Merge branch 'master' into bagatur/community

2026-02-04 00:00:34 +00:00 · 2023-12-08 09:14:06 -08:00
parent b46802ad88 a05230a4ba
commit 0de98e7830
40 changed files with 282 additions and 179 deletions
--- a/cookbook/multi_modal_output_agent.ipynb
+++ b/cookbook/multi_modal_output_agent.ipynb
@@ -31,7 +31,7 @@
   "source": [
    "import re\n",
    "\n",
-    "from IPython.display import Image\n",
+    "from IPython.display import Image, display\n",
    "from steamship import Block, Steamship"
   ]
  },
@@ -180,7 +180,7 @@
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
-   "version": "3.11.3"
+   "version": "3.10.12"
  }
 },
 "nbformat": 4,
--- a/cookbook/qianfan_baidu_elasticesearch_RAG.ipynb
+++ b/cookbook/qianfan_baidu_elasticesearch_RAG.ipynb
@@ -37,7 +37,8 @@
   "source": [
    "#!pip install qianfan\n",
    "#!pip install bce-python-sdk\n",
-    "#!pip install elasticsearch == 7.11.0"
+    "#!pip install elasticsearch == 7.11.0\n",
+    "#!pip install sentence-transformers"
   ]
  },
  {
@@ -54,8 +55,10 @@
   "metadata": {},
   "outputs": [],
   "source": [
+    "import sentence_transformers\n",
    "from baidubce.auth.bce_credentials import BceCredentials\n",
    "from baidubce.bce_client_configuration import BceClientConfiguration\n",
+    "from langchain.chains.retrieval_qa import RetrievalQA\n",
    "from langchain.document_loaders.baiducloud_bos_directory import BaiduBOSDirectoryLoader\n",
    "from langchain.embeddings.huggingface import HuggingFaceEmbeddings\n",
    "from langchain.llms.baidu_qianfan_endpoint import QianfanLLMEndpoint\n",
@@ -161,15 +164,22 @@
 ],
 "metadata": {
  "kernelspec": {
-   "display_name": "Python 3",
+   "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",
-   "version": "3.9.17"
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.12"
  },
-  "orig_nbformat": 4,
  "vscode": {
   "interpreter": {
    "hash": "aee8b7b246df8f9039afb4144a1f6fd8d2ca17a180786b69acc140d282b71a49"
@@ -177,5 +187,5 @@
  }
 },
 "nbformat": 4,
- "nbformat_minor": 2
+ "nbformat_minor": 4
 }
--- a/cookbook/retrieval_in_sql.ipynb
+++ b/cookbook/retrieval_in_sql.ipynb
@@ -133,7 +133,7 @@
    "from tqdm import tqdm\n",
    "\n",
    "for i in tqdm(range(len(title_embeddings))):\n",
-    "    title = titles[i].replace(\"'\", \"''\")\n",
+    "    title = song_titles[i].replace(\"'\", \"''\")\n",
    "    embedding = title_embeddings[i]\n",
    "    sql_command = (\n",
    "        f'UPDATE \"Track\" SET \"embeddings\" = ARRAY{embedding} WHERE \"Name\" ='\n",
@@ -681,9 +681,9 @@
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
-   "version": "3.8.18"
+   "version": "3.10.12"
  }
 },
 "nbformat": 4,
- "nbformat_minor": 2
+ "nbformat_minor": 4
 }
--- a/cookbook/wikibase_agent.ipynb
+++ b/cookbook/wikibase_agent.ipynb
@@ -187,7 +187,7 @@
    "    for key in path:\n",
    "        try:\n",
    "            current = current[key]\n",
-    "        except:\n",
+    "        except KeyError:\n",
    "            return None\n",
    "    return current\n",
    "\n",
--- a/docs/docs/expression_language/how_to/fallbacks.ipynb
+++ b/docs/docs/expression_language/how_to/fallbacks.ipynb
@@ -91,7 +91,7 @@
    "with patch(\"openai.resources.chat.completions.Completions.create\", side_effect=error):\n",
    "    try:\n",
    "        print(openai_llm.invoke(\"Why did the chicken cross the road?\"))\n",
-    "    except:\n",
+    "    except RateLimitError:\n",
    "        print(\"Hit error\")"
   ]
  },
@@ -114,7 +114,7 @@
    "with patch(\"openai.resources.chat.completions.Completions.create\", side_effect=error):\n",
    "    try:\n",
    "        print(llm.invoke(\"Why did the chicken cross the road?\"))\n",
-    "    except:\n",
+    "    except RateLimitError:\n",
    "        print(\"Hit error\")"
   ]
  },
@@ -156,7 +156,7 @@
    "with patch(\"openai.resources.chat.completions.Completions.create\", side_effect=error):\n",
    "    try:\n",
    "        print(chain.invoke({\"animal\": \"kangaroo\"}))\n",
-    "    except:\n",
+    "    except RateLimitError:\n",
    "        print(\"Hit error\")"
   ]
  },
@@ -190,10 +190,10 @@
    ")\n",
    "\n",
    "chain = prompt | llm\n",
-    "with patch(\"openai.ChatCompletion.create\", side_effect=error):\n",
+    "with patch(\"openai.resources.chat.completions.Completions.create\", side_effect=error):\n",
    "    try:\n",
    "        print(chain.invoke({\"animal\": \"kangaroo\"}))\n",
-    "    except:\n",
+    "    except RateLimitError:\n",
    "        print(\"Hit error\")"
   ]
  },
@@ -291,7 +291,7 @@
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
-   "version": "3.11.5"
+   "version": "3.10.12"
  }
 },
 "nbformat": 4,
--- a/docs/docs/guides/fallbacks.ipynb
+++ b/docs/docs/guides/fallbacks.ipynb
@@ -93,7 +93,7 @@
    "with patch(\"openai.resources.chat.completions.Completions.create\", side_effect=error):\n",
    "    try:\n",
    "        print(openai_llm.invoke(\"Why did the chicken cross the road?\"))\n",
-    "    except:\n",
+    "    except RateLimitError:\n",
    "        print(\"Hit error\")"
   ]
  },
@@ -116,7 +116,7 @@
    "with patch(\"openai.resources.chat.completions.Completions.create\", side_effect=error):\n",
    "    try:\n",
    "        print(llm.invoke(\"Why did the chicken cross the road?\"))\n",
-    "    except:\n",
+    "    except RateLimitError:\n",
    "        print(\"Hit error\")"
   ]
  },
@@ -158,7 +158,7 @@
    "with patch(\"openai.resources.chat.completions.Completions.create\", side_effect=error):\n",
    "    try:\n",
    "        print(chain.invoke({\"animal\": \"kangaroo\"}))\n",
-    "    except:\n",
+    "    except RateLimitError:\n",
    "        print(\"Hit error\")"
   ]
  },
--- a/docs/docs/integrations/callbacks/promptlayer.ipynb
+++ b/docs/docs/integrations/callbacks/promptlayer.ipynb
@@ -7,12 +7,13 @@
   "source": [
    "# PromptLayer\n",
    "\n",
+    ">[PromptLayer](https://docs.promptlayer.com/introduction) is a platform for prompt engineering. It also helps with the LLM observability to visualize requests, version prompts, and track usage.\n",
+    ">\n",
+    ">While `PromptLayer` does have LLMs that integrate directly with LangChain (e.g. [`PromptLayerOpenAI`](https://python.langchain.com/docs/integrations/llms/promptlayer_openai)), using a callback is the recommended way to integrate `PromptLayer` with LangChain.\n",
    "\n",
-    ">[PromptLayer](https://promptlayer.com) is a an LLM observability platform that lets you visualize requests, version prompts, and track usage. In this guide we will go over how to setup the `PromptLayerCallbackHandler`. \n",
+    "In this guide, we will go over how to setup the `PromptLayerCallbackHandler`. \n",
    "\n",
-    "While `PromptLayer` does have LLMs that integrate directly with LangChain (e.g. [`PromptLayerOpenAI`](https://python.langchain.com/docs/integrations/llms/promptlayer_openai)), this callback is the recommended way to integrate PromptLayer with LangChain.\n",
-    "\n",
-    "See [our docs](https://docs.promptlayer.com/languages/langchain) for more information."
+    "See [PromptLayer docs](https://docs.promptlayer.com/languages/langchain) for more information."
   ]
  },
  {
--- a/docs/docs/integrations/chat/google_vertex_ai_palm.ipynb
+++ b/docs/docs/integrations/chat/google_vertex_ai_palm.ipynb
@@ -45,7 +45,7 @@
  },
  {
   "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
@@ -55,7 +55,7 @@
  },
  {
   "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
@@ -64,7 +64,7 @@
       "AIMessage(content=\" J'aime la programmation.\")"
      ]
     },
-     "execution_count": 3,
+     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
@@ -89,7 +89,7 @@
  },
  {
   "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
@@ -98,7 +98,7 @@
       "AIMessage(content=' プログラミングが大好きです')"
      ]
     },
-     "execution_count": 4,
+     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
@@ -142,7 +142,7 @@
  },
  {
   "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 4,
   "metadata": {
    "tags": []
   },
@@ -198,7 +198,7 @@
  },
  {
   "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
@@ -212,7 +212,7 @@
  },
  {
   "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
@@ -221,12 +221,17 @@
       "AIMessage(content=' Why do you love programming?')"
      ]
     },
-     "execution_count": 7,
+     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
+    "system = (\n",
+    "    \"You are a helpful assistant that translates {input_language} to {output_language}.\"\n",
+    ")\n",
+    "human = \"{text}\"\n",
+    "prompt = ChatPromptTemplate.from_messages([(\"system\", system), (\"human\", human)])\n",
    "chain = prompt | chat\n",
    "\n",
    "asyncio.run(\n",
@@ -251,7 +256,7 @@
  },
  {
   "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
--- a/docs/docs/integrations/chat/promptlayer_chatopenai.ipynb
+++ b/docs/docs/integrations/chat/promptlayer_chatopenai.ipynb
@@ -129,12 +129,6 @@
    "**The above request should now appear on your [PromptLayer dashboard](https://www.promptlayer.com).**"
   ]
  },
-  {
-   "cell_type": "markdown",
-   "id": "05e9e2fe",
-   "metadata": {},
-   "source": []
-  },
  {
   "attachments": {},
   "cell_type": "markdown",
@@ -152,6 +146,8 @@
   "metadata": {},
   "outputs": [],
   "source": [
+    "import promptlayer\n",
+    "\n",
    "chat = PromptLayerChatOpenAI(return_pl_id=True)\n",
    "chat_results = chat.generate([[HumanMessage(content=\"I am a cat and I want\")]])\n",
    "\n",
@@ -172,7 +168,7 @@
 ],
 "metadata": {
  "kernelspec": {
-   "display_name": "base",
+   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
@@ -186,7 +182,7 @@
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
-   "version": "3.8.8 (default, Apr 13 2021, 12:59:45) \n[Clang 10.0.0 ]"
+   "version": "3.10.12"
  },
  "vscode": {
   "interpreter": {
--- a/docs/docs/integrations/chat_loaders/imessage.ipynb
+++ b/docs/docs/integrations/chat_loaders/imessage.ipynb
@@ -153,7 +153,7 @@
   "source": [
    "# Now all of the Tortoise's messages will take the AI message class\n",
    "# which maps to the 'assistant' role in OpenAI's training format\n",
-    "alternating_sessions[0][\"messages\"][:3]"
+    "chat_sessions[0][\"messages\"][:3]"
   ]
  },
  {
@@ -191,7 +191,7 @@
    }
   ],
   "source": [
-    "training_data = convert_messages_for_finetuning(alternating_sessions)\n",
+    "training_data = convert_messages_for_finetuning(chat_sessions)\n",
    "print(f\"Prepared {len(training_data)} dialogues for training\")"
   ]
  },
@@ -416,7 +416,7 @@
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
-   "version": "3.11.5"
+   "version": "3.10.12"
  }
 },
 "nbformat": 4,
--- a/docs/docs/integrations/document_loaders/arcgis.ipynb
+++ b/docs/docs/integrations/document_loaders/arcgis.ipynb
@@ -23,8 +23,18 @@
   "source": [
    "from langchain.document_loaders import ArcGISLoader\n",
    "\n",
-    "url = \"https://maps1.vcgov.org/arcgis/rest/services/Beaches/MapServer/7\"\n",
-    "loader = ArcGISLoader(url)"
+    "URL = \"https://maps1.vcgov.org/arcgis/rest/services/Beaches/MapServer/7\"\n",
+    "loader = ArcGISLoader(URL)\n",
+    "\n",
+    "docs = loader.load()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1e174ebd-bbbd-4a66-a644-51e0df12982d",
+   "metadata": {},
+   "source": [
+    "Let's measure loader latency."
   ]
  },
  {
@@ -261,7 +271,7 @@
   "metadata": {},
   "outputs": [],
   "source": [
-    "loader_geom = ArcGISLoader(url, return_geometry=True)"
+    "loader_geom = ArcGISLoader(URL, return_geometry=True)"
   ]
  },
  {
--- a/docs/docs/integrations/document_loaders/datadog_logs.ipynb
+++ b/docs/docs/integrations/document_loaders/datadog_logs.ipynb
@@ -30,6 +30,16 @@
    "#!pip install datadog-api-client"
   ]
  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "DD_API_KEY = \"...\"\n",
+    "DD_APP_KEY = \"...\""
+   ]
+  },
  {
   "cell_type": "code",
   "execution_count": null,
@@ -73,7 +83,7 @@
 ],
 "metadata": {
  "kernelspec": {
-   "display_name": ".venv",
+   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
@@ -87,10 +97,9 @@
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
-   "version": "3.9.11"
-  },
-  "orig_nbformat": 4
+   "version": "3.10.12"
+  }
 },
 "nbformat": 4,
- "nbformat_minor": 2
+ "nbformat_minor": 4
 }
--- a/docs/docs/integrations/document_loaders/etherscan.ipynb
+++ b/docs/docs/integrations/document_loaders/etherscan.ipynb
@@ -65,6 +65,16 @@
    "%pip install langchain -q"
   ]
  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "2ab73cc1-d8e0-4b6d-bb03-9522b112fce5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "etherscanAPIKey = \"...\""
+   ]
+  },
  {
   "cell_type": "code",
   "execution_count": 1,
--- a/docs/docs/integrations/document_loaders/larksuite.ipynb
+++ b/docs/docs/integrations/document_loaders/larksuite.ipynb
@@ -74,7 +74,9 @@
   "source": [
    "# see https://python.langchain.com/docs/use_cases/summarization for more details\n",
    "from langchain.chains.summarize import load_summarize_chain\n",
+    "from langchain.llms.fake import FakeListLLM\n",
    "\n",
+    "llm = FakeListLLM()\n",
    "chain = load_summarize_chain(llm, chain_type=\"map_reduce\")\n",
    "chain.run(docs)"
   ]
@@ -96,7 +98,7 @@
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
-   "version": "3.11.3"
+   "version": "3.10.12"
  }
 },
 "nbformat": 4,
--- a/docs/docs/integrations/document_loaders/tensorflow_datasets.ipynb
+++ b/docs/docs/integrations/document_loaders/tensorflow_datasets.ipynb
@@ -166,6 +166,9 @@
    }
   ],
   "source": [
+    "from langchain_core.documents import Document\n",
+    "\n",
+    "\n",
    "def decode_to_str(item: tf.Tensor) -> str:\n",
    "    return item.numpy().decode(\"utf-8\")\n",
    "\n",
--- a/docs/docs/integrations/llms/anyscale.ipynb
+++ b/docs/docs/integrations/llms/anyscale.ipynb
@@ -12,6 +12,18 @@
    "This example goes over how to use LangChain to interact with [Anyscale Endpoint](https://app.endpoints.anyscale.com/). "
   ]
  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "515070aa-e241-480e-8d9a-afdf52f35322",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ANYSCALE_API_BASE = \"...\"\n",
+    "ANYSCALE_API_KEY = \"...\"\n",
+    "ANYSCALE_MODEL_NAME = \"...\""
+   ]
+  },
  {
   "cell_type": "code",
   "execution_count": null,
@@ -160,7 +172,7 @@
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
-   "version": "3.10.8"
+   "version": "3.10.12"
  },
  "vscode": {
   "interpreter": {
--- a/docs/docs/integrations/llms/bittensor.ipynb
+++ b/docs/docs/integrations/llms/bittensor.ipynb
@@ -112,6 +112,24 @@
    "##  Using NIBittensorLLM with Conversational Agent and Google Search Tool"
   ]
  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from langchain.tools import Tool\n",
+    "from langchain.utilities import GoogleSearchAPIWrapper\n",
+    "\n",
+    "search = GoogleSearchAPIWrapper()\n",
+    "\n",
+    "tool = Tool(\n",
+    "    name=\"Google Search\",\n",
+    "    description=\"Search Google for recent results.\",\n",
+    "    func=search.run,\n",
+    ")"
+   ]
+  },
  {
   "cell_type": "code",
   "execution_count": null,
@@ -129,7 +147,7 @@
    "\n",
    "memory = ConversationBufferMemory(memory_key=\"chat_history\")\n",
    "\n",
-    "\n",
+    "tools = [tool]\n",
    "prefix = \"\"\"Answer prompt based on LLM if there is need to search something then use internet and observe internet result and give accurate reply of user questions also try to use authenticated sources\"\"\"\n",
    "suffix = \"\"\"Begin!\n",
    "            {chat_history}\n",
@@ -137,14 +155,14 @@
    "            {agent_scratchpad}\"\"\"\n",
    "\n",
    "prompt = ZeroShotAgent.create_prompt(\n",
-    "    tools,\n",
+    "    tools=tools,\n",
    "    prefix=prefix,\n",
    "    suffix=suffix,\n",
    "    input_variables=[\"input\", \"chat_history\", \"agent_scratchpad\"],\n",
    ")\n",
    "\n",
    "llm = NIBittensorLLM(\n",
-    "    system_prompt=\"Your task is to determine response based on user prompt\"\n",
+    "    system_prompt=\"Your task is to determine a response based on user prompt\"\n",
    ")\n",
    "\n",
    "llm_chain = LLMChain(llm=llm, prompt=prompt)\n",
@@ -176,7 +194,7 @@
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
-   "version": "3.10.1"
+   "version": "3.10.12"
  }
 },
 "nbformat": 4,
--- a/docs/docs/integrations/llms/databricks.ipynb
+++ b/docs/docs/integrations/llms/databricks.ipynb
@@ -33,7 +33,13 @@
    "\n",
    "```\n",
    "pip install mlflow>=2.9\n",
-    "```"
+    "```\n",
+    "\n",
+    "Also, we need `dbutils` for this example.\n",
+    "\n",
+    "```\n",
+    "pip install dbutils\n",
+    "```\n"
   ]
  },
  {
@@ -269,6 +275,8 @@
    "\n",
    "import os\n",
    "\n",
+    "import dbutils\n",
+    "\n",
    "os.environ[\"DATABRICKS_TOKEN\"] = dbutils.secrets.get(\"myworkspace\", \"api_token\")\n",
    "\n",
    "llm = Databricks(host=\"myworkspace.cloud.databricks.com\", endpoint_name=\"dolly\")\n",
@@ -606,7 +614,7 @@
   "widgets": {}
  },
  "kernelspec": {
-   "display_name": "llm",
+   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
@@ -620,10 +628,9 @@
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
-   "version": "3.9.18"
-  },
-  "orig_nbformat": 4
+   "version": "3.10.12"
+  }
 },
 "nbformat": 4,
- "nbformat_minor": 0
+ "nbformat_minor": 4
 }
--- a/docs/docs/integrations/llms/llm_caching.ipynb
+++ b/docs/docs/integrations/llms/llm_caching.ipynb
@@ -28,7 +28,6 @@
   "cell_type": "markdown",
   "id": "b50f0598",
   "metadata": {
-    "jp-MarkdownHeadingCollapsed": true,
    "tags": []
   },
   "source": [
@@ -113,7 +112,6 @@
   "cell_type": "markdown",
   "id": "4bf59c12",
   "metadata": {
-    "jp-MarkdownHeadingCollapsed": true,
    "tags": []
   },
   "source": [
@@ -231,6 +229,7 @@
   "metadata": {},
   "outputs": [],
   "source": [
+    "import langchain\n",
    "from langchain.cache import UpstashRedisCache\n",
    "from upstash_redis import Redis\n",
    "\n",
@@ -1589,7 +1588,7 @@
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
-   "version": "3.10.1"
+   "version": "3.10.12"
  }
 },
 "nbformat": 4,
--- a/docs/docs/integrations/llms/runhouse.ipynb
+++ b/docs/docs/integrations/llms/runhouse.ipynb
@@ -289,7 +289,7 @@
   "source": [
    "pipeline = load_pipeline()\n",
    "llm = SelfHostedPipeline.from_pipeline(\n",
-    "    pipeline=pipeline, hardware=gpu, model_reqs=model_reqs\n",
+    "    pipeline=pipeline, hardware=gpu, model_reqs=[\"pip:./\", \"transformers\", \"torch\"]\n",
    ")"
   ]
  },
@@ -308,6 +308,8 @@
   "metadata": {},
   "outputs": [],
   "source": [
+    "import pickle\n",
+    "\n",
    "rh.blob(pickle.dumps(pipeline), path=\"models/pipeline.pkl\").save().to(\n",
    "    gpu, path=\"models\"\n",
    ")\n",
@@ -332,7 +334,7 @@
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
-   "version": "3.10.6"
+   "version": "3.10.12"
  }
 },
 "nbformat": 4,
--- a/docs/docs/integrations/providers/promptlayer.mdx
+++ b/docs/docs/integrations/providers/promptlayer.mdx
@@ -1,49 +1,49 @@
 # PromptLayer

-This page covers how to use [PromptLayer](https://www.promptlayer.com) within LangChain.
-It is broken into two parts: installation and setup, and then references to specific PromptLayer wrappers.
+>[PromptLayer](https://docs.promptlayer.com/introduction) is a platform for prompt engineering. 
+> It also helps with the LLM observability to visualize requests, version prompts, and track usage.
+>
+>While `PromptLayer` does have LLMs that integrate directly with LangChain (e.g. 
+> [`PromptLayerOpenAI`](https://docs.promptlayer.com/languages/langchain)), 
+> using a callback is the recommended way to integrate `PromptLayer` with LangChain.

 ## Installation and Setup

-If you want to work with PromptLayer:
- Install the promptlayer python library `pip install promptlayer`
- Create a PromptLayer account
+To work with `PromptLayer`, we have to:
+- Create a `PromptLayer` account
 - Create an api token and set it as an environment variable (`PROMPTLAYER_API_KEY`)

-## Wrappers
+Install a Python package:

-### LLM
+```bash
+pip install promptlayer
+```
+
+
+## Callback
+
+See a [usage example](/docs/integrations/callbacks/promptlayer).
+
+```python
+import promptlayer  # Don't forget this import!
+from langchain.callbacks import PromptLayerCallbackHandler
+```
+
+
+## LLM
+
+See a [usage example](/docs/integrations/llms/promptlayer_openai).

-There exists an PromptLayer OpenAI LLM wrapper, which you can access with
 ```python
 from langchain.llms import PromptLayerOpenAI
 ```

-To tag your requests, use the argument `pl_tags` when initializing the LLM
+
+## Chat Models
+
+See a [usage example](/docs/integrations/chat/promptlayer_chatopenai).
+
 ```python
-from langchain.llms import PromptLayerOpenAI
-llm = PromptLayerOpenAI(pl_tags=["langchain-requests", "chatbot"])
+from langchain.chat_models import PromptLayerChatOpenAI
 ```

-To get the PromptLayer request id, use the argument `return_pl_id` when initializing the LLM
-```python
-from langchain.llms import PromptLayerOpenAI
-llm = PromptLayerOpenAI(return_pl_id=True)
-```
-This will add the PromptLayer request ID in the `generation_info` field of the `Generation` returned when using `.generate` or `.agenerate`
-
-For example:
-```python
-llm_results = llm.generate(["hello world"])
-for res in llm_results.generations:
-    print("pl request id: ", res[0].generation_info["pl_request_id"])
-```
-You can use the PromptLayer request ID to add a prompt, score, or other metadata to your request. [Read more about it here](https://magniv.notion.site/Track-4deee1b1f7a34c1680d085f82567dab9).
-
-This LLM is identical to the [OpenAI](/docs/ecosystem/integrations/openai) LLM, except that
- all your requests will be logged to your PromptLayer account
- you can add `pl_tags` when instantiating to tag your requests on PromptLayer
- you can add `return_pl_id` when instantiating to return a PromptLayer request id to use [while tracking requests](https://magniv.notion.site/Track-4deee1b1f7a34c1680d085f82567dab9).
-
-
-PromptLayer also provides native wrappers for [`PromptLayerChatOpenAI`](/docs/integrations/chat/promptlayer_chatopenai) and `PromptLayerOpenAIChat`
--- a/docs/docs/integrations/retrievers/Activeloop
+++ b/docs/docs/integrations/retrievers/Activeloop
@@ -54,6 +54,15 @@
    "Also you'll need to create a [Activeloop]((https://activeloop.ai/)) account."
   ]
  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ORG_ID = \"...\""
+   ]
+  },
  {
   "cell_type": "code",
   "execution_count": null,
--- a/docs/docs/integrations/text_embedding/elasticsearch.ipynb
+++ b/docs/docs/integrations/text_embedding/elasticsearch.ipynb
@@ -160,6 +160,8 @@
   "outputs": [],
   "source": [
    "# Create Elasticsearch connection\n",
+    "from elasticsearch import Elasticsearch\n",
+    "\n",
    "es_connection = Elasticsearch(\n",
    "    hosts=[\"https://es_cluster_url:port\"], basic_auth=(\"user\", \"password\")\n",
    ")"
@@ -259,9 +261,9 @@
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
-   "version": "3.11.3"
+   "version": "3.10.12"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
-}
+}
--- a/docs/docs/integrations/text_embedding/embaas.ipynb
+++ b/docs/docs/integrations/text_embedding/embaas.ipynb
@@ -20,6 +20,8 @@
   "metadata": {},
   "outputs": [],
   "source": [
+    "import os\n",
+    "\n",
    "# Set API key\n",
    "embaas_api_key = \"YOUR_API_KEY\"\n",
    "# or set environment variable\n",
@@ -139,9 +141,9 @@
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
-   "version": "3.9.1"
+   "version": "3.10.12"
  }
 },
 "nbformat": 4,
- "nbformat_minor": 1
+ "nbformat_minor": 4
 }
--- a/docs/docs/integrations/text_embedding/localai.ipynb
+++ b/docs/docs/integrations/text_embedding/localai.ipynb
@@ -131,6 +131,8 @@
   "metadata": {},
   "outputs": [],
   "source": [
+    "import os\n",
+    "\n",
    "# if you are behind an explicit proxy, you can use the OPENAI_PROXY environment variable to pass through\n",
    "os.environ[\"OPENAI_PROXY\"] = \"http://proxy.yourcompany.com:8080\""
   ]
@@ -138,7 +140,7 @@
 ],
 "metadata": {
  "kernelspec": {
-   "display_name": "Python 3.11.1 64-bit",
+   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
@@ -152,7 +154,7 @@
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
-   "version": "3.11.1"
+   "version": "3.10.12"
  },
  "vscode": {
   "interpreter": {
--- a/docs/docs/integrations/text_embedding/openai.ipynb
+++ b/docs/docs/integrations/text_embedding/openai.ipynb
@@ -225,6 +225,8 @@
   "metadata": {},
   "outputs": [],
   "source": [
+    "import os\n",
+    "\n",
    "# if you are behind an explicit proxy, you can use the OPENAI_PROXY environment variable to pass through\n",
    "os.environ[\"OPENAI_PROXY\"] = \"http://proxy.yourcompany.com:8080\""
   ]
@@ -246,7 +248,7 @@
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
-   "version": "3.9.1"
+   "version": "3.10.12"
  },
  "vscode": {
   "interpreter": {
--- a/docs/docs/integrations/tools/dalle_image_generator.ipynb
+++ b/docs/docs/integrations/tools/dalle_image_generator.ipynb
@@ -101,8 +101,10 @@
    "# Or you can try the options below to display the image inline in this notebook\n",
    "\n",
    "try:\n",
+    "    import google.colab\n",
+    "\n",
    "    IN_COLAB = True\n",
-    "except:\n",
+    "except ImportError:\n",
    "    IN_COLAB = False\n",
    "\n",
    "if IN_COLAB:\n",
--- a/docs/docs/integrations/tools/google_search.ipynb
+++ b/docs/docs/integrations/tools/google_search.ipynb
@@ -187,7 +187,7 @@
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
-   "version": "3.9.1"
+   "version": "3.10.12"
  },
  "vscode": {
   "interpreter": {
--- a/docs/docs/integrations/tools/gradio_tools.ipynb
+++ b/docs/docs/integrations/tools/gradio_tools.ipynb
@@ -104,6 +104,8 @@
   },
   "outputs": [],
   "source": [
+    "from IPython.display import display\n",
+    "\n",
    "display(im)"
   ]
  },
@@ -232,7 +234,7 @@
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
-   "version": "3.11.3"
+   "version": "3.10.12"
  }
 },
 "nbformat": 4,
--- a/docs/docs/integrations/vectorstores/awadb.ipynb
+++ b/docs/docs/integrations/vectorstores/awadb.ipynb
@@ -145,6 +145,8 @@
   "metadata": {},
   "outputs": [],
   "source": [
+    "import awadb\n",
+    "\n",
    "awadb_client = awadb.Client()\n",
    "ret = awadb_client.Load(\"langchain_awadb\")\n",
    "if ret:\n",
@@ -178,7 +180,7 @@
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
-   "version": "3.10.6"
+   "version": "3.10.12"
  }
 },
 "nbformat": 4,
--- a/docs/docs/integrations/vectorstores/baiducloud_vector_search.ipynb
+++ b/docs/docs/integrations/vectorstores/baiducloud_vector_search.ipynb
@@ -78,6 +78,7 @@
   "outputs": [],
   "source": [
    "from langchain.document_loaders import TextLoader\n",
+    "from langchain.text_splitter import CharacterTextSplitter\n",
    "\n",
    "loader = TextLoader(\"../../../state_of_the_union.txt\")\n",
    "documents = loader.load()\n",
@@ -145,15 +146,22 @@
 ],
 "metadata": {
  "kernelspec": {
-   "display_name": "Python 3",
+   "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",
-   "version": "3.9.17"
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.12"
  },
-  "orig_nbformat": 4,
  "vscode": {
   "interpreter": {
    "hash": "aee8b7b246df8f9039afb4144a1f6fd8d2ca17a180786b69acc140d282b71a49"
@@ -161,5 +169,5 @@
  }
 },
 "nbformat": 4,
- "nbformat_minor": 2
+ "nbformat_minor": 4
 }
--- a/docs/docs/integrations/vectorstores/mongodb_atlas.ipynb
+++ b/docs/docs/integrations/vectorstores/mongodb_atlas.ipynb
@@ -52,6 +52,9 @@
   "metadata": {},
   "outputs": [],
   "source": [
+    "import getpass\n",
+    "import os\n",
+    "\n",
    "os.environ[\"OPENAI_API_KEY\"] = getpass.getpass(\"OpenAI API Key:\")"
   ]
  },
--- a/docs/docs/integrations/vectorstores/nucliadb.ipynb
+++ b/docs/docs/integrations/vectorstores/nucliadb.ipynb
@@ -99,7 +99,7 @@
   "outputs": [],
   "source": [
    "results = ndb.similarity_search(\"Who was inspired by Ada Lovelace?\")\n",
-    "print(res.page_content)"
+    "print(results[0].page_content)"
   ]
  }
 ],
@@ -119,7 +119,7 @@
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
-   "version": "3.9.1"
+   "version": "3.10.12"
  }
 },
 "nbformat": 4,
--- a/docs/docs/integrations/vectorstores/opensearch.ipynb
+++ b/docs/docs/integrations/vectorstores/opensearch.ipynb
@@ -344,7 +344,7 @@
   "metadata": {},
   "outputs": [],
   "source": [
-    "#!pip install requests requests-aws4auth"
+    "#!pip install boto3 requests requests-aws4auth"
   ]
  },
  {
@@ -362,6 +362,8 @@
   },
   "outputs": [],
   "source": [
+    "import boto3\n",
+    "from opensearchpy import RequestsHttpConnection\n",
    "from requests_aws4auth import AWS4Auth\n",
    "\n",
    "service = \"aoss\"  # must set the service as 'aoss'\n",
@@ -404,6 +406,16 @@
    "## Using AOS (Amazon OpenSearch Service)"
   ]
  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4b02cd8d-f182-476b-935a-737f9c05d8e4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#!pip install boto3"
+   ]
+  },
  {
   "cell_type": "code",
   "execution_count": null,
@@ -419,7 +431,9 @@
   },
   "outputs": [],
   "source": [
-    "# This is just an example to show how to use AOS , you need to set proper values.\n",
+    "# This is just an example to show how to use Amazon OpenSearch Service, you need to set proper values.\n",
+    "import boto3\n",
+    "from opensearchpy import RequestsHttpConnection\n",
    "\n",
    "service = \"es\"  # must set the service as 'es'\n",
    "region = \"us-east-2\"\n",
--- a/docs/docs/modules/agents/agent_types/chat_conversation_agent.ipynb
+++ b/docs/docs/modules/agents/agent_types/chat_conversation_agent.ipynb
@@ -13,6 +13,16 @@
    "We want it to be much more conversational."
   ]
  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7b9e9ef1-dc3c-4253-bd8b-5e95637bfe33",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "OPENAI_API_KEY = \"...\""
+   ]
+  },
  {
   "cell_type": "code",
   "execution_count": 1,
@@ -575,7 +585,7 @@
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
-   "version": "3.10.1"
+   "version": "3.10.12"
  }
 },
 "nbformat": 4,
--- a/docs/docs/modules/chains/how_to/call_methods.ipynb
+++ b/docs/docs/modules/chains/how_to/call_methods.ipynb
@@ -27,6 +27,10 @@
    }
   ],
   "source": [
+    "from langchain.chains.llm import LLMChain\n",
+    "from langchain.chat_models.openai import ChatOpenAI\n",
+    "from langchain_core.prompts import PromptTemplate\n",
+    "\n",
    "chat = ChatOpenAI(temperature=0)\n",
    "prompt_template = \"Tell me a {adjective} joke\"\n",
    "llm_chain = LLMChain(llm=chat, prompt=PromptTemplate.from_template(prompt_template))\n",
@@ -174,7 +178,7 @@
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
-   "version": "3.11.3"
+   "version": "3.10.12"
  },
  "vscode": {
   "interpreter": {
--- a/docs/docs/modules/data_connection/retrievers/ensemble.ipynb
+++ b/docs/docs/modules/data_connection/retrievers/ensemble.ipynb
@@ -19,6 +19,7 @@
   "metadata": {},
   "outputs": [],
   "source": [
+    "from langchain.embeddings import OpenAIEmbeddings\n",
    "from langchain.retrievers import BM25Retriever, EnsembleRetriever\n",
    "from langchain.vectorstores import FAISS"
   ]
@@ -81,7 +82,7 @@
 ],
 "metadata": {
  "kernelspec": {
-   "display_name": ".venv",
+   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
@@ -95,10 +96,9 @@
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
-   "version": "3.10.8"
-  },
-  "orig_nbformat": 4
+   "version": "3.10.12"
+  }
 },
 "nbformat": 4,
- "nbformat_minor": 2
+ "nbformat_minor": 4
 }
--- a/docs/docs/modules/data_connection/retrievers/multi_vector.ipynb
+++ b/docs/docs/modules/data_connection/retrievers/multi_vector.ipynb
@@ -55,8 +55,8 @@
    "    TextLoader(\"../../state_of_the_union.txt\"),\n",
    "]\n",
    "docs = []\n",
-    "for l in loaders:\n",
-    "    docs.extend(l.load())\n",
+    "for loader in loaders:\n",
+    "    docs.extend(loader.load())\n",
    "text_splitter = RecursiveCharacterTextSplitter(chunk_size=10000)\n",
    "docs = text_splitter.split_documents(docs)"
   ]
@@ -601,7 +601,7 @@
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
-   "version": "3.10.5"
+   "version": "3.10.12"
  }
 },
 "nbformat": 4,
--- a/docs/docs/modules/data_connection/retrievers/parent_document_retriever.ipynb
+++ b/docs/docs/modules/data_connection/retrievers/parent_document_retriever.ipynb
@@ -61,8 +61,8 @@
    "    TextLoader(\"../../state_of_the_union.txt\"),\n",
    "]\n",
    "docs = []\n",
-    "for l in loaders:\n",
-    "    docs.extend(l.load())"
+    "for loader in loaders:\n",
+    "    docs.extend(loader.load())"
   ]
  },
  {
@@ -432,7 +432,7 @@
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
-   "version": "3.10.5"
+   "version": "3.10.12"
  }
 },
 "nbformat": 4,
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -78,48 +78,5 @@ extend-exclude = [
 # These files were failing the listed rules at the time ruff was adopted for notebooks.
 # Don't require them to change at once, though we should look into them eventually.
 "cookbook/gymnasium_agent_simulation.ipynb" = ["F821"]
-"cookbook/multi_modal_output_agent.ipynb" = ["F821"]
-"cookbook/multi_modal_RAG_chroma.ipynb" = ["F821"]
-"cookbook/qianfan_baidu_elasticesearch_RAG.ipynb" = ["F821"]
-"cookbook/retrieval_in_sql.ipynb" = ["F821"]
-"cookbook/wikibase_agent.ipynb" = ["E722"]
-"docs/docs/expression_language/how_to/configure.ipynb" = ["F821"]
-"docs/docs/expression_language/how_to/fallbacks.ipynb" = ["E722"]
-"docs/docs/guides/fallbacks.ipynb" = ["E722"]
-"docs/docs/integrations/chat_loaders/imessage.ipynb" = ["F821"]
-"docs/docs/integrations/chat_loaders/langsmith_dataset.ipynb" = ["F821"]
-"docs/docs/integrations/chat/google_vertex_ai_palm.ipynb" = ["F821"]
-"docs/docs/integrations/chat/promptlayer_chatopenai.ipynb" = ["F821"]
-"docs/docs/integrations/document_loaders/arcgis.ipynb" = ["F821"]
-"docs/docs/integrations/document_loaders/datadog_logs.ipynb" = ["F821"]
-"docs/docs/integrations/document_loaders/embaas.ipynb" = ["F821"]
-"docs/docs/integrations/document_loaders/etherscan.ipynb" = ["F821"]
-"docs/docs/integrations/document_loaders/larksuite.ipynb" = ["F821"]
 "docs/docs/integrations/document_loaders/tensorflow_datasets.ipynb" = ["F821"]
-"docs/docs/integrations/llms/anyscale.ipynb" = ["F821"]
-"docs/docs/integrations/llms/bittensor.ipynb" = ["F821"]
-"docs/docs/integrations/llms/databricks.ipynb" = ["F821"]
-"docs/docs/integrations/llms/llm_caching.ipynb" = ["F821"]
-"docs/docs/integrations/llms/runhouse.ipynb" = ["F821"]
-"docs/docs/integrations/retrievers/Activeloop DeepMemory+LangChain.ipynb" = ["F821"]
-"docs/docs/integrations/text_embedding/cohere.ipynb" = ["F821"]
-"docs/docs/integrations/text_embedding/elasticsearch.ipynb" = ["F821"]
-"docs/docs/integrations/text_embedding/embaas.ipynb" = ["F821"]
-"docs/docs/integrations/text_embedding/jina.ipynb" = ["F821"]
-"docs/docs/integrations/text_embedding/localai.ipynb" = ["F821"]
-"docs/docs/integrations/text_embedding/openai.ipynb" = ["F821"]
-"docs/docs/integrations/tools/dalle_image_generator.ipynb" = ["E722"]
-"docs/docs/integrations/tools/gradio_tools.ipynb" = ["F821"]
-"docs/docs/integrations/vectorstores/async_faiss.ipynb" = ["F821"]
-"docs/docs/integrations/vectorstores/awadb.ipynb" = ["F821"]
-"docs/docs/integrations/vectorstores/baiducloud_vector_search.ipynb" = ["F821"]
-"docs/docs/integrations/vectorstores/faiss.ipynb" = ["F821"]
-"docs/docs/integrations/vectorstores/mongodb_atlas.ipynb" = ["F821"]
-"docs/docs/integrations/vectorstores/nucliadb.ipynb" = ["F821"]
-"docs/docs/integrations/vectorstores/opensearch.ipynb" = ["F821"]
-"docs/docs/modules/agents/agent_types/chat_conversation_agent.ipynb" = ["F821"]
-"docs/docs/modules/chains/how_to/call_methods.ipynb" = ["F821"]
-"docs/docs/modules/data_connection/retrievers/ensemble.ipynb" = ["F821"]
-"docs/docs/modules/data_connection/retrievers/multi_vector.ipynb" = ["E741"]
-"docs/docs/modules/data_connection/retrievers/parent_document_retriever.ipynb" = ["E741"]
-"docs/docs/modules/data_connection/text_embedding/caching_embeddings.ipynb" = ["F821"]
+