Will Anderson
51 lines
1.8 KiB
Rust
51 lines
1.8 KiB
Rust
/// Engram Reasoning Engine — graph-native inference separated from language generation.
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///
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/// # What this crate is
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///
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/// This is NOT an LLM wrapper. It is a reasoning system that traverses the Engram
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/// knowledge graph to reach conclusions through evidence chains.
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///
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/// LLMs: input tokens → transformer → output tokens. Reasoning and generation are
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/// the same process. You cannot separate them.
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///
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/// This engine: hypothesis → graph traversal → evidence chains → confidence-weighted
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/// conclusion. Generation happens separately (a codec converts the conclusion to
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/// language). The reasoning IS the traversal.
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///
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/// # Quick Start
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///
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/// ```rust,no_run
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/// use engram_core::{EngramDb, Node, Edge, NodeType, MemoryTier, RelationType};
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/// use engram_reasoning::{ReasoningEngine, Hypothesis, HypothesisType, ReasoningConfig};
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/// use std::path::Path;
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/// use std::sync::{Arc, Mutex};
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///
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/// let db = Arc::new(Mutex::new(EngramDb::open(Path::new("/tmp/engram-reason-test")).unwrap()));
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/// let config = ReasoningConfig::default();
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/// let mut engine = ReasoningEngine::new(db, config);
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///
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/// let hypothesis = Hypothesis::new(
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/// "Spreading activation improves memory retrieval",
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/// vec![0.9f32, 0.1, 0.3, 0.7],
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/// HypothesisType::IsTrue,
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/// );
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///
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/// let result = engine.reason(&hypothesis).unwrap();
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/// println!("Verdict: {:?}", result.conclusion.verdict);
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/// println!("Confidence: {:.2}", result.confidence);
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/// ```
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pub mod engine;
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pub mod types;
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#[cfg(test)]
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mod tests;
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// Re-export the primary public surface
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pub use engine::ReasoningEngine;
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pub use types::{
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CausalDirection, ChainType, Conclusion, EvidenceChain, EvidenceNode, EvidenceType,
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Hypothesis, HypothesisType, InferenceEdge, InferenceEdgeType, ReasoningConfig,
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ReasoningResult, Verdict,
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};
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