Commit Graph
6 Commits
Author SHA1 Message Date
Celia ChenandGitHub 51fc4b0559 feat: use provider defaults for memory models (#27129)
## Why

Memory startup used hardcoded OpenAI model slugs for extraction and
consolidation. That works for the default OpenAI-compatible path, but
provider-specific backends can require different model identifiers. In
particular, Amazon Bedrock should use its Bedrock model ID for these
background memory requests instead of the OpenAI `gpt-5.4-mini` /
`gpt-5.4` slugs.

## What Changed

- Added provider-owned preferred memory model methods alongside
`approval_review_preferred_model`.
- Updated memory extraction and consolidation to resolve their default
model through the active `ModelProvider`.
- Added Amazon Bedrock overrides so both memory stages use
`openai.gpt-5.4` through Bedrock’s provider-specific model ID.
- Kept explicit `memories.extract_model` and
`memories.consolidation_model` config overrides taking precedence.
- Added startup coverage for default OpenAI and Bedrock memory model
selection.

#closes #26288
2026-06-09 23:49:09 +00:00
jif-oaiandGitHub aad59a0916 Move memory state to a dedicated SQLite DB (#24591)
## Summary

Generated memory rows and their stage-one/stage-two job state currently
live in `state_5.sqlite` alongside thread metadata. That makes memory
cleanup and regeneration share the main state schema even though those
rows are memory-pipeline data and can be rebuilt independently from the
durable thread records.

This PR moves the memory-owned tables into a dedicated
`memories_1.sqlite` runtime database while keeping thread metadata in
`state_5.sqlite`.

## Changes

- Adds a separate memories DB runtime, migrator, path helpers, telemetry
kind, and Bazel compile data for `state/memory_migrations`.
- Introduces `MemoryStore` behind `StateRuntime::memories()` and moves
memory table/job operations onto that store.
- Drops the old memory tables from the state DB and recreates their
schema in `state/memory_migrations/0001_memories.sql`.
- Updates memory startup, citation usage tracking, rollout pollution
handling, `debug clear-memories`, and app-server `memory/reset` to
operate through the memories DB.
- Preserves cross-DB behavior by hydrating thread metadata from the
state DB when selecting visible memory outputs and checking stage-one
staleness.

## Verification

- Added/updated `codex-state` tests for deleted-thread memory visibility
and already-polluted phase-two enqueue behavior.
- Updated `debug clear-memories`, app-server `memory/reset`, and
memories startup tests to seed and assert memory rows through
`memories_1.sqlite`.
2026-05-26 20:07:25 +02:00
jif-oaiandGitHub 5b7d6f5c4f feat: house-keeping memories 3 (#20005)
Move stuff in memories, no behavioural change expected
2026-04-28 18:13:35 +02:00
jif-oaiandGitHub 21e19912e0 feat: house-keeping memories 2 (#20000)
Just move metrics in a dedicated file
2026-04-28 17:26:44 +02:00
a9e5c34083 feat: trigger memories from user turns with cooldown (#19970)
## Why

Memory startup was tied to thread lifecycle events such as create, load,
and fork. That can run memory work before a thread receives real user
input, and it makes startup cost scale with thread management instead of
actual turns. Moving the trigger to `thread/sendInput` keeps memory
startup aligned with the first real user turn and lets it use the
current thread config at turn time.

The idea is to prevent ghost cost due to pre-warm triggered by the app

Turn-based startup can also make global phase-2 consolidation easier to
request repeatedly, so this adds a success cooldown and tightens the
default startup scan window.

## What Changed

- Start `codex_memories_write::start_memories_startup_task` after a
non-empty `thread/sendInput` turn is submitted, instead of from thread
create/load/fork paths:
https://github.com/openai/codex/blob/d4a6885b7829e2fd2ec7a09355e4f75ebe1d1fe3/codex-rs/app-server/src/codex_message_processor.rs#L6477-L6487
- Expose `CodexThread::config()` so app-server can pass the live config
into memory startup at turn time.
- Add a six-hour successful-run cooldown for global phase-2
consolidation via `SkippedCooldown`:
https://github.com/openai/codex/blob/d4a6885b7829e2fd2ec7a09355e4f75ebe1d1fe3/codex-rs/state/src/runtime/memories.rs#L963-L966
- Reduce memory startup defaults to at most 2 rollouts over 10 days:
https://github.com/openai/codex/blob/d4a6885b7829e2fd2ec7a09355e4f75ebe1d1fe3/codex-rs/config/src/types.rs#L31-L34

## Verification

Updated the memory runtime coverage around phase-2 reclaim behavior,
including `phase2_global_lock_respects_success_cooldown`.

---------

Co-authored-by: Codex <noreply@openai.com>
2026-04-28 16:23:13 +02:00
431ebeaef7 feat: split memories part 2 (#19860)
Keep extracting memories out of core and moving the write trigger in the
app-server
This is temporary and it should move at the client level as a follow-up
This makes core fully independant from `codex-memories-write`

---------

Co-authored-by: Codex <noreply@openai.com>
2026-04-28 13:03:28 +02:00