6ixPulse / Dockerfile
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6ixPulse: clean agentic Space with full dimension scoring (OSM, Toronto Police, TTC/GO, CMHC)
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FROM node:22-bookworm-slim
ENV PYTHONUNBUFFERED=1
ENV PORT=7860
ENV AGENT_PORT=8787
ENV AGENT_MODEL_PROVIDER=auto
ENV NVIDIA_MODEL=nvidia/nemotron-3-nano-omni-30b-a3b-reasoning
ENV SEARCH_PROVIDER=disabled
ENV MCP_WEB_SEARCH_ENABLED=0
ENV MCP_WEB_SEARCH_TIMEOUT_MS=6000
ENV RESEARCH_ENABLED=1
ENV RESEARCH_DEPTH=standard
ENV RESEARCH_MAX_QUERIES=6
ENV RESEARCH_RESULTS_PER_QUERY=3
ENV RESEARCH_MAX_SOURCES=24
ENV RESEARCH_TOTAL_TIMEOUT_MS=45000
ENV OFFICIAL_DATA_ENABLED=1
# Keep the full agentic workflow on the Space: the model discovers neighbourhoods
# (nothing hardcoded) and each City Agent reasons via the configured agentic model.
ENV AGENT_DISCOVER=1
ENV AGENT_FANOUT=1
WORKDIR /app
RUN apt-get update \
&& apt-get install -y --no-install-recommends python3 python3-pip python3-venv \
&& rm -rf /var/lib/apt/lists/*
COPY package.json package-lock.json requirements.txt ./
RUN npm ci
RUN python3 -m venv /opt/venv
ENV PATH="/opt/venv/bin:${PATH}"
RUN pip install --no-cache-dir -r requirements.txt
COPY . .
RUN npm run build
EXPOSE 7860
CMD ["python", "app.py"]