
Name	AnswerJoiner
Folder path	/joiners/
Most common position in a pipeline	In query pipelines, after Generators and, subsequently, components that return a list of answers such as `AnswerBuilder`
Mandatory input variables	“answers”: A nested list of answers to be merged, received from the Generator. This input is `variadic`, meaning you can connect a variable number of components to it.
Output variables	“answers”: A merged list of answers

Overvew

AnswerJoiner joins input lists of Answer objects from multiple connections and returns them as one list.

You can optionally set the top_k parameter, which specifies the maximum number of answers to return. If you don’t set this parameter, the component returns all answers it receives.

Usage

In this simple example pipeline, the AnswerJoiner merges answers from two instances of Generators:

from haystack.components.builders import AnswerBuilder
from haystack.components.joiners import AnswerJoiner

from haystack.core.pipeline import Pipeline

from haystack.components.generators.chat import OpenAIChatGenerator
from haystack.dataclasses import ChatMessage


query = "What's Natural Language Processing?"
messages = [ChatMessage.from_system("You are a helpful, respectful and honest assistant. Be super concise."),
            ChatMessage.from_user(query)]

pipe = Pipeline()
pipe.add_component("gpt-4o", OpenAIChatGenerator(model="gpt-4o"))
pipe.add_component("llama", OpenAIChatGenerator(model="gpt-3.5-turbo"))
pipe.add_component("aba", AnswerBuilder())
pipe.add_component("abb", AnswerBuilder())
pipe.add_component("joiner", AnswerJoiner())

pipe.connect("gpt-4o.replies", "aba")
pipe.connect("llama.replies", "abb")
pipe.connect("aba.answers", "joiner")
pipe.connect("abb.answers", "joiner")

results = pipe.run(data={"gpt-4o": {"messages": messages},
                            "llama": {"messages": messages},
                            "aba": {"query": query},
                            "abb": {"query": query}})