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docs: remove @meta blocks from solve manuals
- Remove Draft=false and CollapsedDocStrings=false meta blocks - Documentation generation works without these blocks - Cleaner markdown files for manual editing
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docs/src/api/private.md

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docs/src/manual-solve-advanced.md

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# [Solve: advanced options](@id manual-solve-advanced)
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This manual covers advanced option management for the [`solve`](@ref) function: how option routing works, how to disambiguate shared options with `route_to`, how to pass unknown options with `bypass`, and how to use introspection tools.
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For basic usage, see [Solve a problem](@ref manual-solve).

docs/src/manual-solve-explicit.md

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# [Solve: explicit mode](@id manual-solve-explicit)
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This manual explains the **explicit mode** of the [`solve`](@ref) function, where you pass typed strategy instances directly instead of symbolic tokens. This gives you full control over component configuration and validation.
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For basic usage with symbolic tokens, see [Solve a problem](@ref manual-solve).

docs/src/manual-solve-gpu.md

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# [Solve on GPU](@id manual-solve-gpu)
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This manual explains how to solve optimal control problems on GPU using the [`solve`](@ref) function. GPU acceleration is available through [ExaModels.jl](https://exanauts.github.io/ExaModels.jl/stable) and [MadNLPGPU.jl](https://github.com/MadNLP/MadNLP.jl), with current support for NVIDIA GPUs via [CUDA.jl](https://github.com/JuliaGPU/CUDA.jl).
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For basic CPU solving, see [Solve a problem](@ref manual-solve).

docs/src/manual-solve.md

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# [Solve a problem](@id manual-solve)
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This manual explains how to use the [`solve`](@ref) function to solve optimal control problems with OptimalControl.jl. The `solve` function provides a **descriptive mode** where you specify strategies using symbolic tokens, with automatic option routing and validation.
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For advanced usage, see:

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