added files

text2image/main.py

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+from text2image import GenerateImage, Nodes, ComfyUIGenerateImageForm, load_workflow
+import random
+
+if __name__ == "__main__":
+
+    base_url = "http://172.22.0.29:8188"
+    client_id = "test_client"
+    image_file_name = "test.png"
+    image_file_folder = "CodeNight/text2image/images"
+    workflow_json = load_workflow("CodeNight/text2image/malerisch.json")
+    nodes = Nodes(
+        prompt=6,
+        negative_prompt=7,
+        width=5,
+        height=5,
+        seed=3,
+        steps=3
+    )
+    payload = ComfyUIGenerateImageForm(
+        workflow=workflow_json,
+        nodes=nodes,
+    #    prompt="fashion photography of 23 y.o blonde woman, beautiful makeup, wearing dot dress, 35mm",
+    #    prompt="b/w fashion photography of 23 y.o black man, instgram, 35mm",
+    #    prompt="Cyberpunk android with glowing eyes, beautiful face, urban background, neon accents, high-tech, realistic style.",
+    #    prompt="Cyberpunk rooftop scene, overlooking city, neon lights, futuristic skyline, atmospheric style.",
+        prompt="A goat with sun glasses on a skateboard. realistic. skatepark, sunny day. 35mm",
+        width=768,
+        height=768,
+        negative_prompt=" (octane render, render, drawing, anime, bad photo, bad photography:1.3), (worst quality, low quality, blurry:1.2), (bad teeth, deformed teeth, deformed lips), (bad anatomy, bad proportions:1.1), (deformed iris, deformed pupils), (deformed eyes, bad eyes), (deformed face, ugly face, bad face), (deformed hands, bad hands, fused fingers), morbid, mutilated, mutation, disfigured",
+        seed=random.randint(0, 1125899906842624),
+        steps=30
+    )
+    
+    GenerateImage(payload, client_id, base_url, image_file_folder, image_file_name)

text2image/main_gradio.py

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+from text2image import GenerateImage, Nodes, ComfyUIGenerateImageForm, load_workflow
+import random, os, gradio
+
+def generate(prompt: str):
+    base_url = "http://172.22.0.29:8188"
+    client_id = "test_client"
+    image_file_name = "test.png"
+    image_file_folder = "CodeNight/text2image/images"
+    workflow_json = load_workflow("CodeNight/text2image/malerisch.json")
+    nodes = Nodes(
+        prompt=6,
+        negative_prompt=7,
+        width=5,
+        height=5,
+        seed=3,
+        steps=3
+    )
+    payload = ComfyUIGenerateImageForm(
+        workflow=workflow_json,
+        nodes=nodes,
+    #    prompt="fashion photography of 23 y.o blonde woman, beautiful makeup, wearing dot dress, 35mm",
+    #    prompt="b/w fashion photography of 23 y.o black man, instgram, 35mm",
+    #    prompt="Cyberpunk android with glowing eyes, beautiful face, urban background, neon accents, high-tech, realistic style.",
+    #    prompt="Cyberpunk rooftop scene, overlooking city, neon lights, futuristic skyline, atmospheric style.",
+    #    prompt="A goat with sun glasses on a skateboard. realistic. skatepark, sunny day. 35mm",
+        prompt=prompt,
+        width=768,
+        height=768,
+        negative_prompt=" (octane render, render, drawing, anime, bad photo, bad photography:1.3), (worst quality, low quality, blurry:1.2), (bad teeth, deformed teeth, deformed lips), (bad anatomy, bad proportions:1.1), (deformed iris, deformed pupils), (deformed eyes, bad eyes), (deformed face, ugly face, bad face), (deformed hands, bad hands, fused fingers), morbid, mutilated, mutation, disfigured",
+        seed=random.randint(0, 1125899906842624),
+        steps=30
+    )
+    
+    GenerateImage(payload, client_id, base_url, image_file_folder, image_file_name)
+    return os.path.join(image_file_folder, image_file_name)
+
+with gradio.Blocks() as demo:
+    gradio.Markdown("# Meine erste Webanwendung")
+    with gradio.Row(equal_height=True):
+        textbox = gradio.Textbox(lines=1, show_label=False, placeholder="Gib hier deinen Prompt ein")
+        button = gradio.Button("Generate", variant="primary")
+    image = gradio.Image(height=768)
+
+    button.click(
+        generate,
+        inputs=textbox,
+        outputs=image
+    )
+
+
+if __name__ == "__main__":
+
+    demo.launch(share=True)

text2image/malerisch.json

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+{
+    "3": {
+      "inputs": {
+        "seed": 766408214160696,
+        "steps": 30,
+        "cfg": 2,
+        "sampler_name": "dpmpp_2m_sde_gpu",
+        "scheduler": "karras",
+        "denoise": 1,
+        "model": [
+          "4",
+          0
+        ],
+        "positive": [
+          "6",
+          0
+        ],
+        "negative": [
+          "7",
+          0
+        ],
+        "latent_image": [
+          "5",
+          0
+        ]
+      },
+      "class_type": "KSampler",
+      "_meta": {
+        "title": "KSampler"
+      }
+    },
+    "4": {
+      "inputs": {
+        "ckpt_name": "dreamshaper/realvis5xl.safetensors"
+      },
+      "class_type": "CheckpointLoaderSimple",
+      "_meta": {
+        "title": "Load Checkpoint"
+      }
+    },
+    "5": {
+      "inputs": {
+        "width": 512,
+        "height": 512,
+        "batch_size": 1
+      },
+      "class_type": "EmptyLatentImage",
+      "_meta": {
+        "title": "Empty Latent Image"
+      }
+    },
+    "6": {
+      "inputs": {
+        "text": "In the vast, untouched wilderness of Kanadensische Alpen, der Sonnenaufgang über einen Schneelandschaft mit Bergrücken und tiefen Schluchten warf einen goldenen Lichtschein, während die unberührte Natur in Stille und Frieden schlug.",
+        "clip": [
+          "4",
+          1
+        ]
+      },
+      "class_type": "CLIPTextEncode",
+      "_meta": {
+        "title": "CLIP Text Encode (Prompt)"
+      }
+    },
+    "7": {
+      "inputs": {
+        "text": "text, watermarks, pornography",
+        "clip": [
+          "4",
+          1
+        ]
+      },
+      "class_type": "CLIPTextEncode",
+      "_meta": {
+        "title": "CLIP Text Encode (Prompt)"
+      }
+    },
+    "8": {
+      "inputs": {
+        "samples": [
+          "3",
+          0
+        ],
+        "vae": [
+          "4",
+          2
+        ]
+      },
+      "class_type": "VAEDecode",
+      "_meta": {
+        "title": "VAE Decode"
+      }
+    },
+    "9": {
+      "inputs": {
+        "filename_prefix": "ComfyUI",
+        "images": [
+          "8",
+          0
+        ]
+      },
+      "class_type": "SaveImage",
+      "_meta": {
+        "title": "Save Image"
+      }
+    }
+  }

text2image/text2image.py

@@ -0,0 +1,134 @@
+import asyncio
+import json
+import random
+import requests
+import websocket
+import os
+from pydantic import BaseModel
+from typing import Optional
+   
+class Nodes(BaseModel):
+    prompt: int
+    width: int
+    height: int
+    negative_prompt: Optional[int] = None
+    seed: Optional[int] = None
+    steps: Optional[int] = None
+
+class ComfyUIGenerateImageForm(BaseModel):
+    workflow: str
+    prompt: str
+    nodes: Nodes
+    negative_prompt: Optional[str] = None
+    width: int
+    height: int
+    steps: Optional[int] = None
+    seed: Optional[int] = None
+
+class GenerateImage:
+    def __init__(self, payload, client_id, base_url, image_file_folder, image_file_name):
+        self.payload = payload
+        self.client_id = client_id
+        self.base_url = base_url
+        self.image_file_folder = image_file_folder
+        self.image_file_name = image_file_name
+        asyncio.run(self.__generate())
+
+    def save_image(self, image_url):
+        """Lädt ein Bild von einer URL herunter und speichert es im angegebenen Ordner mit dem gewünschten Dateinamen."""
+        response = requests.get(image_url, stream=True)
+
+        if response.status_code == 200:
+            os.makedirs(self.image_file_folder, exist_ok=True)  # Erstelle den Ordner, falls er nicht existiert
+            file_path = os.path.join(self.image_file_folder, self.image_file_name)
+
+            with open(file_path, "wb") as file:
+                for chunk in response.iter_content(1024):
+                    file.write(chunk)
+            
+            print(f"Bild gespeichert unter: {file_path}")
+        else:
+            print(f"Fehler beim Download des Bildes: {response.status_code}")
+
+    def get_image_url(self, filename, subfolder, img_type):
+        return f"{self.base_url}/view?filename={filename}&subfolder={subfolder}&type={img_type}"
+
+    def queue_prompt(self):
+        response = requests.post(
+            f"{self.base_url}/prompt",
+            json={"prompt": self.workflow, "client_id": self.client_id}, 
+            headers={"Authorization": f"Bearer "},
+        )
+        return response.json()
+
+    def get_history(self, prompt_id):
+        response = requests.get(
+            f"{self.base_url}/history/{prompt_id}",
+            headers={"Authorization": f"Bearer "},
+        )
+        return response.json()
+
+    def get_images(self, ws):
+        prompt_id = self.queue_prompt()["prompt_id"]
+        output_images = []
+        while True:
+            out = ws.recv()
+            if isinstance(out, str):
+                message = json.loads(out)
+                if message["type"] == "executing":
+                    data = message["data"]
+                    if data["node"] is None and data["prompt_id"] == prompt_id:
+                        break  # Execution is done
+            else:
+                continue  # previews are binary data
+
+        history = self.get_history(prompt_id)[prompt_id]
+        for node_id, node_output in history["outputs"].items():
+            if "images" in node_output:
+                for image in node_output["images"]:
+                    url = self.get_image_url(
+                        image["filename"], image["subfolder"], image["type"]
+                    )
+                    output_images.append({"url": url})
+        return {"data": output_images}
+
+
+    async def comfyui_generate_image(self):
+        ws_url = self.base_url.replace("http://", "ws://").replace("https://", "wss://")
+        self.workflow = json.loads(self.payload.workflow)
+        self.workflow[f"{self.payload.nodes.prompt}"]["inputs"]["text"] = self.payload.prompt
+        self.workflow[f"{self.payload.nodes.width}"]["inputs"]["width"] = self.payload.width
+        self.workflow[f"{self.payload.nodes.height}"]["inputs"]["height"] = self.payload.height
+        if self.payload.seed and self.payload.nodes.seed:
+            self.workflow[f"{self.payload.nodes.seed}"]["inputs"]["seed"] = self.payload.seed
+        if self.payload.steps and self.payload.nodes.steps:
+            self.workflow[f"{self.payload.nodes.steps}"]["inputs"]["steps"] = self.payload.steps
+        if self.payload.negative_prompt and self.payload.nodes.negative_prompt:
+            self.workflow[f"{self.payload.nodes.negative_prompt}"]["inputs"]["text"] = self.payload.negative_prompt       
+
+        try:
+            ws = websocket.WebSocket()
+            headers = {"Authorization": f"Bearer "}
+            ws.connect(f"{ws_url}/ws?clientId={self.client_id}", header=headers)
+        except Exception as e:
+            return None
+
+        try:
+            images = await asyncio.to_thread(self.get_images, ws)
+        except Exception as e:
+            images = None
+        finally:
+            ws.close()
+        return images
+
+    async def __generate(self):
+        images = await self.comfyui_generate_image()
+        if images and "data" in images and images["data"]:
+            image_url = images["data"][0]["url"]
+            self.save_image(image_url)
+
+def load_workflow(file_path):
+    with open(file_path, "r", encoding="utf-8") as file:
+        return file.read()
+
+