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dbx-tools-graphiti

Run Graphiti REST, MCP, model routing, and PostgreSQL-backed graph memory from one Python runtime. The build synchronizes the upstream REST and MCP source plus the pinned PostGraph driver from Graphiti PR 1777 into the generated package tree, so the published wheel has no direct Git dependencies.

Both upstream surfaces come from the same Graphiti commit:

  • graph-service from server/
  • mcp-server from mcp_server/

Run

UVICORN_HOST=0.0.0.0 \
UVICORN_PORT=8000 \
uv run uvicorn dbx_tools.graphiti.main:app

From the repository root, the local launcher starts the unified runtime:

DATABRICKS_CONFIG_PROFILE=<profile> \
MODEL_NAME=databricks-gpt-5-nano \
bash scripts/run-graphiti-python.sh

The combined application exposes:

  • FastAPI documentation at /docs
  • OpenAPI at /openapi.json
  • REST health and Graphiti routes, including /healthcheck, /search, and ingestion endpoints
  • Streamable HTTP MCP at /mcp/

Configure Graphiti through the shared environment contract used by the Node runtime and CLI.

Databricks Model Resolution

The process creates one generated auth client and one generated model client at startup. It resolves the fuzzy chat model, ranks embedding endpoints by the configured name, embedding class, and dimensions, then resolves both endpoint routes. REST and MCP reuse the same Graphiti model clients, while the auth client injects refreshed Databricks headers into every model request.

Use From A Notebook

Use the same resolved option names without starting Uvicorn:

from dbx_tools.graphiti.runtime import GraphitiRuntime

async with GraphitiRuntime.from_options(
    {
        "profile": "MY-PROFILE",
    }
) as runtime:
    graphiti = runtime.graphiti

When databaseUrl is omitted, the runtime starts bundled PostgreSQL with pgvector and persists it under graphitiHome, or the platform data directory when no home is configured. The owned PostgreSQL process stops with the runtime, while its data remains for the next start.

Pass a regular PostgreSQL URL to use an existing database. A passwordless non-local URL, Lakebase resource path, or Lakebase project name is resolved by the generated Node Lakebase client. It injects a fresh short-lived credential whenever the asyncpg pool opens a physical connection, without persisting that credential in the URL.

Composition Boundary

dbx_tools.graphiti.main adds FastAPI REST and MCP surfaces around the same importable runtime. Shared environment options are parsed through generated PythonMonkey bindings and mapped into both upstream settings objects.

Metadata

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