provide sampler by name

modules/api/api.py

@@ -1,14 +1,17 @@
 from modules.api.processing import StableDiffusionProcessingAPI
 from modules.processing import StableDiffusionProcessingTxt2Img, process_images
+from modules.sd_samplers import samplers_k_diffusion
 import modules.shared as shared
 import uvicorn
-from fastapi import Body, APIRouter
+from fastapi import Body, APIRouter, HTTPException
 from fastapi.responses import JSONResponse
 from pydantic import BaseModel, Field, Json
 import json
 import io
 import base64
 
+sampler_to_index = lambda name: next(filter(lambda row: name in row[1][2], enumerate(samplers_k_diffusion)), None)
+
 class TextToImageResponse(BaseModel):
     images: list[str] = Field(default=None, title="Image", description="The generated image in base64 format.")
     parameters: Json
@@ -23,9 +26,14 @@ class Api:
         self.app.add_api_route("/sdapi/v1/txt2img", self.text2imgapi, methods=["POST"])
 
     def text2imgapi(self, txt2imgreq: StableDiffusionProcessingAPI ):
+        sampler_index = sampler_to_index(txt2imgreq.sampler_index)
+        
+        if sampler_index is None:
+            raise HTTPException(status_code=404, detail="Sampler not found") 
+        
         populate = txt2imgreq.copy(update={ # Override __init__ params
             "sd_model": shared.sd_model, 
-            "sampler_index": 0,
+            "sampler_index": sampler_index[0],
             "do_not_save_samples": True,
             "do_not_save_grid": True
             }

modules/api/processing.py

@@ -42,7 +42,8 @@ class PydanticModelGenerator:
     def __init__(
         self,
         model_name: str = None,
-        class_instance = None
+        class_instance = None,
+        additional_fields = None,
     ):
         def field_type_generator(k, v):
             # field_type = str if not overrides.get(k) else overrides[k]["type"]
@@ -70,6 +71,13 @@ class PydanticModelGenerator:
             )
             for (k,v) in self._class_data.items() if k not in API_NOT_ALLOWED
         ]
+        
+        for fields in additional_fields:
+            self._model_def.append(ModelDef(
+                field=underscore(fields["key"]), 
+                field_alias=fields["key"], 
+                field_type=fields["type"],
+                field_value=fields["default"]))
 
     def generate_model(self):
         """
@@ -84,4 +92,8 @@ class PydanticModelGenerator:
         DynamicModel.__config__.allow_mutation = True
         return DynamicModel
     
-StableDiffusionProcessingAPI = PydanticModelGenerator("StableDiffusionProcessingTxt2Img", StableDiffusionProcessingTxt2Img).generate_model()
+StableDiffusionProcessingAPI = PydanticModelGenerator(
+    "StableDiffusionProcessingTxt2Img", 
+    StableDiffusionProcessingTxt2Img,
+    [{"key": "sampler_index", "type": str, "default": "k_euler_a"}]
+).generate_model()