feat: Horde will now return information about potential problems

CHANGELOG.md

@@ -1,5 +1,9 @@
 # Changelog
 
+# 4.33.0
+
+* When there is any potential issues with the request, the warnings key will be returned containing an array of potential issues. This should be returned to the user to inform them to potentially cancel the request in advance.
+
 # 4.32.5
 
 * parses url-escaped values for model names

horde/apis/models/v2.py

@@ -2,6 +2,7 @@
 
 from horde.exceptions import KNOWN_RC
 from horde.vars import horde_noun, horde_title
+from horde.enums import WarningMessage
 
 
 class Parsers:
@@ -309,6 +310,18 @@ def __init__(self, api):
                 "generations": fields.List(fields.Nested(self.response_model_generation_result)),
             },
         )
+        self.response_model_warning = api.model(
+            "RequestSingleWarning",
+            {
+                "code": fields.String(
+                    description="A unique identifier for this warning.",
+                    enum=[i.name for i in WarningMessage]
+                ),
+                "message": fields.String(
+                    description="Something that you should be aware about this request, in plain text.",
+                ),
+            },
+        )        
         self.response_model_async = api.model(
             "RequestAsync",
             {
@@ -320,6 +333,7 @@ def __init__(self, api):
                     default=None,
                     description="Any extra information from the horde about this request.",
                 ),
+                "warnings": fields.List(fields.Nested(self.response_model_warning)),
             },
         )
         self.response_model_generation_payload = api.model(

horde/apis/v2/base.py

@@ -114,6 +114,7 @@ def post(self):
         # I have to extract and store them this way, because if I use the defaults
         # It causes them to be a shared object from the parsers class
         self.params = {}
+        self.warnings = set()
         if self.args.params:
             self.params = self.args.params
         self.models = []

horde/apis/v2/stable.py

@@ -30,6 +30,7 @@
 from horde.patreon import patrons
 from horde.utils import hash_dictionary
 from horde.vars import horde_title
+from horde.enums import WarningMessage
 
 models = ImageModels(api)
 parsers = ImageParsers()
@@ -82,10 +83,13 @@ def post(self):
             return ret_dict, 200
         ret_dict = {
             "id": self.wp.id,
-            "kudos": round(self.kudos),
+            "kudos": round(self.kudos),            
         }
         if not database.wp_has_valid_workers(self.wp) and not settings.mode_raid():
             ret_dict["message"] = self.get_size_too_big_message()
+            self.warnings.add(WarningMessage.NoAvailableWorker)
+        if len(self.warnings) > 0:
+            ret_dict["warnings"] = list(self.warnings)
         return ret_dict, 202
 
     def get_size_too_big_message(self):
@@ -131,6 +135,19 @@ def validate(self):
             model_reference.get_model_baseline(model_name).startswith("stable diffusion 2") for model_name in self.args.models
         ):
             raise e.UnsupportedModel("No current model available for this particular ControlNet for SD2.x", rc="ControlNetUnsupported")
+        for model_req_dict in [model_reference.get_model_requirements(m) for m in self.args.models]:
+            if "clip_skip" in model_req_dict and model_req_dict["clip_skip"] != self.params.get("clip_skip", 1):
+                self.warnings.add(WarningMessage.ClipSkipMismatch)
+            if "min_steps" in model_req_dict and model_req_dict["min_steps"] > self.params.get("steps", 30):
+                self.warnings.add(WarningMessage.StepsTooFew)
+            if "max_steps" in model_req_dict and model_req_dict["max_steps"] < self.params.get("steps", 30):
+                self.warnings.add(WarningMessage.StepsTooMany)
+            if "cfg_scale" in model_req_dict and model_req_dict["cfg_scale"] != self.params.get("cfg_scale", 7.5):
+                self.warnings.add(WarningMessage.CfgScaleMismatch)
+            if "min_cfg_scale" in model_req_dict and model_req_dict["min_cfg_scale"] > self.params.get("cfg_scale", 7.5):
+                self.warnings.add(WarningMessage.CfgScaleTooSmall)
+            if "max_cfg_scale" in model_req_dict and model_req_dict["max_cfg_scale"] < self.params.get("cfg_scale", 7.5):
+                self.warnings.add(WarningMessage.CfgScaleTooLarge)
         if "control_type" in self.params and any(model_name in ["pix2pix"] for model_name in self.args.models):
             raise e.UnsupportedModel("You cannot use ControlNet with these models.", rc="ControlNetUnsupported")
         # if self.params.get("image_is_control"):

horde/consts.py

@@ -1,4 +1,4 @@
-HORDE_VERSION = "4.32.5"
+HORDE_VERSION = "4.33.0"
 
 WHITELISTED_SERVICE_IPS = {
     "212.227.227.178",  # Turing Bot

horde/enums.py

@@ -33,3 +33,26 @@ class UserRoleTypes(enum.Enum):
     SPECIAL = 6
     SERVICE = 7
     EDUCATION = 8
+
+class ReturnedEnum(enum.Enum):
+
+    @property
+    def code(self):
+        return self.name
+
+    @property
+    def message(self):
+        return self.value
+
+class WarningMessage(ReturnedEnum):
+    NoAvailableWorker = (
+            "Warning: No available workers can fulfill this request. "
+            "It will expire in 20 minutes unless a worker appears. "
+            "Please confider reducing its size of the request or choosing a different model."
+        )
+    ClipSkipMismatch = "The clip skip specified for this generation does not match the requirements of one of the requested models."
+    StepsTooFew = "The steps specified for this generation are too few for this model."
+    StepsTooMany = "The steps specified for this generation are too many for this model."
+    CfgScaleMismatch = "The cfg scale specified for this generation does not match the requirements of one of the requested models."
+    CfgScaleTooSmall = "The cfg_scale specified for this generation is too small for this model."
+    CfgScaleTooLarge = "The cfg_scale specified for this generation is too large for this model."

horde/model_reference.py

@@ -18,12 +18,6 @@ class ModelReference(PrimaryTimedFunction):
     # However due to a racing or caching issue, this causes them to still pick jobs using those models
     # Need to investigate more to remove this workaround
     testing_models = {
-        "Juggernaut XL",
-        "Animagine XL",
-        "DreamShaper XL",
-        "Stable Cascade 1.0",
-        "Anime Illust Diffusion XL",
-        "Pony Diffusion XL",
     }
 
     def call_function(self):
@@ -94,6 +88,10 @@ def get_model_baseline(self, model_name):
         model_details = self.reference.get(model_name, {})
         return model_details.get("baseline", "stable diffusion 1")
 
+    def get_model_requirements(self, model_name):
+        model_details = self.reference.get(model_name, {})
+        return model_details.get("requirements", {})
+
     def get_model_csam_whitelist(self, model_name):
         model_details = self.reference.get(model_name, {})
         return set(model_details.get("csam_whitelist", []))