Dynamiq is an open-source Python framework for orchestrating agentic AI and LLM applications, specializing in Retrieval-Augmented Generation (RAG) and complex agent workflows. It targets developers building sophisticated AI applications, offering a structured approach to managing LLM interactions, tool usage, and multi-agent coordination.

How It Works

Dynamiq employs a node-based architecture where each component (LLM, tool, data processor) is a distinct node. These nodes can be chained together using Workflow or Flow objects to define sequential or parallel execution paths. The framework supports various agent types like ReAct and Reflection agents, integrates with external tools (e.g., E2B Code Interpreter, ScaleSerp), and includes memory management for conversational AI. Its graph orchestrator allows for dynamic, state-driven agent execution based on feedback loops.

Quick Start & Requirements

• Install via pip: pip install dynamiq
• Requires Python.
• API keys for services like OpenAI and E2B are necessary for most examples.
• Documentation: https://dynamiq.ai/

Highlighted Details

• Supports complex agent orchestration with adaptive and graph-based managers.
• Includes built-in RAG pipelines for document indexing and retrieval.
• Offers a memory module for stateful chatbots.
• Provides examples for sequential, parallel, and conditional agent workflows.

Maintenance & Community

The project is actively maintained by the dynamiq-ai team. Community engagement channels are not explicitly listed in the README.

Licensing & Compatibility

Dynamiq is released under the Apache 2 License, which permits commercial use and integration with closed-source applications.

Limitations & Caveats

The README assumes familiarity with LLM concepts and requires external API keys for many core functionalities, which may incur costs. Some examples reference specific versions or configurations of external services (e.g., Pinecone index dimensions).