👁️ Observer AI

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The Agent that monitors your screen, so you don't have to.

Using local models, keeping your data 100% private and secure.

What Observer Does Best

When X then Y

• When I'm distracted, call me.
• When my download finishes, SMS me.
• When my render is done, Whatsapp me.
• When this dashboard changes, email me.
• When a person is on camera, telegram me.
• When my dog finishes their food, log it.

How Observer Micro-Agents Work

Sensors →

Models →

Tools

Screen • Camera • Mic • Audio

Local LLMs

Messaging • Notifications • Recording • Memory • Code

Base Micro-Agent Example

Sends an email when the Observer logo is on screen

System Prompt (uses $SCREEN for multimodal screen input)

You are an Observer agent, watch the screen and if you see the Observer logo say OBSERVER, if you don't, say CONTINUE. 
$SCREEN

Code using Email Tool if model identified an Observer logo

if(response.includes("OBSERVER")){
  sendEmail("your@email.com", response, screen); //sends the screen as an attached image
}

Building Your Own Micro-Agent

Creating your own Observer AI consist of three things:

• SENSORS - input that your model will have
• MODELS - Small LLMs
• TOOLS - functions for your model to use

Quick Start

1. Navigate to the Agent Dashboard and click "Create New Agent"
2. Fill in the "Configuration" tab with basic details (name, description, model, loop interval)
3. Give your model a system prompt and Sensors! The current Sensors that exist are:
   • Screenshot ($SCREEN) Captures screen as an image for multimodal models.
   • Screen OCR ($SCREEN_OCR) Captures screen content as text via OCR.
   • CAMERA ($CAMERA) Captures the camera for multimodal models.
   • CAMERA OCR ($CAMERA_OCR) Captures the camera text via OCR.
   • Agent Memory ($MEMORY or $MEMORY@agent_id) Accesses agents' stored information (defaults to current agent)
   • Agent Image Memory ($IMEMORY or $IMEMORY@agent_id) Accesses agents' stored images (defaults to current agent)
   • Agent Image Memory OCR ($IMEMORY_OCR) Captures text on an image's memory via OCR.
   • Clipboard ($CLIPBOARD) It pastes the clipboard contents
   • Microphone* ($MICROPHONE) Captures the microphone and adds a transcription
   • Screen Audio* ($SCREEN_AUDIO) Captures the audio transcription of screen sharing a tab.
   • All audio* ($ALL_AUDIO) Mixes the microphone and screen audio and provides a complete transcription of both (used for meetings).

* Uses a whisper model with transformers.js

Agent Tools:

• getMemory(agentId?)* – Retrieve stored memory
• setMemory(agentId?, content)* – Replace stored memory
• appendMemory(agentId?, content)* – Add to existing memory
• getImageMemory(agentId?)* - Retrieve images stored in memory
• setImageMemory(agentId?, images)* - Set images to memory
• appendImageMemory(agentId?, images)* - Add images to memory
• startAgent(agentId?)* – Starts an agent
• stopAgent(agentId?)* – Stops an agent
• time() - Gets current time
• sleep(ms) - Waits that ammount of miliseconds

* agentId is optional, deaults to agent running code

Notification Tools:

• sendDiscord(discord_webhook, message, images?, videos?) - Directly sends a discord message to a server.
• sendTelegram(chat_id, message, images?, videos?) Sends a telegram message with the Observer bot. Get the chat_id messaging the bot @observer_notification_bot.
• sendEmail(email, message, images?, videos?) - Sends an email. Email must be the signed in email.
• sendPushover(user_token, message, images?, title?) - Sends a pushover notification.
• call(phone_number, message)* - Makes an automated phone call with text-to-speech message. Needs whitelisting.
• sendWhatsapp(phone_number, message, images?, videos?)* - Sends a whatsapp message with the Observer bot. Needs whitelisting.
• sendSms(phone_number, message, images?, videos?)* - Sends an SMS to a phone number. Due to A2P policy, blocked for US/Canada. Needs whitelisting.
• notify(title, options) – Send browser notification ⚠️IMPORTANT: Some browsers block notifications
• sound(name?, volume?) - Plays a notification sound locally. No account needed, works on web and app.

* To whitelist, SMS or call +1 (863)208-5341 or whatsapp +1 (555)783-4727

Video Recording Tools:

• startClip() - Starts a recording of any video media and saves it to the recording Tab.
• stopClip() - Stops an active recording
• markClip(label) - Adds a label to any active recording that will be displayed in the recording Tab.
• getVideo() - Returns array of videos on buffer.

App Tools:

• ask(question, title="Confirmation") - Pops up a system confirmation dialog
• message(message, title="Agent Message") - Pops up a system message
• system_notify(body, title="Observer AI") - Sends a system notification
• overlay(body) - Pushes a message to the overlay
• click('left'|'right') - Triggers a mouse click at the current cursor position accepts either 'left' or 'right', defaults to left.
• celebrate() - Triggers a celebration animation in the Observer UI.

Code Tab

The "Code" tab receives the following variables as context before running:

• response - The model's response (null when using a decision model)
• decision - The decision model's answer (null for text models, see Decision Models)
• agentId - The id of the agent running the code
• screen - The screen if captured
• camera - The camera if captured
• imemory - The agent's current image in memory
• images - All images sent to the model
• prompt - The model's prompt
• microphone - Trascription from the microphone in this loop
• screenAudio - Transcription from screen audio in this loop
• allAudio - Transcription from microphone and screen audio mixed in this loop

JavaScript agents run in the browser sandbox, making them ideal for passive monitoring and notifications:

// Remove Think tags for deepseek model
const cleanedResponse = response.replace(/<think>[\s\S]*?<\/think>/g, '').trim();

// Get time
const time = time();

// Update memory with timestamp
appendMemory(`[${time}] ${cleanedResponse}`);

// Send to Telegram if the model mentions a word
if(response.includes("word")){
  sendTelegram(cleanedResponse, "12345678") // Example chat_id
}

Decision Models

Decision models don't write text, they answer typed questions with probabilities. response is null and the result is in decision instead.

Plain-text prompt – a single yes/no (noul) question, the sensor images are the state:

Is there a person in the room? $CAMERA

decision is one answer:

// { type: 'noul', noul: 0.94, start: 0.12, dropped: false }
if (decision.noul > 0.8) {
  sendTelegram("12345678", "Someone is in the room", camera);
}

• noul - Probability of "yes" (0 to 1)
• start - Average noul over the run's first 3 iterations
• dropped - true once noul has stayed well below start for 3 iterations in a row (useful for "t