Semantic Grep

jina-grep-style semantic search, done in-process via Python rather than as an external CLI. Embeds query + corpus chunks with gemini-embedding-001, ranks by cosine similarity, returns grep-format output.

When Semantic Search Helps

The core trade-off (lifted from jina-grep-cli's own docs and validated in testing):

Regression test result (workshop session corpus, 135 docs):

• "handling regulatory constraints" → top hit "Engineering AI Systems Under Sovereignty Constraints" (0.67). ✓
• "sessions about GEPA" → top hit "Gemma, DeepMind's Family of Open Models" (0.69). ✗ — false positive on phonetic neighbor. GEPA is mentioned verbatim in one session description; grep would find it correctly.

Rule: when the user query reads like a named entity or keyword, try grep first. Only reach for semantic-grep when paraphrase/concept matching is actually needed.