awrepl

A REPL an agent can actually use — state that survives between turns.

pip install awrepl

from awrepl import ReplSession

session = ReplSession("agent-1")
result = session.execute("items = [1, 2, 3]")
result = session.execute("print(len(items))")
print(result.stdout)  # "3"
session.close()

awrepl run "print('hello')"
awrepl serve                    # Interactive session
awrepl --session myagent run "x = 42"
awrepl --self-test              # Verify the contract

---

The problem it exists for

An agent given one-shot shell commands rebuilds its whole world on every call, so it guesses instead of looks. Every variable it wanted is gone the moment the command exits. This REPL keeps state.

You ask the live object, not the agent's memory.

# Turn 1
session.execute("data = load_file('config.json')")

# Turn 2 (later, different agent instance)
session.execute("print(data['server'])")  # data is STILL there

---

⚠️ This is NOT a sandbox

Critical: awrepl executes arbitrary code with the privileges of the process that started it.

It does not protect against:

• Filesystem access — code can read/write/delete files
• Network access — code can make HTTP requests, connect to services
• Subprocess execution — code can launch processes and scripts
• Resource exhaustion — timeouts can be circumvented (see below)
• Memory/disk consumption — unbounded allocations are possible

Real isolation requires a container (Docker/Podman) or VM. awrepl is a session manager, not a sandbox. Shipping something that looks like a sandbox and is not would be actively dangerous — so this is stated plainly.

Use awrepl only:

• In trusted environments (your own machine, internal tools)
• When running code you wrote or thoroughly reviewed
• Behind proper auth and network boundaries if exposed as a service
• With resource limits imposed at the OS/container level if needed

If you need to run untrusted code, use a container or virtual machine. Do not rely on awrepl alone.

---

API

ReplSession

A persistent Python interpreter backed by a subprocess worker.

from awrepl import ReplSession, ExecResult

session = ReplSession(
    session_id="my-session",
    timeout_ms=30000,           # per-call timeout
    max_output_bytes=65536,     # output cap before truncation
)

# Execute code
result: ExecResult = session.execute("x = [1, 2, 3]")

ExecResult fields:

• stdout (str): Captured stdout
• stderr (str): Captured stderr
• value (str|None): repr() of the last expression, if any
• exception (str|None): Error message if execution failed
• traceback (str): Full traceback on exception
• duration_ms (float): Wall-clock time for execution
• truncated (bool): Output was truncated due to size limit
• truncated_bytes (int): How many bytes were dropped

Methods:

# Execute code in the persistent namespace
result = session.execute("code", timeout_ms=30000)

# Get all bound variables (type and short repr)
variables: dict[str, str] = session.variables()
# {"x": "list: [1, 2, 3]", "name": "str: 'Alice'"}

# Inspect a single variable (type, repr, docstring, etc.)
info: dict = session.inspect("x")
# {"type": "list", "repr": "[1, 2, 3]", "dir": [...], "len": 3}

# Clear all user-defined variables (keeps builtins)
session.reset()

# Close the session and terminate the worker
session.close()

# Use as a context manager
with ReplSession("temp") as s:
    s.execute("x = 42")

SessionPool

Manage multiple REPL sessions indexed by ID.

from awrepl import SessionPool

pool = SessionPool(timeout_ms=30000, max_output_bytes=65536)

# Create a session (auto-generate ID)
sid1 = pool.create_session()

# Create a session with a custom ID
sid2 = pool.create_session("agent-2")

# Get a session
session = pool.get_session(sid2)
session.execute("x = 42")

# List all session IDs
sessions = pool.list_sessions()

# Delete a session
pool.delete_session(sid1)

# Close all sessions
pool.close_all()

Each session has its own namespace — one agent's variables don't affect another.

---

CLI

# Execute code once (ephemeral session)
awrepl run "print(1 + 2)"

# Use a persistent session across multiple calls
awrepl --session myagent run "x = 42"
awrepl --session myagent run "print(x)"  # Prints 42

# Output as JSON
awrepl run "42" --json
# {"stdout": "", "stderr": "", "value": "42", "exception": null, ...}

# Interactive REPL (basic, stdin-based)
awrepl serve

# Session-based interactive REPL
awrepl --session agent serve

# Verify the REPL contract (no network required)
awrepl --self-test

Options:

• --session ID — Use a specific session (creates if needed)
• --json — Output result as JSON
• --traceback — Show full traceback on exception

---

How it works

awrepl runs a Python subprocess (python -i-style worker) and communicates via JSON over pipes. The worker:

• Maintains a single persistent namespace
• Executes code and captures stdout/stderr
• Handles timeouts and output truncation
• Survives syntax errors and exceptions

Multiple ReplSession instances can run in parallel, each with its own worker subprocess, enabling concurrent agents to maintain separate state.

Why subprocess, not in-process exec()?

• In-process execution lets agent code crash or corrupt the host process
• Subprocess isolation means a fatal error in agent code doesn't kill the agent
• Each session gets its own Python interpreter with its own memory space
• Timeouts are more reliable (can interrupt the subprocess)

Platform support: Linux, macOS, Windows (tested on all three). Uses only Python standard library — no external dependencies.

---

--self-test

Every install can prove the contract, with no service and no network:

$ awrepl --self-test
  PASS  Variables persist across calls
  PASS  Syntax error doesn't kill session
  PASS  Exception doesn't kill session
  PASS  Output truncation works
  PASS  variables() lists bound names
  PASS  Pool sessions are isolated

SELF-TEST: awrepl ok (6/6)

The test asserts:

1. Variables defined in one call are readable in another (the whole point)
2. A syntax error doesn't terminate the session
3. An exception is reported, but the session survives
4. Output longer than max_output_bytes is truncated with a flag
5. variables() lists bound names correctly
6. Sessions in a pool don't see each other's variables

---

The bug this package exists to prevent

An agent with access to a live object can look at it instead of guessing about it from memory.

Without awrepl:

# Agent's turn 1: I ran this, but I don't remember the result
code = "data = load_json('config.json')"
result = subprocess.run(["python", "-c", code])
# Stdout gone, no access to `data`

# Agent's turn 2: Guess based on memory (but agent memory is compressed/forgotten)
# "What was in that file again? Let me re-run the whole thing..."

With awrepl:

# Agent's turn 1: Run code, data persists
session.execute("data = load_json('config.json')")

# Agent's turn 2: Look at it
vars = session.variables()  # {"data": "dict: {...}"}
info = session.inspect("data")  # {"type": "dict", "len": 5, "keys": [...]}

Cuts through the memory layer. What you ask is what you get.

---

Limitations and design choices

Timeouts: The timeout_ms parameter exists, but relies on the subprocess signal handler. Some heavy operations (deep recursion, infinite loops in C extensions) may not be interruptible. Use OS-level resource limits (cgroups, ulimit) for hard guarantees.

Namespace pollution: The namespace persists, so a large object assigned to x stays in memory until reset() or the session closes. Plan for that.

No remote execution: This is a local subprocess REPL. For distributed execution, wrap it in an HTTP service or use it alongside a message queue.

---

The aw family

Standalone tools that share one idea: replace something you would otherwise have to trust with something you can check.

Each installs on its own, works offline, and needs no account.

	instead of trusting	you check
awdk	a framework's idea of how your agents should run	one loop you can read, pointed at a backend you already pay for
awskills	that an agent knows your procedure	the procedure written down, versioned, and loadable by any agent
awm	that memory stayed in its lane	tenant:user:project scopes, so a write cannot cross a boundary
awnode	a vendor's cloud with every prompt	a local gateway routing to backends you chose
awgraph	that grep found everything	an AST + tree-sitter call graph an agent can traverse
awgit	that no one else is editing this file	a lease, refused at commit time if you do not hold it
awseal	that the artifact came from who you think	an Ed25519 seal — the key that verifies is not the key that forges
awshare	that the download is intact	content-addressed bundles, verified on fetch
awnest	that there is a person on the other end	a verdict with evidence, where "we could not tell" is not "yes"
awnboard	a share link anyone who sees it can use	an invitation addressed to one person, for one gate, revocable
awnix	that the box is what you left it as	an immutable image you built, with atomic rollback
awrecover	that the restore worked	a restore that fully lands or does not land at all
awkno	that the docs site is up, or that you remember the family	the whole ecosystem in your terminal, with no network at all
awrelay	a SaaS in the middle of your agents	findings, alerts and coordination over your own transport
awmail	a mailbox somebody else can read	mail your agents send and receive over your own server
awfind	one vendor's idea of the web	results from whichever providers you configured
awbrowse	that the page said what you were told	the render, the DOM and the requests it made
aitherkvcache	a vendor's quantisation defaults	sub-byte KV cache kernels you can benchmark yourself
AitherZero	a pile of scripts nobody has numbered	numbered, discoverable automation with declarative playbooks
AitherConnect	what a page tells your browser to do	a federated search and desktop bridge you host
awreason	a confident paragraph	the phases it went through, and every tool call it made to get there
awrecurse	that everything you pasted in was actually read	which slices it opened, and what it concluded from each
awprism	the first explanation that fits	the ranked alternatives, and the observation that separates them
awrepl (you are here)	what the agent believes the value is	the value, printed from the live session
awresearch	a summary of pages nobody opened	every claim against the source it came from

awnix is the ground floor — A Linux you can hand to an agent — immutable base, capabilities included.

The Aitherium ecosystem

Every repository here is public. Each publishes an aither-manifest.json beside its page, so any surface can read every sibling's — the network is browsable from any node in it.

repo	what it is	pages
awdk	Build AI agent fleets — 3 lines, any backend, local or cloud	docs
awskills	Portable agent skills — self-contained procedures an agent loads on demand	docs
awm	A portable, scoped agent memory	docs
awnode	A lightweight local gateway — bridges your apps to the AI backends you chose	docs
awrun	A priority-aware queue and dispatcher for agentic runs and ad-hoc CI builds	docs
awgraph	A semantic code graph for agents — AST + tree-sitter, call graphs	docs
awgit	Semantic version control on top of git — edit-ops and leases	docs
awseal	Sign an artifact so a stranger can verify it	docs
awshare	Publish an artifact and fetch it back verified	docs
awnest	Prove there is a human before you let them into the nest	docs
awnboard	A front gate you can put in front of anything, and hand someone the key to	docs
awnix	A Linux you can hand to an agent — immutable base, capabilities included	docs
awrecover	Labelled snapshots with an all-or-nothing restore	docs
awkno	The man page for the Aither World — every brick, stack and law, offline	docs
awrelay	Portable agent messaging — findings, alerts, coordination	docs
awmail	Give an agent an email address — send, and actually receive	docs
awfind	A portable search client — query, results, ranking	docs
awbrowse	A portable browser client — navigate, console, network, DOM, screenshot	docs
aitherkvcache	Near-optimal KV cache quantization for LLM inference — sub-byte compression	docs
AitherZero	PowerShell 7+ automation framework — numbered, self-describing scripts	docs
AitherConnect	Browser extension — federated AI search, page context, and the Living OS overlay	docs
awreason	A portable reasoning client — sessions, phases, thoughts, and the chain that produced the answer	docs
awrecurse	Answer a question over a context far larger than the window — recursively, with the trace kept	docs
awprism	Turn a failure into ranked hypotheses — and say what would confirm each one	docs
awrepl (you are here)	A REPL an agent can actually use — state that survives between turns	docs
awresearch	Ask a research question, get a cited report you can check	docs