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@tanushree-sharma tanushree-sharma commented Sep 26, 2025

Goals

  • be explicit about the message formats we render well
  • show how to use process_inputs and process_outputs to convert messages before they are logged

To-do:

  • Figure out formatting for reasoning, citations, streaming, list of available tools for the model to call

Preview deployment: https://langchain-5e9cc07a-preview-llmcal-1759474889-0b7785c.mintlify.app/langsmith/log-llm-trace

@github-actions github-actions bot added the langsmith For docs changes to LangSmith label Sep 26, 2025
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Preview ID generated: preview-llmcal-1758848807-b95b6b2

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Preview ID generated: preview-llmcal-1759194510-092ba06

@tanushree-sharma tanushree-sharma changed the title clarifications to llm call formats langsmith: clarifications to messages format Sep 30, 2025
@tanushree-sharma tanushree-sharma marked this pull request as ready for review September 30, 2025 01:14
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Preview ID generated: preview-llmcal-1759195340-f7db8a9

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Preview ID generated: preview-llmcal-1759195522-41a72bb

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@hwchase17 hwchase17 left a comment

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i think table of contents can be better (too much under "Tracing a Model with a Custom Input/Output Format") . input/output format should be at a higher level. there should probably be more explicit setions for tool calls and content blocks. O

class LangSmithOutputs(BaseModel):
"""The output format LangSmith expects."""

def process_inputs(inputs: dict) -> dict:
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Maybe add a real example?

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github-actions bot commented Oct 3, 2025

Preview ID generated: preview-llmcal-1759474889-0b7785c

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@katmayb katmayb left a comment

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LGTM, couple of edits to consider.

]
chat_model_choices(inputs)
```
<Expandable title="the code">
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I think you could leave in a regular, open code block — but your call.

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4 participants