b

.env

@@ -1 +0,0 @@
-TRANSFORMERS_CACHE="/f/cache"

Dockerfile

@@ -1,29 +1,9 @@
-# Stage 1: Install dependencies (slim base)
-FROM python:3.12.2-slim AS build-stage
-
+FROM python:3.12.2-slim
 RUN apt-get update && apt-get install -y rustc cargo
 
-# Install Python dependencies
-WORKDIR /app
-COPY requirements.txt ./
-RUN pip install --no-cache-dir --upgrade -r requirements.txt
-
-# Stage 2: Copy application code (smaller base)
-FROM python:3.12.2-alpine AS final-stage
-
-WORKDIR /app
-
-# Copy application code (replace ./app with your actual directory)
-COPY ./app .
-
-# Read cache path from .env file (assuming .env is in the same directory)
-ENV TRANSFORMERS_CACHE=/app/models
-
-# Expose port
+WORKDIR /code
+COPY ./requirements.txt /code/requirements.txt
+RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt
+COPY ./app /code/app
 EXPOSE 80
-
-RUN pip install fastapi uvicorn transformers
-
-# Command to run the application
-CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "80"]
-
+CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "80"]

app/main.py

@@ -1,5 +1,6 @@
 from fastapi import FastAPI
 from transformers import BartForConditionalGeneration, BartTokenizer
+import pickle
 from pydantic import BaseModel
 
 app = FastAPI()
@@ -32,4 +33,3 @@ async def predict(request: Request) -> Response:
 
 
 
-