use async_trait::async_trait;
use std::sync::Arc;
use crate::error::RagError;
use crate::pipeline::channel::{ChannelConfig, ChannelType};
use crate::types::chunk::ChunkMetadata;
use crate::types::retrieval::{RetrievedChunk, StructuredFilter};
#[async_trait]
pub trait MetadataStore: Send + Sync {
async fn search_by_metadata(
&self,
query: &str,
filters: &[StructuredFilter],
top_k: usize,
namespace: Option<&str>,
) -> Result<Vec<(String, f32, ChunkMetadata, String, String)>, RagError>;
}
pub struct MetadataChannelExecutor {
store: Arc<dyn MetadataStore>,
}
impl MetadataChannelExecutor {
pub fn new(store: Arc<dyn MetadataStore>) -> Self {
Self { store }
}
pub async fn execute(
&self,
query: &str,
config: &ChannelConfig,
global_filters: &[StructuredFilter],
namespace: Option<&str>,
) -> Result<Vec<RetrievedChunk>, RagError> {
let results = self
.store
.search_by_metadata(query, global_filters, config.top_k, namespace)
.await
.map_err(|e| RagError::Store(e.to_string()))?;
let hits: Vec<RetrievedChunk> =
results
.into_iter()
.filter(|(_, score, _, _, _)| {
if let Some(min_score) = config.min_score { *score >= min_score } else { true }
})
.map(|(id, score, metadata, content, document_id)| RetrievedChunk {
chunk_id: id,
document_id,
content,
score,
channel: ChannelType::Metadata.as_str().to_string(),
channel_score: score,
metadata,
embedding: None,
})
.collect();
Ok(hits)
}
}