deep agent

- Replace langgraph create_react_agent with deepagents create_deep_agent
- Sub-agents now configured as SubAgent dicts dispatched via built-in task tool
- Stream filter updated: langgraph_node 'agent' → 'model'
- Accept both AIMessage and AIMessageChunk in stream filter
- Collector only captures write mutations (insert/update/delete)
- Add deepagents>=0.4.10 to requirements.txt

alembic/versions/9a1f2d0b6c7e_deprecate_backend_agent_config_tables.py

@@ -1,92 +0,0 @@
-"""Deprecate backend agent config tables.
-
-The Electron client is now the source of truth for agent configuration
-(directory, extract targets, batch interval, custom prompt). Backend keeps
-billing checks and trigger/run logs only.
-
-Revision ID: 9a1f2d0b6c7e
-Revises: 818478c251dc
-Create Date: 2026-03-16
-"""
-
-from __future__ import annotations
-
-from typing import Sequence, Union
-
-import sqlalchemy as sa
-from alembic import op
-from sqlalchemy.dialects import postgresql
-
-revision: str = "9a1f2d0b6c7e"
-down_revision: Union[str, None] = "818478c251dc"
-branch_labels: Union[str, Sequence[str], None] = None
-depends_on: Union[str, Sequence[str], None] = None
-
-
-def upgrade() -> None:
-    bind = op.get_bind()
-    inspector = sa.inspect(bind)
-    existing = set(inspector.get_table_names())
-
-    if "cloud_agent_configs" in existing:
-        op.drop_index("ix_cloud_agent_configs_user_id", table_name="cloud_agent_configs")
-        op.drop_table("cloud_agent_configs")
-
-    if "local_agent_configs" in existing:
-        op.drop_index("ix_local_agent_configs_user_id", table_name="local_agent_configs")
-        op.drop_table("local_agent_configs")
-
-
-def downgrade() -> None:
-    op.create_table(
-        "local_agent_configs",
-        sa.Column("id", postgresql.UUID(as_uuid=False), nullable=False),
-        sa.Column("user_id", postgresql.UUID(as_uuid=False), nullable=False),
-        sa.Column("device_id", sa.String(255), nullable=False),
-        sa.Column("name", sa.String(255), nullable=False),
-        sa.Column("directory_paths", sa.JSON, nullable=False, server_default="[]"),
-        sa.Column("data_types", sa.JSON, nullable=False, server_default="[]"),
-        sa.Column("prompt_template", sa.Text, nullable=False, server_default=""),
-        sa.Column("file_extensions", sa.JSON, nullable=False, server_default="[]"),
-        sa.Column("schedule_cron", sa.String(100), nullable=False, server_default="0 */6 * * *"),
-        sa.Column("enabled", sa.Boolean, nullable=False, server_default=sa.true()),
-        sa.Column("last_run_at", sa.DateTime(timezone=True), nullable=True),
-        sa.Column("created_at", sa.DateTime(timezone=True), nullable=False, server_default=sa.text("now()")),
-        sa.Column("updated_at", sa.DateTime(timezone=True), nullable=False, server_default=sa.text("now()")),
-        sa.PrimaryKeyConstraint("id"),
-        sa.ForeignKeyConstraint(["user_id"], ["users.id"], ondelete="CASCADE"),
-    )
-    op.create_index("ix_local_agent_configs_user_id", "local_agent_configs", ["user_id"])
-
-    op.execute(
-        """
-        DO $$ BEGIN
-            CREATE TYPE cloud_provider AS ENUM ('gmail', 'teams', 'outlook');
-        EXCEPTION WHEN duplicate_object THEN NULL;
-        END $$;
-        """
-    )
-
-    op.create_table(
-        "cloud_agent_configs",
-        sa.Column("id", postgresql.UUID(as_uuid=False), nullable=False),
-        sa.Column("user_id", postgresql.UUID(as_uuid=False), nullable=False),
-        sa.Column(
-            "provider",
-            postgresql.ENUM("gmail", "teams", "outlook", name="cloud_provider", create_type=False),
-            nullable=False,
-        ),
-        sa.Column("name", sa.String(255), nullable=False),
-        sa.Column("data_types", sa.JSON, nullable=False, server_default="[]"),
-        sa.Column("prompt_template", sa.Text, nullable=False, server_default=""),
-        sa.Column("oauth_token_encrypted", sa.Text, nullable=True),
-        sa.Column("filter_config", sa.JSON, nullable=True),
-        sa.Column("schedule_cron", sa.String(100), nullable=False, server_default="0 */6 * * *"),
-        sa.Column("enabled", sa.Boolean, nullable=False, server_default=sa.true()),
-        sa.Column("last_run_at", sa.DateTime(timezone=True), nullable=True),
-        sa.Column("created_at", sa.DateTime(timezone=True), nullable=False, server_default=sa.text("now()")),
-        sa.Column("updated_at", sa.DateTime(timezone=True), nullable=False, server_default=sa.text("now()")),
-        sa.PrimaryKeyConstraint("id"),
-        sa.ForeignKeyConstraint(["user_id"], ["users.id"], ondelete="CASCADE"),
-    )
-    op.create_index("ix_cloud_agent_configs_user_id", "cloud_agent_configs", ["user_id"])

app/agents/__init__.py

@@ -1,5 +1,5 @@
-"""Expose tool modules used by deep orchestrator-worker graphs."""
+"""Agent tool modules — imported by deep_agent.py to build sub-agent graphs."""
 
-from app.agents import filesystem_agent, timeline_agent, note_agent, project_agent, task_agent
+from app.agents import timeline_agent, note_agent, project_agent, task_agent
 
-__all__ = ["filesystem_agent", "timeline_agent", "note_agent", "project_agent", "task_agent"]
+__all__ = ["timeline_agent", "note_agent", "project_agent", "task_agent"]

app/agents/filesystem_agent.py

@@ -1,85 +0,0 @@
-"""Filesystem agent — tools for reading local directories and files on Electron.
-
-These tools delegate to the Electron client via ``execute_on_client()`` using
-the same WS tool-call round-trip pattern as CRUD tools.  The Electron app
-handles actual disk I/O and responds with ``tool_result`` frames.
-"""
-
-from __future__ import annotations
-
-from typing import Any
-
-from langchain_core.tools import tool
-
-from app.core.ws_context import execute_on_client
-
-
-@tool
-async def list_directory(path: str) -> str:
-    """List files and folders in a local directory on the user's device.
-
-    Returns a formatted listing of entries with name, type (file/directory),
-    and full path.
-    """
-    result = await execute_on_client(
-        action="list_directory",
-        data={"path": path},
-    )
-    entries: list[dict[str, Any]] = result.get("entries", [])
-    if not entries:
-        return f"Directory '{path}' is empty or does not exist."
-    lines: list[str] = []
-    for entry in entries:
-        entry_type = entry.get("type", "unknown")
-        entry_name = entry.get("name", "")
-        entry_path = entry.get("path", "")
-        lines.append(f"- [{entry_type}] {entry_name}  ({entry_path})")
-    return f"Directory listing for '{path}' ({len(entries)} entries):\n" + "\n".join(lines)
-
-
-@tool
-async def read_file_content(path: str) -> str:
-    """Read the text content of a local file on the user's device.
-
-    Returns the file content as a string.  Large files may be truncated
-    by the Electron client.
-    """
-    result = await execute_on_client(
-        action="read_file_content",
-        data={"path": path},
-    )
-    content: str = result.get("content", "")
-    if not content:
-        return f"File '{path}' is empty or could not be read."
-    return content
-
-
-@tool
-async def get_file_metadata(path: str) -> str:
-    """Get metadata for a local file: size, creation date, modification date, extension.
-
-    Returns a formatted summary of the file's metadata.
-    """
-    result = await execute_on_client(
-        action="get_file_metadata",
-        data={"path": path},
-    )
-    size = result.get("size", "unknown")
-    created = result.get("createdAt", "unknown")
-    modified = result.get("modifiedAt", "unknown")
-    extension = result.get("extension", "unknown")
-    name = result.get("name", path)
-    return (
-        f"File: {name}\n"
-        f"  Extension: {extension}\n"
-        f"  Size: {size} bytes\n"
-        f"  Created: {created}\n"
-        f"  Modified: {modified}"
-    )
-
-
-FILESYSTEM_TOOLS: list[Any] = [
-    list_directory,
-    read_file_content,
-    get_file_metadata,
-]

app/agents/note_agent.py

@@ -1,8 +1,7 @@
-"""Note agent — Markdown note management (list, get, create, update, delete)."""
+"""Note agent — tool definitions for Markdown note CRUD."""
 
 from __future__ import annotations
 
-import re
 from typing import Any
 
 from langchain_core.tools import tool
@@ -10,38 +9,14 @@ from langchain_core.tools import tool
 from app.core.llm import embed
 from app.core.ws_context import execute_on_client
 
-_UUID_RE = re.compile(
-    r"^[0-9a-fA-F]{8}-[0-9a-fA-F]{4}-[1-5][0-9a-fA-F]{3}-[89abAB][0-9a-fA-F]{3}-[0-9a-fA-F]{12}$"
-)
-
-
-def _is_uuid(value: str) -> bool:
-    return bool(_UUID_RE.match(value))
-
-NOTE_SYSTEM_PROMPT = (
-    "You are a note-taking assistant. You help users create, retrieve, update,\n"
-    "and delete Markdown notes in their workspace.\n\n"
-    "Rules:\n"
-    "  - content is always Markdown; preserve formatting when updating\n"
-    "  - project_id is optional; link a note to a project when mentioned\n"
-    "  - When updating, call get_note first if you need to read existing content\n"
-    "    before appending or replacing sections\n"
-    "  - list_notes without project_id returns all notes; scope with project_id\n"
-    "    when the user is working within a specific project\n"
-    "  - project_id must be a UUID; if you only know a project name, do not pass it as project_id\n"
-    "  - Do not fabricate note content — reflect what the user provides or what\n"
-    "    is already in the note (retrieved via get_note)."
-)
-
 
 @tool
 async def list_notes(project_id: str = "") -> str:
     """List notes, optionally scoped to a project by project_id."""
-    normalized_project_id = project_id if (project_id and _is_uuid(project_id)) else ""
     result = await execute_on_client(
         action="select",
         table="notes",
-        filters={"projectId": normalized_project_id or None},
+        filters={"projectId": project_id or None},
     )
     rows = result.get("rows", [])
     if not rows:
@@ -130,10 +105,4 @@ async def delete_note(note_id: str) -> str:
     return f"Note {note_id} deleted."
 
 
-NOTE_TOOLS: list[Any] = [
+
-    list_notes,
-    get_note,
-    create_note,
-    update_note,
-    delete_note,
-]

app/agents/project_agent.py

@@ -1,4 +1,4 @@
-"""Project agent — full lifecycle management (list, get, create, update, archive, delete)."""
+"""Project agent — tool definitions for project lifecycle CRUD."""
 
 from __future__ import annotations
 
@@ -8,22 +8,6 @@ from langchain_core.tools import tool
 
 from app.core.ws_context import execute_on_client
 
-PROJECT_SYSTEM_PROMPT = (
-    "You are a project management assistant. You help users create, find,\n"
-    "update, and archive projects in their workspace.\n\n"
-    "Rules:\n"
-    "  - status must be one of: active, archived\n"
-    "  - client_id is optional; link to a client only when explicitly mentioned\n"
-    "  - ai_summary is populated only when the user asks for a project summary;\n"
-    "    derive it from context data — do not fabricate content\n"
-    "  - Use list_projects for scoped queries; list_all_projects only when the\n"
-    "    user wants a complete cross-client view including archived projects\n"
-    "  - get_project requires a project UUID; resolve the ID first by calling\n"
-    "    list_projects if you only have a project name\n"
-    "  - Prefer archiving (update_project status=archived) over deletion;\n"
-    "    only call delete_project when the user explicitly confirms deletion."
-)
-
 
 @tool
 async def list_projects(
@@ -133,11 +117,4 @@ async def delete_project(project_id: str) -> str:
     return f"Project {project_id} permanently deleted."
 
 
-PROJECT_TOOLS: list[Any] = [
+
-    list_projects,
-    list_all_projects,
-    get_project,
-    create_project,
-    update_project,
-    delete_project,
-]

app/agents/task_agent.py

@@ -1,40 +1,14 @@
-"""Task agent — full CRUD for tasks and task comments."""
+"""Task agent — tool definitions for task and task comment CRUD."""
 
 from __future__ import annotations
 
 from datetime import datetime, timezone
-import re
 from typing import Any
 
 from langchain_core.tools import tool
 
 from app.core.ws_context import execute_on_client
 
-_UUID_RE = re.compile(
-    r"^[0-9a-fA-F]{8}-[0-9a-fA-F]{4}-[1-5][0-9a-fA-F]{3}-[89abAB][0-9a-fA-F]{3}-[0-9a-fA-F]{12}$"
-)
-
-
-def _is_uuid(value: str) -> bool:
-    return bool(_UUID_RE.match(value))
-
-TASK_SYSTEM_PROMPT = (
-    "You are a task management assistant for a project workspace.\n"
-    "You create, update, list, and track tasks and their comments.\n\n"
-    "Rules:\n"
-    "  - status must be one of: todo, in_progress, done\n"
-    "  - priority must be one of: high, medium, low\n"
-    "  - due_date is a Unix timestamp in milliseconds; convert human dates\n"
-    "  - assignees is a JSON-encoded array of strings (e.g. '[\"Alice\",\"Bob\"]')\n"
-    "  - project_id is optional; link to a project when the user mentions one\n"
-    "  - is_ai_suggested: 1 only when proactively proposing a task the user\n"
-    "    did not explicitly request; 0 otherwise\n"
-    "  - is_ai_suggested: 1 only when proactively proposing a task the user did not explicitly request; 0 otherwise\n"
-    "  - Use list_tasks_due_today for 'what's due today' queries\n"
-    "  - For update_task, use -1 for integer fields you do not want to change\n"
-    "  - Always confirm the action in plain, user-friendly language."
-)
-
 
 # ── Task tools ────────────────────────────────────────────────────────
 
@@ -48,12 +22,11 @@ async def list_tasks(
 ) -> str:
     """List tasks, optionally filtered by project_id, status (todo|in_progress|done),
     a search string, or an order_by field name (dueDate|priority|createdAt)."""
-    normalized_project_id = project_id if (project_id and _is_uuid(project_id)) else ""
     result = await execute_on_client(
         action="select",
         table="tasks",
         filters={
-            "projectId": normalized_project_id or None,
+            "projectId": project_id or None,
             "status": status or None,
             "search": search or None,
             "orderBy": order_by or None,
@@ -79,6 +52,7 @@ async def create_task(
     due_date: int = 0,
     project_id: str = "",
     is_ai_suggested: int = 0,
+    is_approved: int = 0,
 ) -> str:
     """Create a new task.
     title: task title (required)
@@ -89,6 +63,7 @@ async def create_task(
     due_date: Unix timestamp in milliseconds; 0 means no due date
     project_id: optional UUID of the parent project
     is_ai_suggested: 1 if proactively suggested, 0 if user-requested
+    is_approved: 0 until the user confirms; 1 when confirmed
     """
     result = await execute_on_client(
         action="insert",
@@ -102,6 +77,7 @@ async def create_task(
             "dueDate": due_date or None,
             "projectId": project_id or None,
             "isAiSuggested": is_ai_suggested,
+            "isApproved": is_approved,
         },
     )
     row = result["row"]
@@ -121,10 +97,12 @@ async def update_task(
     assignees: str = "",
     due_date: int = -1,
     project_id: str = "",
+    is_approved: int = -1,
 ) -> str:
     """Update fields on an existing task. Only pass fields you want to change.
     task_id: the task's UUID (required)
     due_date: -1 means unchanged; 0 clears the due date; any positive value sets it
+    is_approved: -1 means unchanged; 0 or 1 sets the value
     """
     updates: dict[str, Any] = {}
     if title:
@@ -141,6 +119,8 @@ async def update_task(
         updates["dueDate"] = due_date or None
     if project_id:
         updates["projectId"] = project_id
+    if is_approved != -1:
+        updates["isApproved"] = is_approved
     result = await execute_on_client(
         action="update",
         table="tasks",
@@ -208,12 +188,8 @@ async def add_task_comment(task_id: str, author: str, content: str) -> str:
         table="taskComments",
         data={"taskId": task_id, "author": author, "content": content},
     )
-    row = result.get("row", {})
+    row = result["row"]
-    row_author = row.get("author", author)
+    return f"Comment added by {row['author']} on task {row['taskId']} (comment id: {row['id']})."
-    # Electron payloads can vary (taskId vs task_id). Fall back to input task_id.
-    row_task_id = row.get("taskId") or row.get("task_id") or task_id
-    row_comment_id = row.get("id", "unknown")
-    return f"Comment added by {row_author} on task {row_task_id} (comment id: {row_comment_id})."
 
 
 @tool
@@ -223,16 +199,4 @@ async def delete_task_comment(comment_id: str) -> str:
     return f"Comment {comment_id} deleted."
 
 
-# ── Agent ─────────────────────────────────────────────────────────────
 
-
-TASK_TOOLS: list[Any] = [
-    list_tasks,
-    create_task,
-    update_task,
-    delete_task,
-    list_tasks_due_today,
-    list_task_comments,
-    add_task_comment,
-    delete_task_comment,
-]

app/agents/timeline_agent.py

@@ -1,45 +1,21 @@
-"""Timeline agent — project milestone management (list, create, update, delete)."""
+"""Timeline agent — tool definitions for project milestone CRUD."""
 
 from __future__ import annotations
 
-import re
 from typing import Any
 
 from langchain_core.tools import tool
 
 from app.core.ws_context import execute_on_client
 
-_UUID_RE = re.compile(
-    r"^[0-9a-fA-F]{8}-[0-9a-fA-F]{4}-[1-5][0-9a-fA-F]{3}-[89abAB][0-9a-fA-F]{3}-[0-9a-fA-F]{12}$"
-)
-
-
-def _is_uuid(value: str) -> bool:
-    return bool(_UUID_RE.match(value))
-
-TIMELINE_SYSTEM_PROMPT = (
-    "You are a project timeline assistant. Timelines are milestone dates that\n"
-    "track progress on a project — they are not calendar events.\n\n"
-    "Rules:\n"
-    "  - project_id is REQUIRED for every create; confirm with the user if unknown\n"
-    "  - For listing, project_id must be a UUID; never pass plain names as project_id\n"
-    "  - date is a Unix timestamp in milliseconds; convert human-readable dates\n"
-    "  - is_ai_suggested: 1 when proactively proposing a timeline, 0 otherwise\n"
-    "  - is_ai_suggested: 1 when proactively proposing a timeline, 0 otherwise\n"
-    "  - For update_timeline, use -1 for integer fields you do not want to change\n"
-    "  - Listing without a project_id returns all timelines across projects\n"
-    "  - Always echo the title and formatted date in your confirmation."
-)
-
 
 @tool
 async def list_timelines(project_id: str = "") -> str:
     """List timelines. Provide project_id to scope to a specific project."""
-    normalized_project_id = project_id if (project_id and _is_uuid(project_id)) else ""
     result = await execute_on_client(
         action="select",
         table="timelines",
-        filters={"projectId": normalized_project_id or None},
+        filters={"projectId": project_id or None},
     )
     rows = result.get("rows", [])
     if not rows:
@@ -54,12 +30,14 @@ async def create_timeline(
     title: str,
     date: int,
     is_ai_suggested: int = 0,
+    is_approved: int = 0,
 ) -> str:
     """Create a project timeline (milestone).
     project_id: REQUIRED UUID of the parent project
     title: descriptive name for the milestone
     date: Unix timestamp in milliseconds
     is_ai_suggested: 1 if proactively suggested, 0 if user-requested
+    is_approved: 0 until the user confirms
     """
     result = await execute_on_client(
         action="insert",
@@ -69,6 +47,7 @@ async def create_timeline(
             "title": title,
             "date": date,
             "isAiSuggested": is_ai_suggested,
+            "isApproved": is_approved,
         },
     )
     row = result["row"]
@@ -80,16 +59,20 @@ async def update_timeline(
     timeline_id: str,
     title: str = "",
     date: int = -1,
+    is_approved: int = -1,
 ) -> str:
     """Update a timeline. Only pass fields that should change.
     timeline_id: UUID of the timeline (required)
     date: -1 means unchanged; any other value sets the new date (ms timestamp)
+    is_approved: -1 means unchanged; 0 or 1 sets the approval state
     """
     updates: dict[str, Any] = {}
     if title:
         updates["title"] = title
     if date != -1:
         updates["date"] = date
+    if is_approved != -1:
+        updates["isApproved"] = is_approved
     result = await execute_on_client(
         action="update",
         table="timelines",
@@ -106,9 +89,4 @@ async def delete_timeline(timeline_id: str) -> str:
     return f"Timeline {timeline_id} deleted."
 
 
-TIMELINE_TOOLS: list[Any] = [
+
-    list_timelines,
-    create_timeline,
-    update_timeline,
-    delete_timeline,
-]

app/api/middleware/auth.py

@@ -55,15 +55,12 @@ async def get_current_user(
         raise credentials_exc
 
     # Live tier lookup — subscription row is the authoritative source.
-    # In dev, fall back to 'power' (unlimited) so quota limits don't
-    # block local development when no Stripe subscription exists.
     from app.models import Subscription, User  # noqa: PLC0415
 
     result = await db.execute(
         select(Subscription.tier).where(Subscription.user_id == user_id)
     )
-    default_tier = "power" if settings.ENV == "dev" else "free"
+    tier: str = result.scalar_one_or_none() or "free"
-    tier: str = result.scalar_one_or_none() or default_tier
 
     # Fetch name/surname from user row.
     user_result = await db.execute(

app/api/routes/agent_setup.py

@@ -1,40 +1,54 @@
-"""Chatbot Journey — WS-based guided conversation to build an agent prompt_template.
+"""Chatbot Journey endpoints — guided conversation to build an agent prompt_template.
 
-The journey is driven entirely through WebSocket frames (no REST endpoints).
+Endpoints:
-The device WS handler dispatches ``journey_start`` and ``journey_message``
+  POST /agents/journey/start    — start a new journey session
-frames to the functions exported here.
+  POST /agents/journey/message  — continue the conversation
+
+Sessions are stored in-memory with a 30-minute TTL.  Stale entries are
+cleaned up lazily on access.  Upgrade to Redis for multi-instance deployments.
 
 Journey flow:
-  1. FE sends ``journey_start`` frame with basic agent config (directory,
+  1. Client sends ``{ agent_type, agent_id? }`` to ``/start``.
-     data_types, schedule).
+  2. Server creates a session, calls the LLM with a contextual system prompt,
-  2. Server creates an in-memory session, sets up a WS executor so the
+     and returns the first question.
-     setup LLM can use file-system tools, does a first directory scrape,
+  3. Client sends follow-up messages to ``/message``.
-     and sends back a ``journey_reply`` with the first question.
+  4. After 3-5 turns the LLM wraps up by emitting a ``prompt_template`` block
-  3. FE sends ``journey_message`` frames for each user reply.
+     delimited by ``PROMPT_TEMPLATE_START`` / ``PROMPT_TEMPLATE_END``.
-  4. Server appends the user message, calls the LLM (which may read files
+  5. Server parses the block, sets ``done=True``, and returns the template.
-     via tools), and sends back a ``journey_reply``.
+
-  5. After 3-5 turns the LLM wraps up by emitting a ``prompt_template``
+The ``prompt_template`` from the final response is meant to be stored in
-     block delimited by ``PROMPT_TEMPLATE_START`` / ``PROMPT_TEMPLATE_END``.
+``LocalAgentConfig.prompt_template`` or ``CloudAgentConfig.prompt_template``
-  6. Server parses the block, sends ``journey_reply`` with ``done=True``
+by the Electron client (via the agent CRUD endpoints).
-     and the template.  FE stores it locally.
 """
 
 from __future__ import annotations
 
-import json
 import logging
 import time
 import uuid
 from dataclasses import dataclass, field
 from typing import Any
 
-from langchain_core.messages import AIMessage, HumanMessage, SystemMessage, ToolMessage
+from fastapi import APIRouter, Depends, HTTPException, status
+from langchain_core.messages import AIMessage, HumanMessage, SystemMessage
+from sqlalchemy import select
+from sqlalchemy.ext.asyncio import AsyncSession
 
-from app.agents.filesystem_agent import FILESYSTEM_TOOLS
+from app.api.deps import get_current_user
 from app.core.llm import get_llm
+from app.db import get_session
+from app.models import CloudAgentConfig, LocalAgentConfig
+from app.schemas import (
+    JourneyMessageRequest,
+    JourneyResponse,
+    JourneyStartRequest,
+    UserProfile,
+)
 
 logger = logging.getLogger(__name__)
 
+router = APIRouter(prefix="/agents/journey", tags=["agents"])
+
 # ── Session TTL ───────────────────────────────────────────────────────────
 
 _SESSION_TTL_SECONDS: int = 1800  # 30 minutes
@@ -43,25 +57,18 @@ _SESSION_TTL_SECONDS: int = 1800  # 30 minutes
 _TEMPLATE_START = "PROMPT_TEMPLATE_START"
 _TEMPLATE_END = "PROMPT_TEMPLATE_END"
 
-# Minimum turns before we consider nudging the LLM to wrap up.
+# Maximum number of conversation turns before the LLM is nudged to wrap up.
-_MIN_TURNS_BEFORE_NUDGE: int = 3
+_MAX_TURNS: int = 5
-# Hard cap to avoid infinite loops (safety net, not the primary stopping criterion).
-_MAX_TURNS: int = 15
-# Max tool-calling steps per LLM invocation.
-_MAX_TOOL_STEPS: int = 6
 
 # ── In-memory session store ───────────────────────────────────────────────
 
 
 @dataclass
-class JourneySession:
+class _JourneySession:
     session_id: str
     user_id: str
     agent_type: str  # "local" | "cloud"
-    directory: str
-    data_types: list[str]
     history: list[dict[str, Any]] = field(default_factory=list)
-    system_prompt: str = ""
     created_at: float = field(default_factory=time.monotonic)
 
     def is_expired(self) -> bool:
@@ -69,84 +76,67 @@ class JourneySession:
 
 
 # session_id → session
-_sessions: dict[str, JourneySession] = {}
+_sessions: dict[str, _JourneySession] = {}
 
 
-def get_journey_session(session_id: str, user_id: str) -> JourneySession | None:
+def _get_session(session_id: str, user_id: str) -> _JourneySession:
-    """Retrieve session; return None on missing, expired, or wrong owner."""
+    """Retrieve session; raise 404 on missing, expired, or wrong owner."""
     s = _sessions.get(session_id)
     if s is None or s.is_expired():
         _sessions.pop(session_id, None)
-        return None
+        raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail="Journey session not found or expired")
     if s.user_id != user_id:
-        return None
+        raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail="Journey session not found or expired")
     return s
 
 
 # ── System prompt builder ─────────────────────────────────────────────────
 
+_LOCAL_PREAMBLE = """\
+What kind of files are in the directories you want to monitor? \
+(for example: emails saved as .eml, documents in .pdf or .txt, markdown notes, etc.)"""
+
+_CLOUD_PREAMBLE = """\
+What kind of emails or messages should I look for? \
+(for example: client communications, invoices, meeting notes, project updates, etc.)"""
+
 _SYSTEM_PROMPT_TEMPLATE = """\
 You are a friendly assistant helping a freelancer configure a data-extraction agent.
-Your job is to understand exactly what data the user wants to extract from their
+Your job is to understand exactly what data the user wants to extract from their {source_description} \
-local directory and produce a detailed prompt_template that a separate AI will use
+and produce a detailed prompt_template that a separate AI will use as its instruction set.
-as its instruction set.
 
-The extraction agent already has this base behaviour built in:
+Ask concise, focused questions one at a time.  Cover these topics (not necessarily in this order):
-  - Reads each file using file-system tools.
+  1. The type and format of the source content.
-  - Creates records (tasks, notes, timelines, projects) via CRUD tools.
+  2. Which data types to extract: tasks, notes, timelines, and/or projects.
-  - Sets isAiSuggested=1 on every new record.
+  3. How fields should be mapped (e.g. email subject → task title).
-  - Only extracts data explicitly present in the files — it never invents information.
+  4. Priority or status rules (e.g. "urgent" keyword → high priority).
-The user's custom prompt is appended AFTER this base behaviour, so focus on
+  5. Any special handling, date extraction, or exclusions.
-what to look for and how to map it — not on the general extraction mechanics.
 
-You have access to file-system tools to explore the user's directory:
+After 3-5 questions (when you have enough information), output the final prompt_template between \
-- list_directory: to see folder structure
+these exact markers on their own lines:
-- read_file_content: to peek at file contents
-- get_file_metadata: to check file info
-
-The user's configured directory is: {directory}
-Target data types: {data_types}
-
-IMPORTANT — project assignment is handled automatically by the main agent runner
-before the custom prompt is ever used.  You MUST NOT ask the user about projects,
-projectId, or how to link records to projects.  Never include projectId logic or
-project creation instructions in the generated prompt_template.
-
-Start by exploring the directory to understand its structure.  Then ask concise,
-focused questions one at a time.  Cover these topics (not necessarily in this order):
-  1. The type and format of the source content (confirmed by your exploration).
-  2. How fields should be mapped (e.g. filename → task title).
-  3. Priority or status rules (e.g. "urgent" keyword → high priority).
-  4. Any special handling, date extraction, or exclusions.
-
-Once you reach 90% confidence, output the final prompt_template between these exact
-markers on their own lines:
 
 {template_start}
 <the complete extraction prompt here>
 {template_end}
 
-The prompt_template must be a self-contained instruction for an AI that reads files
+The prompt_template must be a self-contained instruction for an AI that receives a document/email/message \
-and must perform CRUD operations using tools to create records.  It should specify:
+and must return a JSON array of records in this shape:
-  - What entity types to create (tasks, notes, timelines) — never projects.
+  [{{ "table": "<tasks|notes|timelines|projects>", "data": {{ <field: value> }} }}, ...]
-  - How to map file content to record fields (camelCase: title, status, priority,
-    dueDate, content, etc.) — never include projectId.
-  - That isAiSuggested must be set to 1 on every new record.
-  - Concrete examples of mappings based on what you discovered in the directory.
 
+Rules for the generated template:
+  - Be explicit about field names (camelCase: title, status, priority, dueDate, projectId, content, etc.).
+  - Include concrete examples of mappings.
+  - Mention that Electron adds id/createdAt/updatedAt automatically.
+  - Set isAiSuggested: true and isApproved: false on every record.
 {existing_section}\
-Keep asking clarifying questions until you are at least 90% confident you have
+Do not ask more than {max_turns} questions total. Start with your first question now.\
-enough information to generate an accurate prompt_template.  Once you reach that
-confidence level, stop asking and produce the final template immediately.
-Begin by exploring the directory, then ask your first question.\
 """
 
 
-def _build_system_prompt(
+def _build_system_prompt(agent_type: str, existing_template: str | None) -> str:
-    directory: str,
+    source_description = (
-    data_types: list[str],
+        "files in local directories" if agent_type == "local" else "emails and messages from cloud providers"
-    existing_template: str | None = None,
+    )
-) -> str:
     existing_section = (
         f"\nThe user already has the following prompt_template — refine it based on their answers:\n"
         f"---\n{existing_template}\n---\n"
@@ -154,14 +144,18 @@ def _build_system_prompt(
         else ""
     )
     return _SYSTEM_PROMPT_TEMPLATE.format(
-        directory=directory,
+        source_description=source_description,
-        data_types=", ".join(data_types),
         template_start=_TEMPLATE_START,
         template_end=_TEMPLATE_END,
         existing_section=existing_section,
+        max_turns=_MAX_TURNS,
     )
 
 
+def _first_question(agent_type: str) -> str:
+    return _LOCAL_PREAMBLE if agent_type == "local" else _CLOUD_PREAMBLE
+
+
 # ── Template extraction ───────────────────────────────────────────────────
 
 
@@ -174,37 +168,11 @@ def _extract_template(text: str) -> str | None:
     return text[start_idx:end_idx].strip() or None
 
 
-# ── LLM call with tool support ───────────────────────────────────────────
+# ── LLM call ─────────────────────────────────────────────────────────────
 
 
-def _as_text(content: Any) -> str:
+async def _call_llm(system_prompt: str, history: list[dict[str, Any]]) -> str:
-    if content is None:
+    """Build LangChain messages from history and invoke the LLM."""
-        return ""
-    if isinstance(content, str):
-        return content
-    if isinstance(content, list):
-        parts: list[str] = []
-        for item in content:
-            if isinstance(item, str):
-                parts.append(item)
-            elif isinstance(item, dict):
-                text = item.get("text")
-                if isinstance(text, str):
-                    parts.append(text)
-        return "".join(parts)
-    return str(content)
-
-
-async def _call_llm_with_tools(
-    system_prompt: str,
-    history: list[dict[str, Any]],
-    tools: list[Any],
-) -> str:
-    """Build LangChain messages from history and invoke the LLM with tools.
-
-    Handles tool-calling loops: if the LLM calls tools, execute them and
-    continue until a final text response is produced.
-    """
     messages: list[Any] = [SystemMessage(content=system_prompt)]
     for turn in history:
         if turn["role"] == "user":
@@ -213,194 +181,137 @@ async def _call_llm_with_tools(
             messages.append(AIMessage(content=turn["content"]))
 
     llm = get_llm(model=None, temperature=0.4)
-    llm_with_tools = llm.bind_tools(tools)
+    response = await llm.ainvoke(messages)
-    tool_map = {tool_def.name: tool_def for tool_def in tools}
+    return response.content  # type: ignore[return-value]
-
-    for _ in range(_MAX_TOOL_STEPS):
-        response: AIMessage = await llm_with_tools.ainvoke(messages)
-        messages.append(response)
-
-        if not response.tool_calls:
-            return _as_text(response.content)
-
-        for call in response.tool_calls:
-            call_name = str(call.get("name", ""))
-            call_args = call.get("args", {})
-            logger.info(
-                "agent_setup: journey tool_call name=%s args=%s",
-                call_name,
-                json.dumps(call_args, ensure_ascii=True)[:500],
-            )
-
-            tool_fn = tool_map.get(call_name)
-            if tool_fn is None:
-                tool_output = f"Unknown tool: {call_name}"
-            else:
-                tool_output = await tool_fn.ainvoke(call_args)
-
-            logger.info(
-                "agent_setup: journey tool_result name=%s output=%s",
-                call_name,
-                str(tool_output)[:800],
-            )
-            messages.append(ToolMessage(content=str(tool_output), tool_call_id=call["id"]))
-
-    # Fallback: exceeded max steps.
-    final = await llm.ainvoke(messages)
-    return _as_text(final.content)
 
 
-# ── Journey handlers (called from device_ws.py) ──────────────────────────
+# ── Existing-config loader ────────────────────────────────────────────────
 
 
-async def handle_journey_start(
+async def _load_existing_template(
+    agent_id: str,
     user_id: str,
-    frame: dict[str, Any],
+    db: AsyncSession,
-) -> dict[str, Any]:
+) -> str | None:
-    """Handle a ``journey_start`` WS frame.
+    """Return the prompt_template of an existing agent config, or None."""
+    # Try local first, then cloud.
+    local_result = await db.execute(
+        select(LocalAgentConfig).where(
+            LocalAgentConfig.id == agent_id,
+            LocalAgentConfig.user_id == user_id,
+        )
+    )
+    local = local_result.scalar_one_or_none()
+    if local is not None:
+        return local.prompt_template
 
-    Creates a session, runs the setup LLM with directory exploration,
+    cloud_result = await db.execute(
-    and returns the ``journey_reply`` payload.
+        select(CloudAgentConfig).where(
+            CloudAgentConfig.id == agent_id,
+            CloudAgentConfig.user_id == user_id,
+        )
+    )
+    cloud = cloud_result.scalar_one_or_none()
+    return cloud.prompt_template if cloud is not None else None
+
+
+# ── Routes ────────────────────────────────────────────────────────────────
+
+
+@router.post("/start", response_model=JourneyResponse, status_code=status.HTTP_200_OK)
+async def start_journey(
+    body: JourneyStartRequest,
+    current_user: UserProfile = Depends(get_current_user),
+    db: AsyncSession = Depends(get_session),
+) -> JourneyResponse:
+    """Start a new Chatbot Journey session.
+
+    If ``agent_id`` is provided the session is pre-seeded with the existing
+    agent's ``prompt_template`` so the user can refine it.
     """
-    agent_type = frame.get("agent_type", "local")
+    # Load existing template (may be None).
-    directory = frame.get("directory", "")
+    existing_template: str | None = None
-    data_types = frame.get("data_types", [])
+    if body.agent_id:
-    existing_template = frame.get("existing_template")
+        existing_template = await _load_existing_template(body.agent_id, current_user.id, db)
+        # If agent_id was given but not found, proceed without seeding (don't 404 —
+        # the user may be starting a fresh journey for a not-yet-persisted config).
 
-    # Use the session_id provided by the FE so the reply matches the
+    system_prompt = _build_system_prompt(body.agent_type, existing_template)
-    # listener key; fall back to a generated one if absent.
+    first_question = _first_question(body.agent_type)
-    session_id = frame.get("session_id") or str(uuid.uuid4())
-    system_prompt = _build_system_prompt(directory, data_types, existing_template)
 
-    session = JourneySession(
+    session_id = str(uuid.uuid4())
+    session = _JourneySession(
         session_id=session_id,
-        user_id=user_id,
+        user_id=current_user.id,
-        agent_type=agent_type,
+        agent_type=body.agent_type,
-        directory=directory,
+        # Seed history with the AI's first question so it stays consistent.
-        data_types=data_types,
+        history=[{"role": "assistant", "content": first_question}],
-        system_prompt=system_prompt,
     )
-
+    # Store the system prompt inside the session for reuse in /message.
-    # The LLM will explore the directory using FILESYSTEM_TOOLS via the
+    session.__dict__["_system_prompt"] = system_prompt  # type: ignore[index]
-    # ws_context executor (already set by the WS handler before calling us).
-    # Seed with an initial user message — some providers (e.g. GitHub Copilot)
-    # require at least one user/input message to be present.
-    seed_history: list[dict[str, Any]] = [
-        {"role": "user", "content": "Hi, I'm ready to set up my agent. Please explore my directory and ask me your first question."},
-    ]
-    ai_reply = await _call_llm_with_tools(
-        system_prompt=system_prompt,
-        history=seed_history,
-        tools=list(FILESYSTEM_TOOLS),
-    )
-
-    session.history.extend(seed_history)
-    session.history.append({"role": "assistant", "content": ai_reply})
     _sessions[session_id] = session
 
-    logger.info(
+    logger.info("Journey session %s started for user %s (agent_type=%s)", session_id, current_user.id, body.agent_type)
-        "agent_setup: journey session %s started for user %s (directory=%s)",
+    return JourneyResponse(session_id=session_id, message=first_question, done=False)
-        session_id,
-        user_id,
-        directory,
-    )
-
-    # Check if the LLM produced the template on the first turn (unlikely but possible).
-    prompt_template = _extract_template(ai_reply)
-    done = prompt_template is not None
-
-    display_message = ai_reply
-    if done:
-        display_message = (
-            ai_reply[: ai_reply.index(_TEMPLATE_START)].strip()
-            or "Here is your agent configuration. You can save it or continue refining."
-        )
-        _sessions.pop(session_id, None)
-
-    return {
-        "type": "journey_reply",
-        "session_id": session_id,
-        "message": display_message,
-        "done": done,
-        "prompt_template": prompt_template,
-    }
 
 
-async def handle_journey_message(
+@router.post("/message", response_model=JourneyResponse, status_code=status.HTTP_200_OK)
-    user_id: str,
+async def send_journey_message(
-    frame: dict[str, Any],
+    body: JourneyMessageRequest,
-) -> dict[str, Any]:
+    current_user: UserProfile = Depends(get_current_user),
-    """Handle a ``journey_message`` WS frame.
+    db: AsyncSession = Depends(get_session),
+) -> JourneyResponse:
+    """Send a message in an existing Chatbot Journey session.
 
-    Appends the user message, calls the LLM, and returns the
+    The server appends the user's message to the conversation history,
-    ``journey_reply`` payload.
+    calls the LLM, and appends the AI reply.  When the LLM wraps up with a
+    ``prompt_template`` block the response includes ``done=True`` and the
+    extracted template.
     """
-    session_id = frame.get("session_id", "")
+    session = _get_session(body.session_id, current_user.id)
-    message = frame.get("message", "")
+    system_prompt: str = session.__dict__.get("_system_prompt", _build_system_prompt(session.agent_type, None))  # type: ignore[assignment]
 
-    session = get_journey_session(session_id, user_id)
+    # Append user turn to history.
-    if session is None:
+    session.history.append({"role": "user", "content": body.message})
-        return {
-            "type": "journey_reply",
-            "session_id": session_id,
-            "message": "Journey session not found or expired. Please start a new setup.",
-            "done": True,
-            "prompt_template": None,
-        }
 
-    # Append user turn.
+    # Call the LLM with the full conversation so far.
-    session.history.append({"role": "user", "content": message})
+    ai_reply = await _call_llm(system_prompt, session.history)
-
-    # Call the LLM with tools.
-    ai_reply = await _call_llm_with_tools(
-        system_prompt=session.system_prompt,
-        history=session.history,
-        tools=list(FILESYSTEM_TOOLS),
-    )
 
+    # Append AI turn.
     session.history.append({"role": "assistant", "content": ai_reply})
 
     # Check if the LLM produced the final template.
     prompt_template = _extract_template(ai_reply)
     done = prompt_template is not None
 
-    # If the LLM didn't produce a template, nudge it once it has asked enough
+    # Strip the sentinel markers from the message shown to the user.
-    # questions (>= _MIN_TURNS_BEFORE_NUDGE) or hits the hard safety cap.
-    if not done:
-        turns = sum(1 for t in session.history if t["role"] == "user")
-        if turns >= _MAX_TURNS:
-            nudge_content = (
-                "[System: You have enough information. Please generate the final "
-                f"prompt_template now, wrapped in {_TEMPLATE_START} / {_TEMPLATE_END} markers.]"
-            )
-            session.history.append({"role": "user", "content": nudge_content})
-
-            nudge_reply = await _call_llm_with_tools(
-                system_prompt=session.system_prompt,
-                history=session.history,
-                tools=list(FILESYSTEM_TOOLS),
-            )
-            session.history.append({"role": "assistant", "content": nudge_reply})
-
-            prompt_template = _extract_template(nudge_reply)
-            if prompt_template is not None:
-                done = True
-                ai_reply = nudge_reply
-
     display_message = ai_reply
     if done:
         display_message = (
             ai_reply[: ai_reply.index(_TEMPLATE_START)].strip()
-            if _TEMPLATE_START in ai_reply
+            or "Here is your agent configuration. You can save it or continue refining."
-            else "Here is your agent configuration. You can save it or continue refining."
         )
-        _sessions.pop(session_id, None)
-        logger.info("agent_setup: journey session %s completed for user %s", session_id, user_id)
 
-    return {
+    if done:
-        "type": "journey_reply",
+        logger.info("Journey session %s completed for user %s", body.session_id, current_user.id)
-        "session_id": session_id,
+        # Clean up the session immediately on completion.
-        "message": display_message,
+        _sessions.pop(body.session_id, None)
-        "done": done,
+    else:
-        "prompt_template": prompt_template,
+        # Nudge the LLM to wrap up after max turns.
-    }
+        turns = sum(1 for t in session.history if t["role"] == "user")
+        if turns >= _MAX_TURNS:
+            # Add a system-level nudge as a hidden user message.
+            session.history.append({
+                "role": "user",
+                "content": (
+                    "[System: You have enough information. Please generate the final "
+                    f"prompt_template now, wrapped in {_TEMPLATE_START} / {_TEMPLATE_END} markers.]"
+                ),
+            })
+
+    return JourneyResponse(
+        session_id=body.session_id,
+        message=display_message,
+        done=done,
+        prompt_template=prompt_template,
+    )

app/api/routes/agents.py

@@ -1,36 +1,45 @@
-"""Agent routes.
+"""Agent CRUD routes: local directory agents and cloud connector agents.
 
-Backend responsibilities are intentionally minimal:
+Endpoints:
-    GET  /agents/catalog         — static catalog for UI display
+  GET    /agents/catalog            — hardcoded agent type catalog
-    POST /agents/can-create      — billing eligibility check
+  GET    /agents/local              — list user's local agent configs
-    POST /agents/trigger         — trigger a local agent run
+  POST   /agents/local              — create local agent (tier-gated)
-
+  PUT    /agents/local/{agent_id}   — partial update (ownership check)
-Agent configuration is owned by the Electron app and is not persisted
+  DELETE /agents/local/{agent_id}   — delete + cascade run logs
-in backend agent-config tables.
+  GET    /agents/cloud              — list user's cloud agent configs
+  POST   /agents/cloud              — create cloud agent (tier-gated)
+  PUT    /agents/cloud/{agent_id}   — partial update (ownership check)
+  DELETE /agents/cloud/{agent_id}   — delete + cascade run logs
+  GET    /agents/runs               — paginated run logs (agent_id, page, limit)
+  POST   /agents/{agent_id}/run     — manual trigger stub (dispatch in Step 3.4)
 """
 
 from __future__ import annotations
 
 import asyncio
-import uuid
+from datetime import datetime
-from datetime import datetime, timedelta, timezone
+from typing import Any
 
-from fastapi import APIRouter, Depends, HTTPException, status
+from fastapi import APIRouter, Depends, HTTPException, Query, status
-from sqlalchemy import func, select
+from pydantic import BaseModel
+from sqlalchemy import func, or_, select
 from sqlalchemy.ext.asyncio import AsyncSession
 
 from app.api.deps import get_current_user
 from app.billing.tier_manager import FEATURES
-from app.core.agent_runner import is_agent_running, run_local_agent
+from app.core.agent_runner import run_cloud_agent, run_local_agent
 from app.core.device_manager import device_manager
 from app.db import get_session
-from app.models import AgentRunLog, LocalAgentConfig
+from app.models import AgentRunLog, CloudAgentConfig, LocalAgentConfig
 from app.schemas import (
     AgentCatalogItem,
-    AgentCreationCheckRequest,
-    AgentCreationCheckResponse,
     AgentRunLogResponse,
-    AgentTriggerRequest,
+    CloudAgentConfigCreate,
+    CloudAgentConfigResponse,
+    CloudAgentConfigUpdate,
+    LocalAgentConfigCreate,
+    LocalAgentConfigResponse,
+    LocalAgentConfigUpdate,
     UserProfile,
 )
 
@@ -47,21 +56,39 @@ def _dt_ms_opt(dt: datetime | None) -> int | None:
     return int(dt.timestamp() * 1000) if dt else None
 
 
-def _to_data_types(values: list[str]) -> list[str]:
+# ── Model → schema converters ─────────────────────────────────────────
-    normalize = {
+
-        "task": "tasks",           "tasks": "tasks",
+def _to_local_response(a: LocalAgentConfig) -> LocalAgentConfigResponse:
-        "note": "notes",           "notes": "notes",
+    return LocalAgentConfigResponse(
-        "timeline": "timelines",   "timelines": "timelines",   "timelineEvents": "timelines",
+        id=a.id,
-        "project": "projects",     "projects": "projects",
+        name=a.name,
-    }
+        device_id=a.device_id,
-    seen: set[str] = set()
+        directory_paths=a.directory_paths,
-    result: list[str] = []
+        data_types=a.data_types,
-    for v in values:
+        prompt_template=a.prompt_template,
-        mapped = normalize.get(v)
+        file_extensions=a.file_extensions,
-        if mapped and mapped not in seen:
+        schedule_cron=a.schedule_cron,
-            seen.add(mapped)
+        enabled=a.enabled,
-            result.append(mapped)
+        last_run_at=_dt_ms_opt(a.last_run_at),
-    return result
+        created_at=_dt_ms(a.created_at),
+        updated_at=_dt_ms(a.updated_at),
+    )
+
+
+def _to_cloud_response(a: CloudAgentConfig) -> CloudAgentConfigResponse:
+    return CloudAgentConfigResponse(
+        id=a.id,
+        provider=a.provider,  # type: ignore[arg-type]
+        name=a.name,
+        data_types=a.data_types,
+        prompt_template=a.prompt_template,
+        schedule_cron=a.schedule_cron,
+        filter_config=a.filter_config,
+        enabled=a.enabled,
+        last_run_at=_dt_ms_opt(a.last_run_at),
+        created_at=_dt_ms(a.created_at),
+        updated_at=_dt_ms(a.updated_at),
+    )
 
 
 def _to_run_log_response(log: AgentRunLog) -> AgentRunLogResponse:
@@ -78,42 +105,77 @@ def _to_run_log_response(log: AgentRunLog) -> AgentRunLogResponse:
     )
 
 
-def _enforce_agent_limit(tier: str, current_count: int) -> int:
+# ── Ownership-checked lookups ─────────────────────────────────────────
+
+async def _get_local_agent_for_user(
+    agent_id: str, user_id: str, db: AsyncSession
+) -> LocalAgentConfig:
+    result = await db.execute(
+        select(LocalAgentConfig).where(
+            LocalAgentConfig.id == agent_id,
+            LocalAgentConfig.user_id == user_id,
+        )
+    )
+    record = result.scalar_one_or_none()
+    if record is None:
+        raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail="Agent not found")
+    return record
+
+
+async def _get_cloud_agent_for_user(
+    agent_id: str, user_id: str, db: AsyncSession
+) -> CloudAgentConfig:
+    result = await db.execute(
+        select(CloudAgentConfig).where(
+            CloudAgentConfig.id == agent_id,
+            CloudAgentConfig.user_id == user_id,
+        )
+    )
+    record = result.scalar_one_or_none()
+    if record is None:
+        raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail="Agent not found")
+    return record
+
+
+# ── Tier limit helper ─────────────────────────────────────────────────
+
+async def _count_enabled_agents(user_id: str, db: AsyncSession) -> int:
+    """Return combined enabled local + cloud agent count for the user."""
+    local_count = (
+        await db.execute(
+            select(func.count(LocalAgentConfig.id)).where(
+                LocalAgentConfig.user_id == user_id,
+                LocalAgentConfig.enabled == True,  # noqa: E712
+            )
+        )
+    ).scalar_one()
+    cloud_count = (
+        await db.execute(
+            select(func.count(CloudAgentConfig.id)).where(
+                CloudAgentConfig.user_id == user_id,
+                CloudAgentConfig.enabled == True,  # noqa: E712
+            )
+        )
+    ).scalar_one()
+    return local_count + cloud_count
+
+
+def _enforce_agent_limit(tier: str, current_count: int) -> None:
     limit: int = FEATURES.get(tier, FEATURES["free"])["batch_active"]
     if limit != -1 and current_count >= limit:
         raise HTTPException(
             status_code=status.HTTP_403_FORBIDDEN,
             detail=f"Agent limit ({limit}) reached for your tier. Upgrade to create more.",
         )
-    return limit
 
 
-async def _enforce_run_frequency(
+# ── Local page schema (used by runs endpoint) ─────────────────────────
-    tier: str,
-    user_id: str,
-    db: AsyncSession,
-) -> None:
-    """Raise HTTP 402 if the user has exceeded their daily batch run limit."""
-    limit: int = FEATURES.get(tier, FEATURES["free"])["batch_runs_per_day"]
-    if limit == -1:
-        return  # unlimited
 
-    today_start = datetime.now(timezone.utc).replace(
+class _RunsPage(BaseModel):
-        hour=0, minute=0, second=0, microsecond=0
+    total: int
-    )
+    page: int
-    result = await db.execute(
+    limit: int
-        select(func.count(AgentRunLog.id)).where(
+    items: list[AgentRunLogResponse]
-            AgentRunLog.user_id == user_id,
-            AgentRunLog.started_at >= today_start,
-        )
-    )
-    runs_today: int = result.scalar_one()
-
-    if runs_today >= limit:
-        raise HTTPException(
-            status_code=status.HTTP_402_PAYMENT_REQUIRED,
-            detail=f"Daily batch run limit ({limit}) reached for your tier. Upgrade for more runs.",
-        )
 
 
 # ── Catalog ───────────────────────────────────────────────────────────
@@ -147,61 +209,229 @@ async def get_agent_catalog(
     ]
 
 
-@router.post("/can-create", response_model=AgentCreationCheckResponse)
+# ── Local agent CRUD ──────────────────────────────────────────────────
-async def can_create_agent(
+
-    body: AgentCreationCheckRequest,
+@router.get("/local", response_model=list[LocalAgentConfigResponse])
+async def list_local_agents(
     current_user: UserProfile = Depends(get_current_user),
-) -> AgentCreationCheckResponse:
+    db: AsyncSession = Depends(get_session),
-    """Check if the user can create one more agent based on billing tier.
+) -> list[LocalAgentConfigResponse]:
-
+    """List all local directory agent configs owned by the authenticated user."""
-    Since configuration is client-owned, the Electron app sends its current
+    result = await db.execute(
-    active agent count and the backend applies tier limits.
+        select(LocalAgentConfig).where(LocalAgentConfig.user_id == current_user.id)
-    """
-    limit: int = FEATURES.get(current_user.tier, FEATURES["free"])["batch_active"]
-    allowed = limit == -1 or body.active_agents < limit
-    return AgentCreationCheckResponse(
-        allowed=allowed,
-        tier=current_user.tier,
-        active_agents=body.active_agents,
-        limit=limit,
     )
+    return [_to_local_response(a) for a in result.scalars().all()]
 
 
-@router.post("/trigger", response_model=AgentRunLogResponse, status_code=status.HTTP_202_ACCEPTED)
+@router.post("/local", response_model=LocalAgentConfigResponse, status_code=status.HTTP_201_CREATED)
+async def create_local_agent(
+    body: LocalAgentConfigCreate,
+    current_user: UserProfile = Depends(get_current_user),
+    db: AsyncSession = Depends(get_session),
+) -> LocalAgentConfigResponse:
+    """Create a new local directory agent config.
+
+    The combined count of enabled local and cloud agents for the user is
+    checked against the ``batch_active`` limit for their billing tier.
+    """
+    _enforce_agent_limit(current_user.tier, await _count_enabled_agents(current_user.id, db))
+    agent = LocalAgentConfig(
+        user_id=current_user.id,
+        name=body.name,
+        device_id=body.device_id,
+        directory_paths=body.directory_paths,
+        data_types=body.data_types,
+        prompt_template=body.prompt_template,
+        file_extensions=body.file_extensions,
+        schedule_cron=body.schedule_cron,
+    )
+    db.add(agent)
+    await db.commit()
+    await db.refresh(agent)
+    return _to_local_response(agent)
+
+
+@router.put("/local/{agent_id}", response_model=LocalAgentConfigResponse)
+async def update_local_agent(
+    agent_id: str,
+    body: LocalAgentConfigUpdate,
+    current_user: UserProfile = Depends(get_current_user),
+    db: AsyncSession = Depends(get_session),
+) -> LocalAgentConfigResponse:
+    """Partially update a local agent config. Only provided fields are changed."""
+    agent = await _get_local_agent_for_user(agent_id, current_user.id, db)
+    for field, value in body.model_dump(exclude_unset=True).items():
+        setattr(agent, field, value)
+    await db.commit()
+    await db.refresh(agent)
+    return _to_local_response(agent)
+
+
+@router.delete("/local/{agent_id}", response_model=dict)
+async def delete_local_agent(
+    agent_id: str,
+    current_user: UserProfile = Depends(get_current_user),
+    db: AsyncSession = Depends(get_session),
+) -> dict[str, bool]:
+    """Delete a local agent config. Associated run logs are cascade-deleted."""
+    agent = await _get_local_agent_for_user(agent_id, current_user.id, db)
+    await db.delete(agent)
+    await db.commit()
+    return {"ok": True}
+
+
+# ── Cloud agent CRUD ──────────────────────────────────────────────────
+
+@router.get("/cloud", response_model=list[CloudAgentConfigResponse])
+async def list_cloud_agents(
+    current_user: UserProfile = Depends(get_current_user),
+    db: AsyncSession = Depends(get_session),
+) -> list[CloudAgentConfigResponse]:
+    """List all cloud connector agent configs owned by the authenticated user."""
+    result = await db.execute(
+        select(CloudAgentConfig).where(CloudAgentConfig.user_id == current_user.id)
+    )
+    return [_to_cloud_response(a) for a in result.scalars().all()]
+
+
+@router.post("/cloud", response_model=CloudAgentConfigResponse, status_code=status.HTTP_201_CREATED)
+async def create_cloud_agent(
+    body: CloudAgentConfigCreate,
+    current_user: UserProfile = Depends(get_current_user),
+    db: AsyncSession = Depends(get_session),
+) -> CloudAgentConfigResponse:
+    """Create a new cloud connector agent config.
+
+    The combined count of enabled local and cloud agents for the user is
+    checked against the ``batch_active`` limit for their billing tier.
+    """
+    _enforce_agent_limit(current_user.tier, await _count_enabled_agents(current_user.id, db))
+    agent = CloudAgentConfig(
+        user_id=current_user.id,
+        provider=body.provider,
+        name=body.name,
+        data_types=body.data_types,
+        prompt_template=body.prompt_template,
+        oauth_token_encrypted=body.oauth_token_encrypted,
+        schedule_cron=body.schedule_cron,
+        filter_config=body.filter_config,
+    )
+    db.add(agent)
+    await db.commit()
+    await db.refresh(agent)
+    return _to_cloud_response(agent)
+
+
+@router.put("/cloud/{agent_id}", response_model=CloudAgentConfigResponse)
+async def update_cloud_agent(
+    agent_id: str,
+    body: CloudAgentConfigUpdate,
+    current_user: UserProfile = Depends(get_current_user),
+    db: AsyncSession = Depends(get_session),
+) -> CloudAgentConfigResponse:
+    """Partially update a cloud agent config. Only provided fields are changed."""
+    agent = await _get_cloud_agent_for_user(agent_id, current_user.id, db)
+    for field, value in body.model_dump(exclude_unset=True).items():
+        setattr(agent, field, value)
+    await db.commit()
+    await db.refresh(agent)
+    return _to_cloud_response(agent)
+
+
+@router.delete("/cloud/{agent_id}", response_model=dict)
+async def delete_cloud_agent(
+    agent_id: str,
+    current_user: UserProfile = Depends(get_current_user),
+    db: AsyncSession = Depends(get_session),
+) -> dict[str, bool]:
+    """Delete a cloud agent config. Associated run logs are cascade-deleted."""
+    agent = await _get_cloud_agent_for_user(agent_id, current_user.id, db)
+    await db.delete(agent)
+    await db.commit()
+    return {"ok": True}
+
+
+# ── Run logs ──────────────────────────────────────────────────────────
+
+@router.get("/runs", response_model=_RunsPage)
+async def list_run_logs(
+    agent_id: str | None = Query(default=None),
+    page: int = Query(default=1, ge=1),
+    limit: int = Query(default=20, ge=1, le=100),
+    current_user: UserProfile = Depends(get_current_user),
+    db: AsyncSession = Depends(get_session),
+) -> _RunsPage:
+    """Return paginated run logs for the authenticated user.
+
+    Optionally filter by ``agent_id``. Results are ordered from newest to oldest.
+    """
+    base_filter = [AgentRunLog.user_id == current_user.id]
+    if agent_id:
+        base_filter.append(AgentRunLog.agent_id == agent_id)
+
+    total = (
+        await db.execute(select(func.count(AgentRunLog.id)).where(*base_filter))
+    ).scalar_one()
+
+    result = await db.execute(
+        select(AgentRunLog)
+        .where(*base_filter)
+        .order_by(AgentRunLog.started_at.desc())
+        .offset((page - 1) * limit)
+        .limit(limit)
+    )
+    items = [_to_run_log_response(log) for log in result.scalars().all()]
+
+    return _RunsPage(total=total, page=page, limit=limit, items=items)
+
+
+# ── Manual trigger stub ───────────────────────────────────────────────
+
+@router.post("/{agent_id}/run", response_model=AgentRunLogResponse, status_code=status.HTTP_202_ACCEPTED)
 async def trigger_agent_run(
-    body: AgentTriggerRequest,
+    agent_id: str,
     current_user: UserProfile = Depends(get_current_user),
     db: AsyncSession = Depends(get_session),
 ) -> AgentRunLogResponse:
-    """Trigger a local agent run using client-provided configuration."""
+    """Manually trigger an agent run.
-    _enforce_agent_limit(current_user.tier, body.active_agents)
-    await _enforce_run_frequency(current_user.tier, current_user.id, db)
 
-    config = LocalAgentConfig(
+    Looks up the agent config (local or cloud) by ID with ownership check,
-        id=str(uuid.uuid4()),
+    creates a run log entry with ``status="running"``, and returns it.
-        user_id=current_user.id,
-        device_id=body.device_id,
-        name="Local Directory Monitor",
-        directory_paths=[body.directory],
-        data_types=_to_data_types(body.what_to_extract),
-        prompt_template=body.custom_agent_prompt,
-        file_extensions=[],
-        schedule_cron=body.batch_interval,
-        enabled=True,
-    )
 
-    # Use the FE's stable agent_id if provided, fall back to the ephemeral config id.
+    Actual dispatch to the agent runner is wired in Step 3.4 once
-    stable_agent_id = body.agent_id or config.id
+    ``DeviceConnectionManager`` and ``agent_runner`` are available.
+    """
+    # Determine agent type by trying local first, then cloud.
+    # Keep the full config object so we can pass it to the agent runner.
+    local_config: LocalAgentConfig | None = None
+    cloud_config: CloudAgentConfig | None = None
 
-    if is_agent_running(stable_agent_id):
+    local_result = await db.execute(
-        raise HTTPException(
+        select(LocalAgentConfig).where(
-            status_code=status.HTTP_409_CONFLICT,
+            LocalAgentConfig.id == agent_id,
-            detail="Agent is already running. Only one run per agent is allowed at a time.",
+            LocalAgentConfig.user_id == current_user.id,
         )
+    )
+    local_config = local_result.scalar_one_or_none()
+
+    if local_config is not None:
+        agent_type = "local"
+    else:
+        cloud_result = await db.execute(
+            select(CloudAgentConfig).where(
+                CloudAgentConfig.id == agent_id,
+                CloudAgentConfig.user_id == current_user.id,
+            )
+        )
+        cloud_config = cloud_result.scalar_one_or_none()
+        if cloud_config is not None:
+            agent_type = "cloud"
+        else:
+            raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail="Agent not found")
 
     run_log = AgentRunLog(
-        agent_id=stable_agent_id,
+        agent_id=agent_id,
-        agent_type="local",
+        agent_type=agent_type,
         user_id=current_user.id,
         status="running",
     )
@@ -209,14 +439,14 @@ async def trigger_agent_run(
     await db.commit()
     await db.refresh(run_log)
 
-    run_context = {
+    # Dispatch the run as a background task — returns 202 immediately.
-        "type": "agent_batch",
+    if agent_type == "local" and local_config is not None:
-        "run_id": run_log.id,
+        asyncio.create_task(
-        "agent_id": stable_agent_id,
+            run_local_agent(current_user.id, local_config, run_log, device_manager)
-    }
+        )
-
+    elif agent_type == "cloud" and cloud_config is not None:
-    asyncio.create_task(
+        asyncio.create_task(
-        run_local_agent(current_user.id, config, run_log, device_manager, run_context)
+            run_cloud_agent(current_user.id, cloud_config, run_log, device_manager)
-    )
+        )
 
     return _to_run_log_response(run_log)

app/api/routes/chat.py

@@ -10,7 +10,9 @@ from fastapi.responses import JSONResponse
 
 from app.api.deps import get_current_user
 from app.core.deep_agent import run_home
-from app.schemas import ChatRequest, UserProfile
+from app.core.memory_middleware import MemoryMiddleware
+from app.db import async_session
+from app.schemas import ChatRequest, ChatResponse, UserProfile
 
 router = APIRouter(prefix="/chat", tags=["chat"])
 
@@ -20,10 +22,21 @@ async def chat(
     body: ChatRequest,
     current_user: UserProfile = Depends(get_current_user),
 ) -> JSONResponse:
-    """REST fallback for home chat when websocket streaming is unavailable."""
+    """Route a chat message through the Home deep agent (non-streaming)."""
-    response = await run_home(
+    async with async_session() as db:
+        memory = MemoryMiddleware(db)
+        memory_context = await memory.enrich_context(current_user.id, body.message)
+
+    context = {
+        **body.context.model_dump(),
+        **memory_context,
+    }
+
+    response_text = await run_home(
         user_id=current_user.id,
         message=body.message,
-        context=body.context.model_dump(),
+        context=context,
+        db_session_factory=async_session,
     )
-    return JSONResponse(content={"response": response})
+    result = ChatResponse(response=response_text)
+    return JSONResponse(content=result.model_dump())

app/api/routes/device_ws.py

@@ -14,11 +14,11 @@ Protocol:
   4. Session enters message dispatch loop + heartbeat.
 
 Incoming frame dispatch:
-  - ``tool_result``      → resolves a pending tool-call Future.
+  - ``tool_result``    → resolves a pending tool-call Future.
-  - ``journey_start``    → starts a guided setup journey session.
+  - ``agent_data``     → enqueued in the per-run agent data queue.
-  - ``journey_message``  → continues a journey conversation.
+  - ``agent_complete`` → sends None sentinel to close the queue stream.
-  - ``pong``             → heartbeat acknowledgement (updates last-seen).
+  - ``pong``           → heartbeat acknowledgement (updates last-seen).
-  - unknown types        → logged, ignored.
+  - unknown types      → logged, ignored.
 
 Outgoing heartbeat: ``{ "type": "ping" }`` every 30 s.
 
@@ -39,13 +39,12 @@ from fastapi import APIRouter, WebSocket, WebSocketDisconnect
 from jose import JWTError, jwt
 from sqlalchemy import update
 
-from app.api.routes.agent_setup import handle_journey_message, handle_journey_start
 from app.config.settings import settings
 from app.core.agent_runner import trigger_pending_runs
-from app.core.deep_agent import run_floating_stream, run_home_stream
 from app.core.device_manager import device_manager
 from app.core.memory_middleware import MemoryMiddleware
-from app.core.output_formatter import StreamFormatter
+from app.core.deep_agent import run_home_stream, run_floating_stream
+from app.core.output_formatter import HomeFormatter, FloatingFormatter
 from app.core.ws_context import clear_client_executor, set_client_executor
 from app.db import async_session
 from app.models import AgentRunLog
@@ -148,6 +147,37 @@ async def _message_loop(websocket: WebSocket, user_id: str) -> None:
                     "device_ws: tool_result missing id from user=%s", user_id
                 )
 
+        elif frame_type == WsFrameType.agent_data:
+            run_id = frame.get("run_id")
+            if run_id:
+                try:
+                    queue = device_manager.get_agent_data_queue(user_id, run_id)
+                    await queue.put(frame)
+                except RuntimeError:
+                    logger.warning(
+                        "device_ws: agent_data for unknown run user=%s run=%s",
+                        user_id,
+                        run_id,
+                    )
+            else:
+                logger.warning(
+                    "device_ws: agent_data missing run_id from user=%s", user_id
+                )
+
+        elif frame_type == WsFrameType.agent_complete:
+            run_id = frame.get("run_id")
+            if run_id:
+                try:
+                    queue = device_manager.get_agent_data_queue(user_id, run_id)
+                    # Sentinel: signals the agent data stream is finished.
+                    await queue.put(None)
+                except RuntimeError:
+                    pass
+            else:
+                logger.warning(
+                    "device_ws: agent_complete missing run_id from user=%s", user_id
+                )
+
         elif frame_type == WsFrameType.home_request:
             asyncio.create_task(
                 _handle_home_request(websocket, user_id, frame)
@@ -158,16 +188,6 @@ async def _message_loop(websocket: WebSocket, user_id: str) -> None:
                 _handle_floating_request(websocket, user_id, frame)
             )
 
-        elif frame_type == WsFrameType.journey_start:
-            asyncio.create_task(
-                _handle_journey_start(websocket, user_id, frame)
-            )
-
-        elif frame_type == WsFrameType.journey_message:
-            asyncio.create_task(
-                _handle_journey_message(websocket, user_id, frame)
-            )
-
         elif frame_type == "pong":
             # Heartbeat ack — nothing to do, connection is alive.
             pass
@@ -180,13 +200,35 @@ async def _message_loop(websocket: WebSocket, user_id: str) -> None:
 
 # ── v3 Chat Handlers ──────────────────────────────────────────────────
 
+_WS_TOOL_CALL_TIMEOUT = 30  # seconds to wait for Electron tool_result
+
+
 async def _make_ws_executor(websocket: WebSocket, user_id: str):
     """Return a callback that sends tool_call frames and awaits tool_result."""
     async def _executor(payload: dict) -> dict:
         payload["type"] = WsFrameType.tool_call
+        call_id = payload["id"]
+        logger.info("ws_executor: sending tool_call id=%s action=%s", call_id, payload.get("action"))
         await websocket.send_text(json.dumps(payload))
-        future = device_manager.create_pending_call(user_id, payload["id"])
+        future = device_manager.create_pending_call(user_id, call_id)
-        return await future
+        try:
+            result = await asyncio.wait_for(future, timeout=_WS_TOOL_CALL_TIMEOUT)
+        except asyncio.TimeoutError:
+            logger.error(
+                "ws_executor: timeout waiting for tool_result id=%s action=%s user=%s",
+                call_id, payload.get("action"), user_id,
+            )
+            # Clean up the pending future so it doesn't leak
+            conn = device_manager._connections.get(user_id)
+            if conn:
+                conn.pending_calls.pop(call_id, None)
+            return {"error": f"Tool call timed out after {_WS_TOOL_CALL_TIMEOUT}s", "rows": []}
+        logger.info("ws_executor: tool_result id=%s result_type=%s result_keys=%s",
+                     call_id, type(result).__name__,
+                     list(result.keys()) if isinstance(result, dict) else "N/A")
+        if result is None:
+            logger.error("ws_executor: future resolved to None for call_id=%s user=%s", call_id, user_id)
+        return result
     return _executor
 
 
@@ -199,27 +241,14 @@ async def _handle_home_request(
     request_id = frame.get("request_id") or str(uuid4())
     message: str = frame.get("message", "")
     session_id: str = frame.get("session_id") or str(uuid4())
-    logger.info(
-        "device_ws: home_request_start user=%s req=%s session=%s msg=%s",
-        user_id,
-        request_id,
-        session_id,
-        message[:200],
-    )
 
     # ── Memory: enrich context before LLM call ────────────────────────
     async with async_session() as db:
         memory = MemoryMiddleware(db)
-        memory_context = await memory.enrich_context(
+        memory_context = await memory.enrich_context(user_id, message)
-            user_id,
-            message,
-            trace_id=request_id,
-            session_id=session_id,
-        )
 
     context: dict = {
         "conversation_history": frame.get("conversation_history", []),
-        "_debug": {"request_id": request_id, "session_id": session_id, "user_id": user_id},
         **memory_context,
     }
 
@@ -227,11 +256,12 @@ async def _handle_home_request(
     set_client_executor(executor)
     response_chunks: list[str] = []
     try:
-        event_stream = run_home_stream(user_id, message, context)
+        event_stream = run_home_stream(
-        formatter = StreamFormatter(request_id=request_id)
+            user_id, message, context, db_session_factory=async_session
+        )
+        formatter = HomeFormatter(request_id=request_id)
         async for ws_frame in formatter.format(event_stream):
             await websocket.send_text(ws_frame.model_dump_json())
-            # Collect text chunks to build the full response for episode storage
             if ws_frame.type == "stream_text":  # type: ignore[union-attr]
                 response_chunks.append(ws_frame.chunk)  # type: ignore[union-attr]
     except Exception as exc:
@@ -246,15 +276,8 @@ async def _handle_home_request(
     async with async_session() as db:
         memory = MemoryMiddleware(db)
         await memory.store_episode(
-            user_id, session_id, message, "".join(response_chunks), trace_id=request_id
+            user_id, session_id, message, "".join(response_chunks)
         )
-    logger.info(
-        "device_ws: home_request_end user=%s req=%s session=%s response_chars=%d",
-        user_id,
-        request_id,
-        session_id,
-        len("".join(response_chunks)),
-    )
 
 
 async def _handle_floating_request(
@@ -267,37 +290,23 @@ async def _handle_floating_request(
     message: str = frame.get("message", "")
     session_id: str = frame.get("session_id") or str(uuid4())
     scope: dict = frame.get("scope", {})
-    logger.info(
-        "device_ws: floating_request_start user=%s req=%s session=%s scope=%s msg=%s",
-        user_id,
-        request_id,
-        session_id,
-        json.dumps(scope, ensure_ascii=True)[:200],
-        message[:200],
-    )
 
     # ── Memory: enrich context before LLM call ────────────────────────
     async with async_session() as db:
         memory = MemoryMiddleware(db)
-        memory_context = await memory.enrich_context(
+        memory_context = await memory.enrich_context(user_id, message)
-            user_id,
-            message,
-            trace_id=request_id,
-            session_id=session_id,
-        )
 
-    context: dict = {
+    context: dict = {"scope": scope, **memory_context}
-        "scope": scope,
-        "_debug": {"request_id": request_id, "session_id": session_id, "user_id": user_id},
-        **memory_context,
-    }
 
     executor = await _make_ws_executor(websocket, user_id)
     set_client_executor(executor)
     response_chunks: list[str] = []
     try:
-        event_stream = run_floating_stream(user_id, message, context)
+        event_stream = run_floating_stream(
-        formatter = StreamFormatter(request_id=request_id)
+            user_id, message, context, scope=scope,
+            db_session_factory=async_session,
+        )
+        formatter = FloatingFormatter(request_id=request_id)
         async for ws_frame in formatter.format(event_stream):
             await websocket.send_text(ws_frame.model_dump_json())
             if ws_frame.type == "stream_text":  # type: ignore[union-attr]
@@ -314,72 +323,8 @@ async def _handle_floating_request(
     async with async_session() as db:
         memory = MemoryMiddleware(db)
         await memory.store_episode(
-            user_id, session_id, message, "".join(response_chunks), trace_id=request_id
+            user_id, session_id, message, "".join(response_chunks)
         )
-    logger.info(
-        "device_ws: floating_request_end user=%s req=%s session=%s response_chars=%d",
-        user_id,
-        request_id,
-        session_id,
-        len("".join(response_chunks)),
-    )
-
-
-# ── v4 Journey Handlers ─────────────────────────────────────────────
-
-
-async def _handle_journey_start(
-    websocket: WebSocket,
-    user_id: str,
-    frame: dict,
-) -> None:
-    """Handle a journey_start frame — explores directory and sends first question."""
-    executor = await _make_ws_executor(websocket, user_id)
-    set_client_executor(executor)
-    try:
-        reply = await handle_journey_start(user_id, frame)
-        await websocket.send_text(json.dumps(reply))
-    except Exception as exc:
-        logger.error(
-            "device_ws: journey_start failed user=%s: %s", user_id, exc
-        )
-        await websocket.send_text(json.dumps({
-            "type": "journey_reply",
-            "session_id": frame.get("session_id", ""),
-            "message": f"Failed to start journey: {exc}",
-            "done": True,
-            "prompt_template": None,
-        }))
-    finally:
-        clear_client_executor()
-
-
-async def _handle_journey_message(
-    websocket: WebSocket,
-    user_id: str,
-    frame: dict,
-) -> None:
-    """Handle a journey_message frame — continues the journey conversation."""
-    executor = await _make_ws_executor(websocket, user_id)
-    set_client_executor(executor)
-    try:
-        reply = await handle_journey_message(user_id, frame)
-        await websocket.send_text(json.dumps(reply))
-    except Exception as exc:
-        session_id = frame.get("session_id", "")
-        logger.error(
-            "device_ws: journey_message failed user=%s session=%s: %s",
-            user_id, session_id, exc,
-        )
-        await websocket.send_text(json.dumps({
-            "type": "journey_reply",
-            "session_id": session_id,
-            "message": f"Journey error: {exc}",
-            "done": True,
-            "prompt_template": None,
-        }))
-    finally:
-        clear_client_executor()
 
 
 # ── Heartbeat ─────────────────────────────────────────────────────────
@@ -415,3 +360,6 @@ async def _mark_runs_disconnected(user_id: str) -> None:
             user_id,
             exc,
         )
+
+
+

app/billing/tier_manager.py

@@ -21,7 +21,6 @@ FEATURES: dict[str, dict[str, Any]] = {
     "free": {
         "agents": 3,
         "batch_active": 2,
-        "batch_runs_per_day": 5,
         "cloud_storage_gb": 0,
         "backup_gb": 0,
         "providers": 1,
@@ -32,7 +31,6 @@ FEATURES: dict[str, dict[str, Any]] = {
     "pro": {
         "agents": -1,           # unlimited
         "batch_active": 10,
-        "batch_runs_per_day": 50,
         "cloud_storage_gb": 5,
         "backup_gb": 5,
         "providers": -1,
@@ -43,7 +41,6 @@ FEATURES: dict[str, dict[str, Any]] = {
     "power": {
         "agents": -1,
         "batch_active": -1,     # unlimited
-        "batch_runs_per_day": -1,  # unlimited
         "cloud_storage_gb": 25,
         "backup_gb": 25,
         "providers": -1,
@@ -54,7 +51,6 @@ FEATURES: dict[str, dict[str, Any]] = {
     "team": {
         "agents": -1,
         "batch_active": -1,
-        "batch_runs_per_day": -1,  # unlimited
         "cloud_storage_gb": -1,  # unlimited
         "backup_gb": -1,         # unlimited
         "providers": -1,
@@ -81,18 +77,16 @@ class TierManager:
     async def get_tier(self, user_id: str, db: AsyncSession) -> BillingTier:
         """Return the current billing tier for ``user_id`` from the DB.
 
-        Falls back to ``'power'`` in dev (unlimited) or ``'free'`` in prod
+        Falls back to ``'free'`` when no subscription row exists.
-        when no subscription row exists.
         """
         from app.models import Subscription  # noqa: PLC0415
-        from app.config.settings import settings  # noqa: PLC0415
 
         result = await db.execute(
             select(Subscription.tier).where(Subscription.user_id == user_id)
         )
         tier: str | None = result.scalar_one_or_none()
         if tier is None or tier not in FEATURES:
-            return "power" if settings.ENV == "dev" else "free"
+            return "free"
         return tier  # type: ignore[return-value]
 
     # ── Feature access ───────────────────────────────────────────────────

app/core/agent_registry.py

@@ -1,30 +0,0 @@
-"""Minimal agent base types retained for compatibility with batch runners."""
-
-from __future__ import annotations
-
-from abc import ABC, abstractmethod
-from typing import Any
-
-
-class BaseAgent(ABC):
-    """Common base for non-chat agents still using the old base contract."""
-
-    def __init__(
-        self,
-        user_id: str = "",
-        shared_memory: dict[str, Any] | None = None,
-        vector_store_context: list[str] | None = None,
-    ) -> None:
-        self.user_id = user_id
-        self.shared_memory: dict[str, Any] = shared_memory or {}
-        self.vector_store_context: list[str] = vector_store_context or []
-
-    @abstractmethod
-    def get_name(self) -> str: ...
-
-    @abstractmethod
-    def get_description(self) -> str: ...
-
-    @property
-    def skills(self) -> list[str]:
-        return []

app/core/device_manager.py

@@ -3,15 +3,20 @@
 Maintains in-memory state for all active Electron → backend WebSocket
 connections.  One connection per user (latest replaces previous).
 
-The manager handles the **tool-call round-trip** pattern:
+The manager participates in two interaction patterns:
-  - Backend sends ``tool_call`` frame → Electron executes the action →
-    returns ``tool_result`` frame.
-  - ``create_pending_call`` registers a Future keyed by ``call_id``.
-  - ``resolve_pending_call`` fulfils the Future; callers awaiting it
-    receive the result dict from Electron.
 
-This pattern is used by all tools (CRUD, file-system, etc.) via
+1. **Tool-call round-trip** (bidirectional CRUD):
-``execute_on_client()`` in ``ws_context.py``.
+   - Backend sends ``tool_call`` frame → Electron executes CRUD → returns
+     ``tool_result`` frame.
+   - ``create_pending_call`` registers a Future keyed by ``call_id``.
+   - ``resolve_pending_call`` fulfils the Future; callers awaiting it
+     receive the result dict from Electron.
+
+2. **Agent-data streaming** (local directory agent runs):
+   - Backend sends ``agent_run`` frame → Electron reads files and sends
+     back a stream of ``agent_data`` frames followed by ``agent_complete``.
+   - ``get_agent_data_queue`` returns (or creates) an asyncio.Queue for
+     a specific ``run_id`` so the agent runner can iterate frames.
 
 The ``device_manager`` module-level singleton is imported by both the
 device WS route and the agent runner.
@@ -37,6 +42,8 @@ class DeviceConnection:
     device_id: str
     # Futures indexed by tool_call id — resolved when tool_result arrives.
     pending_calls: dict[str, asyncio.Future[dict]] = field(default_factory=dict)
+    # Per-run queues for agent_data / agent_complete frames.
+    agent_data_queues: dict[str, asyncio.Queue[dict | None]] = field(default_factory=dict)
 
 
 class DeviceConnectionManager:
@@ -146,6 +153,31 @@ class DeviceConnectionManager:
         if fut is not None and not fut.done():
             fut.set_result(result)
 
+    # ── Agent-data queue ──────────────────────────────────────────────
+
+    def get_agent_data_queue(
+        self, user_id: str, run_id: str
+    ) -> asyncio.Queue[dict | None]:
+        """Return (creating if absent) the queue for *run_id* agent frames.
+
+        The agent runner reads from this queue.  The device WS handler writes
+        to it.  ``None`` is the sentinel that signals the stream is finished.
+        """
+        conn = self._connections.get(user_id)
+        if conn is None:
+            raise RuntimeError(
+                f"get_agent_data_queue: user {user_id!r} is not connected"
+            )
+        if run_id not in conn.agent_data_queues:
+            conn.agent_data_queues[run_id] = asyncio.Queue()
+        return conn.agent_data_queues[run_id]
+
+    def cleanup_agent_data_queue(self, user_id: str, run_id: str) -> None:
+        """Remove the queue for *run_id* once a run has completed."""
+        conn = self._connections.get(user_id)
+        if conn:
+            conn.agent_data_queues.pop(run_id, None)
+
 
 # Module-level singleton — import this everywhere.
 device_manager = DeviceConnectionManager()

app/core/llm.py

@@ -1,6 +1,6 @@
 """LLM factory — centralised model instantiation via LiteLLM.
 
-Every agent and the orchestrator call ``get_llm()`` or ``get_router_llm()``
+Every agent and the deep-agent supervisors call ``get_llm()`` or ``get_router_llm()``
 instead of directly constructing a provider-specific class.  The model string
 follows the `LiteLLM model naming convention
 <https://docs.litellm.ai/docs/providers>`_:
@@ -18,7 +18,6 @@ Switch providers by changing **LLM_MODEL** / **LLM_ROUTER_MODEL** in ``.env``
 from __future__ import annotations
 
 import os
-import warnings
 
 from openai import AsyncOpenAI
 import litellm
@@ -33,14 +32,6 @@ from app.config.settings import settings
 # Drop them silently instead of raising UnsupportedParamsError.
 litellm.drop_params = True
 
-# Some provider responses include a plain dict in the `usage` field where a
-# richer Pydantic model is expected. This warning is noisy but non-fatal.
-warnings.filterwarnings(
-    "ignore",
-    message=r"PydanticSerializationUnexpectedValue\(Expected `ResponseAPIUsage`",
-    category=UserWarning,
-)
-
 
 def _api_key_for_model(model: str) -> str | None:
     """Return the most appropriate API key for the given LiteLLM model string."""

app/core/memory_middleware.py

@@ -43,21 +43,15 @@ _PROACTIVE_CONFIDENCE_THRESHOLD = 0.6
 
 
 class MemoryMiddleware:
-    """Enrich orchestrator context with memory and persist interactions after."""
+    """Enrich agent context with memory and persist interactions after."""
 
     def __init__(self, db: AsyncSession) -> None:
         self._db = db
 
     # ── Public API ────────────────────────────────────────────────────────────
 
-    async def enrich_context(
+    async def enrich_context(self, user_id: str, message: str) -> dict[str, Any]:
-        self,
+        """Build memory context dict to inject into the agent before LLM call.
-        user_id: str,
-        message: str,
-        trace_id: str | None = None,
-        session_id: str | None = None,
-    ) -> dict[str, Any]:
-        """Build memory context dict to inject into the orchestrator before LLM call.
 
         Returns a dict with keys:
           core_memory        — {key: plaintext_value, ...}
@@ -71,21 +65,9 @@ class MemoryMiddleware:
 
         core = await self._load_core(user_id, fernet)
         associative = await self._load_associative(user_id, message, fernet)
-        episodic = await self._load_episodic(user_id, fernet, session_id=session_id)
+        episodic = await self._load_episodic(user_id, fernet)
         proactive = await self._load_proactive(user_id, fernet)
 
-        user_dbg = await self._get_user_debug(user_id)
-        logger.info(
-            "memory: enrich_context trace=%s user=%s tier=%s core=%d associative=%d episodic=%d proactive=%d",
-            trace_id or "-",
-            user_id,
-            user_dbg.get("tier") or "-",
-            len(core),
-            len(associative),
-            len(episodic),
-            len(proactive),
-        )
-
         return {
             "core_memory": core,
             "associative_memory": associative,
@@ -99,7 +81,6 @@ class MemoryMiddleware:
         session_id: str,
         message: str,
         response: str,
-        trace_id: str | None = None,
     ) -> None:
         """Summarise and store a completed interaction in episodic memory.
 
@@ -122,19 +103,11 @@ class MemoryMiddleware:
         self._db.add(row)
         try:
             await self._db.commit()
-            user_dbg = await self._get_user_debug(user_id)
-            logger.info(
-                "memory: store_episode trace=%s user=%s tier=%s session=%s",
-                trace_id or "-",
-                user_id,
-                user_dbg.get("tier") or "-",
-                session_id,
-            )
         except Exception as exc:
             logger.error("memory: store_episode failed user=%s: %s", user_id, exc)
             await self._db.rollback()
 
-    async def update_core(self, user_id: str, key: str, value: str, trace_id: str | None = None) -> None:
+    async def update_core(self, user_id: str, key: str, value: str) -> None:
         """Upsert a core memory key/value for a user."""
         fernet = await self._get_fernet(user_id)
         if fernet is None:
@@ -160,176 +133,10 @@ class MemoryMiddleware:
             ))
         try:
             await self._db.commit()
-            user_dbg = await self._get_user_debug(user_id)
-            logger.info(
-                "memory: update_core trace=%s user=%s tier=%s key=%s",
-                trace_id or "-",
-                user_id,
-                user_dbg.get("tier") or "-",
-                key,
-            )
         except Exception as exc:
             logger.error("memory: update_core failed user=%s key=%s: %s", user_id, key, exc)
             await self._db.rollback()
 
-    async def list_core_blocks(self, user_id: str) -> list[dict[str, str]]:
-        """Return core memory as editable blocks (label/value)."""
-        fernet = await self._get_fernet(user_id)
-        if fernet is None:
-            return []
-
-        result = await self._db.execute(
-            select(MemoryCore)
-            .where(MemoryCore.user_id == user_id)
-            .order_by(MemoryCore.key.asc())
-        )
-        rows = result.scalars().all()
-        out: list[dict[str, str]] = []
-        for row in rows:
-            plaintext = _safe_decrypt(fernet, row.value_encrypted)
-            if plaintext is not None:
-                out.append({"label": row.key, "value": plaintext})
-        logger.debug("memory: list_core_blocks user=%s count=%d", user_id, len(out))
-        return out
-
-    async def get_core_block(self, user_id: str, label: str) -> str | None:
-        """Return a single core memory block value by label."""
-        fernet = await self._get_fernet(user_id)
-        if fernet is None:
-            return None
-
-        result = await self._db.execute(
-            select(MemoryCore).where(
-                MemoryCore.user_id == user_id,
-                MemoryCore.key == label,
-            )
-        )
-        row = result.scalar_one_or_none()
-        if row is None:
-            logger.debug("memory: get_core_block user=%s label=%s found=0", user_id, label)
-            return None
-        value = _safe_decrypt(fernet, row.value_encrypted)
-        logger.debug("memory: get_core_block user=%s label=%s found=%d", user_id, label, 1 if value is not None else 0)
-        return value
-
-    async def delete_core(self, user_id: str, label: str) -> bool:
-        """Delete a core memory block by label. Returns True if deleted."""
-        result = await self._db.execute(
-            select(MemoryCore).where(
-                MemoryCore.user_id == user_id,
-                MemoryCore.key == label,
-            )
-        )
-        row = result.scalar_one_or_none()
-        if row is None:
-            logger.debug("memory: delete_core user=%s label=%s found=0", user_id, label)
-            return False
-
-        await self._db.delete(row)
-        try:
-            await self._db.commit()
-            logger.info("memory: delete_core user=%s label=%s", user_id, label)
-            return True
-        except Exception as exc:
-            logger.error("memory: delete_core failed user=%s label=%s: %s", user_id, label, exc)
-            await self._db.rollback()
-            return False
-
-    async def append_core(self, user_id: str, label: str, content: str) -> None:
-        """Append content to a core block, creating it if missing."""
-        current = await self.get_core_block(user_id, label)
-        if current is None:
-            await self.update_core(user_id, label, content)
-            logger.info("memory: append_core user=%s label=%s created=1", user_id, label)
-            return
-        await self.update_core(user_id, label, f"{current}\n{content}")
-        logger.info("memory: append_core user=%s label=%s created=0", user_id, label)
-
-    async def replace_core(self, user_id: str, label: str, old: str, new: str) -> bool:
-        """Replace one exact string inside a core block. Returns False if not found."""
-        current = await self.get_core_block(user_id, label)
-        if current is None or old not in current:
-            logger.debug("memory: replace_core user=%s label=%s changed=0", user_id, label)
-            return False
-        await self.update_core(user_id, label, current.replace(old, new, 1))
-        logger.info("memory: replace_core user=%s label=%s changed=1", user_id, label)
-        return True
-
-    async def insert_archival(self, user_id: str, content: str, source: str = "manual") -> None:
-        """Insert a long-term archival memory entry."""
-        fernet = await self._get_fernet(user_id)
-        if fernet is None:
-            return
-
-        encrypted = _encrypt(fernet, content)
-        row = MemoryAssociative(
-            id=str(uuid.uuid4()),
-            user_id=user_id,
-            content_encrypted=encrypted,
-            embedding=None,
-            entity_type=source,
-            entity_id=None,
-        )
-        self._db.add(row)
-        try:
-            await self._db.commit()
-            logger.info("memory: insert_archival user=%s source=%s", user_id, source)
-        except Exception as exc:
-            logger.error("memory: insert_archival failed user=%s: %s", user_id, exc)
-            await self._db.rollback()
-
-    async def search_archival(self, user_id: str, query: str, top_k: int = 5) -> list[str]:
-        """Search archival memory (keyword fallback; semantic ranking can replace this)."""
-        fernet = await self._get_fernet(user_id)
-        if fernet is None:
-            return []
-
-        result = await self._db.execute(
-            select(MemoryAssociative)
-            .where(MemoryAssociative.user_id == user_id)
-            .order_by(MemoryAssociative.updated_at.desc())
-            .limit(100)
-        )
-        rows = result.scalars().all()
-        needle = query.strip().lower()
-        out: list[str] = []
-        for row in rows:
-            plaintext = _safe_decrypt(fernet, row.content_encrypted)
-            if plaintext is None:
-                continue
-            if not needle or needle in plaintext.lower():
-                out.append(plaintext)
-            if len(out) >= max(top_k, 1):
-                break
-        logger.info("memory: search_archival user=%s query=%s hits=%d", user_id, query[:80], len(out))
-        return out
-
-    async def search_recall(self, user_id: str, query: str, top_k: int = 5) -> list[str]:
-        """Search recall memory (episodic summaries) by keyword."""
-        fernet = await self._get_fernet(user_id)
-        if fernet is None:
-            return []
-
-        result = await self._db.execute(
-            select(MemoryEpisodic)
-            .where(MemoryEpisodic.user_id == user_id)
-            .order_by(MemoryEpisodic.created_at.desc())
-            .limit(100)
-        )
-        rows = result.scalars().all()
-        needle = query.strip().lower()
-        out: list[str] = []
-        for row in rows:
-            plaintext = _safe_decrypt(fernet, row.summary_encrypted)
-            if plaintext is None:
-                continue
-            if not needle or needle in plaintext.lower():
-                out.append(plaintext)
-            if len(out) >= max(top_k, 1):
-                break
-        logger.info("memory: search_recall user=%s query=%s hits=%d", user_id, query[:80], len(out))
-        return out
-
     # ── Private helpers ───────────────────────────────────────────────────────
 
     async def _get_fernet(self, user_id: str) -> Fernet | None:
@@ -341,16 +148,6 @@ class MemoryMiddleware:
             return None
         return Fernet(user.encryption_key.encode())
 
-    async def _get_user_debug(self, user_id: str) -> dict[str, str | None]:
-        """Load lightweight user debug fields for trace logs."""
-        result = await self._db.execute(select(User).where(User.id == user_id))
-        user = result.scalar_one_or_none()
-        if user is None:
-            return {"tier": None}
-        return {
-            "tier": user.tier,
-        }
-
     async def _load_core(self, user_id: str, fernet: Fernet) -> dict[str, str]:
         result = await self._db.execute(
             select(MemoryCore).where(MemoryCore.user_id == user_id)
@@ -386,17 +183,10 @@ class MemoryMiddleware:
                 out.append(plaintext)
         return out
 
-    async def _load_episodic(
+    async def _load_episodic(self, user_id: str, fernet: Fernet) -> list[str]:
-        self,
-        user_id: str,
-        fernet: Fernet,
-        session_id: str | None = None,
-    ) -> list[str]:
-        query = select(MemoryEpisodic).where(MemoryEpisodic.user_id == user_id)
-        if session_id:
-            query = query.where(MemoryEpisodic.session_id == session_id)
         result = await self._db.execute(
-            query
+            select(MemoryEpisodic)
+            .where(MemoryEpisodic.user_id == user_id)
             .order_by(MemoryEpisodic.created_at.desc())
             .limit(_EPISODIC_RECENT_N)
         )

app/core/output_formatter.py

@@ -1,47 +1,141 @@
-"""Output formatter for deep-agent stream events."""
+"""Output Formatter — transforms deep-agent event streams into WS frame sequences.
+
+Consumes ``(event_type, data)`` tuples yielded by ``deep_agent.run_*_stream()``:
+  * ``("token", str)``       — supervisor text token
+  * ``("tool_end", dict)``   — sub-agent finished: ``{name, result}``
+  * ``("mutations", list)``  — collected CRUD mutations for ``stream_end``
+
+HomeFormatter:
+  * Streams text tokens as-is → emits ``WsStreamText``
+    (text may contain inline ``<type>[id,...]</type>`` entity tags
+    for the frontend to parse and render as interactive components)
+  * Attaches mutations        → injects into ``WsStreamEnd``
+
+FloatingFormatter:
+  * Sniffs first ``tool_end`` name → emits ``WsFloatingDomain``
+  * Streams text tokens             → emits ``WsStreamText``
+  * Attaches mutations              → injects into ``WsStreamEnd``
+"""
 
 from __future__ import annotations
 
+import logging
 from collections.abc import AsyncGenerator
 from typing import Any
 
-from app.schemas import WsFloatingDomain, WsStreamEnd, WsStreamStart, WsStreamText
+from app.schemas import (
+    WsFloatingDomain,
+    WsStreamEnd,
+    WsStreamStart,
+    WsStreamText,
+)
+
+logger = logging.getLogger(__name__)
+
+# Map sub-agent tool name → floating domain / entity type
+_AGENT_DOMAIN: dict[str, str] = {
+    "task_agent": "tasks",
+    "timeline_agent": "timelines",
+    "note_agent": "notes",
+    "project_agent": "projects",
+}
 
 WsFrame = WsStreamStart | WsStreamText | WsStreamEnd | WsFloatingDomain
 
 
-class StreamFormatter:
+class HomeFormatter:
-    """Convert `(event_type, data)` stream events into websocket frame models."""
+    """Consumes a deep-agent event stream and yields WS frames for the Home view.
+
+    Text tokens are forwarded as-is via ``WsStreamText``.  The supervisor
+    embeds ``<type>[id1,id2]</type>`` entity tags inline — the frontend
+    is responsible for parsing those and rendering interactive components.
+    Mutations are attached to ``WsStreamEnd``.
+    """
 
     def __init__(self, request_id: str) -> None:
         self.request_id = request_id
+        self._mutations: list[dict] = []
 
     async def format(
         self,
         event_stream: AsyncGenerator[tuple[str, Any], None],
     ) -> AsyncGenerator[WsFrame, None]:
-        started = False
+        yield WsStreamStart(request_id=self.request_id)
 
         async for event_type, data in event_stream:
-            if event_type == "floating_domain":
+            if event_type == "token":
-                if isinstance(data, dict):
+                if data:
+                    yield WsStreamText(request_id=self.request_id, chunk=data)
+
+            elif event_type == "mutations":
+                self._mutations = data or []
+
+        yield WsStreamEnd(
+            request_id=self.request_id,
+            mutations=[
+                {"action": m["action"], "table": m["table"], "data": m["data"]}
+                for m in self._mutations
+            ],
+        )
+
+
+class FloatingFormatter:
+    """Consumes a deep-agent event stream and yields WS frames for the Floating view.
+
+    Sniffs the first ``tool_end`` event name to derive the domain (e.g.
+    ``task_agent`` → ``"tasks"``), then streams text tokens as plain
+    ``WsStreamText``.  No block parsing for floating context.
+    """
+
+    def __init__(self, request_id: str) -> None:
+        self.request_id = request_id
+        self._mutations: list[dict] = []
+
+    async def format(
+        self,
+        event_stream: AsyncGenerator[tuple[str, Any], None],
+    ) -> AsyncGenerator[WsFrame, None]:
+        domain_sent = False
+
+        async for event_type, data in event_stream:
+            if event_type == "tool_end" and not domain_sent:
+                # Sniff domain from the first sub-agent that completes
+                name = data.get("name", "")
+                domain = _AGENT_DOMAIN.get(name, "tasks")
+                yield WsFloatingDomain(
+                    request_id=self.request_id,
+                    domain=domain,  # type: ignore[arg-type]
+                )
+                yield WsStreamStart(request_id=self.request_id)
+                domain_sent = True
+
+            elif event_type == "token":
+                if not domain_sent:
+                    # First token arrived before any tool_end — default domain
                     yield WsFloatingDomain(
                         request_id=self.request_id,
-                        domain=data,
+                        domain="tasks",  # type: ignore[arg-type]
                     )
-                continue
+                    yield WsStreamStart(request_id=self.request_id)
+                    domain_sent = True
+                if data:
+                    yield WsStreamText(request_id=self.request_id, chunk=data)
 
-            if event_type != "token":
+            elif event_type == "mutations":
-                continue
+                self._mutations = data or []
 
-            if not started:
+        # If no events triggered domain_sent (edge case), still emit structure
-                yield WsStreamStart(request_id=self.request_id)
+        if not domain_sent:
-                started = True
+            yield WsFloatingDomain(
-
+                request_id=self.request_id,
-            text = str(data or "")
+                domain="tasks",  # type: ignore[arg-type]
-            if text:
+            )
-                yield WsStreamText(request_id=self.request_id, chunk=text)
-
-        if not started:
             yield WsStreamStart(request_id=self.request_id)
-        yield WsStreamEnd(request_id=self.request_id)
+
+        yield WsStreamEnd(
+            request_id=self.request_id,
+            mutations=[
+                {"action": m["action"], "table": m["table"], "data": m["data"]}
+                for m in self._mutations
+            ],
+        )

app/core/ws_context.py

@@ -7,18 +7,21 @@ The callback sends a `tool_call` WS frame and awaits the `tool_result`.
 
 from __future__ import annotations
 
+import logging
 from contextvars import ContextVar
 from typing import Any, Callable, Coroutine
 from uuid import uuid4
 
+logger = logging.getLogger(__name__)
+
 # Holds the execute callback for the current WS session.
-# Set by the chat WS handler before the orchestrator runs; cleared after.
+# Set by the chat WS handler before the deep agent runs; cleared after.
 _client_executor: ContextVar[Callable[[dict], Coroutine[Any, Any, dict]]] = ContextVar(
     "_client_executor"
 )
 
 # Optional collector that captures raw execute_on_client results.
-# Set by _tool_loop / _tool_loop_stream to populate ChatAgent.tool_results.
+# Set by the deep agent tool loop to capture CRUD mutations.
 _tool_result_collector: ContextVar[list[dict] | None] = ContextVar(
     "_tool_result_collector", default=None
 )
@@ -81,12 +84,17 @@ async def execute_on_client(
     if limit is not None:
         payload["limit"] = limit
 
+    logger.info("execute_on_client: sending payload action=%s table=%s id=%s", action, table, payload["id"])
     result = await callback(payload)
+    if result is None:
+        logger.error("execute_on_client: callback returned None for action=%s table=%s id=%s", action, table, payload["id"])
+    else:
+        logger.info("execute_on_client: got result type=%s keys=%s", type(result).__name__, list(result.keys()) if isinstance(result, dict) else "N/A")
     collector = _tool_result_collector.get(None)
-    if collector is not None:
+    if collector is not None and action in ("insert", "update", "delete"):
         collector.append({
             "action": action,
             "table": table,
-            "data": result,
+            "data": data or {},
         })
     return result

app/main.py

@@ -18,9 +18,7 @@ from app.config.settings import settings
 
 @asynccontextmanager
 async def lifespan(app: FastAPI):
-    # Startup: ensure agent tool modules are loaded.
+    # Startup: initialise DB connection pool
-    import app.agents  # noqa: F401
-
     yield
 
     # Shutdown: dispose SQLAlchemy connection pool
@@ -50,7 +48,7 @@ def create_app() -> FastAPI:
     app.add_middleware(SanitizerMiddleware)
     app.add_middleware(TierRateLimitMiddleware)
 
-    from app.api.routes import agents, auth, backup, billing, chat, device_ws, plugins, storage, vectors
+    from app.api.routes import agent_setup, agents, auth, backup, billing, chat, device_ws, plugins, storage, vectors
 
     app.include_router(auth.router,       prefix="/api/v1")
     app.include_router(chat.router,       prefix="/api/v1")
@@ -60,6 +58,7 @@ def create_app() -> FastAPI:
     app.include_router(plugins.router,    prefix="/api/v1")
     app.include_router(billing.router,    prefix="/api/v1")
     app.include_router(agents.router,     prefix="/api/v1")
+    app.include_router(agent_setup.router, prefix="/api/v1")
     app.include_router(device_ws.router,  prefix="/api/v1")
 
     @app.get("/api/v1/health", tags=["health"])

app/schemas.py

@@ -142,6 +142,9 @@ class WsFrameType(str, Enum):
     tool_result = "tool_result"
     final = "final"
     ping = "ping"
+    agent_run = "agent_run"
+    agent_data = "agent_data"
+    agent_complete = "agent_complete"
     device_hello = "device_hello"
     # ── v3 frame types ─────────────────────────────────────────────────
     home_request = "home_request"
@@ -153,10 +156,6 @@ class WsFrameType(str, Enum):
     data_request = "data_request"
     data_response = "data_response"
     mutation = "mutation"
-    # ── v4 journey frame types ────────────────────────────────────────
-    journey_start = "journey_start"
-    journey_message = "journey_message"
-    journey_reply = "journey_reply"
 
 
 class WsToolCall(BaseModel):
@@ -209,6 +208,31 @@ class WsDeviceHello(BaseModel):
     agent_ids: list[str] = Field(default_factory=list)
 
 
+class WsAgentRun(BaseModel):
+    """Server → Client: trigger an agent run on the connected device."""
+
+    type: Literal[WsFrameType.agent_run] = WsFrameType.agent_run
+    run_id: str
+    agent_id: str
+    config: dict[str, Any]
+
+
+class WsAgentData(BaseModel):
+    """Client → Server: files read by the local agent."""
+
+    type: Literal[WsFrameType.agent_data] = WsFrameType.agent_data
+    run_id: str
+    files: list[dict[str, Any]]
+
+
+class WsAgentComplete(BaseModel):
+    """Client → Server: Electron signals it has finished reading files."""
+
+    type: Literal[WsFrameType.agent_complete] = WsFrameType.agent_complete
+    run_id: str
+    files_read: int
+    errors: list[str] = Field(default_factory=list)
+
 
 # ── WebSocket v3 Frame Models ─────────────────────────────────────────
 
@@ -255,14 +279,7 @@ class WsStreamEnd(BaseModel):
 
     type: Literal[WsFrameType.stream_end] = WsFrameType.stream_end
     request_id: str
-
+    mutations: list[dict[str, Any]] = Field(default_factory=list)
-
-class WsDomain(BaseModel):
-    """Structured floating domain payload for UI routing decisions."""
-
-    type: Literal["task", "timeline", "project", "node"]
-    id: str | None = None
-    section: Literal["task", "timeline", "note"] | None = None
 
 
 class WsFloatingDomain(BaseModel):
@@ -270,7 +287,7 @@ class WsFloatingDomain(BaseModel):
 
     type: Literal[WsFrameType.floating_domain] = WsFrameType.floating_domain
     request_id: str
-    domain: WsDomain
+    domain: Literal["tasks", "timelines", "notes", "projects"]
 
 
 # ── Agent Catalog ─────────────────────────────────────────────────────
@@ -279,28 +296,84 @@ class AgentCatalogItem(BaseModel):
     type: str
     name: str
     description: str
+    config_schema: dict[str, Any] = Field(default_factory=dict)
 
 
-class AgentCreationCheckRequest(BaseModel):
+# ── Local Agent Config ────────────────────────────────────────────────
-    active_agents: int = Field(ge=0, default=0)
+
+class LocalAgentConfigCreate(BaseModel):
+    name: str
+    device_id: str
+    directory_paths: list[str]
+    data_types: list[str]
+    prompt_template: str
+    file_extensions: list[str]
+    schedule_cron: str
 
 
-class AgentCreationCheckResponse(BaseModel):
+class LocalAgentConfigUpdate(BaseModel):
-    allowed: bool
+    name: str | None = None
-    tier: BillingTier
+    device_id: str | None = None
-    active_agents: int
+    directory_paths: list[str] | None = None
-    limit: int
+    data_types: list[str] | None = None
+    prompt_template: str | None = None
+    file_extensions: list[str] | None = None
+    schedule_cron: str | None = None
+    enabled: bool | None = None
 
 
-class AgentTriggerRequest(BaseModel):
+class LocalAgentConfigResponse(BaseModel):
-    directory: str = Field(min_length=1)
+    id: str
-    device_id: str = Field(default="")
+    name: str
-    agent_id: str | None = None  # FE stable agent ID (electron-store UUID)
+    device_id: str
-    what_to_extract: list[str] = Field(min_length=1)
+    directory_paths: list[str]
-    actions_by_type: dict[str, list[str]] | None = None
+    data_types: list[str]
-    batch_interval: str = Field(min_length=1)
+    prompt_template: str
-    custom_agent_prompt: str = Field(min_length=1)
+    file_extensions: list[str]
-    active_agents: int = Field(ge=0, default=0)
+    schedule_cron: str
+    enabled: bool
+    last_run_at: int | None
+    created_at: int
+    updated_at: int
+
+
+# ── Cloud Agent Config ────────────────────────────────────────────────
+
+class CloudAgentConfigCreate(BaseModel):
+    provider: Literal["gmail", "teams", "outlook"]
+    name: str
+    data_types: list[str]
+    prompt_template: str
+    oauth_token_encrypted: str
+    schedule_cron: str
+    filter_config: dict[str, Any] | None = None
+
+
+class CloudAgentConfigUpdate(BaseModel):
+    provider: Literal["gmail", "teams", "outlook"] | None = None
+    name: str | None = None
+    data_types: list[str] | None = None
+    prompt_template: str | None = None
+    oauth_token_encrypted: str | None = None
+    schedule_cron: str | None = None
+    filter_config: dict[str, Any] | None = None
+    enabled: bool | None = None
+
+
+class CloudAgentConfigResponse(BaseModel):
+    """oauth_token_encrypted is intentionally excluded — never returned to clients."""
+
+    id: str
+    provider: Literal["gmail", "teams", "outlook"]
+    name: str
+    data_types: list[str]
+    prompt_template: str
+    schedule_cron: str
+    filter_config: dict[str, Any] | None
+    enabled: bool
+    last_run_at: int | None
+    created_at: int
+    updated_at: int
 
 
 # ── Agent Run Log ─────────────────────────────────────────────────────
@@ -319,3 +392,18 @@ class AgentRunLogResponse(BaseModel):
 
 # ── Chatbot Journey ───────────────────────────────────────────────────
 
+class JourneyStartRequest(BaseModel):
+    agent_type: Literal["local", "cloud"]
+    agent_id: str | None = None
+
+
+class JourneyMessageRequest(BaseModel):
+    session_id: str
+    message: str
+
+
+class JourneyResponse(BaseModel):
+    session_id: str
+    message: str
+    done: bool
+    prompt_template: str | None = None

docs/MICROSERVICES_ARCHITECTURE.md

@@ -1,941 +0,0 @@
-# Adiuva — Architettura Microservizi (MVP)
-
-## Panoramica
-
-Il monolite viene suddiviso in **4 servizi MVP** + un **API Gateway (Traefik)**, orchestrati con Docker Compose su un singolo VPS raggiungibile via Cloudflare.
-
-> **Fuori dall'MVP**: Storage Service (S3/backup CRUD) e Plugin Service (marketplace). Verranno aggiunti come servizi indipendenti in una fase successiva.
-
-```
-                          ┌──────────────┐
-                          │  Cloudflare  │
-                          │  (DNS + CDN) │
-                          └──────┬───────┘
-                                 │ HTTPS / WSS
-                          ┌──────▼───────┐
-                          │   Traefik    │
-                          │ API Gateway  │
-                          │  (routing,   │
-                          │   TLS, rate  │
-                          │   limiting)  │
-                          └──────┬───────┘
-                                 │
-          ┌──────────┬───────────┼───────────┐
-          │          │           │           │
-    ┌─────▼────┐ ┌───▼───┐ ┌────▼────┐ ┌────▼───┐
-    │  Auth    │ │  Chat │ │  Agent  │ │Billing │
-    │ Service  │ │Service│ │ Service │ │Service │
-    └─────┬────┘ └───┬───┘ └────┬────┘ └────┬───┘
-          │          │          │           │
-    ┌─────▼──────────▼──────────▼───────────▼────┐
-    │              Infrastruttura                 │
-    │  PostgreSQL  │  Redis  │  Qdrant            │
-    └─────────────────────────────────────────────┘
-```
-
----
-
-## 1. Suddivisione dei Servizi
-
-### 1.1 Auth Service (`auth-service`)
-
-**Responsabilità**: Registrazione, login, refresh token, profilo utente, encryption key.
-
-| Endpoint originale | Metodo |
-|---|---|
-| `/api/v1/auth/register` | POST |
-| `/api/v1/auth/login` | POST |
-| `/api/v1/auth/refresh` | POST |
-| `/api/v1/auth/me` | GET / PUT |
-
-**Database**: Tabelle `users`, `refresh_tokens` (PostgreSQL condiviso, schema `auth`).
-
-**Modifica chiave — JWT con RS256**:
-Il monolite usa un `SECRET_KEY` simmetrico (HS256). Con i microservizi, passare a **RS256** (asimmetrico):
-- L'Auth Service firma i JWT con la **chiave privata**.
-- Tutti gli altri servizi verificano i JWT con la **chiave pubblica** senza mai contattare l'Auth Service.
-- La chiave pubblica viene esposta via `GET /api/v1/auth/.well-known/jwks.json` oppure montata come volume condiviso.
-
-```python
-# auth-service/app/auth/jwt.py
-from cryptography.hazmat.primitives.asymmetric import rsa
-from jose import jwt
-
-PRIVATE_KEY = ...  # Da env/secret
-PUBLIC_KEY = ...   # Derivata o da env
-
-def create_access_token(user_id: str, tier: str) -> str:
-    return jwt.encode(
-        {"sub": user_id, "tier": tier, "exp": ...},
-        PRIVATE_KEY,
-        algorithm="RS256",
-    )
-```
-
-```python
-# shared/auth.py  (usato da tutti gli altri servizi)
-from jose import jwt
-
-PUBLIC_KEY = ...  # Volume montato o fetched da JWKS endpoint
-
-def verify_token(token: str) -> dict:
-    return jwt.decode(token, PUBLIC_KEY, algorithms=["RS256"])
-```
-
-**Scaling**: 2 repliche sufficienti, stateless. Rate-limit dedicato su `/login` e `/register`.
-
----
-
-### 1.2 Chat Service (`chat-service`) ⭐ Real-time
-
-**Responsabilità**: WebSocket device connection, home chat, floating chat, memory middleware, streaming LLM responses verso il client.
-
-Questo servizio gestisce la **connessione persistente** con l'app Electron e le interazioni **real-time** dell'utente (chat home, floating chat). È il proprietario della WebSocket.
-
-| Endpoint | Tipo |
-|---|---|
-| `/api/v1/ws/device` | WebSocket (connessione persistente) |
-| `/api/v1/chat` | POST (REST fallback) |
-
-**Moduli inclusi**: `deep_agent`, `memory_middleware`, `ws_context`, `device_manager` (Redis-backed), `output_formatter`, `llm`, tutti gli agent tools (`task_agent`, `project_agent`, `note_agent`, `timeline_agent`).
-
-**Perché separato dall'Agent Service**: Il Chat Service tiene la WebSocket aperta e risponde in tempo reale (streaming). Scalare aggiungendo repliche è semplice con sticky sessions + Redis pub/sub per il cross-instance routing dei tool_call.
-
-**Scaling**: 2–N repliche. Sticky cookies per le WS + Redis per cross-instance.
-
----
-
-### 1.3 Agent Service (`agent-service`) ⭐ Batch
-
-**Responsabilità**: Batch agent processing (directory scanning, file classification, entity extraction), agent setup journeys, agent configuration CRUD.
-
-Questo servizio gestisce i processi **long-running** e **CPU-intensive**: scansione filesystem, classificazione file con LLM, estrazione entità in batch. Non possiede la WebSocket — comunica con il device dell'utente tramite **Redis pub/sub** passando per il Chat Service.
-
-| Endpoint | Tipo |
-|---|---|
-| `/api/v1/agents/catalog` | GET |
-| `/api/v1/agents/can-create` | POST |
-| `/api/v1/agents/trigger` | POST |
-| `/api/v1/agents/journey/start` | POST (o WS relay) |
-| `/api/v1/agents/journey/message` | POST (o WS relay) |
-
-**Moduli inclusi**: `agent_runner`, `agent_registry`, `filesystem_agent`, `llm`.
-
-**Flusso tool-call cross-service** (l'Agent Service non ha la WS):
-
-```
-┌──────────────┐            ┌──────────────┐            ┌──────────┐
-│ Agent Service│            │    Redis     │            │  Chat    │
-│ (batch run)  │            │              │            │ Service  │
-│              │            │              │            │ (ha WS)  │
-│ 1. Needs to  │  PUBLISH   │              │ SUBSCRIBE  │          │
-│    read file ├───────────►│tool_call:u123├───────────►│ 2. Invia │
-│    from      │            │              │            │    al    │
-│    device    │            │              │            │    device│
-│              │            │              │            │    via WS│
-│              │  SUBSCRIBE │              │  PUBLISH   │          │
-│ 4. Riceve   ◄────────────┤tool_result:id│◄───────────┤ 3. Device│
-│    risultato │            │              │            │    reply │
-└──────────────┘            └──────────────┘            └──────────┘
-```
-
-**Scaling**: 1–N repliche. Completamente stateless, scala indipendentemente dalla chat. Ogni replica processa batch job diversi. Può essere scalato a 0 se non ci sono agent attivi (risparmio risorse).
-
-**Vantaggio dello split**: Se 50 utenti triggerano agenti batch contemporaneamente, il Chat Service non ne risente — le risposte real-time rimangono veloci.
-
----
-
-### 1.4 Billing Service (`billing-service`)
-
-**Responsabilità**: Stripe checkout, webhook, subscription management.
-
-| Endpoint originale | Metodo |
-|---|---|
-| `/api/v1/billing/checkout` | POST |
-| `/api/v1/billing/webhook` | POST |
-| `/api/v1/billing/subscription` | GET / DELETE |
-
-**Database**: Tabelle `subscriptions` (schema `billing`).
-
-**Comunicazione inter-servizio**: Quando Stripe invia un webhook e il tier cambia, il Billing Service pubblica un evento su **Redis pub/sub** channel `tier_changed:{user_id}`. L'Auth Service aggiorna il campo `tier` nella tabella users. Al prossimo token refresh il JWT conterrà il tier aggiornato.
-
-**Scaling**: 1 replica sufficiente. Basso traffico.
-
----
-
-### 1.5 Servizi esclusi dall'MVP
-
-I seguenti servizi verranno aggiunti post-MVP come servizi indipendenti:
-
-| Servizio | Responsabilità | Note |
-|---|---|---|
-| **Storage Service** | S3 blobs CRUD, vector ops, backup | Le funzionalità vector/embed possono restare nel Chat Service per il MVP |
-| **Plugin Service** | Marketplace, install, revenue split | Feature non critica per il lancio |
-
----
-
-## 2. Tier Check — Dove e Come
-
-Il tier dell'utente (free/pro/power/team) determina rate-limiting, quote e accesso a funzionalità. Con i microservizi, **ogni servizio controlla il tier autonomamente** senza chiamare l'Auth Service.
-
-### Strategia: Tier nel JWT
-
-L'Auth Service include il `tier` come claim nel JWT al momento del login/refresh:
-
-```json
-{
-  "sub": "user_123",
-  "tier": "pro",
-  "exp": 1742515200,
-  "iat": 1742511600
-}
-```
-
-Ogni servizio:
-1. Decodifica il JWT con la chiave pubblica (già lo fa per l'auth)
-2. Legge `payload["tier"]` — **zero chiamate extra**
-3. Applica le sue regole di enforcement localmente
-
-```python
-# shared/auth.py — dependency FastAPI condivisa
-from fastapi import Depends, HTTPException, Request
-from jose import jwt
-
-PUBLIC_KEY = ...
-
-class CurrentUser:
-    def __init__(self, user_id: str, tier: str):
-        self.user_id = user_id
-        self.tier = tier
-
-async def get_current_user(request: Request) -> CurrentUser:
-    token = request.headers.get("Authorization", "").removeprefix("Bearer ")
-    payload = jwt.decode(token, PUBLIC_KEY, algorithms=["RS256"])
-    return CurrentUser(user_id=payload["sub"], tier=payload["tier"])
-
-def require_tier(*allowed_tiers: str):
-    """Dependency che blocca se il tier non è tra quelli ammessi."""
-    async def check(user: CurrentUser = Depends(get_current_user)):
-        if user.tier not in allowed_tiers:
-            raise HTTPException(403, "Tier insufficient")
-        return user
-    return check
-```
-
-### Cosa succede quando il tier cambia (upgrade/downgrade)?
-
-```
-┌──────────┐  Stripe webhook   ┌──────────┐  tier_changed   ┌──────────┐
-│  Stripe  │ ─────────────────►│ Billing  │ ───────────────►│   Auth   │
-│          │                    │ Service  │  (Redis pub/sub) │ Service  │
-└──────────┘                    └──────────┘                  └────┬─────┘
-                                                                   │
-                                                          UPDATE users
-                                                          SET tier = 'power'
-                                                                   │
-                                                    Al prossimo /refresh
-                                                    il JWT conterrà tier='power'
-```
-
-**Latenza del cambio**: Il tier si propaga al prossimo token refresh (tipicamente 15–30 min, o il client può forzare un refresh immediato dopo il checkout). Per il billing webhook, il downgrade può essere forzato invalidando il refresh token su Redis → il client è obbligato a ri-autenticarsi.
-
-### Dove si applica in ciascun servizio
-
-| Servizio | Enforcement |
-|---|---|
-| **Auth Service** | Nessuno (è lui che scrive il tier) |
-| **Chat Service** | Rate-limit per tier (req/min), quota messaggi |
-| **Agent Service** | Max agent configs, max runs/day, max concurrent batches |
-| **Billing Service** | Nessuno (gestisce i tier, non li consuma) |
-
-### Rate-limit distribuito via Redis
-
-Poiché ogni servizio ha le sue repliche, il rate-limiting deve essere **condiviso** via Redis:
-
-```python
-# shared/middleware/rate_limit.py
-import redis.asyncio as aioredis
-
-class DistributedRateLimiter:
-    def __init__(self, redis: aioredis.Redis):
-        self._redis = redis
-
-    async def check(self, user_id: str, tier: str, service: str) -> bool:
-        limits = {"free": 20, "pro": 60, "power": 120, "team": 200}
-        max_req = limits.get(tier, 20)
-        key = f"rate:{service}:{user_id}"
-
-        pipe = self._redis.pipeline()
-        pipe.incr(key)
-        pipe.expire(key, 60)
-        count, _ = await pipe.execute()
-
-        return count <= max_req
-```
-
----
-
-## 3. WebSocket con Scaling Orizzontale — Il Problema Chiave
-
-`DeviceConnectionManager` è un **singleton in-memory**:
-
-```python
-class DeviceConnectionManager:
-    def __init__(self):
-        self._connections: dict[str, DeviceConnection] = {}  # ← In-memory!
-```
-
-Con N istanze del Chat Service, il device si connette a **una sola** istanza. Quando un'altra istanza deve inviare un `tool_call` a quel device (es. un agent trigger da un'API call), non trova la connessione.
-
-### La soluzione: Redis Pub/Sub + Registry
-
-```
-┌──────────────────────────────────────────────────────────────┐
-│                     Redis                                    │
-│                                                              │
-│  Hash: ws:connections                                        │
-│    user_123 → instance_A                                     │
-│    user_456 → instance_B                                     │
-│                                                              │
-│  Pub/Sub channels:                                           │
-│    tool_call:{user_id}  → tool call payloads                 │
-│    tool_result:{call_id} → tool result payloads              │
-│    stream:{user_id}     → text_chunk streaming               │
-└──────────────────────────────────────────────────────────────┘
-
- Instance A (ha WS di user_123)     Instance B (deve chiamare tool su user_123)
- ┌───────────────────────┐          ┌───────────────────────┐
- │  1. Sottoscrive a     │          │  1. Lookup Redis Hash │
- │     tool_call:user_123│          │     → user_123 è su A │
- │                       │          │                       │
- │  2. Riceve tool_call  │◄─────────│  2. PUBLISH           │
- │     da Redis channel  │          │    tool_call:user_123 │
- │                       │          │    {id, action, ...}  │
- │  3. Invia al device   │          │                       │
- │     via WS            │          │  4. SUBSCRIBE         │
- │                       │          │    tool_result:{id}   │
- │  4. Device risponde   │          │                       │
- │     tool_result       │──────────│► 5. Riceve risultato  │
- │                       │          │                       │
- │  5. PUBLISH           │          │                       │
- │    tool_result:{id}   │          │                       │
- └───────────────────────┘          └───────────────────────┘
-```
-
-### Implementazione: `RedisDeviceManager`
-
-```python
-# chat-service/app/core/device_manager.py
-
-import asyncio
-import json
-import os
-import redis.asyncio as aioredis
-from dataclasses import dataclass, field
-from fastapi import WebSocket
-
-INSTANCE_ID = os.environ.get("INSTANCE_ID", os.urandom(8).hex())
-
-@dataclass
-class LocalConnection:
-    ws: WebSocket
-    device_id: str
-    pending_calls: dict[str, asyncio.Future[dict]] = field(default_factory=dict)
-
-
-class RedisDeviceManager:
-    """Device manager backed by Redis for cross-instance communication."""
-
-    def __init__(self, redis_url: str = "redis://redis:6379"):
-        self._redis = aioredis.from_url(redis_url)
-        self._pubsub = self._redis.pubsub()
-        self._local: dict[str, LocalConnection] = {}  # Solo connessioni locali
-        self._remote_futures: dict[str, asyncio.Future[dict]] = {}
-
-    async def start(self):
-        """Avvia il listener Redis per tool_call in arrivo."""
-        asyncio.create_task(self._listen_tool_calls())
-
-    # ── Registrazione ──
-
-    async def register(self, user_id: str, device_id: str, ws: WebSocket):
-        # Registra localmente
-        self._local[user_id] = LocalConnection(ws=ws, device_id=device_id)
-        # Registra in Redis quale istanza ha la connessione
-        await self._redis.hset("ws:connections", user_id, INSTANCE_ID)
-        # Sottoscrivi ai tool_call per questo utente
-        await self._pubsub.subscribe(f"tool_call:{user_id}")
-
-    async def unregister(self, user_id: str):
-        conn = self._local.pop(user_id, None)
-        if conn:
-            for fut in conn.pending_calls.values():
-                if not fut.done():
-                    fut.cancel()
-        await self._redis.hdel("ws:connections", user_id)
-        await self._pubsub.unsubscribe(f"tool_call:{user_id}")
-
-    # ── Presenza ──
-
-    async def is_online(self, user_id: str) -> bool:
-        return await self._redis.hexists("ws:connections", user_id)
-
-    # ── Tool-call round-trip (cross-instance) ──
-
-    async def execute_tool_call(self, user_id: str, payload: dict) -> dict:
-        """
-        Invia un tool_call al device dell'utente.
-        Funziona sia che la WS sia locale che su un'altra istanza.
-        """
-        call_id = payload["id"]
-
-        # Caso 1: connessione locale → invio diretto
-        if user_id in self._local:
-            conn = self._local[user_id]
-            loop = asyncio.get_event_loop()
-            fut: asyncio.Future[dict] = loop.create_future()
-            conn.pending_calls[call_id] = fut
-            await conn.ws.send_text(json.dumps({"type": "tool_call", **payload}))
-            return await asyncio.wait_for(fut, timeout=30.0)
-
-        # Caso 2: connessione remota → Redis pub/sub
-        loop = asyncio.get_event_loop()
-        fut = loop.create_future()
-        self._remote_futures[call_id] = fut
-
-        # Sottoscrivi al canale di risposta
-        result_channel = f"tool_result:{call_id}"
-        await self._pubsub.subscribe(result_channel)
-
-        # Pubblica il tool_call
-        await self._redis.publish(
-            f"tool_call:{user_id}",
-            json.dumps(payload),
-        )
-
-        try:
-            return await asyncio.wait_for(fut, timeout=30.0)
-        finally:
-            self._remote_futures.pop(call_id, None)
-            await self._pubsub.unsubscribe(result_channel)
-
-    # ── Risoluzione tool_result (da WS locale) ──
-
-    def resolve_local(self, user_id: str, call_id: str, result: dict):
-        conn = self._local.get(user_id)
-        if conn:
-            fut = conn.pending_calls.pop(call_id, None)
-            if fut and not fut.done():
-                fut.set_result(result)
-
-    async def resolve_and_publish(self, user_id: str, call_id: str, result: dict):
-        """Chiamato quando il device locale invia un tool_result."""
-        self.resolve_local(user_id, call_id, result)
-        # Pubblica anche su Redis per l'istanza remota che aspetta
-        await self._redis.publish(
-            f"tool_result:{call_id}",
-            json.dumps(result),
-        )
-
-    # ── Listener Redis ──
-
-    async def _listen_tool_calls(self):
-        """Loop che ascolta i tool_call in arrivo da altre istanze."""
-        async for message in self._pubsub.listen():
-            if message["type"] != "message":
-                continue
-            channel = message["channel"]
-            if isinstance(channel, bytes):
-                channel = channel.decode()
-
-            data = json.loads(message["data"])
-
-            if channel.startswith("tool_call:"):
-                # Un'altra istanza vuole che inviamo un tool_call al nostro device
-                user_id = channel.split(":", 1)[1]
-                conn = self._local.get(user_id)
-                if conn:
-                    await conn.ws.send_text(json.dumps({"type": "tool_call", **data}))
-
-            elif channel.startswith("tool_result:"):
-                # Risposta a un tool_call che abbiamo inviato tramite Redis
-                call_id = channel.split(":", 1)[1]
-                fut = self._remote_futures.pop(call_id, None)
-                if fut and not fut.done():
-                    fut.set_result(data)
-
-    # ── Stream cross-instance ──
-
-    async def publish_stream_chunk(self, user_id: str, chunk: dict):
-        """Pubblica un chunk di streaming su Redis (per REST→WS relay)."""
-        await self._redis.publish(f"stream:{user_id}", json.dumps(chunk))
-```
-
----
-
-## 4. Struttura Directory Proposta (MVP)
-
-```
-adiuva-api/
-├── docker-compose.yml          # Orchestrazione completa
-├── docker-compose.dev.yml      # Override per sviluppo locale
-├── shared/                     # Codice condiviso (montato come volume)
-│   ├── auth.py                 # JWT verification (chiave pubblica)
-│   ├── schemas.py              # Pydantic schemas condivisi
-│   ├── middleware/
-│   │   ├── rate_limit.py       # DistributedRateLimiter (Redis)
-│   │   └── sanitizer.py
-│   └── models/
-│       └── base.py             # SQLAlchemy base condivisa
-│
-├── auth-service/
-│   ├── Dockerfile
-│   ├── requirements.txt
-│   └── app/
-│       ├── main.py
-│       ├── config.py
-│       ├── db.py
-│       ├── models.py           # users, refresh_tokens
-│       ├── routes/
-│       │   └── auth.py
-│       └── services/
-│           ├── jwt_service.py  # RS256 signing
-│           └── user_service.py
-│
-├── chat-service/
-│   ├── Dockerfile
-│   ├── requirements.txt
-│   └── app/
-│       ├── main.py
-│       ├── config.py
-│       ├── db.py
-│       ├── models.py           # memory_*
-│       ├── routes/
-│       │   ├── device_ws.py    # WS connection owner
-│       │   └── chat.py         # REST fallback
-│       ├── core/
-│       │   ├── device_manager.py   # RedisDeviceManager
-│       │   ├── deep_agent.py       # Home + floating chat
-│       │   ├── memory_middleware.py
-│       │   ├── ws_context.py
-│       │   ├── output_formatter.py
-│       │   └── llm.py
-│       └── agents/                 # Tool definitions (used by deep_agent)
-│           ├── task_agent.py
-│           ├── project_agent.py
-│           ├── note_agent.py
-│           └── timeline_agent.py
-│
-├── agent-service/
-│   ├── Dockerfile
-│   ├── requirements.txt
-│   └── app/
-│       ├── main.py
-│       ├── config.py
-│       ├── db.py
-│       ├── models.py           # agent_run_logs, local/cloud_agent_configs
-│       ├── routes/
-│       │   ├── agents.py       # catalog, can-create, trigger
-│       │   └── agent_setup.py  # journey start/message
-│       ├── core/
-│       │   ├── agent_runner.py     # Batch classify → process
-│       │   ├── agent_registry.py
-│       │   ├── redis_executor.py   # execute_on_client via Redis pub/sub
-│       │   └── llm.py
-│       └── agents/
-│           ├── task_agent.py       # Tool definitions (batch context)
-│           ├── project_agent.py
-│           ├── note_agent.py
-│           ├── timeline_agent.py
-│           └── filesystem_agent.py
-│
-├── billing-service/
-│   ├── Dockerfile
-│   ├── requirements.txt
-│   └── app/
-│       ├── main.py
-│       ├── config.py
-│       ├── db.py
-│       ├── models.py           # subscriptions
-│       ├── routes/
-│       │   └── billing.py
-│       └── services/
-│           ├── stripe_service.py
-│           └── tier_manager.py
-│
-└── infra/
-    ├── traefik/
-    │   └── traefik.yml
-    ├── keys/
-    │   ├── jwt_private.pem     # Solo auth-service
-    │   └── jwt_public.pem      # Tutti i servizi
-    └── alembic/                # Migrazioni condivise o per-servizio
-```
-
----
-
-## 5. Docker Compose — Configurazione MVP
-
-```yaml
-# docker-compose.yml
-
-services:
-
-  # ══════════════════════════════════════════════════════════
-  # API Gateway
-  # ══════════════════════════════════════════════════════════
-  traefik:
-    image: traefik:v3.2
-    command:
-      - "--api.insecure=true"
-      - "--providers.docker=true"
-      - "--providers.docker.exposedbydefault=false"
-      - "--entrypoints.web.address=:80"
-      - "--entrypoints.websecure.address=:443"
-      - "--entrypoints.web.http.redirections.entrypoint.to=websecure"
-    ports:
-      - "80:80"
-      - "443:443"
-      - "8080:8080"   # Dashboard Traefik (disabilitare in prod)
-    volumes:
-      - /var/run/docker.sock:/var/run/docker.sock:ro
-      - ./infra/certs:/certs:ro
-    restart: unless-stopped
-
-  # ══════════════════════════════════════════════════════════
-  # Auth Service (2 repliche)
-  # ══════════════════════════════════════════════════════════
-  auth-service:
-    build: ./auth-service
-    deploy:
-      replicas: 2
-    env_file: .env
-    environment:
-      DATABASE_URL: postgresql+asyncpg://postgres:postgres@db:5432/adiuva
-      REDIS_URL: redis://redis:6379
-      JWT_PRIVATE_KEY_FILE: /run/secrets/jwt_private_key
-      SERVICE_NAME: auth
-    secrets:
-      - jwt_private_key
-      - jwt_public_key
-    labels:
-      - "traefik.enable=true"
-      - "traefik.http.routers.auth.rule=PathPrefix(`/api/v1/auth`)"
-      - "traefik.http.services.auth.loadbalancer.server.port=8000"
-    depends_on:
-      db:
-        condition: service_healthy
-      redis:
-        condition: service_healthy
-
-  # ══════════════════════════════════════════════════════════
-  # Chat Service — Real-time WS + Chat (scalabile)
-  # ══════════════════════════════════════════════════════════
-  chat-service:
-    build: ./chat-service
-    deploy:
-      replicas: 2
-    env_file: .env
-    environment:
-      DATABASE_URL: postgresql+asyncpg://postgres:postgres@db:5432/adiuva
-      REDIS_URL: redis://redis:6379
-      JWT_PUBLIC_KEY_FILE: /run/secrets/jwt_public_key
-      SERVICE_NAME: chat
-    secrets:
-      - jwt_public_key
-    labels:
-      - "traefik.enable=true"
-      # REST chat endpoint
-      - "traefik.http.routers.chat.rule=PathPrefix(`/api/v1/chat`)"
-      - "traefik.http.services.chat.loadbalancer.server.port=8000"
-      # WebSocket route con sticky session
-      - "traefik.http.routers.ws.rule=PathPrefix(`/api/v1/ws`)"
-      - "traefik.http.routers.ws.service=chat-ws"
-      - "traefik.http.services.chat-ws.loadbalancer.server.port=8000"
-      - "traefik.http.services.chat-ws.loadbalancer.sticky.cookie.name=ws_affinity"
-      - "traefik.http.services.chat-ws.loadbalancer.sticky.cookie.httpOnly=true"
-    depends_on:
-      db:
-        condition: service_healthy
-      redis:
-        condition: service_healthy
-
-  # ══════════════════════════════════════════════════════════
-  # Agent Service — Batch processing (scalabile indipendentemente)
-  # ══════════════════════════════════════════════════════════
-  agent-service:
-    build: ./agent-service
-    deploy:
-      replicas: 2
-    env_file: .env
-    environment:
-      DATABASE_URL: postgresql+asyncpg://postgres:postgres@db:5432/adiuva
-      REDIS_URL: redis://redis:6379
-      JWT_PUBLIC_KEY_FILE: /run/secrets/jwt_public_key
-      SERVICE_NAME: agent
-    secrets:
-      - jwt_public_key
-    labels:
-      - "traefik.enable=true"
-      - "traefik.http.routers.agents.rule=PathPrefix(`/api/v1/agents`)"
-      - "traefik.http.services.agents.loadbalancer.server.port=8000"
-    depends_on:
-      db:
-        condition: service_healthy
-      redis:
-        condition: service_healthy
-
-  # ══════════════════════════════════════════════════════════
-  # Billing Service (1 replica)
-  # ══════════════════════════════════════════════════════════
-  billing-service:
-    build: ./billing-service
-    deploy:
-      replicas: 1
-    env_file: .env
-    environment:
-      DATABASE_URL: postgresql+asyncpg://postgres:postgres@db:5432/adiuva
-      REDIS_URL: redis://redis:6379
-      JWT_PUBLIC_KEY_FILE: /run/secrets/jwt_public_key
-      SERVICE_NAME: billing
-    secrets:
-      - jwt_public_key
-    labels:
-      - "traefik.enable=true"
-      - "traefik.http.routers.billing.rule=PathPrefix(`/api/v1/billing`)"
-      - "traefik.http.services.billing.loadbalancer.server.port=8000"
-    depends_on:
-      db:
-        condition: service_healthy
-      redis:
-        condition: service_healthy
-
-  # ══════════════════════════════════════════════════════════
-  # Infrastruttura
-  # ══════════════════════════════════════════════════════════
-  db:
-    image: pgvector/pgvector:pg16
-    environment:
-      POSTGRES_USER: postgres
-      POSTGRES_PASSWORD: postgres
-      POSTGRES_DB: adiuva
-    volumes:
-      - postgres_data:/var/lib/postgresql/data
-    healthcheck:
-      test: ["CMD-SHELL", "pg_isready -U postgres"]
-      interval: 5s
-      timeout: 5s
-      retries: 5
-    restart: unless-stopped
-
-  redis:
-    image: redis:7-alpine
-    command: redis-server --maxmemory 256mb --maxmemory-policy allkeys-lru
-    volumes:
-      - redis_data:/data
-    healthcheck:
-      test: ["CMD", "redis-cli", "ping"]
-      interval: 5s
-      timeout: 3s
-      retries: 5
-    restart: unless-stopped
-
-  qdrant:
-    image: qdrant/qdrant:latest
-    volumes:
-      - qdrant_data:/qdrant/storage
-    restart: unless-stopped
-
-secrets:
-  jwt_private_key:
-    file: ./infra/keys/jwt_private.pem
-  jwt_public_key:
-    file: ./infra/keys/jwt_public.pem
-
-volumes:
-  postgres_data:
-  redis_data:
-  qdrant_data:
-```
-
----
-
-## 6. Configurazione Cloudflare + VPS
-
-### 6.1 DNS
-
-```
-api.tuodominio.com  →  A record  →  IP del VPS
-                    →  Proxy: ON (orange cloud)
-```
-
-### 6.2 Cloudflare Settings
-
-| Setting | Valore | Motivo |
-|---------|--------|--------|
-| SSL/TLS mode | **Full (Strict)** | Cloudflare ↔ VPS con certificato valido |
-| WebSocket | **ON** | Necessario per `/api/v1/ws/device` |
-| Proxy timeout | **100s** (Enterprise) o default | Le LLM calls possono durare 30s+ |
-| Under Attack Mode | Off (attivare se necessario) | |
-
-### 6.3 TLS sul VPS
-
-Due opzioni:
-- **Opzione A (consigliata)**: Cloudflare Origin Certificate → montato in Traefik
-- **Opzione B**: Let's Encrypt via Traefik (con DNS challenge Cloudflare)
-
-```yaml
-# traefik.yml — con Cloudflare Origin Certificate
-entryPoints:
-  websecure:
-    address: ":443"
-
-tls:
-  certificates:
-    - certFile: /certs/origin.pem
-      keyFile: /certs/origin-key.pem
-```
-
-### 6.4 Rete VPS
-
-```bash
-# UFW firewall — solo Cloudflare può raggiungere le porte 80/443
-# https://www.cloudflare.com/ips/
-ufw default deny incoming
-ufw allow from 173.245.48.0/20 to any port 443
-ufw allow from 103.21.244.0/22 to any port 443
-# ... (tutti gli IP range di Cloudflare)
-ufw allow ssh
-ufw enable
-```
-
----
-
-## 7. Comunicazione Inter-Servizio
-
-### 7.1 Redis Pub/Sub — Event Bus
-
-```
-┌──────────┐  tier_changed:user_123   ┌──────────┐
-│ Billing  │ ────────────────────────► │   Auth   │
-│ Service  │                           │ Service  │
-└──────────┘                           └──────────┘
-
-┌──────────┐  tool_call:user_123      ┌──────────┐
-│  Agent   │ ────────────────────────► │   Chat   │
-│ Service  │                           │ Service  │
-│ (batch)  │ ◄────────────────────────│ (ha WS)  │
-└──────────┘  tool_result:{call_id}    └──────────┘
-```
-
-### 7.2 Health Checks e Service Discovery
-
-Traefik gestisce automaticamente il service discovery via Docker labels. I servizi non devono conoscersi tra loro — comunicano solo via:
-- **Redis pub/sub** (tool-call cross-instance, tier events)
-- **Redis hash** (stato condiviso: `ws:connections`, rate-limit counters)
-- **PostgreSQL** (dati persistenti condivisi)
-
----
-
-## 8. Piano di Migrazione Incrementale (MVP)
-
-### Fase 1 — Preparazione (nel monolite attuale)
-1. Aggiungere Redis al `docker-compose.yml` attuale
-2. Migrare JWT da HS256 → RS256 (backward-compatible: accetta entrambi per un periodo)
-3. Implementare `RedisDeviceManager` come drop-in replacement del singleton in-memory
-4. Estrarre `shared/` con auth verification, schemas, middleware
-
-### Fase 2 — Auth Service (primo split)
-1. Estrarre `auth.py` routes + models in `auth-service/`
-2. Verificare che i JWT firmati da `auth-service` vengano validati dal monolite
-3. Aggiungere Traefik e routare `/api/v1/auth/*` al nuovo servizio
-4. Il monolite continua a servire tutto il resto
-
-### Fase 3 — Billing Service
-1. Estrarre billing routes, Stripe service, tier manager
-2. Configurare Redis pub/sub per `tier_changed` events
-3. Routare via Traefik
-
-### Fase 4 — Split Chat + Agent (il più delicato)
-1. Il monolite residuo contiene WS + chat + agents
-2. Separare Agent Service: estrarre `agent_runner`, `agent_registry`, `agent_setup`, route `/agents/*`
-3. Implementare `redis_executor.py` nell'Agent Service per tool-call via Redis
-4. Il Chat Service resta proprietario della WS e sottoscrive i canali `tool_call:{user_id}`
-5. Testare: trigger agent dall'Agent Service → tool_call via Redis → Chat Service → WS → device → risposta
-
-### Fase 5 — Scaling test
-1. Scalare Chat Service a 2 repliche, verificare sticky sessions
-2. Scalare Agent Service a 2 repliche, verificare batch processing distribuito
-3. Monitoring (Prometheus + Grafana) per ogni servizio
-
----
-
-## 9. Monitoraggio e Logging
-
-```yaml
-# Aggiungere al docker-compose.yml
-
-  prometheus:
-    image: prom/prometheus:latest
-    volumes:
-      - ./infra/prometheus/prometheus.yml:/etc/prometheus/prometheus.yml
-    restart: unless-stopped
-
-  grafana:
-    image: grafana/grafana:latest
-    ports:
-      - "3000:3000"
-    volumes:
-      - grafana_data:/var/lib/grafana
-    restart: unless-stopped
-
-  loki:
-    image: grafana/loki:latest
-    restart: unless-stopped
-```
-
-Ogni servizio espone `/metrics` (Prometheus) e scrive log strutturati (JSON) raccolti da Loki.
-
----
-
-## 10. Sizing VPS Minimo Consigliato (MVP)
-
-| Componente | CPU | RAM | Note |
-|---|---|---|---|
-| Traefik | 0.25 | 128MB | |
-| Auth Service ×2 | 0.25 ×2 | 128MB ×2 | Stateless, leggero |
-| Chat Service ×2 | 1.0 ×2 | 1GB ×2 | WS + streaming LLM |
-| Agent Service ×2 | 0.75 ×2 | 512MB ×2 | Batch LLM, CPU-bound |
-| Billing Service | 0.25 | 128MB | |
-| PostgreSQL | 1.0 | 1GB | |
-| Redis | 0.25 | 256MB | |
-| Qdrant | 0.5 | 512MB | |
-| **Totale MVP** | **~5.5 vCPU** | **~5 GB** | |
-
-**Raccomandazione**: VPS con **8 vCPU / 16 GB RAM** per avere margine. Hetzner CPX41 (~€30/mese) o equivalente. Senza Storage/Plugin si risparmia ~1 vCPU e 512MB rispetto alla versione completa.
-
----
-
-## Riepilogo Architettura MVP
-
-| Servizio | Repliche | Proprietario di |
-|---|---|---|
-| **Traefik** | 1 | Routing, TLS, sticky sessions |
-| **Auth Service** | 2 | JWT RS256, registrazione, login, profilo |
-| **Chat Service** | 2–N | WebSocket, home/floating chat, streaming |
-| **Agent Service** | 2–N | Batch processing, directory scan, agent setup |
-| **Billing Service** | 1 | Stripe, subscriptions, tier management |
-
-| Decisione | Scelta | Motivazione |
-|---|---|---|
-| API Gateway | Traefik | Nativo Docker, WebSocket support, service discovery automatico |
-| JWT | RS256 (asimmetrico) | Verifica distribuita senza contattare Auth Service |
-| Tier check | Claim nel JWT | Ogni servizio verifica localmente, zero roundtrip |
-| WebSocket scaling | Redis pub/sub + sticky cookies | Cross-instance tool-call routing |
-| Chat ↔ Agent split | Servizi separati | Batch CPU-bound non impatta real-time chat |
-| Agent → Device comms | Redis pub/sub via Chat Service | Agent non possiede la WS, usa un relay |
-| Rate limiting | Redis contatori distribuiti | Sliding window condivisa tra repliche |
-| Database | PostgreSQL condiviso | Semplicità MVP; split DB futuro facile |
-| TLS | Cloudflare Origin Certificate | Zero maintenance |
-| Orchestrazione | Docker Compose | Sufficiente per un singolo VPS |
-| Storage / Plugin | Post-MVP | Non critici per il lancio |

requirements.txt

@@ -4,6 +4,8 @@ gunicorn>=22.0.0
 langchain>=0.3.0
 langchain-openai>=0.3.0
 langchain-litellm>=0.1.0
+langgraph>=0.3.0
+deepagents>=0.4.10
 litellm>=1.50.0
 pydantic>=2.10.0
 pydantic-settings>=2.7.0

tests/test_agent_runner.py

@@ -10,13 +10,13 @@ Coverage:
     - run_local_agent             — file-read timeout path
     - run_local_agent             — LLM extraction error path
     - run_cloud_agent             — stub returns error immediately
-    - trigger_pending_runs        — skipped when config is client-owned
+    - trigger_pending_runs        — overdue local + cloud dispatched
     - trigger_pending_runs        — non-overdue skipped
     - trigger_pending_runs        — device_id filter for local agents
 
-    Integration:
+  Integration:
-        - POST /agents/can-create     — billing eligibility check
+    - POST /agents/{id}/run       — 404 on unknown agent
-        - POST /agents/trigger        — creates run log + dispatches background task
+    - POST /agents/{id}/run       — creates run log + dispatches background task
 """
 
 from __future__ import annotations
@@ -373,7 +373,7 @@ async def test_run_local_agent_happy_path():
     assert kwargs["items_processed"] == 1
     assert kwargs["items_created"] == 1
     assert kwargs["errors"] == []
-    assert kwargs["update_config_last_run"] is False
+    assert kwargs["update_config_last_run"] is True
 
     # Verify agent_run frame was sent.
     agent_run_frames = [f for f in sent_frames if f.get("type") == "agent_run"]
@@ -690,11 +690,31 @@ async def test_finalize_run_updates_cloud_config_last_run_at():
 
 @pytest.mark.asyncio
 async def test_trigger_pending_runs_no_overdue():
-    """Pending-run scan is skipped because agent config is client-owned."""
+    """If no agents are overdue trigger_pending_runs does nothing."""
+    from datetime import timedelta
+
+    config = _make_local_config()
+    config.last_run_at = datetime.now(timezone.utc) - timedelta(minutes=30)  # ran 30m ago
+    config.schedule_cron = "0 */6 * * *"  # every 6h — not due yet
+
+    mock_db_result_local = MagicMock()
+    mock_db_result_local.scalars.return_value.all.return_value = [config]
+
+    mock_db_result_cloud = MagicMock()
+    mock_db_result_cloud.scalars.return_value.all.return_value = []
 
     mgr = _make_manager()
 
-    with patch("app.core.agent_runner.run_local_agent", new_callable=AsyncMock) as mock_run:
+    with patch("app.core.agent_runner.async_session") as mock_session_factory, \
+         patch("app.core.agent_runner.run_local_agent", new_callable=AsyncMock) as mock_run:
+        mock_ctx = AsyncMock()
+        mock_ctx.__aenter__ = AsyncMock(return_value=mock_ctx)
+        mock_ctx.__aexit__ = AsyncMock(return_value=False)
+        mock_ctx.execute = AsyncMock(
+            side_effect=[mock_db_result_local, mock_db_result_cloud]
+        )
+        mock_session_factory.return_value = mock_ctx
+
         await trigger_pending_runs(_FREE_UID, "dev-001", mgr)
 
     mock_run.assert_not_called()
@@ -702,11 +722,31 @@ async def test_trigger_pending_runs_no_overdue():
 
 @pytest.mark.asyncio
 async def test_trigger_pending_runs_device_id_filter():
-    """Device filtering is no longer backend-managed in pending runs."""
+    """Local agents are only triggered for the matching device_id."""
+    # The DB query already filters by device_id, so we verify the SELECT
+    # includes the device_id filter by checking that a config bound to a
+    # different device is never dispatched.
+    #
+    # Since trigger_pending_runs queries with device_id == "dev-001",
+    # simulate the DB returning an empty list (as it would for a mismatch).
+    mock_db_result_local = MagicMock()
+    mock_db_result_local.scalars.return_value.all.return_value = []  # no match
+
+    mock_db_result_cloud = MagicMock()
+    mock_db_result_cloud.scalars.return_value.all.return_value = []
 
     mgr = _make_manager(device_id="dev-001")
 
-    with patch("app.core.agent_runner.run_local_agent", new_callable=AsyncMock) as mock_run:
+    with patch("app.core.agent_runner.async_session") as mock_session_factory, \
+         patch("app.core.agent_runner.run_local_agent", new_callable=AsyncMock) as mock_run:
+        mock_ctx = AsyncMock()
+        mock_ctx.__aenter__ = AsyncMock(return_value=mock_ctx)
+        mock_ctx.__aexit__ = AsyncMock(return_value=False)
+        mock_ctx.execute = AsyncMock(
+            side_effect=[mock_db_result_local, mock_db_result_cloud]
+        )
+        mock_session_factory.return_value = mock_ctx
+
         await trigger_pending_runs(_FREE_UID, "dev-001", mgr)
 
     mock_run.assert_not_called()
@@ -714,18 +754,56 @@ async def test_trigger_pending_runs_device_id_filter():
 
 @pytest.mark.asyncio
 async def test_trigger_pending_runs_dispatches_overdue():
-    """No pending runs are dispatched by backend after config deprecation."""
+    """Overdue local agent triggers run_local_agent sequentially."""
+    config = _make_local_config()  # last_run_at=None → always overdue
+
+    mock_db_result_local = MagicMock()
+    mock_db_result_local.scalars.return_value.all.return_value = [config]
+
+    mock_db_result_cloud = MagicMock()
+    mock_db_result_cloud.scalars.return_value.all.return_value = []
 
     mgr = _make_manager()
 
-    with patch("app.core.agent_runner.run_local_agent", new_callable=AsyncMock) as mock_run:
+    call_order: list[str] = []
+
+    async def _mock_run_local(user_id, cfg, run_log, device_mgr):
+        call_order.append("run_local")
+
+    with patch("app.core.agent_runner.async_session") as mock_session_factory, \
+         patch("app.core.agent_runner.run_local_agent", side_effect=_mock_run_local):
+        # First call: query configs. Subsequent calls: create run_log.
+        mock_query_ctx = AsyncMock()
+        mock_query_ctx.__aenter__ = AsyncMock(return_value=mock_query_ctx)
+        mock_query_ctx.__aexit__ = AsyncMock(return_value=False)
+        mock_query_ctx.execute = AsyncMock(
+            side_effect=[mock_db_result_local, mock_db_result_cloud]
+        )
+
+        run_log_obj = AgentRunLog(
+            id=str(uuid.uuid4()),
+            agent_id=config.id,
+            agent_type="local",
+            user_id=_FREE_UID,
+            status="running",
+            started_at=datetime.now(timezone.utc),
+        )
+        mock_insert_ctx = AsyncMock()
+        mock_insert_ctx.__aenter__ = AsyncMock(return_value=mock_insert_ctx)
+        mock_insert_ctx.__aexit__ = AsyncMock(return_value=False)
+        mock_insert_ctx.add = MagicMock()
+        mock_insert_ctx.commit = AsyncMock()
+        mock_insert_ctx.refresh = AsyncMock(side_effect=lambda obj: None)
+
+        mock_session_factory.side_effect = [mock_query_ctx, mock_insert_ctx]
+
         await trigger_pending_runs(_FREE_UID, "dev-001", mgr)
 
-    mock_run.assert_not_called()
+    assert call_order == ["run_local"]
 
 
 # ---------------------------------------------------------------------------
-# Integration: POST /agents/can-create and /agents/trigger
+# Integration: POST /agents/{id}/run
 # ---------------------------------------------------------------------------
 
 
@@ -742,67 +820,50 @@ def _override_db(db_session):
 
 
 @pytest.mark.asyncio
-async def test_can_create_agent_allows_when_under_limit(client):
+async def test_trigger_run_unknown_agent(client):
-    """POST /agents/can-create returns allowed=True when under tier limit."""
+    """POST /agents/{id}/run returns 404 for unknown agent id."""
     resp = client.post(
-        "/api/v1/agents/can-create",
+        f"/api/v1/agents/{uuid.uuid4()}/run",
-        json={"active_agents": 0},
+        headers=auth_header("power"),
-        headers=auth_header("free"),
     )
-    assert resp.status_code == 200
+    assert resp.status_code == 404
-    body = resp.json()
-    assert body["allowed"] is True
-    assert body["tier"] == "free"
-    assert body["active_agents"] == 0
-    assert body["limit"] == 2
-
-
-@pytest.mark.asyncio
-async def test_can_create_agent_denies_when_at_limit(client):
-    """POST /agents/can-create returns allowed=False at free-tier limit."""
-    resp = client.post(
-        "/api/v1/agents/can-create",
-        json={"active_agents": 2},
-        headers=auth_header("free"),
-    )
-    assert resp.status_code == 200
-    body = resp.json()
-    assert body["allowed"] is False
-    assert body["limit"] == 2
 
 
 @pytest.mark.asyncio
 async def test_trigger_run_local_agent_creates_run_log(client, db_session):
-    """POST /agents/trigger creates a local run log and dispatches background task."""
+    """POST /agents/{id}/run creates a run log and dispatches a background task."""
-    dispatched: list[tuple[str, str]] = []
+    # Create the local agent config in the DB.
+    config = LocalAgentConfig(
+        id=str(uuid.uuid4()),
+        user_id=TEST_USER_IDS["power"],
+        device_id="dev-001",
+        name="My Agent",
+        directory_paths=["/home/user/docs"],
+        data_types=["tasks"],
+        prompt_template="Extract tasks.",
+        file_extensions=[".txt"],
+        schedule_cron="0 */6 * * *",
+        enabled=True,
+    )
+    db_session.add(config)
+    await db_session.commit()
+
+    dispatched: list = []
 
     async def _fake_run(user_id, cfg, run_log, device_mgr):
         dispatched.append((user_id, cfg.id))
 
-    def _fake_create_task(coro):
-        coro.close()
-        return MagicMock()
-
     with patch("app.api.routes.agents.run_local_agent", new_callable=AsyncMock, side_effect=_fake_run), \
+         patch("app.api.routes.agents.run_cloud_agent", new_callable=AsyncMock), \
          patch("asyncio.create_task") as mock_create_task:
-        mock_create_task.side_effect = _fake_create_task
         resp = client.post(
-            "/api/v1/agents/trigger",
+            f"/api/v1/agents/{config.id}/run",
-            json={
-                "directory": "/home/user/docs",
-                "what_to_extract": ["task", "note"],
-                "actions_by_type": {"task": ["add", "update"], "note": ["add"]},
-                "batch_interval": "0 */6 * * *",
-                "custom_agent_prompt": "Extract tasks and notes.",
-                "active_agents": 0,
-            },
             headers=auth_header("power"),
         )
 
     assert resp.status_code == 202
     data = resp.json()
-    assert isinstance(data["agent_id"], str)
+    assert data["agent_id"] == config.id
-    assert data["agent_id"]
     assert data["status"] == "running"
     assert data["agent_type"] == "local"
 

tests/test_classify_file.py

@@ -1,184 +0,0 @@
-"""Unit tests for Step 1 file classification (_classify_file).
-
-These tests call the real LLM so they require OPENAI_API_KEY / LLM env vars.
-Run with: pytest tests/test_classify_file.py -v
-
-To run a quick manual check against a real file without the full UI:
-    python -m tests.test_classify_file <path/to/file.txt> [project_name...]
-"""
-
-from __future__ import annotations
-
-import asyncio
-import sys
-
-import pytest
-
-from app.core.agent_runner import _classify_file
-
-
-# ── Fixtures ──────────────────────────────────────────────────────────────
-
-PROJECTS_SAMPLE = [
-    {
-        "id": "aaaa-0001-0000-0000-000000000001",
-        "name": "ARPA Sicilia POC",
-        "status": "active",
-        "aiSummary": "Proof of concept for AI features targeting ARPA Sicilia agency.",
-    },
-    {
-        "id": "bbbb-0002-0000-0000-000000000002",
-        "name": "SNAM AI Meeting Prep",
-        "status": "active",
-        "aiSummary": "AI-assisted preparation of meeting materials for SNAM.",
-    },
-    {
-        "id": "cccc-0003-0000-0000-000000000003",
-        "name": "SFERA+ Wave 2",
-        "status": "active",
-        "aiSummary": "Second wave of the SFERA+ whitelist project.",
-    },
-]
-
-ARPA_EMAIL = """\
-to: roberto.musso@hpe.com; luca.tondin@hpecds.com
-isImportance: normal
-hasAttachment: True
----
-## Body
-Buongiorno,
-
-In riferimento alla riunione di ieri sul POC ARPA Sicilia, vi invio il riassunto
-dei deliverable concordati:
-- Preparare demo entro il 30 marzo
-- Condividere documentazione tecnica con il team ARPA
-- Fissare call di follow-up la prossima settimana
-
-Cordiali saluti
-Roberto Marchetti
-"""
-
-SNAM_EMAIL = """\
-to: roberto.musso@hpe.com
-isImportance: high
-hasAttachment: False
----
-## Body
-Ciao,
-ti invio l'agenda per la riunione SNAM di domani.
-Per favore conferma la tua presenza.
-"""
-
-UNRELATED_EMAIL = """\
-to: roberto.musso@hpe.com
-isImportance: normal
----
-## Body
-Benvenuto nel programma HPE Employee Learning Series.
-Completa la formazione richiesta entro la fine del trimestre.
-"""
-
-
-# ── Tests ─────────────────────────────────────────────────────────────────
-
-
-@pytest.mark.asyncio
-async def test_classify_arpa_matches_existing():
-    project_id, domains, new_name = await _classify_file(
-        file_path="arpa_email.txt",
-        file_content=ARPA_EMAIL,
-        projects=PROJECTS_SAMPLE,
-        config_data_types=["tasks", "notes", "timelines"],
-    )
-    assert project_id == "aaaa-0001-0000-0000-000000000001", (
-        f"Expected ARPA project, got project_id={project_id!r} new_name={new_name!r}"
-    )
-    assert new_name is None
-
-
-@pytest.mark.asyncio
-async def test_classify_snam_matches_existing():
-    project_id, domains, new_name = await _classify_file(
-        file_path="snam_email.txt",
-        file_content=SNAM_EMAIL,
-        projects=PROJECTS_SAMPLE,
-        config_data_types=["tasks", "notes"],
-    )
-    assert project_id == "bbbb-0002-0000-0000-000000000002", (
-        f"Expected SNAM project, got project_id={project_id!r} new_name={new_name!r}"
-    )
-
-
-@pytest.mark.asyncio
-async def test_classify_unrelated_returns_new():
-    project_id, domains, new_name = await _classify_file(
-        file_path="learning_email.txt",
-        file_content=UNRELATED_EMAIL,
-        projects=PROJECTS_SAMPLE,
-        config_data_types=["tasks", "notes"],
-    )
-    assert project_id == "new"
-    assert new_name is not None  # LLM should suggest a name
-
-
-@pytest.mark.asyncio
-async def test_classify_empty_file_returns_new():
-    project_id, domains, new_name = await _classify_file(
-        file_path="empty.txt",
-        file_content="   ",
-        projects=PROJECTS_SAMPLE,
-        config_data_types=["tasks"],
-    )
-    assert project_id == "new"
-
-
-@pytest.mark.asyncio
-async def test_classify_no_projects_returns_new():
-    project_id, domains, new_name = await _classify_file(
-        file_path="arpa_email.txt",
-        file_content=ARPA_EMAIL,
-        projects=[],
-        config_data_types=["tasks", "notes"],
-    )
-    assert project_id == "new"
-    assert new_name is not None
-
-
-# ── CLI quick-test runner ─────────────────────────────────────────────────
-
-
-async def _cli_test(file_path: str, project_names: list[str]) -> None:
-    """Run Step 1 classification against a real file from the CLI."""
-    import json
-    from pathlib import Path
-
-    content = Path(file_path).read_text(encoding="utf-8", errors="replace")
-    projects = [
-        {"id": f"test-id-{i:04d}", "name": name, "status": "active", "aiSummary": ""}
-        for i, name in enumerate(project_names)
-    ]
-
-    print(f"\nClassifying: {file_path}")
-    print(f"Projects in context: {[p['name'] for p in projects]}\n")
-
-    project_id, domains, new_name = await _classify_file(
-        file_path=file_path,
-        file_content=content,
-        projects=projects,
-        config_data_types=["tasks", "notes", "timelines"],
-    )
-
-    result = {
-        "project_id": project_id,
-        "matched_name": next((p["name"] for p in projects if p["id"] == project_id), None),
-        "new_project_name": new_name,
-        "domains": domains,
-    }
-    print(json.dumps(result, indent=2, ensure_ascii=False))
-
-
-if __name__ == "__main__":
-    if len(sys.argv) < 2:
-        print("Usage: python -m tests.test_classify_file <file_path> [project_name ...]")
-        sys.exit(1)
-    asyncio.run(_cli_test(sys.argv[1], sys.argv[2:]))

tests/test_deep_agent.py

@@ -1,288 +0,0 @@
-"""Unit tests for single-agent deep_agent flows with mocked tool results."""
-
-from __future__ import annotations
-
-from datetime import date, timedelta
-from types import SimpleNamespace
-from unittest.mock import patch
-
-import pytest
-from langchain_core.messages import AIMessage, ToolMessage
-
-from app.core.deep_agent import (
-    _infer_floating_domain,
-    _normalize_tagged_list_lines,
-    run_floating,
-    run_floating_stream,
-    run_home,
-)
-
-
-class _FakeTool:
-    name = "list_tasks"
-
-    async def ainvoke(self, args):
-        return {"rows": [{"id": "task-1", "title": "Mock Task"}], "echo": args}
-
-
-class _FakeLLM:
-    def __init__(self) -> None:
-        self.agent_calls = 0
-
-    def bind_tools(self, _tools):
-        return self
-
-    async def ainvoke(self, messages):
-        system_prompt = str(getattr(messages[0], "content", "")) if messages else ""
-        if "strict domain classifier" in system_prompt:
-            return AIMessage(content='{"type":"timeline","id":"tl-1","section":null}')
-
-        self.agent_calls += 1
-        if self.agent_calls == 1:
-            return AIMessage(
-                content="",
-                tool_calls=[
-                    {
-                        "id": "call-1",
-                        "name": "list_tasks",
-                        "args": {"project_id": "proj-1"},
-                    }
-                ],
-            )
-
-        tool_messages = [m for m in messages if isinstance(m, ToolMessage)]
-        assert tool_messages, "Expected at least one tool message"
-        return AIMessage(content=f"Final answer from mocked tool: {tool_messages[-1].content}")
-
-    async def astream(self, _messages):
-        yield SimpleNamespace(content="stream-")
-        yield SimpleNamespace(content="ok")
-
-
-@pytest.mark.asyncio
-async def test_run_home_uses_mocked_tool_result():
-    fake_llm = _FakeLLM()
-
-    with patch("app.core.deep_agent.get_llm", return_value=fake_llm), patch(
-        "app.core.deep_agent._all_tools", return_value=[_FakeTool()]
-    ):
-        out = await run_home("user-1", "list my tasks", {})
-
-    assert "Final answer from mocked tool" in out
-    assert "Mock Task" in out
-
-
-@pytest.mark.asyncio
-async def test_run_floating_stream_emits_domain_then_tokens_with_mocked_tool_result():
-    fake_llm = _FakeLLM()
-
-    with patch("app.core.deep_agent.get_llm", return_value=fake_llm), patch(
-        "app.core.deep_agent._all_tools", return_value=[_FakeTool()]
-    ):
-        events = []
-        async for event in run_floating_stream(
-            "user-1",
-            "show me timeline updates",
-            {"scope": {"type": "timeline", "id": "tl-1"}},
-        ):
-            events.append(event)
-
-    assert events[0] == (
-        "floating_domain",
-        {"type": "timeline", "id": "tl-1", "section": None},
-    )
-    assert ("token", "stream-") in events
-    assert ("token", "ok") in events
-
-
-@pytest.mark.asyncio
-async def test_infer_floating_domain_prefers_message_intent_over_scope_type():
-    class _ClassifierOnlyLLM:
-        async def ainvoke(self, _messages):
-            return AIMessage(
-                content='{"type":"project","id":"213213-312321-312312-421321","section":"task"}'
-            )
-
-    with patch("app.core.deep_agent.get_llm", return_value=_ClassifierOnlyLLM()):
-        domain = await _infer_floating_domain(
-            "Quali sono i miei task per il progetto X",
-            {
-                "scope": {"type": "timeline"},
-                "resolved_project_id": "213213-312321-312312-421321",
-            },
-        )
-
-    assert domain == {
-        "type": "project",
-        "id": "213213-312321-312312-421321",
-        "section": "task",
-    }
-
-
-def test_normalize_tagged_list_lines_rewrites_mixed_task_lines_to_tag_only_lines():
-    raw = (
-        "Certo!\n\n"
-        "1. **Task A** — priorita high <task>[task-1]</task>\n"
-        "2. **Task B** — priorita medium <task>[task-2]</task>\n"
-    )
-
-    out = _normalize_tagged_list_lines(raw, "quali sono le prossime attivita?")
-
-    assert "<task>[task-1]</task>" in out
-    assert "<task>[task-2]</task>" in out
-    assert "Task A" not in out
-    assert "Task B" not in out
-
-
-def test_normalize_tagged_list_lines_filters_upcoming_timeline_query_to_current_month_future_only():
-    today = date.today()
-    tomorrow = today + timedelta(days=1)
-    yesterday = today - timedelta(days=1)
-    next_month = (today.replace(day=28) + timedelta(days=5)).replace(day=1)
-
-    raw = "\n".join(
-        [
-            f"- Milestone old — {yesterday.strftime('%d/%m/%Y')} <timeline>[tl-old]</timeline>",
-            f"- Milestone next — {tomorrow.strftime('%d/%m/%Y')} <timeline>[tl-next]</timeline>",
-            f"- Milestone future — {next_month.strftime('%d/%m/%Y')} <timeline>[tl-future]</timeline>",
-        ]
-    )
-
-    out = _normalize_tagged_list_lines(raw, "invece i miei eventi prossimi?")
-
-    assert "<timeline>[tl-next]</timeline>" in out
-    assert "<timeline>[tl-old]</timeline>" not in out
-    assert "<timeline>[tl-future]</timeline>" not in out
-
-
-@pytest.mark.asyncio
-async def test_run_floating_strips_xml_like_tags_from_final_text():
-    fake_llm = _FakeLLM()
-
-    async def _fake_run_single_agent(**_kwargs):
-        return (
-            "Hai 1 task:\\n"
-            "Mail barra in prod <task>[180faff3-507d-4d88-aba8-66f204eb59ef]</task>"
-        )
-
-    with patch("app.core.deep_agent.get_llm", return_value=fake_llm), patch(
-        "app.core.deep_agent._run_single_agent", side_effect=_fake_run_single_agent
-    ):
-        text, _domain = await run_floating(
-            "user-1",
-            "quali task ho?",
-            {"scope": {"type": "task"}},
-        )
-
-    assert "<task>" not in text
-    assert "</task>" not in text
-    assert "[180faff3-507d-4d88-aba8-66f204eb59ef]" not in text
-
-
-@pytest.mark.asyncio
-async def test_run_floating_stream_strips_xml_like_tags_from_streamed_text():
-    fake_llm = _FakeLLM()
-
-    async def _fake_stream(**_kwargs):
-        yield "token", "Hai 1 task:\\n"
-        yield "token", "Mail barra in prod <task>[180faff3-507d-4d88-aba8-66f204eb59ef]</task>"
-
-    with patch("app.core.deep_agent.get_llm", return_value=fake_llm), patch(
-        "app.core.deep_agent._run_single_agent_stream", side_effect=_fake_stream
-    ):
-        events = []
-        async for event in run_floating_stream(
-            "user-1",
-            "quali task ho?",
-            {"scope": {"type": "task"}},
-        ):
-            events.append(event)
-
-    token_events = [str(data) for event_type, data in events if event_type == "token"]
-    combined = "".join(token_events)
-    assert "<task>" not in combined
-    assert "</task>" not in combined
-    assert "[180faff3-507d-4d88-aba8-66f204eb59ef]" not in combined
-
-
-@pytest.mark.asyncio
-async def test_run_floating_stream_falls_back_to_final_response_content_when_astream_is_empty():
-    class _NoChunkLLM:
-        def __init__(self) -> None:
-            self.calls = 0
-
-        def bind_tools(self, _tools):
-            return self
-
-        async def ainvoke(self, _messages):
-            self.calls += 1
-            if self.calls == 1:
-                return AIMessage(
-                    content="",
-                    tool_calls=[
-                        {
-                            "id": "call-1",
-                            "name": "list_tasks",
-                            "args": {},
-                        }
-                    ],
-                )
-            return AIMessage(content="No notes found.")
-
-        async def astream(self, _messages):
-            if False:
-                yield None
-
-    with patch("app.core.deep_agent.get_llm", return_value=_NoChunkLLM()), patch(
-        "app.core.deep_agent._all_tools", return_value=[_FakeTool()]
-    ):
-        events = []
-        async for event in run_floating_stream(
-            "user-1",
-            "quali sono le note?",
-            {"scope": {"type": "note"}},
-        ):
-            events.append(event)
-
-    assert events[0][0] == "floating_domain"
-    assert ("token", "No notes found.") in events
-
-
-@pytest.mark.asyncio
-async def test_run_floating_returns_fallback_when_sanitization_would_empty_text():
-    fake_llm = _FakeLLM()
-
-    async def _fake_run_single_agent(**_kwargs):
-        return "<task>[180faff3-507d-4d88-aba8-66f204eb59ef]</task>"
-
-    with patch("app.core.deep_agent.get_llm", return_value=fake_llm), patch(
-        "app.core.deep_agent._run_single_agent", side_effect=_fake_run_single_agent
-    ):
-        text, _domain = await run_floating(
-            "user-1",
-            "quali task ho?",
-            {"scope": {"type": "task"}},
-        )
-
-    assert text == "No results found."
-
-
-@pytest.mark.asyncio
-async def test_run_floating_stream_returns_fallback_when_sanitization_would_empty_text():
-    fake_llm = _FakeLLM()
-
-    async def _fake_stream(**_kwargs):
-        yield "token", "<task>[180faff3-507d-4d88-aba8-66f204eb59ef]</task>"
-
-    with patch("app.core.deep_agent.get_llm", return_value=fake_llm), patch(
-        "app.core.deep_agent._run_single_agent_stream", side_effect=_fake_stream
-    ):
-        events = []
-        async for event in run_floating_stream(
-            "user-1",
-            "quali task ho?",
-            {"scope": {"type": "task"}},
-        ):
-            events.append(event)
-
-    assert ("token", "No results found.") in events

tests/test_memory_middleware.py

@@ -110,32 +110,6 @@ async def test_enrich_context_returns_episodic_memory(db_session, user_with_key)
     assert any("Q1 tasks" in s for s in ctx["episodic_memory"])
 
 
-@pytest.mark.asyncio
-async def test_enrich_context_filters_episodic_by_session_id(db_session, user_with_key):
-    target_session = str(uuid.uuid4())
-    other_session = str(uuid.uuid4())
-    db_session.add(MemoryEpisodic(
-        id=str(uuid.uuid4()),
-        user_id=USER_ID,
-        summary_encrypted=_enc("Target session memory"),
-        session_id=target_session,
-    ))
-    db_session.add(MemoryEpisodic(
-        id=str(uuid.uuid4()),
-        user_id=USER_ID,
-        summary_encrypted=_enc("Other session memory"),
-        session_id=other_session,
-    ))
-    await db_session.commit()
-
-    middleware = MemoryMiddleware(db_session)
-    ctx = await middleware.enrich_context(USER_ID, "any message", session_id=target_session)
-
-    episodic = ctx.get("episodic_memory", [])
-    assert any("Target session" in s for s in episodic)
-    assert not any("Other session" in s for s in episodic)
-
-
 @pytest.mark.asyncio
 async def test_enrich_context_returns_proactive_hints(db_session, user_with_key):
     # Add one pattern above threshold and one below
@@ -255,40 +229,6 @@ async def test_update_core_upsert(db_session, user_with_key):
     assert _dec(rows[0].value_encrypted) == "fr"
 
 
-@pytest.mark.asyncio
-async def test_core_block_edit_ops(db_session, user_with_key):
-    middleware = MemoryMiddleware(db_session)
-
-    await middleware.update_core(USER_ID, "human", "Name: Roberto")
-    await middleware.append_core(USER_ID, "human", "Timezone: Europe/Rome")
-    replaced = await middleware.replace_core(USER_ID, "human", "Roberto", "Robert")
-
-    blocks = await middleware.list_core_blocks(USER_ID)
-    human = next(b for b in blocks if b["label"] == "human")
-
-    assert replaced is True
-    assert "Name: Robert" in human["value"]
-    assert "Timezone: Europe/Rome" in human["value"]
-
-    deleted = await middleware.delete_core(USER_ID, "human")
-    assert deleted is True
-    assert await middleware.get_core_block(USER_ID, "human") is None
-
-
-@pytest.mark.asyncio
-async def test_archival_and_recall_search_helpers(db_session, user_with_key):
-    middleware = MemoryMiddleware(db_session)
-
-    await middleware.insert_archival(USER_ID, "Project whitelist has release risk", source="assistant")
-    await middleware.store_episode(USER_ID, str(uuid.uuid4()), "How is whitelist?", "Whitelist is delayed")
-
-    arch = await middleware.search_archival(USER_ID, "whitelist", top_k=3)
-    rec = await middleware.search_recall(USER_ID, "delayed", top_k=3)
-
-    assert any("whitelist" in item.lower() for item in arch)
-    assert any("delayed" in item.lower() for item in rec)
-
-
 # ── End-to-end WS: memory middleware is called during home_request ────────────
 
 def test_home_request_calls_memory_middleware(client):
@@ -300,20 +240,21 @@ def test_home_request_calls_memory_middleware(client):
         def __init__(self, db):
             pass
 
-        async def enrich_context(self, user_id, message, **kwargs):
+        async def enrich_context(self, user_id, message):
             enrich_calls.append((user_id, message))
             return {"core_memory": {"tz": "UTC"}}
 
-        async def store_episode(self, user_id, session_id, message, response, **kwargs):
+        async def store_episode(self, user_id, session_id, message, response):
             store_calls.append((user_id, session_id, message, response))
 
     token = make_jwt("power", user_id=USER_ID)
     session_id = str(uuid.uuid4())
 
-    async def _mock_stream(user_id, message, context):
+    async def _mock_stream(user_id, message, context, db_session_factory=None):
         # Verify memory context was injected
         assert context.get("core_memory") == {"tz": "UTC"}
-        yield "token", "Done"
+        yield ("token", "Done")
+        yield ("mutations", [])
 
     with (
         patch("app.api.routes.device_ws.MemoryMiddleware", _MockMiddleware),

tests/test_output_formatter.py

@@ -1,82 +1,214 @@
-"""Tests for app.core.output_formatter.StreamFormatter."""
+"""Tests for app.core.output_formatter — HomeFormatter and FloatingFormatter."""
 
 from __future__ import annotations
 
 import pytest
 
-from app.core.output_formatter import StreamFormatter
+from app.core.output_formatter import HomeFormatter, FloatingFormatter
-from app.schemas import WsFloatingDomain, WsStreamEnd, WsStreamStart, WsStreamText
+from app.schemas import (
+    WsFloatingDomain,
+    WsStreamEnd,
+    WsStreamStart,
+    WsStreamText,
+)
 
 
+# ── helpers ───────────────────────────────────────────────────────────────────
+
 async def _stream(*events: tuple[str, object]):
+    """Async generator that yields (event_type, data) tuples."""
     for event in events:
         yield event
 
 
-async def _collect(formatter: StreamFormatter, event_stream):
+async def collect(formatter, event_stream):
     frames = []
     async for frame in formatter.format(event_stream):
         frames.append(frame)
     return frames
 
 
+# ── HomeFormatter ─────────────────────────────────────────────────────────────
+
 @pytest.mark.asyncio
-async def test_stream_formatter_text_stream() -> None:
+async def test_home_formatter_plain_text():
-    formatter = StreamFormatter(request_id="req-1")
+    req_id = "req-1"
-    frames = await _collect(
+    events = [
-        formatter,
+        ("token", "Hello world"),
-        _stream(("token", "Hello"), ("token", " world")),
+        ("mutations", []),
-    )
+    ]
+    formatter = HomeFormatter(request_id=req_id)
+    frames = await collect(formatter, _stream(*events))
 
     assert isinstance(frames[0], WsStreamStart)
-    assert isinstance(frames[1], WsStreamText)
+    assert frames[0].request_id == req_id
-    assert frames[1].chunk == "Hello"
+    text_frames = [f for f in frames if isinstance(f, WsStreamText)]
-    assert isinstance(frames[2], WsStreamText)
+    assert any("Hello world" in f.chunk for f in text_frames)
-    assert frames[2].chunk == " world"
     assert isinstance(frames[-1], WsStreamEnd)
 
 
 @pytest.mark.asyncio
-async def test_stream_formatter_floating_domain_first() -> None:
+async def test_home_formatter_entity_tags_passed_through():
-    formatter = StreamFormatter(request_id="req-2")
+    """Entity tags are streamed as-is — the frontend parses them."""
-    frames = await _collect(
+    req_id = "req-2"
-        formatter,
+    events = [
-        _stream(
+        ("token", "Here is your project:\n<project>[abc-123]</project>\nAll good."),
-            (
+        ("mutations", []),
-                "floating_domain",
+    ]
-                {"type": "node", "id": "n-1", "section": None},
+    formatter = HomeFormatter(request_id=req_id)
-            ),
+    frames = await collect(formatter, _stream(*events))
-            ("token", "Summary"),
+
-        ),
+    text = "".join(f.chunk for f in frames if isinstance(f, WsStreamText))
-    )
+    assert "<project>[abc-123]</project>" in text
+    assert "Here is your project:" in text
+    assert "All good." in text
+
+
+@pytest.mark.asyncio
+async def test_home_formatter_multiple_tags_passed_through():
+    req_id = "req-3"
+    events = [
+        ("token", "<project>[p1]</project>\nText\n<task>[t1,t2]</task>"),
+        ("mutations", []),
+    ]
+    formatter = HomeFormatter(request_id=req_id)
+    frames = await collect(formatter, _stream(*events))
+
+    text = "".join(f.chunk for f in frames if isinstance(f, WsStreamText))
+    assert "<project>[p1]</project>" in text
+    assert "<task>[t1,t2]</task>" in text
+
+
+@pytest.mark.asyncio
+async def test_home_formatter_tool_end_ignored():
+    """tool_end events are silently ignored by HomeFormatter."""
+    req_id = "req-4"
+    events = [
+        ("tool_end", {"name": "task_agent", "result": "3 tasks"}),
+        ("token", "No tags here."),
+        ("mutations", []),
+    ]
+    formatter = HomeFormatter(request_id=req_id)
+    frames = await collect(formatter, _stream(*events))
+
+    text = "".join(f.chunk for f in frames if isinstance(f, WsStreamText))
+    assert text == "No tags here."
+
+
+@pytest.mark.asyncio
+async def test_home_formatter_mutations_in_stream_end():
+    req_id = "req-5"
+    muts = [{"action": "insert", "table": "tasks", "data": {"id": "t1"}}]
+    events = [
+        ("token", "Done"),
+        ("mutations", muts),
+    ]
+    formatter = HomeFormatter(request_id=req_id)
+    frames = await collect(formatter, _stream(*events))
+
+    end_frame = frames[-1]
+    assert isinstance(end_frame, WsStreamEnd)
+    assert len(end_frame.mutations) == 1
+    assert end_frame.mutations[0]["action"] == "insert"
+
+
+@pytest.mark.asyncio
+async def test_home_formatter_frame_order():
+    """stream_start is first, stream_end is last."""
+    req_id = "req-6"
+    formatter = HomeFormatter(request_id=req_id)
+    frames = await collect(formatter, _stream(("token", "Hi"), ("mutations", [])))
+    assert isinstance(frames[0], WsStreamStart)
+    assert isinstance(frames[-1], WsStreamEnd)
+
+
+# ── FloatingFormatter ─────────────────────────────────────────────────────────
+
+@pytest.mark.asyncio
+async def test_floating_formatter_domain_from_tool_end():
+    req_id = "pop-1"
+    formatter = FloatingFormatter(request_id=req_id)
+    events = [
+        ("tool_end", {"name": "task_agent", "result": "ok"}),
+        ("token", "Hello"),
+        ("mutations", []),
+    ]
+    frames = await collect(formatter, _stream(*events))
 
     assert isinstance(frames[0], WsFloatingDomain)
-    assert frames[0].domain.type == "node"
+    assert frames[0].domain == "tasks"
-    assert frames[0].domain.id == "n-1"
+    assert frames[0].request_id == req_id
-    assert isinstance(frames[1], WsStreamStart)
+
-    assert isinstance(frames[2], WsStreamText)
+
-    assert frames[2].chunk == "Summary"
+@pytest.mark.asyncio
+async def test_floating_formatter_text_only():
+    req_id = "pop-2"
+    formatter = FloatingFormatter(request_id=req_id)
+    events = [
+        ("tool_end", {"name": "timeline_agent", "result": "done"}),
+        ("token", "Summary"),
+        ("mutations", []),
+    ]
+    frames = await collect(formatter, _stream(*events))
+
+    assert isinstance(frames[0], WsFloatingDomain)
+    assert frames[0].domain == "timelines"
+    text_frames = [f for f in frames if isinstance(f, WsStreamText)]
+    assert len(text_frames) == 1
+    assert text_frames[0].chunk == "Summary"
+
+
+@pytest.mark.asyncio
+async def test_floating_formatter_no_entity_tags():
+    """FloatingFormatter never emits entity tag blocks."""
+    req_id = "pop-3"
+    formatter = FloatingFormatter(request_id=req_id)
+    events = [
+        ("tool_end", {"name": "note_agent", "result": "data"}),
+        ("token", "some text"),
+        ("mutations", []),
+    ]
+    frames = await collect(formatter, _stream(*events))
+    # Only expected frame types
+    for f in frames:
+        assert isinstance(f, (WsFloatingDomain, WsStreamStart, WsStreamText, WsStreamEnd))
+
+
+@pytest.mark.asyncio
+async def test_floating_formatter_end_frame():
+    req_id = "pop-4"
+    formatter = FloatingFormatter(request_id=req_id)
+    events = [
+        ("tool_end", {"name": "project_agent", "result": "ok"}),
+        ("token", "Done"),
+        ("mutations", []),
+    ]
+    frames = await collect(formatter, _stream(*events))
     assert isinstance(frames[-1], WsStreamEnd)
 
 
 @pytest.mark.asyncio
-async def test_stream_formatter_ignores_unknown_events() -> None:
+async def test_floating_formatter_default_domain_on_early_token():
-    formatter = StreamFormatter(request_id="req-3")
+    """When the first event is a token (no tool_end yet), default to 'tasks'."""
-    frames = await _collect(
+    req_id = "pop-5"
-        formatter,
+    formatter = FloatingFormatter(request_id=req_id)
-        _stream(("tool_end", {"name": "x"}), ("token", "ok")),
+    events = [("token", "hi"), ("mutations", [])]
-    )
+    frames = await collect(formatter, _stream(*events))
-
+    assert isinstance(frames[0], WsFloatingDomain)
-    text_frames = [f for f in frames if isinstance(f, WsStreamText)]
+    assert frames[0].domain == "tasks"
-    assert len(text_frames) == 1
-    assert text_frames[0].chunk == "ok"
 
 
 @pytest.mark.asyncio
-async def test_stream_formatter_empty_stream_still_brackets() -> None:
+async def test_floating_formatter_mutations_in_stream_end():
-    formatter = StreamFormatter(request_id="req-4")
+    req_id = "pop-6"
-    frames = await _collect(formatter, _stream())
+    muts = [{"action": "update", "table": "tasks", "data": {"id": "t2"}}]
+    events = [
+        ("token", "Updated"),
+        ("mutations", muts),
+    ]
+    formatter = FloatingFormatter(request_id=req_id)
+    frames = await collect(formatter, _stream(*events))
 
-    assert len(frames) == 2
+    end_frame = frames[-1]
-    assert isinstance(frames[0], WsStreamStart)
+    assert isinstance(end_frame, WsStreamEnd)
-    assert isinstance(frames[1], WsStreamEnd)
+    assert len(end_frame.mutations) == 1

tests/test_plugins.py

@@ -88,7 +88,7 @@ class TestPluginRegistry:
     async def test_list_filter_by_query(
         self, reg: PluginRegistry, db_session: AsyncSession, seed_plugins: list[Plugin]
     ) -> None:
-        result = await reg.list_plugins(db_session, query="time")
+        result = await reg.list_plugins(db_session, query="time tracker")
         assert result.total == 1
         assert result.plugins[0].id == "plugin-time-tracker"
 

tests/test_schemas_v3.py

@@ -4,7 +4,6 @@ import pytest
 from pydantic import ValidationError
 
 from app.schemas import (
-    WsDomain,
     WsFrameType,
     WsHomeRequest,
     WsFloatingDomain,
@@ -179,15 +178,23 @@ def test_stream_text_deserializes():
 def test_stream_end_defaults():
     frame = WsStreamEnd(request_id="r1")
     assert frame.type == WsFrameType.stream_end
+    assert frame.mutations == []
+
+
+def test_stream_end_with_mutations():
+    mutations = [{"action": "create", "table": "tasks", "data": {"title": "New task"}}]
+    frame = WsStreamEnd(request_id="r1", mutations=mutations)
+    assert len(frame.mutations) == 1
+    assert frame.mutations[0]["action"] == "create"
 
 
 def test_stream_end_serializes():
     data = WsStreamEnd(request_id="r2").model_dump()
-    assert data == {"type": "stream_end", "request_id": "r2"}
+    assert data == {"type": "stream_end", "request_id": "r2", "mutations": []}
 
 
 def test_stream_end_deserializes():
-    raw = {"type": "stream_end", "request_id": "r3"}
+    raw = {"type": "stream_end", "request_id": "r3", "mutations": []}
     frame = WsStreamEnd.model_validate(raw)
     assert frame.request_id == "r3"
 
@@ -196,47 +203,28 @@ def test_stream_end_deserializes():
 
 
 def test_floating_domain_tasks():
-    frame = WsFloatingDomain(request_id="r1", domain=WsDomain(type="task"))
+    frame = WsFloatingDomain(request_id="r1", domain="tasks")
     assert frame.type == WsFrameType.floating_domain
-    assert frame.domain.type == "task"
+    assert frame.domain == "tasks"
 
 
-def test_floating_domain_valid_domains():
+@pytest.mark.parametrize("domain", ["tasks", "timelines", "notes", "projects"])
-    frame = WsFloatingDomain(
+def test_floating_domain_valid_domains(domain: str):
-        request_id="r1",
+    frame = WsFloatingDomain(request_id="r1", domain=domain)  # type: ignore[arg-type]
-        domain=WsDomain(type="project", id="213213-312321-312312-421321", section="task"),
+    assert frame.domain == domain
-    )
-    assert frame.domain.type == "project"
-    assert frame.domain.id == "213213-312321-312312-421321"
-    assert frame.domain.section == "task"
 
 
-def test_floating_domain_object_valid():
+def test_floating_domain_invalid():
-    frame = WsFloatingDomain(
+    with pytest.raises(ValidationError):
-        request_id="r1",
+        WsFloatingDomain(request_id="r1", domain="invalid")  # type: ignore[arg-type]
-        domain=WsDomain(type="project", id="p1", section="task"),
-    )
-    assert frame.domain.type == "project"
 
 
 def test_floating_domain_serializes():
-    d = WsFloatingDomain(
+    d = WsFloatingDomain(request_id="r1", domain="notes").model_dump()
-        request_id="r1",
+    assert d == {"type": "floating_domain", "request_id": "r1", "domain": "notes"}
-        domain=WsDomain(type="timeline"),
-    ).model_dump()
-    assert d == {
-        "type": "floating_domain",
-        "request_id": "r1",
-        "domain": {"type": "timeline", "id": None, "section": None},
-    }
 
 
 def test_floating_domain_deserializes():
-    raw = {
+    raw = {"type": "floating_domain", "request_id": "r1", "domain": "projects"}
-        "type": "floating_domain",
-        "request_id": "r1",
-        "domain": {"type": "node", "id": "n-1", "section": None},
-    }
     frame = WsFloatingDomain.model_validate(raw)
-    assert frame.domain.type == "node"
+    assert frame.domain == "projects"
-    assert frame.domain.id == "n-1"

tests/test_ws_unified.py

@@ -45,13 +45,15 @@ def _recv_until_end(ws, max_frames: int = 20) -> list[dict]:
     return frames
 
 
-async def _mock_home_stream(user_id, message, context):
+async def _mock_home_stream(user_id, message, context, db_session_factory=None):
-    yield "token", "Hello"
+    yield "token", "Here are your tasks:\n<task>[t1,t2]</task>"
+    yield "mutations", []
 
 
-async def _mock_floating_stream(user_id, message, context):
+async def _mock_floating_stream(user_id, message, context, scope=None, db_session_factory=None):
-    yield "floating_domain", {"type": "task", "id": None, "section": None}
+    yield "tool_end", {"name": "task_agent", "result": "ok"}
     yield "token", "Here is a summary"
+    yield "mutations", []
 
 
 # ── tests ─────────────────────────────────────────────────────────────────────
@@ -102,7 +104,7 @@ def test_floating_request_produces_domain_frame(client):
     assert types.index(WsFrameType.floating_domain) < types.index(WsFrameType.stream_end)
 
     domain_frame = next(f for f in frames if f["type"] == WsFrameType.floating_domain)
-    assert domain_frame["domain"]["type"] == "task"
+    assert domain_frame["domain"] == "tasks"
     assert domain_frame["request_id"] == "p1"
 
 
@@ -111,8 +113,9 @@ def test_home_request_request_id_propagated(client):
     token = make_jwt("power", user_id=USER_ID)
     req_id = "my-unique-req-id"
 
-    async def _stream(user_id, message, context):
+    async def _stream(user_id, message, context, db_session_factory=None):
         yield "token", "ok"
+        yield "mutations", []
 
     with patch("app.api.routes.device_ws.run_home_stream", side_effect=_stream):
         with client.websocket_connect(f"/api/v1/ws/device?token={token}") as ws: