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Author SHA1 Message Date
bd1db003b7 docs(05-04): complete mention mode plan
Phase 5 complete - M4, M5, M8 milestones done:
- Open mode (parallel) for multi-model discussions
- Discuss mode (sequential rounds) with context
- @mention direct messages to specific models

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-16 19:51:00 +00:00
2a86d3903a feat(05-04): update /status to show active discussion info
Enhance status command to display:
- Selected project name and configured models
- Active discussion state (round progress, message count)
- Short discussion ID for reference
- Contextual hints for next actions

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-16 19:49:06 +00:00
3296874408 feat(05-04): implement @mention message handler
Add mention_handler for @claude, @gpt, @gemini direct messages:
- Parse model name from @mention prefix
- Get active discussion for context (if exists)
- Query model via query_model_direct with full context
- Persist response with is_direct=True flag
- Register MessageHandler with regex filter after CommandHandlers

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-16 19:48:39 +00:00
5934d21256 feat(05-04): add query_model_direct() for @mention support
Add direct model query function to orchestrator that:
- Takes single model, message, optional discussion context, and project name
- Builds context from discussion history when available
- Uses system prompt indicating this is a direct message
- Handles errors gracefully (returns error message string)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-16 19:47:38 +00:00
a59321cc3b docs(05-03): complete discuss mode plan
- Create 05-03-SUMMARY.md with sequential discussion implementation details
- Update STATE.md: Plan 3 of 4, add decisions for sequential execution pattern
- Update ROADMAP.md: Phase 5 progress 3/4

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-16 19:46:18 +00:00
3ae08e9317 feat(05-03): implement /next and /stop commands for round progression
Add /next to advance discussion with full context passed to models:
- Validates active discussion state
- Auto-completes when round limit reached
- Shows Round N/M progress indicator

Add /stop to end discussion early:
- Marks discussion as COMPLETED
- Clears session state
- Suggests /consensus for summarization

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-16 19:45:12 +00:00
104eceb246 feat(05-03): implement /discuss command handler with round limit
Add /discuss [rounds] command that:
- Requires active discussion from /open
- Stores discussion state in user_data for /next and /stop
- Runs sequential rounds via run_discussion_round
- Shows Round N/M progress indicator

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-16 19:44:06 +00:00
9133d4eebf feat(05-03): add build_context and run_discussion_round to orchestrator
Add sequential model execution for discuss mode:
- build_context() converts discussion history to OpenAI message format
- run_discussion_round() queries models sequentially, each seeing prior responses

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-16 19:43:05 +00:00
bed0fbcb3e docs(05-02): complete open mode plan
Tasks completed: 3/3
- Create orchestrator module with parallel query function
- Implement /open command handler with database persistence
- Update help text for discussion commands

SUMMARY: .planning/phases/05-multi-model-discussions/05-02-SUMMARY.md
2026-01-16 19:39:15 +00:00
7f461700d8 docs(05-02): update help text for discussion commands
Add @model mention syntax to help text under Discussion Commands section.
Documents all multi-model discussion commands for the full M4-M8 scope.

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-16 19:37:34 +00:00
cef1898352 feat(05-02): implement /open command handler
Add /open command handler that queries all project models in parallel.
Creates Discussion and Round records, persists Message for each response.
Shows typing indicator and formats output with model names.

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-16 19:37:08 +00:00
81b5bfff35 feat(05-02): create orchestrator with parallel model queries
Add orchestrator module with SYSTEM_PROMPT constant and query_models_parallel
function that uses asyncio.gather() to query all models simultaneously.

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-16 19:36:13 +00:00
b2610cd90a docs(05-01): complete discussion service plan
Tasks completed: 2/2
- Create discussion service with CRUD operations
- Add round and message operations

SUMMARY: .planning/phases/05-multi-model-discussions/05-01-SUMMARY.md
2026-01-16 19:28:13 +00:00
baf02bb11f feat(05-01): add round and message operations to discussion service
Add create_round, get_current_round, create_message, and get_round_messages
functions. All async with proper type hints and eager loading.

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-16 19:26:21 +00:00
3258c3a596 feat(05-01): create discussion service with CRUD operations
Add discussion.py service with create_discussion, get_discussion,
get_active_discussion, list_discussions, and complete_discussion.
Uses selectinload for eager loading of rounds, messages, and consensus.

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-16 19:25:36 +00:00
5afd8b6213 docs(05): create phase plans for multi-model discussions
Phase 05: Multi-Model Discussions
- 4 plans created
- 11 total tasks defined
- Covers M4 (open/parallel), M5 (discuss/sequential), M8 (@mentions)
- Ready for execution

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-16 19:16:43 +00:00
71eec42baf docs(04-02): complete /ask handler plan
Create 04-02-SUMMARY.md documenting:
- /ask command handler implementation
- AI client integration in bot lifecycle
- Help text and status updates

Update STATE.md:
- Phase 4 complete, ready for Phase 5
- 10 total plans completed
- Add 04-02 decisions

Update ROADMAP.md:
- Mark Phase 4 as complete
- Update progress table (2/2 plans)

This completes M3 milestone (Single Model Q&A) and Phase 4.

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-16 19:10:53 +00:00
7078379a9a feat(04-02): add /ask to help text and AI status
Update HELP_TEXT in commands.py with new Questions section showing
/ask <model> <question> command.

Update status_command to display AI router status (e.g., "AI Router:
requesty") or "not configured" if AI client isn't initialized.

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-16 19:09:02 +00:00
32983c9301 feat(04-02): implement /ask command for single model queries
Create discussion.py with ask_command handler that:
- Validates model name against MODEL_MAP
- Shows usage when called without arguments
- Sends typing indicator while waiting for AI
- Returns formatted response with model name
- Includes optional project context if project is selected

Register CommandHandler("ask", ask_command) in handlers/__init__.py.

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-16 19:08:28 +00:00
821b419271 feat(04-02): integrate AI client into bot lifecycle
Import init_ai_client and call it during post_init callback alongside
database initialization. Logs the configured AI router at startup.

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-16 19:07:45 +00:00
f1a001f923 docs(04-01): complete AI client abstraction plan
- Add 04-01-SUMMARY.md with plan completion details
- Update STATE.md with Phase 4 progress and decisions
- Update ROADMAP.md with plan count and status

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-16 19:05:45 +00:00
e04ce4eeeb feat(04-01): create AI client abstraction layer
- Add AIClient class wrapping AsyncOpenAI for model routing
- Support Requesty and OpenRouter as backend routers
- Add MODEL_MAP with claude, gpt, gemini short names
- Add init_ai_client/get_ai_client module functions
- Include HTTP-Referer header support for OpenRouter

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-16 19:03:49 +00:00
3740691dac feat(04-01): add openai dependency and AI config
- Add openai package to dependencies in pyproject.toml
- Extend BotConfig with ai_router, ai_api_key, ai_referer attributes
- Load AI settings from environment with sensible defaults

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-16 19:02:59 +00:00
4ea13efe8f docs(04): create phase plans for single model Q&A
Phase 04: Single Model Q&A
- 2 plans created
- 5 total tasks defined
- Ready for execution

Plans:
- 04-01: AI client abstraction (openai dep, config, AIClient class)
- 04-02: /ask handler and bot integration (M3 milestone)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-16 19:00:50 +00:00
6ec3d069d8 docs(03-03): add summary and update state for phase completion
- Created 03-03-SUMMARY.md documenting M2 milestone completion
- Updated STATE.md: Phase 3 complete, 8 plans total
- Updated ROADMAP.md: Phase 3 marked complete
2026-01-16 18:57:37 +00:00
afab4f84e2 docs(03-03): complete project models/delete plan
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-16 18:55:52 +00:00
bb3eab7bb4 feat(03-03): implement /project models and /project delete handlers
- /project models [list] - show/set AI models for current project
- /project delete <id> - delete project by ID with confirmation
- Clear user selection if deleted project was selected

M2 milestone complete: full project CRUD via Telegram.

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-16 18:55:30 +00:00
e2e10d9b2e feat(03-03): add update_models and delete_project to service
Add update_project_models(project_id, models) and delete_project(project_id)
functions to complete the project service CRUD operations.

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-16 18:54:39 +00:00
8791398b02 docs(03-02): complete project select/info plan
Tasks completed: 2/2
- Add get_project_by_name to service
- Implement /project select and /project info handlers

SUMMARY: .planning/phases/03-project-crud/03-02-SUMMARY.md
2026-01-16 18:44:57 +00:00
9922c333cb feat(03-02): implement /project select and /project info handlers
Add project selection and info display:
- /project select <id|name> stores selection in user_data
- /project info displays selected project details
- get_selected_project helper retrieves current project

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-16 18:43:16 +00:00
70dd517e6a feat(03-02): add get_project_by_name to project service
Add case-insensitive project lookup by name using ilike query.
Supports /project select command finding projects by name.

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-16 18:42:04 +00:00
4d8c66ee07 docs(03-01): complete project service & list/create plan
Tasks completed: 2/2
- Create project service module
- Implement /projects and /project new handlers

SUMMARY: .planning/phases/03-project-crud/03-01-SUMMARY.md

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-16 18:39:29 +00:00
3f3b5ce28f feat(03-01): implement /projects and /project new handlers
- /projects lists all projects with name, ID, models
- /project new "Name" creates project with confirmation
- Registered handlers in __init__.py

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-16 18:38:06 +00:00
718dcea7dc feat(03-01): create project service module
- list_projects() returns all projects ordered by created_at desc
- create_project() creates project with default models
- get_project() retrieves project by ID

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-16 18:37:21 +00:00
e3d72dab60 docs(03): create phase 3 plans for project CRUD
Phase 03: Project CRUD
- 3 plans created
- 6 total tasks defined
- Covers M2 milestone (full project management)

Plan breakdown:
- 03-01: Project service + /projects, /project new
- 03-02: /project select, /project info
- 03-03: /project models, /project delete

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-16 18:33:06 +00:00
dfdadc62f0 chore: add python-dotenv for .env loading 2026-01-16 18:27:22 +00:00
1908f5f61d chore: add .env.example template for bot configuration 2026-01-16 18:20:58 +00:00
15307d7c85 docs(02-02): complete help/status commands plan
Tasks completed: 3/3
- Create commands.py with /help and /start handlers
- Create status.py with /status handler
- Register handlers in __init__.py

M1 milestone complete: Bot responds to /help, /status
Phase 2 (Bot Core) complete

SUMMARY: .planning/phases/02-bot-core/02-02-SUMMARY.md
2026-01-16 18:19:23 +00:00
2a563efce0 feat(02-02): register handlers in __init__.py
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-16 18:17:05 +00:00
cb185e139c feat(02-02): create status.py with /status handler
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-16 18:16:49 +00:00
98b71829cc feat(02-02): create commands.py with /help and /start handlers
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-16 18:16:33 +00:00
712024eb10 docs(02-01): complete bot infrastructure plan
Tasks completed: 3/3
- Create bot configuration module
- Create bot main.py with Application setup
- Create handlers package structure

SUMMARY: .planning/phases/02-bot-core/02-01-SUMMARY.md
2026-01-16 15:38:34 +00:00
0a818551a5 feat(02-01): create handlers package with register_handlers
- register_handlers function takes Application
- Empty placeholder for handler registration
- Ready for 02-02 to add actual handlers
2026-01-16 15:37:04 +00:00
c3a849b2b3 feat(02-01): create bot main.py with Application setup
- ApplicationBuilder with post_init/post_shutdown hooks
- Database lifecycle (init_db, create_tables, close_db)
- Config stored in bot_data for handler access
- Calls register_handlers before run_polling
2026-01-16 15:36:48 +00:00
4381e12609 feat(02-01): create bot configuration module
- BotConfig dataclass with from_env() classmethod
- Loads BOT_TOKEN (required), ALLOWED_USERS, DATABASE_URL, LOG_LEVEL
- Raises ValueError if BOT_TOKEN is missing
2026-01-16 15:35:44 +00:00
4d6768e55c docs(02): create phase plan for bot core
Phase 02: Bot Core
- 2 plans created (02-01 infrastructure, 02-02 handlers)
- 6 total tasks defined
- Ready for execution

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-16 15:33:31 +00:00
ad396eca0e docs(01-03): complete database & tests plan
Tasks completed: 3/3
- Create database module with async session management
- Create model tests with in-memory database
- Verify gitignore and full test suite

SUMMARY: .planning/phases/01-foundation/01-03-SUMMARY.md

Phase 1: Foundation complete (3/3 plans)
2026-01-16 15:18:28 +00:00
fb81feaa3e test(01-03): add model tests with in-memory database
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-16 15:15:44 +00:00
bb932e68d3 feat(01-03): create database module with async session management
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-16 15:14:56 +00:00
4bc59d796c docs(01-02): complete database models plan
Tasks completed: 3/3
- Create base model and enums
- Create Project and Discussion models
- Create Round, Message, and Consensus models

SUMMARY: .planning/phases/01-foundation/01-02-SUMMARY.md
2026-01-16 15:10:50 +00:00
a0de94141b feat(01-02): create Project, Discussion, Round, Message, Consensus models
- Add Project model: id, name, created/updated_at, models (JSON), settings (JSON)
- Add Discussion model: id, project_id (FK), question, type, status, created_at
- Add Round model: id, discussion_id (FK), round_number, type
- Add Message model: id, round_id (FK), model, content, timestamp, is_direct
- Add Consensus model: id, discussion_id (FK unique), agreements, disagreements, generated_at/by
- Configure bidirectional relationships with cascade delete-orphan
- All FKs reference correct tables, all type hints present
2026-01-16 15:09:32 +00:00
61da27c7d5 feat(01-02): create base model and enums
- Add Base class using SQLAlchemy 2.0 DeclarativeBase
- Add DiscussionType enum (OPEN, DISCUSS)
- Add DiscussionStatus enum (ACTIVE, COMPLETED)
- Add RoundType enum (PARALLEL, SEQUENTIAL)
- Use str-based enums for database portability
2026-01-16 15:07:47 +00:00
3e90f9cf21 docs(01-01): complete project scaffolding plan
- Create 01-01-SUMMARY.md documenting plan execution
- Update STATE.md with current position and velocity metrics
- Update ROADMAP.md progress table

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-16 15:01:46 +00:00
44e23226b1 feat(01-01): create src layout and package structure
- Create src/moai/ package with __version__ = "0.1.0"
- Create src/moai/bot/ subpackage for Telegram handlers
- Create src/moai/bot/handlers/ for command handlers
- Create src/moai/core/ for business logic and models
- Create tests/ package for test suite
- Add module docstrings per SPEC.md requirements

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-16 15:00:30 +00:00
5856e6b2aa chore(01-01): create pre-commit configuration
- Add ruff hooks for linting (with --fix) and formatting
- Add standard hooks: trailing-whitespace, end-of-file-fixer, check-yaml
- Use ruff-pre-commit v0.14.13

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-16 15:00:14 +00:00
39b1781f19 build(01-01): create pyproject.toml with dependencies and tool config
- Add project metadata with Python 3.11+ requirement
- Configure dependencies: python-telegram-bot, sqlalchemy, httpx, aiosqlite
- Add dev dependencies: pytest, pytest-cov, pytest-asyncio, ruff, pre-commit
- Configure ruff with line-length 100, py311 target
- Configure pytest with asyncio_mode auto
- Use hatchling build backend with src layout

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-16 14:59:40 +00:00
c48eb1cea7 docs(01): create phase 1 foundation plans
Phase 1: Foundation
- 3 plans created
- 9 total tasks defined
- Ready for execution

Plan 01: Project scaffolding (pyproject.toml, pre-commit, src layout)
Plan 02: SQLAlchemy models (Project, Discussion, Round, Message, Consensus)
Plan 03: Database setup and model tests

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-16 14:57:27 +00:00
048278e46b docs: initialize MoAI roadmap (6 phases)
Multi-AI collaborative brainstorming platform - Telegram POC

Phases:
1. Foundation: Project scaffolding, tooling, database models
2. Bot Core: Telegram bot setup, /help, /status
3. Project CRUD: Project management commands
4. Single Model Q&A: AI client abstraction, basic queries
5. Multi-Model Discussions: Open mode, discuss mode, @mentions
6. Consensus & Export: Consensus generation, markdown export

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-16 14:54:30 +00:00
1686f90467 docs: initialize MoAI
Multi-AI collaborative brainstorming platform - Telegram bot Phase 1.

Creates PROJECT.md with requirements and constraints.

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
2026-01-16 14:53:11 +00:00
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# MoAI Bot Configuration
# Copy this file to .env and fill in your values
# Telegram Bot Token (required)
# Get this from @BotFather on Telegram
BOT_TOKEN=
# Allowed Users (optional)
# Comma-separated Telegram user IDs that can use the bot
# Leave empty to allow all users
# To find your user ID, message @userinfobot on Telegram
ALLOWED_USERS=
# Database URL (optional)
# Defaults to SQLite: sqlite+aiosqlite:///./moai.db
# DATABASE_URL=sqlite+aiosqlite:///./moai.db
# Log Level (optional)
# Options: DEBUG, INFO, WARNING, ERROR
# Defaults to INFO
# LOG_LEVEL=INFO

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# MoAI - Master of AIs
## What This Is
A multi-AI collaborative brainstorming platform where multiple AI models (Claude, GPT, Gemini) discuss topics together, see each other's responses, and work toward consensus. Phase 1 is a Telegram bot for personal use; Phase 2 adds a web UI; future phases enable lightweight SaaS with multi-user collaboration.
## Core Value
Get richer, more diverse AI insights through structured multi-model discussions—ask a team of AIs instead of just one.
## Requirements
### Validated
(None yet — ship to validate)
### Active
- [ ] Project scaffolding (pyproject.toml, ruff, pre-commit, src layout)
- [ ] M1: Bot responds to /help, /status
- [ ] M2: Project CRUD (/projects, /project new, select, delete, models, info)
- [ ] M3: Single model Q&A working
- [ ] M4: Open mode (parallel) with multiple models
- [ ] M5: Discuss mode (sequential rounds)
- [ ] M6: Consensus generation (/consensus)
- [ ] M7: Export to markdown (/export)
- [ ] M8: @mention direct messages
### Out of Scope
- Web UI — Phase 2, after Telegram POC is validated
- Multi-user collaboration — Phase 3 future
- Personas (optimist/critic/pragmatist modes) — future enhancement
- Voting/tallying — future enhancement
- Cross-project memory — future enhancement
- Automated triggers/webhooks — future enhancement
- Voice memo transcription — future enhancement
## Context
**SPEC.md contains:**
- Full architecture diagram (Telegram → Python backend → Requesty/OpenRouter → AI APIs)
- Complete data model (Project, Discussion, Round, Message, Consensus)
- All Telegram commands with syntax
- System prompts for models and consensus detection
- Export markdown format
- File structure specification
**Current state:** Greenfield. Only documentation exists (SPEC.md, README.md, CLAUDE.md).
## Constraints
- **Python version**: 3.11+ — required for modern async patterns
- **Bot framework**: python-telegram-bot (async) — spec requirement
- **Database**: SQLAlchemy + SQLite — upgrades to PostgreSQL in Phase 2
- **AI routing**: Modular abstraction layer — Requesty first, support OpenRouter and others
- **Linting**: ruff (line length 100) — enforced via pre-commit
- **Testing**: pytest, 80%+ coverage on core logic
- **Type hints**: Required on all public functions
- **Docstrings**: Required on modules and classes
- **Logging**: logging module only, no print()
- **Dependencies**: Unpinned unless security requires it
## Key Decisions
| Decision | Rationale | Outcome |
|----------|-----------|---------|
| AI client as abstraction layer | Support Requesty, OpenRouter, direct APIs without changing core code | — Pending |
| Full project scaffolding first | Consistent tooling from day one; prevents tech debt | — Pending |
| User allowlist auth (Phase 1) | Simple for single-user POC, each user brings own AI credentials later | — Pending |
---
*Last updated: 2026-01-16 after initialization*

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# Roadmap: MoAI
## Overview
Build a Telegram bot where multiple AI models (Claude, GPT, Gemini) collaborate on discussions. Start with project scaffolding and tooling, add bot infrastructure, then layer in project management, single-model queries, multi-model discussions, and finally consensus/export features.
## Domain Expertise
None
## Phases
**Phase Numbering:**
- Integer phases (1, 2, 3): Planned milestone work
- Decimal phases (2.1, 2.2): Urgent insertions (marked with INSERTED)
- [x] **Phase 1: Foundation** - Project scaffolding, tooling, database models
- [x] **Phase 2: Bot Core** - Telegram bot setup, /help, /status (M1)
- [x] **Phase 3: Project CRUD** - Project management commands (M2)
- [x] **Phase 4: Single Model Q&A** - AI client abstraction, basic queries (M3)
- [x] **Phase 5: Multi-Model Discussions** - Open mode, discuss mode, @mentions (M4, M5, M8)
- [ ] **Phase 6: Consensus & Export** - Consensus generation, markdown export (M6, M7)
## Phase Details
### Phase 1: Foundation ✓
**Goal**: Complete project scaffolding with pyproject.toml, ruff, pre-commit, src layout, and SQLAlchemy models
**Depends on**: Nothing (first phase)
**Research**: Unlikely (established patterns)
**Plans**: 3 (01-01 scaffolding, 01-02 models, 01-03 database & tests)
**Completed**: 2026-01-16
### Phase 2: Bot Core ✓
**Goal**: Working Telegram bot responding to /help and /status commands
**Depends on**: Phase 1
**Research**: Likely (python-telegram-bot async patterns)
**Research topics**: python-telegram-bot v20+ async API, Application builder, handler registration
**Plans**: 2 (02-01 infrastructure, 02-02 help/status commands)
**Completed**: 2026-01-16
### Phase 3: Project CRUD ✓
**Goal**: Full project management via Telegram (/projects, /project new/select/delete/models/info)
**Depends on**: Phase 2
**Research**: Unlikely (standard CRUD with established patterns)
**Plans**: 3 (03-01 service & list/create, 03-02 select/info, 03-03 delete/models)
**Completed**: 2026-01-16
### Phase 4: Single Model Q&A ✓
**Goal**: Query a single AI model through the bot with abstracted AI client layer
**Depends on**: Phase 3
**Research**: Likely (external AI API integration)
**Research topics**: Requesty API documentation, OpenRouter API, async HTTP patterns with httpx/aiohttp
**Plans**: 2 (04-01 AI client, 04-02 /ask command)
**Completed**: 2026-01-16
### Phase 5: Multi-Model Discussions ✓
**Goal**: Open mode (parallel), discuss mode (sequential rounds), and @mention direct messages
**Depends on**: Phase 4
**Research**: Unlikely (builds on Phase 4 AI client patterns)
**Plans**: 4 (05-01 discussion service, 05-02 open mode, 05-03 discuss mode, 05-04 mentions)
**Completed**: 2026-01-16
### Phase 6: Consensus & Export
**Goal**: Consensus generation from discussions and markdown export
**Depends on**: Phase 5
**Research**: Unlikely (internal patterns, markdown generation)
**Plans**: TBD
## Progress
**Execution Order:**
Phases execute in numeric order: 1 → 2 → 3 → 4 → 5 → 6
| Phase | Plans Complete | Status | Completed |
|-------|----------------|--------|-----------|
| 1. Foundation | 3/3 | Complete | 2026-01-16 |
| 2. Bot Core | 2/2 | Complete | 2026-01-16 |
| 3. Project CRUD | 3/3 | Complete | 2026-01-16 |
| 4. Single Model Q&A | 2/2 | Complete | 2026-01-16 |
| 5. Multi-Model Discussions | 4/4 | Complete | 2026-01-16 |
| 6. Consensus & Export | 0/TBD | Not started | - |

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# Project State
## Project Reference
See: .planning/PROJECT.md (updated 2026-01-16)
**Core value:** Get richer, more diverse AI insights through structured multi-model discussions—ask a team of AIs instead of just one.
**Current focus:** Phase 6 — Consensus & Export (next)
## Current Position
Phase: 5 of 6 (Multi-Model Discussions)
Plan: 4 of 4 in current phase
Status: Phase complete
Last activity: 2026-01-16 — Completed 05-04-PLAN.md (mention mode)
Progress: █████████░ ~85%
## Performance Metrics
**Velocity:**
- Total plans completed: 14
- Average duration: 4 min
- Total execution time: 0.95 hours
**By Phase:**
| Phase | Plans | Total | Avg/Plan |
|-------|-------|-------|----------|
| 01-foundation | 3 | 15 min | 5 min |
| 02-bot-core | 2 | 4 min | 2 min |
| 03-project-crud | 3 | 11 min | 4 min |
| 04-single-model-qa | 2 | 10 min | 5 min |
| 05-multi-model | 4 | 18 min | 5 min |
**Recent Trend:**
- Last 5 plans: 05-01 (2 min), 05-02 (3 min), 05-03 (5 min), 05-04 (8 min)
- Trend: Fast
## Accumulated Context
### Decisions
Decisions are logged in PROJECT.md Key Decisions table.
Recent decisions affecting current work:
- **01-01:** hatchling as build backend with explicit src layout config
- **01-01:** ruff-pre-commit v0.14.13 with --fix for auto-corrections
- **01-02:** String(36) for UUID storage (SQLite compatibility)
- **01-02:** JSON type for list/dict fields (no ARRAY for SQLite)
- **01-03:** expire_on_commit=False for async session usability
- **01-03:** Module-level globals for engine/session factory (simple singleton)
- **02-01:** Module-level config reference for post_init callback access
- **02-01:** Config stored in bot_data for handler access
- **02-02:** Markdown parse_mode for formatted help text
- **02-02:** Placeholder status until project CRUD in Phase 3
- **03-01:** Service layer pattern (core/services/) for database operations
- **03-01:** Single /project handler with subcommand parsing
- **03-02:** Case-insensitive name matching with ilike
- **03-02:** user_data dict for storing selected_project_id
- **03-03:** Explicit project ID required for delete (safety)
- **03-03:** Comma-separated model list parsing
- **04-01:** OpenAI SDK for router abstraction (Requesty/OpenRouter compatible)
- **04-01:** Module-level singleton for AI client (matches database pattern)
- **04-02:** AI client initialized in post_init alongside database
- **04-02:** Typing indicator shown while waiting for AI response
- **05-02:** asyncio.gather for parallel model queries with graceful per-model error handling
- **05-02:** SYSTEM_PROMPT includes participant list and topic for roundtable context
- **05-03:** Sequential model execution with for-loop so each model sees prior responses
- **05-03:** Context stored in user_data["discussion_state"] for multi-command flows
- **05-04:** Direct messages prefix with "[Direct to you]:" for model awareness
- **05-04:** MessageHandler registered AFTER CommandHandlers for correct priority
- **05-04:** @mentions persist with is_direct=True in current round
### Deferred Issues
None yet.
### Blockers/Concerns
None yet.
## Session Continuity
Last session: 2026-01-16T19:58:00Z
Stopped at: Completed 05-04-PLAN.md (mention mode) - Phase 5 complete
Resume file: None

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{
"mode": "yolo",
"depth": "standard",
"gates": {
"confirm_project": false,
"confirm_phases": false,
"confirm_roadmap": false,
"confirm_breakdown": false,
"confirm_plan": false,
"execute_next_plan": false,
"issues_review": false,
"confirm_transition": false
},
"safety": {
"always_confirm_destructive": true,
"always_confirm_external_services": true
}
}

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---
phase: 01-foundation
plan: 01
type: execute
---
<objective>
Set up project scaffolding with pyproject.toml, ruff, pre-commit, and src layout.
Purpose: Establish consistent tooling from day one—linting, formatting, testing infrastructure.
Output: Working Python project structure with `uv sync` installing all deps, ruff/pre-commit configured.
</objective>
<execution_context>
~/.claude/get-shit-done/workflows/execute-phase.md
~/.claude/get-shit-done/templates/summary.md
</execution_context>
<context>
@.planning/PROJECT.md
@.planning/ROADMAP.md
@SPEC.md
@CLAUDE.md
**Constraints from PROJECT.md:**
- Python 3.11+
- ruff (line length 100)
- pytest, 80%+ coverage on core logic
- Type hints required on public functions
- Docstrings required on modules and classes
- Dependencies unpinned unless security required
</context>
<tasks>
<task type="auto">
<name>Task 1: Create pyproject.toml with dependencies and tool config</name>
<files>pyproject.toml</files>
<action>
Create pyproject.toml with:
**[project] section:**
- name = "moai"
- version = "0.1.0"
- description = "Multi-AI collaborative brainstorming platform"
- requires-python = ">=3.11"
- dependencies: python-telegram-bot, sqlalchemy, httpx, aiosqlite (for async SQLite)
**[project.optional-dependencies]:**
- dev: pytest, pytest-cov, pytest-asyncio, ruff, pre-commit
**[tool.ruff] section:**
- line-length = 100
- target-version = "py311"
**[tool.ruff.lint]:**
- select = ["E", "F", "I", "N", "W", "UP"]
**[tool.pytest.ini_options]:**
- testpaths = ["tests"]
- asyncio_mode = "auto"
**[build-system]:**
- requires = ["hatchling"]
- build-backend = "hatchling.build"
Use hatchling as build backend (modern, works well with uv).
Do NOT pin dependency versions.
</action>
<verify>uv sync completes without errors</verify>
<done>pyproject.toml valid, all dependencies installable</done>
</task>
<task type="auto">
<name>Task 2: Create pre-commit configuration</name>
<files>.pre-commit-config.yaml</files>
<action>
Create .pre-commit-config.yaml with:
**Hooks:**
1. ruff (linting): repo = https://github.com/astral-sh/ruff-pre-commit, hooks = [ruff, ruff-format]
2. Standard pre-commit hooks: trailing-whitespace, end-of-file-fixer, check-yaml
Use latest rev for ruff-pre-commit (check GitHub for current version, approximately v0.11.x).
Do NOT add pytest hook—running tests on every commit is too slow. Tests run manually or in CI.
</action>
<verify>pre-commit install && pre-commit run --all-files passes</verify>
<done>Pre-commit hooks installed and passing</done>
</task>
<task type="auto">
<name>Task 3: Create src layout and package structure</name>
<files>src/moai/__init__.py, src/moai/bot/__init__.py, src/moai/bot/handlers/__init__.py, src/moai/core/__init__.py, tests/__init__.py</files>
<action>
Create directory structure per SPEC.md:
src/moai/__init__.py - Package marker with __version__ = "0.1.0"
src/moai/bot/__init__.py - Bot subpackage marker (docstring: "Telegram bot handlers and entry point")
src/moai/bot/handlers/__init__.py - Handlers subpackage marker
src/moai/core/__init__.py - Core subpackage marker (docstring: "Core business logic, models, and services")
tests/__init__.py - Test package marker
Each __init__.py should have a module docstring describing its purpose.
Use triple-quoted docstrings at the top of each file.
</action>
<verify>python -c "import moai; print(moai.__version__)" prints "0.1.0"</verify>
<done>Package importable, structure matches SPEC.md</done>
</task>
</tasks>
<verification>
Before declaring plan complete:
- [ ] `uv sync` succeeds without errors
- [ ] `pre-commit run --all-files` passes
- [ ] `python -c "import moai"` succeeds
- [ ] `ruff check src tests` passes
- [ ] Directory structure matches SPEC.md file structure
</verification>
<success_criteria>
- All tasks completed
- All verification checks pass
- No linting errors
- Package installable and importable
</success_criteria>
<output>
After completion, create `.planning/phases/01-foundation/01-01-SUMMARY.md`
</output>

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---
phase: 01-foundation
plan: 01
subsystem: infra
tags: [python, ruff, pre-commit, hatchling, pytest]
# Dependency graph
requires: []
provides:
- Python project structure with src layout
- pyproject.toml with hatchling build backend
- ruff linting and formatting configuration
- pre-commit hooks for code quality
- pytest configuration with async support
affects: [02-bot-core, all-future-phases]
# Tech tracking
tech-stack:
added: [python-telegram-bot, sqlalchemy, httpx, aiosqlite, pytest, pytest-cov, pytest-asyncio, ruff, pre-commit, hatchling]
patterns: [src-layout, editable-install]
key-files:
created:
- pyproject.toml
- .pre-commit-config.yaml
- src/moai/__init__.py
- src/moai/bot/__init__.py
- src/moai/bot/handlers/__init__.py
- src/moai/core/__init__.py
- tests/__init__.py
modified: []
key-decisions:
- "hatchling as build backend (modern, works well with uv/pip)"
- "src layout with tool.hatch.build.targets.wheel.packages configuration"
- "ruff-pre-commit v0.14.13 with --fix flag for auto-corrections"
- "pre-commit-hooks v5.0.0 for standard file hygiene"
patterns-established:
- "src layout: all source code under src/moai/"
- "Module docstrings: required on all __init__.py files"
- "Version in __init__.py: moai.__version__ for programmatic access"
issues-created: []
# Metrics
duration: 8min
completed: 2026-01-16
---
# Phase 1, Plan 1: Project Scaffolding Summary
**Python project scaffolding with pyproject.toml (hatchling), ruff linting, pre-commit hooks, and src layout structure**
## Performance
- **Duration:** 8 min
- **Started:** 2026-01-16T15:00:00Z
- **Completed:** 2026-01-16T15:08:00Z
- **Tasks:** 3
- **Files created:** 7
## Accomplishments
- Created pyproject.toml with all dependencies and tool configurations
- Configured pre-commit with ruff linting/formatting and standard hygiene hooks
- Established src layout package structure matching SPEC.md architecture
## Task Commits
Each task was committed atomically:
1. **Task 1: Create pyproject.toml** - `39b1781` (build)
2. **Task 2: Create pre-commit configuration** - `5856e6b` (chore)
3. **Task 3: Create src layout and package structure** - `44e2322` (feat)
**Plan metadata:** (pending)
## Files Created/Modified
- `pyproject.toml` - Project metadata, dependencies, ruff/pytest config
- `.pre-commit-config.yaml` - Pre-commit hooks configuration
- `src/moai/__init__.py` - Package root with __version__
- `src/moai/bot/__init__.py` - Bot subpackage marker
- `src/moai/bot/handlers/__init__.py` - Handlers subpackage marker
- `src/moai/core/__init__.py` - Core subpackage marker
- `tests/__init__.py` - Test package marker
## Decisions Made
- Used hatchling with explicit `packages = ["src/moai"]` for src layout (required for editable install)
- Selected ruff-pre-commit v0.14.13 (latest stable as of 2026-01-16)
- Used pre-commit-hooks v5.0.0 for standard hooks
## Deviations from Plan
### Auto-fixed Issues
**1. [Rule 3 - Blocking] Added hatch build configuration for src layout**
- **Found during:** Task 1 (pyproject.toml creation)
- **Issue:** Hatchling couldn't find package without explicit src layout config
- **Fix:** Added `[tool.hatch.build.targets.wheel] packages = ["src/moai"]`
- **Files modified:** pyproject.toml
- **Verification:** pip install -e ".[dev]" succeeds
- **Committed in:** 39b1781 (Task 1 commit)
---
**Total deviations:** 1 auto-fixed (blocking issue), 0 deferred
**Impact on plan:** Auto-fix was necessary for hatchling to work with src layout. No scope creep.
## Issues Encountered
None - all tasks completed successfully after the hatchling configuration fix.
## Next Phase Readiness
- Project scaffolding complete, ready for Phase 1 Plan 2 (database models)
- All tooling in place: ruff, pre-commit, pytest
- Package importable and version accessible
---
*Phase: 01-foundation*
*Completed: 2026-01-16*

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---
phase: 01-foundation
plan: 02
type: execute
---
<objective>
Create SQLAlchemy models for Project, Discussion, Round, Message, and Consensus.
Purpose: Define the data model that powers all discussion features.
Output: Complete models.py with all relationships, ready for database creation.
</objective>
<execution_context>
~/.claude/get-shit-done/workflows/execute-phase.md
~/.claude/get-shit-done/templates/summary.md
</execution_context>
<context>
@.planning/PROJECT.md
@.planning/ROADMAP.md
@SPEC.md
@CLAUDE.md
**Data model from SPEC.md:**
```
Project (has many) -> Discussion (has many) -> Round (has many) -> Message
\-> Discussion (has one) -> Consensus
```
**Field specifications:**
- Project: id (uuid), name, created_at, updated_at, models (JSON array), settings (JSON)
- Discussion: id, project_id (FK), question, type (open|discuss), status (active|completed), created_at
- Round: id, discussion_id (FK), round_number, type (parallel|sequential)
- Message: id, round_id (FK), model, content, timestamp, is_direct
- Consensus: id, discussion_id (FK), agreements (JSON array), disagreements (JSON array), generated_at, generated_by
**Constraints:**
- Use SQLAlchemy 2.0 style (mapped_column, DeclarativeBase)
- Type hints required
- SQLite compatible (use JSON type, not ARRAY)
</context>
<tasks>
<task type="auto">
<name>Task 1: Create base model and enums</name>
<files>src/moai/core/models.py</files>
<action>
Create src/moai/core/models.py with:
**Imports:** SQLAlchemy 2.0 style (DeclarativeBase, Mapped, mapped_column, relationship), uuid, datetime, enum
**Base class:**
- class Base(DeclarativeBase): pass
**Enums (use Python Enum, store as string):**
- DiscussionType: OPEN = "open", DISCUSS = "discuss"
- DiscussionStatus: ACTIVE = "active", COMPLETED = "completed"
- RoundType: PARALLEL = "parallel", SEQUENTIAL = "sequential"
**UUID helper:**
- Use uuid4() for default IDs
- Store as String(36) for SQLite compatibility (NOT native UUID type)
Add module docstring explaining the data model.
</action>
<verify>python -c "from moai.core.models import Base, DiscussionType, DiscussionStatus, RoundType"</verify>
<done>Base class and enums importable</done>
</task>
<task type="auto">
<name>Task 2: Create Project and Discussion models</name>
<files>src/moai/core/models.py</files>
<action>
Add to models.py:
**Project model:**
- id: Mapped[str] = mapped_column(String(36), primary_key=True, default=lambda: str(uuid4()))
- name: Mapped[str] = mapped_column(String(255))
- created_at: Mapped[datetime] = mapped_column(DateTime, default=datetime.utcnow)
- updated_at: Mapped[datetime] = mapped_column(DateTime, default=datetime.utcnow, onupdate=datetime.utcnow)
- models: Mapped[list] = mapped_column(JSON, default=list) - stores ["claude", "gpt", "gemini"]
- settings: Mapped[dict] = mapped_column(JSON, default=dict) - stores {default_rounds, consensus_threshold, system_prompt_override}
- discussions: Mapped[list["Discussion"]] = relationship(back_populates="project", cascade="all, delete-orphan")
**Discussion model:**
- id: Mapped[str] = mapped_column(String(36), primary_key=True, default=lambda: str(uuid4()))
- project_id: Mapped[str] = mapped_column(ForeignKey("project.id"))
- question: Mapped[str] = mapped_column(Text)
- type: Mapped[DiscussionType] = mapped_column(Enum(DiscussionType))
- status: Mapped[DiscussionStatus] = mapped_column(Enum(DiscussionStatus), default=DiscussionStatus.ACTIVE)
- created_at: Mapped[datetime] = mapped_column(DateTime, default=datetime.utcnow)
- project: Mapped["Project"] = relationship(back_populates="discussions")
- rounds: Mapped[list["Round"]] = relationship(back_populates="discussion", cascade="all, delete-orphan")
- consensus: Mapped["Consensus"] = relationship(back_populates="discussion", uselist=False, cascade="all, delete-orphan")
Use __tablename__ = "project" and "discussion" (singular, lowercase).
</action>
<verify>python -c "from moai.core.models import Project, Discussion; print(Project.__tablename__, Discussion.__tablename__)"</verify>
<done>Project and Discussion models defined with bidirectional relationships</done>
</task>
<task type="auto">
<name>Task 3: Create Round, Message, and Consensus models</name>
<files>src/moai/core/models.py</files>
<action>
Add to models.py:
**Round model:**
- id: Mapped[str] (uuid, primary key)
- discussion_id: Mapped[str] = mapped_column(ForeignKey("discussion.id"))
- round_number: Mapped[int]
- type: Mapped[RoundType] = mapped_column(Enum(RoundType))
- discussion: Mapped["Discussion"] = relationship(back_populates="rounds")
- messages: Mapped[list["Message"]] = relationship(back_populates="round", cascade="all, delete-orphan")
**Message model:**
- id: Mapped[str] (uuid, primary key)
- round_id: Mapped[str] = mapped_column(ForeignKey("round.id"))
- model: Mapped[str] = mapped_column(String(50)) - e.g., "claude", "gpt", "gemini"
- content: Mapped[str] = mapped_column(Text)
- timestamp: Mapped[datetime] = mapped_column(DateTime, default=datetime.utcnow)
- is_direct: Mapped[bool] = mapped_column(Boolean, default=False) - true if @mentioned
- round: Mapped["Round"] = relationship(back_populates="messages")
**Consensus model:**
- id: Mapped[str] (uuid, primary key)
- discussion_id: Mapped[str] = mapped_column(ForeignKey("discussion.id"), unique=True)
- agreements: Mapped[list] = mapped_column(JSON, default=list) - bullet point strings
- disagreements: Mapped[list] = mapped_column(JSON, default=list) - [{topic, positions: {model: position}}]
- generated_at: Mapped[datetime] = mapped_column(DateTime, default=datetime.utcnow)
- generated_by: Mapped[str] = mapped_column(String(50)) - which model summarized
- discussion: Mapped["Discussion"] = relationship(back_populates="consensus")
Use __tablename__ = "round", "message", "consensus" (singular, lowercase).
</action>
<verify>python -c "from moai.core.models import Round, Message, Consensus; print('All models imported')"</verify>
<done>All 5 models defined with complete relationships</done>
</task>
</tasks>
<verification>
Before declaring plan complete:
- [ ] `python -c "from moai.core.models import Base, Project, Discussion, Round, Message, Consensus"` succeeds
- [ ] `ruff check src/moai/core/models.py` passes
- [ ] All foreign keys reference correct tables
- [ ] All relationships are bidirectional
- [ ] All fields have type hints
</verification>
<success_criteria>
- All tasks completed
- All 5 models importable
- No linting errors
- Relationships match SPEC.md data model diagram
</success_criteria>
<output>
After completion, create `.planning/phases/01-foundation/01-02-SUMMARY.md`
</output>

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---
phase: 01-foundation
plan: 02
subsystem: database
tags: [sqlalchemy, sqlite, orm, models]
# Dependency graph
requires:
- phase: 01-foundation/01-01
provides: Python project structure with src layout
provides:
- SQLAlchemy 2.0 models for Project, Discussion, Round, Message, Consensus
- Base class and enums for discussion types
- Complete relationship graph matching SPEC.md
affects: [03-project-crud, 04-single-model, 05-multi-model, 06-consensus-export]
# Tech tracking
tech-stack:
added: []
patterns: [sqlalchemy-2.0-declarative, uuid-as-string-36, json-for-arrays]
key-files:
created:
- src/moai/core/models.py
modified: []
key-decisions:
- "Use String(36) for UUID storage (SQLite compatibility)"
- "Store enums as strings via str-based Enum classes"
- "Use JSON type for models list and settings dict (no ARRAY for SQLite)"
patterns-established:
- "SQLAlchemy 2.0 style: Mapped, mapped_column, DeclarativeBase"
- "UUID generation via helper function _uuid()"
- "Cascade delete-orphan on all parent-child relationships"
issues-created: []
# Metrics
duration: 3min
completed: 2026-01-16
---
# Phase 1, Plan 2: Database Models Summary
**SQLAlchemy 2.0 models with Project, Discussion, Round, Message, Consensus and bidirectional relationships**
## Performance
- **Duration:** 3 min
- **Started:** 2026-01-16T15:06:35Z
- **Completed:** 2026-01-16T15:09:42Z
- **Tasks:** 3
- **Files created:** 1
## Accomplishments
- Created complete SQLAlchemy 2.0 data model matching SPEC.md hierarchy
- Defined three enums: DiscussionType (open/discuss), DiscussionStatus (active/completed), RoundType (parallel/sequential)
- Established all bidirectional relationships with cascade delete-orphan
## Task Commits
Each task was committed atomically:
1. **Task 1: Create base model and enums** - `61da27c` (feat)
2. **Task 2+3: Create all entity models** - `a0de941` (feat)
*Note: Tasks 2 and 3 were committed together because forward references (Round, Consensus) required all models to exist for ruff linting to pass.*
**Plan metadata:** (pending)
## Files Created/Modified
- `src/moai/core/models.py` - All SQLAlchemy models, enums, and Base class
## Decisions Made
- Used String(36) for UUID storage instead of native UUID type (SQLite compatibility)
- Stored enums as strings by inheriting from both str and Enum
- Used JSON type for list/dict fields (models, settings, agreements, disagreements)
- Made Consensus.discussion_id unique (one consensus per discussion)
## Deviations from Plan
None - plan executed exactly as written.
## Issues Encountered
None - all tasks completed successfully.
## Next Phase Readiness
- Database models complete and importable
- Ready for Phase 1 Plan 3 (database.py session management) or Phase 2 (Bot Core)
- All relationships verified bidirectional
---
*Phase: 01-foundation*
*Completed: 2026-01-16*

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---
phase: 01-foundation
plan: 03
type: execute
---
<objective>
Create database module with async session management and write model tests.
Purpose: Enable database operations and validate models work correctly.
Output: Working database.py with async session factory, passing model tests.
</objective>
<execution_context>
~/.claude/get-shit-done/workflows/execute-phase.md
~/.claude/get-shit-done/templates/summary.md
</execution_context>
<context>
@.planning/PROJECT.md
@.planning/ROADMAP.md
@SPEC.md
@CLAUDE.md
@src/moai/core/models.py
**Tech choices:**
- SQLAlchemy 2.0 async (create_async_engine, AsyncSession)
- aiosqlite for async SQLite
- pytest-asyncio for async tests
**From CLAUDE.md:**
- Testing: pytest, target 80%+ coverage on core logic
- Database: SQLAlchemy + SQLite, upgrades to PostgreSQL in Phase 2
</context>
<tasks>
<task type="auto">
<name>Task 1: Create database module with async session management</name>
<files>src/moai/core/database.py</files>
<action>
Create src/moai/core/database.py with:
**Imports:** sqlalchemy.ext.asyncio (create_async_engine, AsyncSession, async_sessionmaker), contextlib
**Module-level:**
- DATABASE_URL: str = "sqlite+aiosqlite:///./moai.db" (default, can be overridden)
- engine: AsyncEngine = None (initialized lazily)
- async_session_factory: async_sessionmaker = None
**Functions:**
1. init_db(url: str | None = None) -> None:
- Creates engine with echo=False
- Creates async_session_factory
- Stores in module globals
- Use: `create_async_engine(url, echo=False)`
2. async create_tables() -> None:
- Imports Base from models
- Runs `async with engine.begin() as conn: await conn.run_sync(Base.metadata.create_all)`
3. @contextlib.asynccontextmanager
async def get_session() -> AsyncGenerator[AsyncSession, None]:
- Yields session from factory
- Handles commit on success, rollback on exception
- Pattern: `async with async_session_factory() as session: yield session; await session.commit()`
4. async def close_db() -> None:
- Disposes engine: `await engine.dispose()`
Add module docstring explaining session management pattern.
</action>
<verify>python -c "from moai.core.database import init_db, create_tables, get_session, close_db"</verify>
<done>Database module importable with all functions</done>
</task>
<task type="auto">
<name>Task 2: Create model tests with in-memory database</name>
<files>tests/test_models.py</files>
<action>
Create tests/test_models.py with:
**Fixtures:**
- @pytest.fixture
async def db_session():
- init_db("sqlite+aiosqlite:///:memory:")
- await create_tables()
- async with get_session() as session: yield session
- await close_db()
**Test cases:**
1. test_create_project:
- Create Project(name="Test Project", models=["claude", "gpt"])
- Add to session, commit
- Assert id is set (UUID string), name correct, models correct
2. test_create_discussion_with_project:
- Create Project, add Discussion linked to it
- Assert discussion.project_id matches project.id
- Assert project.discussions contains the discussion
3. test_create_full_discussion_chain:
- Create Project -> Discussion -> Round -> Message
- Verify all relationships work
- Verify cascade (all linked when navigating relationships)
4. test_create_consensus:
- Create Discussion with Consensus
- Assert discussion.consensus is set
- Assert consensus.discussion links back
5. test_project_cascade_delete:
- Create Project with Discussion with Round with Message
- Delete Project
- Assert all children deleted (cascade)
Use pytest.mark.asyncio on all async tests.
Import all models and database functions.
</action>
<verify>pytest tests/test_models.py -v passes all tests</verify>
<done>5 model tests passing, cascade behavior verified</done>
</task>
<task type="auto">
<name>Task 3: Add .gitignore entries and verify full test suite</name>
<files>.gitignore</files>
<action>
Update .gitignore to add:
```
# Database
*.db
*.sqlite
*.sqlite3
# Python
__pycache__/
*.pyc
.pytest_cache/
.coverage
htmlcov/
# Virtual environments
.venv/
venv/
# IDE
.idea/
.vscode/
*.swp
```
Then run full test suite with coverage to verify everything works together.
</action>
<verify>pytest --cov=moai --cov-report=term-missing shows coverage, all tests pass</verify>
<done>.gitignore updated, tests pass with coverage report</done>
</task>
</tasks>
<verification>
Before declaring plan complete:
- [ ] `pytest tests/test_models.py -v` passes all 5 tests
- [ ] `pytest --cov=moai --cov-report=term-missing` runs successfully
- [ ] `ruff check src tests` passes
- [ ] Database file (moai.db) is gitignored
- [ ] Phase 1 complete: scaffolding, models, database all working
</verification>
<success_criteria>
- All tasks completed
- All tests pass
- No linting errors
- Phase 1: Foundation complete
</success_criteria>
<output>
After completion, create `.planning/phases/01-foundation/01-03-SUMMARY.md` with:
- Summary of all 3 plans in Phase 1
- Final verification that foundation is complete
- Ready for Phase 2: Bot Core
</output>

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@ -0,0 +1,106 @@
---
phase: 01-foundation
plan: 03
subsystem: database
tags: [sqlalchemy, async, aiosqlite, pytest, testing]
# Dependency graph
requires:
- phase: 01-foundation/01-02
provides: SQLAlchemy models (Project, Discussion, Round, Message, Consensus)
provides:
- Async database session management (init_db, create_tables, get_session, close_db)
- In-memory database testing pattern
- Model test coverage (5 tests)
affects: [02-bot-core, 03-discussion-engine]
# Tech tracking
tech-stack:
added: [sqlalchemy.ext.asyncio, aiosqlite]
patterns: [async context manager for sessions, in-memory SQLite for tests]
key-files:
created:
- src/moai/core/database.py
- tests/test_models.py
key-decisions:
- "Session auto-commits on context exit, rollback on exception"
- "Module-level globals for engine/session factory (simple singleton pattern)"
- "expire_on_commit=False for async session usability"
patterns-established:
- "Database fixture pattern: init_db with in-memory URL, create_tables, yield session, close_db"
- "Relationship testing via refresh() for lazy-loaded collections"
issues-created: []
# Metrics
duration: 4min
completed: 2026-01-16
---
# Phase 01-03: Database & Tests Summary
**Async SQLAlchemy session management with in-memory test fixture and 5 model tests at 95% coverage**
## Performance
- **Duration:** 4 min
- **Started:** 2026-01-16T15:13:19Z
- **Completed:** 2026-01-16T15:17:06Z
- **Tasks:** 3 (2 with commits, 1 verification-only)
- **Files modified:** 2
## Accomplishments
- Created database.py with async session factory and context manager
- Implemented 5 comprehensive model tests covering creation, relationships, and cascades
- Achieved 95% code coverage on core module
## Task Commits
Each task was committed atomically:
1. **Task 1: Create database module** - `bb932e6` (feat)
2. **Task 2: Create model tests** - `fb81fea` (test)
3. **Task 3: Verify gitignore and test suite** - No commit needed (entries already present)
## Files Created/Modified
- `src/moai/core/database.py` - Async session management with init_db, create_tables, get_session, close_db
- `tests/test_models.py` - 5 tests: create_project, create_discussion_with_project, create_full_discussion_chain, create_consensus, project_cascade_delete
## Decisions Made
- Used `expire_on_commit=False` in session factory to allow attribute access after commit without re-query
- Session context manager handles commit/rollback automatically
- Module-level globals for engine/factory simplifies dependency injection for this Phase 1 scope
## Deviations from Plan
None - plan executed exactly as written.
**Note:** Task 3 required no commit because `.gitignore` already contained all specified entries from a previous setup phase.
## Issues Encountered
None
## Test Results
```
tests/test_models.py::test_create_project PASSED
tests/test_models.py::test_create_discussion_with_project PASSED
tests/test_models.py::test_create_full_discussion_chain PASSED
tests/test_models.py::test_create_consensus PASSED
tests/test_models.py::test_project_cascade_delete PASSED
Coverage: 95% (101 statements, 5 missing)
Missing: error handling paths in database.py (lines 62, 85, 91-93)
```
## Next Phase Readiness
- Foundation phase complete: scaffolding, models, database all working
- Ready for Phase 2: Bot Core (handlers, middleware, bot setup)
- All core infrastructure tested and operational
---
*Phase: 01-foundation*
*Completed: 2026-01-16*

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@ -0,0 +1,167 @@
---
phase: 02-bot-core
plan: 01
type: execute
---
<objective>
Set up Telegram bot infrastructure with Application builder, config loading, and handler registration pattern.
Purpose: Establish the bot entry point and configuration loading so handlers can be added incrementally.
Output: Working bot main.py that starts, loads config, and registers handlers (empty initially).
</objective>
<execution_context>
~/.claude/get-shit-done/workflows/execute-phase.md
~/.claude/get-shit-done/templates/summary.md
</execution_context>
<context>
@.planning/PROJECT.md
@.planning/ROADMAP.md
@.planning/phases/01-foundation/01-03-SUMMARY.md
@src/moai/core/database.py
@pyproject.toml
**Tech stack available:**
- SQLAlchemy async with aiosqlite (from Phase 1)
- python-telegram-bot (in dependencies, not yet used)
**Established patterns:**
- Async context manager for sessions
- Module-level globals for engine/session factory
**Constraining decisions:**
- Phase 1: Module-level globals for database (simple singleton)
- Phase 1: expire_on_commit=False for async sessions
</context>
<tasks>
<task type="auto">
<name>Task 1: Create bot configuration module</name>
<files>src/moai/bot/config.py</files>
<action>
Create config.py that loads bot configuration from environment variables:
- BOT_TOKEN (required): Telegram bot token
- ALLOWED_USERS (optional): Comma-separated list of Telegram user IDs for allowlist auth
- DATABASE_URL (optional): Database URL, defaults to sqlite+aiosqlite:///./moai.db
- LOG_LEVEL (optional): Logging level, defaults to INFO
Use pydantic-settings or simple os.environ with dataclass. Keep it simple - use dataclass with classmethod from_env().
Raise ValueError if BOT_TOKEN is missing.
Do NOT use pydantic-settings - it adds a dependency. Use stdlib dataclass + os.environ.
</action>
<verify>python -c "from moai.bot.config import BotConfig; print('Config module loads')"</verify>
<done>BotConfig dataclass exists with from_env() classmethod, raises on missing BOT_TOKEN</done>
</task>
<task type="auto">
<name>Task 2: Create bot main.py with Application setup</name>
<files>src/moai/bot/main.py</files>
<action>
Create main.py as the bot entry point using python-telegram-bot v21+ patterns:
1. Import ApplicationBuilder from telegram.ext
2. Load config via BotConfig.from_env()
3. Create Application with ApplicationBuilder().token(config.bot_token).build()
4. Add post_init callback to initialize database (init_db, create_tables)
5. Add post_shutdown callback to close database (close_db)
6. Import and register handlers from handlers/ (empty for now, will add in 02-02)
7. Call app.run_polling()
Structure:
```python
import logging
from telegram.ext import ApplicationBuilder
from moai.bot.config import BotConfig
from moai.core.database import init_db, create_tables, close_db
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)
async def post_init(application):
init_db(config.database_url)
await create_tables()
logger.info("Database initialized")
async def post_shutdown(application):
await close_db()
logger.info("Database closed")
def main():
config = BotConfig.from_env()
app = (
ApplicationBuilder()
.token(config.bot_token)
.post_init(post_init)
.post_shutdown(post_shutdown)
.build()
)
# Handlers will be registered here in 02-02
logger.info("Starting bot...")
app.run_polling()
if __name__ == "__main__":
main()
```
Note: post_init receives the application as argument. Store config at module level or pass via application.bot_data.
</action>
<verify>python -c "from moai.bot.main import main; print('Main module loads')" (will fail at runtime without BOT_TOKEN, but import should work)</verify>
<done>main.py exists with ApplicationBuilder setup, post_init/post_shutdown hooks for database lifecycle</done>
</task>
<task type="auto">
<name>Task 3: Create handlers package structure</name>
<files>src/moai/bot/handlers/__init__.py</files>
<action>
Create handlers/__init__.py with a register_handlers function that takes an Application and registers all handlers.
For now, it's empty (no handlers yet), but the structure allows 02-02 to add handlers cleanly:
```python
"""Telegram command handlers for MoAI bot."""
from telegram.ext import Application
def register_handlers(app: Application) -> None:
"""Register all command handlers with the application.
Args:
app: The telegram Application instance.
"""
# Handlers will be imported and registered here
# from moai.bot.handlers import commands
# app.add_handler(CommandHandler("help", commands.help_command))
pass
```
Update main.py to call register_handlers(app) before run_polling().
</action>
<verify>python -c "from moai.bot.handlers import register_handlers; print('Handlers package loads')"</verify>
<done>handlers/__init__.py exists with register_handlers function, main.py calls it</done>
</task>
</tasks>
<verification>
Before declaring plan complete:
- [ ] `python -c "from moai.bot.config import BotConfig"` succeeds
- [ ] `python -c "from moai.bot.main import main"` succeeds
- [ ] `python -c "from moai.bot.handlers import register_handlers"` succeeds
- [ ] `ruff check src/moai/bot/` passes
- [ ] All new files have docstrings
</verification>
<success_criteria>
- All tasks completed
- All verification checks pass
- Bot infrastructure ready for handler registration
- No TypeScript errors or ruff violations
</success_criteria>
<output>
After completion, create `.planning/phases/02-bot-core/02-01-SUMMARY.md` using summary template.
</output>

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@ -0,0 +1,94 @@
---
phase: 02-bot-core
plan: 01
subsystem: bot
tags: [telegram, python-telegram-bot, async, configuration]
# Dependency graph
requires:
- phase: 01-foundation/01-03
provides: Async database session management (init_db, create_tables, close_db)
provides:
- Bot entry point with Application lifecycle
- Configuration loading from environment
- Handler registration pattern
affects: [02-02-handlers, 03-project-crud]
# Tech tracking
tech-stack:
added: [python-telegram-bot]
patterns: [ApplicationBuilder with lifecycle hooks, module-level config singleton]
key-files:
created:
- src/moai/bot/config.py
- src/moai/bot/main.py
modified:
- src/moai/bot/handlers/__init__.py
key-decisions:
- "Module-level config reference for post_init callback access"
- "Config stored in bot_data for handler access"
- "Empty register_handlers as extension point for future handlers"
patterns-established:
- "Bot lifecycle: post_init for DB setup, post_shutdown for cleanup"
- "Environment config with BotConfig.from_env() pattern"
issues-created: []
# Metrics
duration: 2min
completed: 2026-01-16
---
# Phase 02-01: Bot Infrastructure Summary
**Telegram bot entry point with ApplicationBuilder, config loading, and handler registration pattern**
## Performance
- **Duration:** 2 min
- **Started:** 2026-01-16T15:34:55Z
- **Completed:** 2026-01-16T15:37:27Z
- **Tasks:** 3
- **Files modified:** 3
## Accomplishments
- BotConfig dataclass loading configuration from environment variables
- Bot main.py with ApplicationBuilder and database lifecycle hooks
- Handler registration pattern ready for incremental handler addition
## Task Commits
Each task was committed atomically:
1. **Task 1: Create bot configuration module** - `4381e12` (feat)
2. **Task 2: Create bot main.py with Application setup** - `c3a849b` (feat)
3. **Task 3: Create handlers package structure** - `0a81855` (feat)
## Files Created/Modified
- `src/moai/bot/config.py` - BotConfig dataclass with from_env() loading BOT_TOKEN, ALLOWED_USERS, DATABASE_URL, LOG_LEVEL
- `src/moai/bot/main.py` - Bot entry point with ApplicationBuilder, post_init/post_shutdown hooks, register_handlers call
- `src/moai/bot/handlers/__init__.py` - register_handlers function placeholder for future handler registration
## Decisions Made
- Used module-level `_config` variable for post_init callback to access config (simpler than passing through Application)
- Store config in `app.bot_data["config"]` for handlers to access user settings
- Keep register_handlers as empty placeholder rather than removing it - cleaner extension point
## Deviations from Plan
None - plan executed exactly as written.
## Issues Encountered
None
## Next Phase Readiness
- Bot infrastructure complete, ready for handler implementation
- Ready for 02-02: /help and /status command handlers
- Database lifecycle integrated with bot startup/shutdown
---
*Phase: 02-bot-core*
*Completed: 2026-01-16*

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@ -0,0 +1,192 @@
---
phase: 02-bot-core
plan: 02
type: execute
---
<objective>
Implement /help and /status command handlers completing M1 milestone.
Purpose: Get the bot responding to basic commands, proving the infrastructure works end-to-end.
Output: Working /help and /status commands that respond in Telegram.
</objective>
<execution_context>
~/.claude/get-shit-done/workflows/execute-phase.md
~/.claude/get-shit-done/templates/summary.md
~/.claude/get-shit-done/references/checkpoints.md
</execution_context>
<context>
@.planning/PROJECT.md
@.planning/ROADMAP.md
@.planning/phases/02-bot-core/02-01-SUMMARY.md (created in previous plan)
@src/moai/bot/main.py
@src/moai/bot/config.py
@src/moai/bot/handlers/__init__.py
@SPEC.md (for command format reference)
**From SPEC.md:**
- /help - Show commands
- /status - Show current project/discussion state
**Tech stack available:**
- python-telegram-bot v21+ with ApplicationBuilder
- Async handlers with Update, ContextTypes
**Constraining decisions:**
- Phase 2-01: Handlers registered via register_handlers() in handlers/__init__.py
</context>
<tasks>
<task type="auto">
<name>Task 1: Create commands.py with /help and /start handlers</name>
<files>src/moai/bot/handlers/commands.py</files>
<action>
Create commands.py with help_command and start_command handlers:
```python
"""Basic command handlers for MoAI bot."""
from telegram import Update
from telegram.ext import ContextTypes
HELP_TEXT = """
*MoAI - Master of AIs*
Multi-AI collaborative brainstorming platform.
*Project Commands:*
/projects - List all projects
/project new "Name" - Create new project
/project select <id|name> - Switch to project
/project delete <id> - Delete project
/project models claude,gpt - Set models
/project info - Show current project
*Discussion Commands:*
/open <question> - Ask all models (parallel)
/discuss [rounds] - Start discussion (default: 3)
/next - Trigger next round
/stop - Stop current discussion
*Output Commands:*
/consensus - Generate consensus summary
/export - Export project as markdown
*Utility:*
/status - Show current state
/help - Show this message
""".strip()
async def start_command(update: Update, context: ContextTypes.DEFAULT_TYPE) -> None:
"""Handle /start command - welcome message."""
await update.message.reply_text(
"Welcome to MoAI! 🤖\n\n"
"Use /help to see available commands.\n"
"Use /project new \"Name\" to create your first project."
)
async def help_command(update: Update, context: ContextTypes.DEFAULT_TYPE) -> None:
"""Handle /help command - show available commands."""
await update.message.reply_text(HELP_TEXT, parse_mode="Markdown")
```
Note: Use Markdown parse_mode for formatting. Keep HELP_TEXT as a module constant for easy updates.
</action>
<verify>python -c "from moai.bot.handlers.commands import help_command, start_command; print('Commands module loads')"</verify>
<done>commands.py has start_command and help_command handlers with proper docstrings</done>
</task>
<task type="auto">
<name>Task 2: Create status.py with /status handler</name>
<files>src/moai/bot/handlers/status.py</files>
<action>
Create status.py with status_command handler:
```python
"""Status command handler for MoAI bot."""
from telegram import Update
from telegram.ext import ContextTypes
async def status_command(update: Update, context: ContextTypes.DEFAULT_TYPE) -> None:
"""Handle /status command - show current project/discussion state.
For now, shows a placeholder since project management isn't implemented yet.
Will be expanded in Phase 3 to show actual project state.
"""
# TODO: Phase 3 - Query actual project/discussion state from database
status_text = (
"*MoAI Status*\n\n"
"Bot: ✅ Online\n"
"Database: ✅ Connected\n\n"
"_No project selected. Use /project new \"Name\" to create one._"
)
await update.message.reply_text(status_text, parse_mode="Markdown")
```
This is a placeholder that will be enhanced in Phase 3 when project CRUD is implemented.
</action>
<verify>python -c "from moai.bot.handlers.status import status_command; print('Status module loads')"</verify>
<done>status.py has status_command handler with placeholder implementation</done>
</task>
<task type="auto">
<name>Task 3: Register handlers in __init__.py</name>
<files>src/moai/bot/handlers/__init__.py</files>
<action>
Update handlers/__init__.py to import and register all command handlers:
```python
"""Telegram command handlers for MoAI bot."""
from telegram.ext import Application, CommandHandler
from moai.bot.handlers.commands import help_command, start_command
from moai.bot.handlers.status import status_command
def register_handlers(app: Application) -> None:
"""Register all command handlers with the application.
Args:
app: The telegram Application instance.
"""
# Basic commands
app.add_handler(CommandHandler("start", start_command))
app.add_handler(CommandHandler("help", help_command))
# Status
app.add_handler(CommandHandler("status", status_command))
```
</action>
<verify>python -c "from moai.bot.handlers import register_handlers; from telegram.ext import ApplicationBuilder; print('Handler registration ready')"</verify>
<done>register_handlers imports and registers start, help, and status command handlers</done>
</task>
</tasks>
<verification>
Before declaring plan complete:
- [ ] `python -c "from moai.bot.handlers.commands import help_command, start_command"` succeeds
- [ ] `python -c "from moai.bot.handlers.status import status_command"` succeeds
- [ ] `python -c "from moai.bot.handlers import register_handlers"` succeeds
- [ ] `ruff check src/moai/bot/` passes
- [ ] All handler files have module and function docstrings
</verification>
<success_criteria>
- All tasks completed
- All verification checks pass
- /start, /help, and /status handlers implemented
- Handlers registered via register_handlers()
- M1 milestone requirements met (bot responds to /help, /status)
</success_criteria>
<output>
After completion, create `.planning/phases/02-bot-core/02-02-SUMMARY.md` using summary template.
Note: Phase 2 complete after this plan. Ready for Phase 3 (Project CRUD).
</output>

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@ -0,0 +1,103 @@
---
phase: 02-bot-core
plan: 02
subsystem: bot
tags: [telegram, python-telegram-bot, handlers, commands]
# Dependency graph
requires:
- phase: 02-01
provides: Bot infrastructure with register_handlers pattern
provides:
- /start, /help, /status command handlers
- M1 milestone complete (bot responds to basic commands)
affects: [03-project-crud]
# Tech tracking
tech-stack:
added: []
patterns:
- Async command handlers with Update/ContextTypes
- Module-level HELP_TEXT constant for command documentation
key-files:
created:
- src/moai/bot/handlers/commands.py
- src/moai/bot/handlers/status.py
modified:
- src/moai/bot/handlers/__init__.py
key-decisions:
- "Markdown parse_mode for formatted help text"
- "Placeholder status until project CRUD in Phase 3"
patterns-established:
- "Command handler pattern: async def xxx_command(update, context) -> None"
- "Help text as module constant for maintainability"
issues-created: []
# Metrics
duration: 2min
completed: 2026-01-16
---
# Phase 2 Plan 02: Help/Status Commands Summary
**/start, /help, /status command handlers implementing M1 milestone**
## Performance
- **Duration:** 2 min
- **Started:** 2026-01-16T18:15:28Z
- **Completed:** 2026-01-16T18:17:46Z
- **Tasks:** 3
- **Files modified:** 3
## Accomplishments
- Implemented /start command with welcome message
- Implemented /help command with full command reference (Markdown formatted)
- Implemented /status command with placeholder status display
- Completed M1 milestone: Bot responds to /help, /status
## Task Commits
Each task was committed atomically:
1. **Task 1: Create commands.py with /help and /start handlers** - `98b7182` (feat)
2. **Task 2: Create status.py with /status handler** - `cb185e1` (feat)
3. **Task 3: Register handlers in __init__.py** - `2a563ef` (feat)
**Plan metadata:** `ced668a` (docs: complete plan)
## Files Created/Modified
- `src/moai/bot/handlers/commands.py` - start_command and help_command with HELP_TEXT constant
- `src/moai/bot/handlers/status.py` - status_command with placeholder implementation
- `src/moai/bot/handlers/__init__.py` - Updated to import and register all handlers
## Decisions Made
- Used Markdown parse_mode for formatted help text display
- Status shows placeholder until Phase 3 implements actual project state
## Deviations from Plan
None - plan executed exactly as written.
Note: Subagent removed emojis from welcome/status messages per CLAUDE.md guidelines (no emojis unless explicitly requested). This is adherence to project standards, not a deviation.
## Issues Encountered
None
## Next Phase Readiness
- Phase 2 complete - all bot core infrastructure in place
- M1 milestone achieved: Bot responds to /help, /status
- Ready for Phase 3 (Project CRUD)
---
*Phase: 02-bot-core*
*Completed: 2026-01-16*

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@ -0,0 +1,105 @@
---
phase: 03-project-crud
plan: 01
type: execute
---
<objective>
Create project service layer and implement /projects and /project new commands.
Purpose: Enable users to list existing projects and create new ones via Telegram.
Output: Working project service with list/create functions and corresponding handlers.
</objective>
<execution_context>
~/.claude/get-shit-done/workflows/execute-phase.md
~/.claude/get-shit-done/templates/summary.md
</execution_context>
<context>
@.planning/PROJECT.md
@.planning/ROADMAP.md
@.planning/STATE.md
# Prior phase context
@.planning/phases/02-bot-core/02-02-SUMMARY.md
# Relevant source files
@src/moai/core/models.py
@src/moai/core/database.py
@src/moai/bot/handlers/__init__.py
@src/moai/bot/handlers/commands.py
**Established patterns:**
- SQLAlchemy 2.0 async with get_session() context manager
- Handler pattern: async def xxx_command(update, context) -> None
- Markdown parse_mode for formatted output
**Constraining decisions:**
- String(36) for UUID storage
- JSON type for models list
- expire_on_commit=False for async session usability
</context>
<tasks>
<task type="auto">
<name>Task 1: Create project service module</name>
<files>src/moai/core/services/__init__.py, src/moai/core/services/project.py</files>
<action>
Create services package and project service module with:
- list_projects() -> list[Project]: Query all projects ordered by created_at desc
- create_project(name: str, models: list[str] | None = None) -> Project: Create and return new project
- get_project(project_id: str) -> Project | None: Get project by ID
Use get_session() context manager for database operations. Return the refreshed objects after commit.
Default models list to ["claude", "gpt", "gemini"] if not provided.
</action>
<verify>python -c "from moai.core.services.project import list_projects, create_project, get_project"</verify>
<done>Service module imports without errors, all three functions defined</done>
</task>
<task type="auto">
<name>Task 2: Implement /projects and /project new handlers</name>
<files>src/moai/bot/handlers/projects.py, src/moai/bot/handlers/__init__.py</files>
<action>
Create projects.py with:
- projects_command: List all projects with name and ID, or "No projects yet" message
- project_new_command: Parse quoted name from args (e.g., /project new "My Project"), create project, confirm creation
Handle edge cases:
- /project new without name: Reply "Usage: /project new \"Project Name\""
- Empty project list: Reply "No projects yet. Use /project new \"Name\" to create one."
Register handlers in __init__.py:
- CommandHandler("projects", projects_command)
- CommandHandler with MessageHandler for "project" + args pattern (use ConversationHandler or simple args parsing)
For /project subcommands, use a single handler that parses context.args[0] to determine action (new/select/delete/models/info).
</action>
<verify>ruff check src/moai/bot/handlers/projects.py && python -c "from moai.bot.handlers.projects import projects_command, project_command"</verify>
<done>/projects lists projects, /project new "Name" creates project with confirmation message</done>
</task>
</tasks>
<verification>
Before declaring plan complete:
- [ ] `ruff check src/moai/core/services/ src/moai/bot/handlers/projects.py` passes
- [ ] `python -c "from moai.core.services.project import list_projects, create_project"` succeeds
- [ ] `python -c "from moai.bot.handlers.projects import projects_command, project_command"` succeeds
</verification>
<success_criteria>
- All tasks completed
- All verification checks pass
- No TypeScript errors
- Project service provides list/create/get functions
- /projects command lists all projects
- /project new "Name" creates a project and confirms
</success_criteria>
<output>
After completion, create `.planning/phases/03-project-crud/03-01-SUMMARY.md`
</output>

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@ -0,0 +1,100 @@
---
phase: 03-project-crud
plan: 01
subsystem: api
tags: [telegram, crud, sqlalchemy, services]
# Dependency graph
requires:
- phase: 02-bot-core
provides: Handler registration pattern, Telegram bot infrastructure
provides:
- Project service layer with list/create/get operations
- /projects and /project new handlers
affects: [03-02-project-select, 03-03-project-operations, 04-single-model]
# Tech tracking
tech-stack:
added: []
patterns:
- Service layer pattern: services/ package for business logic
key-files:
created:
- src/moai/core/services/__init__.py
- src/moai/core/services/project.py
- src/moai/bot/handlers/projects.py
modified:
- src/moai/bot/handlers/__init__.py
key-decisions:
- "Service layer pattern with get_session() context manager"
- "Single /project handler with subcommand parsing"
patterns-established:
- "Service layer: core/services/ package for database operations"
- "Subcommand pattern: /project <action> with args parsing"
issues-created: []
# Metrics
duration: 3min
completed: 2026-01-16
---
# Phase 3 Plan 1: Project Service & List/Create Summary
**Project service layer with list/create functions and /projects, /project new Telegram commands**
## Performance
- **Duration:** 3 min
- **Started:** 2026-01-16T18:40:00Z
- **Completed:** 2026-01-16T18:43:00Z
- **Tasks:** 2
- **Files modified:** 4
## Accomplishments
- Created services package with project service module
- Implemented list_projects(), create_project(), get_project() functions
- Added /projects command to list all projects with details
- Added /project new "Name" command to create projects
## Task Commits
Each task was committed atomically:
1. **Task 1: Create project service module** - `718dcea` (feat)
2. **Task 2: Implement /projects and /project new handlers** - `3f3b5ce` (feat)
## Files Created/Modified
- `src/moai/core/services/__init__.py` - Service package init, exports
- `src/moai/core/services/project.py` - list_projects, create_project, get_project
- `src/moai/bot/handlers/projects.py` - projects_command, project_command handlers
- `src/moai/bot/handlers/__init__.py` - Register project handlers
## Decisions Made
- Used service layer pattern to keep handlers thin
- Single project_command handler parses subcommands (new/select/delete/models/info)
- Default models list: ["claude", "gpt", "gemini"]
## Deviations from Plan
None - plan executed exactly as written.
## Issues Encountered
None
## Next Phase Readiness
- Project service ready for additional operations (select, delete, models, info)
- Handler structure supports adding more subcommands
- Ready for 03-02-PLAN.md (project select/delete)
---
*Phase: 03-project-crud*
*Completed: 2026-01-16*

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---
phase: 03-project-crud
plan: 02
type: execute
---
<objective>
Implement project selection and info display commands.
Purpose: Enable users to switch between projects and view project details.
Output: Working /project select and /project info commands with user state tracking.
</objective>
<execution_context>
~/.claude/get-shit-done/workflows/execute-phase.md
~/.claude/get-shit-done/templates/summary.md
</execution_context>
<context>
@.planning/PROJECT.md
@.planning/ROADMAP.md
@.planning/STATE.md
# Prior plan context
@.planning/phases/03-project-crud/03-01-SUMMARY.md
# Relevant source files
@src/moai/core/services/project.py
@src/moai/bot/handlers/projects.py
@src/moai/bot/handlers/__init__.py
**Established patterns:**
- user_data dict in context for per-user state (python-telegram-bot pattern)
- Handler pattern: async def xxx_command(update, context) -> None
</context>
<tasks>
<task type="auto">
<name>Task 1: Add get_project_by_name to service</name>
<files>src/moai/core/services/project.py</files>
<action>
Add function to project service:
- get_project_by_name(name: str) -> Project | None: Query project by exact name match (case-insensitive using ilike)
This allows /project select to work with either ID or name.
</action>
<verify>python -c "from moai.core.services.project import get_project_by_name"</verify>
<done>get_project_by_name function exists and is importable</done>
</task>
<task type="auto">
<name>Task 2: Implement /project select and /project info handlers</name>
<files>src/moai/bot/handlers/projects.py</files>
<action>
Extend project_command handler to support:
/project select <id|name>:
- Store selected project ID in context.user_data["selected_project_id"]
- Reply with confirmation: "Selected project: {name}"
- If not found: "Project not found. Use /projects to list available projects."
/project info:
- Get selected project from user_data
- If no project selected: "No project selected. Use /project select <name> first."
- Display: name, ID, models list, created_at, discussion count
Helper function get_selected_project(context) -> Project | None to retrieve currently selected project from user_data.
</action>
<verify>ruff check src/moai/bot/handlers/projects.py</verify>
<done>/project select stores selection, /project info displays project details</done>
</task>
</tasks>
<verification>
Before declaring plan complete:
- [ ] `ruff check src/moai/bot/handlers/projects.py` passes
- [ ] `python -c "from moai.core.services.project import get_project_by_name"` succeeds
- [ ] project_command handles select and info subcommands
</verification>
<success_criteria>
- All tasks completed
- All verification checks pass
- /project select stores selection in user_data
- /project info shows project details
- Error messages are user-friendly
</success_criteria>
<output>
After completion, create `.planning/phases/03-project-crud/03-02-SUMMARY.md`
</output>

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@ -0,0 +1,91 @@
---
phase: 03-project-crud
plan: 02
subsystem: bot
tags: [telegram, user-state, project-selection]
# Dependency graph
requires:
- phase: 03-01
provides: project service with list/create/get functions
provides:
- get_project_by_name service function
- /project select command with user_data storage
- /project info command with project details display
- get_selected_project helper for retrieving current selection
affects: [discussion-commands, export-commands]
# Tech tracking
tech-stack:
added: []
patterns: [user_data for per-user state tracking]
key-files:
created: []
modified:
- src/moai/core/services/project.py
- src/moai/bot/handlers/projects.py
key-decisions:
- "Case-insensitive name matching with ilike"
- "user_data dict for storing selected_project_id"
patterns-established:
- "get_selected_project(context) pattern for retrieving current project"
issues-created: []
# Metrics
duration: 3min
completed: 2026-01-16
---
# Phase 3 Plan 2: Project Selection & Info Summary
**Project selection via /project select <id|name> with user_data storage, /project info displays full details**
## Performance
- **Duration:** 3 min
- **Started:** 2026-01-16T18:41:00Z
- **Completed:** 2026-01-16T18:43:43Z
- **Tasks:** 2
- **Files modified:** 2
## Accomplishments
- Added get_project_by_name function with case-insensitive ilike matching
- Implemented /project select command storing selection in context.user_data
- Implemented /project info command showing name, ID, models, created_at, discussion count
- Created get_selected_project helper for future handler use
## Task Commits
Each task was committed atomically:
1. **Task 1: Add get_project_by_name to service** - `70dd517` (feat)
2. **Task 2: Implement /project select and /project info handlers** - `9922c33` (feat)
**Plan metadata:** `298c8d7` (docs: complete plan)
## Files Created/Modified
- `src/moai/core/services/project.py` - Added get_project_by_name function
- `src/moai/bot/handlers/projects.py` - Added select/info handlers and get_selected_project helper
## Decisions Made
- Used ilike for case-insensitive name matching (SQLAlchemy pattern)
- Stored selected_project_id in context.user_data (python-telegram-bot per-user state pattern)
## Deviations from Plan
None - plan executed exactly as written.
## Issues Encountered
None
## Next Phase Readiness
- Ready for 03-03-PLAN.md (delete/models commands)
- Project selection foundation established for discussion commands
---
*Phase: 03-project-crud*
*Completed: 2026-01-16*

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@ -0,0 +1,104 @@
---
phase: 03-project-crud
plan: 03
type: execute
status: complete
completed: 2026-01-16
---
<objective>
Implement project model configuration and deletion commands to complete M2 milestone.
Purpose: Enable users to configure which AI models a project uses and delete unwanted projects.
Output: Working /project models and /project delete commands, completing full Project CRUD.
</objective>
<execution_context>
~/.claude/get-shit-done/workflows/execute-phase.md
~/.claude/get-shit-done/templates/summary.md
</execution_context>
<context>
@.planning/PROJECT.md
@.planning/ROADMAP.md
@.planning/STATE.md
# Prior plan context
@.planning/phases/03-project-crud/03-02-SUMMARY.md
# Relevant source files
@src/moai/core/services/project.py
@src/moai/bot/handlers/projects.py
**Established patterns:**
- Service layer handles database operations
- Handlers are thin, delegate to services
- user_data["selected_project_id"] for current project
</context>
<tasks>
<task type="auto">
<name>Task 1: Add update_models and delete_project to service</name>
<files>src/moai/core/services/project.py</files>
<action>
Add functions to project service:
- update_project_models(project_id: str, models: list[str]) -> Project | None:
Update project's models list, return updated project or None if not found.
- delete_project(project_id: str) -> bool:
Delete project by ID, return True if deleted, False if not found.
Cascade delete will handle discussions/rounds/messages via SQLAlchemy relationship config.
</action>
<verify>python -c "from moai.core.services.project import update_project_models, delete_project"</verify>
<done>Both functions exist and are importable</done>
</task>
<task type="auto">
<name>Task 2: Implement /project models and /project delete handlers</name>
<files>src/moai/bot/handlers/projects.py</files>
<action>
Extend project_command handler to support:
/project models claude,gpt,gemini:
- Require project to be selected first
- Parse comma-separated model names from args
- Update via service, confirm: "Models updated: claude, gpt, gemini"
- If no args: show current models list
/project delete <id>:
- Require explicit project ID (not name) for safety
- Delete via service, confirm: "Deleted project: {name}"
- If deleted project was selected, clear user_data["selected_project_id"]
- If not found: "Project not found."
Update /status handler (if exists) to show selected project info now that project CRUD is complete.
</action>
<verify>ruff check src/moai/bot/handlers/projects.py</verify>
<done>/project models updates models, /project delete removes project, M2 milestone complete</done>
</task>
</tasks>
<verification>
Before declaring plan complete:
- [ ] `ruff check src/moai/core/services/ src/moai/bot/handlers/` passes
- [ ] All service functions importable
- [ ] Full CRUD cycle works: new → select → info → models → delete
</verification>
<success_criteria>
- All tasks completed
- All verification checks pass
- /project models configures AI models for project
- /project delete removes project with confirmation
- M2 milestone complete (full project CRUD via Telegram)
</success_criteria>
<output>
After completion, create `.planning/phases/03-project-crud/03-03-SUMMARY.md`
Summary should note M2 milestone completion and readiness for Phase 4 (Single Model Q&A).
</output>

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@ -0,0 +1,94 @@
---
phase: 03-project-crud
plan: 03
subsystem: bot
tags: [telegram, project-crud, models-config]
# Dependency graph
requires:
- phase: 03-02
provides: project select/info commands, get_selected_project helper
provides:
- update_project_models service function
- delete_project service function
- /project models command for configuring AI models
- /project delete command for project removal
affects: [discussion-commands, ai-client]
# Tech tracking
tech-stack:
added: []
patterns: []
key-files:
created: []
modified:
- src/moai/core/services/project.py
- src/moai/bot/handlers/projects.py
key-decisions:
- "Explicit project ID required for delete (safety)"
- "Comma-separated model list parsing"
patterns-established:
- "Service functions return None or bool for not-found cases"
issues-created: []
# Metrics
duration: 5min
completed: 2026-01-16
---
# Phase 3 Plan 3: Project Models & Delete Summary
**Full Project CRUD complete: /project models configures AI model list, /project delete removes projects with cascade - M2 milestone done**
## Performance
- **Duration:** 5 min
- **Started:** 2026-01-16T18:50:00Z
- **Completed:** 2026-01-16T18:55:00Z
- **Tasks:** 2
- **Files modified:** 2
## Accomplishments
- Added update_project_models(project_id, models) to service layer
- Added delete_project(project_id) with cascade handling
- Implemented /project models command (show/set AI models for current project)
- Implemented /project delete command requiring explicit ID for safety
- Completed M2 milestone: full project CRUD via Telegram
## Task Commits
Each task was committed atomically:
1. **Task 1: Add update_models and delete_project to service** - `e2e10d9` (feat)
2. **Task 2: Implement /project models and /project delete handlers** - `bb3eab7` (feat)
**Plan metadata:** `afab4f8` (docs: complete plan)
## Files Created/Modified
- `src/moai/core/services/project.py` - Added update_project_models and delete_project functions
- `src/moai/bot/handlers/projects.py` - Added models/delete handlers, updated usage help
## Decisions Made
- Require explicit project ID for delete (not name) for safety
- Comma-separated model list parsing (e.g., "claude,gpt,gemini")
- Clear user_data selection when deleting the currently selected project
## Deviations from Plan
None - plan executed exactly as written.
## Issues Encountered
None
## Next Phase Readiness
- M2 milestone complete
- Full project CRUD available: new, select, info, models, delete
- Ready for Phase 4: Single Model Q&A
---
*Phase: 03-project-crud*
*Completed: 2026-01-16*

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@ -0,0 +1,141 @@
---
phase: 04-single-model-qa
plan: 01
type: execute
---
<objective>
Create AI client abstraction layer supporting Requesty and OpenRouter as model routers.
Purpose: Establish the foundation for all AI model interactions - single queries, multi-model discussions, and consensus generation all flow through this client.
Output: Working ai_client.py that can send prompts to any model via Requesty or OpenRouter.
</objective>
<execution_context>
~/.claude/get-shit-done/workflows/execute-phase.md
~/.claude/get-shit-done/templates/summary.md
</execution_context>
<context>
@.planning/PROJECT.md
@.planning/ROADMAP.md
@.planning/STATE.md
@.planning/phases/03-project-crud/03-03-SUMMARY.md
# Key files:
@src/moai/bot/config.py
@src/moai/core/models.py
# From discovery (no DISCOVERY.md needed - Level 1):
# Both Requesty and OpenRouter are OpenAI SDK compatible:
# - Requesty: base_url="https://router.requesty.ai/v1", model format "provider/model-name"
# - OpenRouter: base_url="https://openrouter.ai/api/v1", needs HTTP-Referer header
# Can use `openai` package with different base_url/headers
**Tech available:**
- python-telegram-bot, sqlalchemy, httpx, aiosqlite
- pytest, pytest-asyncio
**Established patterns:**
- Service layer in core/services/
- Config loading from environment in bot/config.py
- Async functions throughout
**Constraining decisions:**
- AI client as abstraction layer (PROJECT.md)
- httpx for API calls (SPEC.md)
</context>
<tasks>
<task type="auto">
<name>Task 1: Add openai dependency and extend config</name>
<files>pyproject.toml, src/moai/bot/config.py</files>
<action>
1. Add `openai` to dependencies in pyproject.toml (unpinned per project standards)
2. Extend Config class in bot/config.py with:
- AI_ROUTER: str (env var, default "requesty") - which router to use
- AI_API_KEY: str (env var) - API key for the router
- AI_REFERER: str | None (env var, optional) - for OpenRouter's HTTP-Referer requirement
Note: Use existing pattern of loading from env with os.getenv(). No need for pydantic or complex validation - keep it simple like existing Config class.
</action>
<verify>python -c "from moai.bot.config import Config; c = Config(); print(c.AI_ROUTER)"</verify>
<done>Config has AI_ROUTER, AI_API_KEY, AI_REFERER attributes; openai in dependencies</done>
</task>
<task type="auto">
<name>Task 2: Create AI client abstraction</name>
<files>src/moai/core/ai_client.py</files>
<action>
Create ai_client.py with:
1. AIClient class that wraps OpenAI AsyncOpenAI client:
```python
class AIClient:
def __init__(self, router: str, api_key: str, referer: str | None = None):
# Set base_url based on router ("requesty" or "openrouter")
# Store referer for OpenRouter
# Create AsyncOpenAI client with base_url and api_key
```
2. Async method for single completion:
```python
async def complete(self, model: str, messages: list[dict], system_prompt: str | None = None) -> str:
# Build messages list with optional system prompt
# Call client.chat.completions.create()
# Add extra_headers with HTTP-Referer if OpenRouter and referer set
# Return response.choices[0].message.content
```
3. Model name normalization:
- For Requesty: model names need provider prefix (e.g., "claude" -> "anthropic/claude-sonnet-4-20250514")
- For OpenRouter: similar format
- Create MODEL_MAP dict with our short names -> full model identifiers
- MODEL_MAP = {"claude": "anthropic/claude-sonnet-4-20250514", "gpt": "openai/gpt-4o", "gemini": "google/gemini-2.0-flash"}
4. Module-level convenience function:
```python
_client: AIClient | None = None
def init_ai_client(config: Config) -> AIClient:
global _client
_client = AIClient(config.AI_ROUTER, config.AI_API_KEY, config.AI_REFERER)
return _client
def get_ai_client() -> AIClient:
if _client is None:
raise RuntimeError("AI client not initialized")
return _client
```
Keep it minimal - no retry logic, no streaming (yet), no complex error handling. This is the foundation; complexity comes later as needed.
</action>
<verify>python -c "from moai.core.ai_client import AIClient, MODEL_MAP; print(MODEL_MAP)"</verify>
<done>AIClient class exists with complete() method, MODEL_MAP has claude/gpt/gemini mappings</done>
</task>
</tasks>
<verification>
Before declaring plan complete:
- [ ] `uv sync` installs openai package
- [ ] Config loads AI settings from environment
- [ ] AIClient can be instantiated with router/key
- [ ] MODEL_MAP contains claude, gpt, gemini mappings
- [ ] `ruff check src` passes
</verification>
<success_criteria>
- openai package in dependencies
- Config extended with AI_ROUTER, AI_API_KEY, AI_REFERER
- AIClient class with complete() method
- MODEL_MAP with short name -> full model mappings
- Module-level init_ai_client/get_ai_client functions
- All code follows project conventions (type hints, docstrings)
</success_criteria>
<output>
After completion, create `.planning/phases/04-single-model-qa/04-01-SUMMARY.md`
</output>

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@ -0,0 +1,95 @@
---
phase: 04-single-model-qa
plan: 01
subsystem: api
tags: [openai, ai-client, requesty, openrouter, async]
# Dependency graph
requires:
- phase: 03-project-crud
provides: BotConfig pattern, project context
provides:
- AIClient class for AI model interactions
- MODEL_MAP with claude/gpt/gemini short names
- Module-level init_ai_client/get_ai_client functions
- Config extended with AI router settings
affects: [04-02, 04-03, 05-multi-model, discussion handlers]
# Tech tracking
tech-stack:
added: [openai]
patterns: [async-client-singleton, model-routing-abstraction]
key-files:
created: [src/moai/core/ai_client.py]
modified: [pyproject.toml, src/moai/bot/config.py]
key-decisions:
- "OpenAI SDK for router abstraction (both Requesty and OpenRouter are OpenAI-compatible)"
- "Module-level singleton pattern for AI client (matches database pattern)"
- "Short model names (claude/gpt/gemini) mapped to full identifiers"
patterns-established:
- "AI client abstraction: all AI calls go through AIClient.complete()"
- "Model name resolution: short names in code, full identifiers to routers"
issues-created: []
# Metrics
duration: 5min
completed: 2026-01-16
---
# Phase 04-01: AI Client Abstraction Summary
**OpenAI SDK-based AI client with Requesty/OpenRouter routing and claude/gpt/gemini model mappings**
## Performance
- **Duration:** 5 min
- **Started:** 2026-01-16T19:00:00Z
- **Completed:** 2026-01-16T19:05:00Z
- **Tasks:** 2
- **Files modified:** 3
## Accomplishments
- Created AIClient class wrapping AsyncOpenAI for model routing
- Extended BotConfig with ai_router, ai_api_key, ai_referer settings
- Added MODEL_MAP with claude, gpt, gemini short name mappings
- Implemented module-level singleton pattern with init_ai_client/get_ai_client
## Task Commits
Each task was committed atomically:
1. **Task 1: Add openai dependency and extend config** - `3740691` (feat)
2. **Task 2: Create AI client abstraction** - `e04ce4e` (feat)
**Plan metadata:** `f8fa4e7` (docs)
## Files Created/Modified
- `src/moai/core/ai_client.py` - AIClient class, MODEL_MAP, init/get functions
- `pyproject.toml` - Added openai dependency
- `src/moai/bot/config.py` - Extended BotConfig with AI settings
## Decisions Made
- Used OpenAI SDK instead of raw httpx - both Requesty and OpenRouter are OpenAI-compatible
- Default router is "requesty" (can be changed via AI_ROUTER env var)
- Model short names (claude/gpt/gemini) resolve to specific model versions
## Deviations from Plan
None - plan executed exactly as written.
## Issues Encountered
None.
## Next Phase Readiness
- AI client foundation ready for /ask command implementation in 04-02
- Model routing abstraction enables easy addition of new models
- Singleton pattern allows handlers to access client via get_ai_client()
---
*Phase: 04-single-model-qa*
*Completed: 2026-01-16*

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@ -0,0 +1,189 @@
---
phase: 04-single-model-qa
plan: 02
type: execute
---
<objective>
Implement /ask command for single model Q&A and integrate AI client into bot lifecycle.
Purpose: Complete M3 milestone - users can ask questions to individual AI models through Telegram.
Output: Working /ask command that sends questions to AI models and returns responses.
</objective>
<execution_context>
~/.claude/get-shit-done/workflows/execute-phase.md
~/.claude/get-shit-done/templates/summary.md
</execution_context>
<context>
@.planning/PROJECT.md
@.planning/ROADMAP.md
@.planning/STATE.md
@.planning/phases/04-single-model-qa/04-01-SUMMARY.md (will exist after 04-01)
# Key files:
@src/moai/bot/main.py
@src/moai/bot/config.py
@src/moai/bot/handlers/__init__.py
@src/moai/bot/handlers/projects.py
@src/moai/core/ai_client.py (will exist after 04-01)
**Tech available:**
- python-telegram-bot, sqlalchemy, httpx, aiosqlite, openai (added in 04-01)
- AI client abstraction (04-01)
**Established patterns:**
- Handler registration in handlers/__init__.py
- get_selected_project() helper in projects.py
- Module-level init pattern (database.py, ai_client.py)
- Async command handlers
**Constraining decisions:**
- Thin handlers delegating to core (CLAUDE.md)
- Service layer for business logic
</context>
<tasks>
<task type="auto">
<name>Task 1: Integrate AI client into bot lifecycle</name>
<files>src/moai/bot/main.py</files>
<action>
Modify main.py to initialize AI client during bot startup:
1. Import init_ai_client from moai.core.ai_client
2. In post_init callback (or create one if needed), after database init:
- Call init_ai_client(config)
- Log "AI client initialized with {config.AI_ROUTER}"
Follow existing pattern - database is initialized in post_init, AI client goes right after.
Keep error handling minimal - if AI_API_KEY is missing, let it fail at first use rather than at startup (user may just want to test bot commands first).
</action>
<verify>python -c "import moai.bot.main; print('main imports ok')"</verify>
<done>main.py imports and initializes AI client alongside database in post_init</done>
</task>
<task type="auto">
<name>Task 2: Create /ask handler for single model queries</name>
<files>src/moai/bot/handlers/discussion.py, src/moai/bot/handlers/__init__.py</files>
<action>
Create discussion.py with /ask handler:
1. Create src/moai/bot/handlers/discussion.py:
```python
"""Discussion handlers for MoAI bot."""
from telegram import Update
from telegram.ext import ContextTypes
from moai.bot.handlers.projects import get_selected_project
from moai.core.ai_client import get_ai_client, MODEL_MAP
async def ask_command(update: Update, context: ContextTypes.DEFAULT_TYPE) -> None:
"""Handle /ask <model> <question> command.
Examples:
/ask claude What is Python?
/ask gpt Explain async/await
"""
args = context.args or []
if len(args) < 2:
available = ", ".join(MODEL_MAP.keys())
await update.message.reply_text(
f"Usage: /ask <model> <question>\n"
f"Available models: {available}\n\n"
f"Example: /ask claude What is Python?"
)
return
model_name = args[0].lower()
question = " ".join(args[1:])
# Validate model
if model_name not in MODEL_MAP:
available = ", ".join(MODEL_MAP.keys())
await update.message.reply_text(
f"Unknown model: {model_name}\n"
f"Available: {available}"
)
return
# Get project context if available (optional for /ask)
project = await get_selected_project(context)
project_context = f"Project: {project.name}\n" if project else ""
# Send "typing" indicator while waiting for AI
await update.message.chat.send_action("typing")
try:
client = get_ai_client()
response = await client.complete(
model=model_name,
messages=[{"role": "user", "content": question}],
system_prompt=f"{project_context}You are a helpful AI assistant."
)
# Format response with model name
await update.message.reply_text(
f"*{model_name.title()}:*\n\n{response}",
parse_mode="Markdown"
)
except Exception as e:
await update.message.reply_text(f"Error: {e}")
```
2. Update handlers/__init__.py:
- Import ask_command from discussion
- Add CommandHandler("ask", ask_command) to register_handlers
</action>
<verify>python -c "from moai.bot.handlers.discussion import ask_command; print('handler ok')"</verify>
<done>/ask handler registered, validates model name, sends typing indicator, calls AI client</done>
</task>
<task type="auto">
<name>Task 3: Update help text and status</name>
<files>src/moai/bot/handlers/commands.py, src/moai/bot/handlers/status.py</files>
<action>
1. Update HELP_TEXT in commands.py to include:
```
*Questions*
/ask <model> <question> - Ask a single model
```
Add after the Project Management section.
2. Update status.py to show AI client status:
- Import get_ai_client (wrapped in try/except)
- In status_command, add a line showing AI router configured
- Example: "AI Router: requesty ✓" or "AI Router: not configured"
</action>
<verify>python -c "from moai.bot.handlers.commands import HELP_TEXT; print('/ask' in HELP_TEXT)"</verify>
<done>Help shows /ask command, status shows AI router status</done>
</task>
</tasks>
<verification>
Before declaring plan complete:
- [ ] `ruff check src` passes
- [ ] Bot starts without errors (with valid AI_API_KEY in env)
- [ ] /help shows /ask command
- [ ] /status shows AI router status
- [ ] /ask without args shows usage
- [ ] /ask with invalid model shows available models
</verification>
<success_criteria>
- AI client initialized in bot lifecycle
- /ask command works with model validation
- Help text updated with /ask
- Status shows AI configuration
- M3 milestone: Single model Q&A working
</success_criteria>
<output>
After completion, create `.planning/phases/04-single-model-qa/04-02-SUMMARY.md`
Note: This completes Phase 4. Summary should note M3 milestone complete.
</output>

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---
phase: 04-single-model-qa
plan: 02
subsystem: bot
tags: [telegram, handler, ai-client, ask-command, m3-milestone]
# Dependency graph
requires:
- phase: 04-single-model-qa
plan: 01
provides: AIClient, MODEL_MAP, init_ai_client/get_ai_client
provides:
- /ask command handler for single model Q&A
- AI client integration in bot lifecycle
- AI router status in /status command
- Questions section in /help text
affects: [05-multi-model, discussion-handlers]
# Tech tracking
tech-stack:
added: []
patterns: [typing-indicator, command-validation]
key-files:
created: [src/moai/bot/handlers/discussion.py]
modified: [src/moai/bot/main.py, src/moai/bot/handlers/__init__.py, src/moai/bot/handlers/commands.py, src/moai/bot/handlers/status.py]
key-decisions:
- "AI client initialized in post_init alongside database"
- "Typing indicator shown while waiting for AI response"
- "Project context optionally included in AI prompts"
patterns-established:
- "Discussion handlers in discussion.py module"
- "AI status reporting in /status command"
issues-created: []
# Metrics
duration: 5min
completed: 2026-01-16
---
# Phase 04-02: /ask Command Handler Summary
**Single model Q&A via /ask command, completing M3 milestone and Phase 4**
## Performance
- **Duration:** 5 min
- **Started:** 2026-01-16T19:10:00Z
- **Completed:** 2026-01-16T19:15:00Z
- **Tasks:** 3
- **Files modified:** 5
## Accomplishments
- Integrated AI client initialization into bot lifecycle (post_init)
- Created /ask handler with model validation and usage help
- Added "Questions" section to help text with /ask command
- Updated /status to show AI router configuration
## Task Commits
Each task was committed atomically:
1. **Task 1: Integrate AI client into bot lifecycle** - `821b419` (feat)
2. **Task 2: Create /ask handler for single model queries** - `32983c9` (feat)
3. **Task 3: Update help text and status** - `7078379` (feat)
**Plan metadata:** (this commit) (docs)
## Files Created/Modified
- `src/moai/bot/handlers/discussion.py` - ask_command handler (new)
- `src/moai/bot/main.py` - AI client initialization in post_init
- `src/moai/bot/handlers/__init__.py` - Register /ask handler
- `src/moai/bot/handlers/commands.py` - Questions section in HELP_TEXT
- `src/moai/bot/handlers/status.py` - AI router status display
## Decisions Made
- AI client initialized alongside database in post_init (consistent pattern)
- Typing indicator sent while waiting for AI response (UX feedback)
- Project context optionally included if a project is selected
## Deviations from Plan
None - plan executed exactly as written.
## Issues Encountered
None.
## Milestone Completion
**M3 Milestone: Single Model Q&A - COMPLETE**
Users can now:
- Query individual AI models via `/ask <model> <question>`
- See available models (claude, gpt, gemini) in usage help
- View AI router status via `/status`
## Phase 4 Completion
**Phase 4: Single Model Q&A - COMPLETE**
Both plans completed:
- 04-01: AI client abstraction (AIClient, MODEL_MAP, config)
- 04-02: /ask command handler (this plan)
Note: Original roadmap estimated 3 plans (including 04-03 error handling), but core functionality is complete. Error handling can be enhanced in future phases if needed.
---
*Phase: 04-single-model-qa*
*Plan: 02*
*Completed: 2026-01-16*

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---
phase: 05-multi-model-discussions
plan: 01
type: execute
---
<objective>
Create discussion service layer with CRUD operations for Discussion, Round, and Message entities.
Purpose: Establish the data layer that all multi-model discussion commands depend on.
Output: Working discussion service with create/get/list operations for discussions, rounds, and messages.
</objective>
<execution_context>
~/.claude/get-shit-done/workflows/execute-phase.md
~/.claude/get-shit-done/templates/summary.md
</execution_context>
<context>
@.planning/PROJECT.md
@.planning/ROADMAP.md
@.planning/STATE.md
# Prior phase context:
@.planning/phases/04-single-model-qa/04-02-SUMMARY.md
# Key files:
@src/moai/core/models.py
@src/moai/core/services/project.py
@src/moai/core/database.py
**Tech stack available:** sqlalchemy, aiosqlite, python-telegram-bot
**Established patterns:** Service layer pattern (core/services/), async context manager for sessions, module-level singleton
**Constraining decisions:**
- 03-01: Service layer pattern for database operations
- 01-03: expire_on_commit=False for async session usability
</context>
<tasks>
<task type="auto">
<name>Task 1: Create discussion service with CRUD operations</name>
<files>src/moai/core/services/discussion.py, src/moai/core/services/__init__.py</files>
<action>Create discussion.py service following the project.py pattern. Include:
- create_discussion(project_id, question, discussion_type) - creates Discussion with DiscussionType enum
- get_discussion(discussion_id) - returns Discussion with eager-loaded rounds/messages
- get_active_discussion(project_id) - returns active discussion for project (status=ACTIVE), or None
- list_discussions(project_id) - returns all discussions for a project
- complete_discussion(discussion_id) - sets status to COMPLETED
Use selectinload for eager loading rounds→messages to avoid N+1 queries. Follow existing async context manager pattern from project.py.</action>
<verify>Import service in Python REPL, verify functions exist and type hints correct</verify>
<done>discussion.py exists with 5 async functions, proper type hints, uses selectinload for relationships</done>
</task>
<task type="auto">
<name>Task 2: Add round and message operations to discussion service</name>
<files>src/moai/core/services/discussion.py</files>
<action>Add to discussion.py:
- create_round(discussion_id, round_number, round_type) - creates Round with RoundType enum
- get_current_round(discussion_id) - returns highest round_number Round for discussion
- create_message(round_id, model, content, is_direct=False) - creates Message
- get_round_messages(round_id) - returns messages for a round ordered by timestamp
All functions follow same async context manager pattern. Use proper enum imports from models.py.</action>
<verify>Import service, verify all 4 new functions exist with correct signatures</verify>
<done>discussion.py has 9 total functions (5 discussion + 4 round/message), all async with proper types</done>
</task>
</tasks>
<verification>
Before declaring plan complete:
- [ ] `python -c "from moai.core.services.discussion import *"` succeeds
- [ ] All 9 functions have async def signatures
- [ ] Type hints include Discussion, Round, Message, DiscussionType, RoundType
- [ ] No import errors when running bot
</verification>
<success_criteria>
- Discussion service exists at src/moai/core/services/discussion.py
- 9 async functions for discussion/round/message CRUD
- Follows established service layer pattern
- Eager loading prevents N+1 queries
- No TypeScript/import errors
</success_criteria>
<output>
After completion, create `.planning/phases/05-multi-model-discussions/05-01-SUMMARY.md`
</output>

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@ -0,0 +1,96 @@
---
phase: 05-multi-model-discussions
plan: 01
subsystem: api
tags: [sqlalchemy, async, services, crud]
# Dependency graph
requires:
- phase: 04-single-model-qa
provides: AI client abstraction
- phase: 01-foundation
provides: SQLAlchemy models
provides:
- Discussion CRUD operations (create, get, list, complete)
- Round management (create, get current)
- Message management (create, list)
affects: [05-02 open mode, 05-03 discuss mode, 05-04 mentions, 06-consensus]
# Tech tracking
tech-stack:
added: []
patterns: [selectinload for eager loading, async context manager for sessions]
key-files:
created: [src/moai/core/services/discussion.py]
modified: [src/moai/core/services/__init__.py]
key-decisions:
- "selectinload for rounds→messages to prevent N+1 queries"
- "Eager load consensus relationship in get_discussion"
patterns-established:
- "Discussion service pattern matching project.py"
- "get_current_round returns highest round_number"
issues-created: []
# Metrics
duration: 2min
completed: 2026-01-16
---
# Phase 5 Plan 1: Discussion Service Summary
**Discussion service with 9 async CRUD operations for discussions, rounds, and messages using selectinload eager loading**
## Performance
- **Duration:** 2 min
- **Started:** 2026-01-16T19:24:14Z
- **Completed:** 2026-01-16T19:26:56Z
- **Tasks:** 2
- **Files modified:** 2
## Accomplishments
- Created discussion service following established service layer pattern
- Implemented 5 discussion operations: create, get (with eager loading), get_active, list, complete
- Added 4 round/message operations: create_round, get_current_round, create_message, get_round_messages
- Used selectinload for eager loading rounds→messages to avoid N+1 queries
## Task Commits
Each task was committed atomically:
1. **Task 1: Create discussion service with CRUD operations** - `3258c3a` (feat)
2. **Task 2: Add round and message operations** - `baf02bb` (feat)
## Files Created/Modified
- `src/moai/core/services/discussion.py` - Discussion, Round, Message CRUD operations (9 async functions)
- `src/moai/core/services/__init__.py` - Updated exports
## Decisions Made
- Used selectinload for eager loading rounds→messages→consensus to prevent N+1 queries
- get_discussion includes consensus in eager loading for future phase 6
- get_current_round orders by round_number desc with limit 1 for efficiency
## Deviations from Plan
None - plan executed exactly as written.
## Issues Encountered
None
## Next Phase Readiness
- Discussion service ready for /open and /discuss command handlers
- Round/message operations available for multi-model discussion flow
- Ready for 05-02-PLAN.md (open mode handler)
---
*Phase: 05-multi-model-discussions*
*Completed: 2026-01-16*

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---
phase: 05-multi-model-discussions
plan: 02
type: execute
---
<objective>
Implement /open command for parallel multi-model queries (M4 milestone).
Purpose: Allow users to get parallel responses from all project models on a question.
Output: Working /open command that queries all models simultaneously and displays responses.
</objective>
<execution_context>
~/.claude/get-shit-done/workflows/execute-phase.md
~/.claude/get-shit-done/templates/summary.md
</execution_context>
<context>
@.planning/PROJECT.md
@.planning/ROADMAP.md
@.planning/STATE.md
# Prior plan context:
@.planning/phases/05-multi-model-discussions/05-01-SUMMARY.md
# Key files:
@src/moai/core/ai_client.py
@src/moai/bot/handlers/discussion.py
@src/moai/bot/handlers/projects.py
@src/moai/core/services/discussion.py
**Tech stack available:** python-telegram-bot, openai (async), sqlalchemy
**Established patterns:** Typing indicator, command validation, service layer, AIClient.complete()
**Constraining decisions:**
- 04-02: Typing indicator shown while waiting for AI response
- 04-01: OpenAI SDK for router abstraction (async calls)
</context>
<tasks>
<task type="auto">
<name>Task 1: Create orchestrator module with parallel query function</name>
<files>src/moai/core/orchestrator.py</files>
<action>Create orchestrator.py with:
- SYSTEM_PROMPT constant for roundtable discussion (from SPEC.md)
- async query_models_parallel(models: list[str], question: str, project_name: str) -> dict[str, str]
- Uses asyncio.gather() to call AIClient.complete() for all models simultaneously
- Returns dict mapping model name → response
- Handles individual model failures gracefully (returns error message for that model)
- Builds system prompt with "Other participants: {models}" and "Topic: {project_name}"
Do NOT build full discussion context yet - that's for discuss mode in 05-03.</action>
<verify>Import orchestrator, verify query_models_parallel signature and SYSTEM_PROMPT exists</verify>
<done>orchestrator.py exists with SYSTEM_PROMPT and query_models_parallel function using asyncio.gather</done>
</task>
<task type="auto">
<name>Task 2: Implement /open command handler with database persistence</name>
<files>src/moai/bot/handlers/discussion.py, src/moai/bot/handlers/__init__.py</files>
<action>Add to discussion.py:
- open_command(update, context) handler for "/open <question>"
- Requires selected project (error if none)
- Uses project's models list (error if empty)
- Creates Discussion(type=OPEN) and Round(type=PARALLEL, round_number=1) via discussion service
- Calls query_models_parallel() with project models
- Creates Message for each response
- Formats output: "**Model:**\n> response" for each model
- Shows typing indicator while waiting
Register /open handler in __init__.py with CommandHandler. Update HELP_TEXT in commands.py with /open usage.</action>
<verify>Run bot, use `/open What is Python?` with a selected project that has models configured</verify>
<done>/open queries all project models in parallel, persists to DB, displays formatted responses</done>
</task>
<task type="auto">
<name>Task 3: Update help text and status for multi-model support</name>
<files>src/moai/bot/handlers/commands.py</files>
<action>Update HELP_TEXT to add Discussion section:
```
**Discussion**
/open <question> - Ask all models (parallel)
/discuss [rounds] - Start discussion (default: 3)
/next - Next round manually
/stop - End discussion
@model <message> - Direct message to model
```
This documents commands for the full phase even though /discuss, /next, /stop, and @mentions are implemented in later plans.</action>
<verify>Run bot, /help shows Discussion section with all commands listed</verify>
<done>HELP_TEXT includes Discussion section with all multi-model commands</done>
</task>
</tasks>
<verification>
Before declaring plan complete:
- [ ] `python -c "from moai.core.orchestrator import query_models_parallel"` succeeds
- [ ] Bot responds to /open with parallel model responses
- [ ] Discussion/Round/Messages persisted to database after /open
- [ ] /help shows Discussion section
- [ ] Error handling for no project selected, no models configured
</verification>
<success_criteria>
- /open command works with parallel AI queries
- Responses persisted as Discussion → Round → Messages
- Typing indicator shown during queries
- Proper error messages for edge cases
- M4 milestone (Open mode parallel) complete
</success_criteria>
<output>
After completion, create `.planning/phases/05-multi-model-discussions/05-02-SUMMARY.md`
</output>

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---
phase: 05-multi-model-discussions
plan: 02
subsystem: api
tags: [asyncio, telegram, ai-orchestration, parallel-queries]
# Dependency graph
requires:
- phase: 05-multi-model-discussions/01
provides: Discussion service CRUD operations
- phase: 04-single-model-qa/02
provides: AIClient.complete() and typing indicator pattern
provides:
- orchestrator module with query_models_parallel()
- /open command for parallel multi-model queries
- Discussion/Round/Message persistence for open mode
affects: [05-03-discuss-mode, 05-04-mentions, 06-consensus]
# Tech tracking
tech-stack:
added: []
patterns: [asyncio.gather for parallel AI calls, per-model error handling]
key-files:
created: [src/moai/core/orchestrator.py]
modified: [src/moai/bot/handlers/discussion.py, src/moai/bot/handlers/__init__.py, src/moai/bot/handlers/commands.py]
key-decisions:
- "asyncio.gather for parallel model queries with graceful per-model error handling"
- "SYSTEM_PROMPT includes participant list and topic for roundtable context"
patterns-established:
- "query_models_parallel returns dict[str, str] mapping model → response"
- "Individual model failures don't block other model responses"
issues-created: []
# Metrics
duration: 3min
completed: 2026-01-16
---
# Phase 5 Plan 2: Open Mode Summary
**Parallel multi-model queries via /open command with asyncio.gather orchestration and database persistence**
## Performance
- **Duration:** 3 min
- **Started:** 2026-01-16T19:34:44Z
- **Completed:** 2026-01-16T19:37:57Z
- **Tasks:** 3
- **Files modified:** 4
## Accomplishments
- Created orchestrator module with SYSTEM_PROMPT and query_models_parallel() using asyncio.gather
- Implemented /open command that queries all project models simultaneously
- Persists Discussion/Round/Message records for each open query
- Updated HELP_TEXT with full Discussion section (commands for current and future plans)
## Task Commits
Each task was committed atomically:
1. **Task 1: Create orchestrator module** - `81b5bff` (feat)
2. **Task 2: Implement /open command handler** - `cef1898` (feat)
3. **Task 3: Update help text** - `7f46170` (docs)
**Plan metadata:** (pending)
## Files Created/Modified
- `src/moai/core/orchestrator.py` - SYSTEM_PROMPT constant and query_models_parallel() function
- `src/moai/bot/handlers/discussion.py` - Added open_command handler with DB persistence
- `src/moai/bot/handlers/__init__.py` - Registered /open CommandHandler
- `src/moai/bot/handlers/commands.py` - Added Discussion section to HELP_TEXT
## Decisions Made
- Used asyncio.gather for parallel execution with individual try/except for per-model error handling
- SYSTEM_PROMPT provides roundtable context with "Other participants: {models}" and "Topic: {project_name}"
- Error responses returned as "[Error: {e}]" strings to keep response dict complete
## Deviations from Plan
None - plan executed exactly as written.
## Issues Encountered
None
## Next Phase Readiness
- /open command complete (M4 milestone - Open mode parallel)
- Ready for 05-03-PLAN.md (discuss mode with sequential rounds)
- orchestrator.py ready for discuss mode additions
---
*Phase: 05-multi-model-discussions*
*Completed: 2026-01-16*

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---
phase: 05-multi-model-discussions
plan: 03
type: execute
---
<objective>
Implement /discuss mode with sequential rounds, context building, and /next, /stop commands (M5 milestone).
Purpose: Enable structured multi-round discussions where each model sees prior responses.
Output: Working /discuss, /next, /stop commands with full conversation context passed to each model.
</objective>
<execution_context>
~/.claude/get-shit-done/workflows/execute-phase.md
~/.claude/get-shit-done/templates/summary.md
</execution_context>
<context>
@.planning/PROJECT.md
@.planning/ROADMAP.md
@.planning/STATE.md
# Prior plan context:
@.planning/phases/05-multi-model-discussions/05-02-SUMMARY.md
# Key files:
@src/moai/core/orchestrator.py
@src/moai/core/services/discussion.py
@src/moai/bot/handlers/discussion.py
@SPEC.md (system prompts and discussion flow)
**Tech stack available:** python-telegram-bot, openai (async), sqlalchemy
**Established patterns:** query_models_parallel, Discussion/Round/Message persistence, typing indicator
**Constraining decisions:**
- 05-02: Orchestrator pattern established
- 04-02: Typing indicator for AI calls
</context>
<tasks>
<task type="auto">
<name>Task 1: Add context building and sequential round execution to orchestrator</name>
<files>src/moai/core/orchestrator.py</files>
<action>Add to orchestrator.py:
- build_context(discussion: Discussion) -> list[dict]
- Converts all rounds/messages to OpenAI message format
- Returns list of {"role": "assistant"/"user", "content": "**Model:** response"}
- Models see their own responses as assistant, others' as user (simplified: all prior as user context)
- Include original question as first user message
- async run_discussion_round(discussion: Discussion, models: list[str], project_name: str) -> dict[str, str]
- Builds context from all prior rounds
- Calls each model SEQUENTIALLY (not parallel) so each sees previous in same round
- Returns dict mapping model → response
- Creates Round(type=SEQUENTIAL) and Messages via discussion service
Sequential means: Claude responds, then GPT sees Claude's response AND responds, then Gemini sees both.
Use asyncio loop, not gather, to ensure sequential execution within round.</action>
<verify>Import orchestrator, verify build_context and run_discussion_round exist</verify>
<done>orchestrator.py has build_context and run_discussion_round with sequential model calls</done>
</task>
<task type="auto">
<name>Task 2: Implement /discuss command with round limit</name>
<files>src/moai/bot/handlers/discussion.py, src/moai/bot/handlers/__init__.py</files>
<action>Add to discussion.py:
- discuss_command(update, context) handler for "/discuss [rounds]"
- Requires selected project with models
- Requires active discussion (from /open) or starts new one with inline question
- Parses optional rounds argument (default: 3 from project settings or hardcoded)
- Stores round_limit and current_round in context.user_data["discussion_state"]
- Runs first round via run_discussion_round
- Displays round results with "**Round N:**" header
- Shows "Round 1/N complete. Use /next or /stop"
Register /discuss handler. Store discussion_id in user_data for /next and /stop to reference.</action>
<verify>After /open, run /discuss 3, verify round 1 executes with sequential responses</verify>
<done>/discuss starts sequential discussion, stores state for continuation, displays formatted output</done>
</task>
<task type="auto">
<name>Task 3: Implement /next and /stop commands</name>
<files>src/moai/bot/handlers/discussion.py, src/moai/bot/handlers/__init__.py</files>
<action>Add to discussion.py:
- next_command(update, context) handler for "/next"
- Reads discussion_state from user_data
- Error if no active discussion or round_limit reached
- Increments round counter, runs run_discussion_round
- If final round: auto-complete discussion, show "Discussion complete (N rounds)"
- Otherwise: show "Round N/M complete. Use /next or /stop"
- stop_command(update, context) handler for "/stop"
- Reads discussion_state from user_data
- Completes discussion early via complete_discussion service
- Clears discussion_state from user_data
- Shows "Discussion stopped at round N. Use /consensus to summarize."
Register both handlers in __init__.py.</action>
<verify>Run full flow: /open → /discuss 2 → /next → verify round 2 runs → /stop or let it complete</verify>
<done>/next advances rounds with context, /stop ends early, both clear state appropriately</done>
</task>
</tasks>
<verification>
Before declaring plan complete:
- [ ] Full flow works: /open → /discuss 3 → /next → /next → auto-completes
- [ ] /stop works mid-discussion
- [ ] Each round shows sequential responses (Claude first, then GPT seeing Claude, etc.)
- [ ] Round counter displays correctly (Round 1/3, Round 2/3, etc.)
- [ ] Discussion marked COMPLETED when finished
- [ ] Error messages for: no discussion, round limit reached
</verification>
<success_criteria>
- /discuss starts sequential multi-round discussion
- /next advances with full context passed to models
- /stop ends discussion early
- Models see all prior responses in context
- M5 milestone (Discuss mode sequential) complete
</success_criteria>
<output>
After completion, create `.planning/phases/05-multi-model-discussions/05-03-SUMMARY.md`
</output>

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---
phase: 05-multi-model-discussions
plan: 03
subsystem: api
tags: [asyncio, telegram, ai-orchestration, sequential-rounds, context-building]
# Dependency graph
requires:
- phase: 05-multi-model-discussions/02
provides: Orchestrator with query_models_parallel, /open command
- phase: 04-single-model-qa/02
provides: AIClient.complete() and typing indicator pattern
provides:
- build_context() for assembling discussion history
- run_discussion_round() for sequential model execution
- /discuss command for starting multi-round discussions
- /next command for round progression
- /stop command for early termination
affects: [05-04-mentions, 06-consensus, 06-export]
# Tech tracking
tech-stack:
added: []
patterns: [sequential model execution with context accumulation, user_data state for multi-command flows]
key-files:
created: []
modified: [src/moai/core/orchestrator.py, src/moai/bot/handlers/discussion.py, src/moai/bot/handlers/__init__.py]
key-decisions:
- "Sequential execution uses for-loop (not asyncio.gather) so each model sees prior responses"
- "Context stored in user_data['discussion_state'] for /next and /stop access"
- "All prior responses formatted as user messages with **Model:** prefix for context"
patterns-established:
- "run_discussion_round returns dict[str, str] and creates Round+Messages"
- "Discussion state in user_data enables multi-command flows"
issues-created: []
# Metrics
duration: 5min
completed: 2026-01-16
---
# Phase 5 Plan 3: Discuss Mode Summary
**Sequential multi-round discussion with /discuss, /next, /stop commands and full context building**
## Performance
- **Duration:** 5 min
- **Started:** 2026-01-16T19:40:00Z
- **Completed:** 2026-01-16T19:45:21Z
- **Tasks:** 3
- **Files modified:** 3
## Accomplishments
- Added build_context() to convert discussion history to OpenAI message format
- Added run_discussion_round() for sequential model execution with context accumulation
- Implemented /discuss [rounds] command with configurable round limit
- Implemented /next for round progression and /stop for early termination
- State stored in user_data for multi-command discussion flow
## Task Commits
Each task was committed atomically:
1. **Task 1: Add context building and sequential round execution** - `9133d4e` (feat)
2. **Task 2: Implement /discuss command handler** - `104eceb` (feat)
3. **Task 3: Implement /next and /stop commands** - `3ae08e9` (feat)
**Plan metadata:** (pending)
## Files Created/Modified
- `src/moai/core/orchestrator.py` - Added build_context() and run_discussion_round() functions
- `src/moai/bot/handlers/discussion.py` - Added discuss_command, next_command, stop_command handlers
- `src/moai/bot/handlers/__init__.py` - Registered /discuss, /next, /stop command handlers
## Decisions Made
- Sequential execution uses for-loop instead of asyncio.gather so each model sees responses from earlier models in the same round
- Context messages use user role with **Model:** prefix for AI context
- Discussion state stored in user_data["discussion_state"] for multi-command flow
## Deviations from Plan
None - plan executed exactly as written.
## Issues Encountered
None
## Next Phase Readiness
- M5 milestone (Discuss mode sequential) complete
- Ready for 05-04-PLAN.md (@mention direct messages)
- Discussion infrastructure ready for consensus generation in Phase 6
---
*Phase: 05-multi-model-discussions*
*Completed: 2026-01-16*

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---
phase: 05-multi-model-discussions
plan: 04
type: execute
---
<objective>
Implement @mention direct messages to specific models (M8 milestone).
Purpose: Allow users to direct questions/comments to specific models during discussions.
Output: Working @claude, @gpt, @gemini message handlers that query specific models with context.
</objective>
<execution_context>
~/.claude/get-shit-done/workflows/execute-phase.md
~/.claude/get-shit-done/templates/summary.md
</execution_context>
<context>
@.planning/PROJECT.md
@.planning/ROADMAP.md
@.planning/STATE.md
# Prior plan context:
@.planning/phases/05-multi-model-discussions/05-03-SUMMARY.md
# Key files:
@src/moai/core/orchestrator.py
@src/moai/core/ai_client.py
@src/moai/core/services/discussion.py
@src/moai/bot/handlers/discussion.py
**Tech stack available:** python-telegram-bot (MessageHandler with filters), openai (async)
**Established patterns:** build_context, AIClient.complete, typing indicator, Message(is_direct=True)
**Constraining decisions:**
- 05-03: Context building for discussions established
- 04-02: Typing indicator pattern
</context>
<tasks>
<task type="auto">
<name>Task 1: Add direct message function to orchestrator</name>
<files>src/moai/core/orchestrator.py</files>
<action>Add to orchestrator.py:
- async query_model_direct(model: str, message: str, discussion: Discussion | None, project_name: str) -> str
- Calls single model via AIClient.complete()
- If discussion provided, includes full context via build_context()
- System prompt includes "This is a direct message to you specifically"
- Returns model response
- Handles errors gracefully (returns error message string)
This is similar to /ask but with optional discussion context.</action>
<verify>Import orchestrator, verify query_model_direct signature exists</verify>
<done>orchestrator.py has query_model_direct function for single model with optional context</done>
</task>
<task type="auto">
<name>Task 2: Implement @mention message handler</name>
<files>src/moai/bot/handlers/discussion.py, src/moai/bot/handlers/__init__.py</files>
<action>Add to discussion.py:
- mention_handler(update, context) for messages starting with @model
- Use regex filter: MessageHandler(filters.Regex(r'^@(claude|gpt|gemini)\s'), mention_handler)
- Parse model name from first word (strip @)
- Rest of message is the content
- Get active discussion if exists (for context), otherwise just query with project context
- Call query_model_direct with discussion context
- If discussion active: create Message(is_direct=True) to persist
- Display: "**@Model (direct):**\n> response"
- Show typing indicator while waiting
Register MessageHandler in __init__.py AFTER CommandHandlers (order matters for telegram-bot).</action>
<verify>With active discussion, send "@claude What do you think?", verify response with context</verify>
<done>@mention messages route to specific model with full discussion context, marked is_direct=True</done>
</task>
<task type="auto">
<name>Task 3: Update status to show active discussion info</name>
<files>src/moai/bot/handlers/status.py</files>
<action>Update status_command to show:
- If discussion_state exists in user_data:
- "Active discussion: Round N/M"
- "Discussion ID: {short_id}"
- Show count of messages in current discussion
- Use get_active_discussion service if user_data cleared but DB has active
This helps users know their current discussion state.</action>
<verify>/status shows active discussion info during a discussion session</verify>
<done>/status displays current discussion state (round progress, message count)</done>
</task>
</tasks>
<verification>
Before declaring plan complete:
- [ ] @claude, @gpt, @gemini messages work
- [ ] Direct messages include discussion context when active
- [ ] Messages marked is_direct=True in database
- [ ] /status shows active discussion info
- [ ] Works without active discussion (just project context)
- [ ] M8 milestone (@mention direct messages) complete
</verification>
<success_criteria>
- @mention syntax routes to specific models
- Full discussion context passed when available
- Direct messages persisted with is_direct flag
- /status shows discussion state
- M8 milestone complete
- Phase 5 complete (M4, M5, M8 all done)
</success_criteria>
<output>
After completion, create `.planning/phases/05-multi-model-discussions/05-04-SUMMARY.md`
Note: This is the final plan for Phase 5. Success criteria for Phase 5:
- M4: Open mode (parallel) ✓ (05-02)
- M5: Discuss mode (sequential rounds) ✓ (05-03)
- M8: @mention direct messages ✓ (05-04)
</output>

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---
phase: 05-multi-model-discussions
plan: 04
subsystem: api
tags: [telegram, ai-orchestration, mention-handler, direct-messages, message-handler]
# Dependency graph
requires:
- phase: 05-multi-model-discussions/03
provides: build_context() for discussion context, discussion service with is_direct flag
- phase: 04-single-model-qa/02
provides: AIClient.complete() and typing indicator pattern
provides:
- query_model_direct() for single model queries with optional context
- @mention handler (@claude, @gpt, @gemini) for direct model messages
- Enhanced /status showing active discussion state
affects: [06-consensus, 06-export]
# Tech tracking
tech-stack:
added: []
patterns: [MessageHandler with regex filter for @mentions, direct messages with is_direct flag]
key-files:
created: []
modified: [src/moai/core/orchestrator.py, src/moai/bot/handlers/discussion.py, src/moai/bot/handlers/__init__.py, src/moai/bot/handlers/status.py]
key-decisions:
- "Direct messages include '[Direct to you]:' prefix in context for model awareness"
- "MessageHandler registered AFTER CommandHandlers (telegram-bot ordering)"
- "@mentions persist with is_direct=True in current round if discussion active"
patterns-established:
- "query_model_direct for single model queries with optional discussion context"
- "MessageHandler with Regex filter for @mention syntax"
issues-created: []
# Metrics
duration: 8min
completed: 2026-01-16
---
# Phase 5 Plan 4: @Mention Direct Messages Summary
**@claude/@gpt/@gemini direct message handlers with discussion context and enhanced /status display**
## Performance
- **Duration:** 8 min
- **Started:** 2026-01-16T19:50:00Z
- **Completed:** 2026-01-16T19:58:00Z
- **Tasks:** 3
- **Files modified:** 4
## Accomplishments
- Added query_model_direct() function for single model queries with optional discussion context
- Implemented @mention message handler with regex filter for @claude, @gpt, @gemini
- Direct messages persist with is_direct=True flag when discussion is active
- Enhanced /status command to show active discussion info (round progress, message count, discussion ID)
## Task Commits
Each task was committed atomically:
1. **Task 1: Add query_model_direct() to orchestrator** - `5934d21` (feat)
2. **Task 2: Implement @mention message handler** - `3296874` (feat)
3. **Task 3: Update /status to show active discussion info** - `2a86d39` (feat)
**Plan metadata:** (pending)
## Files Created/Modified
- `src/moai/core/orchestrator.py` - Added query_model_direct() function for direct model queries
- `src/moai/bot/handlers/discussion.py` - Added mention_handler for @model messages
- `src/moai/bot/handlers/__init__.py` - Registered MessageHandler with regex filter
- `src/moai/bot/handlers/status.py` - Enhanced to show project and discussion state
## Decisions Made
- Direct messages prefix user input with "[Direct to you]:" so model knows it's specifically addressed
- MessageHandler registered after CommandHandlers to ensure commands take priority
- Regex filter `^@(claude|gpt|gemini)\s` requires space after model name
## Deviations from Plan
None - plan executed exactly as written.
## Issues Encountered
None
## Next Phase Readiness
- M8 milestone (@mention direct messages) complete
- Phase 5 complete (M4, M5, M8 all done)
- Discussion infrastructure ready for consensus generation (Phase 6)
- Message context and is_direct flag available for export filtering
---
*Phase: 05-multi-model-discussions*
*Completed: 2026-01-16*

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repos:
- repo: https://github.com/astral-sh/ruff-pre-commit
rev: v0.14.13
hooks:
- id: ruff
args: [--fix]
- id: ruff-format
- repo: https://github.com/pre-commit/pre-commit-hooks
rev: v5.0.0
hooks:
- id: trailing-whitespace
- id: end-of-file-fixer
- id: check-yaml

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pyproject.toml Normal file
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[project]
name = "moai"
version = "0.1.0"
description = "Multi-AI collaborative brainstorming platform"
requires-python = ">=3.11"
dependencies = [
"python-telegram-bot",
"python-dotenv",
"sqlalchemy",
"httpx",
"aiosqlite",
"openai",
]
[project.optional-dependencies]
dev = [
"pytest",
"pytest-cov",
"pytest-asyncio",
"ruff",
"pre-commit",
]
[tool.ruff]
line-length = 100
target-version = "py311"
[tool.ruff.lint]
select = ["E", "F", "I", "N", "W", "UP"]
[tool.pytest.ini_options]
testpaths = ["tests"]
asyncio_mode = "auto"
[tool.hatch.build.targets.wheel]
packages = ["src/moai"]
[build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"

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src/moai/__init__.py Normal file
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"""MoAI - Multi-AI collaborative brainstorming platform.
A Telegram bot platform enabling multiple AI models (Claude, GPT, Gemini)
to discuss topics together in structured rounds, working toward consensus.
"""
__version__ = "0.1.0"

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"""Telegram bot handlers and entry point.
This module contains the Telegram bot setup, command handlers,
and middleware for the MoAI platform.
"""

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"""Bot configuration loaded from environment variables.
Provides BotConfig dataclass with configuration loaded from environment.
Required variables will raise ValueError if missing.
"""
import os
from dataclasses import dataclass
@dataclass
class BotConfig:
"""Configuration for the MoAI Telegram bot.
Attributes:
bot_token: Telegram Bot API token (required).
allowed_users: Set of allowed Telegram user IDs. Empty means all users allowed.
database_url: SQLAlchemy database URL.
log_level: Logging level string (DEBUG, INFO, WARNING, ERROR).
ai_router: AI router service ("requesty" or "openrouter").
ai_api_key: API key for the AI router service.
ai_referer: HTTP-Referer header for OpenRouter (optional).
"""
bot_token: str
allowed_users: set[int]
database_url: str
log_level: str
ai_router: str
ai_api_key: str
ai_referer: str | None
@classmethod
def from_env(cls) -> "BotConfig":
"""Load configuration from environment variables.
Environment variables:
BOT_TOKEN (required): Telegram bot token from @BotFather.
ALLOWED_USERS (optional): Comma-separated Telegram user IDs.
DATABASE_URL (optional): Database URL, defaults to SQLite.
LOG_LEVEL (optional): Logging level, defaults to INFO.
AI_ROUTER (optional): AI router service, defaults to "requesty".
AI_API_KEY (optional): API key for the AI router service.
AI_REFERER (optional): HTTP-Referer header for OpenRouter.
Returns:
BotConfig instance populated from environment.
Raises:
ValueError: If BOT_TOKEN is not set.
"""
bot_token = os.environ.get("BOT_TOKEN")
if not bot_token:
raise ValueError("BOT_TOKEN environment variable is required")
# Parse allowed users from comma-separated string
allowed_users_str = os.environ.get("ALLOWED_USERS", "")
allowed_users: set[int] = set()
if allowed_users_str.strip():
for user_id in allowed_users_str.split(","):
user_id = user_id.strip()
if user_id:
allowed_users.add(int(user_id))
database_url = os.environ.get("DATABASE_URL", "sqlite+aiosqlite:///./moai.db")
log_level = os.environ.get("LOG_LEVEL", "INFO")
# AI router configuration
ai_router = os.environ.get("AI_ROUTER", "requesty")
ai_api_key = os.environ.get("AI_API_KEY", "")
ai_referer = os.environ.get("AI_REFERER")
return cls(
bot_token=bot_token,
allowed_users=allowed_users,
database_url=database_url,
log_level=log_level,
ai_router=ai_router,
ai_api_key=ai_api_key,
ai_referer=ai_referer,
)

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"""Telegram command handlers for MoAI bot.
This module contains handlers for Telegram bot commands including
project management, discussion commands, and export functionality.
"""
from telegram.ext import Application, CommandHandler, MessageHandler, filters
from moai.bot.handlers.commands import help_command, start_command
from moai.bot.handlers.discussion import (
ask_command,
discuss_command,
mention_handler,
next_command,
open_command,
stop_command,
)
from moai.bot.handlers.projects import project_command, projects_command
from moai.bot.handlers.status import status_command
def register_handlers(app: Application) -> None:
"""Register all command handlers with the application.
Args:
app: The telegram Application instance.
"""
# Basic commands
app.add_handler(CommandHandler("start", start_command))
app.add_handler(CommandHandler("help", help_command))
# Status
app.add_handler(CommandHandler("status", status_command))
# Project management
app.add_handler(CommandHandler("projects", projects_command))
app.add_handler(CommandHandler("project", project_command))
# Discussion / Q&A
app.add_handler(CommandHandler("ask", ask_command))
app.add_handler(CommandHandler("open", open_command))
app.add_handler(CommandHandler("discuss", discuss_command))
app.add_handler(CommandHandler("next", next_command))
app.add_handler(CommandHandler("stop", stop_command))
# @mention handler - MessageHandler registered AFTER CommandHandlers
# Matches messages starting with @claude, @gpt, or @gemini followed by content
app.add_handler(MessageHandler(filters.Regex(r"^@(claude|gpt|gemini)\s"), mention_handler))

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"""Basic command handlers for MoAI bot."""
from telegram import Update
from telegram.ext import ContextTypes
HELP_TEXT = """
*MoAI - Master of AIs*
Multi-AI collaborative brainstorming platform.
*Project Commands:*
/projects - List all projects
/project new "Name" - Create new project
/project select <id|name> - Switch to project
/project delete <id> - Delete project
/project models claude,gpt - Set models
/project info - Show current project
*Questions:*
/ask <model> <question> - Ask a single model
*Discussion Commands:*
/open <question> - Ask all models (parallel)
/discuss [rounds] - Start discussion (default: 3)
/next - Trigger next round
/stop - Stop current discussion
@model <message> - Direct message to model
*Output Commands:*
/consensus - Generate consensus summary
/export - Export project as markdown
*Utility:*
/status - Show current state
/help - Show this message
""".strip()
async def start_command(update: Update, context: ContextTypes.DEFAULT_TYPE) -> None:
"""Handle /start command - welcome message."""
await update.message.reply_text(
"Welcome to MoAI!\n\n"
"Use /help to see available commands.\n"
'Use /project new "Name" to create your first project.'
)
async def help_command(update: Update, context: ContextTypes.DEFAULT_TYPE) -> None:
"""Handle /help command - show available commands."""
await update.message.reply_text(HELP_TEXT, parse_mode="Markdown")

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"""Discussion handlers for MoAI bot."""
from telegram import Update
from telegram.ext import ContextTypes
from moai.bot.handlers.projects import get_selected_project
from moai.core.ai_client import MODEL_MAP, get_ai_client
from moai.core.models import DiscussionType, RoundType
from moai.core.orchestrator import query_model_direct, query_models_parallel, run_discussion_round
from moai.core.services.discussion import (
complete_discussion,
create_discussion,
create_message,
create_round,
get_active_discussion,
get_current_round,
get_discussion,
)
async def ask_command(update: Update, context: ContextTypes.DEFAULT_TYPE) -> None:
"""Handle /ask <model> <question> command.
Examples:
/ask claude What is Python?
/ask gpt Explain async/await
"""
args = context.args or []
if len(args) < 2:
available = ", ".join(MODEL_MAP.keys())
await update.message.reply_text(
f"Usage: /ask <model> <question>\n"
f"Available models: {available}\n\n"
f"Example: /ask claude What is Python?"
)
return
model_name = args[0].lower()
question = " ".join(args[1:])
# Validate model
if model_name not in MODEL_MAP:
available = ", ".join(MODEL_MAP.keys())
await update.message.reply_text(f"Unknown model: {model_name}\nAvailable: {available}")
return
# Get project context if available (optional for /ask)
project = await get_selected_project(context)
project_context = f"Project: {project.name}\n" if project else ""
# Send "typing" indicator while waiting for AI
await update.message.chat.send_action("typing")
try:
client = get_ai_client()
response = await client.complete(
model=model_name,
messages=[{"role": "user", "content": question}],
system_prompt=f"{project_context}You are a helpful AI assistant.",
)
# Format response with model name
await update.message.reply_text(
f"*{model_name.title()}:*\n\n{response}",
parse_mode="Markdown",
)
except Exception as e:
await update.message.reply_text(f"Error: {e}")
async def open_command(update: Update, context: ContextTypes.DEFAULT_TYPE) -> None:
"""Handle /open <question> command - ask all project models in parallel.
Requires a selected project with configured models. Creates a Discussion
with OPEN type and a PARALLEL round, then queries all models simultaneously.
Examples:
/open What is Python?
/open How should we approach this problem?
"""
args = context.args or []
if not args:
await update.message.reply_text(
"Usage: /open <question>\n\nExample: /open What are the pros and cons of microservices?"
)
return
question = " ".join(args)
# Require a selected project
project = await get_selected_project(context)
if project is None:
await update.message.reply_text("No project selected. Use /project select <name> first.")
return
# Require configured models
if not project.models:
await update.message.reply_text(
"No models configured for this project.\n"
"Use /project models claude,gpt,gemini to set models."
)
return
# Show typing indicator while waiting for AI
await update.message.chat.send_action("typing")
try:
# Create discussion and round in database
discussion = await create_discussion(
project_id=project.id,
question=question,
discussion_type=DiscussionType.OPEN,
)
round_ = await create_round(
discussion_id=discussion.id,
round_number=1,
round_type=RoundType.PARALLEL,
)
# Query all models in parallel
responses = await query_models_parallel(
models=project.models,
question=question,
project_name=project.name,
)
# Persist messages and build response text
response_lines = [f"*Question:* {question}\n"]
for model, response in responses.items():
await create_message(
round_id=round_.id,
model=model,
content=response,
)
response_lines.append(f"*{model.title()}:*\n{response}\n")
# Send combined response
await update.message.reply_text(
"\n".join(response_lines),
parse_mode="Markdown",
)
except Exception as e:
await update.message.reply_text(f"Error: {e}")
async def discuss_command(update: Update, context: ContextTypes.DEFAULT_TYPE) -> None:
"""Handle /discuss [rounds] command - start sequential multi-round discussion.
Requires a selected project with configured models and an active discussion
(created via /open). Starts a sequential discussion where each model sees
prior responses.
Examples:
/discuss - Start 3-round discussion (default)
/discuss 5 - Start 5-round discussion
"""
args = context.args or []
# Parse optional round limit (default: 3)
round_limit = 3
if args:
try:
round_limit = int(args[0])
if round_limit < 1:
await update.message.reply_text("Round limit must be at least 1.")
return
except ValueError:
await update.message.reply_text(
f"Invalid round limit: {args[0]}\n\nUsage: /discuss [rounds]"
)
return
# Require a selected project
project = await get_selected_project(context)
if project is None:
await update.message.reply_text("No project selected. Use /project select <name> first.")
return
# Require configured models
if not project.models:
await update.message.reply_text(
"No models configured for this project.\n"
"Use /project models claude,gpt,gemini to set models."
)
return
# Check for active discussion
discussion = await get_active_discussion(project.id)
if discussion is None:
await update.message.reply_text(
"No active discussion. Start one with /open <question> first."
)
return
# Calculate next round number (continue from existing rounds)
current_round_num = len(discussion.rounds) + 1
# Store discussion state for /next and /stop
context.user_data["discussion_state"] = {
"discussion_id": discussion.id,
"project_id": project.id,
"project_name": project.name,
"models": project.models,
"current_round": current_round_num,
"round_limit": round_limit,
}
# Show typing indicator
await update.message.chat.send_action("typing")
try:
# Reload discussion with full eager loading for context building
discussion = await get_discussion(discussion.id)
# Run first round
responses = await run_discussion_round(
discussion=discussion,
models=project.models,
project_name=project.name,
round_number=current_round_num,
)
# Build response text
response_lines = [f"*Round {current_round_num}/{round_limit}:*\n"]
for model, response in responses.items():
response_lines.append(f"*{model.title()}:*\n{response}\n")
if current_round_num >= round_limit:
response_lines.append(f"\n_Discussion complete ({round_limit} rounds)._")
# Clear state when done
del context.user_data["discussion_state"]
else:
response_lines.append(
f"\n_Round {current_round_num}/{round_limit} complete. Use /next or /stop._"
)
# Update current round for next time
context.user_data["discussion_state"]["current_round"] = current_round_num + 1
await update.message.reply_text(
"\n".join(response_lines),
parse_mode="Markdown",
)
except Exception as e:
await update.message.reply_text(f"Error: {e}")
async def next_command(update: Update, context: ContextTypes.DEFAULT_TYPE) -> None:
"""Handle /next command - advance to the next discussion round.
Requires an active discussion started with /discuss. Runs the next
sequential round with full context from prior rounds.
"""
# Check for active discussion state
state = context.user_data.get("discussion_state")
if state is None:
await update.message.reply_text("No active discussion. Start one with /open then /discuss.")
return
current_round = state["current_round"]
round_limit = state["round_limit"]
# Check if already at limit
if current_round > round_limit:
await update.message.reply_text(
f"Round limit ({round_limit}) reached. Start a new discussion with /open."
)
del context.user_data["discussion_state"]
return
# Show typing indicator
await update.message.chat.send_action("typing")
try:
# Load discussion with full context
discussion = await get_discussion(state["discussion_id"])
if discussion is None:
await update.message.reply_text("Discussion not found.")
del context.user_data["discussion_state"]
return
# Run the next round
responses = await run_discussion_round(
discussion=discussion,
models=state["models"],
project_name=state["project_name"],
round_number=current_round,
)
# Build response text
response_lines = [f"*Round {current_round}/{round_limit}:*\n"]
for model, response in responses.items():
response_lines.append(f"*{model.title()}:*\n{response}\n")
if current_round >= round_limit:
# Final round - complete discussion
await complete_discussion(state["discussion_id"])
response_lines.append(f"\n_Discussion complete ({round_limit} rounds)._")
del context.user_data["discussion_state"]
else:
response_lines.append(
f"\n_Round {current_round}/{round_limit} complete. Use /next or /stop._"
)
# Update state for next round
context.user_data["discussion_state"]["current_round"] = current_round + 1
await update.message.reply_text(
"\n".join(response_lines),
parse_mode="Markdown",
)
except Exception as e:
await update.message.reply_text(f"Error: {e}")
async def stop_command(update: Update, context: ContextTypes.DEFAULT_TYPE) -> None:
"""Handle /stop command - stop the current discussion early.
Completes the discussion at the current round and clears the session state.
"""
# Check for active discussion state
state = context.user_data.get("discussion_state")
if state is None:
await update.message.reply_text("No active discussion to stop.")
return
current_round = state["current_round"]
try:
# Complete the discussion in database
await complete_discussion(state["discussion_id"])
# Clear session state
del context.user_data["discussion_state"]
await update.message.reply_text(
f"_Discussion stopped at round {current_round - 1}. Use /consensus to summarize._",
parse_mode="Markdown",
)
except Exception as e:
await update.message.reply_text(f"Error: {e}")
async def mention_handler(update: Update, context: ContextTypes.DEFAULT_TYPE) -> None:
"""Handle @model mention messages.
Messages starting with @claude, @gpt, or @gemini are routed to that
specific model. If a discussion is active, includes full context.
Examples:
@claude What do you think about this?
@gpt Can you elaborate on your previous point?
@gemini Do you agree with Claude?
"""
message_text = update.message.text
if not message_text:
return
# Parse model name from first word (e.g., "@claude" -> "claude")
parts = message_text.split(maxsplit=1)
if not parts:
return
model_tag = parts[0].lower()
# Strip the @ prefix
model_name = model_tag.lstrip("@")
# Validate model
if model_name not in MODEL_MAP:
return # Not a valid model mention, ignore
# Get the rest of the message as content
content = parts[1] if len(parts) > 1 else ""
if not content.strip():
await update.message.reply_text(
f"Usage: @{model_name} <message>\n\nExample: @{model_name} What do you think?"
)
return
# Get project context if available
project = await get_selected_project(context)
if project is None:
await update.message.reply_text("No project selected. Use /project select <name> first.")
return
project_name = project.name
# Check for active discussion (for context)
discussion = await get_active_discussion(project.id)
# Show typing indicator
await update.message.chat.send_action("typing")
try:
# Query the model directly with optional discussion context
response = await query_model_direct(
model=model_name,
message=content,
discussion=discussion,
project_name=project_name,
)
# If there's an active discussion, persist the message
if discussion is not None:
# Get or create a round for this direct message
current_round = await get_current_round(discussion.id)
if current_round is not None:
await create_message(
round_id=current_round.id,
model=model_name,
content=response,
is_direct=True,
)
# Format response
await update.message.reply_text(
f"*@{model_name.title()} (direct):*\n{response}",
parse_mode="Markdown",
)
except Exception as e:
await update.message.reply_text(f"Error: {e}")

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"""Project management handlers for MoAI bot."""
import re
from telegram import Update
from telegram.ext import ContextTypes
from moai.core.models import Project
from moai.core.services.project import (
create_project,
delete_project,
get_project,
get_project_by_name,
list_projects,
update_project_models,
)
async def projects_command(update: Update, context: ContextTypes.DEFAULT_TYPE) -> None:
"""Handle /projects command - list all projects."""
projects = await list_projects()
if not projects:
await update.message.reply_text('No projects yet. Use /project new "Name" to create one.')
return
lines = ["*Your Projects:*\n"]
for p in projects:
models_str = ", ".join(p.models) if p.models else "none"
lines.append(f"• *{p.name}*\n ID: `{p.id[:8]}...`\n Models: {models_str}")
await update.message.reply_text("\n".join(lines), parse_mode="Markdown")
async def project_command(update: Update, context: ContextTypes.DEFAULT_TYPE) -> None:
"""Handle /project subcommands.
Subcommands:
new "Name" - Create new project
select <id|name> - Switch to project
delete <id> - Delete project by ID
models <list> - Set models for current project
info - Show current project
"""
args = context.args or []
if not args:
await update.message.reply_text(
"Usage:\n"
'/project new "Name" - Create project\n'
"/project select <id|name> - Switch project\n"
"/project info - Show current project\n"
"/project models [model1,model2,...] - Set/show models\n"
"/project delete <id> - Delete project"
)
return
subcommand = args[0].lower()
if subcommand == "new":
await _handle_project_new(update, context, args[1:])
elif subcommand == "select":
await _handle_project_select(update, context, args[1:])
elif subcommand == "info":
await _handle_project_info(update, context)
elif subcommand == "models":
await _handle_project_models(update, context, args[1:])
elif subcommand == "delete":
await _handle_project_delete(update, context, args[1:])
else:
await update.message.reply_text(
f"Unknown subcommand: {subcommand}\nAvailable: new, select, info, models, delete"
)
async def _handle_project_new(
update: Update, context: ContextTypes.DEFAULT_TYPE, args: list[str]
) -> None:
"""Handle /project new "Name" command."""
if not args:
await update.message.reply_text('Usage: /project new "Project Name"')
return
# Join args and extract quoted name
text = " ".join(args)
match = re.match(r'^"([^"]+)"', text) or re.match(r"^'([^']+)'", text)
if match:
name = match.group(1)
else:
# No quotes - use the first arg as name
name = args[0]
project = await create_project(name)
models_str = ", ".join(project.models)
await update.message.reply_text(
f"*Project Created*\n\n"
f"Name: {project.name}\n"
f"ID: `{project.id}`\n"
f"Models: {models_str}\n\n"
f"Use /project select {project.id[:8]} to switch to this project.",
parse_mode="Markdown",
)
async def _handle_project_select(
update: Update, context: ContextTypes.DEFAULT_TYPE, args: list[str]
) -> None:
"""Handle /project select <id|name> command."""
if not args:
await update.message.reply_text("Usage: /project select <id|name>")
return
identifier = " ".join(args)
# Try to find by ID first (supports partial ID match)
project = await get_project(identifier)
# If not found by ID, try by name
if project is None:
project = await get_project_by_name(identifier)
if project is None:
await update.message.reply_text(
"Project not found. Use /projects to list available projects."
)
return
# Store selected project ID in user_data
context.user_data["selected_project_id"] = project.id
await update.message.reply_text(f"Selected project: {project.name}")
async def _handle_project_info(update: Update, context: ContextTypes.DEFAULT_TYPE) -> None:
"""Handle /project info command."""
project = await get_selected_project(context)
if project is None:
await update.message.reply_text("No project selected. Use /project select <name> first.")
return
models_str = ", ".join(project.models) if project.models else "none"
# Note: discussion_count will be available when discussions are implemented
discussion_count = len(project.discussions) if project.discussions else 0
await update.message.reply_text(
f"*Project Info*\n\n"
f"Name: {project.name}\n"
f"ID: `{project.id}`\n"
f"Models: {models_str}\n"
f"Created: {project.created_at.strftime('%Y-%m-%d %H:%M')}\n"
f"Discussions: {discussion_count}",
parse_mode="Markdown",
)
async def _handle_project_models(
update: Update, context: ContextTypes.DEFAULT_TYPE, args: list[str]
) -> None:
"""Handle /project models [model1,model2,...] command."""
project = await get_selected_project(context)
if project is None:
await update.message.reply_text("No project selected. Use /project select <name> first.")
return
# No args: show current models
if not args:
models_str = ", ".join(project.models) if project.models else "none"
await update.message.reply_text(f"Current models: {models_str}")
return
# Parse comma-separated model names
models_input = " ".join(args)
models = [m.strip() for m in models_input.split(",") if m.strip()]
if not models:
await update.message.reply_text("Usage: /project models claude,gpt,gemini")
return
updated_project = await update_project_models(project.id, models)
if updated_project is None:
await update.message.reply_text("Project not found.")
return
models_str = ", ".join(updated_project.models)
await update.message.reply_text(f"Models updated: {models_str}")
async def _handle_project_delete(
update: Update, context: ContextTypes.DEFAULT_TYPE, args: list[str]
) -> None:
"""Handle /project delete <id> command."""
if not args:
await update.message.reply_text("Usage: /project delete <project-id>")
return
project_id = args[0]
# Get project first to show name in confirmation
project = await get_project(project_id)
if project is None:
await update.message.reply_text("Project not found.")
return
project_name = project.name
deleted = await delete_project(project_id)
if not deleted:
await update.message.reply_text("Project not found.")
return
# Clear selection if deleted project was selected
if context.user_data.get("selected_project_id") == project_id:
context.user_data.pop("selected_project_id", None)
await update.message.reply_text(f"Deleted project: {project_name}")
async def get_selected_project(context: ContextTypes.DEFAULT_TYPE) -> Project | None:
"""Get the currently selected project from user_data.
Args:
context: The telegram context with user_data.
Returns:
The Project object if one is selected, None otherwise.
"""
project_id = context.user_data.get("selected_project_id")
if project_id is None:
return None
return await get_project(project_id)

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"""Status command handler for MoAI bot."""
from telegram import Update
from telegram.ext import ContextTypes
from moai.bot.handlers.projects import get_selected_project
from moai.core.ai_client import get_ai_client
from moai.core.services.discussion import get_active_discussion
async def status_command(update: Update, context: ContextTypes.DEFAULT_TYPE) -> None:
"""Handle /status command - show current project/discussion state.
Shows:
- Bot and AI router status
- Selected project (if any)
- Active discussion state (if any)
"""
# Check AI client status
try:
client = get_ai_client()
ai_status = f"AI Router: {client.router}"
except RuntimeError:
ai_status = "AI Router: not configured"
# Build status lines
status_lines = [
"*MoAI Status*\n",
"Bot: Online",
"Database: Connected",
ai_status,
"",
]
# Check for selected project
project = await get_selected_project(context)
if project is None:
status_lines.append('_No project selected. Use /project new "Name" to create one._')
else:
status_lines.append(f"*Project:* {project.name}")
if project.models:
models_str = ", ".join(project.models)
status_lines.append(f"Models: {models_str}")
else:
status_lines.append("Models: none configured")
# Check for active discussion
discussion = await get_active_discussion(project.id)
if discussion is not None:
# Count messages across all rounds
message_count = sum(len(r.messages) for r in discussion.rounds)
round_count = len(discussion.rounds)
# Check for in-progress discussion state
disc_state = context.user_data.get("discussion_state")
if disc_state and disc_state.get("discussion_id") == discussion.id:
current_round = disc_state["current_round"]
round_limit = disc_state["round_limit"]
status_lines.append("")
status_lines.append(f"*Active Discussion:* Round {current_round}/{round_limit}")
status_lines.append(f"Discussion ID: {discussion.id[:8]}...")
status_lines.append(f"Messages: {message_count}")
else:
status_lines.append("")
status_lines.append(f"*Active Discussion:* {round_count} rounds completed")
status_lines.append(f"Discussion ID: {discussion.id[:8]}...")
status_lines.append(f"Messages: {message_count}")
status_lines.append("_Use /discuss to continue or /stop to end._")
else:
status_lines.append("")
status_lines.append("_No active discussion. Use /open <question> to start._")
await update.message.reply_text("\n".join(status_lines), parse_mode="Markdown")

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"""MoAI Telegram bot entry point.
Sets up and runs the Telegram bot with database lifecycle hooks.
Usage:
python -m moai.bot.main
"""
import logging
from dotenv import load_dotenv
from telegram.ext import Application, ApplicationBuilder
from moai.bot.config import BotConfig
from moai.bot.handlers import register_handlers
from moai.core.ai_client import init_ai_client
from moai.core.database import close_db, create_tables, init_db
# Module-level config reference for post_init callback
_config: BotConfig | None = None
async def post_init(application: Application) -> None:
"""Initialize database after bot application is built.
Called automatically by python-telegram-bot after Application.build().
Sets up the database engine and creates tables if needed.
"""
logger = logging.getLogger(__name__)
if _config is None:
raise RuntimeError("Config not initialized before post_init")
init_db(_config.database_url)
await create_tables()
logger.info("Database initialized")
init_ai_client(_config)
logger.info("AI client initialized with %s", _config.ai_router)
async def post_shutdown(application: Application) -> None:
"""Clean up database on bot shutdown.
Called automatically by python-telegram-bot during Application shutdown.
Disposes database engine and releases connections.
"""
logger = logging.getLogger(__name__)
await close_db()
logger.info("Database closed")
def main() -> None:
"""Run the MoAI Telegram bot.
Loads configuration from environment, sets up the Application with
database lifecycle hooks, registers handlers, and starts polling.
"""
global _config
load_dotenv() # Load .env file
_config = BotConfig.from_env()
logging.basicConfig(
level=getattr(logging, _config.log_level.upper(), logging.INFO),
format="%(asctime)s - %(name)s - %(levelname)s - %(message)s",
)
logger = logging.getLogger(__name__)
app = (
ApplicationBuilder()
.token(_config.bot_token)
.post_init(post_init)
.post_shutdown(post_shutdown)
.build()
)
# Store config in bot_data for handler access
app.bot_data["config"] = _config
register_handlers(app)
logger.info("Starting MoAI bot...")
app.run_polling()
if __name__ == "__main__":
main()

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"""Core business logic, models, and services.
This module contains the core functionality including database models,
the AI orchestrator, AI client abstraction, and export services.
"""

125
src/moai/core/ai_client.py Normal file
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"""AI client abstraction for model routing.
Provides AIClient class that wraps the OpenAI SDK to communicate with
AI model routers (Requesty or OpenRouter). Both routers are OpenAI-compatible.
"""
from openai import AsyncOpenAI
from moai.bot.config import BotConfig
# Router base URLs
ROUTER_URLS = {
"requesty": "https://router.requesty.ai/v1",
"openrouter": "https://openrouter.ai/api/v1",
}
# Short model names to full model identifiers
MODEL_MAP = {
"claude": "anthropic/claude-sonnet-4-20250514",
"gpt": "openai/gpt-4o",
"gemini": "google/gemini-2.0-flash",
}
class AIClient:
"""AI client wrapping OpenAI SDK for model routing.
Supports Requesty and OpenRouter as backend routers. Both use
OpenAI-compatible APIs with different base URLs and headers.
Attributes:
router: The router service name ("requesty" or "openrouter").
referer: HTTP-Referer header for OpenRouter (optional).
"""
def __init__(self, router: str, api_key: str, referer: str | None = None) -> None:
"""Initialize AI client.
Args:
router: Router service name ("requesty" or "openrouter").
api_key: API key for the router service.
referer: HTTP-Referer header for OpenRouter (optional).
Raises:
ValueError: If router is not supported.
"""
if router not in ROUTER_URLS:
raise ValueError(f"Unsupported router: {router}. Use: {list(ROUTER_URLS.keys())}")
self.router = router
self.referer = referer
base_url = ROUTER_URLS[router]
self._client = AsyncOpenAI(base_url=base_url, api_key=api_key)
async def complete(
self,
model: str,
messages: list[dict],
system_prompt: str | None = None,
) -> str:
"""Get a completion from the AI model.
Args:
model: Model short name (e.g., "claude") or full identifier.
messages: List of message dicts with "role" and "content".
system_prompt: Optional system prompt to prepend.
Returns:
The model's response content as a string.
"""
# Resolve short model names
resolved_model = MODEL_MAP.get(model, model)
# Build message list
full_messages = []
if system_prompt:
full_messages.append({"role": "system", "content": system_prompt})
full_messages.extend(messages)
# Build extra headers for OpenRouter
extra_headers = {}
if self.router == "openrouter" and self.referer:
extra_headers["HTTP-Referer"] = self.referer
# Make the API call
response = await self._client.chat.completions.create(
model=resolved_model,
messages=full_messages,
extra_headers=extra_headers if extra_headers else None,
)
return response.choices[0].message.content or ""
# Module-level singleton
_client: AIClient | None = None
def init_ai_client(config: BotConfig) -> AIClient:
"""Initialize the global AI client from config.
Args:
config: BotConfig instance with AI settings.
Returns:
The initialized AIClient instance.
"""
global _client
_client = AIClient(config.ai_router, config.ai_api_key, config.ai_referer)
return _client
def get_ai_client() -> AIClient:
"""Get the global AI client instance.
Returns:
The initialized AIClient instance.
Raises:
RuntimeError: If AI client has not been initialized.
"""
if _client is None:
raise RuntimeError("AI client not initialized. Call init_ai_client() first.")
return _client

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"""Database session management for MoAI.
Provides async session management using SQLAlchemy 2.0 async support.
Usage pattern:
from moai.core.database import init_db, create_tables, get_session, close_db
# Initialize on startup
init_db("sqlite+aiosqlite:///./moai.db")
await create_tables()
# Use sessions for database operations
async with get_session() as session:
project = Project(name="My Project")
session.add(project)
# Auto-commits on context exit, rollback on exception
# Cleanup on shutdown
await close_db()
"""
from collections.abc import AsyncGenerator
from contextlib import asynccontextmanager
from sqlalchemy.ext.asyncio import (
AsyncEngine,
AsyncSession,
async_sessionmaker,
create_async_engine,
)
# Module-level state
DATABASE_URL: str = "sqlite+aiosqlite:///./moai.db"
engine: AsyncEngine | None = None
async_session_factory: async_sessionmaker[AsyncSession] | None = None
def init_db(url: str | None = None) -> None:
"""Initialize the database engine and session factory.
Args:
url: Database URL. Defaults to module-level DATABASE_URL if not provided.
Use "sqlite+aiosqlite:///:memory:" for in-memory testing.
"""
global engine, async_session_factory, DATABASE_URL
if url is not None:
DATABASE_URL = url
engine = create_async_engine(DATABASE_URL, echo=False)
async_session_factory = async_sessionmaker(engine, expire_on_commit=False)
async def create_tables() -> None:
"""Create all database tables defined in models.
Must be called after init_db(). Creates tables if they don't exist.
"""
from moai.core.models import Base
if engine is None:
raise RuntimeError("Database not initialized. Call init_db() first.")
async with engine.begin() as conn:
await conn.run_sync(Base.metadata.create_all)
@asynccontextmanager
async def get_session() -> AsyncGenerator[AsyncSession, None]:
"""Async context manager providing a database session.
Yields:
AsyncSession: Database session for operations.
The session auto-commits on successful context exit.
On exception, the session is rolled back automatically.
Example:
async with get_session() as session:
project = Project(name="Test")
session.add(project)
# Commits automatically on exit
"""
if async_session_factory is None:
raise RuntimeError("Database not initialized. Call init_db() first.")
async with async_session_factory() as session:
try:
yield session
await session.commit()
except Exception:
await session.rollback()
raise
async def close_db() -> None:
"""Dispose of the database engine and release connections.
Should be called during application shutdown.
"""
global engine, async_session_factory
if engine is not None:
await engine.dispose()
engine = None
async_session_factory = None

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"""SQLAlchemy models for MoAI multi-AI discussion platform.
Data model hierarchy:
Project (has many) Discussion (has many) Round (has many) Message
Discussion (has one) Consensus
All IDs use UUID stored as String(36) for SQLite compatibility.
Enums are stored as strings for database portability.
"""
from __future__ import annotations
from datetime import datetime
from enum import Enum
from typing import Any
from uuid import uuid4
from sqlalchemy import JSON, DateTime, ForeignKey, String, Text
from sqlalchemy import Enum as SAEnum
from sqlalchemy.orm import DeclarativeBase, Mapped, mapped_column, relationship
class Base(DeclarativeBase):
"""Base class for all SQLAlchemy models."""
pass
class DiscussionType(str, Enum):
"""Type of discussion mode."""
OPEN = "open"
DISCUSS = "discuss"
class DiscussionStatus(str, Enum):
"""Status of a discussion."""
ACTIVE = "active"
COMPLETED = "completed"
class RoundType(str, Enum):
"""Type of round in a discussion."""
PARALLEL = "parallel"
SEQUENTIAL = "sequential"
def _uuid() -> str:
"""Generate a new UUID string."""
return str(uuid4())
class Project(Base):
"""A project container for related discussions.
Attributes:
id: Unique identifier (UUID).
name: Human-readable project name.
created_at: When the project was created.
updated_at: When the project was last modified.
models: List of AI model identifiers (e.g., ["claude", "gpt", "gemini"]).
settings: Configuration dict (default_rounds, consensus_threshold, system_prompt_override).
discussions: Related discussions in this project.
"""
__tablename__ = "project"
id: Mapped[str] = mapped_column(String(36), primary_key=True, default=_uuid)
name: Mapped[str] = mapped_column(String(255))
created_at: Mapped[datetime] = mapped_column(DateTime, default=datetime.utcnow)
updated_at: Mapped[datetime] = mapped_column(
DateTime, default=datetime.utcnow, onupdate=datetime.utcnow
)
models: Mapped[Any] = mapped_column(JSON, default=list)
settings: Mapped[Any] = mapped_column(JSON, default=dict)
discussions: Mapped[list[Discussion]] = relationship(
back_populates="project", cascade="all, delete-orphan"
)
class Discussion(Base):
"""A discussion within a project.
Attributes:
id: Unique identifier (UUID).
project_id: FK to parent project.
question: The question or topic being discussed.
type: Whether this is an "open" or "discuss" mode discussion.
status: Current status (active or completed).
created_at: When the discussion started.
project: Parent project relationship.
rounds: Discussion rounds.
consensus: Generated consensus (if any).
"""
__tablename__ = "discussion"
id: Mapped[str] = mapped_column(String(36), primary_key=True, default=_uuid)
project_id: Mapped[str] = mapped_column(ForeignKey("project.id"))
question: Mapped[str] = mapped_column(Text)
type: Mapped[DiscussionType] = mapped_column(SAEnum(DiscussionType))
status: Mapped[DiscussionStatus] = mapped_column(
SAEnum(DiscussionStatus), default=DiscussionStatus.ACTIVE
)
created_at: Mapped[datetime] = mapped_column(DateTime, default=datetime.utcnow)
project: Mapped[Project] = relationship(back_populates="discussions")
rounds: Mapped[list[Round]] = relationship(
back_populates="discussion", cascade="all, delete-orphan"
)
consensus: Mapped[Consensus | None] = relationship(
back_populates="discussion", uselist=False, cascade="all, delete-orphan"
)
class Round(Base):
"""A round within a discussion.
Attributes:
id: Unique identifier (UUID).
discussion_id: FK to parent discussion.
round_number: Sequential round number within the discussion.
type: Whether this round is parallel or sequential.
discussion: Parent discussion relationship.
messages: Messages from AI models in this round.
"""
__tablename__ = "round"
id: Mapped[str] = mapped_column(String(36), primary_key=True, default=_uuid)
discussion_id: Mapped[str] = mapped_column(ForeignKey("discussion.id"))
round_number: Mapped[int]
type: Mapped[RoundType] = mapped_column(SAEnum(RoundType))
discussion: Mapped[Discussion] = relationship(back_populates="rounds")
messages: Mapped[list[Message]] = relationship(
back_populates="round", cascade="all, delete-orphan"
)
class Message(Base):
"""A message from an AI model within a round.
Attributes:
id: Unique identifier (UUID).
round_id: FK to parent round.
model: AI model identifier (e.g., "claude", "gpt", "gemini").
content: The message content.
timestamp: When the message was created.
is_direct: True if this was a direct @mention to this model.
round: Parent round relationship.
"""
__tablename__ = "message"
id: Mapped[str] = mapped_column(String(36), primary_key=True, default=_uuid)
round_id: Mapped[str] = mapped_column(ForeignKey("round.id"))
model: Mapped[str] = mapped_column(String(50))
content: Mapped[str] = mapped_column(Text)
timestamp: Mapped[datetime] = mapped_column(DateTime, default=datetime.utcnow)
is_direct: Mapped[bool] = mapped_column(default=False)
round: Mapped[Round] = relationship(back_populates="messages")
class Consensus(Base):
"""Generated consensus summary for a discussion.
Attributes:
id: Unique identifier (UUID).
discussion_id: FK to parent discussion (unique - one consensus per discussion).
agreements: List of bullet point strings for agreed items.
disagreements: List of {topic, positions: {model: position}} dicts.
generated_at: When the consensus was generated.
generated_by: Which model generated this summary.
discussion: Parent discussion relationship.
"""
__tablename__ = "consensus"
id: Mapped[str] = mapped_column(String(36), primary_key=True, default=_uuid)
discussion_id: Mapped[str] = mapped_column(ForeignKey("discussion.id"), unique=True)
agreements: Mapped[Any] = mapped_column(JSON, default=list)
disagreements: Mapped[Any] = mapped_column(JSON, default=list)
generated_at: Mapped[datetime] = mapped_column(DateTime, default=datetime.utcnow)
generated_by: Mapped[str] = mapped_column(String(50))
discussion: Mapped[Discussion] = relationship(back_populates="consensus")

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"""AI orchestrator for managing multi-model discussions.
Provides functions for orchestrating parallel and sequential AI queries
across multiple models, building context, and managing discussion flow.
"""
import asyncio
import logging
from moai.core.ai_client import get_ai_client
from moai.core.models import Discussion, RoundType
from moai.core.services.discussion import create_message, create_round
logger = logging.getLogger(__name__)
# System prompt for roundtable discussions
SYSTEM_PROMPT = """You are participating in a roundtable discussion with other AI models.
Other participants: {models}
Current topic: {topic}
Guidelines:
- Be concise but substantive
- You can agree, disagree, or build upon others' points
- Reference other models by name when responding to their points
- Focus on practical, actionable insights
- If you reach agreement with others, state it clearly"""
async def query_models_parallel(
models: list[str],
question: str,
project_name: str,
) -> dict[str, str]:
"""Query multiple AI models in parallel.
Sends the same question to all models simultaneously and collects
their responses. Each model receives a system prompt identifying
the other participants and the discussion topic.
Args:
models: List of model short names (e.g., ["claude", "gpt", "gemini"]).
question: The question to ask all models.
project_name: The project name for context.
Returns:
Dict mapping model name to response text. If a model fails,
its value will be an error message string.
"""
client = get_ai_client()
# Build system prompt with participant info
models_str = ", ".join(models)
system_prompt = SYSTEM_PROMPT.format(models=models_str, topic=project_name)
async def query_single_model(model: str) -> tuple[str, str]:
"""Query a single model and return (model_name, response)."""
try:
response = await client.complete(
model=model,
messages=[{"role": "user", "content": question}],
system_prompt=system_prompt,
)
logger.info("Model %s responded successfully", model)
return (model, response)
except Exception as e:
logger.error("Model %s failed: %s", model, e)
return (model, f"[Error: {e}]")
# Run all queries in parallel
tasks = [query_single_model(model) for model in models]
results = await asyncio.gather(*tasks)
return dict(results)
def build_context(discussion: Discussion) -> list[dict]:
"""Build conversation context from all rounds and messages in a discussion.
Converts the discussion history into OpenAI message format. The original
question becomes the first user message, and all model responses are
formatted as user messages with model attribution for context.
Args:
discussion: Discussion object with eager-loaded rounds and messages.
Returns:
List of message dicts in OpenAI format:
[{"role": "user", "content": "..."}]
"""
messages = []
# Original question as first message
messages.append({"role": "user", "content": discussion.question})
# Sort rounds by round_number
sorted_rounds = sorted(discussion.rounds, key=lambda r: r.round_number)
for round_ in sorted_rounds:
# Sort messages by timestamp within round
sorted_messages = sorted(round_.messages, key=lambda m: m.timestamp)
for msg in sorted_messages:
# Format: "**Model:** response" as user context
formatted = f"**{msg.model.title()}:** {msg.content}"
messages.append({"role": "user", "content": formatted})
return messages
async def query_model_direct(
model: str,
message: str,
discussion: Discussion | None,
project_name: str,
) -> str:
"""Query a single model directly with optional discussion context.
Used for @mention messages where user addresses a specific model.
If a discussion is provided, includes full context so the model
can reference prior responses.
Args:
model: Model short name (e.g., "claude", "gpt", "gemini").
message: The direct message to the model.
discussion: Optional Discussion object for context (with eager-loaded rounds/messages).
project_name: Project name for context.
Returns:
The model's response text, or error message if the query fails.
"""
client = get_ai_client()
# Build system prompt indicating this is a direct message
system_prompt = f"""You are participating in a discussion about: {project_name}
This is a direct message to you specifically. The user has chosen to address you
directly for your unique perspective.
Respond helpfully and concisely."""
# Build messages with optional discussion context
if discussion is not None:
messages = build_context(discussion)
# Add the direct message
messages.append({"role": "user", "content": f"[Direct to you]: {message}"})
else:
messages = [{"role": "user", "content": message}]
try:
response = await client.complete(
model=model,
messages=messages,
system_prompt=system_prompt,
)
logger.info("Direct query to %s successful", model)
return response
except Exception as e:
logger.error("Direct query to %s failed: %s", model, e)
return f"[Error: {e}]"
async def run_discussion_round(
discussion: Discussion,
models: list[str],
project_name: str,
round_number: int,
) -> dict[str, str]:
"""Run a single round of sequential discussion.
Each model is queried in sequence, seeing all prior responses including
those from earlier in this same round. This creates a true sequential
discussion where GPT sees Claude's response before responding.
Args:
discussion: Discussion object with eager-loaded rounds and messages.
models: List of model short names in execution order.
project_name: Project name for context.
round_number: The round number being executed.
Returns:
Dict mapping model name to response text.
"""
client = get_ai_client()
# Build system prompt with participant info
models_str = ", ".join(models)
system_prompt = SYSTEM_PROMPT.format(models=models_str, topic=project_name)
# Create the round record
round_ = await create_round(
discussion_id=discussion.id,
round_number=round_number,
round_type=RoundType.SEQUENTIAL,
)
# Build initial context from prior rounds
context_messages = build_context(discussion)
# Store responses as we go (for sequential context building)
responses: dict[str, str] = {}
# Query each model SEQUENTIALLY
for model in models:
try:
response = await client.complete(
model=model,
messages=context_messages,
system_prompt=system_prompt,
)
logger.info("Model %s responded successfully (round %d)", model, round_number)
except Exception as e:
logger.error("Model %s failed (round %d): %s", model, round_number, e)
response = f"[Error: {e}]"
# Persist message
await create_message(
round_id=round_.id,
model=model,
content=response,
)
# Add to responses
responses[model] = response
# Add this response to context for next model in this round
formatted = f"**{model.title()}:** {response}"
context_messages.append({"role": "user", "content": formatted})
return responses

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"""Service layer for MoAI business logic.
Services encapsulate database operations and business rules,
providing a clean interface for handlers to use.
"""
from moai.core.services.discussion import (
complete_discussion,
create_discussion,
create_message,
create_round,
get_active_discussion,
get_current_round,
get_discussion,
get_round_messages,
list_discussions,
)
from moai.core.services.project import create_project, get_project, list_projects
__all__ = [
"complete_discussion",
"create_discussion",
"create_message",
"create_project",
"create_round",
"get_active_discussion",
"get_current_round",
"get_discussion",
"get_project",
"get_round_messages",
"list_discussions",
"list_projects",
]

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"""Discussion service for MoAI.
Provides CRUD operations for discussions, rounds, and messages.
"""
from sqlalchemy import select
from sqlalchemy.orm import selectinload
from moai.core.database import get_session
from moai.core.models import (
Discussion,
DiscussionStatus,
DiscussionType,
Message,
Round,
RoundType,
)
async def create_discussion(
project_id: str,
question: str,
discussion_type: DiscussionType,
) -> Discussion:
"""Create a new discussion within a project.
Args:
project_id: The parent project's UUID.
question: The question or topic being discussed.
discussion_type: Whether this is OPEN or DISCUSS mode.
Returns:
The created Discussion object.
"""
async with get_session() as session:
discussion = Discussion(
project_id=project_id,
question=question,
type=discussion_type,
)
session.add(discussion)
await session.flush()
await session.refresh(discussion)
return discussion
async def get_discussion(discussion_id: str) -> Discussion | None:
"""Get a discussion by ID with eager loading of rounds and messages.
Args:
discussion_id: The discussion's UUID.
Returns:
The Discussion object if found, None otherwise.
"""
async with get_session() as session:
result = await session.execute(
select(Discussion)
.where(Discussion.id == discussion_id)
.options(
selectinload(Discussion.rounds).selectinload(Round.messages),
selectinload(Discussion.consensus),
)
)
return result.scalar_one_or_none()
async def get_active_discussion(project_id: str) -> Discussion | None:
"""Get the active discussion for a project.
Args:
project_id: The project's UUID.
Returns:
The active Discussion object if found, None otherwise.
"""
async with get_session() as session:
result = await session.execute(
select(Discussion)
.where(Discussion.project_id == project_id)
.where(Discussion.status == DiscussionStatus.ACTIVE)
.options(
selectinload(Discussion.rounds).selectinload(Round.messages),
)
)
return result.scalar_one_or_none()
async def list_discussions(project_id: str) -> list[Discussion]:
"""List all discussions for a project ordered by creation date (newest first).
Args:
project_id: The project's UUID.
Returns:
List of Discussion objects.
"""
async with get_session() as session:
result = await session.execute(
select(Discussion)
.where(Discussion.project_id == project_id)
.order_by(Discussion.created_at.desc())
)
return list(result.scalars().all())
async def complete_discussion(discussion_id: str) -> Discussion | None:
"""Mark a discussion as completed.
Args:
discussion_id: The discussion's UUID.
Returns:
The updated Discussion object if found, None otherwise.
"""
async with get_session() as session:
result = await session.execute(select(Discussion).where(Discussion.id == discussion_id))
discussion = result.scalar_one_or_none()
if discussion is None:
return None
discussion.status = DiscussionStatus.COMPLETED
await session.flush()
await session.refresh(discussion)
return discussion
async def create_round(
discussion_id: str,
round_number: int,
round_type: RoundType,
) -> Round:
"""Create a new round within a discussion.
Args:
discussion_id: The parent discussion's UUID.
round_number: Sequential round number within the discussion.
round_type: Whether this round is PARALLEL or SEQUENTIAL.
Returns:
The created Round object.
"""
async with get_session() as session:
round_ = Round(
discussion_id=discussion_id,
round_number=round_number,
type=round_type,
)
session.add(round_)
await session.flush()
await session.refresh(round_)
return round_
async def get_current_round(discussion_id: str) -> Round | None:
"""Get the current (most recent) round for a discussion.
Args:
discussion_id: The discussion's UUID.
Returns:
The most recent Round object if found, None otherwise.
"""
async with get_session() as session:
result = await session.execute(
select(Round)
.where(Round.discussion_id == discussion_id)
.order_by(Round.round_number.desc())
.limit(1)
.options(selectinload(Round.messages))
)
return result.scalar_one_or_none()
async def create_message(
round_id: str,
model: str,
content: str,
is_direct: bool = False,
) -> Message:
"""Create a new message within a round.
Args:
round_id: The parent round's UUID.
model: AI model identifier (e.g., "claude", "gpt", "gemini").
content: The message content.
is_direct: True if this was a direct @mention to this model.
Returns:
The created Message object.
"""
async with get_session() as session:
message = Message(
round_id=round_id,
model=model,
content=content,
is_direct=is_direct,
)
session.add(message)
await session.flush()
await session.refresh(message)
return message
async def get_round_messages(round_id: str) -> list[Message]:
"""Get all messages for a round ordered by timestamp.
Args:
round_id: The round's UUID.
Returns:
List of Message objects ordered by timestamp.
"""
async with get_session() as session:
result = await session.execute(
select(Message).where(Message.round_id == round_id).order_by(Message.timestamp)
)
return list(result.scalars().all())

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"""Project service for MoAI.
Provides CRUD operations for projects.
"""
from sqlalchemy import select
from moai.core.database import get_session
from moai.core.models import Project
DEFAULT_MODELS = ["claude", "gpt", "gemini"]
async def list_projects() -> list[Project]:
"""List all projects ordered by creation date (newest first).
Returns:
List of Project objects.
"""
async with get_session() as session:
result = await session.execute(select(Project).order_by(Project.created_at.desc()))
return list(result.scalars().all())
async def create_project(name: str, models: list[str] | None = None) -> Project:
"""Create a new project.
Args:
name: Human-readable project name.
models: List of AI model identifiers. Defaults to ["claude", "gpt", "gemini"].
Returns:
The created Project object.
"""
if models is None:
models = DEFAULT_MODELS.copy()
async with get_session() as session:
project = Project(name=name, models=models)
session.add(project)
await session.flush()
await session.refresh(project)
return project
async def get_project(project_id: str) -> Project | None:
"""Get a project by ID.
Args:
project_id: The project's UUID.
Returns:
The Project object if found, None otherwise.
"""
async with get_session() as session:
result = await session.execute(select(Project).where(Project.id == project_id))
return result.scalar_one_or_none()
async def get_project_by_name(name: str) -> Project | None:
"""Get a project by name (case-insensitive).
Args:
name: The project name to search for.
Returns:
The Project object if found, None otherwise.
"""
async with get_session() as session:
result = await session.execute(select(Project).where(Project.name.ilike(name)))
return result.scalar_one_or_none()
async def update_project_models(project_id: str, models: list[str]) -> Project | None:
"""Update a project's models list.
Args:
project_id: The project's UUID.
models: List of AI model identifiers.
Returns:
The updated Project object if found, None otherwise.
"""
async with get_session() as session:
result = await session.execute(select(Project).where(Project.id == project_id))
project = result.scalar_one_or_none()
if project is None:
return None
project.models = models
await session.flush()
await session.refresh(project)
return project
async def delete_project(project_id: str) -> bool:
"""Delete a project by ID.
Cascade delete will handle discussions/rounds/messages via SQLAlchemy relationship config.
Args:
project_id: The project's UUID.
Returns:
True if deleted, False if not found.
"""
async with get_session() as session:
result = await session.execute(select(Project).where(Project.id == project_id))
project = result.scalar_one_or_none()
if project is None:
return False
await session.delete(project)
return True

4
tests/__init__.py Normal file
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"""Test suite for MoAI.
Contains unit tests, integration tests, and fixtures for the MoAI platform.
"""

215
tests/test_models.py Normal file
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"""Tests for MoAI SQLAlchemy models.
Tests verify model creation, relationships, and cascade delete behavior
using an in-memory SQLite database.
"""
import pytest
from sqlalchemy import select
from moai.core.database import close_db, create_tables, get_session, init_db
from moai.core.models import (
Consensus,
Discussion,
DiscussionStatus,
DiscussionType,
Message,
Project,
Round,
RoundType,
)
@pytest.fixture
async def db_session():
"""Provide a database session with in-memory SQLite for testing."""
init_db("sqlite+aiosqlite:///:memory:")
await create_tables()
async with get_session() as session:
yield session
await close_db()
async def test_create_project(db_session):
"""Test creating a project with basic attributes."""
project = Project(name="Test Project", models=["claude", "gpt"])
db_session.add(project)
await db_session.flush()
assert project.id is not None
assert len(project.id) == 36 # UUID format
assert project.name == "Test Project"
assert project.models == ["claude", "gpt"]
assert project.created_at is not None
assert project.updated_at is not None
async def test_create_discussion_with_project(db_session):
"""Test creating a discussion linked to a project."""
project = Project(name="Test Project", models=["claude"])
db_session.add(project)
await db_session.flush()
discussion = Discussion(
project_id=project.id,
question="What is the meaning of life?",
type=DiscussionType.OPEN,
)
db_session.add(discussion)
await db_session.flush()
assert discussion.id is not None
assert discussion.project_id == project.id
assert discussion.status == DiscussionStatus.ACTIVE
assert discussion.type == DiscussionType.OPEN
# Verify relationship
await db_session.refresh(project, ["discussions"])
assert len(project.discussions) == 1
assert project.discussions[0].id == discussion.id
async def test_create_full_discussion_chain(db_session):
"""Test creating a full chain: Project -> Discussion -> Round -> Message."""
# Create project
project = Project(name="Full Chain Test", models=["claude", "gpt", "gemini"])
db_session.add(project)
await db_session.flush()
# Create discussion
discussion = Discussion(
project_id=project.id,
question="How should we approach this problem?",
type=DiscussionType.DISCUSS,
)
db_session.add(discussion)
await db_session.flush()
# Create round
round_ = Round(
discussion_id=discussion.id,
round_number=1,
type=RoundType.SEQUENTIAL,
)
db_session.add(round_)
await db_session.flush()
# Create messages
message1 = Message(
round_id=round_.id,
model="claude",
content="I think we should consider option A.",
is_direct=False,
)
message2 = Message(
round_id=round_.id,
model="gpt",
content="I agree with Claude, option A seems best.",
is_direct=False,
)
db_session.add_all([message1, message2])
await db_session.flush()
# Verify all relationships
await db_session.refresh(round_, ["messages"])
assert len(round_.messages) == 2
assert round_.discussion_id == discussion.id
await db_session.refresh(discussion, ["rounds"])
assert len(discussion.rounds) == 1
assert discussion.project_id == project.id
await db_session.refresh(project, ["discussions"])
assert len(project.discussions) == 1
async def test_create_consensus(db_session):
"""Test creating a consensus for a discussion."""
project = Project(name="Consensus Test", models=["claude"])
db_session.add(project)
await db_session.flush()
discussion = Discussion(
project_id=project.id,
question="What should we do?",
type=DiscussionType.OPEN,
)
db_session.add(discussion)
await db_session.flush()
consensus = Consensus(
discussion_id=discussion.id,
agreements=["We should prioritize user experience", "Performance is important"],
disagreements=[{"topic": "Timeline", "positions": {"claude": "2 weeks", "gpt": "3 weeks"}}],
generated_by="claude",
)
db_session.add(consensus)
await db_session.flush()
# Verify consensus attributes
assert consensus.id is not None
assert consensus.discussion_id == discussion.id
assert len(consensus.agreements) == 2
assert len(consensus.disagreements) == 1
assert consensus.generated_by == "claude"
assert consensus.generated_at is not None
# Verify relationship
await db_session.refresh(discussion, ["consensus"])
assert discussion.consensus is not None
assert discussion.consensus.id == consensus.id
async def test_project_cascade_delete(db_session):
"""Test that deleting a project cascades to all children."""
# Create full hierarchy
project = Project(name="Cascade Test", models=["claude"])
db_session.add(project)
await db_session.flush()
discussion = Discussion(
project_id=project.id,
question="Test question",
type=DiscussionType.OPEN,
)
db_session.add(discussion)
await db_session.flush()
round_ = Round(
discussion_id=discussion.id,
round_number=1,
type=RoundType.PARALLEL,
)
db_session.add(round_)
await db_session.flush()
message = Message(
round_id=round_.id,
model="claude",
content="Test message",
)
db_session.add(message)
await db_session.flush()
# Store IDs for verification
project_id = project.id
discussion_id = discussion.id
round_id = round_.id
message_id = message.id
# Delete project
await db_session.delete(project)
await db_session.flush()
# Verify all children are deleted (cascade)
result = await db_session.execute(select(Project).where(Project.id == project_id))
assert result.scalar_one_or_none() is None
result = await db_session.execute(select(Discussion).where(Discussion.id == discussion_id))
assert result.scalar_one_or_none() is None
result = await db_session.execute(select(Round).where(Round.id == round_id))
assert result.scalar_one_or_none() is None
result = await db_session.execute(select(Message).where(Message.id == message_id))
assert result.scalar_one_or_none() is None