[Feature Request]: Add Chroma vector database ingestion connector for RAG pipelines

[nitinware]

What would you like to happen?

Motivation

Beam's Python ml/rag ingestion module currently supports Milvus and Qdrant (sdks/python/apache_beam/ml/rag/ingestion/). Chroma is one of the most widely-adopted open-source vector databases, especially for local and embedded RAG workloads, and is the missing piece in Beam's OSS vector-DB coverage.

Proposal

Add sdks/python/apache_beam/ml/rag/ingestion/chroma.py implementing a WriteToChroma PTransform matching the shape of the existing Milvus and Qdrant connectors:

• Accepts Chunk records from the existing RAG chunking transforms
• Supports both chromadb.HttpClient (remote) and chromadb.PersistentClient
  (embedded / local) client modes
• Configurable collection name, embedding + metadata mapping, batch size
• Standard retry/backoff

Benefits

• Completes Beam's coverage of the OSS local-first vector-DB tier
• Chroma is Apache-2.0 licensed — no dependency-license concerns
• PersistentClient runs in-process, so integration tests do not need
  Docker or a remote service — a meaningful advantage over Milvus/Qdrant
  which require running servers in CI

Testing plan

• Unit tests mirroring qdrant_test.py
• Integration test using chromadb.PersistentClient against a tmpdir
  (no external service required)
• Docs + example consistent with existing Milvus / Qdrant docs

Issue Priority

Priority: 2 (default / most feature requests should be filed as P2)

Issue Components

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[nitinware]

.take-issue