Handle Ragas testset batch size compatibility

@@ -2,6 +2,7 @@ from __future__ import annotations
 
 
 import json
 import json
 import logging
 import logging
+import inspect
 from typing import Any
 from typing import Any
 
 
 from langchain_core.documents import Document
 from langchain_core.documents import Document
@@ -95,16 +96,17 @@ def generate_ragas_testset(
     )
     )
     ragas_llm, ragas_embeddings = _wrap_langchain_models(llm, embeddings)
     ragas_llm, ragas_embeddings = _wrap_langchain_models(llm, embeddings)
     generator = TestsetGenerator(llm=ragas_llm, embedding_model=ragas_embeddings)
     generator = TestsetGenerator(llm=ragas_llm, embedding_model=ragas_embeddings)
-    result = generator.generate_with_langchain_docs(
-        documents,
-        testset_size=size,
-        run_config=RunConfig(
+    generate_kwargs: dict[str, Any] = {
+        "testset_size": size,
+        "run_config": RunConfig(
             timeout=int(ragas_config.get("timeout_seconds", 600)),
             timeout=int(ragas_config.get("timeout_seconds", 600)),
             max_workers=int(ragas_config.get("max_workers", 1)),
             max_workers=int(ragas_config.get("max_workers", 1)),
         ),
         ),
-        batch_size=1,
-        raise_exceptions=False,
-    )
+        "raise_exceptions": False,
+    }
+    if "batch_size" in inspect.signature(generator.generate_with_langchain_docs).parameters:
+        generate_kwargs["batch_size"] = 1
+    result = generator.generate_with_langchain_docs(documents, **generate_kwargs)
 
 
     ragas_rows = result.to_list()
     ragas_rows = result.to_list()
     rows = _normalize_ragas_rows(ragas_rows, selected_source_rows)
     rows = _normalize_ragas_rows(ragas_rows, selected_source_rows)