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DOCS: Fix typo/line break in python code (#13708)

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19
templates/chat-bot-feedback/README.md
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@ -26,16 +26,15 @@ As shown, the evaluator sees that the user is increasingly frustrated, indicatin
The user feedback is inferred by custom `RunEvaluator`. This evaluator is called using the `EvaluatorCallbackHandler`, which run it in a separate thread to avoid interfering with the chat bot's runtime. You can use this custom evaluator on any compatible chat bot by calling the following function on your LangChain object:
```python
my_chain
.with_config(
callbacks=[
EvaluatorCallbackHandler(
evaluators=[
ResponseEffectivenessEvaluator(evaluate_response_effectiveness)
]
)
],
)
my_chain.with_config(
callbacks=[
EvaluatorCallbackHandler(
evaluators=[
ResponseEffectivenessEvaluator(evaluate_response_effectiveness)
]
)
],
)
```
The evaluator instructs an LLM, specifically `gpt-3.5-turbo`, to evaluate the AI's most recent chat message based on the user's followup response. It generates a score and accompanying reasoning that is converted to feedback in LangSmith, applied to the value provided as the `last_run_id`.