Update Dockerfile

Dockerfile

@@ -1,52 +1,69 @@
-# M3GNet FastMCP HuggingFace Space image
-FROM python:3.10-slim
-
-ENV PIP_NO_CACHE_DIR=1 \
-    HF_HUB_DISABLE_TELEMETRY=1 \
-    TF_CPP_MIN_LOG_LEVEL=2 \
-    CUDA_VISIBLE_DEVICES=-1
-
-WORKDIR /app
-
-# System build/runtime dependencies for pymatgen, ASE, and TensorFlow
-RUN apt-get update \
-    && apt-get install -y --no-install-recommends \
-        build-essential \
-        git \
-        curl \
-        libopenblas-dev \
-        liblapack-dev \
-        libffi-dev \
-        libssl-dev \
-        ca-certificates \
-    && rm -rf /var/lib/apt/lists/*
-
-# Copy everything from the build context into the image
-COPY . /app
-
-# Install the core M3GNet library. The logic below works for both
-# "full repository" contexts (with setup.py at root) and the case where
-# the repo lives in a nested m3gnet/ directory. If neither is present we
-# fall back to installing the published package from PyPI.
-RUN set -ex \
-    && pip install --upgrade pip \
-    && if [ -f "setup.py" ] || [ -f "pyproject.toml" ]; then \
-        if [ -f "requirements.txt" ]; then pip install --no-cache-dir -r requirements.txt; fi && \
-        pip install --no-cache-dir .; \
-    elif [ -f "m3gnet/setup.py" ] || [ -f "m3gnet/pyproject.toml" ]; then \
-        if [ -f "m3gnet/requirements.txt" ]; then pip install --no-cache-dir -r m3gnet/requirements.txt; fi && \
-        pip install --no-cache-dir ./m3gnet; \
-    else \
-        pip install --no-cache-dir m3gnet==0.2.4; \
-    fi
-
-# Install MCP service dependencies
-RUN if [ -f "mcp_output/requirements.txt" ]; then \
-                pip install --no-cache-dir -r mcp_output/requirements.txt; \
-        elif [ -f "requirements.txt" ]; then \
-                pip install --no-cache-dir -r requirements.txt; \
-        fi
-
-EXPOSE 7860
-
-CMD ["python", "/app/entrypoint.py"]
+# M3GNet FastMCP HuggingFace Space image
+FROM python:3.10-slim
+
+ENV PIP_NO_CACHE_DIR=1 \
+    HF_HUB_DISABLE_TELEMETRY=1 \
+    TF_CPP_MIN_LOG_LEVEL=2 \
+    CUDA_VISIBLE_DEVICES=-1
+
+WORKDIR /app
+
+# System build/runtime dependencies for pymatgen, ASE, and TensorFlow
+RUN apt-get update \
+    && apt-get install -y --no-install-recommends \
+        build-essential \
+        git \
+        curl \
+        libopenblas-dev \
+        liblapack-dev \
+        libffi-dev \
+        libssl-dev \
+        ca-certificates \
+    && rm -rf /var/lib/apt/lists/*
+
+# Copy everything from the build context into the image
+COPY . /app
+
+# Staged installation to avoid dependency conflicts:
+# 1) Install TensorFlow 2.13 (requires numpy<=1.24.3)
+# 2) Install m3gnet with --no-deps, then its deps manually with compatible versions
+# 3) Install MCP service deps (needs pydantic v2)
+# 4) Force upgrade pydantic to v2 (pymatgen works fine with it at runtime)
+
+RUN pip install --upgrade pip
+
+# Stage 1: TensorFlow with compatible numpy
+RUN pip install --no-cache-dir tensorflow==2.13.0 numpy==1.24.3
+
+# Stage 2: M3GNet and materials science stack
+RUN pip install --no-cache-dir \
+    ase==3.22.1 \
+    monty==2024.2.2 \
+    sympy \
+    spglib \
+    scipy \
+    matplotlib \
+    pandas \
+    networkx \
+    requests \
+    ruamel.yaml \
+    tabulate \
+    uncertainties
+
+# Install pymatgen with relaxed deps, then m3gnet
+RUN pip install --no-cache-dir --no-deps pymatgen==2024.2.20 \
+    && pip install --no-cache-dir --no-deps m3gnet==0.2.4
+
+# Stage 3: MCP service dependencies
+RUN if [ -f "mcp_output/requirements.txt" ]; then \
+        pip install --no-cache-dir -r mcp_output/requirements.txt; \
+    elif [ -f "requirements.txt" ]; then \
+        pip install --no-cache-dir -r requirements.txt; \
+    fi
+
+# Stage 4: Ensure pydantic v2 for MCP (runtime compatible with pymatgen)
+RUN pip install --no-cache-dir --upgrade "pydantic>=2.0"
+
+EXPOSE 7860
+
+CMD ["python", "/app/entrypoint.py"]