From eb572f41a65c9636b9e0e5a5fb4210a00a67a353 Mon Sep 17 00:00:00 2001
From: William FH <13333726+hinthornw@users.noreply.github.com>
Date: Sat, 7 Oct 2023 09:02:18 +0900
Subject: [PATCH] Add LangSmith Run Chat Loader (#11458)

---
 .../example_data/langsmith_chat_dataset.json  |   1 +
 .../chat_loaders/langsmith_dataset.ipynb      | 279 ++++++++++++
 .../chat_loaders/langsmith_llm_runs.ipynb     | 429 ++++++++++++++++++
 .../langchain/chat_loaders/langsmith.py       | 156 +++++++
 libs/langchain/langchain/schema/chat.py       |   4 +-
 libs/langchain/poetry.lock                    |  50 +-
 libs/langchain/pyproject.toml                 |   2 +-
 7 files changed, 882 insertions(+), 39 deletions(-)
 create mode 100644 docs/docs_skeleton/docs/integrations/chat_loaders/example_data/langsmith_chat_dataset.json
 create mode 100644 docs/docs_skeleton/docs/integrations/chat_loaders/langsmith_dataset.ipynb
 create mode 100644 docs/docs_skeleton/docs/integrations/chat_loaders/langsmith_llm_runs.ipynb
 create mode 100644 libs/langchain/langchain/chat_loaders/langsmith.py

diff --git a/docs/docs_skeleton/docs/integrations/chat_loaders/example_data/langsmith_chat_dataset.json b/docs/docs_skeleton/docs/integrations/chat_loaders/example_data/langsmith_chat_dataset.json
new file mode 100644
index 0000000000..e96bcc4a71
--- /dev/null
+++ b/docs/docs_skeleton/docs/integrations/chat_loaders/example_data/langsmith_chat_dataset.json
@@ -0,0 +1 @@
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\"relation\": \"can be\"}, {\"s\": \"[The] residue\", \"object\": \"a fine beef stock\", \"relation\": \"can be [an] ingredient for\"}, {\"s\": \"[The] residue\", \"object\": \"for a fine beef stock\", \"relation\": \"can be [an] ingredient\"}]", "additional_kwargs": {}}, "type": "ai"}, {"data": {"content": "He has been considered several times for appointments to federal district and appellate court vacancies in Pennsylvania .", "additional_kwargs": {}}, "type": "human"}, {"data": {"content": "[{\"s\": \"has been considered several times for\", \"object\": \"appointments to federal district\", \"relation\": \"He\"}, {\"s\": \"has been considered several times for\", \"object\": \"appellate court vacancies\", \"relation\": \"He\"}, {\"s\": \"has been considered several times for appointments to\", \"object\": \"federal district\", \"relation\": \"He\"}, {\"s\": \"has\", \"object\": \"appointments to federal district\", \"relation\": \"Pennsylvania\"}, {\"s\": \"has\", \"object\": \"appellate court vacancies\", \"relation\": \"Pennsylvania\"}]", "additional_kwargs": {}}, "type": "ai"}, {"data": {"content": "Callaghan 's decision on the Japanese pilot 's funeral in 1945 would receive praise years later , although a memorial service aboard the `` Missouri '' in April 2001 attracted controversy .", "additional_kwargs": {}}, "type": "human"}, {"data": {"content": "[{\"s\": \"the Japanese pilot 's funeral\", \"object\": \"Callaghan 's decision\", \"relation\": \"was\"}, {\"s\": \"the Japanese pilot\", \"object\": \"funeral\", \"relation\": \"had a\"}, {\"s\": \"Callaghan 's decision on the Japanese pilot 's funeral\", \"object\": \"years later\", \"relation\": \"would receive praise\"}, {\"s\": \"a memorial service aboard the `` Missouri ''\", \"object\": \"in April 2001\", \"relation\": \"attracted controversy\"}, {\"s\": \"the Japanese pilot\", \"object\": \"memorial service aboard the `` Missouri ''\", \"relation\": \"had a\"}]", "additional_kwargs": {}}, "type": "ai"}, {"data": {"content": "If the second excitation pulse is sent prematurely before the relaxation is complete , the average magnetization vector still points in a nonparallel direction , giving suboptimal absorption and emission of the pulse .", "additional_kwargs": {}}, "type": "human"}]}, "outputs": {"output": {"data": {"content": "[{\"s\": \"the second excitation pulse\", \"object\": \"prematurely\", \"relation\": \"is sent\"}, {\"s\": \"the second excitation pulse\", \"object\": \"before the relaxation is complete\", \"relation\": \"is sent\"}, {\"s\": \"the average magnetization vector\", \"object\": \"in a nonparallel direction\", \"relation\": \"still points\"}, {\"s\": \"the average magnetization vector\", \"object\": \"suboptimal absorption and emission of the pulse\", \"relation\": \"giving\"}]", "additional_kwargs": {}}, "type": "ai"}}}, {"inputs": {"input": [{"data": {"content": "Wide acceptance of zero-energy building technology may require more government incentives or building code regulations , the development of recognized standards , or significant increases in the cost of conventional energy .", "additional_kwargs": {}}, "type": "human"}, {"data": {"content": "[{\"s\": \"Wide acceptance of zero-energy building technology\", \"object\": \"government incentives\", \"relation\": \"may require more\"}, {\"s\": \"Wide acceptance of zero-energy building technology\", \"object\": \"building code regulations\", \"relation\": \"may require more\"}, {\"s\": \"Wide acceptance of zero-energy building technology\", \"object\": \"the development of recognized standards\", \"relation\": \"may require\"}, {\"s\": \"Wide acceptance of zero-energy building technology\", \"object\": \"significant increases in the cost of conventional energy\", \"relation\": \"may require\"}]", "additional_kwargs": {}}, "type": "ai"}, {"data": {"content": "Ms. Waleson is a free - lance writer based in New York .", "additional_kwargs": {}}, "type": "human"}, {"data": {"content": "[{\"s\": \"[Ms.] Waleson\", \"object\": \"a free - lance writer based in New York\", \"relation\": \"is\"}, {\"s\": \"[Ms.] Waleson\", \"object\": \"a free-lance writer based in New York\", \"relation\": \"is\"}, {\"s\": \"[Ms.] Waleson\", \"object\": \"a freelance writer based in New York\", \"relation\": \"is\"}, {\"s\": \"[Ms.] Waleson\", \"object\": \"New York\", \"relation\": \"[is] based in\"}, {\"s\": \"[Ms.] Waleson\", \"object\": \"in New York\", \"relation\": \"[is] based\"}, {\"s\": \"[Ms.] Waleson\", \"object\": \"based in New York\", \"relation\": \"is\"}, {\"s\": \"[a] free-lance writer\", \"object\": \"based in New York\", \"relation\": \"is\"}, {\"s\": \"[a] free-lance writer\", \"object\": \"in New York\", \"relation\": \"[is] based\"}, {\"s\": \"[a] free-lance writer\", \"object\": \"New York\", \"relation\": \"[is] based in\"}, {\"s\": \"[a] free [-] lance writer\", \"object\": \"based in New York\", \"relation\": \"is\"}, {\"s\": \"[a] free [-] lance writer\", \"object\": \"in New York\", \"relation\": \"[is] based\"}, {\"s\": \"[a] free [-] lance writer\", \"object\": \"New York\", \"relation\": \"[is] based in\"}, {\"s\": \"[a] freelance writer\", \"object\": \"based in New York\", \"relation\": \"is\"}, {\"s\": \"[a] freelance writer\", \"object\": \"in New York\", \"relation\": \"[is] based\"}, {\"s\": \"[a] freelance writer\", \"object\": \"New York\", \"relation\": \"[is] based in\"}, {\"s\": \"[Ms.] Waleson\", \"object\": \"New York\", \"relation\": \"is [a] free [-] lance writer based in\"}, {\"s\": \"[Ms.] Waleson\", \"object\": \"in New York\", \"relation\": \"is [a] free [-] lance writer based\"}, {\"s\": \"[Ms.] Waleson\", \"object\": \"New York\", \"relation\": \"is [a] free [-] lance writer based in\"}, {\"s\": \"[Ms.] Waleson\", \"object\": \"based in New York\", \"relation\": \"is [a] free [-] lance writer\"}, {\"s\": \"[Ms.] Waleson\", \"object\": \"New York\", \"relation\": \"is [a] free-lance writer based in\"}, {\"s\": \"[Ms.] Waleson\", \"object\": \"in New York\", \"relation\": \"is [a] free-lance writer based\"}, {\"s\": \"[Ms.] Waleson\", \"object\": \"New York\", \"relation\": \"is [a] free-lance writer based in\"}, {\"s\": \"[Ms.] Waleson\", \"object\": \"based in New York\", \"relation\": \"is [a] free-lance writer\"}]", "additional_kwargs": {}}, "type": "ai"}, {"data": {"content": "The residue can be reprocessed for more dripping and strained through a cheesecloth lined sieve as an ingredient for a fine beef stock .", "additional_kwargs": {}}, "type": "human"}, {"data": {"content": "[{\"s\": \"[The] residue\", \"object\": \"more dripping\", \"relation\": \"can be reprocessed for\"}, {\"s\": \"[The] residue\", \"object\": \"for more dripping\", \"relation\": \"can be reprocessed\"}, {\"s\": \"[The] residue\", \"object\": \"be reprocessed for more dripping\", \"relation\": \"can\"}, {\"s\": \"[The] residue\", \"object\": \"reprocessed for more dripping\", \"relation\": \"can be\"}, {\"s\": \"[The] residue\", \"object\": \"a cheesecloth lined sieve\", \"relation\": \"can be strained through\"}, {\"s\": \"[The] residue\", \"object\": \"be strained through a cheesecloth lined sieve\", \"relation\": \"can\"}, {\"s\": \"[The] residue\", \"object\": \"strained through a cheesecloth lined sieve\", \"relation\": \"can be\"}, {\"s\": \"[The] residue\", \"object\": \"through a cheesecloth lined sieve\", \"relation\": \"can be strained\"}, {\"s\": \"[The] residue\", \"object\": \"an ingredient\", \"relation\": \"can be\"}, {\"s\": \"[The] residue\", \"object\": \"be an ingredient\", \"relation\": \"can\"}, {\"s\": \"[The] residue\", \"object\": \"be an ingredient for a fine beef stock\", \"relation\": \"can\"}, {\"s\": \"[The] residue\", \"object\": \"an ingredient for a fine beef stock\", \"relation\": \"can be\"}, {\"s\": \"[The] residue\", \"object\": \"a fine beef stock\", \"relation\": \"can be [an] ingredient for\"}, {\"s\": \"[The] residue\", \"object\": \"for a fine beef stock\", \"relation\": \"can be [an] ingredient\"}]", "additional_kwargs": {}}, "type": "ai"}, {"data": {"content": "He has been considered several times for appointments to federal district and appellate court vacancies in Pennsylvania .", "additional_kwargs": {}}, "type": "human"}, {"data": {"content": "[{\"s\": \"has been considered several times for\", \"object\": \"appointments to federal district\", \"relation\": \"He\"}, {\"s\": \"has been considered several times for\", \"object\": \"appellate court vacancies\", \"relation\": \"He\"}, {\"s\": \"has been considered several times for appointments to\", \"object\": \"federal district\", \"relation\": \"He\"}, {\"s\": \"has\", \"object\": \"appointments to federal district\", \"relation\": \"Pennsylvania\"}, {\"s\": \"has\", \"object\": \"appellate court vacancies\", \"relation\": \"Pennsylvania\"}]", "additional_kwargs": {}}, "type": "ai"}, {"data": {"content": "Callaghan 's decision on the Japanese pilot 's funeral in 1945 would receive praise years later , although a memorial service aboard the `` Missouri '' in April 2001 attracted controversy .", "additional_kwargs": {}}, "type": "human"}, {"data": {"content": "[{\"s\": \"the Japanese pilot 's funeral\", \"object\": \"Callaghan 's decision\", \"relation\": \"was\"}, {\"s\": \"the Japanese pilot\", \"object\": \"funeral\", \"relation\": \"had a\"}, {\"s\": \"Callaghan 's decision on the Japanese pilot 's funeral\", \"object\": \"years later\", \"relation\": \"would receive praise\"}, {\"s\": \"a memorial service aboard the `` Missouri ''\", \"object\": \"in April 2001\", \"relation\": \"attracted controversy\"}, {\"s\": \"the Japanese pilot\", \"object\": \"memorial service aboard the `` Missouri ''\", \"relation\": \"had a\"}]", "additional_kwargs": {}}, "type": "ai"}, {"data": {"content": "A surprising 78 % of people said they exercise regularly , up from 73 % in 1981 .", "additional_kwargs": {}}, "type": "human"}]}, "outputs": {"output": {"data": {"content": "[{\"s\": \"A surprising 78 % of people\", \"object\": \"they exercise regularly\", \"relation\": \"said\"}, {\"s\": \"A surprising 78 % of people\", \"object\": \"up from 73 % in 1981\", \"relation\": \"said\"}]", "additional_kwargs": {}}, "type": "ai"}}}]
\ No newline at end of file
diff --git a/docs/docs_skeleton/docs/integrations/chat_loaders/langsmith_dataset.ipynb b/docs/docs_skeleton/docs/integrations/chat_loaders/langsmith_dataset.ipynb
new file mode 100644
index 0000000000..2bdd04227c
--- /dev/null
+++ b/docs/docs_skeleton/docs/integrations/chat_loaders/langsmith_dataset.ipynb
@@ -0,0 +1,279 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "a9ab2a39-7c2d-4119-9dc7-8035fdfba3cb",
+   "metadata": {},
+   "source": [
+    "# Fine-Tuning on LangSmith Chat Datasets\n",
+    "\n",
+    "This notebook demonstrates an easy way to load a LangSmith chat dataset fine-tune a model on that data.\n",
+    "The process is simple and comprises 3 steps.\n",
+    "\n",
+    "1. Create the chat dataset.\n",
+    "2. Use the LangSmithDatasetChatLoader to load examples.\n",
+    "3. Fine-tune your model.\n",
+    "\n",
+    "Then you can use the fine-tuned model in your LangChain app.\n",
+    "\n",
+    "Before diving in, let's install our prerequisites.\n",
+    "\n",
+    "## Prerequisites\n",
+    "\n",
+    "Ensure you've installed langchain >= 0.0.311 and have configured your environment with your LangSmith API key."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ef488003-514a-48b4-93f1-7de4417abf5d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%pip install -U langchain openai"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "9fba5c30-9e72-48aa-9535-80f2b3d18ead",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "import uuid\n",
+    "uid = uuid.uuid4().hex[:6]\n",
+    "os.environ[\"LANGCHAIN_TRACING_V2\"] = \"true\"\n",
+    "os.environ[\"LANGCHAIN_API_KEY\"] = \"YOUR API KEY\""
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "8533ab63-d437-492a-aaec-ccca31167bf2",
+   "metadata": {},
+   "source": [
+    "## 1. Select dataset\n",
+    "\n",
+    "This notebook fine-tunes a model directly on a selecting which runs to fine-tune on. You will often curate these from traced runs. You can learn more about LangSmith datasets in the docs [docs](https://docs.smith.langchain.com/evaluation/datasets).\n",
+    "\n",
+    "For the sake of this tutorial, we will upload an existing dataset here that you can use."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "462515e0-872a-446e-abbd-6166d73d7414",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from langsmith.client import Client\n",
+    "\n",
+    "client = Client()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "d384e4ac-5e8f-42a2-8bb5-7d3c9a8a540d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import requests\n",
+    "url = \"https://raw.githubusercontent.com/langchain-ai/langchain/master/docs/docs_skeleton/docs/integrations/chat_loaders/example_data/langsmith_chat_dataset.json\"\n",
+    "response = requests.get(url)\n",
+    "response.raise_for_status()\n",
+    "data = response.json()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "b0d8ae47-2d3f-4b01-b15f-da58bd750fb4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "dataset_name = f\"Extraction Fine-tuning Dataset {uid}\"\n",
+    "ds = client.create_dataset(dataset_name=dataset_name, data_type=\"chat\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "87f085b7-71e1-4ff4-a622-e4e1248aa94a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "_ = client.create_examples(\n",
+    "    inputs = [e['inputs'] for e in data],\n",
+    "    outputs = [e['outputs'] for e in data],\n",
+    "    dataset_id=ds.id,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f365a359-52f7-47ff-8c36-aadc1070b409",
+   "metadata": {},
+   "source": [
+    "## 2. Prepare Data\n",
+    "Now we can create an instance of LangSmithRunChatLoader and load the chat sessions using its lazy_load() method."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "817bc077-c18a-473b-94a4-a7d810d583a8",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from langchain.chat_loaders.langsmith import LangSmithDatasetChatLoader\n",
+    "\n",
+    "loader = LangSmithDatasetChatLoader(dataset_name=dataset_name)\n",
+    "\n",
+    "chat_sessions = loader.lazy_load()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f21a3bbd-1ed4-481b-9640-206b8bf0d751",
+   "metadata": {},
+   "source": [
+    "#### With the chat sessions loaded, convert them into a format suitable for fine-tuning."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "9e5ac127-b094-4584-9159-5a6d3d7315c7",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from langchain.adapters.openai import convert_messages_for_finetuning\n",
+    "\n",
+    "training_data = convert_messages_for_finetuning(chat_sessions)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "188c4978-d85e-4984-a008-a50f6cd6bb84",
+   "metadata": {},
+   "source": [
+    "## 3. Fine-tune the Model\n",
+    "Now, initiate the fine-tuning process using the OpenAI library."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "11d19e28-be49-4801-8065-1a58d13cd192",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Status=[running]... 302.42s. 143.85s\r"
+     ]
+    }
+   ],
+   "source": [
+    "import openai\n",
+    "import time\n",
+    "import json\n",
+    "from io import BytesIO\n",
+    "\n",
+    "my_file = BytesIO()\n",
+    "for dialog in training_data:\n",
+    "    my_file.write((json.dumps({\"messages\": dialog}) + \"\\n\").encode('utf-8'))\n",
+    "\n",
+    "my_file.seek(0)\n",
+    "training_file = openai.File.create(\n",
+    "  file=my_file,\n",
+    "  purpose='fine-tune'\n",
+    ")\n",
+    "\n",
+    "job = openai.FineTuningJob.create(\n",
+    "    training_file=training_file.id,\n",
+    "    model=\"gpt-3.5-turbo\",\n",
+    ")\n",
+    "\n",
+    "# Wait for the fine-tuning to complete (this may take some time)\n",
+    "status = openai.FineTuningJob.retrieve(job.id).status\n",
+    "start_time = time.time()\n",
+    "while status != \"succeeded\":\n",
+    "    print(f\"Status=[{status}]... {time.time() - start_time:.2f}s\", end=\"\\r\", flush=True)\n",
+    "    time.sleep(5)\n",
+    "    status = openai.FineTuningJob.retrieve(job.id).status\n",
+    "\n",
+    "# Now your model is fine-tuned!"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "54c4cead-500d-41dd-8333-2defde634396",
+   "metadata": {},
+   "source": [
+    "## 4. Use in LangChain\n",
+    "\n",
+    "After fine-tuning, use the resulting model ID with the ChatOpenAI model class in your LangChain app."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "3f472ca4-fa9b-485d-bd37-8ce3c59c44db",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Get the fine-tuned model ID\n",
+    "job = openai.FineTuningJob.retrieve(job.id)\n",
+    "model_id = job.fine_tuned_model\n",
+    "\n",
+    "# Use the fine-tuned model in LangChain\n",
+    "model = ChatOpenAI(\n",
+    "    model=model_id,\n",
+    "    temperature=1,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7d3b5845-6385-42d1-9f7d-5ea798dc2cd9",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "model.invoke(\"There were three ravens sat on a tree.\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5b8c2c79-ce27-4f37-b1b2-5977db8c4e84",
+   "metadata": {},
+   "source": [
+    "Now you have successfully fine-tuned a model using data from LangSmith LLM runs!"
+   ]
+  }
+ ],
+ "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
+}
diff --git a/docs/docs_skeleton/docs/integrations/chat_loaders/langsmith_llm_runs.ipynb b/docs/docs_skeleton/docs/integrations/chat_loaders/langsmith_llm_runs.ipynb
new file mode 100644
index 0000000000..35a1fb7492
--- /dev/null
+++ b/docs/docs_skeleton/docs/integrations/chat_loaders/langsmith_llm_runs.ipynb
@@ -0,0 +1,429 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "a9ab2a39-7c2d-4119-9dc7-8035fdfba3cb",
+   "metadata": {},
+   "source": [
+    "# Fine-Tuning on LangSmith LLM Runs\n",
+    "\n",
+    "This notebook demonstrates how to directly load data from LangSmith's LLM runs and fine-tune a model on that data.\n",
+    "The process is simple and comprises 3 steps.\n",
+    "\n",
+    "1. Select the LLM runs to train on.\n",
+    "2. Use the LangSmithRunChatLoader to load runs as chat sessions.\n",
+    "3. Fine-tune your model.\n",
+    "\n",
+    "Then you can use the fine-tuned model in your LangChain app.\n",
+    "\n",
+    "Before diving in, let's install our prerequisites.\n",
+    "\n",
+    "## Prerequisites\n",
+    "\n",
+    "Ensure you've installed langchain >= 0.0.311 and have configured your environment with your LangSmith API key."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "ef488003-514a-48b4-93f1-7de4417abf5d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%pip install -U langchain openai"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "473adce5-c863-49e6-85c3-049e0ec2222e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "import uuid\n",
+    "uid = uuid.uuid4().hex[:6]\n",
+    "project_name = f\"Run Fine-tuning Walkthrough {uid}\"\n",
+    "os.environ[\"LANGCHAIN_TRACING_V2\"] = \"true\"\n",
+    "os.environ[\"LANGCHAIN_API_KEY\"] = \"YOUR API KEY\"\n",
+    "os.environ[\"LANGCHAIN_PROJECT\"] = project_name"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "8533ab63-d437-492a-aaec-ccca31167bf2",
+   "metadata": {},
+   "source": [
+    "## 1. Select Runs\n",
+    "The first step is selecting which runs to fine-tune on. A common case would be to select LLM runs within\n",
+    "traces that have received positive user feedback. You can find examples of this in the[LangSmith Cookbook](https://github.com/langchain-ai/langsmith-cookbook/blob/main/exploratory-data-analysis/exporting-llm-runs-and-feedback/llm_run_etl.ipynb) and in the [docs](https://docs.smith.langchain.com/tracing/use-cases/export-runs/local).\n",
+    "\n",
+    "For the sake of this tutorial, we will generate some runs for you to use here. Let's try fine-tuning a\n",
+    "simple function-calling chain."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "9a36d27f-2f3b-4148-b94a-9436fe8b00e0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from langchain.pydantic_v1 import BaseModel, Field\n",
+    "from enum import Enum\n",
+    "\n",
+    "\n",
+    "class Operation(Enum):\n",
+    "    add = \"+\"\n",
+    "    subtract = \"-\"\n",
+    "    multiply = \"*\"\n",
+    "    divide = \"/\"\n",
+    "\n",
+    "class Calculator(BaseModel):\n",
+    "    \"\"\"A calculator function\"\"\"\n",
+    "    num1: float\n",
+    "    num2: float\n",
+    "    operation: Operation = Field(..., description=\"+,-,*,/\")\n",
+    "\n",
+    "    def calculate(self):\n",
+    "        if self.operation == Operation.add:\n",
+    "            return self.num1 + self.num2\n",
+    "        elif self.operation == Operation.subtract:\n",
+    "            return self.num1 - self.num2\n",
+    "        elif self.operation == Operation.multiply:\n",
+    "            return self.num1 * self.num2\n",
+    "        elif self.operation == Operation.divide:\n",
+    "            if self.num2 != 0:\n",
+    "                return self.num1 / self.num2\n",
+    "            else:\n",
+    "                return \"Cannot divide by zero\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "89bcc676-27e8-40dc-a4d6-92cf28e0db58",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'description': 'A calculator function',\n",
+      " 'name': 'Calculator',\n",
+      " 'parameters': {'description': 'A calculator function',\n",
+      "                'properties': {'num1': {'title': 'Num1', 'type': 'number'},\n",
+      "                               'num2': {'title': 'Num2', 'type': 'number'},\n",
+      "                               'operation': {'allOf': [{'description': 'An '\n",
+      "                                                                       'enumeration.',\n",
+      "                                                        'enum': ['+',\n",
+      "                                                                 '-',\n",
+      "                                                                 '*',\n",
+      "                                                                 '/'],\n",
+      "                                                        'title': 'Operation'}],\n",
+      "                                             'description': '+,-,*,/'}},\n",
+      "                'required': ['num1', 'num2', 'operation'],\n",
+      "                'title': 'Calculator',\n",
+      "                'type': 'object'}}\n"
+     ]
+    }
+   ],
+   "source": [
+    "from langchain.utils.openai_functions import convert_pydantic_to_openai_function\n",
+    "from langchain.pydantic_v1 import BaseModel\n",
+    "from pprint import pprint\n",
+    "\n",
+    "openai_function_def = convert_pydantic_to_openai_function(Calculator)\n",
+    "pprint(openai_function_def)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "cd44ff01-22cf-431a-8bf4-29a758d1fcff",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from langchain.prompts import ChatPromptTemplate\n",
+    "from langchain.chat_models import ChatOpenAI\n",
+    "from langchain.output_parsers.openai_functions import PydanticOutputFunctionsParser\n",
+    "\n",
+    "prompt = ChatPromptTemplate.from_messages(\n",
+    "    [\n",
+    "        (\"system\", \"You are an accounting assistant.\"),\n",
+    "        (\"user\", \"{input}\"),\n",
+    "    ]\n",
+    ")\n",
+    "chain = (\n",
+    "    prompt\n",
+    "    | ChatOpenAI().bind(functions=[openai_function_def])\n",
+    "    | PydanticOutputFunctionsParser(pydantic_schema=Calculator)\n",
+    "    | (lambda x: x.calculate())\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "62da7d8f-5cfc-45a6-946e-2bcda2b0ba1f",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Retrying langchain.chat_models.openai.ChatOpenAI.completion_with_retry.<locals>._completion_with_retry in 4.0 seconds as it raised ServiceUnavailableError: The server is overloaded or not ready yet..\n"
+     ]
+    }
+   ],
+   "source": [
+    "math_questions = [\n",
+    "    \"What's 45/9?\",\n",
+    "    \"What's 81/9?\",\n",
+    "    \"What's 72/8?\",\n",
+    "    \"What's 56/7?\",\n",
+    "    \"What's 36/6?\",\n",
+    "    \"What's 64/8?\",\n",
+    "    \"What's 12*6?\",\n",
+    "    \"What's 8*8?\",\n",
+    "    \"What's 10*10?\",\n",
+    "    \"What's 11*11?\",\n",
+    "    \"What's 13*13?\",\n",
+    "    \"What's 45+30?\",\n",
+    "    \"What's 72+28?\",\n",
+    "    \"What's 56+44?\",\n",
+    "    \"What's 63+37?\",\n",
+    "    \"What's 70-35?\",\n",
+    "    \"What's 60-30?\",\n",
+    "    \"What's 50-25?\",\n",
+    "    \"What's 40-20?\",\n",
+    "    \"What's 30-15?\"\n",
+    "]\n",
+    "results = chain.batch([{\"input\": q} for q in math_questions], return_exceptions=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "cbb1bcae-b922-4d38-b4bd-4b65be400b88",
+   "metadata": {},
+   "source": [
+    "#### Load runs that did not error\n",
+    "\n",
+    "Now we can select the successful runs to fine-tune on."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "d6037992-050d-4ada-a061-860c124f0bf1",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from langsmith.client import Client\n",
+    "\n",
+    "client = Client()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "0444919a-6f5a-4726-9916-4603b1420d0e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "successful_traces = {\n",
+    "    run.trace_id\n",
+    "    for run in client.list_runs(\n",
+    "        project_name=project_name,\n",
+    "        execution_order=1,\n",
+    "        error=False,\n",
+    "    )\n",
+    "}\n",
+    "    \n",
+    "llm_runs = [\n",
+    "    run for run in client.list_runs(\n",
+    "        project_name=project_name,\n",
+    "        run_type=\"llm\",\n",
+    "    ) \n",
+    "    if run.trace_id in successful_traces\n",
+    "]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f365a359-52f7-47ff-8c36-aadc1070b409",
+   "metadata": {},
+   "source": [
+    "## 2. Prepare data\n",
+    "Now we can create an instance of LangSmithRunChatLoader and load the chat sessions using its lazy_load() method."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "817bc077-c18a-473b-94a4-a7d810d583a8",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from langchain.chat_loaders.langsmith import LangSmithRunChatLoader\n",
+    "\n",
+    "loader = LangSmithRunChatLoader(runs=llm_runs)\n",
+    "\n",
+    "chat_sessions = loader.lazy_load()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f21a3bbd-1ed4-481b-9640-206b8bf0d751",
+   "metadata": {},
+   "source": [
+    "#### With the chat sessions loaded, convert them into a format suitable for fine-tuning."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "9e5ac127-b094-4584-9159-5a6d3d7315c7",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from langchain.adapters.openai import convert_messages_for_finetuning\n",
+    "\n",
+    "training_data = convert_messages_for_finetuning(chat_sessions)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "188c4978-d85e-4984-a008-a50f6cd6bb84",
+   "metadata": {},
+   "source": [
+    "## 3. Fine-tune the model\n",
+    "Now, initiate the fine-tuning process using the OpenAI library."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "11d19e28-be49-4801-8065-1a58d13cd192",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Status=[running]... 346.26s. 31.70s\r"
+     ]
+    }
+   ],
+   "source": [
+    "import openai\n",
+    "import time\n",
+    "import json\n",
+    "from io import BytesIO\n",
+    "\n",
+    "my_file = BytesIO()\n",
+    "for dialog in training_data:\n",
+    "    my_file.write((json.dumps({\"messages\": dialog}) + \"\\n\").encode('utf-8'))\n",
+    "\n",
+    "my_file.seek(0)\n",
+    "training_file = openai.File.create(\n",
+    "  file=my_file,\n",
+    "  purpose='fine-tune'\n",
+    ")\n",
+    "\n",
+    "job = openai.FineTuningJob.create(\n",
+    "    training_file=training_file.id,\n",
+    "    model=\"gpt-3.5-turbo\",\n",
+    ")\n",
+    "\n",
+    "# Wait for the fine-tuning to complete (this may take some time)\n",
+    "status = openai.FineTuningJob.retrieve(job.id).status\n",
+    "start_time = time.time()\n",
+    "while status != \"succeeded\":\n",
+    "    print(f\"Status=[{status}]... {time.time() - start_time:.2f}s\", end=\"\\r\", flush=True)\n",
+    "    time.sleep(5)\n",
+    "    status = openai.FineTuningJob.retrieve(job.id).status\n",
+    "\n",
+    "# Now your model is fine-tuned!"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "54c4cead-500d-41dd-8333-2defde634396",
+   "metadata": {},
+   "source": [
+    "## 4. Use in LangChain\n",
+    "\n",
+    "After fine-tuning, use the resulting model ID with the ChatOpenAI model class in your LangChain app."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "7f45b281-1dfa-43cb-bd28-99fa7e9f45d1",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Get the fine-tuned model ID\n",
+    "job = openai.FineTuningJob.retrieve(job.id)\n",
+    "model_id = job.fine_tuned_model\n",
+    "\n",
+    "# Use the fine-tuned model in LangChain\n",
+    "model = ChatOpenAI(\n",
+    "    model=model_id,\n",
+    "    temperature=1,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "7d3b5845-6385-42d1-9f7d-5ea798dc2cd9",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "AIMessage(content='{\\n  \"num1\": 56,\\n  \"num2\": 7,\\n  \"operation\": \"/\"\\n}')"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "(prompt | model).invoke({\"input\": \"What's 56/7?\"})"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5b8c2c79-ce27-4f37-b1b2-5977db8c4e84",
+   "metadata": {},
+   "source": [
+    "Now you have successfully fine-tuned a model using data from LangSmith LLM runs!"
+   ]
+  }
+ ],
+ "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
+}
diff --git a/libs/langchain/langchain/chat_loaders/langsmith.py b/libs/langchain/langchain/chat_loaders/langsmith.py
new file mode 100644
index 0000000000..db9b85ea85
--- /dev/null
+++ b/libs/langchain/langchain/chat_loaders/langsmith.py
@@ -0,0 +1,156 @@
+from __future__ import annotations
+
+import logging
+from typing import TYPE_CHECKING, Dict, Iterable, Iterator, List, Optional, Union
+
+from langchain.chat_loaders.base import BaseChatLoader
+from langchain.load import load
+from langchain.schema.chat import ChatSession
+
+if TYPE_CHECKING:
+    from langsmith.client import Client
+    from langsmith.schemas import Run
+
+logger = logging.getLogger(__name__)
+
+
+class LangSmithRunChatLoader(BaseChatLoader):
+    """
+    Load chat sessions from a list of LangSmith "llm" runs.
+
+    Attributes:
+        runs (Iterable[Union[str, Run]]): The list of LLM run IDs or run objects.
+        client (Client): Instance of LangSmith client for fetching data.
+    """
+
+    def __init__(
+        self, runs: Iterable[Union[str, Run]], client: Optional["Client"] = None
+    ):
+        """
+        Initialize a new LangSmithRunChatLoader instance.
+
+        :param runs: List of LLM run IDs or run objects.
+        :param client: An instance of LangSmith client, if not provided,
+            a new client instance will be created.
+        """
+        from langsmith.client import Client
+
+        self.runs = runs
+        self.client = client or Client()
+
+    def _load_single_chat_session(self, llm_run: "Run") -> ChatSession:
+        """
+        Convert an individual LangSmith LLM run to a ChatSession.
+
+        :param llm_run: The LLM run object.
+        :return: A chat session representing the run's data.
+        """
+        chat_session = LangSmithRunChatLoader._get_messages_from_llm_run(llm_run)
+        functions = LangSmithRunChatLoader._get_functions_from_llm_run(llm_run)
+        if functions:
+            chat_session["functions"] = functions
+        return chat_session
+
+    @staticmethod
+    def _get_messages_from_llm_run(llm_run: "Run") -> ChatSession:
+        """
+        Extract messages from a LangSmith LLM run.
+
+        :param llm_run: The LLM run object.
+        :return: ChatSession with the extracted messages.
+        """
+        if llm_run.run_type != "llm":
+            raise ValueError(f"Expected run of type llm. Got: {llm_run.run_type}")
+        if "messages" not in llm_run.inputs:
+            raise ValueError(f"Run has no 'messages' inputs. Got {llm_run.inputs}")
+        if not llm_run.outputs:
+            raise ValueError("Cannot convert pending run")
+        messages = load(llm_run.inputs)["messages"]
+        message_chunk = load(llm_run.outputs)["generations"][0]["message"]
+        return ChatSession(messages=messages + [message_chunk])
+
+    @staticmethod
+    def _get_functions_from_llm_run(llm_run: "Run") -> Optional[List[Dict]]:
+        """
+        Extract functions from a LangSmith LLM run if they exist.
+
+        :param llm_run: The LLM run object.
+        :return: Functions from the run or None.
+        """
+        if llm_run.run_type != "llm":
+            raise ValueError(f"Expected run of type llm. Got: {llm_run.run_type}")
+        return llm_run.extra.get("invocation_params", {}).get("functions")
+
+    def lazy_load(self) -> Iterator[ChatSession]:
+        """
+        Lazy load the chat sessions from the iterable of run IDs.
+
+        This method fetches the runs and converts them to chat sessions on-the-fly,
+        yielding one session at a time.
+
+        :return: Iterator of chat sessions containing messages.
+        """
+        for run_obj in self.runs:
+            try:
+                if hasattr(run_obj, "id"):
+                    run = run_obj
+                else:
+                    run = self.client.read_run(run_obj)
+                session = self._load_single_chat_session(run)
+                yield session
+            except ValueError as e:
+                logger.warning(f"Could not load run {run_obj}: {repr(e)}")
+                continue
+
+
+class LangSmithDatasetChatLoader(BaseChatLoader):
+    """
+    Load chat sessions from a LangSmith dataset with the "chat" data type.
+
+    Attributes:
+        dataset_name (str): The name of the LangSmith dataset.
+        client (Client): Instance of LangSmith client for fetching data.
+    """
+
+    def __init__(self, *, dataset_name: str, client: Optional["Client"] = None):
+        """
+        Initialize a new LangSmithChatDatasetLoader instance.
+
+        :param dataset_name: The name of the LangSmith dataset.
+        :param client: An instance of LangSmith client; if not provided,
+            a new client instance will be created.
+        """
+        try:
+            from langsmith.client import Client
+        except ImportError as e:
+            raise ImportError(
+                "The LangSmith client is required to load LangSmith datasets.\n"
+                "Please install it with `pip install langsmith`"
+            ) from e
+
+        self.dataset_name = dataset_name
+        self.client = client or Client()
+
+    def lazy_load(self) -> Iterator[ChatSession]:
+        """
+        Lazy load the chat sessions from the specified LangSmith dataset.
+
+        This method fetches the chat data from the dataset and
+        converts each data point to chat sessions on-the-fly,
+        yielding one session at a time.
+
+        :return: Iterator of chat sessions containing messages.
+        """
+        from langchain.adapters import openai as oai_adapter  # noqa: E402
+
+        data = self.client.read_dataset_openai_finetuning(
+            dataset_name=self.dataset_name
+        )
+        for data_point in data:
+            yield ChatSession(
+                messages=[
+                    oai_adapter.convert_dict_to_message(m)
+                    for m in data_point.get("messages", [])
+                ],
+                functions=data_point.get("functions"),
+            )
diff --git a/libs/langchain/langchain/schema/chat.py b/libs/langchain/langchain/schema/chat.py
index 659e734853..f76194f4f8 100644
--- a/libs/langchain/langchain/schema/chat.py
+++ b/libs/langchain/langchain/schema/chat.py
@@ -3,9 +3,11 @@ from typing import Sequence, TypedDict
 from langchain.schema import BaseMessage
 
 
-class ChatSession(TypedDict):
+class ChatSession(TypedDict, total=False):
     """Chat Session represents a single
     conversation, channel, or other group of messages."""
 
     messages: Sequence[BaseMessage]
     """The LangChain chat messages loaded from the source."""
+    functions: Sequence[dict]
+    """The function calling specs for the messages."""
diff --git a/libs/langchain/poetry.lock b/libs/langchain/poetry.lock
index 4ebd7042c9..fc211d1f4e 100644
--- a/libs/langchain/poetry.lock
+++ b/libs/langchain/poetry.lock
@@ -1,4 +1,4 @@
-# This file is automatically @generated by Poetry 1.6.1 and should not be changed by hand.
+# This file is automatically @generated by Poetry 1.5.1 and should not be changed by hand.
 
 [[package]]
 name = "absl-py"
@@ -2884,7 +2884,6 @@ files = [
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@@ -2893,7 +2892,6 @@ files = [
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@@ -2923,7 +2921,6 @@ files = [
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@@ -2932,7 +2929,6 @@ files = [
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-    {file = "greenlet-2.0.2-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:8512a0c38cfd4e66a858ddd1b17705587900dd760c6003998e9472b77b56d417"},
     {file = "greenlet-2.0.2-cp39-cp39-macosx_11_0_x86_64.whl", hash = "sha256:88d9ab96491d38a5ab7c56dd7a3cc37d83336ecc564e4e8816dbed12e5aaefc8"},
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@@ -3726,7 +3722,6 @@ optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*, !=3.6.*"
 files = [
     {file = "jsonpointer-2.4-py2.py3-none-any.whl", hash = "sha256:15d51bba20eea3165644553647711d150376234112651b4f1811022aecad7d7a"},
-    {file = "jsonpointer-2.4.tar.gz", hash = "sha256:585cee82b70211fa9e6043b7bb89db6e1aa49524340dde8ad6b63206ea689d88"},
 ]
 
 [[package]]
@@ -4095,13 +4090,13 @@ all = ["datasets (>=2.12.0,<3.0.0)", "evaluate (>=0.4.0,<0.5.0)", "faiss-cpu (>=
 
 [[package]]
 name = "langsmith"
-version = "0.0.41"
+version = "0.0.43"
 description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform."
 optional = false
 python-versions = ">=3.8.1,<4.0"
 files = [
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-    {file = "langsmith-0.0.41.tar.gz", hash = "sha256:ea05649bb140d6e58614e171df6539410b77ce393c23545453278677e916e351"},
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+    {file = "langsmith-0.0.43.tar.gz", hash = "sha256:f7705f13eb8ce3b8eb16c4d2b2760c62cfb9a3b3ab6aa0728afa84d26b2a6e55"},
 ]
 
 [package.dependencies]
@@ -4534,16 +4529,6 @@ files = [
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-    {file = "MarkupSafe-2.1.3-cp312-cp312-win_amd64.whl", hash = "sha256:1b8dd8c3fd14349433c79fa8abeb573a55fc0fdd769133baac1f5e07abf54aeb"},
     {file = "MarkupSafe-2.1.3-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:8e254ae696c88d98da6555f5ace2279cf7cd5b3f52be2b5cf97feafe883b58d2"},
     {file = "MarkupSafe-2.1.3-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:cb0932dc158471523c9637e807d9bfb93e06a95cbf010f1a38b98623b929ef2b"},
     {file = "MarkupSafe-2.1.3-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:9402b03f1a1b4dc4c19845e5c749e3ab82d5078d16a2a4c2cd2df62d57bb0707"},
@@ -5783,11 +5768,12 @@ files = [
 
 [package.dependencies]
 numpy = [
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-    {version = ">=1.19.3", markers = "platform_system == \"Linux\" and platform_machine == \"aarch64\" and python_version >= \"3.8\" and python_version < \"3.10\" or python_version > \"3.9\" and python_version < \"3.10\" or python_version >= \"3.9\" and platform_system != \"Darwin\" and python_version < \"3.10\" or python_version >= \"3.9\" and platform_machine != \"arm64\" and python_version < \"3.10\""},
-    {version = ">=1.17.3", markers = "(platform_system != \"Darwin\" and platform_system != \"Linux\") and python_version >= \"3.8\" and python_version < \"3.9\" or platform_system != \"Darwin\" and python_version >= \"3.8\" and python_version < \"3.9\" and platform_machine != \"aarch64\" or platform_machine != \"arm64\" and python_version >= \"3.8\" and python_version < \"3.9\" and platform_system != \"Linux\" or (platform_machine != \"arm64\" and platform_machine != \"aarch64\") and python_version >= \"3.8\" and python_version < \"3.9\""},
-    {version = ">=1.21.4", markers = "python_version >= \"3.10\" and platform_system == \"Darwin\" and python_version < \"3.11\""},
-    {version = ">=1.21.2", markers = "platform_system != \"Darwin\" and python_version >= \"3.10\" and python_version < \"3.11\""},
+    {version = ">=1.21.0", markers = "python_version <= \"3.9\" and platform_system == \"Darwin\" and platform_machine == \"arm64\""},
+    {version = ">=1.19.3", markers = "python_version >= \"3.6\" and platform_system == \"Linux\" and platform_machine == \"aarch64\" or python_version >= \"3.9\""},
+    {version = ">=1.17.0", markers = "python_version >= \"3.7\""},
+    {version = ">=1.17.3", markers = "python_version >= \"3.8\""},
+    {version = ">=1.21.2", markers = "python_version >= \"3.10\""},
+    {version = ">=1.21.4", markers = "python_version >= \"3.10\" and platform_system == \"Darwin\""},
     {version = ">=1.23.5", markers = "python_version >= \"3.11\""},
 ]
 
@@ -5975,7 +5961,7 @@ files = [
 [package.dependencies]
 numpy = [
     {version = ">=1.20.3", markers = "python_version < \"3.10\""},
-    {version = ">=1.21.0", markers = "python_version >= \"3.10\" and python_version < \"3.11\""},
+    {version = ">=1.21.0", markers = "python_version >= \"3.10\""},
     {version = ">=1.23.2", markers = "python_version >= \"3.11\""},
 ]
 python-dateutil = ">=2.8.2"
@@ -7643,7 +7629,6 @@ files = [
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-    {file = "PyYAML-6.0.1-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:326c013efe8048858a6d312ddd31d56e468118ad4cdeda36c719bf5bb6192290"},
     {file = "PyYAML-6.0.1-cp310-cp310-win32.whl", hash = "sha256:bd4af7373a854424dabd882decdc5579653d7868b8fb26dc7d0e99f823aa5924"},
     {file = "PyYAML-6.0.1-cp310-cp310-win_amd64.whl", hash = "sha256:fd1592b3fdf65fff2ad0004b5e363300ef59ced41c2e6b3a99d4089fa8c5435d"},
     {file = "PyYAML-6.0.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:6965a7bc3cf88e5a1c3bd2e0b5c22f8d677dc88a455344035f03399034eb3007"},
@@ -7651,15 +7636,8 @@ files = [
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-    {file = "PyYAML-6.0.1-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:e7d73685e87afe9f3b36c799222440d6cf362062f78be1013661b00c5c6f678b"},
     {file = "PyYAML-6.0.1-cp311-cp311-win32.whl", hash = "sha256:1635fd110e8d85d55237ab316b5b011de701ea0f29d07611174a1b42f1444741"},
     {file = "PyYAML-6.0.1-cp311-cp311-win_amd64.whl", hash = "sha256:bf07ee2fef7014951eeb99f56f39c9bb4af143d8aa3c21b1677805985307da34"},
-    {file = "PyYAML-6.0.1-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:855fb52b0dc35af121542a76b9a84f8d1cd886ea97c84703eaa6d88e37a2ad28"},
-    {file = "PyYAML-6.0.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:40df9b996c2b73138957fe23a16a4f0ba614f4c0efce1e9406a184b6d07fa3a9"},
-    {file = "PyYAML-6.0.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6c22bec3fbe2524cde73d7ada88f6566758a8f7227bfbf93a408a9d86bcc12a0"},
-    {file = "PyYAML-6.0.1-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:8d4e9c88387b0f5c7d5f281e55304de64cf7f9c0021a3525bd3b1c542da3b0e4"},
-    {file = "PyYAML-6.0.1-cp312-cp312-win32.whl", hash = "sha256:d483d2cdf104e7c9fa60c544d92981f12ad66a457afae824d146093b8c294c54"},
-    {file = "PyYAML-6.0.1-cp312-cp312-win_amd64.whl", hash = "sha256:0d3304d8c0adc42be59c5f8a4d9e3d7379e6955ad754aa9d6ab7a398b59dd1df"},
     {file = "PyYAML-6.0.1-cp36-cp36m-macosx_10_9_x86_64.whl", hash = "sha256:50550eb667afee136e9a77d6dc71ae76a44df8b3e51e41b77f6de2932bfe0f47"},
     {file = "PyYAML-6.0.1-cp36-cp36m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:1fe35611261b29bd1de0070f0b2f47cb6ff71fa6595c077e42bd0c419fa27b98"},
     {file = "PyYAML-6.0.1-cp36-cp36m-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:704219a11b772aea0d8ecd7058d0082713c3562b4e271b849ad7dc4a5c90c13c"},
@@ -7676,7 +7654,6 @@ files = [
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     {file = "PyYAML-6.0.1-cp38-cp38-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:28c119d996beec18c05208a8bd78cbe4007878c6dd15091efb73a30e90539696"},
     {file = "PyYAML-6.0.1-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:7e07cbde391ba96ab58e532ff4803f79c4129397514e1413a7dc761ccd755735"},
-    {file = "PyYAML-6.0.1-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:49a183be227561de579b4a36efbb21b3eab9651dd81b1858589f796549873dd6"},
     {file = "PyYAML-6.0.1-cp38-cp38-win32.whl", hash = "sha256:184c5108a2aca3c5b3d3bf9395d50893a7ab82a38004c8f61c258d4428e80206"},
     {file = "PyYAML-6.0.1-cp38-cp38-win_amd64.whl", hash = "sha256:1e2722cc9fbb45d9b87631ac70924c11d3a401b2d7f410cc0e3bbf249f2dca62"},
     {file = "PyYAML-6.0.1-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:9eb6caa9a297fc2c2fb8862bc5370d0303ddba53ba97e71f08023b6cd73d16a8"},
@@ -7684,7 +7661,6 @@ files = [
     {file = "PyYAML-6.0.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:5773183b6446b2c99bb77e77595dd486303b4faab2b086e7b17bc6bef28865f6"},
     {file = "PyYAML-6.0.1-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:b786eecbdf8499b9ca1d697215862083bd6d2a99965554781d0d8d1ad31e13a0"},
     {file = "PyYAML-6.0.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bc1bf2925a1ecd43da378f4db9e4f799775d6367bdb94671027b73b393a7c42c"},
-    {file = "PyYAML-6.0.1-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:04ac92ad1925b2cff1db0cfebffb6ffc43457495c9b3c39d3fcae417d7125dc5"},
     {file = "PyYAML-6.0.1-cp39-cp39-win32.whl", hash = "sha256:faca3bdcf85b2fc05d06ff3fbc1f83e1391b3e724afa3feba7d13eeab355484c"},
     {file = "PyYAML-6.0.1-cp39-cp39-win_amd64.whl", hash = "sha256:510c9deebc5c0225e8c96813043e62b680ba2f9c50a08d3724c7f28a747d1486"},
     {file = "PyYAML-6.0.1.tar.gz", hash = "sha256:bfdf460b1736c775f2ba9f6a92bca30bc2095067b8a9d77876d1fad6cc3b4a43"},
@@ -9038,7 +9014,7 @@ files = [
 ]
 
 [package.dependencies]
-greenlet = {version = "!=0.4.17", markers = "platform_machine == \"aarch64\" or platform_machine == \"ppc64le\" or platform_machine == \"x86_64\" or platform_machine == \"amd64\" or platform_machine == \"AMD64\" or platform_machine == \"win32\" or platform_machine == \"WIN32\""}
+greenlet = {version = "!=0.4.17", markers = "platform_machine == \"win32\" or platform_machine == \"WIN32\" or platform_machine == \"AMD64\" or platform_machine == \"amd64\" or platform_machine == \"x86_64\" or platform_machine == \"ppc64le\" or platform_machine == \"aarch64\""}
 typing-extensions = ">=4.2.0"
 
 [package.extras]
@@ -10873,4 +10849,4 @@ text-helpers = ["chardet"]
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.8.1,<4.0"
-content-hash = "8458ce2704b1fcba33f5b6bb8cb3d6fdf4d6b9a2006563f461a3edf7b8dd0d17"
+content-hash = "e25dfb2dbe4090086ccaa9f483d75bed50fa65bb196dd5e63fd9f819d71d03f6"
diff --git a/libs/langchain/pyproject.toml b/libs/langchain/pyproject.toml
index 1d34cc3979..b9cf1622a4 100644
--- a/libs/langchain/pyproject.toml
+++ b/libs/langchain/pyproject.toml
@@ -115,7 +115,7 @@ cassio = {version = "^0.1.0", optional = true}
 rdflib = {version = "^6.3.2", optional = true}
 sympy = {version = "^1.12", optional = true}
 rapidfuzz = {version = "^3.1.1", optional = true}
-langsmith = "~0.0.40"
+langsmith = "~0.0.43"
 rank-bm25 = {version = "^0.2.2", optional = true}
 amadeus = {version = ">=8.1.0", optional = true}
 geopandas = {version = "^0.13.1", optional = true}