Write Less, Build More
From Zero to AI Agent in 3 Lines
⚡
Simple API
from openstackai import ask, summarize, research
# One-liner AI calls
answer = ask("What is machine learning?")
summary = summarize("Long document text...")
report = research("Latest AI trends 2026")
🤖
Agent API
from openstackai import Agent, Runner
# Create an AI agent
agent = Agent(
name="Assistant",
instructions="You are a helpful AI assistant."
)
# Run synchronously
result = Runner.run_sync(agent, "Hello!")
print(result.final_output)
👥
Multi-Agent
from openstackai import Agent, Runner
from openstackai.blueprint import ChainWorkflow
# Multi-agent workflow
researcher = Agent(name="Researcher", instructions="Research topics")
writer = Agent(name="Writer", instructions="Write articles")
workflow = ChainWorkflow([researcher, writer])
result = Runner.run_sync(workflow, "AI in healthcare")
What It Does
Everything You Need to Build AI Agents
🎯
Simple by Design
One-liner APIs like ask(), summarize(), research(). No boilerplate, just results.
🔌
Multi-Provider
OpenAI, Azure OpenAI, Anthropic, Ollama, Gemini - switch with one line.
👥
Multi-Agent
Chain, supervisor, and custom orchestration patterns out of the box.
🏢
Enterprise Ready
Azure AD auth, sessions, guardrails, tracing, and evaluation built-in.
🧩
Extensible
Custom skills, OpenAPI tools, A2A protocol, and plugin architecture.
📊
RAG & Vector DBs
ChromaDB, Pinecone, Qdrant, Weaviate - connect your knowledge base.
Works With Everything
Any Provider. Your Choice.
🤖OpenAI
☁️Azure
🧠Anthropic
🦙Ollama
🔮ChromaDB
🌲Pinecone
🎯Qdrant
🕸️Weaviate
Ready to Build AI Agents?
Join developers building the next generation of AI applications.