Apache Burr (Incubating) - Build Reliable AI Agents and Applications
Apache Incubating Project
Build reliable AI agents and applications
Apache Burr (Incubating) makes it easy to develop applications that make decisions, from simple chatbots to complex multi-agent systems. Pure Python, no magic.
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Simple, powerful Python API<br>Build anything from chatbots to multi-agent systems with a clean, composable interface.
chatbot.py<br>Copy<br>ChatbotMulti-AgentState Machine<br>from burr.core import action, State, ApplicationBuilder
@action(reads=["messages"], writes=["messages"])<br>def chat(state: State, llm_client) -> State:<br>response = llm_client.chat(state["messages"])<br>return state.update(<br>messages=[*state["messages"], response]
app = (<br>ApplicationBuilder()<br>.with_actions(chat)<br>.with_transitions(("chat", "chat"))<br>.with_state(messages=[])<br>.with_tracker("local")<br>.build()
app.run(halt_after=["chat"], inputs={"llm_client": client})<br>Python 3.12UTF-8burr >= 0.30
Everything you need to build AI applications<br>Burr provides the building blocks for reliable, observable, and testable AI-powered applications.
Simple Python API<br>Define your application as a set of actions and transitions. No DSL, no YAML — just Python functions and decorators.
Built-in Observability<br>The Burr UI lets you monitor, debug, and trace every step of your application in real time. See state changes as they happen.
Persistence & State Management<br>Automatically persist state to disk, databases, or custom backends. Resume applications from where they left off.
Human-in-the-Loop<br>Pause execution and wait for human input at any step. Perfect for approval workflows and interactive agents.
Branching & Parallelism<br>Run actions in parallel, fan out / fan in, and build complex DAGs. Compose sub-applications for modular design.
Testing & Replay<br>Replay past runs, unit test individual actions, and validate state transitions. Build confidence in your AI systems.
Works with your stack<br>Burr integrates with the tools and frameworks you already use. No lock-in, no wrappers.
OpenAI<br>LLM
Anthropic<br>LLM
LangChain<br>Framework
Hamilton<br>Framework
Streamlit<br>UI
OpenAI<br>LLM
Anthropic<br>LLM
LangChain<br>Framework
Hamilton<br>Framework
Streamlit<br>UI
OpenAI<br>LLM
Anthropic<br>LLM
LangChain<br>Framework
Hamilton<br>Framework
Streamlit<br>UI
OpenAI<br>LLM
Anthropic<br>LLM
LangChain<br>Framework
Hamilton<br>Framework
Streamlit<br>UI
FastAPI<br>Serving
Haystack<br>Framework
Instructor<br>LLM
Pydantic<br>Validation
PostgreSQL<br>Storage
FastAPI<br>Serving
Haystack<br>Framework
Instructor<br>LLM
Pydantic<br>Validation
PostgreSQL<br>Storage
FastAPI<br>Serving
Haystack<br>Framework
Instructor<br>LLM
Pydantic<br>Validation
PostgreSQL<br>Storage
FastAPI<br>Serving
Haystack<br>Framework
Instructor<br>LLM
Pydantic<br>Validation
PostgreSQL<br>Storage
View all integrations
Trusted by engineers worldwide<br>See what developers and teams are saying about Burr.
Peanut Robotics<br>Watto.ai<br>Paxton AI<br>Provectus<br>TaskHuman
“After evaluating several other obfuscating LLM frameworks, their elegant yet comprehensive state management solution proved to be the powerful answer to rolling out robots driven by AI decision making.”<br>Ashish Ghosh<br>CTO, Peanut Robotics
“Using Burr is a no-brainer if you want to build a modular AI application. It is so easy to build with and I especially love their UI which makes debugging a piece of cake. And the always ready to help team is the cherry on top.”<br>Ishita<br>Founder, Watto.ai
“I just came across Burr and I'm like WOW, this seems like you guys predicted this exact need when building this. No weird esoteric concepts just because it's AI.”<br>Matthew Rideout<br>Staff Software Engineer, Paxton AI
“Burr's state management part is really helpful for creating state snapshots and build debugging, replaying and even building evaluation cases around that.”<br>Rinat Gareev<br>Senior Solutions Architect, Provectus
“I have been using Burr over the past few months, and compared to many agentic LLM platforms out there (e.g. LangChain, CrewAi, AutoGen, Agency Swarm, etc), Burr provides a more robust framework for designing complex behaviors.”<br>Hadi Nayebi<br>Co-founder, CognitiveGraphs
“Moving from LangChain to Burr was a game-changer! It took me just a few hours to get started with Burr, compared to the days and weeks I spent trying to navigate LangChain. I pitched Burr to my teammates, and we pivoted our entire codebase to it.”<br>Aditya K.<br>DS Architect, TaskHuman
“Of course, you can use it [LangChain], but whether it's really production-ready and improves the time from code-to-prod, we've been doing LLM apps for two years, and the answer is no. Honestly, take a look at Burr. Thank me later.”<br>Reddit User<br>Developer, r/LocalLlama
“After evaluating several other obfuscating LLM frameworks, their elegant yet comprehensive state management solution proved to be the powerful answer to rolling out robots driven by AI decision making.”<br>Ashish Ghosh<br>CTO, Peanut Robotics
“Using Burr is a...