.Net: Add PostgresVectorStore Memory connector.

[lossyrob]

This PR adds a PostgresVectorStore and related classes to Microsoft.SemanticKernel.Connectors.Postgres.

Motivation and Context

As part of the move to having memory connectors implement the new Microsoft.Extensions.VectorData.IVectorStore architecture (see https:/microsoft/semantic-kernel/blob/main/docs/decisions/0050-updated-vector-store-design.md), each memory connector needs to be updated with the new architecture. This PR tackles updating the existing Microsoft.SemanticKernel.Connectors.Postgres package to include this implementation. This will supercede the PostgresMemoryStore implementation.

Some high level comments about design:

• PostgresVectorStore and PostgresVectorStoreRecordCollection get injected with an IPostgresVectorStoreDbClient. This abstracts the database communication and allows for unit tests to mock database interactions.
• The PostgresVectorStoreDbClient gets passed in a NpgsqlDataSource from the user, which is used to manage connections to the database. The responsibility of connection pool lifecycle management is on the user.
• The IPostgresVectorStoreDbClient is designed to accept and produce the storage model, which in this case is a Dictionary<string, object?> . This is the intermediate type that is mapped to by the IVectorStoreRecordMapper.
• The PostgresVectorStoreDbClient also takes a IPostgresVectorStoreCollectionSqlBuilder, which generates SQL command information for interacting with the database. This abstracts the SQL queries related to each task, and allows for future expansion. This is particularly targeted at creating a AzureDBForPostgre vector store that will enable alternate vector implementations like DiskANN, while leveraging the same database client as the Postgres connector.
•  The integration tests for the vector store utilize Docker.Net to bring up a pgvector/pgvector docker container, which test are run against.

TODO:

• Finish implementing and testing all methods of PostgresVectorStoreRecordCollection, most of which can follow the existing code and patterns except for VectorizedSearchAsync and VectorizableTextSearchAsync, which are part of the IVectorizableTextSearch interface.
• Update the README in the package
• Create a sample in dotnet/samples/Concepts/Memory

Contribution Checklist

• The code builds clean without any errors or warnings
• The PR follows the SK Contribution Guidelines and the pre-submission formatting script raises no violations
• All unit tests pass, and I have added new tests where possible
• I didn't break anyone 😄