Quickstart

Get started with AgentSight in seconds. With just a few lines of code, you can start monitoring your AI agent's conversations, questions, answers, and more. No setup or infrastructure required.

AgentSight is designed to be lightweight and developer-friendly. Instantiate the client with your API key, and you're ready to track your data.

Installation

First, install the AgentSight SDK. We also recommend installing python-dotenv to manage your API key securely via environment variables.

pip install agentsight python-dotenv

Setup

1. Get your API key from the AgentSight Dashboard
2. Add it to a .env file:

AGENTSIGHT_API_KEY="your_api_key_here"

Basic Usage

from agentsight import conversation_tracker
from dotenv import load_dotenv

load_dotenv()

# 1. Create a conversation
conversation_tracker.get_or_create_conversation(
    conversation_id="chat-123",
    customer_id="user-456",
    name="Support Chat"
)

# 2. Track user message
conversation_tracker.track_human_message("How do I reset my password?")

# 3. Track AI response
conversation_tracker.track_agent_message("Click 'Forgot Password' on the login page.")

# 4. Send all tracked data
response = conversation_tracker.send_tracked_data()
print(f"✅ Sent {response['summary']['questions']} questions and {response['summary']['answers']} answers")

That's it! Your conversation is now tracked in AgentSight.

Conversation tracking

Conversations are uniquely identified to help you maintain context across multiple interactions. Once you create a conversation with your ID, use that same ID to reference your tracking methods with that conversation.

What Can You Track?

• Messages - User questions and AI responses
• Actions - Tool usage, database queries, API calls
• Attachments - Files, images, documents
• Buttons - User interactions and clicks
• Tokens - LLM token usage for cost tracking

Three SDK Clients

AgentSight provides three clients for different needs:

Client	Purpose	Import
ConversationTracker	Track conversations in real-time	from agentsight import conversation_tracker
ConversationManager	Manage conversations (rename, feedback, delete...)	from agentsight import conversation_manager
AgentSightAPI	Fetch and query conversation data	from agentsight import agentsight_api

All clients are automatically initialized and ready to use.

Example: Complete Conversation

from agentsight import conversation_tracker
from dotenv import load_dotenv

load_dotenv()

# Create conversation
conversation_tracker.get_or_create_conversation(
    conversation_id="support-123",
    name="Password Reset"
)

# User asks
conversation_tracker.track_human_message("I can't log in")

# AI performs action
conversation_tracker.track_action(
    action_name="check_database",
    duration_ms=150,
    response="User found"
)

# AI responds
conversation_tracker.track_agent_message("I found your account. Let me help reset your password.")

# Track token usage
conversation_tracker.track_token_usage(
    prompt_tokens=45,
    completion_tokens=32,
    total_tokens=77
)

# User clicks button
conversation_tracker.track_button(
    button_event="password_reset",
    label="Send Reset Email",
    value="confirmed"
)

# Send everything
conversation_tracker.send_tracked_data()

Next Steps

Now that you’ve set up the basics, let’s continue with looking into Core Concepts