diff --git a/docs/.local_build.sh b/docs/.local_build.sh
index ee1bd67b30c73d..0c67d35024a702 100755
--- a/docs/.local_build.sh
+++ b/docs/.local_build.sh
@@ -12,14 +12,12 @@ mkdir -p ../_dist
 rsync -ruv . ../_dist
 cd ../_dist
 poetry run python scripts/model_feat_table.py
-poetry run nbdoc_build --srcdir docs --pause 0
-mkdir docs/templates
-cp ../templates/docs/INDEX.md docs/templates/index.md
 cp ../cookbook/README.md src/pages/cookbook.mdx
 cp ../.github/CONTRIBUTING.md docs/contributing.md
 mkdir -p docs/templates
 cp ../templates/docs/INDEX.md docs/templates/index.md
 wget https://raw.githubusercontent.com/langchain-ai/langserve/main/README.md -O docs/langserve.md
-poetry run python scripts/generate_api_reference_links.py
-yarn install
-yarn start
+
+yarn
+
+quarto preview docs
diff --git a/docs/docs/expression_language/why.ipynb b/docs/docs/expression_language/why.ipynb
index aac03fed562df5..a1e17a1cbddae0 100644
--- a/docs/docs/expression_language/why.ipynb
+++ b/docs/docs/expression_language/why.ipynb
@@ -10,7 +10,7 @@
     "title: Why use LCEL\n",
     "---\n",
     "\n",
-    "import { ColumnContainer, Column } from '@theme/Columns';"
+    "{ import { ColumnContainer, Column } from \"@theme/Columns\"; }"
    ]
   },
   {
@@ -18,7 +18,8 @@
    "id": "919a5ae2-ed21-4923-b98f-723c111bac67",
    "metadata": {},
    "source": [
-    ":::tip We recommend reading the LCEL [Get started](/docs/expression_language/get_started) section first.\n",
+    ":::tip \n",
+    "We recommend reading the LCEL [Get started](/docs/expression_language/get_started) section first.\n",
     ":::"
    ]
   },
@@ -62,11 +63,12 @@
     "In the simplest case, we just want to pass in a topic string and get back a joke string:\n",
     "\n",
     "<ColumnContainer>\n",
+    "\n",
     "<Column>\n",
     "\n",
     "#### Without LCEL\n",
     "\n",
-    "<div style={{ zoom: \"80%\" }}>"
+    "<div style=\"zoom:80%\">"
    ]
   },
   {
@@ -76,6 +78,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
+    "\n",
     "from typing import List\n",
     "\n",
     "import openai\n",
@@ -111,7 +114,7 @@
     "\n",
     "#### LCEL\n",
     "\n",
-    "<div style={{ zoom: \"80%\" }}>"
+    "<div style=\"zoom:80%\">"
    ]
   },
   {
@@ -156,7 +159,7 @@
     "\n",
     "#### Without LCEL\n",
     "\n",
-    "<div style={{ zoom: \"80%\" }}>"
+    "<div style=\"zoom:80%\">"
    ]
   },
   {
@@ -201,7 +204,7 @@
     "\n",
     "#### LCEL\n",
     "\n",
-    "<div style={{ zoom: \"80%\" }}>"
+    "<div style=\"zoom:80%\">"
    ]
   },
   {
@@ -233,7 +236,7 @@
     "\n",
     "#### Without LCEL\n",
     "\n",
-    "<div style={{ zoom: \"80%\" }}>"
+    "<div style=\"zoom:80%\">"
    ]
   },
   {
@@ -265,7 +268,7 @@
     "\n",
     "#### LCEL\n",
     "\n",
-    "<div style={{ zoom: \"80%\" }}>"
+    "<div style=\"zoom:80%\">"
    ]
   },
   {
@@ -296,7 +299,7 @@
     "\n",
     "#### Without LCEL\n",
     "\n",
-    "<div style={{ zoom: \"80%\" }}>"
+    "<div style=\"zoom:80%\">"
    ]
   },
   {
@@ -337,7 +340,7 @@
     "\n",
     "#### LCEL\n",
     "\n",
-    "<div style={{ zoom: \"80%\" }}>\n",
+    "<div style=\"zoom:80%\">\n",
     "\n",
     "```python\n",
     "chain.ainvoke(\"ice cream\")\n",
@@ -362,7 +365,7 @@
     "\n",
     "#### Without LCEL\n",
     "\n",
-    "<div style={{ zoom: \"80%\" }}>"
+    "<div style=\"zoom:80%\">"
    ]
   },
   {
@@ -398,7 +401,7 @@
     "\n",
     "#### LCEL\n",
     "\n",
-    "<div style={{ zoom: \"80%\" }}>"
+    "<div style=\"zoom:80%\">"
    ]
   },
   {
@@ -439,7 +442,7 @@
     "\n",
     "#### Without LCEL\n",
     "\n",
-    "<div style={{ zoom: \"80%\" }}>"
+    "<div style=\"zoom:80%\">"
    ]
   },
   {
@@ -481,7 +484,7 @@
     "\n",
     "#### LCEL\n",
     "\n",
-    "<div style={{ zoom: \"80%\" }}>"
+    "<div style=\"zoom:80%\">"
    ]
   },
   {
@@ -522,7 +525,7 @@
     "\n",
     "#### Without LCEL\n",
     "\n",
-    "<div style={{ zoom: \"80%\" }}>"
+    "<div style=\"zoom:80%\">"
    ]
   },
   {
@@ -607,7 +610,7 @@
     "\n",
     "#### With LCEL\n",
     "\n",
-    "<div style={{ zoom: \"80%\" }}>"
+    "<div style=\"zoom:80%\">"
    ]
   },
   {
@@ -677,7 +680,7 @@
     "\n",
     "We'll `print` intermediate steps for illustrative purposes\n",
     "\n",
-    "<div style={{ zoom: \"80%\" }}>"
+    "<div style=\"zoom:80%\">"
    ]
   },
   {
@@ -711,7 +714,7 @@
     "#### LCEL\n",
     "Every component has built-in integrations with LangSmith. If we set the following two environment variables, all chain traces are logged to LangSmith.\n",
     "\n",
-    "<div style={{ zoom: \"80%\" }}>"
+    "<div style=\"zoom:80%\">"
    ]
   },
   {
@@ -757,7 +760,7 @@
     "#### Without LCEL\n",
     "\n",
     "\n",
-    "<div style={{ zoom: \"80%\" }}>"
+    "<div style=\"zoom:80%\">"
    ]
   },
   {
@@ -804,7 +807,7 @@
     "\n",
     "#### LCEL\n",
     "\n",
-    "<div style={{ zoom: \"80%\" }}>"
+    "<div style=\"zoom:80%\">"
    ]
   },
   {
@@ -845,7 +848,7 @@
     "\n",
     "#### Without LCEL\n",
     "\n",
-    "<div style={{ zoom: \"80%\" }}>"
+    "<div style=\"zoom:80%\">"
    ]
   },
   {
@@ -1029,7 +1032,7 @@
     "\n",
     "#### LCEL\n",
     "\n",
-    "<div style={{ zoom: \"80%\" }}>"
+    "<div style=\"zoom:80%\">"
    ]
   },
   {
diff --git a/docs/docs/guides/debugging.md b/docs/docs/guides/debugging.md
index 6fefa9fa5bf265..a0ac5a5e894bf7 100644
--- a/docs/docs/guides/debugging.md
+++ b/docs/docs/guides/debugging.md
@@ -12,7 +12,7 @@ Platforms with tracing capabilities like [LangSmith](/docs/langsmith/) and [Wand
 
 For anyone building production-grade LLM applications, we highly recommend using a platform like this.
 
-![LangSmith run](/img/run_details.png)
+![LangSmith run](../../static/img/run_details.png)
 
 ## `set_debug` and `set_verbose`
 
diff --git a/docs/docs/guides/local_llms.ipynb b/docs/docs/guides/local_llms.ipynb
index 60e271463d5989..5541d1d608f990 100644
--- a/docs/docs/guides/local_llms.ipynb
+++ b/docs/docs/guides/local_llms.ipynb
@@ -32,7 +32,7 @@
     "1. `Base model`: What is the base-model and how was it trained?\n",
     "2. `Fine-tuning approach`: Was the base-model fine-tuned and, if so, what [set of instructions](https://cameronrwolfe.substack.com/p/beyond-llama-the-power-of-open-llms#%C2%A7alpaca-an-instruction-following-llama-model) was used?\n",
     "\n",
-    "![Image description](/img/OSS_LLM_overview.png)\n",
+    "![Image description](../../static/img/OSS_LLM_overview.png)\n",
     "\n",
     "The relative performance of these models can be assessed using several leaderboards, including:\n",
     "\n",
@@ -55,7 +55,7 @@
     "\n",
     "In particular, see [this excellent post](https://finbarr.ca/how-is-llama-cpp-possible/) on the importance of quantization.\n",
     "\n",
-    "![Image description](/img/llama-memory-weights.png)\n",
+    "![Image description](../../static/img/llama-memory-weights.png)\n",
     "\n",
     "With less precision, we radically decrease the memory needed to store the LLM in memory.\n",
     "\n",
@@ -63,7 +63,7 @@
     "\n",
     "A Mac M2 Max is 5-6x faster than a M1 for inference due to the larger GPU memory bandwidth.\n",
     "\n",
-    "![Image description](/img/llama_t_put.png)\n",
+    "![Image description](../../static/img/llama_t_put.png)\n",
     "\n",
     "## Quickstart\n",
     "\n",
diff --git a/docs/docs/modules/chains/document/map_reduce.ipynb b/docs/docs/modules/chains/document/map_reduce.ipynb
index 2214fa75c4438f..126ce5c8fa8478 100644
--- a/docs/docs/modules/chains/document/map_reduce.ipynb
+++ b/docs/docs/modules/chains/document/map_reduce.ipynb
@@ -9,7 +9,7 @@
     "\n",
     "The map reduce documents chain first applies an LLM chain to each document individually (the Map step), treating the chain output as a new document. It then passes all the new documents to a separate combine documents chain to get a single output (the Reduce step). It can optionally first compress, or collapse, the mapped documents to make sure that they fit in the combine documents chain (which will often pass them to an LLM). This compression step is performed recursively if necessary.\n",
     "\n",
-    "![map_reduce_diagram](/img/map_reduce.jpg)"
+    "![map_reduce_diagram](../../../../static/img/map_reduce.jpg)"
    ]
   },
   {
diff --git a/docs/docs/modules/chains/document/map_rerank.ipynb b/docs/docs/modules/chains/document/map_rerank.ipynb
index 1367b7abeedbfe..dd6445decae5a0 100644
--- a/docs/docs/modules/chains/document/map_rerank.ipynb
+++ b/docs/docs/modules/chains/document/map_rerank.ipynb
@@ -9,7 +9,7 @@
     "\n",
     "The map re-rank documents chain runs an initial prompt on each document, that not only tries to complete a task but also gives a score for how certain it is in its answer. The highest scoring response is returned.\n",
     "\n",
-    "![map_rerank_diagram](/img/map_rerank.jpg)"
+    "![map_rerank_diagram](../../../../static/img/map_rerank.jpg)"
    ]
   },
   {
diff --git a/docs/docs/modules/chains/document/refine.ipynb b/docs/docs/modules/chains/document/refine.ipynb
index 6869336021036f..d84724def4df35 100644
--- a/docs/docs/modules/chains/document/refine.ipynb
+++ b/docs/docs/modules/chains/document/refine.ipynb
@@ -24,7 +24,7 @@
     "The obvious tradeoff is that this chain will make far more LLM calls than, for example, the Stuff documents chain.\n",
     "There are also certain tasks which are difficult to accomplish iteratively. For example, the Refine chain can perform poorly when documents frequently cross-reference one another or when a task requires detailed information from many documents.\n",
     "\n",
-    "![refine_diagram](/img/refine.jpg)\n"
+    "![refine_diagram](../../../../static/img/refine.jpg)\n"
    ]
   },
   {
diff --git a/docs/docs/modules/chains/document/stuff.ipynb b/docs/docs/modules/chains/document/stuff.ipynb
index e97da5bceb630f..92798440fcbc80 100644
--- a/docs/docs/modules/chains/document/stuff.ipynb
+++ b/docs/docs/modules/chains/document/stuff.ipynb
@@ -20,7 +20,7 @@
     "\n",
     "This chain is well-suited for applications where documents are small and only a few are passed in for most calls.\n",
     "\n",
-    "![stuff_diagram](/img/stuff.jpg)"
+    "![stuff_diagram](../../../../static/img/stuff.jpg)"
    ]
   },
   {
diff --git a/docs/docs/use_cases/apis.ipynb b/docs/docs/use_cases/apis.ipynb
index 0c8d3cb2394407..a051fc250f73a8 100644
--- a/docs/docs/use_cases/apis.ipynb
+++ b/docs/docs/use_cases/apis.ipynb
@@ -34,7 +34,7 @@
     "* `Functions`: For example, [OpenAI functions](https://platform.openai.com/docs/guides/gpt/function-calling) is one popular means of doing this.\n",
     "* `LLM-generated interface`: Use an LLM with access to API documentation to create an interface.\n",
     "\n",
-    "![Image description](/img/api_use_case.png)"
+    "![Image description](../../static/img/api_use_case.png)"
    ]
   },
   {
@@ -188,7 +188,7 @@
     "    }\n",
     " ```\n",
     " \n",
-    "![Image description](/img/api_function_call.png)\n",
+    "![Image description](../../static/img/api_function_call.png)\n",
     " \n",
     "* This `Dict` above split and the [API is called here](https://github.com/langchain-ai/langchain/blob/7fc07ba5df99b9fa8bef837b0fafa220bc5c932c/libs/langchain/langchain/chains/openai_functions/openapi.py#L215)."
    ]
@@ -293,12 +293,12 @@
     "\n",
     "* The `api_request_chain` produces the API url from our question and the API documentation:\n",
     "\n",
-    "![Image description](/img/api_chain.png)\n",
+    "![Image description](../../static/img/api_chain.png)\n",
     "\n",
     "* [Here](https://github.com/langchain-ai/langchain/blob/bbd22b9b761389a5e40fc45b0570e1830aabb707/libs/langchain/langchain/chains/api/base.py#L82) we make the API request with the API url.\n",
     "* The `api_answer_chain` takes the response from the API and provides us with a natural language response:\n",
     "\n",
-    "![Image description](/img/api_chain_response.png)"
+    "![Image description](../../static/img/api_chain_response.png)"
    ]
   },
   {
diff --git a/docs/docs/use_cases/chatbots.ipynb b/docs/docs/use_cases/chatbots.ipynb
index 68a1ffc6de19c1..711dedd7a44c6c 100644
--- a/docs/docs/use_cases/chatbots.ipynb
+++ b/docs/docs/use_cases/chatbots.ipynb
@@ -30,7 +30,7 @@
    "id": "56615b45",
    "metadata": {},
    "source": [
-    "![Image description](/img/chat_use_case.png)"
+    "![Image description](../../static/img/chat_use_case.png)"
    ]
   },
   {
@@ -546,7 +546,7 @@
    "source": [
     "We can see the chat history preserved in the prompt using the [LangSmith trace](https://smith.langchain.com/public/dce34c57-21ca-4283-9020-a8e0d78a59de/r).\n",
     "\n",
-    "![Image description](/img/chat_use_case_2.png)"
+    "![Image description](../../static/img/chat_use_case_2.png)"
    ]
   },
   {
diff --git a/docs/docs/use_cases/extraction.ipynb b/docs/docs/use_cases/extraction.ipynb
index 4b5d580b5d905a..7fdf12694defd6 100644
--- a/docs/docs/use_cases/extraction.ipynb
+++ b/docs/docs/use_cases/extraction.ipynb
@@ -34,7 +34,7 @@
    "id": "178dbc59",
    "metadata": {},
    "source": [
-    "![Image description](/img/extraction.png)"
+    "![Image description](../../static/img/extraction.png)"
    ]
   },
   {
@@ -139,7 +139,7 @@
     "\n",
     "The [LangSmith trace](https://smith.langchain.com/public/72bc3205-7743-4ca6-929a-966a9d4c2a77/r) shows that we call the function `information_extraction` on the input string, `inp`.\n",
     "\n",
-    "![Image description](/img/extraction_trace_function.png)\n",
+    "![Image description](../../static/img/extraction_trace_function.png)\n",
     "\n",
     "This `information_extraction` function is defined [here](https://github.com/langchain-ai/langchain/blob/master/libs/langchain/langchain/chains/openai_functions/extraction.py) and returns a dict.\n",
     "\n",
@@ -497,7 +497,7 @@
    "source": [
     "We can see from the [LangSmith trace](https://smith.langchain.com/public/8e3aa858-467e-46a5-aa49-5db65f0a2b9a/r) that we get the same output as above.\n",
     "\n",
-    "![Image description](/img/extraction_trace_function_2.png)\n",
+    "![Image description](../../static/img/extraction_trace_function_2.png)\n",
     "\n",
     "We can see that we provide a two-shot prompt in order to instruct the LLM to output in our desired format.\n",
     "\n",
@@ -577,7 +577,7 @@
     "\n",
     "We can look at the [LangSmith trace](https://smith.langchain.com/public/69f11d41-41be-4319-93b0-6d0eda66e969/r) to see exactly what is going on under the hood.\n",
     "\n",
-    "![Image description](/img/extraction_trace_joke.png)\n",
+    "![Image description](../../static/img/extraction_trace_joke.png)\n",
     "\n",
     "### Going deeper\n",
     "\n",
@@ -587,6 +587,12 @@
     "* [JSONFormer](/docs/integrations/llms/jsonformer_experimental) offers another way for structured decoding of a subset of the JSON Schema.\n",
     "* [Kor](https://eyurtsev.github.io/kor/) is another library for extraction where schema and examples can be provided to the LLM."
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "aab95ecf",
+   "metadata": {},
+   "source": []
   }
  ],
  "metadata": {
diff --git a/docs/docs/use_cases/qa_structured/sql.ipynb b/docs/docs/use_cases/qa_structured/sql.ipynb
index 32718d4e1a7577..3f5b0981d05046 100644
--- a/docs/docs/use_cases/qa_structured/sql.ipynb
+++ b/docs/docs/use_cases/qa_structured/sql.ipynb
@@ -40,7 +40,7 @@
     "2. `Query a SQL database` using chains for query creation and execution\n",
     "3. `Interact with a SQL database` using agents for robust and flexible querying \n",
     "\n",
-    "![sql_usecase.png](/img/sql_usecase.png)\n",
+    "![sql_usecase.png](../../../static/img/sql_usecase.png)\n",
     "\n",
     "## Quickstart\n",
     "\n",
@@ -240,7 +240,7 @@
     "* Followed by three example rows in a `SELECT` statement\n",
     "\n",
     "`create_sql_query_chain` adopts this the best practice (see more in this [blog](https://blog.langchain.dev/llms-and-sql/)).  \n",
-    "![sql_usecase.png](/img/create_sql_query_chain.png)\n",
+    "![sql_usecase.png](../../../static/img/create_sql_query_chain.png)\n",
     "\n",
     "**Improvements**\n",
     "\n",
@@ -397,7 +397,7 @@
     "\n",
     "* Then, it executes the query and passes the results to an LLM for synthesis.\n",
     "\n",
-    "![sql_usecase.png](/img/sqldbchain_trace.png)\n",
+    "![sql_usecase.png](../../../static/img/sqldbchain_trace.png)\n",
     "\n",
     "**Improvements**\n",
     "\n",
@@ -661,7 +661,7 @@
     "\n",
     "* It finally executes the generated query using tool `sql_db_query`\n",
     "\n",
-    "![sql_usecase.png](/img/SQLDatabaseToolkit.png)"
+    "![sql_usecase.png](../../../static/img/SQLDatabaseToolkit.png)"
    ]
   },
   {
diff --git a/docs/docs/use_cases/question_answering/code_understanding.ipynb b/docs/docs/use_cases/question_answering/code_understanding.ipynb
index 9d1823abafab23..d848db2c9d57ce 100644
--- a/docs/docs/use_cases/question_answering/code_understanding.ipynb
+++ b/docs/docs/use_cases/question_answering/code_understanding.ipynb
@@ -24,7 +24,7 @@
     "- Using LLMs for suggesting refactors or improvements\n",
     "- Using LLMs for documenting the code\n",
     "\n",
-    "![Image description](/img/code_understanding.png)\n",
+    "![Image description](../../../static/img/code_understanding.png)\n",
     "\n",
     "## Overview\n",
     "\n",
@@ -339,7 +339,7 @@
     "* In particular, the code well structured and kept together in the retrieval output\n",
     "* The retrieved code and chat history are passed to the LLM for answer distillation\n",
     "\n",
-    "![Image description](/img/code_retrieval.png)"
+    "![Image description](../../../static/img/code_retrieval.png)"
    ]
   },
   {
diff --git a/docs/docs/use_cases/question_answering/index.ipynb b/docs/docs/use_cases/question_answering/index.ipynb
index b1264e11952ad8..8e5fbe2a2c14de 100644
--- a/docs/docs/use_cases/question_answering/index.ipynb
+++ b/docs/docs/use_cases/question_answering/index.ipynb
@@ -58,13 +58,13 @@
     "2. **Split**: [Text splitters](/docs/modules/data_connection/document_transformers/) break large `Documents` into smaller chunks. This is useful both for indexing data and for passing it in to a model, since large chunks are harder to search over and won't in a model's finite context window.\n",
     "3. **Store**: We need somewhere to store and index our splits, so that they can later be searched over. This is often done using a [VectorStore](/docs/modules/data_connection/vectorstores/) and [Embeddings](/docs/modules/data_connection/text_embedding/) model.\n",
     "\n",
-    "![index_diagram](/img/rag_indexing.png)\n",
+    "![index_diagram](../../../static/img/rag_indexing.png)\n",
     "\n",
     "#### Retrieval and generation\n",
     "4. **Retrieve**: Given a user input, relevant splits are retrieved from storage using a [Retriever](/docs/modules/data_connection/retrievers/).\n",
     "5. **Generate**: A [ChatModel](/docs/modules/model_io/chat_models) / [LLM](/docs/modules/model_io/llms/) produces an answer using a prompt that includes the question and the retrieved data\n",
     "\n",
-    "![retrieval_diagram](/img/rag_retrieval_generation.png)"
+    "![retrieval_diagram](../../../static/img/rag_retrieval_generation.png)"
    ]
   },
   {
diff --git a/docs/docs/use_cases/summarization.ipynb b/docs/docs/use_cases/summarization.ipynb
index 82a5b16c667bcd..a04c0ba50328f0 100644
--- a/docs/docs/use_cases/summarization.ipynb
+++ b/docs/docs/use_cases/summarization.ipynb
@@ -32,7 +32,7 @@
    "id": "8e233997",
    "metadata": {},
    "source": [
-    "![Image description](/img/summarization_use_case_1.png)"
+    "![Image description](../../static/img/summarization_use_case_1.png)"
    ]
   },
   {
@@ -56,7 +56,7 @@
    "id": "08ec66bc",
    "metadata": {},
    "source": [
-    "![Image description](/img/summarization_use_case_2.png)"
+    "![Image description](../../static/img/summarization_use_case_2.png)"
    ]
   },
   {
@@ -514,7 +514,7 @@
     "* The blog post and associated [repo](https://github.com/mendableai/QA_clustering) also introduce clustering as a means of summarization.\n",
     "* This opens up a third path beyond the `stuff` or `map-reduce` approaches that is worth considering.\n",
     "\n",
-    "![Image description](/img/summarization_use_case_3.png)"
+    "![Image description](../../static/img/summarization_use_case_3.png)"
    ]
   },
   {
diff --git a/docs/docs/use_cases/tagging.ipynb b/docs/docs/use_cases/tagging.ipynb
index cffa8bebfd32d0..94435ed20e7b6c 100644
--- a/docs/docs/use_cases/tagging.ipynb
+++ b/docs/docs/use_cases/tagging.ipynb
@@ -28,7 +28,7 @@
     "- covered topics\n",
     "- political tendency\n",
     "\n",
-    "![Image description](/img/tagging.png)\n",
+    "![Image description](../../static/img/tagging.png)\n",
     "\n",
     "## Overview\n",
     "\n",
@@ -293,7 +293,7 @@
     "* As with [extraction](/docs/use_cases/extraction), we call the `information_extraction` function [here](https://github.com/langchain-ai/langchain/blob/269f85b7b7ffd74b38cd422d4164fc033388c3d0/libs/langchain/langchain/chains/openai_functions/extraction.py#L20) on the input string.\n",
     "* This OpenAI function extraction information based upon the provided schema.\n",
     "\n",
-    "![Image description](/img/tagging_trace.png)"
+    "![Image description](../../static/img/tagging_trace.png)"
    ]
   },
   {
diff --git a/docs/docs/use_cases/web_scraping.ipynb b/docs/docs/use_cases/web_scraping.ipynb
index 62d64d1b333251..c536e5136f30ca 100644
--- a/docs/docs/use_cases/web_scraping.ipynb
+++ b/docs/docs/use_cases/web_scraping.ipynb
@@ -25,7 +25,7 @@
     "* Users have [highlighted it](https://twitter.com/GregKamradt/status/1679913813297225729?s=20) as one of his top desired AI tools. \n",
     "* OSS repos like [gpt-researcher](https://github.com/assafelovic/gpt-researcher) are growing in popularity. \n",
     " \n",
-    "![Image description](/img/web_scraping.png)\n",
+    "![Image description](../../static/img/web_scraping.png)\n",
     " \n",
     "## Overview\n",
     "\n",
@@ -443,7 +443,7 @@
    "source": [
     "We can compare the headlines scraped to the page:\n",
     "\n",
-    "![Image description](/img/wsj_page.png)\n",
+    "![Image description](../../static/img/wsj_page.png)\n",
     "\n",
     "Looking at the [LangSmith trace](https://smith.langchain.com/public/c3070198-5b13-419b-87bf-3821cdf34fa6/r), we can see what is going on under the hood:\n",
     "\n",
@@ -463,7 +463,7 @@
     "\n",
     "We can automate the process of [web research](https://blog.langchain.dev/automating-web-research/) using a retriever, such as the `WebResearchRetriever` ([docs](https://python.langchain.com/docs/modules/data_connection/retrievers/web_research)).\n",
     "\n",
-    "![Image description](/img/web_research.png)\n",
+    "![Image description](../../static/img/web_research.png)\n",
     "\n",
     "Copy requirements [from here](https://github.com/langchain-ai/web-explorer/blob/main/requirements.txt):\n",
     "\n",
diff --git a/docs/vercel_build.sh b/docs/vercel_build.sh
index 3793a77123ce1d..145a7e9acbc625 100755
--- a/docs/vercel_build.sh
+++ b/docs/vercel_build.sh
@@ -1,57 +1,24 @@
 #!/bin/bash
 
-version_compare() {
-    local v1=(${1//./ })
-    local v2=(${2//./ })
-    for i in {0..2}; do
-        if (( ${v1[i]} < ${v2[i]} )); then
-            return 1
-        fi
-    done
-    return 0
-}
+yum -y update
+yum install gcc bzip2-devel libffi-devel zlib-devel wget tar gzip -y
+amazon-linux-extras install python3.8 -y
 
-openssl_version=$(openssl version | awk '{print $2}')
-required_openssl_version="1.1.1"
+# install quarto
+wget -q https://github.com/quarto-dev/quarto-cli/releases/download/v1.3.450/quarto-1.3.450-linux-amd64.tar.gz
+tar -xzf quarto-1.3.450-linux-amd64.tar.gz
+export PATH=$PATH:$(pwd)/quarto-1.3.450/bin/
 
-python_version=$(python3 --version 2>&1 | awk '{print $2}')
-required_python_version="3.10"
 
-echo "OpenSSL Version"
-echo $openssl_version
-echo "Python Version"
-echo $python_version
-# If openssl version is less than 1.1.1 AND python version is less than 3.10
-if ! version_compare $openssl_version $required_openssl_version && ! version_compare $python_version $required_python_version; then
-### See: https://github.com/urllib3/urllib3/issues/2168
-# Requests lib breaks for old SSL versions,
-# which are defaults on Amazon Linux 2 (which Vercel uses for builds)
-    yum -y update
-    yum remove openssl-devel -y
-    yum install gcc bzip2-devel libffi-devel zlib-devel wget tar -y
-    yum install openssl11 -y
-    yum install openssl11-devel -y
-
-    wget https://www.python.org/ftp/python/3.11.4/Python-3.11.4.tgz
-    tar xzf Python-3.11.4.tgz
-    cd Python-3.11.4
-    ./configure
-    make altinstall
-    echo "Python Version"
-    python3.11 --version
-    cd ..
-fi
-
-python3.11 -m venv .venv
+python3.8 -m venv .venv
 source .venv/bin/activate
-python3.11 -m pip install --upgrade pip
-python3.11 -m pip install -r vercel_requirements.txt
-python3.11 scripts/model_feat_table.py
+python3.8 -m pip install --upgrade pip
+python3.8 -m pip install -r vercel_requirements.txt
+python3.8 scripts/model_feat_table.py
 mkdir docs/templates
 cp ../templates/docs/INDEX.md docs/templates/index.md
-python3.11 scripts/copy_templates.py
+python3.8 scripts/copy_templates.py
 cp ../cookbook/README.md src/pages/cookbook.mdx
 cp ../.github/CONTRIBUTING.md docs/contributing.md
-wget https://raw.githubusercontent.com/langchain-ai/langserve/main/README.md -O docs/langserve.md
-nbdoc_build --srcdir docs --pause 0
-python3.11 scripts/generate_api_reference_links.py
+wget -q https://raw.githubusercontent.com/langchain-ai/langserve/main/README.md -O docs/langserve.md
+quarto render docs/
diff --git a/docs/vercel_requirements.txt b/docs/vercel_requirements.txt
index 6b44d4069b798a..bffe000f94e354 100644
--- a/docs/vercel_requirements.txt
+++ b/docs/vercel_requirements.txt
@@ -1,3 +1,3 @@
 -e ../libs/langchain
 -e ../libs/core
-nbdoc
\ No newline at end of file
+urllib3==1.26.18