text: There are several ways to learn Python, and the best method for you will depend on your learning style and goals. Here are a few suggestions:    Stopped output runtime: 3.2350128999969456 secondsChaining Callsâ€‹The whole point of langchain is to... chain! Here's an example of how do that.from langchain.chains import SimpleSequentialChainFirst, let's define the LLM for this model as a flan-5, and text2image as a stable diffusion model.dolly_llm = Replicate(    model="replicate/dolly-v2-12b:ef0e1aefc61f8e096ebe4db6b2bacc297daf2ef6899f0f7e001ec445893500e5")text2image = Replicate(    model="stability-ai/stable-diffusion:db21e45d3f7023abc2a46ee38a23973f6dce16bb082a930b0c49861f96d1e5bf")First prompt in the chainprompt = PromptTemplate(    input_variables=["product"],    template="What is a good name for a company that makes {product}?",)chain = LLMChain(llm=dolly_llm, prompt=prompt)Second prompt to get the logo for company descriptionsecond_prompt = PromptTemplate(    input_variables=["company_name"],    template="Write a description of a logo for this company: {company_name}",)chain_two = LLMChain(llm=dolly_llm, prompt=second_prompt)Third prompt, let's create the image based on the description output from prompt 2third_prompt = PromptTemplate(    input_variables=["company_logo_description"],    template="{company_logo_description}",)chain_three =