openwebui-cli 0.1.1

Command line client for Open WebUI, built on top of the openwebui-sdk library.

openwebui-cli

A thin terminal client for Open WebUI, built directly on the openwebui-sdk library. It adds only the terminal surface (argparse and a formatter) and maps flags onto the SDK's orchestration, so you get tool-using chats from a shell, with no browser and no server.

• Thin by design. All Open WebUI logic lives in the SDK; the CLI is a minimal flag→call wrapper you can study as an example of using the library.
• Tool execution from a terminal. ask runs the model's attached tools over Socket.IO (--tool, --no-tools), streaming reasoning and tool activity to stderr.
• Clean machine output. --plain for raw text, --json for a structured {answer, reasoning, tool_calls} blob, scripting-friendly.
• Chat persistence. --save writes the chat (with a generated title) back to the web UI sidebar.

openwebui-cli auth login --url http://localhost:8080 --email [e-mail]
openwebui-cli ask sample-workspace-model-1 "Use the tool to get current time." --json | jq -r .answer
# "The current time is 7:33 PM."

Agent skills

The CLI ships with a set of self-contained agent skills for working with it, authored in the skills.sh format (SKILL.md + optional references/) under skills/:

skill	what it covers
owui-auth	log in, saved profiles, whoami, env-var credentials, resolution precedence
owui-models	create/edit/delete workspace models, attach tools & functions
owui-tools	create/update/inspect Python tools and valves, canonical template
owui-functions	admin filter/action functions and valves
owui-ask	chat with a model, tool execution, structured/plain output

Install with the skills CLI:

npx skills add vedmaka/openwebui-sdk

Install

Install the CLI from the registry (PyPI-compatible; works with pip and uv). It depends on openwebui-sdk, which is pulled in automatically:

pip install openwebui-cli
# or with uv
uv add openwebui-cli

Quick start without installing — run it straight from the registry with uvx:

uvx openwebui-cli --help

Quick start

Sign in once. The token is saved to ~/.config/openwebui-cli/config.json (perms 0600):

openwebui-cli auth login --url http://localhost:8080 --email [e-mail]
# password is prompted via getpass

Use an API key instead of a password:

openwebui-cli auth login --url http://localhost:8080 --api-key sk-...

See who you are:

openwebui-cli auth whoami

List models:

openwebui-cli models list
openwebui-cli models list --json

Ask a model (streams tokens to stdout by default):

openwebui-cli ask llama3.1 "What is the capital of France?"
openwebui-cli ask llama3.1 "Summarize this" --system "Be concise" --no-stream
cat notes.txt | openwebui-cli ask gpt-4o "Tidy this up" --stdin

The model is the first positional argument; the remaining arguments form the prompt: ask <model> "<prompt>".

ask flags

flag	default	meaning
--system TEXT	(none)	optional system prompt leading the messages
--stdin	off	read prompt text from stdin (appended to any positional prompt)
--temperature N	(model default)	sampling temperature
--tool TOOL_ID	(model attached)	add a tool (repeatable); Adds to the model's attached tools
--no-tools	off	ignore model-attached tools; force plain HTTP streaming
--hide-tool-activity	off	suppress the ↳ name lines on stderr (tools still run)
--hide-reasoning	off	suppress chain-of-thought on stderr
--plain	off	disable all formatting + suppress reasoning/tool/status; pipe-friendly
--no-stream	off	wait for the full answer instead of streaming
--json	off	emit a structured JSON result {answer, reasoning, tool_calls} on stdout (works with or without tools); suppresses streaming/formatted output
--save	off	persist the chat to Open WebUI so it appears in the sidebar (creates a chat row, saves messages, generates a title). Default: chats are ephemeral
--url / --api-key / --token / --profile / --timeout	(profile)	see Ad-hoc usage

Tools in chat

By default, ask automatically enables any tools attached to the model (its info.meta.toolIds, the same field the web UI reads when it picks a model). So if your model has dummytools attached, this just works with no flags. The tool is available and the model decides whether to call it:

openwebui-cli ask sample-workspace-model-1 "Use the tool to get current time."

When tools are in play, the CLI connects a Socket.IO session (the only path Open WebUI runs the tool-call loop on), sends session_id + chat_id + message_id + tool_ids, and streams the answer back. Tool activity prints to stderr (↳ name … while running, ↳ name -> result when done); the model's final answer streams to stdout.

--tool TOOL_ID (repeatable) adds to the model's attached tools (deduped):

openwebui-cli ask sample-workspace-model-1 "..." --tool extra_tool

--no-tools opts out. It ignores the model's attached tools and uses the plain HTTP streaming path (no tool execution, no socket session):

openwebui-cli ask sample-workspace-model-1 "just answer" --no-tools

--hide-tool-activity suppresses the tool progress lines on stderr (↳ name … / ↳ name -> result) for a clean output. The tools still execute, only their display is hidden. Default: tool activity is shown.

openwebui-cli ask google/gemma-4-31b-it "..." --hide-tool-activity

Reasoning

Models that emit chain-of-thought (e.g. gpt-oss-120b) have their reasoning streamed to stderr by default, so the model's final answer stays clean on stdout. Use --hide-reasoning to suppress the reasoning for a clean output (it still streams from the model; only the display is hidden):

openwebui-cli ask openai/gpt-oss-120b "Think step by step." --hide-reasoning

Output formatting

By default, ask renders reasoning and tool activity inline on stderr in color (grey for reasoning, cyan for tool calls). No section headers, so the natural stream-of-consciousness order (reason → tool → reason → tool → answer) is preserved. The final answer goes to stdout, preceded by a blank line so it visually separates from the diagnostic stream:

[stderr] We need to call get_current_time...
[stderr]   ↳ get_current_time ...
[stderr]   ↳ get_current_time -> Current Date and Time = ...
[stderr]  
[stderr] Now we should respond with the result.
[stdout] 
[stdout] The current time is 7:33 PM.

When stdout is piped (not a TTY) color is skipped automatically so | grep, > file etc. keep working.

--plain disables all formatting and suppresses reasoning/tool/status entirely. It emits only the model's answer text on stdout. Use it for scripting:

openwebui-cli ask sample-workspace-model-1 "..." --plain | jq -r .

For finer control, --hide-reasoning and --hide-tool-activity suppress individual channels while keeping the rest.

JSON output (--json)

--json emits one machine-readable JSON object on stdout (nothing on stderr) and works the same whether or not the model has tools attached:

{
  "answer": "The current time is ...",
  "reasoning": "We need to call get_current_time ...",
  "tool_calls": [
    {"name": "get_current_time", "result": "Current Date and Time = ..."}
  ]
}

reasoning is null when the model didn't produce chain-of-thought; tool_calls is [] when no tools ran. With tools it routes through the Socket.IO path (so tools execute) and captures the structured result; without tools it uses the plain HTTP path. It suppresses all streaming/formatting, ideal for piping into jq or another tool:

openwebui-cli ask google/gemma-4-31b-it "Use the tool to get current time." --json | jq -r .answer

--json is mutually exclusive with --no-stream (you either stream or emit one JSON blob).

Chat persistence (--save)

By default, ask runs are ephemeral. The answer streams to stdout but no chat row is created in Open WebUI, so nothing appears in the sidebar. Add --save to persist the conversation:

openwebui-cli ask openai/gpt-4.1-nano "What is the capital of France?" --save
# stderr: [chat: 3f2b...9ee]
# → appears in the OWUI sidebar with a generated title + both messages

This mirrors the web UI flow:

1. POST /api/v1/chats/new - create a chat row, get the server-minted id
2. run the completion (plain HTTP, or Socket.IO if tools are attached)
3. POST /api/v1/tasks/title/completions - generate a title from the conversation
4. POST /api/v1/chats/{id} - persist the user+assistant messages and title

Note that --save persists messages with the serialized reasoning/tool-call <details> blocks intact, so the reasoning and tool calls render in the web UI when you open the chat.

Function calling mode (native vs. prompt-based) is also read from the model config (info.params.function_calling), just like the web UI, no flag needed. A model with function_calling: "native" configured uses OpenAI-style function calling automatically; one without uses Open WebUI's prompt-based tool calling (works on any model). The CLI never overrides model config.

Sign out / remove a profile:

openwebui-cli auth list          # what's stored
openwebui-cli auth logout default

Docker

A prebuilt image is published to GitHub Container Registry as part of the CI pipeline (docker job in .github/workflows/ci.yml, built from cli/Dockerfile). It runs as the non-root user owui (uid 1000, home /home/owui).

Tags: latest tracks the default branch; a v* tag push also publishes the semver (e.g. 0.1.0) and a commit-sha tag. Pin an explicit version when pulling reproducibly.

Run the CLI from a container

Pass credentials via env so no stored profile is needed:

docker run --rm \
  -e OPENWEBUI_URL=https://owui.example.com \
  -e OPENWEBUI_API_KEY=sk-... \
  ghcr.io/vedmaka/openwebui-cli:latest \
  ask sample-workspace-model-1 "What time is it?" --json

Or mount the profiles you saved on the host:

docker run --rm \
  -v ~/.config/openwebui-cli:/home/owui/.config/openwebui-cli \
  ghcr.io/vedmaka/openwebui-cli:latest auth whoami

Drop into a shell inside the container:

docker run --rm -it --entrypoint sh ghcr.io/vedmaka/openwebui-cli:latest
openwebui-cli --help

Add the CLI to your existing image

Use the published image as a build stage and copy the CLI into your own image (a multi-stage FROM). The CLI's Python version must match your target base (the published image is built on Python 3.13):

FROM ghcr.io/vedmaka/openwebui-cli:latest AS owui-cli

FROM python:3.13-slim
# your existing image setup ...

COPY --from=owui-cli /usr/local/bin/openwebui-cli /usr/local/bin/openwebui-cli
COPY --from=owui-cli /usr/local/lib/python3.13/site-packages \
                    /usr/local/lib/python3.13/site-packages

Both openwebui-sdk and openwebui-cli are on PyPI, so you can also install the CLI directly in your image and skip the COPY layer:

RUN pip install openwebui-cli

Models

Create, edit and delete workspace models (Settings → Workspace Models), in addition to models list.

# create from a JSON spec file
tee my-model.json <<'EOF'
{
  "name": "My Model",
  "base_model_id": "gpt-4o",
  "system": "You are a helpful assistant.",
  "tools": ["dummytools"],
  "capabilities": {"vision": true, "web_search": true},
  "function_calling": "native",
  "visibility": "private"
}
EOF
openwebui-cli models create my-model --spec-file my-model.json

# or provide the required values as flags (id + base model + name minimum)
openwebui-cli models create my-model --base-model gpt-4o --name "My Model" \
  --system "You are a helpful assistant." \
  --tool dummytools --function my_filter \
  --capabilities '{"vision": true}' \
  --function-calling native --visibility private

# edit an existing model (only the fields you pass change)
openwebui-cli models edit my-model --name "Better Name" \
  --system "New system prompt" --base-model gpt-4o \
  --tool dummytools --visibility public

# enable / disable tools for a model
openwebui-cli models tools add my-model dummytools web_search
openwebui-cli models tools remove my-model dummytools

# enable / disable functions (filters + actions) for a model
openwebui-cli models functions add my-model my_filter
openwebui-cli models functions remove my-model my_filter

# delete
openwebui-cli models delete my-model

The JSON spec file accepts the same fields as the flags: id, name, base_model_id, system, description, tools, functions, capabilities, function_calling and visibility. Flags given alongside --spec-file override the file. visibility maps to public (no access control) or private (owner only).

Tools

Create and manage workspace tools (Settings → Workspace Tools). The tool id must be a valid Python identifier ([A-Za-z_][A-Za-z0-9_]*); the server loads the source as a Tools class module and derives its function specs.

openwebui-cli tools list                       # all tools visible to you
openwebui-cli tools list --owned --json        # only your own / writable
openwebui-cli tools get my_tool                 # details + spec listing
openwebui-cli tools get my_tool --content       # raw source (for backup)

# create: source from an inline @file, --content-file, or --stdin
openwebui-cli tools create my_tool --name "My Tool" \
  --content @tools/my_tool.py --description "does X"
python -m openwebui_cli tools create my_tool --content-file my_tool.py

cat my_tool.py | openwebui-cli tools create my_tool --stdin

# update: omit --content to keep the current source (e.g. just rename)
openwebui-cli tools update my_tool --name "Better Name"
openwebui-cli tools update my_tool --description "new desc" --content @v2.py

# delete
openwebui-cli tools delete my_tool

# valves (admin config for a tool's Valves class)
openwebui-cli tools valves my_tool              # current values
openwebui-cli tools valves-spec my_tool         # JSON schema
openwebui-cli tools valves-set my_tool --data '{"api_key":"sk-..."}'
openwebui-cli tools valves-set my_tool --data-file valves.json

Functions

Create and manage workspace functions (Settings → Workspace Functions). Like tools, the function id must be a valid Python identifier; the server loads the source and derives its type (filter or action), which determines how a model can attach it. Requires an admin account.

openwebui-cli functions list                       # all functions visible
openwebui-cli functions list --json
openwebui-cli functions get my_filter               # details + type
openwebui-cli functions get my_filter --content     # raw source (for backup)

# create: source from an inline @file, --content-file, or --stdin
openwebui-cli functions create my_filter --name "My Filter" \
  --content @filters/my_filter.py --description "does X"
cat my_filter.py | openwebui-cli functions create my_filter --stdin

# update: omit --content to keep the current source (e.g. just rename)
openwebui-cli functions update my_filter --name "Better Name"
openwebui-cli functions update my_filter --description "new desc" --content @v2.py

# delete
openwebui-cli functions delete my_filter

# valves (admin config for a function's Valves class)
openwebui-cli functions valves my_filter
openwebui-cli functions valves-spec my_filter
openwebui-cli functions valves-set my_filter --data '{"api_key":"sk-..."}'
openwebui-cli functions valves-set my_filter --data-file valves.json

Ad-hoc usage (no saved profile)

Every server flag has an env-var equivalent, so you can drive Open WebUI from a script without persisting anything:

OPENWEBUI_URL=http://localhost:8080 \
OPENWEBUI_API_KEY=sk-... \
  openwebui-cli models list

Or pass flags directly:

openwebui-cli models list --url http://localhost:8080 --api-key sk-...
openwebui-cli ask llama3.1 "hi" --url http://localhost:8080 --token eyJ...

flag / env var	meaning
--url / OPENWEBUI_URL	base URL
--api-key / OPENWEBUI_API_KEY	sk-... API key (mutually exclusive with --token)
--token / OPENWEBUI_TOKEN	raw JWT bearer token
--profile / OPENWEBUI_PROFILE	name of a stored profile
--timeout / OPENWEBUI_TIMEOUT	per-request timeout (seconds, default 60)

Self-signed TLS

urllib verifies certificates by default. For a self-signed deployment, point Python at your CA rather than disabling verification:

SSL_CERT_FILE=/path/to/ca.pem openwebui-cli models list
# or, for a whole CA dir:
SSL_CERT_DIR=/etc/ssl/certs openwebui-cli models list

Exit codes

code	meaning
0	success
1	app error (auth, network, …)
2	usage / argument error
130	interrupted (Ctrl-C)

Layout

cli/
  pyproject.toml        # CLI distribution: openwebui-cli (depends on openwebui-sdk)
  src/openwebui_cli/
    __init__.py     # version
    __main__.py     # `python -m openwebui_cli`
    cli.py          # argparse subcommands: auth / models / tools / ask (thin wrapper over SDK)
    config.py       # profile persistence (~/.config/openwebui-cli/, perms 0600)
    formatting.py   # terminal output: inline color + answer separator, --plain mode
  tests/                  # <-- CLI tests (unittest)

The underlying Open WebUI library lives in the parent repo's ../README.md (openwebui-sdk).