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Gemini and Temporal Durable Agent
Google AI documentation shows how to build a durable AI agent by combining Gemini with Temporal.
About Gemini and Temporal Durable Agent
This Google AI developer tutorial explains how to build a durable AI agent that uses the Gemini API for reasoning and Temporal for durability, through Temporal's built-in Gemini SDK integration. The example agent calls tools such as weather alert lookups or IP address geolocation and loops until it has enough information to respond.
The distinguishing element is durability: every LLM call and tool invocation is persisted by Temporal, so if the process crashes, the network drops or an API times out, work retries and resumes from the last completed step. The walkthrough covers a single-file Python worker, with workflows, activities and the worker described separately as a real-world practice. Prerequisites include Python 3.10 or later, uv, the Temporal CLI and a Gemini API key; the tutorial notes that the integration is experimental and its API may change.
Key features
- Durable agent combining Gemini API reasoning with Temporal persistence
- Persists every LLM call and tool invocation, resuming after crashes or timeouts
- Uses Temporal's built-in Gemini SDK integration (temporalio.contrib.google_genai)
- Example tools include weather alerts and IP address geolocation
- Gemini API key kept in worker process, not workflow code
- Runs against a local Temporal development server via Temporal CLI
Best for: Developers building Python AI agents that must survive process crashes, network drops and API timeouts without losing progress.
Good for
- Resumes from the last completed step, so conversation history is not lost and tool calls are not repeated
- The Gemini API key lives only in the worker process, so no auth material appears in Temporal's event history
- A free Gemini API key can be created in Google AI Studio
Watch out for
- Requires Python 3.10 or later, uv, the Temporal CLI and a running local Temporal development server
- The temporalio.contrib.google_genai integration is experimental and its API may change in future SDK versions
- The example places workflow, activities and worker in one file; separating them is left to real-world implementations
Gemini and Temporal Durable Agent at a glance
- Category
- AI & Machine Learning › AI Agents & Automation
- Type
- Online tool
- Pricing
- Not confirmed. Check the site
- Platforms
- Web
- Open source
- Not stated
- Language
- English
- Good for
- Developers
- Last checked
- Oct 5, 2026 · Online when checked
- Listed
- Oct 5, 2026
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Gemini and Temporal Durable Agent FAQ
What makes this agent durable?
Temporal persists every LLM call and tool invocation. If the process crashes, the network drops or an API times out, Temporal automatically retries and resumes from the last completed step.
What is needed to follow the tutorial?
A Gemini API key from Google AI Studio, Python 3.10 or later, uv for dependency management, and the Temporal CLI for running a local development server and starting workflows.
Is the Gemini SDK integration stable?
No. The temporalio.contrib.google_genai integration is described as experimental and its API may change in future versions of the Temporal Python SDK.
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