#!/bin/env python3.11 import os import sqlite3 import replicate import argparse import requests from datetime import datetime from fastapi import FastAPI, WebSocket, WebSocketDisconnect, HTTPException, Request, Form, Query,Response from fastapi.templating import Jinja2Templates from fastapi.responses import FileResponse from fastapi.staticfiles import StaticFiles from pydantic import BaseModel from typing import Optional, List import uvicorn from asyncio import gather, Semaphore, create_task from mistralai import Mistral from contextlib import contextmanager from io import BytesIO import zipfile import sys print(f"Arguments: {sys.argv}") token = os.getenv("HF_TOKEN") api_key = os.getenv("MISTRAL_API_KEY") agent_id = os.getenv("MISTRAL_FLUX_AGENT") HEADER = "\033[38;2;255;255;153m" TITLE = "\033[38;2;255;255;153m" MENU = "\033[38;2;255;165;0m" SUCCESS = "\033[38;2;153;255;153m" ERROR = "\033[38;2;255;69;0m" MAIN = "\033[38;2;204;204;255m" SPEAKER1 = "\033[38;2;173;216;230m" SPEAKER2 = "\033[38;2;255;179;102m" RESET = "\033[0m" #os.system("clear") #print(f"{HEADER}--------------------\nMY FLUX CREATOR v1.0\n--------------------{RESET}\n") DOWNLOAD_DIR = "/mnt/d/ai/dialog/2/flux-pics" DATABASE_PATH = "flux_logs_neu.db" TIMEOUT_DURATION = 900 # Timeout-Dauer in Sekunden IMAGE_STORAGE_PATH = DOWNLOAD_DIR # Pfad auf flux-pics setzen app = FastAPI() app.mount("/static", StaticFiles(directory="static"), name="static") app.mount("/flux-pics", StaticFiles(directory=DOWNLOAD_DIR), name="flux-pics") templates = Jinja2Templates(directory="templates") @contextmanager def get_db_connection(db_path=DATABASE_PATH): conn = sqlite3.connect(db_path) try: yield conn finally: conn.close() def initialize_database(db_path=DATABASE_PATH): with get_db_connection(db_path) as conn: cursor = conn.cursor() cursor.execute(""" CREATE TABLE IF NOT EXISTS generation_logs ( id INTEGER PRIMARY KEY AUTOINCREMENT, timestamp TEXT, prompt TEXT, optimized_prompt TEXT, hf_lora TEXT, lora_scale REAL, aspect_ratio TEXT, guidance_scale REAL, output_quality INTEGER, prompt_strength REAL, num_inference_steps INTEGER, output_file TEXT, album_id INTEGER, category_id INTEGER ) """) cursor.execute(""" CREATE TABLE IF NOT EXISTS albums ( id INTEGER PRIMARY KEY AUTOINCREMENT, name TEXT NOT NULL ) """) cursor.execute(""" CREATE TABLE IF NOT EXISTS categories ( id INTEGER PRIMARY KEY AUTOINCREMENT, name TEXT NOT NULL ) """) cursor.execute(""" CREATE TABLE IF NOT EXISTS pictures ( id INTEGER PRIMARY KEY AUTOINCREMENT, timestamp TEXT, file_path TEXT, file_name TEXT, album_id INTEGER, FOREIGN KEY (album_id) REFERENCES albums(id) ) """) cursor.execute(""" CREATE TABLE IF NOT EXISTS picture_categories ( picture_id INTEGER, category_id INTEGER, FOREIGN KEY (picture_id) REFERENCES pictures(id), FOREIGN KEY (category_id) REFERENCES categories(id), PRIMARY KEY (picture_id, category_id) ) """) conn.commit() def log_generation(args, optimized_prompt, image_file): file_path, file_name = os.path.split(image_file) try: with get_db_connection() as conn: cursor = conn.cursor() cursor.execute(""" INSERT INTO generation_logs ( timestamp, prompt, optimized_prompt, hf_lora, lora_scale, aspect_ratio, guidance_scale, output_quality, prompt_strength, num_inference_steps, output_file, album_id, category_id ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?) """, ( datetime.now().strftime("%Y-%m-%d %H:%M:%S"), args.prompt, optimized_prompt, args.hf_lora, args.lora_scale, args.aspect_ratio, args.guidance_scale, args.output_quality, args.prompt_strength, args.num_inference_steps, image_file, args.album_id, args.category_id )) picture_id = cursor.lastrowid cursor.execute(""" INSERT INTO pictures ( timestamp, file_path, file_name, album_id ) VALUES (?, ?, ?, ?) """, ( datetime.now().strftime("%Y-%m-%d %H:%M:%S"), file_path, file_name, args.album_id )) picture_id = cursor.lastrowid # Insert multiple categories for category_id in args.category_ids: cursor.execute(""" INSERT INTO picture_categories (picture_id, category_id) VALUES (?, ?) """, (picture_id, category_id)) conn.commit() except sqlite3.Error as e: print(f"Error logging generation: {e}") @app.on_event("startup") def startup_event(): initialize_database() @app.get("/") def read_root(request: Request): with get_db_connection() as conn: cursor = conn.cursor() cursor.execute("SELECT id, name FROM albums") albums = cursor.fetchall() cursor.execute("SELECT id, name FROM categories") categories = cursor.fetchall() return templates.TemplateResponse("index.html", {"request": request, "albums": albums, "categories": categories}) @app.get("/archive") def read_archive( request: Request, album: Optional[str] = Query(None), category: Optional[List[str]] = Query(None), search: Optional[str] = None, items_per_page: int = Query(30), page: int = Query(1) ): album_id = int(album) if album and album.isdigit() else None category_ids = [int(cat) for cat in category] if category else [] offset = (page - 1) * items_per_page with get_db_connection() as conn: cursor = conn.cursor() query = """ SELECT gl.timestamp, gl.prompt, gl.optimized_prompt, gl.output_file, a.name as album, c.name as category FROM generation_logs gl LEFT JOIN albums a ON gl.album_id = a.id LEFT JOIN categories c ON gl.category_id = c.id WHERE 1=1 """ params = [] if album_id is not None: query += " AND gl.album_id = ?" params.append(album_id) if category_ids: query += " AND gl.category_id IN ({})".format(','.join('?' for _ in category_ids)) params.extend(category_ids) if search: query += " AND (gl.prompt LIKE ? OR gl.optimized_prompt LIKE ?)" params.append(f'%{search}%') params.append(f'%{search}%') query += " ORDER BY gl.timestamp DESC LIMIT ? OFFSET ?" params.extend([items_per_page, offset]) cursor.execute(query, params) logs = cursor.fetchall() logs = [{ "timestamp": log[0], "prompt": log[1], "optimized_prompt": log[2], "output_file": log[3], "album": log[4], "category": log[5] } for log in logs] cursor.execute("SELECT id, name FROM albums") albums = cursor.fetchall() cursor.execute("SELECT id, name FROM categories") categories = cursor.fetchall() return templates.TemplateResponse("archive.html", { "request": request, "logs": logs, "albums": albums, "categories": categories, "selected_album": album, "selected_categories": category_ids, "search_query": search, "items_per_page": items_per_page, "page": page }) @app.get("/backend") def read_backend(request: Request): with get_db_connection() as conn: cursor = conn.cursor() cursor.execute("SELECT id, name FROM albums") albums = cursor.fetchall() cursor.execute("SELECT id, name FROM categories") categories = cursor.fetchall() return templates.TemplateResponse("backend.html", {"request": request, "albums": albums, "categories": categories}) @app.post("/create_album") def create_album(name: str = Form(...)): try: with get_db_connection() as conn: cursor = conn.cursor() cursor.execute("INSERT INTO albums (name) VALUES (?)", (name,)) conn.commit() return {"message": "Album erstellt"} except sqlite3.Error as e: raise HTTPException(status_code=500, detail=f"Error creating album: {e}") @app.post("/create_category") def create_category(name: str = Form(...)): try: with get_db_connection() as conn: cursor = conn.cursor() cursor.execute("INSERT INTO categories (name) VALUES (?)", (name,)) conn.commit() return {"message": "Kategorie erstellt"} except sqlite3.Error as e: raise HTTPException(status_code=500, detail=f"Error creating category: {e}") @app.post("/flux-pics") async def download_images(request: Request): try: body = await request.json() print(f"Received request body: {body}") # Debug log image_files = body.get("selectedImages", []) if not image_files: raise HTTPException(status_code=400, detail="Keine Bilder ausgewählt.") print(f"Processing image files: {image_files}") # Debug log # Überprüfe ob Download-Verzeichnis existiert if not os.path.exists(IMAGE_STORAGE_PATH): print(f"Storage path not found: {IMAGE_STORAGE_PATH}") # Debug log raise HTTPException(status_code=500, detail="Storage path not found") zip_buffer = BytesIO() with zipfile.ZipFile(zip_buffer, "w", zipfile.ZIP_DEFLATED) as zip_file: for image_file in image_files: image_path = os.path.join(IMAGE_STORAGE_PATH, image_file) print(f"Processing file: {image_path}") # Debug log if os.path.exists(image_path): zip_file.write(image_path, arcname=image_file) else: print(f"File not found: {image_path}") # Debug log raise HTTPException(status_code=404, detail=f"Bild {image_file} nicht gefunden.") zip_buffer.seek(0) # Korrekter Response mit Buffer return Response( content=zip_buffer.getvalue(), media_type="application/zip", headers={ "Content-Disposition": f"attachment; filename=images.zip" } ) except Exception as e: print(f"Error in download_images: {str(e)}") # Debug log raise HTTPException(status_code=500, detail=str(e)) @app.post("/flux-pics/single") async def download_single_image(request: Request): try: data = await request.json() filename = data.get("filename") print(f"Requested file download: {filename}") # Debug log if not filename: print("No filename provided") # Debug log raise HTTPException(status_code=400, detail="Kein Dateiname angegeben") file_path = os.path.join(IMAGE_STORAGE_PATH, filename) print(f"Full file path: {file_path}") # Debug log if not os.path.exists(file_path): print(f"File not found: {file_path}") # Debug log raise HTTPException(status_code=404, detail=f"Datei {filename} nicht gefunden") # Determine MIME type file_extension = filename.lower().split('.')[-1] mime_types = { 'png': 'image/png', 'jpg': 'image/jpeg', 'jpeg': 'image/jpeg', 'gif': 'image/gif', 'webp': 'image/webp' } media_type = mime_types.get(file_extension, 'application/octet-stream') print(f"Serving file with media type: {media_type}") # Debug log return FileResponse( path=file_path, filename=filename, media_type=media_type, headers={ "Content-Disposition": f"attachment; filename={filename}" } ) except Exception as e: print(f"Error in download_single_image: {str(e)}") # Debug log raise HTTPException(status_code=500, detail=str(e)) @app.websocket("/ws") async def websocket_endpoint(websocket: WebSocket): await websocket.accept() try: data = await websocket.receive_json() prompts = data.get("prompts", [data]) for prompt_data in prompts: prompt_data['lora_scale'] = float(prompt_data['lora_scale']) prompt_data['guidance_scale'] = float(prompt_data['guidance_scale']) prompt_data['prompt_strength'] = float(prompt_data['prompt_strength']) prompt_data['num_inference_steps'] = int(prompt_data['num_inference_steps']) prompt_data['num_outputs'] = int(prompt_data['num_outputs']) prompt_data['output_quality'] = int(prompt_data['output_quality']) # Handle new album and category creation album_name = prompt_data.get('album_id') category_names = prompt_data.get('category_ids', []) if album_name and not album_name.isdigit(): with get_db_connection() as conn: cursor = conn.cursor() cursor.execute("INSERT INTO albums (name) VALUES (?)", (album_name,)) conn.commit() prompt_data['album_id'] = cursor.lastrowid else: prompt_data['album_id'] = int(album_name) if album_name else None category_ids = [] for category_name in category_names: if not category_name.isdigit(): with get_db_connection() as conn: cursor = conn.cursor() cursor.execute("INSERT INTO categories (name) VALUES (?)", (category_name,)) conn.commit() category_ids.append(cursor.lastrowid) else: category_ids.append(int(category_name) if category_name else None) prompt_data['category_ids'] = category_ids args = argparse.Namespace(**prompt_data) await websocket.send_json({"message": "Optimiere Prompt..."}) optimized_prompt = optimize_prompt(args.prompt) if getattr(args, 'agent', False) else args.prompt await websocket.send_json({"optimized_prompt": optimized_prompt}) if prompt_data.get("optimize_only"): continue await generate_and_download_image(websocket, args, optimized_prompt) except WebSocketDisconnect: print("Client disconnected") except Exception as e: await websocket.send_json({"message": str(e)}) raise e finally: await websocket.close() async def fetch_image(item, index, args, filenames, semaphore, websocket, timestamp): async with semaphore: try: response = requests.get(item, timeout=TIMEOUT_DURATION) if response.status_code == 200: filename = f"{DOWNLOAD_DIR}/image_{timestamp}_{index}.{args.output_format}" with open(filename, "wb") as file: file.write(response.content) filenames.append(f"/flux-pics/image_{timestamp}_{index}.{args.output_format}") progress = int((index + 1) / args.num_outputs * 100) await websocket.send_json({"progress": progress}) else: await websocket.send_json({"message": f"Fehler beim Herunterladen des Bildes {index + 1}: {response.status_code}"}) except requests.exceptions.Timeout: await websocket.send_json({"message": f"Timeout beim Herunterladen des Bildes {index + 1}"}) async def generate_and_download_image(websocket: WebSocket, args, optimized_prompt): try: input_data = { "prompt": optimized_prompt, "hf_lora": getattr(args, 'hf_lora', None), # Use getattr to safely access hf_lora "lora_scale": args.lora_scale, "num_outputs": args.num_outputs, "aspect_ratio": args.aspect_ratio, "output_format": args.output_format, "guidance_scale": args.guidance_scale, "output_quality": args.output_quality, "prompt_strength": args.prompt_strength, "num_inference_steps": args.num_inference_steps, "disable_safety_checker": False } await websocket.send_json({"message": "Generiere Bilder..."}) # Debug: Log the start of the replication process print(f"Starting replication process for {args.num_outputs} outputs with timeout {TIMEOUT_DURATION}") output = replicate.run( "lucataco/flux-dev-lora:091495765fa5ef2725a175a57b276ec30dc9d39c22d30410f2ede68a3eab66b3", input=input_data, timeout=TIMEOUT_DURATION ) if not os.path.exists(DOWNLOAD_DIR): os.makedirs(DOWNLOAD_DIR) timestamp = datetime.now().strftime("%Y%m%d_%H%M%S") filenames = [] semaphore = Semaphore(3) # Limit concurrent downloads tasks = [create_task(fetch_image(item, index, args, filenames, semaphore, websocket, timestamp)) for index, item in enumerate(output)] await gather(*tasks) for file in filenames: log_generation(args, optimized_prompt, file) await websocket.send_json({"message": "Bilder erfolgreich generiert", "generated_files": filenames}) except requests.exceptions.Timeout: await websocket.send_json({"message": "Fehler bei der Bildgenerierung: Timeout überschritten"}) except Exception as e: await websocket.send_json({"message": f"Fehler bei der Bildgenerierung: {str(e)}"}) raise Exception(f"Fehler bei der Bildgenerierung: {str(e)}") def optimize_prompt(prompt): api_key = os.environ.get("MISTRAL_API_KEY") agent_id = os.environ.get("MISTRAL_FLUX_AGENT") if not api_key or not agent_id: raise ValueError("MISTRAL_API_KEY oder MISTRAL_FLUX_AGENT nicht gesetzt") client = Mistral(api_key=api_key) chat_response = client.agents.complete( agent_id=agent_id, messages=[{"role": "user", "content": f"Optimiere folgenden Prompt für Flux Lora: {prompt}"}] ) return chat_response.choices[0].message.content if __name__ == "__main__": # Parse command line arguments parser = argparse.ArgumentParser(description="Beschreibung") parser.add_argument('--hf_lora', default=None, help='HF LoRA Model') args = parser.parse_args() # Pass arguments to the FastAPI application app.state.args = args # Run the Uvicorn server # uvicorn.run(app, host="0.0.0.0", port=8000, timeout_keep_alive=900) # Run server uvicorn.run( "main:app", host="0.0.0.0", port=8000, reload=True, log_level="debug" )