diff --git a/docs/components/embedders/models/together.mdx b/docs/components/embedders/models/together.mdx
index 75f44227e..a71c1764a 100644
--- a/docs/components/embedders/models/together.mdx
+++ b/docs/components/embedders/models/together.mdx
@@ -11,7 +11,7 @@ To use Together embedding models, set the `TOGETHER_API_KEY` environment variabl
 <Note> The `embedding_model_dims` parameter for `vector_store` should be set to `1024` for Together embedder. </Note>
 
 <Warning>
-**Breaking default change.** The default Together embedding model is now `intfloat/multilingual-e5-large-instruct` (**1024-dim**), replacing the previous default `togethercomputer/m2-bert-80M-8k-retrieval` (**768-dim**). If you created a self-hosted vector store with the old default, its collection is 768-dim and will reject the new 1024-dim vectors **recreate/reindex the collection at 1024 dimensions** after upgrading. To defer the change, pin the previous values explicitly (`model="togethercomputer/m2-bert-80M-8k-retrieval"`, `embedding_dims=768`) note Together no longer lists this model among its recommended embeddings, so reindexing at 1024 is the durable path.
+**Breaking default change.** The default Together embedding model is now `intfloat/multilingual-e5-large-instruct` (**1024-dim**), replacing the previous default `togethercomputer/m2-bert-80M-8k-retrieval` (**768-dim**). If you created a self-hosted vector store with the old default, its collection is 768-dim and will reject the new 1024-dim vectors — **recreate/reindex the collection at 1024 dimensions** after upgrading. To defer the change, pin the previous values explicitly (`model="togethercomputer/m2-bert-80M-8k-retrieval"`, `embedding_dims=768`) — note Together no longer lists this model among its recommended embeddings, so reindexing at 1024 is the durable path.
 </Warning>
 
 <CodeGroup>
diff --git a/docs/components/vectordbs/dbs/azure.mdx b/docs/components/vectordbs/dbs/azure.mdx
index 93a0bf4ad..8577b50cc 100644
--- a/docs/components/vectordbs/dbs/azure.mdx
+++ b/docs/components/vectordbs/dbs/azure.mdx
@@ -95,7 +95,7 @@ Uses the identity from Azure PowerShell (`Connect-AzAccount`).
 7. **Azure Developer CLI Credential:**
 Uses the session from Azure Developer CLI (`azd auth login`).
 
-<Note> If an API is provided, it will be used for authentication over an Azure Identity </Note>
+<Note> If an API key is provided, it will be used for authentication over an Azure Identity </Note>
 To enable Role-Based Access Control (RBAC) for Azure AI Search, follow these steps:
 
 1. In the Azure Portal, navigate to your **Azure AI Search** service.
diff --git a/docs/cookbooks/integrations/healthcare-google-adk.mdx b/docs/cookbooks/integrations/healthcare-google-adk.mdx
index 0696f45e5..9c9571a66 100644
--- a/docs/cookbooks/integrations/healthcare-google-adk.mdx
+++ b/docs/cookbooks/integrations/healthcare-google-adk.mdx
@@ -30,7 +30,7 @@ pip install google-adk mem0ai python-dotenv
 
 ## Code Breakdown
 
-Let's get started and understand the different components required in building a healthcare assistant powered by memory
+Let's get started and understand the different components required in building a healthcare assistant powered by memory.
 
 ```python
 # Import dependencies
diff --git a/docs/integrations/llama-index.mdx b/docs/integrations/llama-index.mdx
index f2bc02491..d529937f6 100644
--- a/docs/integrations/llama-index.mdx
+++ b/docs/integrations/llama-index.mdx
@@ -45,7 +45,7 @@ memory_from_client = Mem0Memory.from_client(
 )
 ```
 
-Context is used to identify the user, agent or the conversation in the Mem0. It is required to be passed in the at least one of the fields in the `Mem0Memory` constructor. It can be any of the following:
+Context is used to identify the user, agent or the conversation in the Mem0. It is required to be passed in at least one of the fields in the `Mem0Memory` constructor. It can be any of the following:
 
 ```python
 context = {