Drop-in performance acceleration for CrewAI - Get up to 34x faster serialization, 17x faster tool execution, and 11x faster database search with zero code changes to your existing CrewAI projects.
Built and maintained by Neul Labs to bring production-ready acceleration to CrewAI workloads.
Links: Website · Docs · GitHub
Get your CrewAI code running faster in seconds:
# Install the acceleration layer (using uv - recommended)
uv add fast-crewai
# Or with pip
pip install fast-crewai
# Add one line to your existing CrewAI code
import fast_crewai.shim # Add this before importing CrewAI
from crewai import Agent, Task, Crew # Your existing code remains unchanged!That's it! Your existing CrewAI code now benefits from Rust-powered acceleration.
| Component | Performance Boost | What This Means |
|---|---|---|
| Serialization | 🚀 34x faster | Agent message serialization using serde |
| Tool Execution | 🚀 17x faster | Result caching and JSON validation |
| Database Search | 🚀 11x faster | FTS5 full-text search with BM25 ranking |
| Memory Storage | ✅ TF-IDF search | Semantic search using cosine similarity |
| Task Execution | ✅ Dependency tracking | Topological sort and parallel scheduling |
See BENCHMARK.md for detailed performance data.
Fast-CrewAI uses smart monkey patching that seamlessly integrates with your existing CrewAI code:
# Your existing CrewAI code - no changes needed!
from crewai import Agent, Task, Crew # This automatically gets accelerated!
# Just add this line once at the top of your main file
import fast_crewai.shim # Activates acceleration for all CrewAI componentsThe acceleration happens automatically through dynamic inheritance - your tools, tasks, and other components get wrapped with performance improvements while keeping 100% API compatibility.
# Using uv (recommended)
uv add fast-crewai
# Or with pip
pip install fast-crewaifast-crewai is also published to crates.io as the PyO3 extension module that powers the Python wheel. The Python package above is the intended interface for most users. To build against the Rust crate directly:
cargo add fast-crewai# Install uv if you haven't already
curl -LsSf https://astral.sh/uv/install.sh | sh
# Clone and setup
git clone https://github.com/neul-labs/fast-crewai.git
cd fast-crewai
uv sync --dev
# Build Rust extensions for maximum performance
uv run maturin develop --releaseVerify Fast-CrewAI is working with these tests:
# Run all unit tests
make test
# Compare performance (with/without acceleration) - runs full CrewAI workflows
make test-comparison
# Run extensive performance tests (1000 iterations)
make test-comparison-extensive
# Full compatibility check with CrewAI
make test-compatibility
# Run internal benchmarks
make benchmarkThe test-comparison command runs complete CrewAI workflows that engage all acceleration components:
- Memory acceleration: Through CrewAI's memory systems (RAG storage, short/long-term memory)
- Database acceleration: Through SQLite operations for memory persistence
- Tool execution: Through any tools used in the workflow (hooks enabled)
- Task execution: Through CrewAI's task processing system (hooks enabled)
For example, on basic workflows the comparison typically shows around 13% performance improvement:
==================================================
Workflow Type: basic
Iterations: 3
Baseline (without Fast-CrewAI): 27.88s
Accelerated (with Fast-CrewAI): 24.50s
Time Saved: 3.38s
Performance Improvement: 1.13x faster
Percent Improvement: 13.00%
==================================================
Higher improvements (2-5x) are typically seen with memory-intensive and database-heavy workflows where Fast-CrewAI's Rust acceleration provides greater benefits.
Fine-tune your acceleration with environment variables:
# Enable all acceleration (default)
export FAST_CREWAI_ACCELERATION=1
# Disable acceleration (for debugging)
export FAST_CREWAI_ACCELERATION=0
# Control specific components
export FAST_CREWAI_MEMORY=true # Memory acceleration
export FAST_CREWAI_TOOLS=false # Tool acceleration
export FAST_CREWAI_DATABASE=true # Database accelerationLatest benchmark results (see BENCHMARK.md for full details):
| Component | Improvement | Details |
|---|---|---|
| Serialization | 🚀 34.5x faster | 80,525 ops/s (Rust) vs 2,333 ops/s (Python) |
| Tool Execution | 🚀 17.3x faster | Result caching with configurable TTL |
| FTS Database Search | 🚀 11.2x faster | 10,206 ops/s (FTS5) vs 913 ops/s (LIKE) |
| Database Query | 🚀 1.3x faster | Connection pooling with r2d2 |
| Memory Storage | ✅ Comparable | TF-IDF semantic search |
| Component | Python | Rust | Savings |
|---|---|---|---|
| Tool Execution | 1.2 MB | 0.0 MB | 99% less |
| Serialization | 8.0 MB | 3.4 MB | 58% less |
| Database | 0.1 MB | 0.1 MB | 31% less |
Database (FTS5)
- Full-text search with BM25 relevance ranking
- Automatic index synchronization via triggers
- Connection pooling for concurrent access
Tool Executor
- Result caching with TTL expiration
- Fast JSON validation using serde
- Execution statistics tracking
Task Executor
- Dependency tracking with topological sort
- Cycle detection for circular dependencies
- Parallel task scheduling via Tokio
Serialization
- serde-based JSON serialization (34x faster)
- Lower memory footprint (58% less)
The project includes comprehensive tools for development and performance analysis:
# Run all tests
make test
# Run performance comparisons
make test-comparison # Quick comparison
make test-comparison-extensive # 1000 iterations for detailed analysis
# Run compatibility tests
make test-compatibility # Verify with latest CrewAI
# Run internal benchmarks
make benchmark # Test components in isolation- Architecture: How the acceleration system works under the hood
- API Reference: Complete API documentation
- Configuration: Fine-tuning Fast-CrewAI for your needs
- Performance: Detailed benchmarking and optimization
- Troubleshooting: Common issues and solutions
For complete documentation, visit the docs/ directory.
| Python Version | Status | Notes |
|---|---|---|
| Python 3.10 | ✅ Supported | Fully tested |
| Python 3.11 | ✅ Supported | Fully tested |
| Python 3.12 | ✅ Supported | Fully tested |
| Python 3.13 | ✅ Supported | Fully tested |
| Python 3.9 | May work but not tested in CI |
- CrewAI: Any recent version supported
- Rust toolchain: Optional, for native extensions (provides maximum performance)
- PyO3 0.23+ is used for Python-Rust bindings
- Falls back to pure Python if Rust extensions aren't available
| Platform | Status |
|---|---|
| Linux (x86_64) | ✅ Fully supported |
| macOS (x86_64) | ✅ Fully supported |
| macOS (ARM64/M1) | ✅ Fully supported |
| Windows (x86_64) | ✅ Supported |
Contributions are welcome! Check out our development guide for setup instructions and coding standards.
MIT License - see LICENSE file for details.
- Maintainer: Neul Labs (contact@neullabs.com)
- Website: https://fast-crewai.neullabs.com
- Issues: GitHub Issues
- Discussions: GitHub Discussions
Fast-CrewAI is in active development. Memory and database acceleration are production-ready, with ongoing optimization for tools and tasks.
Fast-CrewAI is part of the Neul Labs accelerators family. Explore the rest of the toolchain from Neul Labs:
| Project | What it does |
|---|---|
| fast-litellm | Drop-in Rust acceleration for LiteLLM. |
| fast-langgraph | Rust accelerators for LangGraph — up to 700x faster checkpoints. |
| fast-axolotl | Rust extensions for Axolotl fine-tuning — no OOM on large datasets. |
| fastagentic | Build agents with any framework; ship them with FastAgentic. |