rerank test and tweak

api/libs/rerank/Cargo.toml

@@ -7,3 +7,7 @@ edition = "2021"
 reqwest = { workspace = true }
 serde = { workspace = true }
 serde_json = { workspace = true }
+
+[dev-dependencies]
+dotenv = { workspace = true }
+tokio = { version = "1", features = ["macros", "rt-multi-thread"] }

api/libs/rerank/src/lib.rs

@@ -2,15 +2,7 @@ use reqwest::Client;
 use serde::{Deserialize, Serialize};
 use std::error::Error;
 
-#[derive(Debug)]
-pub enum RerankerType {
-    Cohere,
-    Mxbai,
-    Jina,
-}
-
 pub struct Reranker {
-    reranker_type: RerankerType,
     api_key: String,
     base_url: String,
     model: String,
@@ -19,23 +11,11 @@ pub struct Reranker {
 
 impl Reranker {
     pub fn new() -> Result<Self, Box<dyn Error>> {
-        let provider = std::env::var("RERANK_PROVIDER")?;
-        let reranker_type = match provider.to_lowercase().as_str() {
-            "cohere" => RerankerType::Cohere,
-            "mxbai" => RerankerType::Mxbai,
-            "jina" => RerankerType::Jina,
-            _ => return Err("Invalid provider specified".into()),
-        };
         let api_key = std::env::var("RERANK_API_KEY")?;
         let model = std::env::var("RERANK_MODEL")?;
-        let base_url = match reranker_type {
-            RerankerType::Cohere => "https://api.cohere.com/v2/rerank",
-            RerankerType::Mxbai => "https://api.mixedbread.ai/v1/rerank",
-            RerankerType::Jina => "https://api.jina.ai/v1/rerank",
-        }.to_string();
+        let base_url = std::env::var("RERANK_BASE_URL")?;
         let client = Client::new();
         Ok(Self {
-            reranker_type,
             api_key,
             base_url,
             model,

api/libs/rerank/tests/integration_test.rs

@@ -0,0 +1,56 @@
+use rerank::{Reranker, RerankResult};
+use std::error::Error;
+
+#[tokio::test]
+async fn test_reranker_integration() -> Result<(), Box<dyn Error>> {
+    // Load environment variables from .env file
+    dotenv::dotenv().ok();
+
+    // Initialize the reranker
+    let reranker = Reranker::new()?;
+
+    // Define a sample query and documents
+    let query = "What is the capital of France?";
+    let documents = vec![
+        "Paris is a major European city and a global center for art, fashion, gastronomy and culture.",
+        "London is the capital and largest city of England and the United Kingdom.",
+        "The Eiffel Tower is a wrought-iron lattice tower on the Champ de Mars in Paris, France.",
+        "Berlin is the capital and largest city of Germany by both area and population.",
+    ];
+    let top_n = 2;
+
+    // Perform reranking
+    let results: Vec<RerankResult> = reranker.rerank(query, &documents, top_n).await?;
+
+    // Assertions
+    assert_eq!(results.len(), top_n, "Should return top_n results");
+
+    // Check that indices are within the bounds of the original documents
+    for result in &results {
+        assert!(result.index < documents.len(), "Result index should be valid");
+    }
+
+    // Optional: Print results for manual verification (can be removed later)
+    println!("Query: {}", query);
+    for result in &results {
+        println!(
+            "Document Index: {}, Score: {:.4}, Document: {}",
+            result.index,
+            result.relevance_score,
+            documents[result.index]
+        );
+    }
+    
+    // Example assertion: if we expect Paris-related documents to be ranked higher.
+    // This is a very basic check and might need adjustment based on actual model behavior.
+    if !results.is_empty() {
+        let first_result_doc = documents[results[0].index];
+        assert!(
+            first_result_doc.to_lowercase().contains("paris"),
+            "The top result for 'capital of France' should ideally mention Paris. Model output: {}",
+            first_result_doc
+        );
+    }
+
+    Ok(())
+}