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feature/de
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552b8eb305
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@@ -0,0 +1,92 @@
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"""Deprecate backend agent config tables.
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The Electron client is now the source of truth for agent configuration
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(directory, extract targets, batch interval, custom prompt). Backend keeps
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billing checks and trigger/run logs only.
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Revision ID: 9a1f2d0b6c7e
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Revises: 818478c251dc
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Create Date: 2026-03-16
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"""
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from __future__ import annotations
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from typing import Sequence, Union
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import sqlalchemy as sa
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from alembic import op
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from sqlalchemy.dialects import postgresql
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revision: str = "9a1f2d0b6c7e"
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down_revision: Union[str, None] = "818478c251dc"
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branch_labels: Union[str, Sequence[str], None] = None
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depends_on: Union[str, Sequence[str], None] = None
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def upgrade() -> None:
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bind = op.get_bind()
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inspector = sa.inspect(bind)
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existing = set(inspector.get_table_names())
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if "cloud_agent_configs" in existing:
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op.drop_index("ix_cloud_agent_configs_user_id", table_name="cloud_agent_configs")
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op.drop_table("cloud_agent_configs")
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if "local_agent_configs" in existing:
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op.drop_index("ix_local_agent_configs_user_id", table_name="local_agent_configs")
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op.drop_table("local_agent_configs")
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def downgrade() -> None:
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op.create_table(
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"local_agent_configs",
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sa.Column("id", postgresql.UUID(as_uuid=False), nullable=False),
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sa.Column("user_id", postgresql.UUID(as_uuid=False), nullable=False),
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sa.Column("device_id", sa.String(255), nullable=False),
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sa.Column("name", sa.String(255), nullable=False),
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sa.Column("directory_paths", sa.JSON, nullable=False, server_default="[]"),
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sa.Column("data_types", sa.JSON, nullable=False, server_default="[]"),
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sa.Column("prompt_template", sa.Text, nullable=False, server_default=""),
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sa.Column("file_extensions", sa.JSON, nullable=False, server_default="[]"),
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sa.Column("schedule_cron", sa.String(100), nullable=False, server_default="0 */6 * * *"),
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sa.Column("enabled", sa.Boolean, nullable=False, server_default=sa.true()),
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sa.Column("last_run_at", sa.DateTime(timezone=True), nullable=True),
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sa.Column("created_at", sa.DateTime(timezone=True), nullable=False, server_default=sa.text("now()")),
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sa.Column("updated_at", sa.DateTime(timezone=True), nullable=False, server_default=sa.text("now()")),
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sa.PrimaryKeyConstraint("id"),
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sa.ForeignKeyConstraint(["user_id"], ["users.id"], ondelete="CASCADE"),
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)
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op.create_index("ix_local_agent_configs_user_id", "local_agent_configs", ["user_id"])
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op.execute(
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"""
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DO $$ BEGIN
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CREATE TYPE cloud_provider AS ENUM ('gmail', 'teams', 'outlook');
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EXCEPTION WHEN duplicate_object THEN NULL;
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END $$;
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"""
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)
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op.create_table(
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"cloud_agent_configs",
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sa.Column("id", postgresql.UUID(as_uuid=False), nullable=False),
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sa.Column("user_id", postgresql.UUID(as_uuid=False), nullable=False),
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sa.Column(
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"provider",
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postgresql.ENUM("gmail", "teams", "outlook", name="cloud_provider", create_type=False),
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nullable=False,
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),
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sa.Column("name", sa.String(255), nullable=False),
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sa.Column("data_types", sa.JSON, nullable=False, server_default="[]"),
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sa.Column("prompt_template", sa.Text, nullable=False, server_default=""),
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sa.Column("oauth_token_encrypted", sa.Text, nullable=True),
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sa.Column("filter_config", sa.JSON, nullable=True),
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sa.Column("schedule_cron", sa.String(100), nullable=False, server_default="0 */6 * * *"),
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sa.Column("enabled", sa.Boolean, nullable=False, server_default=sa.true()),
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sa.Column("last_run_at", sa.DateTime(timezone=True), nullable=True),
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sa.Column("created_at", sa.DateTime(timezone=True), nullable=False, server_default=sa.text("now()")),
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sa.Column("updated_at", sa.DateTime(timezone=True), nullable=False, server_default=sa.text("now()")),
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sa.PrimaryKeyConstraint("id"),
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sa.ForeignKeyConstraint(["user_id"], ["users.id"], ondelete="CASCADE"),
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)
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op.create_index("ix_cloud_agent_configs_user_id", "cloud_agent_configs", ["user_id"])
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@@ -1,5 +1,5 @@
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"""Agent tool modules — imported by deep_agent.py to build sub-agent graphs."""
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"""Expose tool modules used by deep orchestrator-worker graphs."""
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from app.agents import timeline_agent, note_agent, project_agent, task_agent
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from app.agents import filesystem_agent, timeline_agent, note_agent, project_agent, task_agent
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__all__ = ["timeline_agent", "note_agent", "project_agent", "task_agent"]
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__all__ = ["filesystem_agent", "timeline_agent", "note_agent", "project_agent", "task_agent"]
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85
app/agents/filesystem_agent.py
Normal file
85
app/agents/filesystem_agent.py
Normal file
@@ -0,0 +1,85 @@
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"""Filesystem agent — tools for reading local directories and files on Electron.
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These tools delegate to the Electron client via ``execute_on_client()`` using
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the same WS tool-call round-trip pattern as CRUD tools. The Electron app
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handles actual disk I/O and responds with ``tool_result`` frames.
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"""
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from __future__ import annotations
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from typing import Any
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from langchain_core.tools import tool
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from app.core.ws_context import execute_on_client
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@tool
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async def list_directory(path: str) -> str:
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"""List files and folders in a local directory on the user's device.
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Returns a formatted listing of entries with name, type (file/directory),
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and full path.
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"""
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result = await execute_on_client(
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action="list_directory",
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data={"path": path},
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)
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entries: list[dict[str, Any]] = result.get("entries", [])
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if not entries:
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return f"Directory '{path}' is empty or does not exist."
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lines: list[str] = []
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for entry in entries:
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entry_type = entry.get("type", "unknown")
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entry_name = entry.get("name", "")
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entry_path = entry.get("path", "")
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lines.append(f"- [{entry_type}] {entry_name} ({entry_path})")
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return f"Directory listing for '{path}' ({len(entries)} entries):\n" + "\n".join(lines)
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@tool
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async def read_file_content(path: str) -> str:
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"""Read the text content of a local file on the user's device.
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Returns the file content as a string. Large files may be truncated
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by the Electron client.
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"""
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result = await execute_on_client(
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action="read_file_content",
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data={"path": path},
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)
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content: str = result.get("content", "")
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if not content:
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return f"File '{path}' is empty or could not be read."
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return content
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@tool
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async def get_file_metadata(path: str) -> str:
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"""Get metadata for a local file: size, creation date, modification date, extension.
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Returns a formatted summary of the file's metadata.
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"""
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result = await execute_on_client(
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action="get_file_metadata",
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data={"path": path},
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)
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size = result.get("size", "unknown")
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created = result.get("createdAt", "unknown")
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modified = result.get("modifiedAt", "unknown")
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extension = result.get("extension", "unknown")
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name = result.get("name", path)
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return (
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f"File: {name}\n"
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f" Extension: {extension}\n"
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f" Size: {size} bytes\n"
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f" Created: {created}\n"
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f" Modified: {modified}"
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)
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FILESYSTEM_TOOLS: list[Any] = [
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list_directory,
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read_file_content,
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get_file_metadata,
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]
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@@ -1,7 +1,8 @@
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"""Note agent — tool definitions for Markdown note CRUD."""
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"""Note agent — Markdown note management (list, get, create, update, delete)."""
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||||
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||||
from __future__ import annotations
|
||||
|
||||
import re
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||||
from typing import Any
|
||||
|
||||
from langchain_core.tools import tool
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||||
@@ -9,14 +10,38 @@ from langchain_core.tools import tool
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from app.core.llm import embed
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from app.core.ws_context import execute_on_client
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_UUID_RE = re.compile(
|
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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:
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return bool(_UUID_RE.match(value))
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NOTE_SYSTEM_PROMPT = (
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"You are a note-taking assistant. You help users create, retrieve, update,\n"
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"and delete Markdown notes in their workspace.\n\n"
|
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"Rules:\n"
|
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" - content is always Markdown; preserve formatting when updating\n"
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||||
" - 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"
|
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" - 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"
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||||
" - Do not fabricate note content — reflect what the user provides or what\n"
|
||||
" is already in the note (retrieved via get_note)."
|
||||
)
|
||||
|
||||
|
||||
@tool
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||||
async def list_notes(project_id: str = "") -> str:
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"""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": project_id or None},
|
||||
filters={"projectId": normalized_project_id or None},
|
||||
)
|
||||
rows = result.get("rows", [])
|
||||
if not rows:
|
||||
@@ -105,4 +130,10 @@ async def delete_note(note_id: str) -> str:
|
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return f"Note {note_id} deleted."
|
||||
|
||||
|
||||
|
||||
NOTE_TOOLS: list[Any] = [
|
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list_notes,
|
||||
get_note,
|
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create_note,
|
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update_note,
|
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delete_note,
|
||||
]
|
||||
|
||||
@@ -1,4 +1,4 @@
|
||||
"""Project agent — tool definitions for project lifecycle CRUD."""
|
||||
"""Project agent — full lifecycle management (list, get, create, update, archive, delete)."""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
@@ -8,6 +8,22 @@ 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(
|
||||
@@ -117,4 +133,11 @@ 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,
|
||||
]
|
||||
|
||||
@@ -1,14 +1,40 @@
|
||||
"""Task agent — tool definitions for task and task comment CRUD."""
|
||||
"""Task agent — full CRUD for tasks and task comments."""
|
||||
|
||||
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 ────────────────────────────────────────────────────────
|
||||
|
||||
@@ -22,11 +48,12 @@ 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": project_id or None,
|
||||
"projectId": normalized_project_id or None,
|
||||
"status": status or None,
|
||||
"search": search or None,
|
||||
"orderBy": order_by or None,
|
||||
@@ -52,7 +79,6 @@ 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)
|
||||
@@ -63,7 +89,6 @@ 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",
|
||||
@@ -77,7 +102,6 @@ async def create_task(
|
||||
"dueDate": due_date or None,
|
||||
"projectId": project_id or None,
|
||||
"isAiSuggested": is_ai_suggested,
|
||||
"isApproved": is_approved,
|
||||
},
|
||||
)
|
||||
row = result["row"]
|
||||
@@ -97,12 +121,10 @@ 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:
|
||||
@@ -119,8 +141,6 @@ 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",
|
||||
@@ -188,8 +208,12 @@ 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["row"]
|
||||
return f"Comment added by {row['author']} on task {row['taskId']} (comment id: {row['id']})."
|
||||
row = result.get("row", {})
|
||||
row_author = row.get("author", author)
|
||||
# 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
|
||||
@@ -199,4 +223,16 @@ 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,
|
||||
]
|
||||
|
||||
@@ -1,21 +1,45 @@
|
||||
"""Timeline agent — tool definitions for project milestone CRUD."""
|
||||
"""Timeline agent — project milestone management (list, create, update, delete)."""
|
||||
|
||||
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": project_id or None},
|
||||
filters={"projectId": normalized_project_id or None},
|
||||
)
|
||||
rows = result.get("rows", [])
|
||||
if not rows:
|
||||
@@ -30,14 +54,12 @@ 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",
|
||||
@@ -47,7 +69,6 @@ async def create_timeline(
|
||||
"title": title,
|
||||
"date": date,
|
||||
"isAiSuggested": is_ai_suggested,
|
||||
"isApproved": is_approved,
|
||||
},
|
||||
)
|
||||
row = result["row"]
|
||||
@@ -59,20 +80,16 @@ 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",
|
||||
@@ -89,4 +106,9 @@ 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,
|
||||
]
|
||||
|
||||
@@ -55,12 +55,15 @@ 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)
|
||||
)
|
||||
tier: str = result.scalar_one_or_none() or "free"
|
||||
default_tier = "power" if settings.ENV == "dev" else "free"
|
||||
tier: str = result.scalar_one_or_none() or default_tier
|
||||
|
||||
# Fetch name/surname from user row.
|
||||
user_result = await db.execute(
|
||||
|
||||
@@ -1,54 +1,40 @@
|
||||
"""Chatbot Journey endpoints — guided conversation to build an agent prompt_template.
|
||||
"""Chatbot Journey — WS-based guided conversation to build an agent prompt_template.
|
||||
|
||||
Endpoints:
|
||||
POST /agents/journey/start — start a new journey session
|
||||
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.
|
||||
The journey is driven entirely through WebSocket frames (no REST endpoints).
|
||||
The device WS handler dispatches ``journey_start`` and ``journey_message``
|
||||
frames to the functions exported here.
|
||||
|
||||
Journey flow:
|
||||
1. Client sends ``{ agent_type, agent_id? }`` to ``/start``.
|
||||
2. Server creates a session, calls the LLM with a contextual system prompt,
|
||||
and returns the first question.
|
||||
3. Client sends follow-up messages to ``/message``.
|
||||
4. After 3-5 turns the LLM wraps up by emitting a ``prompt_template`` block
|
||||
delimited by ``PROMPT_TEMPLATE_START`` / ``PROMPT_TEMPLATE_END``.
|
||||
5. Server parses the block, sets ``done=True``, and returns the template.
|
||||
|
||||
The ``prompt_template`` from the final response is meant to be stored in
|
||||
``LocalAgentConfig.prompt_template`` or ``CloudAgentConfig.prompt_template``
|
||||
by the Electron client (via the agent CRUD endpoints).
|
||||
1. FE sends ``journey_start`` frame with basic agent config (directory,
|
||||
data_types, schedule).
|
||||
2. Server creates an in-memory session, sets up a WS executor so the
|
||||
setup LLM can use file-system tools, does a first directory scrape,
|
||||
and sends back a ``journey_reply`` with the first question.
|
||||
3. FE sends ``journey_message`` frames for each user reply.
|
||||
4. Server appends the user message, calls the LLM (which may read files
|
||||
via tools), and sends back a ``journey_reply``.
|
||||
5. After 3-5 turns the LLM wraps up by emitting a ``prompt_template``
|
||||
block delimited by ``PROMPT_TEMPLATE_START`` / ``PROMPT_TEMPLATE_END``.
|
||||
6. Server parses the block, sends ``journey_reply`` with ``done=True``
|
||||
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 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 langchain_core.messages import AIMessage, HumanMessage, SystemMessage, ToolMessage
|
||||
|
||||
from app.api.deps import get_current_user
|
||||
from app.agents.filesystem_agent import FILESYSTEM_TOOLS
|
||||
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
|
||||
@@ -57,18 +43,25 @@ _SESSION_TTL_SECONDS: int = 1800 # 30 minutes
|
||||
_TEMPLATE_START = "PROMPT_TEMPLATE_START"
|
||||
_TEMPLATE_END = "PROMPT_TEMPLATE_END"
|
||||
|
||||
# Maximum number of conversation turns before the LLM is nudged to wrap up.
|
||||
_MAX_TURNS: int = 5
|
||||
# Minimum turns before we consider nudging the LLM to wrap up.
|
||||
_MIN_TURNS_BEFORE_NUDGE: int = 3
|
||||
# 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:
|
||||
@@ -76,67 +69,84 @@ class _JourneySession:
|
||||
|
||||
|
||||
# session_id → session
|
||||
_sessions: dict[str, _JourneySession] = {}
|
||||
_sessions: dict[str, JourneySession] = {}
|
||||
|
||||
|
||||
def _get_session(session_id: str, user_id: str) -> _JourneySession:
|
||||
"""Retrieve session; raise 404 on missing, expired, or wrong owner."""
|
||||
def get_journey_session(session_id: str, user_id: str) -> JourneySession | None:
|
||||
"""Retrieve session; return None on missing, expired, or wrong owner."""
|
||||
s = _sessions.get(session_id)
|
||||
if s is None or s.is_expired():
|
||||
_sessions.pop(session_id, None)
|
||||
raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail="Journey session not found or expired")
|
||||
return None
|
||||
if s.user_id != user_id:
|
||||
raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail="Journey session not found or expired")
|
||||
return None
|
||||
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 {source_description} \
|
||||
and produce a detailed prompt_template that a separate AI will use as its instruction set.
|
||||
Your job is to understand exactly what data the user wants to extract from their
|
||||
local directory and produce a detailed prompt_template that a separate AI will use
|
||||
as its instruction set.
|
||||
|
||||
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.
|
||||
2. Which data types to extract: tasks, notes, timelines, and/or projects.
|
||||
3. How fields should be mapped (e.g. email subject → task title).
|
||||
4. Priority or status rules (e.g. "urgent" keyword → high priority).
|
||||
5. Any special handling, date extraction, or exclusions.
|
||||
The extraction agent already has this base behaviour built in:
|
||||
- Reads each file using file-system tools.
|
||||
- Creates records (tasks, notes, timelines, projects) via CRUD tools.
|
||||
- Sets isAiSuggested=1 on every new record.
|
||||
- Only extracts data explicitly present in the files — it never invents information.
|
||||
The user's custom prompt is appended AFTER this base behaviour, so focus on
|
||||
what to look for and how to map it — not on the general extraction mechanics.
|
||||
|
||||
After 3-5 questions (when you have enough information), output the final prompt_template between \
|
||||
these exact markers on their own lines:
|
||||
You have access to file-system tools to explore the user's directory:
|
||||
- list_directory: to see folder structure
|
||||
- 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 receives a document/email/message \
|
||||
and must return a JSON array of records in this shape:
|
||||
[{{ "table": "<tasks|notes|timelines|projects>", "data": {{ <field: value> }} }}, ...]
|
||||
The prompt_template must be a self-contained instruction for an AI that reads files
|
||||
and must perform CRUD operations using tools to create records. It should specify:
|
||||
- What entity types to create (tasks, notes, timelines) — never projects.
|
||||
- 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}\
|
||||
Do not ask more than {max_turns} questions total. Start with your first question now.\
|
||||
Keep asking clarifying questions until you are at least 90% confident you have
|
||||
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(agent_type: str, existing_template: str | None) -> str:
|
||||
source_description = (
|
||||
"files in local directories" if agent_type == "local" else "emails and messages from cloud providers"
|
||||
)
|
||||
def _build_system_prompt(
|
||||
directory: str,
|
||||
data_types: list[str],
|
||||
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"
|
||||
@@ -144,18 +154,14 @@ def _build_system_prompt(agent_type: str, existing_template: str | None) -> str:
|
||||
else ""
|
||||
)
|
||||
return _SYSTEM_PROMPT_TEMPLATE.format(
|
||||
source_description=source_description,
|
||||
directory=directory,
|
||||
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 ───────────────────────────────────────────────────
|
||||
|
||||
|
||||
@@ -168,11 +174,37 @@ def _extract_template(text: str) -> str | None:
|
||||
return text[start_idx:end_idx].strip() or None
|
||||
|
||||
|
||||
# ── LLM call ─────────────────────────────────────────────────────────────
|
||||
# ── LLM call with tool support ───────────────────────────────────────────
|
||||
|
||||
|
||||
async def _call_llm(system_prompt: str, history: list[dict[str, Any]]) -> str:
|
||||
"""Build LangChain messages from history and invoke the LLM."""
|
||||
def _as_text(content: Any) -> str:
|
||||
if content is None:
|
||||
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":
|
||||
@@ -181,137 +213,194 @@ async def _call_llm(system_prompt: str, history: list[dict[str, Any]]) -> str:
|
||||
messages.append(AIMessage(content=turn["content"]))
|
||||
|
||||
llm = get_llm(model=None, temperature=0.4)
|
||||
response = await llm.ainvoke(messages)
|
||||
return response.content # type: ignore[return-value]
|
||||
llm_with_tools = llm.bind_tools(tools)
|
||||
tool_map = {tool_def.name: tool_def for tool_def in tools}
|
||||
|
||||
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)
|
||||
|
||||
|
||||
# ── Existing-config loader ────────────────────────────────────────────────
|
||||
# ── Journey handlers (called from device_ws.py) ──────────────────────────
|
||||
|
||||
|
||||
async def _load_existing_template(
|
||||
agent_id: str,
|
||||
async def handle_journey_start(
|
||||
user_id: str,
|
||||
db: AsyncSession,
|
||||
) -> str | None:
|
||||
"""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
|
||||
frame: dict[str, Any],
|
||||
) -> dict[str, Any]:
|
||||
"""Handle a ``journey_start`` WS frame.
|
||||
|
||||
cloud_result = await db.execute(
|
||||
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.
|
||||
Creates a session, runs the setup LLM with directory exploration,
|
||||
and returns the ``journey_reply`` payload.
|
||||
"""
|
||||
# Load existing template (may be None).
|
||||
existing_template: str | None = None
|
||||
if body.agent_id:
|
||||
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).
|
||||
agent_type = frame.get("agent_type", "local")
|
||||
directory = frame.get("directory", "")
|
||||
data_types = frame.get("data_types", [])
|
||||
existing_template = frame.get("existing_template")
|
||||
|
||||
system_prompt = _build_system_prompt(body.agent_type, existing_template)
|
||||
first_question = _first_question(body.agent_type)
|
||||
# Use the session_id provided by the FE so the reply matches the
|
||||
# listener key; fall back to a generated one if absent.
|
||||
session_id = frame.get("session_id") or str(uuid.uuid4())
|
||||
system_prompt = _build_system_prompt(directory, data_types, existing_template)
|
||||
|
||||
session_id = str(uuid.uuid4())
|
||||
session = _JourneySession(
|
||||
session = JourneySession(
|
||||
session_id=session_id,
|
||||
user_id=current_user.id,
|
||||
agent_type=body.agent_type,
|
||||
# Seed history with the AI's first question so it stays consistent.
|
||||
history=[{"role": "assistant", "content": first_question}],
|
||||
user_id=user_id,
|
||||
agent_type=agent_type,
|
||||
directory=directory,
|
||||
data_types=data_types,
|
||||
system_prompt=system_prompt,
|
||||
)
|
||||
# Store the system prompt inside the session for reuse in /message.
|
||||
session.__dict__["_system_prompt"] = system_prompt # type: ignore[index]
|
||||
|
||||
# The LLM will explore the directory using FILESYSTEM_TOOLS via the
|
||||
# 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("Journey session %s started for user %s (agent_type=%s)", session_id, current_user.id, body.agent_type)
|
||||
return JourneyResponse(session_id=session_id, message=first_question, done=False)
|
||||
logger.info(
|
||||
"agent_setup: journey session %s started for user %s (directory=%s)",
|
||||
session_id,
|
||||
user_id,
|
||||
directory,
|
||||
)
|
||||
|
||||
|
||||
@router.post("/message", response_model=JourneyResponse, status_code=status.HTTP_200_OK)
|
||||
async def send_journey_message(
|
||||
body: JourneyMessageRequest,
|
||||
current_user: UserProfile = Depends(get_current_user),
|
||||
db: AsyncSession = Depends(get_session),
|
||||
) -> JourneyResponse:
|
||||
"""Send a message in an existing Chatbot Journey session.
|
||||
|
||||
The server appends the user's message to the conversation history,
|
||||
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 = _get_session(body.session_id, current_user.id)
|
||||
system_prompt: str = session.__dict__.get("_system_prompt", _build_system_prompt(session.agent_type, None)) # type: ignore[assignment]
|
||||
|
||||
# Append user turn to history.
|
||||
session.history.append({"role": "user", "content": body.message})
|
||||
|
||||
# Call the LLM with the full conversation so far.
|
||||
ai_reply = await _call_llm(system_prompt, session.history)
|
||||
|
||||
# Append AI turn.
|
||||
session.history.append({"role": "assistant", "content": ai_reply})
|
||||
|
||||
# Check if the LLM produced the final template.
|
||||
# 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
|
||||
|
||||
# Strip the sentinel markers from the message shown to the user.
|
||||
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)
|
||||
|
||||
if done:
|
||||
logger.info("Journey session %s completed for user %s", body.session_id, current_user.id)
|
||||
# Clean up the session immediately on completion.
|
||||
_sessions.pop(body.session_id, None)
|
||||
else:
|
||||
# Nudge the LLM to wrap up after max turns.
|
||||
return {
|
||||
"type": "journey_reply",
|
||||
"session_id": session_id,
|
||||
"message": display_message,
|
||||
"done": done,
|
||||
"prompt_template": prompt_template,
|
||||
}
|
||||
|
||||
|
||||
async def handle_journey_message(
|
||||
user_id: str,
|
||||
frame: dict[str, Any],
|
||||
) -> dict[str, Any]:
|
||||
"""Handle a ``journey_message`` WS frame.
|
||||
|
||||
Appends the user message, calls the LLM, and returns the
|
||||
``journey_reply`` payload.
|
||||
"""
|
||||
session_id = frame.get("session_id", "")
|
||||
message = frame.get("message", "")
|
||||
|
||||
session = get_journey_session(session_id, user_id)
|
||||
if session is None:
|
||||
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.
|
||||
session.history.append({"role": "user", "content": message})
|
||||
|
||||
# Call the LLM with tools.
|
||||
ai_reply = await _call_llm_with_tools(
|
||||
system_prompt=session.system_prompt,
|
||||
history=session.history,
|
||||
tools=list(FILESYSTEM_TOOLS),
|
||||
)
|
||||
|
||||
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
|
||||
# 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:
|
||||
# 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.]"
|
||||
),
|
||||
})
|
||||
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})
|
||||
|
||||
return JourneyResponse(
|
||||
session_id=body.session_id,
|
||||
message=display_message,
|
||||
done=done,
|
||||
prompt_template=prompt_template,
|
||||
)
|
||||
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
|
||||
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 {
|
||||
"type": "journey_reply",
|
||||
"session_id": session_id,
|
||||
"message": display_message,
|
||||
"done": done,
|
||||
"prompt_template": prompt_template,
|
||||
}
|
||||
|
||||
@@ -1,45 +1,36 @@
|
||||
"""Agent CRUD routes: local directory agents and cloud connector agents.
|
||||
"""Agent routes.
|
||||
|
||||
Endpoints:
|
||||
GET /agents/catalog — hardcoded agent type catalog
|
||||
GET /agents/local — list user's local agent configs
|
||||
POST /agents/local — create local agent (tier-gated)
|
||||
PUT /agents/local/{agent_id} — partial update (ownership check)
|
||||
DELETE /agents/local/{agent_id} — delete + cascade run logs
|
||||
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)
|
||||
Backend responsibilities are intentionally minimal:
|
||||
GET /agents/catalog — static catalog for UI display
|
||||
POST /agents/can-create — billing eligibility check
|
||||
POST /agents/trigger — trigger a local agent run
|
||||
|
||||
Agent configuration is owned by the Electron app and is not persisted
|
||||
in backend agent-config tables.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import asyncio
|
||||
from datetime import datetime
|
||||
from typing import Any
|
||||
import uuid
|
||||
from datetime import datetime, timedelta, timezone
|
||||
|
||||
from fastapi import APIRouter, Depends, HTTPException, Query, status
|
||||
from pydantic import BaseModel
|
||||
from sqlalchemy import func, or_, select
|
||||
from fastapi import APIRouter, Depends, HTTPException, status
|
||||
from sqlalchemy import func, 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 run_cloud_agent, run_local_agent
|
||||
from app.core.agent_runner import is_agent_running, run_local_agent
|
||||
from app.core.device_manager import device_manager
|
||||
from app.db import get_session
|
||||
from app.models import AgentRunLog, CloudAgentConfig, LocalAgentConfig
|
||||
from app.models import AgentRunLog, LocalAgentConfig
|
||||
from app.schemas import (
|
||||
AgentCatalogItem,
|
||||
AgentCreationCheckRequest,
|
||||
AgentCreationCheckResponse,
|
||||
AgentRunLogResponse,
|
||||
CloudAgentConfigCreate,
|
||||
CloudAgentConfigResponse,
|
||||
CloudAgentConfigUpdate,
|
||||
LocalAgentConfigCreate,
|
||||
LocalAgentConfigResponse,
|
||||
LocalAgentConfigUpdate,
|
||||
AgentTriggerRequest,
|
||||
UserProfile,
|
||||
)
|
||||
|
||||
@@ -56,39 +47,21 @@ def _dt_ms_opt(dt: datetime | None) -> int | None:
|
||||
return int(dt.timestamp() * 1000) if dt else None
|
||||
|
||||
|
||||
# ── Model → schema converters ─────────────────────────────────────────
|
||||
|
||||
def _to_local_response(a: LocalAgentConfig) -> LocalAgentConfigResponse:
|
||||
return LocalAgentConfigResponse(
|
||||
id=a.id,
|
||||
name=a.name,
|
||||
device_id=a.device_id,
|
||||
directory_paths=a.directory_paths,
|
||||
data_types=a.data_types,
|
||||
prompt_template=a.prompt_template,
|
||||
file_extensions=a.file_extensions,
|
||||
schedule_cron=a.schedule_cron,
|
||||
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_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_data_types(values: list[str]) -> list[str]:
|
||||
normalize = {
|
||||
"task": "tasks", "tasks": "tasks",
|
||||
"note": "notes", "notes": "notes",
|
||||
"timeline": "timelines", "timelines": "timelines", "timelineEvents": "timelines",
|
||||
"project": "projects", "projects": "projects",
|
||||
}
|
||||
seen: set[str] = set()
|
||||
result: list[str] = []
|
||||
for v in values:
|
||||
mapped = normalize.get(v)
|
||||
if mapped and mapped not in seen:
|
||||
seen.add(mapped)
|
||||
result.append(mapped)
|
||||
return result
|
||||
|
||||
|
||||
def _to_run_log_response(log: AgentRunLog) -> AgentRunLogResponse:
|
||||
@@ -105,77 +78,42 @@ def _to_run_log_response(log: AgentRunLog) -> AgentRunLogResponse:
|
||||
)
|
||||
|
||||
|
||||
# ── 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:
|
||||
def _enforce_agent_limit(tier: str, current_count: int) -> int:
|
||||
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
|
||||
|
||||
|
||||
# ── Local page schema (used by runs endpoint) ─────────────────────────
|
||||
async def _enforce_run_frequency(
|
||||
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
|
||||
|
||||
class _RunsPage(BaseModel):
|
||||
total: int
|
||||
page: int
|
||||
limit: int
|
||||
items: list[AgentRunLogResponse]
|
||||
today_start = datetime.now(timezone.utc).replace(
|
||||
hour=0, minute=0, second=0, microsecond=0
|
||||
)
|
||||
result = await db.execute(
|
||||
select(func.count(AgentRunLog.id)).where(
|
||||
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 ───────────────────────────────────────────────────────────
|
||||
@@ -209,229 +147,61 @@ async def get_agent_catalog(
|
||||
]
|
||||
|
||||
|
||||
# ── Local agent CRUD ──────────────────────────────────────────────────
|
||||
|
||||
@router.get("/local", response_model=list[LocalAgentConfigResponse])
|
||||
async def list_local_agents(
|
||||
@router.post("/can-create", response_model=AgentCreationCheckResponse)
|
||||
async def can_create_agent(
|
||||
body: AgentCreationCheckRequest,
|
||||
current_user: UserProfile = Depends(get_current_user),
|
||||
db: AsyncSession = Depends(get_session),
|
||||
) -> list[LocalAgentConfigResponse]:
|
||||
"""List all local directory agent configs owned by the authenticated user."""
|
||||
result = await db.execute(
|
||||
select(LocalAgentConfig).where(LocalAgentConfig.user_id == current_user.id)
|
||||
)
|
||||
return [_to_local_response(a) for a in result.scalars().all()]
|
||||
) -> AgentCreationCheckResponse:
|
||||
"""Check if the user can create one more agent based on billing tier.
|
||||
|
||||
|
||||
@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.
|
||||
Since configuration is client-owned, the Electron app sends its current
|
||||
active agent count and the backend applies tier limits.
|
||||
"""
|
||||
_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,
|
||||
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,
|
||||
)
|
||||
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)
|
||||
@router.post("/trigger", response_model=AgentRunLogResponse, status_code=status.HTTP_202_ACCEPTED)
|
||||
async def trigger_agent_run(
|
||||
agent_id: str,
|
||||
body: AgentTriggerRequest,
|
||||
current_user: UserProfile = Depends(get_current_user),
|
||||
db: AsyncSession = Depends(get_session),
|
||||
) -> AgentRunLogResponse:
|
||||
"""Manually trigger an agent run.
|
||||
"""Trigger a local agent run using client-provided configuration."""
|
||||
_enforce_agent_limit(current_user.tier, body.active_agents)
|
||||
await _enforce_run_frequency(current_user.tier, current_user.id, db)
|
||||
|
||||
Looks up the agent config (local or cloud) by ID with ownership check,
|
||||
creates a run log entry with ``status="running"``, and returns it.
|
||||
|
||||
Actual dispatch to the agent runner is wired in Step 3.4 once
|
||||
``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
|
||||
|
||||
local_result = await db.execute(
|
||||
select(LocalAgentConfig).where(
|
||||
LocalAgentConfig.id == agent_id,
|
||||
LocalAgentConfig.user_id == current_user.id,
|
||||
)
|
||||
config = LocalAgentConfig(
|
||||
id=str(uuid.uuid4()),
|
||||
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,
|
||||
)
|
||||
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,
|
||||
)
|
||||
# Use the FE's stable agent_id if provided, fall back to the ephemeral config id.
|
||||
stable_agent_id = body.agent_id or config.id
|
||||
|
||||
if is_agent_running(stable_agent_id):
|
||||
raise HTTPException(
|
||||
status_code=status.HTTP_409_CONFLICT,
|
||||
detail="Agent is already running. Only one run per agent is allowed at a time.",
|
||||
)
|
||||
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=agent_id,
|
||||
agent_type=agent_type,
|
||||
agent_id=stable_agent_id,
|
||||
agent_type="local",
|
||||
user_id=current_user.id,
|
||||
status="running",
|
||||
)
|
||||
@@ -439,14 +209,14 @@ async def trigger_agent_run(
|
||||
await db.commit()
|
||||
await db.refresh(run_log)
|
||||
|
||||
# Dispatch the run as a background task — returns 202 immediately.
|
||||
if agent_type == "local" and local_config is not None:
|
||||
asyncio.create_task(
|
||||
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(
|
||||
run_cloud_agent(current_user.id, cloud_config, run_log, device_manager)
|
||||
)
|
||||
run_context = {
|
||||
"type": "agent_batch",
|
||||
"run_id": run_log.id,
|
||||
"agent_id": stable_agent_id,
|
||||
}
|
||||
|
||||
asyncio.create_task(
|
||||
run_local_agent(current_user.id, config, run_log, device_manager, run_context)
|
||||
)
|
||||
|
||||
return _to_run_log_response(run_log)
|
||||
|
||||
@@ -10,9 +10,7 @@ from fastapi.responses import JSONResponse
|
||||
|
||||
from app.api.deps import get_current_user
|
||||
from app.core.deep_agent import run_home
|
||||
from app.core.memory_middleware import MemoryMiddleware
|
||||
from app.db import async_session
|
||||
from app.schemas import ChatRequest, ChatResponse, UserProfile
|
||||
from app.schemas import ChatRequest, UserProfile
|
||||
|
||||
router = APIRouter(prefix="/chat", tags=["chat"])
|
||||
|
||||
@@ -22,21 +20,10 @@ async def chat(
|
||||
body: ChatRequest,
|
||||
current_user: UserProfile = Depends(get_current_user),
|
||||
) -> JSONResponse:
|
||||
"""Route a chat message through the Home deep agent (non-streaming)."""
|
||||
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(
|
||||
"""REST fallback for home chat when websocket streaming is unavailable."""
|
||||
response = await run_home(
|
||||
user_id=current_user.id,
|
||||
message=body.message,
|
||||
context=context,
|
||||
db_session_factory=async_session,
|
||||
context=body.context.model_dump(),
|
||||
)
|
||||
result = ChatResponse(response=response_text)
|
||||
return JSONResponse(content=result.model_dump())
|
||||
return JSONResponse(content={"response": response})
|
||||
|
||||
@@ -14,11 +14,11 @@ Protocol:
|
||||
4. Session enters message dispatch loop + heartbeat.
|
||||
|
||||
Incoming frame dispatch:
|
||||
- ``tool_result`` → resolves a pending tool-call Future.
|
||||
- ``agent_data`` → enqueued in the per-run agent data queue.
|
||||
- ``agent_complete`` → sends None sentinel to close the queue stream.
|
||||
- ``pong`` → heartbeat acknowledgement (updates last-seen).
|
||||
- unknown types → logged, ignored.
|
||||
- ``tool_result`` → resolves a pending tool-call Future.
|
||||
- ``journey_start`` → starts a guided setup journey session.
|
||||
- ``journey_message`` → continues a journey conversation.
|
||||
- ``pong`` → heartbeat acknowledgement (updates last-seen).
|
||||
- unknown types → logged, ignored.
|
||||
|
||||
Outgoing heartbeat: ``{ "type": "ping" }`` every 30 s.
|
||||
|
||||
@@ -39,12 +39,13 @@ 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.deep_agent import run_home_stream, run_floating_stream
|
||||
from app.core.output_formatter import HomeFormatter, FloatingFormatter
|
||||
from app.core.output_formatter import StreamFormatter
|
||||
from app.core.ws_context import clear_client_executor, set_client_executor
|
||||
from app.db import async_session
|
||||
from app.models import AgentRunLog
|
||||
@@ -147,37 +148,6 @@ 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)
|
||||
@@ -188,6 +158,16 @@ 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
|
||||
@@ -200,35 +180,13 @@ 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, call_id)
|
||||
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
|
||||
future = device_manager.create_pending_call(user_id, payload["id"])
|
||||
return await future
|
||||
return _executor
|
||||
|
||||
|
||||
@@ -241,14 +199,27 @@ 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(user_id, message)
|
||||
memory_context = await memory.enrich_context(
|
||||
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,
|
||||
}
|
||||
|
||||
@@ -256,12 +227,11 @@ async def _handle_home_request(
|
||||
set_client_executor(executor)
|
||||
response_chunks: list[str] = []
|
||||
try:
|
||||
event_stream = run_home_stream(
|
||||
user_id, message, context, db_session_factory=async_session
|
||||
)
|
||||
formatter = HomeFormatter(request_id=request_id)
|
||||
event_stream = run_home_stream(user_id, message, context)
|
||||
formatter = StreamFormatter(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:
|
||||
@@ -276,8 +246,15 @@ 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)
|
||||
user_id, session_id, message, "".join(response_chunks), trace_id=request_id
|
||||
)
|
||||
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(
|
||||
@@ -290,23 +267,37 @@ 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(user_id, message)
|
||||
memory_context = await memory.enrich_context(
|
||||
user_id,
|
||||
message,
|
||||
trace_id=request_id,
|
||||
session_id=session_id,
|
||||
)
|
||||
|
||||
context: dict = {"scope": scope, **memory_context}
|
||||
context: dict = {
|
||||
"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, scope=scope,
|
||||
db_session_factory=async_session,
|
||||
)
|
||||
formatter = FloatingFormatter(request_id=request_id)
|
||||
event_stream = run_floating_stream(user_id, message, context)
|
||||
formatter = StreamFormatter(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]
|
||||
@@ -323,8 +314,72 @@ 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)
|
||||
user_id, session_id, message, "".join(response_chunks), trace_id=request_id
|
||||
)
|
||||
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 ─────────────────────────────────────────────────────────
|
||||
@@ -360,6 +415,3 @@ async def _mark_runs_disconnected(user_id: str) -> None:
|
||||
user_id,
|
||||
exc,
|
||||
)
|
||||
|
||||
|
||||
|
||||
|
||||
@@ -21,6 +21,7 @@ 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,
|
||||
@@ -31,6 +32,7 @@ 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,
|
||||
@@ -41,6 +43,7 @@ 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,
|
||||
@@ -51,6 +54,7 @@ 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,
|
||||
@@ -77,16 +81,18 @@ 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 ``'free'`` when no subscription row exists.
|
||||
Falls back to ``'power'`` in dev (unlimited) or ``'free'`` in prod
|
||||
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 "free"
|
||||
return "power" if settings.ENV == "dev" else "free"
|
||||
return tier # type: ignore[return-value]
|
||||
|
||||
# ── Feature access ───────────────────────────────────────────────────
|
||||
|
||||
30
app/core/agent_registry.py
Normal file
30
app/core/agent_registry.py
Normal file
@@ -0,0 +1,30 @@
|
||||
"""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 []
|
||||
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
@@ -3,20 +3,15 @@
|
||||
Maintains in-memory state for all active Electron → backend WebSocket
|
||||
connections. One connection per user (latest replaces previous).
|
||||
|
||||
The manager participates in two interaction patterns:
|
||||
The manager handles the **tool-call round-trip** pattern:
|
||||
- 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.
|
||||
|
||||
1. **Tool-call round-trip** (bidirectional CRUD):
|
||||
- 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.
|
||||
This pattern is used by all tools (CRUD, file-system, etc.) via
|
||||
``execute_on_client()`` in ``ws_context.py``.
|
||||
|
||||
The ``device_manager`` module-level singleton is imported by both the
|
||||
device WS route and the agent runner.
|
||||
@@ -42,8 +37,6 @@ 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:
|
||||
@@ -153,31 +146,6 @@ 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()
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
"""LLM factory — centralised model instantiation via LiteLLM.
|
||||
|
||||
Every agent and the deep-agent supervisors call ``get_llm()`` or ``get_router_llm()``
|
||||
Every agent and the orchestrator 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>`_:
|
||||
@@ -18,6 +18,7 @@ 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
|
||||
@@ -32,6 +33,14 @@ 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."""
|
||||
|
||||
@@ -43,15 +43,21 @@ _PROACTIVE_CONFIDENCE_THRESHOLD = 0.6
|
||||
|
||||
|
||||
class MemoryMiddleware:
|
||||
"""Enrich agent context with memory and persist interactions after."""
|
||||
"""Enrich orchestrator context with memory and persist interactions after."""
|
||||
|
||||
def __init__(self, db: AsyncSession) -> None:
|
||||
self._db = db
|
||||
|
||||
# ── Public API ────────────────────────────────────────────────────────────
|
||||
|
||||
async def enrich_context(self, user_id: str, message: str) -> dict[str, Any]:
|
||||
"""Build memory context dict to inject into the agent before LLM call.
|
||||
async def enrich_context(
|
||||
self,
|
||||
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, ...}
|
||||
@@ -65,9 +71,21 @@ 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)
|
||||
episodic = await self._load_episodic(user_id, fernet, session_id=session_id)
|
||||
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,
|
||||
@@ -81,6 +99,7 @@ class MemoryMiddleware:
|
||||
session_id: str,
|
||||
message: str,
|
||||
response: str,
|
||||
trace_id: str | None = None,
|
||||
) -> None:
|
||||
"""Summarise and store a completed interaction in episodic memory.
|
||||
|
||||
@@ -103,11 +122,19 @@ 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) -> None:
|
||||
async def update_core(self, user_id: str, key: str, value: str, trace_id: str | None = None) -> None:
|
||||
"""Upsert a core memory key/value for a user."""
|
||||
fernet = await self._get_fernet(user_id)
|
||||
if fernet is None:
|
||||
@@ -133,10 +160,176 @@ 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:
|
||||
@@ -148,6 +341,16 @@ 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)
|
||||
@@ -183,10 +386,17 @@ class MemoryMiddleware:
|
||||
out.append(plaintext)
|
||||
return out
|
||||
|
||||
async def _load_episodic(self, user_id: str, fernet: Fernet) -> list[str]:
|
||||
async def _load_episodic(
|
||||
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(
|
||||
select(MemoryEpisodic)
|
||||
.where(MemoryEpisodic.user_id == user_id)
|
||||
query
|
||||
.order_by(MemoryEpisodic.created_at.desc())
|
||||
.limit(_EPISODIC_RECENT_N)
|
||||
)
|
||||
|
||||
@@ -1,141 +1,47 @@
|
||||
"""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``
|
||||
"""
|
||||
"""Output formatter for deep-agent stream events."""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import logging
|
||||
from collections.abc import AsyncGenerator
|
||||
from typing import Any
|
||||
|
||||
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",
|
||||
}
|
||||
from app.schemas import WsFloatingDomain, WsStreamEnd, WsStreamStart, WsStreamText
|
||||
|
||||
WsFrame = WsStreamStart | WsStreamText | WsStreamEnd | WsFloatingDomain
|
||||
|
||||
|
||||
class HomeFormatter:
|
||||
"""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``.
|
||||
"""
|
||||
class StreamFormatter:
|
||||
"""Convert `(event_type, data)` stream events into websocket frame models."""
|
||||
|
||||
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]:
|
||||
yield WsStreamStart(request_id=self.request_id)
|
||||
started = False
|
||||
|
||||
async for event_type, data in event_stream:
|
||||
if event_type == "token":
|
||||
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
|
||||
if event_type == "floating_domain":
|
||||
if isinstance(data, dict):
|
||||
yield WsFloatingDomain(
|
||||
request_id=self.request_id,
|
||||
domain="tasks", # type: ignore[arg-type]
|
||||
domain=data,
|
||||
)
|
||||
yield WsStreamStart(request_id=self.request_id)
|
||||
domain_sent = True
|
||||
if data:
|
||||
yield WsStreamText(request_id=self.request_id, chunk=data)
|
||||
continue
|
||||
|
||||
elif event_type == "mutations":
|
||||
self._mutations = data or []
|
||||
if event_type != "token":
|
||||
continue
|
||||
|
||||
# If no events triggered domain_sent (edge case), still emit structure
|
||||
if not domain_sent:
|
||||
yield WsFloatingDomain(
|
||||
request_id=self.request_id,
|
||||
domain="tasks", # type: ignore[arg-type]
|
||||
)
|
||||
if not started:
|
||||
yield WsStreamStart(request_id=self.request_id)
|
||||
started = True
|
||||
|
||||
text = str(data or "")
|
||||
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,
|
||||
mutations=[
|
||||
{"action": m["action"], "table": m["table"], "data": m["data"]}
|
||||
for m in self._mutations
|
||||
],
|
||||
)
|
||||
yield WsStreamEnd(request_id=self.request_id)
|
||||
|
||||
@@ -7,21 +7,18 @@ 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 deep agent runs; cleared after.
|
||||
# Set by the chat WS handler before the orchestrator 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 the deep agent tool loop to capture CRUD mutations.
|
||||
# Set by _tool_loop / _tool_loop_stream to populate ChatAgent.tool_results.
|
||||
_tool_result_collector: ContextVar[list[dict] | None] = ContextVar(
|
||||
"_tool_result_collector", default=None
|
||||
)
|
||||
@@ -84,17 +81,12 @@ 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 and action in ("insert", "update", "delete"):
|
||||
if collector is not None:
|
||||
collector.append({
|
||||
"action": action,
|
||||
"table": table,
|
||||
"data": data or {},
|
||||
"data": result,
|
||||
})
|
||||
return result
|
||||
|
||||
@@ -18,7 +18,9 @@ from app.config.settings import settings
|
||||
|
||||
@asynccontextmanager
|
||||
async def lifespan(app: FastAPI):
|
||||
# Startup: initialise DB connection pool
|
||||
# Startup: ensure agent tool modules are loaded.
|
||||
import app.agents # noqa: F401
|
||||
|
||||
yield
|
||||
|
||||
# Shutdown: dispose SQLAlchemy connection pool
|
||||
@@ -48,7 +50,7 @@ def create_app() -> FastAPI:
|
||||
app.add_middleware(SanitizerMiddleware)
|
||||
app.add_middleware(TierRateLimitMiddleware)
|
||||
|
||||
from app.api.routes import agent_setup, agents, auth, backup, billing, chat, device_ws, plugins, storage, vectors
|
||||
from app.api.routes import 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")
|
||||
@@ -58,7 +60,6 @@ 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"])
|
||||
|
||||
146
app/schemas.py
146
app/schemas.py
@@ -142,9 +142,6 @@ 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"
|
||||
@@ -156,6 +153,10 @@ 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):
|
||||
@@ -208,31 +209,6 @@ 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 ─────────────────────────────────────────
|
||||
|
||||
@@ -279,7 +255,14 @@ 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):
|
||||
@@ -287,7 +270,7 @@ class WsFloatingDomain(BaseModel):
|
||||
|
||||
type: Literal[WsFrameType.floating_domain] = WsFrameType.floating_domain
|
||||
request_id: str
|
||||
domain: Literal["tasks", "timelines", "notes", "projects"]
|
||||
domain: WsDomain
|
||||
|
||||
|
||||
# ── Agent Catalog ─────────────────────────────────────────────────────
|
||||
@@ -296,84 +279,28 @@ class AgentCatalogItem(BaseModel):
|
||||
type: str
|
||||
name: str
|
||||
description: str
|
||||
config_schema: dict[str, Any] = Field(default_factory=dict)
|
||||
|
||||
|
||||
# ── Local Agent Config ────────────────────────────────────────────────
|
||||
|
||||
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 AgentCreationCheckRequest(BaseModel):
|
||||
active_agents: int = Field(ge=0, default=0)
|
||||
|
||||
|
||||
class LocalAgentConfigUpdate(BaseModel):
|
||||
name: str | None = None
|
||||
device_id: str | None = None
|
||||
directory_paths: list[str] | None = None
|
||||
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 AgentCreationCheckResponse(BaseModel):
|
||||
allowed: bool
|
||||
tier: BillingTier
|
||||
active_agents: int
|
||||
limit: int
|
||||
|
||||
|
||||
class LocalAgentConfigResponse(BaseModel):
|
||||
id: str
|
||||
name: str
|
||||
device_id: str
|
||||
directory_paths: list[str]
|
||||
data_types: list[str]
|
||||
prompt_template: str
|
||||
file_extensions: list[str]
|
||||
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
|
||||
class AgentTriggerRequest(BaseModel):
|
||||
directory: str = Field(min_length=1)
|
||||
device_id: str = Field(default="")
|
||||
agent_id: str | None = None # FE stable agent ID (electron-store UUID)
|
||||
what_to_extract: list[str] = Field(min_length=1)
|
||||
actions_by_type: dict[str, list[str]] | None = None
|
||||
batch_interval: str = Field(min_length=1)
|
||||
custom_agent_prompt: str = Field(min_length=1)
|
||||
active_agents: int = Field(ge=0, default=0)
|
||||
|
||||
|
||||
# ── Agent Run Log ─────────────────────────────────────────────────────
|
||||
@@ -392,18 +319,3 @@ 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
|
||||
|
||||
941
docs/MICROSERVICES_ARCHITECTURE.md
Normal file
941
docs/MICROSERVICES_ARCHITECTURE.md
Normal file
@@ -0,0 +1,941 @@
|
||||
# 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 |
|
||||
@@ -4,8 +4,6 @@ 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
|
||||
|
||||
@@ -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 — overdue local + cloud dispatched
|
||||
- trigger_pending_runs — skipped when config is client-owned
|
||||
- trigger_pending_runs — non-overdue skipped
|
||||
- trigger_pending_runs — device_id filter for local agents
|
||||
|
||||
Integration:
|
||||
- POST /agents/{id}/run — 404 on unknown agent
|
||||
- POST /agents/{id}/run — creates run log + dispatches background task
|
||||
Integration:
|
||||
- POST /agents/can-create — billing eligibility check
|
||||
- POST /agents/trigger — 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 True
|
||||
assert kwargs["update_config_last_run"] is False
|
||||
|
||||
# Verify agent_run frame was sent.
|
||||
agent_run_frames = [f for f in sent_frames if f.get("type") == "agent_run"]
|
||||
@@ -690,31 +690,11 @@ async def test_finalize_run_updates_cloud_config_last_run_at():
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_trigger_pending_runs_no_overdue():
|
||||
"""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 = []
|
||||
"""Pending-run scan is skipped because agent config is client-owned."""
|
||||
|
||||
mgr = _make_manager()
|
||||
|
||||
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
|
||||
|
||||
with patch("app.core.agent_runner.run_local_agent", new_callable=AsyncMock) as mock_run:
|
||||
await trigger_pending_runs(_FREE_UID, "dev-001", mgr)
|
||||
|
||||
mock_run.assert_not_called()
|
||||
@@ -722,31 +702,11 @@ async def test_trigger_pending_runs_no_overdue():
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_trigger_pending_runs_device_id_filter():
|
||||
"""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 = []
|
||||
"""Device filtering is no longer backend-managed in pending runs."""
|
||||
|
||||
mgr = _make_manager(device_id="dev-001")
|
||||
|
||||
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
|
||||
|
||||
with patch("app.core.agent_runner.run_local_agent", new_callable=AsyncMock) as mock_run:
|
||||
await trigger_pending_runs(_FREE_UID, "dev-001", mgr)
|
||||
|
||||
mock_run.assert_not_called()
|
||||
@@ -754,56 +714,18 @@ async def test_trigger_pending_runs_device_id_filter():
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_trigger_pending_runs_dispatches_overdue():
|
||||
"""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 = []
|
||||
"""No pending runs are dispatched by backend after config deprecation."""
|
||||
|
||||
mgr = _make_manager()
|
||||
|
||||
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]
|
||||
|
||||
with patch("app.core.agent_runner.run_local_agent", new_callable=AsyncMock) as mock_run:
|
||||
await trigger_pending_runs(_FREE_UID, "dev-001", mgr)
|
||||
|
||||
assert call_order == ["run_local"]
|
||||
mock_run.assert_not_called()
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Integration: POST /agents/{id}/run
|
||||
# Integration: POST /agents/can-create and /agents/trigger
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
|
||||
@@ -820,50 +742,67 @@ def _override_db(db_session):
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_trigger_run_unknown_agent(client):
|
||||
"""POST /agents/{id}/run returns 404 for unknown agent id."""
|
||||
async def test_can_create_agent_allows_when_under_limit(client):
|
||||
"""POST /agents/can-create returns allowed=True when under tier limit."""
|
||||
resp = client.post(
|
||||
f"/api/v1/agents/{uuid.uuid4()}/run",
|
||||
headers=auth_header("power"),
|
||||
"/api/v1/agents/can-create",
|
||||
json={"active_agents": 0},
|
||||
headers=auth_header("free"),
|
||||
)
|
||||
assert resp.status_code == 404
|
||||
assert resp.status_code == 200
|
||||
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/{id}/run creates a run log and dispatches a background task."""
|
||||
# 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 = []
|
||||
"""POST /agents/trigger creates a local run log and dispatches background task."""
|
||||
dispatched: list[tuple[str, str]] = []
|
||||
|
||||
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(
|
||||
f"/api/v1/agents/{config.id}/run",
|
||||
"/api/v1/agents/trigger",
|
||||
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 data["agent_id"] == config.id
|
||||
assert isinstance(data["agent_id"], str)
|
||||
assert data["agent_id"]
|
||||
assert data["status"] == "running"
|
||||
assert data["agent_type"] == "local"
|
||||
|
||||
|
||||
184
tests/test_classify_file.py
Normal file
184
tests/test_classify_file.py
Normal file
@@ -0,0 +1,184 @@
|
||||
"""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:]))
|
||||
288
tests/test_deep_agent.py
Normal file
288
tests/test_deep_agent.py
Normal file
@@ -0,0 +1,288 @@
|
||||
"""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
|
||||
@@ -110,6 +110,32 @@ 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
|
||||
@@ -229,6 +255,40 @@ 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):
|
||||
@@ -240,21 +300,20 @@ def test_home_request_calls_memory_middleware(client):
|
||||
def __init__(self, db):
|
||||
pass
|
||||
|
||||
async def enrich_context(self, user_id, message):
|
||||
async def enrich_context(self, user_id, message, **kwargs):
|
||||
enrich_calls.append((user_id, message))
|
||||
return {"core_memory": {"tz": "UTC"}}
|
||||
|
||||
async def store_episode(self, user_id, session_id, message, response):
|
||||
async def store_episode(self, user_id, session_id, message, response, **kwargs):
|
||||
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, db_session_factory=None):
|
||||
async def _mock_stream(user_id, message, context):
|
||||
# Verify memory context was injected
|
||||
assert context.get("core_memory") == {"tz": "UTC"}
|
||||
yield ("token", "Done")
|
||||
yield ("mutations", [])
|
||||
yield "token", "Done"
|
||||
|
||||
with (
|
||||
patch("app.api.routes.device_ws.MemoryMiddleware", _MockMiddleware),
|
||||
|
||||
@@ -1,214 +1,82 @@
|
||||
"""Tests for app.core.output_formatter — HomeFormatter and FloatingFormatter."""
|
||||
"""Tests for app.core.output_formatter.StreamFormatter."""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import pytest
|
||||
|
||||
from app.core.output_formatter import HomeFormatter, FloatingFormatter
|
||||
from app.schemas import (
|
||||
WsFloatingDomain,
|
||||
WsStreamEnd,
|
||||
WsStreamStart,
|
||||
WsStreamText,
|
||||
)
|
||||
from app.core.output_formatter import StreamFormatter
|
||||
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, event_stream):
|
||||
async def _collect(formatter: StreamFormatter, event_stream):
|
||||
frames = []
|
||||
async for frame in formatter.format(event_stream):
|
||||
frames.append(frame)
|
||||
return frames
|
||||
|
||||
|
||||
# ── HomeFormatter ─────────────────────────────────────────────────────────────
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_home_formatter_plain_text():
|
||||
req_id = "req-1"
|
||||
events = [
|
||||
("token", "Hello world"),
|
||||
("mutations", []),
|
||||
]
|
||||
formatter = HomeFormatter(request_id=req_id)
|
||||
frames = await collect(formatter, _stream(*events))
|
||||
async def test_stream_formatter_text_stream() -> None:
|
||||
formatter = StreamFormatter(request_id="req-1")
|
||||
frames = await _collect(
|
||||
formatter,
|
||||
_stream(("token", "Hello"), ("token", " world")),
|
||||
)
|
||||
|
||||
assert isinstance(frames[0], WsStreamStart)
|
||||
assert frames[0].request_id == req_id
|
||||
text_frames = [f for f in frames if isinstance(f, WsStreamText)]
|
||||
assert any("Hello world" in f.chunk for f in text_frames)
|
||||
assert isinstance(frames[1], WsStreamText)
|
||||
assert frames[1].chunk == "Hello"
|
||||
assert isinstance(frames[2], WsStreamText)
|
||||
assert frames[2].chunk == " world"
|
||||
assert isinstance(frames[-1], WsStreamEnd)
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_home_formatter_entity_tags_passed_through():
|
||||
"""Entity tags are streamed as-is — the frontend parses them."""
|
||||
req_id = "req-2"
|
||||
events = [
|
||||
("token", "Here is your project:\n<project>[abc-123]</project>\nAll good."),
|
||||
("mutations", []),
|
||||
]
|
||||
formatter = HomeFormatter(request_id=req_id)
|
||||
frames = await collect(formatter, _stream(*events))
|
||||
async def test_stream_formatter_floating_domain_first() -> None:
|
||||
formatter = StreamFormatter(request_id="req-2")
|
||||
frames = await _collect(
|
||||
formatter,
|
||||
_stream(
|
||||
(
|
||||
"floating_domain",
|
||||
{"type": "node", "id": "n-1", "section": None},
|
||||
),
|
||||
("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[0], WsFloatingDomain)
|
||||
assert frames[0].domain.type == "node"
|
||||
assert frames[0].domain.id == "n-1"
|
||||
assert isinstance(frames[1], WsStreamStart)
|
||||
assert isinstance(frames[2], WsStreamText)
|
||||
assert frames[2].chunk == "Summary"
|
||||
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))
|
||||
async def test_stream_formatter_ignores_unknown_events() -> None:
|
||||
formatter = StreamFormatter(request_id="req-3")
|
||||
frames = await _collect(
|
||||
formatter,
|
||||
_stream(("tool_end", {"name": "x"}), ("token", "ok")),
|
||||
)
|
||||
|
||||
assert isinstance(frames[0], WsFloatingDomain)
|
||||
assert frames[0].domain == "tasks"
|
||||
assert frames[0].request_id == req_id
|
||||
|
||||
|
||||
@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"
|
||||
assert text_frames[0].chunk == "ok"
|
||||
|
||||
|
||||
@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))
|
||||
async def test_stream_formatter_empty_stream_still_brackets() -> None:
|
||||
formatter = StreamFormatter(request_id="req-4")
|
||||
frames = await _collect(formatter, _stream())
|
||||
|
||||
|
||||
@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_floating_formatter_default_domain_on_early_token():
|
||||
"""When the first event is a token (no tool_end yet), default to 'tasks'."""
|
||||
req_id = "pop-5"
|
||||
formatter = FloatingFormatter(request_id=req_id)
|
||||
events = [("token", "hi"), ("mutations", [])]
|
||||
frames = await collect(formatter, _stream(*events))
|
||||
assert isinstance(frames[0], WsFloatingDomain)
|
||||
assert frames[0].domain == "tasks"
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_floating_formatter_mutations_in_stream_end():
|
||||
req_id = "pop-6"
|
||||
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))
|
||||
|
||||
end_frame = frames[-1]
|
||||
assert isinstance(end_frame, WsStreamEnd)
|
||||
assert len(end_frame.mutations) == 1
|
||||
assert len(frames) == 2
|
||||
assert isinstance(frames[0], WsStreamStart)
|
||||
assert isinstance(frames[1], WsStreamEnd)
|
||||
|
||||
@@ -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 tracker")
|
||||
result = await reg.list_plugins(db_session, query="time")
|
||||
assert result.total == 1
|
||||
assert result.plugins[0].id == "plugin-time-tracker"
|
||||
|
||||
|
||||
@@ -4,6 +4,7 @@ import pytest
|
||||
from pydantic import ValidationError
|
||||
|
||||
from app.schemas import (
|
||||
WsDomain,
|
||||
WsFrameType,
|
||||
WsHomeRequest,
|
||||
WsFloatingDomain,
|
||||
@@ -178,23 +179,15 @@ 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", "mutations": []}
|
||||
assert data == {"type": "stream_end", "request_id": "r2"}
|
||||
|
||||
|
||||
def test_stream_end_deserializes():
|
||||
raw = {"type": "stream_end", "request_id": "r3", "mutations": []}
|
||||
raw = {"type": "stream_end", "request_id": "r3"}
|
||||
frame = WsStreamEnd.model_validate(raw)
|
||||
assert frame.request_id == "r3"
|
||||
|
||||
@@ -203,28 +196,47 @@ def test_stream_end_deserializes():
|
||||
|
||||
|
||||
def test_floating_domain_tasks():
|
||||
frame = WsFloatingDomain(request_id="r1", domain="tasks")
|
||||
frame = WsFloatingDomain(request_id="r1", domain=WsDomain(type="task"))
|
||||
assert frame.type == WsFrameType.floating_domain
|
||||
assert frame.domain == "tasks"
|
||||
assert frame.domain.type == "task"
|
||||
|
||||
|
||||
@pytest.mark.parametrize("domain", ["tasks", "timelines", "notes", "projects"])
|
||||
def test_floating_domain_valid_domains(domain: str):
|
||||
frame = WsFloatingDomain(request_id="r1", domain=domain) # type: ignore[arg-type]
|
||||
assert frame.domain == domain
|
||||
def test_floating_domain_valid_domains():
|
||||
frame = WsFloatingDomain(
|
||||
request_id="r1",
|
||||
domain=WsDomain(type="project", id="213213-312321-312312-421321", section="task"),
|
||||
)
|
||||
assert frame.domain.type == "project"
|
||||
assert frame.domain.id == "213213-312321-312312-421321"
|
||||
assert frame.domain.section == "task"
|
||||
|
||||
|
||||
def test_floating_domain_invalid():
|
||||
with pytest.raises(ValidationError):
|
||||
WsFloatingDomain(request_id="r1", domain="invalid") # type: ignore[arg-type]
|
||||
def test_floating_domain_object_valid():
|
||||
frame = WsFloatingDomain(
|
||||
request_id="r1",
|
||||
domain=WsDomain(type="project", id="p1", section="task"),
|
||||
)
|
||||
assert frame.domain.type == "project"
|
||||
|
||||
|
||||
def test_floating_domain_serializes():
|
||||
d = WsFloatingDomain(request_id="r1", domain="notes").model_dump()
|
||||
assert d == {"type": "floating_domain", "request_id": "r1", "domain": "notes"}
|
||||
d = WsFloatingDomain(
|
||||
request_id="r1",
|
||||
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 = {"type": "floating_domain", "request_id": "r1", "domain": "projects"}
|
||||
raw = {
|
||||
"type": "floating_domain",
|
||||
"request_id": "r1",
|
||||
"domain": {"type": "node", "id": "n-1", "section": None},
|
||||
}
|
||||
frame = WsFloatingDomain.model_validate(raw)
|
||||
assert frame.domain == "projects"
|
||||
assert frame.domain.type == "node"
|
||||
assert frame.domain.id == "n-1"
|
||||
|
||||
@@ -45,15 +45,13 @@ def _recv_until_end(ws, max_frames: int = 20) -> list[dict]:
|
||||
return frames
|
||||
|
||||
|
||||
async def _mock_home_stream(user_id, message, context, db_session_factory=None):
|
||||
yield "token", "Here are your tasks:\n<task>[t1,t2]</task>"
|
||||
yield "mutations", []
|
||||
async def _mock_home_stream(user_id, message, context):
|
||||
yield "token", "Hello"
|
||||
|
||||
|
||||
async def _mock_floating_stream(user_id, message, context, scope=None, db_session_factory=None):
|
||||
yield "tool_end", {"name": "task_agent", "result": "ok"}
|
||||
async def _mock_floating_stream(user_id, message, context):
|
||||
yield "floating_domain", {"type": "task", "id": None, "section": None}
|
||||
yield "token", "Here is a summary"
|
||||
yield "mutations", []
|
||||
|
||||
|
||||
# ── tests ─────────────────────────────────────────────────────────────────────
|
||||
@@ -104,7 +102,7 @@ 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"] == "tasks"
|
||||
assert domain_frame["domain"]["type"] == "task"
|
||||
assert domain_frame["request_id"] == "p1"
|
||||
|
||||
|
||||
@@ -113,9 +111,8 @@ 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, db_session_factory=None):
|
||||
async def _stream(user_id, message, context):
|
||||
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:
|
||||
|
||||
Reference in New Issue
Block a user