Add dataset (examples.jsonl, equivalence.csv), IR visualizations, didactic labeling, Space link

README.md

@@ -12,6 +12,8 @@ tags:
 - cross-language
 - ast
 - code-compression
+- dataset
+- demo
 pipeline_tag: other
 ---
 
@@ -26,6 +28,9 @@ Ruby, PHP, Zig, C, C++) into a single canonical graph of **12 universal IR
 kinds**. It is not a new language — it is a discovery: different syntaxes
 converge to the same structure when their intent is equivalent.
 
+> **[Try it now on Spaces →](https://huggingface.co/spaces/Jose-dev/graphlang)**
+> — paste code and see it collapse into a GraphLang IR graph, live.
+
 ```text
 Python:   def add(a, b): return a + b          ─┐
 Java:     int add(int a, int b){ return a+b; }  ─┤  →  SAME GraphLang IR
@@ -52,6 +57,27 @@ JavaScript: function add(a,b){ return a+b; }    ─┘     (identical graph)
 The 12 kinds were derived from the analysis of ~2,215 Concrete Syntax Tree
 (CST) node types across the 13 languages.
 
+## Cross-language equivalence (measured, not claimed)
+
+12 canonical intents were compiled in Python, Java, and JavaScript through the
+**real engine** (`complete_normalizer.py`) and fingerprinted with a recursive
+structural hash (content-addressed, not node-id based).
+
+| Group | Identical IR? | Notes |
+|-------|---------------|-------|
+| `add`, `max2`, `abs`, `square`, `compare`, `negate`, `twice` | **Yes (7/7)** | arithmetic / expression intents |
+| `is_even`, `sum_loop`, `fact`, `fib`, `grade` | Partial | comparison/loop sugar (`elif` vs `else if`, `for-of` vs `for-in`, Python `Compare` vs binary op) |
+
+Arithmetic and expression-level intents collapse to **bit-identical IR** across
+the three languages. The remaining divergence is a known normalization gap in
+comparison and loop sugar — documented, not hidden. See `data/equivalence.csv`.
+
+## IR visualization
+
+`grade(score)` in Python, normalized to GraphLang IR:
+
+![GraphLang IR graph](assets/grade.png)
+
 ## Reproducible Benchmarks
 
 The compression ratio converges to a constant — **22.5x monolingual** and
@@ -65,17 +91,27 @@ reproducible with the engine (`benchmark_100k.py` / `benchmark_1m.py`).
 | 100,000 | 2,170,018 | 96,616 | 22.5x | 0 |
 | 1,000,000 | 21,721,197 | 965,045 | 22.5x | 0 |
 
-Cross-language equivalence: the same function written in Python, Java, and
-JavaScript produces a **100% identical IR graph**.
+## Datasets (downloadable)
+
+| File | Content |
+|------|---------|
+| `data/examples.jsonl` | 36 code→IR samples (12 intents × Python/Java/JavaScript), full IR node dump + fingerprint |
+| `data/equivalence.csv` | Cross-language equivalence matrix with recursive structural hashes |
+| `benchmark_100k_results.json` | 100K-function compression measurement |
+| `benchmark_1m_results.json` | 1M-function compression measurement |
 
 ## Included in this repository
 
+- `app.py` — **didactic** interactive demo (Gradio): paste code, see the IR
+  graph, merge two functions, measure structural deduplication. This is a
+  self-contained educational reimplementation, **not** the production engine.
 - `parallel_ir.py` — GPU/HPC extension (CUDA / OpenCL / Metal detection and
   thread-index normalization) sitting on top of the 12 core kinds.
-- `app.py` — interactive demo (Gradio): paste code, see the IR graph, merge
-  two functions, and measure structural deduplication.
 - `benchmark_100k_results.json`, `benchmark_1m_results.json` — reproducible
   benchmark measurements.
+- `data/` — the code→IR dataset and equivalence matrix (generated by the real
+  engine).
+- `assets/` — IR graph visualizations (SVG + PNG).
 - `paper/` — the academic paper (GraphLang: a universal semantic kernel for
   code).
 
@@ -87,6 +123,10 @@ research use, restricted for AI/ML training (drafted as a copyright condition,
 enforceable under *Jacobsen v. Katzer*), and commercial use requires a
 license.
 
+The benchmarks and `data/` files in this repository were produced by the real
+engine. The `app.py` demo is a simplified didactic reimplementation that
+illustrates the concept only.
+
 For the engine, the 20M aligned function-pair dataset, or commercial
 licensing: **josu31.jas@gmail.com**
 

app.py

@@ -1,11 +1,14 @@
-"""GraphLang interactive demo (Gradio).
+"""GraphLang interactive demo (Gradio) — DIDACTIC.
 
-Demonstrates the core idea of GraphLang:
+This is NOT the production GraphLang engine. It is a self-contained,
+educational Python-AST reimplementation used only to illustrate the core
+idea:
     source code  ->  semantic IR graph (12 kinds)  ->  hash-merge / dedup
 
-This demo ships with a compact, didactic Python-AST builder so the concept
-runs fully in the browser/space. The production multi-language normalizer
-(13 languages via tree-sitter) is available under the MII license.
+The production engine (13 languages via tree-sitter, 238+296+242 CST node
+types mapped to 12 IR kinds) is available under the MII Open License v1.1.
+The benchmarks and datasets shipped alongside this demo were generated by
+the REAL engine, not by this file.
 """
 
 import ast
@@ -222,6 +225,11 @@ with gr.Blocks(title="GraphLang demo") as demo:
 
 Same intent = same graph. Paste Python code and see its canonical IR graph;
 merge two snippets and measure structural deduplication.
+
+> **Didactic demo.** This Space runs a simplified Python-AST reimplementation
+> to illustrate the concept. The production engine normalizes **13 languages**
+> via tree-sitter and is licensed separately (MII Open License v1.1).
+> Benchmarks and datasets in the companion model repo are from the real engine.
 """)
 
     with gr.Tabs():

data/equivalence.csv

@@ -0,0 +1,13 @@
+group,fingerprint_hash,equivalent_across_languages,node_count,python,java,javascript
+add,1cb54b4a51c8323e,True,13,1cb54b4a51c8323e,1cb54b4a51c8323e,1cb54b4a51c8323e
+max2,319417b5dc83a126,True,16,319417b5dc83a126,319417b5dc83a126,319417b5dc83a126
+is_even,8ca1cf467caffe4d,False,20,8ca1cf467caffe4d,71a72719623fe81f,71a72719623fe81f
+abs,9fc45665896fc4fc,True,17,9fc45665896fc4fc,9fc45665896fc4fc,9fc45665896fc4fc
+sum_loop,84f9e7128409e53f,False,22,84f9e7128409e53f,3b25bb6ce2e8cb94,3b25bb6ce2e8cb94
+fact,425a92902a1f7541,False,32,425a92902a1f7541,097812ac0e7fe0bb,097812ac0e7fe0bb
+fib,88861d1c9c43d085,False,49,88861d1c9c43d085,efbfbda4ad33971a,efbfbda4ad33971a
+square,9ffac4e60936ca02,True,12,9ffac4e60936ca02,9ffac4e60936ca02,9ffac4e60936ca02
+compare,6a1868e5f54bdc54,True,13,6a1868e5f54bdc54,6a1868e5f54bdc54,6a1868e5f54bdc54
+negate,3d4827b7cd720d78,True,10,3d4827b7cd720d78,3d4827b7cd720d78,3d4827b7cd720d78
+twice,3b8a0abbba2d6801,True,12,3b8a0abbba2d6801,3b8a0abbba2d6801,3b8a0abbba2d6801
+grade,cdd6a91db531f8fe,False,28,cdd6a91db531f8fe,af78b58b308c5a57,a2c214c9d34e0d50

data/examples.jsonl

@@ -0,0 +1,36 @@
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+{"id": "add.javascript", "group": "add", "language": "javascript", "code": "function add(a,b){return a+b;}", "node_count": 13, "fingerprint_hash": "1cb54b4a51c8323e", "ir": [{"id": "n1", "kind": "var", "value": "add", "op": "", "args": [], "hash": "c1d620f61929"}, {"id": "n2", "kind": "var", "value": "a", "op": "", "args": [], "hash": "f3a849ba2036"}, {"id": "n3", "kind": "var", "value": "b", "op": "", "args": [], "hash": "d49a4df3f36b"}, {"id": "n4", "kind": "args", "value": null, "op": "", "args": ["n2", "n3"], "hash": "d2b9ccd75131"}, {"id": "n5", "kind": "var", "value": "a", "op": "", "args": [], "hash": "f3a849ba2036"}, {"id": "n6", "kind": "var", "value": "b", "op": "", "args": [], "hash": "d49a4df3f36b"}, {"id": "n7", "kind": "var", "value": "a", "op": "", "args": [], "hash": "f3a849ba2036"}, {"id": "n8", "kind": "var", "value": "b", "op": "", "args": [], "hash": "d49a4df3f36b"}, {"id": "n9", "kind": "binop", "value": null, "op": "", "args": ["n7", "n8"], "hash": "8eee4291c0e2"}, {"id": "n10", "kind": "return", "value": null, "op": "", "args": ["n9"], "hash": "d6f5c2b8ba60"}, {"id": "n11", "kind": "block", "value": null, "op": "", "args": ["n10"], "hash": "d689a347b3f7"}, {"id": "n12", "kind": "function", "value": "add", "op": "", "args": ["n2", "n3", "n11"], "hash": "939311d4da41"}, {"id": "n13", "kind": "module", "value": null, "op": "", "args": ["n12"], "hash": "2239939ddb09"}]}
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