using direct local API.    Using DuckDB in-memory for database. Data will be transient.Examplesâ€‹Now we need some examples to evaluate. We can do this in two ways:Hard code some examples ourselvesGenerate examples automatically, using a language model# Hard-coded examplesexamples = [    {        "query": "What did the president say about Ketanji Brown Jackson",        "answer": "He praised her legal ability and said he nominated her for the supreme court.",    },    {"query": "What did the president say about Michael Jackson", "answer": "Nothing"},]# Generated examplesfrom langchain.evaluation.qa import QAGenerateChainexample_gen_chain = QAGenerateChain.from_llm(OpenAI())new_examples = example_gen_chain.apply_and_parse([{"doc": t} for t in texts[:5]])new_examples    [{'query': 'According to the document, what did Vladimir Putin miscalculate?',      'answer': 'He miscalculated that he could roll into Ukraine and the world would roll over.'},     {'query': 'Who is the Ukrainian Ambassador to the United States?',      'answer': 'The Ukrainian Ambassador to the United States is here tonight.'},     {'query': 'How many countries were part of the coalition formed to confront Putin?',      'answer': '27 members of the European Union, France, Germany, Italy, the United Kingdom, Canada, Japan, Korea, Australia, New Zealand, and many others, even Switzerland.'},     {'query': 'What action is the U.S. Department of Justice taking to target Russian oligarchs?',      'answer': 'The U.S. Department of Justice is assembling a dedicated task force to go after the