chore: import upstream snapshot with attribution

examples/README.md

@@ -0,0 +1,11 @@
+# LangGraph examples
+
+This directory is retained purely for archival purposes and is no longer updated.
+
+## 🤔 What is this?
+
+The examples previously found here have been moved to the consolidated LangChain documentation. This directory remains available for historical reference, but new examples and usage guidance are published in the docs.
+
+## 📖 Documentation
+
+For up-to-date LangGraph examples, tutorials, and guides, see the [LangGraph Docs](https://docs.langchain.com/oss/python/langgraph/overview). Get started with the [LangGraph Quickstart](https://docs.langchain.com/oss/python/langgraph/quickstart).

examples/chatbot-simulation-evaluation/agent-simulation-evaluation.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "10251c1c",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/tutorials/chatbot-simulation-evaluation/agent-simulation-evaluation.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c5fc63df",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.1"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/chatbot-simulation-evaluation/langsmith-agent-simulation-evaluation.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "a4351a24",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/tutorials/chatbot-simulation-evaluation/langsmith-agent-simulation-evaluation.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "4cc9af1e",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/chatbot-simulation-evaluation/simulation_utils.py

@@ -0,0 +1,203 @@
+import functools
+from typing import Annotated, Any, Callable, Dict, List, Optional, Union
+
+from langchain_community.adapters.openai import convert_message_to_dict
+from langchain_core.messages import AIMessage, AnyMessage, BaseMessage, HumanMessage
+from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
+from langchain_core.runnables import Runnable, RunnableLambda
+from langchain_core.runnables import chain as as_runnable
+from langchain_openai import ChatOpenAI
+from typing_extensions import TypedDict
+
+from langgraph.graph import END, StateGraph, START
+
+
+def langchain_to_openai_messages(messages: List[BaseMessage]):
+    """
+    Convert a list of langchain base messages to a list of openai messages.
+
+    Parameters:
+        messages (List[BaseMessage]): A list of langchain base messages.
+
+    Returns:
+        List[dict]: A list of openai messages.
+    """
+
+    return [
+        convert_message_to_dict(m) if isinstance(m, BaseMessage) else m
+        for m in messages
+    ]
+
+
+def create_simulated_user(
+    system_prompt: str, llm: Runnable | None = None
+) -> Runnable[Dict, AIMessage]:
+    """
+    Creates a simulated user for chatbot simulation.
+
+    Args:
+        system_prompt (str): The system prompt to be used by the simulated user.
+        llm (Runnable | None, optional): The language model to be used for the simulation.
+            Defaults to gpt-3.5-turbo.
+
+    Returns:
+        Runnable[Dict, AIMessage]: The simulated user for chatbot simulation.
+    """
+    return ChatPromptTemplate.from_messages(
+        [
+            ("system", system_prompt),
+            MessagesPlaceholder(variable_name="messages"),
+        ]
+    ) | (llm or ChatOpenAI(model="gpt-3.5-turbo")).with_config(
+        run_name="simulated_user"
+    )
+
+
+Messages = Union[list[AnyMessage], AnyMessage]
+
+
+def add_messages(left: Messages, right: Messages) -> Messages:
+    if not isinstance(left, list):
+        left = [left]
+    if not isinstance(right, list):
+        right = [right]
+    return left + right
+
+
+class SimulationState(TypedDict):
+    """
+    Represents the state of a simulation.
+
+    Attributes:
+        messages (List[AnyMessage]): A list of messages in the simulation.
+        inputs (Optional[dict[str, Any]]): Optional inputs for the simulation.
+    """
+
+    messages: Annotated[List[AnyMessage], add_messages]
+    inputs: Optional[dict[str, Any]]
+
+
+def create_chat_simulator(
+    assistant: (
+        Callable[[List[AnyMessage]], str | AIMessage]
+        | Runnable[List[AnyMessage], str | AIMessage]
+    ),
+    simulated_user: Runnable[Dict, AIMessage],
+    *,
+    input_key: str,
+    max_turns: int = 6,
+    should_continue: Optional[Callable[[SimulationState], str]] = None,
+):
+    """Creates a chat simulator for evaluating a chatbot.
+
+    Args:
+        assistant: The chatbot assistant function or runnable object.
+        simulated_user: The simulated user object.
+        input_key: The key for the input to the chat simulation.
+        max_turns: The maximum number of turns in the chat simulation. Default is 6.
+        should_continue: Optional function to determine if the simulation should continue.
+            If not provided, a default function will be used.
+
+    Returns:
+        The compiled chat simulation graph.
+
+    """
+    graph_builder = StateGraph(SimulationState)
+    graph_builder.add_node(
+        "user",
+        _create_simulated_user_node(simulated_user),
+    )
+    graph_builder.add_node(
+        "assistant", _fetch_messages | assistant | _coerce_to_message
+    )
+    graph_builder.add_edge("assistant", "user")
+    graph_builder.add_conditional_edges(
+        "user",
+        should_continue or functools.partial(_should_continue, max_turns=max_turns),
+    )
+    # If your dataset has a 'leading question/input', then we route first to the assistant, otherwise, we let the user take the lead.
+    graph_builder.add_edge(START, "assistant" if input_key is not None else "user")
+
+    return (
+        RunnableLambda(_prepare_example).bind(input_key=input_key)
+        | graph_builder.compile()
+    )
+
+
+## Private methods
+
+
+def _prepare_example(inputs: dict[str, Any], input_key: Optional[str] = None):
+    if input_key is not None:
+        if input_key not in inputs:
+            raise ValueError(
+                f"Dataset's example input must contain the provided input key: '{input_key}'.\nFound: {list(inputs.keys())}"
+            )
+        messages = [HumanMessage(content=inputs[input_key])]
+        return {
+            "inputs": {k: v for k, v in inputs.items() if k != input_key},
+            "messages": messages,
+        }
+    return {"inputs": inputs, "messages": []}
+
+
+def _invoke_simulated_user(state: SimulationState, simulated_user: Runnable):
+    """Invoke the simulated user node."""
+    runnable = (
+        simulated_user
+        if isinstance(simulated_user, Runnable)
+        else RunnableLambda(simulated_user)
+    )
+    inputs = state.get("inputs", {})
+    inputs["messages"] = state["messages"]
+    return runnable.invoke(inputs)
+
+
+def _swap_roles(state: SimulationState):
+    new_messages = []
+    for m in state["messages"]:
+        if isinstance(m, AIMessage):
+            new_messages.append(HumanMessage(content=m.content))
+        else:
+            new_messages.append(AIMessage(content=m.content))
+    return {
+        "inputs": state.get("inputs", {}),
+        "messages": new_messages,
+    }
+
+
+@as_runnable
+def _fetch_messages(state: SimulationState):
+    """Invoke the simulated user node."""
+    return state["messages"]
+
+
+def _convert_to_human_message(message: BaseMessage):
+    return {"messages": [HumanMessage(content=message.content)]}
+
+
+def _create_simulated_user_node(simulated_user: Runnable):
+    """Simulated user accepts a {"messages": [...]} argument and returns a single message."""
+    return (
+        _swap_roles
+        | RunnableLambda(_invoke_simulated_user).bind(simulated_user=simulated_user)
+        | _convert_to_human_message
+    )
+
+
+def _coerce_to_message(assistant_output: str | BaseMessage):
+    if isinstance(assistant_output, str):
+        return {"messages": [AIMessage(content=assistant_output)]}
+    else:
+        return {"messages": [assistant_output]}
+
+
+def _should_continue(state: SimulationState, max_turns: int = 6):
+    messages = state["messages"]
+    # TODO support other stop criteria
+    if len(messages) > max_turns:
+        return END
+    elif messages[-1].content.strip() == "FINISHED":
+        return END
+    else:
+        return "assistant"

examples/chatbots/information-gather-prompting.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "a9014f94",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/tutorials/chatbots/information-gather-prompting.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f47ce992",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/code_assistant/langgraph_code_assistant.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "1f2f13ca",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/tutorials/code_assistant/langgraph_code_assistant.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5e4c9bfe",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/customer-support/customer-support.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "a8232bc9",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/tutorials/customer-support/customer-support.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "63da8671",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/delta-channel-dump/README.md

@@ -0,0 +1,132 @@
+# delta-channel-dump
+
+Recover messages (and other channels) from a Postgres-backed LangGraph thread
+written by **langgraph >= 1.2** (DeltaChannel format) — including **LangGraph
+Server / langgraph-api** deployments on the Postgres runtime, **deepagents
+0.6.x**, or any OSS app using `PostgresSaver` — before rolling back to an older
+runtime such as **deepagents 0.5.x / langgraph < 1.2**.
+
+langgraph-api uses the same `checkpoints` / `checkpoint_blobs` / `checkpoint_writes`
+schema as OSS `checkpoint-postgres`; this script reads those tables directly.
+
+On the older runtime, `add_messages` does not understand the `EXT_DELTA_SNAPSHOT`
+msgpack ext code and silently returns an empty list for affected channels. This
+tool reads the raw checkpoint blobs from Postgres and emits JSON you can inspect
+and re-apply via `update_state` (LangGraph Server SDK) or `graph.update_state`
+(OSS).
+
+## Install
+
+```bash
+pip install "psycopg[binary]" ormsgpack
+```
+
+## Run
+
+```bash
+export DATABASE_URI=postgres://user:pass@host:5432/dbname
+python3 dump.py \
+    --thread-id <uuid> \
+    --channel messages \
+    [--channel files ...] \
+    [--checkpoint-id <uuid>] \
+    [--checkpoint-ns ""] \
+    --output recovery.json
+```
+
+- `--thread-id` (required): thread UUID
+- `--channel` (required, repeatable): channel names to recover
+- `--checkpoint-id` (optional): target checkpoint; defaults to latest
+- `--checkpoint-ns` (optional): namespace; defaults to `""`
+- `--database-uri` (optional): Postgres URI; defaults to `DATABASE_URI` env var
+- `--output` (optional): output file; defaults to stdout
+
+## Output
+
+```json
+{
+  "thread_id": "...",
+  "checkpoint_ns": "",
+  "target_checkpoint_id": "...",
+  "parent_checkpoint_id": "...",
+  "channels": {
+    "messages": {
+      "delta_kind": "snapshot",
+      "seed_checkpoint_id": "...",
+      "seed_version": "...",
+      "seed": [{ "type": "ai", "content": "...", "id": "ai-0" }],
+      "writes": [
+        {
+          "checkpoint_id": "...",
+          "task_id": "...",
+          "idx": 0,
+          "value": [{ "type": "ai", "content": "...", "id": "ai-10" }]
+        }
+      ]
+    }
+  }
+}
+```
+
+`delta_kind` is one of:
+
+- `snapshot` — DeltaChannel snapshot blob (`channel_values[ch] == true`)
+- `legacy_plain` — pre-DeltaChannel inline or blob value
+- `no_seed` — walked to root without finding a populated ancestor
+
+`writes` are ordered oldest-to-newest (the order a reducer would replay them).
+
+## Reducing back to a single list
+
+For deepagents-style messages, combine seed and writes, then deduplicate:
+
+```python
+import json
+
+data = json.load(open("recovery.json"))
+ch = data["channels"]["messages"]
+messages = list(ch["seed"] or [])
+for w in ch["writes"]:
+    messages.extend(w["value"] or [])
+
+# Dedup by id, keep last; drop RemoveMessage tombstones
+by_id = {}
+for m in messages:
+    if isinstance(m, dict) and m.get("type") == "remove":
+        by_id.pop(m.get("id"), None)
+    elif isinstance(m, dict) and m.get("id"):
+        by_id[m["id"]] = m
+    else:
+        by_id[id(m)] = m
+reduced = list(by_id.values())
+```
+
+This approximates `_messages_delta_reducer` semantics; adjust for your graph.
+
+## Re-applying
+
+```python
+from langgraph_sdk import get_client
+
+client = get_client(url="http://localhost:8123")
+await client.threads.update_state(
+    thread_id,
+    values={"messages": reduced},
+)
+```
+
+Review the recovered JSON before calling `update_state`. This tool is
+read-only and intentionally does not mutate the database.
+
+## Scope / non-goals (v1)
+
+- **Postgres only** — OSS `PostgresSaver` or langgraph-api Postgres runtime; not
+  inmem, gRPC core, Mongo, or Redis checkpointer backends
+- **No AES decryption** (`LANGGRAPH_AES_KEY`) or custom encryption
+- **No reducer** — raw seed + writes only
+- **No automatic `update_state`** — operator applies manually
+
+## Copying
+
+`dump.py` is self-contained. Copy it anywhere; only `psycopg[binary]` and
+`ormsgpack` are required at runtime. No langgraph imports.

examples/delta-channel-dump/dump.py

@@ -0,0 +1,469 @@
+#!/usr/bin/env python3
+"""Recover delta-channel state from a Postgres-backed LangGraph thread.
+
+Works with OSS ``PostgresSaver`` and LangGraph Server / langgraph-api on the
+Postgres runtime (same checkpoint schema). Use after rolling back from
+langgraph >= 1.2 / deepagents 0.6.x to an older runtime that does not
+understand ``EXT_DELTA_SNAPSHOT`` msgpack blobs. The script walks the checkpoint
+parent chain, decodes msgpack blobs, and emits a JSON dump of per-channel
+``seed`` plus oldest-to-newest ``writes``. Apply the recovered values manually
+via ``client.threads.update_state(...)`` (Server) or ``graph.update_state``
+(OSS).
+
+Install::
+
+    pip install "psycopg[binary]" ormsgpack
+
+Run::
+
+    export DATABASE_URI=postgres://...
+    python3 dump.py --thread-id <uuid> --channel messages --output recovery.json
+
+Scope (v1): Postgres only; no AES/custom encryption; no reducer application.
+"""
+
+from __future__ import annotations
+
+import argparse
+import base64
+import json
+import os
+import sys
+import uuid
+from typing import Any
+
+import ormsgpack
+import psycopg
+
+# LangGraph msgpack EXT type codes (langgraph/checkpoint/serde/jsonplus.py).
+EXT_CONSTRUCTOR_SINGLE_ARG = 0
+EXT_CONSTRUCTOR_POS_ARGS = 1
+EXT_CONSTRUCTOR_KW_ARGS = 2
+EXT_METHOD_SINGLE_ARG = 3
+EXT_PYDANTIC_V1 = 4
+EXT_PYDANTIC_V2 = 5
+EXT_NUMPY_ARRAY = 6
+EXT_DELTA_SNAPSHOT = 7
+
+_MSGPACK_OPTION = ormsgpack.OPT_NON_STR_KEYS
+
+
+def ext_hook(code: int, data: bytes) -> Any:
+    """Decode LangGraph msgpack EXT payloads to JSON-friendly Python values."""
+    if code == EXT_DELTA_SNAPSHOT:
+        inner = ormsgpack.unpackb(data, ext_hook=ext_hook, option=_MSGPACK_OPTION)
+        return {"__delta_snapshot__": inner}
+    if code == EXT_CONSTRUCTOR_SINGLE_ARG:
+        try:
+            tup = ormsgpack.unpackb(data, ext_hook=ext_hook, option=_MSGPACK_OPTION)
+            if tup[0] == "uuid" and tup[1] == "UUID":
+                hex_ = tup[2]
+                return (
+                    f"{hex_[:8]}-{hex_[8:12]}-{hex_[12:16]}-"
+                    f"{hex_[16:20]}-{hex_[20:]}"
+                )
+            return tup[2]
+        except Exception:
+            return None
+    if code == EXT_CONSTRUCTOR_POS_ARGS:
+        try:
+            tup = ormsgpack.unpackb(data, ext_hook=ext_hook, option=_MSGPACK_OPTION)
+            if tup[0] == "langgraph.types" and tup[1] == "Send":
+                args = tup[2]
+                if len(args) == 2:
+                    return {"__send__": {"node": args[0], "arg": args[1]}}
+                return {
+                    "__send__": {
+                        "node": args[0],
+                        "arg": args[1],
+                        "timeout": args[2],
+                    }
+                }
+            return tup[2]
+        except Exception:
+            return None
+    if code in (EXT_CONSTRUCTOR_KW_ARGS, EXT_METHOD_SINGLE_ARG):
+        try:
+            tup = ormsgpack.unpackb(data, ext_hook=ext_hook, option=_MSGPACK_OPTION)
+            return tup[2]
+        except Exception:
+            return None
+    if code in (EXT_PYDANTIC_V1, EXT_PYDANTIC_V2):
+        try:
+            tup = ormsgpack.unpackb(data, ext_hook=ext_hook, option=_MSGPACK_OPTION)
+            return tup[2]
+        except Exception:
+            return None
+    if code == EXT_NUMPY_ARRAY:
+        try:
+            dtype_str, shape, order, buf = ormsgpack.unpackb(
+                data, ext_hook=ext_hook, option=_MSGPACK_OPTION
+            )
+            return {
+                "__numpy_array__": {
+                    "dtype": dtype_str,
+                    "shape": shape,
+                    "order": order,
+                    "data_b64": base64.b64encode(buf).decode("ascii"),
+                }
+            }
+        except Exception:
+            return None
+    return None
+
+
+def decode_blob(blob_type: str, blob_bytes: bytes | None) -> Any:
+    if blob_type in ("empty", "null") or blob_bytes is None:
+        return None
+    if blob_type == "msgpack":
+        return ormsgpack.unpackb(
+            blob_bytes, ext_hook=ext_hook, option=_MSGPACK_OPTION
+        )
+    if blob_type in ("bytes", "bytearray"):
+        return base64.b64encode(blob_bytes).decode("ascii")
+    raise RuntimeError(
+        f"Unknown blob type {blob_type!r}. "
+        "AES/custom-encrypted deployments are out of scope for v1."
+    )
+
+
+def delta_unwrap(value: Any) -> Any:
+    if isinstance(value, dict) and "__delta_snapshot__" in value:
+        return value["__delta_snapshot__"]
+    return value
+
+
+def json_default(obj: Any) -> Any:
+    if isinstance(obj, (bytes, bytearray)):
+        return base64.b64encode(bytes(obj)).decode("ascii")
+    if isinstance(obj, uuid.UUID):
+        return str(obj)
+    raise TypeError(f"Object of type {type(obj).__name__} is not JSON serializable")
+
+
+def resolve_target_checkpoint_id(
+    conn: psycopg.Connection[Any],
+    thread_id: str,
+    checkpoint_ns: str,
+    checkpoint_id: str | None,
+) -> str:
+    if checkpoint_id is not None:
+        return checkpoint_id
+    row = conn.execute(
+        """
+        SELECT checkpoint_id::text
+        FROM checkpoints
+        WHERE thread_id = %s AND checkpoint_ns = %s
+        ORDER BY checkpoint_id DESC
+        LIMIT 1
+        """,
+        (thread_id, checkpoint_ns),
+    ).fetchone()
+    if row is None:
+        raise SystemExit(
+            f"No checkpoints found for thread_id={thread_id!r} "
+            f"checkpoint_ns={checkpoint_ns!r}"
+        )
+    return row[0]
+
+
+def _load_checkpoint(
+    conn: psycopg.Connection[Any],
+    thread_id: str,
+    checkpoint_ns: str,
+    checkpoint_id: str,
+) -> tuple[dict[str, Any], str | None] | None:
+    row = conn.execute(
+        """
+        SELECT checkpoint, parent_checkpoint_id::text
+        FROM checkpoints
+        WHERE thread_id = %s AND checkpoint_ns = %s AND checkpoint_id = %s
+        """,
+        (thread_id, checkpoint_ns, checkpoint_id),
+    ).fetchone()
+    if row is None:
+        return None
+    return row[0], row[1]
+
+
+def _load_seed(
+    conn: psycopg.Connection[Any],
+    *,
+    thread_id: str,
+    checkpoint_ns: str,
+    channel: str,
+    checkpoint_id: str,
+    channel_values: dict[str, Any],
+    channel_versions: dict[str, str],
+) -> dict[str, Any]:
+    cv = channel_values[channel]
+    version = channel_versions.get(channel)
+    if cv is True:
+        blob_row = conn.execute(
+            """
+            SELECT type, blob
+            FROM checkpoint_blobs
+            WHERE thread_id = %s AND checkpoint_ns = %s
+              AND channel = %s AND version = %s
+            """,
+            (thread_id, checkpoint_ns, channel, version),
+        ).fetchone()
+        seed_value = None
+        if blob_row is not None and blob_row[0] != "empty":
+            seed_value = delta_unwrap(decode_blob(blob_row[0], blob_row[1]))
+        return {
+            "delta_kind": "snapshot",
+            "seed_checkpoint_id": checkpoint_id,
+            "seed_version": version,
+            "seed": seed_value,
+        }
+    if isinstance(cv, (int, float, str, bool)) or cv is None:
+        return {
+            "delta_kind": "legacy_plain",
+            "seed_checkpoint_id": checkpoint_id,
+            "seed_version": version,
+            "seed": cv,
+        }
+    blob_row = conn.execute(
+        """
+        SELECT type, blob
+        FROM checkpoint_blobs
+        WHERE thread_id = %s AND checkpoint_ns = %s
+          AND channel = %s AND version = %s
+        """,
+        (thread_id, checkpoint_ns, channel, version),
+    ).fetchone()
+    seed_value = cv if blob_row is None else decode_blob(blob_row[0], blob_row[1])
+    return {
+        "delta_kind": "legacy_plain",
+        "seed_checkpoint_id": checkpoint_id,
+        "seed_version": version,
+        "seed": seed_value,
+    }
+
+
+def _load_writes_for_checkpoint(
+    conn: psycopg.Connection[Any],
+    *,
+    thread_id: str,
+    checkpoint_ns: str,
+    checkpoint_id: str,
+    channel: str,
+) -> list[dict[str, Any]]:
+    """Load writes for one checkpoint, newest-first by ``(task_id, idx)``.
+
+    ``walk_channel`` reverses the accumulated flat list before returning;
+    DESC here yields oldest-first within each checkpoint in the final output,
+    matching ``PostgresSaver._build_delta_channels_writes_history``.
+    """
+    rows = conn.execute(
+        """
+        SELECT task_id::text, idx, type, blob
+        FROM checkpoint_writes
+        WHERE thread_id = %s AND checkpoint_ns = %s
+          AND checkpoint_id = %s AND channel = %s
+        ORDER BY task_id DESC, idx DESC
+        """,
+        (thread_id, checkpoint_ns, checkpoint_id, channel),
+    ).fetchall()
+    return [
+        {
+            "checkpoint_id": checkpoint_id,
+            "task_id": task_id,
+            "idx": idx,
+            "value": decode_blob(blob_type, blob_bytes),
+        }
+        for task_id, idx, blob_type, blob_bytes in rows
+    ]
+
+
+def walk_channel(
+    conn: psycopg.Connection[Any],
+    *,
+    thread_id: str,
+    checkpoint_ns: str,
+    start_checkpoint_id: str | None,
+    channel: str,
+) -> dict[str, Any]:
+    """Walk one channel's parent chain from target.parent backward to seed."""
+    chain_writes_newest_first: list[dict[str, Any]] = []
+    cur = start_checkpoint_id
+    while cur is not None:
+        loaded = _load_checkpoint(conn, thread_id, checkpoint_ns, cur)
+        if loaded is None:
+            break
+        checkpoint_json, parent_id = loaded
+        channel_values = checkpoint_json.get("channel_values") or {}
+        channel_versions = checkpoint_json.get("channel_versions") or {}
+
+        chain_writes_newest_first.extend(
+            _load_writes_for_checkpoint(
+                conn,
+                thread_id=thread_id,
+                checkpoint_ns=checkpoint_ns,
+                checkpoint_id=cur,
+                channel=channel,
+            )
+        )
+
+        if channel in channel_values:
+            seed = _load_seed(
+                conn,
+                thread_id=thread_id,
+                checkpoint_ns=checkpoint_ns,
+                channel=channel,
+                checkpoint_id=cur,
+                channel_values=channel_values,
+                channel_versions=channel_versions,
+            )
+            seed["writes"] = list(reversed(chain_writes_newest_first))
+            return seed
+
+        cur = parent_id
+
+    return {
+        "delta_kind": "no_seed",
+        "seed_checkpoint_id": None,
+        "seed_version": None,
+        "seed": None,
+        "writes": list(reversed(chain_writes_newest_first)),
+    }
+
+
+def walk_parent_chain(
+    conn: psycopg.Connection[Any],
+    *,
+    thread_id: str,
+    checkpoint_ns: str,
+    target_checkpoint_id: str,
+    channels: list[str],
+) -> tuple[str | None, dict[str, dict[str, Any]]]:
+    """Walk parent chain and return per-channel seed + writes (oldest-first)."""
+    parent_row = conn.execute(
+        """
+        SELECT parent_checkpoint_id::text
+        FROM checkpoints
+        WHERE thread_id = %s AND checkpoint_ns = %s AND checkpoint_id = %s
+        """,
+        (thread_id, checkpoint_ns, target_checkpoint_id),
+    ).fetchone()
+    if parent_row is None:
+        raise SystemExit(
+            f"Checkpoint {target_checkpoint_id!r} not found for thread {thread_id!r}"
+        )
+    parent_checkpoint_id = parent_row[0]
+
+    result = {
+        ch: walk_channel(
+            conn,
+            thread_id=thread_id,
+            checkpoint_ns=checkpoint_ns,
+            start_checkpoint_id=parent_checkpoint_id,
+            channel=ch,
+        )
+        for ch in channels
+    }
+    return parent_checkpoint_id, result
+
+
+def build_output(
+    *,
+    thread_id: str,
+    checkpoint_ns: str,
+    target_checkpoint_id: str,
+    parent_checkpoint_id: str | None,
+    channels: dict[str, dict[str, Any]],
+) -> dict[str, Any]:
+    return {
+        "thread_id": thread_id,
+        "checkpoint_ns": checkpoint_ns,
+        "target_checkpoint_id": target_checkpoint_id,
+        "parent_checkpoint_id": parent_checkpoint_id,
+        "channels": channels,
+    }
+
+
+def parse_args(argv: list[str] | None = None) -> argparse.Namespace:
+    parser = argparse.ArgumentParser(
+        description=(
+            "Recover delta-channel seed + writes from Postgres checkpoint data."
+        ),
+    )
+    parser.add_argument("--thread-id", required=True, help="Thread UUID")
+    parser.add_argument(
+        "--channel",
+        action="append",
+        required=True,
+        dest="channels",
+        help="Channel name (repeatable)",
+    )
+    parser.add_argument(
+        "--checkpoint-id",
+        default=None,
+        help="Target checkpoint UUID (default: latest for thread)",
+    )
+    parser.add_argument(
+        "--checkpoint-ns",
+        default="",
+        help='Checkpoint namespace (default: "")',
+    )
+    parser.add_argument(
+        "--database-uri",
+        default=os.environ.get("DATABASE_URI"),
+        help="Postgres URI (default: DATABASE_URI env var)",
+    )
+    parser.add_argument(
+        "--output",
+        default="-",
+        help="Output JSON file path (default: stdout)",
+    )
+    return parser.parse_args(argv)
+
+
+def main(argv: list[str] | None = None) -> int:
+    args = parse_args(argv)
+    if not args.database_uri:
+        print(
+            "error: --database-uri or DATABASE_URI is required",
+            file=sys.stderr,
+        )
+        return 2
+
+    thread_id = str(uuid.UUID(args.thread_id))
+    channels = list(dict.fromkeys(args.channels))
+
+    with psycopg.connect(args.database_uri) as conn:
+        target_checkpoint_id = resolve_target_checkpoint_id(
+            conn,
+            thread_id,
+            args.checkpoint_ns,
+            args.checkpoint_id,
+        )
+        parent_checkpoint_id, channel_data = walk_parent_chain(
+            conn,
+            thread_id=thread_id,
+            checkpoint_ns=args.checkpoint_ns,
+            target_checkpoint_id=target_checkpoint_id,
+            channels=channels,
+        )
+
+    output = build_output(
+        thread_id=thread_id,
+        checkpoint_ns=args.checkpoint_ns,
+        target_checkpoint_id=target_checkpoint_id,
+        parent_checkpoint_id=parent_checkpoint_id,
+        channels=channel_data,
+    )
+    payload = json.dumps(output, indent=2, default=json_default)
+
+    if args.output == "-":
+        print(payload)
+    else:
+        with open(args.output, "w", encoding="utf-8") as f:
+            f.write(payload)
+            f.write("\n")
+    return 0
+
+
+if __name__ == "__main__":
+    raise SystemExit(main())

examples/extraction/retries.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "8dbdba5b",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/tutorials/extraction/retries.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1d444b7f",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/human_in_the_loop/wait-user-input.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "3ecab357",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/how-tos/human_in_the_loop/wait-user-input.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3f2866bd",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/lats/lats.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "09038b53",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/tutorials/lats/lats.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b1669748",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/llm-compiler/LLMCompiler.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "85205e97",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/tutorials/llm-compiler/LLMCompiler.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2fdab366",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/multi_agent/hierarchical_agent_teams.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "5cc8a2ad",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/tutorials/multi_agent/hierarchical_agent_teams.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b9f3508a",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/multi_agent/multi-agent-collaboration.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "d2b507b9",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/tutorials/multi_agent/multi-agent-collaboration.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "41a8f10a",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/plan-and-execute/plan-and-execute.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "9138f92e",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/tutorials/plan-and-execute/plan-and-execute.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "093678ba",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/react-agent-from-scratch.ipynb

@@ -0,0 +1,40 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "294995c4",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/how-tos/react-agent-from-scratch.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

examples/react-agent-structured-output.ipynb

@@ -0,0 +1,40 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "40f0d107",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/how-tos/react-agent-structured-output.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}

examples/reflection/reflection.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "658773a2",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/tutorials/reflection/reflection.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1cb60657",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/reflexion/reflexion.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "caf07859",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/tutorials/reflexion/reflexion.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "cd1df0e0",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/rewoo/rewoo.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "961f43ec",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/tutorials/rewoo/rewoo.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7f00c427",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/run-id-langsmith.ipynb

@@ -0,0 +1,40 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "bbd6e9b8",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/how-tos/run-id-langsmith.md)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}

examples/self-discover/self-discover.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "f6db1873",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/tutorials/self-discover/self-discover.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "219a78f9",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.12.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/subgraph.ipynb

@@ -0,0 +1,40 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "f49876e1",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/how-tos/subgraph.md)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}

examples/tool-calling.ipynb

@@ -0,0 +1,40 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "7fd8bd65",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/how-tos/tool-calling.md)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}

examples/tutorials/sql-agent.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "83c2223f",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/tutorials/sql/sql-agent.md)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "57f924b1",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/tutorials/tnt-llm/tnt-llm.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "11140167",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/tutorials/tnt-llm/tnt-llm.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1a2ba3e6",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/usaco/usaco.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "9dffdb54",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/tutorials/usaco/usaco.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "579c9959",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

examples/web-navigation/web_voyager.ipynb

@@ -0,0 +1,41 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "007ea2e9",
+   "metadata": {},
+   "source": [
+    "[This file has been moved](https://github.com/langchain-ai/langgraph/blob/23961cff61a42b52525f3b20b4094d8d2fba1744/docs/docs/tutorials/web-navigation/web_voyager.ipynb)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f0d7b895",
+   "metadata": {},
+   "source": [
+    "This directory is retained purely for archival purposes and is no longer updated. The examples previously found here have been moved to the newly [consolidated LangChain documentation](https://docs.langchain.com/oss/python/langgraph/overview)."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}