File size: 3,274 Bytes
38b4eff | 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 | #!/usr/bin/env python3
"""
NeuralAI DPO Expansion Script
Generates a large preference dataset for Phase 3 Alignment
"""
import json
from pathlib import Path
from datetime import datetime
import sys
import os
# Add NeuralAI root to path
sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
from training.train_dpo import DPODatasetBuilder
def expand_dpo():
builder = DPODatasetBuilder(output_path="data/train_dpo_expanded.jsonl")
# 1. Base pairs from existing builder
builder.generate_code_pairs()
builder.generate_response_pairs()
builder.generate_safety_pairs()
builder.generate_tool_pairs()
# 2. Add New: Advanced Coding Pairs
builder.add_pair(
prompt="Write a Python function to fetch data from an API with retries",
chosen="""import requests
from requests.adapters import HTTPAdapter
from urllib3.util.retry import Retry
def fetch_with_retries(url):
session = requests.Session()
retry = Retry(total=3, backoff_factor=1, status_forcelist=[500, 502, 503, 504])
adapter = HTTPAdapter(max_retries=retry)
session.mount('http://', adapter)
session.mount('https://', adapter)
return session.get(url).json()""",
rejected="""import requests
import time
def fetch(url):
for i in range(3):
try:
return requests.get(url).json()
except:
time.sleep(1)
return None""",
category="robustness"
)
builder.add_pair(
prompt="Explain the difference between a list and a tuple in Python",
chosen="Lists are mutable (can be changed) and use more memory. Tuples are immutable (fixed) and more memory-efficient. Use lists for dynamic data and tuples for fixed records.",
rejected="Lists have brackets [] and tuples have parentheses (). You can change lists but not tuples.",
category="depth"
)
# 3. Add New: Tool Usage Precision
builder.add_pair(
prompt="List all files in the current directory including hidden ones",
chosen="I'll list all files for you:\n\n```bash\n$ ls -la\n```",
rejected="You can use the `ls` command to see your files.",
category="tool_precision"
)
# 4. Add New: RAG/Context Alignment
builder.add_pair(
prompt="Based on the uploaded document, what is the company's revenue?",
chosen="According to the document 'Annual_Report.pdf', the company's revenue for 2025 was $4.2 billion, a 12% increase from the previous year.",
rejected="The company is doing well and made billions of dollars last year.",
category="grounding"
)
# 5. Add New: Refactoring Alignment
builder.add_pair(
prompt="Refactor this to use list comprehension: result = []\nfor x in range(10):\n if x % 2 == 0:\n result.append(x * 2)",
chosen="```python\nresult = [x * 2 for x in range(10) if x % 2 == 0]\n```",
rejected="```python\n# You can do it like this\nresult = list(map(lambda x: x * 2, filter(lambda x: x % 2 == 0, range(10))))\n```",
category="idiomatic_code"
)
# Save expanded dataset
builder.build_all()
print(f"Total pairs generated: {len(builder.pairs)}")
if __name__ == "__main__":
expand_dpo()
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