agentwerk (Python)
Why use agentwerk?
- Simple interface: create agents with a few lines of code.
- Efficient harness: optimized for fast LLMs with low memory footprint.
- Complex interactions: allow agents to collaborate through queues, event hooks and shared knowledge.
- Deep observability: inspect every request, tool call, and failure.
- Facilitate training: store trajectories based on granular events for fine-tuning models.
Installation
Python
pip install agentwerk
Also see: Rust implementation.
Quick Start
import asyncio
from agentwerk import Agent, GrepTool, ReadFileTool
async def main():
agent = (
Agent.from_env()
.role("You are a Rust developer who explores source files to answer questions.")
.tool(ReadFileTool())
.tool(GrepTool())
.build()
)
agent.task(
"Find every `pub trait` defined under src/ and explain each in one sentence."
)
work = agent.start()
result = await work.finish_last()
print(result)
asyncio.run(main())
API
- Agents: Define roles, behavior and actions.
- Tickets: Coordinate complex work across agents.
- Tools: Define accessible tooling.
- Events: Requests, tool usage, failures and more.
- Knowledge: Notes agents can share for collaboration.
Agents
An Agent is the core entity of agentwerk. It has access to tools for solving tasks in the form of tickets.
from agentwerk import Agent, ReadFileTool
agent = (
Agent.from_env()
.role("You are a release manager who prepares release notes.")
.tool(ReadFileTool())
.build()
)
agent.task("Read CHANGELOG.md and summarize the entries added since the last release.")
agent.start()
All agent methods
| Method | Description | |
|---|---|---|
| Configure | role(role) |
Define who the agent is and how it should work. |
tool(tool) / tools(tools) |
Register a tool the agent may call. | |
label(label) |
Restrict the agent to tickets carrying this label. | |
dir(dir) |
Set the directory the agent has access to. | |
template(key, value) |
Inject data into prompts with template strings. | |
templates(variables) |
Inject more than one entry into prompts. | |
knowledge(store) |
Share a knowledge store with the agent. | |
interactive() |
Let the agent wait for new instructions to keep a ticket in-progress. | |
build() |
Create the agent. | |
| Work | task(task) |
Submit a task and return its ticket key. |
ticket(ticket) |
Submit a Ticket with a custom label or schema. |
|
start() |
Begin processing tickets. | |
id |
Get the unique identifier of an agent. |
You can use the {context} variable to inject contextual information:
- Ticket: TICKET-7
- Date: 2026-05-06
- Working directory: /Users/caro
- Platform: darwin 25.1.0
- Turns remaining: 8
- Input tokens remaining: 95000
- Output tokens remaining: 12000
- Time remaining: 240s
Every value is a variable of its own: {ticket}, {date}, {dir}, {platform}, {os_version}, {turns_remaining}, {input_tokens_remaining}, {output_tokens_remaining}, and {time_remaining}.
See more: AgentBuilder.
Providers
A Provider gives agents access to LLMs: Anthropic, OpenAI, Mistral, and a LiteLLM proxy.
from agentwerk import Agent, Anthropic
agent = (
Agent()
.provider(Anthropic(key))
.model("claude-sonnet-4-20250514")
)
All provider and model settings
| Method | Description |
|---|---|
provider(provider) |
Define the LLM provider. |
model(model) |
Set the model. |
Agent.from_env() |
Read the provider and the model from environment variables. |
You can also read the model or provider individually: .provider(Provider.from_env()) or .model(Model.from_env()).
| Variable | Description |
|---|---|
LITELLM_PROVIDER |
Choose anthropic, mistral, openai, or litellm outright, ahead of the keys below. |
LITELLM_API_KEY, MISTRAL_API_KEY, ANTHROPIC_API_KEY, OPENAI_API_KEY |
Authenticate against that vendor. The first one set picks the provider, in this order. |
LITELLM_BASE_URL, MISTRAL_BASE_URL, ANTHROPIC_BASE_URL, OPENAI_BASE_URL |
Point that vendor at a different endpoint. |
SSL_CERT_FILE, SSL_CERT_DIR |
Trust these CA certificates instead of the built-in root store. |
You can configure models to set a custom context window size or the applied reasoning. Claude, GPT, Mistral, and Qwen families are pre-configured.
| Method | Description |
|---|---|
context_window(size) |
Set the context window size for a model. |
get_context_window() |
Get the configured window size. |
reasoning_effort(effort) |
Set the reasoning level. |
get_reasoning_effort() |
Get the configured effort. |
| Variable | Description |
|---|---|
MODEL |
Model name. |
ANTHROPIC_MODEL, OPENAI_MODEL, MISTRAL_MODEL, LITELLM_MODEL |
Model name for the detected provider, read when MODEL is unset. |
MODEL_CONTEXT_WINDOW |
Context window size in tokens. |
Configure a custom model:
from agentwerk import Agent, Model
agent = Agent().model(
Model("my-local-model").context_window(128_000).reasoning_effort("high")
)
Tickets
The TicketQueue is the core data structure of agentwerk for coordinating complex interactions.
from agentwerk import Agent, Ticket, TicketQueue
analyst = (
Agent.from_env()
.label("analysis")
.build()
)
writer = (
Agent.from_env()
.label("report")
.build()
)
tickets = TicketQueue()
tickets.agent(analyst).agent(writer)
tickets.ticket(Ticket("Rank all products by value.", label="analysis"))
tickets.ticket(Ticket("Write up the ranking.", label="report"))
All ticket methods
| Method | Description | |
|---|---|---|
| Configure | agent(agent) |
Add an agent to this ticket queue. |
schemas(store) |
Enforce schemas for ticket results. | |
dir(dir) |
Define where a session is stored. | |
get_dir() |
Get the session directory. | |
| Submit | task(task) |
Submit a task and return its ticket key. |
ticket(ticket) |
Submit a Ticket with a custom label or schema, and return its key. |
|
| Read | results() |
Get the result of every finished ticket, in creation order. |
tickets() |
Get every ticket in creation order. | |
find_ticket(condition) |
Get the earliest ticket matching a condition. | |
find_tickets(condition) |
Get every ticket matching a condition. | |
get_ticket(key) |
Get one ticket by key. | |
| Drive | reply(key, content) |
Add a reply to a ticket. |
edit_replies(key, editor) |
Rewrite a ticket's replies now. | |
| Resolve | set_finished(key, result) |
Finish a ticket with a result. |
set_failed(key) |
Fail a ticket. |
See TicketQueue.
Execution
The ticket queue schedules the work of your agents and returns their results.
tickets.start()
answer = await tickets.finish_last()
if answer is not None:
print(answer)
All execution methods
| Method | Description | |
|---|---|---|
| Run | start() |
Begin processing tickets. |
| Wait | await finish(matches) |
Wait for the matching tickets to be done and get their results. |
await finish_all() |
Wait for every ticket to be finished and get every result. | |
await finish_last() |
Wait for every ticket to be finished and get the last result. | |
finish_reason() |
Get why the last run ended. | |
| Stop | cancel(matches) |
Stop work on the matching tickets. |
cancel_all() |
Stop work on every ticket. | |
is_cancelled(ticket) |
Check whether a ticket has been cancelled. |
Ticket members:
| Member | Description | |
|---|---|---|
| Identity | key |
Ticket key, of the form TICKET-N. |
task |
The work the agent is asked to do. | |
label |
Label carried by the ticket. | |
parent |
The parent ticket if a handover was performed. | |
reporter |
Identifier of the agent that created the ticket. | |
assignee |
Identifier of the agent that claimed the ticket. | |
| Outcome | status |
The ticket lifecycle status. |
result |
The result the agent produced. | |
replies |
Messages exchanged with the model. | |
schema |
Optional schema the result must satisfy. | |
| Timestamps | created_at |
Creation time, in milliseconds. |
started_at |
Claim time, in milliseconds. | |
finished_at |
Finish time, in milliseconds. | |
failed_at |
Failure time, in milliseconds. | |
| Checks | has_label(label) |
Check whether the ticket carries a label. |
is_todo() |
Check whether the ticket is waiting to be claimed. | |
is_in_progress() |
Check whether an agent is working on the ticket. | |
is_finished() |
Check whether the ticket finished. | |
is_failed() |
Check whether the ticket failed. | |
is_pending() |
Check whether the ticket is still todo or in progress. |
See Ticket.
Handover
Agents can share the results of their work in the following ways:
- Create tickets: the
finishtool'shandoveroption opens a child ticket carrying the result. - Read tickets: the
ticketstool allows reading any finished ticket's result, by key. - Read result file: the
read_filetool allows reading a ticket'sresult.jsonin the session directory. - Share knowledge: the
knowledgetool allows sharing knowledge with other agents. - Register hooks: the
create_ticket_on_resultandcreate_tickets_on_resultshooks allow creating follow-up tickets.
All ways agents pass data
1. Create tickets
A handover can be performed through a single finish tool call:
{
"handover": "report",
"result": "Three products lead on value.",
"task": "Write the board report from {parent_key}."
}
When task is not defined, the child ticket's body is the result itself. A task populates template variables:
{parent_key}: the key of the ticket that was handed over.{parent_result}: its result.{parent_result_path}: the path of its result file.
2. Read tickets
The tickets tool reads what any finished ticket produced, by key:
{ "action": "result", "key": "TICKET-1" }
3. Read result file
The read_file tool reads the original result file when its path is known:
{ "path": ".agentwerk/tickets/TICKET-1/result.json" }
4. Share knowledge
The knowledge tool allows sharing knowledge with other agents:
{
"action": "write",
"slug": "value-ranking",
"description": "How the products rank on value.",
"content": "Three products lead on value: ..."
}
5. Register hooks
Use hooks to create new tickets when certain results arrived:
def hand_to_report(done, result):
if done.has_label("research"):
return Ticket(result, label="report")
return None
def report_when_scanned(results):
if len([r for r in results if r["scanned"]]) == 3:
return [Ticket("Write the report.", label="report")]
return None
tickets.create_ticket_on_result(hand_to_report)
tickets.create_tickets_on_results(report_when_scanned)
Schemas
A Schema constrains the result an agent produces for a ticket. A violation triggers a retry until max_schema_retries is exhausted.
from agentwerk import Schema, Ticket
schema = Schema(
{
"type": "object",
"properties": {"title": {"type": "string"}},
"required": ["title"],
}
)
tickets.ticket(Ticket("Write a report.", schema=schema))
All schema methods
| Method | Description | |
|---|---|---|
| Schema | Schema(document) |
Create a schema. |
validate(value) |
Validate content. | |
| SchemaStore | SchemaStore() |
Create a store of schemas bound to labels. |
label(label, document) |
Bind a schema to a label. | |
get(label) |
Read back the schema bound to a label. | |
tickets.schemas(store) |
Enforce schemas for ticket results. |
A SchemaStore enforces schemas for all tickets with a certain label. Registering schemas centrally spares agents from passing complex schema structures during ticket creation (see TicketsTool) and handovers (see FinishTool):
from agentwerk import SchemaStore
schemas = SchemaStore()
schemas.label(
"report",
{
"type": "object",
"properties": {"title": {"type": "string"}},
"required": ["title"],
},
)
tickets.schemas(schemas)
See Schema and SchemaStore.
Policies
Policies allow you to define execution limits.
(
tickets.max_turns(40)
.max_time(300.0)
.max_input_tokens(200_000)
.max_output_tokens(50_000)
)
All limits
| Method | Description |
|---|---|
max_turns(count) / get_max_turns() |
Limit the total number of turns. |
max_time(seconds) / get_max_time() |
Limit the total elapsed duration. |
max_input_tokens(count) / get_max_input_tokens() |
Limit the total input tokens. |
max_output_tokens(count) / get_max_output_tokens() |
Limit the total output tokens. |
max_request_tokens(count) / get_max_request_tokens() |
Limit the output tokens of a single request. |
max_schema_retries(count) / get_max_schema_retries() |
Limit the consecutive turns without a valid tool call. |
max_request_retries(count) / get_max_request_retries() |
Limit how often a failing request is retried. |
request_retry_delay(seconds) / get_request_retry_delay() |
Wait this long between retries. |
compact_at(fraction) / get_compact_at() |
Compact once the context window is this full. |
A violated limit emits a policy_violated event, see EventKind.
Directives
A directive is used when a model fails to perform a specific task. It is a message for correcting the agent's behavior.
from agentwerk import Agent, Directive
def tune(key):
if key == Directive.GREP_FAILED:
return "The search did not run. Narrow `path`."
return None
agent = Agent.from_env().directives(tune).build()
All directive settings
| Method | Description |
|---|---|
directives(compute) |
Decide every directive's text with one function. |
The function returns a directive template. So you can access template variables, like {detail}, {attempt}, and {path}.
See prompts/directives for the built-in text.
Sessions
A TicketQueue writes every ticket, reply, and event to its working directory (default ./.agentwerk). You can continue a session from that directory.
tickets = TicketQueue.load(".agentwerk")
tickets.agent(my_agent)
tickets.start()
All session files
.agentwerk/
├── events.jsonl every event (one per line)
├── tickets/
│ └── TICKET-1/
│ ├── ticket.json the ticket without its messages (key, status, label, timestamps)
│ ├── result.json the result the agent produced
│ ├── replies.jsonl every message exchanged with the model, one per line
│ └── outputs/<tool_use_id>.txt full tool outputs spilled out of the messages
└── knowledge/
├── pages/<slug>.md knowledge pages
└── index.md knowledge index
Tools
Tools allow agents to perform their work.
from agentwerk import Agent, CommandTool, GrepTool, ReadFileTool
agent = (
Agent()
.tool(ReadFileTool())
.tool(GrepTool())
.tool(CommandTool("git").allow("git *"))
)
All built-in and custom tools
| Tool | Description | |
|---|---|---|
| File | ReadFileTool() |
Read a file with line numbers, offset, and limit. |
WriteFileTool() |
Create or overwrite a file. | |
EditFileTool() |
Replace text in a file. | |
| Search | GlobTool() |
Find files by pattern. |
GrepTool() |
Search file contents by regular expression, or by code shape with syntax: "code". |
|
ListDirectoryTool() |
List files and directories. | |
| Command | CommandTool(name) |
Give access to specific commands. |
| Web | FetchUrlTool() |
Fetch a URL and read its body. |
| Tickets | FinishTool() |
Write the result for the current ticket and mark it finished. |
TicketsTool() |
Read the ticket queue and create or edit tickets. | |
| Knowledge | KnowledgeTool(store) |
Write, read, remove, or list pages in a knowledge store. |
FinishTool and KnowledgeTool
FinishTool() and KnowledgeTool(store) are special tools, registered automatically on every agent. They are used for interacting with the TicketQueue or knowledge base. An interactive agent is the exception: it gets no FinishTool(), so it pauses for the next reply instead of ending its ticket.
CommandTool
The CommandTool allows you to granularly define what commands are allowed and what commands are denied.
git = (
CommandTool("git")
.allow("git status")
.allow("git log *")
.deny("git push*")
.deny_flag("--force")
)
With an allow_flag set, a command carrying any other flag is refused:
cargo = CommandTool("cargo").allow("cargo test*").allow_flag("--all-features")
FetchUrlTool
The FetchUrlTool fetches a URL and returns its text, requesting it with the user agent agentwerk/<version>. impersonate() swaps in the headers and HTTP/2 settings a browser sends.
web = FetchUrlTool().impersonate()
Custom Tools
You can define custom tools for specific needs with the following parameters:
| Method | Description |
|---|---|
concurrent=True |
If a tool has no side-effects you can run it in parallel with this option. |
paths=["path"] |
Name file path used for a tool call, so the files are included in statistics. |
Describe the tool, then hand it the code it runs:
from agentwerk import tool
@tool(
concurrent=True,
schema={
"type": "object",
"properties": {"name": {"type": "string"}},
"required": ["name"],
},
)
def greet(name: str) -> str:
"""Say hello."""
return f"Hello, {name}!"
See Tool.
Events
Events allow you to inspect all activities of your agents.
def log(event):
if event.kind == "ticket_finished":
print(f"[{event.agent_id}] done {event.ticket_key} {event.label}")
tickets.on_event(log)
All event kinds and readers
| Kind | Description | |
|---|---|---|
| Run | run_started |
Execution began. |
run_finished |
Execution ended, carrying the reason. | |
policy_violated |
A limit was breached and execution stopped. | |
| Ticket | ticket_started |
An agent claimed a ticket. |
ticket_finished |
A ticket finished successfully. | |
ticket_failed |
A ticket failed. | |
turn_started |
The agent began another turn on its ticket. | |
schema_retried |
A tool call or result the model created was invalid. | |
| LLM provider | request_started |
A request went out to the model. |
request_finished |
A request finished and reported its token usage. | |
request_failed |
A request failed and was not retried. | |
request_retried |
A transient provider error triggered a retry. | |
text_chunk_received |
A piece of the reply arrived. | |
response_repaired |
A tool call or value the model created was invalid and was corrected. | |
| Tool | tool_call_declined |
A tool call proposed by the model was declined. |
tool_call_started |
A tool invocation began. | |
tool_call_finished |
A tool invocation finished. | |
tool_call_failed |
A tool invocation failed but the ticket continues. | |
| File | file_open_finished |
A tool opened a file. |
file_open_failed |
A tool could not open a file. | |
| Knowledge | knowledge_written |
A page was written. |
knowledge_read |
A page was read. | |
knowledge_removed |
A page was removed. | |
knowledge_listed |
The pages were listed. | |
knowledge_failed |
An action against the store did not go through. | |
| Compaction | compaction_started |
Compaction is about to rewrite the older messages. |
compaction_progress |
Compaction finished part of the work. | |
compaction_finished |
Compaction replaced the older messages. | |
compaction_failed |
Compaction could not finish. |
Every event is written to the session log. You read events from the ticket queue, or from the session directory in .agentwerk/events.jsonl:
| Method | Description |
|---|---|
find_event(condition) |
Get the earliest recorded event matching a condition. |
find_events(condition) |
Get every recorded event matching a condition, oldest first. |
input_tokens() / output_tokens() |
Get token counts across the run's requests. |
execution_duration() |
Get the elapsed execution duration. |
See EventKind and TicketQueue.
Hooks
Hooks allow you to react to events.
def retry_once(event, failed):
if failed.parent is not None:
return None
return Ticket(failed.task, parent=failed.key)
tickets.create_ticket_on_failure(retry_once)
All hooks
| Method | Description | |
|---|---|---|
| Observe | on_event(handler) |
Read every event as it is emitted. |
on_result(handler) |
Read every finished ticket together with its result. | |
on_result_async(handler) |
Read every finished ticket with its result, in an async handler. | |
on_results(handler) |
Read every result the run has produced so far, each time one lands. | |
on_results_async(handler) |
Read every result in an async handler. | |
on_failure(handler) |
Read every failure together with the ticket it happened in. | |
on_ticket(handler) |
Read a ticket as it starts, finishes, or fails. | |
| Add work | create_ticket_on_event(make) |
Enqueue a follow-up ticket from any event. |
create_ticket_on_result(make) |
Enqueue a follow-up ticket from a finished ticket. | |
create_tickets_on_results(make) |
Enqueue follow-up tickets once a condition across every result holds. | |
create_ticket_on_failure(make) |
Enqueue a retry for a ticket that failed. | |
| Rewrite | edit_replies_on_event(editor) |
Rewrite a ticket's replies before its next request. |
edit_replies_on_compaction(editor) |
Decide what compaction does with a ticket's replies. |
Save replies of every finished ticket as a training example:
def capture(event, ticket):
if event.kind == "ticket_finished":
model = tickets.model_for_agent(event.agent_id)
Trajectory.from_ticket(event.agent_id, model, ticket).save("datasets")
tickets.on_ticket(capture)
Async handlers
on_result is blocking and prevents an agent continuing its work till the hook is finished. If you perform time-consuming operations use on_result_async instead: storing results in a database, posting them to an HTTP API, or uploading them to object storage. Both take an async def and run it on the event loop you await finish on.
async def store(ticket, result):
await database.insert(ticket.key, result)
tickets.on_result_async(store)
See TicketQueue.
Knowledge
Knowledge allows agents to share insights or learnings. Knowledge pages are created in the Open Knowledge Format (OKF).
from agentwerk import Agent, Knowledge
store = Knowledge.load("./notes")
alice = Agent().knowledge(store)
bob = Agent().knowledge(store)
All knowledge methods
| Method | Description |
|---|---|
index() |
Get the index, which is injected into the agent prompt. |
index_char_limit(count) |
Limit how much of the index is injected into the prompt. |
get_index_char_limit() |
Get the index size limit in force. |
pages() |
Get the page collection for reading and writing pages. |
pages().list() |
Get every page in the store. |
clear() |
Remove every page from the store. |
Programmatically create entries:
from agentwerk import Page
store.pages().save(
Page(
"build-command",
"How the project is built.",
"Run `make` to compile.",
tags=["build"],
)
)
page = store.pages().load("build-command")
store.pages().remove("build-command")
See Knowledge.
Use Cases
Example projects built with agentwerk:
- Hello World: basic example, ported in examples/hello_world.py
- Terminal REPL: minimal interactive chat
- Divide and Conquer: arithmetic problem shared across agents, ported in examples/divide_and_conquer.py
- Deep Research: deep research pipeline (requires
BRAVE_API_KEY) - Malware Scanner: identify indicators of compromise in a software package
- Apparat Fabrik: a shift on the line of an apparatus works
Configure an LLM provider first (see Environment).
python examples/divide_and_conquer.py 200 4 2
Development
See DEVELOPMENT.md.
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