* Updated model support.

* Fixed some model identifiers that had uppercase letters.
* Fixed missing env_info refactoring in one node.
* Improved documentation.

docs/CONFIG.md

@@ -61,9 +61,9 @@ The outputs are lists, and in combinatorial/multiple modes there will be multipl
 
 The run_mode can be explained like this:
 
-* single: only one result is returned.
-* multiple: multiple results are returned, the count is in results_limit.
-* combinatorial: all the combinations are returned, up to results_limit.
+* **single**: only one result is returned.
+* **multiple**: multiple results are returned, the count is in results_limit.
+* **combinatorial**: all the combinations are returned, up to results_limit.
 
 In single and multiple modes the default choice sampler is the one set in default_sampler. In combinatorial mode the default sampling is equivalent to cyclical. In all modes specified samplers are respected. The value of random samplers in combinatorial mode depends on comb_random_fixed.
 
@@ -175,6 +175,18 @@ Options for extranetworks mapping, in case you want to change them from the defa
 * **Fix random sampler across combinations**: If checked all specified random samplers will have a fixed value across the combinations.
 * **Default sampler**: The default choice sampler when not specified.
 
+The `Run mode` can be explained like this:
+
+* **single**: only one result is returned (for each image).
+* **multiple**: multiple results are returned, the count is in `Results limit` (but limited by the number of images). The results are assigned to the images. If there are more images than results, the results wrap.
+* **combinatorial**: all the combinations are returned, up to `Results limit` (but limited by the number of images). The results are assigned to the images. If there are more images than results, the results wrap.
+
+In single and multiple modes the default choice sampler is the one set in `Default sampler`. In combinatorial mode the default sampling is equivalent to cyclical. In all modes specified samplers are respected. The value of random samplers in combinatorial mode depends on `Fix random sampler across combinations`.
+
+Multiple mode with a default of cyclical sampler is very similar to combinatorial. The only difference is that `Fix random sampler across combinations` does not apply and random samplers are thus not cached. There is no need for this mode with a random default sampler, since it would be the same as in single mode.
+
+Single mode with a default of cyclical sampler can be used as similar to combinatorial but in separated runs instead of one.
+
 ### General settings
 
 * **Debug level**: What to write to the console. Note: in *SD.Next* debug messages only show if you launch it with the `--debug` argument.

ppp_comfyui.py

@@ -472,7 +472,6 @@ class PromptPostProcessorComfyUINode:
             jobinfo={"job_timestamp": datetime.now().isoformat()},
         )
         self.ppp.process_prompts_group_end()
-
         return tuple(zip(*results))  # unzip the list of tuples into tuple of lists
 
     def interrupt(self):
@@ -996,13 +995,13 @@ class PromptPostProcessorWildcardConcatComfyUINode:
             lf = PromptPostProcessorLogFactory()
             cls._ppp = PromptPostProcessor(
                 lf.log,
-                {
-                    "app": SUPPORTED_APPS.comfyui.value,
-                    "models_path": folder_paths.models_dir,
-                    "model_filename": "",
-                    "model_class": "",
-                    "property_base": None,
-                },
+                PPPEnvInfo(
+                    app=SUPPORTED_APPS.comfyui,
+                    models_path=folder_paths.models_dir,
+                    model_filename="",
+                    model_class="",
+                    property_base=None,
+                ),
                 PPPStateOptions(debug_level=DEBUG_LEVEL.minimal),
                 wildcards_obj=PPPWildcards(lf.log),
             )

ppp_config.yaml.defaults

@@ -190,7 +190,7 @@ models:
             a1111: null
             forge: null
             forgeneo: null
-            reforge: null
+            reforge: { class: ["LTXV"] }
             sdnext: null
             comfyui: { class: ["LTXV", "LTXAV"] }
     cosmos: # Cosmos
@@ -341,11 +341,11 @@ models:
         detect:
             a1111: null
             forge: null
-            forgeneo: null
+            forgeneo: { class: ["Krea2"] }
             reforge: null
             sdnext: null
             comfyui: { class: ["Krea2"] }
-    Ideogram4: # Ideogram4
+    ideogram4: # Ideogram4
         detect:
             a1111: null
             forge: null
@@ -353,7 +353,7 @@ models:
             reforge: null
             sdnext: null
             comfyui: { class: ["Ideogram4"] }
-    Lens: # Lens
+    lens: # Lens
         detect:
             a1111: null
             forge: null
@@ -361,7 +361,7 @@ models:
             reforge: null
             sdnext: null
             comfyui: { class: ["Lens"] }
-    Boogu: # Boogu
+    boogu: # Boogu
         detect:
             a1111: null
             forge: null
@@ -369,3 +369,19 @@ models:
             reforge: null
             sdnext: null
             comfyui: { class: ["Boogu"] }
+    mageflow: # MageFlow
+        detect:
+            a1111: null
+            forge: null
+            forgeneo: null
+            reforge: null
+            sdnext: null
+            comfyui: { class: ["MageFlow"] }
+    pid: # PiD
+        detect:
+            a1111: null
+            forge: null
+            forgeneo: { class: ["PiD"] }
+            reforge: null
+            sdnext: null
+            comfyui: { class: ["PiD"] }