Initial commit: Ajarbot with optimizations

Features:
- Multi-platform bot (Slack, Telegram)
- Memory system with SQLite FTS
- Tool use capabilities (file ops, commands)
- Scheduled tasks system
- Dynamic model switching (/sonnet, /haiku)
- Prompt caching for cost optimization

Optimizations:
- Default to Haiku 4.5 (12x cheaper)
- Reduced context: 3 messages, 2 memory results
- Optimized SOUL.md (48% smaller)
- Automatic caching when using Sonnet (90% savings)

Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
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2026-02-13 19:06:28 -07:00
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# Pulse & Brain Architecture
The **most efficient** way to run an agent with proactive monitoring.
## 🎯 The Problem
Running an agent in a loop is expensive:
```python
# ❌ EXPENSIVE: Agent asks "What should I do?" every loop
while True:
response = agent.chat("What should I do?") # Costs tokens!
time.sleep(60)
```
**Cost:** If you check every minute for 24 hours:
- 1,440 API calls/day
- ~50,000 tokens/day
- ~$0.50/day just to ask "nothing to do"
## ✅ The Solution: Pulse & Brain
Think of it like a **security guard**:
- **Pulse (Guard)**: Walks the perimeter every 60 seconds. Checks doors (pure Python). **Cost: $0**
- **Brain (Manager)**: Only called when guard sees a problem or it's time for the morning report. **Cost: Only when needed**
```python
# ✅ EFFICIENT: Agent only invoked when needed
while True:
# Pulse: Pure Python checks (zero cost)
disk_check = check_disk_space() # $0
log_check = check_for_errors() # $0
task_check = check_stale_tasks() # $0
# Brain: Only if something needs attention
if disk_check.status == "error":
agent.chat("Disk space critical!") # Costs tokens (but only when needed)
if current_time == "08:00":
agent.chat("Morning briefing") # Costs tokens (scheduled)
time.sleep(60)
```
## 📊 Cost Comparison
### Old Heartbeat System (Always Uses Agent)
```python
# Every 30 minutes, agent processes checklist
while True:
response = agent.chat(checklist) # ~1000 tokens
time.sleep(1800) # 30 min
```
**Cost per day:**
- 48 checks/day
- ~48,000 tokens/day
- ~$0.48/day
### Pulse & Brain (Conditional Agent)
```python
# Every 60 seconds, pure Python checks (zero cost)
# Agent only invoked when:
# 1. Error detected (~2x/day)
# 2. Scheduled briefings (2x/day)
# = ~4 agent calls/day
```
**Cost per day:**
- 1,440 pulse checks (pure Python) = **$0**
- 4 brain invocations (~4,000 tokens) = **$0.04/day**
**Savings: 92%** 💰
## 🏗️ Architecture
```
┌─────────────────────────────────────────────────────┐
│ PULSE LOOP │
│ (Pure Python, $0 cost) │
│ │
│ ┌───────────┐ ┌───────────┐ ┌───────────┐ │
│ │ Disk Space│ │ Log Errors│ │ Tasks │ │
│ │ Check │ │ Check │ │ Check │ ... │
│ └─────┬─────┘ └─────┬─────┘ └─────┬─────┘ │
│ │ │ │ │
│ └──────────────┼──────────────┘ │
│ │ │
│ ┌───────▼───────┐ │
│ │ Conditions? │ │
│ └───────┬───────┘ │
│ │ │
│ ┌──────────────┴──────────────┐ │
│ │ │ │
│ ┌────▼────┐ ┌────▼────┐ │
│ │ Error? │ │ 8:00 AM?│ │
│ └────┬────┘ └────┬────┘ │
│ │ YES │ YES │
└────────┼─────────────────────────────┼──────────────┘
│ │
└──────────┬──────────────────┘
┌──────────▼──────────┐
│ BRAIN │
│ (Agent/SDK) │
│ COSTS TOKENS │
└─────────────────────┘
```
## 🔧 Usage
### Basic Setup
```python
from agent import Agent
from pulse_brain import PulseBrain
agent = Agent(provider="claude", enable_heartbeat=False)
# Create Pulse & Brain
pb = PulseBrain(agent, pulse_interval=60) # Pulse every 60 seconds
# Start
pb.start()
```
### With Messaging Platforms
```python
from adapters.runtime import AdapterRuntime
from pulse_brain import PulseBrain
# Set up runtime with adapters
runtime = AdapterRuntime(agent)
runtime.add_adapter(slack_adapter)
# Create Pulse & Brain
pb = PulseBrain(agent)
pb.add_adapter("slack", slack_adapter)
# Start both
await runtime.start()
pb.start()
```
## 📝 Default Checks
### Pulse Checks (Zero Cost)
| Check | Interval | What It Does |
|-------|----------|--------------|
| `disk-space` | 5 min | Checks disk usage, warns >80% |
| `memory-tasks` | 10 min | Counts pending tasks |
| `log-errors` | 1 min | Scans logs for errors |
### Brain Tasks (Uses Tokens)
| Task | Type | Trigger |
|------|------|---------|
| `disk-space-advisor` | Conditional | Disk >90% used |
| `error-analyst` | Conditional | Errors found in logs |
| `morning-briefing` | Scheduled | Daily at 8:00 AM |
| `evening-summary` | Scheduled | Daily at 6:00 PM |
## 🎨 Custom Configuration
Create `config/pulse_brain_config.py`:
```python
from pulse_brain import PulseCheck, BrainTask, CheckType
def check_my_server() -> dict:
"""Pure Python check (zero cost)."""
import requests
try:
r = requests.get("http://localhost:8000/health")
return {
"status": "ok" if r.status_code == 200 else "error",
"message": f"Server: {r.status_code}"
}
except:
return {"status": "error", "message": "Server down"}
CUSTOM_PULSE_CHECKS = [
PulseCheck("my-server", check_my_server, interval_seconds=60)
]
CUSTOM_BRAIN_TASKS = [
BrainTask(
name="server-medic",
check_type=CheckType.CONDITIONAL,
prompt_template="Server is down! {message}\n\nWhat should I check?",
condition_func=lambda data: data.get("status") == "error"
)
]
```
## 🌟 Real-World Examples
### Example 1: Homelab Monitoring (from Gemini)
**The "Morning Briefing"** (Scheduled Brain):
```python
BrainTask(
name="homelab-morning",
check_type=CheckType.SCHEDULED,
schedule_time="08:00",
prompt_template="""Good morning Jordan!
Overnight summary:
- Plex: {plex_status}
- Star Citizen: {game_status}
- UniFi: {network_status}
Any restarts or patches detected?""",
send_to_platform="slack",
send_to_channel="C_HOMELAB"
)
```
**Cost:** 1 API call/day = ~$0.01
**The "Medic"** (Conditional Brain):
```python
def check_logs():
"""Pure Python log scanner."""
with open("/var/log/syslog") as f:
recent = f.readlines()[-100:]
errors = [line for line in recent if "ERROR" in line]
return {
"status": "error" if errors else "ok",
"error_lines": errors
}
BrainTask(
name="error-medic",
check_type=CheckType.CONDITIONAL,
prompt_template="""Errors detected in logs:
{error_lines}
What does this mean and should I fix it?""",
condition_func=lambda data: data.get("status") == "error"
)
```
**Cost:** Only when errors found = ~$0.01 per error
**The "Resource Manager"** (Conditional Brain):
```python
BrainTask(
name="disk-cleanup",
check_type=CheckType.CONDITIONAL,
prompt_template="""Disk space is low: {gb_free:.1f} GB free.
Please:
1. Scan temp folders
2. Recommend what to delete (>7 days old)
3. Provide cleanup commands""",
condition_func=lambda data: data.get("gb_free", 100) < 10
)
```
**Cost:** Only when disk < 10GB = ~$0.02 per trigger
### Example 2: Docker Monitoring
```python
def check_docker():
import subprocess
result = subprocess.run(
["docker", "ps", "--format", "{{.Status}}"],
capture_output=True, text=True
)
unhealthy = sum(1 for line in result.stdout.split("\n")
if "unhealthy" in line)
return {
"status": "error" if unhealthy > 0 else "ok",
"unhealthy_count": unhealthy
}
PULSE_CHECK = PulseCheck("docker", check_docker, interval_seconds=60)
BRAIN_TASK = BrainTask(
name="docker-fixer",
check_type=CheckType.CONDITIONAL,
prompt_template="{unhealthy_count} containers unhealthy. What should I do?",
condition_func=lambda data: data.get("unhealthy_count", 0) > 0
)
```
**Pulse runs every 60s:** $0
**Brain only when unhealthy:** ~$0.01 per incident
## 🎯 When to Use What
| System | Best For | Cost |
|--------|----------|------|
| **Pulse & Brain** | Production monitoring | ~$1-2/month |
| **TaskScheduler** | Scheduled content | ~$3-5/month |
| **Old Heartbeat** | Simple health checks | ~$15/month |
### Recommended Stack
For maximum efficiency:
```python
# Pulse & Brain for monitoring (cheapest)
pb = PulseBrain(agent, pulse_interval=60)
pb.start()
# TaskScheduler for scheduled content only
scheduler = TaskScheduler(agent)
# Only enable specific scheduled tasks
scheduler.start()
```
## 📊 Monitoring Your Costs
```python
pb = PulseBrain(agent)
pb.start()
# After running for a while
status = pb.get_status()
print(f"Brain invoked {status['brain_invocations']} times")
# Estimate cost
tokens_per_invocation = 1000 # Average
total_tokens = status['brain_invocations'] * tokens_per_invocation
cost = total_tokens * 0.000003 # Claude Sonnet pricing
print(f"Estimated cost: ${cost:.4f}")
```
## 🚀 Getting Started
1. **Edit** `config/pulse_brain_config.py` with your checks
2. **Test** your pulse checks (they should return `{"status": "ok|warn|error"}`)
3. **Configure** brain tasks (conditional or scheduled)
4. **Run** `python -m pulse_brain`
5. **Monitor** brain invocation count
## 🔥 Pro Tips
1. **Make pulse checks fast** (<1 second each)
2. **Use conditional brain tasks** for errors/warnings
3. **Use scheduled brain tasks** for daily summaries
4. **Test pulse checks** without brain first
5. **Monitor brain invocations** to track costs
## 🎉 Summary
**Pulse & Brain is the most cost-effective way to run a proactive agent:**
**Pulse runs constantly** - Zero cost
**Brain only when needed** - Pay for value
**92% cost savings** vs always-on agent
**Smart monitoring** - Python checks + Agent analysis
**Scalable** - Add more checks without increasing cost
**Perfect for:**
- Homelab monitoring
- Server health checks
- Log analysis
- Resource management
- Scheduled briefings
**Result:** An agent that's always watching but only speaks when it has something important to say. 🫀🧠