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Getting started

Under 30 seconds

The agents API ships as an extra of conductor-python (see pyproject.toml).

pip install 'conductor-python[agents]'

Or, per framework, install just what you need — e.g. conductor-python[langchain], conductor-python[adk], conductor-python[claude].

Point the SDK at a running Agentspan server (defaults to http://localhost:8080/api):

export AGENTSPAN_SERVER_URL=http://localhost:8080/api
export OPENAI_API_KEY=<YOUR-KEY>
export AGENTSPAN_LLM_MODEL=openai/gpt-4o-mini

Write hello.py:

from conductor.ai.agents import Agent, AgentRuntime

agent = Agent(
    name="greeter",
    model="anthropic/claude-sonnet-4-6",
    instructions="You are a friendly assistant. Keep responses brief.",
)

with AgentRuntime() as runtime:
    result = runtime.run(agent, "Say hello and tell me a fun fact about Python.")
    print(result.output)

Run it:

uv run python hello.py

That is the whole loop: define an Agent, open an AgentRuntime, call run. The runtime compiles the agent to a workflow, starts it, and blocks until it returns an AgentResult. result.print_result() pretty-prints the output if you prefer.

Environment variables

AgentConfig.from_env() reads these (all optional — defaults shown):

Variable Default Purpose
AGENTSPAN_SERVER_URL http://localhost:8080/api Server base URL
AGENTSPAN_API_KEY — API key auth
AGENTSPAN_AUTH_KEY — Key/secret auth — key
AGENTSPAN_AUTH_SECRET — Key/secret auth — secret
AGENTSPAN_LLM_RETRY_COUNT 3 LLM call retries
AGENTSPAN_WORKER_POLL_INTERVAL 100 Worker poll interval (ms)
AGENTSPAN_WORKER_THREADS 1 Worker thread count
AGENTSPAN_AUTO_START_WORKERS true Auto-start local tool workers
AGENTSPAN_AUTO_START_SERVER true Auto-start a local server if none is reachable
AGENTSPAN_DAEMON_WORKERS true Run workers as daemon threads
AGENTSPAN_INTEGRATIONS_AUTO_REGISTER false Auto-register provider integrations
AGENTSPAN_STREAMING_ENABLED true Enable SSE streaming
AGENTSPAN_SECRET_STRICT_MODE false Fail hard on missing secrets
AGENTSPAN_LOG_LEVEL INFO Log level

The model string is "provider/model", e.g. anthropic/claude-sonnet-4-6, anthropic/claude-sonnet-4-20250514, google_gemini/gemini-2.0-flash. Set the matching provider API key in the environment of whoever runs the agent's workers.

What model looks like

Agent(name="a", model="openai/gpt-4o")              # OpenAI
Agent(name="b", model="anthropic/claude-sonnet-4-20250514")
Agent(name="c", model="google_gemini/gemini-2.0-flash")

Next

  • Add tools, sub-agents, and human-in-the-loop: Writing agents.
  • Deploy once and serve workers separately for production: Advanced.