v0.4.0 — PPR Graph Intelligence

What's New

PPR Graph Intelligence (Phase 5)

Personalized PageRank is now a third ranking signal in Tessera's hybrid search, bringing structure-aware code retrieval alongside keyword and semantic search.

Core Features:

• Three-way RRF merge — keyword + semantic + PPR graph signal, with graceful degradation when graphs are sparse
• graph.py — PPR via scipy CSR sparse matrices with LRU-cached per-query results
• Adaptive sparse threshold — percolation theory-based check (density + largest connected component) decides whether PPR engages
• Cross-file edge resolution — post-indexing pass connects unresolved references across files, dramatically improving graph connectivity (LCC from 1.4% → 67.7% on real codebases)
• Memory monitoring — LRU eviction for graph cache with configurable limits

Extended JS/TS Symbol Extraction

• Object property functions ({ click_open: function() {} })
• Assignment expressions (window.PUM.foo = function() {})
• function_expression in variable declarations (previously only arrow_function)
• +475 symbols extracted from Popup Maker Core after fix

Search Quality — Validated on Real Codebases

Tested against Popup Maker ecosystem (Core + Pro, 14,540 symbols, 14,758 edges):

• 4/6 exit intent queries had top result improved by PPR
• Implementation files consistently surface above noise (images, lock files, docs)
• Score lifts up to +59% on relevant queries

Other

• doc_search argument order bug fix
• Search latency benchmarks and 80ms threshold guard
• Configurable embedding endpoint for hybrid search and reindex
• Multi-project spike tests with nDCG@5 metrics
• 11,400+ lines of new code and tests

Upgrade

uv sync  # or pip install -e .

Existing indexes work — PPR engages automatically when graph density is sufficient. No re-indexing required unless you want the improved JS/TS symbol extraction.