Performance Benchmarks

Verify your agent stack meets performance targets — import under 200 ms, heavy deps loaded only when needed.

from praisonaiagents import Agent

# Silent output (default) keeps import overhead minimal
agent = Agent(name="Bench", instructions="You are helpful.")
result = agent.start("Say hello in one word")

The user runs a lightweight agent; benchmarks verify import time and lazy-loading stay within targets.

Quick Start

Simple Usage

Run the built-in benchmark from the CLI:

pip install praisonai
praisonai perf benchmark

With Configuration

Add a CI gate that fails on agent-instantiation regressions using the built-in benchmark:

# .github/workflows/agent-performance.yml
name: agent-performance
on:
  pull_request:
    paths:
      - 'src/praisonai-agents/praisonaiagents/**'
      - 'src/praisonai-agents/benchmarks/**'
jobs:
  benchmark:
    runs-on: ubuntu-latest
    timeout-minutes: 5
    steps:
      - uses: actions/checkout@v4
      - uses: actions/setup-python@v5
        with:
          python-version: '3.11'
      - run: pip install -e src/praisonai-agents
      - name: Run benchmark with threshold gate
        working-directory: src/praisonai-agents
        run: python benchmarks/simple_benchmark.py --skip-crewai --json --fail-over-threshold | tee agent-perf-baseline.json
      - uses: actions/upload-artifact@v4
        with:
          name: agent-perf-baseline
          path: src/praisonai-agents/agent-perf-baseline.json

Budgets live in src/praisonai-agents/benchmarks/thresholds.json:

{
  "praisonai_instantiation_us_max": 450,
  "iterations": 100,
  "warmup": 10
}

Performance Targets

Metric	Target	Hard fail	Description
Import time	< 200 ms	> 300 ms	Time to `import praisonaiagents`
Memory usage	< 30 MB	> 45 MB	Memory after import
Lazy imports	All lazy	Any eager	Heavy deps not loaded at import
Agent instantiation	< 400 µs	> 450 µs	CI regression budget, not a typical value. Gated by `simple_benchmark.py --fail-over-threshold` using `thresholds.json`.

How It Works

CLI commands

praisonai perf benchmark    # Full suite
praisonai perf import-time  # Import time only
praisonai perf memory       # Memory usage only
praisonai perf lazy-check   # Verify lazy imports

Python benchmark scripts

From the SDK repo:

python benchmarks/import_time.py
python benchmarks/memory_usage.py

Configuration Options

Option	Type	Default	Description
`output`	`str`	`"silent"`	Silent mode avoids loading Rich at import
Import gate	CI threshold	300 ms	Hard fail limit for CI pipelines
Lazy modules	`sys.modules` check	—	`litellm`, `chromadb`, `mem0`, `requests`

Typical results (agent instantiation measured 2026-06-17, see BENCHMARK_RESULTS.md):

Metric	Target	Typical
Import time	< 200 ms	Varies by machine; see CI gate
Agent instantiation	< 450 μs (CI gate)	~13.6 μs (Jun 2026)
Memory per agent	< 10 KB	~4 KB
Heavy deps	Lazy	Lazy

As of PR #5630, Agent.__init__ skips the plugin-manager scan entirely when no plugins are registered (the common case), trimming ~18% off init latency and ~21% off function-call count on warmed inits.

Best Practices

Use silent output in production

output="silent" is the default — zero Rich overhead on the hot path. Keep it for APIs and batch jobs.

Import only what you need

Prefer from praisonaiagents import Agent over star imports to minimise load time.

Gate CI on import time

Add the 300 ms assert to your pipeline so lazy-loading regressions fail early.

Use LiteAgent for minimal footprint

For embedded or high-volume use, from praisonaiagents.lite import LiteAgent reduces memory further.

Lazy Imports

How lazy loading keeps startup fast

Performance CLI

CLI commands for benchmarking and regression checks

Benchmarks Reference

Full simple_benchmark.py flag reference and thresholds.json schema

Getting Started

Install

Core Concepts

Guides

Features

Models

Databases

Observability

Memory

Telemetry & Analytics

Knowledge

RAG

Persistence

Tools

Other Features

Developers

Configuration

Best Practices

Getting Started (No Code)

Performance Benchmarks

Quick Start

Performance Targets

How It Works

CLI commands

Python benchmark scripts

Configuration Options

Best Practices

Lazy Imports

Performance CLI

Benchmarks Reference

​Quick Start

​Performance Targets

​How It Works

​CLI commands

​Python benchmark scripts

​Configuration Options

​Best Practices

​Related

Lazy Imports

Performance CLI

Benchmarks Reference

Quick Start

Performance Targets

How It Works

CLI commands

Python benchmark scripts

Configuration Options

Best Practices

Related