Search with `recompute` second level latency for code RAG

[ASuresh0524]

What happened?

Title: Search with recompute takes ~15s even after warmup

Environment

• macOS (darwin 24.6.0)
• Python 3.10.18
• LEANN branch: feature/colqwen-integration

Steps to Reproduce

1. Create a tiny code repo:

   mkdir -p /tmp/quick_test_code
   cat <<'PY' > /tmp/quick_test_code/test.py
   def hello():
       return "world"
   
   class Test:
       pass
   PY

2. Build an index:

   leann build quick-test-index \
     --docs /tmp/quick_test_code \
     --use-ast-chunking \
     --embedding-model facebook/contriever \
     --embedding-mode sentence-transformers

3. Run searches (measure wall time):

   time leann search quick-test-index "hello" --top-k 3
   time leann search quick-test-index "Test" --top-k 3
   time leann search quick-test-index "function" --top-k 3

Observed

• Build completes (~15 s).
• Each search takes 13–19 s, even after multiple runs.
• Warm vs cold only differs by ~1.2 s, so most time is spent recomputing embeddings per query.

Expected

• Searches with recompute=True may be slower, but not 13–19 s for a trivial index.
• Would like to understand if there’s a way to avoid full model reload or make on-the-fly query embedding faster.

How to reproduce

Follow steps from above.

Error message

LEANN Version

0.1.0

Operating System

macOS