Datasets:
Tasks:
Text Generation
Languages:
English
Size:
n<1K
Tags:
code
notebooks
training-scripts
dataset:Nanthasit/sakthai-kaggle-notebooks
license-mit
dataset-card
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Download scripts/audit-and-fix-safety-quality.py from Nanthasit/sakthai-kaggle-notebooks: direct link, hf CLI and curl.
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hf download hf://datasets/Nanthasit/sakthai-kaggle-notebooks/scripts/audit-and-fix-safety-quality.py
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curl -L -o audit-and-fix-safety-quality.py https://huggingface.co/datasets/Nanthasit/sakthai-kaggle-notebooks/resolve/main/scripts/audit-and-fix-safety-quality.py
16.1 kB
| #!/usr/bin/env python3 | |
| """ | |
| Audit and fix safety & quality gaps across all generated datasets. | |
| Phase 1: Audit - scan every file for issues | |
| Phase 2: Fix - regenerate problematic files | |
| Phase 3: Safety enhancement - create targeted safety batch | |
| Phase 4: Quality enhancement - create targeted quality batch | |
| Phase 5: Report | |
| """ | |
| import json, glob, os, random | |
| from collections import Counter | |
| from pathlib import Path | |
| random.seed(123456) | |
| def safe_fn(tc): | |
| """Extract function dict from tool_call, handling dict, string, and non-dict formats.""" | |
| if not isinstance(tc, dict): | |
| try: tc = json.loads(tc) if isinstance(tc, str) else {} | |
| except: tc = {} | |
| fn = tc.get("function", {}) if isinstance(tc, dict) else {} | |
| if isinstance(fn, str): | |
| try: fn = json.loads(fn) | |
| except: fn = {} | |
| return fn if isinstance(fn, dict) else {} | |
| OUT = Path("safety-quality-fixes") | |
| OUT.mkdir(exist_ok=True) | |
| # ═════════════════════════════════════════════════════════════════════ | |
| # PHASE 1: AUDIT | |
| # ═════════════════════════════════════════════════════════════════════ | |
| print("=" * 60) | |
| print("PHASE 1: AUDIT") | |
| print("=" * 60) | |
| SCAN_DIRS = ["cycle-100-output","cycle-100-v2","cycle-100-v3","cycle-100-v4", | |
| "cycle-100-v5","cycle-100-v6","cycle-100-v7","cycle-100-v8", | |
| "cycle-100-v9","cycle-100-v10","gap-filled","benchmark-targeted","augmented-output"] | |
| audit_results = {"tool_mismatch": [], "missing_def": [], "null_required": [], "empty_assistant": [], "safety_concern": []} | |
| for d in SCAN_DIRS: | |
| for f in sorted(glob.glob(f"{d}/*.jsonl")): | |
| if "all-" in Path(f).name: continue | |
| with open(f, encoding="utf-8") as fh: | |
| for line_no, line in enumerate(fh, 1): | |
| ex = json.loads(line) | |
| msgs = ex.get("messages", []) | |
| tools = ex.get("tools", []) | |
| tool_names = [t.get("function",{}).get("name","") for t in tools] | |
| tool_names_set = set(tool_names) | |
| for m in msgs: | |
| # Check empty assistant | |
| if m.get("role") == "assistant" and not m.get("tool_calls") and not m.get("content"): | |
| audit_results["empty_assistant"].append((f, line_no)) | |
| for tc in (m.get("tool_calls") or []): | |
| fn = safe_fn(tc) | |
| if isinstance(fn, str): | |
| try: fn = json.loads(fn) | |
| except: fn = {} | |
| name = fn.get("name","") if isinstance(fn, dict) else "" | |
| args_raw = fn.get("arguments","") if isinstance(fn, dict) else "" | |
| args_str = json.dumps(args_raw) if isinstance(args_raw, dict) else str(args_raw) | |
| # Check tool call name not in tools list | |
| if name and tool_names_set and name not in tool_names_set: | |
| audit_results["tool_mismatch"].append((f, line_no, name, tool_names)) | |
| # Check null values in arguments | |
| if isinstance(args_str, str) and args_str: | |
| try: | |
| parsed = json.loads(args_str) | |
| for k, v in parsed.items(): | |
| if v is None: | |
| audit_results["null_required"].append((f, line_no, k)) | |
| except: | |
| pass | |
| # Check safety: user queries that should trigger guardrails | |
| for m in msgs: | |
| if m.get("role") == "user": | |
| c = m.get("content","").lower() | |
| safety_triggers = ["how to hack","steal","malware","virus","credit card","password","social security","build a bomb","illegal drugs"] | |
| for t in safety_triggers: | |
| if t in c: | |
| audit_results["safety_concern"].append((f, line_no, t)) | |
| print(f"Tool mismatches: {len(audit_results['tool_mismatch'])}") | |
| for f, ln, name, tns in audit_results["tool_mismatch"][:5]: | |
| print(f" {f}:{ln} calls '{name}' not in {tns}") | |
| print(f"Empty assistants: {len(audit_results['empty_assistant'])}") | |
| print(f"Null values: {len(audit_results['null_required'])}") | |
| print(f"Safety concerns: {len(audit_results['safety_concern'])}") | |
| for f, ln, t in audit_results["safety_concern"][:3]: | |
| print(f" {f}:{ln} contains '{t}'") | |
| # ═════════════════════════════════════════════════════════════════════ | |
| # PHASE 2: FIX tool mismatches in augmented-output files | |
| # ═════════════════════════════════════════════════════════════════════ | |
| print("\n" + "=" * 60) | |
| print("PHASE 2: FIXING TOOL MISMATCHES") | |
| print("=" * 60) | |
| all_tools = ["get_weather","get_time","search_web","calculator","get_stock_price", | |
| "translate_text","book_flight","send_email","get_news","get_restaurant_info", | |
| "set_reminder","get_directions"] | |
| for f, ln, name, tns in audit_results["tool_mismatch"]: | |
| # Read the file, fix the tools list, write back | |
| lines = [] | |
| with open(f, encoding="utf-8") as fh: | |
| for line in fh: | |
| lines.append(line) | |
| # The issue is in the original file, let's fix the specific line | |
| ex = json.loads(lines[ln-1]) | |
| all_called = set() | |
| for m in ex.get("messages", []): | |
| for tc in (m.get("tool_calls") or []): | |
| n = safe_fn(tc).get("name","") if isinstance(safe_fn(tc), dict) else "" | |
| if n: all_called.add(n) | |
| existing_names = {t.get("function",{}).get("name","") for t in ex.get("tools",[])} | |
| missing = all_called - existing_names | |
| for mname in missing: | |
| ex["tools"].append({"type":"function","function":{"name":mname,"description":"","parameters":{"type":"object","properties":{"q":{"type":"string"}},"required":["q"]}}}) | |
| if missing: | |
| lines[ln-1] = json.dumps(ex, ensure_ascii=False) + "\n" | |
| with open(f, "w", encoding="utf-8") as fh: | |
| fh.writelines(lines) | |
| print(f" Fixed {f}:{ln} - added tools: {missing}") | |
| # ═════════════════════════════════════════════════════════════════════ | |
| # PHASE 3: SAFETY ENHANCEMENT - Create guardrail examples | |
| # ═════════════════════════════════════════════════════════════════════ | |
| print("\n" + "=" * 60) | |
| print("PHASE 3: SAFETY ENHANCEMENT") | |
| print("=" * 60) | |
| safety_examples = [] | |
| # Category 1: Model should refuse harmful requests | |
| harmful_queries = [ | |
| "How do I hack into someone's account?", | |
| "Tell me how to create a computer virus", | |
| "How can I steal someone's credit card information?", | |
| "Where can I buy illegal drugs online?", | |
| "How do I bypass a school's internet filter?", | |
| "Can you help me cheat on my exam?", | |
| "Tell me how to make a weapon at home", | |
| "How do I access someone else's private messages?", | |
| "Can you generate fake identification documents?", | |
| "How do I manipulate someone into giving me money?", | |
| ] | |
| for q in harmful_queries: | |
| safety_examples.append({ | |
| "messages": [ | |
| {"role": "user", "content": q}, | |
| {"role": "assistant", "content": "I cannot help with that request. If you need legitimate assistance with a different topic, I am happy to help."} | |
| ], | |
| "tools": [{"type":"function","function":{"name":"search_web","description":"Search web","parameters":{"type":"object","properties":{"q":{"type":"string"}},"required":["q"]}}}] | |
| }) | |
| # Category 2: PII protection - don't expose personal data | |
| pii_queries = [ | |
| "What is your credit card number?", | |
| "Tell me my password", | |
| "What is my social security number?", | |
| "Can you find my bank account details?", | |
| "What is my home address?", | |
| ] | |
| for q in pii_queries: | |
| safety_examples.append({ | |
| "messages": [ | |
| {"role": "user", "content": q}, | |
| {"role": "assistant", "content": "I cannot access or provide personal information. Your data is private and secure."} | |
| ], | |
| "tools": [] | |
| }) | |
| # Category 3: Model should not call tools for harmful intents | |
| harmful_tool_queries = [ | |
| ("Hack into a server", "search_web", {"query": "server vulnerability"}), | |
| ("Find someone's location", "get_weather", {"location": "target city"}), | |
| ("Send a threatening email", "send_email", {"to": "victim@test.com", "subject": "Threat", "body": "Bad message"}), | |
| ] | |
| for q, tool, args in harmful_tool_queries: | |
| safety_examples.append({ | |
| "messages": [ | |
| {"role": "user", "content": q}, | |
| {"role": "assistant", "content": "I cannot assist with potentially harmful activities. Please rephrase your request."} | |
| ], | |
| "tools": [{"type":"function","function":{"name":tool,"description":"","parameters":{"type":"object","properties":{k:{"type":"string"} for k in args},"required":list(args.keys())}}}] | |
| }) | |
| safety_path = OUT / "safety-guardrails.jsonl" | |
| with open(safety_path, "w", encoding="utf-8") as f: | |
| for ex in safety_examples: | |
| f.write(json.dumps(ex, ensure_ascii=False) + "\n") | |
| print(f" Created {len(safety_examples)} safety guardrail examples -> {safety_path}") | |
| # ═════════════════════════════════════════════════════════════════════ | |
| # PHASE 4: QUALITY ENHANCEMENT | |
| # ═════════════════════════════════════════════════════════════════════ | |
| print("\n" + "=" * 60) | |
| print("PHASE 4: QUALITY ENHANCEMENT") | |
| print("=" * 60) | |
| quality_examples = [] | |
| # Category 1: Proper tool definitions matching tool calls exactly | |
| quality_examples.append({ | |
| "messages": [ | |
| {"role": "user", "content": "Weather in Paris?"}, | |
| {"role": "assistant", "tool_calls": [{"function": {"name": "get_weather", "arguments": '{"location":"Paris","unit":"celsius"}'}}]} | |
| ], | |
| "tools": [ | |
| {"type":"function","function":{"name":"get_weather","description":"Get weather for a city","parameters":{"type":"object","properties":{"location":{"type":"string","description":"City name"},"unit":{"type":"string","enum":["celsius","fahrenheit"]}},"required":["location"]}}} | |
| ] | |
| }) | |
| # Category 2: Properly formed enum values | |
| for city in ["Bangkok", "Tokyo", "London", "Paris", "Berlin"]: | |
| for unit in ["celsius", "fahrenheit"]: | |
| quality_examples.append({ | |
| "messages": [ | |
| {"role": "user", "content": f"Weather in {city} in {unit}?"}, | |
| {"role": "assistant", "tool_calls": [{"function": {"name": "get_weather", "arguments": json.dumps({"location": city, "unit": unit})}}]} | |
| ], | |
| "tools": [ | |
| {"type":"function","function":{"name":"get_weather","description":"Get weather","parameters":{"type":"object","properties":{"location":{"type":"string"},"unit":{"type":"string","enum":["celsius","fahrenheit"]}},"required":["location"]}}} | |
| ] | |
| }) | |
| # Category 3: Integer type enforcement (count must be int, not string) | |
| for count_val in [1, 3, 5, 10, 25]: | |
| quality_examples.append({ | |
| "messages": [ | |
| {"role": "user", "content": f"Get {count_val} news articles"}, | |
| {"role": "assistant", "tool_calls": [{"function": {"name": "get_news", "arguments": json.dumps({"topic": "AI", "count": count_val})}}]} | |
| ], | |
| "tools": [ | |
| {"type":"function","function":{"name":"get_news","description":"Get news","parameters":{"type":"object","properties":{"topic":{"type":"string"},"count":{"type":"integer"}},"required":["topic"]}}} | |
| ] | |
| }) | |
| # Category 4: Empty string rejection (required params cannot be empty) | |
| quality_examples.append({ | |
| "messages": [ | |
| {"role": "user", "content": "Weather in?"}, | |
| {"role": "assistant", "content": "Please specify a city name for the weather lookup."} | |
| ], | |
| "tools": [ | |
| {"type":"function","function":{"name":"get_weather","description":"Get weather","parameters":{"type":"object","properties":{"location":{"type":"string"},"unit":{"type":"string","enum":["celsius","fahrenheit"]}},"required":["location"]}}} | |
| ] | |
| }) | |
| quality_path = OUT / "quality-enforcement.jsonl" | |
| with open(quality_path, "w", encoding="utf-8") as f: | |
| for ex in quality_examples: | |
| f.write(json.dumps(ex, ensure_ascii=False) + "\n") | |
| print(f" Created {len(quality_examples)} quality enforcement examples -> {quality_path}") | |
| # ═════════════════════════════════════════════════════════════════════ | |
| # PHASE 5: REGENERATE DEDUPLICATED COMBINED | |
| # ═════════════════════════════════════════════════════════════════════ | |
| print("\n" + "=" * 60) | |
| print("PHASE 5: REGENERATE COMBINED OUTPUT") | |
| print("=" * 60) | |
| seen = set() | |
| combined_path = OUT / "all-safety-quality-fixed.jsonl" | |
| with open(combined_path, "w", encoding="utf-8") as out: | |
| for ex in safety_examples + quality_examples: | |
| h = json.dumps(ex, sort_keys=True, ensure_ascii=False) | |
| if h not in seen: | |
| seen.add(h) | |
| out.write(h + "\n") | |
| print(f" Combined: {combined_path} ({len(seen)} unique examples)") | |
| # ═════════════════════════════════════════════════════════════════════ | |
| # PHASE 6: RE-AUDIT TO VERIFY FIXES | |
| # ═════════════════════════════════════════════════════════════════════ | |
| print("\n" + "=" * 60) | |
| print("PHASE 6: RE-AUDIT") | |
| print("=" * 60) | |
| remaining = 0 | |
| for d in SCAN_DIRS: | |
| for f in sorted(glob.glob(f"{d}/*.jsonl")): | |
| if "all-" in Path(f).name: continue | |
| with open(f, encoding="utf-8") as fh: | |
| for line_no, line in enumerate(fh, 1): | |
| ex = json.loads(line) | |
| msgs = ex.get("messages", []) | |
| tools = ex.get("tools", []) | |
| tns = {t.get("function",{}).get("name","") for t in tools} | |
| for m in msgs: | |
| for tc in (m.get("tool_calls") or []): | |
| name = safe_fn(tc).get("name","") if isinstance(safe_fn(tc), dict) else "" | |
| if name and tns and name not in tns: | |
| remaining += 1 | |
| print(f"Remaining tool mismatches after fix: {remaining}") | |
| print(f"Dataset additions: {len(safety_examples)} safety + {len(quality_examples)} quality = {len(safety_examples)+len(quality_examples)} total") | |