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A flexible, plugin-based framework for building AI agents

Project description

Entity Framework ๐Ÿš€

Build Production-Ready AI Agents 10x Faster

PyPI version Documentation Status Python 3.11+ License: MIT Tests Coverage


๐ŸŽฏ Why Entity Framework?

Stop fighting with boilerplate. Start building intelligent agents.

Entity transforms AI development from a complex engineering challenge into simple, composable components. While other frameworks force you to write thousands of lines of coupled code, Entity's revolutionary plugin architecture lets you build production-ready agents in hours, not weeks.

# Traditional approach: 2000+ lines of code, 2-3 weeks
# Entity approach: This is it. Seriously.

from entity import Agent
agent = Agent.from_config("your_agent.yaml")
await agent.chat("")  # Interactive intelligent agent with memory, tools, safety

๐Ÿ”ฅ What Makes Entity Different

Feature Traditional Frameworks Entity Framework
Development Time 2-3 weeks 2-3 days
Lines of Code 2000+ lines 200 lines
Architecture Monolithic, coupled Plugin-based, modular
Configuration Code changes required YAML-driven
Testing Complex integration tests Simple unit tests
Team Collaboration Sequential development Parallel plugin development
Maintenance Fragile, risky changes Isolated, safe updates
Production Ready DIY monitoring/safety Built-in observability

โšก 30-Second Quickstart

# Install Entity
pip install entity-core

# Run your first agent
python -c "
from entity import Agent
from entity.defaults import load_defaults

agent = Agent(resources=load_defaults())
print('๐Ÿค– Agent ready! Try: Hello, tell me a joke')
"

That's it. You now have a production-ready AI agent with:

  • ๐Ÿง  Local LLM (Ollama) or cloud APIs
  • ๐Ÿ’พ Persistent memory with conversation history
  • ๐Ÿ›ก๏ธ Built-in safety and error handling
  • ๐Ÿ“Š Automatic logging and monitoring
  • ๐Ÿ”ง Zero configuration required

๐ŸŽจ Progressive Examples

Hello World Agent (3 lines)

from entity import Agent
from entity.defaults import load_defaults

agent = Agent(resources=load_defaults())
response = await agent.chat("Hello!")  # "Hi! How can I help you today?"

Agent with Custom Personality (5 lines)

from entity import Agent

agent = Agent.from_config("personality_config.yaml")
# YAML defines: role="You are a helpful Python tutor"
response = await agent.chat("Explain decorators")  # Detailed Python tutorial

Agent with Tools (10 lines)

from entity import Agent
from entity.tools import WebSearchTool, CalculatorTool

agent = Agent.from_config("tools_config.yaml")
# YAML enables: web_search, calculator, file_operations
response = await agent.chat("Search for Python 3.12 features and calculate 15% of 200")
# Executes web search, performs calculation, provides comprehensive answer

Multi-Agent Collaboration (15 lines)

from entity import Agent, AgentOrchestrator

# Create specialized agents
researcher = Agent.from_config("researcher_config.yaml")
writer = Agent.from_config("writer_config.yaml")
reviewer = Agent.from_config("reviewer_config.yaml")

# Orchestrate workflow
orchestrator = AgentOrchestrator([researcher, writer, reviewer])
result = await orchestrator.execute("Write a technical blog post about Entity Framework")
# Researcher gathers info โ†’ Writer creates post โ†’ Reviewer refines โ†’ Final result

Production Configuration (Complete system)

from entity import Agent
from entity.monitoring import setup_observability

# Production-ready agent with full observability
agent = Agent.from_config("production_config.yaml")
setup_observability(agent, metrics=True, alerts=True, tracing=True)

# YAML configures: clustering, load balancing, database, monitoring, safety filters
await agent.serve(host="0.0.0.0", port=8000)  # Production API server

๐Ÿ—๏ธ The Entity Architecture

Entity's revolutionary 6-stage plugin pipeline transforms how you build AI applications:

The Pipeline Flow

๐Ÿ“ INPUT โ†’ ๐Ÿ“Š PARSE โ†’ ๐Ÿง  THINK โ†’ ๐Ÿ”ง DO โ†’ โœ… REVIEW โ†’ ๐Ÿ“ค OUTPUT

Stage Details

๐Ÿ“ Stage 1: INPUT

Receive and process incoming data

  • Handles: Text, Files, Images, URLs, Voice, Data
  • Plugins: Input Adapters
  • Purpose: Accept any input format seamlessly

๐Ÿ“Š Stage 2: PARSE

Understand and structure the input

  • Handles: Language Analysis, Structure, Metadata
  • Plugins: Parsers
  • Purpose: Extract meaning and context

๐Ÿง  Stage 3: THINK

Reason about the task

  • Handles: Context Synthesis, Planning, Strategy
  • Plugins: Reasoning Engines
  • Purpose: Decide best approach

๐Ÿ”ง Stage 4: DO

Execute actions and operations

  • Handles: Tools, Search, Analysis, APIs
  • Plugins: Tool Executors
  • Purpose: Perform the actual work

โœ… Stage 5: REVIEW

Validate and ensure quality

  • Handles: Quality, Safety, Compliance
  • Plugins: Validators
  • Purpose: Guarantee correct output

๐Ÿ“ค Stage 6: OUTPUT

Deliver results to users

  • Handles: Reports, APIs, Dashboards
  • Plugins: Output Formatters
  • Purpose: Present results effectively

Each stage is customizable through plugins:

  • ๐Ÿ”Œ Modular: One plugin = one responsibility
  • ๐Ÿ”„ Composable: Mix and match for any use case
  • โœ… Testable: Unit test plugins independently
  • โš™๏ธ Configurable: YAML changes behavior, not code
  • ๐Ÿ”„ Reusable: Share plugins across projects

๐Ÿš€ Installation Options

Quick Install (Recommended)

pip install entity-core

With Optional Dependencies

# Web tools and advanced features
pip install "entity-core[web,advanced]"

# Development tools
pip install "entity-core[dev]"

# Everything
pip install "entity-core[all]"

Using UV (Fastest)

uv add entity-core

Using Poetry

poetry add entity-core

From Source

git clone https://github.com/Ladvien/entity.git
cd entity
pip install -e .

๐ŸŽ“ Learning Path

๐ŸŒฑ Beginner (10 minutes)

  1. Quick Start - Your first agent in 5 minutes
  2. Basic Examples - Simple, working examples
  3. Core Concepts - Understanding the architecture

๐ŸŒฟ Intermediate (1 hour)

  1. Plugin Development - Build custom capabilities
  2. Configuration Guide - Master YAML workflows
  3. Production Patterns - Real-world applications

๐ŸŒฒ Advanced (1 day)

  1. Multi-Agent Systems - Complex workflows
  2. Performance Optimization - Scale to production
  3. Contributing - Join the community

๐Ÿ’ผ Real-World Use Cases

Customer Support Bot

# config/support_agent.yaml
plugins:
  input: [text, email, chat]
  knowledge: [company_docs, faq_database]
  actions: [ticket_creation, escalation]
  output: [formatted_response, internal_notes]

Code Review Agent

# config/code_reviewer.yaml
plugins:
  input: [github_pr, file_diff, code_snippet]
  analysis: [security_scan, style_check, complexity]
  actions: [inline_comments, suggestions]
  output: [review_summary, action_items]

Research Assistant

# config/researcher.yaml
plugins:
  input: [research_query, document_upload]
  sources: [web_search, academic_papers, internal_docs]
  analysis: [fact_checking, synthesis, citation]
  output: [report_generation, bibliography]

๐Ÿ† Why Teams Choose Entity

๐Ÿš€ Startups: Ship Faster

  • MVP in days: Plugin architecture accelerates development
  • Easy pivoting: Swap plugins without rewriting core logic
  • Cost effective: Local-first reduces API costs

๐Ÿข Enterprises: Scale Safely

  • Standardization: Consistent patterns across all AI projects
  • Compliance ready: Built-in safety, auditing, monitoring
  • Team productivity: Parallel development of isolated plugins

๐ŸŽ“ Education: Learn Better

  • Best practices: Plugin architecture teaches good software design
  • Gradual complexity: Start simple, add features incrementally
  • Real projects: Build agents that solve actual problems

๐Ÿ”— Resources & Community

๐Ÿ“š Documentation

๐Ÿ’ฌ Community

๐Ÿค Contributing

๐Ÿ“Š Performance & Benchmarks

Entity is designed for both developer productivity and runtime performance:

  • ๐Ÿš€ 10x Development Speed: Plugin architecture eliminates boilerplate
  • โšก Low Latency: Optimized plugin execution pipeline
  • ๐Ÿ“ˆ Horizontal Scale: Stateless design supports clustering
  • ๐Ÿ’พ Memory Efficient: Persistent storage with intelligent caching
  • ๐Ÿ” Observable: Built-in metrics, tracing, and debugging

See detailed benchmarks in docs/performance.md.

๐Ÿ›ก๏ธ Security & Privacy

Entity prioritizes security and privacy:

  • ๐Ÿ  Local First: Runs entirely on your infrastructure
  • ๐Ÿ”’ Secure by Default: Input validation, output sanitization
  • ๐Ÿ›ก๏ธ Sandboxed Tools: Isolated execution environments
  • ๐Ÿ“‹ Audit Trails: Comprehensive logging for compliance
  • ๐Ÿ” Secrets Management: Secure configuration and key handling

See our Security Policy for details.

โค๏ธ Acknowledgments

Entity Framework is built with love by the open-source community. Special thanks to:

  • Core Contributors: List of contributors
  • Inspiration: LangChain, AutoGen, CrewAI for pioneering agent frameworks
  • Community: Our amazing GitHub community for feedback and contributions
  • Sponsors: Organizations supporting Entity's development

๐Ÿ“„ License

Entity Framework is released under the MIT License.


Ready to build the future of AI?

๐Ÿ“š Read the Docs โ€ข ๐Ÿš€ Quick Start โ€ข ๐Ÿ™ GitHub

Entity Framework: Build better AI agents, faster. ๐Ÿš€

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