How can I integrate the new RunnableSequence pipeline with ConstitutionalChain?

Below is a summary of your options:

1. Use the Legacy LLMChain for ConstitutionalChain:
   Since ConstitutionalChain still expects an LLMChain-like interface (with methods like get), you can revert to initializing your chain with LLMChain instead of the new runnable sequence. This avoids the error immediately—even though LLMChain is deprecated, it will work until you migrate.

   Example:

   PYTHONCopied
   from langchain.chains import LLMChain
   from langchain.prompts import ChatPromptTemplate
   from langchain.chains.constitutional_ai.base import ConstitutionalChain
   from langchain.chains.constitutional_ai.models import ConstitutionalPrinciple
   
   llm = ChatGoogleGenerativeAI(
       google_api_key=GEMINI_API_KEY, model="gemini-1.5-flash", temperature=0.3
   )
   
   chat_chain = LLMChain(
       llm=llm,
       prompt=ChatPromptTemplate.from_template("{query}")
   )
   
   principle = ConstitutionalPrinciple(
       name="Fear of Spiders",
       critique_request="The model should not include spiders in stories it writes.",
       revision_request="Modify the story to be about animals other than spiders.",
   )
   
   constitutional_chain = ConstitutionalChain.from_llm(
       chain=chat_chain,
       constitutional_principles=[principle],
       llm=llm  # required by the legacy implementation
   )
   
   query = {"query": "Please give me the main events of a story about three household pets."}
   result = constitutional_chain.invoke(query)
   print(result["output"])

2. Migrate to the New LangGraph/LCEL Approach:
   The LangChain team recommends transitioning to LangGraph (or using LCEL directly) to build constitutional or self-reflection chains. LangGraph offers:

   • Native support for structured outputs.
   • Streaming and async support.
   • A more modular way to compose chains.

   In this approach, you would decompose your chain into steps (e.g., initial response, critique, and revision) and build a state graph that uses the new tools. This means you won’t be using ConstitutionalChain at all but building your own chain following the LangGraph guides which show examples on constructing similar pipelines.

   For instance, instead of using the legacy ConstitutionalChain, you might design:

   • A chain to produce the initial answer.
   • A critique chain using a prompt (e.g., via ChatPromptTemplate).
   • A revision chain that acts on the critique.

   LangGraph provides primitives to tie these steps together in an easily debuggable manner.

   Although this approach involves some refactoring, it’s the recommended long-term solution as the legacy components (including ConstitutionalChain) are planned for removal.

3. Adapter/Wrapping (Not Recommended Long-Term):
   If you must use your runnable sequence with ConstitutionalChain, you’d need to write an adapter that mimics the old LLMChain interface (i.e., implementing a get method or any other expected attributes). This could work as a stopgap measure but isn’t ideal given the overall migration direction.

In summary, the error occurs because your new pipeline (a RunnableSequence) doesn’t implement the interface methods ConstitutionalChain expects. While you could wrap your new chain into a legacy adapter, the best solution is to either use LLMChain (until you’re ready to rewrite your logic) or—preferably—migrate your code to use the LangGraph/LCEL approach as demonstrated in the latest LangChain guides.

Choose the option that best fits your timeline and codebase while keeping in mind that a move to LangGraph is recommended since the legacy chains (including ConstitutionalChain) are deprecated.