Fix new broken links

Author: npentrel

src/oss/contributing/implement-langchain.mdx

@@ -33,7 +33,7 @@ Your integration package will typically implement a subclass of at least one of
         Retrievers are used to retrieve documents from APIs, databases, or other sources based on a query. The Retriever class must inherit from the BaseRetriever base class.
 
         <Warning>
-            The retriever integration guide is currently WIP. In the meantime, read the [retriever conceptual guide](/oss/langchain/retrievers) for details on how LangChain retrievers function.
+            The retriever integration guide is currently WIP. In the meantime, read the [retriever conceptual guide](/oss/integrations/retrievers) for details on how LangChain retrievers function.
         </Warning>
     </Tab>
     <Tab title="Vector Stores">
@@ -42,14 +42,14 @@ Your integration package will typically implement a subclass of at least one of
         See the [vector store integration guide](/oss/integrations/vectorstores) for details on implementing a vector store integration.
 
         <Warning>
-            The vector store integration guide is currently WIP. In the meantime, read the [vector store conceptual guide](/oss/langchain/vectorstores) for details on how LangChain vector stores function.
+            The vector store integration guide is currently WIP. In the meantime, read the [vector store conceptual guide](/oss/integrations/vectorstores) for details on how LangChain vector stores function.
         </Warning>
     </Tab>
     <Tab title="Embeddings">
         Embedding models are subclasses of the [`Embeddings`](https://python.langchain.com/api_reference/core/embeddings/langchain_core.embeddings.embeddings.Embeddings.html) class.
 
         <Warning>
-            The embedding model integration guide is currently WIP. In the meantime, read the [embedding model conceptual guide](/oss/langchain/text_embedding) for details on how LangChain embedding models function.
+            The embedding model integration guide is currently WIP. In the meantime, read the [embedding model conceptual guide](/oss/integrations/text_embedding) for details on how LangChain embedding models function.
         </Warning>
     </Tab>
 </Tabs>