Fix: use writable cache dirs for HF/Transformers

Dockerfile

@@ -3,6 +3,14 @@ FROM python:3.11-slim
 WORKDIR /app
 RUN apt-get update && apt-get install -y git && rm -rf /var/lib/apt/lists/*
 
+# Writable caches for HF/Transformers inside the container
+ENV HF_HOME=/tmp/hf \
+    TRANSFORMERS_CACHE=/tmp/transformers \
+    HF_DATASETS_CACHE=/tmp/hf_datasets \
+    HF_HUB_DISABLE_TELEMETRY=1
+
+RUN mkdir -p /tmp/hf /tmp/transformers /tmp/hf_datasets && chmod -R 777 /tmp
+
 COPY requirements.txt .
 RUN pip install --no-cache-dir -r requirements.txt
 

app.py

@@ -3,16 +3,27 @@ from fastapi import FastAPI
 from pydantic import BaseModel
 from pathlib import Path
 from transformers import pipeline
+import os
+
+# Put all caches in writable /tmp
+os.environ.setdefault("HF_HOME", "/tmp/hf")
+os.environ.setdefault("TRANSFORMERS_CACHE", "/tmp/transformers")
+os.environ.setdefault("HF_DATASETS_CACHE", "/tmp/hf_datasets")
+os.environ.setdefault("HF_HUB_DISABLE_TELEMETRY", "1")
+
 
 app = FastAPI(title="Incident ML Inference API")
 
-LOCAL_MODEL = Path(__file__).resolve().parents[1] / "models" / "incident_classifier"
 
-# Category classifier (your fine-tuned model if available)
-if LOCAL_MODEL.exists():
-    incident_classifier = pipeline("text-classification", model="brijeshpandya/incident-classifier")
-else:
-    incident_classifier = pipeline("text-classification", model="cardiffnlp/twitter-xlm-roberta-base")
+# LOCAL_MODEL = Path(__file__).resolve().parents[1] / "models" / "incident_classifier"
+
+# # Category classifier (your fine-tuned model if available)
+# if LOCAL_MODEL.exists():
+#     incident_classifier = pipeline("text-classification", model="brijeshpandya/incident-classifier")
+# else:
+#     incident_classifier = pipeline("text-classification", model="cardiffnlp/twitter-xlm-roberta-base")
+
+incident_classifier = pipeline("text-classification", model="brijeshpandya/incident-classifier")
 
 # Sentiment (keep public model for now)
 sentiment_analyzer = pipeline("sentiment-analysis", model="cardiffnlp/twitter-xlm-roberta-base-sentiment")