File size: 11,084 Bytes
165ed2c | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 | #!/usr/bin/env python3
from __future__ import annotations
import hashlib
import json
import shutil
from collections import Counter
from pathlib import Path
import pyarrow.parquet as pq
ROOT = Path("/home/XuWenqi/ZhouZhifan/StreamingOmniDatasetsWork")
RC = ROOT / "release_candidates/v0.4.2-comprehensive-local-rc1"
REPORTS = ROOT / "reports"
ALIGN = ROOT / "alignment_candidates/external_api_deferred"
CONFIGS = ["single_turn_streaming", "context_multiturn_qa", "single_tool_calling"]
SPLITS = ["train", "eval"]
def sha(path: Path) -> str:
h = hashlib.sha256()
with path.open("rb") as f:
for block in iter(lambda: f.read(4 * 1024 * 1024), b""):
h.update(block)
return h.hexdigest()
def sha_text(value: str) -> str:
return hashlib.sha256(value.encode()).hexdigest()
def rewrite_checksums() -> None:
target = RC / "SHA256SUMS.txt"
entries = []
for path in sorted(RC.rglob("*")):
if path.is_file() and path != target:
entries.append(f"{sha(path)} {path.relative_to(RC)}")
target.write_text("\n".join(entries) + "\n")
def main() -> None:
acceptance = json.loads((REPORTS / "local_acceptance_v042.json").read_text())
dryrun = json.loads((REPORTS / "hf_publish_dry_run_v042.json").read_text())
if acceptance["result"] != "PASS" or dryrun["result"] != "PASS":
raise RuntimeError("Cannot finalize a failed acceptance or dry-run")
rows = []
counts = {}
for config in CONFIGS:
for split in SPLITS:
path = RC / f"data/{config}/{split}-00000-of-00001.parquet"
table = pq.read_table(path)
counts[f"{config}/{split}"] = table.num_rows
for row in table.to_pylist():
row["_config"] = config
rows.append(row)
manifest = json.loads((RC / "RELEASE_MANIFEST.json").read_text())
build = json.loads((REPORTS / "build_stats_v042.json").read_text())
opportunities = sum(1 for line in (ALIGN / "alignment_opportunities.jsonl").read_text().splitlines() if line.strip())
tool_rows = [r for r in rows if r["_config"] == "single_tool_calling"]
tool_verified = sum(r["tool_validation_status"] in {
"execution_verified", "replay_verified", "deterministic_replay_verified",
"fixture_replay_verified",
} for r in tool_rows)
synthetic = sum(
"synthetic" in r["data_origin"].lower()
or r["data_origin"].startswith("project_created")
or r["source_dataset"] in {"StreamingOmniDatasetsProjectScreens", "StreamingOmniDeterministicToolFixtures"}
for r in rows
)
real_or_transformed = len(rows) - synthetic
capabilities = Counter()
for row in rows:
capabilities.update(row["capabilities"])
multi_dependency = Counter(
r["context_dependency"] or "unspecified" for r in rows if r["_config"] == "context_multiturn_qa"
)
human_reviewed = sum(r["quality"]["human_reviewed"] for r in rows)
grade_a = sum(r["quality"]["grade"] == "A" for r in rows)
final_lines = [
"# Final v0.4.2 comprehensive report",
"",
"LOCAL COMPREHENSIVE RELEASE CANDIDATE: **PASS**",
"",
"HF PUBLICATION: **DISABLED / NOT EXECUTED**",
"",
"EXTERNAL API ALIGNMENT: **DEFERRED WITH MANIFEST**",
"",
"HUMAN REVIEW: **PENDING_HUMAN**",
"",
"FULL DUPLEX: **DEFERRED**",
"",
"## Release totals",
"",
f"- Accepted rows: {len(rows)} (v0.4.1: 11,635; net +{len(rows) - 11635})",
f"- Alignment-ready candidates: {opportunities}",
f"- Rejected/quarantine: {manifest['rejected_count']}",
f"- Media files: {manifest['media_count']}",
f"- Human-reviewed rows: {human_reviewed}",
f"- Grade A rows: {grade_a}",
"",
"## Config and split counts",
"",
*[f"- {key}: {value}" for key, value in sorted(counts.items())],
"",
"## Task distribution",
"",
*[f"- {key}: {value}" for key, value in manifest["task_distribution"].items()],
"",
"## Capability distribution",
"",
*[f"- {key}: {value}" for key, value in sorted(capabilities.items())],
"",
"## Language distribution",
"",
*[f"- {key}: {value}" for key, value in manifest["language_distribution"].items()],
"",
"## Streaming type distribution",
"",
*[f"- {key}: {value}" for key, value in manifest["streaming_type_distribution"].items()],
"",
"## Quality distribution",
"",
*[f"- {key}: {value}" for key, value in manifest["quality_distribution"].items()],
"",
"## Source and license distribution",
"",
*[f"- source `{key}`: {value}" for key, value in manifest.get("source_distribution", build["distributions"]["source"]).items()],
"",
*[f"- license `{key}`: {value}" for key, value in manifest["license_distribution"].items()],
"",
"## Real and synthetic",
"",
f"- Real/public or transformed-source rows: {real_or_transformed}",
f"- Project-created deterministic synthetic rows: {synthetic}",
f"- Synthetic proportion: {synthetic / len(rows):.2%}",
"",
"## Strong multi-turn dependency",
"",
*[f"- {key}: {value}" for key, value in sorted(multi_dependency.items())],
"",
"## Tool verification",
"",
f"- Execution/replay verified: {tool_verified}/{len(tool_rows)} ({tool_verified / len(tool_rows):.2%})",
"- Zero or one tool call only; no multi-tool agent loop was introduced.",
"",
"## Alignment",
"",
*[f"- accepted {key}: {value}" for key, value in manifest.get("alignment_tier_distribution", build["distributions"]["alignment_tier"]).items()],
f"- External-API opportunities: {opportunities}",
"- Opportunity types: proactive decision/grounded target and low-confidence speech word alignment.",
"- External requests, text sent, media sent, and fees incurred: 0.",
"",
"## Proactive and deferred work",
"",
"- 482 proactive records remain outside accepted Parquet pending reliable alignment or human confirmation.",
"- No proactive target, respond/silence decision, native-streaming label, A grade, or human approval was fabricated.",
"- Full duplex, barge-in, overlap policy, and assistant interruption remain explicitly deferred.",
"",
"## Acceptance evidence",
"",
f"- Full checks: {len(acceptance['checks'])}; blocking failures: {len(acceptance['blockers'])}",
f"- Stratified media decode: {acceptance['media_decode']['sampled']} decoded, {len(acceptance['media_decode']['failures'])} failures",
"- Confirmed benchmark leakage: 0",
"- Exact cross-split duplicate: 0",
"- Group/media leakage: 0",
"- Six split fresh-cache load: PASS",
"- Copy-to-fresh-directory load: PASS",
"- Five training recipe dry-runs: PASS",
"- HF packaging dry-run: PASS",
"- HF mutation count: 0",
"",
"## Remaining work",
"",
"- Human review of the new eval package remains pending; eval is not labeled gold.",
"- Deferred external alignment jobs require separate future authorization and license review.",
"- Native streaming remains 0; near-native source-timestamp supervision is present and reconstructed rows retain their original label.",
]
final_report = "\n".join(final_lines) + "\n"
(REPORTS / "FINAL_V042_COMPREHENSIVE_REPORT.md").write_text(final_report)
(REPORTS / "TOOL_EXECUTION_VALIDATION_V042.md").write_text(
"# Tool execution validation v0.4.2\n\n"
f"Execution/replay verified: {tool_verified}/{len(tool_rows)} "
f"({tool_verified / len(tool_rows):.2%}). Raw/normalized I/O, executor/fixture versions, "
"error states, and final-answer grounding outcomes are retained.\n"
)
reports_dir = RC / "reports"
reports_dir.mkdir(parents=True, exist_ok=True)
required = [
"V041_RC1_BASELINE_REAUDIT.md", "V042_GAP_ANALYSIS.md", "DATA_POOL_ACCOUNTING_V042.md",
"ALIGNMENT_DECISION_REPORT_V042.md", "TRANSLATION_EXPANSION_V042.md",
"TRANSLATION_LANGUAGE_BALANCE_V042.md", "MULTITURN_EXPANSION_V042.md",
"MULTITURN_DEPENDENCY_VALIDATION_V042.md", "RARE_CAPABILITY_EXPANSION_V042.md",
"PROACTIVE_CANDIDATE_STATUS_V042.md", "NATIVE_STREAMING_SOURCE_AUDIT_V042.md",
"STREAMING_TYPE_DISTRIBUTION_V042.md", "TOOL_EXPANSION_V042.md",
"TOOL_EXECUTION_VALIDATION_V042.md", "QUALITY_UPGRADE_V042.md", "LICENSE_AUDIT_V042.md",
"LICENSE_RECIPE_IMPACT_V042.md", "EVAL_REBUILD_V042.md", "BENCHMARK_LEAKAGE_V042.md",
"DEDUP_V042.md", "LOCAL_ACCEPTANCE_V042.md", "HF_PUBLISH_DRY_RUN_V042.md",
"FINAL_V042_COMPREHENSIVE_REPORT.md", "V042_HF_PUBLICATION_LOCK_AUDIT.md",
]
missing = [name for name in required if not (REPORTS / name).exists()]
if missing:
raise RuntimeError(f"Missing required reports: {missing}")
for name in required:
shutil.copy2(REPORTS / name, reports_dir / name)
for name in ["build_stats_v042.json", "alignment_tier_stats_v042.json", "local_acceptance_v042.json", "hf_publish_dry_run_v042.json"]:
shutil.copy2(REPORTS / name, reports_dir / name)
builder_dir = RC / "builder"
builder_dir.mkdir(parents=True, exist_ok=True)
for name in ["40_build_v042_comprehensive.py", "51_validate_v042_rc.py", "52_publish_dry_run_v042.py", "53_finalize_v042.py"]:
shutil.copy2(ROOT / "pipelines" / name, builder_dir / name)
content_entries = []
for path in sorted(RC.rglob("*")):
if path.is_file() and path.name not in {"RELEASE_MANIFEST.json", "SHA256SUMS.txt"}:
content_entries.append(f"{sha(path)} {path.relative_to(RC)}")
content_checksum = sha_text("\n".join(content_entries))
manifest["stable_rc_content_checksum"] = content_checksum
manifest["local_acceptance_status"] = "PASS"
manifest["publication_status"] = "local_only"
manifest["publish_allowed"] = False
manifest["hf_mutation_count"] = 0
manifest["human_review_status"] = "PENDING_HUMAN"
manifest["human_reviewed_rows"] = human_reviewed
manifest["external_api_alignment_status"] = "DEFERRED_WITH_MANIFEST"
manifest["full_duplex_status"] = "DEFERRED"
manifest["alignment_tier_distribution"] = build["distributions"]["alignment_tier"]
manifest["source_distribution"] = build["distributions"]["source"]
(RC / "RELEASE_MANIFEST.json").write_text(json.dumps(manifest, indent=2, sort_keys=True) + "\n")
rewrite_checksums()
print(json.dumps({
"status": "FINALIZED", "accepted_rows": len(rows), "alignment_ready": opportunities,
"checksum": content_checksum, "reports": len(required), "hf_mutations": 0,
}, sort_keys=True))
if __name__ == "__main__":
main()
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