[docs] use the correct formatting for Pinecone

README.md

@@ -26,7 +26,7 @@ You can find more details in the [Reference Documentation](https://docs.spring.i
   - **Latest Models**: GPT-5, and other cutting-edge models for advanced AI applications.
 * Portable API support across AI providers for both synchronous and streaming options. Access to [model-specific features](https://docs.spring.io/spring-ai/reference/api/chatmodel.html#_chat_options) is also available.
 * [Structured Outputs](https://docs.spring.io/spring-ai/reference/api/structured-output-converter.html) - Mapping of AI Model output to POJOs.
-* Support for all major [Vector Database providers](https://docs.spring.io/spring-ai/reference/api/vectordbs.html) such as *Apache Cassandra, Azure Vector Search, Chroma, Elasticsearch, Milvus, MongoDB Atlas, MariaDB, Neo4j, Oracle, PostgreSQL/PGVector, PineCone, Qdrant, Redis, and Weaviate*.
+* Support for all major [Vector Database providers](https://docs.spring.io/spring-ai/reference/api/vectordbs.html) such as *Apache Cassandra, Azure Vector Search, Chroma, Elasticsearch, Milvus, MongoDB Atlas, MariaDB, Neo4j, Oracle, PostgreSQL/PGVector, Pinecone, Qdrant, Redis, and Weaviate*.
 * Portable API across Vector Store providers, including a novel SQL-like [metadata filter API](https://docs.spring.io/spring-ai/reference/api/vectordbs.html#metadata-filters).
 * [Tools/Function Calling](https://docs.spring.io/spring-ai/reference/api/tools.html) - permits the model to request the execution of client-side tools and functions, thereby accessing necessary real-time information as required.
 * [Observability](https://docs.spring.io/spring-ai/reference/observability/index.html) - Provides insights into AI-related operations.
@@ -156,4 +156,4 @@ define the source file coding standards we use along with some IDEA editor setti
 
 ## Contributing
 
-Your contributions are always welcome! Please read the [contribution guidelines](CONTRIBUTING.adoc) first.
+Your contributions are always welcome! Please read the [contribution guidelines](CONTRIBUTING.adoc) first.

spring-ai-docs/src/main/antora/modules/ROOT/pages/api/vectordbs.adoc

@@ -391,7 +391,7 @@ These are the available implementations of the `VectorStore` interface:
 * xref:api/vectordbs/opensearch.adoc[OpenSearch Vector Store] - The https://opensearch.org/platform/search/vector-database.html[OpenSearch] vector store.
 * xref:api/vectordbs/oracle.adoc[Oracle Vector Store] - The https://docs.oracle.com/en/database/oracle/oracle-database/23/vecse/overview-ai-vector-search.html[Oracle Database] vector store.
 * xref:api/vectordbs/pgvector.adoc[PgVector Store] - The https://github.com/pgvector/pgvector[PostgreSQL/PGVector] vector store.
-* xref:api/vectordbs/pinecone.adoc[Pinecone Vector Store] - https://www.pinecone.io/[PineCone] vector store.
+* xref:api/vectordbs/pinecone.adoc[Pinecone Vector Store] - https://www.pinecone.io/[Pinecone] vector store.
 * xref:api/vectordbs/qdrant.adoc[Qdrant Vector Store] - https://www.qdrant.tech/[Qdrant] vector store.
 * xref:api/vectordbs/redis.adoc[Redis Vector Store] - The https://redis.io/[Redis] vector store.
 * xref:api/vectordbs/hana.adoc[SAP Hana Vector Store] - The https://news.sap.com/2024/04/sap-hana-cloud-vector-engine-ai-with-business-context/[SAP HANA] vector store.

spring-ai-docs/src/main/antora/modules/ROOT/pages/index.adoc

@@ -26,7 +26,7 @@ Spring AI provides the following features:
 ** xref:api/audio/speech.adoc[Text to Speech]
 ** xref:api/moderation[Moderation]
 * xref:api/structured-output-converter.adoc[Structured Outputs] - Mapping of AI Model output to POJOs.
-* Support for all major xref:api/vectordbs.adoc[Vector Database providers] such as Apache Cassandra, Azure Cosmos DB, Azure Vector Search, Chroma, Elasticsearch, GemFire, MariaDB, Milvus, MongoDB Atlas, Neo4j, OpenSearch, Oracle, PostgreSQL/PGVector, PineCone, Qdrant, Redis, SAP Hana, Typesense and Weaviate.
+* Support for all major xref:api/vectordbs.adoc[Vector Database providers] such as Apache Cassandra, Azure Cosmos DB, Azure Vector Search, Chroma, Elasticsearch, GemFire, MariaDB, Milvus, MongoDB Atlas, Neo4j, OpenSearch, Oracle, PostgreSQL/PGVector, Pinecone, Qdrant, Redis, SAP Hana, Typesense and Weaviate.
 * Portable API across Vector Store providers, including a novel SQL-like metadata filter API.
 * xref:api/tools.adoc[Tools/Function Calling] - Permits the model to request the execution of client-side tools and functions, thereby accessing necessary real-time information as required and taking action.
 * xref:observability/index.adoc[Observability] - Provides insights into AI-related operations.