--- title: AI SDK for Python product: vercel url: /docs/ai-gateway/sdks-and-apis/ai-sdk-python canonical_url: "https://vercel.com/docs/ai-gateway/sdks-and-apis/ai-sdk-python" last_updated: 2026-07-30 type: integration prerequisites: - /docs/ai-gateway/sdks-and-apis - /docs/ai-gateway related: - /docs/ai-gateway/authentication-and-byok/oidc - /docs/ai-gateway/authentication-and-byok - /docs/ai-gateway/models-and-providers/provider-options - /docs/ai-gateway/sdks-and-apis/ai-sdk summary: Build AI-powered Python applications using the AI SDK for Python with AI Gateway for unified access to 200+ models. install_vercel_plugin: npx plugins add vercel/vercel-plugin --- # AI SDK for Python The [AI SDK for Python](https://ai-python.dev) is a toolkit for building LLM-powered applications and agents in Python. It uses AI Gateway to route requests by default. ## Related pages > **For AI agents:** Follow these links to understand how this page connects to the rest of the Vercel ecosystem. For the full cross-link map (inbound, outbound, prerequisites, and semantic neighbors), see the .graph.md link below. - [How to build AI Agents with Vercel and the AI SDK](https://vercel.com/kb/guide/how-to-build-ai-agents-with-vercel-and-the-ai-sdk?from=related) — Learn how to build, deploy, and scale AI agents on Vercel using the AI SDK. This guide covers calling LLMs, defining too - [Building AI apps on Vercel: an overview](https://vercel.com/kb/guide/how-to-build-ai-app?from=related) — Learn the key AI concepts and tools for building and scaling AI apps. - [Python](https://workflow-sdk.dev/docs/getting-started/python?from=related) — Set up the Workflow Python SDK in your Python application. - [How to build an AI agent for Slack with Chat SDK and AI SDK](https://vercel.com/kb/guide/how-to-build-an-ai-agent-for-slack-with-chat-sdk-and-ai-sdk?from=related) — Build a Slack AI agent using Chat SDK, AI SDK's ToolLoopAgent, and Vercel AI Gateway. Covers project setup, tool definit - [Run Python code securely with AI SDK and Vercel Sandbox](https://vercel.com/kb/guide/python-ai-sdk-vercel-sandbox?from=related) — Add an \\`executeCode\\` tool to your AI SDK agent with the \\`ai-sdk-tool-code-execution\\` package to run Python 3.13 insi - [AI SDK](https://vercel.com/docs/ai-sdk?from=related) — TypeScript toolkit for building AI-powered applications with React, Next.js, Vue, Svelte and Node.js - [Pydantic AI](https://vercel.com/docs/ai-gateway/ecosystem/framework-integrations/pydantic-ai?from=related) — Learn how to integrate Vercel AI Gateway with Pydantic AI to access multiple AI models through a unified interface - [OpenAI](https://vercel.com/docs/agent-resources/integrations-for-models/openai?from=related) — Integrate your Vercel project with OpenAI's powerful suite of models. - [Integrations for Models](https://vercel.com/docs/agent-resources/integrations-for-models?from=related) — Integrate powerful AI services and models seamlessly into your Vercel projects. - [Ecosystem](https://vercel.com/docs/ai-gateway/ecosystem?from=related) — Explore community framework integrations and ecosystem features for the AI Gateway. Full cross-link map for this page: [/docs/ai-gateway/sdks-and-apis/ai-sdk-python.graph.md](/docs/ai-gateway/sdks-and-apis/ai-sdk-python.graph.md) > **💡 Note:** The AI SDK for Python is in public beta. ## Installation The SDK requires Python 3.12 or later. Install the `ai` package: #### uv ```bash filename="Terminal" uv add ai ``` #### pip ```bash filename="Terminal" pip install ai ``` ## Quick start Create a model with a string model ID and pass it to `ai.stream` to get a streaming response. You can omit the provider prefix or use `gateway:` to route through AI Gateway. ```python filename="quickstart.py" import asyncio import ai async def main() -> None: model = ai.get_model('anthropic/claude-sonnet-4.6') messages = [ai.user_message('Explain quantum computing in one paragraph.')] async with ai.stream(model, messages) as stream: async for event in stream: if isinstance(event, ai.events.TextDelta): print(event.chunk, end='', flush=True) asyncio.run(main()) ``` Responses always stream. After iteration, the full response is available on `stream.text`, and token counts on `stream.usage`. ## Structured outputs Pass a [Pydantic](https://pydantic.dev/docs/validation/latest/concepts/models/) model as `output_type` to get validated, structured data. After the stream finishes, `stream.output` returns an instance of your model: ```python filename="structured.py" import asyncio import ai import pydantic class Person(pydantic.BaseModel): name: str age: int city: str async def main() -> None: model = ai.get_model('anthropic/claude-sonnet-4.6') messages = [ ai.user_message('Extract: John is 30 years old and lives in NYC.') ] async with ai.stream(model, messages, output_type=Person) as stream: async for event in stream: pass print(stream.output) # Person(name='John', age=30, city='NYC') asyncio.run(main()) ``` ## Tool calling with agents Define tools as Python functions with the `@ai.tool` decorator. An `ai.Agent` runs a loop: it streams model output and executes requested tools until the model returns a final answer. ```python filename="agent.py" import asyncio import ai @ai.tool async def get_weather(city: str) -> str: """Get the current weather for a city.""" return 'Sunny, 72F' async def main() -> None: model = ai.get_model('anthropic/claude-sonnet-4.6') agent = ai.Agent(tools=[get_weather]) messages = [ai.user_message("What's the weather in Tokyo?")] async with agent.run(model, messages) as stream: async for event in stream: if isinstance(event, ai.events.TextDelta): print(event.chunk, end='', flush=True) history = stream.messages # Full conversation, including tool results asyncio.run(main()) ``` The function signature and docstring become the tool schema. The model sees the tool name, description, and typed parameters. ## Authentication The SDK can use `AI_GATEWAY_API_KEY` environment variable to authenticate: ```bash filename="Terminal" export AI_GATEWAY_API_KEY="your_ai_gateway_api_key" ``` When deploying to Vercel or using `vercel dev` for local development, you are encouraged to use [OIDC](/docs/ai-gateway/authentication-and-byok/oidc) instead of an API key. Install the `vercel` extra and the SDK will handle authentication automatically: ```bash filename="Terminal" uv add "ai[vercel]" ``` See [Authentication](/docs/ai-gateway/authentication-and-byok) for more details. ## Next steps - Explore the full [AI SDK for Python documentation](https://ai-python.dev) for agents, subagents, human-in-the-loop hooks, and custom loops - Browse [examples on GitHub](https://github.com/vercel-labs/ai-python/tree/main/examples), from single-file scripts to end-to-end demos - Learn about [model routing and fallbacks](/docs/ai-gateway/models-and-providers/provider-options) - Building with TypeScript? See the [AI SDK](/docs/ai-gateway/sdks-and-apis/ai-sdk) page --- [View full sitemap](/docs/sitemap)