Verify token-based chunking and build script integration

[Copilot]

Review requested to confirm token chunking ingestion creates proper chunks for embeddings and build script integration is correct.

Verification Completed

Token Chunking (00_ingest.py)

• Uses RecursiveCharacterTextSplitter.from_tiktoken_encoder() with text-embedding-3-small tokenizer
• 400-token chunks with 80-token overlap (20%)
• Safety guards prevent overlap >= chunk_size misconfiguration
• Fallback to word-based approximation when tiktoken unavailable
• Metadata includes source, source_path, chunk_index, chunk_count

Build Integration (01_build_index.py)

• Imports scripts.ingest and calls ingest() to get Document chunks
• Sanitizes metadata for Chroma (converts sets/complex types to JSON-serializable)
• Uses Chroma.from_texts() for proper text/metadata pairing
• Clean rebuild workflow (removes old index before persisting)

Test Coverage

• Hidden file filtering verified
• Document chunking with metadata confirmed
• Metadata sanitization tested
• Summary output validated

Result

Token ingestion correctly produces chunks suitable for embeddings. Build script properly integrates with ingestion pipeline. No functional issues found.

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