code: from langchain.chains import LLMChain
  from langchain_core.prompts import PromptTemplate
  from langchain_openai import ChatOpenAI
  
  from output_parsers import summary_parser, ice_breaker_parser, topics_of_interest_parser
  
  llm = ChatOpenAI(temperature=0, model_name="gpt-3.5-turbo")
  llm_creative = ChatOpenAI(temperature=1, model_name="gpt-3.5-turbo")
  
  
  def get_summary_chain() -> LLMChain:
      summary_template = """
           given the information about a person from linkedin {information}, and twitter posts {twitter_posts} I want you to create:
           1. a short summary
           2. two interesting facts about them
           \n{format_instructions}
       """
  
      summary_prompt_template = PromptTemplate(
          input_variables=["information", "twitter_posts"],
          template=summary_template,
          partial_variables={
              "format_instructions": summary_parser.get_format_instructions()
          },
      )
  
      return LLMChain(llm=llm, prompt=summary_prompt_template)
  
  
  def get_interests_chain() -> LLMChain:
      interesting_facts_template = """
           given the information about a person from linkedin {information}, and twitter posts {twitter_posts} I want you to create:
           3 topics that might interest them
          \n{format_instructions}
       """
  
      interesting_facts_prompt_template = PromptTemplate(
          input_variables=["information", "twitter_posts"],
          template=interesting_facts_template,
          partial_variables={
              "format_instructions": topics_of_interest_parser.get_format_instructions()
          },
      )
  
      return LLMChain(llm=llm, prompt=interesting_facts_prompt_template)
  
  
  def get_ice_breaker_chain() -> LLMChain:
      ice_breaker_template = """
           given the information about a person from linkedin {information}, and twitter posts {twitter_posts} I want you to create:
           2 creative Ice breakers with them that are derived from their activity on Linkedin and twitter, preferably on latest tweets
          \n{format_instructions}
       """
  
      ice_breaker_prompt_template = PromptTemplate(
          input_variables=["information", "twitter_posts"],
          template=ice_breaker_template,
          partial_variables={
              "format_instructions": ice_breaker_parser.get_format_instructions()
          },
      )
  
      return LLMChain(llm=llm_creative, prompt=ice_breaker_prompt_template)
  
apis: langchain.chains.LLMChain langchain_openai.ChatOpenAI
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