Michael Chihlas e8ba74ed6d
All checks were successful
Mirror to GitHub / mirror (push) Successful in 6m5s
CI / frontend (pull_request) Successful in 11m59s
CI / e2e (pull_request) Successful in 10m7s
CI / backend (pull_request) Successful in 16m22s
feat(escalations): distinguishable notifications, async AI, richer sidebar
Three improvements driven by live wedge testing.

1) Notification title now includes a problem snippet and PSA ticket
   suffix when present:
     "Escalation from Jane · #12345: Outlook is failing to sync email…"
   Replaces the prior "Session escalated by Jane" copy that made every
   escalation from the same junior look identical in the bell panel.
   Snippet is trimmed to 70 chars with ellipsis. handoff_manager now
   passes psa_ticket_id through in the notify() payload so this works
   for both /escalate and /handoff entry points.

2) AI enrichment (assessment + enhanced escalation_package) moved to
   a FastAPI BackgroundTask. The escalating engineer no longer waits
   on 15-25s of Sonnet latency — handoff creation returns as soon as
   snapshot, status flip, dual-write, documentation, PSA push, and
   notify() are committed. enrich_escalation_async opens its own DB
   session, runs both AI calls, updates handoff.ai_assessment +
   session.escalation_package, commits, and publishes a new
   `handoff_assessment_ready` event on the escalation bus. Frontend
   doesn't yet listen for that event — the magic-moment screen still
   shows a placeholder ("AI assessment is still generating. Reopen
   this view in a few seconds…") which is honest about the state.
   Live polling / auto-refresh on the bus event is the natural next
   step.

3) ChatSidebar entries now surface the problem summary as a secondary
   line and tag PSA-linked sessions with a monospace #ticket badge plus
   an "Escalated" pill on in-transit sessions. ChatListItem grew
   problem_summary, psa_ticket_id, and status fields; loadChats
   populates them from listSessions. The user couldn't tell their own
   sessions apart in the sidebar because they all rendered as "New
   Chat" with no distinguishing detail — this fixes that for any
   session, escalated or not.

Test plan
- Backend full suite: 1103 passed in 255.85s with -n auto.
- Frontend tsc -b clean.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
2026-04-28 00:34:32 -04:00
2026-04-24 23:17:06 -04:00
2026-04-24 23:17:06 -04:00

ResolutionFlow

Stop writing ticket notes. Start generating them.

ResolutionFlow is an AI-powered troubleshooting platform for MSP professionals. Engineers follow guided flows while an AI copilot assists — and documentation writes itself as a byproduct of the work.

Production: resolutionflow.com


Quick Start

# Prerequisites: Docker, Python 3.11+, Node.js 20+

# Start PostgreSQL
docker start patherly_postgres

# Backend
cd backend
source venv/bin/activate
pip install -r requirements.txt
alembic upgrade head
uvicorn app.main:app --reload

# Frontend (separate terminal)
cd frontend
npm install
npm run dev

See DEV-ENV.md for full environment setup (devserver, Docker, CORS).


Features

FlowPilot AI Copilot

Like having a senior engineer on every call. FlowPilot guides troubleshooting decisions, suggests next steps with context-aware intelligence, and automatically captures documentation as a byproduct of the session.

  • Confidence-tiered model routing (fast responses for simple steps, deeper reasoning for complex decisions)
  • AI-generated ticket summaries and session documentation
  • Standalone assistant chat with RAG for open-ended troubleshooting
  • Knowledge Flywheel: AI analyzes completed sessions and proposes new flows automatically

Guided Flows

  • Troubleshooting Flows — Decision trees with branching paths for diagnosing issues
  • Procedural Flows (Projects) — Step-by-step checklists for onboarding, migrations, deployments
  • Maintenance Flows — Scheduled recurring tasks with batch execution across multiple targets
  • Visual Flow Editor with drag-and-drop canvas, undo/redo, markdown support
  • AI Flow Builder — describe what you need, get a complete flow generated

Auto-Documentation

Every session generates timestamped, detailed notes formatted for your PSA. Engineers never write another ticket note.

  • Export to Markdown, plain text, or HTML
  • Sensitive data redaction
  • One-click push to ConnectWise PSA tickets

ConnectWise PSA Integration

  • Post session documentation directly to ConnectWise tickets as internal notes
  • Pull ticket details and client context into FlowPilot sessions
  • Member mapping between ResolutionFlow and ConnectWise users
  • Credentials encrypted at rest (Fernet), stored per-team

Team & Knowledge Management

  • Role-based access (super_admin, team_admin, engineer, viewer)
  • Shared flow library with categories, tags, folders, full-text search
  • Step Library — reusable troubleshooting steps with ratings and reviews
  • Session sharing via link (authenticated and public views)
  • Escalation workflow with AI-enhanced briefing packages
  • Flow proposals from AI analysis (review queue for team leads)

Tech Stack

Layer Technology
Frontend React 19, TypeScript, Vite, Tailwind CSS v4
State Zustand (immer + zundo for undo/redo)
Routing React Router v7
Canvas @xyflow/react (React Flow) + dagre
Backend Python FastAPI, async SQLAlchemy 2.0 + asyncpg
Database PostgreSQL 16
Migrations Alembic (75+ migrations)
Auth JWT (python-jose) + bcrypt, refresh token rotation
AI Anthropic Claude API (tiered model routing)
Embeddings Voyage AI (semantic search)
Scheduling APScheduler 3.x (async)
Analytics PostHog
Hosting Railway (auto-deploy on push to main)

Project Structure

patherly/
├── backend/
│   ├── app/
│   │   ├── main.py                 # FastAPI entry point
│   │   ├── api/endpoints/          # Route handlers (35+ endpoints)
│   │   ├── core/                   # Config, database, permissions, security
│   │   ├── models/                 # SQLAlchemy models
│   │   ├── schemas/                # Pydantic schemas
│   │   └── services/psa/           # PSA provider abstraction layer
│   ├── alembic/                    # Database migrations
│   └── tests/                      # Integration tests (100+)
├── frontend/
│   ├── src/
│   │   ├── components/             # UI components by domain
│   │   ├── pages/                  # Page components
│   │   ├── store/                  # Zustand stores
│   │   └── types/                  # TypeScript interfaces
├── docs/                           # Design docs, plans, ConnectWise reference
├── brand-assets/                   # SVGs, brand guide
├── CLAUDE.md                       # AI assistant project context
├── CURRENT-STATE.md                # Detailed feature status
└── CHANGELOG.md                    # Release history

Running Tests

# Backend integration tests
cd backend
pytest --override-ini="addopts="

# Frontend build (stricter than tsc --noEmit)
cd frontend
npm run build

Documentation

Document Purpose
CLAUDE.md Full project context for AI-assisted development
CURRENT-STATE.md Detailed feature status
03-DEVELOPMENT-ROADMAP.md Development roadmap
UI-DESIGN-SYSTEM.md Design system (Slate & Ice)
DEV-ENV.md Development environment setup
CHANGELOG.md Release history

License

Proprietary. All rights reserved.

Description
Troubleshooting decision tree application for MSP engineers - automatically generates professional documentation from guided diagnostic workflows
Readme 16 MiB
Languages
Python 54.7%
TypeScript 43.5%
HTML 1.1%
CSS 0.6%