developing-genkit-python

Genkit Python

Build AI features in Python — generate, stream, tools, flows, and multi-turn agents — with one SDK.

Prerequisites

• Python 3.10+ and uv (install)
• Genkit CLI: npm install -g genkit-cli if genkit --version is missing

New app? Setup. Patterns? Examples.

Hello World

from genkit import Genkit
from genkit_google_genai import GoogleAI

ai = Genkit(
    plugins=[GoogleAI()],
    model='googleai/gemini-flash-latest',
)

async def main():
    response = await ai.generate(prompt='Tell me a joke about Python.')
    print(response.text)

if __name__ == '__main__':
    ai.run_main(main())

Agents (Beta)

Multi-turn chats with history, typed state, human approval, branching, and background work. Start here: Agents.

chat = agent.chat()
res = await chat.send('Hello')           # AgentResponse
turn = chat.send_stream('Hello')         # AgentTurn — .stream / .response

More: sessions · HITL · branching · background · state · artifacts · custom · HTTP

Imports

• Google AI: from genkit_google_genai import GoogleAI
• Agents: from genkit.agent import InMemorySessionStore, ...
• Middleware: from genkit_middleware import Middleware, ToolApproval, ...
• FastAPI: from genkit_fastapi import serve_agent, serve_flow
• Evals: from genkit_evaluators import register_genkit_evaluators

Workflow

1. Agent or flow? If the task is conversational, multi-turn, or described as "an agent", "assistant", or "chatbot", build it with ai.define_agent (see Agents) rather than hand-rolling a generate + tools loop inside a flow. Reach for a plain flow only for single-shot, stateless generation.
2. Set GEMINI_API_KEY. Use prefixed model ids (googleai/gemini-flash-latest).
3. Enter via ai.run_main(main()) for Genkit apps (especially under genkit start). See Common Errors.
4. Run with Dev Workflow (genkit start + Dev UI).
5. Verify with traces, not a blind run. Running the app directly (uv run) does not capture dev traces. See Genkit CLI for how to run your app and capture traces.
6. Stuck? Common Errors first.