TidierErrors

TidierErrors.jl

Make Julia errors easier to read—and easier to fix.

TidierErrors shortens lengthy stack traces in the REPL and streamlines optional next steps to:

• copy the full error (plus useful context) to your clipboard, or
• send the error directly to an LLM (OpenAI or Ollama) via PromptingTools.jl to get a quick suggestion.

It also ships a quick setup helper for configuring your preferred LLM provider and model.

---

Features

• Cleaner errors in the REPL. Uses AbbreviatedStackTraces to hide internal frames and truncate verbose types. Optionally hide stack traces and/or error messages completely.
• Actionable next steps. After an error you’ll see:
  • show(err) to reveal the complete trace
  • aicopy(err) to copy the error with context to your clipboard
  • ai(err) to send the error with context to an LLM and print the reply
• One-time setup. aisetup() guides you through selecting OpenAI or Ollama and stores your choices with Preferences.jl. Use errordisplaysetup() to change error display settings.
• Take actions automatically on error. Copy error with context or send the whole thing to the LLM automatically.

---

Installation

pkg> using Pkg; Pkg.add(url="https://github.com/TidierOrg/TidierErrors.jl")

julia> using TidierErrors
julia> aisetup()
Which LLM Provider would you like to use?
   OpenAI
 > Ollama
Enter the name of the Ollama model:
gpt-oss:20B

Example

Heres a quick demonstration

julia> using TidierErrors

julia> sum([])
ERROR: MethodError: no method matching zero(::Type{Any})
This error has been manually thrown, explicitly, so the method may exist but be intentionally marked as unimplemented.

Closest candidates are:
  zero(::Type{Union{Missing, T}}) where T
   @ Base missing.jl:105
  zero(::Type{Union{}}, Any...)
   @ Base number.jl:310
  zero(::Type{Missing})
   @ Base missing.jl:104
  ...

Stacktrace:
      ⋮ internal @ Base, Unknown
 [13] sum(a::Vector{Any})
    @ Base ./reducedim.jl:982
Some frames were hidden. Use `show(err)` to see complete trace.

Versus the full stacktrace

julia> sum([])
ERROR: MethodError: no method matching zero(::Type{Any})
This error has been manually thrown, explicitly, so the method may exist but be intentionally marked as unimplemented.

Closest candidates are:
  zero(::Type{Union{Missing, T}}) where T
   @ Base missing.jl:105
  zero(::Type{Union{}}, Any...)
   @ Base number.jl:310
  zero(::Type{Missing})
   @ Base missing.jl:104
  ...

Stacktrace:
  [1] zero(::Type{Any})
    @ Base ./missing.jl:106
  [2] reduce_empty(::typeof(+), ::Type{Any})
    @ Base ./reduce.jl:343
  [3] reduce_empty(::typeof(Base.add_sum), ::Type{Any})
    @ Base ./reduce.jl:350
  [4] mapreduce_empty(::typeof(identity), op::Function, T::Type)
    @ Base ./reduce.jl:369
  [5] reduce_empty(op::Base.MappingRF{typeof(identity), typeof(Base.add_sum)}, ::Type{Any})
    @ Base ./reduce.jl:358
  [6] reduce_empty_iter
    @ ./reduce.jl:381 [inlined]
  [7] mapreduce_empty_iter(f::Function, op::Function, itr::Vector{Any}, ItrEltype::Base.HasEltype)
    @ Base ./reduce.jl:377
  [8] _mapreduce(f::typeof(identity), op::typeof(Base.add_sum), ::IndexLinear, A::Vector{Any})
    @ Base ./reduce.jl:429
  [9] _mapreduce_dim
    @ ./reducedim.jl:337 [inlined]
 [10] mapreduce
    @ ./reducedim.jl:329 [inlined]
 [11] _sum
    @ ./reducedim.jl:987 [inlined]
 [12] _sum
    @ ./reducedim.jl:986 [inlined]
 [13] sum(a::Vector{Any})
    @ Base ./reducedim.jl:982
 [14] top-level scope
    @ REPL[1]:1

Using ai(err) and a local LLM to trouble shoot

julia> ai(err)
[ Info: Tokens: 1983 in 37.6 seconds
  Short fix

  sum([]) is an empty array of type Any. Julia can’t find a default zero(Any) so
  it throws

  MethodError: no method matching zero(::Type{Any})

  Replace that call with one of the following:

  sum(Int[])          # → 0
  sum(Float64[])      # → 0.0
  sum([], init=0)    # ← gives zero of the same type you specify in init

  If you’re summing values that come from a groupby/summarise pipeline, let
  summarise handle the aggregation instead of calling sum([]) directly.

  ────────────────────────────────────────────────────────────────────────────────

  Why it happened

  [] defaults to Vector{Any}, and zero(Any) is intentionally undefined. Providing
  an explicit element type or an init value removes the ambiguity.