roboomp
aa463f9008
Calling /compact remote with an OpenAI/Responses active model + a
non-remote compactionModel (e.g. an Anthropic summarizer) used to leave
remoteReady=true on the readiness check via shouldUseOpenAiRemoteCompaction(
this.model), but #compactWithFallbackModel walked the candidate chain
starting from the configured compactionModel and ran a local summary on it
— silently doing the opposite of the explicit mode.
Make the readiness check and candidate selection share one source of truth.
When /compact remote is requested and no compaction.remoteEndpoint is set
(an endpoint short-circuits per-model gating in compact()), filter the
candidate chain through shouldUseOpenAiRemoteCompaction so non-remote
fallbacks are skipped. If the filter empties the chain, warn and fall back
to the unfiltered chain so the operation still completes — matching the
spirit of the prior warning. The filter is threaded through
#getCompactionModelCandidates / #resolveCompactionModelCandidates and the
resolved candidates are passed into #compactWithFallbackModel so both
paths see the same list.
Added a regression test that wires an OpenAI active model with an Anthropic
compactionModel, invokes session.compact({ mode: 'remote' }), and asserts
the OpenAI model — not the configured compactionModel — is the first
candidate handed to compact().
Fixes #3104
@oh-my-pi/pi-coding-agent
Core implementation package for the omp coding agent in the oh-my-pi monorepo.
For installation, setup, provider configuration, model roles, slash commands, and full CLI reference, see:
Package-specific references:
Memory backends
The agent supports three mutually-exclusive memory backends, selected via the memory.backend setting (Settings → Memory tab, or ~/.omp/config.yml):
off(default) — no memory subsystem runs.local— existing rollout-summarisation pipeline; writesmemory_summary.mdand consolidated artifacts under the agent dir.hindsight— talks to a Hindsight server (Cloud or self-hosted Docker), retains transcripts every Nth user turn, recalls memories on the first turn of a session, and exposesretain,recall, andreflect.
Hindsight quickstart
- Run a Hindsight server (Cloud or
docker run -p 8888:8888 ghcr.io/vectorize-io/hindsight:latest). - Set
memory.backend = "hindsight"andhindsight.apiUrl = "http://localhost:8888"(or your Cloud URL). - Optional environment overrides (env wins over settings):
HINDSIGHT_API_URL,HINDSIGHT_API_TOKEN— connectionHINDSIGHT_BANK_ID,HINDSIGHT_DYNAMIC_BANK_ID,HINDSIGHT_AGENT_NAME— bank addressingHINDSIGHT_AUTO_RECALL,HINDSIGHT_AUTO_RETAIN,HINDSIGHT_RETAIN_MODE— lifecycleHINDSIGHT_RECALL_BUDGET,HINDSIGHT_RECALL_MAX_TOKENS— recall sizingHINDSIGHT_BANK_MISSION,HINDSIGHT_DEBUG
Switching backends mid-session is honoured on the next system-prompt rebuild and the next /memory slash command. Existing users with memories.enabled = true|false are migrated to memory.backend = "local"|"off" exactly once on first launch.