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Update docs: LangChain agent memory (#23673)

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**Description:** Update docs content on agent memory

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baskaryan, efriis, eyurtsev, ccurme, vbarda, hwchase17.
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docs/docs/integrations/platforms/microsoft.mdx
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@ -223,9 +223,15 @@ See a [usage example](/docs/integrations/document_loaders/microsoft_onenote).
from langchain_community.document_loaders.onenote import OneNoteLoader
```
## Vector stores
## AI Agent Memory System
### Azure Cosmos DB MongoDB vCore
[AI agent](https://learn.microsoft.com/en-us/azure/cosmos-db/ai-agents) needs robust memory systems that support multi-modality, offer strong operational performance, and enable agent memory sharing as well as separation.
AI agents can rely on Azure Cosmos DB as a unified [memory system](https://learn.microsoft.com/en-us/azure/cosmos-db/ai-agents#memory-can-make-or-break-agents) solution, enjoying speed, scale, and simplicity. This service successfully [enabled OpenAI's ChatGPT service](https://www.youtube.com/watch?v=6IIUtEFKJec&t) to scale dynamically with high reliability and low maintenance. Powered by an atom-record-sequence engine, it is the world's first globally distributed [NoSQL](https://learn.microsoft.com/en-us/azure/cosmos-db/distributed-nosql), [relational](https://learn.microsoft.com/en-us/azure/cosmos-db/distributed-relational), and [vector database](https://learn.microsoft.com/en-us/azure/cosmos-db/vector-database) service that offers a serverless mode.
Below are two available Azure Cosmos DB APIs that can provide vector store functionalities.
### Azure Cosmos DB for MongoDB (vCore)
>[Azure Cosmos DB for MongoDB vCore](https://learn.microsoft.com/en-us/azure/cosmos-db/mongodb/vcore/) makes it easy to create a database with full native MongoDB support.
> You can apply your MongoDB experience and continue to use your favorite MongoDB drivers, SDKs, and tools by pointing your application to the API for MongoDB vCore account's connection string.