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LlmReply carried a bare `microjoules`, and charge_llm_step tagged every model step Estimated. A backend that ran a model in this process and read it on a live counter (an eoc-local backend's MeterSpan, now backed by the per-process counter) had no way to say so. Its measured figure was recorded as an estimate. - LlmReply carries a JouleCost. LlmReply::new is the provider's estimate, as before, and LlmReply::with_cost gives a figure with its grade. - charge_llm_step records the provider's cost as graded and charges the budget that figure. - NeuralProvider wraps any in-process NeuralBackend as an LlmProvider. The reply's energy is the backend's own JouleCost. Tokens are counted from the text (approx_tokens, or the model's tokenizer through with_token_counter) and feed only the token budget. A model served over the network still reports an estimate: it ran on hardware no counter here reads. Tests: an MlcBackend metered by an advancing counter gives a measured span, and a held, failed or stub counter gives the estimate. A whole ReAct run records the model step measured. Reverting charge_llm_step to always-estimated fails both end-to-end tests. Co-Authored-By: Claude Opus 5.5 <[email protected]>
24 lines
742 B
TOML
24 lines
742 B
TOML
[package]
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name = "eoc-agent"
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version.workspace = true
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edition.workspace = true
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rust-version.workspace = true
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license.workspace = true
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repository.workspace = true
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authors.workspace = true
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description = "EOC — agentic loops (ReAct, Reflexion, ToT, LATS, Plan-and-Execute, CodeAct) with per-step token + joule budgets."
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[dependencies]
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eoc-core.workspace = true
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eoc-meter.workspace = true
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eoc-neural.workspace = true
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serde = { workspace = true }
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serde_json = "1"
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thiserror.workspace = true
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async-trait.workspace = true
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tokio = { workspace = true, features = ["macros", "rt", "sync", "time"] }
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[dev-dependencies]
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eoc-local = { path = "../eoc-local", features = ["mlc"] }
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tokio = { workspace = true, features = ["macros", "rt-multi-thread"] }
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