# Standalone example (own workspace) — does NOT join joule-code-rs's workspace, so
# the standard's lib stays free of a JouleClaw dependency. This is a *consumer
# binding*: how to wire JouleClaw's L3 (Model) tier into the Joule Code cascade.
[workspace]

[package]
name = "l3-jouleclaw-binding"
version = "0.1.0"
edition = "2021"
rust-version = "1.97"
license = "Apache-2.0"
description = "Example binding: JouleClaw's L3 model tier (jouleclaw-llm LlmBackend) as a Joule Code cascade FnStage. Verified model-free via EchoBackend; a real backend (vLLM, or jouleclaw-runtime GGUF) drops into the same slot."
publish = false

[dependencies]
joule-code-schema = { path = "../../joule-code-rs/crates/joule-code-schema" }
joule-code-cargo = { path = "../../joule-code-rs/crates/joule-code-cargo" }
joule-code-receipt = { path = "../../joule-code-rs/crates/joule-code-receipt" }
joule-code-cascade = { path = "../../joule-code-rs/crates/joule-code-cascade" }
jouleclaw-llm = { path = "../../../jouleclaw/jouleclaw-rs/crates/jouleclaw-llm" }
jouleclaw-energy = { path = "../../../jouleclaw/jouleclaw-rs/crates/jouleclaw-energy", features = ["ioreport"] }
# JouleClaw's own from-scratch GGUF tensor runtime (no llama.cpp, no FFI) —
# the in-process L3 backend.
jouleclaw-runtime = { path = "../../../jouleclaw/jouleclaw-rs/crates/jouleclaw-runtime" }
jouleclaw-loader-gguf = { path = "../../../jouleclaw/jouleclaw-rs/crates/jouleclaw-loader-gguf", features = ["rayon", "fabric"] }
# The grades (`Measured` / `Benchmarked` / `Estimated`) the fabric ledger prices
# a call from, which the L3 stage grades the call's projected energy by.
jouleclaw-fabric = { path = "../../../jouleclaw/jouleclaw-rs/crates/jouleclaw-fabric" }
# The GPU load the in-process meter's GPU-counter liveness probe runs
# (`gpu_liveness_load`): the `run` binary meters the in-process engine on this
# process's own CPU and GPU (`jouleclaw_energy::span::ProcessSpanMeter`).
jouleclaw-backend-apple = { path = "../../../jouleclaw/jouleclaw-rs/crates/jouleclaw-backend-apple" }
# The llama engine's subprocess, read on its own process tree where the host
# counts each process's CPU energy (macOS): `TreeMeter`.
sandbox-meter = { path = "../../../sandbox/sandbox-rs/crates/sandbox-meter" }
serde_json = "1"

# macOS: the llama engine's process is waited for without being reaped
# (`waitid` with `WNOWAIT`), so the tree meter reads its exited count.
[target.'cfg(target_os = "macos")'.dependencies]
libc = "0.2"