# Durable AI

> For the complete documentation index, see [llms.txt](https://docs.temporal.io/llms.txt).
> Any documentation page is available as raw Markdown by appending `.md` to its URL.

> Build AI applications and agents on Temporal, with links to the AI Cookbook, SDK integrations, and relevant design patterns.

Temporal gives AI applications and agents Durable Execution: a Workflow resumes automatically after a crash, a
network timeout, or a multi-day wait for a human to approve a step. Use it to keep long-running agent loops, LLM tool
calls, and multi-step AI pipelines running reliably, without hand-rolling retry logic, checkpointing, or state
machines.

Looking to use an AI coding assistant to write Temporal code instead? See [Develop with AI](/with-ai).

## AI Cookbook

Runnable, step-by-step recipes for building AI systems and agents with Temporal: tool calling, MCP, structured
output, human-in-the-loop, and more.

- [Hello world](/ai/cookbook/hello-world-openai-responses-python) — Call an LLM from a durable Temporal Workflow in Python using the OpenAI API library.
- [Hello world with LiteLLM](/ai/cookbook/hello-world-litellm-python) — Integrate LiteLLM into a durable Temporal Workflow in Python to call and switch between LLM providers.
- [Durable agent with tools using the AI SDK by Vercel](/ai/cookbook/ai-sdk-by-vercel-typescript) — Build a durable AI agent with the AI SDK by Vercel and Temporal that chooses tools to answer user questions.
- [Structured outputs with Temporal and OpenAI](/ai/cookbook/structured-output-openai-responses-python) — Use Temporal and the OpenAI Responses API to reliably request output conforming to a specific data structure.

[Browse all recipes](/ai/cookbook)

## Agent framework integrations

Temporal integrations for the SDKs and frameworks teams use to build agents. This view is pre-filtered to agent
frameworks — browse [every integration](/integrations) for the full catalog.

- [AI SDK by Vercel](/develop/typescript/integrations/ai-sdk) — Build AI-powered applications with Durable Execution using the Vercel AI SDK. _(TypeScript · Agent framework)_
- [Deep Agents](/develop/python/integrations/deepagents) — Make LangChain Deep Agents durable with Temporal Workflows and Activities. _(Python · Agent framework)_
- [Google ADK](https://adk.dev/integrations/temporal/) — Orchestrate Google ADK agents with durable Temporal Workflows. _(Python · Agent framework)_
- [Google ADK](/develop/go/integrations/google-adk) — Run Google ADK agents with durable execution using the Temporal Go SDK. _(Go · Agent framework)_
- [Google GenAI](/develop/python/integrations/google-genai) — Call Google Gemini models durably from Temporal Workflows with the Google Gen AI SDK. _(Python · Agent framework)_
- [LangGraph](/develop/python/integrations/langgraph) — Run LangGraph agent graphs as durable, resumable Temporal Workflows. _(Python · Agent framework)_
- [Mastra](https://mastra.ai/guides/deployment/temporal) — Build durable AI agents and workflows with the Mastra TypeScript framework. _(TypeScript · Agent framework)_
- [OpenAI Agents SDK](https://github.com/temporalio/sdk-python/blob/main/temporalio/contrib/openai_agents/README.md) — Run OpenAI Agents with Durable Execution using Temporal. _(Python · Agent framework)_
- [OpenAI Agents SDK](/develop/typescript/integrations/openai-agents) — Run OpenAI Agents with Durable Execution using Temporal. _(TypeScript · Agent framework)_
- [Pydantic AI](https://ai.pydantic.dev/durable_execution/temporal/) — Build type-safe AI agents with Durable Execution through Pydantic AI. _(Python · Agent framework)_
- [Spring AI](/develop/java/integrations/spring-ai) — Build AI-powered Java applications with durable Spring AI tool calls. _(Java · Agent framework)_
- [Strands Agents](/develop/python/integrations/strands-agents) — Orchestrate AWS Strands Agents with durable Temporal Workflows. _(Python · Agent framework)_
- [Strands Agents](/develop/typescript/integrations/strands-agents) — Orchestrate AWS Strands Agents with durable Temporal Workflows. _(TypeScript · Agent framework)_

## Featured from the Code Exchange

A hand-picked look at samples built with Temporal and AI. Browse the full
[Code Exchange](https://temporal.io/code-exchange) for more.

- [AI enhanced e-commerce application](https://temporal.io/code-exchange/ai-enhanced-e-commerce-application): A sample e-commerce gift shop with hybrid full-text and vector search plus an AI-powered chat shopping assistant, built with Stripe and Temporal Workflows. _(Dotnet · Hybrid search)_
- [Temporal AI Question Planetarium](https://temporal.io/code-exchange/ai-question-planetarium): Runs a Hugging Face model inside Temporal Activities and Workers, streaming updates to the browser over WebSockets in real time. _(Python · Demo)_
- [Document Processing w/ AI](https://temporal.io/code-exchange/document-processing-w-ai): A mortgage underwriting demo that uses Gemini OCR and policy-grounded AI analysis in deterministic Workflows, with human-in-the-loop review and full traceability. _(Python · Gemini · Mortgage)_
- [Rust Confessional: a durable AI agent demo](https://temporal.io/code-exchange/rust-confessional): A live demo where an AI agent judges audience programming confessions, its progress surviving a Worker crash mid-task. _(Rust · Demo)_

## Use cases

Temporal shows up in four recurring shapes of AI system:

**Agents.** Long-running, stateful agent loops that call LLMs and tools, wait on humans, and pick up exactly where
they left off after a failure. Start with the [AI Cookbook](/ai/cookbook) and the
[Approval](/design-patterns/approval) and [Entity Workflow](/design-patterns/entity-workflow) patterns.

**Processing pipelines.** Multi-step data and document pipelines, such as extraction, embedding, or batch inference,
that need to fan out, retry failed steps in isolation, and resume without reprocessing completed work. See the
[batch processing patterns](/design-patterns#batch-processing-patterns).

**Internal agent platforms.** Teams building a shared runtime for many agents reuse Temporal's Worker and Task Queue
primitives instead of building their own scheduler. See the
[worker configuration patterns](/design-patterns#worker-configuration-patterns) for routing and isolating agent
workloads.

**Model training.** Long-running training and fine-tuning jobs coordinated across GPU resources, with checkpointing
and recovery handled by Temporal's Event History instead of custom orchestration code.

## Design patterns for AI agents

- [Approval](/design-patterns/approval): Human-in-the-loop Workflows that block until external approval decisions are made. Uses Signals to capture approval data with metadata.
- [Saga Pattern](/design-patterns/saga-pattern): Manages distributed transactions with compensating actions. Each step has a compensation that undoes its effects if subsequent steps fail.
- [Long-Running Activity](/design-patterns/long-running-activity): Long-running Activities report progress via heartbeats and enable resumption after failures with cancellation support.
- [Entity Workflow](/design-patterns/entity-workflow): Models long-lived business entities as individual Workflows that persist for the entity's entire lifetime, handling all state transitions through Signals and Updates.
- [Local Activities](/design-patterns/local-activities): Run Activity functions in-process inside the Workflow Task, eliminating all server scheduling round-trips. Best for short, idempotent Activities on a latency-sensitive path.

Browse the full [Design Patterns catalog](/design-patterns) for more, or jump straight into the
[AI Cookbook](/ai/cookbook) for runnable code.