[dotnet-ai] Vector data search + data ingestion pipeline

[luisquintanilla]

Fixes #230
Part of #225

Dependencies

Merge order: This PR should be merged after #237 Plugin scaffold.

Summary

Adds two tightly related skills that form the data infrastructure layer of the RAG stack:

• vector-data-search Microsoft.Extensions.VectorData abstractions for storing, indexing, and querying vector embeddings with connector selection (Azure AI Search, Qdrant, Milvus, Weaviate, in-memory)
• data-ingestion-pipeline Microsoft.Extensions.DataIngestion pipeline for document loading, chunking strategies, enrichment, and integration with embeddings and vector storage

Changes

File	Description
plugins/dotnet-ai/skills/vector-data-search/SKILL.md	IVectorStore, record model definition, connector selection, hybrid search, provenance metadata
plugins/dotnet-ai/skills/data-ingestion-pipeline/SKILL.md	Pipeline builder, document loading, chunking strategies, chunk enrichment, error handling
tests/dotnet-ai/vector-data-search/eval.yaml	Eval: vector search setup scenario
tests/dotnet-ai/data-ingestion-pipeline/eval.yaml	Eval: document ingestion pipeline scenario

Key Packages

• Microsoft.Extensions.VectorData
• Connectors: Microsoft.Extensions.VectorData.AzureAISearch, .Qdrant, etc.
• Microsoft.Extensions.DataIngestion

Validation

• Both SKILL.md files have valid YAML frontmatter
• vector-data-search covers IVectorStore, record model, connector selection, hybrid search
• data-ingestion-pipeline covers pipeline builder, chunking, enrichment, error handling
• Both eval.yaml files have at least one scenario
• Cross-references between the two skills are correct

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