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Admin ff604e53a3 splash: string-compare early-out in deep_eq, thread stack prealloc, bench additions 
- deep_eq returns false immediately when both sides are string-like and
  the bit-compare failed (strings are interned, so bit-equality IS string
  equality) — trims the type-check chain on the hot failed-compare path
  of string-tag dispatch (a.kind == "...")
- pre-reserve thread stacks (value stack, scopes, calls, mes, loops)
- splash_bench: string_cmp workload, arith_hostmode (instruction limit +
  run budget installed, the game-host configuration; measured: the two
  per-instruction counters cost ~nothing, branch prediction hides them),
  BENCH_ONLY profiler filter

Tried and rejected: batching consecutive value-pushes in run_core into
one dispatch iteration — the scan overhead outweighed the per-value
limit/budget checks it skipped (they were already free); reverted.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
2026-08-11 15:59:05 +02:00
..
src splash: string-compare early-out in deep_eq, thread stack prealloc, bench additions 2026-08-11 15:59:05 +02:00
Cargo.toml First 2.0 2026-02-12 14:52:33 +01:00
README.md First 2.0 2026-02-12 14:52:33 +01:00

README.md

Makepad Example: ChatGPT

A simple example of a Makepad Framework application that uses its network layer to interact with OpenAI's GPT model.

How to Run

  1. Set up your OpenAI API key:

    • Visit OpenAI's API Key page and follow the instructions to create and retrieve your API key.
    • Note: Using the OpenAI API incurs costs.

  2. Configure the API key as an environment variable:

    export OPENAI_API_KEY=your_openai_api_key

    Optionally, you can configure the model and endpoint:

    export OPENAI_MODEL=your_desired_model  # default is "gpt-4o"
export OPENAI_BASE_URL=your_custom_api_base_url  # default is "https://api.openai.com/v1"

  3. Run the application:

    cargo run