File size: 1,636 Bytes
1521ce5 | 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 | from __future__ import annotations
from datetime import datetime, timedelta
import random
def format_session_as_context(sessions: list[dict], include_timestamps: bool = True) -> str:
parts = []
for sess in sessions:
header = f"[Session: {sess['session_id']}"
if include_timestamps and "timestamp" in sess:
header += f" | {sess['timestamp']}"
header += "]"
parts.append(header)
for turn in sess.get("turns", []):
parts.append(f" {turn['role'].capitalize()}: {turn['content']}")
parts.append("")
return "\n".join(parts)
def format_evidence_sessions_text(sessions: list[dict]) -> str:
parts = []
for i, sess in enumerate(sessions, 1):
parts.append(f"--- Evidence Session {i} (ID: {sess['session_id']}) ---")
for turn in sess.get("turns", []):
parts.append(f"{turn['role'].capitalize()}: {turn['content']}")
parts.append("")
return "\n".join(parts)
def generate_timestamps(n: int, start_date: str = "2023/01/01", span_days: int = 180) -> list[str]:
base = datetime.strptime(start_date, "%Y/%m/%d")
dates = sorted([
base + timedelta(days=random.randint(0, span_days), hours=random.randint(8, 22), minutes=random.randint(0, 59))
for _ in range(n)
])
return [d.strftime("%Y/%m/%d (%a) %H:%M") for d in dates]
def build_memory_bank(sessions: list[dict]) -> list[dict]:
return [
{
"session_id": sess["session_id"],
"timestamp": sess.get("timestamp", ""),
"turns": sess["turns"],
}
for sess in sessions
]
|