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When tracing agents, it's common to see prompts that combine a) variable text and b) static text defined in templates that are included in multiple prompts (for example, a system prompt).
It would be nice if Langfuse cuold identify repetitive text patterns (prompt templates) and visualize them in other color, inside a text container that can be labeled, expanded and collapsed.
Example
Let's say we traced this input prompt:
We can now click the text block and assign it a custom label:
When viewing other prompts that contain the same text block, it will be displayed using our custom label:
This feature will make it much more easier to analyze prompts.
Optional
Please also consider that some templates have variables inside.
Eg: "The current date is {{date}} and the current time is {{time}}."
In this case, we would see this:
It would be nice if we could tell Langfuse to treat it as just one block that contains variables.
This way we could add it a custom label and only see:
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Describe the feature or potential improvement
When tracing agents, it's common to see prompts that combine a) variable text and b) static text defined in templates that are included in multiple prompts (for example, a system prompt).
It would be nice if Langfuse cuold identify repetitive text patterns (prompt templates) and visualize them in other color, inside a text container that can be labeled, expanded and collapsed.
Example
Let's say we traced this input prompt:
We can now click the text block and assign it a custom label:
When viewing other prompts that contain the same text block, it will be displayed using our custom label:
This feature will make it much more easier to analyze prompts.
Optional
Please also consider that some templates have variables inside.
Eg:
"The current date is {{date}} and the current time is {{time}}."
In this case, we would see this:
It would be nice if we could tell Langfuse to treat it as just one block that contains variables.
This way we could add it a custom label and only see:
Additional information
No response
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