Files
AgapHost/openai/tei-reranker/Dockerfile
alvis b27d31b3ca openai: compose healthchecks + dependency ordering, registries, LiteLLM routing
docker-compose.yml gains healthchecks and depends_on/condition chains for the
litellm/langfuse/postgres tier so dependants wait for a genuinely ready
service instead of a started container. Also plumbs AGAP_MCP_TOKEN into the
adolf and adolf-llm containers, sourced from openai/.env (gitignored), for the
kb#180 bearer auth on the agap MCP server; shared-mcp.json consumes it via
bearerTokenEnvVar so the Kimi backbone authenticates too.

agent-registry.yaml / agent_registry.py: the version-controlled source of
truth for agent identities and trust classes -- the same ids the agap-mcp
token map resolves to (`adolf`, `claude-coder`; note `claude-code-cli` is the
runtime entry, not an agent identity).

model-registry.yaml, litellm-config.yaml, auto-router-routes.json and
provision_litellm_keys.py: model tiering, virtual-key provisioning and
auto-router routes. tei-reranker/ is the local reranker service backing
Hindsight recall.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
2026-07-30 04:41:31 +00:00

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Docker

# CUDA torch base with Pascal (sm_61) support — cu118 wheels include sm_61,
# so the GTX 1070 works (unlike the stock TEI GPU image, which needs sm_75+).
FROM pytorch/pytorch:2.3.1-cuda11.8-cudnn8-runtime
WORKDIR /app
COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt
COPY server.py .
ENV HF_HOME=/root/.cache/huggingface
EXPOSE 80
CMD ["uvicorn", "server:app", "--host", "0.0.0.0", "--port", "80"]