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feat: support for other providers of ai models

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Per Stark
2025-06-06 23:16:41 +02:00
parent 811aaec554
commit a363c6cc05
22 changed files with 519 additions and 66 deletions
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8
composite-retrieval/src/vector.rs
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@@ -1,6 +1,4 @@
use surrealdb::{engine::any::Any, Surreal};
use common::{error::AppError, utils::embedding::generate_embedding};
use common::{error::AppError, storage::db::SurrealDbClient, utils::embedding::generate_embedding};
/// Compares vectors and retrieves a number of items from the specified table.
///
@@ -26,7 +24,7 @@ use common::{error::AppError, utils::embedding::generate_embedding};
pub async fn find_items_by_vector_similarity<T>(
take: u8,
input_text: &str,
db_client: &Surreal<Any>,
db_client: &SurrealDbClient,
table: &str,
openai_client: &async_openai::Client<async_openai::config::OpenAIConfig>,
user_id: &str,
@@ -35,7 +33,7 @@ where
T: for<'de> serde::Deserialize<'de>,
{
// Generate embeddings
let input_embedding = generate_embedding(openai_client, input_text).await?;
let input_embedding = generate_embedding(openai_client, input_text, db_client).await?;
// Construct the query
let closest_query = format!("SELECT *, vector::distance::knn() AS distance FROM {} WHERE user_id = '{}' AND embedding <|{},40|> {:?} ORDER BY distance", table, user_id, take, input_embedding);