Upload rag.py

rag.py

@@ -15,6 +15,7 @@ from functools import partial
 from pathlib import Path
 
 import httpx
+import numpy as np
 from lightrag import LightRAG, QueryParam
 from lightrag.llm.openai import openai_complete
 from lightrag.utils import EmbeddingFunc
@@ -75,7 +76,8 @@ async def embed_model_func(texts: list[str]) -> list[list[float]]:
         )
         resp.raise_for_status()
         data = resp.json()["data"]
-        return [item["embedding"] for item in sorted(data, key=lambda x: x["index"])]
+        vectors = [item["embedding"] for item in sorted(data, key=lambda x: x["index"])]
+        return np.array(vectors, dtype=np.float32)
 
 
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