Feature/add-parameters (#6)

* safety_tolerance available on all models

* added validators and additional parameters

griptape/black_forest/drivers/black_forest_image_generation_driver.py

@@ -12,6 +12,40 @@
 from griptape.drivers import BaseImageGenerationDriver
 
 
+def steps_validator(instance, attribute, value):
+    if value and (value < 1 or value > 50):
+        raise ValueError("steps must be between 1 and 50")
+
+
+def size_validator(instance, attribute, value):
+    if value and value % 32 != 0:
+        raise ValueError(f"{attribute} must be a multiple of 32")
+    if value and value < 256 or value > 1440:
+        raise ValueError(f"{attribute} must be between 256 and 1440")
+
+
+def safety_validator(instance, attribute, value):
+    if value and (value < 0 or value > 6):
+        raise ValueError("safety_tolerance must be between 0 and 6")
+
+
+def aspect_ratio_validator(instance, attribute, value):
+    if value:
+        width, height = value.split(":")
+        if width < 9 or width > 21 or height < 9 or height > 21:
+            raise ValueError("aspect_ratio must be between 9:21 and 21:9")
+
+
+def guidance_validator(instance, attribute, value):
+    if value and (value < 1.5 or value > 5):
+        raise ValueError("guidance must be between 1.5 and 5")
+
+
+def interval_validator(instance, attribute, value):
+    if value and (value < 1 or value > 4):
+        raise ValueError("interval must be between 1 and 4")
+
+
 @define
 class BlackForestImageGenerationDriver(BaseImageGenerationDriver):
     """Driver for the Black Forest Labs image generation API.
@@ -22,11 +56,12 @@ class BlackForestImageGenerationDriver(BaseImageGenerationDriver):
         height: Height of the generated image. Valid for 'flux-pro-1.1', 'flux-pro', 'flux-dev' models only. Integer range from 256 to 1440. Must be a multiple of 32. Default is 1024.
         aspect_ratio: Aspect ratio of the generated image between 21:9 and 9:21. Valid for 'flux-pro-1.1-ultra' model only. Default is 16:9.
         prompt_upsampling: Optional flag to perform upsampling on the prompt. Valid for `flux-pro-1.1', 'flux-pro', 'flux-dev' models only. If active, automatically modifies the prompt for more creative generation.
-        safety_tolerance: Optional tolerance level for input and output moderation. Valid for 'flux-pro-1.1', 'flux-pro', 'flux-dev' models only. Between 0 and 6, 0 being most strict, 6 being least strict.
+        safety_tolerance: Optional tolerance level for input and output moderation. Between 0 and 6, 0 being most strict, 6 being least strict.
         seed: Optional seed for reproducing results. Default is None.
-        steps: Optional number of steps for the image generation process. Valid for 'flux-dev' model only. Default is None.
-
-
+        steps: Optional number of steps for the image generation process. Valid for 'flux-dev' and `flux-pro` models only. Can be a value between 1 and 50. Default is None.
+        guidance: Optional guidance scale for image generation. High guidance scales improve prompt adherence at the cost of reduced realism. Min: 1.5, max: 5. Valid for 'flux-dev' and 'flux-pro' models only.
+        interval: Optional interval parameter for guidance control. Valid for 'flux-pro' model only. Value is an integer between 1 and 4. Default is None.
+        raw: Optional flag to generate less processed, more natural-looking images. Valid for 'flux-pro-1.1-ultra' model only. Default is False.
     """
 
     base_url: str = field(
@@ -39,45 +74,58 @@ class BlackForestImageGenerationDriver(BaseImageGenerationDriver):
         kw_only=True,
         metadata={"serializable": False},
     )
-    width: int = field(default=1024, kw_only=True)
-    height: int = field(default=768, kw_only=True)
+    width: int = field(default=1024, kw_only=True, validator=size_validator)
+    height: int = field(default=768, kw_only=True, validator=size_validator)
     sleep_interval: float = field(default=0.5, kw_only=True)
-    safety_tolerance: int | None = field(default=None, kw_only=True)
-    aspect_ratio: str = field(default=None, kw_only=True)
+    safety_tolerance: int | None = field(
+        default=None, kw_only=True, validator=safety_validator
+    )
+    aspect_ratio: str = field(
+        default=None, kw_only=True, validator=aspect_ratio_validator
+    )
     seed: int | None = field(default=None, kw_only=True)
     prompt_upsampling: bool = field(default=False, kw_only=True)
-    steps: int | None = field(default=None, kw_only=True)
+    steps: int | None = field(default=None, kw_only=True, validator=steps_validator)
+    guidance: float | None = field(
+        default=None, kw_only=True, validator=guidance_validator
+    )
+    interval: int | None = field(
+        default=None, kw_only=True, validator=interval_validator
+    )
+    raw: bool = field(default=False, kw_only=True)
 
     def try_text_to_image(
         self, prompts: list[str], negative_prompts: list[str] | None = None
     ) -> ImageArtifact:
         prompt = " ".join(prompts)
 
-        if self.width % 32 != 0 or self.height % 32 != 0:
-            msg = "width and height must be multiples of 32"
-            raise ValueError(msg)
-        if self.width < 256 or self.width > 1440:
-            raise ValueError("width must be between 256 and 1440")
-        if self.safety_tolerance and (
-            self.safety_tolerance < 0 or self.safety_tolerance > 6
-        ):
-            raise ValueError("safety_tolerance must be between 0 and 6")
-
         data: dict[str, Any] = {
             "prompt": prompt,
         }
 
         if self.seed:
             data["seed"] = self.seed
+        if self.safety_tolerance:
+            data["safety_tolerance"] = self.safety_tolerance
 
-        if self.model == "flux-pro-1.1-ultra" and self.aspect_ratio:
+        if self.aspect_ratio and self.model == "flux-pro-1.1-ultra":
             data["aspect_ratio"] = self.aspect_ratio
 
+        if self.raw and self.model == "flux-pro-1.1-ultra":
+            data["raw"] = self.raw
+
+        if self.guidance and self.model in ["flux-dev", "flux-pro"]:
+            data["guidance"] = float(self.guidance)
+
+        if self.steps and self.model in ["flux-dev", "flux-pro"]:
+            data["steps"] = int(self.steps)
+
+        if self.interval and self.model == "flux-pro":
+            data["interval"] = int(self.interval)
+
         if self.model in ["flux-pro-1.1", "flux-pro", "flux-dev"]:
             data["width"] = self.width
             data["height"] = self.height
-            if self.safety_tolerance:
-                data["safety_tolerance"] = self.safety_tolerance
             if self.prompt_upsampling:
                 data["prompt_upsampling"] = self.prompt_upsampling