apache/burr

Health v2 · maintenance only

Adoption not part of the score

2528 stars · 188 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Apache Burr is a Python framework for building stateful applications that make decisions, such as chatbots, agents, and simulations, using actions and transitions as simple Python building blocks. It includes a self-hosted UI for real-time monitoring, tracing, and debugging, plus pluggable state persistence and human-in-the-loop support.

Use cases

• build a chatbot with persistent conversation state
• create multi-agent LLM workflows with branching and parallelism
• trace and debug LLM application steps in real time
• add human-in-the-loop approval steps to an agent
• persist and resume long-running AI application state
• build decision-making simulations in Python
• monitor production LLM apps on my own infrastructure

When to choose

• you want a pure-Python, no-DSL way to build stateful LLM agents or chatbots
• you need built-in observability, tracing, and state persistence you can self-host
• you want human-in-the-loop pauses and replay/testing of AI workflows

When to avoid

• you need a fully managed cloud agent platform rather than self-hosted infrastructure
• you want a high-level opinionated agent framework with prebuilt tools rather than composable primitives
• you are not building stateful or decision-driven applications

Facets

framework · maturity active

agent-framework state-management workflow-automation chatbot monitoring tracing rag llm-inference large-language-models chatbots developer-tools artificial-intelligence python cross-platform self-hosted state-machine llmops observability human-in-the-loop dags persistence apache-incubating ai-agents retrieval-augmented-generation

Member repositories

For agents

markdown · JSON · MCP: product_card(name="apache/burr")