The rebuild lock file accumulated concatenated PIDs across post-commit
rebuilds without a separator, and was never removed when the rebuild
finished. Two practical consequences for users:
1. Downstream tooling that polls for `.rebuild.lock` to disappear before
doing post-rebuild work (publish scripts copying graph.html to a web
root, etc.) blocked forever / until its own timeout.
2. The accumulated digit string could not be parsed by humans or tooling
to find the owning PID.
The `_rebuild_lock` context manager now:
- Opens the lock file with `a+` so a non-acquiring caller does not
truncate the existing holder's PID.
- After flock acquisition, truncates and writes a single `<pid>\n` line
so external readers can `kill -0 $(cat .rebuild.lock)` to check
liveness.
- Unlinks the lock file in the finally block (only when *we* held the
lock), restoring the "signal-by-absence" convention users rely on.
Four regression tests added under `tests/test_watch.py` covering the
PID-with-newline payload, post-release unlink, no-accumulation across
sequential acquisitions, and the non-blocking-caller-does-not-clobber
invariant.
Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
- skill.md + skill-windows.md: add encoding="utf-8" to all read_text()/write_text()
calls and ensure_ascii=False to json.dumps — bare calls defaulted to system
codepage on Chinese-locale Windows, mojibaking non-ASCII content (#832)
- skill.md + skill-windows.md: prefer uv tool install --upgrade graphifyy over
pip in the Step 1 install fallback — pip installs to the wrong env when
graphify was installed via uv tool (#831)
- serve.py + __main__.py: replace flat substring scoring in _score_nodes with
three-tier precedence (exact 1000 / prefix 100 / substring 1); _find_node
returns results ordered exact→prefix→substring; both path CLI and MCP now
emit a clear error when src and tgt resolve to the same node (#828)
- cache.py: normalize path key via .as_posix().lower() in file_hash so Windows
junction/case variants hash identically; mirror abs-path normalization from
save_semantic_cache into check_semantic_cache so relative source_file paths
resolve the same way on both sides (#826)
- __main__.py: add /graphify skill trigger line to _AGENTS_MD_SECTION — affects
all 7 AGENTS.md platforms (OpenCode, Codex, Aider, Trae, Hermes, Claw, Droid)
so typing /graphify actually invokes the skill tool (#827)
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Add a pre-cluster topology comparison fast path in update rebuilds so unchanged graphs short-circuit before clustering and report generation, preventing residual run-to-run community-count drift.
Co-authored-by: Cursor <cursoragent@cursor.com>
Use safe JSON serialization fallbacks for deterministic sort keys in clustering and graph canonicalization, and skip invalid community IDs with a stderr warning instead of raising during update rebuilds.
Co-authored-by: Cursor <cursoragent@cursor.com>
Make `graphify update` idempotent by skipping output rewrites when graph/report content is unchanged, add `update --no-cluster`, and preserve community IDs across runs via overlap-based remapping with deterministic partition inputs.
Co-authored-by: Cursor <cursoragent@cursor.com>
- Universal -h/--help/-? guard after cmd dispatch: any help flag anywhere in
argv stops execution and prints "Run 'graphify --help'" instead of triggering
the subcommand — cursor/kiro/gemini install --help no longer silently installs;
benchmark --help no longer crashes with FileNotFoundError (#821)
- --version / -v / version subcommand: print graphify {__version__} and exit (#818)
- GRAPHIFY_OLLAMA_NUM_CTX=<invalid> now falls through to auto-derived num_ctx
instead of hardcoding 131072 (the cap that causes OOM on constrained VRAM);
pinned num_ctx < estimated input now triggers an explicit truncation warning
with a suggested --token-budget correction (#820)
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- extract/_make_id + build/_normalize_id: use NFKC normalization and casefold
so composed/decomposed Unicode forms produce the same ID; collapse consecutive
underscores; both functions are now byte-for-byte equivalent (#811)
- dedup: use explicit key-presence check instead of `or` for source/from
fallback; pop stale from/to keys so they don't leak into graph.json attrs (#803)
- skill --update: use build_merge() to avoid NetworkX round-trip direction flip;
fix dict merge ordering so explicit source/target win; pull hyperedges from
G.graph (merged) not new_extraction only (#801)
- skill subagents: inject absolute CHUNK_PATH so Write tool doesn't lose chunk
files to undefined cwd (#808)
- __main__: skip skill version check during hook-check (runs on every editor
tool use, must be silent); move warning to stderr
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
#796: add edge_data()/edge_datas() helpers in build.py that tolerate
MultiGraph/MultiDiGraph; replace all G.edges[u,v] 2-tuple call sites in
__main__.py, serve.py, wiki.py, export.py, analyze.py, benchmark.py;
fix same pattern in 10 skill file inline heredocs
#795: all 12 skill files now short-circuit on /graphify --help or -h
and print the Usage block without running any pipeline steps
#792 (hollow response): add _response_is_hollow() predicate in llm.py;
when Ollama (or any backend) returns empty/null/whitespace content or a
parsed result with no nodes/edges, rewrite finish_reason="length" so
_extract_with_adaptive_retry bisects the chunk instead of silently
dropping it; applied to _call_openai_compat, _call_claude, _call_bedrock
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
#791: per-repo fcntl flock in _rebuild_code prevents concurrent hook rebuilds
from exhausting memory; changed_paths wired through so only modified files are
re-extracted; stale nodes evicted on deletion; SIGALRM watchdog with
GRAPHIFY_REBUILD_TIMEOUT; Darwin-aware RLIMIT_DATA memory cap
#792: remove hard 8-worker cap (GRAPHIFY_MAX_WORKERS env var); add
--max-workers, --token-budget, --max-concurrency, --api-timeout CLI flags
to graphify extract; fix ollama API key gate for loopback URLs; explicit
timeout on OpenAI client (GRAPHIFY_API_TIMEOUT, default 600s); per-chunk
progress prints during extraction
#453 + #785: rename .agent -> .agents throughout antigravity install/uninstall;
add trigger:always_on YAML frontmatter to _ANTIGRAVITY_RULES so Antigravity
recognises the rules file
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
tree-sitter-pascal is not on PyPI so extract_pascal() fell back to an
empty error result for all users. _extract_pascal_regex() now handles
unit/program/library headers, uses clauses, class/interface declarations
with inheritance, forward method decls, qualified impl headers, balanced
begin/end body extraction, and intra-file calls edges. All 15 previously
skipped pascal_required tests now run unconditionally and pass.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* feat(extract): add Pascal/Delphi language support
Adds full AST extraction for Pascal and Delphi source files using
tree-sitter-pascal (https://github.com/Isopod/tree-sitter-pascal).
Supported file extensions: .pas, .pp, .dpr, .dpk, .inc
Extracted nodes:
- File node (the .pas file itself)
- unit / program / library declarations
- class, interface, and helper type declarations
- procedure and function implementations
Extracted edges:
- file --contains--> module
- module --imports--> dependency (via uses clause, resolved to path-based IDs)
- class --inherits--> base class / interface
- class/module --contains/method--> procedure or function
- procedure --calls--> procedure (in-file call resolution)
Key design: uses clause targets are resolved to path-based node IDs by
scanning all Pascal files under the project root (_pascal_project_root +
_pascal_resolve_unit helpers). This avoids dangling import edges that
result from resolving bare unit names like "SysUtils" to IDs that never
match any file node.
Bare procedure calls (e.g. `Reset;` without parentheses) are detected
by inspecting statement nodes whose sole named child is an identifier,
in addition to the standard exprCall nodes used for calls with arguments.
Requires: pip install tree-sitter-pascal
(https://github.com/Isopod/tree-sitter-pascal)
If not installed, extract_pascal returns {"nodes":[], "edges":[], "error": ...}
so the rest of the pipeline is unaffected.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* feat(extract): add Lazarus .lfm and .lpk file support
Adds two new extractors for Lazarus IDE-specific file formats:
extract_lazarus_form() — .lfm (Lazarus Form files)
.lfm files are text-based UI component trees. The extractor parses
`object Name: TClassName ... end` blocks to build a containment graph
of form components, and captures `OnXxx = HandlerName` event bindings
as `references` edges (context: "event") linking each component to
its handler procedure.
extract_lazarus_package() — .lpk (Lazarus Package files)
.lpk files are XML package definitions. The extractor reads the
package name, required package dependencies (→ imports edges), and
listed unit files (→ contains edges). Unit names are resolved to
path-based node IDs via _pascal_resolve_unit so they connect to the
same nodes produced by extract_pascal on .pas files.
Both extensions added to CODE_EXTENSIONS in detect.py and to _DISPATCH.
13 new tests in test_pascal.py cover both extractors.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* fix(pascal): fix dangling inherits-edge targets and capture all base classes
The declType/typeref handler built inherits edge targets with
_make_id(_read(child)) — just the bare class name. But class nodes
use _make_id(stem, type_name), so targets never matched, making the
entire class hierarchy invisible in the graph.
Add _pascal_class_stem_cache and _pascal_resolve_class(): strips the
conventional T/I prefix, locates the defining file by stem lookup
(same cache mechanism as _pascal_resolve_unit), and returns the
correct _make_id(file_stem, class_name) ID. RTL/unresolvable bases
(e.g. TObject) fall back to _make_id(bare_name) with an explicit
stub node, following the same pattern as the Python extractor.
Also remove the `break` that stopped after the first typeref, so
all parents are captured (e.g. class(TBase, IInterface)).
Extend test_pascal_no_dangling_edges to also assert that within-file
edge targets (contains, method, inherits, calls) resolve to real nodes.
* feat(extract): add Delphi .dfm form file support
Adds extract_delphi_form() for Delphi Form files (.dfm), which use the
same `object Name: TClassName ... end` text syntax as Lazarus .lfm files.
Binary .dfm files (FF 0A magic header) are skipped gracefully with an
informative error message so the pipeline is unaffected. Text .dfm files
are parsed identically to .lfm: component containment (`contains` edges)
and event handler references (`references`, context "event").
Adds .dfm to _DISPATCH and CODE_EXTENSIONS.
10 new tests in test_pascal.py, including a regression test for the
binary-format detection.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
* Add .lpr extension and fix removesuffix in Pascal extractor
Address review feedback from @safishamsi:
- Add .lpr (Lazarus program file, identical syntax to .dpr) to _DISPATCH
in extract.py and CODE_EXTENSIONS in detect.py so Lazarus project entry
points are indexed. Completes the promised Lazarus IDE support.
- Replace rstrip("()") with removesuffix("()") in the call-resolution
dict comprehension for precise suffix removal (rstrip strips individual
characters, not the literal string "()").
- Add .lpr assertions to test_pascal_dispatch_registered and
test_pascal_detect_extensions_registered.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
---------
Co-authored-by: Simeon Bodurov <simeon.bodurov@speedy.bg>
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
Three independent Windows compatibility fixes shipped together because they
all surface during the same first /graphify run on Windows.
graphify/benchmark.py
print_benchmark() unconditionally printed U+2500 (box-drawing) and U+2192
(rightwards arrow), which UnicodeEncodeError'd on stdouts that can't encode
them — most notably the legacy Windows console at cp1252. New _safe()
helper falls back to ASCII when the active stdout encoding can't carry the
glyph; _hr() uses it. Two regression tests cover both paths and prove
print_benchmark survives a cp1252-strict stream.
graphify/extract.py
ProcessPoolExecutor on Windows uses spawn, so worker subprocesses
re-import the calling __main__. When the caller is `python -c "..."` or a
script without an `if __name__ == "__main__":` guard, the workers
recursively spawn themselves and the pool dies. The user-visible failure
was a 290-line traceback ending in BrokenProcessPool, hiding the actual
cause. _extract_parallel now catches BrokenProcessPool, prints a one-line
warning that names the __main__-guard idiom, and returns False so the
public extract() routes to the existing _extract_sequential fallback. Two
tests cover the parallel-returns-False contract and the sequential
fallback wiring.
graphify/skill-windows.md
Every `python -c "..."` block (30 in total) is replaced with a
Write+run+delete pattern using PowerShell's literal here-string @'...'@.
The old form was a quote-escaping minefield: any double-quote inside the
Python source had to be backslash-escaped for the shell, and PowerShell's
parser ate them inconsistently — failing on f-strings like
`f'AST: {len(result["nodes"])} nodes'`. The new form passes Python source
to disk literally, so what the model writes is what Python sees. The AST
step's script template now includes an explicit `if __name__ == "__main__":`
guard so multi-core extraction works even before the runtime fallback above
kicks in. All 31 resulting heredoc blocks parse cleanly under
`ast.parse`.
Co-authored-by: Nauman Hameed <Nauman.Hameed@enghouse.com>
Adaptive retry only recovered from `finish_reason="length"` (output
truncation). It did not handle the other shape of overflow: the API
rejecting the prompt outright with a 400 because the input plus
`max_completion_tokens` doesn't fit in the model's context window.
This shows up immediately on local OpenAI-compatible servers (LM
Studio, llama.cpp, vLLM) where the default context is small (4K-32K)
and a 60K-token chunk packed for cloud Kimi/Claude blows past it.
Without retry the whole chunk fails with no output, even though the
two halves would each fit cleanly.
Catch a heuristic set of context-overflow exception messages,
classify them as the same kind of recoverable failure as
`finish_reason="length"`, and split-recurse on the same path. Single-
file overflow returns an empty fragment so the rest of the corpus
keeps running. Unrelated errors (rate limit, auth, etc.) still
propagate.
Tested with qwen3.5-9b on LM Studio (32K ctx) against a 215-file
corpus where chunks 4-12 of 12 previously failed; with this change
the overflowing chunks self-heal by splitting in half.
The SQL parser (`extract_sql`) previously only extracted foreign key
relationships defined inline within CREATE TABLE column definitions.
FK constraints added via ALTER TABLE ... ADD CONSTRAINT ... FOREIGN KEY
... REFERENCES were silently ignored.
Additionally, `_obj_name()` only read the first identifier child of
object_reference nodes, so schema-qualified names like `Sales.Customer`
were truncated to just `Sales`.
Changes:
- Add `alter_table` handler to `walk()` that extracts FK edges from
ALTER TABLE ... ADD CONSTRAINT ... FOREIGN KEY ... REFERENCES
- Fix `_obj_name()` to read the full object_reference text, preserving
schema-qualified names (e.g. `Sales.Customer`)
- Fix inline FK resolution in create_table and _walk_from_refs to use
full object_reference text instead of first identifier only
Rewrote _CLAUDE_MD_SECTION, _AGENTS_MD_SECTION, and _GEMINI_MD_SECTION to use forceful ALWAYS/NEVER directives instead of soft suggestions.
Agents must now consult the knowledge graph before file operations.
Context:
- Updated AGENTS.md template injected via _agents_install()
- Updated CLAUDE.md template injected via claude install
- Updated GEMINI.md template injected via gemini_install()
10 skill-*.md files had descriptions that only described what graphify does (input->pipeline->output), not when agents should use it. This meant skills never loaded proactively on codebase questions.
Changed to hybrid descriptions that retain the pipeline summary but add trigger conditions: 'Use when user asks any question about a codebase, project content, architecture, or file relationships'.
tree-sitter-typescript ships two grammars:
- language_typescript: pure TypeScript, no JSX support
- language_tsx: JSX-aware variant for .tsx files
Currently both .ts and .tsx are parsed with language_typescript, which
treats JSX syntax as parse errors. Every function declaration, arrow
function, and call_expression nested inside a JSX tree is silently
dropped from the extracted graph.
Repro on a representative React+TypeScript codebase (a 13-file Tauri app):
parsing each .tsx with language_typescript produces ~276 ERROR nodes per
file. Only declarations that happen to live before the first JSX block
survive.
Fix: add _TSX_CONFIG that mirrors _TS_CONFIG but selects language_tsx,
and route .tsx files to it in extract_js().
Effect on the same repo (graphify update --force):
Nodes: 303 → 618 (+104%)
Edges: 482 → 779 (+62%)
Communities: 28 → 45 (+61%)
Parse errors 276 → 0 per .tsx file
Tests added:
- tsx fixture with helpers + JSX-returning component
- helpers and component are captured
- JSX expression calls ({fmtDate(now)}) resolve to call edges
- wiring check: .tsx uses language_tsx, .ts uses language_typescript
Note: this fixes the parsing layer. Calls inside deeply nested arrow
function callbacks (e.g. items.map(x => <T>{f(x)}</T>)) are still
missed by the call extraction logic — separate enhancement.
Co-authored-by: Serkan Gezici <serkan@quadroaipilot.com>
voidborne-d