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*Botbot, your not so friendly Bot*
A Matrix chat bot that listens to specified rooms, records conversations, leverages OpenAI for AI-driven summaries, and assists with answering questions.
**Botbot** aimsto be a multiservice chat assistant for [Matrix](https://matrix.org) that captures room conversations, stores them, and uses LargeLanguageModels to provide concise summaries, answer followup questions, and surface action points.
## Objectives
### Roadmap / Aspirational goals
- Record message history on rooms its participating.
- Create discussion summaries to capture actionable items, deadlines, and decisions on subjects discussed on those rooms.
- Use collected knoledge to answer questions placed by participants in discussions that are left unansewerd after some time, and also when its direclty addressed using it's @handle
* Persistent conversation store (PostgreSQL) for longrange context.
* Pluggable LLM backends (local models, Ollama, etc.).
* Structured meeting summaries with actionitems and deadlines.
* Additional chat frontends (Telegram, WhatsApp, …).
also,
---
- Support additional AI backends beyond OpenAI (e.g., local LLMs, alternative APIs).
- Possibly support other Chat services beyownd Matrix like Telegram, Teams or Whatsapp.
## Architecture
```mermaid
flowchart LR
MS["matrix_service<br/>(Python & nio)"]
AI["ai_service<br/>(FastAPI)"]
Redis["Redis<br/>Deduplicates replies / guarantees idempotency"]
MS -- "HTTP (Bearer token)" --> AI
AI -- "Matrix Events" --> MS
MS -.-> Redis
AI -.-> Redis
```
| Component | Image / EntryPoint | Purpose |
| ------------------- | ------------------------------------- | ------------------------------------------------------------------------------------- |
| **matrix\_service** | `python matrix_service/main.py` | Listens to Matrix rooms, forwards each message to `ai_service`, posts the reply back. |
| **ai\_service** | `python ai_service/main.py` (FastAPI) | Builds a prompt, calls the configured LLM (OpenAI today), caches the reply in Redis. |
| **redis** | `redis:7` | Reply cache & simple key/value store. |
The services talk to each other over the internal Docker network. Authentication between them is a static bearer token (`AI_HANDLER_TOKEN`).
---
## Current Features
- **Auto-join Rooms**: Automatically joins rooms when invited.
- **Message Callbacks**: Responds to basic commands:
- `!ping``Pong!`
- `hello botbot` → Greeting
* **AutoJoin on Invite** secure E2EE join including device verification.
* **Stateless AI handler** FastAPI endpoint `/api/v1/message` receiving a JSON payload.
* **Idempotent replies** duplicate Matrix events reuse the cached answer.
## Prerequisites
- Docker & Docker Compose (or Python 3.8+)
- A Matrix account for the bot
- OpenAI API key
---
## Installation
1. **Clone the repository**
## Quick Start (development)
```bash
git clone https://gitea.alluna.pt/jfig/botbot.git
cd botbot
# clone & cd
$ git clone https://gitea.alluna.pt/jfig/botbot.git
$ cd botbot
# copy environment template
$ cp .env.example .env
# edit .env with your homeserver, credentials and OpenAI key
# start everything (hotreload volumes mounted)
$ docker compose up --build
```
2. **Configure environment variables**
The default compose file launches three containers:
Copy the example file and edit it:
* `matrix_service` watches your rooms
* `ai_service` handles AI prompts
* `redis` reply cache
Stop with <kbd>CtrlC</kbd> or `docker compose down`.
### Production (single image per service)
Build once, then deploy with your orchestrator of choice:
```bash
cp .env.example .env
$ docker compose -f docker-compose.yml --profile prod build
$ docker compose -f docker-compose.yml --profile prod up -d
```
Then open `.env` and set:
---
```ini
LOG_LEVEL=INFO
HOMESERVER_URL=https://matrix.org
USER_ID=@botbot_user:matrix.org
PASSWORD=your_matrix_password
OPENAI_API_KEY=your_openai_api_key
## Configuration
All settings are environment variables. The table below reflects the current codebase (commit `ae27a2c`).
| Variable | Service | Default | Description |
| ------------------------------ | --------------- | ------------------------ | ---------------------------------------- |
| `LOG_LEVEL` | both | `INFO` | Python logging level. |
| `MATRIX_HOMESERVER_URL` | matrix\_service | |  Matrix homeserver base URL. |
| `MATRIX_USER_ID` | matrix\_service | |    Full user id of the bot. |
| `MATRIX_PASSWORD` | matrix\_service | |    Password for the bot account. |
| `MATRIX_LOGIN_TRIES` | matrix\_service |  `5` |    Number of login attempts before exit. |
| `MATRIX_LOGIN_DELAY_INCREMENT` | matrix\_service |  `5` | Seconds added per retry. |
| `AI_HANDLER_URL` | matrix\_service | `http://ai_service:8000` | Where to POST messages. |
| `AI_HANDLER_TOKEN` | both | | Shared bearer token (keep secret). |
| `OPENAI_API_KEY` | ai\_service | | Key for `openai` Python SDK. |
| `REDIS_URL` | ai\_service | `redis://redis:6379` | Connection string used by `redis-py`. |
---
## API (ai\_service)
```http
POST /api/v1/message
Authorization: Bearer <AI_HANDLER_TOKEN>
Content-Type: application/json
{
"roomId": "!foo:matrix.org",
"userId": "@alice:matrix.org",
"eventId": "$abc123",
"serverTimestamp": 1714821630123,
"content": "Hello there"
}
```
## Usage
Returns `{"reply": "Hello Alice!"}` or HTTP 401/500 on error.
### Using Docker Compose (development/hot-reload)
```bash
docker-compose up --build
```
### Building and Running Manually (production)
```bash
# Build container
docker build -t botbot .
# Run container
docker run -d --env-file .env \
-v matrix_data:/app/data \
--restart unless-stopped \
botbot
```
## Configuration Options
- `LOG_LEVEL`: One of `CRITICAL`, `ERROR`, `WARNING`, `INFO`, `DEBUG`, `NOTSET`.
- `HOMESERVER_URL`: Matrix homeserver endpoint (e.g., `https://matrix.org`).
- `USER_ID`: Bot's full Matrix user ID (e.g., `@botbot_user:matrix.org`).
- `PASSWORD`: Password for the bot account.
- `OPENAI_API_KEY`: API key for OpenAI usage.
## How It Works
1. **Startup**: Loads environment and logs into the Matrix homeserver.
2. **Callbacks**:
- `message_callback`: Handles text messages and triggers AI logic.
- `invite_cb`: Joins rooms on invitation.
3. **AI Integration**: Future development will:
- Pull recent chat history.
- Call OpenAI endpoints to generate summaries or answers.
---
## Contributing
1. Fork the repository.
2. Create a feature branch (`git checkout -b feature/xyz`).
3. Commit changes and push (`git push origin feature/xyz`).
4. Open a pull request with a description of your changes.
Pull requests are welcome! Please open an issue first to discuss what you want to change. All source code is formatted with **ruff** / **black** run `pre-commit run --all-files` before pushing.
---
## License
This project is licensed under the [MIT License](LICENSE).
[MIT](LICENSE)