Update Dockerfile

Dockerfile

@@ -1,66 +1,55 @@
-# 1. 파이썬 버전을 3.11으로 설정
+# 1) Python 3.11
 FROM python:3.11-slim
 
-# 2. 필요한 시스템 패키지 및 git-lfs 설치
-RUN pip install --no-cache-dir hf_transfer>=0.1.6
-RUN apt-get update && apt-get install -y \
-    build-essential \
-    curl \
-    git \
-    git-lfs \
+# 2) System deps & git-lfs
+RUN pip install --no-cache-dir hf_transfer>=0.1.6 && \
+    apt-get update && apt-get install -y \
+      build-essential \
+      curl \
+      git \
+      git-lfs \
     && rm -rf /var/lib/apt/lists/*
 
-# Ollama 설치
+# 3) Install Ollama
 RUN curl -fsSL https://ollama.com/install.sh | sh
 
-# ✅ 작은 모델 + 권한 문제 없는 설정
+# 4) Ollama storage → /tmp (writeable in Spaces)
 ENV OLLAMA_HOME=/tmp/ollama
 ENV OLLAMA_MODELS=/tmp/ollama
 ENV OLLAMA_MODEL=gemma2:9b
+RUN install -d -m 777 /tmp/ollama
 
-# 빌드 중 모델 다운로드 (작은 모델이라 빠름)
-RUN set -eux; \
-  mkdir -p /tmp/ollama; \
-  env HOME=/tmp OLLAMA_HOME=/tmp/ollama OLLAMA_MODELS=/tmp/ollama ollama serve & pid=$!; \
-  for i in {1..60}; do curl -sf http://127.0.0.1:11434/api/version >/dev/null && break || sleep 1; done; \
-  env HOME=/tmp OLLAMA_HOME=/tmp/ollama OLLAMA_MODELS=/tmp/ollama ollama pull gemma2:9b; \
-  kill "$pid" || true
-
-# 3. 작업 디렉터리 설정
+# 5) App setup
 WORKDIR /app
-
-# 6. 파이썬 라이브러리 설치
 COPY requirements.txt .
 RUN pip install --no-cache-dir -r requirements.txt
-
-# 4. 소스 코드 복사
 COPY . /app
-
-# 5. Git LFS 설정 및 대용량 파일 다운로드
 RUN git lfs install && git lfs pull || true
 
-# 환경변수 설정
+# 6) Streamlit & caches
 ENV HOME=/app
 ENV STREAMLIT_HOME=/app/.streamlit
-RUN mkdir -p /app/.streamlit
+RUN install -d -m 777 /app/.streamlit
 
 ENV HF_HOME=/tmp/hf-home \
     TRANSFORMERS_CACHE=/tmp/hf-cache \
     HUGGINGFACE_HUB_CACHE=/tmp/hf-cache \
     TORCH_HOME=/tmp/torch-cache \
     XDG_CACHE_HOME=/tmp/xdg-cache
+RUN install -d -m 777 /tmp/hf-home /tmp/hf-cache /tmp/torch-cache /tmp/xdg-cache
 
-RUN mkdir -p /tmp/hf-home /tmp/hf-cache /tmp/torch-cache /tmp/xdg-cache
-
+# 7) Internal Ollama host (same container)
 ENV OLLAMA_HOST=http://127.0.0.1:11434
+ENV OLLAMA_TIMEOUT=300
+
 EXPOSE 8501
 
-# ✅ 간단하고 확실한 CMD
+# 8) Runtime: clean /tmp/ollama → serve → healthcheck → pull gemma2:9b → Streamlit
 CMD bash -lc '\
-  mkdir -p /tmp/ollama; \
-  echo "Starting Ollama with model: gemma2:9b"; \
+  set -euo pipefail; \
+  rm -rf /tmp/ollama && install -d -m 777 /tmp/ollama; \
+  echo "Starting Ollama with model: ${OLLAMA_MODEL}"; \
   env HOME=/tmp OLLAMA_HOME=/tmp/ollama OLLAMA_MODELS=/tmp/ollama ollama serve & \
-  sleep 10; \
-  echo "Ollama server should be ready"; \
-  echo "Starting Streamlit app"; \
-  streamlit run app.py --server.address=0.0.0.0 --server.port=${PORT:-8501}'
+  for i in {1..240}; do curl -sf http://127.0.0.1:11434/api/version >/dev/null && break || sleep 1; done; \
+  env HOME=/tmp OLLAMA_HOME=/tmp/ollama OLLAMA_MODELS=/tmp/ollama ollama pull "${OLLAMA_MODEL}"; \
+  exec streamlit run app.py --server.address=0.0.0.0 --server.port=${PORT:-8501}'