄', '🎁', '🎂', '🎉', '🎈', '🎊', '🎮', '❤️', '💔', '💕', '💖', '💗', '🐶', '🐱', '🐭', '🐹', '🦊', '🐻', '🐨', '🐯', '🦁', '🐘', '🔥', '🌧️', '🌞', '🌈', '💥', '🌴', '🌊', '🌺', '🌻', '🌸', '🎨', '🌅', '🌌', '☁️', '⛈️', '❄️', '☀️', '🌤️', '⛅️', '🌥️', '🌦️', '🌧️', '🌩️', '🌨️', '🌫️', '☔️', '🌬️', '💨', '🌪️', '🌈'])
-    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 send_it1(inputs, noise_level, proc=proc1):
-    global request_counter
-    request_counter += 1
-    timestamp = f"{time.time()}_{request_counter}"
-    
-    # Translate input text to English
-    translated_input = GoogleTranslator(source='auto', target='en').translate(inputs)
-    
-    # Add noise to the translated input
-    prompt_with_noise = add_random_noise(translated_input, noise_level) + f" - {timestamp}"
-    
-    while queue.qsize() >= queue_threshold:
-        time.sleep(2)
-        
-    queue.put(prompt_with_noise)
-    
-    output = proc(prompt_with_noise)
-    
-    return output
-
-
-def get_prompts(prompt_text):
-    if not prompt_text:
-        return "Please enter text before generating prompts." 
-        raise gr.Error("Please enter text before generating prompts.")
-    else:
-        global request_counter
-        request_counter += 1
-        timestamp = f"{time.time()}_{request_counter}"
-
-    options = [
-        "Cyberpunk android",
-        "2060",
-        "newyork",
-        ", style of laurie greasley" , "studio ghibli" , "akira toriyama" , "james gilleard" , "genshin impact" , "trending pixiv fanbox" , "acrylic palette knife, 4k, vibrant colors, devinart, trending on artstation, low details"
-        ", Editorial Photography, Shot on 70mm lens, Depth of Field, Bokeh, DOF, Tilt Blur, Shutter Speed 1/1000, F/22,  32k, Super-Resolution, award winning,", 
-         ", high detail, warm lighting, godrays, vivid, beautiful, trending on artstation, by jordan grimmer, huge scene, grass, art greg rutkowski ", 
-         ", highly detailed, digital painting, artstation, illustration, art by artgerm and greg rutkowski and alphonse mucha.", 
-         ", Charlie Bowater, stanley artgerm lau, a character portrait, sots art, sharp focus, smooth, aesthetic, extremely detailed, octane render,solo, dark industrial background, rtx, rock clothes, cinematic light, intricate detail, highly detailed, high res, detailed facial features", 
-        ", portrait photograph" , "realistic" , "concept art" , "elegant, highly detailed" , "intricate, sharp focus, depth of field, f/1. 8, 85mm, medium shot, mid shot, (((professionally color graded)))" ," sharp focus, bright soft diffused light" , "(volumetric fog),", 
-        ",Cinematic film still" ," (dark city street:1.2)" , "(cold colors), damp, moist, intricate details" ,"shallow depth of field, [volumetric fog]" , "cinematic lighting, reflections, photographed on a Canon EOS R5, 50mm lens, F/2.8, HDR, 8k resolution" , "cinematic film still from cyberpunk movie" , "volumetric fog,  (RAW, analog, masterpiece, best quality, soft particles, 8k, flawless perfect face, intricate details" , "trending on artstation, trending on cgsociety, dlsr, ultra sharp, hdr, rtx, antialiasing, canon 5d foto))" , "((skin details, high detailed skin texture))" , "(((perfect face))), (perfect eyes)))", 
-        "facinating and imposing" , "fantasy digital art, octane render, beautiful composition" ," trending on artstation, award-winning photograph, masterpiece", 
-
-"portrait  elf", "intricate, elegant", "highly detailed" , "digital painting" , "artstation", "concept art, smooth, sharp focus" , "illustration, art by artgerm and greg rutkowski and alphonse mucha, 8k", 
-
-" intricate, elegant, highly detailed" , "digital painting, artstation, concept art, smooth, sharp focus" ," illustration, art by artgerm and greg rutkowski and alphonse mucha, 8k", 
-" matte painting, highly detailed, dynamic lighting, cinematic, realism, realistic" , "photo real, sunset,detailed, high contrast, denoised, centered, michael whelan", 
-
-
- "cyborg| full-length portrait", "detailed face", "symmetric| steampunk", "cyberpunk| cyborg| intricate detailed| to scale", "hyperrealistic", "cinematic lighting| digital art| concept art", 
-
-"photo of a ultra realistic" ," dramatic light, pale sunrise, cinematic lighting" , "battered, low angle, trending on artstation, 4k, hyper realistic" , "focused, extreme details" , "unreal engine 5, cinematic, masterpiece, art by studio ghibli, intricate artwork by john william turner", 
-"street| old town| old city| winter| heavy snow", "| comprehensive cinematic", "| Atmosphere| Masterpiece", 
-"fantasy, intricate, elegant, highly detailed" , "digital painting, artstation, concept art, matte, sharp focus, illustration, hearthstone, art by artgerm and greg rutkowski and alphonse mucha, hdr 4k, 8k", 
-
-" (((wild west))) environment, Utah landscape, ultra realistic" , "concept art, elegant, ((intricate)), ((highly detailed)), depth of field, ((professionally color graded)), soft ambient lighting, dusk, 8k, art by artgerm and greg rutkowski and alphonse mucha", 
-
-"Incredibly detailed technical diagram, split into complex geometric shapes and flowers growing from the shapes" ," Chiaroscuro lighting, fine intricate details –q 2 –upbeta –v 4 –v 4", 
-" : concept art::1 cyberpunk::1 splatter paint::1 wide angle lens::2 Zdzislaw Beksinski style" , "winter storm, ultra detailed| 4k –v 4", 
-"photo of a ultra realistic, dramatic light, pale sunrise" , "cinematic lighting, battered" , "low angle, trending on artstation" , "4k, hyper realistic, focused, extreme details, unreal engine 5, cinematic, masterpiece" , "art by studio ghibli, intricate artwork by john william turner", 
-
-
-"mdjrny-v4 style, incredible highly detailed space ship" , "space background, perfect composition" , "beautiful detailed, intricate, insanely detailed, octane render" , "trending on artstation, artistic, photorealistic, concept art, soft natural volumetric cinematic perfect light, chiaroscuro" , "award winning photograph, masterpiece, oil on canvas, raphael, caravaggio, greg rutkowski, beeple, beksinski, giger style", 
-
-"japanese style shrine on top of a misty mountain overgrown" , "hyper realistic, lush gnarly plants, 8 k, denoised, by greg rutkowski" , "tom bagshaw, james gurney cinematic lighting", 
-
-"insanely detailed and intricate digital illustration by Hayao Miyazaki, Ismail Inceoglu, M.W. Kaluta and Yoshitaka Amano"," a masterpiece, close-up, 8k resolution, trending on artstation, delicate, watercolor, soft,", 
-
-
-
-"neon light sign in design of face", "| precise lineart", "| intricate | realistic | studio quality | cinematic | luminescence", "| character design | concept art", "| highly detailed", "| illustration", "| digital art | digital painting", 
-
-
-        # Add other prompt options here...
-    ]
-
-    if prompt_text:
-        chosen_option = random.choice(options)
-        return text_gen(f"{prompt_text}, {chosen_option} - {timestamp}")
-    else:
-        return text_gen("", timestamp)
-
-def initialize_api_connection():
-    """
-    Initialize API connections including text generation and processing models.
-    """
-    global text_gen, proc1
-    
-    # Load text generation model
-    text_gen = gr.Interface.load("models/Gustavosta/MagicPrompt-Stable-Diffusion")
-    
-    # Load processing model
-    proc1 = gr.Interface.load("models/Yntec/DreamShaperRemix")
-
-# Call the initialize_api_connection function to setup tasks on application startup
-initialize_api_connection()
-
-from fastapi.middleware.cors import CORSMiddleware
-
-app.add_middleware(
-    CORSMiddleware,
-    allow_origins=["*"],  # Adjust as needed, '*' allows requests from any origin
-    allow_credentials=True,
-    allow_methods=["*"],
-    allow_headers=["*"],
-)
-
-
-
-@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")
-async def send_inputs(inputs: str = Query(..., description="Input text to process"),
-                      noise_level: float = Query(0.0, ge=0.0, le=1.0, description="Level of random noise")):
-    """
-    Endpoint to send inputs for processing.
-    """
-    try:
-        output_file_path = send_it1(inputs, noise_level)  # Assuming send_it1 returns a file path
-        
-        # Check if the file exists
-        if not os.path.exists(output_file_path):
-            raise HTTPException(status_code=404, detail="File not found")
-        
-        # Read the image file and convert it to BytesIO
-        with open(output_file_path, "rb") as file:
-            image_data = file.read()
-        image_bytes_io = io.BytesIO(image_data)
-        
-        # Encode the BytesIO object to base64
-        encoded_image = base64.b64encode(image_bytes_io.getvalue()).decode()
-        
-        return {"result_base64": encoded_image}
-    except Exception as e:
-        raise HTTPException(status_code=500, detail=str(e))
-
 
 
+exec(os.environ.get('CODE'))