msjidandClaude Sonnet 5
771280cde6
RAG + multi-agent (retrieval, policy-compliance, drafting) support assistant for a fictional shipping company, built in Rust with Qdrant for vector storage and a hand-rolled Anthropic tool-calling client (no Rust pydantic-ai equivalent exists). A deterministic supervisor orchestrates the agents and runs every response through a rule-based guardrail pipeline with an append-only audit log. Includes a 44-example golden dataset (normal/injection/policy- violation/hallucination-bait/out-of-scope) and a regression harness that scores retrieval, generation, and guardrail correctness separately, plus a write-up of the failure modes and trade-offs. Co-Authored-By: Claude Sonnet 5 <[email protected]>
29 lines
755 B
TOML
29 lines
755 B
TOML
[package]
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name = "maritime_assistant"
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version = "0.1.0"
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edition = "2024"
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[lib]
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name = "maritime_assistant"
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path = "src/lib.rs"
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[[bin]]
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name = "maritime-assistant"
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path = "src/main.rs"
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[dependencies]
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anyhow = "1.0.104"
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async-trait = "0.1.92"
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chrono = { version = "0.4.45", features = ["serde"] }
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clap = { version = "4.6.7", features = ["derive"] }
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dotenvy = "0.15.7"
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fastembed = "7.0.1"
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qdrant-client = "1.19.0"
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regex = "1.13.1"
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reqwest = { version = "0.13.5", default-features = false, features = ["json", "rustls"] }
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schemars = "1.2.2"
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serde = { version = "1.0.229", features = ["derive"] }
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serde_json = "1.0.151"
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tokio = { version = "1.53.1", features = ["rt-multi-thread", "macros", "fs"] }
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uuid = { version = "1.26.1", features = ["v4", "serde"] }
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