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-rw-r--r--src/rag/mod.rs118
1 files changed, 83 insertions, 35 deletions
diff --git a/src/rag/mod.rs b/src/rag/mod.rs
index 7939d98..16c3d99 100644
--- a/src/rag/mod.rs
+++ b/src/rag/mod.rs
@@ -14,6 +14,7 @@ use anyhow::bail;
use anyhow::{anyhow, Context, Result};
use hnsw_rs::prelude::*;
use indexmap::IndexMap;
+use indexmap::IndexSet;
use inquire::{required, validator::Validation, Select, Text};
use path_absolutize::Absolutize;
use serde::{Deserialize, Serialize};
@@ -22,13 +23,13 @@ use std::{collections::HashMap, fmt::Debug, io::BufReader, path::Path};
use tokio::sync::mpsc;
pub struct Rag {
- client: Box<dyn Client>,
name: String,
path: String,
- model: Model,
+ embedding_model: Model,
hnsw: Hnsw<'static, f32, DistCosine>,
bm25: BM25<VectorID>,
data: RagData,
+ embedding_client: Box<dyn Client>,
}
impl Debug for Rag {
@@ -36,7 +37,7 @@ impl Debug for Rag {
f.debug_struct("Rag")
.field("name", &self.name)
.field("path", &self.path)
- .field("model", &self.model)
+ .field("embedding_model", &self.embedding_model)
.field("data", &self.data)
.finish()
}
@@ -51,8 +52,8 @@ impl Rag {
abort_signal: AbortSignal,
) -> Result<Self> {
debug!("init rag: {name}");
- let (model, chunk_size, chunk_overlap) = Self::config(config)?;
- let data = RagData::new(&model.id(), chunk_size, chunk_overlap);
+ let (embedding_model, chunk_size, chunk_overlap) = Self::config(config)?;
+ let data = RagData::new(embedding_model.id(), chunk_size, chunk_overlap);
let mut rag = Self::create(config, name, save_path, data)?;
let mut paths = doc_paths.to_vec();
if paths.is_empty() {
@@ -88,22 +89,22 @@ impl Rag {
pub fn create(config: &GlobalConfig, name: &str, path: &Path, data: RagData) -> Result<Self> {
let hnsw = data.build_hnsw();
let bm25 = data.build_bm25();
- let model = Model::retrieve_embedding(&config.read(), &data.model)?;
- let client = init_client(config, Some(model.clone()))?;
+ let embedding_model = Model::retrieve_embedding(&config.read(), &data.embedding_model)?;
+ let embedding_client = init_client(config, Some(embedding_model.clone()))?;
let rag = Rag {
- client,
name: name.to_string(),
path: path.display().to_string(),
data,
- model,
+ embedding_model,
hnsw,
bm25,
+ embedding_client,
};
Ok(rag)
}
pub fn config(config: &GlobalConfig) -> Result<(Model, usize, usize)> {
- let (embedding_model, chunk_size, chunk_overlap) = {
+ let (embedding_model_id, chunk_size, chunk_overlap) = {
let config = config.read();
(
config.rag_embedding_model.clone(),
@@ -111,7 +112,7 @@ impl Rag {
config.rag_chunk_overlap,
)
};
- let model_id = match embedding_model {
+ let embedding_model_id = match embedding_model_id {
Some(value) => {
println!("Select embedding model: {value}");
value
@@ -130,7 +131,8 @@ impl Rag {
}
}
};
- let model = Model::retrieve_embedding(&config.read(), &model_id)?;
+ let embedding_model = Model::retrieve_embedding(&config.read(), &embedding_model_id)?;
+
let chunk_size = match chunk_size {
Some(value) => {
println!("Set chunk size: {value}");
@@ -138,9 +140,9 @@ impl Rag {
}
None => {
if *IS_STDOUT_TERMINAL {
- set_chunk_size(&model)?
+ set_chunk_size(&embedding_model)?
} else {
- let value = model.default_chunk_size();
+ let value = embedding_model.default_chunk_size();
println!("Set chunk size: {value}");
value
}
@@ -161,7 +163,8 @@ impl Rag {
}
}
};
- Ok((model, chunk_size, chunk_overlap))
+
+ Ok((embedding_model, chunk_size, chunk_overlap))
}
pub fn save(&self, path: &Path) -> Result<()> {
@@ -176,7 +179,7 @@ impl Rag {
let files: Vec<_> = self.data.files.iter().map(|v| &v.path).collect();
let data = json!({
"path": self.path,
- "model": self.model.id(),
+ "embedding_model": self.embedding_model.id(),
"chunk_size": self.data.chunk_size,
"chunk_overlap": self.data.chunk_overlap,
"files": files,
@@ -198,13 +201,14 @@ impl Rag {
&self,
text: &str,
top_k: usize,
- min_score_vector: f32,
- min_score_text: f32,
+ min_score_vector_search: f32,
+ min_score_fulltext_search: f32,
+ rerank: Option<(Box<dyn Client>, f32)>,
abort_signal: AbortSignal,
) -> Result<String> {
let (stop_spinner_tx, _) = run_spinner("Searching").await;
let ret = tokio::select! {
- ret = self.hybird_search(text, top_k, min_score_vector, min_score_text) => {
+ ret = self.hybird_search(text, top_k, min_score_vector_search, min_score_fulltext_search, rerank) => {
ret
}
_ = watch_abort_signal(abort_signal) => {
@@ -290,6 +294,7 @@ impl Rag {
self.data.add(rag_files, vector_ids, embeddings);
progress(&progress_tx, "Building vector store".into());
self.hnsw = self.data.build_hnsw();
+ self.bm25 = self.data.build_bm25();
Ok(())
}
@@ -298,22 +303,58 @@ impl Rag {
&self,
query: &str,
top_k: usize,
- min_score_vector: f32,
- min_score_text: f32,
+ min_score_vector_search: f32,
+ min_score_fulltext_search: f32,
+ rerank: Option<(Box<dyn Client>, f32)>,
) -> Result<Vec<String>> {
let (vector_search_result, text_search_result) = tokio::join!(
- self.vector_search(query, top_k, min_score_vector),
- self.text_search(query, top_k, min_score_text)
+ self.vector_search(query, top_k, min_score_vector_search),
+ self.fulltext_search(query, top_k, min_score_fulltext_search)
);
let vector_search_ids = vector_search_result?;
- let text_search_ids = text_search_result?;
- let ids = reciprocal_rank_fusion(vector_search_ids, text_search_ids, 1.0, 1.0, top_k);
- let output: Vec<_> = ids
+ let fulltext_search_ids = text_search_result?;
+ debug!("vector_search_ids: {vector_search_ids:?}, fulltext_search_ids: {fulltext_search_ids:?}");
+ let ids = match rerank {
+ Some((client, min_score)) => {
+ let min_score = min_score as f64;
+ let ids: IndexSet<VectorID> = [vector_search_ids, fulltext_search_ids]
+ .concat()
+ .into_iter()
+ .collect();
+ let mut documents = vec![];
+ let mut documents_ids = vec![];
+ for id in ids {
+ if let Some(document) = self.data.get(id) {
+ documents_ids.push(id);
+ documents.push(document.page_content.to_string());
+ }
+ }
+ let data = RerankData::new(query.to_string(), documents, top_k);
+ let list = client.rerank(data).await?;
+ let ids = list
+ .into_iter()
+ .filter_map(|item| {
+ if item.relevance_score < min_score {
+ None
+ } else {
+ documents_ids.get(item.index).cloned()
+ }
+ })
+ .collect();
+ debug!("rerank_ids: {ids:?}");
+ ids
+ }
+ None => {
+ let ids =
+ reciprocal_rank_fusion(vector_search_ids, fulltext_search_ids, 1.0, 1.0, top_k);
+ debug!("rrf_ids: {ids:?}");
+ ids
+ }
+ };
+ let output = ids
.into_iter()
.filter_map(|id| {
- let (file_index, document_index) = split_vector_id(id);
- let file = self.data.files.get(file_index)?;
- let document = file.documents.get(document_index)?;
+ let document = self.data.get(id)?;
Some(document.page_content.clone())
})
.collect();
@@ -352,7 +393,7 @@ impl Rag {
Ok(output)
}
- async fn text_search(
+ async fn fulltext_search(
&self,
query: &str,
top_k: usize,
@@ -369,7 +410,7 @@ impl Rag {
) -> Result<EmbeddingsOutput> {
let EmbeddingsData { texts, query } = data;
let mut output = vec![];
- let chunks = texts.chunks(self.model.max_concurrent_chunks());
+ let chunks = texts.chunks(self.embedding_model.max_concurrent_chunks());
let chunks_len = chunks.len();
progress(
&progress_tx,
@@ -381,7 +422,7 @@ impl Rag {
query,
};
let chunk_output = self
- .client
+ .embedding_client
.embeddings(chunk_data)
.await
.context("Failed to create embedding")?;
@@ -397,7 +438,7 @@ impl Rag {
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct RagData {
- pub model: String,
+ pub embedding_model: String,
pub chunk_size: usize,
pub chunk_overlap: usize,
pub files: Vec<RagFile>,
@@ -405,9 +446,9 @@ pub struct RagData {
}
impl RagData {
- pub fn new(model: &str, chunk_size: usize, chunk_overlap: usize) -> Self {
+ pub fn new(embedding_model: String, chunk_size: usize, chunk_overlap: usize) -> Self {
Self {
- model: model.to_string(),
+ embedding_model,
chunk_size,
chunk_overlap,
files: Default::default(),
@@ -415,6 +456,13 @@ impl RagData {
}
}
+ pub fn get(&self, id: VectorID) -> Option<&RagDocument> {
+ let (file_index, document_index) = split_vector_id(id);
+ let file = self.files.get(file_index)?;
+ let document = file.documents.get(document_index)?;
+ Some(document)
+ }
+
pub fn add(
&mut self,
files: Vec<RagFile>,
generated by cgit v1.2.3 (git 2.39.1) at 2026-10-03 01:20:27 +0000