debugging setup

Dockerfile

@@ -7,16 +7,21 @@ ENV PYTHONDONTWRITEBYTECODE 1
 ENV PYTHONUNBUFFERED 1
 ENV HF_HOME /app/cache
 
+RUN useradd -m -u 1000 user
+USER user
+
 # Set the working directory in the container
 WORKDIR /app
 
 # Upgrade pip to the latest version and install Python dependencies
 COPY requirements.txt .
+
+RUN chown -R user:user /app
 RUN pip install --upgrade pip && pip install -r requirements.txt
 
 # Copy the FastAPI application code and other necessary files into the container
-COPY ./app .
-COPY .env .
+COPY --chown=user:user ./app .
+COPY --chown=user:user .env .
 
 # Expose port 7860 for the application
 EXPOSE 7860

app/main.py

@@ -2,7 +2,7 @@
 from fastapi import FastAPI, HTTPException
 from pydantic import BaseModel
 from typing import List
-import redis
+#import redis
 from transformers import BartForSequenceClassification, BartTokenizer, AutoTokenizer, AutoConfig, pipeline
 from dotenv import load_dotenv
 import os
@@ -21,7 +21,7 @@ print("FastAPI port:", fastapi_port)
 
 # Initialize FastAPI app and Redis client
 app = FastAPI()
-redis_client = redis.Redis(host='redis', port=6379)
+#redis_client = redis.Redis(host='redis', port=6379)
 
 # Load BART model and tokenizer
 #model = BartForSequenceClassification.from_pretrained("facebook/bart-large-mnli")
@@ -78,13 +78,13 @@ async def rerank_items(items: List[Item]) -> RerankedItems:
         labels = classify_item(item.text)
 
         # Save the item with labels in Redis
-        redis_client.hset(item.id, mapping={"title": item.title, "text": item.text, "labels": ",".join(labels)})
+        #redis_client.hset(item.id, mapping={"title": item.title, "text": item.text, "labels": ",".join(labels)})
 
         # Add the item id to the reranked list
         reranked_ids.append(item.id)
 
     # Sort the items based on model confidence
-    reranked_ids.sort(key=lambda x: redis_client.zscore("classified_items", x), reverse=True)
+    #reranked_ids.sort(key=lambda x: redis_client.zscore("classified_items", x), reverse=True)
 
     # Return the reranked items
     return {"ranked_ids": reranked_ids, "new_items": []}  # Ignore "new_items" for now

requirements.txt

@@ -5,5 +5,4 @@ python-dotenv
 dotenv-cli
 pandas
 uvicorn
-pydantic
-redis# remove for prototype
+pydantic