feat: Add a ListJoiner component

haystack/components/joiners/__init__.py

@@ -5,6 +5,7 @@
 from .answer_joiner import AnswerJoiner
 from .branch import BranchJoiner
 from .document_joiner import DocumentJoiner
+from .list_joiner import ListJoiner
 from .string_joiner import StringJoiner
 
-__all__ = ["DocumentJoiner", "BranchJoiner", "AnswerJoiner", "StringJoiner"]
+__all__ = ["DocumentJoiner", "BranchJoiner", "AnswerJoiner", "StringJoiner", "ListJoiner"]

haystack/components/joiners/list_joiner.py

@@ -0,0 +1,105 @@
+# SPDX-FileCopyrightText: 2022-present deepset GmbH <[email protected]>
+#
+# SPDX-License-Identifier: Apache-2.0
+
+from itertools import chain
+from typing import Any, Dict, Type
+
+from haystack import component, default_from_dict, default_to_dict
+from haystack.core.component.types import Variadic
+from haystack.utils import deserialize_type, serialize_type
+
+
+@component
+class ListJoiner:
+    """
+    A component that joins multiple lists into a single flat list.
+
+    The ListJoiner receives multiple lists of the same type and concatenates them into a single flat list.
+    The output order respects the pipeline's execution sequence, with earlier inputs being added first.
+
+    Usage example:
+    ```python
+    from haystack.components.builders import ChatPromptBuilder
+    from haystack.components.generators.chat import OpenAIChatGenerator
+    from haystack.dataclasses import ChatMessage
+    from haystack import Pipeline
+    from haystack.components.joiners import ListJoiner
+    from typing import List
+
+
+    user_message = [ChatMessage.from_user("Give a brief answer the following question: {{query}}")]
+
+    feedback_prompt = \"""
+        You are given a question and an answer.
+        Your task is to provide a score and a brief feedback on the answer.
+        Question: {{query}}
+        Answer: {{response}}
+        \"""
+    feedback_message = [ChatMessage.from_system(feedback_prompt)]
+
+    prompt_builder = ChatPromptBuilder(template=user_message)
+    feedback_prompt_builder = ChatPromptBuilder(template=feedback_message)
+    llm = OpenAIChatGenerator(model="gpt-4o-mini")
+    feedback_llm = OpenAIChatGenerator(model="gpt-4o-mini")
+
+    pipe = Pipeline()
+    pipe.add_component("prompt_builder", prompt_builder)
+    pipe.add_component("llm", llm)
+    pipe.add_component("feedback_prompt_builder", feedback_prompt_builder)
+    pipe.add_component("feedback_llm", feedback_llm)
+    pipe.add_component("list_joiner", ListJoiner(List[ChatMessage]))
+
+    pipe.connect("prompt_builder.prompt", "llm.messages")
+    pipe.connect("prompt_builder.prompt", "list_joiner")
+    pipe.connect("llm.replies", "list_joiner")
+    pipe.connect("llm.replies", "feedback_prompt_builder.response")
+    pipe.connect("feedback_prompt_builder.prompt", "feedback_llm.messages")
+    pipe.connect("feedback_llm.replies", "list_joiner")
+
+    query = "What is nuclear physics?"
+    ans = pipe.run(data={"prompt_builder": {"template_variables":{"query": query}},
+        "feedback_prompt_builder": {"template_variables":{"query": query}}})
+
+    print(ans["list_joiner"]["values"])
+    ```
+    """
+
+    def __init__(self, list_type_: Type):
+        """
+        Creates a ListJoiner component.
+
+        :param list_type_: The type of list that this joiner will handle (e.g., List[ChatMessage]).
+                     All input lists must be of this type.
+        """
+        self.list_type_ = list_type_
+        component.set_output_types(self, values=list_type_)
+
+    def to_dict(self) -> Dict[str, Any]:
+        """
+        Serializes the component to a dictionary.
+
+        :returns: Dictionary with serialized data.
+        """
+        return default_to_dict(self, list_type_=serialize_type(self.list_type_))
+
+    @classmethod
+    def from_dict(cls, data: Dict[str, Any]) -> "ListJoiner":
+        """
+        Deserializes the component from a dictionary.
+
+        :param data: Dictionary to deserialize from.
+        :returns: Deserialized component.
+        """
+        data["init_parameters"]["list_type_"] = deserialize_type(data["init_parameters"]["list_type_"])
+        return default_from_dict(cls, data)
+
+    def run(self, values: Variadic[Any]) -> Dict[str, Any]:
+        """
+        Joins multiple lists into a single flat list.
+
+        :param values:The list to be joined.
+        :returns: Dictionary with 'values' key containing the joined list.
+        """
+        result = list(chain(*values))
+        return {"values": result}

releasenotes/notes/add-list-joiner-4f0ea84e195fa461.yaml

@@ -0,0 +1,4 @@
+---
+features:
+  - |
+    Added a new component `ListJoiner` which joins lists of values from different components to a single list.

test/components/joiners/test_list_joiner.py

@@ -0,0 +1,71 @@
+# SPDX-FileCopyrightText: 2022-present deepset GmbH <[email protected]>
+#
+# SPDX-License-Identifier: Apache-2.0
+
+from typing import List
+
+from haystack import Document
+from haystack.dataclasses import ChatMessage
+from haystack.dataclasses.answer import GeneratedAnswer
+from haystack.components.joiners.list_joiner import ListJoiner
+
+
+class TestListJoiner:
+    def test_init(self):
+        joiner = ListJoiner(List[ChatMessage])
+        assert isinstance(joiner, ListJoiner)
+        assert joiner.list_type_ == List[ChatMessage]
+
+    def test_to_dict(self):
+        joiner = ListJoiner(List[ChatMessage])
+        data = joiner.to_dict()
+        assert data == {
+            "type": "haystack.components.joiners.list_joiner.ListJoiner",
+            "init_parameters": {"list_type_": "typing.List[haystack.dataclasses.chat_message.ChatMessage]"},
+        }
+
+    def test_from_dict(self):
+        data = {
+            "type": "haystack.components.joiners.list_joiner.ListJoiner",
+            "init_parameters": {"list_type_": "typing.List[haystack.dataclasses.chat_message.ChatMessage]"},
+        }
+        list_joiner = ListJoiner.from_dict(data)
+        assert isinstance(list_joiner, ListJoiner)
+        assert list_joiner.list_type_ == List[ChatMessage]
+
+    def test_empty_list(self):
+        joiner = ListJoiner(List[ChatMessage])
+        result = joiner.run([])
+        assert result == {"values": []}
+
+    def test_list_of_empty_lists(self):
+        joiner = ListJoiner(List[ChatMessage])
+        result = joiner.run([[], []])
+        assert result == {"values": []}
+
+    def test_single_list_of_chat_messages(self):
+        joiner = ListJoiner(List[ChatMessage])
+        messages = [ChatMessage.from_user("Hello"), ChatMessage.from_assistant("Hi there")]
+        result = joiner.run([messages])
+        assert result == {"values": messages}
+
+    def test_multiple_lists_of_chat_messages(self):
+        joiner = ListJoiner(List[ChatMessage])
+        messages1 = [ChatMessage.from_user("Hello")]
+        messages2 = [ChatMessage.from_assistant("Hi there")]
+        messages3 = [ChatMessage.from_system("System message")]
+        result = joiner.run([messages1, messages2, messages3])
+        assert result == {"values": messages1 + messages2 + messages3}
+
+    def test_list_of_generated_answers(self):
+        joiner = ListJoiner(List[GeneratedAnswer])
+        answers1 = [GeneratedAnswer(query="q1", data="a1", meta={}, documents=[Document(content="d1")])]
+        answers2 = [GeneratedAnswer(query="q2", data="a2", meta={}, documents=[Document(content="d2")])]
+        result = joiner.run([answers1, answers2])
+        assert result == {"values": answers1 + answers2}
+
+    def test_mixed_empty_and_non_empty_lists(self):
+        joiner = ListJoiner(List[ChatMessage])
+        messages = [ChatMessage.from_user("Hello")]
+        result = joiner.run([messages, [], messages])
+        assert result == {"values": messages + messages}