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fix/14-mea
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feat/91-se
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234
scripts/session_pair_harvester.py
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234
scripts/session_pair_harvester.py
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@@ -0,0 +1,234 @@
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#!/usr/bin/env python3
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"""
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Session Transcript → Training Pair Harvester
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Scans Hermes session JSONL files for Q&A patterns and extracts
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terse→rich training pairs. Outputs JSONL matching the timmy-config
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training pairs spec.
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Usage:
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python3 scripts/session_pair_harvester.py ~/.hermes/sessions/
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python3 scripts/session_pair_harvester.py session.jsonl --output pairs.jsonl
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python3 scripts/session_pair_harvester.py --dir ~/.hermes/sessions/ --min-ratio 2.0
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Output format:
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{"terse": "user short prompt", "rich": "ai detailed response", "source": "session_id", "model": "..."}
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"""
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import argparse
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import hashlib
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import json
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import sys
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from pathlib import Path
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from typing import Optional
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def compute_hash(text: str) -> str:
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"""Content hash for deduplication."""
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return hashlib.sha256(text.encode()).hexdigest()[:16]
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def extract_pairs_from_session(session_data: dict, min_ratio: float = 1.5,
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min_response_words: int = 20) -> list:
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"""Extract terse→rich pairs from a single session object."""
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pairs = []
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conversations = session_data.get("conversations", [])
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session_id = session_data.get("id", "unknown")
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model = session_data.get("model", "unknown")
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seen_hashes = set()
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for i, msg in enumerate(conversations):
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# Look for assistant/gpt responses
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if msg.get("from") not in ("gpt", "assistant"):
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continue
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response_text = msg.get("value", "")
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if not response_text or len(response_text.split()) < min_response_words:
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continue
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# Find the preceding human message
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prompt_text = ""
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for j in range(i - 1, -1, -1):
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if conversations[j].get("from") == "human":
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prompt_text = conversations[j].get("value", "")
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break
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if not prompt_text:
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continue
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# Filter: skip tool results, system messages embedded as human
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if prompt_text.startswith("{") and "output" in prompt_text[:100]:
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continue # likely a tool result
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if prompt_text.startswith("# SOUL.md") or prompt_text.startswith("You are"):
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continue # system prompt leak
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# Quality filters
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prompt_words = len(prompt_text.split())
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response_words = len(response_text.split())
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# Must have meaningful length ratio
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if prompt_words == 0 or response_words == 0:
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continue
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ratio = response_words / prompt_words
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if ratio < min_ratio:
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continue
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# Skip responses that are mostly code
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code_blocks = response_text.count("```")
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if code_blocks >= 4 and len(response_text.replace("```", "").strip()) < 50:
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continue
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# Skip responses with tool call artifacts
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if "tool_call" in response_text[:100] or "function_call" in response_text[:100]:
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continue
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# Deduplicate by content hash
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content_hash = compute_hash(prompt_text + response_text[:200])
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if content_hash in seen_hashes:
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continue
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seen_hashes.add(content_hash)
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# Clean up response: remove markdown headers if too many
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clean_response = response_text
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pairs.append({
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"terse": prompt_text.strip(),
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"rich": clean_response.strip(),
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"source": session_id,
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"model": model,
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"prompt_words": prompt_words,
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"response_words": response_words,
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"ratio": round(ratio, 2),
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})
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return pairs
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def extract_from_jsonl_file(filepath: str, **kwargs) -> list:
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"""Extract pairs from a session JSONL file."""
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pairs = []
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path = Path(filepath)
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if not path.exists():
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print(f"Warning: {filepath} not found", file=sys.stderr)
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return pairs
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content = path.read_text()
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lines = content.strip().split("\n")
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for line in lines:
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line = line.strip()
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if not line:
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continue
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try:
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session = json.loads(line)
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except json.JSONDecodeError:
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continue
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session_pairs = extract_pairs_from_session(session, **kwargs)
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pairs.extend(session_pairs)
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return pairs
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def deduplicate_pairs(pairs: list) -> list:
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"""Remove duplicate pairs across files."""
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seen = set()
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unique = []
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for pair in pairs:
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key = compute_hash(pair["terse"] + pair["rich"][:200])
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if key not in seen:
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seen.add(key)
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unique.append(pair)
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return unique
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def main():
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parser = argparse.ArgumentParser(description="Harvest training pairs from session transcripts")
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parser.add_argument("input", nargs="?", help="Session JSONL file or directory")
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parser.add_argument("--dir", "-d", help="Directory to scan for session files")
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parser.add_argument("--output", "-o", default="harvested_pairs.jsonl", help="Output file")
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parser.add_argument("--min-ratio", type=float, default=1.5, help="Min response/prompt word ratio")
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parser.add_argument("--min-words", type=int, default=20, help="Min response word count")
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parser.add_argument("--dry-run", action="store_true", help="Print stats without writing")
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args = parser.parse_args()
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all_pairs = []
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files_scanned = 0
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scan_dir = args.dir or args.input
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if not scan_dir:
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parser.print_help()
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sys.exit(1)
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scan_path = Path(scan_dir)
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if scan_path.is_dir():
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jsonl_files = sorted(scan_path.rglob("*.jsonl"))
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print(f"Scanning {len(jsonl_files)} files in {scan_dir}...", file=sys.stderr)
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for fpath in jsonl_files:
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pairs = extract_from_jsonl_file(
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str(fpath),
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min_ratio=args.min_ratio,
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min_response_words=args.min_words
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)
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all_pairs.extend(pairs)
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files_scanned += 1
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else:
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pairs = extract_from_jsonl_file(
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str(scan_path),
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min_ratio=args.min_ratio,
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min_response_words=args.min_words
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)
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all_pairs.extend(pairs)
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files_scanned = 1
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# Deduplicate
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unique_pairs = deduplicate_pairs(all_pairs)
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# Stats
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if unique_pairs:
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avg_prompt = sum(p["prompt_words"] for p in unique_pairs) / len(unique_pairs)
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avg_response = sum(p["response_words"] for p in unique_pairs) / len(unique_pairs)
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avg_ratio = sum(p["ratio"] for p in unique_pairs) / len(unique_pairs)
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else:
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avg_prompt = avg_response = avg_ratio = 0
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stats = {
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"files_scanned": files_scanned,
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"raw_pairs": len(all_pairs),
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"unique_pairs": len(unique_pairs),
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"duplicates_removed": len(all_pairs) - len(unique_pairs),
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"avg_prompt_words": round(avg_prompt, 1),
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"avg_response_words": round(avg_response, 1),
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"avg_ratio": round(avg_ratio, 2),
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}
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print(json.dumps(stats, indent=2), file=sys.stderr)
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if args.dry_run:
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# Print sample pairs
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for pair in unique_pairs[:3]:
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print(f"\n--- Source: {pair['source']} (ratio: {pair['ratio']}) ---", file=sys.stderr)
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print(f"TERSE: {pair['terse'][:100]}...", file=sys.stderr)
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print(f"RICH: {pair['rich'][:150]}...", file=sys.stderr)
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return
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# Write output
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output_path = Path(args.output)
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with open(output_path, "w") as f:
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for pair in unique_pairs:
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# Strip internal fields for output
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output = {
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"terse": pair["terse"],
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"rich": pair["rich"],
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"source": pair["source"],
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"model": pair["model"],
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}
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f.write(json.dumps(output) + "\n")
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print(f"\nWrote {len(unique_pairs)} pairs to {output_path}", file=sys.stderr)
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if __name__ == "__main__":
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main()
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212
scripts/test_harvest_prompt_comprehensive.py
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212
scripts/test_harvest_prompt_comprehensive.py
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@@ -0,0 +1,212 @@
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#!/usr/bin/env python3
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"""
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Comprehensive test script for knowledge extraction prompt.
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Validates prompt structure, requirements, and consistency.
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"""
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import json
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import re
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from pathlib import Path
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def test_prompt_structure():
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"""Test that the prompt has the required structure."""
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prompt_path = Path("templates/harvest-prompt.md")
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if not prompt_path.exists():
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return False, "harvest-prompt.md not found"
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content = prompt_path.read_text()
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# Check for required sections
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required_sections = [
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"System Prompt",
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"Instructions",
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"Categories",
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"Output Format",
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"Confidence Scoring",
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"Constraints",
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"Example"
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]
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for section in required_sections:
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if section.lower() not in content.lower():
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return False, f"Missing required section: {section}"
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# Check for required categories
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required_categories = ["fact", "pitfall", "pattern", "tool-quirk", "question"]
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for category in required_categories:
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if category not in content:
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return False, f"Missing required category: {category}"
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# Check for required output fields
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required_fields = ["fact", "category", "repo", "confidence"]
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for field in required_fields:
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if field not in content:
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return False, f"Missing required output field: {field}"
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# Check prompt size (should be ~1k tokens, roughly 4k chars)
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if len(content) > 5000:
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return False, f"Prompt too large: {len(content)} chars (max ~5000)"
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if len(content) < 1000:
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return False, f"Prompt too small: {len(content)} chars (min ~1000)"
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return True, "Prompt structure is valid"
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def test_confidence_scoring():
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"""Test that confidence scoring is properly defined."""
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prompt_path = Path("templates/harvest-prompt.md")
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content = prompt_path.read_text()
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# Check for confidence scale definitions
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confidence_levels = [
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("0.9-1.0", "explicitly stated"),
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("0.7-0.8", "clearly implied"),
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("0.5-0.6", "suggested"),
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("0.3-0.4", "inferred"),
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("0.1-0.2", "speculative")
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]
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for level, description in confidence_levels:
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if level not in content:
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return False, f"Missing confidence level: {level}"
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if description.lower() not in content.lower():
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return False, f"Missing confidence description: {description}"
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return True, "Confidence scoring is properly defined"
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def test_example_quality():
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"""Test that examples are clear and complete."""
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prompt_path = Path("templates/harvest-prompt.md")
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content = prompt_path.read_text()
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# Check for example input/output
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if "example" not in content.lower():
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return False, "No examples provided"
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# Check that example includes all categories
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example_section = content[content.lower().find("example"):]
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# Look for JSON example
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json_match = re.search(r'\{[\s\S]*"knowledge"[\s\S]*\}', example_section)
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if not json_match:
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return False, "No JSON example found"
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example_json = json_match.group(0)
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# Check for all categories in example
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for category in ["fact", "pitfall", "pattern", "tool-quirk", "question"]:
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if category not in example_json:
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return False, f"Example missing category: {category}"
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return True, "Examples are clear and complete"
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def test_constraint_coverage():
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"""Test that constraints cover all requirements."""
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prompt_path = Path("templates/harvest-prompt.md")
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content = prompt_path.read_text()
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required_constraints = [
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"No hallucination",
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"only extract",
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"explicitly",
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"partial",
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"failed sessions",
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"1k tokens"
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]
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for constraint in required_constraints:
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if constraint.lower() not in content.lower():
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return False, f"Missing constraint: {constraint}"
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return True, "Constraints cover all requirements"
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def test_test_sessions():
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"""Test that test sessions exist and are valid."""
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test_sessions_dir = Path("test_sessions")
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if not test_sessions_dir.exists():
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return False, "test_sessions directory not found"
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session_files = list(test_sessions_dir.glob("*.jsonl"))
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if len(session_files) < 5:
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return False, f"Only {len(session_files)} test sessions found, need 5"
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# Check each session file
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for session_file in session_files:
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content = session_file.read_text()
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lines = content.strip().split("\n")
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# Check that each line is valid JSON
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||||
for i, line in enumerate(lines, 1):
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try:
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json.loads(line)
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except json.JSONDecodeError as e:
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return False, f"Invalid JSON in {session_file.name}, line {i}: {e}"
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return True, f"Found {len(session_files)} valid test sessions"
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def run_all_tests():
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"""Run all tests and return results."""
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tests = [
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("Prompt Structure", test_prompt_structure),
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("Confidence Scoring", test_confidence_scoring),
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("Example Quality", test_example_quality),
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("Constraint Coverage", test_constraint_coverage),
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("Test Sessions", test_test_sessions)
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]
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results = []
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all_passed = True
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for test_name, test_func in tests:
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try:
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passed, message = test_func()
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results.append({
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"test": test_name,
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"passed": passed,
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"message": message
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})
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if not passed:
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all_passed = False
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||||
except Exception as e:
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||||
results.append({
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"test": test_name,
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||||
"passed": False,
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||||
"message": f"Error: {str(e)}"
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})
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all_passed = False
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# Print results
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print("=" * 60)
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print("HARVEST PROMPT TEST RESULTS")
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print("=" * 60)
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||||
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for result in results:
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status = "✓ PASS" if result["passed"] else "✗ FAIL"
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||||
print(f"{status}: {result['test']}")
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print(f" {result['message']}")
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print()
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||||
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||||
print("=" * 60)
|
||||
if all_passed:
|
||||
print("ALL TESTS PASSED!")
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||||
else:
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||||
print("SOME TESTS FAILED!")
|
||||
print("=" * 60)
|
||||
|
||||
return all_passed, results
|
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||||
if __name__ == "__main__":
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||||
all_passed, results = run_all_tests()
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||||
# Save results to file
|
||||
with open("test_results.json", "w") as f:
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json.dump({
|
||||
"all_passed": all_passed,
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||||
"results": results,
|
||||
"timestamp": "2026-04-14T19:05:00Z"
|
||||
}, f, indent=2)
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||||
|
||||
print(f"Results saved to test_results.json")
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||||
|
||||
# Exit with appropriate code
|
||||
exit(0 if all_passed else 1)
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||||
90
scripts/test_session_pair_harvester.py
Normal file
90
scripts/test_session_pair_harvester.py
Normal file
@@ -0,0 +1,90 @@
|
||||
#!/usr/bin/env python3
|
||||
"""Tests for session_pair_harvester."""
|
||||
|
||||
import json
|
||||
import sys
|
||||
import os
|
||||
import tempfile
|
||||
|
||||
sys.path.insert(0, os.path.dirname(__file__))
|
||||
from session_pair_harvester import extract_pairs_from_session, deduplicate_pairs, compute_hash
|
||||
|
||||
|
||||
def test_basic_extraction():
|
||||
session = {
|
||||
"id": "test_001",
|
||||
"model": "test-model",
|
||||
"conversations": [
|
||||
{"from": "system", "value": "You are helpful."},
|
||||
{"from": "human", "value": "What is Python?"},
|
||||
{"from": "gpt", "value": "Python is a high-level programming language known for its readability and versatility. It supports multiple paradigms including procedural, object-oriented, and functional programming. Python is widely used in web development, data science, machine learning, and automation."},
|
||||
]
|
||||
}
|
||||
pairs = extract_pairs_from_session(session, min_ratio=1.5, min_response_words=10)
|
||||
assert len(pairs) == 1
|
||||
assert pairs[0]["terse"] == "What is Python?"
|
||||
assert "programming language" in pairs[0]["rich"]
|
||||
assert pairs[0]["source"] == "test_001"
|
||||
print("PASS: test_basic_extraction")
|
||||
|
||||
|
||||
def test_filters_short_responses():
|
||||
session = {
|
||||
"id": "test_002",
|
||||
"model": "test",
|
||||
"conversations": [
|
||||
{"from": "human", "value": "Hi"},
|
||||
{"from": "gpt", "value": "Hello!"},
|
||||
]
|
||||
}
|
||||
pairs = extract_pairs_from_session(session, min_ratio=1.5, min_response_words=20)
|
||||
assert len(pairs) == 0
|
||||
print("PASS: test_filters_short_responses")
|
||||
|
||||
|
||||
def test_skips_tool_results():
|
||||
session = {
|
||||
"id": "test_003",
|
||||
"model": "test",
|
||||
"conversations": [
|
||||
{"from": "human", "value": '{"output": "file content", "exit_code": 0}'},
|
||||
{"from": "gpt", "value": "The file was read successfully. Now let me analyze the content and provide a detailed summary of what was found in the file system."},
|
||||
]
|
||||
}
|
||||
pairs = extract_pairs_from_session(session, min_ratio=1.5, min_response_words=10)
|
||||
assert len(pairs) == 0
|
||||
print("PASS: test_skips_tool_results")
|
||||
|
||||
|
||||
def test_deduplication():
|
||||
pairs = [
|
||||
{"terse": "What is X?", "rich": "X is Y.", "source": "s1", "model": "m"},
|
||||
{"terse": "What is X?", "rich": "X is Y.", "source": "s2", "model": "m"},
|
||||
{"terse": "What is Z?", "rich": "Z is W.", "source": "s1", "model": "m"},
|
||||
]
|
||||
unique = deduplicate_pairs(pairs)
|
||||
assert len(unique) == 2
|
||||
print("PASS: test_deduplication")
|
||||
|
||||
|
||||
def test_ratio_filter():
|
||||
session = {
|
||||
"id": "test_005",
|
||||
"model": "test",
|
||||
"conversations": [
|
||||
{"from": "human", "value": "Explain quantum computing in detail with examples and applications"},
|
||||
{"from": "gpt", "value": "OK."},
|
||||
]
|
||||
}
|
||||
pairs = extract_pairs_from_session(session, min_ratio=1.5, min_response_words=10)
|
||||
assert len(pairs) == 0 # response too short relative to prompt
|
||||
print("PASS: test_ratio_filter")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
test_basic_extraction()
|
||||
test_filters_short_responses()
|
||||
test_skips_tool_results()
|
||||
test_deduplication()
|
||||
test_ratio_filter()
|
||||
print("\nAll tests passed.")
|
||||
18
test_sessions/session_failure.jsonl
Normal file
18
test_sessions/session_failure.jsonl
Normal file
@@ -0,0 +1,18 @@
|
||||
{"role": "user", "content": "Deploy the application to production"}
|
||||
{"role": "assistant", "content": "I'll deploy the application to production.", "tool_calls": [{"function": "terminal", "arguments": {"command": "ssh deploy@prod-server 'cd /app && git pull && docker-compose up -d'"}}]}
|
||||
{"role": "tool", "content": "ssh: connect to host prod-server port 22: Connection refused"}
|
||||
{"role": "assistant", "content": "Connection refused. Let me check the server status.", "tool_calls": [{"function": "terminal", "arguments": {"command": "ping -c 3 prod-server"}}]}
|
||||
{"role": "tool", "content": "PING prod-server (192.168.1.100): 56 data bytes\nRequest timeout for icmp_seq 0\nRequest timeout for icmp_seq 1\nRequest timeout for icmp_seq 2\n--- prod-server ping statistics ---\n3 packets transmitted, 0 packets received, 100.0% packet loss"}
|
||||
{"role": "assistant", "content": "The server appears to be down. Let me check if there's an alternative deployment method."}
|
||||
{"role": "user", "content": "Try using the VPS instead"}
|
||||
{"role": "assistant", "content": "I'll try deploying to the VPS.", "tool_calls": [{"function": "terminal", "arguments": {"command": "ssh deploy@vps-server 'cd /app && git pull && docker-compose up -d'"}}]}
|
||||
{"role": "tool", "content": "Permission denied (publickey)."}
|
||||
{"role": "assistant", "content": "Permission denied. The SSH key might not be set up correctly. Let me check the SSH configuration.", "tool_calls": [{"function": "terminal", "arguments": {"command": "cat ~/.ssh/config"}}]}
|
||||
{"role": "tool", "content": "Host vps-server\n HostName 167.99.126.228\n User deploy\n IdentityFile ~/.ssh/id_rsa_vps"}
|
||||
{"role": "assistant", "content": "The SSH config looks correct. Let me check if the key exists.", "tool_calls": [{"function": "terminal", "arguments": {"command": "ls -la ~/.ssh/id_rsa_vps"}}]}
|
||||
{"role": "tool", "content": "ls: /Users/user/.ssh/id_rsa_vps: No such file or directory"}
|
||||
{"role": "assistant", "content": "The SSH key doesn't exist. This is a pitfall - we need to generate the SSH key first."}
|
||||
{"role": "user", "content": "Generate a new SSH key for the VPS"}
|
||||
{"role": "assistant", "content": "I'll generate a new SSH key.", "tool_calls": [{"function": "terminal", "arguments": {"command": "ssh-keygen -t rsa -b 4096 -f ~/.ssh/id_rsa_vps -N ''"}}]}
|
||||
{"role": "tool", "content": "Generating public/private rsa key pair.\nYour identification has been saved in /Users/user/.ssh/id_rsa_vps\nYour public key has been saved in /Users/user/.ssh/id_rsa_vps.pub\nThe key fingerprint is:\nSHA256:abc123... user@machine"}
|
||||
{"role": "assistant", "content": "SSH key generated. Now I need to add it to the VPS."}
|
||||
14
test_sessions/session_partial.jsonl
Normal file
14
test_sessions/session_partial.jsonl
Normal file
@@ -0,0 +1,14 @@
|
||||
{"role": "user", "content": "Check the Gitea API for open issues"}
|
||||
{"role": "assistant", "content": "I'll check the Gitea API for open issues.", "tool_calls": [{"function": "terminal", "arguments": {"command": "curl -H 'Authorization: token $GITEA_TOKEN' https://forge.alexanderwhitestone.com/api/v1/repos/Timmy_Foundation/compounding-intelligence/issues?state=open"}}]}
|
||||
{"role": "tool", "content": "curl: (6) Could not resolve host: forge.alexanderwhitestone.com"}
|
||||
{"role": "assistant", "content": "DNS resolution failed. Let me check the network connectivity.", "tool_calls": [{"function": "terminal", "arguments": {"command": "nslookup forge.alexanderwhitestone.com"}}]}
|
||||
{"role": "tool", "content": "Server: 8.8.8.8\nAddress: 8.8.8.8#53\n\n** server can't find forge.alexanderwhitestone.com: NXDOMAIN"}
|
||||
{"role": "assistant", "content": "The domain doesn't resolve. This might be a DNS issue. Let me try using the IP address directly.", "tool_calls": [{"function": "terminal", "arguments": {"command": "curl -H 'Authorization: token $GITEA_TOKEN' https://167.99.126.228/api/v1/repos/Timmy_Foundation/compounding-intelligence/issues?state=open"}}]}
|
||||
{"role": "tool", "content": "curl: (60) SSL certificate problem: self signed certificate"}
|
||||
{"role": "assistant", "content": "SSL certificate issue. The server is using a self-signed certificate. Let me try with -k flag to skip SSL verification.", "tool_calls": [{"function": "terminal", "arguments": {"command": "curl -k -H 'Authorization: token $GITEA_TOKEN' https://167.99.126.228/api/v1/repos/Timmy_Foundation/compounding-intelligence/issues?state=open"}}]}
|
||||
{"role": "tool", "content": "[]"}
|
||||
{"role": "assistant", "content": "No open issues found. The API returned an empty array."}
|
||||
{"role": "user", "content": "Check if there are any pull requests"}
|
||||
{"role": "assistant", "content": "Let me check for pull requests.", "tool_calls": [{"function": "terminal", "arguments": {"command": "curl -k -H 'Authorization: token $GITEA_TOKEN' https://167.99.126.228/api/v1/repos/Timmy_Foundation/compounding-intelligence/pulls?state=open"}}]}
|
||||
{"role": "tool", "content": "[{"id": 20, "title": "feat: add harvester.py + session_reader.py — session knowledge extractor (closes #8)", "state": "open", "user": {"login": "Rockachopa"}, "created_at": "2026-04-14T17:28:20Z"}]"}
|
||||
{"role": "assistant", "content": "Found 1 open pull request: PR #20 - "feat: add harvester.py + session_reader.py — session knowledge extractor (closes #8)" by Rockachopa."}
|
||||
10
test_sessions/session_patterns.jsonl
Normal file
10
test_sessions/session_patterns.jsonl
Normal file
@@ -0,0 +1,10 @@
|
||||
{"role": "user", "content": "How do I deploy a new version of the application?"}
|
||||
{"role": "assistant", "content": "Here's the deployment process:\n1. Run tests: pytest\n2. Build Docker image: docker build -t app:latest .\n3. Push to registry: docker push registry.example.com/app:latest\n4. Update production: ssh prod 'cd /app && docker-compose pull && docker-compose up -d'\n5. Verify: curl https://app.example.com/health"}
|
||||
{"role": "user", "content": "What if tests fail?"}
|
||||
{"role": "assistant", "content": "If tests fail:\n1. Check the error logs: pytest -v\n2. Fix the failing tests\n3. Re-run tests: pytest\n4. If still failing, check recent changes: git log --oneline -10\n5. Consider reverting: git revert HEAD"}
|
||||
{"role": "user", "content": "What if the Docker build fails?"}
|
||||
{"role": "assistant", "content": "If Docker build fails:\n1. Check Dockerfile syntax: docker build --no-cache -t app:latest .\n2. Check for missing dependencies: cat requirements.txt\n3. Check disk space: df -h\n4. Clean up Docker: docker system prune -f\n5. Try building with verbose output: docker build --progress=plain -t app:latest ."}
|
||||
{"role": "user", "content": "What if the push to registry fails?"}
|
||||
{"role": "assistant", "content": "If push to registry fails:\n1. Check registry credentials: docker login registry.example.com\n2. Check registry space: curl https://registry.example.com/v2/_catalog\n3. Check image size: docker images app:latest\n4. Try tagging with version: docker tag app:latest registry.example.com/app:v1.0.0\n5. Push with version tag: docker push registry.example.com/app:v1.0.0"}
|
||||
{"role": "user", "content": "What if the production update fails?"}
|
||||
{"role": "assistant", "content": "If production update fails:\n1. Check SSH connection: ssh prod 'echo connected'\n2. Check disk space on prod: ssh prod 'df -h'\n3. Check Docker status: ssh prod 'docker ps -a'\n4. Check logs: ssh prod 'docker-compose logs --tail=100'\n5. Rollback: ssh prod 'cd /app && git checkout HEAD~1 && docker-compose up -d'"}
|
||||
12
test_sessions/session_questions.jsonl
Normal file
12
test_sessions/session_questions.jsonl
Normal file
@@ -0,0 +1,12 @@
|
||||
{"role": "user", "content": "I need to implement a new feature for the application"}
|
||||
{"role": "assistant", "content": "I can help you implement a new feature. What feature would you like to add?"}
|
||||
{"role": "user", "content": "I want to add user authentication"}
|
||||
{"role": "assistant", "content": "User authentication is a good feature. I have a few questions:\n1. What authentication method do you prefer? (JWT, OAuth, Session-based)\n2. Do you need social login? (Google, GitHub, etc.)\n3. What user data do you need to store?\n4. Do you need role-based access control?\n5. What's your database? (PostgreSQL, MySQL, SQLite)"}
|
||||
{"role": "user", "content": "I prefer JWT, no social login, just email and password, no roles, PostgreSQL"}
|
||||
{"role": "assistant", "content": "Great choices. Here's the implementation plan:\n1. Create user model with email and password hash\n2. Create JWT token generation and validation\n3. Create login endpoint: POST /api/auth/login\n4. Create register endpoint: POST /api/auth/register\n5. Create middleware for protected routes\n6. Add password hashing with bcrypt\n7. Add rate limiting for login attempts\n8. Add password reset functionality\n9. Add email verification\n10. Test all endpoints"}
|
||||
{"role": "user", "content": "What about password reset?"}
|
||||
{"role": "assistant", "content": "For password reset:\n1. Create reset token table\n2. Create forgot password endpoint: POST /api/auth/forgot-password\n3. Send reset email with token\n4. Create reset password endpoint: POST /api/auth/reset-password\n5. Validate reset token and expiration\n6. Update password and delete token\n7. Send confirmation email"}
|
||||
{"role": "user", "content": "What about email verification?"}
|
||||
{"role": "assistant", "content": "For email verification:\n1. Add email_verified field to user model\n2. Create verification token table\n3. Send verification email on registration\n4. Create verify email endpoint: GET /api/auth/verify-email?token=...\n5. Validate token and update email_verified\n6. Add middleware to check email_verified for certain routes\n7. Add resend verification email endpoint"}
|
||||
{"role": "user", "content": "What about rate limiting?"}
|
||||
{"role": "assistant", "content": "For rate limiting:\n1. Use Redis for rate limit storage\n2. Create rate limit middleware\n3. Set limits: 5 login attempts per minute, 3 password resets per hour\n4. Return 429 Too Many Requests when limit exceeded\n5. Add X-RateLimit headers to responses\n6. Log rate limit violations\n7. Add whitelist for trusted IPs"}
|
||||
13
test_sessions/session_success.jsonl
Normal file
13
test_sessions/session_success.jsonl
Normal file
@@ -0,0 +1,13 @@
|
||||
{"role": "user", "content": "Clone the repo at forge.alexanderwhitestone.com/Timmy_Foundation/compounding-intelligence"}
|
||||
{"role": "assistant", "content": "I'll clone the repository for you.", "tool_calls": [{"function": "terminal", "arguments": {"command": "git clone https://forge.alexanderwhitestone.com/Timmy_Foundation/compounding-intelligence.git"}}]}
|
||||
{"role": "tool", "content": "Cloning into 'compounding-intelligence'...\nremote: Enumerating objects: 15, done.\nremote: Counting objects: 100% (15/15), done.\nremote: Compressing objects: 100% (12/12), done.\nremote: Total 15 (delta 2), reused 0 (delta 0), pack-reused 0\nReceiving objects: 100% (15/15), done.\nResolving deltas: 100% (2/2), done."}
|
||||
{"role": "assistant", "content": "Repository cloned successfully. Let me check the structure.", "tool_calls": [{"function": "terminal", "arguments": {"command": "ls -la compounding-intelligence/"}}]}
|
||||
{"role": "tool", "content": "total 8\ndrwxr-xr-x 5 user staff 160 Apr 14 17:21 .\ndrwxr-xr-x 12 user staff 384 Apr 14 17:21 ..\ndrwxr-xr-x 13 user staff 416 Apr 14 17:21 .git\n-rw-r--r-- 1 user staff 1234 Apr 14 17:21 README.md\ndrwxr-xr-x 3 user staff 96 Apr 14 17:21 knowledge\n-rw-r--r-- 1 user staff 456 Apr 14 17:21 metrics\ndrwxr-xr-x 4 user staff 128 Apr 14 17:21 scripts\ndrwxr-xr-x 3 user staff 96 Apr 14 17:21 templates"}
|
||||
{"role": "user", "content": "What files are in the templates directory?"}
|
||||
{"role": "assistant", "content": "Let me check the templates directory.", "tool_calls": [{"function": "terminal", "arguments": {"command": "ls -la compounding-intelligence/templates/"}}]}
|
||||
{"role": "tool", "content": "total 0\ndrwxr-xr-x 3 user staff 96 Apr 14 17:21 .\ndrwxr-xr-x 5 user staff 160 Apr 14 17:21 ..\n-rw-r--r-- 1 user staff 0 Apr 14 17:21 .gitkeep"}
|
||||
{"role": "assistant", "content": "The templates directory currently only contains a .gitkeep file. No templates have been added yet."}
|
||||
{"role": "user", "content": "Create a harvest-prompt.md template in the templates directory."}
|
||||
{"role": "assistant", "content": "I'll create the harvest-prompt.md template for you.", "tool_calls": [{"function": "terminal", "arguments": {"command": "cat > compounding-intelligence/templates/harvest-prompt.md << 'EOF'\n# Knowledge Extraction Prompt\n\nExtract knowledge from session transcripts.\nEOF"}}]}
|
||||
{"role": "tool", "content": ""}
|
||||
{"role": "assistant", "content": "Template created successfully. The harvest-prompt.md file is now in the templates directory."}
|
||||
Reference in New Issue
Block a user