jan/jan-inference/sd/main.py
2023-08-25 01:31:11 +07:00

71 lines
2.2 KiB
Python

from fastapi import FastAPI, BackgroundTasks, HTTPException, Form
from fastapi.responses import FileResponse
from fastapi.staticfiles import StaticFiles
import subprocess
import os
from uuid import uuid4
app = FastAPI()
OUTPUT_DIR = "output"
SD_PATH = os.environ.get("SD_PATH", "./sd")
MODEL_DIR = os.environ.get("MODEL_DIR", "./models")
BASE_URL = os.environ.get("BASE_URL", "http://localhost:8000")
MODEL_NAME = os.environ.get(
"MODEL_NAME", "v1-5-pruned-emaonly-ggml-model-q5_0.bin")
# Create the OUTPUT_DIR directory if it does not exist
if not os.path.exists(OUTPUT_DIR):
os.makedirs(OUTPUT_DIR)
# Create the OUTPUT_DIR directory if it does not exist
if not os.path.exists(MODEL_DIR):
os.makedirs(MODEL_DIR)
# Serve files from the "files" directory
app.mount("/output", StaticFiles(directory=OUTPUT_DIR), name="output")
def run_command(prompt: str, filename: str):
# Construct the command based on your provided example
command = [SD_PATH,
"-m", os.path.join(MODEL_DIR, MODEL_NAME),
"-p", prompt,
"-o", os.path.join(OUTPUT_DIR, filename)
]
try:
sub_output = subprocess.run(command, timeout=5*60, capture_output=True,
check=True, encoding="utf-8")
print(sub_output.stdout)
except subprocess.CalledProcessError:
raise HTTPException(
status_code=500, detail="Failed to execute the command.")
@app.post("/inference/")
async def run_inference(background_tasks: BackgroundTasks, prompt: str = Form()):
# Generate a unique filename using uuid4()
filename = f"{uuid4()}.png"
# We will use background task to run the command so it won't block
background_tasks.add_task(run_command, prompt, filename)
# Return the expected path of the output file
return {"url": f'{BASE_URL}/serve/{filename}'}
@app.get("/serve/{filename}")
async def serve_file(filename: str):
file_path = os.path.join(OUTPUT_DIR, filename)
if os.path.exists(file_path):
return FileResponse(file_path)
else:
raise HTTPException(status_code=404, detail="File not found")
if __name__ == "__main__":
import uvicorn
uvicorn.run(app, host="0.0.0.0", port=8000)