Update Dockerfile

Dockerfile

@@ -1,99 +1,63 @@
-# We use Python 3.10 because it has the best pre-built wheels for Llama
-FROM python:3.10-slim
 
+# ---- Base image ----
+FROM python:3.11-slim
+
+# Workdir inside the container
 WORKDIR /app
 
-# 1. Install minimal tools (Git/Curl) but NO heavy compilers
+# ---- System dependencies ----
 RUN apt-get update && apt-get install -y \
+    build-essential \
     curl \
     git \
-    build-essential \
-    && rm -rf /var/lib/apt/lists/*
-
-# 2. Upgrade pip (Critical for finding the right wheels)
-RUN pip install --upgrade pip
-
-# 3. Install LLM Engine (Pre-built)
-# This installs the tool on the hard drive. It takes space, but ZERO CPU to run.
-# The --prefer-binary flag ensures we don't try to compile it.
-RUN pip install llama-cpp-python \
-    --no-cache-dir \
-    --prefer-binary \
-    --extra-index-url https://abetlen.github.io/llama-cpp-python/whl/cpu
-
-# 4. Install other requirements
-COPY requirements.txt .
-RUN pip install --no-cache-dir -r requirements.txt
-
-# 5. Download NLTK data
-RUN python -c "import nltk; nltk.download('punkt'); nltk.download('punkt_tab'); nltk.download('stopwords')"
-
-COPY . .
-
-# 6. Run the Unified App (Back to app.py!)
-CMD ["streamlit", "run", "app.py", "--server.port=7860", "--server.address=0.0.0.0"]
-
-
+    unzip \
+ && rm -rf /var/lib/apt/lists/*
 
-# # ---- Base image ----
-# FROM python:3.11-slim
 
-# # Workdir inside the container
-# WORKDIR /app
+# ---- Python deps ----
+COPY requirements.txt ./
 
-# # ---- System dependencies ----
-# RUN apt-get update && apt-get install -y \
-#     build-essential \
-#     curl \
-#     git \
-#     unzip \
-#  && rm -rf /var/lib/apt/lists/*
+# Torch / sentence-transformers like having the CPU wheel index explicitly
+RUN pip install --no-cache-dir \
+    --extra-index-url https://download.pytorch.org/whl/cpu \
+    -r requirements.txt
 
+# ---- NLTK data (punkt + stopwords) ----
+RUN mkdir -p /usr/local/share/nltk_data
 
-# # ---- Python deps ----
-# COPY requirements.txt ./
+# punkt tokenizer
+# RUN curl -L "https://raw.githubusercontent.com/nltk/nltk_data/gh-pages/packages/tokenizers/punkt.zip" \
+#       -o /tmp/punkt.zip && \
+#     unzip /tmp/punkt.zip -d /usr/local/share/nltk_data && \
+#     rm /tmp/punkt.zip
+# punkt_tab tokenizer (for NLTK >= 3.9)
+RUN curl -L "https://raw.githubusercontent.com/nltk/nltk_data/gh-pages/packages/tokenizers/punkt_tab.zip" \
+      -o /tmp/punkt_tab.zip && \
+    unzip /tmp/punkt_tab.zip -d /usr/local/share/nltk_data && \
+    rm /tmp/punkt_tab.zip
 
-# # Torch / sentence-transformers like having the CPU wheel index explicitly
-# RUN pip install --no-cache-dir \
-#     --extra-index-url https://download.pytorch.org/whl/cpu \
-#     -r requirements.txt
 
-# # ---- NLTK data (punkt + stopwords) ----
-# RUN mkdir -p /usr/local/share/nltk_data
+# stopwords corpus
+RUN curl -L "https://raw.githubusercontent.com/nltk/nltk_data/gh-pages/packages/corpora/stopwords.zip" \
+      -o /tmp/stopwords.zip && \
+    unzip /tmp/stopwords.zip -d /usr/local/share/nltk_data && \
+    rm /tmp/stopwords.zip
 
-# # punkt tokenizer
-# # RUN curl -L "https://raw.githubusercontent.com/nltk/nltk_data/gh-pages/packages/tokenizers/punkt.zip" \
-# #       -o /tmp/punkt.zip && \
-# #     unzip /tmp/punkt.zip -d /usr/local/share/nltk_data && \
-# #     rm /tmp/punkt.zip
-# # punkt_tab tokenizer (for NLTK >= 3.9)
-# RUN curl -L "https://raw.githubusercontent.com/nltk/nltk_data/gh-pages/packages/tokenizers/punkt_tab.zip" \
-#       -o /tmp/punkt_tab.zip && \
-#     unzip /tmp/punkt_tab.zip -d /usr/local/share/nltk_data && \
-#     rm /tmp/punkt_tab.zip
-
-
-# # stopwords corpus
-# RUN curl -L "https://raw.githubusercontent.com/nltk/nltk_data/gh-pages/packages/corpora/stopwords.zip" \
-#       -o /tmp/stopwords.zip && \
-#     unzip /tmp/stopwords.zip -d /usr/local/share/nltk_data && \
-#     rm /tmp/stopwords.zip
-
-# # ---- Copy app code ----
-# # If you only want app.py + data, you can narrow this, but copying all is fine.
-# COPY . .
+# ---- Copy app code ----
+# If you only want app.py + data, you can narrow this, but copying all is fine.
+COPY . .
 
-# # ---- Hugging Face port wiring ----
-# ENV PORT=7860
-# EXPOSE 7860
+# ---- Hugging Face port wiring ----
+ENV PORT=7860
+EXPOSE 7860
 
-# # Optional healthcheck; HF will just ignore failures but nice to have
-# HEALTHCHECK CMD curl --fail http://localhost:${PORT}/_stcore/health || exit 1
+# Optional healthcheck; HF will just ignore failures but nice to have
+HEALTHCHECK CMD curl --fail http://localhost:${PORT}/_stcore/health || exit 1
 
-# # ---- Run Streamlit ----
-# ENTRYPOINT ["bash", "-c", "streamlit run app.py \
-#     --server.port=${PORT} \
-#     --server.address=0.0.0.0 \
-#     --server.enableCORS=false \
-#     --server.enableXsrfProtection=false"]
+# ---- Run Streamlit ----
+ENTRYPOINT ["bash", "-c", "streamlit run app.py \
+    --server.port=${PORT} \
+    --server.address=0.0.0.0 \
+    --server.enableCORS=false \
+    --server.enableXsrfProtection=false"]