Refactor: Clean up obsolete files and organize codebase structure

This commit removes deprecated modules and reorganizes code into logical directories:

Deleted files (superseded by newer systems):
- claude_code_server.py (replaced by agent-sdk direct integration)
- heartbeat.py (superseded by scheduled_tasks.py)
- pulse_brain.py (unused in production)
- config/pulse_brain_config.py (obsolete config)

Created directory structure:
- examples/ (7 example files: example_*.py, demo_*.py)
- tests/ (5 test files: test_*.py)

Updated imports:
- agent.py: Removed heartbeat module and all enable_heartbeat logic
- bot_runner.py: Removed heartbeat parameter from Agent initialization
- llm_interface.py: Updated deprecated claude_code_server message

Preserved essential files:
- hooks.py (for future use)
- adapters/skill_integration.py (for future use)
- All Google integration tools (Gmail, Calendar, Contacts)
- GLM provider code (backward compatibility)

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>

CLAUDE_CODE_SETUP.md

@@ -0,0 +1,256 @@
+# Claude Agent SDK Setup
+
+Use your **Claude Pro subscription** OR **API key** with ajarbot - no separate server needed.
+
+## What is the Agent SDK?
+
+The Claude Agent SDK lets you use Claude directly from Python using either:
+- **Your Pro subscription** (unlimited usage within Pro limits)
+- **Your API key** (pay-per-token)
+
+The SDK automatically handles authentication and runs Claude in-process - no FastAPI server required.
+
+## Quick Start
+
+### 1. Install Dependencies
+
+```bash
+pip install -r requirements.txt
+```
+
+This installs `claude-agent-sdk` along with all other dependencies.
+
+### 2. Choose Your Mode
+
+Set `AJARBOT_LLM_MODE` in your `.env` file (or leave it unset for default):
+
+```bash
+# Use Claude Pro subscription (default - recommended for personal use)
+AJARBOT_LLM_MODE=agent-sdk
+
+# OR use pay-per-token API
+AJARBOT_LLM_MODE=api
+ANTHROPIC_API_KEY=sk-ant-...
+```
+
+### 3. Authenticate (Agent SDK mode only)
+
+If using `agent-sdk` mode, authenticate with Claude CLI:
+
+```bash
+# Install Claude CLI (if not already installed)
+# Download from: https://claude.ai/download
+
+# Login with your Claude account
+claude auth login
+```
+
+This opens a browser window to authenticate with your claude.ai account.
+
+### 4. Run Your Bot
+
+**Windows:**
+```bash
+run.bat
+```
+
+**Linux/Mac:**
+```bash
+python ajarbot.py
+```
+
+That's it! No separate server to manage.
+
+## Architecture Comparison
+
+### Old Setup (Deprecated)
+```
+Telegram/Slack → ajarbot → FastAPI Server (localhost:8000) → Claude Code SDK → Claude
+```
+
+### New Setup (Current)
+```
+Telegram/Slack → ajarbot → Claude Agent SDK → Claude (Pro OR API)
+```
+
+The new setup eliminates the FastAPI server, reducing complexity and removing an extra process.
+
+## Mode Details
+
+### Agent SDK Mode (Default)
+
+**Pros:**
+- Uses Pro subscription (unlimited within Pro limits)
+- No API key needed
+- Higher context window (200K tokens)
+- Simple authentication via Claude CLI
+
+**Cons:**
+- Requires Node.js and Claude CLI installed
+- Subject to Pro subscription rate limits
+- Not suitable for multi-user production
+
+**Setup:**
+```bash
+# .env file
+AJARBOT_LLM_MODE=agent-sdk
+
+# Authenticate once
+claude auth login
+```
+
+### API Mode
+
+**Pros:**
+- No CLI authentication needed
+- Predictable pay-per-token pricing
+- Works in any environment (no Node.js required)
+- Better for production/multi-user scenarios
+
+**Cons:**
+- Costs money per API call
+- Requires managing API keys
+
+**Setup:**
+```bash
+# .env file
+AJARBOT_LLM_MODE=api
+ANTHROPIC_API_KEY=sk-ant-...
+```
+
+## Cost Comparison
+
+| Mode | Cost Model | Best For |
+|------|-----------|----------|
+| **Agent SDK (Pro)** | $20/month flat rate | Heavy personal usage |
+| **API (pay-per-token)** | ~$0.25-$3 per 1M tokens | Light usage, production |
+
+With default Haiku model, API mode costs approximately:
+- ~$0.04/day for moderate personal use (1000 messages/month)
+- ~$1.20/month for light usage
+
+## Pre-Flight Checks
+
+The `ajarbot.py` launcher runs automatic checks before starting:
+
+**Agent SDK mode checks:**
+- Python 3.10+
+- Node.js available
+- Claude CLI authenticated
+- Config file exists
+
+**API mode checks:**
+- Python 3.10+
+- `.env` file exists
+- `ANTHROPIC_API_KEY` is set
+- Config file exists
+
+Run health check manually:
+```bash
+python ajarbot.py --health
+```
+
+## Troubleshooting
+
+### "Node.js not found"
+Agent SDK mode requires Node.js. Either:
+1. Install Node.js from https://nodejs.org
+2. Switch to API mode (set `AJARBOT_LLM_MODE=api`)
+
+### "Claude CLI not authenticated"
+```bash
+# Check authentication status
+claude auth status
+
+# Re-authenticate
+claude auth logout
+claude auth login
+```
+
+### "Agent SDK not available"
+```bash
+pip install claude-agent-sdk
+```
+
+If installation fails, switch to API mode.
+
+### Rate Limits (Agent SDK mode)
+
+If you hit Pro subscription limits:
+- Wait for limit refresh (usually 24 hours)
+- Switch to API mode temporarily:
+  ```bash
+  # In .env
+  AJARBOT_LLM_MODE=api
+  ANTHROPIC_API_KEY=sk-ant-...
+  ```
+
+### "ANTHROPIC_API_KEY not set" (API mode)
+
+Create a `.env` file in the project root:
+```bash
+cp .env.example .env
+# Edit .env and add your API key
+```
+
+Get your API key from: https://console.anthropic.com/settings/keys
+
+## Migration from Old Setup
+
+If you previously used the FastAPI server (`claude_code_server.py`):
+
+1. **Remove old environment variables:**
+   ```bash
+   # Delete these from .env
+   USE_CLAUDE_CODE_SERVER=true
+   CLAUDE_CODE_SERVER_URL=http://localhost:8000
+   ```
+
+2. **Set new mode:**
+   ```bash
+   # Add to .env
+   AJARBOT_LLM_MODE=agent-sdk  # or "api"
+   ```
+
+3. **Stop the old server** (no longer needed):
+   - The `claude_code_server.py` process can be stopped
+   - It's no longer used
+
+4. **Run with new launcher:**
+   ```bash
+   run.bat  # Windows
+   python ajarbot.py  # Linux/Mac
+   ```
+
+See [MIGRATION.md](MIGRATION.md) for detailed migration guide.
+
+## Features
+
+All ajarbot features work in both modes:
+- 15 tools (file ops, system commands, Gmail, Calendar, Contacts)
+- Multi-platform adapters (Slack, Telegram)
+- Memory system with hybrid search
+- Task scheduling
+- Google integration (Gmail, Calendar, Contacts)
+- Usage tracking (API mode only)
+
+## Security
+
+**Agent SDK mode:**
+- Uses your Claude.ai authentication
+- No API keys to manage
+- Credentials stored by Claude CLI (secure)
+- Runs entirely on localhost
+
+**API mode:**
+- API key in `.env` file (gitignored)
+- Environment variable isolation
+- No data leaves your machine except to Claude's API
+
+Both modes are suitable for personal bots. API mode is recommended for production/multi-user scenarios.
+
+## Sources
+
+- [Claude Agent SDK GitHub](https://github.com/anthropics/anthropic-sdk-python)
+- [Claude CLI Download](https://claude.ai/download)
+- [Anthropic API Documentation](https://docs.anthropic.com/)

README.md

@@ -15,12 +15,13 @@ A lightweight, cost-effective AI agent framework for building proactive bots wit
 
 ## Features
 
+- **Flexible Claude Integration**: Use Pro subscription OR pay-per-token API via Agent SDK (no server needed)
 - **Cost-Optimized AI**: Default Haiku 4.5 model (12x cheaper), auto-caching on Sonnet (90% savings), dynamic model switching
-- **Smart Memory System**: SQLite-based memory with automatic context retrieval and FTS search
+- **Smart Memory System**: SQLite-based memory with automatic context retrieval and hybrid vector search
 - **Multi-Platform Adapters**: Run on Slack, Telegram, and more simultaneously
+- **15 Integrated Tools**: File ops, shell commands, Gmail, Google Calendar, Contacts
 - **Pulse & Brain Monitoring**: 92% cost savings with intelligent conditional monitoring (recommended)
 - **Task Scheduling**: Cron-like scheduled tasks with flexible cadences
-- **Tool Use System**: File operations, command execution, and autonomous task completion
 - **Multi-LLM Support**: Claude (Anthropic) primary, GLM (z.ai) optional
 
 ## Quick Start

agent.py

@@ -3,7 +3,6 @@
 import threading
 from typing import List, Optional
 
-from heartbeat import Heartbeat
 from hooks import HooksSystem
 from llm_interface import LLMInterface
 from memory_system import MemorySystem
@@ -11,7 +10,7 @@ from self_healing import SelfHealingSystem
 from tools import TOOL_DEFINITIONS, execute_tool
 
 # Maximum number of recent messages to include in LLM context
-MAX_CONTEXT_MESSAGES = 3  # Reduced from 5 to save tokens
+MAX_CONTEXT_MESSAGES = 10  # Increased for better context retention
 # Maximum characters of agent response to store in memory
 MEMORY_RESPONSE_PREVIEW_LENGTH = 200
 # Maximum conversation history entries before pruning
@@ -19,13 +18,12 @@ MAX_CONVERSATION_HISTORY = 50
 
 
 class Agent:
-    """AI Agent with memory, LLM, heartbeat, and hooks."""
+    """AI Agent with memory, LLM, and hooks."""
 
     def __init__(
         self,
         provider: str = "claude",
         workspace_dir: str = "./memory_workspace",
-        enable_heartbeat: bool = False,
     ) -> None:
         self.memory = MemorySystem(workspace_dir)
         self.llm = LLMInterface(provider)
@@ -37,12 +35,6 @@ class Agent:
         self.memory.sync()
         self.hooks.trigger("agent", "startup", {"workspace_dir": workspace_dir})
 
-        self.heartbeat: Optional[Heartbeat] = None
-        if enable_heartbeat:
-            self.heartbeat = Heartbeat(self.memory, self.llm)
-            self.heartbeat.on_alert = self._on_heartbeat_alert
-            self.heartbeat.start()
-
     def _get_context_messages(self, max_messages: int) -> List[dict]:
         """Get recent messages without breaking tool_use/tool_result pairs.
 
@@ -91,10 +83,6 @@ class Agent:
 
         return result
 
-    def _on_heartbeat_alert(self, message: str) -> None:
-        """Handle heartbeat alerts."""
-        print(f"\nHeartbeat Alert:\n{message}\n")
-
     def _prune_conversation_history(self) -> None:
         """Prune conversation history to prevent unbounded growth.
 
@@ -172,7 +160,7 @@ class Agent:
         self._prune_conversation_history()
 
         # Tool execution loop
-        max_iterations = 5  # Reduced from 10 to save costs
+        max_iterations = 15  # Increased for complex multi-step operations
         # Enable caching for Sonnet to save 90% on repeated system prompts
         use_caching = "sonnet" in self.llm.model.lower()
 
@@ -282,13 +270,9 @@ class Agent:
     def switch_model(self, provider: str) -> None:
         """Switch LLM provider."""
         self.llm = LLMInterface(provider)
-        if self.heartbeat:
-            self.heartbeat.llm = self.llm
 
     def shutdown(self) -> None:
         """Cleanup and stop background services."""
-        if self.heartbeat:
-            self.heartbeat.stop()
         self.memory.close()
         self.hooks.trigger("agent", "shutdown", {})
 

ajarbot.py

@@ -0,0 +1,205 @@
+"""
+Unified launcher for ajarbot with pre-flight checks.
+
+This launcher:
+1. Performs environment checks (Node.js, Claude CLI auth)
+2. Sets sensible defaults (agent-sdk mode)
+3. Delegates to bot_runner.main() for actual execution
+
+Usage:
+    python ajarbot.py                       # Run with default config
+    python ajarbot.py --config custom.yaml  # Use custom config file
+    python ajarbot.py --init                # Generate config template
+    python ajarbot.py --setup-google        # Set up Google OAuth
+    python ajarbot.py --health              # Run health check
+
+Environment variables:
+    AJARBOT_LLM_MODE                # LLM mode: "agent-sdk" or "api" (default: agent-sdk)
+    AJARBOT_SLACK_BOT_TOKEN         # Slack bot token (xoxb-...)
+    AJARBOT_SLACK_APP_TOKEN         # Slack app token (xapp-...)
+    AJARBOT_TELEGRAM_BOT_TOKEN      # Telegram bot token
+    ANTHROPIC_API_KEY               # Claude API key (only needed for api mode)
+"""
+
+import os
+import sys
+import shutil
+import subprocess
+from pathlib import Path
+
+
+class PreflightCheck:
+    """Performs environment checks before launching the bot."""
+
+    def __init__(self):
+        self.warnings = []
+        self.errors = []
+
+    def check_nodejs(self) -> bool:
+        """Check if Node.js is available (required for agent-sdk mode)."""
+        try:
+            result = subprocess.run(
+                ["node", "--version"],
+                capture_output=True,
+                text=True,
+                timeout=5
+            )
+            if result.returncode == 0:
+                version = result.stdout.strip()
+                print(f"✓ Node.js found: {version}")
+                return True
+            else:
+                self.warnings.append("Node.js not found (required for agent-sdk mode)")
+                return False
+        except FileNotFoundError:
+            self.warnings.append("Node.js not found (required for agent-sdk mode)")
+            return False
+        except Exception as e:
+            self.warnings.append(f"Error checking Node.js: {e}")
+            return False
+
+    def check_claude_cli_auth(self) -> bool:
+        """Check if Claude CLI is authenticated."""
+        try:
+            result = subprocess.run(
+                ["claude", "auth", "status"],
+                capture_output=True,
+                text=True,
+                timeout=5
+            )
+            if result.returncode == 0 and "Authenticated" in result.stdout:
+                print("✓ Claude CLI authenticated")
+                return True
+            else:
+                self.warnings.append("Claude CLI not authenticated (run: claude auth login)")
+                return False
+        except FileNotFoundError:
+            self.warnings.append("Claude CLI not found (install from: https://claude.ai/download)")
+            return False
+        except Exception as e:
+            self.warnings.append(f"Error checking Claude CLI: {e}")
+            return False
+
+    def check_python_version(self) -> bool:
+        """Check if Python version is compatible."""
+        version_info = sys.version_info
+        if version_info >= (3, 10):
+            print(f"✓ Python {version_info.major}.{version_info.minor}.{version_info.micro}")
+            return True
+        else:
+            self.errors.append(
+                f"Python 3.10+ required (found {version_info.major}.{version_info.minor}.{version_info.micro})"
+            )
+            return False
+
+    def check_env_file(self) -> bool:
+        """Check if .env file exists (for API key storage)."""
+        env_path = Path(".env")
+        if env_path.exists():
+            print(f"✓ .env file found")
+            return True
+        else:
+            self.warnings.append(".env file not found (create one if using API mode)")
+            return False
+
+    def check_config_file(self) -> bool:
+        """Check if adapter config exists."""
+        config_path = Path("config/adapters.local.yaml")
+        if config_path.exists():
+            print(f"✓ Config file found: {config_path}")
+            return True
+        else:
+            self.warnings.append(
+                "config/adapters.local.yaml not found (run: python ajarbot.py --init)"
+            )
+            return False
+
+    def set_default_llm_mode(self):
+        """Set default LLM mode to agent-sdk if not specified."""
+        if "AJARBOT_LLM_MODE" not in os.environ:
+            os.environ["AJARBOT_LLM_MODE"] = "agent-sdk"
+            print("ℹ Using LLM mode: agent-sdk (default)")
+        else:
+            mode = os.environ["AJARBOT_LLM_MODE"]
+            print(f"ℹ Using LLM mode: {mode} (from environment)")
+
+    def run_all_checks(self) -> bool:
+        """Run all pre-flight checks. Returns True if safe to proceed."""
+        print("=" * 60)
+        print("Ajarbot Pre-Flight Checks")
+        print("=" * 60)
+        print()
+
+        # Critical checks
+        self.check_python_version()
+
+        # LLM mode dependent checks
+        llm_mode = os.environ.get("AJARBOT_LLM_MODE", "agent-sdk")
+
+        if llm_mode == "agent-sdk":
+            print("\n[Agent SDK Mode Checks]")
+            self.check_nodejs()
+            self.check_claude_cli_auth()
+        elif llm_mode == "api":
+            print("\n[API Mode Checks]")
+            has_env = self.check_env_file()
+            if has_env:
+                if not os.environ.get("ANTHROPIC_API_KEY"):
+                    self.errors.append("ANTHROPIC_API_KEY not set in .env file (required for API mode)")
+            else:
+                self.errors.append(".env file with ANTHROPIC_API_KEY required for API mode")
+
+        # Common checks
+        print("\n[Configuration Checks]")
+        self.check_config_file()
+
+        # Display results
+        print()
+        print("=" * 60)
+
+        if self.errors:
+            print("ERRORS (must fix before running):")
+            for error in self.errors:
+                print(f"  ✗ {error}")
+            print()
+            return False
+
+        if self.warnings:
+            print("WARNINGS (optional, but recommended):")
+            for warning in self.warnings:
+                print(f"  ⚠ {warning}")
+            print()
+
+        print("Pre-flight checks complete!")
+        print("=" * 60)
+        print()
+        return True
+
+
+def main():
+    """Main entry point with pre-flight checks."""
+    # Set default LLM mode before checks
+    checker = PreflightCheck()
+    checker.set_default_llm_mode()
+
+    # Special commands that bypass pre-flight checks
+    bypass_commands = ["--init", "--help", "-h"]
+    if any(arg in sys.argv for arg in bypass_commands):
+        # Import and run bot_runner directly
+        from bot_runner import main as bot_main
+        bot_main()
+        return
+
+    # Run pre-flight checks for normal operation
+    if not checker.run_all_checks():
+        print("\nPre-flight checks failed. Please fix the errors above.")
+        sys.exit(1)
+
+    # All checks passed - delegate to bot_runner
+    print("Launching ajarbot...\n")
+    from bot_runner import main as bot_main
+    bot_main()
+
+
+if __name__ == "__main__":
+    main()

bot_runner.py

@@ -77,7 +77,6 @@ class BotRunner:
         self.agent = Agent(
             provider="claude",
             workspace_dir="./memory_workspace",
-            enable_heartbeat=False,
         )
         print("[Setup] Agent initialized")
 

config/pulse_brain_config.py

@@ -1,307 +0,0 @@
-"""
-Custom Pulse & Brain configuration.
-
-Define your own pulse checks (zero cost) and brain tasks (uses tokens).
-"""
-
-import subprocess
-from typing import Any, Dict, List
-
-import requests
-
-from pulse_brain import BrainTask, CheckType, PulseCheck
-
-
-# === PULSE CHECKS (Pure Python, Zero Cost) ===
-
-
-def check_server_uptime() -> Dict[str, Any]:
-    """Check if server is responsive (pure Python, no agent)."""
-    try:
-        response = requests.get(
-            "http://localhost:8000/health", timeout=5
-        )
-        status = "ok" if response.status_code == 200 else "error"
-        return {
-            "status": status,
-            "message": f"Server responded: {response.status_code}",
-        }
-    except Exception as e:
-        return {
-            "status": "error",
-            "message": f"Server unreachable: {e}",
-        }
-
-
-def check_docker_containers() -> Dict[str, Any]:
-    """Check Docker container status (pure Python)."""
-    try:
-        result = subprocess.run(
-            ["docker", "ps", "--format", "{{.Status}}"],
-            capture_output=True,
-            text=True,
-            timeout=5,
-        )
-
-        if result.returncode != 0:
-            return {
-                "status": "error",
-                "message": "Docker check failed",
-            }
-
-        unhealthy = sum(
-            1
-            for line in result.stdout.split("\n")
-            if "unhealthy" in line.lower()
-        )
-
-        if unhealthy > 0:
-            message = f"{unhealthy} unhealthy container(s)"
-        else:
-            message = "All containers healthy"
-
-        return {
-            "status": "error" if unhealthy > 0 else "ok",
-            "unhealthy_count": unhealthy,
-            "message": message,
-        }
-    except Exception as e:
-        return {"status": "error", "message": str(e)}
-
-
-def check_plex_server() -> Dict[str, Any]:
-    """Check if Plex is running (pure Python)."""
-    try:
-        response = requests.get(
-            "http://localhost:32400/identity", timeout=5
-        )
-        is_ok = response.status_code == 200
-        return {
-            "status": "ok" if is_ok else "warn",
-            "message": (
-                "Plex server is running"
-                if is_ok
-                else "Plex unreachable"
-            ),
-        }
-    except Exception as e:
-        return {
-            "status": "warn",
-            "message": f"Plex check failed: {e}",
-        }
-
-
-def check_unifi_controller() -> Dict[str, Any]:
-    """Check UniFi controller (pure Python)."""
-    try:
-        requests.get(
-            "https://localhost:8443", verify=False, timeout=5
-        )
-        return {
-            "status": "ok",
-            "message": "UniFi controller responding",
-        }
-    except Exception as e:
-        return {
-            "status": "error",
-            "message": f"UniFi unreachable: {e}",
-        }
-
-
-def check_gpu_temperature() -> Dict[str, Any]:
-    """Check GPU temperature (pure Python, requires nvidia-smi)."""
-    try:
-        result = subprocess.run(
-            [
-                "nvidia-smi",
-                "--query-gpu=temperature.gpu",
-                "--format=csv,noheader",
-            ],
-            capture_output=True,
-            text=True,
-            timeout=5,
-        )
-
-        if result.returncode != 0:
-            return {"status": "ok", "message": "GPU check skipped"}
-
-        temp = int(result.stdout.strip())
-
-        if temp > 85:
-            status = "error"
-        elif temp > 75:
-            status = "warn"
-        else:
-            status = "ok"
-
-        return {
-            "status": status,
-            "temperature": temp,
-            "message": f"GPU temperature: {temp}C",
-        }
-    except Exception:
-        return {"status": "ok", "message": "GPU check skipped"}
-
-
-def check_star_citizen_patch() -> Dict[str, Any]:
-    """Check for Star Citizen patches (pure Python, placeholder)."""
-    return {
-        "status": "ok",
-        "new_patch": False,
-        "message": "No new Star Citizen patches",
-    }
-
-
-# === CUSTOM PULSE CHECKS ===
-
-CUSTOM_PULSE_CHECKS: List[PulseCheck] = [
-    PulseCheck(
-        "server-uptime", check_server_uptime,
-        interval_seconds=60,
-    ),
-    PulseCheck(
-        "docker-health", check_docker_containers,
-        interval_seconds=120,
-    ),
-    PulseCheck(
-        "plex-status", check_plex_server,
-        interval_seconds=300,
-    ),
-    PulseCheck(
-        "unifi-controller", check_unifi_controller,
-        interval_seconds=300,
-    ),
-    PulseCheck(
-        "gpu-temp", check_gpu_temperature,
-        interval_seconds=60,
-    ),
-    PulseCheck(
-        "star-citizen", check_star_citizen_patch,
-        interval_seconds=3600,
-    ),
-]
-
-
-# === BRAIN TASKS (Agent/SDK, Uses Tokens) ===
-
-CUSTOM_BRAIN_TASKS: List[BrainTask] = [
-    BrainTask(
-        name="server-medic",
-        check_type=CheckType.CONDITIONAL,
-        prompt_template=(
-            "Server is down!\n\n"
-            "Status: $message\n\n"
-            "Please analyze:\n"
-            "1. What could cause this?\n"
-            "2. What should I check first?\n"
-            "3. Should I restart services?\n\n"
-            "Be concise and actionable."
-        ),
-        condition_func=lambda data: data.get("status") == "error",
-        send_to_platform="slack",
-        send_to_channel="C_ALERTS",
-    ),
-    BrainTask(
-        name="docker-diagnostician",
-        check_type=CheckType.CONDITIONAL,
-        prompt_template=(
-            "Docker containers unhealthy!\n\n"
-            "Unhealthy count: $unhealthy_count\n\n"
-            "Please diagnose:\n"
-            "1. What might cause container health issues?\n"
-            "2. Should I restart them?\n"
-            "3. What logs should I check?"
-        ),
-        condition_func=lambda data: (
-            data.get("unhealthy_count", 0) > 0
-        ),
-        send_to_platform="telegram",
-        send_to_channel="123456789",
-    ),
-    BrainTask(
-        name="gpu-thermal-advisor",
-        check_type=CheckType.CONDITIONAL,
-        prompt_template=(
-            "GPU temperature is high!\n\n"
-            "Current: $temperatureC\n\n"
-            "Please advise:\n"
-            "1. Is this dangerous?\n"
-            "2. What can I do to cool it down?\n"
-            "3. Should I stop current workloads?"
-        ),
-        condition_func=lambda data: (
-            data.get("temperature", 0) > 80
-        ),
-    ),
-    BrainTask(
-        name="homelab-briefing",
-        check_type=CheckType.SCHEDULED,
-        schedule_time="08:00",
-        prompt_template=(
-            "Good morning! Homelab status report:\n\n"
-            "Server: $server_message\n"
-            "Docker: $docker_message\n"
-            "Plex: $plex_message\n"
-            "UniFi: $unifi_message\n"
-            "Star Citizen: $star_citizen_message\n\n"
-            "Overnight summary:\n"
-            "1. Any services restart?\n"
-            "2. Notable events?\n"
-            "3. Action items for today?\n\n"
-            "Keep it brief and friendly."
-        ),
-        send_to_platform="slack",
-        send_to_channel="C_HOMELAB",
-    ),
-    BrainTask(
-        name="homelab-evening-report",
-        check_type=CheckType.SCHEDULED,
-        schedule_time="22:00",
-        prompt_template=(
-            "Evening homelab report:\n\n"
-            "Today's status:\n"
-            "- Server uptime: $server_message\n"
-            "- Docker health: $docker_message\n"
-            "- GPU temp: $gpu_message\n\n"
-            "Summary:\n"
-            "1. Any issues today?\n"
-            "2. Services that needed attention?\n"
-            "3. Overnight monitoring notes?"
-        ),
-        send_to_platform="telegram",
-        send_to_channel="123456789",
-    ),
-    BrainTask(
-        name="patch-notifier",
-        check_type=CheckType.CONDITIONAL,
-        prompt_template=(
-            "New Star Citizen patch detected!\n\n"
-            "Please:\n"
-            "1. Summarize patch notes (if available)\n"
-            "2. Note any breaking changes\n"
-            "3. Recommend if I should update now or wait"
-        ),
-        condition_func=lambda data: data.get("new_patch", False),
-        send_to_platform="discord",
-        send_to_channel="GAMING_CHANNEL",
-    ),
-]
-
-
-def apply_custom_config(pulse_brain: Any) -> None:
-    """Apply custom configuration to PulseBrain instance."""
-    existing_pulse_names = {c.name for c in pulse_brain.pulse_checks}
-    for check in CUSTOM_PULSE_CHECKS:
-        if check.name not in existing_pulse_names:
-            pulse_brain.pulse_checks.append(check)
-
-    existing_brain_names = {t.name for t in pulse_brain.brain_tasks}
-    for task in CUSTOM_BRAIN_TASKS:
-        if task.name not in existing_brain_names:
-            pulse_brain.brain_tasks.append(task)
-
-    print(
-        f"Applied custom config: "
-        f"{len(CUSTOM_PULSE_CHECKS)} pulse checks, "
-        f"{len(CUSTOM_BRAIN_TASKS)} brain tasks"
-    )

config/scheduled_tasks.yaml

@@ -5,7 +5,16 @@ tasks:
   # Morning briefing - sent to Slack/Telegram
   - name: morning-weather
     prompt: |
-      Current weather report for my location. Just the weather - keep it brief.
+      Check the user profile (Jordan.md) for the location (Centennial, CO). Use the get_weather tool with OpenWeatherMap API to fetch the current weather. Format the report as:
+      
+      🌤️ **Weather Report for Centennial, CO**
+      - Current: [current]°F
+      - High: [high]°F
+      - Low: [low]°F
+      - Conditions: [conditions]
+      - Recommendation: [brief clothing/activity suggestion]
+      
+      Keep it brief and friendly!
     schedule: "daily 06:00"
     enabled: true
     send_to_platform: "telegram"

heartbeat.py

@@ -1,192 +0,0 @@
-"""Simple Heartbeat System - Periodic agent awareness checks."""
-
-import threading
-import time
-from datetime import datetime
-from typing import Callable, Optional
-
-from llm_interface import LLMInterface
-from memory_system import MemorySystem
-
-# Default heartbeat checklist template
-_HEARTBEAT_TEMPLATE = """\
-# Heartbeat Checklist
-
-Run these checks every heartbeat cycle:
-
-## Memory Checks
-- Review pending tasks (status = pending)
-- Check if any tasks have been pending > 24 hours
-
-## System Checks
-- Verify memory system is synced
-- Log heartbeat ran successfully
-
-## Notes
-- Return HEARTBEAT_OK if nothing needs attention
-- Only alert if something requires user action
-"""
-
-# Maximum number of pending tasks to include in context
-MAX_PENDING_TASKS_IN_CONTEXT = 5
-
-# Maximum characters of soul content to include in context
-SOUL_PREVIEW_LENGTH = 200
-
-
-class Heartbeat:
-    """Periodic background checks with LLM awareness."""
-
-    def __init__(
-        self,
-        memory: MemorySystem,
-        llm: LLMInterface,
-        interval_minutes: int = 30,
-        active_hours: tuple = (8, 22),
-    ) -> None:
-        self.memory = memory
-        self.llm = llm
-        self.interval = interval_minutes * 60
-        self.active_hours = active_hours
-        self.running = False
-        self.thread: Optional[threading.Thread] = None
-        self.on_alert: Optional[Callable[[str], None]] = None
-
-        self.heartbeat_file = memory.workspace_dir / "HEARTBEAT.md"
-        if not self.heartbeat_file.exists():
-            self.heartbeat_file.write_text(
-                _HEARTBEAT_TEMPLATE, encoding="utf-8"
-            )
-
-    def start(self) -> None:
-        """Start heartbeat in background thread."""
-        if self.running:
-            return
-
-        self.running = True
-        self.thread = threading.Thread(
-            target=self._heartbeat_loop, daemon=True
-        )
-        self.thread.start()
-        print(f"Heartbeat started (every {self.interval // 60}min)")
-
-    def stop(self) -> None:
-        """Stop heartbeat."""
-        self.running = False
-        if self.thread:
-            self.thread.join()
-        print("Heartbeat stopped")
-
-    def _is_active_hours(self) -> bool:
-        """Check if current time is within active hours."""
-        current_hour = datetime.now().hour
-        start, end = self.active_hours
-        return start <= current_hour < end
-
-    def _heartbeat_loop(self) -> None:
-        """Main heartbeat loop."""
-        while self.running:
-            try:
-                if self._is_active_hours():
-                    self._run_heartbeat()
-                else:
-                    start, end = self.active_hours
-                    print(
-                        f"Heartbeat skipped "
-                        f"(outside active hours {start}-{end})"
-                    )
-            except Exception as e:
-                print(f"Heartbeat error: {e}")
-
-            time.sleep(self.interval)
-
-    def _build_context(self) -> str:
-        """Build system context for heartbeat check."""
-        soul = self.memory.get_soul()
-        pending_tasks = self.memory.get_tasks(status="pending")
-
-        context_parts = [
-            "# HEARTBEAT CHECK",
-            f"Current time: {datetime.now().isoformat()}",
-            f"\nSOUL:\n{soul[:SOUL_PREVIEW_LENGTH]}...",
-            f"\nPending tasks: {len(pending_tasks)}",
-        ]
-
-        if pending_tasks:
-            context_parts.append("\nPending Tasks:")
-            for task in pending_tasks[:MAX_PENDING_TASKS_IN_CONTEXT]:
-                context_parts.append(f"- [{task['id']}] {task['title']}")
-
-        return "\n".join(context_parts)
-
-    def _run_heartbeat(self) -> None:
-        """Execute one heartbeat cycle."""
-        timestamp = datetime.now().strftime("%H:%M:%S")
-        print(f"Heartbeat running ({timestamp})")
-
-        checklist = self.heartbeat_file.read_text(encoding="utf-8")
-        system = self._build_context()
-
-        messages = [{
-            "role": "user",
-            "content": (
-                f"{checklist}\n\n"
-                "Process this checklist. If nothing needs attention, "
-                "respond with EXACTLY 'HEARTBEAT_OK'. If something "
-                "needs attention, describe it briefly."
-            ),
-        }]
-
-        response = self.llm.chat(messages, system=system, max_tokens=500)
-
-        if response.strip() != "HEARTBEAT_OK":
-            print(f"Heartbeat alert: {response[:100]}...")
-            if self.on_alert:
-                self.on_alert(response)
-            self.memory.write_memory(
-                f"## Heartbeat Alert\n{response}", daily=True
-            )
-        else:
-            print("Heartbeat OK")
-
-    def check_now(self) -> str:
-        """Run heartbeat check immediately (for testing)."""
-        print("Running immediate heartbeat check...")
-
-        checklist = self.heartbeat_file.read_text(encoding="utf-8")
-        pending_tasks = self.memory.get_tasks(status="pending")
-        soul = self.memory.get_soul()
-
-        system = (
-            f"Time: {datetime.now().isoformat()}\n"
-            f"SOUL: {soul[:SOUL_PREVIEW_LENGTH]}...\n"
-            f"Pending tasks: {len(pending_tasks)}"
-        )
-
-        messages = [{
-            "role": "user",
-            "content": (
-                f"{checklist}\n\n"
-                "Process this checklist. "
-                "Return HEARTBEAT_OK if nothing needs attention."
-            ),
-        }]
-
-        return self.llm.chat(messages, system=system, max_tokens=500)
-
-
-if __name__ == "__main__":
-    memory = MemorySystem()
-    llm = LLMInterface(provider="claude")
-
-    heartbeat = Heartbeat(
-        memory, llm, interval_minutes=30, active_hours=(8, 22)
-    )
-
-    def on_alert(message: str) -> None:
-        print(f"\nALERT: {message}\n")
-
-    heartbeat.on_alert = on_alert
-
-    result = heartbeat.check_now()
-    print(f"\nResult: {result}")

llm_interface.py

@@ -1,20 +1,41 @@
-"""LLM Interface - Claude API, GLM, and other models."""
+"""LLM Interface - Claude API, GLM, and other models.
+
+Supports three modes for Claude:
+1. Agent SDK (uses Pro subscription) - DEFAULT - Set USE_AGENT_SDK=true (default)
+2. Direct API (pay-per-token) - Set USE_DIRECT_API=true
+3. Legacy: Local Claude Code server - Set USE_CLAUDE_CODE_SERVER=true (deprecated)
+"""
 
 import os
 from typing import Any, Dict, List, Optional
 
 import requests
 from anthropic import Anthropic
-from anthropic.types import Message
+from anthropic.types import Message, ContentBlock, TextBlock, ToolUseBlock, Usage
 
 from usage_tracker import UsageTracker
 
+# Try to import Agent SDK (optional dependency)
+try:
+    from claude_agent_sdk import AgentSDK
+    import anyio
+    AGENT_SDK_AVAILABLE = True
+except ImportError:
+    AGENT_SDK_AVAILABLE = False
+
 # API key environment variable names by provider
 _API_KEY_ENV_VARS = {
     "claude": "ANTHROPIC_API_KEY",
     "glm": "GLM_API_KEY",
 }
 
+# Mode selection (priority order: USE_DIRECT_API > USE_CLAUDE_CODE_SERVER > default to Agent SDK)
+_USE_DIRECT_API = os.getenv("USE_DIRECT_API", "false").lower() == "true"
+_CLAUDE_CODE_SERVER_URL = os.getenv("CLAUDE_CODE_SERVER_URL", "http://localhost:8000")
+_USE_CLAUDE_CODE_SERVER = os.getenv("USE_CLAUDE_CODE_SERVER", "false").lower() == "true"
+# Agent SDK is the default if available and no other mode is explicitly enabled
+_USE_AGENT_SDK = os.getenv("USE_AGENT_SDK", "true").lower() == "true"
+
 # Default models by provider
 _DEFAULT_MODELS = {
     "claude": "claude-haiku-4-5-20251001",  # 12x cheaper than Sonnet!
@@ -39,12 +60,46 @@ class LLMInterface:
         )
         self.model = _DEFAULT_MODELS.get(provider, "")
         self.client: Optional[Anthropic] = None
+        self.agent_sdk: Optional[Any] = None
 
-        # Usage tracking
-        self.tracker = UsageTracker() if track_usage else None
-
+        # Determine mode (priority: direct API > legacy server > agent SDK)
         if provider == "claude":
-            self.client = Anthropic(api_key=self.api_key)
+            if _USE_DIRECT_API:
+                self.mode = "direct_api"
+            elif _USE_CLAUDE_CODE_SERVER:
+                self.mode = "legacy_server"
+            elif _USE_AGENT_SDK and AGENT_SDK_AVAILABLE:
+                self.mode = "agent_sdk"
+            else:
+                # Fallback to direct API if Agent SDK not available
+                self.mode = "direct_api"
+                if _USE_AGENT_SDK and not AGENT_SDK_AVAILABLE:
+                    print("[LLM] Warning: Agent SDK not available, falling back to Direct API")
+                    print("[LLM] Install with: pip install claude-agent-sdk")
+        else:
+            self.mode = "direct_api"  # Non-Claude providers use direct API
+
+        # Usage tracking (disabled when using Agent SDK or legacy server)
+        self.tracker = UsageTracker() if (track_usage and self.mode == "direct_api") else None
+
+        # Initialize based on mode
+        if provider == "claude":
+            if self.mode == "agent_sdk":
+                print(f"[LLM] Using Claude Agent SDK (Pro subscription)")
+                self.agent_sdk = AgentSDK()
+            elif self.mode == "direct_api":
+                print(f"[LLM] Using Direct API (pay-per-token)")
+                self.client = Anthropic(api_key=self.api_key)
+            elif self.mode == "legacy_server":
+                print(f"[LLM] Using Claude Code server at {_CLAUDE_CODE_SERVER_URL} (Pro subscription)")
+                # Verify server is running
+                try:
+                    response = requests.get(f"{_CLAUDE_CODE_SERVER_URL}/", timeout=2)
+                    response.raise_for_status()
+                    print(f"[LLM] Claude Code server is running: {response.json()}")
+                except Exception as e:
+                    print(f"[LLM] Warning: Could not connect to Claude Code server: {e}")
+                    print(f"[LLM] Note: Claude Code server mode is deprecated. Using Agent SDK instead.")
 
     def chat(
         self,
@@ -58,30 +113,65 @@ class LLMInterface:
             Exception: If the API call fails or returns an unexpected response.
         """
         if self.provider == "claude":
-            response = self.client.messages.create(
-                model=self.model,
-                max_tokens=max_tokens,
-                system=system or "",
-                messages=messages,
-            )
+            # Agent SDK mode (Pro subscription)
+            if self.mode == "agent_sdk":
+                try:
+                    # Use anyio to bridge async SDK to sync interface
+                    response = anyio.from_thread.run(
+                        self._agent_sdk_chat,
+                        messages,
+                        system,
+                        max_tokens
+                    )
+                    return response
+                except Exception as e:
+                    raise Exception(f"Agent SDK error: {e}")
 
-            # Track usage
-            if self.tracker and hasattr(response, "usage"):
-                self.tracker.track(
+            # Legacy Claude Code server (Pro subscription)
+            elif self.mode == "legacy_server":
+                try:
+                    payload = {
+                        "messages": [{"role": m["role"], "content": m["content"]} for m in messages],
+                        "system": system,
+                        "max_tokens": max_tokens
+                    }
+                    response = requests.post(
+                        f"{_CLAUDE_CODE_SERVER_URL}/v1/chat",
+                        json=payload,
+                        timeout=120
+                    )
+                    response.raise_for_status()
+                    data = response.json()
+                    return data.get("content", "")
+                except Exception as e:
+                    raise Exception(f"Claude Code server error: {e}")
+
+            # Direct API (pay-per-token)
+            elif self.mode == "direct_api":
+                response = self.client.messages.create(
                     model=self.model,
-                    input_tokens=response.usage.input_tokens,
-                    output_tokens=response.usage.output_tokens,
-                    cache_creation_tokens=getattr(
-                        response.usage, "cache_creation_input_tokens", 0
-                    ),
-                    cache_read_tokens=getattr(
-                        response.usage, "cache_read_input_tokens", 0
-                    ),
+                    max_tokens=max_tokens,
+                    system=system or "",
+                    messages=messages,
                 )
 
-            if not response.content:
-                return ""
-            return response.content[0].text
+                # Track usage
+                if self.tracker and hasattr(response, "usage"):
+                    self.tracker.track(
+                        model=self.model,
+                        input_tokens=response.usage.input_tokens,
+                        output_tokens=response.usage.output_tokens,
+                        cache_creation_tokens=getattr(
+                            response.usage, "cache_creation_input_tokens", 0
+                        ),
+                        cache_read_tokens=getattr(
+                            response.usage, "cache_read_input_tokens", 0
+                        ),
+                    )
+
+                if not response.content:
+                    return ""
+                return response.content[0].text
 
         if self.provider == "glm":
             payload = {
@@ -101,6 +191,102 @@ class LLMInterface:
 
         raise ValueError(f"Unsupported provider: {self.provider}")
 
+    async def _agent_sdk_chat(
+        self,
+        messages: List[Dict],
+        system: Optional[str],
+        max_tokens: int
+    ) -> str:
+        """Internal async method for Agent SDK chat (called via anyio bridge)."""
+        response = await self.agent_sdk.chat(
+            messages=messages,
+            system=system,
+            max_tokens=max_tokens,
+            model=self.model
+        )
+        # Extract text from response
+        if isinstance(response, dict):
+            return response.get("content", "")
+        return str(response)
+
+    async def _agent_sdk_chat_with_tools(
+        self,
+        messages: List[Dict],
+        tools: List[Dict[str, Any]],
+        system: Optional[str],
+        max_tokens: int
+    ) -> Message:
+        """Internal async method for Agent SDK chat with tools (called via anyio bridge)."""
+        response = await self.agent_sdk.chat(
+            messages=messages,
+            tools=tools,
+            system=system,
+            max_tokens=max_tokens,
+            model=self.model
+        )
+
+        # Convert Agent SDK response to anthropic.types.Message format
+        return self._convert_sdk_response_to_message(response)
+
+    def _convert_sdk_response_to_message(self, sdk_response: Dict[str, Any]) -> Message:
+        """Convert Agent SDK response to anthropic.types.Message format.
+
+        This ensures compatibility with agent.py's existing tool loop.
+        """
+        # Extract content blocks
+        content_blocks = []
+        raw_content = sdk_response.get("content", [])
+
+        if isinstance(raw_content, str):
+            # Simple text response
+            content_blocks = [TextBlock(type="text", text=raw_content)]
+        elif isinstance(raw_content, list):
+            # List of content blocks
+            for block in raw_content:
+                if isinstance(block, dict):
+                    if block.get("type") == "text":
+                        content_blocks.append(TextBlock(
+                            type="text",
+                            text=block.get("text", "")
+                        ))
+                    elif block.get("type") == "tool_use":
+                        content_blocks.append(ToolUseBlock(
+                            type="tool_use",
+                            id=block.get("id", ""),
+                            name=block.get("name", ""),
+                            input=block.get("input", {})
+                        ))
+
+        # Extract usage information
+        usage_data = sdk_response.get("usage", {})
+        usage = Usage(
+            input_tokens=usage_data.get("input_tokens", 0),
+            output_tokens=usage_data.get("output_tokens", 0)
+        )
+
+        # Create Message object
+        # Note: We create a minimal Message-compatible object
+        # The Message class from anthropic.types is read-only, so we create a mock
+        # Capture self.model before defining inner class
+        model_name = sdk_response.get("model", self.model)
+
+        class MessageLike:
+            def __init__(self, content, stop_reason, usage, model):
+                self.content = content
+                self.stop_reason = stop_reason
+                self.usage = usage
+                self.id = sdk_response.get("id", "sdk_message")
+                self.model = model
+                self.role = "assistant"
+                self.type = "message"
+
+        return MessageLike(
+            content=content_blocks,
+            stop_reason=sdk_response.get("stop_reason", "end_turn"),
+            usage=usage,
+            model=model_name
+        )
+
     def chat_with_tools(
         self,
         messages: List[Dict],
@@ -117,45 +303,94 @@ class LLMInterface:
         if self.provider != "claude":
             raise ValueError("Tool use only supported for Claude provider")
 
-        # Enable caching only for Sonnet models (not worth it for Haiku)
-        enable_caching = use_cache and "sonnet" in self.model.lower()
+        # Agent SDK mode (Pro subscription)
+        if self.mode == "agent_sdk":
+            try:
+                # Use anyio to bridge async SDK to sync interface
+                response = anyio.from_thread.run(
+                    self._agent_sdk_chat_with_tools,
+                    messages,
+                    tools,
+                    system,
+                    max_tokens
+                )
+                return response
+            except Exception as e:
+                raise Exception(f"Agent SDK error: {e}")
 
-        # Structure system prompt for optimal caching
-        if enable_caching and system:
-            # Convert string to list format with cache control
-            system_blocks = [
-                {
-                    "type": "text",
-                    "text": system,
-                    "cache_control": {"type": "ephemeral"}
+        # Legacy Claude Code server (Pro subscription)
+        elif self.mode == "legacy_server":
+            try:
+                payload = {
+                    "messages": messages,
+                    "tools": tools,
+                    "system": system,
+                    "max_tokens": max_tokens
                 }
-            ]
-        else:
-            system_blocks = system or ""
+                response = requests.post(
+                    f"{_CLAUDE_CODE_SERVER_URL}/v1/chat/tools",
+                    json=payload,
+                    timeout=120
+                )
+                response.raise_for_status()
+                # Convert response to Message-like object
+                data = response.json()
 
-        response = self.client.messages.create(
-            model=self.model,
-            max_tokens=max_tokens,
-            system=system_blocks,
-            messages=messages,
-            tools=tools,
-        )
+                # Create a mock Message object with the response
+                class MockMessage:
+                    def __init__(self, data):
+                        self.content = data.get("content", [])
+                        self.stop_reason = data.get("stop_reason", "end_turn")
+                        self.usage = type('obj', (object,), {
+                            'input_tokens': data.get("usage", {}).get("input_tokens", 0),
+                            'output_tokens': data.get("usage", {}).get("output_tokens", 0)
+                        })
 
-        # Track usage
-        if self.tracker and hasattr(response, "usage"):
-            self.tracker.track(
+                return MockMessage(data)
+            except Exception as e:
+                raise Exception(f"Claude Code server error: {e}")
+
+        # Direct API (pay-per-token)
+        elif self.mode == "direct_api":
+            # Enable caching only for Sonnet models (not worth it for Haiku)
+            enable_caching = use_cache and "sonnet" in self.model.lower()
+
+            # Structure system prompt for optimal caching
+            if enable_caching and system:
+                # Convert string to list format with cache control
+                system_blocks = [
+                    {
+                        "type": "text",
+                        "text": system,
+                        "cache_control": {"type": "ephemeral"}
+                    }
+                ]
+            else:
+                system_blocks = system or ""
+
+            response = self.client.messages.create(
                 model=self.model,
-                input_tokens=response.usage.input_tokens,
-                output_tokens=response.usage.output_tokens,
-                cache_creation_tokens=getattr(
-                    response.usage, "cache_creation_input_tokens", 0
-                ),
-                cache_read_tokens=getattr(
-                    response.usage, "cache_read_input_tokens", 0
-                ),
+                max_tokens=max_tokens,
+                system=system_blocks,
+                messages=messages,
+                tools=tools,
             )
 
-        return response
+            # Track usage
+            if self.tracker and hasattr(response, "usage"):
+                self.tracker.track(
+                    model=self.model,
+                    input_tokens=response.usage.input_tokens,
+                    output_tokens=response.usage.output_tokens,
+                    cache_creation_tokens=getattr(
+                        response.usage, "cache_creation_input_tokens", 0
+                    ),
+                    cache_read_tokens=getattr(
+                        response.usage, "cache_read_input_tokens", 0
+                    ),
+                )
+
+            return response
 
     def set_model(self, model: str) -> None:
         """Change the active model."""

pulse_brain.py

@@ -1,487 +0,0 @@
-"""
-Pulse & Brain Architecture for Ajarbot.
-
-PULSE (Pure Python):
-- Runs every N seconds
-- Zero API token cost
-- Checks: server health, disk space, log files, task queue
-- Only wakes the BRAIN when needed
-
-BRAIN (Agent/SDK):
-- Only invoked when:
-  1. Pulse detects an issue (error logs, low disk space, etc.)
-  2. Scheduled time for content generation (morning briefing)
-  3. Manual trigger requested
-
-This is much more efficient than running Agent in a loop.
-"""
-
-import asyncio
-import shutil
-import string
-import threading
-import time
-import traceback
-from dataclasses import dataclass
-from datetime import datetime
-from enum import Enum
-from typing import Any, Callable, Dict, List, Optional
-
-from agent import Agent
-
-# How many seconds between brain invocations to avoid duplicates
-_BRAIN_COOLDOWN_SECONDS = 3600
-
-
-class CheckType(Enum):
-    """Type of check to perform."""
-    PURE_PYTHON = "pure_python"
-    CONDITIONAL = "conditional"
-    SCHEDULED = "scheduled"
-
-
-@dataclass
-class PulseCheck:
-    """A check performed by the Pulse (pure Python)."""
-    name: str
-    check_func: Callable[[], Dict[str, Any]]
-    interval_seconds: int = 60
-    last_run: Optional[datetime] = None
-
-
-@dataclass
-class BrainTask:
-    """A task that requires the Brain (Agent/SDK)."""
-    name: str
-    check_type: CheckType
-    prompt_template: str
-
-    # For CONDITIONAL: condition to check
-    condition_func: Optional[Callable[[Dict[str, Any]], bool]] = None
-
-    # For SCHEDULED: when to run
-    schedule_time: Optional[str] = None  # "08:00", "18:00", etc.
-    last_brain_run: Optional[datetime] = None
-
-    # Output options
-    send_to_platform: Optional[str] = None
-    send_to_channel: Optional[str] = None
-
-
-_STATUS_ICONS = {"ok": "+", "warn": "!", "error": "x"}
-
-
-class PulseBrain:
-    """
-    Hybrid monitoring system with zero-cost pulse and smart brain.
-
-    The Pulse runs continuously checking system health (zero tokens).
-    The Brain only activates when needed (uses tokens wisely).
-    """
-
-    def __init__(
-        self,
-        agent: Agent,
-        pulse_interval: int = 60,
-        enable_defaults: bool = True,
-    ) -> None:
-        """
-        Initialize Pulse & Brain system.
-
-        Args:
-            agent: The Agent instance to use for brain tasks.
-            pulse_interval: How often pulse loop runs (seconds).
-            enable_defaults: Load example checks. Set False to start clean.
-        """
-        self.agent = agent
-        self.pulse_interval = pulse_interval
-
-        self.pulse_checks: List[PulseCheck] = []
-        self.brain_tasks: List[BrainTask] = []
-
-        self.running = False
-        self.thread: Optional[threading.Thread] = None
-
-        self.adapters: Dict[str, Any] = {}
-
-        # State tracking (protected by lock)
-        self._lock = threading.Lock()
-        self.pulse_data: Dict[str, Any] = {}
-        self.brain_invocations = 0
-
-        if enable_defaults:
-            self._setup_default_checks()
-            print("[PulseBrain] Loaded default example checks")
-            print(
-                "            To start clean: "
-                "PulseBrain(agent, enable_defaults=False)"
-            )
-
-    def _setup_default_checks(self) -> None:
-        """Set up default pulse checks and brain tasks."""
-
-        def check_disk_space() -> Dict[str, Any]:
-            """Check disk space (pure Python, no agent)."""
-            try:
-                usage = shutil.disk_usage(".")
-                percent_used = (usage.used / usage.total) * 100
-                gb_free = usage.free / (1024 ** 3)
-
-                if percent_used > 90:
-                    status = "error"
-                elif percent_used > 80:
-                    status = "warn"
-                else:
-                    status = "ok"
-
-                return {
-                    "status": status,
-                    "percent_used": percent_used,
-                    "gb_free": gb_free,
-                    "message": (
-                        f"Disk: {percent_used:.1f}% used, "
-                        f"{gb_free:.1f} GB free"
-                    ),
-                }
-            except Exception as e:
-                return {"status": "error", "message": str(e)}
-
-        def check_memory_tasks() -> Dict[str, Any]:
-            """Check for stale tasks (pure Python)."""
-            try:
-                pending = self.agent.memory.get_tasks(status="pending")
-                stale_count = len(pending)
-
-                status = "warn" if stale_count > 5 else "ok"
-
-                return {
-                    "status": status,
-                    "pending_count": len(pending),
-                    "stale_count": stale_count,
-                    "message": (
-                        f"{len(pending)} pending tasks, "
-                        f"{stale_count} stale"
-                    ),
-                }
-            except Exception as e:
-                return {"status": "error", "message": str(e)}
-
-        def check_log_errors() -> Dict[str, Any]:
-            """Check recent logs for errors (pure Python)."""
-            return {
-                "status": "ok",
-                "errors_found": 0,
-                "message": "No errors in recent logs",
-            }
-
-        self.pulse_checks.extend([
-            PulseCheck(
-                "disk-space", check_disk_space,
-                interval_seconds=300,
-            ),
-            PulseCheck(
-                "memory-tasks", check_memory_tasks,
-                interval_seconds=600,
-            ),
-            PulseCheck(
-                "log-errors", check_log_errors,
-                interval_seconds=60,
-            ),
-        ])
-
-        self.brain_tasks.extend([
-            BrainTask(
-                name="disk-space-advisor",
-                check_type=CheckType.CONDITIONAL,
-                prompt_template=(
-                    "Disk space is running low:\n"
-                    "- Used: {percent_used:.1f}%\n"
-                    "- Free: {gb_free:.1f} GB\n\n"
-                    "Please analyze:\n"
-                    "1. Is this critical?\n"
-                    "2. What files/directories should I check?\n"
-                    "3. Should I set up automated cleanup?\n\n"
-                    "Be concise and actionable."
-                ),
-                condition_func=lambda data: (
-                    data.get("status") == "error"
-                ),
-            ),
-            BrainTask(
-                name="error-analyst",
-                check_type=CheckType.CONDITIONAL,
-                prompt_template=(
-                    "Errors detected in logs:\n"
-                    "{message}\n\n"
-                    "Please analyze:\n"
-                    "1. What does this error mean?\n"
-                    "2. How critical is it?\n"
-                    "3. What should I do to fix it?"
-                ),
-                condition_func=lambda data: (
-                    data.get("errors_found", 0) > 0
-                ),
-            ),
-            BrainTask(
-                name="morning-briefing",
-                check_type=CheckType.SCHEDULED,
-                schedule_time="08:00",
-                prompt_template=(
-                    "Good morning! Please provide a brief summary:\n\n"
-                    "1. System health "
-                    "(disk: {disk_space_message}, "
-                    "tasks: {tasks_message})\n"
-                    "2. Any pending tasks that need attention\n"
-                    "3. Priorities for today\n"
-                    "4. A motivational message\n\n"
-                    "Keep it brief and actionable."
-                ),
-            ),
-            BrainTask(
-                name="evening-summary",
-                check_type=CheckType.SCHEDULED,
-                schedule_time="18:00",
-                prompt_template=(
-                    "Good evening! Daily wrap-up:\n\n"
-                    "1. What was accomplished today\n"
-                    "2. Tasks still pending: {pending_count}\n"
-                    "3. Any issues detected (disk, errors, etc.)\n"
-                    "4. Preview for tomorrow\n\n"
-                    "Keep it concise."
-                ),
-            ),
-        ])
-
-    def add_adapter(self, platform: str, adapter: Any) -> None:
-        """Register an adapter for sending messages."""
-        self.adapters[platform] = adapter
-
-    def start(self) -> None:
-        """Start the Pulse & Brain system."""
-        if self.running:
-            return
-
-        self.running = True
-        self.thread = threading.Thread(
-            target=self._pulse_loop, daemon=True
-        )
-        self.thread.start()
-
-        print("=" * 60)
-        print("PULSE & BRAIN Started")
-        print("=" * 60)
-        print(f"\nPulse interval: {self.pulse_interval}s")
-        print(f"Pulse checks: {len(self.pulse_checks)}")
-        print(f"Brain tasks: {len(self.brain_tasks)}\n")
-
-        for check in self.pulse_checks:
-            print(
-                f"  [Pulse] {check.name} "
-                f"(every {check.interval_seconds}s)"
-            )
-
-        for task in self.brain_tasks:
-            if task.check_type == CheckType.SCHEDULED:
-                print(
-                    f"  [Brain] {task.name} "
-                    f"(scheduled {task.schedule_time})"
-                )
-            else:
-                print(f"  [Brain] {task.name} (conditional)")
-
-        print("\n" + "=" * 60 + "\n")
-
-    def stop(self) -> None:
-        """Stop the Pulse & Brain system."""
-        self.running = False
-        if self.thread:
-            self.thread.join()
-        print(
-            f"\nPULSE & BRAIN Stopped "
-            f"(Brain invoked {self.brain_invocations} times)"
-        )
-
-    def _pulse_loop(self) -> None:
-        """Main pulse loop (runs continuously, zero cost)."""
-        while self.running:
-            try:
-                now = datetime.now()
-
-                for check in self.pulse_checks:
-                    should_run = (
-                        check.last_run is None
-                        or (now - check.last_run).total_seconds()
-                        >= check.interval_seconds
-                    )
-                    if not should_run:
-                        continue
-
-                    result = check.check_func()
-                    check.last_run = now
-
-                    # Thread-safe update of pulse_data
-                    with self._lock:
-                        self.pulse_data[check.name] = result
-
-                    icon = _STATUS_ICONS.get(
-                        result.get("status"), "?"
-                    )
-                    print(
-                        f"[{icon}] {check.name}: "
-                        f"{result.get('message', 'OK')}"
-                    )
-
-                self._check_brain_tasks(now)
-
-            except Exception as e:
-                print(f"Pulse error: {e}")
-                traceback.print_exc()
-
-            time.sleep(self.pulse_interval)
-
-    def _check_brain_tasks(self, now: datetime) -> None:
-        """Check if any brain tasks need to be invoked."""
-        for task in self.brain_tasks:
-            should_invoke = False
-            prompt_data: Dict[str, Any] = {}
-
-            if (
-                task.check_type == CheckType.CONDITIONAL
-                and task.condition_func
-            ):
-                for check_name, check_data in self.pulse_data.items():
-                    if task.condition_func(check_data):
-                        should_invoke = True
-                        prompt_data = check_data
-                        print(
-                            f"Condition met for brain task: "
-                            f"{task.name}"
-                        )
-                        break
-
-            elif (
-                task.check_type == CheckType.SCHEDULED
-                and task.schedule_time
-            ):
-                target_time = datetime.strptime(
-                    task.schedule_time, "%H:%M"
-                ).time()
-                current_time = now.time()
-
-                time_match = (
-                    current_time.hour == target_time.hour
-                    and current_time.minute == target_time.minute
-                )
-
-                already_ran_recently = (
-                    task.last_brain_run
-                    and (now - task.last_brain_run).total_seconds()
-                    < _BRAIN_COOLDOWN_SECONDS
-                )
-
-                if time_match and not already_ran_recently:
-                    should_invoke = True
-                    prompt_data = self._gather_scheduled_data()
-                    print(
-                        f"Scheduled time for brain task: {task.name}"
-                    )
-
-            if should_invoke:
-                self._invoke_brain(task, prompt_data)
-                task.last_brain_run = now
-
-    def _gather_scheduled_data(self) -> Dict[str, Any]:
-        """Gather data from all pulse checks for scheduled brain tasks."""
-        disk_data = self.pulse_data.get("disk-space", {})
-        task_data = self.pulse_data.get("memory-tasks", {})
-
-        return {
-            "disk_space_message": disk_data.get(
-                "message", "Unknown"
-            ),
-            "tasks_message": task_data.get("message", "Unknown"),
-            "pending_count": task_data.get("pending_count", 0),
-            **disk_data,
-        }
-
-    def _invoke_brain(
-        self, task: BrainTask, data: Dict[str, Any]
-    ) -> None:
-        """Invoke the Brain (Agent/SDK) for a task."""
-        print(f"Invoking brain: {task.name}")
-
-        # Thread-safe increment
-        with self._lock:
-            self.brain_invocations += 1
-
-        try:
-            # Use safe_substitute to prevent format string injection
-            # Convert all data values to strings first
-            safe_data = {k: str(v) for k, v in data.items()}
-            template = string.Template(task.prompt_template)
-            prompt = template.safe_substitute(safe_data)
-
-            response = self.agent.chat(
-                user_message=prompt, username="pulse-brain"
-            )
-
-            print(f"Brain response ({len(response)} chars)")
-            print(f"   Preview: {response[:100]}...")
-
-            if task.send_to_platform and task.send_to_channel:
-                asyncio.run(self._send_to_platform(task, response))
-
-        except Exception as e:
-            print(f"Brain error: {e}")
-            traceback.print_exc()
-
-    async def _send_to_platform(
-        self, task: BrainTask, response: str
-    ) -> None:
-        """Send brain output to messaging platform."""
-        adapter = self.adapters.get(task.send_to_platform)
-        if not adapter:
-            return
-
-        from adapters.base import OutboundMessage
-
-        message = OutboundMessage(
-            platform=task.send_to_platform,
-            channel_id=task.send_to_channel,
-            text=f"**{task.name}**\n\n{response}",
-        )
-
-        result = await adapter.send_message(message)
-        if result.get("success"):
-            print(f"Sent to {task.send_to_platform}")
-
-    def get_status(self) -> Dict[str, Any]:
-        """Get current status of Pulse & Brain."""
-        # Thread-safe read of shared state
-        with self._lock:
-            return {
-                "running": self.running,
-                "pulse_interval": self.pulse_interval,
-                "brain_invocations": self.brain_invocations,
-                "pulse_checks": len(self.pulse_checks),
-                "brain_tasks": len(self.brain_tasks),
-                "latest_pulse_data": dict(self.pulse_data),  # Copy
-            }
-
-
-if __name__ == "__main__":
-    agent = Agent(
-        provider="claude",
-        workspace_dir="./memory_workspace",
-        enable_heartbeat=False,
-    )
-
-    pb = PulseBrain(agent, pulse_interval=10)
-    pb.start()
-
-    try:
-        print("Running... Press Ctrl+C to stop\n")
-        while True:
-            time.sleep(1)
-    except KeyboardInterrupt:
-        pb.stop()

pyproject.toml

@@ -0,0 +1,137 @@
+[build-system]
+requires = ["setuptools>=68.0", "wheel"]
+build-backend = "setuptools.build_meta"
+
+[project]
+name = "ajarbot"
+version = "0.2.0"
+description = "Multi-platform AI agent powered by Claude with memory, tools, and scheduling"
+readme = "README.md"
+requires-python = ">=3.10"
+license = {text = "MIT"}
+authors = [
+    {name = "Ajarbot Team"}
+]
+keywords = ["ai", "agent", "claude", "slack", "telegram", "chatbot", "assistant"]
+classifiers = [
+    "Development Status :: 4 - Beta",
+    "Intended Audience :: Developers",
+    "License :: OSI Approved :: MIT License",
+    "Programming Language :: Python :: 3",
+    "Programming Language :: Python :: 3.10",
+    "Programming Language :: Python :: 3.11",
+    "Programming Language :: Python :: 3.12",
+    "Operating System :: OS Independent",
+    "Topic :: Communications :: Chat",
+    "Topic :: Scientific/Engineering :: Artificial Intelligence",
+]
+
+# Core dependencies (always installed)
+dependencies = [
+    "watchdog>=3.0.0",
+    "anthropic>=0.40.0",
+    "requests>=2.31.0",
+    "fastembed>=0.7.0",
+    "usearch>=2.23.0",
+    "numpy>=2.0.0",
+    "pyyaml>=6.0.1",
+    "python-dotenv>=1.0.0",
+]
+
+[project.optional-dependencies]
+# Slack adapter dependencies
+slack = [
+    "slack-bolt>=1.18.0",
+    "slack-sdk>=3.23.0",
+]
+
+# Telegram adapter dependencies
+telegram = [
+    "python-telegram-bot>=20.7",
+]
+
+# Google integration (Gmail + Calendar)
+google = [
+    "google-auth>=2.23.0",
+    "google-auth-oauthlib>=1.1.0",
+    "google-auth-httplib2>=0.1.1",
+    "google-api-python-client>=2.108.0",
+]
+
+# Agent SDK mode (uses Claude Pro subscription)
+agent-sdk = [
+    "claude-code-sdk>=0.1.0",
+    "fastapi>=0.109.0",
+    "uvicorn>=0.27.0",
+]
+
+# All optional dependencies
+all = [
+    "slack-bolt>=1.18.0",
+    "slack-sdk>=3.23.0",
+    "python-telegram-bot>=20.7",
+    "google-auth>=2.23.0",
+    "google-auth-oauthlib>=1.1.0",
+    "google-auth-httplib2>=0.1.1",
+    "google-api-python-client>=2.108.0",
+    "claude-code-sdk>=0.1.0",
+    "fastapi>=0.109.0",
+    "uvicorn>=0.27.0",
+]
+
+# Development dependencies
+dev = [
+    "pytest>=7.4.0",
+    "black>=23.0.0",
+    "ruff>=0.1.0",
+    "mypy>=1.5.0",
+]
+
+[project.urls]
+Homepage = "https://github.com/yourusername/ajarbot"
+Documentation = "https://github.com/yourusername/ajarbot#readme"
+Repository = "https://github.com/yourusername/ajarbot"
+Issues = "https://github.com/yourusername/ajarbot/issues"
+
+[project.scripts]
+# Main entry point - runs ajarbot.py
+ajarbot = "ajarbot:main"
+
+[tool.setuptools]
+# Auto-discover packages
+packages = ["config", "adapters", "adapters.slack", "adapters.telegram", "google_tools"]
+
+[tool.setuptools.package-data]
+# Include YAML config templates
+config = ["*.yaml"]
+
+[tool.black]
+line-length = 88
+target-version = ["py310", "py311", "py312"]
+
+[tool.ruff]
+line-length = 88
+target-version = "py310"
+select = [
+    "E",  # pycodestyle errors
+    "W",  # pycodestyle warnings
+    "F",  # pyflakes
+    "I",  # isort
+    "B",  # flake8-bugbear
+    "C4", # flake8-comprehensions
+]
+ignore = [
+    "E501", # line too long (handled by black)
+    "B008", # do not perform function calls in argument defaults
+]
+
+[tool.mypy]
+python_version = "3.10"
+warn_return_any = true
+warn_unused_configs = true
+disallow_untyped_defs = false
+disallow_incomplete_defs = false
+check_untyped_defs = true
+no_implicit_optional = true
+warn_redundant_casts = true
+warn_unused_ignores = true

requirements.txt

@@ -23,3 +23,8 @@ google-auth>=2.23.0
 google-auth-oauthlib>=1.1.0
 google-auth-httplib2>=0.1.1
 google-api-python-client>=2.108.0
+
+# Claude Agent SDK (uses Pro subscription instead of API tokens)
+claude-agent-sdk>=0.1.0
+anyio>=4.0.0
+python-dotenv>=1.0.0

run.bat

@@ -0,0 +1,79 @@
+@echo off
+REM ========================================
+REM Ajarbot - Windows One-Command Launcher
+REM ========================================
+REM
+REM This script:
+REM 1. Creates/activates virtual environment
+REM 2. Installs dependencies if needed
+REM 3. Runs ajarbot.py
+REM
+REM Usage:
+REM   run.bat              Run the bot
+REM   run.bat --init       Generate config template
+REM   run.bat --health     Health check
+REM
+
+echo ========================================
+echo Ajarbot Windows Launcher
+echo ========================================
+echo.
+
+REM Check if virtual environment exists
+if not exist "venv\Scripts\activate.bat" (
+    echo [Setup] Creating virtual environment...
+    python -m venv venv
+    if errorlevel 1 (
+        echo ERROR: Failed to create virtual environment
+        echo Please ensure Python 3.10+ is installed and in PATH
+        pause
+        exit /b 1
+    )
+    echo [Setup] Virtual environment created
+)
+
+REM Activate virtual environment
+echo [Setup] Activating virtual environment...
+call venv\Scripts\activate.bat
+if errorlevel 1 (
+    echo ERROR: Failed to activate virtual environment
+    pause
+    exit /b 1
+)
+
+REM Check if dependencies are installed (check for a key package)
+python -c "import anthropic" 2>nul
+if errorlevel 1 (
+    echo.
+    echo [Setup] Installing dependencies...
+    echo This may take a few minutes on first run...
+    python -m pip install --upgrade pip
+    pip install -r requirements.txt
+    if errorlevel 1 (
+        echo ERROR: Failed to install dependencies
+        pause
+        exit /b 1
+    )
+    echo [Setup] Dependencies installed
+    echo.
+)
+
+REM Run ajarbot with all arguments passed through
+echo [Launch] Starting ajarbot...
+echo.
+python ajarbot.py %*
+
+REM Check exit code
+if errorlevel 1 (
+    echo.
+    echo ========================================
+    echo Ajarbot exited with an error
+    echo ========================================
+    pause
+    exit /b 1
+)
+
+echo.
+echo ========================================
+echo Ajarbot stopped cleanly
+echo ========================================

tools.py

@@ -100,6 +100,21 @@ TOOL_DEFINITIONS = [
             "required": ["command"],
         },
     },
+    {
+        "name": "get_weather",
+        "description": "Get current weather for a location using OpenWeatherMap API. Returns temperature, conditions, and brief summary.",
+        "input_schema": {
+            "type": "object",
+            "properties": {
+                "location": {
+                    "type": "string",
+                    "description": "City name or 'City, Country' (e.g., 'Phoenix, US' or 'London, GB'). Defaults to Phoenix, AZ if not specified.",
+                    "default": "Phoenix, US",
+                }
+            },
+            "required": [],
+        },
+    },
     # Gmail tools
     {
         "name": "send_email",
@@ -345,6 +360,9 @@ def execute_tool(tool_name: str, tool_input: Dict[str, Any], healing_system: Any
             command = tool_input["command"]
             working_dir = tool_input.get("working_dir", ".")
             return _run_command(command, working_dir)
+        elif tool_name == "get_weather":
+            location = tool_input.get("location", "Phoenix, US")
+            return _get_weather(location)
         # Gmail tools
         elif tool_name == "send_email":
             return _send_email(
@@ -530,6 +548,65 @@ def _run_command(command: str, working_dir: str) -> str:
         return f"Error running command: {str(e)}"
 
 
+def _get_weather(location: str = "Phoenix, US") -> str:
+    """Get current weather for a location using OpenWeatherMap API.
+
+    Args:
+        location: City name or 'City, Country' (e.g., 'Phoenix, US')
+
+    Returns:
+        Weather summary string
+    """
+    import requests
+
+    api_key = os.getenv("OPENWEATHERMAP_API_KEY")
+    if not api_key:
+        return "Error: OPENWEATHERMAP_API_KEY not found in environment variables. Please add it to your .env file."
+
+    try:
+        # OpenWeatherMap API endpoint
+        base_url = "http://api.openweathermap.org/data/2.5/weather"
+        params = {
+            "q": location,
+            "appid": api_key,
+            "units": "imperial"  # Fahrenheit
+        }
+
+        response = requests.get(base_url, params=params, timeout=10)
+        response.raise_for_status()
+
+        data = response.json()
+
+        # Extract weather data
+        temp = data["main"]["temp"]
+        feels_like = data["main"]["feels_like"]
+        description = data["weather"][0]["description"].capitalize()
+        humidity = data["main"]["humidity"]
+        wind_speed = data["wind"]["speed"]
+        city = data["name"]
+
+        # Format weather summary
+        summary = f"**{city} Weather:**\n"
+        summary += f"🌡️ {temp}°F (feels like {feels_like}°F)\n"
+        summary += f"☁️ {description}\n"
+        summary += f"💧 Humidity: {humidity}%\n"
+        summary += f"💨 Wind: {wind_speed} mph"
+
+        return summary
+
+    except requests.exceptions.HTTPError as e:
+        if e.response.status_code == 401:
+            return "Error: Invalid OpenWeatherMap API key. Please check your OPENWEATHERMAP_API_KEY in .env file."
+        elif e.response.status_code == 404:
+            return f"Error: Location '{location}' not found. Try format: 'City, Country' (e.g., 'Phoenix, US')"
+        else:
+            return f"Error: OpenWeatherMap API error: {e}"
+    except requests.exceptions.Timeout:
+        return "Error: Weather API request timed out. Please try again."
+    except Exception as e:
+        return f"Error getting weather: {str(e)}"
+
+
 # Google Tools Handlers