190 lines
6.2 KiB
Python
190 lines
6.2 KiB
Python
"""Append-only JSONL audit log for agent sessions.
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Every event is written as one JSON object per line, with an auto-added
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ISO timestamp and session id. The log is flushed after every record so
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that a crash still leaves a complete trail. The file alone is enough
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to reconstruct what the agent did, in order.
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tool results are truncated to ``MAX_RESULT_BYTES`` in the log to
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prevent unbounded growth; a SHA-256 and full length are stored alongside
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so the truncated entry is self-describing and tamper-evident.
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dedicated events for every decision step,
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``log_permission_decision``, ``log_llm_request``, ``log_llm_response``,
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``log_session_abort``, give full forensic replay without guessing.
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"""
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import hashlib
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import json
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import uuid
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from datetime import datetime, timezone
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from pathlib import Path
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from typing import Any
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# Tool results larger than this are stored truncated in the audit log.
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MAX_RESULT_BYTES = 8 * 1024
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def _truncate_for_log(result: str) -> dict:
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"""Return a dict describing *result*, truncating if large.
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The dict always has ``size`` (bytes) and ``sha256``. If the result
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is short enough it is included verbatim under ``result``; otherwise
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only the first ``MAX_RESULT_BYTES`` are kept under ``result_truncated``.
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"""
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raw = result if isinstance(result, str) else str(result)
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encoded = raw.encode("utf-8", errors="replace")
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digest = hashlib.sha256(encoded).hexdigest()
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size = len(encoded)
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if size <= MAX_RESULT_BYTES:
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return {"result": raw, "size": size, "sha256": digest}
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truncated = encoded[:MAX_RESULT_BYTES].decode("utf-8", errors="replace")
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return {
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"result_truncated": truncated,
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"truncated_from_size": size,
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"sha256": digest,
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}
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class AuditLog:
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"""Append-only JSONL audit log of agent activity."""
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def __init__(self, log_dir: Path, session_id: str | None = None):
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self.log_dir = Path(log_dir)
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self.log_dir.mkdir(parents=True, exist_ok=True)
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self.session_id = session_id or uuid.uuid4().hex[:12]
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ts = datetime.now(timezone.utc).strftime("%Y%m%dT%H%M%SZ")
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self.path = self.log_dir / f"audit-{self.session_id}-{ts}.jsonl"
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self._fh = self.path.open("a", encoding="utf-8")
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self.log("session_start", log_file=str(self.path))
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def log(self, event: str, **fields: Any) -> None:
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record = {
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"ts": datetime.now(timezone.utc).isoformat(timespec="milliseconds"),
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"session": self.session_id,
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"event": event,
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}
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record.update(fields)
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self._fh.write(json.dumps(
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record, ensure_ascii=False, default=str) + "\n")
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self._fh.flush()
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# -- convenience wrappers ------------------------------------------
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def log_config(self, **fields: Any) -> None:
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"""Record the session configuration (mode, sandbox root, etc.)."""
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self.log("config", **fields)
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def log_user_message(self, content: str) -> None:
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self.log("user_message", content=content)
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def log_assistant_message(self, content: str | None, tool_calls) -> None:
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calls = []
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if tool_calls:
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for tc in tool_calls:
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try:
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args = json.loads(tc.function.arguments)
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except Exception:
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args = tc.function.arguments
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calls.append(
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{"id": tc.id, "name": tc.function.name, "args": args})
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self.log("assistant_message", content=content, tool_calls=calls)
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def log_tool_result(
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self,
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tool_call_id: str,
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name: str,
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args: dict,
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permission_allowed: bool,
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container_error: bool,
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container_reason: str | None,
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result: str,
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intent_drift: bool = False,
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intent_reason: str | None = None,
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permission_reason: str | None = None,
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) -> None:
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self.log(
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"tool_result",
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tool_call_id=tool_call_id,
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tool=name,
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args=args,
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permission_allowed=permission_allowed,
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permission_reason=permission_reason,
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container_error=container_error,
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container_reason=container_reason,
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intent_drift=intent_drift,
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intent_reason=intent_reason,
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**_truncate_for_log(result),
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)
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def log_permission_decision(
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self,
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tool: str,
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args: dict,
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mode: str,
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allowed: bool,
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reason: str | None = None,
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) -> None:
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"""Record a standalone permission decision.
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This is emitted *before* the tool runs (or is refused), so the
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audit trail shows the decision and its reason even if the
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subsequent tool execution crashes.
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"""
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self.log(
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"permission_decision",
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tool=tool,
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args=args,
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mode=mode,
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allowed=allowed,
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reason=reason,
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)
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def log_llm_request(
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self,
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model: str,
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message_count: int,
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token_estimate: int,
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has_tools: bool,
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) -> None:
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"""Record that an LLM request is about to be sent."""
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self.log(
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"llm_request",
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model=model,
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message_count=message_count,
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token_estimate=token_estimate,
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has_tools=has_tools,
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)
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def log_llm_response(
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self,
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model: str,
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finish_reason: str | None,
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usage: dict | None = None,
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message_hash: str | None = None,
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tool_call_count: int = 0,
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) -> None:
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"""Record the LLM response metadata.
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``message_hash`` is a SHA-256 of the assistant message content
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so the full conversation can be verified for forensic replay
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without storing every token in the log.
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"""
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self.log(
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"llm_response",
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model=model,
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finish_reason=finish_reason,
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usage=usage,
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message_hash=message_hash,
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tool_call_count=tool_call_count,
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)
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def log_session_abort(self, reason: str) -> None:
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"""Record that the session was aborted."""
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self.log("session_abort", reason=reason)
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def close(self) -> None:
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self.log("session_end")
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self._fh.close()
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