Guilhem LemouelandClaude Opus 5
0e20a5d751
The flow chat ran on its own components; this points it at the ones the AI session chat already uses, so the two surfaces share a transcript, a composer and a sidebar instead of keeping two of each. The seam is `ChatViewHost` (copilot/chat/chatViewHost.ts): the view components read the host rather than `AIChatManager` directly, and `getChatViewHost()` falls back to the session manager, so the copilot's call sites are unchanged. `FlowChatViewHost` is the second adapter, over `FlowChatManager`. What the flow chat gains from the move: - turns running in several conversations at once, with a status, a queue and a Stop per chat, and an unread count on the rail - attachments, uploaded to the workspace's object storage for the worker to read - a composer that speaks for the agent steps a message is fed to: the model, the thinking effort, and the flow inputs the agent reads straight out of `flow_input`; everything else is asked for in a Configure-inputs modal - tool cards with the call and the result, the model's reasoning, and a step name per answer once a conversation holds more than one agent - Retry, which replays the failed turn's own run arguments read back from its job - named and renamable conversations, and test chats kept out of the deployed flow's list Backend: conversation rows carry an MCP tool's call and result and the model's reasoning, which live nowhere else; every row gets a job so retention can empty it; and the providers parse a non-streaming answer's reasoning. Stacked on #11134, which keeps the windmill-chat SDK for external frontends and raw apps while the in-app flow chat runs on these components. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Windmill CLI
A simple CLI allowing interactions with windmill from the command line.
You can find more information in Windmill Docs
Installation
Install the wmill CLI tool using npm install -g windmill-cli.
Update to the latest version using wmill upgrade.
Workspaces
To get started run wmill workspace add or use the instructions from the
workspace settings.
Running Flows & Scripts
Run a script or flow using wmill flow/script run u/username/path/to/script and
pass any inputs using --data + Inputs specified as a JSON string or a file
using @ <filename> or stdin using @-.
Curl-style syntax using -d @- for stdin or -d @<filename> is also supported.
Flow Steps and Logs will be streamed during execution automatically.
Pushing Resources, Scripts & More
The CLI can push specifications to a windmill instance. See the examples/ folder for formats.
Switch to a different workspace
wmill workspace switch <workspace_name>
Sync a workspace
Pull
wmill sync pull
Push
wmill sync push
We recommend using the --yaml option to use yaml instead of json as the encoding format. Yaml will be made the default soon.
Pushing individual files
You can push individual resources using
wmill <type> push <file_name> \<remote_name\>. This does not require a special
folder layout or file name, as this is given at runtime.
Listing
All commands support listing by just not providing a subcommand, ie
wmill script will result in a list of scripts. Some allow additional options,
learn about this by specifying --help.
User Management
You can add & remove users via wmill user add/remove, and list them using
wmill user
Pulling
You can pull the entire workspace using wmill pull
Completion
The CLI comes with completions out of the box via wmill completions <shell>.
(Via cliffy)
Bash
To enable bash completions add the following line to your ~/.bashrc:
source <(wmill completions bash)
Fish
To enable fish completions add the following line to your
~/.config/fish/config.fish:
source (wmill completions fish | psub)
Zsh
To enable zsh completions add the following line to your ~/.zshrc:
source <(wmill completions zsh)
Development
AI Guidance Variants
wmill init can now materialize alternate AI guidance bundles without changing
the generated defaults in the repo, but this is exposed as internal env-var
overrides rather than public CLI flags.
Examples:
WMILL_INIT_AI_SKILLS_SOURCE=/path/to/custom/skills wmill init --use-default
WMILL_INIT_AI_SKILLS_SOURCE=/path/to/custom/skills WMILL_INIT_AI_AGENTS_SOURCE=/path/to/AGENTS.md wmill init --use-default
WMILL_INIT_AI_SKILLS_SOURCE=/path/to/custom/skills WMILL_INIT_AI_CLAUDE_SOURCE=/path/to/CLAUDE.md wmill init --use-default
This is the same guidance-writing path used by the benchmark CLI under
ai_evals/, so the benchmark harness and wmill init now generate the same
project guidance shape:
AGENTS.mdCLAUDE.md.agents/skills/*.claude/skills/*
windmill-yaml-validator
wmill lint imports the sibling windmill-yaml-validator package from source rather than
from npm, so its schemas always match the OpenAPI specs of the current checkout. bun install regenerates them through this package's preinstall script; run it again after
editing openflow.openapi.yaml or backend/windmill-api/openapi.yaml:
npm --prefix ../windmill-yaml-validator run gen
Running Tests
Prerequisites:
- PostgreSQL running locally (default:
postgres://postgres:changeme@localhost:5432) - Rust toolchain installed
Run tests locally (full features):
bun test test/
Run tests in CI mode (minimal features, skips EE tests):
CI_MINIMAL_FEATURES=true bun test test/
| Variable | Description |
|---|---|
CI_MINIMAL_FEATURES |
Set to true to skip EE-dependent tests |
DATABASE_URL |
PostgreSQL connection string |
EE_LICENSE_KEY |
Enterprise license key for EE features |