Set pgvector.dimension to 384

compose.yml

@@ -47,6 +47,7 @@ services:
       # 2. sagemaker - for Sagemaker
       NESIS_RAG_EMBEDDING_MODE: local
       OPENAI_API_KEY: <your-api-key>
+      NESIS_RAG_EMBEDDING_DIMENSIONS: "1536"
 #      OPENAI_API_BASE: <your-api-base>
     networks:
       - nesis

nesis/rag/core/server/ingest/ingest_router.py

@@ -60,13 +60,15 @@ def ingest_file(
         _metadata_str = request.query_params.get("metadata") or str(metadata)
         _metadata = json.loads(_metadata_str)
     except ValueError:
-        raise HTTPException(400, "Invalid of missing metadata field")
+        error = "Invalid of missing metadata field"
+        _logger.exception(error)
+        raise HTTPException(400, error)
     try:
         ingested_documents = service.ingest_bin_data(
             file.filename, file.file, metadata=_metadata
         )
     except ServiceException as se:
-        _logger.exception(f"Error injesting file {_metadata['file_name']}")
+        _logger.exception(f"Error ingesting file {file.filename}")
         raise HTTPException(400, str(se))
     return IngestResponse(object="list", model="private-gpt", data=ingested_documents)
 

nesis/rag/settings-test.yaml

@@ -21,8 +21,7 @@ vectorstore:
 pgvector:
   url: ${NESIS_RAG_PGVECTOR_URL:postgresql://postgres:password@localhost:65432/nesis}
   table: embeddings
-  dimensions: 384 #pg_vector dimensions
-#  dimensions: 1536 #openai dimensions
+  dimensions: 384 #openai dimensions
 
 local:
   prompt_style: "llama2"