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from modules.api.processing import StableDiffusionProcessingAPI
from modules.processing import StableDiffusionProcessingTxt2Img, process_images
from modules.sd_samplers import all_samplers
from modules.extras import run_pnginfo
import modules.shared as shared
import uvicorn
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.lower() == row[1].name.lower(), enumerate(all_samplers)), None)
class TextToImageResponse(BaseModel):
images: list[str] = Field(default=None, title="Image", description="The generated image in base64 format.")
parameters: Json
info: Json
class Api:
def __init__(self, app, queue_lock):
self.router = APIRouter()
self.app = app
self.queue_lock = queue_lock
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": sampler_index[0],
"do_not_save_samples": True,
"do_not_save_grid": True
}
)
p = StableDiffusionProcessingTxt2Img(**vars(populate))
# Override object param
with self.queue_lock:
processed = process_images(p)
b64images = []
for i in processed.images:
buffer = io.BytesIO()
i.save(buffer, format="png")
b64images.append(base64.b64encode(buffer.getvalue()))
return TextToImageResponse(images=b64images, parameters=json.dumps(vars(txt2imgreq)), info=json.dumps(processed.info))
def img2imgapi(self):
raise NotImplementedError
def extrasapi(self):
raise NotImplementedError
def pnginfoapi(self):
raise NotImplementedError
def launch(self, server_name, port):
self.app.include_router(self.router)
uvicorn.run(self.app, host=server_name, port=port)
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