feat(vector-stores): add S3 Vectors provider to TypeScript OSS SDK (#5822)

Co-authored-by: kartik-mem0 <kartik.labhshetwar@mem0.ai>

docs/components/vectordbs/dbs/s3_vectors.mdx

@@ -9,15 +9,22 @@ description: "Use Amazon S3 Vectors as a cost-optimized vector storage service i
 
 S3 Vectors support requires additional dependencies. Install them with:
 
-```bash
+<CodeGroup>
+```bash Python
 pip install boto3
 ```
 
+```bash TypeScript
+npm install @aws-sdk/client-s3vectors
+```
+</CodeGroup>
+
 ### Usage
 
 To use Amazon S3 Vectors with Mem0, you need to have an AWS account and the necessary IAM permissions (`s3vectors:*`). Ensure your environment is configured with AWS credentials (e.g., via `~/.aws/credentials` or environment variables).
 
-```python
+<CodeGroup>
+```python Python
 import os
 from mem0 import Memory
 
@@ -47,6 +54,36 @@ messages = [
 m.add(messages, user_id="alice", metadata={"category": "movies"})
 ```
 
+```typescript TypeScript
+import { Memory } from 'mem0ai/oss';
+
+// Ensure your AWS credentials are configured in your environment
+// e.g., by setting AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, and AWS_DEFAULT_REGION
+
+const config = {
+  vectorStore: {
+    provider: 's3_vectors',
+    config: {
+      vectorBucketName: 'my-mem0-vector-bucket',
+      collectionName: 'my-memories-index',
+      embeddingModelDims: 1536,
+      distanceMetric: 'cosine',
+      region: 'us-east-1',
+    },
+  },
+};
+
+const memory = new Memory(config);
+const messages = [
+    {"role": "user", "content": "I'm planning to watch a movie tonight. Any recommendations?"},
+    {"role": "assistant", "content": "How about a thriller movie? They can be quite engaging."},
+    {"role": "user", "content": "I'm not a big fan of thriller movies but I love sci-fi movies."},
+    {"role": "assistant", "content": "Got it! I'll avoid thriller recommendations and suggest sci-fi movies in the future."}
+]
+await memory.add(messages, { userId: "alice", metadata: { category: "movies" } });
+```
+</CodeGroup>
+
 ### Config
 
 Here are the parameters available for configuring Amazon S3 Vectors:

docs/components/vectordbs/overview.mdx

@@ -10,7 +10,7 @@ Mem0 includes built-in support for various popular databases. Memory can utilize
 See the list of supported vector databases below.
 
 <Note>
-  The following vector databases are supported in the Python implementation. The TypeScript implementation currently supports Qdrant, Redis, PGVector, Supabase, LangChain, Azure AI Search, Vectorize, and an in-memory store.
+  The following vector databases are supported in the Python implementation. The TypeScript implementation currently supports Qdrant, Redis, PGVector, Supabase, LangChain, Azure AI Search, Vectorize, Amazon S3 Vectors, and an in-memory store.
 </Note>
 
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