text: Docker Hub or GitHub Container Registry (GHCR) is a convenient option to begin with.Once you have selected a registry, you can proceed to create Flyte tasks that log the LangChain metrics to Flyte Deck.The following examples demonstrate tasks related to OpenAI LLM, chains and agent with tools:LLMâ€‹@task(disable_deck=False, container_image=custom_image)def langchain_llm() -> str:    llm = ChatOpenAI(        model_name="gpt-3.5-turbo",        temperature=0.2,        callbacks=[FlyteCallbackHandler()],    )    return llm([HumanMessage(content="Tell me a joke")]).contentChainâ€‹@task(disable_deck=False, container_image=custom_image)def langchain_chain() -> list[dict[str, str]]:    template = """You are a playwright. Given the title of play, it is your job to write a synopsis for that title.Title: {title}Playwright: This is a synopsis for the above play:"""    llm = ChatOpenAI(        model_name="gpt-3.5-turbo",        temperature=0,        callbacks=[FlyteCallbackHandler()],    )    prompt_template = PromptTemplate(input_variables=["title"], template=template)    synopsis_chain = LLMChain(        llm=llm, prompt=prompt_template, callbacks=[FlyteCallbackHandler()]    )    test_prompts = [        {            "title": "documentary about good video games that