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- Add `docs/develop/python/integrations/langsmith.mdx` covering the LangSmithPlugin, @Traceable usage, wrap_openai, and the add_temporal_runs toggle. Modeled after the Braintrust guide. - Add LangSmith row to the Python integrations index. - Add the new page to the Python integrations sidebar. Jira: AI-141 Samples PR: temporalio/samples-python#292
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📖 Docs PR preview links
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| Temporal's integration with [LangSmith](https://smith.langchain.com/) gives you end-to-end traces of your AI agent | ||
| Workflows—capturing every LLM call, tool execution, and orchestration step in a single LangSmith project. |
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| Workflows—capturing every LLM call, tool execution, and orchestration step in a single LangSmith project. | |
| Workflows—capturing every LLM call, tool execution, and orchestration step in a LangSmith project. |
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| When building AI agents with Temporal, you get durable execution: automatic retries, state persistence, and recovery | ||
| from failures mid-Workflow. LangSmith adds the observability layer: see exactly what your agents do, inspect LLM | ||
| inputs and outputs, and trace a single request from the Client all the way through to the model. |
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The usage of "single" everywhere feels like it's trying to emphasize the wrong thing.
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| inputs and outputs, and trace a single request from the Client all the way through to the model. | |
| inputs and outputs, and trace a request from the Client all the way through to the model. |
| 1. Install the Temporal Python SDK with the LangSmith extra. | ||
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| ```bash | ||
| pip install "temporalio[langsmith]>=1.26.0" |
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| # wrap_openai patches the client — every API call adds a ChatOpenAI run under the @traceable. | ||
| # max_retries=0 because Temporal's Activity retry policy handles retries. |
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| # max_retries=0 because Temporal's Activity retry policy handles retries. | |
| # Set max_retries=0 and use Temporal's Activity retry policy instead. |
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Summary
/develop/python/integrations/langsmithcovering thetemporalio.contrib.langsmith.LangSmithPlugin(shipped intemporalio1.26.0).@traceableusage,wrap_openaifor richer LLM runs, theadd_temporal_runstoggle, and trace hierarchy examples for both modes.