Create Dockerfile

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+# 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 and install Python dependencies
+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
+
+# 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 (sports predictor specific models)
+RUN python -c "from huggingface_hub import snapshot_download; snapshot_download(repo_id='valhalla/distilbart-mnli-12-1')" \
+ && python -c "from huggingface_hub import snapshot_download; snapshot_download(repo_id='google/flan-t5-base')" \
+ && python -c "from huggingface_hub import snapshot_download; snapshot_download(repo_id='sentence-transformers/all-MiniLM-L6-v2')" \
+ && find /models/huggingface -name '*.lock' -delete
+
+# Preload tokenizers (avoid runtime delays)
+RUN python -c "from transformers import AutoTokenizer; AutoTokenizer.from_pretrained('valhalla/distilbart-mnli-12-1', use_fast=True)" \
+ && python -c "from transformers import AutoTokenizer; AutoTokenizer.from_pretrained('google/flan-t5-base', use_fast=True)" \
+ && python -c "from transformers import AutoTokenizer; AutoTokenizer.from_pretrained('sentence-transformers/all-MiniLM-L6-v2', use_fast=True)"
+
+# Copy project files
+COPY . .
+
+# Expose FastAPI port
+EXPOSE 7860
+
+# Run FastAPI app with uvicorn (1 workers for concurrency)
+CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860", "--workers", "1"]