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Fix grammar & typos: minor fixes across docs (#7423)

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Co-authored-by: mintlify[bot] <109931778+mintlify[bot]@users.noreply.github.com>
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mintlify[bot]
2026-09-23 19:53:11 +05:30
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parent 8c02c425a5
commit 83b07b1537
4 changed files with 4 additions and 4 deletions
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docs/components/embedders/models/together.mdx
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@@ -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>
docs/components/vectordbs/dbs/azure.mdx
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@@ -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.
docs/cookbooks/integrations/healthcare-google-adk.mdx
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@@ -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
docs/integrations/llama-index.mdx
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@@ -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 = {