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)