mirror of
https://github.com/langchain-ai/deepagents.git
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fix(sdk): stable HumanMessage IDs across resumed threads (#3591)
**Depends on:** langchain-ai/langgraph#7913 (merged as langgraph 1.2.2) ## Summary - **Bumps `langchain` minimum to 1.3.2** — which pulls in `langgraph>=1.2.2` transitively; explicit `langgraph` pin removed - **Removes `Overwrite` workaround** in summarization middleware (`bee514fd2`): now that DeltaChannel writes are stamped with stable IDs before serialisation, same-ID message updates work correctly via the reducer's in-place update path - **Removes ID assignment from `_messages_delta_reducer`** — IDs are now assigned by `ensure_message_ids()` in LangGraph's `put_writes()` before writes reach the checkpointer, making reducer-level assignment redundant - **Updates snapshots** — langchain 1.3.2 updated the `write_todos` tool description and system prompt wording - **Updates all lockfiles** across libs and examples ## Root cause (from investigation) `DeltaChannel` stores raw writes and replays them through the reducer. In the default async/sync durability modes, `put_writes()` submits checkpoint writes to a background thread before `apply_writes()` runs. If the thread serialised a message before the reducer assigned its ID, the checkpoint stored `id=None` and every `get_state()` call produced a different UUID — the same message appeared with a different ID in each LangSmith trace. ## Fix (in LangGraph 1.2.2) `ensure_message_ids()` in `put_writes()` coerces message-like write values to typed `BaseMessage` objects with stable UUIDs before the background thread serialises them. Handles `BaseMessage` objects (single and in lists) and dicts with known `role`/`type` keys (OpenAI-style API input). ## Tests - `test_get_state_messages_have_ids` — all messages have non-None ids after `get_state()` - `test_dict_style_invoke_messages_have_stable_ids` — dict-style `{"role": "user"}` input also gets stable IDs (covers the API / over-the-wire path) - `test_human_message_id_stable_across_invocations_sync` — original HumanMessage keeps its ID across resumed threads (sync) - `test_human_message_id_stable_across_invocations_async` — same, async path
This commit is contained in:
Sydney Runkle
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||||
]
|
||||
|
||||
[[package]]
|
||||
|
||||
Generated
+7
-7
@@ -443,7 +443,7 @@ dependencies = [
|
||||
|
||||
[package.metadata]
|
||||
requires-dist = [
|
||||
{ name = "langchain", specifier = ">=1.3.0,<2.0.0" },
|
||||
{ name = "langchain", specifier = ">=1.3.2,<2.0.0" },
|
||||
{ name = "langchain-anthropic", specifier = ">=1.4.3,<2.0.0" },
|
||||
{ name = "langchain-core", specifier = ">=1.4.0,<2.0.0" },
|
||||
{ name = "langchain-google-genai", specifier = ">=4.2.2,<5.0.0" },
|
||||
@@ -752,16 +752,16 @@ wheels = [
|
||||
|
||||
[[package]]
|
||||
name = "langchain"
|
||||
version = "1.3.0"
|
||||
version = "1.3.2"
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||||
source = { registry = "https://pypi.org/simple" }
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dependencies = [
|
||||
{ name = "langchain-core" },
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{ name = "langgraph" },
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{ url = "https://files.pythonhosted.org/packages/f8/82/a54edcd1c48163de5642eb10fa2cb58b13a8889c659964f63f0306b58b1e/langchain-1.3.2-py3-none-any.whl", hash = "sha256:900f6b3f4ee08b9ba3cdbe667dbf42525bd6f66a4a07a7f1db26262673e41ed6", size = 121225, upload-time = "2026-05-26T18:17:56.075Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
@@ -855,7 +855,7 @@ wheels = [
|
||||
|
||||
[[package]]
|
||||
name = "langgraph"
|
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version = "1.2.0"
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version = "1.2.2"
|
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source = { registry = "https://pypi.org/simple" }
|
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dependencies = [
|
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{ name = "langchain-core" },
|
||||
@@ -865,9 +865,9 @@ dependencies = [
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{ name = "pydantic" },
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||||
{ name = "xxhash" },
|
||||
]
|
||||
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wheels = [
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{ url = "https://files.pythonhosted.org/packages/42/9b/b08d578bba73e25351152dfd3d6d21e81210a5fff1b6f26e56f33197c8f5/langgraph-1.2.2-py3-none-any.whl", hash = "sha256:0a851bf4ba5939c5474a2fd57e6b439b5315283e254e42943bd392c2d71a5e03", size = 236376, upload-time = "2026-05-26T18:07:26.577Z" },
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||||
]
|
||||
|
||||
[[package]]
|
||||
|
||||
Generated
+7
-7
@@ -805,7 +805,7 @@ dependencies = [
|
||||
|
||||
[package.metadata]
|
||||
requires-dist = [
|
||||
{ name = "langchain", specifier = ">=1.3.0,<2.0.0" },
|
||||
{ name = "langchain", specifier = ">=1.3.2,<2.0.0" },
|
||||
{ name = "langchain-anthropic", specifier = ">=1.4.3,<2.0.0" },
|
||||
{ name = "langchain-core", specifier = ">=1.4.0,<2.0.0" },
|
||||
{ name = "langchain-google-genai", specifier = ">=4.2.2,<5.0.0" },
|
||||
@@ -1642,16 +1642,16 @@ wheels = [
|
||||
|
||||
[[package]]
|
||||
name = "langchain"
|
||||
version = "1.3.0"
|
||||
version = "1.3.2"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "langchain-core" },
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wheels = [
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{ url = "https://files.pythonhosted.org/packages/f8/82/a54edcd1c48163de5642eb10fa2cb58b13a8889c659964f63f0306b58b1e/langchain-1.3.2-py3-none-any.whl", hash = "sha256:900f6b3f4ee08b9ba3cdbe667dbf42525bd6f66a4a07a7f1db26262673e41ed6", size = 121225, upload-time = "2026-05-26T18:17:56.075Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
@@ -1815,7 +1815,7 @@ test = [
|
||||
|
||||
[[package]]
|
||||
name = "langgraph"
|
||||
version = "1.2.0"
|
||||
version = "1.2.2"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "langchain-core" },
|
||||
@@ -1825,9 +1825,9 @@ dependencies = [
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{ name = "pydantic" },
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{ name = "xxhash" },
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wheels = [
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{ url = "https://files.pythonhosted.org/packages/42/9b/b08d578bba73e25351152dfd3d6d21e81210a5fff1b6f26e56f33197c8f5/langgraph-1.2.2-py3-none-any.whl", hash = "sha256:0a851bf4ba5939c5474a2fd57e6b439b5315283e254e42943bd392c2d71a5e03", size = 236376, upload-time = "2026-05-26T18:07:26.577Z" },
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]
|
||||
|
||||
[[package]]
|
||||
|
||||
@@ -27,8 +27,7 @@ classifiers = [
|
||||
dependencies = [
|
||||
# Framework
|
||||
"deepagents==0.6.3",
|
||||
"langchain>=1.3.1,<2.0.0",
|
||||
"langgraph>=1.2.0,<2.0.0",
|
||||
"langchain>=1.3.2,<2.0.0",
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||||
"langgraph-checkpoint-sqlite>=3.1.0,<4.0.0",
|
||||
|
||||
# Client-server architecture
|
||||
|
||||
Generated
+13
-10
@@ -980,7 +980,7 @@ dependencies = [
|
||||
|
||||
[package.metadata]
|
||||
requires-dist = [
|
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{ name = "langchain", specifier = ">=1.3.0,<2.0.0" },
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||||
{ name = "langchain", specifier = ">=1.3.2,<2.0.0" },
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||||
{ name = "langchain-anthropic", specifier = ">=1.4.3,<2.0.0" },
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||||
{ name = "langchain-core", specifier = ">=1.4.0,<2.0.0" },
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||||
{ name = "langchain-google-genai", specifier = ">=4.2.2,<5.0.0" },
|
||||
@@ -1037,7 +1037,6 @@ dependencies = [
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||||
{ name = "langchain-google-genai" },
|
||||
{ name = "langchain-mcp-adapters" },
|
||||
{ name = "langchain-openai" },
|
||||
{ name = "langgraph" },
|
||||
{ name = "langgraph-checkpoint-sqlite" },
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||||
{ name = "langgraph-cli", extra = ["inmem"] },
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||||
{ name = "langgraph-runtime-inmem" },
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||||
@@ -1194,7 +1193,7 @@ requires-dist = [
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||||
{ name = "deepagents-code", extras = ["agentcore", "daytona", "modal", "runloop"], marker = "extra == 'all-sandboxes'" },
|
||||
{ name = "deepagents-code", 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'" },
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||||
{ name = "httpx", specifier = ">=0.28.1,<1.0.0" },
|
||||
{ name = "langchain", specifier = ">=1.3.1,<2.0.0" },
|
||||
{ name = "langchain", specifier = ">=1.3.2,<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" },
|
||||
@@ -1224,7 +1223,6 @@ requires-dist = [
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||||
{ 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 = ">=1.2.0,<2.0.0" },
|
||||
{ name = "langgraph-checkpoint-sqlite", specifier = ">=3.1.0,<4.0.0" },
|
||||
{ name = "langgraph-cli", extras = ["inmem"], specifier = ">=0.4.24,<1.0.0" },
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||||
{ name = "langgraph-runtime-inmem", specifier = ">=0.28.1,<1.0.0" },
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@@ -1810,6 +1808,7 @@ wheels = [
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{ url = "https://files.pythonhosted.org/packages/96/61/373c30b7197f9e756e4c81ae90a8d55dc3598c17673f91f4d31c3c689c3f/greenlet-3.3.1-cp314-cp314-musllinux_1_2_aarch64.whl", hash = "sha256:aec9ab04e82918e623415947921dea15851b152b822661cce3f8e4393c3df683", size = 1615261, upload-time = "2026-01-23T16:04:25.066Z" },
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{ url = "https://files.pythonhosted.org/packages/fd/d3/ca534310343f5945316f9451e953dcd89b36fe7a19de652a1dc5a0eeef3f/greenlet-3.3.1-cp314-cp314-musllinux_1_2_x86_64.whl", hash = "sha256:71c767cf281a80d02b6c1bdc41c9468e1f5a494fb11bc8688c360524e273d7b1", size = 1683719, upload-time = "2026-01-23T15:33:50.61Z" },
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{ url = "https://files.pythonhosted.org/packages/97/43/8bf0ffa3d498eeee4c58c212a3905dd6146c01c8dc0b0a046481ca29b18c/greenlet-3.3.1-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:ed6b402bc74d6557a705e197d47f9063733091ed6357b3de33619d8a8d93ac53", size = 1614917, upload-time = "2026-01-23T16:04:26.276Z" },
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{ url = "https://files.pythonhosted.org/packages/89/90/a3be7a5f378fc6e84abe4dcfb2ba32b07786861172e502388b4c90000d1b/greenlet-3.3.1-cp314-cp314t-musllinux_1_2_x86_64.whl", hash = "sha256:59913f1e5ada20fde795ba906916aea25d442abcc0593fba7e26c92b7ad76249", size = 1676092, upload-time = "2026-01-23T15:33:52.176Z" },
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@@ -2553,16 +2556,16 @@ wheels = [
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[[package]]
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name = "langchain"
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version = "1.3.1"
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version = "1.3.2"
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source = { registry = "https://pypi.org/simple" }
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dependencies = [
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{ name = "langchain-core" },
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{ name = "langgraph" },
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{ name = "pydantic" },
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]
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sdist = { url = "https://files.pythonhosted.org/packages/11/e5/6350e77a9e2764eaafcb2d581cbf0b800f53c6bc98fdf5ebc85f3a931ded/langchain-1.3.1.tar.gz", hash = "sha256:bc283c220233230f48b8e50ab1fbf1b688bcb206d933fa448d40a9b143177f62", size = 581329, upload-time = "2026-05-15T18:14:55.368Z" }
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wheels = [
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{ url = "https://files.pythonhosted.org/packages/78/11/3d7ed10b535413a07ed5e15682abcb77f3c4204ac49586977a495f9b24e6/langchain-1.3.1-py3-none-any.whl", hash = "sha256:154e9c30c90b391eba4315296f6bf6b6fac6b058ddea4cc771a10470968fe36f", size = 114345, upload-time = "2026-05-15T18:14:53.984Z" },
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{ url = "https://files.pythonhosted.org/packages/f8/82/a54edcd1c48163de5642eb10fa2cb58b13a8889c659964f63f0306b58b1e/langchain-1.3.2-py3-none-any.whl", hash = "sha256:900f6b3f4ee08b9ba3cdbe667dbf42525bd6f66a4a07a7f1db26262673e41ed6", size = 121225, upload-time = "2026-05-26T18:17:56.075Z" },
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[[package]]
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@@ -3126,7 +3129,7 @@ wheels = [
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[[package]]
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name = "langgraph"
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version = "1.2.2"
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source = { registry = "https://pypi.org/simple" }
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dependencies = [
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{ name = "langchain-core" },
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@@ -3136,9 +3139,9 @@ dependencies = [
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{ name = "pydantic" },
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{ name = "xxhash" },
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sdist = { url = "https://files.pythonhosted.org/packages/58/61/d5d25e783035aa307d289b37e082258a6061c0fb4caa4a284f3bf1e87169/langgraph-1.2.0.tar.gz", hash = "sha256:4a9baaf62afc5d5f63144a50095140a34b9aa9b7cea695d25326d564775348e7", size = 690248, upload-time = "2026-05-12T03:46:39.164Z" }
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wheels = [
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{ url = "https://files.pythonhosted.org/packages/f6/e8/e3304ac0015c2bdb04ad9785e4ed65c788855ce7857ce6104dd2f5d322db/langgraph-1.2.0-py3-none-any.whl", hash = "sha256:03fd5895a8d4b70db1ff63ebc3bacead29dd20cd794a8b1a483e7ec9018f7a65", size = 234262, upload-time = "2026-05-12T03:46:37.971Z" },
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{ url = "https://files.pythonhosted.org/packages/42/9b/b08d578bba73e25351152dfd3d6d21e81210a5fff1b6f26e56f33197c8f5/langgraph-1.2.2-py3-none-any.whl", hash = "sha256:0a851bf4ba5939c5474a2fd57e6b439b5315283e254e42943bd392c2d71a5e03", size = 236376, upload-time = "2026-05-26T18:07:26.577Z" },
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[[package]]
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||||
|
||||
@@ -6,11 +6,17 @@ version coerces `BaseMessageChunk` writes to full messages for parity with
|
||||
`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.
|
||||
|
||||
ID assignment is intentionally absent here. LangGraph's `ensure_message_ids`
|
||||
stamps stable UUIDs onto all `BaseMessage` writes before they are serialised
|
||||
to the checkpoint, so by the time the reducer sees a message it already has a
|
||||
stable ID. Assigning IDs in the reducer would be both redundant and fragile
|
||||
(a reducer runs on replay too, where a randomly-assigned ID would differ from
|
||||
the one stored in the checkpoint).
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import uuid
|
||||
from typing import Any, cast
|
||||
|
||||
from langchain_core.messages import (
|
||||
@@ -28,8 +34,8 @@ def _messages_delta_reducer( # noqa: C901, PLR0912
|
||||
"""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 assigned a UUID before
|
||||
being appended, matching the behaviour of `add_messages`.
|
||||
`REMOVE_ALL_MESSAGES`. IDs are expected to be pre-assigned by LangGraph's
|
||||
`ensure_message_ids` hook; id=None messages are appended as-is.
|
||||
|
||||
Raw dict / string / tuple inputs are coerced to typed `BaseMessage` so
|
||||
HTTP-driven graphs work without a separate coercion step.
|
||||
@@ -62,16 +68,12 @@ def _messages_delta_reducer( # noqa: C901, PLR0912
|
||||
result: list[AnyMessage | None] = []
|
||||
index: dict[str, int] = {}
|
||||
for m in state_msgs:
|
||||
if m.id is None:
|
||||
m.id = str(uuid.uuid4())
|
||||
index[m.id] = len(result)
|
||||
if m.id is not None:
|
||||
index[m.id] = len(result)
|
||||
result.append(m)
|
||||
for msg in msgs:
|
||||
mid = msg.id
|
||||
if mid is None:
|
||||
msg.id = str(uuid.uuid4())
|
||||
mid = msg.id
|
||||
index[mid] = len(result)
|
||||
result.append(msg)
|
||||
elif isinstance(msg, RemoveMessage):
|
||||
if mid in index:
|
||||
|
||||
@@ -70,7 +70,7 @@ from langchain_core.exceptions import ContextOverflowError
|
||||
from langchain_core.messages import AIMessage, AnyMessage, HumanMessage, SystemMessage, ToolMessage, get_buffer_string
|
||||
from langchain_core.messages.utils import count_tokens_approximately
|
||||
from langgraph.config import get_config
|
||||
from langgraph.types import Command, Overwrite
|
||||
from langgraph.types import Command
|
||||
from pydantic import BaseModel
|
||||
from typing_extensions import TypedDict
|
||||
|
||||
@@ -1016,15 +1016,9 @@ A condensed summary follows:
|
||||
modified_messages = [*new_messages, *preserved_messages]
|
||||
response = handler(request.override(messages=modified_messages))
|
||||
|
||||
# Persist the clipped tail into state via Overwrite. Match the
|
||||
# pattern from filesystem.py: atomically replace the messages channel
|
||||
# so the clipped TMs survive DeltaChannel replay (append + reducer
|
||||
# id-matching is broken until langchain-core auto-assigns ids upstream).
|
||||
update: dict[str, Any] = {"_summarization_event": new_event}
|
||||
if new_state_tail:
|
||||
state_messages = list(request.state.get("messages", []))
|
||||
new_state_messages = [*state_messages[: len(state_messages) - len(new_state_tail)], *new_state_tail]
|
||||
update["messages"] = Overwrite(new_state_messages)
|
||||
update["messages"] = list(new_state_tail)
|
||||
|
||||
# Return ExtendedModelResponse with state update
|
||||
return ExtendedModelResponse(
|
||||
@@ -1143,15 +1137,9 @@ A condensed summary follows:
|
||||
modified_messages = [*new_messages, *preserved_messages]
|
||||
response = await handler(request.override(messages=modified_messages))
|
||||
|
||||
# Persist the clipped tail into state via Overwrite. Match the
|
||||
# pattern from filesystem.py: atomically replace the messages channel
|
||||
# so the clipped TMs survive DeltaChannel replay (append + reducer
|
||||
# id-matching is broken until langchain-core auto-assigns ids upstream).
|
||||
update: dict[str, Any] = {"_summarization_event": new_event}
|
||||
if new_state_tail:
|
||||
state_messages = list(request.state.get("messages", []))
|
||||
new_state_messages = [*state_messages[: len(state_messages) - len(new_state_tail)], *new_state_tail]
|
||||
update["messages"] = Overwrite(new_state_messages)
|
||||
update["messages"] = list(new_state_tail)
|
||||
|
||||
# Return ExtendedModelResponse with state update
|
||||
return ExtendedModelResponse(
|
||||
|
||||
@@ -22,7 +22,7 @@ classifiers = [
|
||||
dependencies = [
|
||||
"langchain-core>=1.4.0,<2.0.0",
|
||||
"langsmith>=0.8.3",
|
||||
"langchain>=1.3.0,<2.0.0",
|
||||
"langchain>=1.3.2,<2.0.0",
|
||||
"langchain-anthropic>=1.4.3,<2.0.0",
|
||||
"langchain-google-genai>=4.2.2,<5.0.0",
|
||||
"wcmatch",
|
||||
|
||||
@@ -47,7 +47,7 @@ For longer tasks, provide brief progress updates at reasonable intervals — a c
|
||||
## `write_todos`
|
||||
|
||||
You have access to the `write_todos` tool to help you manage and plan complex objectives.
|
||||
Use this tool for complex objectives to ensure that you are tracking each necessary step and giving the user visibility into your progress.
|
||||
Use this tool for complex objectives to ensure that you are tracking each necessary step.
|
||||
This tool is very helpful for planning complex objectives, and for breaking down these larger complex objectives into smaller steps.
|
||||
|
||||
It is critical that you mark todos as completed as soon as you are done with a step. Do not batch up multiple steps before marking them as completed.
|
||||
@@ -55,9 +55,14 @@ For simple objectives that only require a few steps, it is better to just comple
|
||||
Writing todos takes time and tokens, use it when it is helpful for managing complex many-step problems! But not for simple few-step requests.
|
||||
|
||||
## Important To-Do List Usage Notes to Remember
|
||||
|
||||
- The `write_todos` tool should never be called multiple times in parallel.
|
||||
- Don't be afraid to revise the To-Do list as you go. New information may reveal new tasks that need to be done, or old tasks that are irrelevant.
|
||||
|
||||
## Finishing a task
|
||||
|
||||
When you finish all work, write your final answer in the message AFTER your last `write_todos` call — not in the same turn as that call. Start the final message with the substantive content the user asked for — the data, computation, summary, or analysis. The user wants the result, not confirmation that the work is done.
|
||||
|
||||
## Following Conventions
|
||||
|
||||
- Read files before editing — understand existing content before making changes
|
||||
|
||||
+1
-1
@@ -1,7 +1,7 @@
|
||||
[
|
||||
{
|
||||
"function": {
|
||||
"description": "Use this tool to create and manage a structured task list for your current work session. This helps you track progress, organize complex tasks, and demonstrate thoroughness to the user.\n\nOnly use this tool if you think it will be helpful in staying organized. If the user's request is trivial and takes less than 3 steps, it is better to NOT use this tool and just do the task directly.\n\n## When to Use This Tool\nUse this tool in these scenarios:\n\n1. Complex multi-step tasks - When a task requires 3 or more distinct steps or actions\n2. Non-trivial and complex tasks - Tasks that require careful planning or multiple operations\n3. User explicitly requests todo list - When the user directly asks you to use the todo list\n4. User provides multiple tasks - When users provide a list of things to be done (numbered or comma-separated)\n5. The plan may need future revisions or updates based on results from the first few steps\n\n## How to Use This Tool\n1. When you start working on a task - Mark it as in_progress BEFORE beginning work.\n2. After completing a task - Mark it as completed and add any new follow-up tasks discovered during implementation.\n3. You can also update future tasks, such as deleting them if they are no longer necessary, or adding new tasks that are necessary. Don't change previously completed tasks.\n4. You can make several updates to the todo list at once. For example, when you complete a task, you can mark the next task you need to start as in_progress.\n\n## When NOT to Use This Tool\nIt is important to skip using this tool when:\n1. There is only a single, straightforward task\n2. The task is trivial and tracking it provides no benefit\n3. The task can be completed in less than 3 trivial steps\n4. The task is purely conversational or informational\n\n## Task States and Management\n\n1. **Task States**: Use these states to track progress:\n - pending: Task not yet started\n - in_progress: Currently working on (you can have multiple tasks in_progress at a time if they are not related to each other and can be run in parallel)\n - completed: Task finished successfully\n\n2. **Task Management**:\n - Update task status in real-time as you work\n - Mark tasks complete IMMEDIATELY after finishing (don't batch completions)\n - Complete current tasks before starting new ones\n - Remove tasks that are no longer relevant from the list entirely\n - IMPORTANT: When you write this todo list, you should mark your first task (or tasks) as in_progress immediately!.\n - IMPORTANT: Unless all tasks are completed, you should always have at least one task in_progress to show the user that you are working on something.\n\n3. **Task Completion Requirements**:\n - ONLY mark a task as completed when you have FULLY accomplished it\n - If you encounter errors, blockers, or cannot finish, keep the task as in_progress\n - When blocked, create a new task describing what needs to be resolved\n - Never mark a task as completed if:\n - There are unresolved issues or errors\n - Work is partial or incomplete\n - You encountered blockers that prevent completion\n - You couldn't find necessary resources or dependencies\n - Quality standards haven't been met\n\n4. **Task Breakdown**:\n - Create specific, actionable items\n - Break complex tasks into smaller, manageable steps\n - Use clear, descriptive task names\n\nBeing proactive with task management demonstrates attentiveness and ensures you complete all requirements successfully\nRemember: If you only need to make a few tool calls to complete a task, and it is clear what you need to do, it is better to just do the task directly and NOT call this tool at all.",
|
||||
"description": "Use this tool to create and manage a structured task list for your current work session. This helps you track progress and organize complex tasks.\n\nOnly use this tool if you think it will be helpful in staying organized. If the user's request is trivial and takes less than 3 steps, it is better to NOT use this tool and just do the task directly.\n\n## When to Use This Tool\n\nUse this tool in these scenarios:\n\n1. Complex multi-step tasks - When a task requires 3 or more distinct steps or actions\n2. Non-trivial and complex tasks - Tasks that require careful planning or multiple operations\n3. User explicitly requests todo list - When the user directly asks you to use the todo list\n4. User provides multiple tasks - When users provide a list of things to be done (numbered or comma-separated)\n5. The plan may need future revisions or updates based on results from the first few steps\n\n## How to Use This Tool\n\n1. When you start working on a task - Mark it as in_progress BEFORE beginning work.\n2. After completing a task - Mark it as completed and add any new follow-up tasks discovered during implementation.\n3. You can also update future tasks, such as deleting them if they are no longer necessary, or adding new tasks that are necessary. Don't change previously completed tasks.\n4. You can make several updates to the todo list at once. For example, when you complete a task, you can mark the next task you need to start as in_progress.\n\n## When NOT to Use This Tool\n\nIt is important to skip using this tool when:\n1. There is only a single, straightforward task\n2. The task is trivial and tracking it provides no benefit\n3. The task can be completed in less than 3 trivial steps\n4. The task is purely conversational or informational\n\n## Task States and Management\n\n1. **Task States**: Use these states to track progress:\n - pending: Task not yet started\n - in_progress: Currently working on (you can have multiple tasks in_progress at a time if they are not related to each other and can be run in parallel)\n - completed: Task finished successfully\n\n2. **Task Management**:\n - Update task status in real-time as you work\n - Mark tasks complete IMMEDIATELY after finishing (don't batch completions)\n - Complete current tasks before starting new ones\n - Remove tasks that are no longer relevant from the list entirely\n - IMPORTANT: When you write this todo list, you should mark your first task (or tasks) as in_progress immediately!.\n - IMPORTANT: Unless all tasks are completed, you should always have at least one task in_progress.\n\n3. **Task Completion Requirements**:\n - ONLY mark a task as completed when you have FULLY accomplished it\n - If you encounter errors, blockers, or cannot finish, keep the task as in_progress\n - When blocked, create a new task describing what needs to be resolved\n - Never mark a task as completed if:\n - There are unresolved issues or errors\n - Work is partial or incomplete\n - You encountered blockers that prevent completion\n - You couldn't find necessary resources or dependencies\n - Quality standards haven't been met\n\n4. **Task Breakdown**:\n - Create specific, actionable items\n - Break complex tasks into smaller, manageable steps\n - Use clear, descriptive task names\n\nBeing proactive with task management ensures you complete all requirements successfully\nRemember: If you only need to make a few tool calls to complete a task, and it is clear what you need to do, it is better to just do the task directly and NOT call this tool at all.\n\n## When You Finish\n\n`write_todos` tracks your work; it does not deliver the answer. Whatever the user asked for \u2014 computations, summaries, comparisons, data \u2014 must appear as text content in a message after your final `write_todos` call. Marking the last todo complete is not itself an answer to the user.",
|
||||
"name": "write_todos",
|
||||
"parameters": {
|
||||
"properties": {
|
||||
|
||||
+6
-1
@@ -45,7 +45,7 @@ For longer tasks, provide brief progress updates at reasonable intervals — a c
|
||||
## `write_todos`
|
||||
|
||||
You have access to the `write_todos` tool to help you manage and plan complex objectives.
|
||||
Use this tool for complex objectives to ensure that you are tracking each necessary step and giving the user visibility into your progress.
|
||||
Use this tool for complex objectives to ensure that you are tracking each necessary step.
|
||||
This tool is very helpful for planning complex objectives, and for breaking down these larger complex objectives into smaller steps.
|
||||
|
||||
It is critical that you mark todos as completed as soon as you are done with a step. Do not batch up multiple steps before marking them as completed.
|
||||
@@ -53,9 +53,14 @@ For simple objectives that only require a few steps, it is better to just comple
|
||||
Writing todos takes time and tokens, use it when it is helpful for managing complex many-step problems! But not for simple few-step requests.
|
||||
|
||||
## Important To-Do List Usage Notes to Remember
|
||||
|
||||
- The `write_todos` tool should never be called multiple times in parallel.
|
||||
- Don't be afraid to revise the To-Do list as you go. New information may reveal new tasks that need to be done, or old tasks that are irrelevant.
|
||||
|
||||
## Finishing a task
|
||||
|
||||
When you finish all work, write your final answer in the message AFTER your last `write_todos` call — not in the same turn as that call. Start the final message with the substantive content the user asked for — the data, computation, summary, or analysis. The user wants the result, not confirmation that the work is done.
|
||||
|
||||
## Following Conventions
|
||||
|
||||
- Read files before editing — understand existing content before making changes
|
||||
|
||||
+1
-1
@@ -1,7 +1,7 @@
|
||||
[
|
||||
{
|
||||
"function": {
|
||||
"description": "Use this tool to create and manage a structured task list for your current work session. This helps you track progress, organize complex tasks, and demonstrate thoroughness to the user.\n\nOnly use this tool if you think it will be helpful in staying organized. If the user's request is trivial and takes less than 3 steps, it is better to NOT use this tool and just do the task directly.\n\n## When to Use This Tool\nUse this tool in these scenarios:\n\n1. Complex multi-step tasks - When a task requires 3 or more distinct steps or actions\n2. Non-trivial and complex tasks - Tasks that require careful planning or multiple operations\n3. User explicitly requests todo list - When the user directly asks you to use the todo list\n4. User provides multiple tasks - When users provide a list of things to be done (numbered or comma-separated)\n5. The plan may need future revisions or updates based on results from the first few steps\n\n## How to Use This Tool\n1. When you start working on a task - Mark it as in_progress BEFORE beginning work.\n2. After completing a task - Mark it as completed and add any new follow-up tasks discovered during implementation.\n3. You can also update future tasks, such as deleting them if they are no longer necessary, or adding new tasks that are necessary. Don't change previously completed tasks.\n4. You can make several updates to the todo list at once. For example, when you complete a task, you can mark the next task you need to start as in_progress.\n\n## When NOT to Use This Tool\nIt is important to skip using this tool when:\n1. There is only a single, straightforward task\n2. The task is trivial and tracking it provides no benefit\n3. The task can be completed in less than 3 trivial steps\n4. The task is purely conversational or informational\n\n## Task States and Management\n\n1. **Task States**: Use these states to track progress:\n - pending: Task not yet started\n - in_progress: Currently working on (you can have multiple tasks in_progress at a time if they are not related to each other and can be run in parallel)\n - completed: Task finished successfully\n\n2. **Task Management**:\n - Update task status in real-time as you work\n - Mark tasks complete IMMEDIATELY after finishing (don't batch completions)\n - Complete current tasks before starting new ones\n - Remove tasks that are no longer relevant from the list entirely\n - IMPORTANT: When you write this todo list, you should mark your first task (or tasks) as in_progress immediately!.\n - IMPORTANT: Unless all tasks are completed, you should always have at least one task in_progress to show the user that you are working on something.\n\n3. **Task Completion Requirements**:\n - ONLY mark a task as completed when you have FULLY accomplished it\n - If you encounter errors, blockers, or cannot finish, keep the task as in_progress\n - When blocked, create a new task describing what needs to be resolved\n - Never mark a task as completed if:\n - There are unresolved issues or errors\n - Work is partial or incomplete\n - You encountered blockers that prevent completion\n - You couldn't find necessary resources or dependencies\n - Quality standards haven't been met\n\n4. **Task Breakdown**:\n - Create specific, actionable items\n - Break complex tasks into smaller, manageable steps\n - Use clear, descriptive task names\n\nBeing proactive with task management demonstrates attentiveness and ensures you complete all requirements successfully\nRemember: If you only need to make a few tool calls to complete a task, and it is clear what you need to do, it is better to just do the task directly and NOT call this tool at all.",
|
||||
"description": "Use this tool to create and manage a structured task list for your current work session. This helps you track progress and organize complex tasks.\n\nOnly use this tool if you think it will be helpful in staying organized. If the user's request is trivial and takes less than 3 steps, it is better to NOT use this tool and just do the task directly.\n\n## When to Use This Tool\n\nUse this tool in these scenarios:\n\n1. Complex multi-step tasks - When a task requires 3 or more distinct steps or actions\n2. Non-trivial and complex tasks - Tasks that require careful planning or multiple operations\n3. User explicitly requests todo list - When the user directly asks you to use the todo list\n4. User provides multiple tasks - When users provide a list of things to be done (numbered or comma-separated)\n5. The plan may need future revisions or updates based on results from the first few steps\n\n## How to Use This Tool\n\n1. When you start working on a task - Mark it as in_progress BEFORE beginning work.\n2. After completing a task - Mark it as completed and add any new follow-up tasks discovered during implementation.\n3. You can also update future tasks, such as deleting them if they are no longer necessary, or adding new tasks that are necessary. Don't change previously completed tasks.\n4. You can make several updates to the todo list at once. For example, when you complete a task, you can mark the next task you need to start as in_progress.\n\n## When NOT to Use This Tool\n\nIt is important to skip using this tool when:\n1. There is only a single, straightforward task\n2. The task is trivial and tracking it provides no benefit\n3. The task can be completed in less than 3 trivial steps\n4. The task is purely conversational or informational\n\n## Task States and Management\n\n1. **Task States**: Use these states to track progress:\n - pending: Task not yet started\n - in_progress: Currently working on (you can have multiple tasks in_progress at a time if they are not related to each other and can be run in parallel)\n - completed: Task finished successfully\n\n2. **Task Management**:\n - Update task status in real-time as you work\n - Mark tasks complete IMMEDIATELY after finishing (don't batch completions)\n - Complete current tasks before starting new ones\n - Remove tasks that are no longer relevant from the list entirely\n - IMPORTANT: When you write this todo list, you should mark your first task (or tasks) as in_progress immediately!.\n - IMPORTANT: Unless all tasks are completed, you should always have at least one task in_progress.\n\n3. **Task Completion Requirements**:\n - ONLY mark a task as completed when you have FULLY accomplished it\n - If you encounter errors, blockers, or cannot finish, keep the task as in_progress\n - When blocked, create a new task describing what needs to be resolved\n - Never mark a task as completed if:\n - There are unresolved issues or errors\n - Work is partial or incomplete\n - You encountered blockers that prevent completion\n - You couldn't find necessary resources or dependencies\n - Quality standards haven't been met\n\n4. **Task Breakdown**:\n - Create specific, actionable items\n - Break complex tasks into smaller, manageable steps\n - Use clear, descriptive task names\n\nBeing proactive with task management ensures you complete all requirements successfully\nRemember: If you only need to make a few tool calls to complete a task, and it is clear what you need to do, it is better to just do the task directly and NOT call this tool at all.\n\n## When You Finish\n\n`write_todos` tracks your work; it does not deliver the answer. Whatever the user asked for \u2014 computations, summaries, comparisons, data \u2014 must appear as text content in a message after your final `write_todos` call. Marking the last todo complete is not itself an answer to the user.",
|
||||
"name": "write_todos",
|
||||
"parameters": {
|
||||
"properties": {
|
||||
|
||||
+6
-1
@@ -45,7 +45,7 @@ For longer tasks, provide brief progress updates at reasonable intervals — a c
|
||||
## `write_todos`
|
||||
|
||||
You have access to the `write_todos` tool to help you manage and plan complex objectives.
|
||||
Use this tool for complex objectives to ensure that you are tracking each necessary step and giving the user visibility into your progress.
|
||||
Use this tool for complex objectives to ensure that you are tracking each necessary step.
|
||||
This tool is very helpful for planning complex objectives, and for breaking down these larger complex objectives into smaller steps.
|
||||
|
||||
It is critical that you mark todos as completed as soon as you are done with a step. Do not batch up multiple steps before marking them as completed.
|
||||
@@ -53,9 +53,14 @@ For simple objectives that only require a few steps, it is better to just comple
|
||||
Writing todos takes time and tokens, use it when it is helpful for managing complex many-step problems! But not for simple few-step requests.
|
||||
|
||||
## Important To-Do List Usage Notes to Remember
|
||||
|
||||
- The `write_todos` tool should never be called multiple times in parallel.
|
||||
- Don't be afraid to revise the To-Do list as you go. New information may reveal new tasks that need to be done, or old tasks that are irrelevant.
|
||||
|
||||
## Finishing a task
|
||||
|
||||
When you finish all work, write your final answer in the message AFTER your last `write_todos` call — not in the same turn as that call. Start the final message with the substantive content the user asked for — the data, computation, summary, or analysis. The user wants the result, not confirmation that the work is done.
|
||||
|
||||
## Skills System
|
||||
|
||||
You have access to a skills library that provides specialized capabilities and domain knowledge.
|
||||
|
||||
+1
-1
@@ -1,7 +1,7 @@
|
||||
[
|
||||
{
|
||||
"function": {
|
||||
"description": "Use this tool to create and manage a structured task list for your current work session. This helps you track progress, organize complex tasks, and demonstrate thoroughness to the user.\n\nOnly use this tool if you think it will be helpful in staying organized. If the user's request is trivial and takes less than 3 steps, it is better to NOT use this tool and just do the task directly.\n\n## When to Use This Tool\nUse this tool in these scenarios:\n\n1. Complex multi-step tasks - When a task requires 3 or more distinct steps or actions\n2. Non-trivial and complex tasks - Tasks that require careful planning or multiple operations\n3. User explicitly requests todo list - When the user directly asks you to use the todo list\n4. User provides multiple tasks - When users provide a list of things to be done (numbered or comma-separated)\n5. The plan may need future revisions or updates based on results from the first few steps\n\n## How to Use This Tool\n1. When you start working on a task - Mark it as in_progress BEFORE beginning work.\n2. After completing a task - Mark it as completed and add any new follow-up tasks discovered during implementation.\n3. You can also update future tasks, such as deleting them if they are no longer necessary, or adding new tasks that are necessary. Don't change previously completed tasks.\n4. You can make several updates to the todo list at once. For example, when you complete a task, you can mark the next task you need to start as in_progress.\n\n## When NOT to Use This Tool\nIt is important to skip using this tool when:\n1. There is only a single, straightforward task\n2. The task is trivial and tracking it provides no benefit\n3. The task can be completed in less than 3 trivial steps\n4. The task is purely conversational or informational\n\n## Task States and Management\n\n1. **Task States**: Use these states to track progress:\n - pending: Task not yet started\n - in_progress: Currently working on (you can have multiple tasks in_progress at a time if they are not related to each other and can be run in parallel)\n - completed: Task finished successfully\n\n2. **Task Management**:\n - Update task status in real-time as you work\n - Mark tasks complete IMMEDIATELY after finishing (don't batch completions)\n - Complete current tasks before starting new ones\n - Remove tasks that are no longer relevant from the list entirely\n - IMPORTANT: When you write this todo list, you should mark your first task (or tasks) as in_progress immediately!.\n - IMPORTANT: Unless all tasks are completed, you should always have at least one task in_progress to show the user that you are working on something.\n\n3. **Task Completion Requirements**:\n - ONLY mark a task as completed when you have FULLY accomplished it\n - If you encounter errors, blockers, or cannot finish, keep the task as in_progress\n - When blocked, create a new task describing what needs to be resolved\n - Never mark a task as completed if:\n - There are unresolved issues or errors\n - Work is partial or incomplete\n - You encountered blockers that prevent completion\n - You couldn't find necessary resources or dependencies\n - Quality standards haven't been met\n\n4. **Task Breakdown**:\n - Create specific, actionable items\n - Break complex tasks into smaller, manageable steps\n - Use clear, descriptive task names\n\nBeing proactive with task management demonstrates attentiveness and ensures you complete all requirements successfully\nRemember: If you only need to make a few tool calls to complete a task, and it is clear what you need to do, it is better to just do the task directly and NOT call this tool at all.",
|
||||
"description": "Use this tool to create and manage a structured task list for your current work session. This helps you track progress and organize complex tasks.\n\nOnly use this tool if you think it will be helpful in staying organized. If the user's request is trivial and takes less than 3 steps, it is better to NOT use this tool and just do the task directly.\n\n## When to Use This Tool\n\nUse this tool in these scenarios:\n\n1. Complex multi-step tasks - When a task requires 3 or more distinct steps or actions\n2. Non-trivial and complex tasks - Tasks that require careful planning or multiple operations\n3. User explicitly requests todo list - When the user directly asks you to use the todo list\n4. User provides multiple tasks - When users provide a list of things to be done (numbered or comma-separated)\n5. The plan may need future revisions or updates based on results from the first few steps\n\n## How to Use This Tool\n\n1. When you start working on a task - Mark it as in_progress BEFORE beginning work.\n2. After completing a task - Mark it as completed and add any new follow-up tasks discovered during implementation.\n3. You can also update future tasks, such as deleting them if they are no longer necessary, or adding new tasks that are necessary. Don't change previously completed tasks.\n4. You can make several updates to the todo list at once. For example, when you complete a task, you can mark the next task you need to start as in_progress.\n\n## When NOT to Use This Tool\n\nIt is important to skip using this tool when:\n1. There is only a single, straightforward task\n2. The task is trivial and tracking it provides no benefit\n3. The task can be completed in less than 3 trivial steps\n4. The task is purely conversational or informational\n\n## Task States and Management\n\n1. **Task States**: Use these states to track progress:\n - pending: Task not yet started\n - in_progress: Currently working on (you can have multiple tasks in_progress at a time if they are not related to each other and can be run in parallel)\n - completed: Task finished successfully\n\n2. **Task Management**:\n - Update task status in real-time as you work\n - Mark tasks complete IMMEDIATELY after finishing (don't batch completions)\n - Complete current tasks before starting new ones\n - Remove tasks that are no longer relevant from the list entirely\n - IMPORTANT: When you write this todo list, you should mark your first task (or tasks) as in_progress immediately!.\n - IMPORTANT: Unless all tasks are completed, you should always have at least one task in_progress.\n\n3. **Task Completion Requirements**:\n - ONLY mark a task as completed when you have FULLY accomplished it\n - If you encounter errors, blockers, or cannot finish, keep the task as in_progress\n - When blocked, create a new task describing what needs to be resolved\n - Never mark a task as completed if:\n - There are unresolved issues or errors\n - Work is partial or incomplete\n - You encountered blockers that prevent completion\n - You couldn't find necessary resources or dependencies\n - Quality standards haven't been met\n\n4. **Task Breakdown**:\n - Create specific, actionable items\n - Break complex tasks into smaller, manageable steps\n - Use clear, descriptive task names\n\nBeing proactive with task management ensures you complete all requirements successfully\nRemember: If you only need to make a few tool calls to complete a task, and it is clear what you need to do, it is better to just do the task directly and NOT call this tool at all.\n\n## When You Finish\n\n`write_todos` tracks your work; it does not deliver the answer. Whatever the user asked for \u2014 computations, summaries, comparisons, data \u2014 must appear as text content in a message after your final `write_todos` call. Marking the last todo complete is not itself an answer to the user.",
|
||||
"name": "write_todos",
|
||||
"parameters": {
|
||||
"properties": {
|
||||
|
||||
+6
-1
@@ -45,7 +45,7 @@ For longer tasks, provide brief progress updates at reasonable intervals — a c
|
||||
## `write_todos`
|
||||
|
||||
You have access to the `write_todos` tool to help you manage and plan complex objectives.
|
||||
Use this tool for complex objectives to ensure that you are tracking each necessary step and giving the user visibility into your progress.
|
||||
Use this tool for complex objectives to ensure that you are tracking each necessary step.
|
||||
This tool is very helpful for planning complex objectives, and for breaking down these larger complex objectives into smaller steps.
|
||||
|
||||
It is critical that you mark todos as completed as soon as you are done with a step. Do not batch up multiple steps before marking them as completed.
|
||||
@@ -53,9 +53,14 @@ For simple objectives that only require a few steps, it is better to just comple
|
||||
Writing todos takes time and tokens, use it when it is helpful for managing complex many-step problems! But not for simple few-step requests.
|
||||
|
||||
## Important To-Do List Usage Notes to Remember
|
||||
|
||||
- The `write_todos` tool should never be called multiple times in parallel.
|
||||
- Don't be afraid to revise the To-Do list as you go. New information may reveal new tasks that need to be done, or old tasks that are irrelevant.
|
||||
|
||||
## Finishing a task
|
||||
|
||||
When you finish all work, write your final answer in the message AFTER your last `write_todos` call — not in the same turn as that call. Start the final message with the substantive content the user asked for — the data, computation, summary, or analysis. The user wants the result, not confirmation that the work is done.
|
||||
|
||||
## Following Conventions
|
||||
|
||||
- Read files before editing — understand existing content before making changes
|
||||
|
||||
+1
-1
@@ -1,7 +1,7 @@
|
||||
[
|
||||
{
|
||||
"function": {
|
||||
"description": "Use this tool to create and manage a structured task list for your current work session. This helps you track progress, organize complex tasks, and demonstrate thoroughness to the user.\n\nOnly use this tool if you think it will be helpful in staying organized. If the user's request is trivial and takes less than 3 steps, it is better to NOT use this tool and just do the task directly.\n\n## When to Use This Tool\nUse this tool in these scenarios:\n\n1. Complex multi-step tasks - When a task requires 3 or more distinct steps or actions\n2. Non-trivial and complex tasks - Tasks that require careful planning or multiple operations\n3. User explicitly requests todo list - When the user directly asks you to use the todo list\n4. User provides multiple tasks - When users provide a list of things to be done (numbered or comma-separated)\n5. The plan may need future revisions or updates based on results from the first few steps\n\n## How to Use This Tool\n1. When you start working on a task - Mark it as in_progress BEFORE beginning work.\n2. After completing a task - Mark it as completed and add any new follow-up tasks discovered during implementation.\n3. You can also update future tasks, such as deleting them if they are no longer necessary, or adding new tasks that are necessary. Don't change previously completed tasks.\n4. You can make several updates to the todo list at once. For example, when you complete a task, you can mark the next task you need to start as in_progress.\n\n## When NOT to Use This Tool\nIt is important to skip using this tool when:\n1. There is only a single, straightforward task\n2. The task is trivial and tracking it provides no benefit\n3. The task can be completed in less than 3 trivial steps\n4. The task is purely conversational or informational\n\n## Task States and Management\n\n1. **Task States**: Use these states to track progress:\n - pending: Task not yet started\n - in_progress: Currently working on (you can have multiple tasks in_progress at a time if they are not related to each other and can be run in parallel)\n - completed: Task finished successfully\n\n2. **Task Management**:\n - Update task status in real-time as you work\n - Mark tasks complete IMMEDIATELY after finishing (don't batch completions)\n - Complete current tasks before starting new ones\n - Remove tasks that are no longer relevant from the list entirely\n - IMPORTANT: When you write this todo list, you should mark your first task (or tasks) as in_progress immediately!.\n - IMPORTANT: Unless all tasks are completed, you should always have at least one task in_progress to show the user that you are working on something.\n\n3. **Task Completion Requirements**:\n - ONLY mark a task as completed when you have FULLY accomplished it\n - If you encounter errors, blockers, or cannot finish, keep the task as in_progress\n - When blocked, create a new task describing what needs to be resolved\n - Never mark a task as completed if:\n - There are unresolved issues or errors\n - Work is partial or incomplete\n - You encountered blockers that prevent completion\n - You couldn't find necessary resources or dependencies\n - Quality standards haven't been met\n\n4. **Task Breakdown**:\n - Create specific, actionable items\n - Break complex tasks into smaller, manageable steps\n - Use clear, descriptive task names\n\nBeing proactive with task management demonstrates attentiveness and ensures you complete all requirements successfully\nRemember: If you only need to make a few tool calls to complete a task, and it is clear what you need to do, it is better to just do the task directly and NOT call this tool at all.",
|
||||
"description": "Use this tool to create and manage a structured task list for your current work session. This helps you track progress and organize complex tasks.\n\nOnly use this tool if you think it will be helpful in staying organized. If the user's request is trivial and takes less than 3 steps, it is better to NOT use this tool and just do the task directly.\n\n## When to Use This Tool\n\nUse this tool in these scenarios:\n\n1. Complex multi-step tasks - When a task requires 3 or more distinct steps or actions\n2. Non-trivial and complex tasks - Tasks that require careful planning or multiple operations\n3. User explicitly requests todo list - When the user directly asks you to use the todo list\n4. User provides multiple tasks - When users provide a list of things to be done (numbered or comma-separated)\n5. The plan may need future revisions or updates based on results from the first few steps\n\n## How to Use This Tool\n\n1. When you start working on a task - Mark it as in_progress BEFORE beginning work.\n2. After completing a task - Mark it as completed and add any new follow-up tasks discovered during implementation.\n3. You can also update future tasks, such as deleting them if they are no longer necessary, or adding new tasks that are necessary. Don't change previously completed tasks.\n4. You can make several updates to the todo list at once. For example, when you complete a task, you can mark the next task you need to start as in_progress.\n\n## When NOT to Use This Tool\n\nIt is important to skip using this tool when:\n1. There is only a single, straightforward task\n2. The task is trivial and tracking it provides no benefit\n3. The task can be completed in less than 3 trivial steps\n4. The task is purely conversational or informational\n\n## Task States and Management\n\n1. **Task States**: Use these states to track progress:\n - pending: Task not yet started\n - in_progress: Currently working on (you can have multiple tasks in_progress at a time if they are not related to each other and can be run in parallel)\n - completed: Task finished successfully\n\n2. **Task Management**:\n - Update task status in real-time as you work\n - Mark tasks complete IMMEDIATELY after finishing (don't batch completions)\n - Complete current tasks before starting new ones\n - Remove tasks that are no longer relevant from the list entirely\n - IMPORTANT: When you write this todo list, you should mark your first task (or tasks) as in_progress immediately!.\n - IMPORTANT: Unless all tasks are completed, you should always have at least one task in_progress.\n\n3. **Task Completion Requirements**:\n - ONLY mark a task as completed when you have FULLY accomplished it\n - If you encounter errors, blockers, or cannot finish, keep the task as in_progress\n - When blocked, create a new task describing what needs to be resolved\n - Never mark a task as completed if:\n - There are unresolved issues or errors\n - Work is partial or incomplete\n - You encountered blockers that prevent completion\n - You couldn't find necessary resources or dependencies\n - Quality standards haven't been met\n\n4. **Task Breakdown**:\n - Create specific, actionable items\n - Break complex tasks into smaller, manageable steps\n - Use clear, descriptive task names\n\nBeing proactive with task management ensures you complete all requirements successfully\nRemember: If you only need to make a few tool calls to complete a task, and it is clear what you need to do, it is better to just do the task directly and NOT call this tool at all.\n\n## When You Finish\n\n`write_todos` tracks your work; it does not deliver the answer. Whatever the user asked for \u2014 computations, summaries, comparisons, data \u2014 must appear as text content in a message after your final `write_todos` call. Marking the last todo complete is not itself an answer to the user.",
|
||||
"name": "write_todos",
|
||||
"parameters": {
|
||||
"properties": {
|
||||
|
||||
+6
-1
@@ -45,7 +45,7 @@ For longer tasks, provide brief progress updates at reasonable intervals — a c
|
||||
## `write_todos`
|
||||
|
||||
You have access to the `write_todos` tool to help you manage and plan complex objectives.
|
||||
Use this tool for complex objectives to ensure that you are tracking each necessary step and giving the user visibility into your progress.
|
||||
Use this tool for complex objectives to ensure that you are tracking each necessary step.
|
||||
This tool is very helpful for planning complex objectives, and for breaking down these larger complex objectives into smaller steps.
|
||||
|
||||
It is critical that you mark todos as completed as soon as you are done with a step. Do not batch up multiple steps before marking them as completed.
|
||||
@@ -53,9 +53,14 @@ For simple objectives that only require a few steps, it is better to just comple
|
||||
Writing todos takes time and tokens, use it when it is helpful for managing complex many-step problems! But not for simple few-step requests.
|
||||
|
||||
## Important To-Do List Usage Notes to Remember
|
||||
|
||||
- The `write_todos` tool should never be called multiple times in parallel.
|
||||
- Don't be afraid to revise the To-Do list as you go. New information may reveal new tasks that need to be done, or old tasks that are irrelevant.
|
||||
|
||||
## Finishing a task
|
||||
|
||||
When you finish all work, write your final answer in the message AFTER your last `write_todos` call — not in the same turn as that call. Start the final message with the substantive content the user asked for — the data, computation, summary, or analysis. The user wants the result, not confirmation that the work is done.
|
||||
|
||||
## Following Conventions
|
||||
|
||||
- Read files before editing — understand existing content before making changes
|
||||
|
||||
+1
-1
@@ -1,7 +1,7 @@
|
||||
[
|
||||
{
|
||||
"function": {
|
||||
"description": "Use this tool to create and manage a structured task list for your current work session. This helps you track progress, organize complex tasks, and demonstrate thoroughness to the user.\n\nOnly use this tool if you think it will be helpful in staying organized. If the user's request is trivial and takes less than 3 steps, it is better to NOT use this tool and just do the task directly.\n\n## When to Use This Tool\nUse this tool in these scenarios:\n\n1. Complex multi-step tasks - When a task requires 3 or more distinct steps or actions\n2. Non-trivial and complex tasks - Tasks that require careful planning or multiple operations\n3. User explicitly requests todo list - When the user directly asks you to use the todo list\n4. User provides multiple tasks - When users provide a list of things to be done (numbered or comma-separated)\n5. The plan may need future revisions or updates based on results from the first few steps\n\n## How to Use This Tool\n1. When you start working on a task - Mark it as in_progress BEFORE beginning work.\n2. After completing a task - Mark it as completed and add any new follow-up tasks discovered during implementation.\n3. You can also update future tasks, such as deleting them if they are no longer necessary, or adding new tasks that are necessary. Don't change previously completed tasks.\n4. You can make several updates to the todo list at once. For example, when you complete a task, you can mark the next task you need to start as in_progress.\n\n## When NOT to Use This Tool\nIt is important to skip using this tool when:\n1. There is only a single, straightforward task\n2. The task is trivial and tracking it provides no benefit\n3. The task can be completed in less than 3 trivial steps\n4. The task is purely conversational or informational\n\n## Task States and Management\n\n1. **Task States**: Use these states to track progress:\n - pending: Task not yet started\n - in_progress: Currently working on (you can have multiple tasks in_progress at a time if they are not related to each other and can be run in parallel)\n - completed: Task finished successfully\n\n2. **Task Management**:\n - Update task status in real-time as you work\n - Mark tasks complete IMMEDIATELY after finishing (don't batch completions)\n - Complete current tasks before starting new ones\n - Remove tasks that are no longer relevant from the list entirely\n - IMPORTANT: When you write this todo list, you should mark your first task (or tasks) as in_progress immediately!.\n - IMPORTANT: Unless all tasks are completed, you should always have at least one task in_progress to show the user that you are working on something.\n\n3. **Task Completion Requirements**:\n - ONLY mark a task as completed when you have FULLY accomplished it\n - If you encounter errors, blockers, or cannot finish, keep the task as in_progress\n - When blocked, create a new task describing what needs to be resolved\n - Never mark a task as completed if:\n - There are unresolved issues or errors\n - Work is partial or incomplete\n - You encountered blockers that prevent completion\n - You couldn't find necessary resources or dependencies\n - Quality standards haven't been met\n\n4. **Task Breakdown**:\n - Create specific, actionable items\n - Break complex tasks into smaller, manageable steps\n - Use clear, descriptive task names\n\nBeing proactive with task management demonstrates attentiveness and ensures you complete all requirements successfully\nRemember: If you only need to make a few tool calls to complete a task, and it is clear what you need to do, it is better to just do the task directly and NOT call this tool at all.",
|
||||
"description": "Use this tool to create and manage a structured task list for your current work session. This helps you track progress and organize complex tasks.\n\nOnly use this tool if you think it will be helpful in staying organized. If the user's request is trivial and takes less than 3 steps, it is better to NOT use this tool and just do the task directly.\n\n## When to Use This Tool\n\nUse this tool in these scenarios:\n\n1. Complex multi-step tasks - When a task requires 3 or more distinct steps or actions\n2. Non-trivial and complex tasks - Tasks that require careful planning or multiple operations\n3. User explicitly requests todo list - When the user directly asks you to use the todo list\n4. User provides multiple tasks - When users provide a list of things to be done (numbered or comma-separated)\n5. The plan may need future revisions or updates based on results from the first few steps\n\n## How to Use This Tool\n\n1. When you start working on a task - Mark it as in_progress BEFORE beginning work.\n2. After completing a task - Mark it as completed and add any new follow-up tasks discovered during implementation.\n3. You can also update future tasks, such as deleting them if they are no longer necessary, or adding new tasks that are necessary. Don't change previously completed tasks.\n4. You can make several updates to the todo list at once. For example, when you complete a task, you can mark the next task you need to start as in_progress.\n\n## When NOT to Use This Tool\n\nIt is important to skip using this tool when:\n1. There is only a single, straightforward task\n2. The task is trivial and tracking it provides no benefit\n3. The task can be completed in less than 3 trivial steps\n4. The task is purely conversational or informational\n\n## Task States and Management\n\n1. **Task States**: Use these states to track progress:\n - pending: Task not yet started\n - in_progress: Currently working on (you can have multiple tasks in_progress at a time if they are not related to each other and can be run in parallel)\n - completed: Task finished successfully\n\n2. **Task Management**:\n - Update task status in real-time as you work\n - Mark tasks complete IMMEDIATELY after finishing (don't batch completions)\n - Complete current tasks before starting new ones\n - Remove tasks that are no longer relevant from the list entirely\n - IMPORTANT: When you write this todo list, you should mark your first task (or tasks) as in_progress immediately!.\n - IMPORTANT: Unless all tasks are completed, you should always have at least one task in_progress.\n\n3. **Task Completion Requirements**:\n - ONLY mark a task as completed when you have FULLY accomplished it\n - If you encounter errors, blockers, or cannot finish, keep the task as in_progress\n - When blocked, create a new task describing what needs to be resolved\n - Never mark a task as completed if:\n - There are unresolved issues or errors\n - Work is partial or incomplete\n - You encountered blockers that prevent completion\n - You couldn't find necessary resources or dependencies\n - Quality standards haven't been met\n\n4. **Task Breakdown**:\n - Create specific, actionable items\n - Break complex tasks into smaller, manageable steps\n - Use clear, descriptive task names\n\nBeing proactive with task management ensures you complete all requirements successfully\nRemember: If you only need to make a few tool calls to complete a task, and it is clear what you need to do, it is better to just do the task directly and NOT call this tool at all.\n\n## When You Finish\n\n`write_todos` tracks your work; it does not deliver the answer. Whatever the user asked for \u2014 computations, summaries, comparisons, data \u2014 must appear as text content in a message after your final `write_todos` call. Marking the last todo complete is not itself an answer to the user.",
|
||||
"name": "write_todos",
|
||||
"parameters": {
|
||||
"properties": {
|
||||
|
||||
@@ -1,19 +1,110 @@
|
||||
"""Unit tests for _messages_delta_reducer."""
|
||||
"""Tests for DeltaChannel message ID stability.
|
||||
|
||||
IDs are assigned by LangGraph's ensure_message_ids() before writes are
|
||||
serialised to the checkpoint. These tests verify the end-to-end property:
|
||||
get_state() always returns messages with stable, non-None IDs — both within
|
||||
a single invocation and across resumed threads.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from typing import Annotated
|
||||
|
||||
import pytest
|
||||
from langchain_core.messages import AIMessage, HumanMessage
|
||||
from langgraph.channels.delta import DeltaChannel
|
||||
from langgraph.checkpoint.memory import InMemorySaver
|
||||
from langgraph.graph import END, START, StateGraph
|
||||
from typing_extensions import TypedDict
|
||||
|
||||
from deepagents._messages_reducer import _messages_delta_reducer
|
||||
|
||||
|
||||
def test_idless_message_gets_id_and_order_preserved() -> None:
|
||||
existing = [AIMessage(content="hello", id="existing-1")]
|
||||
new_msg = HumanMessage(content="follow-up") # no id
|
||||
def _build_graph(checkpointer: object) -> object:
|
||||
State = TypedDict( # noqa: UP013
|
||||
"State",
|
||||
{"messages": Annotated[list, DeltaChannel(_messages_delta_reducer, snapshot_frequency=50)]},
|
||||
) # type: ignore[call-overload]
|
||||
|
||||
result = _messages_delta_reducer(existing, [[new_msg]])
|
||||
turn = [0]
|
||||
|
||||
assert len(result) == 2
|
||||
assert result[0].id == "existing-1"
|
||||
assert result[1] is new_msg
|
||||
assert result[1].id is not None
|
||||
def agent(_state: dict) -> dict: # type: ignore[type-arg]
|
||||
turn[0] += 1
|
||||
return {"messages": [AIMessage(content=f"reply-{turn[0]}", id=f"ai-{turn[0]}")]}
|
||||
|
||||
return StateGraph(State).add_node("agent", agent).add_edge(START, "agent").add_edge("agent", END).compile(checkpointer=checkpointer)
|
||||
|
||||
|
||||
def test_get_state_messages_have_ids() -> None:
|
||||
"""Every message returned by get_state() must have a non-None id."""
|
||||
saver = InMemorySaver()
|
||||
graph = _build_graph(saver)
|
||||
config = {"configurable": {"thread_id": "has-ids"}}
|
||||
|
||||
graph.invoke({"messages": [HumanMessage(content="hello")]}, config)
|
||||
|
||||
state = graph.get_state(config)
|
||||
for msg in state.values["messages"]:
|
||||
assert msg.id is not None, f"{type(msg).__name__} has id=None after get_state()"
|
||||
|
||||
|
||||
def test_dict_style_invoke_messages_have_stable_ids() -> None:
|
||||
"""Dict-style input (API / over-the-wire format) must also yield stable IDs.
|
||||
|
||||
When the graph is invoked with {"role": "user", "content": "..."} dicts
|
||||
instead of BaseMessage objects, ensure_message_ids() coerces them before
|
||||
serialisation so the checkpoint never stores id=None.
|
||||
"""
|
||||
saver = InMemorySaver()
|
||||
graph = _build_graph(saver)
|
||||
config = {"configurable": {"thread_id": "dict-style"}}
|
||||
|
||||
graph.invoke({"messages": [{"role": "user", "content": "hello"}]}, config)
|
||||
|
||||
state = graph.get_state(config)
|
||||
human = next(m for m in state.values["messages"] if isinstance(m, HumanMessage))
|
||||
assert human.id is not None, "dict-style HumanMessage should have a stable ID"
|
||||
|
||||
# ID must be stable across repeated get_state() calls
|
||||
ids = [next(m.id for m in graph.get_state(config).values["messages"] if isinstance(m, HumanMessage)) for _ in range(3)]
|
||||
assert len(set(ids)) == 1, f"dict-style HumanMessage id unstable: {ids}"
|
||||
|
||||
|
||||
def test_human_message_id_stable_across_invocations_sync() -> None:
|
||||
"""The same HumanMessage must keep its ID when a thread is resumed."""
|
||||
saver = InMemorySaver()
|
||||
graph = _build_graph(saver)
|
||||
config = {"configurable": {"thread_id": "stability-sync"}}
|
||||
|
||||
graph.invoke({"messages": [HumanMessage(content="write a hello world script")]}, config)
|
||||
id_turn1 = next(m.id for m in graph.get_state(config).values["messages"] if isinstance(m, HumanMessage))
|
||||
|
||||
graph.invoke({"messages": [HumanMessage(content="add error handling")]}, config)
|
||||
id_turn2 = next(
|
||||
m.id for m in graph.get_state(config).values["messages"] if isinstance(m, HumanMessage) and m.content == "write a hello world script"
|
||||
)
|
||||
|
||||
assert id_turn1 is not None
|
||||
assert id_turn1 == id_turn2, (
|
||||
f"HumanMessage ID changed across invocations: turn 1={id_turn1!r}, turn 2={id_turn2!r}. "
|
||||
"Checkpoint is storing id=None — see langchain-ai/langgraph#7913."
|
||||
)
|
||||
|
||||
|
||||
@pytest.mark.anyio
|
||||
async def test_human_message_id_stable_across_invocations_async() -> None:
|
||||
"""Same check via ainvoke (AsyncPregelLoop path)."""
|
||||
saver = InMemorySaver()
|
||||
graph = _build_graph(saver)
|
||||
config = {"configurable": {"thread_id": "stability-async"}}
|
||||
|
||||
await graph.ainvoke({"messages": [HumanMessage(content="write a hello world script")]}, config)
|
||||
id_turn1 = next(m.id for m in (await graph.aget_state(config)).values["messages"] if isinstance(m, HumanMessage))
|
||||
|
||||
await graph.ainvoke({"messages": [HumanMessage(content="add error handling")]}, config)
|
||||
id_turn2 = next(
|
||||
m.id for m in (await graph.aget_state(config)).values["messages"] if isinstance(m, HumanMessage) and m.content == "write a hello world script"
|
||||
)
|
||||
|
||||
assert id_turn1 is not None
|
||||
assert id_turn1 == id_turn2, f"Async: HumanMessage ID changed across invocations: turn 1={id_turn1!r}, turn 2={id_turn2!r}"
|
||||
|
||||
Generated
+10
-10
@@ -449,7 +449,7 @@ test = [
|
||||
|
||||
[package.metadata]
|
||||
requires-dist = [
|
||||
{ name = "langchain", specifier = ">=1.3.0,<2.0.0" },
|
||||
{ name = "langchain", specifier = ">=1.3.2,<2.0.0" },
|
||||
{ name = "langchain-anthropic", specifier = ">=1.4.3,<2.0.0" },
|
||||
{ name = "langchain-core", specifier = ">=1.4.0,<2.0.0" },
|
||||
{ name = "langchain-google-genai", specifier = ">=4.2.2,<5.0.0" },
|
||||
@@ -812,16 +812,16 @@ wheels = [
|
||||
|
||||
[[package]]
|
||||
name = "langchain"
|
||||
version = "1.3.0"
|
||||
version = "1.3.2"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "langchain-core" },
|
||||
{ name = "langgraph" },
|
||||
{ name = "pydantic" },
|
||||
]
|
||||
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" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/d5/d0/c7f9d3d26c0e3f8bb146c6d707ee0fc1d30d8da65a59626e8a580085e929/langchain-1.3.2.tar.gz", hash = "sha256:ffd5f204a46b5fa1a38bf89ba3b45ca0902c02d18fa7d2a2eaeaeb1f5bf19d0a", size = 600598, upload-time = "2026-05-26T18:17:57.715Z" }
|
||||
wheels = [
|
||||
{ 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" },
|
||||
{ url = "https://files.pythonhosted.org/packages/f8/82/a54edcd1c48163de5642eb10fa2cb58b13a8889c659964f63f0306b58b1e/langchain-1.3.2-py3-none-any.whl", hash = "sha256:900f6b3f4ee08b9ba3cdbe667dbf42525bd6f66a4a07a7f1db26262673e41ed6", size = 121225, upload-time = "2026-05-26T18:17:56.075Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
@@ -939,7 +939,7 @@ wheels = [
|
||||
|
||||
[[package]]
|
||||
name = "langgraph"
|
||||
version = "1.2.0"
|
||||
version = "1.2.2"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "langchain-core" },
|
||||
@@ -949,9 +949,9 @@ dependencies = [
|
||||
{ name = "pydantic" },
|
||||
{ name = "xxhash" },
|
||||
]
|
||||
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{ name = "langchain-mcp-adapters", marker = "(platform_machine == 'arm64' and sys_platform == 'darwin') or (platform_machine == 'x86_64' and sys_platform == 'linux')" },
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{ name = "langchain-openai", marker = "(platform_machine == 'arm64' and sys_platform == 'darwin') or (platform_machine == 'x86_64' and sys_platform == 'linux')" },
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|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/f6/e8/e3304ac0015c2bdb04ad9785e4ed65c788855ce7857ce6104dd2f5d322db/langgraph-1.2.0-py3-none-any.whl", hash = "sha256:03fd5895a8d4b70db1ff63ebc3bacead29dd20cd794a8b1a483e7ec9018f7a65", size = 234262, upload-time = "2026-05-12T03:46:37.971Z" },
|
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{ url = "https://files.pythonhosted.org/packages/42/9b/b08d578bba73e25351152dfd3d6d21e81210a5fff1b6f26e56f33197c8f5/langgraph-1.2.2-py3-none-any.whl", hash = "sha256:0a851bf4ba5939c5474a2fd57e6b439b5315283e254e42943bd392c2d71a5e03", size = 236376, upload-time = "2026-05-26T18:07:26.577Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
|
||||
Generated
+7
-7
@@ -590,7 +590,7 @@ dependencies = [
|
||||
|
||||
[package.metadata]
|
||||
requires-dist = [
|
||||
{ name = "langchain", specifier = ">=1.3.0,<2.0.0" },
|
||||
{ name = "langchain", specifier = ">=1.3.2,<2.0.0" },
|
||||
{ name = "langchain-anthropic", specifier = ">=1.4.3,<2.0.0" },
|
||||
{ name = "langchain-core", specifier = ">=1.4.0,<2.0.0" },
|
||||
{ name = "langchain-google-genai", specifier = ">=4.2.2,<5.0.0" },
|
||||
@@ -1006,16 +1006,16 @@ wheels = [
|
||||
|
||||
[[package]]
|
||||
name = "langchain"
|
||||
version = "1.3.0"
|
||||
version = "1.3.2"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "langchain-core" },
|
||||
{ name = "langgraph" },
|
||||
{ name = "pydantic" },
|
||||
]
|
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||||
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|
||||
wheels = [
|
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{ 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" },
|
||||
{ url = "https://files.pythonhosted.org/packages/f8/82/a54edcd1c48163de5642eb10fa2cb58b13a8889c659964f63f0306b58b1e/langchain-1.3.2-py3-none-any.whl", hash = "sha256:900f6b3f4ee08b9ba3cdbe667dbf42525bd6f66a4a07a7f1db26262673e41ed6", size = 121225, upload-time = "2026-05-26T18:17:56.075Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
@@ -1144,7 +1144,7 @@ wheels = [
|
||||
|
||||
[[package]]
|
||||
name = "langgraph"
|
||||
version = "1.2.0"
|
||||
version = "1.2.2"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "langchain-core" },
|
||||
@@ -1154,9 +1154,9 @@ dependencies = [
|
||||
{ name = "pydantic" },
|
||||
{ name = "xxhash" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/58/61/d5d25e783035aa307d289b37e082258a6061c0fb4caa4a284f3bf1e87169/langgraph-1.2.0.tar.gz", hash = "sha256:4a9baaf62afc5d5f63144a50095140a34b9aa9b7cea695d25326d564775348e7", size = 690248, upload-time = "2026-05-12T03:46:39.164Z" }
|
||||
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|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/f6/e8/e3304ac0015c2bdb04ad9785e4ed65c788855ce7857ce6104dd2f5d322db/langgraph-1.2.0-py3-none-any.whl", hash = "sha256:03fd5895a8d4b70db1ff63ebc3bacead29dd20cd794a8b1a483e7ec9018f7a65", size = 234262, upload-time = "2026-05-12T03:46:37.971Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/42/9b/b08d578bba73e25351152dfd3d6d21e81210a5fff1b6f26e56f33197c8f5/langgraph-1.2.2-py3-none-any.whl", hash = "sha256:0a851bf4ba5939c5474a2fd57e6b439b5315283e254e42943bd392c2d71a5e03", size = 236376, upload-time = "2026-05-26T18:07:26.577Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
|
||||
+5
-1
@@ -45,7 +45,7 @@ For longer tasks, provide brief progress updates at reasonable intervals — a c
|
||||
## `write_todos`
|
||||
|
||||
You have access to the `write_todos` tool to help you manage and plan complex objectives.
|
||||
Use this tool for complex objectives to ensure that you are tracking each necessary step and giving the user visibility into your progress.
|
||||
Use this tool for complex objectives to ensure that you are tracking each necessary step.
|
||||
This tool is very helpful for planning complex objectives, and for breaking down these larger complex objectives into smaller steps.
|
||||
|
||||
It is critical that you mark todos as completed as soon as you are done with a step. Do not batch up multiple steps before marking them as completed.
|
||||
@@ -57,6 +57,10 @@ Writing todos takes time and tokens, use it when it is helpful for managing comp
|
||||
- The `write_todos` tool should never be called multiple times in parallel.
|
||||
- Don't be afraid to revise the To-Do list as you go. New information may reveal new tasks that need to be done, or old tasks that are irrelevant.
|
||||
|
||||
## Finishing a task
|
||||
|
||||
When you finish all work, write your final answer in the message AFTER your last `write_todos` call — not in the same turn as that call. Start the final message with the substantive content the user asked for — the data, computation, summary, or analysis. The user wants the result, not confirmation that the work is done.
|
||||
|
||||
## Following Conventions
|
||||
|
||||
- Read files before editing — understand existing content before making changes
|
||||
|
||||
+5
-1
@@ -45,7 +45,7 @@ For longer tasks, provide brief progress updates at reasonable intervals — a c
|
||||
## `write_todos`
|
||||
|
||||
You have access to the `write_todos` tool to help you manage and plan complex objectives.
|
||||
Use this tool for complex objectives to ensure that you are tracking each necessary step and giving the user visibility into your progress.
|
||||
Use this tool for complex objectives to ensure that you are tracking each necessary step.
|
||||
This tool is very helpful for planning complex objectives, and for breaking down these larger complex objectives into smaller steps.
|
||||
|
||||
It is critical that you mark todos as completed as soon as you are done with a step. Do not batch up multiple steps before marking them as completed.
|
||||
@@ -57,6 +57,10 @@ Writing todos takes time and tokens, use it when it is helpful for managing comp
|
||||
- The `write_todos` tool should never be called multiple times in parallel.
|
||||
- Don't be afraid to revise the To-Do list as you go. New information may reveal new tasks that need to be done, or old tasks that are irrelevant.
|
||||
|
||||
## Finishing a task
|
||||
|
||||
When you finish all work, write your final answer in the message AFTER your last `write_todos` call — not in the same turn as that call. Start the final message with the substantive content the user asked for — the data, computation, summary, or analysis. The user wants the result, not confirmation that the work is done.
|
||||
|
||||
## Following Conventions
|
||||
|
||||
- Read files before editing — understand existing content before making changes
|
||||
|
||||
Generated
+7
-7
@@ -433,7 +433,7 @@ dependencies = [
|
||||
|
||||
[package.metadata]
|
||||
requires-dist = [
|
||||
{ name = "langchain", specifier = ">=1.3.0,<2.0.0" },
|
||||
{ name = "langchain", specifier = ">=1.3.2,<2.0.0" },
|
||||
{ name = "langchain-anthropic", specifier = ">=1.4.3,<2.0.0" },
|
||||
{ name = "langchain-core", specifier = ">=1.4.0,<2.0.0" },
|
||||
{ name = "langchain-google-genai", specifier = ">=4.2.2,<5.0.0" },
|
||||
@@ -815,16 +815,16 @@ wheels = [
|
||||
|
||||
[[package]]
|
||||
name = "langchain"
|
||||
version = "1.3.0"
|
||||
version = "1.3.2"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "langchain-core" },
|
||||
{ name = "langgraph" },
|
||||
{ name = "pydantic" },
|
||||
]
|
||||
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" }
|
||||
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|
||||
wheels = [
|
||||
{ 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" },
|
||||
{ url = "https://files.pythonhosted.org/packages/f8/82/a54edcd1c48163de5642eb10fa2cb58b13a8889c659964f63f0306b58b1e/langchain-1.3.2-py3-none-any.whl", hash = "sha256:900f6b3f4ee08b9ba3cdbe667dbf42525bd6f66a4a07a7f1db26262673e41ed6", size = 121225, upload-time = "2026-05-26T18:17:56.075Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
@@ -951,7 +951,7 @@ test = [
|
||||
|
||||
[[package]]
|
||||
name = "langgraph"
|
||||
version = "1.2.0"
|
||||
version = "1.2.2"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "langchain-core" },
|
||||
@@ -961,9 +961,9 @@ dependencies = [
|
||||
{ name = "pydantic" },
|
||||
{ name = "xxhash" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/58/61/d5d25e783035aa307d289b37e082258a6061c0fb4caa4a284f3bf1e87169/langgraph-1.2.0.tar.gz", hash = "sha256:4a9baaf62afc5d5f63144a50095140a34b9aa9b7cea695d25326d564775348e7", size = 690248, upload-time = "2026-05-12T03:46:39.164Z" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/e6/5a/ffc12434ee8aecab830d58b4d204ddea45073eae7639c963310f671a5bf5/langgraph-1.2.2.tar.gz", hash = "sha256:f54a98458976b3ff0774683867df125fb52d8dbedeb2441d0b0656a51331cee5", size = 695730, upload-time = "2026-05-26T18:07:28.49Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/f6/e8/e3304ac0015c2bdb04ad9785e4ed65c788855ce7857ce6104dd2f5d322db/langgraph-1.2.0-py3-none-any.whl", hash = "sha256:03fd5895a8d4b70db1ff63ebc3bacead29dd20cd794a8b1a483e7ec9018f7a65", size = 234262, upload-time = "2026-05-12T03:46:37.971Z" },
|
||||
{ url = "https://files.pythonhosted.org/packages/42/9b/b08d578bba73e25351152dfd3d6d21e81210a5fff1b6f26e56f33197c8f5/langgraph-1.2.2-py3-none-any.whl", hash = "sha256:0a851bf4ba5939c5474a2fd57e6b439b5315283e254e42943bd392c2d71a5e03", size = 236376, upload-time = "2026-05-26T18:07:26.577Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
|
||||
Generated
+7
-7
@@ -398,7 +398,7 @@ dependencies = [
|
||||
|
||||
[package.metadata]
|
||||
requires-dist = [
|
||||
{ name = "langchain", specifier = ">=1.3.0,<2.0.0" },
|
||||
{ name = "langchain", specifier = ">=1.3.2,<2.0.0" },
|
||||
{ name = "langchain-anthropic", specifier = ">=1.4.3,<2.0.0" },
|
||||
{ name = "langchain-core", specifier = ">=1.4.0,<2.0.0" },
|
||||
{ name = "langchain-google-genai", specifier = ">=4.2.2,<5.0.0" },
|
||||
@@ -665,16 +665,16 @@ wheels = [
|
||||
|
||||
[[package]]
|
||||
name = "langchain"
|
||||
version = "1.3.0"
|
||||
version = "1.3.2"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "langchain-core" },
|
||||
{ name = "langgraph" },
|
||||
{ name = "pydantic" },
|
||||
]
|
||||
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" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/d5/d0/c7f9d3d26c0e3f8bb146c6d707ee0fc1d30d8da65a59626e8a580085e929/langchain-1.3.2.tar.gz", hash = "sha256:ffd5f204a46b5fa1a38bf89ba3b45ca0902c02d18fa7d2a2eaeaeb1f5bf19d0a", size = 600598, upload-time = "2026-05-26T18:17:57.715Z" }
|
||||
wheels = [
|
||||
{ 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" },
|
||||
{ url = "https://files.pythonhosted.org/packages/f8/82/a54edcd1c48163de5642eb10fa2cb58b13a8889c659964f63f0306b58b1e/langchain-1.3.2-py3-none-any.whl", hash = "sha256:900f6b3f4ee08b9ba3cdbe667dbf42525bd6f66a4a07a7f1db26262673e41ed6", size = 121225, upload-time = "2026-05-26T18:17:56.075Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
@@ -803,7 +803,7 @@ wheels = [
|
||||
|
||||
[[package]]
|
||||
name = "langgraph"
|
||||
version = "1.2.0"
|
||||
version = "1.2.2"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
dependencies = [
|
||||
{ name = "langchain-core" },
|
||||
@@ -813,9 +813,9 @@ dependencies = [
|
||||
{ name = "pydantic" },
|
||||
{ name = "xxhash" },
|
||||
]
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/58/61/d5d25e783035aa307d289b37e082258a6061c0fb4caa4a284f3bf1e87169/langgraph-1.2.0.tar.gz", hash = "sha256:4a9baaf62afc5d5f63144a50095140a34b9aa9b7cea695d25326d564775348e7", size = 690248, upload-time = "2026-05-12T03:46:39.164Z" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/e6/5a/ffc12434ee8aecab830d58b4d204ddea45073eae7639c963310f671a5bf5/langgraph-1.2.2.tar.gz", hash = "sha256:f54a98458976b3ff0774683867df125fb52d8dbedeb2441d0b0656a51331cee5", size = 695730, upload-time = "2026-05-26T18:07:28.49Z" }
|
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wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/f6/e8/e3304ac0015c2bdb04ad9785e4ed65c788855ce7857ce6104dd2f5d322db/langgraph-1.2.0-py3-none-any.whl", hash = "sha256:03fd5895a8d4b70db1ff63ebc3bacead29dd20cd794a8b1a483e7ec9018f7a65", size = 234262, upload-time = "2026-05-12T03:46:37.971Z" },
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{ url = "https://files.pythonhosted.org/packages/42/9b/b08d578bba73e25351152dfd3d6d21e81210a5fff1b6f26e56f33197c8f5/langgraph-1.2.2-py3-none-any.whl", hash = "sha256:0a851bf4ba5939c5474a2fd57e6b439b5315283e254e42943bd392c2d71a5e03", size = 236376, upload-time = "2026-05-26T18:07:26.577Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
|
||||
Reference in New Issue
Block a user