centdix 4296a6ae1f feat(ai-chat): cap read_app_file + search_app grep tool to bound context in large raw apps (#9653)
* docs: add global AI chat context-optimization plan for raw apps

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* test(ai-evals): add global raw-app debugging cases on a large fixture

Adds a ~20-file analytics_dashboard raw-app fixture (incl. a 5k-line data module
and a planted wrong-totals bug), two global cases (read-heavy debug + small-edit
baseline), app-seed support in the mock backend, directory-fixture loading, and a
decorateHelpers seam so read-dedupe is measurable. Records tokenUsage for before/
after comparison of the read-tool optimization.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* feat(ai-chat): cap and dedupe read_app_file to bound context in large apps

read_app_file now defaults to a head slice (1500 lines / 50k chars) with offset/
limit to page further, and skips resending a file whose earlier read is still in
context (per-conversation ledger keyed off the originating tool-call id, so it
self-heals after compaction). Bounds the file-content portion of global-chat
context when working in large raw apps.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* test(ai-evals): add read-heavy raw-app debug case (large data module)

global-test31 induces the model to inspect the 5k-line seedData module, exercising
the read_app_file cap/offset path. Baseline ~262k tokens vs ~200k with the cap+dedupe
change (-24%).

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* docs: record A+B benchmark results and fixed-overhead finding

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* fix(ai-chat): clearer read_app_file past-EOF message + unit tests for cap/dedupe

Addresses local-review nits: out-of-range offset now reports 'offset N is past the
end of the file' instead of a backwards 'lines 11-10' label; adds unit coverage for
the slicing (line cap, offset/limit window, char budget, past-EOF) and re-read dedupe
(hit + miss-when-not-retained).

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* feat(ai-chat): char-level paging + per-range dedupe for read_app_file

Adds char_offset/char_limit so minified/long-line files can be paged within a line
window, keys the re-read ledger by range (so reading different ranges no longer
collides), and dedupes on the full-file hash (a cached range stub is invalidated
when any byte of the file changes, not just the returned range). Tests updated for
the char-slice behavior plus single-line capping, char paging, and out-of-window
change detection.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* test(ai-chat): add read_app_file context micro-benchmark + re-read eval case

Adds a deterministic micro-benchmark (no LLM) that drives read_app_file through a
realistic big-project read pattern (large file, re-read, minified bundle, paging)
and asserts the cap+dedupe cut returned context >50% vs the old whole-file behavior
— isolating the feature's effect from model nondeterminism and guarding against
silent weakening. Adds global-test32, a cross-file consistency investigation that
revisits overlapping files so re-read dedupe is exercised in a real run.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* test(ai-evals): clarify test32 measures the read cap, not dedupe

Verified: sonnet and haiku both read each file once per conversation and retain
it, so test32 never triggers read_app_file re-read dedupe. Dedupe is measured
deterministically by the micro-benchmark instead. Comment corrected to match.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* refactor(ai-chat): drop read_app_file re-read dedupe, ship the cap only

Benchmarking showed the per-conversation re-read dedupe never fires in practice:
across sonnet/opus/gpt-5.5/haiku, every model reads each file once per conversation
and keeps it in context (0 within-conversation re-reads). It was a correct but unused
guard, so this removes the ledger, full-file hash, retention predicate, the
AIChatManager wiring, and the eval decorateHelpers seam — keeping the read cap +
offset/limit/char paging (A), which is the lever that actually bounds context. The
micro-benchmark is now cap-only; test32 is kept as a multi-file read-load case.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* feat(ai-chat): add search_app grep tool for global raw-app chat (experimental)

Client-side grep over a raw app's frontend files and inline runnables (literal,
case-insensitive, optional file_glob/context_lines/max_matches, head-capped).
Completes the list -> search -> ranged-read triad. Includes the eval A/B gate
(WMILL_AI_EVAL_DISABLE_SEARCH_APP), unit tests + micro-benchmark, and a
find-all-usages eval case (global-test33).

Experimental: A/B benchmarking shows it is not an unconditional win — it helps
on find-all-usages but adds agentic iterations on navigable apps.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* test(ai-evals): accept search_app as a valid file-inspection tool in raw-app cases

Add requiredToolsAnyOf alternatives-group to ToolValidationSpec and switch
global-test29..32 to it so a model that locates files via search_app instead
of read_app_file no longer false-fails the tool assertion.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* docs: remove stale ai-chat context-optimization planning doc

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* refactor(ai-chat): drop read_app_file char paging for a hard char cap

The char_offset/char_limit params guarded minified files (a single line over
the char budget) but were effectively unused in benchmarks. Remove them and the
in-window char paging; keep the hard 50k-char budget and, when a read hits it,
tell the model to narrow the line limit (or treat the file as unreadable if a
single line exceeds the budget). Proper long-line handling is left as a TODO.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* refactor(ai-chat): bake search_app context to 1 line, clarify query is literal

Drop the context_lines param (models varied it to little effect) for a fixed
SEARCH_APP_CONTEXT_LINES=1, and cap on matching lines instead of pushed rows so
max_matches stays accurate with context always on. Sharpen the query description
to state it is a literal (non-regex) substring and to suggest the call form
(e.g. formatCurrency() to hit call sites and skip formatCurrencyPrecise.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* refactor(ai-chat): widen baked search_app context to 2 lines

Models that set the old context_lines param leaned to 2; match the lean.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* fix(ai-chat): count every file with a match in search_app header

Move fileHadMatch ahead of the render cap so files whose matches fall past max_matches are still counted (with a regression test). Also swap the raw NUL globstar sentinel for a printable escape (the NUL bytes made core.ts read as binary to grep) and reword two comments to describe current constraints instead of drafting history.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* fix(ai-chat): drop redundant input echoes from app tool results

read_app_file and search_app no longer prefix results with the tool name or echo back the caller's own inputs (file path, query, file_glob) — the model already has them from the call args, and the unbounded query echo could push the search result past its output budget. Keeps the useful signals (line range, match/file counts, truncation) and the actionable advice. Also reword max_matches to 'matching lines' since it caps lines (each expands to context rows). Unit tests updated to the new format.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

---------

Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
2026-06-19 13:33:54 +00:00
2024-02-08 16:09:11 +01:00
2026-06-19 11:34:59 +00:00
2026-06-18 18:09:02 +02:00
2026-02-03 17:50:56 +00:00
2026-06-19 11:34:59 +00:00
2023-08-26 09:17:07 +02:00
2025-04-21 16:53:23 +02:00
2026-06-18 18:09:02 +02:00
2026-04-16 06:26:25 -07:00
2025-12-08 10:34:16 +00:00
2026-02-11 16:30:19 +00:00
2025-03-07 15:08:19 +01:00
2022-05-05 04:25:58 +02:00
2026-02-16 23:36:41 +00:00
2024-02-08 16:09:11 +01:00

windmill.dev

Open-source developer platform for internal code: APIs, background jobs, workflows and UIs. Self-hostable alternative to Retool, Pipedream, Superblocks and a simplified Temporal with autogenerated UIs and custom UIs to trigger workflows and scripts as internal apps.

Scripts are turned into sharable UIs automatically, and can be composed together into flows or used into richer apps built with low-code. Supported languages: Python, TypeScript, Go, Bash, SQL, GraphQL, PowerShell, Rust, and more.

Package version Docker Image CI Package version

Commit activity Discord Shield

Try it - Website - Docs - Discord - Hub - Contributor's guide

Windmill - Developer platform for APIs, background jobs, workflows and UIs

Windmill is fully open-sourced (AGPLv3) and Windmill Labs offers dedicated instances and commercial support and licenses.

Windmill Diagram

https://github.com/user-attachments/assets/d80de1d9-64de-4d89-aacd-6df23fa81fc4

Main Concepts

  1. Define a minimal and generic script in Python, TypeScript, Go or Bash that solves a specific task. The code can be defined in the provided Web IDE or synchronized with your own GitHub repo (e.g. through VS Code extension): provided Web IDE or synchronized with your own GitHub repo (e.g. through VS Code extension):

Step 1

  1. Your scripts parameters are automatically parsed and generate a frontend.

Step 2

Step 3

  1. Make it flow! You can chain your scripts or scripts made by the community shared on WindmillHub.

Step 3

  1. Build complex UIs on top of your scripts and flows.

Step 4

Scripts and flows can be triggered by schedules, webhooks, HTTP routes, Kafka, WebSockets, emails, and more.

Build your entire infra on top of Windmill!

Show me some actual script code

//import any dependency  from npm
import * as wmill from "windmill-client";
import * as cowsay from "cowsay@1.5.0";

// fill the type, or use the +Resource type to get a type-safe reference to a resource
type Postgresql = {
  host: string;
  port: number;
  user: string;
  dbname: string;
  sslmode: string;
  password: string;
};

export async function main(
  a: number,
  b: "my" | "enum",
  c: Postgresql,
  d = "inferred type string from default arg",
  e = { nested: "object" }
  //f: wmill.Base64
) {
  const email = process.env["WM_EMAIL"];
  // variables are permissioned and by path
  let variable = await wmill.getVariable("f/company-folder/my_secret");
  const lastTimeRun = await wmill.getState();
  // logs are printed and always inspectable
  console.log(cowsay.say({ text: "hello " + email + " " + lastTimeRun }));
  await wmill.setState(Date.now());

  // return is serialized as JSON
  return { foo: d, variable };
}

Local Development

Windmill supports multiple ways to develop locally and sync with your instance:

Tool Description
CLI Sync scripts from local files or GitHub, run scripts/flows from the command line
VS Code Extension Edit and test scripts & flows directly from VS Code / Cursor with full IDE support
Git Sync Two-way sync between Windmill and your Git repository
Claude Code AI-assisted development with Claude for scripts, flows, and apps

https://github.com/user-attachments/assets/c541c326-e9ae-4602-a09a-1989aaded1e9

You can run scripts locally by passing the right environment variables for the wmill client library to fetch resources and variables from your instance. See local development docs.

Stack

  • Database: Postgres (compatible with Aurora, Cloud SQL, Neon, Azure PostgreSQL)
  • Backend: Rust - stateless API servers and workers pulling jobs from a Postgres queue
  • Frontend: Svelte 5
  • Sandboxing: nsjail and PID namespace isolation
  • Runtimes:
    • TypeScript/JavaScript: Bun (default) and Deno
    • Python: python3 with uv for dependency management
    • Go, Bash, PowerShell, PHP, Rust, C#, Java, Ansible

Fastest Self-Hostable Workflow Engine

We have compared Windmill to other self-hostable workflow engines (Airflow, Prefect & Temporal) and Windmill is the most performant solution for both benchmarks: one flow composed of 40 lightweight tasks & one flow composed of 10 long-running tasks.

All methodology & results on our Benchmarks page.

Fastest workflow engine

Security

  • Sandboxing: nsjail for filesystem/resource isolation, and PID namespace isolation (enabled by default) to prevent jobs from accessing worker process memory
  • Secrets: One encryption key per workspace for credentials stored in Windmill's K/V store. We recommend encrypting the Postgres database as well.

See Security documentation for details.

Performance

Once a job started, there is no overhead compared to running the same script on the node with its corresponding runner (Deno/Go/Python/Bash). The added latency from a job being pulled from the queue, started, and then having its result sent back to the database is ~50ms. A typical lightweight deno job will take around 100ms total.

Architecture

How to self-host

For detailed setup options, see Self-Host documentation.

Docker compose

Deploy Windmill with 3 files (docker-compose.yml, Caddyfile, .env):

curl https://raw.githubusercontent.com/windmill-labs/windmill/main/docker-compose.yml -o docker-compose.yml
curl https://raw.githubusercontent.com/windmill-labs/windmill/main/Caddyfile -o Caddyfile
curl https://raw.githubusercontent.com/windmill-labs/windmill/main/.env -o .env

docker compose up -d

Go to http://localhost - default credentials: admin@windmill.dev / changeme

Using an external database: Set DATABASE_URL in .env to point to your managed Postgres (AWS RDS, GCP Cloud SQL, Azure, Neon, etc.) and set db replicas to 0.

Kubernetes (Helm charts)

helm repo add windmill https://windmill-labs.github.io/windmill-helm-charts/
helm install windmill-chart windmill/windmill --namespace=windmill --create-namespace

See windmill-helm-charts for configuration options.

Cloud providers

Windmill works on AWS (EKS/ECS), GCP, Azure, Ubicloud, Fly.io, Render.com, Hetzner, Digital Ocean, and others. Rule of thumb: 1 worker per 1vCPU and 1-2 GB RAM.

OAuth, SSO & SMTP

Configure OAuth and SSO (Google Workspace, Microsoft/Azure, Okta) directly from the superadmin UI. See documentation.

License

The Community Edition is free to use internally. For commercial redistribution or managed services, contact sales@windmill.dev. See LICENSE and Pricing for details.

The "Community Edition" of Windmill available in the docker images hosted under ghcr.io/windmill-labs/windmill and the github binary releases contains the files under the AGPLv3 and Apache 2 sources but also includes proprietary and non-public code and features which are not open source and under the following terms: Windmill Labs, Inc. grants a right to use all the features of the "Community Edition" for free without restrictions other than the limits and quotas set in the software and a right to distribute the community edition as is but not to sell, resell, serve Windmill as a managed service, modify or wrap under any form without an explicit agreement.

The binary compilable from source code in this repository without the "enterprise" feature flag is open-source under the LICENSE-AGPLv3 License terms and conditions.

To re-expose directly any Windmill parts to your users as a feature of your product, with the exception of iframed public Windmill "apps", or to build a feature on top of "Windmill Community Edition" that you sell commercially or embed in a distributable product or binary, you must get a commercial license. Contact us at sales@windmill.dev if you have any questions. To do the same from the binary compiled from the source code in this repository without the "enterprise" feature flag, you must comply with the AGPLv3 license terms and conditions or get a commercial license from Windmill Labs, Inc.

To use Windmill "Community Edition" as is internally in your organization, or to use its APIs as is, you do NOT need a commercial license.

Integrations

In Windmill, integrations are referred to as resources and resource types. Each Resource has a Resource Type that defines the schema that the resource needs to implement.

On self-hosted instances, you might want to import all the approved resource types from WindmillHub. A setup script will prompt you to have it being synced automatically everyday.

Environment Variables

Environment Variable name Default Description Api Server/Worker/All
DATABASE_URL The Postgres database url. All
WORKER_GROUP default The worker group the worker belongs to and get its configuration pulled from Worker
MODE standalone The mode if the binary. Possible values: standalone, worker, server, agent All
METRICS_ADDR None (ee only) The socket addr at which to expose Prometheus metrics at the /metrics path. Set to "true" to expose it on port 8001 All
JSON_FMT false Output the logs in json format instead of logfmt All
BASE_URL http://localhost:8000 The base url that is exposed publicly to access your instance. Is overriden by the instance settings if any. Server
ZOMBIE_JOB_TIMEOUT 30 The timeout after which a job is considered to be zombie if the worker did not send pings about processing the job (every server check for zombie jobs every 30s) Server
RESTART_ZOMBIE_JOBS true If true then a zombie job is restarted (in-place with the same uuid and some logs), if false the zombie job is failed Server
NATIVE_MODE false Enable native mode: sets NUM_WORKERS=8, rejects non-native jobs (nativets, postgresql, mysql, etc.) Worker
SLEEP_QUEUE 50 The number of ms to sleep in between the last check for new jobs in the DB. It is multiplied by NUM_WORKERS such that in average, for one worker instance, there is one pull every SLEEP_QUEUE ms. Worker
KEEP_JOB_DIR false Keep the job directory after the job is done. Useful for debugging. Worker
LICENSE_KEY (EE only) None License key checked at startup for the Enterprise Edition of Windmill Worker
SLACK_SIGNING_SECRET None The signing secret of your Slack app. See Slack documentation Server
COOKIE_DOMAIN None The domain of the cookie. If not set, the cookie will be set by the browser based on the full origin Server
DENO_PATH /usr/bin/deno The path to the deno binary. Worker
PYTHON_PATH The path to the python binary if wanting to not have it managed by uv. Worker
GO_PATH /usr/bin/go The path to the go binary. Worker
GOPRIVATE The GOPRIVATE env variable to use private go modules Worker
GOPROXY The GOPROXY env variable to use Worker
NETRC The netrc content to use a private go registry Worker
PY_CONCURRENT_DOWNLOADS 20 Sets the maximum number of in-flight concurrent python downloads that windmill will perform at any given time. Worker
PATH None The path environment variable, usually inherited Worker
HOME None The home directory to use for Go and Bash , usually inherited Worker
DATABASE_CONNECTIONS 50 (Server)/3 (Worker) The max number of connections in the database connection pool All
SUPERADMIN_SECRET None A token that would let the caller act as a virtual superadmin superadmin@windmill.dev Server
TIMEOUT_WAIT_RESULT 20 The number of seconds to wait before timeout on the 'run_wait_result' endpoint Worker
QUEUE_LIMIT_WAIT_RESULT None The number of max jobs in the queue before rejecting immediately the request in 'run_wait_result' endpoint. Takes precedence on the query arg. If none is specified, there are no limit. Worker
DENO_AUTH_TOKENS None Custom DENO_AUTH_TOKENS to pass to worker to allow the use of private modules Worker
DISABLE_RESPONSE_LOGS false Disable response logs Server
CREATE_WORKSPACE_REQUIRE_SUPERADMIN true If true, only superadmins can create new workspaces Server
MIN_FREE_DISK_SPACE_MB 15000 Minimum amount of free space on worker. Sends critical alert if worker has less free space. Worker
RUN_UPDATE_CA_CERTIFICATE_AT_START false If true, runs CA certificate update command at startup before other initialization All
RUN_UPDATE_CA_CERTIFICATE_PATH /usr/sbin/update-ca-certificates Path to the CA certificate update command/script to run when RUN_UPDATE_CA_CERTIFICATE_AT_START is true All

Run a local dev setup

We recommend using Nix. See ./frontend/README_DEV.md for all options.

Frontend only

Uses the backend of https://app.windmill.dev with local frontend (hot-reload):

cd frontend
npm install
npm run generate-backend-client  # or generate-backend-client-mac on Mac
npm run dev

Windmill available at http://localhost/

Backend + Frontend

See the ./frontend/README_DEV.md file for all running options.

  1. Start a local Postgres database using for instance the start-dev-db.sh script which will make a database available at postgres://postgres:changeme@localhost:5432/windmill Then run the migrations using the following command:
    cargo install sqlx-cli
    env DATABASE_URL=<YOUR_DATABASE_URL> sqlx migrate run
    
    This will also avoid compile time issue with sqlx's query! macro.
  2. (optional, linux only) Install nsjail and have it accessible in your PATH
  3. Install bun, deno and python3 (+ any languages you want to use), have the bins at /usr/bin/bun,/usr/bin/deno, and /usr/local/bin/python3 or set the corresponding environment variables.
  4. (optional) Install the lld linker
  5. Go to frontend/:
    1. npm install, npm run generate-backend-client then REMOTE=http://localhost:8000 npm run dev
    2. You might need to set some extra heap space for the node runtime export NODE_OPTIONS="--max-old-space-size=4096"
    3. Create an empty frontend/build folder using mkdir frontend/build
  6. Go to backend/:
    1. env DATABASE_URL=<YOUR_DATABASE_URL> RUST_LOG=info cargo run
    2. You can specify any feature flag you want to enable, for example cargo run --features python to enable the python executor.
  7. Windmill should be available at http://localhost:3000

Contributors

© 2023-2026 Windmill Labs, Inc.

S
Description
Open-source developer platform to power your entire infra and turn scripts into webhooks, workflows and UIs. Fastest workflow engine (13x vs Airflow). Open-source alternative to Retool and Temporal.
Readme 827 MiB
Languages
Rust 33.4%
Svelte 24.3%
TypeScript 24.2%
HTML 14%
JavaScript 1.6%
Other 2.3%