fix: add tests to cycles in Graph and improve error handling (#3628)

* Add cycle detection and handling in graph edge building process

- Introduced `cycles` property to detect cycles in the graph.
- Modified `_build_edges` and `build_edge` methods to differentiate between `CycleEdge` and `Edge`.
- Updated imports and type hints to support new functionality.

* Add cycle detection and handling in graph processing

- Introduced `is_cyclic` property to check for cycles in the graph.
- Added `_snapshot` method for capturing the current state of the graph.
- Modified `layered_topological_sort` to handle cyclic graphs by starting from a specified start component.
- Updated imports and type hints for better code clarity and functionality.

* Refactor tests and components for improved caching and data handling

- Updated `test_vector_store_rag.py` to use `set_on_output` with `cache=True` and simplified assertions.
- Enhanced `test_memory_chatbot.py` with additional assertions for graph structure and caching.
- Simplified `to_data` method in `base.py` to directly return `_data` without JSON serialization.

* Add unit tests for detecting cycles in graph

- Introduce `test_cycle_in_graph` to verify cyclic behavior in the graph.
- Add `test_cycle_in_graph_max_iterations` to ensure max iterations limit is respected.
- Implement `Concatenate` component for testing purposes.

* Disable output cache in graph tests to allow loops to work

* Refactor: Update VertexStates enum values to uppercase and optimize imports in base.py

* Refactor type hints and improve error handling in `Vertex` class

- Replace `ValueError` with `NoComponentInstance` exception for missing component instances.
- Add `target_handle_name` parameter to `_get_result` method for better result retrieval.
- Refactor type hints to use `collections.abc` for `AsyncIterator`, `Generator`, and `Iterator`.
- Update type hints for `extract_messages_from_artifacts` and `successors_ids` methods to use generic `dict` and `list`.

src/backend/base/langflow/graph/graph/base.py

@@ -4,24 +4,31 @@ import json
 import uuid
 import warnings
 from collections import defaultdict, deque
+from collections.abc import Generator, Iterable
 from datetime import datetime, timezone
 from functools import partial
 from itertools import chain
-from typing import TYPE_CHECKING, Any, Optional
+from typing import TYPE_CHECKING, Any, Optional, cast
-from collections.abc import Generator
 
 import nest_asyncio
 from loguru import logger
 
 from langflow.exceptions.component import ComponentBuildException
-from langflow.graph.edge.base import CycleEdge
+from langflow.graph.edge.base import CycleEdge, Edge
 from langflow.graph.edge.schema import EdgeData
 from langflow.graph.graph.constants import Finish, lazy_load_vertex_dict
 from langflow.graph.graph.runnable_vertices_manager import RunnableVerticesManager
 from langflow.graph.graph.schema import GraphData, GraphDump, StartConfigDict, VertexBuildResult
 from langflow.graph.graph.state_manager import GraphStateManager
 from langflow.graph.graph.state_model import create_state_model_from_graph
-from langflow.graph.graph.utils import find_start_component_id, process_flow, should_continue, sort_up_to_vertex
+from langflow.graph.graph.utils import (
+    find_all_cycle_edges,
+    find_start_component_id,
+    has_cycle,
+    process_flow,
+    should_continue,
+    sort_up_to_vertex,
+)
 from langflow.graph.schema import InterfaceComponentTypes, RunOutputs
 from langflow.graph.vertex.base import Vertex, VertexStates
 from langflow.graph.vertex.schema import NodeData
@@ -279,6 +286,15 @@ class Graph:
 
         raise ValueError("Max iterations reached")
 
+    def _snapshot(self):
+        return {
+            "_run_queue": self._run_queue.copy(),
+            "_first_layer": self._first_layer.copy(),
+            "vertices_layers": copy.deepcopy(self.vertices_layers),
+            "vertices_to_run": copy.deepcopy(self.vertices_to_run),
+            "run_manager": copy.deepcopy(self.run_manager.to_dict()),
+        }
+
     def __apply_config(self, config: StartConfigDict):
         for vertex in self.vertices:
             if vertex._custom_component is None:
@@ -460,6 +476,23 @@ class Graph:
             raise ValueError("Graph not prepared. Call prepare() first.")
         return self._first_layer
 
+    @property
+    def is_cyclic(self):
+        """
+        Check if the graph has any cycles.
+
+        Returns:
+            bool: True if the graph has any cycles, False otherwise.
+        """
+        if self._is_cyclic is None:
+            vertices = [vertex.id for vertex in self.vertices]
+            try:
+                edges = [(e["data"]["sourceHandle"]["id"], e["data"]["targetHandle"]["id"]) for e in self._edges]
+            except KeyError:
+                edges = [(e["source"], e["target"]) for e in self._edges]
+            self._is_cyclic = has_cycle(vertices, edges)
+        return self._is_cyclic
+
     @property
     def run_id(self):
         """
@@ -1380,7 +1413,7 @@ class Graph:
 
     def find_next_runnable_vertices(self, vertex_id: str, vertex_successors_ids: list[str]) -> list[str]:
         next_runnable_vertices = set()
-        for v_id in vertex_successors_ids:
+        for v_id in sorted(vertex_successors_ids):
             if not self.is_vertex_runnable(v_id):
                 next_runnable_vertices.update(self.find_runnable_predecessors_for_successor(v_id))
             else:
@@ -1536,21 +1569,31 @@ class Graph:
                 neighbors[neighbor] += 1
         return neighbors
 
+    @property
+    def cycles(self):
+        if self._cycles is None:
+            if self._start is None:
+                self._cycles = []
+            else:
+                entry_vertex = self._start._id
+                edges = [(e["data"]["sourceHandle"]["id"], e["data"]["targetHandle"]["id"]) for e in self._edges]
+                self._cycles = find_all_cycle_edges(entry_vertex, edges)
+        return self._cycles
+
     def _build_edges(self) -> list[CycleEdge]:
         """Builds the edges of the graph."""
         # Edge takes two vertices as arguments, so we need to build the vertices first
         # and then build the edges
         # if we can't find a vertex, we raise an error
-
+        edges: set[CycleEdge | Edge] = set()
-        edges: set[CycleEdge] = set()
         for edge in self._edges:
             new_edge = self.build_edge(edge)
             edges.add(new_edge)
         if self.vertices and not edges:
             warnings.warn("Graph has vertices but no edges")
-        return list(edges)
+        return list(cast(Iterable[CycleEdge], edges))
 
-    def build_edge(self, edge: EdgeData) -> CycleEdge:
+    def build_edge(self, edge: EdgeData) -> CycleEdge | Edge:
         source = self.get_vertex(edge["source"])
         target = self.get_vertex(edge["target"])
 
@@ -1558,7 +1601,10 @@ class Graph:
             raise ValueError(f"Source vertex {edge['source']} not found")
         if target is None:
             raise ValueError(f"Target vertex {edge['target']} not found")
-        new_edge = CycleEdge(source, target, edge)
+        if (source.id, target.id) in self.cycles:
+            new_edge: CycleEdge | Edge = CycleEdge(source, target, edge)
+        else:
+            new_edge = Edge(source, target, edge)
         return new_edge
 
     def _get_vertex_class(self, node_type: str, node_base_type: str, node_id: str) -> type["Vertex"]:
@@ -1608,7 +1654,6 @@ class Graph:
         if stop_component_id and start_component_id:
             raise ValueError("You can only provide one of stop_component_id or start_component_id")
         self.validate_stream()
-        self.edges = self._build_edges()
 
         if stop_component_id or start_component_id:
             try:
@@ -1658,12 +1703,25 @@ class Graph:
         """Performs a layered topological sort of the vertices in the graph."""
         vertices_ids = {vertex.id for vertex in vertices}
         # Queue for vertices with no incoming edges
-        queue = deque(
+        in_degree_map = self.in_degree_map.copy()
-            vertex.id
+        if self.is_cyclic and all(in_degree_map.values()):
-            for vertex in vertices
+            # This means we have a cycle because all vertex have in_degree_map > 0
-            # if filter_graphs then only vertex.is_input will be considered
+            # because of this we set the queue to start on the ._start if it exists
-            if self.in_degree_map[vertex.id] == 0 and (not filter_graphs or vertex.is_input)
+            if self._start is not None:
-        )
+                queue = deque([self._start._id])
+            else:
+                # Find the chat input component
+                chat_input = find_start_component_id(vertices_ids)
+                if chat_input is None:
+                    raise ValueError("No input component found and no start component provided")
+                queue = deque([chat_input])
+        else:
+            queue = deque(
+                vertex.id
+                for vertex in vertices
+                # if filter_graphs then only vertex.is_input will be considered
+                if in_degree_map[vertex.id] == 0 and (not filter_graphs or vertex.is_input)
+            )
         layers: list[list[str]] = []
         visited = set(queue)
 
@@ -1684,13 +1742,13 @@ class Graph:
                     if neighbor not in vertices_ids:
                         continue
 
-                    self.in_degree_map[neighbor] -= 1  # 'remove' edge
+                    in_degree_map[neighbor] -= 1  # 'remove' edge
-                    if self.in_degree_map[neighbor] == 0 and neighbor not in visited:
+                    if in_degree_map[neighbor] == 0 and neighbor not in visited:
                         queue.append(neighbor)
 
                     # if > 0 it might mean not all predecessors have added to the queue
                     # so we should process the neighbors predecessors
-                    elif self.in_degree_map[neighbor] > 0:
+                    elif in_degree_map[neighbor] > 0:
                         for predecessor in self.predecessor_map[neighbor]:
                             if predecessor not in queue and predecessor not in visited:
                                 queue.append(predecessor)

src/backend/base/langflow/graph/vertex/base.py

@@ -4,10 +4,9 @@ import inspect
 import os
 import traceback
 import types
-import json
+from collections.abc import AsyncIterator, Callable, Iterator, Mapping
 from enum import Enum
 from typing import TYPE_CHECKING, Any, Optional
-from collections.abc import AsyncIterator, Callable, Iterator, Mapping
 
 import pandas as pd
 from loguru import logger
@@ -37,9 +36,9 @@ if TYPE_CHECKING:
 class VertexStates(str, Enum):
     """Vertex are related to it being active, inactive, or in an error state."""
 
-    ACTIVE = "active"
+    ACTIVE = "ACTIVE"
-    INACTIVE = "inactive"
+    INACTIVE = "INACTIVE"
-    ERROR = "error"
+    ERROR = "ERROR"
 
 
 class Vertex:
@@ -105,12 +104,7 @@ class Vertex:
         self._custom_component._set_input_value(name, value)
 
     def to_data(self):
-        try:
+        return self._data
-            data = json.loads(json.dumps(self._data, default=str))
-        except TypeError:
-            data = self._data
-
-        return data
 
     def add_component_instance(self, component_instance: "Component"):
         component_instance.set_vertex(self)

src/backend/base/langflow/graph/vertex/types.py

@@ -102,8 +102,6 @@ class ComponentVertex(Vertex):
                 )
             for edge in self.get_edge_with_target(requester.id):
                 # We need to check if the edge is a normal edge
-                # or a contract edge
-
                 if edge.is_cycle and edge.target_param:
                     return requester.get_value_from_template_dict(edge.target_param)
 

src/backend/tests/unit/graph/graph/test_cycles.py

@@ -0,0 +1,111 @@
+import pytest
+
+from langflow.components.inputs.ChatInput import ChatInput
+from langflow.components.outputs.ChatOutput import ChatOutput
+from langflow.components.outputs.TextOutput import TextOutputComponent
+from langflow.components.prototypes.ConditionalRouter import ConditionalRouterComponent
+from langflow.custom.custom_component.component import Component
+from langflow.graph.graph.base import Graph
+from langflow.io import MessageTextInput, Output
+from langflow.schema.message import Message
+
+
+@pytest.fixture
+def client():
+    pass
+
+
+class Concatenate(Component):
+    display_name = "Concatenate"
+    description = "Concatenates two strings"
+
+    inputs = [
+        MessageTextInput(name="text", display_name="Text", required=True),
+    ]
+    outputs = [
+        Output(display_name="Text", name="some_text", method="concatenate"),
+    ]
+
+    def concatenate(self) -> Message:
+        return Message(text=f"{self.text}{self.text}" or "test")
+
+
+def test_cycle_in_graph():
+    chat_input = ChatInput(_id="chat_input")
+    router = ConditionalRouterComponent(_id="router")
+    chat_input.set(input_value=router.false_response)
+    concat_component = Concatenate(_id="concatenate")
+    concat_component.set(text=chat_input.message_response)
+    router.set(
+        input_text=chat_input.message_response,
+        match_text="testtesttesttest",
+        operator="equals",
+        message=concat_component.concatenate,
+    )
+    text_output = TextOutputComponent(_id="text_output")
+    text_output.set(input_value=router.true_response)
+    chat_output = ChatOutput(_id="chat_output")
+    chat_output.set(input_value=text_output.text_response)
+
+    graph = Graph(chat_input, chat_output)
+    assert graph.is_cyclic is True
+
+    # Run queue should contain chat_input and not router
+    assert "chat_input" in graph._run_queue
+    assert "router" not in graph._run_queue
+    results = []
+    max_iterations = 20
+    snapshots = [graph._snapshot()]
+    for result in graph.start(max_iterations=max_iterations, config={"output": {"cache": False}}):
+        snapshots.append(graph._snapshot())
+        results.append(result)
+    results_ids = [result.vertex.id for result in results if hasattr(result, "vertex")]
+    assert results_ids[-2:] == ["text_output", "chat_output"]
+    assert len(results_ids) > len(graph.vertices), snapshots
+    # Check that chat_output and text_output are the last vertices in the results
+    assert results_ids == [
+        "chat_input",
+        "concatenate",
+        "router",
+        "chat_input",
+        "concatenate",
+        "router",
+        "chat_input",
+        "concatenate",
+        "router",
+        "chat_input",
+        "concatenate",
+        "router",
+        "text_output",
+        "chat_output",
+    ], f"Results: {results_ids}"
+
+
+def test_cycle_in_graph_max_iterations():
+    chat_input = ChatInput(_id="chat_input")
+    router = ConditionalRouterComponent(_id="router")
+    chat_input.set(input_value=router.false_response)
+    concat_component = Concatenate(_id="concatenate")
+    concat_component.set(text=chat_input.message_response)
+    router.set(
+        input_text=chat_input.message_response,
+        match_text="testtesttesttest",
+        operator="equals",
+        message=concat_component.concatenate,
+    )
+    text_output = TextOutputComponent(_id="text_output")
+    text_output.set(input_value=router.true_response)
+    chat_output = ChatOutput(_id="chat_output")
+    chat_output.set(input_value=text_output.text_response)
+
+    graph = Graph(chat_input, chat_output)
+    assert graph.is_cyclic is True
+
+    # Run queue should contain chat_input and not router
+    assert "chat_input" in graph._run_queue
+    assert "router" not in graph._run_queue
+    results = []
+
+    with pytest.raises(ValueError, match="Max iterations reached"):
+        for result in graph.start(max_iterations=2, config={"output": {"cache": False}}):
+            results.append(result)

src/backend/tests/unit/initial_setup/starter_projects/test_memory_chatbot.py

@@ -30,23 +30,35 @@ AI: """
     openai_component.set(
         input_value=prompt_component.build_prompt, max_tokens=100, temperature=0.1, api_key="test_api_key"
     )
-    openai_component.get_output("text_output").value = "Mock response"
+    openai_component.set_on_output(name="text_output", value="Mock response", cache=True)
 
     chat_output = ChatOutput(_id="chat_output")
     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}
     return graph
 
 
 def test_memory_chatbot(memory_chatbot_graph):
     # Now we run step by step
     expected_order = deque(["chat_input", "chat_memory", "prompt", "openai", "chat_output"])
+    assert memory_chatbot_graph.in_degree_map == {
+        "chat_output": 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.first_layer == ["chat_input", "chat_memory"]
+
     for step in expected_order:
         result = memory_chatbot_graph.step()
         if isinstance(result, Finish):
             break
-        assert step == result.vertex.id
+
+        assert step == result.vertex.id, (memory_chatbot_graph.in_degree_map, memory_chatbot_graph.vertices_layers)
 
 
 def test_memory_chatbot_dump_structure(memory_chatbot_graph: Graph):

src/backend/tests/unit/initial_setup/starter_projects/test_vector_store_rag.py

@@ -1,5 +1,4 @@
 import copy
-from collections import Counter, defaultdict
 from textwrap import dedent
 
 import pytest
@@ -15,7 +14,6 @@ from langflow.components.prompts.Prompt import PromptComponent
 from langflow.components.vectorstores.AstraDB import AstraVectorStoreComponent
 from langflow.graph.graph.base import Graph
 from langflow.graph.graph.constants import Finish
-from langflow.graph.graph.schema import VertexBuildResult
 from langflow.schema.data import Data
 
 
@@ -29,7 +27,7 @@ def ingestion_graph():
     # Ingestion Graph
     file_component = FileComponent(_id="file-123")
     file_component.set(path="test.txt")
-    file_component.set_on_output("data", value=Data(text="This is a test file."))
+    file_component.set_on_output(name="data", value=Data(text="This is a test file."), cache=True)
     text_splitter = SplitTextComponent(_id="text-splitter-123")
     text_splitter.set(data_inputs=file_component.load_file)
     openai_embeddings = OpenAIEmbeddingsComponent(_id="openai-embeddings-123")
@@ -43,9 +41,10 @@ def ingestion_graph():
         api_endpoint="https://astra.example.com",
         token="token",
     )
-    vector_store.set_on_output("vector_store", value="mock_vector_store")
+    vector_store.set_on_output(name="vector_store", value="mock_vector_store", cache=True)
-    vector_store.set_on_output("base_retriever", value="mock_retriever")
+    vector_store.set_on_output(name="base_retriever", value="mock_retriever", cache=True)
-    vector_store.set_on_output("search_results", value=[Data(text="This is a test file.")])
+    vector_store.set_on_output(name="search_results", value=[Data(text="This is a test file.")], cache=True)
+
     ingestion_graph = Graph(file_component, vector_store)
     return ingestion_graph
 
@@ -65,14 +64,15 @@ def rag_graph():
     )
     # Mock search_documents
     rag_vector_store.set_on_output(
-        "search_results",
+        name="search_results",
         value=[
             Data(data={"text": "Hello, world!"}),
             Data(data={"text": "Goodbye, world!"}),
         ],
+        cache=True,
     )
-    rag_vector_store.set_on_output("base_retriever", value="mock_retriever")
+    rag_vector_store.set_on_output(name="vector_store", value="mock_vector_store", cache=True)
-    rag_vector_store.set_on_output("vector_store", value="mock_vector_store")
+    rag_vector_store.set_on_output(name="base_retriever", value="mock_retriever", cache=True)
     parse_data = ParseDataComponent(_id="parse-data-123")
     parse_data.set(data=rag_vector_store.search_documents)
     prompt_component = PromptComponent(_id="prompt-123")
@@ -88,7 +88,7 @@ def rag_graph():
 
     openai_component = OpenAIModelComponent(_id="openai-123")
     openai_component.set(api_key="sk-123", openai_api_base="https://api.openai.com/v1")
-    openai_component.set_on_output("text_output", value="Hello, world!")
+    openai_component.set_on_output(name="text_output", value="Hello, world!", cache=True)
     openai_component.set(input_value=prompt_component.build_prompt)
 
     chat_output = ChatOutput(_id="chatoutput-123")
@@ -98,7 +98,7 @@ def rag_graph():
     return graph
 
 
-def test_vector_store_rag(ingestion_graph: Graph, rag_graph: Graph):
+def test_vector_store_rag(ingestion_graph, rag_graph):
     assert ingestion_graph is not None
     ingestion_ids = [
         "file-123",
@@ -117,17 +117,11 @@ def test_vector_store_rag(ingestion_graph: Graph, rag_graph: Graph):
         "openai-embeddings-124",
     ]
     for ids, graph, len_results in zip([ingestion_ids, rag_ids], [ingestion_graph, rag_graph], [5, 8]):
-        results: list[VertexBuildResult] = []
+        results = []
-        ids_count = Counter(ids)
+        for result in graph.start():
-        results_id_count: dict[str, int] = defaultdict(int)
-        for result in graph.start(config={"output": {"cache": True}}):
             results.append(result)
-            if hasattr(result, "vertex"):
-                results_id_count[result.vertex.id] += 1
 
-        assert (
+        assert len(results) == len_results
-            len(results) == len_results
-        ), f"Counts: {ids_count} != {results_id_count}, Diff: {set(ids_count.keys()) - set(results_id_count.keys())}"
         vids = [result.vertex.id for result in results if hasattr(result, "vertex")]
         assert all(vid in ids for vid in vids), f"Diff: {set(vids) - set(ids)}"
         assert results[-1] == Finish()