Merge branch 'refs/heads/main' into feat/workflow-parallel-support

# Conflicts:
#	api/core/app/apps/advanced_chat/app_generator.py
#	api/core/app/apps/advanced_chat/generate_task_pipeline.py
#	api/core/app/apps/workflow/app_runner.py
#	api/core/app/apps/workflow/generate_task_pipeline.py
#	api/core/app/task_pipeline/workflow_cycle_state_manager.py
#	api/core/workflow/entities/variable_pool.py
#	api/core/workflow/nodes/code/code_node.py
#	api/core/workflow/nodes/llm/llm_node.py
#	api/core/workflow/nodes/start/start_node.py
#	api/core/workflow/nodes/variable_assigner/__init__.py
#	api/tests/integration_tests/workflow/nodes/test_llm.py
#	api/tests/integration_tests/workflow/nodes/test_parameter_extractor.py
#	api/tests/unit_tests/core/workflow/nodes/test_answer.py
#	api/tests/unit_tests/core/workflow/nodes/test_if_else.py
#	api/tests/unit_tests/core/workflow/nodes/test_variable_assigner.py

api/tests/integration_tests/model_runtime/siliconflow/test_rerank.py

@@ -0,0 +1,49 @@
+import os
+
+import pytest
+
+from core.model_runtime.entities.rerank_entities import RerankResult
+from core.model_runtime.errors.validate import CredentialsValidateFailedError
+from core.model_runtime.model_providers.siliconflow.rerank.rerank import SiliconflowRerankModel
+
+
+def test_validate_credentials():
+    model = SiliconflowRerankModel()
+
+    with pytest.raises(CredentialsValidateFailedError):
+        model.validate_credentials(
+            model="BAAI/bge-reranker-v2-m3",
+            credentials={
+                "api_key": "invalid_key"
+            },
+        )
+
+    model.validate_credentials(
+        model="BAAI/bge-reranker-v2-m3",
+        credentials={
+            "api_key": os.environ.get("API_KEY"),
+        },
+    )
+
+
+def test_invoke_model():
+    model = SiliconflowRerankModel()
+
+    result = model.invoke(
+        model='BAAI/bge-reranker-v2-m3',
+        credentials={
+            "api_key": os.environ.get("API_KEY"),
+        },
+        query="Who is Kasumi?",
+        docs=[
+            "Kasumi is a girl's name of Japanese origin meaning \"mist\".",
+            "Her music is a kawaii bass, a mix of future bass, pop, and kawaii music ",
+            "and she leads a team named PopiParty."
+        ],
+        score_threshold=0.8
+    )
+
+    assert isinstance(result, RerankResult)
+    assert len(result.docs) == 1
+    assert result.docs[0].index == 0
+    assert result.docs[0].score >= 0.8

api/tests/integration_tests/model_runtime/wenxin/test_embedding.py

@@ -0,0 +1,81 @@
+import os
+from time import sleep
+
+from core.model_runtime.entities.text_embedding_entities import TextEmbeddingResult
+from core.model_runtime.model_providers.wenxin.text_embedding.text_embedding import WenxinTextEmbeddingModel
+
+
+def test_invoke_embedding_v1():
+    sleep(3)
+    model = WenxinTextEmbeddingModel()
+
+    response = model.invoke(
+        model='embedding-v1',
+        credentials={
+            'api_key': os.environ.get('WENXIN_API_KEY'),
+            'secret_key': os.environ.get('WENXIN_SECRET_KEY')
+        },
+        texts=['hello', '你好', 'xxxxx'],
+        user="abc-123"
+    )
+
+    assert isinstance(response, TextEmbeddingResult)
+    assert len(response.embeddings) == 3
+    assert isinstance(response.embeddings[0], list)
+
+
+def test_invoke_embedding_bge_large_en():
+    sleep(3)
+    model = WenxinTextEmbeddingModel()
+
+    response = model.invoke(
+        model='bge-large-en',
+        credentials={
+            'api_key': os.environ.get('WENXIN_API_KEY'),
+            'secret_key': os.environ.get('WENXIN_SECRET_KEY')
+        },
+        texts=['hello', '你好', 'xxxxx'],
+        user="abc-123"
+    )
+
+    assert isinstance(response, TextEmbeddingResult)
+    assert len(response.embeddings) == 3
+    assert isinstance(response.embeddings[0], list)
+
+
+def test_invoke_embedding_bge_large_zh():
+    sleep(3)
+    model = WenxinTextEmbeddingModel()
+
+    response = model.invoke(
+        model='bge-large-zh',
+        credentials={
+            'api_key': os.environ.get('WENXIN_API_KEY'),
+            'secret_key': os.environ.get('WENXIN_SECRET_KEY')
+        },
+        texts=['hello', '你好', 'xxxxx'],
+        user="abc-123"
+    )
+
+    assert isinstance(response, TextEmbeddingResult)
+    assert len(response.embeddings) == 3
+    assert isinstance(response.embeddings[0], list)
+
+
+def test_invoke_embedding_tao_8k():
+    sleep(3)
+    model = WenxinTextEmbeddingModel()
+
+    response = model.invoke(
+        model='tao-8k',
+        credentials={
+            'api_key': os.environ.get('WENXIN_API_KEY'),
+            'secret_key': os.environ.get('WENXIN_SECRET_KEY')
+        },
+        texts=['hello', '你好', 'xxxxx'],
+        user="abc-123"
+    )
+
+    assert isinstance(response, TextEmbeddingResult)
+    assert len(response.embeddings) == 3
+    assert isinstance(response.embeddings[0], list)

api/tests/integration_tests/vdb/pgvector/test_pgvector.py

@@ -21,10 +21,6 @@ class PGVectorTest(AbstractVectorTest):
             ),
         )
 
-    def search_by_full_text(self):
-        hits_by_full_text: list[Document] = self.vector.search_by_full_text(query=get_example_text())
-        assert len(hits_by_full_text) == 0
-
 
 def test_pgvector(setup_mock_redis):
     PGVectorTest().run_all_tests()

api/tests/integration_tests/workflow/nodes/test_llm.py

@@ -12,7 +12,7 @@ from core.model_runtime.entities.model_entities import ModelType
 from core.model_runtime.model_providers import ModelProviderFactory
 from core.workflow.entities.node_entities import UserFrom
 from core.workflow.entities.variable_pool import VariablePool
-from core.workflow.enums import SystemVariable
+from core.workflow.enums import SystemVariableKey
 from core.workflow.nodes.llm.llm_node import LLMNode
 from extensions.ext_database import db
 from models.provider import ProviderType
@@ -66,10 +66,10 @@ def test_execute_llm(setup_openai_mock):
 
     # construct variable pool
     pool = VariablePool(system_variables={
-        SystemVariable.QUERY: 'what\'s the weather today?',
-        SystemVariable.FILES: [],
-        SystemVariable.CONVERSATION_ID: 'abababa',
-        SystemVariable.USER_ID: 'aaa'
+        SystemVariableKey.QUERY: 'what\'s the weather today?',
+        SystemVariableKey.FILES: [],
+        SystemVariableKey.CONVERSATION_ID: 'abababa',
+        SystemVariableKey.USER_ID: 'aaa'
     }, user_inputs={}, environment_variables=[])
     pool.add(['abc', 'output'], 'sunny')
 
@@ -181,10 +181,10 @@ def test_execute_llm_with_jinja2(setup_code_executor_mock, setup_openai_mock):
 
     # construct variable pool
     pool = VariablePool(system_variables={
-        SystemVariable.QUERY: 'what\'s the weather today?',
-        SystemVariable.FILES: [],
-        SystemVariable.CONVERSATION_ID: 'abababa',
-        SystemVariable.USER_ID: 'aaa'
+        SystemVariableKey.QUERY: 'what\'s the weather today?',
+        SystemVariableKey.FILES: [],
+        SystemVariableKey.CONVERSATION_ID: 'abababa',
+        SystemVariableKey.USER_ID: 'aaa'
     }, user_inputs={}, environment_variables=[])
     pool.add(['abc', 'output'], 'sunny')
 

api/tests/integration_tests/workflow/nodes/test_parameter_extractor.py

@@ -13,7 +13,7 @@ from core.model_runtime.entities.model_entities import ModelType
 from core.model_runtime.model_providers.model_provider_factory import ModelProviderFactory
 from core.workflow.entities.node_entities import UserFrom
 from core.workflow.entities.variable_pool import VariablePool
-from core.workflow.enums import SystemVariable
+from core.workflow.enums import SystemVariableKey
 from core.workflow.nodes.parameter_extractor.parameter_extractor_node import ParameterExtractorNode
 from extensions.ext_database import db
 from models.provider import ProviderType
@@ -118,10 +118,10 @@ def test_function_calling_parameter_extractor(setup_openai_mock):
 
     # construct variable pool
     pool = VariablePool(system_variables={
-        SystemVariable.QUERY: 'what\'s the weather in SF',
-        SystemVariable.FILES: [],
-        SystemVariable.CONVERSATION_ID: 'abababa',
-        SystemVariable.USER_ID: 'aaa'
+        SystemVariableKey.QUERY: 'what\'s the weather in SF',
+        SystemVariableKey.FILES: [],
+        SystemVariableKey.CONVERSATION_ID: 'abababa',
+        SystemVariableKey.USER_ID: 'aaa'
     }, user_inputs={}, environment_variables=[])
 
     result = node.run(pool)
@@ -176,10 +176,10 @@ def test_instructions(setup_openai_mock):
 
     # construct variable pool
     pool = VariablePool(system_variables={
-        SystemVariable.QUERY: 'what\'s the weather in SF',
-        SystemVariable.FILES: [],
-        SystemVariable.CONVERSATION_ID: 'abababa',
-        SystemVariable.USER_ID: 'aaa'
+        SystemVariableKey.QUERY: 'what\'s the weather in SF',
+        SystemVariableKey.FILES: [],
+        SystemVariableKey.CONVERSATION_ID: 'abababa',
+        SystemVariableKey.USER_ID: 'aaa'
     }, user_inputs={}, environment_variables=[])
 
     result = node.run(pool)
@@ -242,10 +242,10 @@ def test_chat_parameter_extractor(setup_anthropic_mock):
 
     # construct variable pool
     pool = VariablePool(system_variables={
-        SystemVariable.QUERY: 'what\'s the weather in SF',
-        SystemVariable.FILES: [],
-        SystemVariable.CONVERSATION_ID: 'abababa',
-        SystemVariable.USER_ID: 'aaa'
+        SystemVariableKey.QUERY: 'what\'s the weather in SF',
+        SystemVariableKey.FILES: [],
+        SystemVariableKey.CONVERSATION_ID: 'abababa',
+        SystemVariableKey.USER_ID: 'aaa'
     }, user_inputs={}, environment_variables=[])
 
     result = node.run(pool)
@@ -306,10 +306,10 @@ def test_completion_parameter_extractor(setup_openai_mock):
 
     # construct variable pool
     pool = VariablePool(system_variables={
-        SystemVariable.QUERY: 'what\'s the weather in SF',
-        SystemVariable.FILES: [],
-        SystemVariable.CONVERSATION_ID: 'abababa',
-        SystemVariable.USER_ID: 'aaa'
+        SystemVariableKey.QUERY: 'what\'s the weather in SF',
+        SystemVariableKey.FILES: [],
+        SystemVariableKey.CONVERSATION_ID: 'abababa',
+        SystemVariableKey.USER_ID: 'aaa'
     }, user_inputs={}, environment_variables=[])
 
     result = node.run(pool)
@@ -419,10 +419,10 @@ def test_chat_parameter_extractor_with_memory(setup_anthropic_mock):
 
     # construct variable pool
     pool = VariablePool(system_variables={
-        SystemVariable.QUERY: 'what\'s the weather in SF',
-        SystemVariable.FILES: [],
-        SystemVariable.CONVERSATION_ID: 'abababa',
-        SystemVariable.USER_ID: 'aaa'
+        SystemVariableKey.QUERY: 'what\'s the weather in SF',
+        SystemVariableKey.FILES: [],
+        SystemVariableKey.CONVERSATION_ID: 'abababa',
+        SystemVariableKey.USER_ID: 'aaa'
     }, user_inputs={}, environment_variables=[])
 
     result = node.run(pool)

api/tests/unit_tests/core/app/segments/test_segment.py

@@ -1,13 +1,13 @@
 from core.app.segments import SecretVariable, StringSegment, parser
 from core.helper import encrypter
 from core.workflow.entities.variable_pool import VariablePool
-from core.workflow.enums import SystemVariable
+from core.workflow.enums import SystemVariableKey
 
 
 def test_segment_group_to_text():
     variable_pool = VariablePool(
         system_variables={
-            SystemVariable('user_id'): 'fake-user-id',
+            SystemVariableKey('user_id'): 'fake-user-id',
         },
         user_inputs={},
         environment_variables=[
@@ -42,7 +42,7 @@ def test_convert_constant_to_segment_group():
 def test_convert_variable_to_segment_group():
     variable_pool = VariablePool(
         system_variables={
-            SystemVariable('user_id'): 'fake-user-id',
+            SystemVariableKey('user_id'): 'fake-user-id',
         },
         user_inputs={},
         environment_variables=[],

api/tests/unit_tests/core/model_runtime/model_providers/wenxin/test_text_embedding.py

@@ -0,0 +1,75 @@
+import numpy as np
+
+from core.model_runtime.entities.text_embedding_entities import TextEmbeddingResult
+from core.model_runtime.model_providers.__base.tokenizers.gpt2_tokenzier import GPT2Tokenizer
+from core.model_runtime.model_providers.wenxin.text_embedding.text_embedding import (
+    TextEmbedding,
+    WenxinTextEmbeddingModel,
+)
+
+
+def test_max_chunks():
+    class _MockTextEmbedding(TextEmbedding):
+        def embed_documents(self, model: str, texts: list[str], user: str) -> (list[list[float]], int, int):
+            embeddings = [[1.0, 2.0, 3.0] for i in range(len(texts))]
+            tokens = 0
+            for text in texts:
+                tokens += len(text)
+
+            return embeddings, tokens, tokens
+
+    def _create_text_embedding(api_key: str, secret_key: str) -> TextEmbedding:
+        return _MockTextEmbedding()
+
+    model = 'embedding-v1'
+    credentials = {
+        'api_key': 'xxxx',
+        'secret_key': 'yyyy',
+    }
+    embedding_model = WenxinTextEmbeddingModel()
+    context_size = embedding_model._get_context_size(model, credentials)
+    max_chunks = embedding_model._get_max_chunks(model, credentials)
+    embedding_model._create_text_embedding = _create_text_embedding
+
+    texts = ['0123456789' for i in range(0, max_chunks * 2)]
+    result: TextEmbeddingResult = embedding_model.invoke(model, credentials, texts, 'test')
+    assert len(result.embeddings) == max_chunks * 2
+
+
+def test_context_size():
+    def get_num_tokens_by_gpt2(text: str) -> int:
+        return GPT2Tokenizer.get_num_tokens(text)
+
+    def mock_text(token_size: int) -> str:
+        _text = "".join(['0' for i in range(token_size)])
+        num_tokens = get_num_tokens_by_gpt2(_text)
+        ratio = int(np.floor(len(_text) / num_tokens))
+        m_text = "".join([_text for i in range(ratio)])
+        return m_text
+
+    model = 'embedding-v1'
+    credentials = {
+        'api_key': 'xxxx',
+        'secret_key': 'yyyy',
+    }
+    embedding_model = WenxinTextEmbeddingModel()
+    context_size = embedding_model._get_context_size(model, credentials)
+
+    class _MockTextEmbedding(TextEmbedding):
+        def embed_documents(self, model: str, texts: list[str], user: str) -> (list[list[float]], int, int):
+            embeddings = [[1.0, 2.0, 3.0] for i in range(len(texts))]
+            tokens = 0
+            for text in texts:
+                tokens += get_num_tokens_by_gpt2(text)
+            return embeddings, tokens, tokens
+
+    def _create_text_embedding(api_key: str, secret_key: str) -> TextEmbedding:
+        return _MockTextEmbedding()
+
+    embedding_model._create_text_embedding = _create_text_embedding
+    text = mock_text(context_size * 2)
+    assert get_num_tokens_by_gpt2(text) == context_size * 2
+
+    texts = [text]
+    result: TextEmbeddingResult = embedding_model.invoke(model, credentials, texts, 'test')
+    assert result.usage.tokens == context_size

api/tests/unit_tests/core/workflow/nodes/test_answer.py

@@ -5,7 +5,7 @@ from unittest.mock import MagicMock
 from core.app.entities.app_invoke_entities import InvokeFrom
 from core.workflow.entities.node_entities import UserFrom
 from core.workflow.entities.variable_pool import VariablePool
-from core.workflow.enums import SystemVariable
+from core.workflow.enums import SystemVariableKey
 from core.workflow.graph_engine.entities.graph import Graph
 from core.workflow.graph_engine.entities.graph_init_params import GraphInitParams
 from core.workflow.graph_engine.entities.graph_runtime_state import GraphRuntimeState
@@ -60,8 +60,8 @@ def test_execute_answer():
     # construct variable pool
     variable_pool = VariablePool(
         system_variables={
-            SystemVariable.FILES: [],
-            SystemVariable.USER_ID: 'aaa'
+            SystemVariableKey.FILES: [],
+            SystemVariableKey.USER_ID: 'aaa'
         },
         user_inputs={},
         environment_variables=[],
@@ -88,6 +88,14 @@ def test_execute_answer():
         }
     )
 
+    # construct variable pool
+    pool = VariablePool(system_variables={
+        SystemVariable.FILES: [],
+        SystemVariable.USER_ID: 'aaa'
+    }, user_inputs={}, environment_variables=[])
+    pool.add(['start', 'weather'], 'sunny')
+    pool.add(['llm', 'text'], 'You are a helpful AI.')
+
     # Mock db.session.close()
     db.session.close = MagicMock()
 

api/tests/unit_tests/core/workflow/nodes/test_if_else.py

@@ -5,7 +5,7 @@ from unittest.mock import MagicMock
 from core.app.entities.app_invoke_entities import InvokeFrom
 from core.workflow.entities.node_entities import UserFrom
 from core.workflow.entities.variable_pool import VariablePool
-from core.workflow.enums import SystemVariable
+from core.workflow.enums import SystemVariableKey
 from core.workflow.graph_engine.entities.graph import Graph
 from core.workflow.graph_engine.entities.graph_init_params import GraphInitParams
 from core.workflow.graph_engine.entities.graph_runtime_state import GraphRuntimeState
@@ -45,8 +45,8 @@ def test_execute_if_else_result_true():
 
     # construct variable pool
     pool = VariablePool(system_variables={
-        SystemVariable.FILES: [],
-        SystemVariable.USER_ID: 'aaa'
+        SystemVariableKey.FILES: [],
+        SystemVariableKey.USER_ID: 'aaa'
     }, user_inputs={})
     pool.add(['start', 'array_contains'], ['ab', 'def'])
     pool.add(['start', 'array_not_contains'], ['ac', 'def'])
@@ -176,8 +176,8 @@ def test_execute_if_else_result_true():
 
     # construct variable pool
     pool = VariablePool(system_variables={
-        SystemVariable.FILES: [],
-        SystemVariable.USER_ID: 'aaa'
+        SystemVariableKey.FILES: [],
+        SystemVariableKey.USER_ID: 'aaa'
     }, user_inputs={}, environment_variables=[])
     pool.add(['start', 'array_contains'], ['ab', 'def'])
     pool.add(['start', 'array_not_contains'], ['ac', 'def'])
@@ -250,8 +250,8 @@ def test_execute_if_else_result_false():
 
     # construct variable pool
     pool = VariablePool(system_variables={
-        SystemVariable.FILES: [],
-        SystemVariable.USER_ID: 'aaa'
+        SystemVariableKey.FILES: [],
+        SystemVariableKey.USER_ID: 'aaa'
     }, user_inputs={}, environment_variables=[])
     pool.add(['start', 'array_contains'], ['1ab', 'def'])
     pool.add(['start', 'array_not_contains'], ['ab', 'def'])

api/tests/unit_tests/core/workflow/nodes/test_variable_assigner.py

@@ -7,7 +7,7 @@ from core.app.entities.app_invoke_entities import InvokeFrom
 from core.app.segments import ArrayStringVariable, StringVariable
 from core.workflow.entities.node_entities import UserFrom
 from core.workflow.entities.variable_pool import VariablePool
-from core.workflow.enums import SystemVariable
+from core.workflow.enums import SystemVariableKey
 from core.workflow.graph_engine.entities.graph import Graph
 from core.workflow.graph_engine.entities.graph_init_params import GraphInitParams
 from core.workflow.graph_engine.entities.graph_runtime_state import GraphRuntimeState
@@ -72,7 +72,7 @@ def test_overwrite_string_variable():
 
     # construct variable pool
     variable_pool = VariablePool(
-        system_variables={SystemVariable.CONVERSATION_ID: 'conversation_id'},
+        system_variables={SystemVariableKey.CONVERSATION_ID: 'conversation_id'},
         user_inputs={},
         environment_variables=[],
         conversation_variables=[conversation_variable],
@@ -101,7 +101,7 @@ def test_overwrite_string_variable():
         },
     )
 
-    with mock.patch('core.workflow.nodes.variable_assigner.update_conversation_variable') as mock_run:
+    with mock.patch('core.workflow.nodes.variable_assigner.node.update_conversation_variable') as mock_run:
         list(node.run())
         mock_run.assert_called_once()
 
@@ -165,7 +165,7 @@ def test_append_variable_to_array():
     )
 
     variable_pool = VariablePool(
-        system_variables={SystemVariable.CONVERSATION_ID: 'conversation_id'},
+        system_variables={SystemVariableKey.CONVERSATION_ID: 'conversation_id'},
         user_inputs={},
         environment_variables=[],
         conversation_variables=[conversation_variable],
@@ -193,7 +193,7 @@ def test_append_variable_to_array():
         },
     )
 
-    with mock.patch('core.workflow.nodes.variable_assigner.update_conversation_variable') as mock_run:
+    with mock.patch('core.workflow.nodes.variable_assigner.node.update_conversation_variable') as mock_run:
         list(node.run())
         mock_run.assert_called_once()
 
@@ -250,7 +250,7 @@ def test_clear_array():
     )
 
     variable_pool = VariablePool(
-        system_variables={SystemVariable.CONVERSATION_ID: 'conversation_id'},
+        system_variables={SystemVariableKey.CONVERSATION_ID: 'conversation_id'},
         user_inputs={},
         environment_variables=[],
         conversation_variables=[conversation_variable],

api/tests/unit_tests/models/test_workflow.py

@@ -11,7 +11,17 @@ def test_environment_variables():
     contexts.tenant_id.set('tenant_id')
 
     # Create a Workflow instance
-    workflow = Workflow()
+    workflow = Workflow(
+        tenant_id='tenant_id',
+        app_id='app_id',
+        type='workflow',
+        version='draft',
+        graph='{}',
+        features='{}',
+        created_by='account_id',
+        environment_variables=[],
+        conversation_variables=[],
+    )
 
     # Create some EnvironmentVariable instances
     variable1 = StringVariable.model_validate({'name': 'var1', 'value': 'value1', 'id': str(uuid4())})
@@ -35,7 +45,17 @@ def test_update_environment_variables():
     contexts.tenant_id.set('tenant_id')
 
     # Create a Workflow instance
-    workflow = Workflow()
+    workflow = Workflow(
+        tenant_id='tenant_id',
+        app_id='app_id',
+        type='workflow',
+        version='draft',
+        graph='{}',
+        features='{}',
+        created_by='account_id',
+        environment_variables=[],
+        conversation_variables=[],
+    )
 
     # Create some EnvironmentVariable instances
     variable1 = StringVariable.model_validate({'name': 'var1', 'value': 'value1', 'id': str(uuid4())})
@@ -70,9 +90,17 @@ def test_to_dict():
     contexts.tenant_id.set('tenant_id')
 
     # Create a Workflow instance
-    workflow = Workflow()
-    workflow.graph = '{}'
-    workflow.features = '{}'
+    workflow = Workflow(
+        tenant_id='tenant_id',
+        app_id='app_id',
+        type='workflow',
+        version='draft',
+        graph='{}',
+        features='{}',
+        created_by='account_id',
+        environment_variables=[],
+        conversation_variables=[],
+    )
 
     # Create some EnvironmentVariable instances
 

api/tests/unit_tests/services/workflow/test_workflow_converter.py

@@ -14,6 +14,7 @@ from core.app.app_config.entities import (
     ModelConfigEntity,
     PromptTemplateEntity,
     VariableEntity,
+    VariableEntityType,
 )
 from core.helper import encrypter
 from core.model_runtime.entities.llm_entities import LLMMode
@@ -25,23 +26,24 @@ from services.workflow.workflow_converter import WorkflowConverter
 
 @pytest.fixture
 def default_variables():
-    return [
+    value = [
         VariableEntity(
             variable="text_input",
             label="text-input",
-            type=VariableEntity.Type.TEXT_INPUT
+            type=VariableEntityType.TEXT_INPUT,
         ),
         VariableEntity(
             variable="paragraph",
             label="paragraph",
-            type=VariableEntity.Type.PARAGRAPH
+            type=VariableEntityType.PARAGRAPH,
         ),
         VariableEntity(
             variable="select",
             label="select",
-            type=VariableEntity.Type.SELECT
-        )
+            type=VariableEntityType.SELECT,
+        ),
     ]
+    return value
 
 
 def test__convert_to_start_node(default_variables):

api/tests/unit_tests/utils/position_helper/test_position_helper.py

@@ -2,7 +2,7 @@ from textwrap import dedent
 
 import pytest
 
-from core.helper.position_helper import get_position_map
+from core.helper.position_helper import get_position_map, is_filtered, pin_position_map, sort_by_position_map
 
 
 @pytest.fixture
@@ -14,7 +14,7 @@ def prepare_example_positions_yaml(tmp_path, monkeypatch) -> str:
         - second
         # - commented
         - third
-        
+
         - 9999999999999
         - forth
         """))
@@ -28,9 +28,9 @@ def prepare_empty_commented_positions_yaml(tmp_path, monkeypatch) -> str:
         """\
         # - commented1
         # - commented2
-        - 
-        -   
-        
+        -
+        -
+
         """))
     return str(tmp_path)
 
@@ -53,3 +53,79 @@ def test_position_helper_with_all_commented(prepare_empty_commented_positions_ya
         folder_path=prepare_empty_commented_positions_yaml,
         file_name='example_positions_all_commented.yaml')
     assert position_map == {}
+
+
+def test_excluded_position_data(prepare_example_positions_yaml):
+    position_map = get_position_map(
+        folder_path=prepare_example_positions_yaml,
+        file_name='example_positions.yaml'
+    )
+    pin_list = ['forth', 'first']
+    include_set = set()
+    exclude_set = {'9999999999999'}
+
+    position_map = pin_position_map(
+        original_position_map=position_map,
+        pin_list=pin_list
+    )
+
+    data = [
+        "forth",
+        "first",
+        "second",
+        "third",
+        "9999999999999",
+        "extra1",
+        "extra2",
+    ]
+
+    # filter out the data
+    data = [item for item in data if not is_filtered(include_set, exclude_set, item, lambda x: x)]
+
+    # sort data by position map
+    sorted_data = sort_by_position_map(
+        position_map=position_map,
+        data=data,
+        name_func=lambda x: x,
+    )
+
+    # assert the result in the correct order
+    assert sorted_data == ['forth', 'first', 'second', 'third', 'extra1', 'extra2']
+
+
+def test_included_position_data(prepare_example_positions_yaml):
+    position_map = get_position_map(
+        folder_path=prepare_example_positions_yaml,
+        file_name='example_positions.yaml'
+    )
+    pin_list = ['forth', 'first']
+    include_set = {'forth', 'first'}
+    exclude_set = {}
+
+    position_map = pin_position_map(
+        original_position_map=position_map,
+        pin_list=pin_list
+    )
+
+    data = [
+        "forth",
+        "first",
+        "second",
+        "third",
+        "9999999999999",
+        "extra1",
+        "extra2",
+    ]
+
+    # filter out the data
+    data = [item for item in data if not is_filtered(include_set, exclude_set, item, lambda x: x)]
+
+    # sort data by position map
+    sorted_data = sort_by_position_map(
+        position_map=position_map,
+        data=data,
+        name_func=lambda x: x,
+    )
+
+    # assert the result in the correct order
+    assert sorted_data == ['forth', 'first']