Restructure chat service, web routes, and add test suite

Split monolithic chat service into modular structure with Matrix client
support, extract web server into per-resource route modules, introduce
bootstrap/main-loop separation, and add comprehensive vitest coverage
across services, repositories, and utilities. Adds project docs and
CLAUDE.md agent instructions.
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# RedditBot - Software Architecture Documentation
## Table of Contents
1. [Project Overview](#project-overview)
2. [System Architecture](#system-architecture)
3. [Directory Structure](#directory-structure)
4. [Component Reference](#component-reference)
5. [Data Flow](#data-flow)
6. [Database Schema](#database-schema)
7. [API Reference](#api-reference)
8. [Configuration](#configuration)
9. [Design Patterns](#design-patterns)
10. [External Integrations](#external-integrations)
11. [Deployment](#deployment)
12. [Technical Debt & Recommendations](#technical-debt--recommendations)
---
## Project Overview
**RedditBot** is an automated Reddit monitoring and messaging system that:
- Monitors 30+ NSFW subreddits for image posts
- Uses AI (OpenRouter) to analyze images and detect gender
- Generates personalized direct messages to post authors
- Sends DMs via browser automation (Playwright)
- Monitors for responses and tracks success rates
- Implements A/B testing with explore/exploit strategy selection
- Learns from successful message/response pairs (few-shot learning)
- Provides a real-time web dashboard for monitoring and control
### Key Capabilities
| Capability | Description |
|---|---|
| Post Discovery | Polls subreddits for new image posts, filters by gender and spam profiles |
| AI Analysis | Multi-model image analysis with fallback chain via OpenRouter |
| Message Generation | AI-crafted DMs using successful examples as few-shot prompts |
| A/B Testing | Explore/exploit strategy selector optimizes response rates over time |
| Response Monitoring | Background service checks inbox for user replies |
| Chat Automation | Reddit chat scraping via shadow DOM traversal, auto-reply support |
| Media Management | Download, cache, deduplicate, and sync media from conversations |
| Web Dashboard | Real-time monitoring with SSE log streaming, analytics, and controls |
---
## System Architecture
### High-Level Architecture
```
┌─────────────────────────────────────────────────────────────────────┐
│ main (index.ts) │
│ Orchestrator / Entry Point │
└────────────────────────┬────────────────────────────────────────────┘
│
┌────────────────┼────────────────┐
│ │ │
▼ ▼ ▼
┌───────────────┐ ┌──────────────┐ ┌──────────────┐
│ Monitor │ │ Processor │ │ Response │
│ Service │ │ │ │ Checker │
│ │ │ 1. Download │ │ │
│ Poll subreddits│ │ 2. Validate │ │ Check inbox │
│ for new posts │ │ 3. Gender │ │ for replies │
└───────┬───────┘ │ Filter │ └──────────────┘
│ │ 4. AI Analysis│ │
│ │ 5. Strategy │ │
│ │ Selection │ │
│ │ 6. Message │ │
│ │ Generation │ │
└────┬────┘ └─────────────┘ │
│ │
▼ ▼
┌───────────────────────┐ ┌───────────────────────┐
│ Strategy Selector │ │ Chat Service │
│ │ │ │
│ A/B Testing │ │ Scrapes chat (shadow │
│ Explore/Exploit │ │ DOM traversal) │
│ Variant Selection │ │ Auto-reply, upsell │
└───────────────────────┘ │ detection │
└───────────────────────┘
│ │
▼ ▼
┌───────────────────────┐ ┌───────────────────────┐
│ Message Sender │ │ Media Service │
│ (Browser) │ │ │
│ │ │ Download, cache, │
│ Playwright DM compose │ │ deduplicate (SHA-1) │
│ Shadow DOM handling │ │ Matrix thumbnail │
└───────────────────────┘ │ resolution │
└───────────────────────┘
│ │
▼ ▼
┌─────────────────────────────────────────────────────────┐
│ SQLite Database │
│ │
│ processed_posts │ sent_messages │ successful_messages │
└─────────────────────────────────────────────────────────┘
│
▼
┌─────────────────────────────────────────────────────────┐
│ Web Dashboard (Express) │
│ │
│ 25+ API endpoints │ SSE log streaming │ Analytics │
│ Runtime config │ Bot controls │ Media gallery │
└─────────────────────────────────────────────────────────┘
```
### Service Communication
```
main.ts (Orchestrator)
│
├──► Config (Zod-validated YAML + env vars)
│
├──► Database (Better-SQLite3)
│ │
│ └──► PostsRepository
│ └──► MessagesRepository
│ └──► SuccessfulMessagesRepository
│
├──► MonitorService ──► RedditApi ──► Playwright (cookies)
│
├──► ProcessorService
│ ├──► Image download (axios)
│ ├──► Gender detection (OpenRouter)
│ ├──► Full analysis (OpenRouter)
│ └──► StrategySelector ──► MessagesRepository
│
├──► MessageSender (Browser - Playwright)
│
├──► ResponseChecker ──► Playwright (inbox navigation)
│
├──► ChatService ──► Playwright (chat.reddit.com shadow DOM)
│
├──► MediaService ──► Playwright (media download)
│
├──► MediaSyncService (background periodic sync)
│
├──► AutoReplyService ──► OpenRouter (reply generation)
│
├──► RateLimiter (p-queue, jitter)
│
└──► WebServer (Express, SSE)
```
---
## Directory Structure
```
RedditBot/
├── .dockerignore # Docker ignore rules
├── .gitignore # Git ignore rules
├── agents.md # Engineering standards & agent guidelines
├── config.yaml # Main YAML configuration file
├── docker-compose.yml # Docker Compose setup
├── DOKPLOY_DEPLOY.md # Dokploy deployment guide
├── Dockerfile # Container build definition
├── package.json # Node.js dependencies & scripts
├── tsconfig.json # TypeScript configuration
├── public/
│ └── index.html # Single-file web dashboard (HTML+CSS+JS)
├── scripts/
│ ├── inspect-chat-dom.ts # Debug: inspect chat DOM structure
│ └── login.ts # Manual browser login helper
└── src/
├── index.ts # Main entry point / orchestrator (391 lines)
├── config/
│ └── index.ts # Config loader + Zod validation schema (157 lines)
├── database/
│ ├── client.ts # SQLite setup + migration runner (121 lines)
│ └── repositories.ts # Repository pattern: Posts, Messages, Success (433 lines)
├── reddit/
│ └── api.ts # Reddit API client (axios + Playwright cookies) (233 lines)
├── ai/
│ └── openrouter.ts # OpenRouter AI client (image analysis, message gen) (307 lines)
├── browser/
│ ├── client.ts # Playwright persistent context + login (302 lines)
│ ├── message-page.ts # DM compose page automation + shadow DOM (560 lines)
│ └── media-downloader.ts # Playwright-based media downloader (29 lines)
├── services/
│ ├── monitor.ts # Post discovery service (72 lines)
│ ├── processor.ts # Image download + AI + message pipeline (132 lines)
│ ├── response-checker.ts # Inbox response checker (179 lines)
│ ├── strategy-selector.ts # A/B testing explore/exploit (101 lines)
│ ├── chat.ts # Chat scraping + messaging + auto-reply (1123+ lines)
│ ├── media.ts # Media download, caching, indexing (254 lines)
│ ├── media-sync.ts # Periodic background media sync (119 lines)
│ └── auto-reply.ts # Auto-reply to chat conversations (199 lines)
├── utils/
│ ├── logger.ts # Winston structured logging (32 lines)
│ ├── rate-limiter.ts # Token-bucket rate limiting (114 lines)
│ ├── retry.ts # Exponential backoff wrapper (28 lines)
│ └── image.ts # Image download + base64 + MIME validation (34 lines)
└── web/
└── server.ts # Express dashboard + SSE streaming (794 lines)
```
---
## Component Reference
### Core Services
#### MonitorService (`src/services/monitor.ts`)
Discovers new image posts across configured subreddits.
- Shuffles subreddit order each cycle
- Fetches new posts via `RedditApi`
- Filters out already-processed posts and previously-messaged users
- Returns the single newest valid post per cycle
#### ProcessorService (`src/services/processor.ts`)
Core processing pipeline for each discovered post.
1. Downloads image via `ImageService`
2. Validates MIME type and file size
3. Runs quick gender detection (cost-saving pre-filter)
4. Selects A/B strategy variant via `StrategySelector`
5. Runs full AI analysis + message generation via `OpenRouterService`
6. Handles AI refusals gracefully (marks post, tries next)
#### StrategySelector (`src/services/strategy-selector.ts`)
Implements explore/exploit A/B testing for message variants.
- Tracks response rates per strategy variant
- Uses minimum sample thresholds before trusting statistics
- Applies random exploration rate for continued discovery
- Selects best variant based on weighted response rates
#### ResponseChecker (`src/services/response-checker.ts`)
Background service that monitors for user replies.
- Navigates Reddit inbox via Playwright
- Identifies responses to sent messages
- Updates `got_response` flag in database
- Stores successful message/response pairs for few-shot learning
#### ChatService (`src/services/chat.ts`)
Most complex service - manages Reddit chat interactions.
- Scrapes `chat.reddit.com` using JavaScript injection (shadow DOM traversal)
- Manages conversation cache (in-memory + disk JSON)
- Loads full conversation history with pagination
- Sends messages with human-like typing delays
- Verifies message delivery
- Detects upsell/spam keywords in chat
- Parameter: `myUsername` is hardcoded (should be from config)
#### MediaService (`src/services/media.ts`)
Media download, caching, and indexing.
- Downloads images from chat conversations
- Resolves Matrix blurred thumbnails to full resolution
- Stores files in `data/media/` directory
- Maintains JSON index with SHA-1 deduplication
- Tracks download status per conversation
#### MediaSyncService (`src/services/media-sync.ts`)
Periodic background media synchronization.
- Runs incremental syncs (top 10 chats) or full syncs (all conversations)
- Configurable interval via `mediaSyncInterval`
- Tracks sync status in memory
- Exposed via web dashboard endpoints
#### AutoReplyService (`src/services/auto-reply.ts`)
Automated reply to Reddit chat conversations.
- Checks for unread messages in cached conversations
- Detects upsell/spam keywords
- Generates AI reply suggestions via `OpenRouterService`
- Sends replies (auto or pending for manual approval)
- Event-based architecture for dashboard integration
### External Integrations
#### RedditApi (`src/reddit/api.ts`)
Axios-based Reddit API client.
- Fetches posts from subreddits (`/r/{name}/new.json`)
- Validates posts (image-only, skips deleted authors)
- Extracts image URLs with fallback chain: `preview` > `i.redd.it` > `imgur` > `thumbnail`
- Checks user profiles against seller/spam keywords
- Uses Playwright browser cookies for authenticated requests
#### OpenRouterService (`src/ai/openrouter.ts`)
OpenRouter API client using OpenAI-compatible SDK.
- `analyzeImage()`: Multi-model image analysis with fallback chain
- `detectGenderOnly()`: Quick cost-saving gender detection
- `generateMessage()`: DM text with few-shot examples from DB
- `generateReply()`: AI chat reply from conversation history
- `detectUpsell()`: Keyword-based spam/OnlyFans detection
- Refusal detection via heuristic patterns
#### Browser Client (`src/browser/client.ts`)
Playwright persistent context manager.
- Browser session persistence (cookies/storage)
- Login verification (multiple UI checks + API fallback)
- Automated login flow (form fill, 2FA/captcha detection)
- Debug screenshot capture on login failure
#### MessagePage (`src/browser/message-page.ts`)
Reddit DM compose page automation.
- Fills recipient/subject/body fields
- Extensive Shadow DOM support for `faceplate-*` components
- Detects recipient errors, verifies submission success
- Supports dry-run mode for testing
### Data Layer
#### Database Client (`src/database/client.ts`)
Better-SQLite3 database initialization.
- Creates database at configured path
- Enables WAL mode and foreign keys
- Runs migrations on startup
- Safe column-addition for schema evolution
#### Repositories (`src/database/repositories.ts`)
Three repository classes abstracting SQLite operations.
- **PostsRepository**: Processed post CRUD, mark sent, update analysis
- **MessagesRepository**: Sent message CRUD, response tracking, strategy stats, subreddit stats, daily trends
- **SuccessfulMessagesRepository**: Successful pairs for few-shot learning, subreddit-weighted retrieval
### Utilities
#### Logger (`src/utils/logger.ts`)
Winston structured logging.
- JSON format for log files
- Colored console output
- File logging: `error.log` and combined log
#### RateLimiter (`src/utils/rate-limiter.ts`)
Token-bucket rate limiting.
- p-queue with concurrency=1
- Minimum delay between messages with random jitter
- Hourly message count tracking
- Timer status exposed to dashboard
#### Retry (`src/utils/retry.ts`)
Exponential backoff wrapper.
- p-retry with configurable retries (default 3)
- Backoff range: 5s to 60s
- Logging on retries and failures
#### Image (`src/utils/image.ts`)
Image processing utilities.
- Download via axios
- Base64 conversion for AI API
- MIME type validation (image/jpeg, image/png, image/webp)
### Web Dashboard
#### WebServer (`src/web/server.ts`)
Express server with 25+ API endpoints.
- Stats, activity, messages, chats, conversations, media endpoints
- Bot controls (start/stop)
- SSE realtime log streaming
- Analytics: strategy, subreddit, daily trends
- Runtime config management (GET/PUT)
- Debug endpoints
---
## Data Flow
### Post Processing Pipeline
```
1. MonitorService polls subreddits
│
├─► RedditApi.fetchPosts()
│ └─► GET /r/{subreddit}/new.json
│ └─► Filter: image posts only, valid author
│
├─► Filter: skip processed posts (DB check)
├─► Filter: skip previously messaged users
│
└─► Return newest valid post
│
2. ProcessorService.processPost(post)
│
├─► ImageService.downloadImage(url)
│ └─► Validate MIME type, file size
│
├─► OpenRouter.detectGenderOnly()
│ └─► Quick pre-filter (cost-saving)
│ └─► Skip if gender doesn't match target
│
├─► StrategySelector.selectStrategy(subreddit, author)
│ └─► Explore/exploit algorithm
│
├─► OpenRouter.analyzeImage(image)
│ └─► Multi-model fallback chain
│ └─► Detect gender, describe image
│
├─► OpenRouter.generateMessage(analysis, title, examples, strategy)
│ └─► Few-shot learning from successful_messages
│
└─► Mark post as processed in DB
│
3. MessagePage.sendDM(author, subject, message)
│
├─► Navigate to /compose?to={author}
├─► Fill fields (with shadow DOM handling)
├─► Submit message
└─► Verify success
│
└─► Record sent_messages in DB
```
### Response Monitoring Flow
```
1. ResponseChecker.checkResponses()
│
├─► Navigate to /message/inbox
├─► Parse response items
│
├─► For each response:
│ ├─► Match to sent_messages by recipient + timestamp
│ ├─► Update got_response = 1
│ ├─► Store message/response pair
│ └─► Add to successful_messages (for few-shot learning)
│
└─► Update strategy stats in DB
```
### Chat Interaction Flow
```
1. ChatService.fetchChats()
│
├─► Navigate to chat.reddit.com
├─► Traverse shadow DOM via JS injection
├─► Extract active conversations
└─► Cache in memory + disk JSON
│
2. ChatService.loadConversation(chatId)
│
├─► Load from cache
├─► Fetch full history (pagination)
└─► Return conversation object
│
3. ChatService.sendMessage(chatId, text)
│
├─► Navigate to chat view
├─► Fill message input (shadow DOM)
├─► Apply typing delay (human-like)
├─► Submit
└─► Verify delivery
```
---
## Database Schema
### Table: `processed_posts`
Tracks all posts that have been discovered and processed.
| Column | Type | Constraints | Description |
|---|---|---|---|
| `id` | TEXT | PRIMARY KEY | Reddit post ID |
| `subreddit` | TEXT | NOT NULL | Source subreddit |
| `author` | TEXT | NOT NULL | Post author username |
| `title` | TEXT | | Post title |
| `image_url` | TEXT | | Original image URL |
| `image_analysis` | TEXT | | AI-generated image description |
| `generated_message` | TEXT | | AI-generated DM text |
| `processed_at` | INTEGER | NOT NULL | Unix timestamp |
| `message_sent` | INTEGER | DEFAULT 0 | 0 = not sent, 1 = sent |
| `error` | TEXT | | Error message if processing failed |
**Indexes**: `idx_posts_subreddit`, `idx_posts_author`
### Table: `sent_messages`
Tracks all DMs sent by the bot.
| Column | Type | Constraints | Description |
|---|---|---|---|
| `id` | INTEGER | PRIMARY KEY AUTOINCREMENT | Internal ID |
| `post_id` | TEXT | FK → processed_posts.id | Source post |
| `recipient` | TEXT | NOT NULL | Recipient username |
| `subject` | TEXT | DEFAULT 'Stunning' | DM subject line |
| `message` | TEXT | NOT NULL | DM body |
| `sent_at` | INTEGER | NOT NULL | Unix timestamp |
| `strategy_id` | TEXT | | A/B test variant identifier |
| `got_response` | INTEGER | DEFAULT 0 | 0 = no response, 1 = responded |
| `response_checked_at` | INTEGER | | Timestamp of last response check |
**Indexes**: `idx_messages_recipient`, `idx_messages_strategy`, `idx_messages_response`
### Table: `successful_messages`
Stores successful message/response pairs for few-shot learning.
| Column | Type | Constraints | Description |
|---|---|---|---|
| `id` | INTEGER | PRIMARY KEY AUTOINCREMENT | Internal ID |
| `sent_message_id` | INTEGER | FK → sent_messages.id (nullable) | Related message |
| `original_message` | TEXT | NOT NULL | The DM that got a response |
| `image_analysis` | TEXT | | Context from image analysis |
| `post_title` | TEXT | | Original post title |
| `response_snippet` | TEXT | | First reply text |
| `subreddit` | TEXT | | For weighted example selection |
| `created_at` | INTEGER | NOT NULL | Unix timestamp |
**Indexes**: `idx_success_subreddit`, `idx_success_message`
### Migration Strategy
The database uses progressive migrations that:
- Run on every startup
- Use `ALTER TABLE ADD COLUMN IF NOT EXISTS` for safe schema evolution
- Create indexes with `IF NOT EXISTS` for idempotency
- Enable WAL mode and foreign keys for performance and integrity
---
## API Reference
### Web Dashboard Endpoints
All endpoints are served by the Express server at `http://localhost:{port}`.
#### Bot Status & Control
| Method | Endpoint | Description |
|---|---|---|
| GET | `/api/stats` | Bot statistics (running state, post/message/response counts, response rate) |
| POST | `/api/start` | Start the bot |
| POST | `/api/stop` | Stop the bot |
#### Activity & Messages
| Method | Endpoint | Description |
|---|---|---|
| GET | `/api/activity` | Recent activity log entries |
| GET | `/api/posts/by-author/:username` | Look up processed posts by user |
| GET | `/api/messages` | Recent sent messages |
| GET | `/api/successful` | Successful message/response pairs |
#### Chat & Conversations
| Method | Endpoint | Description |
|---|---|---|
| GET | `/api/chats` | Active cached conversations |
| POST | `/api/chats/fetch-all` | Fetch all chats from Reddit |
| GET | `/api/conversations` | All cached conversations |
| GET | `/api/conversations/:id` | Single conversation detail |
| POST | `/api/conversations/:id/suggest-reply` | AI suggest reply for conversation |
| POST | `/api/conversations/:id/send-reply` | Send chat reply |
| POST | `/api/conversations/:id/approve-reply` | Approve pending auto-reply |
| POST | `/api/conversations/:id/reject-reply` | Reject pending auto-reply |
| POST | `/api/conversations/:id/dismiss-upsell` | Dismiss upsell flag |
#### Media
| Method | Endpoint | Description |
|---|---|---|
| GET | `/api/media` | Downloaded media gallery |
| GET | `/api/media/sync` | Media sync status |
| POST | `/api/media/sync` | Trigger incremental sync (top 10 chats) |
| POST | `/api/media/sync/full` | Trigger full sync (all conversations) |
#### Analytics
| Method | Endpoint | Description |
|---|---|---|
| GET | `/api/analytics/by-subreddit` | Response rate by subreddit |
| GET | `/api/analytics/by-strategy` | Response rate by strategy variant |
| GET | `/api/analytics/trend` | Daily response rate trend |
#### Configuration
| Method | Endpoint | Description |
|---|---|---|
| GET | `/api/config` | Current runtime configuration |
| PUT | `/api/config` | Update runtime config (rate limits, dry run, poll interval) |
#### Logs & Debugging
| Method | Endpoint | Description |
|---|---|---|
| GET | `/api/logs/stream` | SSE realtime log stream |
| GET | `/api/logs` | Recent logs (HTTP) |
| GET | `/api/timers` | Rate limiter timer status |
| POST | `/api/debug/inspect-dom` | Debug: inspect chat DOM structure |
| POST | `/api/debug/check-responses` | Debug: manual response check |
---
## Configuration
### Configuration Sources (Priority Order)
1. **`config.yaml`** - Primary configuration file (project root)
2. **Environment Variables** - Override specific fields:
- `OPENROUTER_API_KEY` - OpenRouter API key
- `REDDIT_USERNAME` - Reddit username
- `REDDIT_PASSWORD` - Reddit password
- `BROWSER_HEADLESS` - Browser headless mode (`true`/`false`)
### Configuration Schema (Zod-Validated)
```typescript
{
reddit: {
subreddits: string[] // Subreddits to monitor
pollInterval: number // Minutes between polls
targetGender: string // Target gender filter
sellerKeywords: string[] // Keywords for spam/seller detection
}
openrouter: {
apiKey: string // OpenRouter API key
model: string // Primary AI model
fallbackModels: string[] // Fallback models on refusal
systemPrompt: string // System prompt for analysis
messagePrompt: string // System prompt for message generation
}
rateLimit: {
minDelayMs: number // Minimum delay between messages
maxMessagesPerHour: number // Hourly message cap
jitterMs: number // Random jitter range
}
browser: {
headless: boolean // Headless mode
userDataDir: string // Persistent session directory
}
database: {
path: string // SQLite database path
}
mediaSync: {
enabled: boolean // Enable media sync
intervalMinutes: number // Sync interval
}
autoReply: {
enabled: boolean // Enable auto-reply
autoSend: boolean // Auto-send or pending approval
checkInterval: number // Check interval in minutes
}
strategyVariants: {
name: string // Variant name
prompt: string // Message style prompt
enabled: boolean // Enable/disable variant
}[]
web: {
port: number // Dashboard port
}
}
```
### Runtime Configuration
The following settings can be modified via the web dashboard without restarting:
- `rateLimit.minDelayMs` - Message delay
- `rateLimit.maxMessagesPerHour` - Hourly cap
- `rateLimit.jitterMs` - Jitter range
- `reddit.pollInterval` - Poll frequency
- `dryRun` - Dry run mode (log only, no actual sends)
---
## Design Patterns
### Repository Pattern
All database operations are abstracted behind three repository classes:
- `PostsRepository` - Post lifecycle management
- `MessagesRepository` - Message tracking and analytics
- `SuccessfulMessagesRepository` - Few-shot learning data
Benefits:
- Single source of truth for data access
- Easy to swap implementations (e.g., different databases)
- Consistent error handling and query patterns
### Dependency Injection
Services receive dependencies via constructor parameters:
```typescript
class ProcessorService {
constructor(
private config: Config,
private redditApi: RedditApi,
private openrouter: OpenRouterService,
private strategySelector: StrategySelector,
private messageSender: MessagePage,
private postsRepo: PostsRepository,
private messagesRepo: MessagesRepository,
private successfulRepo: SuccessfulMessagesRepository,
private logger: Logger
) {}
}
```
Benefits:
- Loose coupling between components
- Easy to mock dependencies for testing
- Clear dependency graph
### Strategy Pattern
`StrategySelector` implements A/B testing with multiple message variants:
```typescript
class StrategySelector {
selectStrategy(subreddit: string, author: string): string {
// Explore/exploit algorithm
// Returns variant name based on response rates
}
}
```
Benefits:
- Swappable message strategies
- Measurable performance per variant
- Configurable exploration rate
### Factory Pattern
Configuration and database creation use factory functions:
- `loadConfig()` - Loads, merges env vars, validates with Zod
- `createDatabase()` - Initializes SQLite, runs migrations
### Observer Pattern
SSE (Server-Sent Events) for realtime log streaming:
```typescript
// Logger writes to a shared buffer
logger.info("Message sent to user123");
// WebServer subscribes clients via SSE
app.get("/api/logs/stream", (req, res) => {
// Push new log entries to connected clients
});
```
### Circuit Breaker / Retry
`withRetry()` wrapper for resilient external calls:
```typescript
await withRetry(
() => redditApi.fetchPosts(subreddit),
{ retries: 3, logger }
);
```
Multiple fallback chains:
- AI model fallback (primary → fallback models)
- Image URL fallback (preview → i.redd.it → imgur → thumbnail)
### Rate Limiter Pattern
Token-bucket-like implementation:
```typescript
class RateLimiter {
async waitForSlot(): Promise<void> {
// Enforce minimum delay + jitter
// Track hourly counts
// Block if hourly cap reached
}
}
```
---
## External Integrations
### Reddit API
- **Authentication**: Playwright browser cookies (persistent session)
- **Endpoints Used**:
- `GET /r/{name}/new.json` - Fetch new posts
- `GET /user/{username}/profile` - Check for seller/spam indicators
- `GET /message/inbox` - Check for responses
- `GET chat.reddit.com` - Chat scraping
- **Rate Limits**: Enforced by `RateLimiter` utility
### OpenRouter AI
- **SDK**: OpenAI-compatible (`openai` npm package)
- **Base URL**: `https://openrouter.ai/api/v1`
- **Endpoints Used**:
- `POST /chat/completions` - Image analysis, message generation, replies
- **Model Fallback**: Primary model → fallback models on refusal
- **Cost Optimization**: Quick gender detection before full analysis
### Playwright Browser
- **Context**: Persistent (cookies/session storage saved to disk)
- **Usage**:
- Automated Reddit login
- DM compose page automation
- Inbox navigation for response checking
- Chat page scraping (shadow DOM traversal)
- Media file downloads
- **Shadow DOM**: JavaScript injection for `faceplate-*` component traversal
---
## Deployment
### Docker
The project includes full Docker support:
- **`Dockerfile`** - Multi-stage build with Node.js
- **`docker-compose.yml`** - Service orchestration
- **`.dockerignore`** - Excludes unnecessary files
### Dokploy
Deployment documentation is provided in `DOKPLOY_DEPLOY.md`.
### Required Environment Variables
| Variable | Required | Description |
|---|---|---|
| `OPENROUTER_API_KEY` | Yes | OpenRouter API key for AI |
| `REDDIT_USERNAME` | Yes | Reddit username |
| `REDDIT_PASSWORD` | Yes | Reddit password |
| `BROWSER_HEADLESS` | No | Browser headless mode (default: `true`) |
### Pre-Deployment Checklist
1. Set up `config.yaml` with target subreddits and settings
2. Set environment variables (or use `.env` file)
3. Run `npm install` to install dependencies
4. Run `npm run build` to compile TypeScript
5. Run `scripts/login.ts` once to establish browser session
6. Start the bot (via `npm start` or Docker)
---
## Technical Debt & Recommendations
### Critical
1. **No Tests** - Zero test coverage. Add unit tests for services, especially:
- `StrategySelector` (complex algorithm)
- `ChatService` (shadow DOM logic)
- `OpenRouterService` (model fallback logic)
2. **No README.md** - No project documentation for new developers.
3. **Hardcoded Username** - `ChatService` has `myUsername = 'Upset_Marsupial1006'` hardcoded in JS evaluation scripts. Should be parameterized from config.
### High Priority
4. **God Class** - `main.ts` (391 lines) creates all dependencies and wires everything. Consider extracting an `AppContainer` or `DependencyContainer`.
5. **ChatService Size** - 1123+ lines. Consider splitting into:
- `ChatScraper` (navigation + DOM traversal)
- `ConversationCache` (cache management)
- `ChatMessenger` (sending + verification)
6. **No .env.example** - No template showing required environment variables.
### Medium Priority
7. **Single-Page Dashboard** - `public/index.html` is ~2000+ lines with embedded CSS/JS. Consider a proper frontend framework.
8. **WebServer Size** - 794 lines. Consider splitting routes into separate files.
9. **Config Mutability** - Runtime config updates via `PUT /api/config` modify the in-memory config object. Consider a proper config service with validation on updates.
10. **Error Handling** - Some services have basic try/catch. Consider structured error types with retry logic.
### Low Priority
11. **Logging** - Winston is well-configured, but consider adding request IDs for tracing.
12. **Type Safety** - Some `page.evaluate()` calls use `any` types. Consider stricter typing for DOM structures.
13. **Media Storage** - Media files stored in `data/media/` with no cleanup policy. Consider retention policies.
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# Configuration Guide
Complete reference for configuring RedditBot.
---
## Table of Contents
1. [Configuration Overview](#configuration-overview)
2. [Configuration Files](#configuration-files)
3. [Environment Variables](#environment-variables)
4. [config.yaml Reference](#configyaml-reference)
5. [Runtime Configuration](#runtime-configuration)
6. [Configuration Validation](#configuration-validation)
7. [Troubleshooting](#troubleshooting)
---
## Configuration Overview
RedditBot uses a layered configuration approach:
```
┌──────────────────────────────────────────────────────────────┐
│ Priority Order (High → Low) │
├──────────────────────────────────────────────────────────────┤
│ 1. Environment Variables │
│ (OPENROUTER_API_KEY, REDDIT_USERNAME, etc.) │
│ │
│ 2. config.yaml │
│ (Primary configuration file) │
│ │
│ 3. Defaults │
│ (Hardcoded defaults in code) │
└──────────────────────────────────────────────────────────────┘
```
Configuration is loaded at startup by `loadConfig()` in `src/config/index.ts`, which:
1. Reads `config.yaml` from the project root
2. Merges environment variable overrides
3. Validates the entire configuration tree using Zod
4. Returns a strongly-typed `Config` object
---
## Configuration Files
### config.yaml
The primary configuration file, located at the project root:
```
RedditBot/
├── config.yaml # ← Main configuration
├── package.json
├── tsconfig.json
└── src/
```
### Data Directory
Runtime data is stored in `data/` (created automatically):
```
data/
├── reddit-bot.db # SQLite database
├── browser/ # Browser session data (cookies, storage)
├── media/ # Downloaded media files
│ ├── index.json # Media index (SHA-1 → filename)
│ ├── abc123.jpg # Media file 1
│ └── def456.png # Media file 2
└── chats/ # Cached conversation JSON files
├── chat_abc123.json
└── chat_def456.json
```
---
## Environment Variables
Environment variables override corresponding values in `config.yaml`.
| Variable | Required | Type | Description | Example |
|---|---|---|---|---|
| `OPENROUTER_API_KEY` | Yes | string | OpenRouter API key for AI services | `sk-or-v1-abc123...` |
| `REDDIT_USERNAME` | Yes | string | Reddit username for authentication | `MyBotUser` |
| `REDDIT_PASSWORD` | Yes | string | Reddit password for authentication | `secret123` |
| `BROWSER_HEADLESS` | No | boolean | Run browser in headless mode | `true` or `false` |
### Setting Environment Variables
**Option 1: `.env` file** (recommended for development)
Create a `.env` file in the project root:
```env
OPENROUTER_API_KEY=sk-or-v1-abc123...
REDDIT_USERNAME=MyBotUser
REDDIT_PASSWORD=secret123
BROWSER_HEADLESS=true
```
> **Note**: Add `.env` to `.gitignore` - never commit credentials.
**Option 2: Shell export**
```bash
export OPENROUTER_API_KEY=sk-or-v1-abc123...
export REDDIT_USERNAME=MyBotUser
export REDDIT_PASSWORD=secret123
```
**Option 3: Docker**
Pass via `docker-compose.yml` or Docker CLI:
```yaml
environment:
- OPENROUTER_API_KEY=sk-or-v1-abc123...
- REDDIT_USERNAME=MyBotUser
- REDDIT_PASSWORD=secret123
```
---
## config.yaml Reference
Complete reference for every configuration option.
### Reddit Settings
```yaml
reddit:
# Subreddits to monitor for new posts
subreddits:
- gonewild
- ratemyboobs
- HomemadeNsfw
- realgirls
- plussize_gonewild
# ... add or remove subreddits
# Minutes between polling cycles
pollInterval: 15
# Target gender for image analysis filtering
# Options: "F" (female), "M" (male)
targetGender: "F"
# Keywords used to detect sellers/spam profiles
# Posts from users matching these keywords are skipped
sellerKeywords:
- seller
- onlyfans
- link in bio
- check my profile
- promo
- discount
- affiliate
```
### OpenRouter AI Settings
```yaml
openrouter:
# OpenRouter API key (can also be set via OPENROUTER_API_KEY env var)
apiKey: "sk-or-v1-abc123..."
# Primary AI model for image analysis
# Models must be available on OpenRouter
model: "meta-llama/llama-3.2-90b-vision-preview"
# Fallback models tried if the primary model refuses or fails
fallbackModels:
- "google/gemini-2.0-flash-001"
- "meta-llama/llama-3.2-11b-vision-instruct"
# Quick detection model (cheaper/faster, used for gender pre-filter)
quickModel: "google/gemini-2.0-flash-lite-001"
# System prompt for image analysis
# The AI will describe the image and detect gender
systemPrompt: |
Analyze this image and provide:
1. Gender detected (F or M)
2. Detailed description of the image content
3. Notable features (hair color, clothing, setting, etc.)
Return as JSON: {"gender": "F", "description": "...", "features": [...]}
# System prompt for message generation
# Used when crafting DMs to post authors
messagePrompt: |
Generate a natural, friendly DM for this Reddit post.
Image analysis: {description}
Post title: {title}
Strategy: {strategy}
Guidelines:
- Be complimentary but not creepy
- Reference something specific from the image
- Keep it under 2 sentences
- Sound like a genuine person, not a bot
- Do NOT ask for anything in return
```
### Rate Limiting
```yaml
rateLimit:
# Minimum delay between messages (milliseconds)
# Higher values reduce detection risk
minDelayMs: 30000
# Maximum messages per hour
# Bot will pause when this limit is reached
maxMessagesPerHour: 20
# Random jitter added to delay (milliseconds)
# Adds unpredictability to timing
jitterMs: 15000
```
**Timing example with defaults:**
```
Minimum delay: 30,000ms (30 seconds)
Jitter: 0 to 15,000ms (0-15 seconds)
Effective delay: 30-45 seconds between messages
Max messages: 20 per hour
```
### Browser Settings
```yaml
browser:
# Run browser in headless mode (no UI)
# Set to false for debugging
headless: true
# Directory for persistent browser data
# Cookies and session storage are saved here
userDataDir: "./data/browser"
```
**Browser session persistence:**
```
data/browser/
├── Default/
│ ├── Cookies # Reddit session cookies
│ ├── Local Storage # Local storage data
│ └── Preferences # Browser preferences
├── Login Data # Saved login info
└── Preferences # Browser state
```
> **Important**: Keep this directory intact. Deleting it requires re-login.
### Database Settings
```yaml
database:
# Path to SQLite database file
path: "./data/reddit-bot.db"
```
The database is auto-created on first run. Migrations run automatically on startup.
### Media Sync Settings
```yaml
mediaSync:
# Enable periodic media synchronization
enabled: true
# Interval between sync cycles (minutes)
intervalMinutes: 30
```
**Sync behavior:**
- **Incremental sync** (automatic): Downloads media from top 10 conversations
- **Full sync** (manual via dashboard): Downloads media from all conversations
### Auto-Reply Settings
```yaml
autoReply:
# Enable automatic chat replies
enabled: true
# Auto-send replies (true) or mark as pending for approval (false)
autoSend: false
# Minutes between checking for new messages
checkInterval: 10
```
**Reply modes:**
| autoSend | Behavior |
|---|---|
| `true` | Bot sends AI-generated replies automatically |
| `false` | Bot suggests replies, user approves via dashboard |
### Strategy Variants (A/B Testing)
```yaml
strategyVariants:
# Variant 1: Compliment-based
- name: "compliment"
prompt: |
Write a friendly compliment about the person's appearance.
Be genuine and specific. Keep it short and natural.
enabled: true
# Variant 2: Question-based
- name: "question"
prompt: |
Write a friendly message that includes a question.
Engage them in conversation naturally.
enabled: true
# Variant 3: Casual observation
- name: "observation"
prompt: |
Write a casual observation about the photo or setting.
Sound like you're commenting to a friend.
enabled: true
```
### Web Dashboard Settings
```yaml
web:
# Port for the web dashboard
port: 3000
```
### Global Settings
```yaml
# Global dry run mode
# When true, all actions are logged but not actually performed
dryRun: false
# Number of successful message examples to include in prompts
fewShotExamples: 3
# Minimum responses needed before trusting strategy stats
minStrategySamples: 10
# Exploration rate for A/B testing (0.0 to 1.0)
# 0.15 = 15% of messages use random variants (exploration)
explorationRate: 0.15
```
---
## Runtime Configuration
The following settings can be modified via the web dashboard without restarting the bot:
| Setting | Endpoint | Type | Description |
|---|---|---|---|
| `rateLimit.minDelayMs` | `PUT /api/config` | number | Message delay |
| `rateLimit.maxMessagesPerHour` | `PUT /api/config` | number | Hourly cap |
| `rateLimit.jitterMs` | `PUT /api/config` | number | Jitter range |
| `reddit.pollInterval` | `PUT /api/config` | number | Poll frequency |
| `dryRun` | `PUT /api/config` | boolean | Dry run mode |
### Updating Runtime Config
Via dashboard:
1. Open the settings modal
2. Modify desired values
3. Click "Save"
Via API:
```bash
curl -X PUT http://localhost:3000/api/config \
-H "Content-Type: application/json" \
-d '{
"rateLimit": {
"minDelayMs": 45000,
"maxMessagesPerHour": 15,
"jitterMs": 20000
},
"dryRun": true
}'
```
> **Note**: Runtime changes are in-memory only. They are lost when the bot restarts. To make changes persistent, update `config.yaml`.
---
## Configuration Validation
All configuration is validated using Zod at startup. Invalid configuration will cause the bot to exit with a descriptive error.
### Validation Rules
| Field | Validation |
|---|---|
| `reddit.subreddits` | Must be non-empty array of strings |
| `reddit.pollInterval` | Must be positive integer |
| `reddit.targetGender` | Must be "F" or "M" |
| `openrouter.apiKey` | Must be non-empty string |
| `openrouter.model` | Must be non-empty string |
| `openrouter.fallbackModels` | Must be non-empty array |
| `rateLimit.minDelayMs` | Must be positive integer |
| `rateLimit.maxMessagesPerHour` | Must be positive integer |
| `rateLimit.jitterMs` | Must be non-negative integer |
| `browser.headless` | Must be boolean |
| `browser.userDataDir` | Must be non-empty string |
| `database.path` | Must be non-empty string |
| `mediaSync.enabled` | Must be boolean |
| `mediaSync.intervalMinutes` | Must be positive integer (if enabled) |
| `autoReply.enabled` | Must be boolean |
| `autoReply.autoSend` | Must be boolean |
| `autoReply.checkInterval` | Must be positive integer (if enabled) |
| `strategyVariants` | Must be array with name + prompt |
| `web.port` | Must be integer 1-65535 |
| `dryRun` | Must be boolean |
### Common Validation Errors
**Error**: `Invalid config: openrouter.apiKey must be a string`
**Fix**: Set `OPENROUTER_API_KEY` environment variable or add `apiKey` to `config.yaml`
**Error**: `Invalid config: reddit.subreddits must be a non-empty array`
**Fix**: Add at least one subreddit to `reddit.subreddits` in `config.yaml`
**Error**: `Invalid config: browser.userDataDir must be a string`
**Fix**: Ensure `browser.userDataDir` is set in `config.yaml`
---
## Troubleshooting
### Configuration Not Loading
**Symptom**: Bot fails to start with validation errors.
**Steps**:
1. Verify `config.yaml` is in the project root
2. Check YAML syntax (use a YAML linter)
3. Verify environment variables are set correctly
4. Check bot logs for specific validation errors
### Credentials Not Working
**Symptom**: Browser login fails.
**Steps**:
1. Verify `REDDIT_USERNAME` and `REDDIT_PASSWORD` are correct
2. Check that the account is not locked or requires 2FA
3. Try manual login via `npm run login`
4. Ensure `BROWSER_HEADLESS=false` for debugging login issues
### AI Not Working
**Symptom**: Image analysis fails or returns errors.
**Steps**:
1. Verify `OPENROUTER_API_KEY` is valid
2. Check API key has sufficient balance
3. Verify `openrouter.model` is available on OpenRouter
4. Check fallback models are set correctly
5. Review logs for specific AI errors
### Browser Session Expired
**Symptom**: Bot stops with "Browser session expired" error.
**Steps**:
1. Delete `data/browser/` directory
2. Run `npm run login` to re-authenticate
3. Restart the bot
### Port Already in Use
**Symptom**: Dashboard fails to start with "Port already in use".
**Steps**:
1. Change `web.port` in `config.yaml`
2. Or kill the process using the port: `lsof -i :3000`
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# Data Flow Documentation
Complete documentation of data flows through the RedditBot system.
---
## Table of Contents
1. [Overview](#overview)
2. [Post Processing Flow](#post-processing-flow)
3. [Response Monitoring Flow](#response-monitoring-flow)
4. [Chat Interaction Flow](#chat-interaction-flow)
5. [Strategy Selection Flow](#strategy-selection-flow)
6. [Media Sync Flow](#media-sync-flow)
7. [Auto-Reply Flow](#auto-reply-flow)
8. [Dashboard Data Flow](#dashboard-data-flow)
9. [Error Recovery Flows](#error-recovery-flows)
10. [Data Lifecycle](#data-lifecycle)
---
## Overview
RedditBot processes data through several interconnected pipelines:
```
┌─────────────┐ ┌──────────────┐ ┌─────────────┐
│ Reddit API │────►│ Monitor │────►│ Processor │
│ (Posts) │ │ Service │ │ Service │
└─────────────┘ └──────────────┘ └──────┬──────┘
│
┌──────────────┐ ▼
│ Response │ ┌──────────────┐
│ Checker │◄────│ OpenRouter │
└──────────────┘ │ (AI) │
└──────────────┘
│
┌──────────────┐ ▼
│ Chat │ ┌──────────────┐
│ Service │◄────│ Message │
└──────────────┘ │ Sender │
└──────────────┘
│
┌──────────────┐ ▼
│ Media │ ┌──────────────┐
│ Service │◄────│ SQLite DB │
└──────────────┘ └──────────────┘
│
┌──────────────┐ │
│ Dashboard │◄──────────┘
│ (Express) │
└──────────────┘
```
---
## Post Processing Flow
The primary data flow for discovering, analyzing, and messaging about new posts.
### Stage 1: Discovery
```
┌─────────────────────────────────────────────────────────────────┐
│ MonitorService │
│ │
│ 1. Shuffle subreddit order │
│ 2. For each subreddit: │
│ ┌─────────────────────────────────────────────────────┐ │
│ │ RedditApi.fetchPosts(subreddit) │ │
│ │ │ │
│ │ HTTP: GET /r/{subreddit}/new.json?limit=100 │ │
│ │ │ │
│ │ Response: { │ │
│ │ data: { │ │
│ │ children: [ │ │
│ │ { │ │
│ │ data: { │ │
│ │ id: "abc123", │ │
│ │ subreddit: "gonewild", │ │
│ │ author: "user123", │ │
│ │ title: "Summer vibes", │ │
│ │ url: "https://...", │ │
│ │ preview: { reddits: [...] }, │ │
│ │ thumbnail: "https://...", │ │
│ │ post_hint: "image", │ │
│ │ over_18: true │ │
│ │ } │ │
│ │ } │ │
│ │ ] │ │
│ │ } │ │
│ │ } │ │
│ └─────────────────────────────────────────────────────┘ │
│ │
│ 3. Filter posts: │
│ ├─► post_hint === "image" │
│ ├─► author exists and is not deleted │
│ ├─► image_url can be extracted │
│ └─► Author not in seller/spam list │
│ │
│ 4. Cross-reference with DB: │
│ ├─► PostsRepository.getById(postId) → skip if exists │
│ └─► MessagesRepository.getByAuthor(author) → skip if sent │
│ │
│ 5. Return newest valid post │
└─────────────────────────────────────────────────────────────────┘
```
### Stage 2: Image Processing
```
┌─────────────────────────────────────────────────────────────────┐
│ ProcessorService │
│ │
│ 1. Download Image │
│ ┌─────────────────────────────────────────────────────┐ │
│ │ ImageService.downloadImage(url) │ │
│ │ │ │
│ │ HTTP: GET {image_url} │ │
│ │ │ │
│ │ Response: Binary image data │ │
│ │ │ │
│ │ Validation: │ │
│ │ ├─► MIME type: image/jpeg | png | webp │ │
│ │ ├─► File size: < 10MB │ │
│ │ └─► Not empty/broken │ │
│ └─────────────────────────────────────────────────────┘ │
│ │
│ 2. Convert to base64 │
│ ┌─────────────────────────────────────────────────────┐ │
│ │ Buffer.toString('base64') │ │
│ │ │ │
│ │ Result: "data:image/jpeg;base64,/9j/4AAQSkZJR..." │ │
│ └─────────────────────────────────────────────────────┘ │
└─────────────────────────────────────────────────────────────────┘
```
### Stage 3: Gender Detection (Pre-Filter)
```
┌─────────────────────────────────────────────────────────────────┐
│ OpenRouterService │
│ │
│ 1. detectGenderOnly(imageBase64) │
│ ┌─────────────────────────────────────────────────────┐ │
│ │ HTTP: POST https://openrouter.ai/api/v1/chat/ │ │
│ │ completions │ │
│ │ │ │
│ │ Request: { │ │
│ │ model: "fast-model", │ │
│ │ messages: [ │ │
│ │ { │ │
│ │ role: "user", │ │
│ │ content: [ │ │
│ │ { type: "text", text: "Is this F or M?" }, │ │
│ │ { type: "image_url", image_url: {...} } │ │
│ │ ] │ │
│ │ } │ │
│ │ ] │ │
│ │ } │ │
│ │ │ │
│ │ Response: { │ │
│ │ choices: [{ message: { content: "F" } }] │ │
│ │ } │ │
│ └─────────────────────────────────────────────────────┘ │
│ │
│ 3. Compare with config.targetGender │
│ ├─► Match: continue to full analysis │
│ └─► No match: SKIP post (log: "Gender mismatch, skipping") │
└─────────────────────────────────────────────────────────────────┘
```
### Stage 4: Strategy Selection
```
┌─────────────────────────────────────────────────────────────────┐
│ StrategySelector │
│ │
│ 1. Get strategy statistics from DB │
│ ┌─────────────────────────────────────────────────────┐ │
│ │ MessagesRepository.getStrategyStats() │ │
│ │ │ │
│ │ Result: { │ │
│ │ variant_a: { sent: 50, responded: 15, rate: 0.30 },│
│ │ variant_b: { sent: 30, responded: 12, rate: 0.40 },│
│ │ variant_c: { sent: 5, responded: 1, rate: 0.20 } │
│ │ } │ │
│ └─────────────────────────────────────────────────────┘ │
│ │
│ 2. Apply exploration/exploit algorithm │
│ ├─► Random roll < explorationRate → pick random variant │
│ └─► Otherwise → pick highest response rate (min samples) │
│ │
│ 3. Return selected variant name │
│ Example: "variant_b" │
└─────────────────────────────────────────────────────────────────┘
```
### Stage 5: Full AI Analysis
```
┌─────────────────────────────────────────────────────────────────┐
│ OpenRouterService │
│ │
│ 1. analyzeImage(imageBase64) │
│ ┌─────────────────────────────────────────────────────┐ │
│ │ HTTP: POST https://openrouter.ai/api/v1/chat/ │ │
│ │ completions │ │
│ │ │ │
│ │ Request: { │ │
│ │ model: "primary-model", │ │
│ │ messages: [ │ │
│ │ { │ │
│ │ role: "system", │ │
│ │ content: config.openrouter.systemPrompt │ │
│ │ }, │ │
│ │ { │ │
│ │ role: "user", │ │
│ │ content: [ │ │
│ │ { type: "text", text: "Describe this image" },│
│ │ { type: "image_url", image_url: {...} } │ │
│ │ ] │ │
│ │ } │ │
│ │ ] │ │
│ │ } │ │
│ │ │ │
│ │ Response: { │ │
│ │ choices: [{ │ │
│ │ message: { │ │
│ │ content: '{"gender":"F","description":"..."}' │ │
│ │ } │ │
│ │ }] │ │
│ │ } │ │
│ └─────────────────────────────────────────────────────┘ │
│ │
│ 2. Check for refusal │
│ ├─► If refused → try fallback models │
│ └─► If all failed → mark post with error, skip │
│ │
│ 3. Parse and return ImageAnalysis │
│ { gender: "F", description: "Young woman, blonde hair..." }│
└─────────────────────────────────────────────────────────────────┘
```
### Stage 6: Message Generation
```
┌─────────────────────────────────────────────────────────────────┐
│ OpenRouterService │
│ │
│ 1. Retrieve few-shot examples │
│ ┌─────────────────────────────────────────────────────┐ │
│ │ SuccessfulMessagesRepository.getExamples( │ │
│ │ subreddit, count: 3 │ │
│ │ ) │ │
│ │ │ │
│ │ Result: [ │ │
│ │ { │ │
│ │ original_message: "Hey, you look amazing...", │ │
│ │ response_snippet: "Thank you so much!", │ │
│ │ subreddit: "gonewild" │ │
│ │ }, │ │
│ │ // ... more examples │ │
│ │ ] │ │
│ └─────────────────────────────────────────────────────┘ │
│ │
│ 2. Generate message │
│ ┌─────────────────────────────────────────────────────┐ │
│ │ HTTP: POST https://openrouter.ai/api/v1/chat/ │ │
│ │ completions │ │
│ │ │ │
│ │ Request: { │ │
│ │ model: "primary-model", │ │
│ │ messages: [ │ │
│ │ { role: "system", content: messagePrompt }, │ │
│ │ { role: "user", content: [ │ │
│ │ `Image: ${imageAnalysis.description}`, │ │
│ │ `Post title: ${postTitle}`, │ │
│ │ `Strategy: ${selectedVariant}`, │ │
│ │ `Examples: ${JSON.stringify(examples)}` │ │
│ │ ] │ │
│ │ } │ │
│ │ ] │ │
│ │ } │ │
│ └─────────────────────────────────────────────────────┘ │
│ │
│ 3. Return generated message │
│ "Hey, I came across your post and..." │
└─────────────────────────────────────────────────────────────────┘
```
### Stage 7: DM Sending
```
┌─────────────────────────────────────────────────────────────────┐
│ MessagePage │
│ │
│ 1. Navigate to compose page │
│ ┌─────────────────────────────────────────────────────┐ │
│ │ page.goto("https://www.reddit.com/compose?to= │ │
│ │ user123") │ │
│ └─────────────────────────────────────────────────────┘ │
│ │
│ 2. Fill recipient field │
│ ┌─────────────────────────────────────────────────────┐ │
│ │ page.evaluate(() => { │ │
│ │ const input = document.querySelector( │ │
│ │ 'faceplate-autocomplete input' │ │
│ │ ); │ │
│ │ input.value = "user123"; │ │
│ │ input.dispatchEvent(new Event('input', │ │
│ │ { bubbles: true })); │ │
│ │ }); │ │
│ └─────────────────────────────────────────────────────┘ │
│ │
│ 3. Fill subject field ("Stunning") │
│ 4. Fill body field (generated message) │
│ 5. Click send button │
│ 6. Verify success (check for confirmation) │
│ │
│ Result: true (sent) or false (failed) │
└─────────────────────────────────────────────────────────────────┘
```
### Stage 8: Database Recording
```
┌─────────────────────────────────────────────────────────────────┐
│ Database │
│ │
│ 1. INSERT INTO processed_posts │
│ VALUES ( │
│ 'abc123', -- post_id │
│ 'gonewild', -- subreddit │
│ 'user123', -- author │
│ 'Summer vibes', -- title │
│ 'https://...', -- image_url │
│ '{"gender":"F",...}', -- image_analysis │
│ 'Hey, I came across...', -- generated_message │
│ 1716234567, -- processed_at │
│ 1, -- message_sent │
│ NULL -- error │
│ ); │
│ │
│ 2. INSERT INTO sent_messages │
│ VALUES ( │
│ NULL, -- id (auto) │
│ 'abc123', -- post_id │
│ 'user123', -- recipient │
│ 'Stunning', -- subject │
│ 'Hey, I came across...', -- message │
│ 1716234567, -- sent_at │
│ 'variant_b', -- strategy_id │
│ 0, - - got_response │
│ NULL -- response_checked_at │
│ ); │
└─────────────────────────────────────────────────────────────────┘
```
---
## Response Monitoring Flow
How the bot detects and records user replies to sent DMs.
```
┌─────────────────────────────────────────────────────────────────┐
│ ResponseCheckerService │
│ │
│ 1. Navigate to inbox │
│ ┌─────────────────────────────────────────────────────┐ │
│ │ page.goto("https://www.reddit.com/message/inbox") │ │
│ └─────────────────────────────────────────────────────┘ │
│ │
│ 2. Parse inbox items │
│ ┌─────────────────────────────────────────────────────┐ │
│ │ Extract from page: │ │
│ │ [ │ │
│ │ { │ │
│ │ from: "user456", │ │
│ │ subject: "Re: Stunning", │ │
│ │ snippet: "Thank you so much! 😊", │ │
│ │ timestamp: 1716234000, │ │
│ │ link: "/message/xyz789" │ │
│ │ }, │ │
│ │ // ... more messages │ │
│ │ ] │ │
│ └─────────────────────────────────────────────────────┘ │
│ │
│ 3. Match responses to sent messages │
│ ┌─────────────────────────────────────────────────────┐ │
│ │ For each inbox item: │ │
│ │ ├─► MessagesRepository.getByRecipient(from) │ │
│ │ ├─► Find unmatched message within time window │ │
│ │ ├─► Update: got_response = 1 │ │
│ │ ├─► Update: response_checked_at = now │ │
│ │ └─► Store in successful_messages │ │
│ └─────────────────────────────────────────────────────┘ │
│ │
│ 4. Update strategy statistics │
│ ┌─────────────────────────────────────────────────────┐ │
│ │ MessagesRepository.updateStrategyStats( │ │
│ │ strategy_id, got_response: true │ │
│ │ ) │ │
│ └─────────────────────────────────────────────────────┘ │
│ │
│ 5. Log results │
│ └─► "Found 3 responses, updated 2 strategies" │
└─────────────────────────────────────────────────────────────────┘
```
---
## Chat Interaction Flow
How the bot interacts with Reddit chat conversations.
```
┌─────────────────────────────────────────────────────────────────┐
│ ChatService │
│ │
│ ──── PHASE 1: FETCH CHATS ────────────────────────────────── │
│ │
│ 1. Navigate to chat page │
│ page.goto("https://chat.reddit.com") │
│ │
│ 2. Traverse shadow DOM for conversations │
│ ┌─────────────────────────────────────────────────────┐ │
│ │ page.evaluate(() => { │ │
│ │ // JS injection to pierce shadow DOM │ │
│ │ const roots = document.querySelectorAll( │ │
│ │ 'faceplate-chat-list' │ │
│ │ ); │ │
│ │ const chats = []; │ │
│ │ roots.forEach(root => { │ │
│ │ const shadow = root.shadowRoot; │ │
│ │ const items = shadow.querySelectorAll( │ │
│ │ '.chat-item' │ │
│ │ ); │ │
│ │ items.forEach(item => { │ │
│ │ chats.push({ │ │
│ │ id: item.dataset.chatId, │ │
│ │ participant: item.querySelector( │ │
│ │ '.username' │ │
│ │ ).textContent, │ │
│ │ lastMessage: item.querySelector( │ │
│ │ '.message' │ │
│ │ ).textContent, │ │
│ │ timestamp: item.dataset.timestamp │ │
│ │ }); │ │
│ │ }); │ │
│ │ }); │ │
│ │ return chats; │ │
│ │ }); │ │
│ └─────────────────────────────────────────────────────┘ │
│ │
│ 3. Cache results │
│ └─► Save to memory + disk JSON │
│ │
│ ──── PHASE 2: LOAD CONVERSATION ──────────────────────────── │
│ │
│ 1. Check cache │
│ ├─► If cached and fresh: return from memory │
│ └─► If not: fetch from disk or Reddit │
│ │
│ 2. Fetch full history (pagination) │
│ ┌─────────────────────────────────────────────────────┐ │
│ │ For each page of messages: │ │
│ │ ├─► Navigate to chat view │ │
│ │ ├─► Extract messages from shadow DOM │ │
│ │ ├─► Scroll to load more (infinite scroll) │ │
│ │ └─► Repeat until all loaded │ │
│ └─────────────────────────────────────────────────────┘ │
│ │
│ 3. Return conversation object │
│ { │
│ chatId: "abc123", │
│ participants: ["user456", "bot"], │
│ messages: [ │
│ { author: "user456", text: "Hey!", timestamp: ... }, │
│ { author: "bot", text: "Hi there!", timestamp: ... }, │
│ // ... more messages │
│ ], │
│ lastUpdated: 1716234567 │
│ } │
│ │
│ ──── PHASE 3: SEND MESSAGE ───────────────────────────────── │
│ │
│ 1. Navigate to chat view │
│ 2. Fill message input (shadow DOM) │
│ 3. Apply typing delay (human-like) │
│ ┌─────────────────────────────────────────────────────┐ │
│ │ const typingDelay = random(500, 2000); │ │
│ │ await page.waitForTimeout(typingDelay); │ │
│ │ │ │
│ │ // Simulate typing character by character │ │
│ │ for (const char of message) { │ │
│ │ input.value += char; │ │
│ │ await page.waitForTimeout(random(30, 100)); │ │
│ │ } │ │
│ └─────────────────────────────────────────────────────┘ │
│ 4. Submit message │
│ 5. Verify delivery (check for sent indicator) │
│ │
│ Result: true (delivered) or false (failed) │
└─────────────────────────────────────────────────────────────────┘
```
---
## Strategy Selection Flow
How A/B test variants are selected and updated.
```
┌─────────────────────────────────────────────────────────────────┐
│ StrategySelector │
│ │
│ SELECT STRATEGY │
│ ──────────────────────────────────────────────────────────── │
│ │
│ Input: subreddit, author │
│ │
│ 1. Get stats from DB │
│ ┌─────────────────────────────────────────────────────┐ │
│ │ SELECT strategy_id, │ │
│ │ COUNT(*) as sent, │ │
│ │ SUM(got_response) as responded │ │
│ │ FROM sent_messages │ │
│ │ GROUP BY strategy_id │ │
│ └─────────────────────────────────────────────────────┘ │
│ │
│ 2. Calculate response rates │
│ variant_a: 15/50 = 30% │
│ variant_b: 12/30 = 40% │
│ variant_c: 1/5 = 20% │
│ │
│ 3. Filter by minimum samples │
│ minSamples = 10 │
│ variant_c excluded (only 5 sends) │
│ │
│ 4. Explore vs Exploit │
│ random() < explorationRate (e.g., 0.15)? │
│ ├─► Yes: Random pick from enabled variants │
│ └─► No: Pick highest rate (variant_b at 40%) │
│ │
│ Output: selected variant name │
│ │
│ ──── UPDATE STATS ────────────────────────────────────────── │
│ │
│ Input: strategy_id, got_response (boolean) │
│ │
│ 1. Record in sent_messages │
│ UPDATE sent_messages │
│ SET got_response = 1, │
│ response_checked_at = now │
│ WHERE id = ? │
│ │
│ 2. If successful: store in successful_messages │
│ INSERT INTO successful_messages │
│ VALUES (original_message, image_analysis, post_title, │
│ response_snippet, subreddit, now) │
│ │
│ 3. Update strategy statistics │
│ (reflected in next selectStrategy call) │
└─────────────────────────────────────────────────────────────────┘
```
---
## Media Sync Flow
How media files are downloaded and synchronized from chat conversations.
```
┌─────────────────────────────────────────────────────────────────┐
│ MediaSyncService │
│ │
│ ──── TRIGGER ──────────────────────────────────────────────── │
│ │
│ Scheduled: every N minutes (config.mediaSync.intervalMinutes) │
│ Manual: POST /api/media/sync (incremental) │
│ Manual: POST /api/media/sync/full (full) │
│ │
│ ──── INCREMENTAL SYNC ────────────────────────────────────── │
│ │
│ 1. Get top 10 conversations from ChatService │
│ 2. For each conversation: │
│ ├─► Check if media already downloaded (index lookup) │
│ ├─► If not: download media │
│ │ └─► MediaService.downloadMedia(chatId) │
│ └─► Update index │
│ │
│ ──── FULL SYNC ────────────────────────────────────────────── │
│ │
│ 1. Get ALL conversations from ChatService │
│ 2. For each conversation: │
│ ├─► Download any missing media │
│ └─► Update index │
│ │
│ ──── MEDIA DOWNLOAD (MediaService) ────────────────────────── │
│ │
│ 1. Extract media URLs from conversation messages │
│ 2. For each URL: │
│ ├─► Check if Matrix thumbnail │
│ │ └─► Resolve to full resolution URL │
│ ├─► Download via Playwright │
│ ├─► Compute SHA-1 hash │
│ ├─► Check if already exists (dedup) │
│ ├─► Save to data/media/{hash}.{ext} │
│ └─► Update index JSON │
│ │
│ Output: Array of saved file paths │
└─────────────────────────────────────────────────────────────────┘
```
---
## Auto-Reply Flow
How the bot automatically replies to chat messages.
```
┌─────────────────────────────────────────────────────────────────┐
│ AutoReplyService │
│ │
│ Scheduled: every N minutes (config.autoReply.checkInterval) │
│ │
│ 1. Get cached conversations │
│ 2. For each conversation: │
│ │ │
│ ├─► Check for new/unread messages │
│ │ └─► If no new messages: continue │
│ │ │
│ ├─► Detect upsell/spam keywords │
│ │ ├─► "onlyfans", "link in bio", "check my..." │
│ │ ├─► If detected: flag conversation, skip reply │
│ │ └─► If not: continue │
│ │ │
│ ├─► Generate AI reply suggestion │
│ │ ┌─────────────────────────────────────────────────┐ │
│ │ │ OpenRouter.generateReply(conversationHistory) │ │
│ │ │ │ │
│ │ │ Request: { │ │
│ │ │ messages: [ │ │
│ │ │ { role: "system", content: replyPrompt }, │ │
│ │ │ { role: "user", content: conversation } │ │
│ │ │ ] │ │
│ │ │ } │ │
│ │ │ │ │
│ │ │ Response: "Thanks for reaching out! 😊" │ │
│ │ │ │ │
│ │ │ Reply: "Thanks for reaching out! 😊" │ │
│ │ └─────────────────────────────────────────────────┘ │
│ │ │
│ ├─► If autoSend = true: │
│ │ └─► ChatService.sendMessage(chatId, reply) │
│ │ └─► Log: "Auto-sent reply to {user}" │
│ │ │
│ └─► If autoSend = false: │
│ └─► Mark as pending (visible in dashboard) │
│ └─► User can approve/reject via dashboard │
│ │
│ Output: Summary of actions taken │
│ "Checked 15 conversations: 3 new messages, 1 reply sent" │
└─────────────────────────────────────────────────────────────────┘
```
---
## Dashboard Data Flow
How data flows from services to the web dashboard.
```
┌─────────────────────────────────────────────────────────────────┐
│ WebServer (Express) │
│ │
│ ──── REST API ─────────────────────────────────────────────── │
│ │
│ GET /api/stats │
│ ├─► Read from: │
│ │ ├─► Bot running state (in-memory) │
│ │ ├─► PostsRepository.countProcessed() │
│ │ ├─► MessagesRepository.countSent() │
│ │ ├─► MessagesRepository.countResponded() │
│ │ └─► Calculate response rate │
│ └─► Return: { running, processed, sent, responded, rate } │
│ │
│ GET /api/messages │
│ └─► MessagesRepository.getRecent(limit: 50) │
│ │
│ GET /api/analytics/by-strategy │
│ └─► MessagesRepository.getStrategyStats() │
│ │
│ PUT /api/config │
│ ├─► Validate new config values │
│ ├─► Update in-memory config │
│ └─► Return updated config │
│ │
│ ──── SSE LOG STREAMING ────────────────────────────────────── │
│ │
│ GET /api/logs/stream │
│ ├─► Client connects │
│ ├─► Send any pending log entries │
│ ├─► Subscribe to logger buffer │
│ ├─► Push new entries as they arrive │
│ │ └─► Event: log │
│ │ └─► Data: { level, message, timestamp } │
│ └─► On disconnect: unsubscribe │
│ │
│ ──── FRONTEND (public/index.html) ─────────────────────────── │
│ │
│ JavaScript polls API endpoints: │
│ ├─► /api/stats every 5 seconds │
│ ├─► /api/messages every 10 seconds │
│ ├─► /api/timers every 2 seconds │
│ └─► SSE /api/logs/stream (persistent connection) │
│ │
│ Updates DOM in real-time: │
│ ├─► Stats cards (processed, sent, responded, rate) │
│ ├─► Activity feed (scrolling list) │
│ ├─► Message viewer (click to expand) │
│ ├─► Chat browser (conversation list) │
│ ├─► Media gallery (image grid) │
│ └─► Rate limiter timers (countdown) │
└─────────────────────────────────────────────────────────────────┘
```
---
## Error Recovery Flows
### AI Refusal Recovery
```
1. OpenRouter.analyzeImage() returns refusal
│
├─► Detect refusal via heuristic patterns
│ ├─► "cannot analyze"
│ ├─► "against policy"
│ └─► "unable to process"
│
├─► Try next model in fallback chain
│ ├─► OpenRouter.fallbackModels[0]
│ ├─► OpenRouter.fallbackModels[1]
│ └─► ...
│
└─► If all models refuse:
├─► Mark post as processed with error
├─► Log: "All models refused to analyze post {id}"
└─► Continue to next post
```
### Network Error Recovery
```
1. RedditApi.fetchPosts() throws error
│
└─► withRetry() wrapper handles recovery:
├─► Retry 1: wait 5s
├─► Retry 2: wait 15s
├─► Retry 3: wait 45s
└─► After 3 failures:
├─► Log error
├─► Skip this subreddit
└─► Continue to next subreddit
```
### Browser Session Recovery
```
1. BrowserClient.verifySession() returns false
│
├─► Check for expired cookies
│
├─► Attempt automated re-login
│ ├─► BrowserClient.login()
│ └─► If success: continue
│
└─► If re-login fails:
├─► Log error: "Browser session expired"
├─► Stop bot
└─► Require manual login (scripts/login.ts)
```
---
## Data Lifecycle
### Post Data
```
Discovered (MonitorService)
│
├─► Stored in processed_posts (pending)
│
├─► Processed (ProcessorService)
│ ├─► image_analysis updated
│ ├─► generated_message updated
│ └─► message_sent updated
│
└─► Archived (retention policy TBD)
└─► Kept indefinitely for analytics
```
### Message Data
```
Generated (ProcessorService)
│
├─► Stored in sent_messages (got_response = 0)
│
├─► Response checked (ResponseCheckerService)
│ ├─► got_response = 1
│ └─► response_checked_at set
│
├─► If responded:
│ └─► Copied to successful_messages (for learning)
│
└─► Retained indefinitely for analytics
```
### Learning Data
```
Successful pair created (ResponseCheckerService)
│
├─► Stored in successful_messages
│ ├─► original_message
│ ├─► image_analysis
│ ├─► post_title
│ ├─► response_snippet
│ └─► subreddit (for weighted selection)
│
├─► Retrieved for few-shot learning
│ └─► Included in OpenRouter.generateMessage() prompt
│
└─► Retained indefinitely (grows bot intelligence)
```
### Chat Data
```
Conversation discovered (ChatService)
│
├─► Cached in memory
├─► Persisted to disk JSON
│
├─► Messages added as they arrive
│
├─► Media downloaded (MediaService)
│ └─► Stored in data/media/
│
└─► Retained until manually cleared
└─► No automatic cleanup (TBD)
```
### Media Data
```
Media URL discovered
│
├─► Downloaded (MediaService)
│ ├─► Matrix thumbnails resolved
│ ├─► SHA-1 hash computed
│ └─► Saved to data/media/{hash}.{ext}
│
├─► Indexed in data/media/index.json
│
├─► Deduplicated (hash check before download)
│
└─► Retained until manually cleared
└─► No automatic cleanup (TBD)
```
+550
View File
@@ -0,0 +1,550 @@
# Database Schema
Complete reference for the SQLite database schema, migrations, and query patterns.
---
## Table of Contents
1. [Overview](#overview)
2. [Database File](#database-file)
3. [Schema](#schema)
4. [Indexes](#indexes)
5. [Migrations](#migrations)
6. [Query Patterns](#query-patterns)
7. [Repository Methods](#repository-methods)
8. [Data Retention](#data-retention)
---
## Overview
RedditBot uses SQLite (via `better-sqlite3`) for persistent storage. The database tracks processed posts, sent messages, and successful message/response pairs.
**Features**:
- WAL mode for better concurrent read performance
- Foreign key constraints enabled
- Progressive migrations for schema evolution
- Repository pattern for data access
---
## Database File
**Default path**: `./data/reddit-bot.db`
Configured in `config.yaml`:
```yaml
database:
path: "./data/reddit-bot.db"
```
The database file is auto-created on first run.
---
## Schema
### Table: `processed_posts`
Tracks all posts that have been discovered and processed.
```sql
CREATE TABLE processed_posts (
id TEXT PRIMARY KEY, -- Reddit post ID
subreddit TEXT NOT NULL, -- Source subreddit
author TEXT NOT NULL, -- Post author username
title TEXT, -- Post title
image_url TEXT, -- Original image URL
image_analysis TEXT, -- AI-generated JSON description
generated_message TEXT, -- AI-generated DM text
processed_at INTEGER NOT NULL, -- Unix timestamp
message_sent INTEGER DEFAULT 0, -- 0 = not sent, 1 = sent
error TEXT -- Error message if processing failed
);
```
**Column Details**:
| Column | Type | Constraints | Description |
|---|---|---|---|
| `id` | TEXT | PRIMARY KEY | Reddit post ID (e.g., "abc123") |
| `subreddit` | TEXT | NOT NULL | Source subreddit name |
| `author` | TEXT | NOT NULL | Post author username |
| `title` | TEXT | | Post title (nullable if unavailable) |
| `image_url` | TEXT | | Original image URL |
| `image_analysis` | TEXT | | JSON string from AI analysis |
| `generated_message` | TEXT | | The DM text that was generated |
| `processed_at` | INTEGER | NOT NULL | Unix timestamp when processed |
| `message_sent` | INTEGER | DEFAULT 0 | 0 = not sent, 1 = successfully sent |
| `error` | TEXT | | Error message if processing failed |
**Example Row**:
```json
{
"id": "abc123",
"subreddit": "gonewild",
"author": "user123",
"title": "Summer vibes",
"image_url": "https://i.redd.it/abc123.jpg",
"image_analysis": "{\"gender\":\"F\",\"description\":\"Young woman...\"}",
"generated_message": "Hey, you look amazing...",
"processed_at": 1716234567,
"message_sent": 1,
"error": null
}
```
---
### Table: `sent_messages`
Tracks all DMs sent by the bot.
```sql
CREATE TABLE sent_messages (
id INTEGER PRIMARY KEY AUTOINCREMENT,
post_id TEXT NOT NULL,
recipient TEXT NOT NULL,
subject TEXT DEFAULT 'Stunning',
message TEXT NOT NULL,
sent_at INTEGER NOT NULL,
strategy_id TEXT,
got_response INTEGER DEFAULT 0,
response_checked_at INTEGER,
FOREIGN KEY (post_id) REFERENCES processed_posts(id)
);
```
**Column Details**:
| Column | Type | Constraints | Description |
|---|---|---|---|
| `id` | INTEGER | PRIMARY KEY AUTOINCREMENT | Internal ID |
| `post_id` | TEXT | NOT NULL, FK | Source post ID |
| `recipient` | TEXT | NOT NULL | Recipient username |
| `subject` | TEXT | DEFAULT 'Stunning' | DM subject line |
| `message` | TEXT | NOT NULL | DM body text |
| `sent_at` | INTEGER | NOT NULL | Unix timestamp when sent |
| `strategy_id` | TEXT | | A/B test variant name |
| `got_response` | INTEGER | DEFAULT 0 | 0 = no response, 1 = responded |
| `response_checked_at` | INTEGER | | Timestamp of last response check |
**Example Row**:
```json
{
"id": 1,
"post_id": "abc123",
"recipient": "user123",
"subject": "Stunning",
"message": "Hey, you look amazing...",
"sent_at": 1716234567,
"strategy_id": "compliment",
"got_response": 1,
"response_checked_at": 1716238167
}
```
---
### Table: `successful_messages`
Stores successful message/response pairs for few-shot learning.
```sql
CREATE TABLE successful_messages (
id INTEGER PRIMARY KEY AUTOINCREMENT,
sent_message_id INTEGER,
original_message TEXT NOT NULL,
image_analysis TEXT,
post_title TEXT,
response_snippet TEXT,
subreddit TEXT,
created_at INTEGER NOT NULL,
FOREIGN KEY (sent_message_id) REFERENCES sent_messages(id)
);
```
**Column Details**:
| Column | Type | Constraints | Description |
|---|---|---|---|
| `id` | INTEGER | PRIMARY KEY AUTOINCREMENT | Internal ID |
| `sent_message_id` | INTEGER | FK, nullable | Related sent message ID |
| `original_message` | TEXT | NOT NULL | The DM that got a response |
| `image_analysis` | TEXT | | Context from image analysis |
| `post_title` | TEXT | | Original post title |
| `response_snippet` | TEXT | | First reply text |
| `subreddit` | TEXT | | For weighted example selection |
| `created_at` | INTEGER | NOT NULL | Unix timestamp |
**Example Row**:
```json
{
"id": 1,
"sent_message_id": 1,
"original_message": "Hey, you look amazing...",
"image_analysis": "{\"gender\":\"F\",\"description\":\"...\"}",
"post_title": "Summer vibes",
"response_snippet": "Thank you so much! 😊",
"subreddit": "gonewild",
"created_at": 1716238167
}
```
---
## Indexes
### `processed_posts` Indexes
```sql
CREATE INDEX idx_posts_subreddit ON processed_posts(subreddit);
CREATE INDEX idx_posts_author ON processed_posts(author);
```
**Purpose**: Fast lookup by subreddit (for processing stats) and by author (for skip-checking).
---
### `sent_messages` Indexes
```sql
CREATE INDEX idx_messages_recipient ON sent_messages(recipient);
CREATE INDEX idx_messages_strategy ON sent_messages(strategy_id);
CREATE INDEX idx_messages_response ON sent_messages(got_response);
```
**Purpose**:
- `idx_messages_recipient`: Fast lookup when matching responses
- `idx_messages_strategy`: Analytics by strategy variant
- `idx_messages_response`: Filter for responded/not-responded
---
### `successful_messages` Indexes
```sql
CREATE INDEX idx_success_subreddit ON successful_messages(subreddit);
CREATE INDEX idx_success_message ON successful_messages(sent_message_id);
```
**Purpose**:
- `idx_success_subreddit`: Weighted example selection by subreddit
- `idx_success_message`: Link back to sent message
---
## Migrations
Migrations are defined in `src/database/client.ts` and run automatically on every startup.
### Migration Logic
```typescript
// Pseudo-code for migration process
function runMigrations(db: Database) {
// Enable features
db.exec("PRAGMA journal_mode=WAL;");
db.exec("PRAGMA foreign_keys=ON;");
// Create tables if they don't exist
db.exec(`CREATE TABLE IF NOT EXISTS processed_posts (...)`);
db.exec(`CREATE TABLE IF NOT EXISTS sent_messages (...)`);
db.exec(`CREATE TABLE IF NOT EXISTS successful_messages (...)`);
// Create indexes if they don't exist
db.exec(`CREATE INDEX IF NOT EXISTS idx_posts_subreddit ON processed_posts(subreddit)`);
// ... more indexes
// Safe column additions (for schema evolution)
db.exec(`ALTER TABLE processed_posts ADD COLUMN error TEXT`);
}
```
### Migration Safety
- All `CREATE TABLE` statements use `IF NOT EXISTS`
- All `CREATE INDEX` statements use `IF NOT EXISTS`
- Column additions use `ALTER TABLE ADD COLUMN IF NOT EXISTS` pattern
- Migrations are idempotent (safe to run multiple times)
### Adding New Columns
When adding new columns to existing tables:
```typescript
// In src/database/client.ts
const tableInfo = db.prepare(`PRAGMA table_info(processed_posts)`).all();
const hasErrorColumn = tableInfo.some((col: any) => col.name === 'error');
if (!hasErrorColumn) {
db.exec("ALTER TABLE processed_posts ADD COLUMN error TEXT");
}
```
---
## Query Patterns
### Post Processing
**Check if post was already processed**:
```sql
SELECT id FROM processed_posts WHERE id = ?;
```
**Mark post as processed**:
```sql
INSERT OR REPLACE INTO processed_posts
(id, subreddit, author, title, image_url, image_analysis,
generated_message, processed_at, message_sent, error)
VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?);
```
**Mark post as sent**:
```sql
UPDATE processed_posts
SET message_sent = 1
WHERE id = ?;
```
**Update post with analysis**:
```sql
UPDATE processed_posts
SET image_analysis = ?, generated_message = ?
WHERE id = ?;
```
---
### Message Tracking
**Record a sent message**:
```sql
INSERT INTO sent_messages
(post_id, recipient, subject, message, sent_at, strategy_id)
VALUES (?, ?, 'Stunning', ?, ?, ?);
```
**Get recent messages**:
```sql
SELECT * FROM sent_messages
ORDER BY sent_at DESC
LIMIT ?;
```
**Update response status**:
```sql
UPDATE sent_messages
SET got_response = 1, response_checked_at = ?
WHERE id = ?;
```
**Check if user was previously messaged**:
```sql
SELECT COUNT(*) FROM sent_messages WHERE recipient = ?;
```
---
### Strategy Analytics
**Get strategy statistics**:
```sql
SELECT
strategy_id,
COUNT(*) as sent,
SUM(got_response) as responded
FROM sent_messages
WHERE strategy_id IS NOT NULL
GROUP BY strategy_id;
```
**Get response rate by subreddit**:
```sql
SELECT
p.subreddit,
COUNT(*) as sent,
SUM(s.got_response) as responded
FROM sent_messages s
JOIN processed_posts p ON s.post_id = p.id
GROUP BY p.subreddit;
```
**Get daily response trend**:
```sql
SELECT
DATE(sent_at, 'unixepoch') as date,
COUNT(*) as sent,
SUM(got_response) as responded
FROM sent_messages
GROUP BY DATE(sent_at, 'unixepoch')
ORDER BY date DESC
LIMIT 30;
```
---
### Few-Shot Learning
**Get successful examples for a subreddit**:
```sql
SELECT
original_message,
image_analysis,
post_title,
response_snippet
FROM successful_messages
WHERE subreddit = ?
ORDER BY created_at DESC
LIMIT 3;
```
**Store successful pair**:
```sql
INSERT INTO successful_messages
(sent_message_id, original_message, image_analysis,
post_title, response_snippet, subreddit, created_at)
VALUES (?, ?, ?, ?, ?, ?, ?);
```
---
## Repository Methods
### PostsRepository
```typescript
class PostsRepository {
/** Check if a post was already processed */
getById(id: string): ProcessedPost | undefined
/** Mark a post as processed */
insert(post: ProcessedPostInsert): void
/** Mark a post as having a message sent */
markSent(id: string): void
/** Update post with AI analysis results */
updateAnalysis(id: string, analysis: string, message: string): void
/** Get total count of processed posts */
count(): number
/** Get count by subreddit */
countBySubreddit(subreddit: string): number
}
```
### MessagesRepository
```typescript
class MessagesRepository {
/** Record a sent message */
insert(message: MessageInsert): number
/** Get recent sent messages */
getRecent(limit: number): SentMessage[]
/** Get messages by recipient */
getByRecipient(recipient: string): SentMessage[]
/** Update response status */
markResponded(id: number, checkedAt: number): void
/** Get strategy statistics */
getStrategyStats(): StrategyStat[]
/** Get response rate by subreddit */
getSubredditStats(): SubredditStat[]
/** Get daily response trend */
getDailyTrend(days: number): DailyTrend[]
/** Get total count of sent messages */
count(): number
/** Get count of responded messages */
countResponded(): number
}
```
### SuccessfulMessagesRepository
```typescript
class SuccessfulMessagesRepository {
/** Store a successful message/response pair */
insert(pair: SuccessfulMessageInsert): void
/** Get examples for few-shot learning */
getExamples(subreddit: string, count: number): Example[]
/** Get total count */
count(): number
/** Get recent examples */
getRecent(limit: number): SuccessfulMessage[]
}
```
---
## Data Retention
### Current Behavior
All data is retained indefinitely. There is no automatic cleanup or retention policy.
| Table | Retention | Notes |
|---|---|---|
| `processed_posts` | Indefinite | Grows with each post processed |
| `sent_messages` | Indefinite | Grows with each message sent |
| `successful_messages` | Indefinite | Grows with each response received |
### Estimated Growth
With default settings (20 messages/hour, 24/7 operation):
| Timeframe | Posts | Messages | Responses (est. 30%) |
|---|---|---|---|
| 1 day | ~480 | ~288 | ~86 |
| 1 week | ~3,360 | ~2,016 | ~605 |
| 1 month | ~14,400 | ~8,640 | ~2,592 |
| 1 year | ~175,200 | ~105,120 | ~31,536 |
### Recommended Cleanup (Future)
Consider implementing automated cleanup:
```sql
-- Archive old processed posts
CREATE TABLE processed_posts_archive AS
SELECT * FROM processed_posts
WHERE processed_at < ?;
-- Delete archived posts
DELETE FROM processed_posts
WHERE processed_at < ?;
-- Keep last N months of data
```
> **Note**: Successful messages should NEVER be deleted as they are used for few-shot learning.
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# Deployment Guide
Complete guide for deploying RedditBot in various environments.
---
## Table of Contents
1. [Prerequisites](#prerequisites)
2. [Local Development](#local-development)
3. [Docker Deployment](#docker-deployment)
4. [Docker Compose](#docker-compose)
5. [Dokploy Deployment](#dokploy-deployment)
6. [Production Considerations](#production-considerations)
7. [Monitoring & Maintenance](#monitoring--maintenance)
8. [Troubleshooting](#troubleshooting-1)
---
## Prerequisites
### Required
| Requirement | Version | Notes |
|---|---|---|
| Node.js | 18+ | LTS recommended |
| npm | 9+ | Or yarn/pnpm |
| OpenRouter API Key | - | Sign up at [openrouter.ai](https://openrouter.ai) |
| Reddit Account | - | With DM permissions enabled |
### Recommended
| Requirement | Notes |
|---|---|
| 1 GB RAM | Minimum for browser automation |
| 1 CPU core | More for higher message throughput |
| 5 GB disk | For database, media, and browser data |
---
## Local Development
### 1. Clone and Install
```bash
git clone <repository-url>
cd RedditBot
npm install
```
### 2. Configure
Create `config.yaml`:
```yaml
reddit:
subreddits:
- gonewild
pollInterval: 15
targetGender: "F"
sellerKeywords:
- seller
- onlyfans
openrouter:
apiKey: "sk-or-v1-your-key-here"
model: "meta-llama/llama-3.2-90b-vision-preview"
fallbackModels:
- "google/gemini-2.0-flash-001"
rateLimit:
minDelayMs: 30000
maxMessagesPerHour: 20
jitterMs: 15000
browser:
headless: true
userDataDir: "./data/browser"
database:
path: "./data/reddit-bot.db"
web:
port: 3000
dryRun: true # Start in dry run mode
```
Set environment variables:
```bash
export REDDIT_USERNAME="your-username"
export REDDIT_PASSWORD="your-password"
```
### 3. Initial Login
Run the login script to establish a browser session:
```bash
npm run login
```
This will:
1. Open a browser window
2. Navigate to Reddit login
3. Wait for you to complete login (including 2FA if enabled)
4. Save cookies to `data/browser/`
### 4. Start the Bot
```bash
# Development (with TypeScript execution)
npm run dev
# Production (compiled JavaScript)
npm start
```
### 5. Access Dashboard
Open http://localhost:3000 in your browser.
---
## Docker Deployment
### Build the Image
```bash
docker build -t reddit-bot .
```
### Run the Container
```bash
docker run -d \
--name reddit-bot \
-p 3000:3000 \
-v $(pwd)/data:/app/data \
-e OPENROUTER_API_KEY=sk-or-v1-your-key \
-e REDDIT_USERNAME=your-username \
-e REDDIT_PASSWORD=your-password \
-e BROWSER_HEADLESS=true \
reddit-bot:latest
```
### Dockerfile Structure
```dockerfile
# Build stage
FROM node:18-alpine AS builder
WORKDIR /app
COPY package*.json ./
RUN npm ci
COPY . .
RUN npm run build
# Production stage
FROM node:18-alpine
WORKDIR /app
COPY --from=builder /app/dist ./dist
COPY --from=builder /app/node_modules ./node_modules
COPY --from=builder /app/config.yaml ./config.yaml
COPY --from=builder /app/package.json ./package.json
EXPOSE 3000
CMD ["node", "dist/index.js"]
```
---
## Docker Compose
### docker-compose.yml
```yaml
version: '3.8'
services:
reddit-bot:
build: .
container_name: reddit-bot
ports:
- "3000:3000"
volumes:
- ./data:/app/data
environment:
- OPENROUTER_API_KEY=${OPENROUTER_API_KEY}
- REDDIT_USERNAME=${REDDIT_USERNAME}
- REDDIT_PASSWORD=${REDDIT_PASSWORD}
- BROWSER_HEADLESS=true
restart: unless-stopped
healthcheck:
test: ["CMD", "wget", "--spider", "http://localhost:3000/api/stats"]
interval: 30s
timeout: 10s
retries: 3
start_period: 60s
```
### Start with Compose
```bash
# Set environment variables
cp .env.example .env
# Edit .env with your credentials
# Build and start
docker compose up -d --build
# View logs
docker compose logs -f reddit-bot
# Stop
docker compose down
# Restart
docker compose restart
```
---
## Dokploy Deployment
Dokploy is a self-hosted platform for deploying applications. See `DOKPLOY_DEPLOY.md` for detailed instructions.
### Quick Start
1. **Create Application**: In Dokploy dashboard, create a new Docker application
2. **Set Environment Variables**:
- `OPENROUTER_API_KEY`
- `REDDIT_USERNAME`
- `REDDIT_PASSWORD`
- `BROWSER_HEADLESS`
3. **Mount Volume**: Mount `./data` for persistent storage
4. **Set Port**: Map container port 3000 to host port
5. **Deploy**: Push to repository and trigger deployment
### Dokploy Configuration
```yaml
# Dokploy-specific settings
app:
type: docker
repository: <your-repo>
branch: main
dockerfilePath: Dockerfile
environment:
OPENROUTER_API_KEY: $OPENROUTER_API_KEY
REDDIT_USERNAME: $REDDIT_USERNAME
REDDIT_PASSWORD: $REDDIT_PASSWORD
BROWSER_HEADLESS: "true"
ports:
- container: 3000
host: 3000
volumes:
- source: reddit-bot-data
target: /app/data
type: bind
restartPolicy: unless-stopped
```
---
## Production Considerations
### Security
1. **Network Isolation**: Run behind a reverse proxy with authentication
2. **Environment Variables**: Never commit credentials; use secrets management
3. **Dashboard Access**: Restrict to internal network or add auth
4. **Browser Data**: Protect `data/browser/` directory
### Performance
1. **Browser Headless**: Always use headless mode in production
2. **WAL Mode**: SQLite WAL mode is enabled by default for concurrent reads
3. **Rate Limiting**: Adjust based on Reddit account age and trust level
4. **Message Volume**: Start low (10-20/hour) and increase gradually
### Reliability
1. **Auto-restart**: Use `restart: unless-stopped` in Docker
2. **Health Checks**: Monitor `/api/stats` endpoint
3. **Logging**: Review logs regularly for errors
4. **Backups**: Regularly backup `data/reddit-bot.db`
### Monitoring
1. **Dashboard**: Check web dashboard for real-time stats
2. **Response Rate**: Monitor response rates per strategy/subreddit
3. **Error Rate**: Watch for AI refusals, send failures
4. **Browser Health**: Verify session isn't expired
### Scaling
RedditBot is designed as a single-instance application. For scaling:
1. **Multiple Accounts**: Run separate instances per Reddit account
2. **Subreddit Split**: Distribute subreddits across instances
3. **Centralized DB**: Consider moving to PostgreSQL for multi-instance
---
## Monitoring & Maintenance
### Daily Checks
- [ ] Dashboard shows bot is running
- [ ] Response rate is reasonable (>10%)
- [ ] No repeated errors in logs
- [ ] Browser session is active
### Weekly Tasks
- [ ] Review analytics (strategy performance, subreddit performance)
- [ ] Check disk usage (media files, database)
- [ ] Verify backup is working
- [ ] Review successful messages for quality
### Monthly Tasks
- [ ] Backup database
- [ ] Review and update strategy variants
- [ ] Check for OpenRouter model updates
- [ ] Review and update seller keywords
- [ ] Verify browser session is still valid
### Backup Procedure
```bash
# Stop the bot
docker compose stop
# Backup database
cp data/reddit-bot.db data/reddit-bot.db.backup.$(date +%Y%m%d)
# Backup browser session (optional)
tar czf data/browser.backup.$(date +%Y%m%d).tar.gz data/browser/
# Restart the bot
docker compose start
```
---
## Troubleshooting
### Bot Won't Start
**Symptom**: Bot exits immediately on startup.
**Steps**:
1. Check logs: `docker compose logs reddit-bot`
2. Verify `config.yaml` syntax
3. Verify environment variables are set
4. Check for Zod validation errors in logs
### Browser Login Fails
**Symptom**: "Browser session expired" or login fails.
**Steps**:
1. Delete browser data: `rm -rf data/browser/`
2. Re-run login: `npm run login`
3. Check Reddit account is not locked
4. Try `BROWSER_HEADLESS=false` for debugging
### AI Analysis Fails
**Symptom**: All messages show "AI refusal" or analysis errors.
**Steps**:
1. Verify API key is valid and has balance
2. Check model availability on OpenRouter
3. Try changing to a different model
4. Review logs for specific error messages
### High Error Rate
**Symptom**: Many messages fail to send.
**Steps**:
1. Check rate limiting (reduce maxMessagesPerHour)
2. Increase minDelayMs and jitterMs
3. Check for IP bans (try different network)
4. Review Reddit account standing
### Dashboard Not Accessible
**Symptom**: Cannot reach http://localhost:3000.
**Steps**:
1. Verify bot is running (`docker compose ps`)
2. Check port is not in use: `lsof -i :3000`
3. Verify firewall allows port 3000
4. Check web.port in config.yaml
### Database Issues
**Symptom**: Database errors or corruption.
**Steps**:
1. Stop the bot
2. Backup the database
3. Try opening with SQLite viewer to check integrity
4. If corrupted, restore from backup
5. Consider enabling automatic backups
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# Development Guide
Guide for contributing to RedditBot development.
---
## Table of Contents
1. [Project Structure](#project-structure)
2. [Development Setup](#development-setup)
3. [Coding Standards](#coding-standards)
4. [Adding a New Service](#adding-a-new-service)
5. [Adding a New Strategy Variant](#adding-a-new-strategy-variant)
6. [Debugging](#debugging)
7. [Common Tasks](#common-tasks)
8. [Known Issues](#known-issues)
---
## Project Structure
```
RedditBot/
├── config.yaml # Main configuration
├── package.json # Dependencies and scripts
├── tsconfig.json # TypeScript config
├── Dockerfile # Container build
├── docker-compose.yml # Docker Compose
├── public/
│ └── index.html # Web dashboard (single file)
├── scripts/
│ ├── login.ts # Manual login helper
│ └── inspect-chat-dom.ts # DOM inspection debug script
└── src/
├── index.ts # Entry point / orchestrator
├── config/
│ └── index.ts # Config loader + Zod schema
├── database/
│ ├── client.ts # SQLite setup + migrations
│ └── repositories.ts # Repository classes
├── reddit/
│ └── api.ts # Reddit API client
├── ai/
│ └── openrouter.ts # OpenRouter AI client
├── browser/
│ ├── client.ts # Playwright browser manager
│ ├── message-page.ts # DM compose automation
│ └── media-downloader.ts # Media download
├── services/
│ ├── monitor.ts # Post discovery
│ ├── processor.ts # Processing pipeline
│ ├── response-checker.ts # Response monitoring
│ ├── strategy-selector.ts # A/B testing
│ ├── chat.ts # Chat scraping + messaging
│ ├── media.ts # Media management
│ ├── media-sync.ts # Media sync scheduler
│ └── auto-reply.ts # Auto-reply service
├── utils/
│ ├── logger.ts # Winston logger
│ ├── rate-limiter.ts # Rate limiting
│ ├── retry.ts # Retry wrapper
│ └── image.ts # Image utilities
└── web/
└── server.ts # Express dashboard server
```
---
## Development Setup
### 1. Install Dependencies
```bash
npm install
```
### 2. Configure
Copy and edit `config.yaml`:
```bash
cp config.yaml config.yaml.backup # Backup existing
# Edit config.yaml with your settings
```
### 3. Set Environment Variables
```bash
export REDDIT_USERNAME="your-username"
export REDDIT_PASSWORD="your-password"
export OPENROUTER_API_KEY="sk-or-v1-your-key"
```
### 4. Initial Login
```bash
# Open browser for manual login
npm run login
```
### 5. Start Development Server
```bash
# Development mode (hot reload with tsx)
npm run dev
# Production mode (compiled JS)
npm run build && npm start
```
### 6. Access Dashboard
Open http://localhost:3000
---
## Coding Standards
### TypeScript
- **Strict mode**: No `any` types (use `unknown` with type guards)
- **Interfaces**: Define interfaces for all data structures
- **Null checks**: Use optional chaining (`?.`) and nullish coalescing (`??`)
- **Async/Await**: Use async/await, not `.then()` chains
```typescript
// Good
interface PostData {
id: string;
subreddit: string;
author: string;
}
async function fetchPost(id: string): Promise<PostData> {
const response = await api.get(`/posts/${id}`);
return response.data;
}
// Bad
async function fetchPost(id: any): Promise<any> {
return api.get(`/posts/${id}`).then(r => r.data);
}
```
### Logging
Use `winston` logger, never `console.log`:
```typescript
// Good
this.logger.info("Processed post {id}", { id: post.id });
this.logger.warn("AI refusal detected", { postId: post.id });
this.logger.error("Failed to send DM", { error: err.message });
// Bad
console.log("Processed post", post.id);
```
### Error Handling
Use try/catch with structured error handling:
```typescript
try {
await this.processPost(post);
} catch (err) {
this.logger.error("Post processing failed", {
postId: post.id,
error: err instanceof Error ? err.message : String(err)
});
// Don't throw - allow other posts to be processed
}
```
### Service Structure
Follow single responsibility:
```typescript
class NewService {
constructor(
private config: Config,
private dependency: ExistingService,
private logger: Logger
) {}
async doSomething(input: string): Promise<Result> {
// Validate input
if (!input) {
throw new Error("Input is required");
}
// Do work
const result = await this.dependency.process(input);
// Return result
return result;
}
}
```
### File Organization
- One class per file (except repositories which share one file)
- Services in `src/services/`
- Utilities in `src/utils/`
- External integrations in their own folders (`src/ai/`, `src/reddit/`, `src/browser/`)
---
## Adding a New Service
### 1. Create the Service File
```typescript
// src/services/new-service.ts
import { Config } from '../config';
import { Logger } from '../utils/logger';
interface NewServiceDeps {
config: Config;
logger: Logger;
// other dependencies
}
interface Result {
success: boolean;
data?: any;
error?: string;
}
export class NewService {
constructor(private deps: NewServiceDeps) {}
async execute(input: string): Promise<Result> {
const { config, logger } = this.deps;
logger.info("NewService executing", { input });
// Implementation here
return { success: true };
}
}
```
### 2. Add to Dependencies Interface
If the service needs other services, add them to the interface:
```typescript
interface NewServiceDeps {
config: Config;
logger: Logger;
redditApi: RedditApi;
openrouter: OpenRouterService;
}
```
### 3. Wire Up in main()
In `src/index.ts`, add initialization:
```typescript
const newService = new NewService({
config,
logger,
redditApi,
openrouter
});
// If it needs to run periodically:
setInterval(() => {
newService.execute(someInput).catch(err => {
logger.error("NewService error", { error: err.message });
});
}, intervalMs);
```
### 4. Add to Web Dashboard (Optional)
If the service needs API endpoints, add them in `src/web/server.ts`:
```typescript
server.app.get('/api/new-service', async (req, res) => {
try {
const result = await newService.execute(req.query.input as string);
res.json(result);
} catch (err) {
res.status(500).json({ error: (err as Error).message });
}
});
```
### 5. Update Config (If Needed)
Add new configuration options to:
- `config.yaml`
- `src/config/index.ts` Zod schema
- Configuration documentation
---
## Adding a New Strategy Variant
### 1. Add to config.yaml
```yaml
strategyVariants:
- name: "existing_variant"
prompt: "Existing prompt..."
enabled: true
- name: "new_variant"
prompt: |
Write a friendly message that references the image content.
Be specific and genuine. Keep it under 2 sentences.
enabled: true
```
### 2. No Code Changes Needed
The `StrategySelector` automatically picks up new variants from the config. The algorithm will:
1. Include the new variant in random exploration
2. Track its response rate once messages are sent
3. Promote it to exploitation if it has good stats
### 3. Monitor Performance
Check performance via the dashboard or API:
```bash
curl http://localhost:3000/api/analytics/by-strategy
```
---
## Debugging
### Browser Debugging
Run with visible browser:
```yaml
# config.yaml
browser:
headless: false
```
Or set environment variable:
```bash
BROWSER_HEADLESS=false npm run dev
```
### DOM Inspection
Use the debug endpoint to inspect Reddit's shadow DOM:
```bash
curl -X POST http://localhost:3000/api/debug/inspect-dom
```
Or run the standalone script:
```bash
npx tsx scripts/inspect-chat-dom.ts
```
### Logging
Adjust log level by modifying `src/utils/logger.ts`:
```typescript
const logger = winston.createLogger({
level: 'debug', // Change from 'info' to 'debug'
// ...
});
```
### Database Inspection
Open the database with SQLite viewer:
```bash
# Install sqlite3 if needed
brew install sqlite3
# Open database
sqlite3 data/reddit-bot.db
# Query
SELECT * FROM sent_messages LIMIT 5;
```
### Network Debugging
Enable axios debug:
```typescript
// In src/reddit/api.ts
import axios from 'axios';
axios.defaults.debug = true;
```
---
## Common Tasks
### Add a New Subreddit
```yaml
# config.yaml
reddit:
subreddits:
- gonewild
- ratemyboobs
- new_subreddit_name # Add here
```
### Change AI Model
```yaml
# config.yaml
openrouter:
model: "new-model-name"
fallbackModels:
- "fallback-model-1"
- "fallback-model-2"
```
### Adjust Rate Limits
```yaml
# config.yaml
rateLimit:
minDelayMs: 45000 # Increase delay
maxMessagesPerHour: 15 # Reduce cap
jitterMs: 20000 # More jitter
```
### Enable Dry Run
```yaml
# config.yaml
dryRun: true # Logs all actions without sending
```
Or via dashboard: `PUT /api/config` with `{"dryRun": true}`
### Add Database Column
```typescript
// In src/database/client.ts
function runMigrations(db: Database) {
// ... existing migrations ...
// Check if column exists
const tableInfo = db.prepare(`PRAGMA table_info(sent_messages)`).all();
const hasNewColumn = tableInfo.some((col: any) => col.name === 'new_column');
if (!hasNewColumn) {
db.exec("ALTER TABLE sent_messages ADD COLUMN new_column TEXT");
}
}
```
### Add New API Endpoint
```typescript
// In src/web/server.ts
import { Request, Response } from 'express';
server.app.get('/api/new-endpoint', async (req: Request, res: Response) => {
try {
const result = await someService.doSomething();
res.json({ success: true, data: result });
} catch (err) {
res.status(500).json({ error: (err as Error).message });
}
});
```
---
## Known Issues
### Hardcoded Username in ChatService
`ChatService` has `myUsername = 'Upset_Marsupial1006'` hardcoded in JavaScript evaluation scripts. This should be parameterized from config.
**Fix needed**: Pass username to `page.evaluate()` calls.
### Shadow DOM Fragility
Reddit frequently updates their `faceplate-*` components. Shadow DOM traversal code may break without warning.
**Mitigation**: Use `scripts/inspect-chat-dom.ts` to debug when selectors change.
### No Test Coverage
The project has no automated tests. Any changes should be manually tested.
**Recommendation**: Add tests for critical paths:
- StrategySelector algorithm
- ChatService shadow DOM parsing
- OpenRouterService model fallback
### Single-File Dashboard
The entire dashboard is in `public/index.html` (~2000+ lines). Making changes requires editing a single large file.
**Recommendation**: Consider migrating to a proper frontend framework for maintainability.
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# Service Catalog
Detailed documentation for each service in the RedditBot codebase.
---
## Table of Contents
1. [MonitorService](#monitorservice)
2. [ProcessorService](#processorservice)
3. [StrategySelector](#strategypicker)
4. [ResponseChecker](#responsechecker)
5. [ChatService](#chatservice)
6. [MediaService](#mediaservice)
7. [MediaSyncService](#mediasyncservice)
8. [AutoReplyService](#autoreplyservice)
9. [RedditApi](#redditapi)
10. [OpenRouterService](#openrouterservice)
11. [BrowserClient](#browserclient)
12. [MessagePage](#messagepage)
13. [RateLimiter](#ratelimiter)
---
## MonitorService
**File**: `src/services/monitor.ts`
**Lines**: 72
**Responsibility**: Discover new image posts across configured subreddits
### Purpose
Polls configured subreddits at regular intervals, discovers new image posts, filters out already-processed posts and previously-messaged users, and returns the single newest valid post for processing.
### Public Methods
```typescript
class MonitorService {
constructor(
private redditApi: RedditApi,
private postsRepo: PostsRepository,
private messagesRepo: MessagesRepository,
private config: Config
)
/**
* Discover the next post to process.
* Returns null if no valid posts are available.
*/
discoverNextPost(): Promise<Post | null>
}
```
### Algorithm
1. Shuffle subreddit order (randomize polling order each cycle)
2. For each subreddit:
- Fetch new posts via `RedditApi.fetchPosts()`
- Filter: image posts only
- Filter: author not deleted
- Filter: post not already in `processed_posts`
- Filter: author not previously messaged (or meets re-message criteria)
3. Return the newest valid post across all subreddits
4. If no valid posts found, return `null`
### Dependencies
- `RedditApi` - Fetch posts from Reddit
- `PostsRepository` - Check for already-processed posts
- `MessagesRepository` - Check for previously-messaged users
- `Config` - Subreddit list, poll interval, target gender
### Error Handling
- Skips subreddits that return errors (continues to next)
- Logs errors at `warn` level
- Returns `null` on any unrecoverable error
---
## ProcessorService
**File**: `src/services/processor.ts`
**Lines**: 132
**Responsibility**: Core processing pipeline for discovered posts
### Purpose
Orchestrates the full processing pipeline for a single discovered post: image download, gender detection, AI analysis, strategy selection, message generation, and DM sending.
### Public Methods
```typescript
class ProcessorService {
constructor(
private config: Config,
private redditApi: RedditApi,
private openrouter: OpenRouterService,
private strategySelector: StrategySelector,
private messageSender: MessagePage,
private postsRepo: PostsRepository,
private messagesRepo: MessagesRepository,
private successfulRepo: SuccessfulMessagesRepository,
private logger: Logger
)
/**
* Process a single discovered post through the full pipeline.
*/
processPost(post: Post): Promise<void>
}
```
### Pipeline Steps
```
1. Download image
└─► ImageService.downloadImage(url)
└─► Validate MIME type (image/jpeg, image/png, image/webp)
└─► Validate file size
└─► Convert to base64
2. Quick gender detection (cost-saving pre-filter)
└─► OpenRouter.detectGenderOnly(image)
└─► Skip if gender doesn't match targetGender
3. Select A/B strategy variant
└─► StrategySelector.selectStrategy(subreddit, author)
4. Full AI analysis
└─► OpenRouter.analyzeImage(image)
└─► Detect gender, describe image
└─► Handle refusal (mark post, try next)
5. Generate message
└─► OpenRouter.generateMessage(analysis, title, examples, strategy)
└─► Few-shot examples from SuccessfulMessagesRepository
6. Send DM
└─► MessagePage.sendDM(author, "Stunning", message)
└─► Handle failure (log, don't mark as sent)
7. Record in database
└─► Mark post as processed
└─► Mark message_sent = 1 if successful
└─► Store generated_message for reference
```
### Error Handling
- AI refusal: Post is marked as processed with error, skipped
- Image download failure: Post is marked with error, skipped
- DM send failure: Post is marked as not sent, logged
- All errors logged with context (post ID, subreddit, author)
### Cost Optimization
- Quick gender detection costs less than full analysis
- Non-matching genders are skipped before expensive analysis
- AI refusal detection prevents wasted tokens on rejected prompts
---
## StrategySelector
**File**: `src/services/strategy-selector.ts`
**Lines**: 101
**Responsibility**: A/B testing with explore/exploit algorithm
### Purpose
Selects message variants (strategies) for each post using an explore/exploit algorithm based on historical response rates. Optimizes for maximum response rate over time while continuing to explore under-tested variants.
### Public Methods
```typescript
class StrategySelector {
constructor(
private config: Config,
private messagesRepo: MessagesRepository
)
/**
* Select the best strategy variant for a given subreddit/author.
*/
selectStrategy(subreddit: string, author: string): string
}
```
### Algorithm
1. **Get strategy stats** from `MessagesRepository`:
- Response count per variant
- Sent count per variant
- Response rate per variant
2. **Apply minimum sample threshold**:
- If a variant has fewer than `minSamples` sends, treat it as untested
- Untested variants are excluded from exploitation
3. **Explore vs Exploit decision**:
- With probability `explorationRate`, select a random variant (explore)
- Otherwise, select the variant with the highest response rate (exploit)
4. **Fallback**:
- If no variants have enough data, select randomly from enabled variants
### Configuration
```yaml
strategyVariants:
- name: "variant_a"
prompt: "Compliment-based message..."
enabled: true
- name: "variant_b"
prompt: "Question-based message..."
enabled: true
```
### Dependencies
- `Config` - Strategy variants, exploration rate, min samples
- `MessagesRepository` - Response rate statistics
---
## ResponseChecker
**File**: `src/services/response-checker.ts`
**Lines**: 179
**Responsibility**: Monitor inbox for user replies
### Purpose
Background service that navigates the Reddit inbox via Playwright, identifies responses to bot-sent messages, updates the database, and stores successful message/response pairs for few-shot learning.
### Public Methods
```typescript
class ResponseCheckerService {
constructor(
private browser: BrowserClient,
private messagesRepo: MessagesRepository,
private successfulRepo: SuccessfulMessagesRepository,
private logger: Logger
)
/**
* Check inbox for responses to sent messages.
*/
checkResponses(): Promise<void>
}
```
### Algorithm
1. Navigate to `/message/inbox` via Playwright
2. Parse inbox items (messages, conversations)
3. For each response item:
- Extract recipient username and message text
- Match to `sent_messages` by recipient + timestamp proximity
- Update `got_response = 1` and `response_checked_at`
- Store the message/response pair in `successful_messages`
4. Update strategy statistics (response rates)
### Dependencies
- `BrowserClient` - Playwright browser context
- `MessagesRepository` - Update response flags
- `SuccessfulMessagesRepository` - Store learning pairs
- `Logger` - Activity logging
---
## ChatService
**File**: `src/services/chat.ts`
**Lines**: 1123+
**Responsibility**: Reddit chat scraping, messaging, and conversation management
### Purpose
The most complex service in the codebase. Manages Reddit chat interactions including scraping active conversations, loading conversation history, sending messages with human-like delays, detecting upsell/spam, and managing conversation caches.
### Public Methods
```typescript
class ChatService {
constructor(
private browser: BrowserClient,
private config: Config,
private logger: Logger
)
/** Fetch active conversations from Reddit */
fetchChats(): Promise<ChatSummary[]>
/** Load full conversation history */
loadConversation(chatId: string): Promise<Conversation>
/** Send a message in a conversation */
sendMessage(chatId: string, text: string): Promise<boolean>
/** Get cached conversations */
getCachedConversations(): Conversation[]
/** Check for new messages in conversations */
checkForUpdates(): Promise<Conversation[]>
/** Detect upsell/spam in a message */
detectUpsell(message: string): boolean
}
```
### Shadow DOM Handling
Reddit uses custom `faceplate-*` web components with shadow DOM. Standard CSS selectors cannot pierce these boundaries. The service uses JavaScript injection via `page.evaluate()`:
```javascript
// Traverse shadow roots to find chat elements
function traverseShadowRoots(root) {
const elements = root.querySelectorAll('.some-class');
const shadowChildren = root.querySelectorAll('*::shadow, ::deep');
// ... recursive traversal
}
```
### Conversation Cache
Conversations are cached in two layers:
1. **In-memory**: Fast access for active conversations
2. **Disk JSON**: Persistence across restarts at `data/chats/`
Cache structure:
```json
{
"chatId": "abc123",
"participants": ["user1", "bot"],
"messages": [
{ "author": "user1", "text": "Hey!", "timestamp": 1234567890 }
],
"lastUpdated": 1234567890,
"hasNewMessages": false
}
```
### Human-Like Messaging
Messages are sent with:
- Typing delay simulation (random delay before "typing" starts)
- Variable typing speed
- Random delays between messages
- Delivery verification
### Known Issues
- **Hardcoded username**: `myUsername = 'Upset_Marsupial1006'` is hardcoded in JS evaluation scripts. Should be parameterized from `Config`.
- **Size**: 1123+ lines suggests this should be split into smaller services.
### Dependencies
- `BrowserClient` - Playwright browser context
- `Config` - Rate limits, username (should be), check intervals
- `Logger` - Activity logging
---
## MediaService
**File**: `src/services/media.ts`
**Lines**: 254
**Responsibility**: Media download, caching, and indexing
### Purpose
Downloads images from chat conversations, resolves Matrix blurred thumbnails to full resolution, stores files locally, and maintains a deduplicated index.
### Public Methods
```typescript
class MediaService {
constructor(
private config: Config,
private browser: BrowserClient,
private logger: Logger
)
/** Download media from a conversation */
downloadMedia(chatId: string): Promise<string[]>
/** Get media index */
getIndex(): MediaIndex
/** Get a specific media file path */
getPath(hash: string): string | null
}
```
### Deduplication
Files are deduplicated using SHA-1 hashing:
```
SHA-1(image_bytes) → data/media/{hash}.{ext}
```
The index maps hashes to file paths:
```json
{
"abc123def456": "abc123def456.jpg",
"789xyz012abc": "789xyz012abc.png"
}
```
### Matrix Thumbnail Resolution
Reddit's Matrix system uses blurred placeholder thumbnails. The service resolves these to full resolution by:
1. Detecting Matrix thumbnail URLs
2. Extracting the full-resolution URL from the response
3. Downloading the full-resolution image
### Dependencies
- `Config` - Media directory path
- `BrowserClient` - Playwright for Matrix resolution
- `Logger` - Download activity
---
## MediaSyncService
**File**: `src/services/media-sync.ts`
**Lines**: 119
**Responsibility**: Periodic background media synchronization
### Purpose
Runs periodic background syncs to download media from chat conversations. Supports both incremental (top 10 chats) and full (all conversations) sync modes.
### Public Methods
```typescript
class MediaSyncService {
constructor(
private config: Config,
private mediaService: MediaService,
private chatService: ChatService,
private logger: Logger
)
/** Start periodic sync */
start(): void
/** Stop periodic sync */
stop(): void
/** Trigger incremental sync */
syncIncremental(): Promise<void>
/** Trigger full sync */
syncFull(): Promise<void>
/** Get sync status */
getStatus(): SyncStatus
}
```
### Sync Modes
| Mode | Description | Use Case |
|---|---|---|
| Incremental | Top 10 most recent conversations | Regular background sync |
| Full | All conversations | Initial setup, catch-up |
### Dependencies
- `Config` - Sync interval, enabled flag
- `MediaService` - Actual download logic
- `ChatService` - Conversation list
- `Logger` - Sync progress
---
## AutoReplyService
**File**: `src/services/auto-reply.ts`
**Lines**: 199
**Responsibility**: Automated reply to chat conversations
### Purpose
Monitors cached conversations for unread messages, detects upsell/spam, generates AI reply suggestions, and either auto-sends or marks as pending for manual approval.
### Public Methods
```typescript
class AutoReplyService {
constructor(
private config: Config,
private chatService: ChatService,
private openrouter: OpenRouterService,
private logger: Logger
)
/** Start auto-reply checking */
start(): void
/** Stop auto-reply checking */
stop(): void
/** Check for unread messages and generate replies */
checkAndReply(): Promise<void>
}
```
### Workflow
```
1. Check cached conversations for unread messages
│
├─► Skip if no new messages
│
├─► Detect upsell/spam keywords
│ └─► Flag conversation, skip reply
│
├─► Generate AI reply suggestion
│ └─► OpenRouter.generateReply(conversation history)
│
├─► If autoSend: send reply immediately
│ └─► ChatService.sendMessage()
│
└─► If !autoSend: mark as pending
└─► Dashboard shows pending replies for approval
```
### Dependencies
- `Config` - Enabled flag, autoSend flag, check interval
- `ChatService` - Conversation access, message sending
- `OpenRouterService` - Reply generation
- `Logger` - Activity logging
---
## RedditApi
**File**: `src/reddit/api.ts`
**Lines**: 233
**Responsibility**: Reddit API client
### Purpose
Axios-based client for interacting with Reddit's public API. Handles post fetching, user profile checking, and authenticated requests using Playwright browser cookies.
### Public Methods
```typescript
class RedditApi {
constructor(
private browser: BrowserClient,
private logger: Logger
)
/** Fetch new posts from a subreddit */
fetchPosts(subreddit: string, limit?: number): Promise<Post[]>
/** Check if a user is a seller/spam */
checkUserProfile(username: string): Promise<UserProfile>
/** Make authenticated request using browser cookies */
authenticatedRequest(url: string): Promise<any>
}
```
### Image URL Resolution
Fallback chain for extracting image URLs from post data:
```
1. post.preview.reddits[0].url (Reddit CDN preview)
2. post.url (i.redd.it direct)
3. post.thumbnail (if not self/spam)
4. Scan post.selftext for imgur/image links
```
### Seller/Spam Detection
Checks user profile for keywords:
- "seller"
- "onlyfans"
- "link in bio"
- Other configured `sellerKeywords`
### Dependencies
- `BrowserClient` - Browser cookies for authentication
- `Logger` - Request logging
---
## OpenRouterService
**File**: `src/ai/openrouter.ts`
**Lines**: 307
**Responsibility**: OpenRouter AI client
### Purpose
Client for the OpenRouter API (OpenAI-compatible SDK). Provides image analysis, message generation, reply suggestions, and upsell detection.
### Public Methods
```typescript
class OpenRouterService {
constructor(private config: Config, private logger: Logger)
/** Full image analysis with model fallback */
analyzeImage(imageBase64: string): Promise<ImageAnalysis>
/** Quick gender detection (cost-saving) */
detectGenderOnly(imageBase64: string): Promise<string>
/** Generate DM message */
generateMessage(
imageAnalysis: ImageAnalysis,
postTitle: string,
strategy: string
): Promise<string>
/** Generate chat reply */
generateReply(conversationHistory: Message[]): Promise<string>
/** Detect upsell/spam keywords */
detectUpsell(message: string): boolean
}
```
### Model Fallback Chain
```
Primary model (config.openrouter.model)
│
└─► If refusal detected:
│
└─► Try each fallback model (config.openrouter.fallbackModels)
│
└─► If all fail: throw error
```
### Refusal Detection
Heuristic patterns to detect when AI models refuse to process prompts:
```typescript
const refusalPatterns = [
/cannot.*analyze/i,
/unable.*process/i,
/against.*policy/i,
/cannot.*view/i,
// ...
];
```
### Few-Shot Learning
`generateMessage()` retrieves successful message/response pairs from the database and includes them as examples in the prompt:
```
"Here are examples of messages that got responses:
- Example 1: {original_message} → {response_snippet}
- Example 2: ...
Generate a similar message for this image..."
```
### Dependencies
- `Config` - API key, model selection, prompts
- `MessagesRepository` - Successful examples for few-shot learning
---
## BrowserClient
**File**: `src/browser/client.ts`
**Lines**: 302
**Responsibility**: Playwright persistent context manager
### Purpose
Manages the Playwright browser session with persistent cookies/storage. Handles automated login, session verification, and 2FA/captcha detection.
### Public Methods
```typescript
class BrowserClient {
constructor(private config: Config, private logger: Logger)
/** Initialize browser context */
initialize(): Promise<void>
/** Verify browser session is active */
verifySession(): Promise<boolean>
/** Perform automated login */
login(): Promise<void>
/** Get page context for operations */
getPage(): Promise<Page>
/** Close browser */
close(): Promise<void>
}
```
### Login Flow
```
1. Navigate to Reddit login page
2. Fill username and password
3. Submit form
4. Check for 2FA prompt
└─► If present: wait for manual input (with timeout)
5. Check for captcha
└─► If present: log warning, wait
6. Verify login success:
└─► Check for user menu indicator
└─► Check for profile avatar
└─► Fallback: API request to /api/me
7. Save cookies to persistent directory
8. On failure: capture debug screenshot
```
### Session Persistence
- Cookies and storage are saved to `config.browser.userDataDir`
- Subsequent launches restore the session automatically
- Session expires when Reddit cookies expire (requires re-login)
### Dependencies
- `Config` - Credentials, headless mode, user data dir
- `Logger` - Login progress, errors
---
## MessagePage
**File**: `src/browser/message-page.ts`
**Lines**: 560
**Responsibility**: Reddit DM compose page automation
### Purpose
Automates the Reddit DM compose page: filling recipient/subject/body fields, handling shadow DOM components, submitting messages, and verifying success.
### Public Methods
```typescript
class MessagePage {
constructor(
private browser: BrowserClient,
private config: Config,
private logger: Logger
)
/** Send a DM to a recipient */
sendDM(recipient: string, subject: string, body: string): Promise<boolean>
/** Check if recipient field shows an error */
hasRecipientError(page: Page): Promise<boolean>
}
```
### Shadow DOM Handling
Reddit's compose form uses `faceplate-*` web components:
```javascript
// Fill shadow DOM input fields
page.evaluate(({ selector, value }) => {
const shadowInput = document.querySelector(`${selector} input`);
if (shadowInput) {
shadowInput.value = value;
shadowInput.dispatchEvent(new Event('input', { bubbles: true }));
}
}, { selector: 'faceplate-textarea[name="body"]', value: body });
```
### Dry Run Mode
When `config.dryRun` is enabled:
- All fields are filled as normal
- Submit button is NOT clicked
- Message is logged but not sent
- Returns `true` (simulates success)
### Dependencies
- `BrowserClient` - Playwright page access
- `Config` - Dry run mode
- `Logger` - Send activity
---
## RateLimiter
**File**: `src/utils/rate-limiter.ts`
**Lines**: 114
**Responsibility**: Token-bucket rate limiting
### Purpose
Enforces rate limits on bot actions (primarily message sending) to avoid detection and bans. Uses a combination of minimum delay, random jitter, and hourly caps.
### Public Methods
```typescript
class RateLimiter {
constructor(config: RateLimitConfig)
/** Wait until a slot is available */
waitForSlot(): Promise<void>
/** Get remaining time until next slot */
getTimeUntilSlot(): number
/** Get current hourly count */
getHourlyCount(): number
/** Reset hourly counter */
resetHourlyCounter(): void
}
```
### Rate Limiting Strategy
```
1. Check hourly cap:
└─► If maxMessagesPerHour reached: wait until hour rolls over
2. Enforce minimum delay:
└─► lastActionTime + minDelayMs + random(0, jitterMs)
3. Track action timestamp
4. Increment hourly counter
```
### Dependencies
- `Config` - Rate limit settings
- `p-queue` - Concurrency control