Docs: Update README and CLAUDE.md for recent architecture changes

- Updated docs to reflect switch to Bigrams (order 1)
- Documented incremental DB updates and performance caching
- Added mention of @-ping protection in features
- Updated AI context guidance (20 messages instead of 50)
- Fixed AI_SYSTEM_PROMPT env fallback in index.ts

CLAUDE.md

@@ -4,7 +4,7 @@ This file provides guidance to Claude Code (claude.ai/code) when working with co
 
 ## Project Overview
 
-Telegram bot built with TypeScript and [Telegraf](https://telegraf.js.org/). Uses Markov chains with trigrams to generate sentences from learned messages. Optional KI/LLM integration via OpenAI-compatible API. Each chat has its own isolated data.
+Telegram bot built with TypeScript and [Telegraf](https://telegraf.js.org/). Uses Markov chains with bigrams to generate sentences from learned messages. Optional KI/LLM integration via OpenAI-compatible API. Each chat has its own isolated data.
 
 ## Commands
 
@@ -20,52 +20,54 @@ docker compose up -d --build  # Docker deployment
 ```
 src/
 ├── index.ts      # Bot entry point, commands, setup wizard
-├── markov.ts     # Markov chain with trigram support
-├── database.ts   # SQLite persistence layer
+├── markov.ts     # Markov chain with bigram support (order 1)
+├── database.ts   # SQLite persistence layer (optimized)
 └── ai.ts         # OpenAI-compatible client
 ```
 
 **Data flow (Markov):**
-1. Message received → `chain.learn(text)` → SQLite
+1. Message received → `chain.learn(text)` → `updateChain(learned)` → SQLite (incremental)
 2. Trigger check (reply/mention/random)
-3. If triggered → `chain.generate()` → reply
+3. If triggered → `chain.generate()` → sanitize (@-removal) → reply
 
 **Data flow (AI):**
 1. `/ask-ai` or trigger word detected
-2. Load last 50 messages as context
+2. Load last 20 messages as context
 3. Build prompt (global + group prompt)
-4. Call OpenAI-compatible API → reply
+4. Call OpenAI-compatible API → sanitize (@-removal) → reply
 
 **Per-chat isolation:**
 - Each chat has separate Markov chain data
 - Each chat has separate AI settings
-- Each chat has separate message context (50 messages)
+- Each chat has separate message context (20 messages)
 
 ## Key Implementation Details
 
 ### Markov Chain (markov.ts)
-- Uses **trigrams** (order=2): "word1 word2" → "word3"
+- Uses **bigrams** (order=1): "word1" → "word2" for higher creativity
 - Weighted random selection based on frequency
-- Generates sentences up to 20 words
+- No character filtering (keeps emojis/punctuation)
 
 ### Database (database.ts)
 - SQLite with `better-sqlite3` (synchronous API)
+- **Optimized storage:** `updateChain` uses `ON CONFLICT` for incremental updates (no full rewrites)
 - Tables:
   - `chat_settings` - Markov probability
   - `markov_transitions` - Word transitions
   - `markov_starts` - Sentence starts
   - `ai_settings` - KI configuration per chat
-  - `message_context` - Last 50 messages per chat
+  - `message_context` - Last 20 messages per chat
   - `setup_sessions` - Setup wizard state
 - Automatic cleanup every 24h
 
 ### AI Client (ai.ts)
 - OpenAI-compatible API (works with OpenAI, Ollama, OpenRouter, etc.)
+- Parameters: `temperature: 0.8`, `presence_penalty: 0.6`, `frequency_penalty: 0.6`
 - Prompt system:
   - Global: `data/system-prompt.txt` → `.env` fallback → default
   - Group-specific: stored in DB per chat
 - API key masking for security
-- Context: Last 50 messages
+- Context: Last 20 messages
 
 ### Setup Wizard
 - Started via `/ai setup` in group
@@ -73,6 +75,12 @@ src/
 - API keys never shown in full
 - Steps: Provider → API Key → Model → URL → Trigger/Prob → Group Prompt
 
+### Performance Features
+- **Admin Cache:** 5-minute cache for chat administrators to reduce API calls
+- **Bot Info Cache:** Cached bot username and ID
+- **Incremental DB:** Markov updates don't delete existing data
+- **Typing Status:** AI responses show "typing" status while generating
+
 ## Environment
 
 ```env
@@ -80,46 +88,14 @@ BOT_TOKEN=                    # Telegram bot token (required)
 AI_DEFAULT_API_KEY=           # Default API key (optional)
 AI_DEFAULT_BASE_URL=          # Default API URL (default: OpenAI)
 AI_DEFAULT_MODEL=             # Default model (default: gpt-4o-mini)
-AI_SYSTEM_PROMPT=             # Global system prompt (fallback, see below)
+AI_SYSTEM_PROMPT=             # Global system prompt (fallback)
 ```
 
 **System Prompt Loading:**
 1. `data/system-prompt.txt` (persistent, editable without rebuild)
 2. `AI_SYSTEM_PROMPT` env variable (fallback)
 3. Hardcoded default (last resort)
-AI_DEFAULT_MODEL=             # Default model (default: gpt-4o-mini)
-AI_SYSTEM_PROMPT=             # Global system prompt
-```
 
-## Database Schema
+## Response Triggers & Sanitization
 
-```sql
--- Markov
-chat_settings (chat_id, probability)
-markov_transitions (chat_id, key, next_word, count)
-markov_starts (chat_id, key, count)
-
--- AI
-ai_settings (chat_id, enabled, trigger_word, random_prob, group_prompt, provider, base_url, model, api_key)
-message_context (chat_id, role, content, timestamp)
-setup_sessions (user_id, chat_id, step, data)
-```
-
-## Response Triggers
-
-### Markov (always active)
-1. Reply to bot's message → always respond
-2. @username mention → always respond
-3. Random probability (configurable per chat)
-
-### AI (when enabled)
-1. `/ask-ai [text]` command
-2. Trigger word (configurable, default: "ask-ai")
-3. Random probability (configurable, default: 0%)
-
-## Security
-
-- API keys stored in database, never logged
-- API keys masked in `/ai status` output: `sk-***...***xyz`
-- Setup only via private chat
-- Admin-only configuration commands
+- **@-Ping Protection:** All responses (AI & Markov) have `@` symbols removed before sending to prevent user notifications.

README.md

@@ -5,11 +5,12 @@ Ein Telegram-Bot, der mithilfe von Markov Chains neue Sätze aus vorherigen Nach
 ## Features
 
 - Lernt von allen Text-Nachrichten in einer Gruppe
-- Generiert grammatikalisch sinnvolle Sätze mit Trigrammen
+- Generiert kreative Sätze mit Bigrammen (hohe Diversität)
+- **Automatischer @-Ping-Schutz** (entfernt @ vor dem Senden)
 - Antwortet bei Reply, Erwähnung (@username) oder zufällig
 - Pro-Chat-Wahrscheinlichkeit einstellbar (Admins)
 - **KI/LLM-Integration** (OpenAI, Ollama, OpenRouter, etc.)
-- Persistente SQLite-Datenbank
+- **Leistungsoptimiert:** Inkrementelle SQLite-Updates statt kompletter Rewrites
 - Docker-Support
 
 ## Schnellstart
@@ -154,8 +155,8 @@ src/
 └── ai.ts         # OpenAI-kompatibler Client
 ```
 
-- **Markov Chain** mit Trigrammen für bessere Grammatik
-- **SQLite** für persistente Speicherung
+- **Markov Chain** mit Bigrammen für hohe Kreativität und Abwechslung
+- **SQLite** mit performanten ON CONFLICT Updates
 - Pro Chat separate Daten/Lernkurve
 
 ### Datenbank-Cleanup

src/index.ts

@@ -56,14 +56,20 @@ function initSystemPrompt(): string {
 
   // Load from persistent file
   try {
-    const prompt = readFileSync(PERSISTENT_PROMPT_FILE, 'utf-8').trim();
+    let prompt = readFileSync(PERSISTENT_PROMPT_FILE, 'utf-8').trim();
+    
+    // Fallback to .env if file is empty
+    if (!prompt && process.env.AI_SYSTEM_PROMPT) {
+      prompt = process.env.AI_SYSTEM_PROMPT.trim();
+    }
+
     if (!prompt) {
-      console.warn('system-prompt.txt is empty, AI will use minimal default');
+      console.warn('system-prompt.txt and AI_SYSTEM_PROMPT env are empty, AI will use minimal default');
     }
     return prompt || 'Du bist ein freundlicher Chat-Bot.';
   } catch (error) {
-    console.warn('Could not load system-prompt.txt:', error);
-    return 'Du bist ein freundlicher Chat-Bot.';
+    console.warn('Could not load system-prompt.txt, checking .env fallback:', error);
+    return process.env.AI_SYSTEM_PROMPT || 'Du bist ein freundlicher Chat-Bot.';
   }
 }