chore: Update Dockerfile and requirements.txt for Huggingface Spaces deployment

Former-commit-id: 348186a5e11ccfaf073fb3abadd0f5f21ad754ec [formerly 6972c89f89c3e6a6f54549211b4d5482a70103d5]
Former-commit-id: 0a43bc1515b0cfbceb025ff39ba7d15ac7dc5d67

.github/workflows/build-docker.yml

@@ -1,4 +1,4 @@
-name: Push to Docker Image
+name: Push Image to Huggingface Spaces
 
 on:
   push:

DockerFile

@@ -0,0 +1,31 @@
+# Use the official Python base image
+FROM python:3.11-slim
+
+# Set the initial working directory
+WORKDIR /api
+
+# Copy the requirements.txt file from the api directory
+COPY api/requirements.txt ./
+
+# Install dependencies specified in requirements.txt
+RUN pip install --no-cache-dir --upgrade -r requirements.txt
+
+# Create a non-root user and set up the environment
+RUN useradd -m -u 1000 user
+
+USER user
+
+ENV HOME=/home/user \
+    PATH=/home/user/.local/bin:$PATH
+
+# Set the final working directory
+WORKDIR $HOME/app
+
+# Copy the entire project into the container, setting the appropriate ownership
+COPY --chown=user . $HOME/app
+
+# Set the working directory to /home/user/app/api
+WORKDIR $HOME/app/api
+
+# Command to run the API
+CMD ["python", "endpoints.py"]

api/endpoints.py

@@ -52,4 +52,4 @@ def check_health():
 
 
 
-uvicorn.run(app, host='127.0.0.1', port=8000)
+uvicorn.run(app, host='127.0.0.1', port=7860)

api/requirements.txt

@@ -10,3 +10,4 @@ pydantic==2.7.4
 torch==2.2.0
 utils==1.0.2
 uvicorn==0.30.1
+boto3

api/routers/sdxl_text_to_image.py

@@ -1,5 +1,5 @@
 import sys
-sys.path.append("../scripts")  # Path of the scripts directory
+sys.path.append("../../scripts")  # Path of the scripts directory
 import config
 from fastapi import APIRouter, HTTPException
 from pydantic import BaseModel
@@ -32,7 +32,7 @@ router = APIRouter()
 
 
 # Load the diffusion pipeline
-
+@lru_cache(maxsize=1)
 def load_pipeline(model_name, adapter_name,enable_compile:bool):
     """
     Load the diffusion pipeline with the specified model and adapter names.

scripts/config.py

@@ -8,7 +8,7 @@ PRODUCTS_10k_DATASET = "VikramSingh178/Products-10k-BLIP-captions"
 CAPTIONING_MODEL_NAME = "Salesforce/blip-image-captioning-base"
 SEGMENTATION_MODEL_NAME = "facebook/sam-vit-large"
 DETECTION_MODEL_NAME = "yolov8l"
-ENABLE_COMPILE = False
+ENABLE_COMPILE = True
 INPAINTING_MODEL_NAME = 'kandinsky-community/kandinsky-2-2-decoder-inpaint'