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https://github.com/pchuan98/codex.git
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Zanie Blue
2ef007dc1a
## Summary - add partial SQLite indexes for visible thread lists ordered by creation or update time - match the `archived` and non-empty `preview` filters used by `thread/list` - add query-plan coverage for both supported sort orders ## Query performance Benchmarked the production query shape on a snapshot of my database with ~10k threads before and after applying these indexes. The query selected the full thread projection with `archived = 0`, `preview <> ''`, the `openai` provider filter, and a page size of 201. Results are the mean of 30 runs after 5 warmups: | Query | Before | After | Speedup | | --- | ---: | ---: | ---: | | First page, `created_at_ms DESC` | 132.3 ms | 15.1 ms | 8.78x | | First page, `updated_at_ms DESC` | 123.6 ms | 15.5 ms | 7.99x | | Cursor page near row 4,000, `created_at_ms DESC` | 51.8 ms | 16.8 ms | 3.07x | | Cursor page near row 4,000, `updated_at_ms DESC` | 52.4 ms | 17.1 ms | 3.06x | Before this change, SQLite used `idx_threads_archived`, filtered the candidate rows, and built a temporary B-tree for the requested ordering. With the partial indexes, SQLite reads matching visible rows directly in timestamp order and stops at the page limit. `EXPLAIN QUERY PLAN` no longer reports `USE TEMP B-TREE FOR ORDER BY`. The result rows were identical before and after. The two partial indexes occupy approximately 168 KiB combined on this snapshot. ## Performance under contention I noticed this issue on a database with high-contention and tried to use simulated contention to validate the performance in that context. A synthetic SQLite benchmark ran five concurrent readers, matching the state database pool size, and fetched 101 rows per query. Results are the median of three runs on fresh copies of the same database snapshot: | Query | Before | After | | --- | ---: | ---: | | `created_at_ms` mean latency under saturation | 328 ms | 12 ms | | `created_at_ms` throughput | 16 queries/s | 412 queries/s | | `updated_at_ms` mean latency under saturation | 336 ms | 14 ms | | `updated_at_ms` throughput | 15 queries/s | 357 queries/s | For a burst of 100 queries queued through five connections, p95 completion time fell from 6.90 seconds to 226 ms for `created_at_ms`, and from 6.31 seconds to 473 ms for `updated_at_ms`. ## Validation - `just test -p codex-state` (135 tests passed) - query-plan regression covers created-at and updated-at ordering, requires the corresponding index, and rejects `TEMP B-TREE` - `just fmt`
2ef007dc1a
·
2026-06-10 11:52:17 -05:00
7,292 Commits
Codex CLI is a coding agent from OpenAI that runs locally on your computer.
If you want Codex in your code editor (VS Code, Cursor, Windsurf), install in your IDE.
If you want the desktop app experience, run
codex app or visit the Codex App page.
If you are looking for the cloud-based agent from OpenAI, Codex Web, go to chatgpt.com/codex.
Quickstart
Installing and running Codex CLI
Run the following on Mac or Linux to install Codex CLI:
curl -fsSL https://chatgpt.com/codex/install.sh | sh
Run the following on Windows to install Codex CLI:
powershell -ExecutionPolicy ByPass -c "irm https://chatgpt.com/codex/install.ps1 | iex"
Codex CLI can also be installed via the following package managers:
# Install using npm
npm install -g @openai/codex
# Install using Homebrew
brew install --cask codex
Then simply run codex to get started.
You can also go to the latest GitHub Release and download the appropriate binary for your platform.
Each GitHub Release contains many executables, but in practice, you likely want one of these:
- macOS
- Apple Silicon/arm64:
codex-aarch64-apple-darwin.tar.gz - x86_64 (older Mac hardware):
codex-x86_64-apple-darwin.tar.gz
- Apple Silicon/arm64:
- Linux
- x86_64:
codex-x86_64-unknown-linux-musl.tar.gz - arm64:
codex-aarch64-unknown-linux-musl.tar.gz
- x86_64:
Each archive contains a single entry with the platform baked into the name (e.g., codex-x86_64-unknown-linux-musl), so you likely want to rename it to codex after extracting it.
Using Codex with your ChatGPT plan
Run codex and select Sign in with ChatGPT. We recommend signing into your ChatGPT account to use Codex as part of your Plus, Pro, Business, Edu, or Enterprise plan. Learn more about what's included in your ChatGPT plan.
You can also use Codex with an API key, but this requires additional setup.
Docs
This repository is licensed under the Apache-2.0 License.