Create weaviate_utils.py

weaviate_utils.py

@@ -0,0 +1,33 @@
+import weaviate
+from weaviate.embedded import EmbeddedOptions
+from weaviate import Client
+
+def initialize_weaviate_client():
+    return weaviate.Client(embedded_options=EmbeddedOptions())
+
+def class_exists(client, class_name):
+    try:
+        client.schema.get_class(class_name)
+        return True
+    except:
+        return False
+
+def map_dtype_to_weaviate(dtype):
+    if "int" in str(dtype):
+        return "int"
+    elif "float" in str(dtype):
+        return "number"
+    elif "bool" in str(dtype):
+        return "boolean"
+    else:
+        return "string"
+
+def ingest_data_to_weaviate(client, dataframe, class_name, class_description):
+    # ... [same as in your code]
+
+def get_class_schema(client, class_name):
+    all_classes = client.schema.get()["classes"]
+    for cls in all_classes:
+        if cls["class"] == class_name:
+            return cls
+    return None