LZH-YS1998
1804 lines
73 KiB
Python
1804 lines
73 KiB
Python
"""Memory hierarchy manager for global/project/session/employee-project scopes."""
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from __future__ import annotations
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import json
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import re
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from datetime import datetime
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from pathlib import Path
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from typing import Any
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from loguru import logger
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from opc.core.models import (
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AgentMemorySnapshotRecord,
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Phase,
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SessionLinkRecord,
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SessionMemorySnapshotRecord,
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SessionMessageRecord,
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SessionPartRecord,
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SessionRecord,
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TaskStatus,
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)
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from opc.layer5_memory.employee_evolution import EmployeeEvolutionManager
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from opc.layer5_memory.markdown_memory import MarkdownMemoryStore
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from opc.layer2_organization.work_item_identity import projection_id_for_task, work_item_identity_payload_for_task
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from opc.layer4_tools.output_budget import clip_text
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class MemoryManager:
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"""Manages four memory scopes.
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- Global memory: durable cross-project memory in `memory/global.md`
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- Project memory: durable project memory in `memory/projects/<project_id>.md`
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- Session memory: persisted transcript + session memory snapshots
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- Employee-project memory: process/final employee memory in the store
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"""
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def __init__(
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self,
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opc_home: Path,
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project_id: str | None = None,
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store: Any | None = None,
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) -> None:
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self.opc_home = opc_home
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self.project_id = project_id
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self.store = store
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self.markdown_store = MarkdownMemoryStore(opc_home)
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self.employee_evolution = EmployeeEvolutionManager(opc_home)
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self.history_compactor: Any | None = None
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self.global_memory_dir = opc_home / "memory"
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self.global_memory_dir.mkdir(parents=True, exist_ok=True)
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self.project_memory_dir: Path | None = None
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if project_id:
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self.project_memory_dir = self.global_memory_dir / "projects"
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self.project_memory_dir.mkdir(parents=True, exist_ok=True)
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def set_project(self, project_id: str | None) -> None:
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self.project_id = project_id
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self.project_memory_dir = None
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if project_id:
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self.project_memory_dir = self.global_memory_dir / "projects"
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self.project_memory_dir.mkdir(parents=True, exist_ok=True)
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def set_history_compactor(self, compactor: Any | None) -> None:
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self.history_compactor = compactor
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def _resolve_project_id(self, project_id: str | None = None) -> str:
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return str(project_id or self.project_id or "default")
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def _project_root(self, project_id: str | None) -> Path:
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return self.opc_home / "projects" / self._resolve_project_id(project_id)
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def _project_memory_path_for_id(self, project_id: str | None) -> Path:
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return self.markdown_store.memory_path(self._resolve_project_id(project_id))
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def _project_history_path_for_id(self, project_id: str | None) -> Path:
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return self._project_root(project_id) / "HISTORY.md"
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# --- Durable Markdown memory ---
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def _memory_path(self, project: bool = False) -> Path:
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project_id = self._resolve_project_id() if project and self.project_id else None
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return self.markdown_store.memory_path(project_id)
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def load_memory(self, project: bool = False) -> str:
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project_id = self._resolve_project_id() if project and self.project_id else None
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return self.markdown_store.load_visible_text(project_id)
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def save_memory(self, content: str, project: bool = False) -> None:
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project_id = self._resolve_project_id() if project and self.project_id else None
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self.markdown_store.save_visible_text(content, project_id)
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logger.debug(f"Memory saved: {self.markdown_store.memory_path(project_id)}")
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def append_memory(self, entry: str, project: bool = False) -> None:
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project_id = self._resolve_project_id() if project and self.project_id else None
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self.markdown_store.append_visible_entry(entry, project_id)
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def delete_project(self, project_id: str) -> None:
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self.markdown_store.delete_project(project_id)
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# --- Legacy HISTORY compatibility ---
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def _history_path(self, project: bool = False) -> Path:
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if project and self.project_memory_dir:
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return self.project_memory_dir / "HISTORY.md"
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return self.global_memory_dir / "HISTORY.md"
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def load_history(self, project: bool = False) -> str:
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_ = project
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return ""
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def append_history(self, task_summary: dict[str, Any], project: bool = False) -> None:
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_ = (task_summary, project)
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def append_autonomy_event(self, event: dict[str, Any], project: bool = False) -> None:
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_ = (event, project)
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def record_task_completion(self, task: Any, result_content: str, project: bool = False) -> None:
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_ = (task, result_content, project)
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async def record_task_completion_async(
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self,
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task: Any,
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result_content: str,
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project: bool = False,
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*,
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record_evolution: bool = True,
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record_reflections: bool = True,
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) -> None:
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self.record_task_completion(task=task, result_content=result_content, project=project)
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is_company_mode = getattr(task, "metadata", {}).get("execution_mode") == "company_mode"
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legacy_company_evolution_enabled = bool(getattr(task, "metadata", {}).get("enable_legacy_employee_evolution", False))
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if (
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record_evolution
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and is_company_mode
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and legacy_company_evolution_enabled
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and getattr(task, "metadata", {}).get("employee_assignment")
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):
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self.employee_evolution.record_work_item_completion(task=task, result_content=result_content)
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if not self.store:
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return
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project_id = getattr(task, "project_id", None) or (self.project_id or "default")
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role_id = getattr(task, "assigned_to", "") or getattr(task, "metadata", {}).get("work_item_role_id", "")
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projection_id = projection_id_for_task(task)
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decisions = list(getattr(task, "metadata", {}).get("decisions", []))
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risks = list(getattr(task, "metadata", {}).get("risks", []))
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artifacts = list(getattr(task, "metadata", {}).get("artifacts", []))
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open_questions = list(getattr(task, "metadata", {}).get("open_questions", []))
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if role_id:
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from opc.core.models import RoleMemoryRecord
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await self.store.record_role_memory(
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RoleMemoryRecord(
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project_id=project_id,
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role_id=role_id,
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summary=f"{getattr(task, 'title', 'Task')}: {(result_content or '').strip()}",
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details={
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"task_id": getattr(task, "id", None),
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"projection_id": projection_id,
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},
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)
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)
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if decisions or risks or open_questions:
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from opc.core.models import WorkItemDecisionRecord
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await self.store.record_work_item_decision(
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WorkItemDecisionRecord(
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project_id=project_id,
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task_id=getattr(task, "id", None),
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role_id=role_id,
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projection_id=projection_id,
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category="work_item_completion",
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summary=(getattr(task, "metadata", {}).get("work_item_summary_for_downstream") or result_content or getattr(task, "title", "Task")),
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details={
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"decisions": decisions,
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"risks": risks,
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"open_questions": open_questions,
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},
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)
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)
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if artifacts:
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from opc.core.models import ArtifactRecord
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for item in artifacts:
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text = str(item)
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location = text.split(": ", 1)[1] if ": " in text else text
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artifact_type = text.split(":", 1)[0] if ":" in text else "generic"
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await self.store.record_artifact(
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ArtifactRecord(
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project_id=project_id,
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task_id=getattr(task, "id", None),
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projection_id=projection_id,
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role_id=role_id,
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name=text,
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artifact_type=artifact_type,
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location=location,
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details={"source": "task_metadata"},
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)
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)
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if record_reflections and is_company_mode and legacy_company_evolution_enabled:
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await self._record_project_reflections_if_ready(task)
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async def record_company_feedback_outcomes(
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self,
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*,
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delivery_task: Any,
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work_item_tasks: list[Any],
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feedback: dict[str, Any],
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evaluation: dict[str, Any],
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) -> None:
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employee_outcomes = {
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str(item.get("employee_id", "")).strip(): dict(item)
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for item in list(evaluation.get("employees", []))
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if str(item.get("employee_id", "")).strip()
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}
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overall_outcome = str(evaluation.get("overall_outcome", "") or "partial_success").strip() or "partial_success"
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feedback_summary = str(evaluation.get("summary", "") or feedback.get("raw_feedback", "")).strip()
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for task in work_item_tasks:
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result_content = str(getattr(task, "result", {}).get("content", "") or "").strip()
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await self.record_task_completion_async(
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task=task,
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result_content=result_content,
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project=bool(getattr(task, "project_id", None) and getattr(task, "project_id", None) != "default"),
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record_evolution=False,
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record_reflections=False,
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)
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assignment = dict(getattr(task, "metadata", {}).get("employee_assignment", {}) or {})
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employee_id = str(assignment.get("employee_id", "")).strip()
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if not employee_id:
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continue
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employee_feedback = employee_outcomes.get(employee_id, {})
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self.employee_evolution.record_work_item_completion(
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task=task,
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result_content=result_content,
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outcome=str(employee_feedback.get("outcome", overall_outcome) or overall_outcome),
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feedback_summary=feedback_summary,
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strengths=list(employee_feedback.get("strengths", [])),
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weaknesses=list(employee_feedback.get("weaknesses", [])),
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rationale=str(employee_feedback.get("reason", "")).strip(),
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)
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partial = overall_outcome != "success"
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await self._record_project_reflections_and_finalize(
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delivery_task,
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work_item_tasks,
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partial=partial,
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feedback=feedback,
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evaluation=evaluation,
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)
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async def _record_project_reflections_if_ready(self, task: Any) -> None:
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execution_task_ids = [
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str(item).strip()
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for item in list(getattr(task, "metadata", {}).get("execution_task_ids", []))
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if str(item).strip()
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]
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if not execution_task_ids or not self.store:
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return
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project_id = getattr(task, "project_id", None) or (self.project_id or "default")
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tasks = await self.store.get_tasks(project_id=project_id)
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task_by_id = {item.id: item for item in tasks}
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task_by_id[getattr(task, "id", "")] = task
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work_item_tasks = [task_by_id[item_id] for item_id in execution_task_ids if item_id in task_by_id]
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if len(work_item_tasks) != len(execution_task_ids):
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return
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terminal = {TaskStatus.DONE, TaskStatus.FAILED, TaskStatus.CANCELLED}
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if any(item.status not in terminal for item in work_item_tasks):
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return
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has_failures = any(item.status != TaskStatus.DONE for item in work_item_tasks)
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await self._record_project_reflections_and_finalize(
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task,
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work_item_tasks,
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partial=has_failures,
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)
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async def _record_project_reflections_and_finalize(
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self,
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delivery_task: Any,
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work_item_tasks: list[Any],
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*,
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partial: bool = False,
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feedback: dict[str, Any] | None = None,
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evaluation: dict[str, Any] | None = None,
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) -> None:
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reflection_results = self.employee_evolution.record_project_reflections(
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delivery_task,
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work_item_tasks,
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partial=partial,
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feedback=feedback,
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evaluation=evaluation,
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)
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await self._finalize_employee_project_memories(
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delivery_task=delivery_task,
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work_item_tasks=work_item_tasks,
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reflection_results=reflection_results,
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feedback=feedback,
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evaluation=evaluation,
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)
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async def _finalize_employee_project_memories(
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self,
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*,
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delivery_task: Any,
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work_item_tasks: list[Any],
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reflection_results: list[dict[str, Any]],
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feedback: dict[str, Any] | None = None,
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evaluation: dict[str, Any] | None = None,
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) -> None:
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if not self.store:
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return
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project_id = getattr(delivery_task, "project_id", None) or self._resolve_project_id()
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reflections_by_employee = {
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str(item.get("employee_id", "")).strip(): dict(item.get("reflection", {}) or {})
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for item in reflection_results
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if str(item.get("employee_id", "")).strip()
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}
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groups: dict[str, dict[str, Any]] = {}
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for task in work_item_tasks:
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assignment = dict(getattr(task, "metadata", {}).get("employee_assignment", {}) or {})
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employee_id = str(assignment.get("employee_id", "")).strip()
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session_id = str(getattr(task, "session_id", "") or "").strip()
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if not employee_id:
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continue
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key = employee_id
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entry = groups.setdefault(
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key,
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{
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"employee_id": employee_id,
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"role_id": str(assignment.get("role_id") or getattr(task, "assigned_to", "") or "").strip(),
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"session_ids": [],
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"tasks": [],
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},
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)
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if not entry["role_id"]:
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entry["role_id"] = str(assignment.get("role_id") or getattr(task, "assigned_to", "") or "").strip()
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if session_id and session_id not in entry["session_ids"]:
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entry["session_ids"].append(session_id)
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entry["tasks"].append(task)
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for group in groups.values():
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employee_id = group["employee_id"]
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role_id = group["role_id"]
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reflection = reflections_by_employee.get(employee_id, {})
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existing_final = await self.store.get_agent_memory_snapshot(
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project_id=project_id,
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employee_id=employee_id,
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memory_kind="final",
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memory_scope="project",
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)
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if existing_final:
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for session_id in group["session_ids"]:
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await self.store.delete_agent_memory_snapshots(
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project_id=project_id,
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session_id=session_id,
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employee_id=employee_id,
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memory_kind="process",
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memory_scope="session",
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)
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continue
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process_memory, process_snapshot = await self._build_project_process_memory(
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project_id=project_id,
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employee_id=employee_id,
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session_ids=list(group["session_ids"]),
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)
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if self.history_compactor:
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final_result = await self.history_compactor.finalize_agent_memory(
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project_id=project_id,
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session_id="",
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employee_id=employee_id,
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role_id=role_id,
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process_memory=process_memory,
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reflection_payload={
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**reflection,
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"feedback": feedback or {},
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"evaluation": evaluation or {},
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},
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)
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else:
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final_result = self._fallback_final_agent_memory(
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process_memory=process_memory,
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reflection_payload=reflection,
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)
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memory_text = str(final_result.get("memory_text", "")).strip()
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if not memory_text:
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continue
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summary_text = str(final_result.get("summary_text", "")).strip() or memory_text
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metadata = dict(final_result.get("metadata", {}) or {})
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metadata.update({
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"reflection": reflection,
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"task_ids": [str(getattr(task, "id", "")) for task in group["tasks"]],
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"session_ids": list(group["session_ids"]),
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})
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await self.store.save_agent_memory_snapshot(
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AgentMemorySnapshotRecord(
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project_id=project_id,
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session_id="",
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employee_id=employee_id,
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role_id=role_id,
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memory_scope="project",
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memory_kind="final",
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summary_message_id=process_snapshot.summary_message_id if process_snapshot else "",
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source_boundary_message_id=process_snapshot.source_boundary_message_id if process_snapshot else "",
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summary_text=summary_text,
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memory_text=memory_text,
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metadata=metadata,
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)
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)
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for session_id in group["session_ids"]:
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await self.store.delete_agent_memory_snapshots(
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project_id=project_id,
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session_id=session_id,
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employee_id=employee_id,
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memory_kind="process",
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memory_scope="session",
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)
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async def _build_project_process_memory(
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self,
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*,
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project_id: str,
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employee_id: str,
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session_ids: list[str],
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) -> tuple[str, AgentMemorySnapshotRecord | None]:
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sections: list[str] = []
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latest_snapshot: AgentMemorySnapshotRecord | None = None
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for session_id in session_ids:
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snapshot = await self.store.get_agent_memory_snapshot(
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project_id=project_id,
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session_id=session_id,
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employee_id=employee_id,
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memory_kind="process",
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memory_scope="session",
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)
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if snapshot and snapshot.memory_text.strip():
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if latest_snapshot is None:
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latest_snapshot = snapshot
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sections.append(f"## Session {session_id}\n{snapshot.memory_text.strip()}")
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continue
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history_tail = await self.build_employee_history_tail_messages(
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project_id=project_id,
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session_id=session_id,
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employee_id=employee_id,
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)
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draft = self._history_messages_to_process_memory(history_tail)
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if draft:
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sections.append(f"## Session {session_id}\n{draft}")
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return "\n\n".join(section for section in sections if section).strip(), latest_snapshot
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|
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def _history_messages_to_process_memory(self, messages: list[dict[str, Any]]) -> str:
|
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if not messages:
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return ""
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lines = ["## Process Memory Draft"]
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for item in messages:
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role = str(item.get("role", "")).strip()
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content = str(item.get("content", "")).strip()
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if not content:
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continue
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prefix = f"[{role}] " if role else ""
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lines.append(f"- {prefix}{content}")
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return "\n".join(lines).strip()
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|
|
def _fallback_final_agent_memory(
|
|
self,
|
|
*,
|
|
process_memory: str,
|
|
reflection_payload: dict[str, Any],
|
|
) -> dict[str, Any]:
|
|
what_worked = [str(item).strip() for item in list(reflection_payload.get("what_worked", [])) if str(item).strip()]
|
|
watchouts = [str(item).strip() for item in list(reflection_payload.get("mistakes_to_avoid", [])) if str(item).strip()]
|
|
preferred_tools = [str(item).strip() for item in list(reflection_payload.get("tool_preferences", [])) if str(item).strip()]
|
|
reviewer_preferences = [str(item).strip() for item in list(reflection_payload.get("reviewer_preferences", [])) if str(item).strip()]
|
|
checklist = [str(item).strip() for item in list(reflection_payload.get("reusable_checklist", [])) if str(item).strip()]
|
|
parts = [
|
|
"## Effective Patterns",
|
|
*([f"- {item}" for item in what_worked] or ["- (none)"]),
|
|
"",
|
|
"## Watchouts",
|
|
*([f"- {item}" for item in watchouts] or ["- (none)"]),
|
|
"",
|
|
"## Preferred Tools",
|
|
*([f"- {item}" for item in preferred_tools] or ["- (none)"]),
|
|
"",
|
|
"## Reviewer Preferences",
|
|
*([f"- {item}" for item in reviewer_preferences] or ["- (none)"]),
|
|
"",
|
|
"## Reusable Checklist",
|
|
*([f"- {item}" for item in checklist] or ["- (none)"]),
|
|
]
|
|
summary = str(reflection_payload.get("project_summary", "")).strip() or process_memory.strip()
|
|
return {
|
|
"summary_text": summary,
|
|
"memory_text": "\n".join(parts).strip(),
|
|
"metadata": {
|
|
"effective_patterns": what_worked,
|
|
"watchouts": watchouts,
|
|
"preferred_tools": preferred_tools,
|
|
"reviewer_preferences": reviewer_preferences,
|
|
"reusable_checklist": checklist,
|
|
},
|
|
}
|
|
|
|
# --- Session memory and context building ---
|
|
|
|
def _build_message_metadata(
|
|
self,
|
|
session: SessionRecord | None,
|
|
*,
|
|
metadata: dict[str, Any] | None = None,
|
|
agent_id: str | None = None,
|
|
task_id: str | None = None,
|
|
) -> dict[str, Any]:
|
|
merged: dict[str, Any] = {}
|
|
if session:
|
|
merged["project_id"] = session.project_id
|
|
merged["session_id"] = session.session_id
|
|
if session.parent_session_id:
|
|
merged["parent_session_id"] = session.parent_session_id
|
|
session_metadata = dict(session.metadata or {})
|
|
for key in (
|
|
"employee_id",
|
|
"role_id",
|
|
"work_item_projection_id",
|
|
"work_item_turn_type",
|
|
"work_item_projection_id",
|
|
"origin_session_id",
|
|
"interface",
|
|
):
|
|
value = session_metadata.get(key)
|
|
if value not in (None, "", [], {}):
|
|
merged[key] = value
|
|
if task_id:
|
|
merged["task_id"] = task_id
|
|
if agent_id and not merged.get("role_id"):
|
|
merged["role_id"] = agent_id
|
|
if metadata:
|
|
merged.update(dict(metadata))
|
|
if agent_id and not merged.get("role_id"):
|
|
merged["role_id"] = agent_id
|
|
return merged
|
|
|
|
async def ensure_session(
|
|
self,
|
|
session_id: str,
|
|
project_id: str | None = None,
|
|
*,
|
|
title: str = "",
|
|
mode: str = "primary",
|
|
parent_session_id: str | None = None,
|
|
metadata: dict[str, Any] | None = None,
|
|
) -> SessionRecord | None:
|
|
if not self.store:
|
|
return None
|
|
shared_role_session = bool((metadata or {}).get("shared_role_session", False))
|
|
existing = await self.store.get_session(session_id)
|
|
if existing:
|
|
changed = False
|
|
if title and not existing.title:
|
|
existing.title = title
|
|
changed = True
|
|
if shared_role_session and existing.parent_session_id is not None:
|
|
existing.parent_session_id = None
|
|
changed = True
|
|
if parent_session_id and not shared_role_session and existing.parent_session_id != parent_session_id:
|
|
existing.parent_session_id = parent_session_id
|
|
changed = True
|
|
if metadata:
|
|
existing.metadata = {**existing.metadata, **metadata}
|
|
changed = True
|
|
if changed:
|
|
existing.updated_at = datetime.now()
|
|
await self.store.save_session(existing)
|
|
return existing
|
|
record = SessionRecord(
|
|
session_id=session_id,
|
|
project_id=project_id or self.project_id or "default",
|
|
parent_session_id=None if shared_role_session else parent_session_id,
|
|
title=title,
|
|
mode=mode,
|
|
metadata=dict(metadata or {}),
|
|
)
|
|
await self.store.save_session(record)
|
|
if parent_session_id and not shared_role_session:
|
|
await self.store.save_session_link(
|
|
SessionLinkRecord(
|
|
project_id=record.project_id,
|
|
session_id=parent_session_id,
|
|
linked_session_id=session_id,
|
|
link_type="child_session",
|
|
metadata={"mode": mode},
|
|
)
|
|
)
|
|
return record
|
|
|
|
async def append_session_message(
|
|
self,
|
|
session_id: str,
|
|
role: str,
|
|
*,
|
|
text: str = "",
|
|
part_type: str = "text",
|
|
project_id: str | None = None,
|
|
agent_id: str | None = None,
|
|
task_id: str | None = None,
|
|
parent_message_id: str | None = None,
|
|
summary_flag: bool = False,
|
|
metadata: dict[str, Any] | None = None,
|
|
) -> SessionMessageRecord | None:
|
|
if not self.store:
|
|
return None
|
|
session = await self.ensure_session(
|
|
session_id,
|
|
project_id=project_id,
|
|
mode="child" if role == "subagent" else "primary",
|
|
)
|
|
message_metadata = self._build_message_metadata(
|
|
session,
|
|
metadata=metadata,
|
|
agent_id=agent_id,
|
|
task_id=task_id,
|
|
)
|
|
message = SessionMessageRecord(
|
|
session_id=session_id,
|
|
role=role,
|
|
task_id=task_id,
|
|
agent_id=agent_id,
|
|
parent_message_id=parent_message_id,
|
|
summary_flag=summary_flag,
|
|
metadata=message_metadata,
|
|
)
|
|
await self.store.save_session_message(message)
|
|
if text or part_type != "text":
|
|
payload = {"text": text} if part_type == "text" else {"text": text, **dict(metadata or {})}
|
|
if part_type == "tool_output":
|
|
payload = {
|
|
"tool_name": str((metadata or {}).get("tool_name", "tool")),
|
|
"output": text,
|
|
**dict(metadata or {}),
|
|
}
|
|
await self.store.save_session_part(
|
|
SessionPartRecord(
|
|
message_id=message.message_id,
|
|
session_id=session_id,
|
|
part_type=part_type,
|
|
payload=payload,
|
|
)
|
|
)
|
|
return message
|
|
|
|
async def append_session_part(
|
|
self,
|
|
session_id: str,
|
|
message_id: str,
|
|
part_type: str,
|
|
payload: dict[str, Any],
|
|
) -> None:
|
|
if not self.store:
|
|
return
|
|
await self.store.save_session_part(
|
|
SessionPartRecord(
|
|
message_id=message_id,
|
|
session_id=session_id,
|
|
part_type=part_type,
|
|
payload=payload,
|
|
)
|
|
)
|
|
|
|
async def record_user_turn(
|
|
self,
|
|
session_id: str,
|
|
content: str,
|
|
project_id: str | None = None,
|
|
*,
|
|
metadata: dict[str, Any] | None = None,
|
|
) -> SessionMessageRecord | None:
|
|
return await self.append_session_message(
|
|
session_id=session_id,
|
|
role="user",
|
|
text=content,
|
|
project_id=project_id,
|
|
metadata=metadata,
|
|
)
|
|
|
|
async def record_assistant_turn(
|
|
self,
|
|
session_id: str,
|
|
content: str,
|
|
*,
|
|
project_id: str | None = None,
|
|
agent_id: str | None = None,
|
|
task_id: str | None = None,
|
|
metadata: dict[str, Any] | None = None,
|
|
) -> SessionMessageRecord | None:
|
|
return await self.append_session_message(
|
|
session_id=session_id,
|
|
role="assistant",
|
|
text=content,
|
|
project_id=project_id,
|
|
agent_id=agent_id,
|
|
task_id=task_id,
|
|
metadata=metadata,
|
|
)
|
|
|
|
async def record_child_session_result(
|
|
self,
|
|
parent_session_id: str,
|
|
child_session_id: str,
|
|
*,
|
|
task: Any,
|
|
result_content: str,
|
|
artifacts: dict[str, Any] | None = None,
|
|
result_delivery_id: str = "",
|
|
source_result_message_id: str = "",
|
|
canonical_turn_id: str = "",
|
|
) -> None:
|
|
if not self.store:
|
|
return
|
|
summary = str(result_content or "").strip()
|
|
assignment = dict(getattr(task, "metadata", {}).get("employee_assignment", {}) or {})
|
|
msg = await self.append_session_message(
|
|
session_id=parent_session_id,
|
|
role="assistant",
|
|
text="",
|
|
project_id=getattr(task, "project_id", None) or self.project_id or "default",
|
|
agent_id=getattr(task, "assigned_to", "") or None,
|
|
task_id=getattr(task, "id", None),
|
|
metadata={
|
|
"kind": "child_result",
|
|
"child_session_id": child_session_id,
|
|
"source_task_id": str(getattr(task, "id", "") or ""),
|
|
"task_title": getattr(task, "title", ""),
|
|
"employee_id": str(assignment.get("employee_id", "")).strip(),
|
|
"role_id": str(assignment.get("role_id") or getattr(task, "assigned_to", "") or "").strip(),
|
|
**({"result_delivery_id": str(result_delivery_id).strip()} if str(result_delivery_id).strip() else {}),
|
|
**({"source_result_message_id": str(source_result_message_id).strip()} if str(source_result_message_id).strip() else {}),
|
|
**({"canonical_turn_id": str(canonical_turn_id).strip()} if str(canonical_turn_id).strip() else {}),
|
|
**work_item_identity_payload_for_task(task),
|
|
},
|
|
)
|
|
if not msg:
|
|
return
|
|
await self.append_session_part(
|
|
parent_session_id,
|
|
msg.message_id,
|
|
"subtask_result",
|
|
{
|
|
"child_session_id": child_session_id,
|
|
"task_id": getattr(task, "id", None),
|
|
"task_title": getattr(task, "title", ""),
|
|
"agent_id": getattr(task, "assigned_to", ""),
|
|
"summary": summary,
|
|
"artifacts": self._compact_artifacts(artifacts or {}),
|
|
**({"result_delivery_id": str(result_delivery_id).strip()} if str(result_delivery_id).strip() else {}),
|
|
**({"source_result_message_id": str(source_result_message_id).strip()} if str(source_result_message_id).strip() else {}),
|
|
},
|
|
)
|
|
|
|
async def update_session_title(self, session_id: str, title: str) -> None:
|
|
"""Update the title of an existing session (unconditional overwrite)."""
|
|
if not self.store:
|
|
return
|
|
session = await self.store.get_session(session_id)
|
|
if not session:
|
|
return
|
|
session.title = title
|
|
session.updated_at = datetime.now()
|
|
await self.store.save_session(session)
|
|
|
|
async def update_session_summary(self, session_id: str, summary: str) -> None:
|
|
if not self.store:
|
|
return
|
|
session = await self.store.get_session(session_id)
|
|
if not session:
|
|
return
|
|
session.summary = summary
|
|
session.updated_at = datetime.now()
|
|
await self.store.save_session(session)
|
|
|
|
async def record_runtime_heartbeat_summary(
|
|
self,
|
|
*,
|
|
session_id: str,
|
|
role_id: str,
|
|
worker_kind: str,
|
|
summary: str,
|
|
project_id: str | None = None,
|
|
metadata: dict[str, Any] | None = None,
|
|
) -> dict[str, Any]:
|
|
if not self.store:
|
|
return {}
|
|
text = str(summary or "").strip()
|
|
if not text:
|
|
return {}
|
|
session = await self.store.get_session(session_id)
|
|
if not session:
|
|
return {}
|
|
heartbeat_entries = list((session.metadata or {}).get("runtime_heartbeat_summaries", []) or [])
|
|
heartbeat_entries.append(
|
|
{
|
|
"role_id": role_id,
|
|
"worker_kind": worker_kind,
|
|
"summary": text,
|
|
"metadata": dict(metadata or {}),
|
|
"recorded_at": datetime.now().isoformat(),
|
|
}
|
|
)
|
|
heartbeat_entries = heartbeat_entries[-24:]
|
|
await self._update_session_metadata(
|
|
session_id,
|
|
{
|
|
"runtime_heartbeat_summaries": heartbeat_entries,
|
|
"runtime_heartbeat_updated_at": datetime.now().isoformat(),
|
|
},
|
|
)
|
|
rollup = await self.build_runtime_heartbeat_context(session_id)
|
|
if rollup:
|
|
await self.update_session_summary(session_id, rollup.replace("## Runtime Heartbeats\n", "").strip())
|
|
return {
|
|
"updated": True,
|
|
"entry_count": len(heartbeat_entries),
|
|
"summary_preview": text[:240],
|
|
}
|
|
|
|
async def build_global_memory_context(self) -> str:
|
|
global_mem = self.load_memory(project=False).strip()
|
|
if not global_mem:
|
|
return ""
|
|
return f"## Global Memory\n{global_mem}"
|
|
|
|
def load_project_memory_markdown(self, project_id: str | None = None) -> str:
|
|
pid = self._resolve_project_id(project_id) if (project_id or self.project_id) else None
|
|
return self.markdown_store.load_visible_text(pid)
|
|
|
|
async def build_project_memory_context(
|
|
self,
|
|
project_id: str | None = None,
|
|
*,
|
|
include_project_knowledge: bool = False,
|
|
) -> str:
|
|
pid = self._resolve_project_id(project_id) if (project_id or self.project_id) else ""
|
|
if not pid or pid == "default":
|
|
return ""
|
|
parts: list[str] = []
|
|
project_mem = self.load_project_memory_markdown(pid).strip()
|
|
if project_mem:
|
|
parts.append(f"## Project Memory ({pid})\n{project_mem}")
|
|
if include_project_knowledge:
|
|
explicit_knowledge = self.employee_evolution.preferences.render_project_knowledge_context(pid)
|
|
if explicit_knowledge:
|
|
parts.append(f"## Project Knowledge ({pid})\n{explicit_knowledge}")
|
|
return "\n\n".join(part for part in parts if part)
|
|
|
|
async def build_project_dossier(
|
|
self,
|
|
*,
|
|
project_id: str | None = None,
|
|
run_id: str | None = None,
|
|
session_id: str | None = None,
|
|
limit: int = 8,
|
|
) -> dict[str, Any]:
|
|
pid = self._resolve_project_id(project_id) if (project_id or self.project_id) else "default"
|
|
project_memory = self.load_project_memory_markdown(pid).strip() if pid and pid != "default" else ""
|
|
if not self.store:
|
|
return {
|
|
"project_id": pid,
|
|
"latest_deliverable_summary": "",
|
|
"architecture_decisions": [],
|
|
"completed_work_items": [],
|
|
"open_issues": [],
|
|
"verification_summary": "",
|
|
"artifact_index": [],
|
|
"work_item_summaries_for_downstream": [],
|
|
"last_failure_summary": "",
|
|
"project_memory_excerpt": clip_text(
|
|
project_memory,
|
|
limit=2000,
|
|
marker="project memory excerpt truncated",
|
|
).text,
|
|
}
|
|
|
|
latest_run = None
|
|
if run_id and hasattr(self.store, "get_delegation_run"):
|
|
latest_run = await self.store.get_delegation_run(run_id)
|
|
elif hasattr(self.store, "get_latest_delegation_run"):
|
|
latest_run = await self.store.get_latest_delegation_run(pid)
|
|
|
|
effective_session_id = session_id or (getattr(latest_run, "session_id", "") or None)
|
|
session_memory = await self.build_session_memory_context(effective_session_id) if effective_session_id else ""
|
|
decisions = await self.store.get_work_item_decisions(pid, limit=limit) if hasattr(self.store, "get_work_item_decisions") else []
|
|
artifacts = await self.store.get_artifacts(pid, limit=limit) if hasattr(self.store, "get_artifacts") else []
|
|
handoffs = await self.store.get_handoff_records(pid, limit=limit) if hasattr(self.store, "get_handoff_records") else []
|
|
work_items = (
|
|
await self.store.list_delegation_work_items(latest_run.run_id)
|
|
if latest_run is not None and hasattr(self.store, "list_delegation_work_items")
|
|
else []
|
|
)
|
|
|
|
completed_work_items = [
|
|
{
|
|
"work_item_id": item.work_item_id,
|
|
"title": item.title,
|
|
"role_id": item.role_id,
|
|
"seat_id": item.seat_id,
|
|
"deliverable_summary": item.deliverable_summary or item.summary,
|
|
}
|
|
for item in work_items
|
|
if item.phase == Phase.APPROVED
|
|
][:limit]
|
|
|
|
open_issues: list[str] = []
|
|
for item in work_items:
|
|
if item.phase in {Phase.FAILED, Phase.NEEDS_ATTENTION, Phase.WAITING_DEPENDENCIES, Phase.WAITING_FOR_PEER, Phase.WAITING_FOR_CHILDREN, Phase.PAUSED}:
|
|
issue = str(item.blocked_reason or item.summary or item.title or "").strip()
|
|
if issue:
|
|
open_issues.append(issue)
|
|
for decision in decisions:
|
|
for question in list((decision.details or {}).get("open_questions", []) or []):
|
|
text = str(question or "").strip()
|
|
if text:
|
|
open_issues.append(text)
|
|
deduped_open_issues = list(dict.fromkeys(open_issues))[:limit]
|
|
|
|
verification_parts = [
|
|
str(getattr(latest_run, "latest_deliverable_summary", "") or "").strip(),
|
|
session_memory.replace("## Session Memory", "").strip(),
|
|
]
|
|
verification_summary = next((part for part in verification_parts if part), "")
|
|
|
|
last_failure_summary = ""
|
|
for item in reversed(work_items):
|
|
if item.phase == Phase.FAILED:
|
|
last_failure_summary = str(item.blocked_reason or item.summary or item.title or "").strip()
|
|
if last_failure_summary:
|
|
break
|
|
|
|
return {
|
|
"project_id": pid,
|
|
"run_id": getattr(latest_run, "run_id", "") if latest_run is not None else (run_id or ""),
|
|
"latest_deliverable_summary": str(getattr(latest_run, "latest_deliverable_summary", "") or "").strip(),
|
|
"architecture_decisions": [
|
|
{
|
|
"decision_id": item.decision_id,
|
|
"role_id": item.role_id,
|
|
"projection_id": item.projection_id,
|
|
"summary": item.summary,
|
|
"created_at": item.created_at.isoformat(),
|
|
}
|
|
for item in decisions[:limit]
|
|
],
|
|
"completed_work_items": completed_work_items,
|
|
"open_issues": deduped_open_issues,
|
|
"verification_summary": verification_summary[:1500],
|
|
"artifact_index": [
|
|
{
|
|
"artifact_id": item.artifact_id,
|
|
"name": item.name,
|
|
"artifact_type": item.artifact_type,
|
|
"location": item.location,
|
|
"status": item.status,
|
|
}
|
|
for item in artifacts[:limit]
|
|
],
|
|
"work_item_summaries_for_downstream": [
|
|
{
|
|
"handoff_id": item.handoff_id,
|
|
"from_role": item.from_role,
|
|
"to_role": item.to_role,
|
|
"summary": item.summary,
|
|
"status": item.status,
|
|
}
|
|
for item in handoffs[:limit]
|
|
],
|
|
"last_failure_summary": last_failure_summary,
|
|
"project_memory_excerpt": clip_text(
|
|
project_memory,
|
|
limit=2000,
|
|
marker="project memory excerpt truncated",
|
|
).text,
|
|
"session_memory_excerpt": clip_text(
|
|
session_memory,
|
|
limit=1200,
|
|
marker="session memory excerpt truncated",
|
|
).text,
|
|
}
|
|
|
|
async def build_memory_context(
|
|
self,
|
|
project_id: str | None = None,
|
|
session_id: str | None = None,
|
|
*,
|
|
include_project_knowledge: bool = False,
|
|
) -> str:
|
|
parts: list[str] = []
|
|
global_ctx = await self.build_global_memory_context()
|
|
if global_ctx:
|
|
parts.append(global_ctx)
|
|
project_ctx = await self.build_project_memory_context(
|
|
project_id=project_id,
|
|
include_project_knowledge=include_project_knowledge,
|
|
)
|
|
if project_ctx:
|
|
parts.append(project_ctx)
|
|
if session_id:
|
|
session_ctx = await self.build_session_memory_context(session_id)
|
|
if session_ctx:
|
|
parts.append(session_ctx)
|
|
return "\n\n".join(part for part in parts if part)
|
|
|
|
async def build_focused_memory_context(
|
|
self,
|
|
*,
|
|
query: str,
|
|
project_id: str | None = None,
|
|
session_id: str | None = None,
|
|
include_project_knowledge: bool = False,
|
|
max_chars: int = 2_400,
|
|
) -> str:
|
|
pid = self._resolve_project_id(project_id) if (project_id or self.project_id) else ""
|
|
normalized_query = " ".join(str(query or "").split()).strip()
|
|
parts: list[str] = []
|
|
|
|
global_sections = self._select_relevant_markdown_sections(
|
|
self.load_memory(project=False),
|
|
query=normalized_query,
|
|
max_sections=2,
|
|
max_chars=max_chars // 2,
|
|
)
|
|
if global_sections:
|
|
parts.append(self._render_selected_sections("Focused Global Memory", global_sections))
|
|
|
|
project_markdown = self.load_project_memory_markdown(pid) if pid and pid != "default" else ""
|
|
project_sections = self._select_relevant_markdown_sections(
|
|
project_markdown,
|
|
query=normalized_query,
|
|
max_sections=3,
|
|
max_chars=max_chars,
|
|
)
|
|
if project_sections:
|
|
parts.append(self._render_selected_sections(f"Focused Project Memory ({pid})", project_sections))
|
|
|
|
if include_project_knowledge and pid and pid != "default":
|
|
explicit_knowledge = self.employee_evolution.preferences.render_project_knowledge_context(pid)
|
|
if explicit_knowledge:
|
|
trimmed = explicit_knowledge.strip()
|
|
if len(trimmed) > max_chars // 2:
|
|
trimmed = trimmed[: max_chars // 2].rstrip() + "\n[project knowledge truncated]"
|
|
parts.append(f"## Project Knowledge ({pid})\n{trimmed}")
|
|
|
|
if session_id:
|
|
session_ctx = await self.build_session_memory_context(session_id)
|
|
if session_ctx:
|
|
parts.append(session_ctx)
|
|
|
|
return "\n\n".join(part for part in parts if part)
|
|
|
|
async def build_project_knowledge_context(self, project_id: str | None = None) -> str:
|
|
parts: list[str] = []
|
|
global_ctx = await self.build_global_memory_context()
|
|
if global_ctx:
|
|
parts.append(global_ctx)
|
|
project_ctx = await self.build_project_memory_context(
|
|
project_id=project_id,
|
|
include_project_knowledge=True,
|
|
)
|
|
if project_ctx:
|
|
parts.append(project_ctx)
|
|
return "\n\n".join(parts)
|
|
|
|
async def extract_durable_memories(
|
|
self,
|
|
*,
|
|
session_id: str,
|
|
project_id: str | None,
|
|
query: str,
|
|
assistant_response: str,
|
|
llm: Any | None = None,
|
|
min_messages: int = 4,
|
|
max_input_chars: int = 12_000,
|
|
) -> dict[str, Any]:
|
|
_ = (session_id, project_id, query, assistant_response, llm, min_messages, max_input_chars)
|
|
return {}
|
|
|
|
def _slice_transcript_from_boundary(
|
|
self,
|
|
transcript: list[dict[str, Any]],
|
|
boundary_message_id: str,
|
|
) -> list[dict[str, Any]]:
|
|
if not boundary_message_id:
|
|
return transcript
|
|
for idx, item in enumerate(transcript):
|
|
if item["message"].message_id == boundary_message_id:
|
|
return transcript[idx + 1:]
|
|
return transcript
|
|
|
|
def _slice_transcript_from_message_id(
|
|
self,
|
|
transcript: list[dict[str, Any]],
|
|
message_id: str,
|
|
) -> list[dict[str, Any]]:
|
|
if not message_id:
|
|
return transcript
|
|
for idx, item in enumerate(transcript):
|
|
if item["message"].message_id == message_id:
|
|
return transcript[idx + 1:]
|
|
return transcript
|
|
|
|
async def build_session_memory_context(self, session_id: str) -> str:
|
|
if not self.store:
|
|
return ""
|
|
snapshot = await self.store.get_latest_session_memory_snapshot(session_id)
|
|
if snapshot and snapshot.memory_text.strip():
|
|
return f"## Session Memory\n{snapshot.memory_text.strip()}"
|
|
session = await self.store.get_session(session_id)
|
|
if session and session.summary.strip():
|
|
return f"## Session Memory\n{session.summary.strip()}"
|
|
return ""
|
|
|
|
async def build_runtime_heartbeat_context(self, session_id: str) -> str:
|
|
if not self.store:
|
|
return ""
|
|
session = await self.store.get_session(session_id)
|
|
if not session:
|
|
return ""
|
|
entries = list((session.metadata or {}).get("runtime_heartbeat_summaries", []) or [])
|
|
if not entries:
|
|
return ""
|
|
latest_by_role: dict[str, dict[str, Any]] = {}
|
|
for item in entries:
|
|
if not isinstance(item, dict):
|
|
continue
|
|
role_id = str(item.get("role_id", "") or "").strip()
|
|
if not role_id:
|
|
continue
|
|
latest_by_role[role_id] = item
|
|
lines = ["## Runtime Heartbeats"]
|
|
for role_id in sorted(latest_by_role):
|
|
item = latest_by_role[role_id]
|
|
worker_kind = str(item.get("worker_kind", "") or "").strip()
|
|
label = f"{role_id} ({worker_kind})" if worker_kind else role_id
|
|
lines.append(f"- {label}: {str(item.get('summary', '') or '').strip()}")
|
|
return "\n".join(lines)
|
|
|
|
async def update_runtime_session_memory(
|
|
self,
|
|
*,
|
|
session_id: str,
|
|
project_id: str | None,
|
|
llm: Any | None,
|
|
messages: list[dict[str, Any]],
|
|
update_interval_messages: int = 4,
|
|
max_input_chars: int = 6_000,
|
|
) -> dict[str, Any]:
|
|
if not self.store or llm is None:
|
|
return {}
|
|
session = await self.store.get_session(session_id)
|
|
if not session:
|
|
return {}
|
|
visible = await self._get_visible_session_transcript(session_id)
|
|
if not visible:
|
|
return {}
|
|
current_message_count = len([item for item in visible if not getattr(item["message"], "summary_flag", False)])
|
|
previous_count = int((session.metadata or {}).get("runtime_session_memory_message_count", 0) or 0)
|
|
if current_message_count - previous_count < max(1, int(update_interval_messages or 1)):
|
|
return {}
|
|
rendered = [
|
|
self._render_session_message(item["message"], item["parts"])
|
|
for item in visible
|
|
if not getattr(item["message"], "summary_flag", False)
|
|
]
|
|
transcript_text = "\n\n".join(item for item in rendered if item).strip()
|
|
if not transcript_text:
|
|
return {}
|
|
if len(transcript_text) > max_input_chars:
|
|
transcript_text = transcript_text[-max_input_chars:]
|
|
raw = await llm.simple_chat(
|
|
prompt=json.dumps(
|
|
{
|
|
"project_id": self._resolve_project_id(project_id),
|
|
"session_id": session_id,
|
|
"conversation_excerpt": transcript_text,
|
|
},
|
|
ensure_ascii=False,
|
|
),
|
|
system=(
|
|
"You maintain a rolling session memory for a coding agent.\n"
|
|
"Return strict JSON with keys `summary_text` and `memory_text`.\n"
|
|
"`memory_text` should be concise markdown with sections `## Primary Goal`, "
|
|
"`## Current State`, `## Active Constraints`, and `## Open Risks` when applicable.\n"
|
|
"Keep it durable for the next few turns; do not include verbose logs."
|
|
),
|
|
task_type="quick_tasks",
|
|
)
|
|
parsed = self._parse_json_object(raw)
|
|
memory_text = str(parsed.get("memory_text", "") or parsed.get("summary_text", "")).strip()
|
|
if not memory_text:
|
|
return {}
|
|
latest_message_id = str(visible[-1]["message"].message_id)
|
|
await self.store.save_session_memory_snapshot(
|
|
SessionMemorySnapshotRecord(
|
|
project_id=self._resolve_project_id(project_id),
|
|
session_id=session_id,
|
|
summary_message_id=latest_message_id,
|
|
source_boundary_message_id=latest_message_id,
|
|
summary_text=str(parsed.get("summary_text", "") or memory_text).strip(),
|
|
memory_text=memory_text,
|
|
metadata={"source": "runtime_background_session_memory"},
|
|
)
|
|
)
|
|
await self.update_session_summary(session_id, memory_text)
|
|
await self._update_session_metadata(
|
|
session_id,
|
|
{
|
|
"runtime_session_memory_message_count": current_message_count,
|
|
"runtime_session_memory_updated_at": datetime.now().isoformat(),
|
|
},
|
|
)
|
|
return {
|
|
"updated": True,
|
|
"message_count": current_message_count,
|
|
"summary_preview": memory_text[:240],
|
|
}
|
|
|
|
async def record_verification_feedback(
|
|
self,
|
|
*,
|
|
task: Any,
|
|
verdict: str,
|
|
content: str,
|
|
) -> dict[str, Any]:
|
|
_ = (task, verdict, content)
|
|
return {}
|
|
|
|
async def _update_session_metadata(self, session_id: str, updates: dict[str, Any]) -> None:
|
|
if not self.store:
|
|
return
|
|
session = await self.store.get_session(session_id)
|
|
if not session:
|
|
return
|
|
session.metadata = {**dict(session.metadata or {}), **dict(updates or {})}
|
|
session.updated_at = datetime.now()
|
|
await self.store.save_session(session)
|
|
|
|
@staticmethod
|
|
def _memory_keywords(text: str) -> set[str]:
|
|
stopwords = {
|
|
"the", "and", "for", "with", "that", "this", "from", "into", "your",
|
|
"about", "after", "before", "while", "when", "where", "have", "has",
|
|
"using", "use", "used", "task", "work", "project", "session", "agent",
|
|
"should", "would", "could", "then", "than", "them", "they", "their",
|
|
"need", "needs", "also", "only", "over", "under", "more",
|
|
}
|
|
tokens = set(re.findall(r"[a-zA-Z0-9_]{3,}", str(text or "").lower()))
|
|
return {token for token in tokens if token not in stopwords}
|
|
|
|
def _split_markdown_sections(self, markdown: str) -> list[dict[str, str]]:
|
|
text = str(markdown or "").strip()
|
|
if not text:
|
|
return []
|
|
sections: list[dict[str, str]] = []
|
|
heading = ""
|
|
body_lines: list[str] = []
|
|
for line in text.splitlines():
|
|
match = re.match(r"^\s{0,3}(#{2,4})\s+(.*\S)\s*$", line)
|
|
if match:
|
|
body = "\n".join(body_lines).strip()
|
|
if heading or body:
|
|
sections.append({"heading": heading, "body": body})
|
|
heading = match.group(2).strip()
|
|
body_lines = []
|
|
continue
|
|
body_lines.append(line)
|
|
body = "\n".join(body_lines).strip()
|
|
if heading or body:
|
|
sections.append({"heading": heading, "body": body})
|
|
if not sections:
|
|
return [{"heading": "", "body": text}]
|
|
return sections
|
|
|
|
def _select_relevant_markdown_sections(
|
|
self,
|
|
markdown: str,
|
|
*,
|
|
query: str,
|
|
max_sections: int,
|
|
max_chars: int,
|
|
) -> list[dict[str, str]]:
|
|
sections = self._split_markdown_sections(markdown)
|
|
if not sections:
|
|
return []
|
|
query_tokens = self._memory_keywords(query)
|
|
scored: list[tuple[float, int, dict[str, str]]] = []
|
|
for index, section in enumerate(sections):
|
|
heading = section.get("heading", "")
|
|
body = section.get("body", "")
|
|
combined = f"{heading}\n{body}".strip()
|
|
if not combined:
|
|
continue
|
|
heading_tokens = self._memory_keywords(heading)
|
|
body_tokens = self._memory_keywords(body)
|
|
overlap_heading = len(query_tokens & heading_tokens)
|
|
overlap_body = len(query_tokens & body_tokens)
|
|
score = overlap_heading * 3 + overlap_body
|
|
lowered = combined.lower()
|
|
if any(token in lowered for token in ("checklist", "warning", "watchout", "gotcha", "risk")):
|
|
score += 0.5
|
|
if not query_tokens and index == 0:
|
|
score += 0.5
|
|
if score <= 0:
|
|
continue
|
|
scored.append((score, -index, section))
|
|
if not scored:
|
|
return []
|
|
scored.sort(reverse=True)
|
|
selected: list[dict[str, str]] = []
|
|
used_chars = 0
|
|
for _, _, section in scored:
|
|
heading = str(section.get("heading", "")).strip()
|
|
body = str(section.get("body", "")).strip()
|
|
snippet = body
|
|
projected = used_chars + len(heading) + len(snippet)
|
|
if projected > max_chars:
|
|
remaining = max_chars - used_chars - len(heading) - 32
|
|
if remaining <= 80:
|
|
continue
|
|
snippet = snippet[:remaining].rstrip() + "\n[memory section truncated]"
|
|
selected.append({"heading": heading, "body": snippet})
|
|
used_chars += len(heading) + len(snippet)
|
|
if len(selected) >= max_sections or used_chars >= max_chars:
|
|
break
|
|
return selected
|
|
|
|
def _render_selected_sections(self, title: str, sections: list[dict[str, str]]) -> str:
|
|
lines = [f"## {title}"]
|
|
for section in sections:
|
|
heading = str(section.get("heading", "")).strip()
|
|
body = str(section.get("body", "")).strip()
|
|
if heading:
|
|
lines.append(f"### {heading}")
|
|
if body:
|
|
lines.append(body)
|
|
return "\n".join(lines).strip()
|
|
|
|
def _parse_json_object(self, raw: str) -> dict[str, Any]:
|
|
text = str(raw or "").strip()
|
|
if text.startswith("```"):
|
|
parts = text.split("\n", 1)
|
|
text = parts[1] if len(parts) == 2 else text[3:]
|
|
if text.endswith("```"):
|
|
text = text[:-3]
|
|
text = text.strip()
|
|
try:
|
|
data = json.loads(text)
|
|
return data if isinstance(data, dict) else {}
|
|
except Exception:
|
|
start = text.find("{")
|
|
end = text.rfind("}")
|
|
if start >= 0 and end > start:
|
|
try:
|
|
data = json.loads(text[start : end + 1])
|
|
return data if isinstance(data, dict) else {}
|
|
except Exception:
|
|
return {}
|
|
return {}
|
|
|
|
def _normalize_memory_entries(self, values: Any) -> list[str]:
|
|
entries: list[str] = []
|
|
if not isinstance(values, list):
|
|
return entries
|
|
for item in values:
|
|
if isinstance(item, str):
|
|
text = item.strip()
|
|
if text:
|
|
entries.append(text)
|
|
continue
|
|
if not isinstance(item, dict):
|
|
continue
|
|
title = str(item.get("title", "") or "").strip()
|
|
content = str(item.get("content", "") or "").strip()
|
|
if not content:
|
|
continue
|
|
entry = f"### {title}\n{content}" if title else content
|
|
entries.append(entry.strip())
|
|
return entries
|
|
|
|
def _append_unique_memory_entry(self, entry: str, *, project_id: str | None) -> bool:
|
|
normalized_entry = " ".join(str(entry or "").split()).strip().lower()
|
|
if not normalized_entry:
|
|
return False
|
|
existing = self.markdown_store.load_visible_text(project_id)
|
|
if normalized_entry in " ".join(existing.split()).strip().lower():
|
|
return False
|
|
self.markdown_store.append_visible_entry(entry, project_id)
|
|
return True
|
|
|
|
async def _get_visible_session_transcript(self, session_id: str) -> list[dict[str, Any]]:
|
|
if not self.store:
|
|
return []
|
|
transcript = await self.store.get_session_transcript(session_id)
|
|
if not transcript:
|
|
return []
|
|
compaction = await self.store.get_latest_session_compaction(session_id)
|
|
boundary_message_id = compaction.source_boundary_message_id if compaction else ""
|
|
return self._slice_transcript_from_boundary(transcript, boundary_message_id)
|
|
|
|
def _render_session_parts(self, parts: list[SessionPartRecord]) -> str:
|
|
rendered_parts: list[str] = []
|
|
for part in parts:
|
|
payload = dict(part.payload)
|
|
if part.part_type == "text":
|
|
text = str(payload.get("text", "")).strip()
|
|
if text:
|
|
rendered_parts.append(text)
|
|
continue
|
|
if part.part_type == "subtask_result":
|
|
title = payload.get("task_title") or payload.get("child_session_id") or "child task"
|
|
summary = str(payload.get("summary", "")).strip()
|
|
artifacts = payload.get("artifacts") or {}
|
|
lines = [f"Child session result: {title}"]
|
|
if summary:
|
|
lines.append(summary)
|
|
artifact_lines = self._format_artifact_lines(artifacts)
|
|
if artifact_lines:
|
|
lines.append("Artifacts:")
|
|
lines.extend(f"- {line}" for line in artifact_lines)
|
|
rendered_parts.append("\n".join(lines))
|
|
continue
|
|
if part.part_type == "task_result":
|
|
title = payload.get("task_title") or payload.get("task_id") or "task"
|
|
outcome = str(payload.get("summary", "")).strip()
|
|
rendered_parts.append(f"Task result: {title}\n{outcome}".strip())
|
|
continue
|
|
if part.part_type == "tool_output":
|
|
name = payload.get("tool_name", "tool")
|
|
output = str(payload.get("output", "")).strip()
|
|
rendered_parts.append(f"Tool output [{name}]\n{output}".strip())
|
|
continue
|
|
if part.part_type == "tool_result":
|
|
name = payload.get("tool_name", "tool")
|
|
output = payload.get("result", {})
|
|
if not isinstance(output, str):
|
|
output = json.dumps(output, ensure_ascii=False, default=str)
|
|
rendered_parts.append(f"Tool result [{name}]\n{str(output).strip()}".strip())
|
|
continue
|
|
if part.part_type == "tool_call":
|
|
name = payload.get("tool_name", "tool")
|
|
arguments = payload.get("arguments", {})
|
|
rendered_parts.append(
|
|
f"Tool call [{name}]\n{json.dumps(arguments, ensure_ascii=False, default=str)}".strip()
|
|
)
|
|
continue
|
|
text = str(payload.get("text", "")).strip()
|
|
if text:
|
|
rendered_parts.append(text)
|
|
return "\n\n".join(rendered_parts).strip()
|
|
|
|
def _filter_prompt_history_items(
|
|
self,
|
|
visible_items: list[dict[str, Any]],
|
|
*,
|
|
include_latest_user_turn: bool,
|
|
) -> list[dict[str, Any]]:
|
|
filtered = [
|
|
item
|
|
for item in list(visible_items)
|
|
if not self._is_child_session_seed_item(item)
|
|
]
|
|
if include_latest_user_turn:
|
|
return filtered
|
|
for idx in range(len(filtered) - 1, -1, -1):
|
|
item = filtered[idx]
|
|
message = item.get("message")
|
|
if getattr(message, "summary_flag", False):
|
|
continue
|
|
role = str(getattr(message, "role", "") or "").strip().lower()
|
|
if role == "user":
|
|
return [*filtered[:idx], *filtered[idx + 1 :]]
|
|
break
|
|
return filtered
|
|
|
|
def _is_child_session_seed_item(self, item: dict[str, Any]) -> bool:
|
|
message = item.get("message")
|
|
if message is None or getattr(message, "summary_flag", False):
|
|
return False
|
|
if str(getattr(message, "role", "") or "").strip().lower() != "user":
|
|
return False
|
|
metadata = dict(getattr(message, "metadata", {}) or {})
|
|
return str(metadata.get("kind", "") or "").strip().lower() == "child_session_seed"
|
|
|
|
async def build_session_history_messages(
|
|
self,
|
|
session_id: str,
|
|
*,
|
|
include_latest_user_turn: bool = True,
|
|
) -> list[dict[str, Any]]:
|
|
visible_items = await self._get_visible_session_transcript(session_id)
|
|
visible_items = self._filter_prompt_history_items(
|
|
visible_items,
|
|
include_latest_user_turn=include_latest_user_turn,
|
|
)
|
|
messages: list[dict[str, Any]] = []
|
|
for item in visible_items:
|
|
message = item["message"]
|
|
content = self._render_session_parts(item["parts"])
|
|
if not content:
|
|
continue
|
|
role = "user" if message.role == "user" else "assistant"
|
|
messages.append({"role": role, "content": content})
|
|
return messages
|
|
|
|
async def build_session_history_tail_messages(
|
|
self,
|
|
session_id: str,
|
|
*,
|
|
include_latest_user_turn: bool = True,
|
|
) -> list[dict[str, Any]]:
|
|
return await self.build_session_history_messages(
|
|
session_id,
|
|
include_latest_user_turn=include_latest_user_turn,
|
|
)
|
|
|
|
async def build_session_prompt_context(
|
|
self,
|
|
session_id: str,
|
|
*,
|
|
include_latest_user_turn: bool = True,
|
|
) -> str:
|
|
visible_items = await self._get_visible_session_transcript(session_id)
|
|
visible_items = self._filter_prompt_history_items(
|
|
visible_items,
|
|
include_latest_user_turn=include_latest_user_turn,
|
|
)
|
|
session_memory = await self.build_session_memory_context(session_id)
|
|
blocks: list[str] = []
|
|
for item in visible_items:
|
|
rendered = self._render_session_message(item["message"], item["parts"])
|
|
if rendered:
|
|
blocks.append(rendered)
|
|
parts: list[str] = []
|
|
if session_memory:
|
|
parts.append(session_memory)
|
|
combined = "\n\n".join(blocks).strip()
|
|
if combined:
|
|
parts.append(f"## Current Session History\n{combined}")
|
|
return "\n\n".join(parts)
|
|
|
|
async def _get_agent_transcript(
|
|
self,
|
|
*,
|
|
project_id: str,
|
|
session_id: str,
|
|
employee_id: str,
|
|
) -> list[dict[str, Any]]:
|
|
if not self.store or not session_id or not employee_id:
|
|
return []
|
|
transcript = await self.store.get_session_transcript(session_id)
|
|
if not transcript:
|
|
return []
|
|
session = await self.store.get_session(session_id)
|
|
session_employee_id = str((session.metadata or {}).get("employee_id", "")).strip() if session else ""
|
|
if session_employee_id and session_employee_id == employee_id:
|
|
return transcript
|
|
visible_items: list[dict[str, Any]] = []
|
|
for item in transcript:
|
|
metadata = dict(item["message"].metadata or {})
|
|
if str(metadata.get("employee_id", "")).strip() == employee_id:
|
|
visible_items.append(item)
|
|
return visible_items
|
|
|
|
async def _get_visible_agent_transcript(
|
|
self,
|
|
*,
|
|
project_id: str,
|
|
session_id: str,
|
|
employee_id: str,
|
|
) -> list[dict[str, Any]]:
|
|
if not self.store:
|
|
return []
|
|
transcript = await self._get_agent_transcript(
|
|
project_id=project_id,
|
|
session_id=session_id,
|
|
employee_id=employee_id,
|
|
)
|
|
if not transcript:
|
|
return []
|
|
compaction = await self.store.get_latest_agent_compaction(
|
|
project_id=project_id,
|
|
session_id=session_id,
|
|
employee_id=employee_id,
|
|
)
|
|
boundary_message_id = compaction.source_boundary_message_id if compaction else ""
|
|
return self._slice_transcript_from_boundary(transcript, boundary_message_id)
|
|
|
|
async def build_employee_memory_context(
|
|
self,
|
|
*,
|
|
project_id: str | None,
|
|
session_id: str | None,
|
|
employee_id: str,
|
|
role_id: str = "",
|
|
) -> str:
|
|
if not self.store or not employee_id:
|
|
return ""
|
|
pid = self._resolve_project_id(project_id)
|
|
snapshot = await self.store.get_agent_memory_snapshot(
|
|
project_id=pid,
|
|
employee_id=employee_id,
|
|
memory_kind="final",
|
|
memory_scope="project",
|
|
)
|
|
if snapshot is None:
|
|
legacy_final = await self.store.get_agent_memory_snapshot(
|
|
project_id=pid,
|
|
employee_id=employee_id,
|
|
memory_kind="final",
|
|
memory_scope="session",
|
|
)
|
|
if legacy_final is not None:
|
|
snapshot = await self._migrate_legacy_project_final_snapshot(legacy_final)
|
|
if snapshot is None and session_id:
|
|
snapshot = await self.store.get_agent_memory_snapshot(
|
|
project_id=pid,
|
|
session_id=session_id,
|
|
employee_id=employee_id,
|
|
memory_kind="final",
|
|
memory_scope="session",
|
|
)
|
|
if snapshot is None and session_id:
|
|
snapshot = await self.store.get_agent_memory_snapshot(
|
|
project_id=pid,
|
|
session_id=session_id,
|
|
employee_id=employee_id,
|
|
memory_kind="process",
|
|
memory_scope="session",
|
|
)
|
|
if not snapshot or not snapshot.memory_text.strip():
|
|
return ""
|
|
if snapshot.memory_kind == "final" and snapshot.memory_scope == "project":
|
|
title = "## Employee Project Memory"
|
|
elif snapshot.memory_kind == "final":
|
|
title = "## Employee Final Memory"
|
|
else:
|
|
title = "## Employee Process Memory"
|
|
resolved_role = role_id or snapshot.role_id
|
|
header_lines = [title, f"- Employee ID: {employee_id}"]
|
|
if resolved_role:
|
|
header_lines.append(f"- Role: {resolved_role}")
|
|
header = "\n".join(header_lines)
|
|
return f"{header}\n\n{snapshot.memory_text.strip()}"
|
|
|
|
async def _migrate_legacy_project_final_snapshot(
|
|
self,
|
|
snapshot: AgentMemorySnapshotRecord,
|
|
) -> AgentMemorySnapshotRecord:
|
|
if not self.store or snapshot.memory_scope == "project":
|
|
return snapshot
|
|
migrated = AgentMemorySnapshotRecord(
|
|
project_id=snapshot.project_id,
|
|
session_id="",
|
|
employee_id=snapshot.employee_id,
|
|
role_id=snapshot.role_id,
|
|
memory_scope="project",
|
|
memory_kind=snapshot.memory_kind,
|
|
summary_message_id=snapshot.summary_message_id,
|
|
source_boundary_message_id=snapshot.source_boundary_message_id,
|
|
summary_text=snapshot.summary_text,
|
|
memory_text=snapshot.memory_text,
|
|
metadata={
|
|
**dict(snapshot.metadata or {}),
|
|
"migrated_from_session_id": snapshot.session_id,
|
|
},
|
|
)
|
|
await self.store.save_agent_memory_snapshot(migrated)
|
|
return migrated
|
|
|
|
async def build_employee_history_tail_messages(
|
|
self,
|
|
*,
|
|
project_id: str | None,
|
|
session_id: str | None,
|
|
employee_id: str,
|
|
) -> list[dict[str, Any]]:
|
|
if not session_id or not employee_id:
|
|
return []
|
|
pid = self._resolve_project_id(project_id)
|
|
visible_items = await self._get_visible_agent_transcript(
|
|
project_id=pid,
|
|
session_id=session_id,
|
|
employee_id=employee_id,
|
|
)
|
|
messages: list[dict[str, Any]] = []
|
|
for item in visible_items:
|
|
message = item["message"]
|
|
content = self._render_session_parts(item["parts"])
|
|
if not content:
|
|
continue
|
|
role = "user" if message.role == "user" else "assistant"
|
|
messages.append({"role": role, "content": content})
|
|
return messages
|
|
|
|
async def build_agent_memory_context(self, task: Any, role_id: str) -> str:
|
|
project_id = getattr(task, "project_id", None) or (self.project_id or "default")
|
|
session_id = getattr(task, "session_id", None)
|
|
assignment = dict(getattr(task, "metadata", {}).get("employee_assignment", {}) or {})
|
|
employee_id = str(
|
|
assignment.get("employee_id")
|
|
or getattr(task, "metadata", {}).get("employee_id", "")
|
|
or ""
|
|
).strip()
|
|
return await self.build_employee_memory_context(
|
|
project_id=project_id,
|
|
session_id=session_id,
|
|
employee_id=employee_id,
|
|
role_id=role_id or str(assignment.get("role_id", "")).strip(),
|
|
)
|
|
|
|
def build_external_prompt_context(self, task: Any, role_id: str, memory_ctx: str, comm_ctx: dict[str, Any] | None = None) -> str:
|
|
parts = [memory_ctx] if memory_ctx else []
|
|
if comm_ctx:
|
|
inbox = list(comm_ctx.get("inbox", []))
|
|
annotations = list(comm_ctx.get("annotations", []))
|
|
if inbox:
|
|
parts.append(
|
|
"## Inbox\n" +
|
|
"\n".join(
|
|
f"- From {item.get('from_agent', '')}: {item.get('subject', '')} :: {item.get('body', '')}"
|
|
for item in inbox
|
|
)
|
|
)
|
|
if annotations:
|
|
parts.append(
|
|
"## Task Annotations\n" +
|
|
"\n".join(
|
|
f"- {item.get('from', '')}: {item.get('body', '')}"
|
|
for item in annotations
|
|
)
|
|
)
|
|
if getattr(task, "metadata", {}).get("handoff_context"):
|
|
parts.append(f"## Handoff Context\n{getattr(task, 'metadata', {}).get('handoff_context', '')}")
|
|
return "\n\n".join(part for part in parts if part)
|
|
|
|
def _render_session_message(self, message: SessionMessageRecord, parts: list[SessionPartRecord]) -> str:
|
|
rendered = self._render_session_parts(parts)
|
|
if not rendered:
|
|
return ""
|
|
role = "User" if message.role == "user" else ("Summary" if message.summary_flag else "Assistant")
|
|
return f"{role}:\n{rendered}"
|
|
|
|
def _compact_artifacts(self, artifacts: dict[str, Any]) -> dict[str, Any]:
|
|
compact: dict[str, Any] = {}
|
|
for key, value in artifacts.items():
|
|
if isinstance(value, str):
|
|
compact[key] = value
|
|
elif isinstance(value, (int, float, bool)) or value is None:
|
|
compact[key] = value
|
|
elif isinstance(value, list):
|
|
compact[key] = [self._normalize_artifact_value(item) for item in value]
|
|
elif isinstance(value, dict):
|
|
compact[key] = {k: self._normalize_artifact_value(v) for k, v in value.items()}
|
|
else:
|
|
compact[key] = str(value)
|
|
return compact
|
|
|
|
def _normalize_artifact_value(self, value: Any) -> Any:
|
|
if isinstance(value, (str, int, float, bool)) or value is None:
|
|
return value
|
|
if isinstance(value, list):
|
|
return [self._normalize_artifact_value(item) for item in value]
|
|
if isinstance(value, dict):
|
|
return {k: self._normalize_artifact_value(v) for k, v in value.items()}
|
|
return str(value)
|
|
|
|
def _format_artifact_lines(self, artifacts: dict[str, Any]) -> list[str]:
|
|
lines: list[str] = []
|
|
for key, value in artifacts.items():
|
|
if isinstance(value, list):
|
|
lines.append(f"{key}: {', '.join(str(item) for item in value)}")
|
|
elif isinstance(value, dict):
|
|
inner = ", ".join(f"{k}={v}" for k, v in value.items())
|
|
lines.append(f"{key}: {inner}")
|
|
else:
|
|
lines.append(f"{key}: {value}")
|
|
return lines
|
|
|
|
def get_compression_prompt(self, messages: list[dict[str, Any]], existing_memory: str) -> str:
|
|
"""Create a prompt to compress conversation history into memory."""
|
|
msg_text = "\n".join(
|
|
f"[{m.get('role', '?')}]: {m.get('content', '')}"
|
|
for m in messages
|
|
)
|
|
return (
|
|
"You are a memory compressor. Summarize the following conversation into "
|
|
"key facts, decisions, and learnings. Preserve important technical details, "
|
|
"user preferences, and outcomes. Be concise but comprehensive. "
|
|
"If the source conversation is large, aggressively deduplicate and abstract instead of copying verbatim.\n\n"
|
|
f"## Existing Memory\n{existing_memory}\n\n"
|
|
f"## New Conversation\n{msg_text}\n\n"
|
|
"Write the updated memory as a structured markdown document. "
|
|
"Merge new information with existing memory. Remove duplicates."
|
|
)
|