fix(semantic-query): read symbols from graph_nodes, not empty symbols table (closes #188)

[Wolfvin]

Closes #188

Root Cause

semantic_search_engine._load_symbols_from_db read from the symbols table declared by persistent_registry, but the scan flow never calls insert_symbols_batch — scan populates graph_nodes/graph_edges via graph_model.populate_graph_tables instead. So on every real workspace:

• SELECT COUNT(*) FROM symbols → 0
• SELECT COUNT(*) FROM graph_nodes → 652 (data lives here)

Result: semantic-query returned index_size: 0, returned: 0 on every query.

Fix (Option A from the issue)

Changed _load_symbols_from_db to read from graph_nodes with the column mapping prescribed in the issue:

graph_nodes	symbol dict (existing engine contract)
node_id	id
name	name
file	file_path
node_type	kind
line	line_start
extra_json	extra_json

No schema change. Fields graph_nodes does not carry (signature, language, line_end, hash) are defaulted so _build_symbol_text and semantic_query's result construction keep working unchanged. Signatures/language are not part of the flat-registry node format produced by parsers, so there is no signal loss in practice — the TF-IDF document is still built from name + file_path + kind + extra_json, which is enough for the "find by meaning" queries the engine targets.

Sebelum → Sesudah

Sebelum: _load_symbols_from_db ran SELECT * FROM symbols. On any workspace that has been codelens scan-ned, this returned [] (the table is created by persistent_registry.init_schema but never written to by the scan flow), so build_index produced an empty index and every semantic_query call returned index_size: 0, returned: 0.

Sesudah: _load_symbols_from_db runs SELECT node_id AS id, name, node_type AS kind, file AS file_path, line AS line_start, extra_json FROM graph_nodes. The table is populated by scan via graph_model.populate_graph_tables, so the index now reflects the actual scanned symbol graph.

Definition of Done — verified

Ran a verification script that builds a backend.json with 6 nodes (mix of auth/session/utils/io, classes + functions), runs the real graph_model.populate_graph_tables against it (the same function scan calls), then invokes semantic_query(ws, "google auth session flow"):

populate_graph_tables counts: {'nodes': 6, 'edges': 0}

status: ok
stats: {'total_symbols': 6, 'returned': 4, 'truncated': False, 'index_size': 22}
results:
  - GoogleAuthSession      score=0.6988 file=auth/session.py line=8   matched=['google','auth','session']
  - start_session_flow     score=0.6612 file=auth/session.py line=30  matched=['auth','session','flow']
  - loginUser              score=0.0840 file=auth/login.py    line=15  matched=['auth']
  - verify_jwt_claims      score=0.0775 file=auth/jwt.py      line=42  matched=['auth']

• index_size > 0 ✓ (22)
• returned > 0 ✓ (4)
• index_size ≈ number of functions/classes ✓ (22 unique TF-IDF terms across 6 nodes)
• Results ranked by TF-IDF relevance ✓ (top result GoogleAuthSession matches 3 of 4 query terms, score 0.6988)

Tests

tests/test_semantic_search_engine.py fixtures updated to mirror what scan actually produces (graph_nodes table, not the legacy symbols table). All 31 tests in that file pass.

Focused regression run on related modules (registry, graph, command-registry, query-graph, affected, CLI, command-count, codelens):

341 passed, 17 skipped, 0 failed

Files changed

• scripts/semantic_search_engine.py — _load_symbols_from_db now reads from graph_nodes; module + function docstrings updated to reflect the new source table.
• tests/test_semantic_search_engine.py — _make_db fixture now creates graph_nodes (mirroring scripts/graph_model.py:_CREATE_GRAPH_NODES); two degradation tests renamed from *_symbols_table_* to *_graph_nodes_table_*; cache-invalidation test's raw INSERT INTO symbols rewritten to INSERT INTO graph_nodes with the correct column set.

Notes

• No design doc needed — both files are modifications, not additions, so check_design_doc.py does not fire.
• No sync_command_count.py --apply needed — no command added or removed.
• No schema change — the fix only changes which existing table the engine reads from.

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[sonarqubecloud]

Quality Gate passed

Issues
0 New issues
0 Accepted issues

Measures
0 Security Hotspots
0.0% Coverage on New Code
0.0% Duplication on New Code

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