AgentLens

Agent observability that traces decisions, not just API calls.

See why your AI agents chose what they chose.

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The Problem

Existing observability tools show you what LLM calls were made. AgentLens shows you why your agent made each decision along the way -- which tool it picked, what alternatives it rejected, and the reasoning behind every choice.

Getting Started

1. Register at agentlens.vectry.tech/register with your email and password.
2. Log in to the dashboard at agentlens.vectry.tech.
3. Create an API key in Settings > API Keys.
4. Install the SDK and start tracing.

Self-hosting? You do not need to register with the hosted service. See Self-Hosting below.

Quick Start

pip install vectry-agentlens

import agentlens

# Use the API key you created in Settings > API Keys
agentlens.init(api_key="your-key", endpoint="https://agentlens.vectry.tech")

with agentlens.trace("my-agent-task", tags=["production"]):
    # Your agent logic here...
    agentlens.log_decision(
        type="TOOL_SELECTION",
        chosen={"name": "search_web", "confidence": 0.92},
        alternatives=[{"name": "search_docs", "reason_rejected": "query too broad"}],
        reasoning="User query requires real-time data not in local docs"
    )

agentlens.shutdown()

Open https://agentlens.vectry.tech/dashboard to see your traces (login required).

Features

• Decision Tracing -- Log every decision point with reasoning, alternatives, and confidence scores
• OpenCode Plugin -- Trace your coding agent sessions with opencode-agentlens
• TypeScript SDK -- First-class TypeScript support with agentlens-sdk
• OpenAI Integration -- Auto-instrument OpenAI calls with one line: wrap_openai(client)
• LangChain Integration -- Drop-in callback handler for LangChain agents
• Nested Traces -- Multi-agent workflows with parent-child span relationships
• Real-time Dashboard -- SSE-powered live trace streaming with filtering and search
• Decision Tree Viz -- Interactive React Flow visualization of agent decision paths
• Analytics -- Token usage, cost tracking, duration timelines per trace
• Self-Hostable -- Docker Compose deployment, bring your own Postgres + Redis

OpenCode Plugin

Trace your OpenCode coding agent sessions automatically.

npm install -g opencode-agentlens

Add to your opencode.json:

{
  "plugin": ["opencode-agentlens"]
}

Set environment variables (use the API key from your dashboard at Settings > API Keys):

export AGENTLENS_API_KEY="your-key"
export AGENTLENS_ENDPOINT="https://agentlens.vectry.tech"

Every coding session automatically captures tool calls, LLM interactions, file edits, and permission flows.

TypeScript SDK

npm install agentlens-sdk

import { init, TraceBuilder, SpanType, SpanStatus } from "agentlens-sdk";

// Use the API key from Settings > API Keys in your dashboard
init({ apiKey: "your-key", endpoint: "https://agentlens.vectry.tech" });

const trace = new TraceBuilder("my-agent-task", {
  tags: ["production"],
});

trace.addSpan({
  name: "tool-call",
  type: SpanType.TOOL_CALL,
  status: SpanStatus.COMPLETED,
});

trace.end();

Architecture

SDK (Python/TS)              API (Next.js)              Dashboard (React)
 agentlens.trace() ------>  POST /api/traces  ------>  Real-time SSE stream
 TraceBuilder.end()          Prisma + Postgres          Decision tree viz
 OpenCode plugin             Redis pub/sub              Analytics & filters

Integrations

OpenAI

import openai
from agentlens.integrations.openai import wrap_openai

client = openai.OpenAI()
wrap_openai(client)  # Auto-traces all completions

with agentlens.trace("openai-task"):
    response = client.chat.completions.create(
        model="gpt-4o",
        messages=[{"role": "user", "content": "Hello!"}]
    )

LangChain

from agentlens.integrations.langchain import AgentLensCallbackHandler

handler = AgentLensCallbackHandler()
agent.run("Do something", callbacks=[handler])

Custom Agents

with agentlens.trace("planner"):
    agentlens.log_decision(
        type="ROUTING",
        chosen={"name": "research_agent"},
        alternatives=[{"name": "writer_agent"}],
        reasoning="Task requires data gathering first"
    )
    with agentlens.trace("researcher"):
        # Nested trace creates child span automatically
        agentlens.log_decision(
            type="TOOL_SELECTION",
            chosen={"name": "web_search"},
            alternatives=[{"name": "database_query"}],
            reasoning="Need real-time information"
        )

Decision Types

Type	Use Case
TOOL_SELECTION	Agent chose which tool/function to call
ROUTING	Agent decided which sub-agent or path to take
PLANNING	Agent formulated a multi-step plan
RETRY	Agent decided to retry a failed operation
ESCALATION	Agent escalated to human or higher-level agent
MEMORY_RETRIEVAL	Agent chose what context to retrieve
CUSTOM	Any other decision type

Pricing

AgentLens cloud (agentlens.vectry.tech) offers three billing tiers. One trace equals one session for billing purposes.

Plan	Price	Sessions	Details
Free	$0	20 sessions/day	No credit card required
Starter	$5/month	1,000 sessions/month	For individual developers
Pro	$20/month	100,000 sessions/month	For teams and production workloads

Manage your subscription in Settings > Billing in the dashboard.

Self-hosted instances are not subject to these limits.

Self-Hosting

Self-hosted AgentLens instances do not require registration with the hosted SaaS service. You manage your own API keys and have no session limits.

git clone https://gitea.repi.fun/repi/agentlens.git
cd agentlens
docker compose up -d

The dashboard will be available at http://localhost:4200.

Environment Variables

Variable	Default	Description
DATABASE_URL	postgresql://agentlens:agentlens@postgres:5432/agentlens	PostgreSQL connection string
REDIS_URL	redis://redis:6379	Redis connection string
NODE_ENV	production	Node environment

Project Structure

agentlens/
  apps/web/                # Next.js 15 dashboard + API
  packages/database/       # Prisma schema + client
  packages/sdk-python/     # Python SDK (PyPI: vectry-agentlens)
  packages/sdk-ts/         # TypeScript SDK (npm: agentlens-sdk)
  packages/opencode-plugin/ # OpenCode plugin (npm: opencode-agentlens)
  examples/                # Example agent scripts
  docker-compose.yml       # Production deployment

SDK Reference

• Python SDK documentation
• TypeScript SDK documentation
• OpenCode plugin documentation

Examples

See the examples directory for runnable agent scripts:

• basic_agent.py -- Minimal AgentLens usage with decision logging
• openai_agent.py -- OpenAI wrapper auto-instrumentation
• multi_agent.py -- Nested multi-agent workflows
• customer_support_agent.py -- Realistic support bot with routing and escalation

Contributing

AgentLens is open source under the MIT license. Contributions welcome.

# Development setup
npm install
npx turbo dev          # Start web app in dev mode
cd packages/sdk-python
pip install -e ".[dev]" # Install SDK in dev mode
pytest                  # Run SDK tests

License

MIT