save code

basic_api.json

@@ -0,0 +1,107 @@
+{
+  "3": {
+    "inputs": {
+      "seed": 1071835675089409,
+      "steps": 20,
+      "cfg": 8,
+      "sampler_name": "euler",
+      "scheduler": "normal",
+      "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": "v1-5-pruned-emaonly-fp16.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": "masterpiece best quality girl",
+      "clip": [
+        "4",
+        1
+      ]
+    },
+    "class_type": "CLIPTextEncode",
+    "_meta": {
+      "title": "CLIP Text Encode (Prompt)"
+    }
+  },
+  "7": {
+    "inputs": {
+      "text": "bad hands",
+      "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"
+    }
+  }
+}

basic_api_example.py

@@ -0,0 +1,42 @@
+import json
+from urllib import request
+
+#This is the ComfyUI api prompt format.
+
+#If you want it for a specific workflow you can "enable dev mode options"
+#in the settings of the UI (gear beside the "Queue Size: ") this will enable
+#a button on the UI to save workflows in api format.
+
+#keep in mind ComfyUI is pre alpha software so this format will change a bit.
+
+#this is the one for the default workflow
+
+def queue_prompt(prompt):
+    p = {"prompt": prompt}
+
+    # If the workflow contains API nodes, you can add a Comfy API key to the `extra_data`` field of the payload.
+    # p["extra_data"] = {
+    #     "api_key_comfy_org": "comfyui-87d01e28d*******************************************************"  # replace with real key
+    # }
+    # See: https://docs.comfy.org/tutorials/api-nodes/overview
+    # Generate a key here: https://platform.comfy.org/login
+
+    data = json.dumps(p).encode('utf-8')
+    req =  request.Request("http://127.0.0.1:8188/prompt", data=data)
+    request.urlopen(req)
+
+
+with open('/home/szlc/basic_api.json', 'r', encoding='utf-8') as file:
+    prompt_text = file.read()
+
+prompt = json.loads(prompt_text)
+#set the text prompt for our positive CLIPTextEncode
+prompt["6"]["inputs"]["text"] = "masterpiece best quality man"
+
+#set the seed for our KSampler node
+prompt["3"]["inputs"]["seed"] = 5
+
+
+queue_prompt(prompt)
+
+

websockets_api_example.py

@@ -55,101 +55,9 @@ def get_images(ws, prompt):
 
     return output_images
 
-prompt_text = """
+with open('/home/szlc/websocket_script.json', 'r', encoding='utf-8') as file:
-{
+    prompt_text = file.read()
-    "3": {
-        "class_type": "KSampler",
-        "inputs": {
-            "cfg": 8,
-            "denoise": 1,
-            "latent_image": [
-                "5",
-                0
-            ],
-            "model": [
-                "4",
-                0
-            ],
-            "negative": [
-                "7",
-                0
-            ],
-            "positive": [
-                "6",
-                0
-            ],
-            "sampler_name": "euler",
-            "scheduler": "normal",
-            "seed": 8566257,
-            "steps": 20
-        }
-    },
-    "4": {
-        "class_type": "CheckpointLoaderSimple",
-        "inputs": {
-            "ckpt_name": "v1-5-pruned-emaonly.safetensors"
-        }
-    },
-    "5": {
-        "class_type": "EmptyLatentImage",
-        "inputs": {
-            "batch_size": 1,
-            "height": 512,
-            "width": 512
-        }
-    },
-    "6": {
-        "class_type": "CLIPTextEncode",
-        "inputs": {
-            "clip": [
-                "4",
-                1
-            ],
-            "text": "masterpiece best quality girl"
-        }
-    },
-    "7": {
-        "class_type": "CLIPTextEncode",
-        "inputs": {
-            "clip": [
-                "4",
-                1
-            ],
-            "text": "bad hands"
-        }
-    },
-    "8": {
-        "class_type": "VAEDecode",
-        "inputs": {
-            "samples": [
-                "3",
-                0
-            ],
-            "vae": [
-                "4",
-                2
-            ]
-        }
-    },
-    "9": {
-        "class_type": "SaveImage",
-        "inputs": {
-            "filename_prefix": "ComfyUI",
-            "images": [
-                "8",
-                0
-            ]
-        }
-    }
-}
-"""
-
 prompt = json.loads(prompt_text)
-#set the text prompt for our positive CLIPTextEncode
-prompt["6"]["inputs"]["text"] = "masterpiece best quality man"
-
-#set the seed for our KSampler node
-prompt["3"]["inputs"]["seed"] = 5
 
 ws = websocket.WebSocket()
 ws.connect("ws://{}/ws?clientId={}".format(server_address, client_id))