working bot, cleaned up git

.env.example

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+# Signal configuration
+SIGNAL_PHONE_NUMBER=+1234567890
+
+# PrivateMode API configuration
+PRIVATEMODE_BASE_URL=http://localhost:8080
+# Optional: Model to use (if not specified, will use first available model)
+# PRIVATEMODE_MODEL=ibnzterrell/Meta-Llama-3.3-70B-Instruct-AWQ-INT4
+
+# Permission System Configuration
+# Path to permissions configuration file (default: permissions.json)
+# PERMISSIONS_CONFIG_PATH=permissions.json
+
+# Signal Service Configuration
+# Signal CLI REST API service endpoint (default: localhost:8080)
+# SIGNAL_SERVICE=localhost:8080
+
+# Security Configuration
+# Enable/disable permission system (default: enabled)
+# PERMISSIONS_ENABLED=true
+
+# Logging Configuration
+# Log level for permission system (default: INFO)
+# PERMISSIONS_LOG_LEVEL=INFO
+
+# Admin Configuration
+# Default admin phone number for initial setup
+# Set this to your phone number to get admin access on first run
+# ADMIN_PHONE_NUMBER=+1234567890
+
+# Whisper ASR Configuration
+# Comma-separated list of Whisper ASR instance URLs (supports failover)
+# Examples for different setups:
+#   - Host machine: http://localhost:9000,http://localhost:9001
+#   - Docker container (bridge network): http://172.17.0.1:9000
+#   - Docker container (host network): http://localhost:9000
+#   - External server: http://whisper.example.com:9000
+# Multiple instances for failover: http://localhost:9000,http://localhost:9001,http://backup-whisper:9000
+WHISPER_ASR_URLS=http://localhost:9000
+# Optional: Whisper output format (text, json, vtt, srt, tsv)
+WHISPER_OUTPUT_FORMAT=text
+# Optional: Enable voice activity detection filter
+WHISPER_VAD_FILTER=true
+# Optional: Language for transcription (auto-detect if not specified)
+# WHISPER_LANGUAGE=en
+
+# Voice Activation Configuration
+# Phrase that triggers AI chat from voice messages (default: "hey jarvis")
+# Examples: "hey computer", "assistant", "ai", "bot"
+VOICE_ACTIVATION_PHRASE=hey jarvis

Dockerfile

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+FROM python:3.11-slim
+
+WORKDIR /app
+COPY permissions.json .
+COPY requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+
+COPY signal_bot.py .
+
+CMD ["python", "signal_bot.py"]

README.md

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+# Shifra - Signal enabled confidential AI.
+
+A Signal messenger bot that gives you AI agent in your chat.
+
+## Features
+
+- Chat with AI assistant via Signal messages
+- Voice message transcription with Whisper ASR
+- Multi-instance Whisper support with automatic failover
+- Maintains conversation context
+- Simple command interface
+- Docker deployment ready
+
+## Setup
+
+1. Copy `.env.example` to `.env` and configure:
+   ```bash
+   cp .env.example .env
+   ```
+
+2. Edit `.env` with your configuration:
+   - `SIGNAL_PHONE_NUMBER`: Your Signal phone number (e.g., +1234567890)
+   - `PRIVATEMODE_BASE_URL`: URL of PrivateMode.ai API (default: http://localhost:8080)
+   - `PRIVATEMODE_MODEL`: Optional - specific model to use (if not set, uses first available)
+   - `WHISPER_ASR_URLS`: Comma-separated list of Whisper ASR instances (e.g., http://localhost:9000,http://localhost:9001)
+   - `WHISPER_OUTPUT_FORMAT`: Output format for transcription (default: text)
+   - `WHISPER_VAD_FILTER`: Enable voice activity detection (default: true)
+   - `WHISPER_LANGUAGE`: Optional - language for transcription (auto-detect if not set)
+
+3. Link Signal account (first time only):
+   ```bash
+   docker compose run --rm signal-cli-rest-api signal-cli link -n "Signal Bot"
+   ```
+   Follow the instructions to scan QR code with Signal app.
+
+4. Start the bot:
+   ```bash
+   docker compose up -d
+   ```
+
+## Usage
+
+Send messages to the bot:
+
+- `!chat <message>` - Chat with AI assistant
+- `!clear` - Clear conversation history
+- `!models` - List available AI models
+- `!help` - Show available commands
+- Any message without command prefix is treated as chat
+- **Voice messages** - Send or forward voice memos for automatic transcription
+
+## Available Models
+
+The bot can use any model available through PrivateMode.ai API. Use `!models` command to see available models. Example models:
+- `ibnzterrell/Meta-Llama-3.3-70B-Instruct-AWQ-INT4`
+
+## Development
+
+Run locally:
+```bash
+pip install -r requirements.txt
+python signal_bot.py
+```
+
+## Architecture
+
+- Uses `signalbot` library for Signal integration
+- Connects to PrivateMode.ai Chat Completions API endpoint
+- Integrates with Whisper ASR for voice transcription
+- Maintains conversation context per sender (last 10 messages)
+- Supports docker deployment with signal-cli-rest-api
+- No authentication required (follows PrivateMode.ai approach)
+
+## Whisper ASR Integration
+
+The bot supports voice message transcription using Whisper ASR. The docker-compose configuration uses `network_mode: "host"` to ensure the Signal bot can access Whisper instances running on:
+
+- **Host machine**: Use `http://localhost:9000` or `http://127.0.0.1:9000`
+- **Docker containers (bridge network)**: Use `http://172.17.0.1:9000` (Docker's default bridge gateway)
+- **Docker containers (host network)**: Use `http://localhost:9000`
+- **External servers**: Use the server's URL (e.g., `http://whisper.example.com:9000`)
+
+### Multiple Whisper Instances
+
+Configure multiple Whisper instances for automatic failover:
+```bash
+WHISPER_ASR_URLS=http://localhost:9000,http://localhost:9001,http://backup-server:9000
+```
+
+If the first instance fails or is unavailable, the bot automatically tries the next one in the list.
+
+### Voice Message Processing
+
+1. User sends or forwards a voice message to the Signal chat
+2. Bot detects the voice attachment
+3. Audio is sent to the first available Whisper instance
+4. Transcribed text is returned with a 📝 prefix
+5. Transcription is stored in conversation history for context

docker-compose.yml

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+services:
+  signal-bot:
+    build: .
+    env_file: .env
+    network_mode: "host"
+    environment:
+      - SIGNAL_SERVICE=127.0.0.1:18380
+      - SIGNAL_PHONE_NUMBER=${SIGNAL_PHONE_NUMBER}
+      - PRIVATEMODE_BASE_URL=${PRIVATEMODE_BASE_URL}
+      - PRIVATEMODE_MODEL=${PRIVATEMODE_MODEL}
+      - WHISPER_ASR_URLS=${WHISPER_ASR_URLS}
+      - WHISPER_OUTPUT_FORMAT=${WHISPER_OUTPUT_FORMAT:-text}
+      - WHISPER_VAD_FILTER=${WHISPER_VAD_FILTER:-true}
+      - WHISPER_LANGUAGE=${WHISPER_LANGUAGE:-}
+    volumes:
+      - ./.env:/app/.env
+    restart: unless-stopped
+
+  privatemode-proxy:
+    image: ghcr.io/edgelesssys/privatemode/privatemode-proxy:latest
+    environment:
+      - PRIVATEMODE_API_KEY=${PRIVATEMODE_API_KEY:-}
+      - PRIVATEMODE_CACHE_MODE=${PRIVATEMODE_CACHE_MODE:-none}
+      - PRIVATEMODE_CACHE_SALT=${PRIVATEMODE_CACHE_SALT:-}
+    entrypoint: ["/bin/privatemode-proxy"]
+    command: [
+      "--apiKey=${PRIVATEMODE_API_KEY}",
+      "--port=8080"
+    ]
+    ports:
+      - "28082:8080"
+    restart: unless-stopped
+
+

example_permissions.json

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+{
+  "roles": {
+    "admin": {
+      "description": "Full access to all commands and user management",
+      "permissions": ["*"]
+    },
+    "user": {
+      "description": "Standard user with chat access",
+      "permissions": ["chat", "clear", "models", "help"]
+    },
+    "guest": {
+      "description": "Limited access user",
+      "permissions": ["help"]
+    }
+  },
+  "users": {
+    "+123456789": {
+      "role": "admin",
+      "name": "Default Admin",
+      "added_by": "system",
+      "added_at": "2024-01-01T00:00:00Z"
+    }
+  }
+}

requirements.txt

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+signalbot==0.8.0
+aiohttp==3.10.11
+python-dotenv==1.0.1
+pyyaml==6.0.2
+watchdog==3.0.0