generate api endpoints allow set model

Signed-off-by: Vladimir Mandic <mandic00@live.com>

CHANGELOG.md

@@ -111,6 +111,8 @@ SD.Next will warn on startup on unused cache entries that can be removed. Also,
 - **API**
   - add `/sdapi/v1/checkpoint` POST endpoint to simply load a model  
   - add `/sdapi/v1/modules` GET endpoint to get info on model components/modules  
+  - all generate endpoints now support `sd_model_checkpoint` parameter  
+    this allows to specify which model to use for generation without needing to use additional endpoints  
 - **Refactor**
   - change default huggingface cache folder from system default to `models/huggingface`  
     sd.next will warn on startup on unused cache entries  

modules/processing.py

@@ -119,6 +119,9 @@ def process_images(p: StableDiffusionProcessing) -> Processed:
     if not hasattr(p.sd_model, 'sd_checkpoint_info'):
         shared.log.error('Processing: incomplete model')
         return None
+    if p.abort:
+        shared.log.debug('Processing: aborted')
+        return None
     if p.scripts is not None and isinstance(p.scripts, scripts_manager.ScriptRunner):
         p.scripts.before_process(p)
     stored_opts = {}

modules/processing_class.py

@@ -15,6 +15,7 @@ debug = shared.log.trace if os.environ.get('SD_PROCESS_DEBUG', None) is not None
 @dataclass(repr=False)
 class StableDiffusionProcessing:
     def __init__(self,
+                 sd_model_checkpoint: str = None, # # used only to set sd_model
                  sd_model=None, # pylint: disable=unused-argument # local instance of sd_model
                  # base params
                  prompt: str = "",
@@ -355,6 +356,17 @@ class StableDiffusionProcessing:
         self.prompt_attention_masks = []
         self.negative_prompt_attention_mask = []
         self.xyz = xyz
+        self.abort = False
+
+        # set model
+        if sd_model_checkpoint is not None and len(sd_model_checkpoint) > 0:
+            from modules import sd_checkpoint
+            if sd_checkpoint.select_checkpoint(op='model', sd_model_checkpoint=sd_model_checkpoint) is None:
+                shared.log.error(f'Processing: model="{sd_model_checkpoint}" not found')
+                self.abort = True
+            else:
+                shared.opts.sd_model_checkpoint = sd_model_checkpoint
+                sd_models.reload_model_weights()
 
     def __str__(self):
         return f'{self.__class__.__name__}: {self.__dict__}'

modules/sd_checkpoint.py

@@ -269,8 +269,8 @@ def model_hash(filename):
         return 'NOHASH'
 
 
-def select_checkpoint(op='model'):
-    model_checkpoint = shared.opts.data.get('sd_model_refiner', None) if op == 'refiner' else shared.opts.data.get('sd_model_checkpoint', None)
+def select_checkpoint(op='model', sd_model_checkpoint=None):
+    model_checkpoint = sd_model_checkpoint or (shared.opts.data.get('sd_model_refiner', None) if op == 'refiner' else shared.opts.data.get('sd_model_checkpoint', None))
     if model_checkpoint is None or model_checkpoint == 'None' or len(model_checkpoint) < 3:
         return None
     checkpoint_info = get_closet_checkpoint_match(model_checkpoint)