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feat(sdk)!: v0.6 (#3193)

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Co-authored-by: Nick Hollon <nick.hollon@langchain.dev>
Co-authored-by: Mason Daugherty <mason@langchain.dev>
Co-authored-by: Mason Daugherty <github@mdrxy.com>
Co-authored-by: Chester Curme <chester.curme@gmail.com>
This commit is contained in:
Sydney Runkle
2026-05-12 12:11:41 -04:00
committed by GitHub
parent 51bd68bf88
commit 4db09acba3
46 changed files with 2787 additions and 1340 deletions
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examples/async-subagent-server/uv.lock
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[[package]]
examples/text-to-sql-agent/uv.lock
Generated
+8
View File
@@ -6,6 +6,9 @@ resolution-markers = [
"python_full_version < '3.13'",
]
[options]
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libs/Makefile
+3 -3
View File
@@ -21,7 +21,7 @@ lock: ## Update all lockfiles
@set -e; \
$(foreach pkg,$(PACKAGE_DIRS), \
echo "🔒 Locking $(pkg)"; \
uv lock --directory '$(pkg)' --python '$(call python_version,$(pkg))'; \
uv lock --directory '$(pkg)' --python '$(call python_version,$(pkg))' --prerelease=allow; \
)
@echo "✅ All lockfiles updated!"
@@ -33,7 +33,7 @@ lock-bump: ## Bump a dependency across all lockfiles (usage: make lock-bump DEP=
@set -e; \
$(foreach pkg,$(PACKAGE_DIRS), \
echo "⬆️ Bumping $(DEP) in $(pkg)"; \
uv lock --directory '$(pkg)' --python '$(call python_version,$(pkg))' -P '$(DEP)'; \
uv lock --directory '$(pkg)' --python '$(call python_version,$(pkg))' --prerelease=allow -P '$(DEP)'; \
)
@echo "✅ Bumped $(DEP) across all lockfiles!"
@@ -41,7 +41,7 @@ lock-check: ## Check all lockfiles are up-to-date
@set -e; \
$(foreach pkg,$(PACKAGE_DIRS), \
echo "🔍 Checking $(pkg)"; \
uv lock --check --directory '$(pkg)' --python '$(call python_version,$(pkg))'; \
uv lock --check --directory '$(pkg)' --python '$(call python_version,$(pkg))' --prerelease=allow; \
)
@echo "✅ All lockfiles are up-to-date!"
libs/acp/uv.lock
Generated
+29 -24
View File
@@ -8,6 +8,9 @@ resolution-markers = [
"python_full_version < '3.13'",
]
[options]
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[[package]]
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version = "0.9.0"
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version = "0.6.0"
source = { editable = "../deepagents" }
dependencies = [
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@@ -443,13 +446,15 @@ dependencies = [
[package.metadata]
requires-dist = [
{ name = "langchain", specifier = ">=1.2.17,<2.0.0" },
{ name = "langchain", specifier = ">=1.3.0,<2.0.0" },
{ name = "langchain-anthropic", specifier = ">=1.4.3,<2.0.0" },
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{ name = "langchain-core", specifier = ">=1.4.0,<2.0.0" },
{ name = "langchain-google-genai", specifier = ">=4.2.2,<5.0.0" },
{ name = "langchain-quickjs", marker = "extra == 'quickjs'" },
{ name = "langsmith", specifier = ">=0.8.0" },
{ name = "wcmatch" },
]
provides-extras = ["quickjs"]
[package.metadata.requires-dev]
test = [
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libs/cli/deepagents_cli/app.py
+16 -83
View File
@@ -1591,7 +1591,7 @@ class DeepAgentsApp(App):
- The agent is a local `Pregel` graph (e.g. ACP mode, test harnesses).
Used to gate features that require a server-backed agent (e.g. model
switching via `ConfigurableModelMiddleware`, checkpointer fallback).
switching via `ConfigurableModelMiddleware`, thread registration).
Checks the agent type rather than server ownership so this works for
both CLI-spawned servers and externally managed ones.
@@ -5486,9 +5486,6 @@ class DeepAgentsApp(App):
if result.offload_warning:
await self._mount_message(ErrorMessage(result.offload_warning))
if remote := self._remote_agent():
await remote.aensure_thread(config) # ty: ignore[invalid-argument-type]
await self._agent.aupdate_state(
config, {"_summarization_event": result.new_event}
)
@@ -5835,12 +5832,14 @@ class DeepAgentsApp(App):
return result
async def _get_thread_state_values(self, thread_id: str) -> dict[str, Any]:
"""Fetch thread state values, with remote checkpointer fallback.
"""Fetch thread state values for a thread.
In server mode the LangGraph dev server can report an empty thread state
after a restart even when checkpoints exist on disk. When that happens,
read the latest checkpoint directly so resumed threads can still load
history and offload correctly.
In server mode the LangGraph dev server starts with an empty in-memory
thread store, so `aget_state` returns empty state for any thread that
was not registered in the current server session. Calling
`aensure_thread` first registers the thread idempotently so the
subsequent `aget_state` call can read from the checkpointer correctly,
including proper reconstruction of delta channels.
Args:
thread_id: Thread ID to fetch from checkpoint storage.
@@ -5853,46 +5852,20 @@ class DeepAgentsApp(App):
return {}
config: RunnableConfig = {"configurable": {"thread_id": thread_id}}
remote_config: dict[str, Any] = {"configurable": {"thread_id": thread_id}}
if remote := self._remote_agent():
await remote.aensure_thread(remote_config)
state = await self._agent.aget_state(config)
values: dict[str, Any] = {}
if state and state.values:
values = dict(state.values)
messages = values.get("messages")
if isinstance(messages, list) and messages:
return values
if not self._remote_agent():
return values
logger.debug(
"Remote state empty for thread %s; falling back to local checkpointer",
thread_id,
)
fallback_values = await self._read_channel_values_from_checkpointer(thread_id)
fallback_messages = fallback_values.get("messages")
if isinstance(fallback_messages, list) and fallback_messages:
values["messages"] = fallback_messages
if (
values.get("_summarization_event") is None
and "_summarization_event" in fallback_values
):
values["_summarization_event"] = fallback_values["_summarization_event"]
if (
values.get("_context_tokens") is None
and "_context_tokens" in fallback_values
):
values["_context_tokens"] = fallback_values["_context_tokens"]
return values
return dict(state.values)
return {}
async def _fetch_thread_history_data(self, thread_id: str) -> _ThreadHistoryPayload:
"""Fetch and convert stored messages for a thread.
In server mode the LangGraph dev server starts with an empty thread
store, so `aget_state` via the HTTP API returns no messages even when
checkpoints exist on disk. We fall back to reading the SQLite
checkpointer directly to guarantee resumed threads load their history.
Args:
thread_id: Thread ID to fetch from checkpoint storage.
@@ -5910,10 +5883,8 @@ class DeepAgentsApp(App):
if not messages:
return _ThreadHistoryPayload([], context_tokens)
# Server mode / direct checkpointer may return dicts; convert to
# RemoteGraph.aget_state returns values as raw JSON dicts; convert to
# LangChain message objects so _convert_messages_to_data works.
# `any(...)` guards against heterogeneous lists where only some
# elements are serialized.
if any(isinstance(m, dict) for m in messages):
from langchain_core.messages.utils import convert_to_messages
@@ -5923,44 +5894,6 @@ class DeepAgentsApp(App):
data = await asyncio.to_thread(self._convert_messages_to_data, messages)
return _ThreadHistoryPayload(data, context_tokens)
@staticmethod
async def _read_channel_values_from_checkpointer(thread_id: str) -> dict[str, Any]:
"""Read checkpoint channel values directly from the SQLite checkpointer.
Args:
thread_id: Thread ID to look up.
Returns:
Channel values from the latest checkpoint, or an empty dict on
failure.
"""
try:
from langgraph.checkpoint.sqlite.aio import AsyncSqliteSaver
from deepagents_cli.sessions import get_db_path
db_path = str(get_db_path())
config: RunnableConfig = {"configurable": {"thread_id": thread_id}}
async with AsyncSqliteSaver.from_conn_string(db_path) as saver:
tup = await saver.aget_tuple(config)
if tup and tup.checkpoint:
channel_values = tup.checkpoint.get("channel_values", {})
if isinstance(channel_values, dict):
return dict(channel_values)
except (ImportError, OSError) as exc:
logger.warning(
"Failed to read checkpointer directly for %s: %s",
thread_id,
exc,
)
except Exception:
logger.warning(
"Unexpected error reading checkpointer for %s",
thread_id,
exc_info=True,
)
return {}
async def _upgrade_thread_message_link(
self,
widget: AppMessage,
libs/cli/deepagents_cli/integrations/sandbox_factory.py
+1 -1
View File
@@ -710,7 +710,7 @@ class _AgentCoreProvider(SandboxProvider):
# Validate AWS credentials early for a clear error message.
try:
import boto3 # ty: ignore[unresolved-import, unused-ignore-comment]
import boto3 # ty: ignore[unresolved-import]
session = boto3.Session()
credentials = session.get_credentials()
libs/cli/deepagents_cli/local_context.py
+1
View File
@@ -104,6 +104,7 @@ class _AsyncExecutableBackend(Protocol):
logger = logging.getLogger(__name__)
# ---------------------------------------------------------------------------
# Context detection script
#
libs/cli/deepagents_cli/remote_client.py
+18 -2
View File
@@ -183,7 +183,8 @@ class RemoteAgent:
) -> Any: # noqa: ANN401
"""Get the current state of a thread.
Returns `None` when the thread does not exist on the server (404).
Returns `None` when the thread does not exist on the server (404) or
when the thread exists but has no checkpoint yet (new/empty thread).
All other errors (network, auth, 500) are logged at WARNING and
re-raised so callers can handle them.
@@ -196,10 +197,11 @@ class RemoteAgent:
Returns:
Thread state object with `values` and `next` attributes, or `None`
if the thread is not found.
if the thread is not found or has no checkpoint.
Raises:
ValueError: If `thread_id` is not present in `config`.
TypeError: If the server returns an unexpected state shape.
""" # noqa: DOC502 — raised by _require_thread_id
from langgraph_sdk.errors import NotFoundError
@@ -211,6 +213,20 @@ class RemoteAgent:
except NotFoundError:
logger.debug("Thread %s not found on server", thread_id)
return None
except TypeError as e:
# langgraph SDK bug: _create_state_snapshot does
# state["checkpoint"]["thread_id"], but the server returns
# checkpoint=null for threads with no checkpoint yet (new threads,
# or threads registered via aensure_thread before any run).
if "subscriptable" in str(e).lower():
logger.debug(
"Thread %s has no checkpoint yet; treating as empty", thread_id
)
return None
logger.warning(
"Failed to get state for thread %s", thread_id, exc_info=True
)
raise
except Exception:
logger.warning(
"Failed to get state for thread %s", thread_id, exc_info=True
libs/cli/pyproject.toml
+5 -5
View File
@@ -26,15 +26,15 @@ classifiers = [
]
dependencies = [
# Framework
"deepagents==0.5.9",
"langchain>=1.2.17,<2.0.0",
"langgraph>=1.1.10,<2.0.0",
"langgraph-checkpoint-sqlite>=3.0.3,<4.0.0",
"langgraph-prebuilt>=1.0.13,<2.0.0",
"deepagents==0.6.0a3",
"langchain>=1.3.0a2,<2.0.0",
"langgraph>=1.2.0a7,<2.0.0",
"langgraph-checkpoint-sqlite>=3.1.0a1,<4.0.0",
# Client-server architecture
"langgraph-sdk>=0.3.13,<1.0.0",
"langgraph-cli[inmem]>=0.4.24,<1.0.0",
"langgraph-runtime-inmem>=0.28.1,<1.0.0",
"httpx>=0.28.1,<1.0.0",
# Core model providers - others are added as optional
libs/cli/tests/integration_tests/test_compact_resume.py
+14 -35
View File
@@ -2,9 +2,7 @@
from __future__ import annotations
from types import SimpleNamespace
from typing import TYPE_CHECKING
from unittest.mock import AsyncMock
import pytest
@@ -62,12 +60,11 @@ def _event_field(event: object, key: str) -> object | None:
async def test_compact_resumed_thread_uses_persisted_history(
tmp_path: Path, monkeypatch: pytest.MonkeyPatch
) -> None:
"""Compacts a resumed thread after restart using SQLite-backed history.
"""Offloads a resumed thread after restart using remote server state.
The test seeds a real persisted thread on one server instance, restarts the
server, resumes that thread in a fresh `DeepAgentsApp`, and verifies that
`/compact` succeeds even when the resumed history comes from the
checkpointer rather than live in-memory server state.
`/offload` succeeds after the app registers the thread with the server.
"""
home_dir = tmp_path / "home"
project_dir = tmp_path / "project"
@@ -92,7 +89,7 @@ async def test_compact_resumed_thread_uses_persisted_history(
from deepagents_cli.app import DeepAgentsApp
from deepagents_cli.config import create_model
from deepagents_cli.server_manager import server_session
from deepagents_cli.sessions import generate_thread_id, thread_exists
from deepagents_cli.sessions import generate_thread_id
from deepagents_cli.widgets.messages import AppMessage, ErrorMessage
config_path = home_dir / ".deepagents" / "config.toml"
@@ -124,15 +121,12 @@ async def test_compact_resumed_thread_uses_persisted_history(
prompt=_build_long_prompt(turn),
)
assert await thread_exists(thread_id)
compact_backend = CompositeBackend(
default=FilesystemBackend(root_dir=backend_root, virtual_mode=True),
routes={},
)
# Server 2: same SQLite DB, but a fresh server process and empty
# in-memory thread registry.
# Server 2: same SQLite DB, but a fresh server process.
async with server_session(
assistant_id=assistant_id,
model_name="itest:fake",
@@ -142,15 +136,6 @@ async def test_compact_resumed_thread_uses_persisted_history(
sandbox_type="none",
) as (agent, _server_proc):
config = {"configurable": {"thread_id": thread_id}}
actual_state = await agent.aget_state(config)
actual_values = getattr(actual_state, "values", None) or {}
# Fresh dev servers may return empty state for persisted threads
# after restart. If that behavior changes upstream, force the
# empty-state precondition so this test still covers the SQLite
# fallback path.
if actual_values:
agent.aget_state = AsyncMock(return_value=SimpleNamespace(values={})) # ty: ignore[invalid-assignment]
app = DeepAgentsApp(
agent=agent, # ty: ignore[invalid-argument-type]
@@ -170,20 +155,15 @@ async def test_compact_resumed_thread_uses_persisted_history(
break
assert app._message_store.total_count > 0
resume_messages = app.query(AppMessage)
assert any(
"Resumed thread:" in str(widget._content)
for widget in resume_messages
)
await app._handle_offload()
# `/compact` posts a success message after the async state write
# `/offload` posts a success message after the async state write
# and archive offload finish.
for _ in range(120):
await pilot.pause(0.1)
if any(
"Conversation compacted." in str(widget._content)
"Offloaded " in str(widget._content)
for widget in app.query(AppMessage)
):
break
@@ -195,16 +175,15 @@ async def test_compact_resumed_thread_uses_persisted_history(
str(widget._content) for widget in app.query(ErrorMessage)
]
assert "Nothing to compact" not in "\n".join(app_messages)
assert any("Conversation compacted." in content for content in app_messages)
assert "Nothing to offload" not in "\n".join(app_messages)
assert any("Offloaded " in content for content in app_messages)
assert not error_messages
# The summarization event must be checkpointed so subsequent turns
# see compacted context instead of the full message history.
channel_values = await DeepAgentsApp._read_channel_values_from_checkpointer(
thread_id
)
summarization_event = channel_values.get("_summarization_event")
# The summarization event must be visible through server state so
# subsequent turns see compacted context instead of full history.
state = await agent.aget_state(config)
values = getattr(state, "values", None) or {}
summarization_event = values.get("_summarization_event")
assert summarization_event is not None
cutoff = _event_field(summarization_event, "cutoff_index")
assert isinstance(cutoff, int)
@@ -219,7 +198,7 @@ async def test_compact_resumed_thread_uses_persisted_history(
archive_path = backend_root / "conversation_history" / f"{thread_id}.md"
assert archive_path.exists()
archive_text = archive_path.read_text()
assert "Compacted at" in archive_text
assert "Offloaded at" in archive_text
assert "keeps enough unique detail" in archive_text
finally:
model_config.clear_caches()
libs/cli/tests/unit_tests/test_app.py
+30 -37
View File
@@ -4355,67 +4355,60 @@ class TestFetchThreadHistoryData:
assert payload.messages[1].type == MessageType.ASSISTANT
assert payload.messages[1].content == "Hi there!"
async def test_server_mode_falls_back_to_checkpointer(self) -> None:
"""When the server returns empty state, read SQLite checkpointer directly."""
async def test_server_mode_ensures_thread_before_fetching_state(self) -> None:
"""Server-mode history reads should fetch state through the remote server."""
from langchain_core.messages import AIMessage, HumanMessage
from deepagents_cli.remote_client import RemoteAgent
from deepagents_cli.widgets.message_store import MessageData, MessageType
from deepagents_cli.widgets.message_store import MessageType
# Server returns empty state (fresh restart, thread not loaded)
empty_state = MagicMock()
empty_state.values = {}
state = MagicMock()
state.values = {
"messages": [
HumanMessage(content="hello", id="h1"),
AIMessage(content="world", id="a1"),
]
}
# spec=RemoteAgent so _remote_agent() isinstance check passes
mock_agent = MagicMock(spec=RemoteAgent)
mock_agent.aget_state = AsyncMock(return_value=empty_state)
mock_agent.aensure_thread = AsyncMock()
mock_agent.aget_state = AsyncMock(return_value=state)
app = DeepAgentsApp(agent=mock_agent, thread_id="t-1")
payload = await app._fetch_thread_history_data("t-1")
# Patch the checkpointer fallback to return messages
checkpointer_msgs = [
HumanMessage(content="hello", id="h1"),
AIMessage(content="world", id="a1"),
]
with patch.object(
DeepAgentsApp,
"_read_channel_values_from_checkpointer",
return_value={"messages": checkpointer_msgs},
):
payload = await app._fetch_thread_history_data("t-1")
mock_agent.aensure_thread.assert_awaited_once_with(
{"configurable": {"thread_id": "t-1"}}
)
assert len(payload.messages) == 2
assert payload.messages[0].type == MessageType.USER
assert payload.messages[0].content == "hello"
assert payload.messages[1].type == MessageType.ASSISTANT
assert payload.messages[1].content == "world"
async def test_server_mode_fallback_includes_context_tokens(self) -> None:
"""Server-mode fallback should merge `_context_tokens` from the checkpointer."""
async def test_server_mode_state_includes_context_tokens(self) -> None:
"""Server-mode history reads should preserve `_context_tokens` from state."""
from langchain_core.messages import HumanMessage
from deepagents_cli.remote_client import RemoteAgent
from deepagents_cli.widgets.message_store import MessageType
empty_state = MagicMock()
empty_state.values = {}
mock_agent = MagicMock(spec=RemoteAgent)
mock_agent.aget_state = AsyncMock(return_value=empty_state)
app = DeepAgentsApp(agent=mock_agent, thread_id="t-1")
checkpointer_data = {
state = MagicMock()
state.values = {
"messages": [HumanMessage(content="hi", id="h1")],
"_context_tokens": 5000,
}
with patch.object(
DeepAgentsApp,
"_read_channel_values_from_checkpointer",
return_value=checkpointer_data,
):
payload = await app._fetch_thread_history_data("t-1")
mock_agent = MagicMock(spec=RemoteAgent)
mock_agent.aensure_thread = AsyncMock()
mock_agent.aget_state = AsyncMock(return_value=state)
app = DeepAgentsApp(agent=mock_agent, thread_id="t-1")
payload = await app._fetch_thread_history_data("t-1")
mock_agent.aensure_thread.assert_awaited_once_with(
{"configurable": {"thread_id": "t-1"}}
)
assert payload.context_tokens == 5000
assert len(payload.messages) == 1
assert payload.messages[0].type == MessageType.USER
libs/cli/tests/unit_tests/test_offload.py
+16 -24
View File
@@ -906,8 +906,8 @@ class TestOffloadRouting:
class TestOffloadRemoteFallback:
"""Verify `/offload` handles resumed remote threads."""
async def test_resumed_remote_thread_uses_checkpointer_state(self) -> None:
"""Should offload using checkpoint fallback when remote state is empty."""
async def test_resumed_remote_thread_uses_server_state(self) -> None:
"""Should offload using state returned by the remote server."""
from deepagents_cli.remote_client import RemoteAgent
app = DeepAgentsApp()
@@ -924,11 +924,14 @@ class TestOffloadRemoteFallback:
"file_path": None,
}
empty_state = MagicMock()
empty_state.values = {}
state = MagicMock()
state.values = {
"messages": messages,
"_summarization_event": prior_event,
}
app._agent = MagicMock(spec=RemoteAgent)
app._agent.aget_state = AsyncMock(return_value=empty_state)
app._agent.aget_state = AsyncMock(return_value=state)
app._agent.aensure_thread = AsyncMock()
app._agent.aupdate_state = AsyncMock()
app._backend = MagicMock()
@@ -942,27 +945,14 @@ class TestOffloadRemoteFallback:
messages_kept=12,
)
with (
patch.object(
DeepAgentsApp,
"_read_channel_values_from_checkpointer",
return_value={
"messages": messages,
"_summarization_event": prior_event,
},
) as checkpointer_mock,
patch(
_PERFORM_OFFLOAD_PATH,
new_callable=AsyncMock,
return_value=result,
) as mock_perform,
):
with patch(
_PERFORM_OFFLOAD_PATH,
new_callable=AsyncMock,
return_value=result,
) as mock_perform:
await app._handle_offload()
await pilot.pause()
checkpointer_mock.assert_awaited_once_with("test-thread")
# Verify perform_offload was called with the fallback state
kwargs = mock_perform.call_args.kwargs
assert kwargs["messages"] == messages
assert kwargs["prior_event"] is prior_event
@@ -1070,7 +1060,9 @@ class TestOffloadRemoteStateNormalization:
passed_event = mock_mw._apply_event_to_messages.call_args[0][1]
assert isinstance(passed_event["summary_message"], BaseMessage)
app._agent.aensure_thread.assert_not_called()
app._agent.aensure_thread.assert_awaited_once_with(
{"configurable": {"thread_id": "test-thread"}}
)
app._agent.aupdate_state.assert_not_called()
libs/cli/tests/unit_tests/test_offload_dict_messages.py
+3 -4
View File
@@ -1,7 +1,7 @@
"""Tests for #2741 fix: `perform_offload()` handles serialized state payloads.
Remote HTTP state snapshots and checkpointer fallbacks may surface messages as
raw dicts rather than `BaseMessage` objects. `perform_offload()` must
Remote HTTP state snapshots may surface messages as raw dicts rather than
`BaseMessage` objects. `perform_offload()` must
normalize these before passing them to middleware helpers like
`get_buffer_string()`.
"""
@@ -18,8 +18,7 @@ from deepagents_cli.offload import OffloadResult, perform_offload
if TYPE_CHECKING:
from deepagents.middleware.summarization import SummarizationEvent
# Raw dict messages — what remote state snapshots and checkpoint fallbacks
# may return before deserialization.
# Raw dict messages — what remote state snapshots may return before deserialization.
_DICT_MESSAGES: list[dict[str, Any]] = [
{
"content": "Hi!",
libs/cli/uv.lock
Generated
+125 -47
View File
@@ -8,6 +8,9 @@ resolution-markers = [
"python_full_version < '3.12'",
]
[options]
prerelease-mode = "allow"
[[package]]
name = "agent-client-protocol"
version = "0.8.0"
@@ -967,7 +970,7 @@ wheels = [
[[package]]
name = "deepagents"
version = "0.5.9"
version = "0.6.0"
source = { editable = "../deepagents" }
dependencies = [
{ name = "langchain" },
@@ -980,13 +983,15 @@ dependencies = [
[package.metadata]
requires-dist = [
{ name = "langchain", specifier = ">=1.2.17,<2.0.0" },
{ name = "langchain", specifier = ">=1.3.0,<2.0.0" },
{ name = "langchain-anthropic", specifier = ">=1.4.3,<2.0.0" },
{ name = "langchain-core", specifier = ">=1.3.2,<2.0.0" },
{ name = "langchain-core", specifier = ">=1.4.0,<2.0.0" },
{ name = "langchain-google-genai", specifier = ">=4.2.2,<5.0.0" },
{ name = "langchain-quickjs", marker = "extra == 'quickjs'" },
{ name = "langsmith", specifier = ">=0.8.0" },
{ name = "wcmatch" },
]
provides-extras = ["quickjs"]
[package.metadata.requires-dev]
test = [
@@ -1038,7 +1043,7 @@ dependencies = [
{ name = "langgraph" },
{ name = "langgraph-checkpoint-sqlite" },
{ name = "langgraph-cli", extra = ["inmem"] },
{ name = "langgraph-prebuilt" },
{ name = "langgraph-runtime-inmem" },
{ name = "langgraph-sdk" },
{ name = "langsmith", extra = ["sandbox"] },
{ name = "markdownify" },
@@ -1188,7 +1193,7 @@ requires-dist = [
{ name = "deepagents-cli", extras = ["agentcore", "daytona", "modal", "runloop"], marker = "extra == 'all-sandboxes'" },
{ name = "deepagents-cli", extras = ["anthropic", "baseten", "bedrock", "cohere", "deepseek", "fireworks", "google-genai", "groq", "huggingface", "ibm", "litellm", "mistralai", "nvidia", "ollama", "openai", "openrouter", "perplexity", "together", "vertexai", "xai"], marker = "extra == 'all-providers'" },
{ name = "httpx", specifier = ">=0.28.1,<1.0.0" },
{ name = "langchain", specifier = ">=1.2.17,<2.0.0" },
{ name = "langchain", specifier = ">=1.3.0a2,<2.0.0" },
{ name = "langchain-agentcore-codeinterpreter", marker = "extra == 'agentcore'", specifier = ">=0.0.2" },
{ name = "langchain-anthropic", specifier = ">=1.4.3,<2.0.0" },
{ name = "langchain-anthropic", marker = "extra == 'anthropic'", specifier = ">=1.4.3,<2.0.0" },
@@ -1217,10 +1222,10 @@ requires-dist = [
{ name = "langchain-runloop", marker = "extra == 'runloop'", editable = "../partners/runloop" },
{ name = "langchain-together", marker = "extra == 'together'", specifier = ">=0.4.0,<2.0.0" },
{ name = "langchain-xai", marker = "extra == 'xai'", specifier = ">=1.2.2,<2.0.0" },
{ name = "langgraph", specifier = ">=1.1.10,<2.0.0" },
{ name = "langgraph-checkpoint-sqlite", specifier = ">=3.0.3,<4.0.0" },
{ name = "langgraph", specifier = ">=1.2.0a7,<2.0.0" },
{ name = "langgraph-checkpoint-sqlite", specifier = ">=3.1.0a1,<4.0.0" },
{ name = "langgraph-cli", extras = ["inmem"], specifier = ">=0.4.24,<1.0.0" },
{ name = "langgraph-prebuilt", specifier = ">=1.0.13,<2.0.0" },
{ name = "langgraph-runtime-inmem", specifier = ">=0.28.1,<1.0.0" },
{ name = "langgraph-sdk", specifier = ">=0.3.13,<1.0.0" },
{ name = "langsmith", extras = ["sandbox"], specifier = ">=0.8.0" },
{ name = "markdownify", specifier = ">=0.13.0,<2.0.0" },
@@ -2088,6 +2093,38 @@ wheels = [
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]
[[package]]
name = "httptools"
version = "0.7.1"
source = { registry = "https://pypi.org/simple" }
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libs/code/uv.lock
Generated
+19
View File
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libs/deepagents/deepagents/__init__.py
+8
View File
@@ -1,5 +1,10 @@
"""Deep Agents package."""
from deepagents._subagent_transformer import (
AsyncSubagentRunStream,
SubagentRunStream,
SubagentTransformer,
)
from deepagents._version import __version__
from deepagents.graph import create_deep_agent
from deepagents.middleware.async_subagents import AsyncSubAgent, AsyncSubAgentMiddleware
@@ -18,6 +23,7 @@ from deepagents.profiles import (
__all__ = [
"AsyncSubAgent",
"AsyncSubAgentMiddleware",
"AsyncSubagentRunStream",
"CompiledSubAgent",
"FilesystemMiddleware",
"FilesystemPermission",
@@ -28,6 +34,8 @@ __all__ = [
"ProviderProfile",
"SubAgent",
"SubAgentMiddleware",
"SubagentRunStream",
"SubagentTransformer",
"__version__",
"create_deep_agent",
"register_harness_profile",
libs/deepagents/deepagents/_messages_reducer.py
+78
View File
@@ -0,0 +1,78 @@
"""Local `DeltaChannel` reducer for the messages key.
Adapted from langgraph's `_messages_delta_reducer` (PR #7729). The upstream
version coerces `BaseMessageChunk` writes to full messages for parity with
`add_messages`. Deepagents never writes chunks to the messages channel —
`langchain.agents.create_agent` appends full `AIMessage` objects, and
streaming via `astream_events` operates on the output side, not the state
side — so we skip the per-message coercion.
"""
from __future__ import annotations
from typing import Any, cast
from langchain_core.messages import (
AnyMessage,
BaseMessage,
RemoveMessage,
convert_to_messages,
)
from langgraph.graph.message import REMOVE_ALL_MESSAGES
def _messages_delta_reducer( # noqa: C901
state: list[AnyMessage], writes: list[list[AnyMessage]]
) -> list[AnyMessage]:
"""Batch reducer for use with `DeltaChannel` on the messages key.
Dedups by ID, tombstones via `RemoveMessage`, resets on
`REMOVE_ALL_MESSAGES`. ID-less messages are appended without ID
assignment — checkpointers serialize pending writes before
`update()` runs, so IDs assigned inside the reducer never reach
stored writes and would differ on replay, defeating deduplication.
Raw dict / string / tuple inputs are coerced to typed `BaseMessage` so
HTTP-driven graphs work without a separate coercion step.
"""
# Each write is either a list of message-likes or a single message-like
# (BaseMessage / dict / str / tuple). Only lists flatten; everything
# else is one message.
flat: list[Any] = []
for w in writes:
if isinstance(w, list):
flat.extend(w)
else:
flat.append(w)
# Steady state: the reducer's own output is already typed BaseMessages,
# so skip convert_to_messages on the fast path. Only raw input (initial
# dicts, deserialized blobs) hits the slow path.
state_msgs = state if state and isinstance(state[0], BaseMessage) else cast("list[AnyMessage]", convert_to_messages(state))
msgs = cast("list[AnyMessage]", convert_to_messages(flat))
# REMOVE_ALL_MESSAGES resets everything; find the last sentinel and
# discard all state plus all writes before it.
remove_all_idx = None
for idx, m in enumerate(msgs):
if isinstance(m, RemoveMessage) and m.id == REMOVE_ALL_MESSAGES:
remove_all_idx = idx
if remove_all_idx is not None:
state_msgs = []
msgs = msgs[remove_all_idx + 1 :]
index: dict[str, int] = {m.id: i for i, m in enumerate(state_msgs) if m.id is not None}
result: list[AnyMessage | None] = list(state_msgs)
for msg in msgs:
mid = msg.id
if mid is None:
result.append(msg)
elif isinstance(msg, RemoveMessage):
if mid in index:
result[index[mid]] = None
del index[mid]
elif mid in index:
result[index[mid]] = msg
else:
index[mid] = len(result)
result.append(msg)
return [m for m in result if m is not None]
libs/deepagents/deepagents/_subagent_transformer.py
+246
View File
@@ -0,0 +1,246 @@
"""Surface declared subagents as typed `run.subagents` handles.
Pregel's `tasks` event names a child task by its parent's node name
(typically `"tools"`) plus a Pregel-assigned task id. The actual
`subagent_type` and the user-facing `tool_call_id` only live in the
**parent** task's `input` payload (the list of tool calls). This
transformer does two things:
1. At parent scope, intercept `tasks` start events whose `name ==
"tools"` and `input` is a list containing one or more `task` tool
calls. For each such tool call, record
``parent_task_id → (subagent_type, tool_call_id)``.
2. When a direct-child `tasks` start fires (segment ``"tools:<id>"``),
look up `id` in the pending map. If it resolves to a declared
subagent name, build a `SubagentRunStream` (or async variant)
wrapping a child mini-mux and push it onto the `subagents` log.
The handle reports `graph_name` as the subagent's declared type
(e.g. ``"researcher"``) and `trigger_call_id` as the user-facing
tool call id (e.g. ``"call-parent-1"``).
A subagent therefore shows up on **both** `run.subgraphs` (untyped,
superset, keyed by the raw Pregel segment) and `run.subagents`
(typed, declared-only, with user-friendly identifiers).
"""
from __future__ import annotations
from typing import TYPE_CHECKING, Any, ClassVar
from langgraph.stream.run_stream import (
AsyncSubgraphRunStream,
SubgraphRunStream,
)
from langgraph.stream.stream_channel import StreamChannel
from langgraph.stream.transformers import (
SubgraphStatus,
_TasksLifecycleBase,
)
if TYPE_CHECKING:
from langgraph.stream._mux import StreamMux
from langgraph.stream._types import ProtocolEvent
class SubagentRunStream(SubgraphRunStream):
"""Typed sync handle for a declared subagent execution."""
def __init__(
self,
mux: StreamMux,
*,
path: tuple[str, ...],
graph_name: str | None = None,
trigger_call_id: str | None = None,
task_input: str | None = None,
) -> None:
super().__init__(
mux,
path=path,
graph_name=graph_name,
trigger_call_id=trigger_call_id,
)
self.task_input = task_input
@property
def name(self) -> str | None:
return self.graph_name
@property
def cause(self) -> dict[str, str] | None:
if self.trigger_call_id is None:
return None
return {"type": "toolCall", "tool_call_id": self.trigger_call_id}
class AsyncSubagentRunStream(AsyncSubgraphRunStream):
"""Typed async handle for a declared subagent execution."""
def __init__(
self,
mux: StreamMux,
*,
path: tuple[str, ...],
graph_name: str | None = None,
trigger_call_id: str | None = None,
task_input: str | None = None,
) -> None:
super().__init__(
mux,
path=path,
graph_name=graph_name,
trigger_call_id=trigger_call_id,
)
self.task_input = task_input
@property
def name(self) -> str | None:
return self.graph_name
@property
def cause(self) -> dict[str, str] | None:
if self.trigger_call_id is None:
return None
return {"type": "toolCall", "tool_call_id": self.trigger_call_id}
class SubagentTransformer(_TasksLifecycleBase):
"""Promote declared subagents into typed handles on `run.subagents`."""
_native: ClassVar[bool] = True
def __init__(
self,
scope: tuple[str, ...] = (),
*,
subagent_names: frozenset[str] = frozenset(),
) -> None:
super().__init__(scope)
self._names = subagent_names
self._log: StreamChannel[SubagentRunStream | AsyncSubagentRunStream] = StreamChannel()
self._handles: dict[tuple[str, ...], SubagentRunStream | AsyncSubagentRunStream] = {}
self._mux: StreamMux | None = None
# parent_task_id -> {"subagent_type": ..., "tool_call_id": ...}
self._pending: dict[str, dict[str, str]] = {}
def init(self) -> dict[str, Any]:
return {"subagents": self._log}
def _on_register(self, mux: StreamMux) -> None:
self._mux = mux
def _should_track(self, ns: tuple[str, ...]) -> bool:
depth = len(self.scope)
return len(ns) == depth + 1 and ns[:depth] == self.scope
def _capture_pending_from_parent(self, event: ProtocolEvent) -> None:
"""Record subagent metadata from a parent-scope `tools`-task start.
Pregel emits a `tasks` start at the parent ns whose `input` is
the list of tool calls being dispatched. Each ``task`` tool
call carries the user-visible ``tool_call_id``, the declared
``subagent_type``, and the ``description`` we need at
child-task time.
"""
ns = tuple(event["params"]["namespace"])
if ns != self.scope:
return
data = event["params"]["data"]
if "result" in data or data.get("name") != "tools":
return
parent_task_id = data.get("id")
tool_calls = data.get("input")
if not isinstance(parent_task_id, str) or not isinstance(tool_calls, list):
return
for tc in tool_calls:
if not isinstance(tc, dict) or tc.get("name") != "task":
continue
args = tc.get("args") or {}
subagent_type = args.get("subagent_type")
tool_call_id = tc.get("id")
task_input = args.get("description")
if not isinstance(subagent_type, str):
continue
self._pending[parent_task_id] = {
"subagent_type": subagent_type,
"tool_call_id": tool_call_id if isinstance(tool_call_id, str) else "",
"task_input": task_input if isinstance(task_input, str) else "",
}
# First task-typed call wins; multiple `task` calls under
# the same parent task aren't expected in the current
# scheduling model.
return
def _on_started(
self,
ns: tuple[str, ...],
graph_name: str | None, # noqa: ARG002
trigger_call_id: str | None,
) -> None:
if trigger_call_id is None:
return
info = self._pending.pop(trigger_call_id, None)
if info is None:
return
subagent_type = info["subagent_type"]
if subagent_type not in self._names:
return
if self._mux is None or ns in self._handles:
return
try:
child_mux = self._mux._make_child(ns)
except RuntimeError:
return
handle_cls = AsyncSubagentRunStream if child_mux.is_async else SubagentRunStream
handle = handle_cls(
mux=child_mux,
path=ns,
graph_name=subagent_type,
trigger_call_id=info["tool_call_id"] or None,
task_input=info["task_input"] or None,
)
self._handles[ns] = handle
self._log.push(handle)
def _on_terminal(
self,
ns: tuple[str, ...],
status: SubgraphStatus,
error: str | None,
) -> None:
handle = self._handles.get(ns)
if handle is None or handle._seen_terminal:
return
handle.status = status
if error is not None and handle.error is None:
handle.error = error
handle._seen_terminal = True
if handle._mux is None or handle._mux._events._closed:
return
if status == "failed":
handle._mux.fail(RuntimeError(error or "Subagent failed"))
else:
handle._mux.close()
def _handle_for_event(self, event: ProtocolEvent) -> SubagentRunStream | AsyncSubagentRunStream | None:
ns = tuple(event["params"]["namespace"])
depth = len(self.scope)
if len(ns) < depth + 1:
return None
handle = self._handles.get(ns[: depth + 1])
if handle is None or handle._mux is None or handle._mux._events._closed:
return None
return handle
def process(self, event: ProtocolEvent) -> bool:
if event.get("method") == "tasks":
self._capture_pending_from_parent(event)
keep = super().process(event)
handle = self._handle_for_event(event)
if handle is not None:
# Mirror SubgraphTransformer.process: observe the event on
# the handle (so `_latest` is populated for `output()`)
# before forwarding it to the child mini-mux.
handle._observe_event(event)
handle._mux.push(event)
return keep
libs/deepagents/deepagents/_version.py
+1 -1
View File
@@ -1,3 +1,3 @@
"""Version information for `deepagents` (SDK)."""
__version__ = "0.5.9" # x-release-please-version
__version__ = "0.6.0"
libs/deepagents/deepagents/graph.py
+38 -12
View File
@@ -7,7 +7,7 @@ subagent, and summarization middleware.
import logging
from collections.abc import Callable, Sequence
from typing import Any, cast
from typing import Annotated, Any, Required, cast
from langchain.agents import AgentState, create_agent
from langchain.agents.middleware import HumanInTheLoopMiddleware, InterruptOnConfig, TodoListMiddleware
@@ -16,9 +16,10 @@ from langchain.agents.structured_output import ResponseFormat
from langchain_anthropic import ChatAnthropic
from langchain_anthropic.middleware import AnthropicPromptCachingMiddleware
from langchain_core.language_models import BaseChatModel
from langchain_core.messages import SystemMessage
from langchain_core.messages import AnyMessage, SystemMessage
from langchain_core.tools import BaseTool
from langgraph.cache.base import BaseCache
from langgraph.channels.delta import DeltaChannel
from langgraph.graph.state import CompiledStateGraph
from langgraph.store.base import BaseStore
from langgraph.types import Checkpointer
@@ -30,7 +31,9 @@ from deepagents._excluded_middleware import (
_validate_excluded_middleware_config,
_verify_excluded_middleware_coverage,
)
from deepagents._messages_reducer import _messages_delta_reducer
from deepagents._models import resolve_model
from deepagents._subagent_transformer import SubagentTransformer
from deepagents._tools import _apply_tool_description_overrides
from deepagents._version import __version__
from deepagents.backends import StateBackend
@@ -56,6 +59,13 @@ from deepagents.profiles.harness.harness_profiles import (
logger = logging.getLogger(__name__)
class _DeepAgentState(AgentState):
"""AgentState with DeltaChannel on messages to reduce checkpoint growth from O(N²) to O(N)."""
messages: Required[Annotated[list[AnyMessage], DeltaChannel(_messages_delta_reducer, snapshot_frequency=50)]] # ty: ignore[invalid-argument-type]
BASE_AGENT_PROMPT = """You are a deep agent, an AI assistant that helps users accomplish tasks using tools. You respond with text and tool calls. The user can see your responses and tool outputs in real time.
## Core Behavior
@@ -670,18 +680,19 @@ def create_deep_agent( # noqa: C901, PLR0912, PLR0915 # Complex graph assembly
_permissions=permissions,
)
)
sub_agent_middleware: SubAgentMiddleware | None = None
if inline_subagents:
deepagent_middleware.append(
SubAgentMiddleware(
backend=backend,
subagents=inline_subagents,
task_description=_profile.tool_description_overrides.get("task"),
)
sub_agent_middleware = SubAgentMiddleware(
backend=backend,
subagents=inline_subagents,
# Overrides the task tool description. Value should include
# {available_agents} — a format placeholder replaced with the
# subagent name/description list. Without it the model can't
# see which subagents exist. None (default) uses the built-in
# template. Stale keys silently no-op if the tool is renamed.
task_description=_profile.tool_description_overrides.get("task"),
)
if async_subagents:
# Async here means that we run these subagents in a non-blocking manner.
# Currently this supports agents deployed via LangSmith deployments.
deepagent_middleware.append(AsyncSubAgentMiddleware(async_subagents=async_subagents))
deepagent_middleware.append(sub_agent_middleware)
deepagent_middleware.extend(
[
create_summarization_middleware(model, backend),
@@ -689,6 +700,11 @@ def create_deep_agent( # noqa: C901, PLR0912, PLR0915 # Complex graph assembly
]
)
if async_subagents:
# Async here means that we run these subagents in a non-blocking manner.
# Currently this supports agents deployed via LangSmith deployments.
deepagent_middleware.append(AsyncSubAgentMiddleware(async_subagents=async_subagents))
if middleware:
deepagent_middleware.extend(middleware)
# Harness-profile middleware goes between user middleware and memory so
@@ -737,6 +753,14 @@ def create_deep_agent( # noqa: C901, PLR0912, PLR0915 # Complex graph assembly
else:
final_system_prompt = system_prompt + "\n\n" + base_prompt
# Bake declared subagent names into a scope-aware factory so each
# subgraph mini-mux spawns a fresh `SubagentTransformer` that knows
# which nested runs belong to declared subagents.
subagent_names = frozenset(sub_agent_middleware.subagent_names if sub_agent_middleware is not None else ())
def _subagent_factory(scope: tuple[str, ...] = ()) -> SubagentTransformer:
return SubagentTransformer(scope, subagent_names=subagent_names)
return create_agent(
model,
system_prompt=final_system_prompt,
@@ -749,6 +773,8 @@ def create_deep_agent( # noqa: C901, PLR0912, PLR0915 # Complex graph assembly
debug=debug,
name=name,
cache=cache,
state_schema=_DeepAgentState,
transformers=[_subagent_factory],
).with_config(
{
"recursion_limit": 9_999,
libs/deepagents/deepagents/middleware/filesystem.py
+32 -5
View File
@@ -29,8 +29,9 @@ from langchain.tools.tool_node import ToolCallRequest
from langchain_core.messages import AnyMessage, BaseMessage, HumanMessage, ToolMessage
from langchain_core.messages.content import ContentBlock
from langchain_core.tools import BaseTool, StructuredTool
from langgraph.channels.delta import DeltaChannel
from langgraph.runtime import Runtime
from langgraph.types import Command
from langgraph.types import Command, Overwrite
from pydantic import BaseModel, Field
from deepagents._api.deprecation import warn_deprecated
@@ -231,11 +232,30 @@ def _file_data_reducer(left: dict[str, FileData] | None, right: dict[str, FileDa
return result
def _file_data_delta_reducer(
left: dict[str, FileData] | None,
values: list[dict[str, FileData | None]],
) -> dict[str, FileData]:
"""Batch reducer for use with DeltaChannel.
DeltaChannel calls reducer(base, list(values)) where values is a list of
all writes in the current step. Single dict copy + one pass over all writes.
"""
result: dict[str, FileData] = dict(left) if left else {}
for writes in values:
for key, value in writes.items():
if value is None:
result.pop(key, None)
else:
result[key] = value
return result
class FilesystemState(AgentState):
"""State for the filesystem middleware."""
files: Annotated[NotRequired[dict[str, FileData]], _file_data_reducer]
"""Files in the filesystem."""
files: Annotated[NotRequired[dict[str, FileData]], DeltaChannel(_file_data_delta_reducer, snapshot_frequency=50)] # ty: ignore[invalid-argument-type]
"""Files in the filesystem. Uses DeltaChannel with snapshots every ~50 pregel steps to bound read depth."""
class LsSchema(BaseModel):
@@ -1953,6 +1973,12 @@ class FilesystemMiddleware(AgentMiddleware[FilesystemState, ContextT, ResponseT]
) -> tuple[list[AnyMessage], Command | None]:
"""Tag a newly evicted message and truncate all tagged messages.
When a new eviction fires, uses `Overwrite` to atomically replace
the messages channel with a fully-identified list. A plain append of
the tagged message would not survive DeltaChannel replay: the original
`HumanMessage(id=None)` write gets a fresh UUID on replay that
doesn't match the eviction Command's ID, producing a duplicate.
Args:
messages: The message list (may be modified if write succeeded).
write_result: Result of the backend write, or `None` if no new
@@ -1968,13 +1994,14 @@ class FilesystemMiddleware(AgentMiddleware[FilesystemState, ContextT, ResponseT]
last = messages[-1]
tagged = last.model_copy(
update={
"id": last.id if last.id is not None else str(uuid.uuid4()),
"additional_kwargs": {
**last.additional_kwargs,
"lc_evicted_to": file_path,
}
},
}
)
state_command = Command(update={"messages": [tagged]})
state_command = Command(update={"messages": Overwrite([*messages[:-1], tagged])})
messages = [*messages[:-1], tagged]
processed: list[AnyMessage] = []
libs/deepagents/deepagents/middleware/skills.py
+1
View File
@@ -135,6 +135,7 @@ from deepagents.middleware._utils import append_to_system_message
logger = logging.getLogger(__name__)
# Security: Maximum size for SKILL.md files to prevent DoS attacks (10MB)
MAX_SKILL_FILE_SIZE = 10 * 1024 * 1024
MAX_SKILLS_LOAD_WARNINGS = 20
libs/deepagents/deepagents/middleware/subagents.py
+68 -9
View File
@@ -1,8 +1,9 @@
"""Middleware for providing subagents to an agent via a `task` tool."""
import contextlib
import dataclasses
import json
from collections.abc import Awaitable, Callable, Sequence
from collections.abc import Awaitable, Callable, Generator, Sequence
from typing import Any, NotRequired, TypedDict, cast
from langchain.agents import create_agent
@@ -15,6 +16,7 @@ from langchain_core.messages import HumanMessage, ToolMessage
from langchain_core.runnables import Runnable, RunnableConfig
from langchain_core.tools import StructuredTool
from langgraph.types import Command
from langsmith.run_helpers import get_tracing_context, tracing_context
from pydantic import BaseModel, Field
from deepagents.backends.protocol import BackendFactory, BackendProtocol
@@ -360,7 +362,28 @@ class _SubagentSpec(TypedDict):
runnable: Runnable
def _build_task_tool( # noqa: C901
@contextlib.contextmanager
def _subagent_tracing_context() -> Generator[None, None, None]:
"""Context manager that tags subagent runs with `ls_agent_type="subagent"`.
Sets `ls_agent_type` on the langsmith tracing context `metadata`, which is
propagated to LangSmith runs. This mirrors
langchain's `ls_agent_type="root"` tagging behavior.
Forwards all other current tracing-context fields (parent, client, tags,
etc.) unchanged so this wrapper does not clobber the enclosing context.
"""
current = get_tracing_context()
merged_metadata = {**(current.get("metadata") or {}), "ls_agent_type": "subagent"}
# Pass every field from the current tracing context through to
# `tracing_context` so we don't accidentally clobber fields that may be
# added to langsmith in the future. The only change is `metadata`.
kwargs: dict[str, Any] = {**current, "metadata": merged_metadata}
with tracing_context(**kwargs):
yield
def _build_task_tool( # noqa: C901, PLR0915
subagents: list[_SubagentSpec],
task_description: str | None = None,
) -> BaseTool:
@@ -425,6 +448,27 @@ def _build_task_tool( # noqa: C901
subagent_state["messages"] = [HumanMessage(content=description)]
return subagent, subagent_state
def _build_subagent_config(runtime: ToolRuntime) -> RunnableConfig:
"""Derive the subagent's RunnableConfig from the parent's runtime config.
Only ``callbacks``, ``tags``, and ``configurable`` are forwarded.
Callbacks let Pregel's streaming handlers propagate into the
subagent so its events land on the parent's stream. Tags are
forwarded for tracing continuity. ``configurable`` is needed
for Pregel to recognize the subagent as a nested subgraph.
``recursion_limit`` and ``metadata`` are intentionally *not*
forwarded — the subagent's own bound config must take precedence.
Passing ``metadata`` in the invoke config replaces the
subagent's bound metadata (e.g. ``lc_agent_name``).
"""
parent_config = runtime.config or {}
config: RunnableConfig = {}
for key in ("callbacks", "tags", "configurable"):
if key in parent_config:
config[key] = parent_config[key] # type: ignore[literal-required]
return config
def task(
description: str,
subagent_type: str,
@@ -437,10 +481,16 @@ def _build_task_tool( # noqa: C901
value_error_msg = "Tool call ID is required for subagent invocation"
raise ValueError(value_error_msg)
subagent, subagent_state = _validate_and_prepare_state(subagent_type, description, runtime)
# Don't merge all fields because this will block out manual `.with_config`
subagent_config: RunnableConfig = {"configurable": {**runtime.config.get("configurable", {}), "ls_agent_type": "subagent"}}
result = subagent.invoke(subagent_state, subagent_config)
subagent_config = _build_subagent_config(runtime)
# Tag the subagent's configurable so downstream readers (e.g. middleware
# that key off `runtime.config["configurable"]["ls_agent_type"]`) see the
# subagent context, in addition to the langsmith tracing-context tag.
subagent_config["configurable"] = {
**subagent_config.get("configurable", {}),
"ls_agent_type": "subagent",
}
with _subagent_tracing_context():
result = subagent.invoke(subagent_state, subagent_config)
return _return_command_with_state_update(result, runtime.tool_call_id)
async def atask(
@@ -455,9 +505,15 @@ def _build_task_tool( # noqa: C901
value_error_msg = "Tool call ID is required for subagent invocation"
raise ValueError(value_error_msg)
subagent, subagent_state = _validate_and_prepare_state(subagent_type, description, runtime)
# Don't merge all fields because this will block out manual `.with_config`
subagent_config: RunnableConfig = {"configurable": {**runtime.config.get("configurable", {}), "ls_agent_type": "subagent"}}
result = await subagent.ainvoke(subagent_state, subagent_config)
subagent_config = _build_subagent_config(runtime)
# Mirror `task()` — tag the subagent's configurable as well as the
# langsmith tracing context so both code paths see `ls_agent_type`.
subagent_config["configurable"] = {
**subagent_config.get("configurable", {}),
"ls_agent_type": "subagent",
}
with _subagent_tracing_context():
result = await subagent.ainvoke(subagent_state, subagent_config)
return _return_command_with_state_update(result, runtime.tool_call_id)
return StructuredTool.from_function(
@@ -535,6 +591,9 @@ class SubAgentMiddleware(AgentMiddleware[Any, ContextT, ResponseT]):
self._backend = backend
self._subagents = subagents
subagent_specs = self._get_subagents()
self.subagent_names: frozenset[str] = frozenset(spec["name"] for spec in subagent_specs)
"""Declared subagent names. Public so streamers can discover them
without introspecting the `task` tool's closure."""
task_tool = _build_task_tool(subagent_specs, task_description)
libs/deepagents/pyproject.toml
+5 -3
View File
@@ -1,6 +1,6 @@
[project]
name = "deepagents"
version = "0.5.9"
version = "0.6.0"
description = "General purpose 'deep agent' with sub-agent spawning, todo list capabilities, and mock file system. Built on LangGraph."
readme = "README.md"
@@ -20,14 +20,16 @@ classifiers = [
"Topic :: Software Development :: Libraries :: Python Modules",
]
dependencies = [
"langchain-core>=1.3.2,<2.0.0",
"langchain-core>=1.4.0,<2.0.0",
"langsmith>=0.8.0",
"langchain>=1.2.17,<2.0.0",
"langchain>=1.3.0,<2.0.0",
"langchain-anthropic>=1.4.3,<2.0.0",
"langchain-google-genai>=4.2.2,<5.0.0",
"wcmatch",
]
[project.optional-dependencies]
quickjs = ["langchain-quickjs"]
[project.urls]
Homepage = "https://docs.langchain.com/oss/python/deepagents/overview"
libs/deepagents/tests/unit_tests/middleware/test_memory_middleware.py
+6 -5
View File
@@ -812,11 +812,12 @@ def test_create_deep_agent_with_memory_default_backend() -> None:
assert len(result["messages"]) > 0
# Verify memory was loaded from state
checkpoint = agent.checkpointer.get(config)
assert "/user/.deepagents/AGENTS.md" in checkpoint["channel_values"]["files"]
assert "memory_contents" in checkpoint["channel_values"]
assert "/user/.deepagents/AGENTS.md" in checkpoint["channel_values"]["memory_contents"]
# Verify memory was loaded. Use get_state() — UntrackedValue channels are never
# written to checkpoint["channel_values"], so inspect reconstructed state instead.
state_values = agent.get_state(config).values
assert "/user/.deepagents/AGENTS.md" in state_values["files"]
assert "memory_contents" in state_values
assert "/user/.deepagents/AGENTS.md" in state_values["memory_contents"]
def test_memory_middleware_order_matters(tmp_path: Path) -> None:
libs/deepagents/tests/unit_tests/middleware/test_skills_middleware.py
+4 -1
View File
@@ -1932,8 +1932,11 @@ def test_create_deep_agent_with_skills_default_backend() -> None:
assert len(result["messages"]) > 0
# Use get_state() for `files`: DeltaChannel only writes a snapshot blob every
# 50 steps, so checkpoint["channel_values"] won't contain "files" on non-snapshot steps.
state_values = agent.get_state(config).values
assert "/skills/user/test-skill/SKILL.md" in state_values["files"]
checkpoint = agent.checkpointer.get(config)
assert "/skills/user/test-skill/SKILL.md" in checkpoint["channel_values"]["files"]
assert checkpoint["channel_values"]["skills_metadata"] == [
{
"allowed_tools": [],
libs/deepagents/tests/unit_tests/middleware/test_summarization_middleware.py
-2
View File
@@ -250,7 +250,6 @@ def make_model_request(
model=mock_model,
messages=state["messages"],
system_message=None,
tools=[],
runtime=runtime,
state=state,
)
@@ -897,7 +896,6 @@ async def test_async_system_message_counts_for_truncate_trigger() -> None:
model=mock_model,
messages=state["messages"],
system_message=SystemMessage(content="sys"),
tools=[],
runtime=runtime,
state=state,
)
libs/deepagents/tests/unit_tests/test_deep_agent_streaming.py
+335
View File
@@ -0,0 +1,335 @@
"""Integration tests for create_deep_agent streaming via stream_events(version="v3").
Drives a real `create_deep_agent` graph end-to-end through the
streaming pipeline and asserts that subagents are surfaced as typed
child streams with the right projections. Runs in both sync and
async paths.
"""
import asyncio
from collections.abc import Callable, Sequence
from contextlib import suppress
from typing import Any
from langchain_core.callbacks import CallbackManagerForLLMRun
from langchain_core.language_models import BaseChatModel, LanguageModelInput
from langchain_core.messages import AIMessage, HumanMessage, ToolCall
from langchain_core.outputs import ChatGeneration, ChatResult
from langchain_core.runnables import Runnable
from langchain_core.tools import BaseTool, tool
from langgraph.graph.state import CompiledStateGraph
from pydantic import Field
from deepagents import (
AsyncSubagentRunStream,
SubagentRunStream,
create_deep_agent,
)
class _Scripted(BaseChatModel):
"""Returns a scripted sequence of `AIMessage`s, clamping at the last."""
responses: list[AIMessage] = Field(default_factory=list)
tools: Sequence[dict[str, Any] | type | Callable | BaseTool] = ()
_idx: int = 0
@property
def _llm_type(self) -> str:
return "scripted"
def _generate(
self,
messages: Sequence[Any],
stop: list[str] | None = None,
run_manager: CallbackManagerForLLMRun | None = None,
**kwargs: Any,
) -> ChatResult:
i = min(self._idx, len(self.responses) - 1)
self._idx += 1
return ChatResult(generations=[ChatGeneration(message=self.responses[i])])
def bind_tools(
self,
tools: Sequence[dict[str, Any] | type | Callable | BaseTool],
*,
tool_choice: str | None = None,
**kwargs: Any,
) -> Runnable[LanguageModelInput, AIMessage]:
self.tools = tools
return self
@tool
def _inner(x: str) -> str:
"""Echo the input with a prefix."""
return f"inner-{x}"
def _task_call(description: str, subagent_type: str, call_id: str) -> AIMessage:
return AIMessage(
content="",
tool_calls=[
ToolCall(
id=call_id,
name="task",
args={"description": description, "subagent_type": subagent_type},
)
],
)
def _tool_call(name: str, args: dict[str, Any], call_id: str) -> AIMessage:
return AIMessage(
content="",
tool_calls=[ToolCall(id=call_id, name=name, args=args)],
)
def _build_agent_with_one_subagent() -> CompiledStateGraph:
parent = _Scripted(
responses=[
_task_call("look something up", "researcher", "call-parent-1"),
AIMessage(content="parent done"),
]
)
subagent = _Scripted(
responses=[
_tool_call("_inner", {"x": "foo"}, "call-sub-1"),
AIMessage(content="subagent done"),
]
)
return create_deep_agent(
model=parent,
subagents=[
{
"name": "researcher",
"description": "research subagent",
"system_prompt": "you are a researcher",
"model": subagent,
"tools": [_inner],
}
],
)
class _Failing(BaseChatModel):
"""A chat model whose `_generate` always raises."""
error_message: str = "boom"
tools: Sequence[dict[str, Any] | type | Callable | BaseTool] = ()
@property
def _llm_type(self) -> str:
return "failing"
def _generate(
self,
messages: Sequence[Any],
stop: list[str] | None = None,
run_manager: CallbackManagerForLLMRun | None = None,
**kwargs: Any,
) -> ChatResult:
raise RuntimeError(self.error_message)
def bind_tools(
self,
tools: Sequence[dict[str, Any] | type | Callable | BaseTool],
*,
tool_choice: str | None = None,
**kwargs: Any,
) -> Runnable[LanguageModelInput, AIMessage]:
self.tools = tools
return self
def _build_agent_with_failing_subagent() -> CompiledStateGraph:
parent = _Scripted(
responses=[
_task_call("look something up", "researcher", "call-parent-1"),
AIMessage(content="parent recovered"),
]
)
return create_deep_agent(
model=parent,
subagents=[
{
"name": "researcher",
"description": "research subagent",
"system_prompt": "you are a researcher",
"model": _Failing(error_message="research failed"),
"tools": [_inner],
}
],
)
class TestCreateDeepAgentAstreamV2:
async def test_run_exposes_native_projections(self) -> None:
"""`run.subagents` / `.messages` / `.tool_calls` / `.middleware` all bound."""
agent = _build_agent_with_one_subagent()
run = await agent.astream_events({"messages": [HumanMessage(content="go")]}, version="v3")
for attr in ("subagents", "subgraphs", "messages", "tool_calls", "values"):
assert hasattr(run, attr), f"missing projection {attr!r}"
# Drain to drive the pump to completion.
async for _ in run.messages:
pass
async def test_subagents_yields_one_typed_handle(self) -> None:
agent = _build_agent_with_one_subagent()
run = await agent.astream_events({"messages": [HumanMessage(content="go")]}, version="v3")
handles: list[AsyncSubagentRunStream] = []
async for sub in run.subagents:
assert isinstance(sub, AsyncSubagentRunStream)
handles.append(sub)
async for _ in sub.messages:
pass
async for _ in run.messages:
pass
assert len(handles) == 1
(sub,) = handles
assert sub.name == "researcher"
assert sub.task_input == "look something up"
assert sub.cause == {"type": "toolCall", "tool_call_id": "call-parent-1"}
assert sub.status == "completed"
# path is ("tools:<pregel_task_id>",) — the tool node hosting the subagent.
assert len(sub.path) == 1
assert sub.path[0].startswith("tools:")
sub_output = await sub.output()
assert isinstance(sub_output, dict)
assert "messages" in sub_output
async def test_subagent_tool_calls_surface(self) -> None:
agent = _build_agent_with_one_subagent()
run = await agent.astream_events({"messages": [HumanMessage(content="go")]}, version="v3")
tool_names: list[str] = []
async for sub in run.subagents:
tool_names.extend([tc.tool_name async for tc in sub.tool_calls])
async for _ in sub.messages:
pass
async for _ in run.messages:
pass
assert "_inner" in tool_names
async def test_output_when_no_subagent_invoked(self) -> None:
"""A run that doesn't dispatch to a subagent still completes cleanly."""
model = _Scripted(responses=[AIMessage(content="no tools today")])
agent = create_deep_agent(
model=model,
subagents=[
{
"name": "researcher",
"description": "r",
"system_prompt": "p",
"model": _Scripted(responses=[AIMessage(content="unused")]),
"tools": [],
}
],
)
run = await agent.astream_events({"messages": [HumanMessage(content="hi")]}, version="v3")
# No subagents should surface.
handles = [sub async for sub in run.subagents]
async for _ in run.messages:
pass
assert handles == []
output = await run.output()
assert isinstance(output, dict)
assert output["messages"][-1].content == "no tools today"
async def test_concurrent_iteration_does_not_drop_events(self) -> None:
"""Iterating `subagents` and `messages` in parallel drops no events."""
agent = _build_agent_with_one_subagent()
run = await agent.astream_events({"messages": [HumanMessage(content="go")]}, version="v3")
subagent_names: list[str] = []
parent_message_count = 0
async def drain_subagents() -> None:
async for sub in run.subagents:
subagent_names.append(sub.name)
# Drain sub projections to keep the sub mini-mux healthy.
async for _ in sub.messages:
pass
async def drain_messages() -> None:
nonlocal parent_message_count
async for _ in run.messages:
parent_message_count += 1
await asyncio.gather(drain_subagents(), drain_messages())
assert subagent_names == ["researcher"]
assert parent_message_count > 0
async def test_subagent_error_surfaces_failed_status(self) -> None:
"""A subagent whose model raises mid-run lands as ``status='failed'``.
The error propagates up through Pregel into the parent stream, so
every projection drain may raise — that's fine. The handle should
still surface on `run.subagents` and reach the failed terminal state.
"""
agent = _build_agent_with_failing_subagent()
run = await agent.astream_events({"messages": [HumanMessage(content="go")]}, version="v3")
handles: list[AsyncSubagentRunStream] = []
async def collect_subagents() -> None:
with suppress(RuntimeError):
async for sub in run.subagents:
handles.append(sub)
with suppress(RuntimeError):
async for _ in sub.messages:
pass
async def drain_parent() -> None:
with suppress(RuntimeError):
async for _ in run.messages:
pass
# Drive both projections concurrently so the pump can advance
# past the subagent's terminal event before the error escapes.
await asyncio.gather(collect_subagents(), drain_parent())
assert len(handles) == 1
(sub,) = handles
assert sub.name == "researcher"
assert sub.task_input == "look something up"
assert sub.status == "failed"
assert sub.error is not None
class TestCreateDeepAgentStreamV2:
def test_run_exposes_native_projections_sync(self) -> None:
agent = _build_agent_with_one_subagent()
run = agent.stream_events({"messages": [HumanMessage(content="go")]}, version="v3")
for attr in ("subagents", "subgraphs", "messages", "tool_calls", "values"):
assert hasattr(run, attr)
# Drain to completion.
for _ in run.messages:
pass
def test_subagents_yields_one_typed_handle_sync(self) -> None:
agent = _build_agent_with_one_subagent()
run = agent.stream_events({"messages": [HumanMessage(content="go")]}, version="v3")
handles: list[SubagentRunStream] = []
for sub in run.subagents:
handles.append(sub)
for _ in sub.messages:
pass
for _ in run.messages:
pass
assert len(handles) == 1
assert handles[0].name == "researcher"
assert handles[0].status == "completed"
libs/deepagents/tests/unit_tests/test_end_to_end.py
+97
View File
@@ -17,6 +17,7 @@ from langchain_core.language_models.fake_chat_models import GenericFakeChatModel
from langchain_core.messages import AIMessage, HumanMessage, SystemMessage
from langchain_core.runnables import Runnable
from langchain_core.tools import BaseTool, tool
from langgraph.channels.delta import DeltaChannel
from langgraph.checkpoint.memory import InMemorySaver
from langgraph.store.memory import InMemoryStore
from pydantic import Field
@@ -3481,3 +3482,99 @@ class TestAsyncSubagentEndToEnd:
async_tasks = result.get("async_tasks", {})
assert async_tasks["thread_err"]["status"] == "error"
class TestDeltaChannels:
"""Verify that messages and files use DeltaChannel.
DeltaChannel stores individual writes in the `writes` table rather than
snapshotting the full accumulated value into `channel_values` on every
checkpoint step. This keeps checkpoint blobs small (O(1) per step instead
of O(N) for messages). The full state is still reconstructable via
`agent.get_state()`, which replays writes through the reducer.
"""
def test_messages_uses_delta_channel(self) -> None:
"""Messages channel must be a DeltaChannel in the compiled graph."""
fake_model = FakeChatModelWithHistory(messages=iter([AIMessage(content="Hello!")]))
agent = create_deep_agent(model=fake_model)
assert isinstance(agent.channels.get("messages"), DeltaChannel), "messages must use DeltaChannel so checkpoint growth is O(N) not O(N²)"
def test_messages_reconstructed_via_get_state(self) -> None:
"""get_state() must reconstruct messages correctly despite DeltaChannel."""
fake_model = FakeChatModelWithHistory(messages=iter([AIMessage(content="Hello!")]))
checkpointer = InMemorySaver()
agent = create_deep_agent(model=fake_model, checkpointer=checkpointer)
config: dict = {"configurable": {"thread_id": "delta-messages-reconstruct"}}
agent.invoke({"messages": [HumanMessage(content="Hi")]}, config)
state = agent.get_state(config)
msgs = state.values["messages"]
assert len(msgs) >= 2
assert any(isinstance(m, HumanMessage) for m in msgs)
assert any(isinstance(m, AIMessage) for m in msgs)
def test_files_not_in_channel_values(self) -> None:
"""Files should not appear in checkpoint channel_values (DeltaChannel)."""
fake_model = FakeChatModelWithHistory(
messages=iter(
[
AIMessage(
content="",
tool_calls=[
{
"id": "call_1",
"name": "write_file",
"args": {"file_path": "hello.txt", "content": "hello"},
}
],
),
AIMessage(content="Done."),
]
)
)
backend = StateBackend()
checkpointer = InMemorySaver()
agent = create_deep_agent(model=fake_model, backend=backend, checkpointer=checkpointer)
config: dict = {"configurable": {"thread_id": "delta-files"}}
agent.invoke({"messages": [HumanMessage(content="Write a file")]}, config)
checkpoint = checkpointer.get(config)
assert checkpoint is not None
# DeltaChannel: full files dict is NOT snapshotted into channel_values on every step
assert "files" not in checkpoint["channel_values"], (
"files is a DeltaChannel and should not appear in channel_values; it should be reconstructed from writes"
)
def test_files_reconstructed_via_get_state(self) -> None:
"""get_state() must reconstruct files correctly despite DeltaChannel."""
fake_model = FakeChatModelWithHistory(
messages=iter(
[
AIMessage(
content="",
tool_calls=[
{
"id": "call_1",
"name": "write_file",
"args": {"file_path": "hello.txt", "content": "hello"},
}
],
),
AIMessage(content="Done."),
]
)
)
backend = StateBackend()
checkpointer = InMemorySaver()
agent = create_deep_agent(model=fake_model, backend=backend, checkpointer=checkpointer)
config: dict = {"configurable": {"thread_id": "delta-files-reconstruct"}}
agent.invoke({"messages": [HumanMessage(content="Write a file")]}, config)
state = agent.get_state(config)
files = state.values.get("files", {})
assert any("hello.txt" in k for k in files)
libs/deepagents/tests/unit_tests/test_middleware.py
+3 -3
View File
@@ -72,7 +72,7 @@ def _runtime(tool_call_id=""):
class TestAddMiddleware:
def test_filesystem_middleware(self):
middleware = [FilesystemMiddleware()]
agent = create_agent(model="claude-sonnet-4-6", middleware=middleware, tools=[])
agent = create_agent(model="claude-sonnet-4-6", middleware=middleware)
assert "files" in agent.stream_channels
agent_tools = agent.nodes["tools"].bound._tools_by_name.keys()
assert "ls" in agent_tools
@@ -89,7 +89,7 @@ class TestAddMiddleware:
subagents=[{**GENERAL_PURPOSE_SUBAGENT, "model": "claude-sonnet-4-6", "tools": []}],
)
]
agent = create_agent(model="claude-sonnet-4-6", middleware=middleware, tools=[])
agent = create_agent(model="claude-sonnet-4-6", middleware=middleware)
assert "task" in agent.nodes["tools"].bound._tools_by_name
def test_multiple_middleware(self):
@@ -100,7 +100,7 @@ class TestAddMiddleware:
subagents=[{**GENERAL_PURPOSE_SUBAGENT, "model": "claude-sonnet-4-6", "tools": []}],
),
]
agent = create_agent(model="claude-sonnet-4-6", middleware=middleware, tools=[])
agent = create_agent(model="claude-sonnet-4-6", middleware=middleware)
assert "files" in agent.stream_channels
agent_tools = agent.nodes["tools"].bound._tools_by_name.keys()
assert "ls" in agent_tools
libs/deepagents/tests/unit_tests/test_subagent_transformer.py
+387
View File
@@ -0,0 +1,387 @@
"""Unit tests for `SubagentTransformer`.
Pushes synthetic `tasks` protocol events into a `StreamMux` configured
with `SubagentTransformer` alongside the usual native transformers.
Mirrors the structure of langgraph's `test_stream_subgraph_transformer.py`.
The realistic event sequence is:
1. Parent-scope `tasks` start with ``name == "tools"`` and ``input``
containing ``task`` tool calls — this is how the transformer learns
``parent_task_id → (subagent_type, tool_call_id)``.
2. Child-scope `tasks` start at ``["tools:<parent_task_id>"]`` —
triggers `_on_started`, which looks up the parent mapping and
builds a `SubagentRunStream` if the type is declared.
3. Parent-scope `tasks` result with the matching ``id`` — closes the
child handle.
"""
from __future__ import annotations
import time
from typing import TYPE_CHECKING, Any
from langgraph.errors import GraphInterrupt
from langgraph.stream._mux import StreamMux
from langgraph.stream.stream_channel import StreamChannel
from langgraph.stream.transformers import (
LifecycleTransformer,
MessagesTransformer,
SubgraphTransformer,
ValuesTransformer,
)
from deepagents import SubagentRunStream, SubagentTransformer
if TYPE_CHECKING:
from langgraph.stream._types import ProtocolEvent
TS = int(time.time() * 1000)
def _tools_start(
namespace: list[str],
*,
parent_task_id: str,
subagent_type: str,
tool_call_id: str,
) -> ProtocolEvent:
"""A parent-scope `tools`-task start that dispatches one `task` tool call."""
return {
"type": "event",
"method": "tasks",
"params": {
"namespace": namespace,
"timestamp": TS,
"data": {
"id": parent_task_id,
"name": "tools",
"input": [
{
"name": "task",
"args": {"subagent_type": subagent_type},
"id": tool_call_id,
}
],
"triggers": [],
},
},
}
def _child_tasks_start(
namespace: list[str],
*,
task_id: str = "child-task",
name: str = "PatchToolCallsMiddleware.before_agent",
) -> ProtocolEvent:
"""A child-scope `tasks` start (any inner node — kicks off the subagent)."""
return {
"type": "event",
"method": "tasks",
"params": {
"namespace": namespace,
"timestamp": TS,
"data": {
"id": task_id,
"name": name,
"input": None,
"triggers": [],
},
},
}
def _parent_tasks_result(
namespace: list[str],
*,
parent_task_id: str,
error: str | None = None,
interrupts: list[dict[str, Any]] | None = None,
) -> ProtocolEvent:
"""A parent-scope `tools`-task result that closes the dispatched subagent."""
return {
"type": "event",
"method": "tasks",
"params": {
"namespace": namespace,
"timestamp": TS,
"data": {
"id": parent_task_id,
"name": "tools",
"error": error,
"interrupts": interrupts or [],
"result": {},
},
},
}
def _spawn(
mux: StreamMux,
*,
parent_task_id: str,
subagent_type: str,
tool_call_id: str,
parent_ns: list[str] | None = None,
) -> None:
"""Push parent + child start events that mimic a real subagent spawn."""
parent_ns = parent_ns or []
mux.push(
_tools_start(
parent_ns,
parent_task_id=parent_task_id,
subagent_type=subagent_type,
tool_call_id=tool_call_id,
)
)
mux.push(_child_tasks_start([*parent_ns, f"tools:{parent_task_id}"]))
def _values(payload: dict[str, Any], *, namespace: list[str]) -> ProtocolEvent:
return {
"type": "event",
"method": "values",
"params": {
"namespace": namespace,
"timestamp": TS,
"data": payload,
},
}
def _subscribe(log: StreamChannel) -> None:
log._subscribed = True
def _pre_subscribe_handle(handle: SubagentRunStream) -> None:
"""Flip `_subscribed` on every StreamChannel inside the handle's mini-mux."""
for value in handle._mux.extensions.values():
if isinstance(value, StreamChannel):
_subscribe(value)
def _factories(names: frozenset[str]):
def subagent_factory(scope: tuple[str, ...]) -> SubagentTransformer:
return SubagentTransformer(scope, subagent_names=names)
return [
ValuesTransformer,
MessagesTransformer,
LifecycleTransformer,
SubgraphTransformer,
subagent_factory,
]
def _handle_values_items(handle: SubagentRunStream) -> list:
# StreamChannel._items now stores `(stamp, item)` tuples; strip the stamp.
return [item for _stamp, item in handle._mux.extensions["values"]._items]
def _handle_subagents_items(handle: SubagentRunStream) -> list:
return [item for _stamp, item in handle._mux.extensions["subagents"]._items]
class TestSubagentTransformerUnit:
NAMES = frozenset({"researcher", "coder"})
def _mux(self) -> tuple[StreamMux, SubagentTransformer]:
mux = StreamMux(factories=_factories(self.NAMES), is_async=False)
transformer = mux.transformer_by_key("subagents")
assert isinstance(transformer, SubagentTransformer)
_subscribe(transformer._log)
return mux, transformer
def _handle(self, transformer: SubagentTransformer) -> SubagentRunStream:
# StreamChannel._items now stores `(stamp, item)` tuples; strip the stamp.
(entry,) = list(transformer._log._items)
_stamp, handle = entry
return handle
def test_nondeclared_subagent_type_is_ignored(self) -> None:
"""A `task` tool call with a non-declared subagent_type stays off `.subagents`."""
mux, transformer = self._mux()
_spawn(
mux,
parent_task_id="abc",
subagent_type="plain_subagent",
tool_call_id="tc-1",
)
assert list(transformer._log._items) == []
assert transformer._handles == {}
def test_declared_subagent_yields_handle(self) -> None:
"""A declared subagent_type produces a `SubagentRunStream` with proper metadata."""
mux, transformer = self._mux()
_spawn(
mux,
parent_task_id="abc",
subagent_type="researcher",
tool_call_id="tc-1",
)
handle = self._handle(transformer)
assert isinstance(handle, SubagentRunStream)
assert handle.path == ("tools:abc",)
assert handle.name == "researcher"
assert handle.cause == {"type": "toolCall", "tool_call_id": "tc-1"}
assert handle.status == "started"
def test_status_transitions(self) -> None:
"""A parent-scope tasks-result closes the subagent and marks completed."""
mux, transformer = self._mux()
_spawn(
mux,
parent_task_id="x",
subagent_type="researcher",
tool_call_id="tc-1",
)
mux.push(_parent_tasks_result([], parent_task_id="x"))
handle = self._handle(transformer)
assert handle.status == "completed"
assert handle._mux.extensions["values"]._closed
def test_failed_stores_error(self) -> None:
mux, transformer = self._mux()
_spawn(
mux,
parent_task_id="x",
subagent_type="researcher",
tool_call_id="tc-1",
)
mux.push(_parent_tasks_result([], parent_task_id="x", error="boom"))
handle = self._handle(transformer)
assert handle.status == "failed"
assert handle.error == "boom"
def test_values_routed_into_handle(self) -> None:
"""Values events under the subagent's ns flow into its mini-mux."""
mux, transformer = self._mux()
_spawn(
mux,
parent_task_id="x",
subagent_type="researcher",
tool_call_id="tc-1",
)
handle = self._handle(transformer)
_pre_subscribe_handle(handle)
mux.push(_values({"k": 1}, namespace=["tools:x"]))
mux.push(_values({"k": 2}, namespace=["tools:x"]))
assert _handle_values_items(handle) == [{"k": 1}, {"k": 2}]
assert handle.output == {"k": 2}
def test_root_values_not_routed(self) -> None:
"""A values event at root ns must not leak into a child handle."""
mux, transformer = self._mux()
_spawn(
mux,
parent_task_id="x",
subagent_type="researcher",
tool_call_id="tc-1",
)
handle = self._handle(transformer)
_pre_subscribe_handle(handle)
mux.push(_values({"k": "root"}, namespace=[]))
assert _handle_values_items(handle) == []
def test_nested_subagent_surfaces_under_parent(self) -> None:
"""A subagent spawned from inside another subagent surfaces on the parent's `.subagents`."""
mux, transformer = self._mux()
_spawn(
mux,
parent_task_id="p",
subagent_type="researcher",
tool_call_id="tc-p",
)
parent = self._handle(transformer)
_pre_subscribe_handle(parent)
# Nested spawn: parent ns is the researcher's ns; same `tools`-then-child pattern.
_spawn(
mux,
parent_task_id="c",
subagent_type="coder",
tool_call_id="tc-c",
parent_ns=["tools:p"],
)
(child,) = _handle_subagents_items(parent)
assert isinstance(child, SubagentRunStream)
assert child.path == ("tools:p", "tools:c")
assert child.name == "coder"
def test_nested_nondeclared_does_not_surface_on_subagents(self) -> None:
"""A nested non-declared subagent_type does NOT appear on `.subagents`."""
mux, transformer = self._mux()
_spawn(
mux,
parent_task_id="p",
subagent_type="researcher",
tool_call_id="tc-p",
)
parent = self._handle(transformer)
_pre_subscribe_handle(parent)
_spawn(
mux,
parent_task_id="c",
subagent_type="plain_nested",
tool_call_id="tc-c",
parent_ns=["tools:p"],
)
assert _handle_subagents_items(parent) == []
def test_finalize_closes_dangling(self) -> None:
"""A still-open child at finalize time is marked completed and its mux closed."""
mux, transformer = self._mux()
_spawn(
mux,
parent_task_id="x",
subagent_type="researcher",
tool_call_id="tc-1",
)
handle = self._handle(transformer)
mux.close()
assert handle.status == "completed"
assert handle._mux.extensions["values"]._closed
assert handle._mux.extensions["subagents"]._closed
def test_fail_with_graph_interrupt_marks_interrupted(self) -> None:
mux, transformer = self._mux()
_spawn(
mux,
parent_task_id="x",
subagent_type="researcher",
tool_call_id="tc-1",
)
handle = self._handle(transformer)
mux.fail(GraphInterrupt())
assert handle.status == "interrupted"
def test_fail_with_generic_error_marks_failed(self) -> None:
mux, transformer = self._mux()
_spawn(
mux,
parent_task_id="x",
subagent_type="researcher",
tool_call_id="tc-1",
)
handle = self._handle(transformer)
mux.fail(RuntimeError("kaboom"))
assert handle.status == "failed"
assert handle.error == "kaboom"
libs/deepagents/tests/unit_tests/test_subagents.py
-2
View File
@@ -2552,7 +2552,6 @@ class TestSubAgents:
description="A test worker subagent.",
system_prompt="You are a test worker.",
model=subagent_model,
tools=[],
)
],
)
@@ -2656,7 +2655,6 @@ class TestSubAgents:
description="A test worker subagent.",
system_prompt="You are a test worker.",
model=subagent_model,
tools=[],
)
],
)
libs/deepagents/uv.lock
Generated
+73 -24
View File
@@ -13,6 +13,9 @@ resolution-markers = [
"python_full_version < '3.13' and sys_platform != 'emscripten' and sys_platform != 'win32'",
]
[options]
prerelease-mode = "allow"
[[package]]
name = "annotated-types"
version = "0.7.0"
@@ -412,7 +415,7 @@ wheels = [
[[package]]
name = "deepagents"
version = "0.5.9"
version = "0.6.0"
source = { editable = "." }
dependencies = [
{ name = "langchain" },
@@ -423,6 +426,11 @@ dependencies = [
{ name = "wcmatch" },
]
[package.optional-dependencies]
quickjs = [
{ name = "langchain-quickjs" },
]
[package.dev-dependencies]
test = [
{ name = "build" },
@@ -444,13 +452,15 @@ test = [
[package.metadata]
requires-dist = [
{ name = "langchain", specifier = ">=1.2.17,<2.0.0" },
{ name = "langchain", specifier = ">=1.3.0,<2.0.0" },
{ name = "langchain-anthropic", specifier = ">=1.4.3,<2.0.0" },
{ name = "langchain-core", specifier = ">=1.3.2,<2.0.0" },
{ name = "langchain-core", specifier = ">=1.4.0,<2.0.0" },
{ name = "langchain-google-genai", specifier = ">=4.2.2,<5.0.0" },
{ name = "langchain-quickjs", marker = "extra == 'quickjs'" },
{ name = "langsmith", specifier = ">=0.8.0" },
{ name = "wcmatch" },
]
provides-extras = ["quickjs"]
[package.metadata.requires-dev]
test = [
@@ -805,16 +815,16 @@ wheels = [
[[package]]
name = "langchain"
version = "1.2.17"
version = "1.3.0"
source = { registry = "https://pypi.org/simple" }
dependencies = [
{ name = "langchain-core" },
{ name = "langgraph" },
{ name = "pydantic" },
]
sdist = { url = "https://files.pythonhosted.org/packages/46/35/322d13339acb61d7a733d03a73a9ade968c64ac0eb982f497d24e22a998f/langchain-1.2.17.tar.gz", hash = "sha256:c30b578c0eebbde8bec9247dbbbae1a791128557b99b65c8be1e007040975d09", size = 577779, upload-time = "2026-04-30T20:25:34.626Z" }
sdist = { url = "https://files.pythonhosted.org/packages/a6/74/03fd4c07993c49c4b80635bb4c723643ff78af81c9471d1266f879f68df1/langchain-1.3.0.tar.gz", hash = "sha256:8ec70ee0cef94255f3e522423b254093a3dd34509638d353c50f3d9dd498debc", size = 580604, upload-time = "2026-05-12T14:45:50.7Z" }
wheels = [
{ url = "https://files.pythonhosted.org/packages/d1/cf/b183dba8667f7b6d1be546fb8089a3bc3bc12b514f551f5317ae03815770/langchain-1.2.17-py3-none-any.whl", hash = "sha256:ff881cdfbe90e0b6afac42eea7999657c282cc73db059c910d803f4e9f8ff305", size = 113131, upload-time = "2026-04-30T20:25:32.895Z" },
{ url = "https://files.pythonhosted.org/packages/7b/6f/b9a9721c27fbb6d29a6a7cd89d6a41eeffc7c79b49b9a5cf5beb1d60952d/langchain-1.3.0-py3-none-any.whl", hash = "sha256:9ce48828c706c00c586304b519fbd910e75d9f5ab3f319c31834e42107437f43", size = 114079, upload-time = "2026-05-12T14:45:48.818Z" },
]
[[package]]
@@ -833,7 +843,7 @@ wheels = [
[[package]]
name = "langchain-core"
version = "1.3.3"
version = "1.4.0"
source = { registry = "https://pypi.org/simple" }
dependencies = [
{ name = "jsonpatch" },
@@ -846,9 +856,9 @@ dependencies = [
{ name = "typing-extensions" },
{ name = "uuid-utils" },
]
sdist = { url = "https://files.pythonhosted.org/packages/d3/ae/8b74458fc3850ec3d150eb9f45e857db129dafa801fb5cf173dfc9f8bbf3/langchain_core-1.3.3.tar.gz", hash = "sha256:fa510a5db8efdc0c6ff41c0939fb5c00a0183c11f6b84233e892e3227ff69182", size = 915041, upload-time = "2026-05-05T19:02:36.612Z" }
sdist = { url = "https://files.pythonhosted.org/packages/59/de/679a53472c25860837e32c0442c962fa86e95317a36460e2c9d5c91b17c2/langchain_core-1.4.0.tar.gz", hash = "sha256:1dc341eed802ed9c117c0df3923c991e5e9e226571e5725c194eeb5bd93d1a7f", size = 920260, upload-time = "2026-05-11T18:42:35.919Z" }
wheels = [
{ url = "https://files.pythonhosted.org/packages/1f/01/4771b7ab2af1d1aba5b710bd8f13d9225c609425214b357590a17b01be77/langchain_core-1.3.3-py3-none-any.whl", hash = "sha256:18aae8506f37da7f74398492279a7d6efcee4f8e23c4c41c7af080eeb7ef7bd1", size = 543857, upload-time = "2026-05-05T19:02:34.52Z" },
{ url = "https://files.pythonhosted.org/packages/0f/1a/86c38c27b81913a1c6c12448cab55defb5a1097c7dc9a4cea83f55477a2d/langchain_core-1.4.0-py3-none-any.whl", hash = "sha256:23cbbdb46e38ddd1dd5247e6167e96013eae74bea4c5949c550809970a9e565c", size = 548120, upload-time = "2026-05-11T18:42:33.992Z" },
]
[[package]]
@@ -882,14 +892,30 @@ wheels = [
[[package]]
name = "langchain-protocol"
version = "0.0.13"
version = "0.0.14"
source = { registry = "https://pypi.org/simple" }
dependencies = [
{ name = "typing-extensions" },
]
sdist = { url = "https://files.pythonhosted.org/packages/ba/7d/ac74b64f9d3150cc90c172490e7321b26ccc76ecef87c3629c83eda6948f/langchain_protocol-0.0.13.tar.gz", hash = "sha256:7448ca507407a6aaa28a73884d74765540e65da891a14a6e062a196412bc554c", size = 5713, upload-time = "2026-04-28T21:08:11.584Z" }
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libs/partners/daytona/uv.lock
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