File size: 7,715 Bytes
4545172 | 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 | """Persist active Gradio redaction task state for multi-turn post-run eval."""
from __future__ import annotations
import sys
import threading
from dataclasses import dataclass, field
from pathlib import Path
from typing import Any
from session_workspace import (
read_active_redaction_task_file,
session_workspace_dir,
write_active_redaction_task_file,
)
_LOCK = threading.Lock()
_REPO_ROOT = Path(__file__).resolve().parents[2]
_EVAL_DIR = Path(__file__).resolve().parents[1] / "eval"
def _ensure_eval_imports() -> None:
text = str(_EVAL_DIR)
if text not in sys.path:
sys.path.insert(0, text)
@dataclass
class ActiveRedactionTask:
document_name: str
task_instructions: str
follow_up_steer_count: int = 0
cumulative_tool_calls: list[dict[str, Any]] = field(default_factory=list)
eval_gold_path: str | None = None
eval_gold_match_level: str = "none"
eval_gold_match_reason: str = ""
encourage_vlm_faces: bool = False
encourage_vlm_signatures: bool = False
def _task_from_raw(raw: dict[str, Any]) -> ActiveRedactionTask | None:
doc = str(raw.get("document_name") or "").strip()
if not doc:
return None
instructions = str(raw.get("task_instructions") or "").strip()
count = raw.get("follow_up_steer_count", 0)
try:
follow_up_steer_count = max(0, int(count))
except (TypeError, ValueError):
follow_up_steer_count = 0
calls = raw.get("cumulative_tool_calls")
if not isinstance(calls, list):
calls = []
cumulative_tool_calls = [
c for c in calls if isinstance(c, dict) and str(c.get("tool") or "").strip()
]
eval_gold_path = str(raw.get("eval_gold_path") or "").strip() or None
return ActiveRedactionTask(
document_name=doc,
task_instructions=instructions,
follow_up_steer_count=follow_up_steer_count,
cumulative_tool_calls=cumulative_tool_calls,
eval_gold_path=eval_gold_path,
eval_gold_match_level=str(raw.get("eval_gold_match_level") or "none"),
eval_gold_match_reason=str(raw.get("eval_gold_match_reason") or ""),
encourage_vlm_faces=bool(raw.get("encourage_vlm_faces")),
encourage_vlm_signatures=bool(raw.get("encourage_vlm_signatures")),
)
def _read_task(session_hash: str) -> ActiveRedactionTask | None:
raw = read_active_redaction_task_file(session_hash)
if raw is None:
return None
return _task_from_raw(raw)
def _write_task(session_hash: str, task: ActiveRedactionTask) -> bool:
payload = {
"document_name": task.document_name,
"task_instructions": task.task_instructions,
"follow_up_steer_count": task.follow_up_steer_count,
"cumulative_tool_calls": task.cumulative_tool_calls,
"eval_gold_path": task.eval_gold_path,
"eval_gold_match_level": task.eval_gold_match_level,
"eval_gold_match_reason": task.eval_gold_match_reason,
"encourage_vlm_faces": bool(task.encourage_vlm_faces),
"encourage_vlm_signatures": bool(task.encourage_vlm_signatures),
}
return write_active_redaction_task_file(session_hash, payload)
def _resolve_pdf_path(
session_hash: str, document_name: str, pdf_path: Path | None
) -> Path | None:
if pdf_path is not None and pdf_path.is_file():
return pdf_path
candidate = session_workspace_dir(session_hash) / document_name
return candidate if candidate.is_file() else None
def begin_redaction_task(
session_hash: str,
document_name: str,
task_instructions: str,
*,
pdf_path: Path | None = None,
encourage_vlm_faces: bool = False,
encourage_vlm_signatures: bool = False,
) -> str:
"""
Start a new redaction task in *session_hash* (resets steer count and tool trace).
Returns a short status line for the activity log (gold match result when auto-gold on).
"""
doc = (document_name or "").strip()
if not doc or not (session_hash or "").strip():
return ""
task = ActiveRedactionTask(
document_name=doc,
task_instructions=(task_instructions or "").strip(),
follow_up_steer_count=0,
cumulative_tool_calls=[],
encourage_vlm_faces=bool(encourage_vlm_faces),
encourage_vlm_signatures=bool(encourage_vlm_signatures),
)
log_line = ""
try:
_ensure_eval_imports()
from agent_eval_env import agent_eval_auto_gold_enabled, resolve_gold_root
from gold_match import resolve_gold_case_for_task
if agent_eval_auto_gold_enabled():
upload = _resolve_pdf_path(session_hash, doc, pdf_path)
if upload is not None:
result = resolve_gold_case_for_task(
pdf_path=upload,
document_name=doc,
task_instructions=task.task_instructions,
gold_root=resolve_gold_root(_REPO_ROOT),
)
task.eval_gold_match_level = result.match_level
task.eval_gold_match_reason = result.reason
if result.gold_dir is not None:
task.eval_gold_path = str(result.gold_dir.resolve())
log_line = (
f"**Eval gold case:** `{result.case_id or result.gold_dir.name}` "
f"({result.match_level})"
)
else:
log_line = (
f"**Eval skipped:** {result.reason or 'no matching gold case'}"
)
else:
task.eval_gold_match_reason = (
"upload PDF not found in session workspace"
)
log_line = f"**Eval skipped:** {task.eval_gold_match_reason}"
except Exception as exc:
task.eval_gold_match_reason = f"gold match error: {exc}"
log_line = f"**Eval skipped:** {task.eval_gold_match_reason}"
with _LOCK:
_write_task(session_hash, task)
return log_line
def note_follow_up_or_steer_message(session_hash: str) -> bool:
"""
Record one user follow-up or in-run steer message for the active task.
Returns True when an active task was updated.
"""
if not (session_hash or "").strip():
return False
with _LOCK:
task = _read_task(session_hash)
if task is None:
return False
task.follow_up_steer_count += 1
return _write_task(session_hash, task)
def _tool_calls_from_events(events: list[Any]) -> list[dict[str, Any]]:
calls: list[dict[str, Any]] = []
for event in events:
kind = str(getattr(event, "kind", "") or "")
if kind != "tool_start":
continue
name = str(getattr(event, "tool_name", None) or "tool")
args = getattr(event, "tool_args", None)
if not isinstance(args, dict):
args = {}
calls.append({"tool": name, "args": args})
return calls
def append_turn_tool_calls(session_hash: str, events: list[Any]) -> None:
"""Merge tool-start events from the latest agent turn into the task trace."""
if not (session_hash or "").strip() or not events:
return
new_calls = _tool_calls_from_events(events)
if not new_calls:
return
with _LOCK:
task = _read_task(session_hash)
if task is None:
return
task.cumulative_tool_calls.extend(new_calls)
_write_task(session_hash, task)
def get_active_task_for_eval(session_hash: str) -> ActiveRedactionTask | None:
"""Return the current task snapshot for post-run eval (or None)."""
if not (session_hash or "").strip():
return None
return _read_task(session_hash)
|