Python SDK for Conductor

The Python SDK for Conductor lets you build durable Conductor agents, workflows, and workers. Conductor coordinates retries, state, and observability while your Python code runs wherever you deploy it.

Get involved: ⭐ Conductor OSS · Choose a Conductor OSS contribution · Contribution guide

Using an AI coding agent? Load Conductor Skills so it can create, run, and operate Conductor workflows and Conductor agents:

npm install -g @conductor-oss/conductor-skills && conductor-skills --all

Choose your path

I want to…	Start here
Build a durable Conductor agent with tools and human approval	Run an AI agent example
Bring an existing Google ADK, LangChain, LangGraph, OpenAI Agents, or Claude Agent SDK agent	Use framework bridges
Build a durable workflow and Python worker	Run the core hello-world example
Browse all examples	AI agent guide · Core examples
Navigate the SDK documentation	Documentation hub

Choose your Conductor server

Connect to a server before following either quickstart. Use the hosted Developer Edition by default, or run Conductor locally when you need a self-managed development environment.

Recommended: Orkes Developer Edition

Orkes Developer Edition is the default hosted option. Create an application and access key in the Developer Edition UI, then configure this SDK with its API endpoint. Keep the key and secret out of source control.

export CONDUCTOR_SERVER_URL=https://developer.orkescloud.com/api
export CONDUCTOR_AUTH_KEY=<your-key-id>
export CONDUCTOR_AUTH_SECRET=<your-key-secret>

For another hosted or self-managed remote cluster, use that cluster's /api URL and its application credentials instead. See server setup for details.

Local alternative: Conductor CLI

The CLI is the preferred local-server path. Install the CLI, start the server, then point the SDK at its API endpoint.

npm install -g @conductor-oss/conductor-cli
conductor server start
conductor server status
export CONDUCTOR_SERVER_URL=http://localhost:8080/api

Docker fallback

Use Docker when you need a containerized local server instead of the CLI:

docker run --rm -p 8080:8080 -p 1234:5000 conductoross/conductor:latest
export CONDUCTOR_SERVER_URL=http://localhost:8080/api

The Docker server UI is available at http://localhost:1234. See server setup for full local, remote, and authentication guidance.

Why Conductor?

• Survive process failures: execution state is durable, so Conductor agents and workflows resume from completed work.
• Build dynamic agent graphs: define workflow graphs in Python or let an LLM plan them at runtime. Conductor executes plans as durable sub-workflows rather than transient in-process loops.
• Run tools as distributed tasks: scale Python workers independently while Conductor manages retries and delivery.
• Orchestrate long-running work: combine AI, schedules, events, and human approval without holding application threads open.
• See every execution: inspect inputs, outputs, tool calls, retries, and status through one execution model.

See the maintained planner-context example for a durable plan-and-execute graph, or start with the agent examples.

Requirements and compatibility

• Python 3.10+
• A running OSS or Orkes Conductor server selected in Choose your Conductor server
• Docker when using the Docker local-server option
• Node.js/npm only when using the optional Conductor CLI

The CI workflows are the source of truth for the server versions exercised by this SDK. See the agent E2E matrix for its pinned server version.

Install the SDK

python3 -m venv conductor-env
source conductor-env/bin/activate  # Windows: conductor-env\Scripts\activate
pip install conductor-python

AI agents

Install the complete Conductor agent surface, including supported framework bridges:

pip install 'conductor-python[agents]'

Workflows and workers

The base package includes the workflow, task, worker, metadata, scheduler, and metrics clients:

pip install conductor-python

Modules

Package or extra	Use it for
conductor-python	Workflow, task, worker, metadata, scheduler, and metrics clients
conductor-python[agents]	Durable Conductor agents, tools, guardrails, handoffs, and all supported framework bridges
conductor-python[adk]	Google ADK bridge
conductor-python[langchain]	LangChain bridge
conductor-python[langgraph]	LangGraph bridge
conductor-python[openai-agents]	OpenAI Agents bridge
conductor-python[claude]	Claude Agent SDK bridge

AI agent quickstart

Use this path when your Conductor agent needs LLM reasoning, tools, guardrails, handoffs, or human approval. Select a server above first. For a local server, configure the LLM provider credential in the server environment before starting it. For Developer Edition, configure the provider integration in the hosted cluster. The agent getting-started guide covers both paths.

export CONDUCTOR_AGENT_LLM_MODEL=openai/gpt-4o-mini
cd examples/agents
python 01_basic_agent.py

Expected outcome: the example prints an AgentResult containing the model response. Continue with the AI agent guide, tools guide, and agent examples.

Framework bridges

Keep using the Python agent framework your team already knows. The SDK bridges native Google ADK, LangChain, LangGraph, OpenAI Agents, and Claude Agent SDK agents into durable Conductor agents.

Workflow and worker quickstart

With a server selected above, this maintained example registers a workflow, starts a Python worker, executes the workflow, and prints its result.

cd examples/helloworld
python helloworld.py

Expected outcome: the workflow finishes with COMPLETED and prints its greeting output. For worker patterns, workflow definitions, and testing, continue with the core examples catalog, worker guide, and workflow guide.

Common tasks

Need	Start with
Build Python Conductor agents	Agent concepts
Add tools and human approval	Agent tools
Use another agent framework	Google ADK · LangChain · LangGraph · OpenAI Agents
Deploy, serve, and run Conductor agents	Agent runtime modes
Implement and scale Python workers	Workers guide · reliability
Define and evolve workflows	Workflows guide · lifecycle/versioning
Upload/download workflow-scoped files	Python compatibility
Test workflows and workers	Workflow testing
Expose worker metrics	Observability
Host Python workers in an application	FastAPI worker example · deployment/scaling
Manage schedules and events	Schedules/events guide
Find typed clients and API references	Core API map

Troubleshooting

Symptom	Check
Connection refused	The server is healthy at http://localhost:8080/health; CONDUCTOR_SERVER_URL ends in /api.
Task remains SCHEDULED	A worker is polling the exact task type and has enough worker capacity.
Authentication failure	CONDUCTOR_AUTH_KEY and CONDUCTOR_AUTH_SECRET are set for the target server.
Conductor agent cannot call a model	The server—not only the Python process—has a configured LLM provider and model.

Support and project policies

Contribute upstream: Choose a Conductor OSS contribution · Read the Conductor OSS contribution guide

• SDK issues for Python SDK bugs and feature requests
• Conductor server issues for OSS server behavior
• Conductor Code of Conduct for community expectations and conduct reporting
• Conductor security policy for private vulnerability reporting
• Conductor Slack and the Orkes Community Forum for questions

License

Apache 2.0. See LICENSE.