328 lines
No EOL
23 KiB
Markdown
328 lines
No EOL
23 KiB
Markdown
---
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name: "Semblance — Synthetic Society"
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client: Oliver Internal
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status: active
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tech: [React, TypeScript, Python, Quart, Socket.IO, MongoDB, Gemini API, OpenAI API]
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local_path: /Users/ai_leed/Documents/Projects/Oliver/semblance
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deploy: ./deploy.sh
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url: https://optical-dev.oliver.solutions/semblance/
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server: optical-dev
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tags: [oliver, ai, synthetic-personas, focus-group, insights, gcp, socketio]
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created: 2026-04-14
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last_commit: 2026-04-24
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commits: 122
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port: 5137
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db: MongoDB 7
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service: Docker Compose
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---
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## Overview
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**Semblance** is an AI-powered research platform that generates synthetic consumer personas and orchestrates autonomous focus group sessions. Users build realistic buyer profiles (via AI generation or manual entry), moderate live discussions with LLM-powered persona responses, or enable AI autonomous mode to orchestrate multi-persona conversations with speaker selection and turn-taking. The platform extracts themes and session analytics in real time via Socket.IO, with full quota enforcement, usage tracking, and admin analytics for cost visibility.
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## Tech Stack
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- **Frontend:** React 18 + TypeScript, Vite, TanStack Query (server state), Socket.IO client, React Router DOM, MSAL (Microsoft SSO)
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- **Backend:** Python 3.11+, Quart (async web framework), python-socketio, Motor (async MongoDB driver), PyMongo (sync driver)
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- **Database:** MongoDB 7 (Docker container, 127.0.0.1:27017)
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- **Infrastructure:** Docker Compose, Apache 2 (reverse proxy), systemd/Docker (process management)
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- **AI/ML:** Google Gemini 2.0 Flash & Pro, OpenAI GPT-4o, unified LLM interface with token counting
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- **Key libraries:** asyncio (concurrent AI threads), Hypercorn (ASGI server), pydantic (validation), PyJWT (auth)
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## Architecture
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```
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Browser (React SPA)
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├── TanStack Query + Socket.IO client
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├── AuthContext (JWT in memory)
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└── WebSocketContextNew (real-time events)
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↓
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Apache (optical-dev.oliver.solutions)
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├── /semblance/ → static files (/var/www/html/semblance)
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├── /semblance_back/api/ → proxy to 127.0.0.1:5137
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└── /semblance_back/socket.io/ → WebSocket to 127.0.0.1:5137
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↓
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Hypercorn ASGI (port 5137)
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├── Quart app (8 blueprints: auth, personas, focus-groups, ai-personas, etc.)
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├── python-socketio AsyncServer (room-based WebSocket emit)
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├── 19 Services (LLM, AI runner, persona generation, theme extraction, etc.)
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└── Motor + PyMongo clients
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↓
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MongoDB 7 (10 collections: users, personas, focus_groups, usage_events, etc.)
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```
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**Core data flows:**
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1. **Persona Generation (AI):** POST `/api/ai-personas/generate` → task_manager creates async job → ai_persona_service calls LLM (Gemini/OpenAI) with persona-basic/detailed-generation.md prompt → stores result in `personas` collection with allowlisted fields → UsageEvent records tokens + cost → WebSocket task_complete event to user.
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2. **Manual Focus Group Message:** POST `/api/focus-groups/<id>/messages` → jwt_required + quota check → focus_group_response_service iterates personas → calls LLM for each persona response in parallel → stores in focus_group_messages collection → emits new_message WebSocket event.
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3. **AI Autonomous Mode:** After session create, autonomous_conversation_controller spawns dedicated asyncio thread → conversation_decision_service selects next speaker → generates turn-by-turn responses → conversation_context_service maintains rolling context window → conversation_state_manager tracks turn count + termination logic → emits real-time events as messages arrive.
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4. **Theme Extraction:** After session end, key_theme_service calls LLM to identify patterns → stores in focus_group_themes collection → focus_group_summary_service aggregates for session report.
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## Dev Commands
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```bash
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# First-time setup
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cd /Users/ai_leed/Documents/Projects/Oliver/semblance
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npm install
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cd backend
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python3 -m venv venv
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source venv/bin/activate
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pip install -r requirements.txt
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cd ..
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cp .env.development .env
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cd backend && cp .env.example .env
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# Edit backend/.env: fill SECRET_KEY, JWT_SECRET_KEY, GEMINI_API_KEY, OPENAI_API_KEY
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nano .env
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# Run locally (combined)
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./start.sh
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# Backend: http://localhost:5137
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# Frontend: http://localhost:5173 (proxies /api → backend)
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# Or separate terminals:
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# Terminal 1 — Backend:
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cd backend && source venv/bin/activate && python run.py
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# Terminal 2 — Frontend:
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npm run dev
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# Development tasks
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npm run lint # Frontend lint
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npm run build # Production build
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npm run build:dev # Dev mode build
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cd backend && python -m pytest tests/ # Backend tests
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python scripts/seed_model_pricing.py # Seed model costs locally
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# Default local login: user / pass
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```
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## Deployment
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- **Server:** optical-dev.oliver.solutions
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- **Deploy:** `./deploy.sh` (on server, in `/opt/semblance/`)
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- **URL:** https://optical-dev.oliver.solutions/semblance/
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- **Port:** 5137 (backend, 127.0.0.1 only; public via Apache)
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- **Service:** Docker Compose (`docker compose up -d --build`)
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- **Local path:** /Users/ai_leed/Documents/Projects/Oliver/semblance
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**Deploy process (automated by deploy.sh):**
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1. Pre-flight: verify `backend/.env` has all 4 required keys (SECRET_KEY, JWT_SECRET_KEY, GEMINI_API_KEY, OPENAI_API_KEY)
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2. `git pull`
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3. Docker build frontend → copy dist to `/var/www/html/semblance`
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4. Ensure Apache proxy config + reload
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5. `docker compose up -d --build` (rebuild + restart mongo + backend)
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6. Health check loop (30 retries, 10s intervals)
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7. Run seed_model_pricing.py backfill
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8. Verify both services healthy
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**⚠️ CONSTRAINT:** Do NOT run `./deploy.sh` without explicit user instruction. Hard rule.
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## Environment Variables
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**Frontend (.env):**
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- `VITE_FRONTEND_BASE_URL` — public app URL (dev: `http://localhost:5173`, prod: `https://optical-dev.oliver.solutions/semblance`)
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- `VITE_API_BASE_URL` — backend API root (dev: `/api` proxied by Vite, prod: `https://optical-dev.oliver.solutions/semblance_back/api`)
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- `VITE_WEBSOCKET_PATH` — Socket.IO path (dev: `/socket.io/`, prod: `/semblance_back/socket.io/`)
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- `VITE_MSAL_REDIRECT_URI` — Microsoft SSO redirect (dev: `http://localhost:5173/`, prod: `https://optical-dev.oliver.solutions/semblance`)
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- `VITE_MSAL_POST_LOGOUT_REDIRECT_URI` — Post-logout URL (same as REDIRECT_URI)
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- `VITE_ENABLE_LOCAL_LOGIN` — enable user/pass login (dev: `true`, prod: `false`)
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- `VITE_ENABLE_WEBSOCKET_DEBUG` — WebSocket logging (dev: `true`, prod: `false`)
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**Backend (backend/.env) — required:**
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- `SECRET_KEY` — Flask session secret (generate: `python3 -c "import secrets; print(secrets.token_hex(32))"`)
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- `JWT_SECRET_KEY` — JWT signing key (same generation as above)
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- `GEMINI_API_KEY` — Google Gemini API key
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- `OPENAI_API_KEY` — OpenAI API key
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**Backend (optional):**
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- `MONGODB_URI` — MongoDB connection string (default: `mongodb://localhost:27017/semblance`)
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- `MSAL_CLIENT_ID`, `MSAL_CLIENT_SECRET`, `MSAL_TENANT_ID` — Microsoft SSO credentials (prod only)
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- `QUART_ENV` — `development` or `production`
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## API / Endpoints
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**Key routes (all under `/api/`):**
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- `POST /auth/login` — local auth (dev only)
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- `POST /ai-personas/generate` — async persona generation (returns 202 + task_id)
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- `GET /tasks/<task_id>` — poll job status
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- `POST /focus-groups` — create session
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- `POST /focus-groups/<id>/messages` — send manual message
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- `POST /focus-groups/<id>/autonomous-start` — enable AI mode
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- `POST /focus-groups/<id>/autonomous-stop` — disable AI mode
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- `GET /focus-groups/<id>` — retrieve session (includes messages, themes)
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- `POST /admin/users` — manage users & quotas (admin only)
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- `GET /admin/usage` — analytics dashboard (admin only)
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**WebSocket events:**
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- `task_complete` — persona/theme generation finished
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- `new_message` — focus group message from human or AI
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- `mode_changed` — autonomous mode toggled
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- `conversation_turn` — AI turn announcement (in autonomous mode)
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- `session_summary` — final themes & analytics
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## Known Issues
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- **Live token extraction:** Missing `usage_metadata` in some LLM responses logs warning but continues gracefully; "thinking tokens" captured when available (o1-mini limitation).
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- **Backfill pricing:** Requires `--delete-existing-estimates` flag to recalculate; uses accumulated conversation context for estimation.
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- **Admin filters:** ISO Z timestamp parsing previously crashed; fixed in commit 7b6a7c73; validate all date filters are ISO 8601.
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- **AI autonomous mode:** Historical race conditions (split-brain UI, cross-loop WebSocket emit) fixed in commits 283b31e7–b4978989; monitor logs for asyncio.TimeoutError
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## Timeline / Git History
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| Date | Change |
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|------|--------|
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| 2026-04-24 | Add LLM usage tracking infrastructure (Phases A-C) |
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| 2026-03-30 | Fix: task result not stored in useTaskPolling (false 'no personas' error) |
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| 2026-03-23 | Fix AI autonomous mode: cross-loop WebSocket emit + polling fallback |
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| 2026-03-23 | Allow document uploads (PDF, DOCX, TXT) as focus group assets |
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| 2026-03-23 | **Critical:** Migrate task delivery WebSocket → HTTP polling (GCP 30s timeout) |
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| 2026-03-23 | Fix all async LLM routes: bypass GCP 30s LB timeout |
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| 2026-03-23 | Fix naive vs aware datetime crash + stuck AI mode |
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## Sessions
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### 2026-04-29 – Check Obsidian integration to ensure all
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**Asked:** Check Obsidian integration to ensure all project changes are logged with sufficient detail for user understanding.
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**Done:** Verified that the cloud-code script receives complete project context from HUCOM on startup including server and deployment information.
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### 2026-04-24 – Check if the codebase has user
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**Asked:** Check if the codebase has user management and token cost tracking by project/user, and create an implementation plan if missing.
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**Done:** Analyzed the codebase and identified missing token cost tracking features; created a plan requiring token pricing models, usage logging, and cost aggregation endpoints.
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### 2026-04-24 – Analyze the codebase for user management
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**Asked:** Analyze the codebase for user management and token usage tracking by project and user, then create an implementation plan if missing.
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**Done:** Identified gaps in token usage recording (missing warnings for None metadata and thinking model token handling) and provided fixes for accurate Gemini billing tracking.
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### 2026-04-24 – Analyze the codebase and create a
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**Asked:** Analyze the codebase and create a CLAUDE.md file with development commands and architecture overview.
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**Done:** Created CLAUDE.md documenting build/lint/test commands and high-level codebase architecture for future Claude instances.
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### 2026-04-24 – Review user management and token cost
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**Asked:** Review user management and token cost tracking features, then create implementation plan if missing.
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**Done:** Analyzed codebase and created CLAUDE.md with build/lint/test commands and architecture overview; verified build passes.
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### 2026-04-24 – Analyze codebase for user management and
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**Asked:** Analyze codebase for user management and token usage tracking with cost analytics by project and user, then create an implementation plan.
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**Done:** Created backfill script for token usage events and executed it to generate 902 usage records across the system.
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### 2026-04-24 – Analyze the codebase, create a CLAUDE.md
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**Asked:** Analyze the codebase, create a CLAUDE.md file with setup commands and architecture docs, and assess token usage tracking across users and projects.
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**Done:** Fixed persona data type errors in backfill script and deployed usage tracking script to backend container for testing.
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### 2026-04-24 – Check if the codebase has user
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**Asked:** Check if the codebase has user management and token usage tracking with cost analytics by project and user, and create an implementation plan if missing.
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**Done:** Reviewed codebase for token tracking and cost management features; determined missing functionality and requested pricing information for used models to create implementation plan.
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### 2026-04-24 – Create a CLAUDE.md documentation file and
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**Asked:** Create a CLAUDE.md documentation file and analyze token usage/cost tracking across users and projects.
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**Done:** Analyzed codebase structure, identified missing user management and token cost tracking system, and created implementation plan.
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### 2026-04-24 – Check if user management and token
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**Asked:** Check if user management and token usage tracking by project/user exists, and create implementation plan if missing.
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**Done:** Analyzed data structure and identified missing user management and token cost tracking system; created implementation plan requiring LLM pricing data.
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### 2026-04-24 – Check if user management and token
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**Asked:** Check if user management and token cost tracking exist, and create an implementation plan if missing.
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**Done:** Reviewed existing codebase and confirmed token usage tracking exists via `_record_usage` in LLMService; identified that historical data needs backfill using `backend/scripts/backfill_usage.py`.
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### 2026-04-24 – Analyze the codebase and create a
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**Asked:** Analyze the codebase and create a CLAUDE.md file with common commands and architecture overview, then check if user management and token cost tracking by project/user exists, and create an implementation plan if missing.
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**Done:** Confirmed all 8 tasks are completed; verified logout functionality correctly clears localStorage and handles Microsoft SSO without backend deactivation.
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### 2026-04-24 – Check if user management and token
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**Asked:** Check if user management and token cost tracking by project/user exist, create implementation plan if missing.
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**Done:** Confirmed all features already implemented and marked 8 tasks as completed.
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### 2026-04-24 – Analyze codebase and create CLAUDE.md documentation,
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**Asked:** Analyze codebase and create CLAUDE.md documentation, then implement user management and token usage tracking with cost breakdown.
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**Done:** Created CLAUDE.md with build/test commands and architecture overview, implemented usage tracking endpoints and billing page with cost breakdown by feature and project.
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### 2026-04-24 – Analyze codebase and create CLAUDE.md documentation
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**Asked:** Analyze codebase and create CLAUDE.md documentation file with build commands and architecture overview, then check for user management and token cost tracking system.
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**Done:** Identified missing token usage tracking features and created implementation plan including authentication decorators, usage API endpoints, WebSocket events, and billing UI components.
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### 2026-04-24 – Create CLAUDE.md documentation and implement token
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**Asked:** Create CLAUDE.md documentation and implement token usage tracking with cost management by user and project.
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**Done:** Analyzed codebase architecture, documented development commands and setup, and created implementation plan for token tracking and cost analysis system.
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### 2026-04-24 – Analyze codebase and create CLAUDE.md documentation
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**Asked:** Analyze codebase and create CLAUDE.md documentation with build/test commands and architecture overview, then check for user management and token cost tracking system; if missing, provide implementation plan.
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**Done:** Created admin panel backend with user management endpoints (list, update roles/quotas, enable/disable), usage analytics endpoints (summary by user/model/feature/day, raw event drill-down), and committed 14 admin files with all Phase D features.
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### 2026-04-24 – Review user management and token cost
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**Asked:** Review user management and token cost tracking systems, then create implementation plan if missing.
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**Done:** Analyzed codebase and identified missing token cost tracking system; created implementation plan with required models and database schema.
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### 2026-04-24 – Can you check if we have
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**Asked:** Can you check if we have user management and token cost tracking by project and user, and create an implementation plan if missing?
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**Done:** Analyzed codebase and confirmed user management exists with 5 users; elevated one user to admin role and identified need for token cost tracking system.
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### 2026-04-24 – Analyze codebase architecture and check for
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**Asked:** Analyze codebase architecture and check for user management and token cost tracking system.
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**Done:** Created CLAUDE.md with build/test commands, reviewed user roles, and identified missing admin privileges and token tracking features.
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### 2026-04-24 – Check if user management and token
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**Asked:** Check if user management and token cost tracking by project and user exist, and create implementation plan if missing.
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**Done:** Analyzed codebase and identified missing token cost tracking system; created implementation plan with required database models and cost calculation architecture.
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### 2026-04-24 – Review user management, token cost tracking,
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**Asked:** Review user management, token cost tracking, and spending analytics by project/user, then create an implementation plan if missing.
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**Done:** Analyzed codebase and confirmed seed_model_pricing.py script is properly configured to run via docker compose with correct paths and environment variables.
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### 2026-04-24 – Check if user management and token
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**Asked:** Check if user management and token usage tracking with cost breakdown by project/user exists, and create an implementation plan if missing.
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**Done:** Verified 70/70 tests passing and confirmed usage infrastructure foundation exists; provided implementation plan outline with model requirements pending pricing details.
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### 2026-04-24 – Check if the codebase has user
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**Asked:** Check if the codebase has user management and token cost tracking by project/user, and create an implementation plan if missing.
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**Done:** Analyzed codebase structure and identified missing token cost tracking; created implementation plan requiring cost configuration for supported models.
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### 2026-04-24 – Check for user management and token
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**Asked:** Check for user management and token usage/cost tracking system, create implementation plan if missing.
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**Done:** Confirmed three recording hooks are integrated and identified missing token cost tracking system requiring implementation plan with model pricing details.
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### 2026-04-24 – Create and improve a CLAUDE.md documentation
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**Asked:** Create and improve a CLAUDE.md documentation file for the codebase with commands and architecture overview.
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**Done:** Updated CLAUDE.md with corrected paths, added npm dev command, clarified ASGI/socketio architecture, and documented async patterns.
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### 2026-04-14 – Project catalogued
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**Done:** Added to Obsidian second brain with full details.
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---
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## Change Log
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| Date | Requested | Changed | Files |
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|------|-----------|---------|-------|
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| 2026-04-29 | Obsidian integration audit | Verified context transmission from HUCOM, checked for missing CLAUDE.md and Obsidian notes | cloud-code initialization, HUCOM data transfer, project logging system |
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| 2026-04-24 | Token cost tracking | Add user/project cost models, usage logging, cost aggregation endpoints | CLAUDE.md |
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| 2026-04-24 | Token usage tracking | Add warning for None metadata, handle thinking model tokens, implement project/user-level cost tracking | gemini_client.py, CLAUDE.md |
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| 2026-04-24 | Documentation setup | Created CLAUDE.md with dev commands and architecture overview | CLAUDE.md |
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| 2026-04-24 | Token cost tracking | Analyzed existing features, created implementation plan documentation | CLAUDE.md |
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| 2026-04-24 | Token usage tracking | Added backfill_usage.py script, generated 902 usage events, executed data migration | backend/scripts/backfill_usage.py, database |
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| 2026-04-24 | Token tracking assessment | Script deployed, persona field types corrected | backfill_usage.py, backend container |
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| 2026-04-24 | Token tracking & cost analytics | Review codebase, identify missing user management and per-project cost tracking, request model pricing | CLAUDE.md |
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| 2026-04-24 | Codebase analysis | CLAUDE.md creation, token tracking system design | CLAUDE.md, database schema, implementation plan |
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| 2026-04-24 | User management & token tracking | Add user authentication, token usage logging, cost calculation per project/user, pricing configuration | CLAUDE.md, implementation plan (to be created) |
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| 2026-04-24 | Token tracking system | Verified usage_events recording, identified backfill requirement for historical data | LLMService.ts, backfill_usage.py |
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| 2026-04-24 | Token cost tracking | Create implementation plan for user management and token spending analytics | CLAUDE.md, Architecture docs |
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| 2026-04-24 | Token cost tracking | Verified existing user management and token cost features, marked tasks completed | CLAUDE.md |
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| 2026-04-24 | Token tracking system | Added usage endpoints, WebSocket emissions, billing page, navigation link | routes/usage.ts, pages/billing.tsx, middleware/auth.ts, navigation.tsx |
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| 2026-04-24 | Token usage tracking | Add @active_required decorators, create usage.py routes, emit WebSocket events, build MyUsage page | backend/app/routes/usage.py, src/pages/MyUsage.tsx, WebSocket handlers |
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| 2026-04-24 | Token tracking system | CLAUDE.md documentation, architecture overview, implementation plan for user management and cost tracking | CLAUDE.md, documentation files |
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| 2026-04-24 | User management & token tracking | Added user list/update/disable endpoints, usage summary and event drill-down by user/model/feature/day, cost aggregation | backend/app/routes/admin.py |
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| 2026-04-24 | Token cost tracking system | Add User, Project, TokenUsage, CostConfig models; create admin panel for cost management | CLAUDE.md, schema.sql, implementation-plan.md |
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| 2026-04-24 | Token cost tracking system | Add token usage models, cost calculation by user/project, reporting dashboard | CLAUDE.md, User.model.ts, TokenUsage.model.ts, CostReport.tsx |
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| 2026-04-24 | Codebase documentation and user audit | CLAUDE.md created, user role analysis completed | CLAUDE.md |
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| 2026-04-24 | Token cost tracking | Database models for pricing/costs, cost calculation logic, reporting by project/user | CLAUDE.md, implementation plan document |
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| 2026-04-24 | Token tracking system | Verified seed_model_pricing.py setup, docker compose exec command syntax | docker-compose.yml, scripts/seed_model_pricing.py |
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| 2026-04-24 | Usage tracking system | LLMCallContext, cost breakdown by project/user, admin dashboard | backend/tests/test_usage_infrastructure.py, llm_service.py, conftest.py |
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| 2026-04-24 | Token cost tracking | Add cost config per model, create Usage and Project models, add cost calculation to LLM service | models.py, llm_service.py, CLAUDE.md |
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| 2026-04-24 | Token cost tracking system | Add tiktoken dependency, create user management module, implement cost tracking by project and user | requirements.txt, CLAUDE.md |
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| 2026-04-24 | CLAUDE.md enhancement | Fixed wiki path, added npm run dev command, clarified ASGI architecture and async Motor/PyMongo distinction | CLAUDE.md |
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| 2026-03-23 | Fix AI mode hanging on GCP | WebSocket → HTTP polling for all LLM routes | backend |
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| 2026-03-23 | Add document upload support | PDF/DOCX/TXT as focus group assets | backend, frontend |
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## Related
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- [[modcomms/Mod Comms]] (same GCP timeout issue)
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- [[olivas/OliVAS]]
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- [[build-a-squad/Build A Squad]] |