Update Dockerfile

Dockerfile

@@ -1,56 +1,56 @@
-# Base Image
-FROM python:3.10-slim
-
-
-ENV DEBIAN_FRONTEND=noninteractive \
-    PYTHONUNBUFFERED=1 \
-    PYTHONDONTWRITEBYTECODE=1
-
-
-WORKDIR /code
-
-# System Dependencies
-RUN apt-get update && apt-get install -y --no-install-recommends \
-    build-essential \
-    git \
-    curl \
-    libopenblas-dev \
-    libomp-dev \
-    && rm -rf /var/lib/apt/lists/*
-
-
-COPY requirements.txt .
-RUN pip install --no-cache-dir -r requirements.txt
-
-# Hugging Face + model tools
-RUN pip install --no-cache-dir huggingface-hub sentencepiece accelerate fasttext
-
-# Hugging Face cache environment
-ENV HF_HOME=/models/huggingface \
-    TRANSFORMERS_CACHE=/models/huggingface \
-    HUGGINGFACE_HUB_CACHE=/models/huggingface \
-    HF_HUB_CACHE=/models/huggingface
-
-# Created cache dir and set permissions
-RUN mkdir -p /models/huggingface && chmod -R 777 /models/huggingface
-
-# Pre-download models at build time
-RUN python -c "from huggingface_hub import snapshot_download; snapshot_download(repo_id='Qwen/Qwen3-4B-Instruct-2507')" \
- && python -c "from huggingface_hub import snapshot_download; snapshot_download(repo_id='sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2')" \
- && python -c "from huggingface_hub import hf_hub_download; hf_hub_download(repo_id='facebook/fasttext-language-identification', filename='model.bin')" \
- && python -c "from huggingface_hub import snapshot_download; snapshot_download(repo_id='drrobot9/nllb-ig-yo-ha-finetuned')" \
- && find /models/huggingface -name '*.lock' -delete
-
-# Preload tokenizers (avoid runtime delays)
-RUN python -c "from transformers import AutoTokenizer; AutoTokenizer.from_pretrained('Qwen/Qwen3-4B-Instruct-2507', use_fast=True)" \
- && python -c "from transformers import AutoTokenizer; AutoTokenizer.from_pretrained('sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2', use_fast=True)" \
- && python -c "from transformers import AutoTokenizer; AutoTokenizer.from_pretrained('drrobot9/nllb-ig-yo-ha-finetuned', use_fast=True)"
-
-# Copy project files
-COPY . .
-
-# Expose FastAPI port
-EXPOSE 7860
-
-# Run FastAPI app with uvicorn (1 workers for concurrency)
+# Base Image
+FROM python:3.10-slim
+
+
+ENV DEBIAN_FRONTEND=noninteractive \
+    PYTHONUNBUFFERED=1 \
+    PYTHONDONTWRITEBYTECODE=1
+
+
+WORKDIR /code
+
+# System Dependencies
+RUN apt-get update && apt-get install -y --no-install-recommends \
+    build-essential \
+    git \
+    curl \
+    libopenblas-dev \
+    libomp-dev \
+    && rm -rf /var/lib/apt/lists/*
+
+
+COPY requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Hugging Face + model tools
+RUN pip install --no-cache-dir huggingface-hub sentencepiece accelerate fasttext
+
+# Hugging Face cache environment
+ENV HF_HOME=/models/huggingface \
+    TRANSFORMERS_CACHE=/models/huggingface \
+    HUGGINGFACE_HUB_CACHE=/models/huggingface \
+    HF_HUB_CACHE=/models/huggingface
+
+# Created cache dir and set permissions
+RUN mkdir -p /models/huggingface && chmod -R 777 /models/huggingface
+
+# Pre-download models at build time
+RUN python -c "from huggingface_hub import snapshot_download; snapshot_download(repo_id='Qwen/Qwen3-4B-Instruct-2507')" \
+ && python -c "from huggingface_hub import snapshot_download; snapshot_download(repo_id='sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2')" \
+ && python -c "from huggingface_hub import hf_hub_download; hf_hub_download(repo_id='facebook/fasttext-language-identification', filename='model.bin')" \
+ && python -c "from huggingface_hub import snapshot_download; snapshot_download(repo_id='facebook/nllb-200-distilled-600M')" \
+ && find /models/huggingface -name '*.lock' -delete
+
+# Preload tokenizers (avoid runtime delays)
+RUN python -c "from transformers import AutoTokenizer; AutoTokenizer.from_pretrained('Qwen/Qwen3-4B-Instruct-2507', use_fast=True)" \
+ && python -c "from transformers import AutoTokenizer; AutoTokenizer.from_pretrained('sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2', use_fast=True)" \
+ && python -c "from transformers import AutoTokenizer; AutoTokenizer.from_pretrained('facebook/nllb-200-distilled-600M', use_fast=True)"
+
+# Copy project files
+COPY . .
+
+# Expose FastAPI port
+EXPOSE 7860
+
+# Run FastAPI app with uvicorn (1 workers for concurrency)
 CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "7860", "--workers", "1"]