feat(agents): embed docs & query together

Embed documents and query together to reduce the time taken for retrieving the sources ~1 seconds.

docker-compose.yaml

@@ -9,6 +9,7 @@ services:
       - 4000:8080
     networks:
       - perplexica-network
+
   perplexica-backend:
     build:
       context: .

src/agents/academicSearchAgent.ts

@@ -166,11 +166,10 @@ const createBasicAcademicSearchAnsweringChain = (
       (doc) => doc.pageContent && doc.pageContent.length > 0,
     );
 
-    const docEmbeddings = await embeddings.embedDocuments(
-      docsWithContent.map((doc) => doc.pageContent),
-    );
-
-    const queryEmbedding = await embeddings.embedQuery(query);
+    const [docEmbeddings, queryEmbedding] = await Promise.all([
+      embeddings.embedDocuments(docsWithContent.map((doc) => doc.pageContent)),
+      embeddings.embedQuery(query),
+    ]);
 
     const similarity = docEmbeddings.map((docEmbedding, i) => {
       const sim = computeSimilarity(queryEmbedding, docEmbedding);

src/agents/redditSearchAgent.ts

@@ -161,11 +161,10 @@ const createBasicRedditSearchAnsweringChain = (
       (doc) => doc.pageContent && doc.pageContent.length > 0,
     );
 
-    const docEmbeddings = await embeddings.embedDocuments(
-      docsWithContent.map((doc) => doc.pageContent),
-    );
-
-    const queryEmbedding = await embeddings.embedQuery(query);
+    const [docEmbeddings, queryEmbedding] = await Promise.all([
+      embeddings.embedDocuments(docsWithContent.map((doc) => doc.pageContent)),
+      embeddings.embedQuery(query),
+    ]);
 
     const similarity = docEmbeddings.map((docEmbedding, i) => {
       const sim = computeSimilarity(queryEmbedding, docEmbedding);

src/agents/webSearchAgent.ts

@@ -159,11 +159,10 @@ const createBasicWebSearchAnsweringChain = (
       (doc) => doc.pageContent && doc.pageContent.length > 0,
     );
 
-    const docEmbeddings = await embeddings.embedDocuments(
-      docsWithContent.map((doc) => doc.pageContent),
-    );
-
-    const queryEmbedding = await embeddings.embedQuery(query);
+    const [docEmbeddings, queryEmbedding] = await Promise.all([
+      embeddings.embedDocuments(docsWithContent.map((doc) => doc.pageContent)),
+      embeddings.embedQuery(query),
+    ]);
 
     const similarity = docEmbeddings.map((docEmbedding, i) => {
       const sim = computeSimilarity(queryEmbedding, docEmbedding);

src/agents/youtubeSearchAgent.ts

@@ -161,11 +161,10 @@ const createBasicYoutubeSearchAnsweringChain = (
       (doc) => doc.pageContent && doc.pageContent.length > 0,
     );
 
-    const docEmbeddings = await embeddings.embedDocuments(
-      docsWithContent.map((doc) => doc.pageContent),
-    );
-
-    const queryEmbedding = await embeddings.embedQuery(query);
+    const [docEmbeddings, queryEmbedding] = await Promise.all([
+      embeddings.embedDocuments(docsWithContent.map((doc) => doc.pageContent)),
+      embeddings.embedQuery(query),
+    ]);
 
     const similarity = docEmbeddings.map((docEmbedding, i) => {
       const sim = computeSimilarity(queryEmbedding, docEmbedding);