Struct LlmStrategy 

pub struct LlmStrategy { /* private fields */ }

LLM-based retrieval strategy.

Uses an LLM to reason about which nodes are most relevant to the query. Includes ToC context for better navigation decisions.

Example

use vectorless::retrieval::strategy::LlmStrategy;
use vectorless::llm::LlmClient;

let client = LlmClient::with_defaults();
let strategy = LlmStrategy::new(client)
    .with_toc_context(true);

Implementations

impl LlmStrategy

pub fn new(client: LlmClient) -> Self

Create a new LLM strategy.

pub fn with_defaults() -> Self

Create with default LLM client.

pub fn with_system_prompt(self, prompt: String) -> Self

Set custom system prompt.

pub fn with_toc_context(self, include: bool) -> Self

Enable or disable ToC context in prompts.

Trait Implementations

impl Clone for LlmStrategy

fn clone(&self) -> LlmStrategy

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl RetrievalStrategy for LlmStrategy

fn evaluate_node<'life0, 'life1, 'life2, 'async_trait>( &'life0 self, tree: &'life1 DocumentTree, node_id: NodeId, context: &'life2 RetrievalContext, ) -> Pin<Box<dyn Future<Output = NodeEvaluation> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait, 'life2: 'async_trait,

Evaluate a single node’s relevance to the query.

fn evaluate_nodes<'life0, 'life1, 'life2, 'life3, 'async_trait>( &'life0 self, tree: &'life1 DocumentTree, node_ids: &'life2 [NodeId], context: &'life3 RetrievalContext, ) -> Pin<Box<dyn Future<Output = Vec<NodeEvaluation>> + Send + 'async_trait>>

where Self: 'async_trait, 'life0: 'async_trait, 'life1: 'async_trait, 'life2: 'async_trait, 'life3: 'async_trait,

Evaluate multiple nodes in batch.

fn name(&self) -> &'static str

Get the name of this strategy.

fn capabilities(&self) -> StrategyCapabilities

Get the capabilities of this strategy.

fn suitable_for_complexity(&self, complexity: QueryComplexity) -> bool

Check if this strategy is suitable for the given query complexity.

fn estimate_cost(&self, node_count: usize) -> StrategyCost

Estimate the cost of evaluating a set of nodes.