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Merge pull request langchain-ai#9 from langchain-ai/wfh/doc_nit
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hinthornw authored Aug 16, 2023
2 parents b183741 + af1ad17 commit ecdbf29
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2 changes: 1 addition & 1 deletion docs/evaluation/capturing-feedback.mdx
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Expand Up @@ -72,7 +72,7 @@ In addition to general production observability, user feedback is a key ingredie

Assuming you've already set up tracing in the [LangSmith quick start](/#quick-start), you can add user feedback to a run by returning the run ID and and including that in the `create_feedback` call.

To return the run ID for a given call, look for the `__run` key of the LangChain component's response dictionary (or typescript object). In python, you will have to specify `include_run_id=True` when calling your chain or LLM. Below is an example:
To return the run ID for a given call, look for the `__run` key of the LangChain component's response dictionary (or typescript object). In python, you will have to specify `include_run_info=True` when calling your chain or LLM. Below is an example:

```bash
export LANGCHAIN_TRACING_V2=true
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2 changes: 1 addition & 1 deletion docs/tracing/tracing-faq.mdx
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Expand Up @@ -266,7 +266,7 @@ try {

### How do I get the run ID from a call?

The run ID is returned in the call response under the `__run` key. In python, it is not returned by default. There you will have to pass the `include_run_id=True` parameter to the call function. Example:
The run ID is returned in the call response under the `__run` key. In python, it is not returned by default. There you will have to pass the `include_run_info=True` parameter to the call function. Example:

<CodeTabs
tabs={[
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