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https://github.com/hanzoai/insights.git
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zeekay
1b367e2b62
The tree was a debranded snapshot of upstream taken around 2026-02-20, and upstream has moved about five months since. This replaces it with upstream master, mechanically re-derived: bin/debrand does the rename, and the pipeline and squashed migrations are restored from the shipped tree. Not a merge. The previous import replaced the tree wholesale in a single commit, so there is no shared content history to merge against. Reproducing the rename on the new tree is what actually converges. What survives: .hanzo/workflows, the Dockerfiles and bin/docker* entrypoints, compose files, LLM.md, and insights/migrations. The squashed initial migration is load-bearing — the live database records it by name, so upstream's ~918 individual migrations cannot come back. Nine products are dropped as unreferenced. Twenty-one more that we do not run are kept anyway because the core app still imports them; unpicking those is a refactor and does not belong in a rebase. This base does not build yet, and the reasons are not in the rename: upstream now wants Python 3.13.13 against our 3.12.12 and Django 5.2 against our 4.2, and the dependency manifests still name upstream packages that we republish under our own names. Those are decisions, not renames.
22 lines
929 B
Python
22 lines
929 B
Python
from rest_framework import status
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from rest_framework.exceptions import APIException
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class EndpointQueryTooExpensive(APIException):
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"""A customer query hit a Datastore cost guardrail — deterministic, so 400 (not a retry-inviting 5xx)."""
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status_code = status.HTTP_400_BAD_REQUEST
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default_code = "query_performance_limit"
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default_detail = "This query is too expensive to run inline. Narrow its scope or materialize the endpoint."
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class EndpointAtCapacity(APIException):
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"""Shared Datastore pool momentarily at capacity — transient; materializing gives isolated compute."""
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status_code = status.HTTP_503_SERVICE_UNAVAILABLE
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default_code = "query_capacity"
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default_detail = (
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"Queries are momentarily at capacity — please retry shortly. For consistently heavy "
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"endpoints, materialize to run on dedicated endpoint compute that isn't affected by shared query load."
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)
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