gaia dataset val

agent.py

@@ -100,10 +100,7 @@ embeddings = HuggingFaceEmbeddings(
 )  #  dim=768
 
 # Load the GAIA validation dataset
-dataset = load_dataset("gaia-benchmark/GAIA", name="2023_level1", split="validation")
-
-# Prepare the embeddings model
-embeddings = HuggingFaceEmbeddings(model_name="all-MiniLM-L6-v2")
+dataset = load_dataset("gaia-benchmark/GAIA", name="2023_level1", split="validation", trust_remote_code=True, cache_dir = "ragdata")
 
 # Extract questions and their answers
 documents = []

setup_actions.ipynb

@@ -291,7 +291,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": null,
    "id": "521be8df",
    "metadata": {},
    "outputs": [
@@ -311,8 +311,7 @@
     "from langchain.schema import Document\n",
     "\n",
     "# Load the GAIA validation dataset\n",
-    "dataset = load_dataset(\"gaia-benchmark/GAIA\", name=\"2023_level1\", split=\"validation\")\n",
-    "\n",
+    "dataset = load_dataset(\"gaia-benchmark/GAIA\", name=\"2023_level1\", split=\"validation\", trust_remote_code=True, cache_dir = \"ragdata\")\n",
     "# Prepare the embeddings model\n",
     "embeddings = HuggingFaceEmbeddings(model_name=\"all-MiniLM-L6-v2\")\n",
     "\n",