feat: combine chat history and chat store into a CRUD component (#8323)

* combine history and store * combine history and store * [autofix.ci] apply automated fixes * Update memory.py * [autofix.ci] apply automated fixes * update json * Update memory.py * Update memory.py * [autofix.ci] apply automated fixes * change order * change order * put retrieve first * add json * [autofix.ci] apply automated fixes * Update memory.py * [autofix.ci] apply automated fixes * [autofix.ci] apply automated fixes (attempt 2/3) * update test * fix test * update tests * update memory_chatbot * change number back * fix py test * update * update pokedex * update flow * [autofix.ci] apply automated fixes * update type converter * format * fix name * update meeting summary * [autofix.ci] apply automated fixes * fix test memory chatbot * update method * update method * fix sort * fix test graph state * fix test * fix locator --------- Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com> Co-authored-by: Edwin Jose <edwin.jose@datastax.com> Co-authored-by: Eric Hare <ericrhare@gmail.com>
2025-06-05 15:19:01 -07:00 · 2025-06-05 15:19:01 -07:00 · e23e543b60
commit e23e543b60
parent a161753a57
31 changed files with 7341 additions and 4739 deletions
--- a/src/backend/tests/unit/build_utils.py
+++ b/src/backend/tests/unit/build_utils.py
@ -72,15 +72,21 @@ async def consume_and_assert_stream(response, job_id, timeout=30.0):
                        "Invalid first event. Expected 'vertices_sorted'. Full event stream:\n" + "\n".join(lines)
                    )
                    ids = parsed["data"]["ids"]
-                    ids.sort()
-                    assert ids == ["ChatInput-CIGht"], "Invalid ids in first event. Full event stream:\n" + "\n".join(
+
+                    assert ids == ["ChatInput-vsgM1"], "Invalid ids in first event. Full event stream:\n" + "\n".join(
                        lines
                    )

                    to_run = parsed["data"]["to_run"]
-                    to_run.sort()
-                    assert to_run == ["ChatInput-CIGht", "ChatOutput-QA7ej", "Memory-amN4Z", "Prompt-iWbCC"], (
-                        "Invalid to_run list in first event. Full event stream:\n" + "\n".join(lines)
+                    expected_to_run = [
+                        "ChatInput-vsgM1",
+                        "Prompt-VSSGR",
+                        "TypeConverterComponent-koSIz",
+                        "Memory-8X8Cq",
+                        "ChatOutput-NAw0P",
+                    ]
+                    assert set(to_run) == set(expected_to_run), (
+                        "Invalid to_run list in the first event. Full event stream:\n" + "\n".join(lines)
                    )
                    first_event_seen = True
                # Last event should be end
--- a/src/backend/tests/unit/graph/graph/test_graph_state_model.py
+++ b/src/backend/tests/unit/graph/graph/test_graph_state_model.py
@ -4,6 +4,7 @@ import pytest
 from langflow.components.helpers.memory import MemoryComponent
 from langflow.components.input_output import ChatInput, ChatOutput
 from langflow.components.languagemodels import OpenAIModelComponent
+from langflow.components.processing.converter import TypeConverterComponent
 from langflow.components.prompts import PromptComponent
 from langflow.graph import Graph
 from langflow.graph.graph.constants import Finish
@ -22,9 +23,13 @@ AI: """
    memory_component = MemoryComponent(_id="chat_memory")
    memory_component.set(session_id=session_id)
    chat_input = ChatInput(_id="chat_input")
+    type_converter = TypeConverterComponent(_id="type_converter")
+    type_converter.set(input_data=memory_component.retrieve_messages_dataframe)
    prompt_component = PromptComponent(_id="prompt")
    prompt_component.set(
-        template=template, user_message=chat_input.message_response, context=memory_component.retrieve_messages_as_text
+        template=template,
+        user_message=chat_input.message_response,
+        context=type_converter.convert_to_message,
    )
    openai_component = OpenAIModelComponent(_id="openai")
    openai_component.set(
@ -44,6 +49,7 @@ AI: """
        "chat_output",
        "openai",
        "prompt",
+        "type_converter",
        "chat_memory",
    ]

--- a/src/backend/tests/unit/graph/test_graph.py
+++ b/src/backend/tests/unit/graph/test_graph.py
@ -257,8 +257,12 @@ def test_update_source_handle():


 async def test_serialize_graph():
+    # Get the actual starter projects and directly await the result
    starter_projects = await load_starter_projects()
-    data = starter_projects[0][1]["data"]
+    project_data = starter_projects[0][1]
+    data = project_data["data"]
+
+    # Create and test the graph
    graph = Graph.from_payload(data)
    assert isinstance(graph, Graph)
    serialized = graph.dumps()
--- a/src/backend/tests/unit/initial_setup/starter_projects/test_memory_chatbot.py
+++ b/src/backend/tests/unit/initial_setup/starter_projects/test_memory_chatbot.py
@ -6,6 +6,7 @@ import pytest
 from langflow.components.helpers.memory import MemoryComponent
 from langflow.components.input_output import ChatInput, ChatOutput
 from langflow.components.languagemodels import OpenAIModelComponent
+from langflow.components.processing.converter import TypeConverterComponent
 from langflow.components.prompts import PromptComponent
 from langflow.graph import Graph
 from langflow.graph.graph.constants import Finish
@ -24,9 +25,13 @@ AI: """
    memory_component = MemoryComponent(_id="chat_memory")
    memory_component.set(session_id=session_id)
    chat_input = ChatInput(_id="chat_input")
+    type_converter = TypeConverterComponent(_id="type_converter")
+    type_converter.set(input_data=memory_component.retrieve_messages_dataframe)
    prompt_component = PromptComponent(_id="prompt")
    prompt_component.set(
-        template=template, user_message=chat_input.message_response, context=memory_component.retrieve_messages_as_text
+        template=template,
+        user_message=chat_input.message_response,
+        context=type_converter.convert_to_message,
    )
    openai_component = OpenAIModelComponent(_id="openai")
    openai_component.set(
@ -38,22 +43,30 @@ AI: """
    chat_output.set(input_value=openai_component.text_response)

    graph = Graph(chat_input, chat_output)
-    assert graph.in_degree_map == {"chat_output": 1, "prompt": 2, "openai": 1, "chat_input": 0, "chat_memory": 0}
+    assert graph.in_degree_map == {
+        "chat_output": 1,
+        "type_converter": 1,
+        "prompt": 2,
+        "openai": 1,
+        "chat_input": 0,
+        "chat_memory": 0,
+    }
    return graph


@pytest.mark.usefixtures("client")
 def test_memory_chatbot(memory_chatbot_graph):
    # Now we run step by step
-    expected_order = deque(["chat_input", "chat_memory", "prompt", "openai", "chat_output"])
+    expected_order = deque(["chat_input", "chat_memory", "type_converter", "prompt", "openai", "chat_output"])
    assert memory_chatbot_graph.in_degree_map == {
        "chat_output": 1,
+        "type_converter": 1,
        "prompt": 2,
        "openai": 1,
        "chat_input": 0,
        "chat_memory": 0,
    }
-    assert memory_chatbot_graph.vertices_layers == [["prompt"], ["openai"], ["chat_output"]]
+    assert memory_chatbot_graph.vertices_layers == [["type_converter"], ["prompt"], ["openai"], ["chat_output"]]
    assert memory_chatbot_graph.first_layer == ["chat_input", "chat_memory"]

    for step in expected_order:
@ -86,8 +99,8 @@ def test_memory_chatbot_dump_structure(memory_chatbot_graph: Graph):
    description = graph_dict["description"]
    endpoint_name = graph_dict["endpoint_name"]

-    assert len(nodes) == 5
-    assert len(edges) == 4
+    assert len(nodes) == 6
+    assert len(edges) == 5
    assert description is not None
    assert endpoint_name is not None

@ -124,7 +137,8 @@ def test_memory_chatbot_dump_components_and_edges(memory_chatbot_graph: Graph):
    # Check edges
    expected_edges = [
        ("chat_input", "prompt"),
-        ("chat_memory", "prompt"),
+        ("chat_memory", "type_converter"),
+        ("type_converter", "prompt"),
        ("prompt", "openai"),
        ("openai", "chat_output"),
    ]