feat (pinecone): Add namespace support and improve type safety (#3216)

docs/components/vectordbs/dbs/pinecone.mdx

@@ -1,5 +1,7 @@
 [Pinecone](https://www.pinecone.io/) is a fully managed vector database designed for machine learning applications, offering high performance vector search with low latency at scale. It's particularly well-suited for semantic search, recommendation systems, and other AI-powered applications.
 
+> **New**: Pinecone integration now supports custom namespaces! Use the `namespace` parameter to logically separate data within the same index. This is especially useful for multi-tenant or multi-user applications.
+
 > **Note**: Before configuring Pinecone, you need to select an embedding model (e.g., OpenAI, Cohere, or custom models) and ensure the `embedding_model_dims` in your config matches your chosen model's dimensions. For example, OpenAI's text-embedding-3-small uses 1536 dimensions.
 
 ### Usage
@@ -18,6 +20,7 @@ config = {
         "config": {
             "collection_name": "testing",
             "embedding_model_dims": 1536,  # Matches OpenAI's text-embedding-3-small
+            "namespace": "my-namespace", # Optional: specify a namespace for multi-tenancy
             "serverless_config": {
                 "cloud": "aws",  # Choose between 'aws' or 'gcp' or 'azure'
                 "region": "us-east-1"
@@ -53,6 +56,7 @@ Here are the parameters available for configuring Pinecone:
 | `hybrid_search` | Whether to enable hybrid search | `False` |
 | `metric` | Distance metric for vector similarity | `"cosine"` |
 | `batch_size` | Batch size for operations | `100` |
+| `namespace` | Namespace for the collection, useful for multi-tenancy. | `None` |
 
 > **Important**: You must choose either `serverless_config` or `pod_config` for your deployment, but not both.
 
@@ -64,6 +68,7 @@ config = {
         "config": {
             "collection_name": "memory_index",
             "embedding_model_dims": 1536,  # For OpenAI's text-embedding-3-small
+            "namespace": "my-namespace",  # Optional: custom namespace
             "serverless_config": {
                 "cloud": "aws",  # or "gcp" or "azure"
                 "region": "us-east-1"  # Choose appropriate region
@@ -81,6 +86,7 @@ config = {
         "config": {
             "collection_name": "memory_index",
             "embedding_model_dims": 1536,  # For OpenAI's text-embedding-ada-002
+            "namespace": "my-namespace",  # Optional: custom namespace
             "pod_config": {
                 "environment": "gcp-starter",
                 "replicas": 1,