adjust basic api

Author: phDoll

basic_api.py

@@ -33,40 +33,6 @@ def open_websocket_connection():
 # ---------------------------------------------------------------------------------------------------------------------
 # Basic API calls
 
-def upload_image(input_path, name, server_address, image_type="input", overwrite=False):
-  """
-  Uploads an image to ComfyUI using multipart/form-data encoding.
-
-  This function opens an image file from the specified path and uploads it to running ComfyUI. The server's address,
-  the name to save the image as, and optional parameters for image type and overwrite behavior are provided as arguments.
-  The image is uploaded as 'image/png'.
-
-  Args:
-    input_path (str): The file system path to the image file to be uploaded.
-    name (str): The name under which the image will be saved on ComfyUI.
-    server_address (str): The address of running ComfyUI where the image will be uploaded, excluding the protocol prefix.
-    image_type (str, optional): The type/category of the image being uploaded. Defaults to "input". Other options are "output" and "temp".
-    overwrite (bool, optional): Flag indicating whether an existing file with the same name should be overwritten.
-                                  Defaults to False.
-
-  Returns:
-    The ComfyUI response to the upload request.
-  """
-  with open(input_path, 'rb') as file:
-    multipart_data = MultipartEncoder(
-      fields= {
-        'image': (name, file, 'image/png'),
-        'type': image_type,
-        'overwrite': str(overwrite).lower()
-      }
-    )
-
-    data = multipart_data
-    headers = { 'Content-Type': multipart_data.content_type }
-    request = urllib.request.Request("http://{}/upload/image".format(server_address), data=data, headers=headers)
-    with urllib.request.urlopen(request) as response:
-      return response.read()
-
 def queue_prompt(prompt, client_id, server_address):
   """
   Sends a prompt to a ComfyUI to place it into the workflow queue
@@ -89,6 +55,26 @@ def queue_prompt(prompt, client_id, server_address):
   req =  urllib.request.Request("http://{}/prompt".format(server_address), data=data, headers=headers)
   return json.loads(urllib.request.urlopen(req).read())
 
+
+
+def get_history(prompt_id, server_address):
+  """
+  Fetches the history to a given prompt ID from ComfyUI
+
+  This function makes an HTTP GET request to a specified server address, requesting the history associated with
+  a given prompt ID. The server is expected to return a JSON response that contains the history data, that
+  include e.g the paths to the generated Images
+
+  Args:
+    prompt_id (str): The unique identifier for the prompt whose history is being requested.
+    server_address (str): The address of ComfyUI from which to retrieve the history, excluding the protocol prefix.
+
+  Returns:
+    A dictionary parsed from the JSON response containing the history associated with the specified prompt ID.
+  """
+  with urllib.request.urlopen("http://{}/history/{}".format(server_address, prompt_id)) as response:
+      return json.loads(response.read())
+
 def get_image(filename, subfolder, folder_type, server_address):
   """
   Retrieves an image from ComfyUI based on specified parameters and returns the image data.
@@ -111,23 +97,39 @@ def get_image(filename, subfolder, folder_type, server_address):
   with urllib.request.urlopen("http://{}/view?{}".format(server_address, url_values)) as response:
       return response.read()
 
-def get_history(prompt_id, server_address):
+def upload_image(input_path, name, server_address, image_type="input", overwrite=False):
   """
-  Fetches the history to a given prompt ID from ComfyUI
+  Uploads an image to ComfyUI using multipart/form-data encoding.
 
-  This function makes an HTTP GET request to a specified server address, requesting the history associated with
-  a given prompt ID. The server is expected to return a JSON response that contains the history data, that
-  include e.g the paths to the generated Images
+  This function opens an image file from the specified path and uploads it to running ComfyUI. The server's address,
+  the name to save the image as, and optional parameters for image type and overwrite behavior are provided as arguments.
+  The image is uploaded as 'image/png'.
 
   Args:
-    prompt_id (str): The unique identifier for the prompt whose history is being requested.
-    server_address (str): The address of ComfyUI from which to retrieve the history, excluding the protocol prefix.
+    input_path (str): The file system path to the image file to be uploaded.
+    name (str): The name under which the image will be saved on ComfyUI.
+    server_address (str): The address of running ComfyUI where the image will be uploaded, excluding the protocol prefix.
+    image_type (str, optional): The type/category of the image being uploaded. Defaults to "input". Other options are "output" and "temp".
+    overwrite (bool, optional): Flag indicating whether an existing file with the same name should be overwritten.
+                                  Defaults to False.
 
   Returns:
-    A dictionary parsed from the JSON response containing the history associated with the specified prompt ID.
+    The ComfyUI response to the upload request.
   """
-  with urllib.request.urlopen("http://{}/history/{}".format(server_address, prompt_id)) as response:
-      return json.loads(response.read())
+  with open(input_path, 'rb') as file:
+    multipart_data = MultipartEncoder(
+      fields= {
+        'image': (name, file, 'image/png'),
+        'type': image_type,
+        'overwrite': str(overwrite).lower()
+      }
+    )
+
+    data = multipart_data
+    headers = { 'Content-Type': multipart_data.content_type }
+    request = urllib.request.Request("http://{}/upload/image".format(server_address), data=data, headers=headers)
+    with urllib.request.urlopen(request) as response:
+      return response.read()
 
 # -------------------------------------------------------------------------------------------------------
 # API helper
@@ -184,7 +186,7 @@ def generate_image_by_prompt_and_image(prompt, output_path, input_path, filename
   """
   try:
     ws, server_address, client_id = open_websocket_connection()
-    upload_image(input_path, filename, server_address, client_id)
+    upload_image(input_path, filename, server_address)
     prompt_id = queue_prompt(prompt, client_id, server_address)['prompt_id']
     track_progress(prompt, ws, prompt_id)
     images = get_images(prompt_id, server_address, save_previews)
@@ -371,9 +373,9 @@ def prompt_to_image(workflow, positve_prompt, negative_prompt='', save_previews=
 
   if negative_prompt != '':
     negative_input_id = prompt.get(k_sampler)['inputs']['negative'][0]
-    prompt.get(negative_input_id)['inputs']['text'] = positve_prompt
+    prompt.get(negative_input_id)['inputs']['text'] = negative_prompt
 
-  generate_image_by_prompt(prompt, './output/', save_previews)
+  generate_image_by_prompt(prompt, './output/blog/cyborg', save_previews)
 
 def prompt_image_to_image(workflow, input_path, positve_prompt, negative_prompt='', save_previews=False):
   """
@@ -403,20 +405,21 @@ def prompt_image_to_image(workflow, input_path, positve_prompt, negative_prompt=
   k_sampler = [key for key, value in id_to_class_type.items() if value == 'KSampler'][0]
   prompt.get(k_sampler)['inputs']['seed'] = random.randint(10**14, 10**15 - 1)
   postive_input_id = prompt.get(k_sampler)['inputs']['positive'][0]
-  prompt.get(postive_input_id)['inputs']['text_g'] = positve_prompt
-  prompt.get(postive_input_id)['inputs']['text_l'] = positve_prompt
+  prompt.get(postive_input_id)['inputs']['text'] = positve_prompt
 
   if negative_prompt != '':
     negative_input_id = prompt.get(k_sampler)['inputs']['negative'][0]
-    id_to_class_type.get(negative_input_id)['inputs']['text_g'] = negative_prompt
-    id_to_class_type.get(negative_input_id)['inputs']['text_l'] = negative_prompt
+    prompt.get(negative_input_id)['inputs']['text'] = negative_prompt
 
   image_loader = [key for key, value in id_to_class_type.items() if value == 'LoadImage'][0]
   filename = input_path.split('/')[-1]
   prompt.get(image_loader)['inputs']['image'] = filename
 
-  generate_image_by_prompt_and_image(prompt, './output/', input_path, filename, save_previews)
+  generate_image_by_prompt_and_image(prompt, './output/blog/img2img', input_path, filename, save_previews)
 
 
 workflow = load_workflow('./workflows/base_workflow.json')
-prompt_to_image(workflow, 'Woman standing in a red dress in the middle of a crowded place with high skyscrapers', 'lowres, branding, watermark', save_previews=True)
+prompt_to_image(workflow, 'Cyborg in the cyberspace connection to different interfaces and screens with wires, cinematic, colorful, black and neon turquioise', 'ugly, lowres, text, branding', save_previews=True)
+# input_path = './input/ComfyUI_00299_.png'
+# for iter in range(1, 6):
+  # prompt_image_to_image(workflow, input_path, 'Woman in a red dress standing in middle of a crowded place, skyscrapers in the background, cinematic, dark colors, distopian', save_previews=True)