diff --git a/.github/DISCUSSION_TEMPLATE/q-a.yml b/.github/DISCUSSION_TEMPLATE/q-a.yml
index d0229b2d7bd10..af6688cde1705 100644
--- a/.github/DISCUSSION_TEMPLATE/q-a.yml
+++ b/.github/DISCUSSION_TEMPLATE/q-a.yml
@@ -22,7 +22,7 @@ body:
         if there's another way to solve your problem:
         
         [LangChain documentation with the integrated search](https://python.langchain.com/docs/get_started/introduction),
-        [API Reference](https://api.python.langchain.com/en/stable/),
+        [API Reference](https://python.langchain.com/api_reference/),
         [GitHub search](https://github.com/langchain-ai/langchain),
         [LangChain Github Discussions](https://github.com/langchain-ai/langchain/discussions),
         [LangChain Github Issues](https://github.com/langchain-ai/langchain/issues?q=is%3Aissue),
diff --git a/.github/ISSUE_TEMPLATE/bug-report.yml b/.github/ISSUE_TEMPLATE/bug-report.yml
index 4fe94a53c8fd7..f1276df4de6c7 100644
--- a/.github/ISSUE_TEMPLATE/bug-report.yml
+++ b/.github/ISSUE_TEMPLATE/bug-report.yml
@@ -16,7 +16,7 @@ body:
         if there's another way to solve your problem:
         
         [LangChain documentation with the integrated search](https://python.langchain.com/docs/get_started/introduction),
-        [API Reference](https://api.python.langchain.com/en/stable/),
+        [API Reference](https://python.langchain.com/api_reference/),
         [GitHub search](https://github.com/langchain-ai/langchain),
         [LangChain Github Discussions](https://github.com/langchain-ai/langchain/discussions),
         [LangChain Github Issues](https://github.com/langchain-ai/langchain/issues?q=is%3Aissue),
diff --git a/.github/ISSUE_TEMPLATE/documentation.yml b/.github/ISSUE_TEMPLATE/documentation.yml
index 0b4bd4bd7d288..a931cef1d2952 100644
--- a/.github/ISSUE_TEMPLATE/documentation.yml
+++ b/.github/ISSUE_TEMPLATE/documentation.yml
@@ -21,7 +21,7 @@ body:
       place to ask your question:
       
       [LangChain documentation with the integrated search](https://python.langchain.com/docs/get_started/introduction),
-      [API Reference](https://api.python.langchain.com/en/stable/),
+      [API Reference](https://python.langchain.com/api_reference/),
       [GitHub search](https://github.com/langchain-ai/langchain),
       [LangChain Github Discussions](https://github.com/langchain-ai/langchain/discussions),
       [LangChain Github Issues](https://github.com/langchain-ai/langchain/issues?q=is%3Aissue),
diff --git a/Makefile b/Makefile
index 5b684c94ac9a7..05fd5b5cfea66 100644
--- a/Makefile
+++ b/Makefile
@@ -69,7 +69,11 @@ lint lint_package lint_tests:
 	poetry run ruff check docs cookbook
 	poetry run ruff format docs cookbook cookbook --diff
 	poetry run ruff check --select I docs cookbook
-	git grep 'from langchain import' docs/docs cookbook | grep -vE 'from langchain import (hub)' && exit 1 || exit 0
+	git --no-pager grep 'from langchain import' docs cookbook | grep -vE 'from langchain import (hub)' && echo "Error: no importing langchain from root in docs, except for hub" && exit 1 || exit 0
+	
+	git --no-pager grep 'api.python.langchain.com' -- docs/docs ':!docs/docs/additional_resources/arxiv_references.mdx' ':!docs/docs/integrations/document_loaders/sitemap.ipynb' || exit 0 && \
+	echo "Error: you should link python.langchain.com/api_reference, not api.python.langchain.com in the docs" && \
+	exit 1
 
 ## format: Format the project files.
 format format_diff:
diff --git a/README.md b/README.md
index f3e64b60cdb7f..04de99fad0f4c 100644
--- a/README.md
+++ b/README.md
@@ -123,7 +123,7 @@ Please see [here](https://python.langchain.com) for full documentation, which in
 - [Tutorials](https://python.langchain.com/docs/tutorials/): If you're looking to build something specific or are more of a hands-on learner, check out our tutorials. This is the best place to get started.
 - [How-to guides](https://python.langchain.com/docs/how_to/): Answers to “How do I….?” type questions. These guides are goal-oriented and concrete; they're meant to help you complete a specific task.
 - [Conceptual guide](https://python.langchain.com/docs/concepts/): Conceptual explanations of the key parts of the framework.
-- [API Reference](https://api.python.langchain.com): Thorough documentation of every class and method.
+- [API Reference](https://python.langchain.com/api_reference/): Thorough documentation of every class and method.
 
 ## 🌐 Ecosystem
 
diff --git a/docs/docs/additional_resources/arxiv_references.mdx b/docs/docs/additional_resources/arxiv_references.mdx
index 461399688f617..fb843aa0c3cdc 100644
--- a/docs/docs/additional_resources/arxiv_references.mdx
+++ b/docs/docs/additional_resources/arxiv_references.mdx
@@ -28,19 +28,19 @@ From the opposite direction, scientists use `LangChain` in research and referenc
 | `2307.09288v2` [Llama 2: Open Foundation and Fine-Tuned Chat Models](http://arxiv.org/abs/2307.09288v2) | Hugo Touvron, Louis Martin, Kevin Stone,  et al. | 2023‑07‑18 | `Cookbook:` [Semi Structured Rag](https://github.com/langchain-ai/langchain/blob/master/cookbook/Semi_Structured_RAG.ipynb)
 | `2307.03172v3` [Lost in the Middle: How Language Models Use Long Contexts](http://arxiv.org/abs/2307.03172v3) | Nelson F. Liu, Kevin Lin, John Hewitt,  et al. | 2023‑07‑06 | `Docs:` [docs/how_to/long_context_reorder](https://python.langchain.com/docs/how_to/long_context_reorder)
 | `2305.14283v3` [Query Rewriting for Retrieval-Augmented Large Language Models](http://arxiv.org/abs/2305.14283v3) | Xinbei Ma, Yeyun Gong, Pengcheng He,  et al. | 2023‑05‑23 | `Template:` [rewrite-retrieve-read](https://python.langchain.com/docs/templates/rewrite-retrieve-read), `Cookbook:` [Rewrite](https://github.com/langchain-ai/langchain/blob/master/cookbook/rewrite.ipynb)
-| `2305.08291v1` [Large Language Model Guided Tree-of-Thought](http://arxiv.org/abs/2305.08291v1) | Jieyi Long | 2023‑05‑15 | `API:` [langchain_experimental.tot](https://api.python.langchain.com/en/latest/experimental_api_reference.html#module-langchain_experimental.tot), `Cookbook:` [Tree Of Thought](https://github.com/langchain-ai/langchain/blob/master/cookbook/tree_of_thought.ipynb)
+| `2305.08291v1` [Large Language Model Guided Tree-of-Thought](http://arxiv.org/abs/2305.08291v1) | Jieyi Long | 2023‑05‑15 | `API:` [langchain_experimental.tot](https://python.langchain.com/api_reference/experimental/tot.html), `Cookbook:` [Tree Of Thought](https://github.com/langchain-ai/langchain/blob/master/cookbook/tree_of_thought.ipynb)
 | `2305.04091v3` [Plan-and-Solve Prompting: Improving Zero-Shot Chain-of-Thought Reasoning by Large Language Models](http://arxiv.org/abs/2305.04091v3) | Lei Wang, Wanyu Xu, Yihuai Lan,  et al. | 2023‑05‑06 | `Cookbook:` [Plan And Execute Agent](https://github.com/langchain-ai/langchain/blob/master/cookbook/plan_and_execute_agent.ipynb)
-| `2305.02156v1` [Zero-Shot Listwise Document Reranking with a Large Language Model](http://arxiv.org/abs/2305.02156v1) | Xueguang Ma, Xinyu Zhang, Ronak Pradeep,  et al. | 2023‑05‑03 | `Docs:` [docs/how_to/contextual_compression](https://python.langchain.com/docs/how_to/contextual_compression), `API:` [langchain...LLMListwiseRerank](https://api.python.langchain.com/en/latest/retrievers/langchain.retrievers.document_compressors.listwise_rerank.LLMListwiseRerank.html#langchain.retrievers.document_compressors.listwise_rerank.LLMListwiseRerank)
+| `2305.02156v1` [Zero-Shot Listwise Document Reranking with a Large Language Model](http://arxiv.org/abs/2305.02156v1) | Xueguang Ma, Xinyu Zhang, Ronak Pradeep,  et al. | 2023‑05‑03 | `Docs:` [docs/how_to/contextual_compression](https://python.langchain.com/docs/how_to/contextual_compression), `API:` [langchain...LLMListwiseRerank](https://python.langchain.com/api_reference/langchain/retrievers/langchain.retrievers.document_compressors.listwise_rerank.LLMListwiseRerank.html#)
 | `2304.08485v2` [Visual Instruction Tuning](http://arxiv.org/abs/2304.08485v2) | Haotian Liu, Chunyuan Li, Qingyang Wu,  et al. | 2023‑04‑17 | `Cookbook:` [Semi Structured Multi Modal Rag Llama2](https://github.com/langchain-ai/langchain/blob/master/cookbook/Semi_structured_multi_modal_RAG_LLaMA2.ipynb), [Semi Structured And Multi Modal Rag](https://github.com/langchain-ai/langchain/blob/master/cookbook/Semi_structured_and_multi_modal_RAG.ipynb)
 | `2304.03442v2` [Generative Agents: Interactive Simulacra of Human Behavior](http://arxiv.org/abs/2304.03442v2) | Joon Sung Park, Joseph C. O'Brien, Carrie J. Cai,  et al. | 2023‑04‑07 | `Cookbook:` [Generative Agents Interactive Simulacra Of Human Behavior](https://github.com/langchain-ai/langchain/blob/master/cookbook/generative_agents_interactive_simulacra_of_human_behavior.ipynb), [Multiagent Bidding](https://github.com/langchain-ai/langchain/blob/master/cookbook/multiagent_bidding.ipynb)
 | `2303.17760v2` [CAMEL: Communicative Agents for "Mind" Exploration of Large Language Model Society](http://arxiv.org/abs/2303.17760v2) | Guohao Li, Hasan Abed Al Kader Hammoud, Hani Itani,  et al. | 2023‑03‑31 | `Cookbook:` [Camel Role Playing](https://github.com/langchain-ai/langchain/blob/master/cookbook/camel_role_playing.ipynb)
-| `2303.17580v4` [HuggingGPT: Solving AI Tasks with ChatGPT and its Friends in Hugging Face](http://arxiv.org/abs/2303.17580v4) | Yongliang Shen, Kaitao Song, Xu Tan,  et al. | 2023‑03‑30 | `API:` [langchain_experimental.autonomous_agents](https://api.python.langchain.com/en/latest/experimental_api_reference.html#module-langchain_experimental.autonomous_agents), `Cookbook:` [Hugginggpt](https://github.com/langchain-ai/langchain/blob/master/cookbook/hugginggpt.ipynb)
+| `2303.17580v4` [HuggingGPT: Solving AI Tasks with ChatGPT and its Friends in Hugging Face](http://arxiv.org/abs/2303.17580v4) | Yongliang Shen, Kaitao Song, Xu Tan,  et al. | 2023‑03‑30 | `API:` [langchain_experimental.autonomous_agents](https://python.langchain.com/api_reference/experimental/autonomous_agents.html), `Cookbook:` [Hugginggpt](https://github.com/langchain-ai/langchain/blob/master/cookbook/hugginggpt.ipynb)
 | `2301.10226v4` [A Watermark for Large Language Models](http://arxiv.org/abs/2301.10226v4) | John Kirchenbauer, Jonas Geiping, Yuxin Wen,  et al. | 2023‑01‑24 | `API:` [langchain_community...OCIModelDeploymentTGI](https://api.python.langchain.com/en/latest/llms/langchain_community.llms.oci_data_science_model_deployment_endpoint.OCIModelDeploymentTGI.html#langchain_community.llms.oci_data_science_model_deployment_endpoint.OCIModelDeploymentTGI), [langchain_huggingface...HuggingFaceEndpoint](https://api.python.langchain.com/en/latest/llms/langchain_huggingface.llms.huggingface_endpoint.HuggingFaceEndpoint.html#langchain_huggingface.llms.huggingface_endpoint.HuggingFaceEndpoint), [langchain_community...HuggingFaceTextGenInference](https://api.python.langchain.com/en/latest/llms/langchain_community.llms.huggingface_text_gen_inference.HuggingFaceTextGenInference.html#langchain_community.llms.huggingface_text_gen_inference.HuggingFaceTextGenInference), [langchain_community...HuggingFaceEndpoint](https://api.python.langchain.com/en/latest/llms/langchain_community.llms.huggingface_endpoint.HuggingFaceEndpoint.html#langchain_community.llms.huggingface_endpoint.HuggingFaceEndpoint)
 | `2212.10496v1` [Precise Zero-Shot Dense Retrieval without Relevance Labels](http://arxiv.org/abs/2212.10496v1) | Luyu Gao, Xueguang Ma, Jimmy Lin,  et al. | 2022‑12‑20 | `Docs:` [docs/concepts](https://python.langchain.com/docs/concepts), `API:` [langchain...HypotheticalDocumentEmbedder](https://api.python.langchain.com/en/latest/chains/langchain.chains.hyde.base.HypotheticalDocumentEmbedder.html#langchain.chains.hyde.base.HypotheticalDocumentEmbedder), `Template:` [hyde](https://python.langchain.com/docs/templates/hyde), `Cookbook:` [Hypothetical Document Embeddings](https://github.com/langchain-ai/langchain/blob/master/cookbook/hypothetical_document_embeddings.ipynb)
 | `2212.08073v1` [Constitutional AI: Harmlessness from AI Feedback](http://arxiv.org/abs/2212.08073v1) | Yuntao Bai, Saurav Kadavath, Sandipan Kundu,  et al. | 2022‑12‑15 | `Docs:` [docs/versions/migrating_chains/constitutional_chain](https://python.langchain.com/docs/versions/migrating_chains/constitutional_chain)
-| `2212.07425v3` [Robust and Explainable Identification of Logical Fallacies in Natural Language Arguments](http://arxiv.org/abs/2212.07425v3) | Zhivar Sourati, Vishnu Priya Prasanna Venkatesh, Darshan Deshpande,  et al. | 2022‑12‑12 | `API:` [langchain_experimental.fallacy_removal](https://api.python.langchain.com/en/latest/experimental_api_reference.html#module-langchain_experimental.fallacy_removal)
+| `2212.07425v3` [Robust and Explainable Identification of Logical Fallacies in Natural Language Arguments](http://arxiv.org/abs/2212.07425v3) | Zhivar Sourati, Vishnu Priya Prasanna Venkatesh, Darshan Deshpande,  et al. | 2022‑12‑12 | `API:` [langchain_experimental.fallacy_removal](https://python.langchain.com/api_reference/experimental/fallacy_removal.html)
 | `2211.13892v2` [Complementary Explanations for Effective In-Context Learning](http://arxiv.org/abs/2211.13892v2) | Xi Ye, Srinivasan Iyer, Asli Celikyilmaz,  et al. | 2022‑11‑25 | `API:` [langchain_core...MaxMarginalRelevanceExampleSelector](https://api.python.langchain.com/en/latest/example_selectors/langchain_core.example_selectors.semantic_similarity.MaxMarginalRelevanceExampleSelector.html#langchain_core.example_selectors.semantic_similarity.MaxMarginalRelevanceExampleSelector)
-| `2211.10435v2` [PAL: Program-aided Language Models](http://arxiv.org/abs/2211.10435v2) | Luyu Gao, Aman Madaan, Shuyan Zhou,  et al. | 2022‑11‑18 | `API:` [langchain_experimental.pal_chain](https://api.python.langchain.com/en/latest/experimental_api_reference.html#module-langchain_experimental.pal_chain), [langchain_experimental...PALChain](https://api.python.langchain.com/en/latest/pal_chain/langchain_experimental.pal_chain.base.PALChain.html#langchain_experimental.pal_chain.base.PALChain), `Cookbook:` [Program Aided Language Model](https://github.com/langchain-ai/langchain/blob/master/cookbook/program_aided_language_model.ipynb)
+| `2211.10435v2` [PAL: Program-aided Language Models](http://arxiv.org/abs/2211.10435v2) | Luyu Gao, Aman Madaan, Shuyan Zhou,  et al. | 2022‑11‑18 | `API:` [langchain_experimental.pal_chain](https://python.langchain.com/api_reference/experimental/pal_chain.html), [langchain_experimental...PALChain](https://api.python.langchain.com/en/latest/pal_chain/langchain_experimental.pal_chain.base.PALChain.html#langchain_experimental.pal_chain.base.PALChain), `Cookbook:` [Program Aided Language Model](https://github.com/langchain-ai/langchain/blob/master/cookbook/program_aided_language_model.ipynb)
 | `2210.11934v2` [An Analysis of Fusion Functions for Hybrid Retrieval](http://arxiv.org/abs/2210.11934v2) | Sebastian Bruch, Siyu Gai, Amir Ingber | 2022‑10‑21 | `Docs:` [docs/concepts](https://python.langchain.com/docs/concepts)
 | `2210.03629v3` [ReAct: Synergizing Reasoning and Acting in Language Models](http://arxiv.org/abs/2210.03629v3) | Shunyu Yao, Jeffrey Zhao, Dian Yu,  et al. | 2022‑10‑06 | `Docs:` [docs/integrations/tools/ionic_shopping](https://python.langchain.com/docs/integrations/tools/ionic_shopping), [docs/integrations/providers/cohere](https://python.langchain.com/docs/integrations/providers/cohere), [docs/concepts](https://python.langchain.com/docs/concepts), `API:` [langchain...create_react_agent](https://api.python.langchain.com/en/latest/agents/langchain.agents.react.agent.create_react_agent.html#langchain.agents.react.agent.create_react_agent), [langchain...TrajectoryEvalChain](https://api.python.langchain.com/en/latest/evaluation/langchain.evaluation.agents.trajectory_eval_chain.TrajectoryEvalChain.html#langchain.evaluation.agents.trajectory_eval_chain.TrajectoryEvalChain)
 | `2209.10785v2` [Deep Lake: a Lakehouse for Deep Learning](http://arxiv.org/abs/2209.10785v2) | Sasun Hambardzumyan, Abhinav Tuli, Levon Ghukasyan,  et al. | 2022‑09‑22 | `Docs:` [docs/integrations/providers/activeloop_deeplake](https://python.langchain.com/docs/integrations/providers/activeloop_deeplake)
@@ -49,7 +49,7 @@ From the opposite direction, scientists use `LangChain` in research and referenc
 | `2204.00498v1` [Evaluating the Text-to-SQL Capabilities of Large Language Models](http://arxiv.org/abs/2204.00498v1) | Nitarshan Rajkumar, Raymond Li, Dzmitry Bahdanau | 2022‑03‑15 | `Docs:` [docs/tutorials/sql_qa](https://python.langchain.com/docs/tutorials/sql_qa), `API:` [langchain_community...SQLDatabase](https://api.python.langchain.com/en/latest/utilities/langchain_community.utilities.sql_database.SQLDatabase.html#langchain_community.utilities.sql_database.SQLDatabase), [langchain_community...SparkSQL](https://api.python.langchain.com/en/latest/utilities/langchain_community.utilities.spark_sql.SparkSQL.html#langchain_community.utilities.spark_sql.SparkSQL)
 | `2202.00666v5` [Locally Typical Sampling](http://arxiv.org/abs/2202.00666v5) | Clara Meister, Tiago Pimentel, Gian Wiher,  et al. | 2022‑02‑01 | `API:` [langchain_huggingface...HuggingFaceEndpoint](https://api.python.langchain.com/en/latest/llms/langchain_huggingface.llms.huggingface_endpoint.HuggingFaceEndpoint.html#langchain_huggingface.llms.huggingface_endpoint.HuggingFaceEndpoint), [langchain_community...HuggingFaceTextGenInference](https://api.python.langchain.com/en/latest/llms/langchain_community.llms.huggingface_text_gen_inference.HuggingFaceTextGenInference.html#langchain_community.llms.huggingface_text_gen_inference.HuggingFaceTextGenInference), [langchain_community...HuggingFaceEndpoint](https://api.python.langchain.com/en/latest/llms/langchain_community.llms.huggingface_endpoint.HuggingFaceEndpoint.html#langchain_community.llms.huggingface_endpoint.HuggingFaceEndpoint)
 | `2112.01488v3` [ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction](http://arxiv.org/abs/2112.01488v3) | Keshav Santhanam, Omar Khattab, Jon Saad-Falcon,  et al. | 2021‑12‑02 | `Docs:` [docs/integrations/retrievers/ragatouille](https://python.langchain.com/docs/integrations/retrievers/ragatouille), [docs/integrations/providers/ragatouille](https://python.langchain.com/docs/integrations/providers/ragatouille), [docs/concepts](https://python.langchain.com/docs/concepts), [docs/integrations/providers/dspy](https://python.langchain.com/docs/integrations/providers/dspy)
-| `2103.00020v1` [Learning Transferable Visual Models From Natural Language Supervision](http://arxiv.org/abs/2103.00020v1) | Alec Radford, Jong Wook Kim, Chris Hallacy,  et al. | 2021‑02‑26 | `API:` [langchain_experimental.open_clip](https://api.python.langchain.com/en/latest/experimental_api_reference.html#module-langchain_experimental.open_clip)
+| `2103.00020v1` [Learning Transferable Visual Models From Natural Language Supervision](http://arxiv.org/abs/2103.00020v1) | Alec Radford, Jong Wook Kim, Chris Hallacy,  et al. | 2021‑02‑26 | `API:` [langchain_experimental.open_clip](https://python.langchain.com/api_reference/experimental/open_clip.html)
 | `2005.14165v4` [Language Models are Few-Shot Learners](http://arxiv.org/abs/2005.14165v4) | Tom B. Brown, Benjamin Mann, Nick Ryder,  et al. | 2020‑05‑28 | `Docs:` [docs/concepts](https://python.langchain.com/docs/concepts)
 | `2005.11401v4` [Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks](http://arxiv.org/abs/2005.11401v4) | Patrick Lewis, Ethan Perez, Aleksandra Piktus,  et al. | 2020‑05‑22 | `Docs:` [docs/concepts](https://python.langchain.com/docs/concepts)
 | `1909.05858v2` [CTRL: A Conditional Transformer Language Model for Controllable Generation](http://arxiv.org/abs/1909.05858v2) | Nitish Shirish Keskar, Bryan McCann, Lav R. Varshney,  et al. | 2019‑09‑11 | `API:` [langchain_huggingface...HuggingFaceEndpoint](https://api.python.langchain.com/en/latest/llms/langchain_huggingface.llms.huggingface_endpoint.HuggingFaceEndpoint.html#langchain_huggingface.llms.huggingface_endpoint.HuggingFaceEndpoint), [langchain_community...HuggingFaceTextGenInference](https://api.python.langchain.com/en/latest/llms/langchain_community.llms.huggingface_text_gen_inference.HuggingFaceTextGenInference.html#langchain_community.llms.huggingface_text_gen_inference.HuggingFaceTextGenInference), [langchain_community...HuggingFaceEndpoint](https://api.python.langchain.com/en/latest/llms/langchain_community.llms.huggingface_endpoint.HuggingFaceEndpoint.html#langchain_community.llms.huggingface_endpoint.HuggingFaceEndpoint)
@@ -433,7 +433,7 @@ for retrieval-augmented LLM.
 - **arXiv id:** [2305.08291v1](http://arxiv.org/abs/2305.08291v1)  **Published Date:** 2023-05-15
 - **LangChain:**
 
-   - **API Reference:** [langchain_experimental.tot](https://api.python.langchain.com/en/latest/experimental_api_reference.html#module-langchain_experimental.tot)
+   - **API Reference:** [langchain_experimental.tot](https://python.langchain.com/api_reference/experimental/tot.html)
    - **Cookbook:** [tree_of_thought](https://github.com/langchain-ai/langchain/blob/master/cookbook/tree_of_thought.ipynb)
 
 **Abstract:** In this paper, we introduce the Tree-of-Thought (ToT) framework, a novel
@@ -490,7 +490,7 @@ https://github.com/AGI-Edgerunners/Plan-and-Solve-Prompting.
 - **LangChain:**
 
    - **Documentation:** [docs/how_to/contextual_compression](https://python.langchain.com/docs/how_to/contextual_compression)
-   - **API Reference:** [langchain...LLMListwiseRerank](https://api.python.langchain.com/en/latest/retrievers/langchain.retrievers.document_compressors.listwise_rerank.LLMListwiseRerank.html#langchain.retrievers.document_compressors.listwise_rerank.LLMListwiseRerank)
+   - **API Reference:** [langchain...LLMListwiseRerank](https://python.langchain.com/api_reference/langchain/retrievers/langchain.retrievers.document_compressors.listwise_rerank.LLMListwiseRerank.html#)
 
 **Abstract:** Supervised ranking methods based on bi-encoder or cross-encoder architectures
 have shown success in multi-stage text ranking tasks, but they require large
@@ -597,7 +597,7 @@ agents and beyond: https://github.com/camel-ai/camel.
 - **arXiv id:** [2303.17580v4](http://arxiv.org/abs/2303.17580v4)  **Published Date:** 2023-03-30
 - **LangChain:**
 
-   - **API Reference:** [langchain_experimental.autonomous_agents](https://api.python.langchain.com/en/latest/experimental_api_reference.html#module-langchain_experimental.autonomous_agents)
+   - **API Reference:** [langchain_experimental.autonomous_agents](https://python.langchain.com/api_reference/experimental/autonomous_agents.html)
    - **Cookbook:** [hugginggpt](https://github.com/langchain-ai/langchain/blob/master/cookbook/hugginggpt.ipynb)
 
 **Abstract:** Solving complicated AI tasks with different domains and modalities is a key
@@ -704,7 +704,7 @@ labels.
 - **arXiv id:** [2212.07425v3](http://arxiv.org/abs/2212.07425v3)  **Published Date:** 2022-12-12
 - **LangChain:**
 
-   - **API Reference:** [langchain_experimental.fallacy_removal](https://api.python.langchain.com/en/latest/experimental_api_reference.html#module-langchain_experimental.fallacy_removal)
+   - **API Reference:** [langchain_experimental.fallacy_removal](https://python.langchain.com/api_reference/experimental/fallacy_removal.html)
 
 **Abstract:** The spread of misinformation, propaganda, and flawed argumentation has been
 amplified in the Internet era. Given the volume of data and the subtlety of
@@ -759,7 +759,7 @@ performance across three real-world tasks on multiple LLMs.
 - **arXiv id:** [2211.10435v2](http://arxiv.org/abs/2211.10435v2)  **Published Date:** 2022-11-18
 - **LangChain:**
 
-   - **API Reference:** [langchain_experimental.pal_chain](https://api.python.langchain.com/en/latest/experimental_api_reference.html#module-langchain_experimental.pal_chain), [langchain_experimental...PALChain](https://api.python.langchain.com/en/latest/pal_chain/langchain_experimental.pal_chain.base.PALChain.html#langchain_experimental.pal_chain.base.PALChain)
+   - **API Reference:** [langchain_experimental.pal_chain](https://python.langchain.com/api_reference/experimental/pal_chain.html), [langchain_experimental...PALChain](https://api.python.langchain.com/en/latest/pal_chain/langchain_experimental.pal_chain.base.PALChain.html#langchain_experimental.pal_chain.base.PALChain)
    - **Cookbook:** [program_aided_language_model](https://github.com/langchain-ai/langchain/blob/master/cookbook/program_aided_language_model.ipynb)
 
 **Abstract:** Large language models (LLMs) have recently demonstrated an impressive ability
@@ -992,7 +992,7 @@ footprint of late interaction models by 6--10$\times$.
 - **arXiv id:** [2103.00020v1](http://arxiv.org/abs/2103.00020v1)  **Published Date:** 2021-02-26
 - **LangChain:**
 
-   - **API Reference:** [langchain_experimental.open_clip](https://api.python.langchain.com/en/latest/experimental_api_reference.html#module-langchain_experimental.open_clip)
+   - **API Reference:** [langchain_experimental.open_clip](https://python.langchain.com/api_reference/experimental/open_clip.html)
 
 **Abstract:** State-of-the-art computer vision systems are trained to predict a fixed set
 of predetermined object categories. This restricted form of supervision limits
diff --git a/docs/docs/concepts/embedding_models.mdx b/docs/docs/concepts/embedding_models.mdx
index 28a7a8c6497c0..a91018036c0af 100644
--- a/docs/docs/concepts/embedding_models.mdx
+++ b/docs/docs/concepts/embedding_models.mdx
@@ -3,7 +3,7 @@
 
 :::info[Prerequisites]
 
-* [Documents](https://api.python.langchain.com/en/latest/documents/langchain_core.documents.base.Document.html)
+* [Documents](https://python.langchain.com/api_reference/core/documents/langchain_core.documents.base.Document.html)
 
 :::
 
diff --git a/docs/docs/concepts/retrieval.mdx b/docs/docs/concepts/retrieval.mdx
index 8d3d75a6082b8..69a2f755550a0 100644
--- a/docs/docs/concepts/retrieval.mdx
+++ b/docs/docs/concepts/retrieval.mdx
@@ -221,7 +221,7 @@ They are particularly useful for storing and querying complex relationships betw
 LangChain provides a unified interface for interacting with various retrieval systems through the [retriever](/docs/concepts/retrievers/) concept. The interface is straightforward:
 
 1. Input: A query (string)
-2. Output: A list of documents (standardized LangChain [Document](https://api.python.langchain.com/en/latest/documents/langchain_core.documents.base.Document.html) objects)
+2. Output: A list of documents (standardized LangChain [Document](https://python.langchain.com/api_reference/core/documents/langchain_core.documents.base.Document.html) objects)
 
 You can create a retriever using any of the retrieval systems mentioned earlier. The query analysis techniques we discussed are particularly useful here, as they enable natural language interfaces for databases that typically require structured query languages.
 For example, you can build a retriever for a SQL database using text-to-SQL conversion. This allows a natural language query (string) to be transformed into a SQL query behind the scenes.
diff --git a/docs/docs/concepts/retrievers.mdx b/docs/docs/concepts/retrievers.mdx
index 3af42544004ee..1fb55a3f1c588 100644
--- a/docs/docs/concepts/retrievers.mdx
+++ b/docs/docs/concepts/retrievers.mdx
@@ -18,7 +18,7 @@ Because of their importance and variability, LangChain provides a uniform interf
 The LangChain [retriever](/docs/concepts/retrievers/) interface is straightforward:
 
 1. Input: A query (string)
-2. Output: A list of documents (standardized LangChain [Document](https://api.python.langchain.com/en/latest/documents/langchain_core.documents.base.Document.html) objects)
+2. Output: A list of documents (standardized LangChain [Document](https://python.langchain.com/api_reference/core/documents/langchain_core.documents.base.Document.html) objects)
 
 ## Key concept
 
@@ -29,7 +29,7 @@ All retrievers implement a simple interface for retrieving documents using natur
 ## Interface 
 
 The only requirement for a retriever is the ability to accepts a query and return documents. 
-In particular, [LangChain's retriever class](https://api.python.langchain.com/en/latest/retrievers/langchain_core.retrievers.BaseRetriever.html) only requires that the `_get_relevant_documents` method is implemented, which takes a `query: str` and returns a list of [Document](https://api.python.langchain.com/en/latest/documents/langchain_core.documents.base.Document.html) objects that are most relevant to the query.
+In particular, [LangChain's retriever class](https://python.langchain.com/api_reference/core/retrievers/langchain_core.retrievers.BaseRetriever.html#) only requires that the `_get_relevant_documents` method is implemented, which takes a `query: str` and returns a list of [Document](https://python.langchain.com/api_reference/core/documents/langchain_core.documents.base.Document.html) objects that are most relevant to the query.
 The underlying logic used to get relevant documents is specified by the retriever and can be whatever is most useful for the application.
 
 A LangChain retriever is a [runnable](/docs/how_to/lcel_cheatsheet/), which is a standard interface is for LangChain components. 
@@ -39,7 +39,7 @@ This means that it has a few common methods, including `invoke`, that are used t
 docs = retriever.invoke(query)
 ```
 
-Retrievers return a list of [Document](https://api.python.langchain.com/en/latest/documents/langchain_core.documents.base.Document.html) objects, which have two attributes:
+Retrievers return a list of [Document](https://python.langchain.com/api_reference/core/documents/langchain_core.documents.base.Document.html) objects, which have two attributes:
 
 * `page_content`: The content of this document. Currently is a string.
 * `metadata`: Arbitrary metadata associated with this document (e.g., document id, file name, source, etc). 
diff --git a/docs/docs/concepts/runnables.mdx b/docs/docs/concepts/runnables.mdx
index dea928568a735..93af2cecadc32 100644
--- a/docs/docs/concepts/runnables.mdx
+++ b/docs/docs/concepts/runnables.mdx
@@ -125,7 +125,7 @@ Please see the [Configurable Runnables](#configurable-runnables) section for mor
 
 LangChain will automatically try to infer the input and output types of a Runnable based on available information.
 
-Currently, this inference does not work well for more complex Runnables that are built using [LCEL](/docs/concepts/lcel) composition, and the inferred input and / or output types may be incorrect. In these cases, we recommend that users override the inferred input and output types using the `with_types` method ([API Reference](https://api.python.langchain.com/en/latest/runnables/langchain_core.runnables.base.Runnable.html#langchain_core.runnables.base.Runnable.with_types
+Currently, this inference does not work well for more complex Runnables that are built using [LCEL](/docs/concepts/lcel) composition, and the inferred input and / or output types may be incorrect. In these cases, we recommend that users override the inferred input and output types using the `with_types` method ([API Reference](https://python.langchain.com/api_reference/core/runnables/langchain_core.runnables.base.Runnable.html#langchain_core.runnables.base.Runnable.with_types
 ).
 
 ## RunnableConfig
diff --git a/docs/docs/concepts/vectorstores.mdx b/docs/docs/concepts/vectorstores.mdx
index aa5bcae7a2cd4..1a909453744a9 100644
--- a/docs/docs/concepts/vectorstores.mdx
+++ b/docs/docs/concepts/vectorstores.mdx
@@ -59,7 +59,7 @@ vector_store = InMemoryVectorStore(embedding=SomeEmbeddingModel())
 
 To add documents, use the `add_documents` method.
 
-This API works with a list of [Document](https://api.python.langchain.com/en/latest/documents/langchain_core.documents.base.Document.html) objects.
+This API works with a list of [Document](https://python.langchain.com/api_reference/core/documents/langchain_core.documents.base.Document.html) objects.
 `Document` objects all have `page_content` and `metadata` attributes, making them a universal way to store unstructured text and associated metadata.
 
 ```python
@@ -126,7 +126,7 @@ to the documentation of the specific vectorstore you are using to see what simil
 Given a similarity metric to measure the distance between the embedded query and any embedded document, we need an algorithm to efficiently search over *all* the embedded documents to find the most similar ones.
 There are various ways to do this. As an example, many vectorstores implement [HNSW (Hierarchical Navigable Small World)](https://www.pinecone.io/learn/series/faiss/hnsw/), a graph-based index structure that allows for efficient similarity search.
 Regardless of the search algorithm used under the hood, the LangChain vectorstore interface has a `similarity_search` method for all integrations. 
-This will take the search query, create an embedding, find similar documents, and return them as a list of [Documents](https://api.python.langchain.com/en/latest/documents/langchain_core.documents.base.Document.html).
+This will take the search query, create an embedding, find similar documents, and return them as a list of [Documents](https://python.langchain.com/api_reference/core/documents/langchain_core.documents.base.Document.html).
 
 ```python
 query = "my query"
diff --git a/docs/docs/how_to/installation.mdx b/docs/docs/how_to/installation.mdx
index f56946f921af2..081fe32fd8546 100644
--- a/docs/docs/how_to/installation.mdx
+++ b/docs/docs/how_to/installation.mdx
@@ -51,7 +51,7 @@ pip install langchain-core
 
 Certain integrations like OpenAI and Anthropic have their own packages.
 Any integrations that require their own package will be documented as such in the [Integration docs](/docs/integrations/providers/).
-You can see a list of all integration packages in the [API reference](https://api.python.langchain.com) under the "Partner libs" dropdown.
+You can see a list of all integration packages in the [API reference](https://python.langchain.com/api_reference/) under the "Partner libs" dropdown.
 To install one of these run:
 
 ```bash
diff --git a/docs/docs/integrations/chat/cerebras.ipynb b/docs/docs/integrations/chat/cerebras.ipynb
index 76c0fb8e1720f..e6ad0cf8938e7 100644
--- a/docs/docs/integrations/chat/cerebras.ipynb
+++ b/docs/docs/integrations/chat/cerebras.ipynb
@@ -17,7 +17,7 @@
    "source": [
     "# ChatCerebras\n",
     "\n",
-    "This notebook provides a quick overview for getting started with Cerebras [chat models](/docs/concepts/chat_models). For detailed documentation of all ChatCerebras features and configurations head to the [API reference](https://api.python.langchain.com/en/latest/chat_models/langchain_cerebras.chat_models.ChatCerebras.html).\n",
+    "This notebook provides a quick overview for getting started with Cerebras [chat models](/docs/concepts/chat_models). For detailed documentation of all ChatCerebras features and configurations head to the [API reference](https://python.langchain.com/api_reference/cerebras/chat_models/langchain_cerebras.chat_models.ChatCerebras.html#).\n",
     "\n",
     "At Cerebras, we've developed the world's largest and fastest AI processor, the Wafer-Scale Engine-3 (WSE-3). The Cerebras CS-3 system, powered by the WSE-3, represents a new class of AI supercomputer that sets the standard for generative AI training and inference with unparalleled performance and scalability.\n",
     "\n",
@@ -37,7 +37,7 @@
     "\n",
     "| Class | Package | Local | Serializable | [JS support](https://js.langchain.com/docs/integrations/chat/cerebras) | Package downloads | Package latest |\n",
     "| :--- | :--- | :---: | :---: |  :---: | :---: | :---: |\n",
-    "| [ChatCerebras](https://api.python.langchain.com/en/latest/chat_models/langchain_cerebras.chat_models.ChatCerebras.html) | [langchain-cerebras](https://api.python.langchain.com/en/latest/cerebras_api_reference.html) | ❌ | beta | ❌ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/langchain-cerebras?style=flat-square&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/langchain-cerebras?style=flat-square&label=%20) |\n",
+    "| [ChatCerebras](https://python.langchain.com/api_reference/cerebras/chat_models/langchain_cerebras.chat_models.ChatCerebras.html#) | [langchain-cerebras](https://python.langchain.com/api_reference/cerebras/index.html) | ❌ | beta | ❌ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/langchain-cerebras?style=flat-square&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/langchain-cerebras?style=flat-square&label=%20) |\n",
     "\n",
     "### Model features\n",
     "| [Tool calling](/docs/how_to/tool_calling/) | [Structured output](/docs/how_to/structured_output/) | JSON mode | [Image input](/docs/how_to/multimodal_inputs/) | Audio input | Video input | [Token-level streaming](/docs/how_to/chat_streaming/) | Native async | [Token usage](/docs/how_to/chat_token_usage_tracking/) | [Logprobs](/docs/how_to/logprobs/) |\n",
@@ -396,7 +396,7 @@
    "source": [
     "## API reference\n",
     "\n",
-    "For detailed documentation of all ChatCerebras features and configurations head to the API reference: https://api.python.langchain.com/en/latest/chat_models/langchain_cerebras.chat_models.ChatCerebras.html"
+    "For detailed documentation of all ChatCerebras features and configurations head to the API reference: https://python.langchain.com/api_reference/cerebras/chat_models/langchain_cerebras.chat_models.ChatCerebras.html#"
    ]
   }
  ],
diff --git a/docs/docs/integrations/chat/oci_data_science.ipynb b/docs/docs/integrations/chat/oci_data_science.ipynb
index b5a8f040d901b..6196d2025c04b 100644
--- a/docs/docs/integrations/chat/oci_data_science.ipynb
+++ b/docs/docs/integrations/chat/oci_data_science.ipynb
@@ -19,7 +19,7 @@
    "source": [
     "# ChatOCIModelDeployment\n",
     "\n",
-    "This will help you getting started with OCIModelDeployment [chat models](/docs/concepts/chat_models). For detailed documentation of all ChatOCIModelDeployment features and configurations head to the [API reference](https://api.python.langchain.com/en/latest/chat_models/langchain_community.chat_models.ChatOCIModelDeployment.html).\n",
+    "This will help you getting started with OCIModelDeployment [chat models](/docs/concepts/chat_models). For detailed documentation of all ChatOCIModelDeployment features and configurations head to the [API reference](https://python.langchain.com/api_reference/community/chat_models/langchain_community.chat_models.oci_data_science.ChatOCIModelDeployment.html).\n",
     "\n",
     "[OCI Data Science](https://docs.oracle.com/en-us/iaas/data-science/using/home.htm) is a fully managed and serverless platform for data science teams to build, train, and manage machine learning models in the Oracle Cloud Infrastructure. You can use [AI Quick Actions](https://blogs.oracle.com/ai-and-datascience/post/ai-quick-actions-in-oci-data-science) to easily deploy LLMs on [OCI Data Science Model Deployment Service](https://docs.oracle.com/en-us/iaas/data-science/using/model-dep-about.htm). You may choose to deploy the model with popular inference frameworks such as vLLM or TGI. By default, the model deployment endpoint mimics the OpenAI API protocol.\n",
     "\n",
@@ -30,7 +30,7 @@
     "\n",
     "| Class | Package | Local | Serializable | JS support | Package downloads | Package latest |\n",
     "| :--- | :--- | :---: | :---: |  :---: | :---: | :---: |\n",
-    "| [ChatOCIModelDeployment](https://api.python.langchain.com/en/latest/chat_models/langchain_community.chat_models.ChatOCIModelDeployment.html) | [langchain-community](https://api.python.langchain.com/en/latest/community_api_reference.html) | ❌ | beta | ❌ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/langchain-community?style=flat-square&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/langchain-community?style=flat-square&label=%20) |\n",
+    "| [ChatOCIModelDeployment](https://python.langchain.com/api_reference/community/chat_models/langchain_community.chat_models.oci_data_science.ChatOCIModelDeployment.html) | [langchain-community](https://python.langchain.com/api_reference/community/index.html) | ❌ | beta | ❌ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/langchain-community?style=flat-square&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/langchain-community?style=flat-square&label=%20) |\n",
     "\n",
     "### Model features\n",
     "\n",
@@ -430,9 +430,9 @@
     "\n",
     "For comprehensive details on all features and configurations, please refer to the API reference documentation for each class:\n",
     "\n",
-    "* [ChatOCIModelDeployment](https://api.python.langchain.com/en/latest/chat_models/langchain_community.chat_models.oci_data_science.ChatOCIModelDeployment.html)\n",
-    "* [ChatOCIModelDeploymentVLLM](https://api.python.langchain.com/en/latest/chat_models/langchain_community.chat_models.oci_data_science.ChatOCIModelDeploymentVLLM.html)\n",
-    "* [ChatOCIModelDeploymentTGI](https://api.python.langchain.com/en/latest/chat_models/langchain_community.chat_models.oci_data_science.ChatOCIModelDeploymentTGI.html)"
+    "* [ChatOCIModelDeployment](https://python.langchain.com/api_reference/community/chat_models/langchain_community.chat_models.oci_data_science.ChatOCIModelDeployment.html)\n",
+    "* [ChatOCIModelDeploymentVLLM](https://python.langchain.com/api_reference/community/chat_models/langchain_community.chat_models.oci_data_science.ChatOCIModelDeploymentVLLM.html)\n",
+    "* [ChatOCIModelDeploymentTGI](https://python.langchain.com/api_reference/community/chat_models/langchain_community.chat_models.oci_data_science.ChatOCIModelDeploymentTGI.html)"
    ]
   }
  ],
diff --git a/docs/docs/integrations/chat/outlines.ipynb b/docs/docs/integrations/chat/outlines.ipynb
index 1d53def18b9aa..001ecf1d2b4ec 100644
--- a/docs/docs/integrations/chat/outlines.ipynb
+++ b/docs/docs/integrations/chat/outlines.ipynb
@@ -17,7 +17,7 @@
             "source": [
                 "# ChatOutlines\n",
                 "\n",
-                "This will help you getting started with Outlines [chat models](/docs/concepts/chat_models/). For detailed documentation of all ChatOutlines features and configurations head to the [API reference](https://api.python.langchain.com/en/latest/chat_models/outlines.chat_models.ChatOutlines.html).\n",
+                "This will help you getting started with Outlines [chat models](/docs/concepts/chat_models/). For detailed documentation of all ChatOutlines features and configurations head to the [API reference](https://python.langchain.com/api_reference/community/chat_models/langchain_community.chat_models.outlines.ChatOutlines.html).\n",
                 "\n",
                 "[Outlines](https://github.com/outlines-dev/outlines) is a library for constrained language generation. It allows you to use large language models (LLMs) with various backends while applying constraints to the generated output.\n",
                 "\n",
@@ -26,7 +26,7 @@
                 "\n",
                 "| Class | Package | Local | Serializable | JS support | Package downloads | Package latest |\n",
                 "| :--- | :--- | :---: | :---: |  :---: | :---: | :---: |\n",
-                "| [ChatOutlines](https://api.python.langchain.com/en/latest/chat_models/outlines.chat_models.ChatOutlines.html) | [langchain-community](https://api.python.langchain.com/en/latest/community_api_reference.html) | ✅ | ❌ | ❌ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/langchain-community?style=flat-square&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/langchain-community?style=flat-square&label=%20) |\n",
+                "| [ChatOutlines](https://python.langchain.com/api_reference/community/chat_models/langchain_community.chat_models.outlines.ChatOutlines.html) | [langchain-community](https://python.langchain.com/api_reference/community/index.html) | ✅ | ❌ | ❌ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/langchain-community?style=flat-square&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/langchain-community?style=flat-square&label=%20) |\n",
                 "\n",
                 "### Model features\n",
                 "| [Tool calling](/docs/how_to/tool_calling) | [Structured output](/docs/how_to/structured_output/) | JSON mode | [Image input](/docs/how_to/multimodal_inputs/) | Audio input | Video input | [Token-level streaming](/docs/how_to/chat_streaming/) | Native async | [Token usage](/docs/how_to/chat_token_usage_tracking/) | [Logprobs](/docs/how_to/logprobs/) |\n",
@@ -316,7 +316,7 @@
             "source": [
                 "## API reference\n",
                 "\n",
-                "For detailed documentation of all ChatOutlines features and configurations head to the API reference: https://api.python.langchain.com/en/latest/chat_models/outlines.chat_models.ChatOutlines.html\n",
+                "For detailed documentation of all ChatOutlines features and configurations head to the API reference: https://python.langchain.com/api_reference/community/chat_models/langchain_community.chat_models.outlines.ChatOutlines.html\n",
                 "\n",
                 "## Full Outlines Documentation: \n",
                 "\n",
diff --git a/docs/docs/integrations/chat/sambastudio.ipynb b/docs/docs/integrations/chat/sambastudio.ipynb
index 64dd05fd96b8c..1ad3ff2805049 100644
--- a/docs/docs/integrations/chat/sambastudio.ipynb
+++ b/docs/docs/integrations/chat/sambastudio.ipynb
@@ -19,7 +19,7 @@
    "source": [
     "# ChatSambaStudio\n",
     "\n",
-    "This will help you getting started with SambaStudio [chat models](/docs/concepts/chat_models). For detailed documentation of all ChatStudio features and configurations head to the [API reference](https://api.python.langchain.com/en/latest/chat_models/langchain_community.chat_models.sambanova.ChatSambaStudio.html).\n",
+    "This will help you getting started with SambaStudio [chat models](/docs/concepts/chat_models). For detailed documentation of all ChatStudio features and configurations head to the [API reference](https://python.langchain.com/api_reference/community/chat_models/langchain_community.chat_models.sambanova.ChatSambaStudio.html).\n",
     "\n",
     "**[SambaNova](https://sambanova.ai/)'s** [SambaStudio](https://docs.sambanova.ai/sambastudio/latest/sambastudio-intro.html) SambaStudio is a rich, GUI-based platform that provides the functionality to train, deploy, and manage models in SambaNova [DataScale](https://sambanova.ai/products/datascale) systems.\n",
     "\n",
@@ -28,7 +28,7 @@
     "\n",
     "| Class | Package | Local | Serializable | JS support | Package downloads | Package latest |\n",
     "| :--- | :--- | :---: | :---: |  :---: | :---: | :---: |\n",
-    "| [ChatSambaStudio](https://api.python.langchain.com/en/latest/chat_models/langchain_community.chat_models.sambanova.ChatSambaStudio.html) | [langchain-community](https://python.langchain.com/api_reference/community/index.html) | ❌ | ❌ | ❌ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/langchain_community?style=flat-square&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/langchain_community?style=flat-square&label=%20) |\n",
+    "| [ChatSambaStudio](https://python.langchain.com/api_reference/community/chat_models/langchain_community.chat_models.sambanova.ChatSambaStudio.html) | [langchain-community](https://python.langchain.com/api_reference/community/index.html) | ❌ | ❌ | ❌ | ![PyPI - Downloads](https://img.shields.io/pypi/dm/langchain_community?style=flat-square&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/langchain_community?style=flat-square&label=%20) |\n",
     "\n",
     "### Model features\n",
     "\n",
@@ -355,7 +355,7 @@
    "source": [
     "## API reference\n",
     "\n",
-    "For detailed documentation of all ChatSambaStudio features and configurations head to the API reference: https://api.python.langchain.com/en/latest/chat_models/langchain_community.chat_models.sambanova.ChatSambaStudio.html"
+    "For detailed documentation of all ChatSambaStudio features and configurations head to the API reference: https://python.langchain.com/api_reference/community/chat_models/langchain_community.chat_models.sambanova.ChatSambaStudio.html"
    ]
   }
  ],
diff --git a/docs/docs/integrations/document_loaders/sitemap.ipynb b/docs/docs/integrations/document_loaders/sitemap.ipynb
index e930b12de31ff..ed6c74d406bfe 100644
--- a/docs/docs/integrations/document_loaders/sitemap.ipynb
+++ b/docs/docs/integrations/document_loaders/sitemap.ipynb
@@ -103,7 +103,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
diff --git a/docs/docs/integrations/document_loaders/tomarkdown.ipynb b/docs/docs/integrations/document_loaders/tomarkdown.ipynb
index ffc41ea4e5f7c..0f3ce0de36a55 100644
--- a/docs/docs/integrations/document_loaders/tomarkdown.ipynb
+++ b/docs/docs/integrations/document_loaders/tomarkdown.ipynb
@@ -153,7 +153,7 @@
       "\n",
       "Best practices for developing with LangChain.\n",
       "\n",
-      "### [API reference](https://api.python.langchain.com) [​](\\#api-reference \"Direct link to api-reference\")\n",
+      "### [API reference](https://python.langchain.com/api_reference/) [​](\\#api-reference \"Direct link to api-reference\")\n",
       "\n",
       "Head to the reference section for full documentation of all classes and methods in the LangChain and LangChain Experimental Python packages.\n",
       "\n",
diff --git a/docs/docs/integrations/llms/oci_model_deployment_endpoint.ipynb b/docs/docs/integrations/llms/oci_model_deployment_endpoint.ipynb
index 0110a9d575646..1449e6789f28c 100644
--- a/docs/docs/integrations/llms/oci_model_deployment_endpoint.ipynb
+++ b/docs/docs/integrations/llms/oci_model_deployment_endpoint.ipynb
@@ -180,9 +180,9 @@
     "\n",
     "For comprehensive details on all features and configurations, please refer to the API reference documentation for each class:\n",
     "\n",
-    "* [OCIModelDeploymentLLM](https://api.python.langchain.com/en/latest/llms/langchain_community.llms.oci_data_science_model_deployment_endpoint.OCIModelDeploymentLLM.html)\n",
-    "* [OCIModelDeploymentVLLM](https://api.python.langchain.com/en/latest/llms/langchain_community.llms.oci_data_science_model_deployment_endpoint.OCIModelDeploymentVLLM.html)\n",
-    "* [OCIModelDeploymentTGI](https://api.python.langchain.com/en/latest/llms/langchain_community.llms.oci_data_science_model_deployment_endpoint.OCIModelDeploymentTGI.html)"
+    "* [OCIModelDeploymentLLM](https://python.langchain.com/api_reference/community/llms/langchain_community.llms.oci_data_science_model_deployment_endpoint.OCIModelDeploymentLLM.html)\n",
+    "* [OCIModelDeploymentVLLM](https://python.langchain.com/api_reference/community/llms/langchain_community.llms.oci_data_science_model_deployment_endpoint.OCIModelDeploymentVLLM.html)\n",
+    "* [OCIModelDeploymentTGI](https://python.langchain.com/api_reference/community/llms/langchain_community.llms.oci_data_science_model_deployment_endpoint.OCIModelDeploymentTGI.html)"
    ]
   }
  ],
diff --git a/docs/docs/integrations/llms/outlines.ipynb b/docs/docs/integrations/llms/outlines.ipynb
index f9c434ef97475..0f29e87300a06 100644
--- a/docs/docs/integrations/llms/outlines.ipynb
+++ b/docs/docs/integrations/llms/outlines.ipynb
@@ -6,7 +6,7 @@
    "source": [
     "# Outlines\n",
     "\n",
-    "This will help you getting started with Outlines LLM. For detailed documentation of all Outlines features and configurations head to the [API reference](https://api.python.langchain.com/en/latest/llms/outlines.llms.Outlines.html).\n",
+    "This will help you getting started with Outlines LLM. For detailed documentation of all Outlines features and configurations head to the [API reference](https://python.langchain.com/api_reference/community/llms/langchain_community.llms.outlines.Outlines.html).\n",
     "\n",
     "[Outlines](https://github.com/outlines-dev/outlines) is a library for constrained language generation. It allows you to use large language models (LLMs) with various backends while applying constraints to the generated output.\n",
     "\n",
@@ -236,7 +236,7 @@
    "source": [
     "## API reference\n",
     "\n",
-    "For detailed documentation of all ChatOutlines features and configurations head to the API reference: https://api.python.langchain.com/en/latest/chat_models/outlines.chat_models.ChatOutlines.html\n",
+    "For detailed documentation of all ChatOutlines features and configurations head to the API reference: https://python.langchain.com/api_reference/community/chat_models/langchain_community.chat_models.outlines.ChatOutlines.html\n",
     "\n",
     "## Outlines Documentation: \n",
     "\n",
diff --git a/docs/docs/integrations/retrievers/fleet_context.ipynb b/docs/docs/integrations/retrievers/fleet_context.ipynb
index db3e6e79cbab6..2c2d7e6083c3d 100644
--- a/docs/docs/integrations/retrievers/fleet_context.ipynb
+++ b/docs/docs/integrations/retrievers/fleet_context.ipynb
@@ -9,7 +9,7 @@
     "\n",
     ">[Fleet AI Context](https://www.fleet.so/context) is a dataset of high-quality embeddings of the top 1200 most popular & permissive Python Libraries & their documentation.\n",
     ">\n",
-    ">The `Fleet AI` team is on a mission to embed the world's most important data. They've started by embedding the top 1200 Python libraries to enable code generation with up-to-date knowledge. They've been kind enough to share their embeddings of the [LangChain docs](/docs/introduction) and [API reference](https://api.python.langchain.com/en/latest/api_reference.html).\n",
+    ">The `Fleet AI` team is on a mission to embed the world's most important data. They've started by embedding the top 1200 Python libraries to enable code generation with up-to-date knowledge. They've been kind enough to share their embeddings of the [LangChain docs](/docs/introduction) and [API reference](https://python.langchain.com/api_reference/).\n",
     "\n",
     "Let's take a look at how we can use these embeddings to power a docs retrieval system and ultimately a simple code-generating chain!"
    ]
diff --git a/docs/docs/integrations/text_embedding/databricks.ipynb b/docs/docs/integrations/text_embedding/databricks.ipynb
index 8dfb6237dd9c4..31505992ca7ed 100644
--- a/docs/docs/integrations/text_embedding/databricks.ipynb
+++ b/docs/docs/integrations/text_embedding/databricks.ipynb
@@ -28,7 +28,7 @@
     "\n",
     "| Class | Package |\n",
     "| :--- | :--- |\n",
-    "| [DatabricksEmbeddings](https://api.python.langchain.com/en/latest/embeddings/langchain_databricks.embeddings.DatabricksEmbeddings.html) | [databricks-langchain](https://python.langchain.com/docs/integrations/providers/databricks/) |\n",
+    "| [DatabricksEmbeddings](https://python.langchain.com/api_reference/community/embeddings/langchain_community.embeddings.databricks.DatabricksEmbeddings.html) | [databricks-langchain](https://python.langchain.com/docs/integrations/providers/databricks/) |\n",
     "\n",
     "### Supported Methods\n",
     "\n",
diff --git a/docs/docs/integrations/text_embedding/zhipuai.ipynb b/docs/docs/integrations/text_embedding/zhipuai.ipynb
index da5de5fbf19a4..d33ac41c93e9b 100644
--- a/docs/docs/integrations/text_embedding/zhipuai.ipynb
+++ b/docs/docs/integrations/text_embedding/zhipuai.ipynb
@@ -251,7 +251,7 @@
    "source": [
     "## API Reference\n",
     "\n",
-    "For detailed documentation on `ZhipuAIEmbeddings` features and configuration options, please refer to the [API reference](https://api.python.langchain.com/en/latest/embeddings/langchain_community.embeddings.zhipuai.ZhipuAIEmbeddings.html).\n"
+    "For detailed documentation on `ZhipuAIEmbeddings` features and configuration options, please refer to the [API reference](https://python.langchain.com/api_reference/community/embeddings/langchain_community.embeddings.zhipuai.ZhipuAIEmbeddings.html).\n"
    ]
   }
  ],
diff --git a/docs/docs/integrations/vectorstores/databricks_vector_search.ipynb b/docs/docs/integrations/vectorstores/databricks_vector_search.ipynb
index 28685cbd0e271..65ed390b9da32 100644
--- a/docs/docs/integrations/vectorstores/databricks_vector_search.ipynb
+++ b/docs/docs/integrations/vectorstores/databricks_vector_search.ipynb
@@ -506,7 +506,7 @@
    "source": [
     "## API reference\n",
     "\n",
-    "For detailed documentation of all DatabricksVectorSearch features and configurations head to the API reference: https://api.python.langchain.com/en/latest/vectorstores/langchain_databricks.vectorstores.DatabricksVectorSearch.html"
+    "For detailed documentation of all DatabricksVectorSearch features and configurations head to the API reference: https://python.langchain.com/api_reference/databricks/vectorstores/langchain_databricks.vectorstores.DatabricksVectorSearch.html"
    ]
   }
  ],
diff --git a/docs/docs/integrations/vectorstores/mongodb_atlas.ipynb b/docs/docs/integrations/vectorstores/mongodb_atlas.ipynb
index 65d19ce6733cc..a891a53f80bf6 100644
--- a/docs/docs/integrations/vectorstores/mongodb_atlas.ipynb
+++ b/docs/docs/integrations/vectorstores/mongodb_atlas.ipynb
@@ -439,7 +439,7 @@
    "source": [
     "#### Other search methods\n",
     "\n",
-    "There are a variety of other search methods that are not covered in this notebook, such as MMR search or searching by vector. For a full list of the search abilities available for `MongoDBAtlasVectorStore` check out the [API reference](https://api.python.langchain.com/en/latest/vectorstores/langchain_mongodb.vectorstores.MongoDBAtlasVectorSearch.html)."
+    "There are a variety of other search methods that are not covered in this notebook, such as MMR search or searching by vector. For a full list of the search abilities available for `MongoDBAtlasVectorStore` check out the [API reference](https://python.langchain.com/api_reference/mongodb/vectorstores/langchain_mongodb.vectorstores.MongoDBAtlasVectorSearch.html)."
    ]
   },
   {
diff --git a/docs/docs/integrations/vectorstores/sqlitevec.ipynb b/docs/docs/integrations/vectorstores/sqlitevec.ipynb
index 33eb5b854d502..2df878ad238bc 100644
--- a/docs/docs/integrations/vectorstores/sqlitevec.ipynb
+++ b/docs/docs/integrations/vectorstores/sqlitevec.ipynb
@@ -155,7 +155,7 @@
    "cell_type": "markdown",
    "source": [
     "## API reference\n",
-    "For detailed documentation of all SQLiteVec features and configurations head to the API reference:https://api.python.langchain.com/en/latest/vectorstores/langchain_community.vectorstores.sqlitevec.SQLiteVec.html"
+    "For detailed documentation of all SQLiteVec features and configurations head to the API reference: https://python.langchain.com/api_reference/community/vectorstores/langchain_community.vectorstores.sqlitevec.SQLiteVec.html"
    ]
   },
   {
diff --git a/docs/docs/versions/migrating_memory/conversation_buffer_window_memory.ipynb b/docs/docs/versions/migrating_memory/conversation_buffer_window_memory.ipynb
index f031e1dbb70d2..4e53e5506b8d4 100644
--- a/docs/docs/versions/migrating_memory/conversation_buffer_window_memory.ipynb
+++ b/docs/docs/versions/migrating_memory/conversation_buffer_window_memory.ipynb
@@ -426,7 +426,7 @@
     "\n",
     "## Usage with a pre-built langgraph agent\n",
     "\n",
-    "This example shows usage of an Agent Executor with a pre-built agent constructed using the [create_tool_calling_agent](https://api.python.langchain.com/en/latest/agents/langchain.agents.tool_calling_agent.base.create_tool_calling_agent.html) function.\n",
+    "This example shows usage of an Agent Executor with a pre-built agent constructed using the [create_tool_calling_agent](https://python.langchain.com/api_reference/langchain/agents/langchain.agents.tool_calling_agent.base.create_tool_calling_agent.html) function.\n",
     "\n",
     "If you are using one of the [old LangChain pre-built agents](https://python.langchain.com/v0.1/docs/modules/agents/agent_types/), you should be able\n",
     "to replace that code with the new [langgraph pre-built agent](https://langchain-ai.github.io/langgraph/how-tos/create-react-agent/) which leverages\n",
@@ -673,7 +673,7 @@
     "</details>\n",
     "\n",
     "If you need to implement more efficient logic and want to use `RunnableWithMessageHistory` for now the way to achieve this\n",
-    "is to subclass from [BaseChatMessageHistory](https://api.python.langchain.com/en/latest/chat_history/langchain_core.chat_history.BaseChatMessageHistory.html) and\n",
+    "is to subclass from [BaseChatMessageHistory](https://python.langchain.com/api_reference/core/chat_history/langchain_core.chat_history.BaseChatMessageHistory.html) and\n",
     "define appropriate logic for `add_messages` (that doesn't simply append the history, but instead re-writes it).\n",
     "\n",
     "Unless you have a good reason to implement this solution, you should instead use LangGraph."
diff --git a/libs/community/README.md b/libs/community/README.md
index 38240d2c9486a..02b1e754764d5 100644
--- a/libs/community/README.md
+++ b/libs/community/README.md
@@ -13,7 +13,7 @@ pip install langchain-community
 
 LangChain Community contains third-party integrations that implement the base interfaces defined in LangChain Core, making them ready-to-use in any LangChain application.
 
-For full documentation see the [API reference](https://api.python.langchain.com/en/stable/community_api_reference.html).
+For full documentation see the [API reference](https://python.langchain.com/api_reference/community/index.html).
 
 ![Diagram outlining the hierarchical organization of the LangChain framework, displaying the interconnected parts across multiple layers.](https://raw.githubusercontent.com/langchain-ai/langchain/e1d113ea84a2edcf4a7709fc5be0e972ea74a5d9/docs/static/svg/langchain_stack_112024.svg "LangChain Framework Overview")
 
diff --git a/libs/community/langchain_community/vectorstores/tencentvectordb.py b/libs/community/langchain_community/vectorstores/tencentvectordb.py
index c3bda890fe241..7d408c21132af 100644
--- a/libs/community/langchain_community/vectorstores/tencentvectordb.py
+++ b/libs/community/langchain_community/vectorstores/tencentvectordb.py
@@ -6,7 +6,18 @@
 import logging
 import time
 from enum import Enum
-from typing import Any, Dict, Iterable, List, Optional, Sequence, Tuple, Union, cast
+from typing import (
+    Any,
+    Callable,
+    Dict,
+    Iterable,
+    List,
+    Optional,
+    Sequence,
+    Tuple,
+    Union,
+    cast,
+)
 
 import numpy as np
 from langchain_core.documents import Document
@@ -168,8 +179,8 @@ def __init__(
         tcvectordb = guard_import("tcvectordb")
         tcollection = guard_import("tcvectordb.model.collection")
         enum = guard_import("tcvectordb.model.enum")
-
-        if t_vdb_embedding:
+        self.embedding_model = None
+        if embedding is None and t_vdb_embedding:
             embedding_model = [
                 model
                 for model in enum.EmbeddingModel
@@ -566,3 +577,17 @@ def max_marginal_relevance_search_by_vector(
         )
         # Reorder the values and return.
         return [documents[x] for x in new_ordering if x != -1]
+
+    def _select_relevance_score_fn(self) -> Callable[[float], float]:
+        metric_type = self.index_params.metric_type
+        if metric_type == "COSINE":
+            return self._cosine_relevance_score_fn
+        elif metric_type == "L2":
+            return self._euclidean_relevance_score_fn
+        elif metric_type == "IP":
+            return self._max_inner_product_relevance_score_fn
+        else:
+            raise ValueError(
+                "No supported normalization function"
+                f" for distance metric of type: {metric_type}."
+            )
diff --git a/libs/core/README.md b/libs/core/README.md
index c833c2039468f..fb09de946ec22 100644
--- a/libs/core/README.md
+++ b/libs/core/README.md
@@ -17,7 +17,7 @@ These abstractions are designed to be as modular and simple as possible. Example
 
 The benefit of having these abstractions is that any provider can implement the required interface and then easily be used in the rest of the LangChain ecosystem.
 
-For full documentation see the [API reference](https://api.python.langchain.com/en/stable/core_api_reference.html).
+For full documentation see the [API reference](https://python.langchain.com/api_reference/core/index.html).
 
 ## 1️⃣ Core Interface: Runnables
 
diff --git a/libs/text-splitters/README.md b/libs/text-splitters/README.md
index 83d711b8ec0f6..fbbfc34f5d69b 100644
--- a/libs/text-splitters/README.md
+++ b/libs/text-splitters/README.md
@@ -13,7 +13,7 @@ pip install langchain-text-splitters
 
 LangChain Text Splitters contains utilities for splitting into chunks a wide variety of text documents.
 
-For full documentation see the [API reference](https://api.python.langchain.com/en/stable/text_splitters_api_reference.html)
+For full documentation see the [API reference](https://python.langchain.com/api_reference/text_splitters/index.html)
 and the [Text Splitters](https://python.langchain.com/docs/modules/data_connection/document_transformers/) module in the main docs.
 
 ## 📕 Releases & Versioning