crewAIInc/crewAI-examplesArchived
CrewAI Examples
Dieses Projekt bietet Referenzimplementierungen und Vorlagen für Multi-Agenten-Orchestrierung, Retrieval-Augmented-Generation-Systeme und Human-in-the-Loop-Muster. Es enthält eine Sammlung von Implementierungsmustern zur Koordination mehrerer KI-Agenten, um komplexe Geschäftsworkflows und Aufgaben zu automatisieren.
Das Projekt demonstriert, wie man operative Logik von der Einrichtung entkoppelt, indem strukturierte Textdateien für Agentenrollen und Aufgabenspezifikationen verwendet werden. Es enthält Anleitungen zur Integration von Vektorsuche und Dokumentenverarbeitung, um Frage-Antwort-Systeme auf Basis externer Wissensdatenbanken aufzubauen, sowie Muster für das Einfügen manueller Validierungs- und Überprüfungsschritte in automatisierte Agentensequenzen.
Die Beispiele decken das Design iterativer Ausführungspfade, paralleler Verarbeitung und dynamischen Routings ab. Diese Implementierungen integrieren Zustandsmanagement, um den Fortschritt über komplexe Sequenzen hinweg zu verfolgen und Agenten mit externen APIs, Datenbanken und Dateisystemen für eine werkzeuggestützte Ausführung zu verknüpfen.
Die Referenzmaterialien werden als Jupyter Notebooks bereitgestellt.
Features
- Role-Based Agent Orchestration - Coordinates multiple specialized AI agents by assigning distinct roles and goals to automate business workflows.
- Multi-Agent Orchestrators - Provides reference implementations for coordinating specialized AI agents to collaborate on complex business workflows.
- Vector Knowledge Bases - Integrates document processing with vector knowledge bases to provide agents with grounded external information.
- Multi-Agent Orchestration Patterns - Offers implementation patterns for coordinating multiple specialized agents to decompose and execute complex workflows.
- AI Workflow Automation - Automates repetitive professional tasks using iterative execution paths and dynamic AI routing.
- Retrieval-Augmented Generation - Implements the retrieval-to-generation pipeline to ground AI responses using external search indices.
- Human-in-the-Loop Systems - Provides tools for integrating human oversight and validation into AI-driven workflows.
- Human-in-the-Loop Workflows - Implements manual review checkpoints and validation steps within automated agent sequences.
- Tool-Augmented Language Models - Extends language model capabilities by linking agents to external APIs, databases, and file systems.
- RAG Implementations - Implements RAG architectures that retrieve relevant documents from vector stores to augment LLM context.
- Iterative Routing - Provides patterns for designing iterative execution paths and dynamic routing to achieve complex goals.
- Agentic Workflows - Provides frameworks for designing autonomous agent processes using iterative refinement and state management.
- External API Tool Exposures - Demonstrates how to expose external API functions as callable tools for AI agents to execute actions.
- YAML-Defined Agents - Defines custom agents and their toolkits using YAML files to decouple configuration from code.
- External Service Integrations - Provides implementations for connecting AI agents to third-party APIs and external platforms to fetch data.
- Workflow State Managements - Includes state management to track progress and context across iterative loops and parallel processing sequences.
- Agent Task State Persistence - Tracks progress and context across iterative loops to maintain consistency during complex agent sequences.
- Iterative Execution Paths - Implements iterative execution paths with dynamic routing and parallel processing to automate complex tasks.
- RAG Implementation Guides - Provides step-by-step frameworks and examples for building retrieval-augmented generation systems.
- YAML Configuration Files - Uses structured YAML files to separate agent definitions and task specifications from execution logic.
- Agent Configuration Files - Defines agent roles and task specifications in YAML files to decouple operational logic from setup.
- Agent Frameworks - Collection of practical implementation examples for multi-agent systems.
- Agent Framework Examples - Collection of role-based multi-agent workflows for business automation.
