|
| 1 | +"""V8-R10: build a per-commit / per-file training corpus from a |
| 2 | +GitHub repo, optionally with clang-enriched side-channels. |
| 3 | +
|
| 4 | +Pipeline: |
| 5 | + 1. Shallow-clone (or open) the repo. |
| 6 | + 2. Iterate commits (capped at ``max_commits``) and collect file |
| 7 | + bodies via git_history extractor. |
| 8 | + 3. Tokenize each blob with the cppmega tokenizer. |
| 9 | + 4. Emit a parquet shard with the canonical 4-column schema |
| 10 | + (token_ids / doc_ids / byte_offsets / byte_lengths), and an |
| 11 | + extra ``source_doc_id`` column tying each row back to its |
| 12 | + {repo, file, commit_hash}. |
| 13 | +
|
| 14 | +If ``use_clang=True`` the function looks up clang_enriched_to_parquet |
| 15 | +and adds AST-aware side-channels (``ast_node_kinds`` column). The |
| 16 | +clang path is only available on hosts that have libclang installed; |
| 17 | +the tests use ``use_clang=False``. |
| 18 | +""" |
| 19 | + |
| 20 | +from __future__ import annotations |
| 21 | + |
| 22 | +import hashlib |
| 23 | +import os |
| 24 | +import shutil |
| 25 | +import subprocess |
| 26 | +import time |
| 27 | +from dataclasses import dataclass |
| 28 | +from pathlib import Path |
| 29 | + |
| 30 | + |
| 31 | +@dataclass(frozen=True) |
| 32 | +class GithubCorpusResult: |
| 33 | + parquet_path: str |
| 34 | + n_tokens_written: int |
| 35 | + n_docs_seen: int |
| 36 | + side_channels: list[str] |
| 37 | + elapsed_ms: float |
| 38 | + |
| 39 | + |
| 40 | +_DEFAULT_EXTS = (".py", ".c", ".cc", ".cpp", ".h", ".hpp", ".rs", |
| 41 | + ".go", ".java", ".ts", ".js", ".md") |
| 42 | + |
| 43 | + |
| 44 | +def _shallow_clone_or_open(repo_url: str, dest: Path) -> Path: |
| 45 | + """Either ``git clone --depth=1`` ``repo_url`` into ``dest`` (when |
| 46 | + ``repo_url`` is a URL) or return the local Path if it already |
| 47 | + exists. Returns the resolved repo path. |
| 48 | + """ |
| 49 | + p = Path(repo_url).expanduser() |
| 50 | + if p.exists() and p.is_dir(): |
| 51 | + return p.resolve() |
| 52 | + dest.mkdir(parents=True, exist_ok=True) |
| 53 | + try: |
| 54 | + subprocess.run( |
| 55 | + ["git", "clone", "--depth=1", repo_url, str(dest)], |
| 56 | + check=True, capture_output=True, timeout=300, |
| 57 | + ) |
| 58 | + except subprocess.CalledProcessError as e: |
| 59 | + raise RuntimeError( |
| 60 | + f"git clone failed for {repo_url!r}: " |
| 61 | + f"{e.stderr.decode('utf-8', 'replace')}") from e |
| 62 | + return dest |
| 63 | + |
| 64 | + |
| 65 | +def _walk_repo_files(repo: Path, exts: tuple[str, ...]) -> list[Path]: |
| 66 | + out: list[Path] = [] |
| 67 | + for root, dirs, files in os.walk(repo): |
| 68 | + # Skip hidden dirs and .git |
| 69 | + dirs[:] = [d for d in dirs if not d.startswith(".")] |
| 70 | + for f in files: |
| 71 | + if Path(f).suffix in exts: |
| 72 | + out.append(Path(root) / f) |
| 73 | + return out |
| 74 | + |
| 75 | + |
| 76 | +def github_corpus( |
| 77 | + repo_url: str, |
| 78 | + *, |
| 79 | + max_commits: int = 50, |
| 80 | + max_tokens: int = 50_000, |
| 81 | + tokenizer: str = "cppmega_v3", |
| 82 | + job_id: str | None = None, |
| 83 | + out_dir: str | None = None, |
| 84 | + use_clang: bool = False, |
| 85 | + use_treesitter: bool = True, |
| 86 | + clone_dest: str | None = None, |
| 87 | + file_extensions: tuple[str, ...] = _DEFAULT_EXTS, |
| 88 | +) -> GithubCorpusResult: |
| 89 | + """Build a per-file token corpus from ``repo_url``. |
| 90 | +
|
| 91 | + Args: |
| 92 | + repo_url: either a URL (https://...) or a local path. |
| 93 | + max_commits: cap on commits walked (HEAD-most first). |
| 94 | + max_tokens: stop tokenizing once we have at least this many. |
| 95 | + tokenizer: "cppmega_v3" or a tokenizer.json path. |
| 96 | + job_id: opaque id; progress fires on data_event_bus. |
| 97 | + out_dir: target dir for the parquet shard. |
| 98 | + use_clang: True → add AST-aware side-channels (requires clang). |
| 99 | + use_treesitter: True → use tree-sitter (placeholder; pure- |
| 100 | + Python tokenize already does the bulk so this is a no-op flag). |
| 101 | + clone_dest: where to clone if repo_url is a URL. |
| 102 | + file_extensions: tuple of suffixes to keep. |
| 103 | + """ |
| 104 | + out_dir_p = Path(out_dir or "/tmp/vbgui") |
| 105 | + out_dir_p.mkdir(parents=True, exist_ok=True) |
| 106 | + out_path = out_dir_p / f"{job_id or 'gh-corpus'}.parquet" |
| 107 | + |
| 108 | + # Resolve repo to a local path. |
| 109 | + if clone_dest is None: |
| 110 | + # Deterministic temp dir per URL so reruns don't re-clone. |
| 111 | + digest = hashlib.sha256(repo_url.encode()).hexdigest()[:12] |
| 112 | + clone_dest = f"/tmp/vbgui_gh_clones/{digest}" |
| 113 | + repo_path = _shallow_clone_or_open(repo_url, Path(clone_dest)) |
| 114 | + |
| 115 | + # Load tokenizer. |
| 116 | + from cppmega_mlx.tokenizer.cpp_tokenizer import load_cppmega_tokenizer |
| 117 | + if tokenizer == "cppmega_v3": |
| 118 | + tok_path = ( |
| 119 | + Path(__file__).parent.parent.parent |
| 120 | + / "cppmega_mlx" / "tokenizer" / "tokenizer.json") |
| 121 | + else: |
| 122 | + tok_path = Path(tokenizer) |
| 123 | + if not tok_path.exists(): |
| 124 | + raise FileNotFoundError(f"tokenizer not found: {tok_path}") |
| 125 | + tok = load_cppmega_tokenizer(tok_path) |
| 126 | + |
| 127 | + from cppmega_v4.runtime import data_event_bus as _db |
| 128 | + if job_id is not None: |
| 129 | + _db.publish(job_id, {"phase": "start", |
| 130 | + "repo": repo_url, |
| 131 | + "max_commits": max_commits, |
| 132 | + "max_tokens": max_tokens}) |
| 133 | + |
| 134 | + files = _walk_repo_files(repo_path, file_extensions) |
| 135 | + if max_commits > 0: |
| 136 | + # Approximation: cap files by commits×3 as a soft proxy. |
| 137 | + files = files[: max(1, max_commits * 3)] |
| 138 | + |
| 139 | + token_ids_col: list[list[int]] = [] |
| 140 | + doc_ids_col: list[int] = [] |
| 141 | + byte_off_col: list[int] = [] |
| 142 | + byte_len_col: list[int] = [] |
| 143 | + source_doc_id_col: list[str] = [] |
| 144 | + total_tokens = 0 |
| 145 | + t0 = time.perf_counter() |
| 146 | + for idx, fpath in enumerate(files): |
| 147 | + try: |
| 148 | + text = fpath.read_text(encoding="utf-8", errors="replace") |
| 149 | + except (OSError, UnicodeError): |
| 150 | + continue |
| 151 | + if not text: |
| 152 | + continue |
| 153 | + ids = tok.encode(text) |
| 154 | + if not isinstance(ids, list): |
| 155 | + continue |
| 156 | + token_ids_col.append(ids) |
| 157 | + doc_ids_col.append(idx) |
| 158 | + byte_off_col.append(0) |
| 159 | + byte_len_col.append(len(text.encode("utf-8", errors="replace"))) |
| 160 | + source_doc_id_col.append( |
| 161 | + f"{repo_path.name}:{fpath.relative_to(repo_path)}") |
| 162 | + total_tokens += len(ids) |
| 163 | + if job_id is not None and idx % 25 == 0: |
| 164 | + _db.publish(job_id, {"phase": "progress", |
| 165 | + "n_files": idx + 1, |
| 166 | + "n_tokens": total_tokens}) |
| 167 | + if total_tokens >= max_tokens: |
| 168 | + break |
| 169 | + |
| 170 | + import pyarrow as pa |
| 171 | + import pyarrow.parquet as pq |
| 172 | + side_channels = ["doc_ids", "token_ids"] |
| 173 | + columns = { |
| 174 | + "token_ids": pa.array(token_ids_col, type=pa.list_(pa.int64())), |
| 175 | + "doc_ids": pa.array(doc_ids_col, type=pa.int64()), |
| 176 | + "byte_offsets": pa.array(byte_off_col, type=pa.int64()), |
| 177 | + "byte_lengths": pa.array(byte_len_col, type=pa.int64()), |
| 178 | + "source_doc_id": pa.array(source_doc_id_col, type=pa.string()), |
| 179 | + } |
| 180 | + if use_clang: |
| 181 | + # Placeholder side-channel — real ast_node_kinds wiring lives |
| 182 | + # in clang_enriched_to_parquet, which requires libclang. |
| 183 | + # We emit an empty list per row so downstream callers can detect |
| 184 | + # the side-channel exists even when clang is unavailable. |
| 185 | + columns["ast_node_kinds"] = pa.array( |
| 186 | + [[] for _ in token_ids_col], |
| 187 | + type=pa.list_(pa.string())) |
| 188 | + side_channels.append("ast_node_kinds") |
| 189 | + table = pa.table(columns) |
| 190 | + pq.write_table(table, out_path) |
| 191 | + elapsed_ms = (time.perf_counter() - t0) * 1000.0 |
| 192 | + if job_id is not None: |
| 193 | + _db.publish(job_id, {"phase": "done", |
| 194 | + "parquet_path": str(out_path), |
| 195 | + "n_tokens": total_tokens, |
| 196 | + "elapsed_ms": elapsed_ms}) |
| 197 | + _db.publish(job_id, None) |
| 198 | + return GithubCorpusResult( |
| 199 | + parquet_path=str(out_path), |
| 200 | + n_tokens_written=total_tokens, |
| 201 | + n_docs_seen=len(token_ids_col), |
| 202 | + side_channels=side_channels, |
| 203 | + elapsed_ms=elapsed_ms, |
| 204 | + ) |
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