feat: add dump and dumps methods to Graph (#3202)
* feat(utils.py): add escape_json_dump function to escape JSON strings for Edge dictionaries * refactor(Output): streamline add_types method to prevent duplicate entries in types list for improved type management * feat(data.py): add classmethod decorator to validate_data for enhanced validation logic when checking data types * feat(setup.py): implement retry logic for loading starter projects to enhance robustness against JSON decode errors * fix(input_mixin.py): improve model_config formatting and update field_type alias for clarity and consistency in field definitions * feat(types.py): refactor vertex constructors to use NodeData and add input/output methods for better component interaction * feat(schema.py): add NodeData and Position TypedDicts for improved type safety and structure in vertex data handling * feat(base.py): update Vertex to use NodeData type and add to_data method for better data management and access * refactor(schema.py): update TargetHandle and SourceHandle models to include model_config attribute * Add TypedDict classes for graph schema serialization in `schema.py` * Refactor `Edge` class to improve handle validation and data handling - Consolidated imports and removed redundant `BaseModel` definitions for `SourceHandle` and `TargetHandle`. - Added `valid_handles`, `target_param`, and `_target_handle` attributes to `Edge` class. - Enhanced handle validation logic to distinguish between dictionary and string types. - Introduced `to_data` method to return edge data. - Updated attribute names to follow consistent naming conventions (`base_classes`, `input_types`, `field_name`). * Refactor `Edge` class to improve handle validation and data handling * Refactor: Standardize attribute naming and add `to_data` method in Edge class - Renamed attributes to use snake_case consistently (`baseClasses` to `base_classes`, `inputTypes` to `input_types`, `fieldName` to `field_name`). - Added `to_data` method to return `_data` attribute. - Updated validation methods to use new attribute names. * Refactor: Update Edge class to consistently use snake_case for attributes and improve validation logic for handles * Refactor: Change node argument type in add_node and _create_vertex methods to NodeData for better type safety and clarity * Refactor: Implement JSON serialization for graph data with `dumps` and `dump` methods, enhancing data export capabilities * Refactor: Add pytest fixtures for ingestion and RAG graphs, enhance test structure for better clarity and organization * Refactor: Add pytest fixtures for memory_chatbot_graph tests and improve test structure * Refactor: Remove unused methods in ComponentVertex class to streamline code and improve readability * Refactor: Remove unnecessary line in ComponentVertex class to enhance code clarity and maintainability * Refactor: Update import path for DefaultPromptField to improve code organization and maintainability in api_utils.py * Refactor: Update import path for DefaultPromptField to enhance code organization and maintainability in prompt.py * fix: Remove fixture in test_memory_chatbot.py that blocked db setup * Refactor: Add durations path for unit tests to improve test reporting * Refactor: Add splitting algorithm option for unit tests * Add async option to Makefile for unit tests and update GitHub Actions workflow - Introduced `async` variable in Makefile to conditionally run unit tests with or without parallel execution. - Updated `unit_tests` target in Makefile to handle `async` flag. - Modified GitHub Actions workflow to set `async=false` for unit tests.
This commit is contained in:
Gabriel Luiz Freitas Almeida
GitHub
parent
8ece1cadf6
commit
bb1bc5c2df
19 changed files with 797 additions and 107 deletions
2
.github/workflows/python_test.yml
vendored
2
.github/workflows/python_test.yml
vendored
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@ -50,7 +50,7 @@ jobs:
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with:
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timeout_minutes: 12
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max_attempts: 2
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command: make unit_tests args="--splits ${{ matrix.splitCount }} --group ${{ matrix.group }}"
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command: make unit_tests async=false args="--splits ${{ matrix.splitCount }} --group ${{ matrix.group }}"
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test-cli:
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name: Test CLI - Python ${{ matrix.python-version }}
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17
Makefile
17
Makefile
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@ -18,7 +18,7 @@ env ?= .env
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open_browser ?= true
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path = src/backend/base/langflow/frontend
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workers ?= 1
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async ?= true
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all: help
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######################
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@ -130,14 +130,25 @@ coverage: ## run the tests and generate a coverage report
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@poetry run coverage erase
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unit_tests: ## run unit tests
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ifeq ($(async), true)
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poetry run pytest src/backend/tests \
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--ignore=src/backend/tests/integration \
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--instafail -ra -n auto -m "not api_key_required" \
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--instafail -n auto -ra -m "not api_key_required" \
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--durations-path src/backend/tests/.test_durations \
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--splitting-algorithm least_duration \
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$(args)
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else
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poetry run pytest src/backend/tests \
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--ignore=src/backend/tests/integration \
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--instafail -ra -m "not api_key_required" \
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--durations-path src/backend/tests/.test_durations \
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--splitting-algorithm least_duration \
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$(args)
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endif
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integration_tests: ## run integration tests
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poetry run pytest src/backend/tests/integration \
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--instafail -ra -n auto \
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--instafail -ra \
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$(args)
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tests: ## run unit, integration, coverage tests
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@ -6,7 +6,7 @@ from langchain_core.prompts import PromptTemplate
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from loguru import logger
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from langflow.interface.utils import extract_input_variables_from_prompt
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from langflow.template.field.prompt import DefaultPromptField
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from langflow.inputs.inputs import DefaultPromptField
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_INVALID_CHARACTERS = {
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@ -1,51 +1,31 @@
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from typing import TYPE_CHECKING, Any, List, Optional, cast
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from typing import TYPE_CHECKING, Any, cast
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from loguru import logger
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from pydantic import BaseModel, Field, field_validator
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from langflow.graph.edge.schema import EdgeData
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from langflow.graph.edge.schema import EdgeData, SourceHandle, TargetHandle, TargetHandleDict
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from langflow.schema.schema import INPUT_FIELD_NAME
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if TYPE_CHECKING:
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from langflow.graph.vertex.base import Vertex
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class SourceHandle(BaseModel):
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baseClasses: list[str] = Field(default_factory=list, description="List of base classes for the source handle.")
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dataType: str = Field(..., description="Data type for the source handle.")
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id: str = Field(..., description="Unique identifier for the source handle.")
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name: Optional[str] = Field(None, description="Name of the source handle.")
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output_types: List[str] = Field(default_factory=list, description="List of output types for the source handle.")
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@field_validator("name", mode="before")
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@classmethod
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def validate_name(cls, v, _info):
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if _info.data["dataType"] == "GroupNode":
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# 'OpenAIModel-u4iGV_text_output'
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splits = v.split("_", 1)
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if len(splits) != 2:
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raise ValueError(f"Invalid source handle name {v}")
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v = splits[1]
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return v
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class TargetHandle(BaseModel):
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fieldName: str = Field(..., description="Field name for the target handle.")
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id: str = Field(..., description="Unique identifier for the target handle.")
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inputTypes: Optional[List[str]] = Field(None, description="List of input types for the target handle.")
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type: str = Field(..., description="Type of the target handle.")
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class Edge:
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def __init__(self, source: "Vertex", target: "Vertex", edge: EdgeData):
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self.source_id: str = source.id if source else ""
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self.target_id: str = target.id if target else ""
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self.valid_handles: bool = False
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self.target_param: str | None = None
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self._target_handle: TargetHandleDict | str | None = None
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self._data = edge.copy()
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if data := edge.get("data", {}):
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self._source_handle = data.get("sourceHandle", {})
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self._target_handle = data.get("targetHandle", {})
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self._target_handle = cast(TargetHandleDict, data.get("targetHandle", {}))
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self.source_handle: SourceHandle = SourceHandle(**self._source_handle)
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self.target_handle: TargetHandle = TargetHandle(**self._target_handle)
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self.target_param = self.target_handle.fieldName
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if isinstance(self._target_handle, dict):
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self.target_handle: TargetHandle = TargetHandle(**self._target_handle)
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else:
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raise ValueError("Target handle is not a dictionary")
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self.target_param = self.target_handle.field_name
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# validate handles
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self.validate_handles(source, target)
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else:
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@ -55,23 +35,31 @@ class Edge:
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self._target_handle = edge.get("targetHandle", "") # type: ignore
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# 'BaseLoader;BaseOutputParser|documents|PromptTemplate-zmTlD'
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# target_param is documents
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self.target_param = cast(str, self._target_handle.split("|")[1]) # type: ignore
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if isinstance(self._target_handle, str):
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self.target_param = self._target_handle.split("|")[1]
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self.source_handle = None
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self.target_handle = None
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else:
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raise ValueError("Target handle is not a string")
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# Validate in __init__ to fail fast
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self.validate_edge(source, target)
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def to_data(self):
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return self._data
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def validate_handles(self, source, target) -> None:
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if isinstance(self._source_handle, str) or self.source_handle.baseClasses:
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if isinstance(self._source_handle, str) or self.source_handle.base_classes:
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self._legacy_validate_handles(source, target)
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else:
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self._validate_handles(source, target)
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def _validate_handles(self, source, target) -> None:
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if self.target_handle.inputTypes is None:
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if self.target_handle.input_types is None:
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self.valid_handles = self.target_handle.type in self.source_handle.output_types
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elif self.source_handle.output_types is not None:
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self.valid_handles = (
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any(output_type in self.target_handle.inputTypes for output_type in self.source_handle.output_types)
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any(output_type in self.target_handle.input_types for output_type in self.source_handle.output_types)
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or self.target_handle.type in self.source_handle.output_types
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)
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@ -81,12 +69,12 @@ class Edge:
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raise ValueError(f"Edge between {source.vertex_type} and {target.vertex_type} " f"has invalid handles")
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def _legacy_validate_handles(self, source, target) -> None:
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if self.target_handle.inputTypes is None:
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self.valid_handles = self.target_handle.type in self.source_handle.baseClasses
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if self.target_handle.input_types is None:
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self.valid_handles = self.target_handle.type in self.source_handle.base_classes
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else:
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self.valid_handles = (
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any(baseClass in self.target_handle.inputTypes for baseClass in self.source_handle.baseClasses)
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or self.target_handle.type in self.source_handle.baseClasses
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any(baseClass in self.target_handle.input_types for baseClass in self.source_handle.base_classes)
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or self.target_handle.type in self.source_handle.base_classes
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)
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if not self.valid_handles:
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logger.debug(self.source_handle)
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@ -101,9 +89,9 @@ class Edge:
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self.target_handle = state.get("target_handle")
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def validate_edge(self, source, target) -> None:
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# If the self.source_handle has baseClasses, then we are using the legacy
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# If the self.source_handle has base_classes, then we are using the legacy
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# way of defining the source and target handles
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if isinstance(self._source_handle, str) or self.source_handle.baseClasses:
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if isinstance(self._source_handle, str) or self.source_handle.base_classes:
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self._legacy_validate_edge(source, target)
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else:
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self._validate_edge(source, target)
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@ -230,5 +218,5 @@ class ContractEdge(Edge):
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if (hasattr(self, "source_handle") and self.source_handle) and (
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hasattr(self, "target_handle") and self.target_handle
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):
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return f"{self.source_id} -[{self.source_handle.name}->{self.target_handle.fieldName}]-> {self.target_id}"
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return f"{self.source_id} -[{self.source_handle.name}->{self.target_handle.field_name}]-> {self.target_id}"
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return f"{self.source_id} -[{self.target_param}]-> {self.target_id}"
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@ -1,6 +1,6 @@
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from typing import Any, List, Optional
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from pydantic import Field, field_validator
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from pydantic import ConfigDict, Field, field_validator
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from typing_extensions import TypedDict
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from langflow.helpers.base_model import BaseModel
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@ -39,7 +39,8 @@ class Payload(BaseModel):
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class TargetHandle(BaseModel):
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fieldName: str = Field(..., alias="fieldName", description="Field name for the target handle.")
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model_config = ConfigDict(populate_by_name=True)
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field_name: str = Field(..., alias="fieldName", description="Field name for the target handle.")
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id: str = Field(..., description="Unique identifier for the target handle.")
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input_types: List[str] = Field(
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default_factory=list, alias="inputTypes", description="List of input types for the target handle."
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@ -48,6 +49,7 @@ class TargetHandle(BaseModel):
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class SourceHandle(BaseModel):
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model_config = ConfigDict(populate_by_name=True)
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base_classes: list[str] = Field(
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default_factory=list, alias="baseClasses", description="List of base classes for the source handle."
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)
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@ -1,4 +1,5 @@
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import asyncio
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import json
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import uuid
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from collections import defaultdict, deque
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from datetime import datetime, timezone
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@ -14,11 +15,12 @@ from langflow.graph.edge.base import ContractEdge
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from langflow.graph.edge.schema import EdgeData
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from langflow.graph.graph.constants import Finish, lazy_load_vertex_dict
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from langflow.graph.graph.runnable_vertices_manager import RunnableVerticesManager
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from langflow.graph.graph.schema import VertexBuildResult
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from langflow.graph.graph.schema import GraphData, GraphDump, VertexBuildResult
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from langflow.graph.graph.state_manager import GraphStateManager
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from langflow.graph.graph.utils import find_start_component_id, process_flow, sort_up_to_vertex
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from langflow.graph.schema import InterfaceComponentTypes, RunOutputs
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from langflow.graph.vertex.base import Vertex, VertexStates
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from langflow.graph.vertex.schema import NodeData
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from langflow.graph.vertex.types import ComponentVertex, InterfaceVertex, StateVertex
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from langflow.schema import Data
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from langflow.schema.schema import INPUT_FIELD_NAME, InputType
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@ -75,7 +77,7 @@ class Graph:
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self.vertices: List[Vertex] = []
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self.run_manager = RunnableVerticesManager()
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self.state_manager = GraphStateManager()
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self._vertices: List[dict] = []
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self._vertices: List[NodeData] = []
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self._edges: List[EdgeData] = []
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self.top_level_vertices: List[str] = []
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self.vertex_map: Dict[str, Vertex] = {}
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@ -86,6 +88,7 @@ class Graph:
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self._run_queue: deque[str] = deque()
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self._first_layer: List[str] = []
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self._lock = asyncio.Lock()
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self.raw_graph_data: GraphData = {"nodes": [], "edges": []}
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try:
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self.tracing_service: "TracingService" | None = get_tracing_service()
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except Exception as exc:
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@ -97,7 +100,39 @@ class Graph:
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if (start is not None and end is None) or (start is None and end is not None):
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raise ValueError("You must provide both input and output components")
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def add_nodes_and_edges(self, nodes: List[Dict], edges: List[EdgeData]):
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def dumps(
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self,
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name: Optional[str] = None,
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description: Optional[str] = None,
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endpoint_name: Optional[str] = None,
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) -> str:
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graph_dict = self.dump(name, description, endpoint_name)
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return json.dumps(graph_dict, indent=4, sort_keys=True)
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def dump(
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self, name: Optional[str] = None, description: Optional[str] = None, endpoint_name: Optional[str] = None
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) -> GraphDump:
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if self.raw_graph_data != {"nodes": [], "edges": []}:
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data_dict = self.raw_graph_data
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else:
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# we need to convert the vertices and edges to json
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nodes = [node.to_data() for node in self.vertices]
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edges = [edge.to_data() for edge in self.edges]
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self.raw_graph_data = {"nodes": nodes, "edges": edges}
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data_dict = self.raw_graph_data
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graph_dict: GraphDump = {
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"data": data_dict,
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"is_component": len(data_dict.get("nodes", [])) == 1 and data_dict["edges"] == [],
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}
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if name:
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graph_dict["name"] = name
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if description:
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graph_dict["description"] = description
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if endpoint_name:
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graph_dict["endpoint_name"] = endpoint_name
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return graph_dict
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def add_nodes_and_edges(self, nodes: List[NodeData], edges: List[EdgeData]):
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self._vertices = nodes
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self._edges = edges
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self.raw_graph_data = {"nodes": nodes, "edges": edges}
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@ -183,7 +218,7 @@ class Graph:
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return
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def start(self, inputs: Optional[List[dict]] = None) -> Generator:
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#! Change this soon
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#! Change this ASAP
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nest_asyncio.apply()
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loop = asyncio.get_event_loop()
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async_gen = self.async_start(inputs)
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@ -208,8 +243,7 @@ class Graph:
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self.in_degree_map[target_id] += 1
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self.parent_child_map[source_id].append(target_id)
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# TODO: Create a TypedDict to represente the node
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def add_node(self, node: dict):
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def add_node(self, node: NodeData):
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self._vertices.append(node)
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def add_edge(self, edge: EdgeData):
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@ -1400,7 +1434,7 @@ class Graph:
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return vertices
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def _create_vertex(self, frontend_data: dict):
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def _create_vertex(self, frontend_data: NodeData):
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vertex_data = frontend_data["data"]
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vertex_type: str = vertex_data["type"] # type: ignore
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vertex_base_type: str = vertex_data["node"]["template"]["_type"] # type: ignore
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|
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@ -1,10 +1,35 @@
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from typing import TYPE_CHECKING, NamedTuple
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from typing_extensions import NotRequired, TypedDict
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from langflow.graph.edge.schema import EdgeData
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from langflow.graph.vertex.schema import NodeData
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if TYPE_CHECKING:
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from langflow.graph.schema import ResultData
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from langflow.graph.vertex.base import Vertex
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class ViewPort(TypedDict):
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x: float
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y: float
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zoom: float
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class GraphData(TypedDict):
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nodes: list[NodeData]
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edges: list[EdgeData]
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viewport: NotRequired[ViewPort]
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class GraphDump(TypedDict, total=False):
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data: GraphData
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is_component: bool
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name: str
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description: str
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endpoint_name: str
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|
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class VertexBuildResult(NamedTuple):
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result_dict: "ResultData"
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params: str
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|
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@ -13,6 +13,7 @@ from loguru import logger
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from langflow.exceptions.component import ComponentBuildException
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from langflow.graph.schema import INPUT_COMPONENTS, OUTPUT_COMPONENTS, InterfaceComponentTypes, ResultData
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from langflow.graph.utils import UnbuiltObject, UnbuiltResult, log_transaction
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||||
from langflow.graph.vertex.schema import NodeData
|
||||
from langflow.interface.initialize import loading
|
||||
from langflow.interface.listing import lazy_load_dict
|
||||
from langflow.schema.artifact import ArtifactType
|
||||
|
|
@ -42,7 +43,7 @@ class VertexStates(str, Enum):
|
|||
class Vertex:
|
||||
def __init__(
|
||||
self,
|
||||
data: Dict,
|
||||
data: NodeData,
|
||||
graph: "Graph",
|
||||
base_type: Optional[str] = None,
|
||||
is_task: bool = False,
|
||||
|
|
@ -63,7 +64,7 @@ class Vertex:
|
|||
self.has_external_input = False
|
||||
self.has_external_output = False
|
||||
self.graph = graph
|
||||
self._data = data
|
||||
self._data = data.copy()
|
||||
self.base_type: Optional[str] = base_type
|
||||
self.outputs: List[Dict] = []
|
||||
self._parse_data()
|
||||
|
|
@ -101,6 +102,9 @@ class Vertex:
|
|||
raise ValueError(f"Vertex {self.id} does not have a component instance.")
|
||||
self._custom_component._set_input_value(name, value)
|
||||
|
||||
def to_data(self):
|
||||
return self._data
|
||||
|
||||
def add_component_instance(self, component_instance: "Component"):
|
||||
component_instance.set_vertex(self)
|
||||
self._custom_component = component_instance
|
||||
|
|
|
|||
21
src/backend/base/langflow/graph/vertex/schema.py
Normal file
21
src/backend/base/langflow/graph/vertex/schema.py
Normal file
|
|
@ -0,0 +1,21 @@
|
|||
from typing import Dict
|
||||
|
||||
from typing_extensions import NotRequired, TypedDict
|
||||
|
||||
|
||||
class Position(TypedDict):
|
||||
x: float
|
||||
y: float
|
||||
|
||||
|
||||
class NodeData(TypedDict):
|
||||
id: str
|
||||
data: Dict
|
||||
dragging: NotRequired[bool]
|
||||
height: NotRequired[int]
|
||||
width: NotRequired[int]
|
||||
position: NotRequired[Position]
|
||||
positionAbsolute: NotRequired[Position]
|
||||
selected: NotRequired[bool]
|
||||
parent_node_id: NotRequired[str]
|
||||
type: str
|
||||
|
|
@ -9,6 +9,7 @@ from loguru import logger
|
|||
from langflow.graph.schema import CHAT_COMPONENTS, RECORDS_COMPONENTS, InterfaceComponentTypes, ResultData
|
||||
from langflow.graph.utils import UnbuiltObject, log_transaction, log_vertex_build, serialize_field
|
||||
from langflow.graph.vertex.base import Vertex
|
||||
from langflow.graph.vertex.schema import NodeData
|
||||
from langflow.inputs.inputs import InputTypes
|
||||
from langflow.schema import Data
|
||||
from langflow.schema.artifact import ArtifactType
|
||||
|
|
@ -23,7 +24,7 @@ if TYPE_CHECKING:
|
|||
|
||||
|
||||
class CustomComponentVertex(Vertex):
|
||||
def __init__(self, data: Dict, graph):
|
||||
def __init__(self, data: NodeData, graph):
|
||||
super().__init__(data, graph=graph, base_type="custom_components")
|
||||
|
||||
def _built_object_repr(self):
|
||||
|
|
@ -32,9 +33,19 @@ class CustomComponentVertex(Vertex):
|
|||
|
||||
|
||||
class ComponentVertex(Vertex):
|
||||
def __init__(self, data: Dict, graph):
|
||||
def __init__(self, data: NodeData, graph):
|
||||
super().__init__(data, graph=graph, base_type="component")
|
||||
|
||||
def get_input(self, name: str) -> InputTypes:
|
||||
if self._custom_component is None:
|
||||
raise ValueError(f"Vertex {self.id} does not have a component instance.")
|
||||
return self._custom_component.get_input(name)
|
||||
|
||||
def get_output(self, name: str) -> Output:
|
||||
if self._custom_component is None:
|
||||
raise ValueError(f"Vertex {self.id} does not have a component instance.")
|
||||
return self._custom_component.get_output(name)
|
||||
|
||||
def _built_object_repr(self):
|
||||
if self.artifacts and "repr" in self.artifacts:
|
||||
return self.artifacts["repr"] or super()._built_object_repr()
|
||||
|
|
@ -58,16 +69,6 @@ class ComponentVertex(Vertex):
|
|||
for key, value in self._built_object.items():
|
||||
self.add_result(key, value)
|
||||
|
||||
def get_input(self, name: str) -> InputTypes:
|
||||
if self._custom_component is None:
|
||||
raise ValueError(f"Vertex {self.id} does not have a component instance.")
|
||||
return self._custom_component.get_input(name)
|
||||
|
||||
def get_output(self, name: str) -> Output:
|
||||
if self._custom_component is None:
|
||||
raise ValueError(f"Vertex {self.id} does not have a component instance.")
|
||||
return self._custom_component.get_output(name)
|
||||
|
||||
def get_edge_with_target(self, target_id: str) -> Generator["ContractEdge", None, None]:
|
||||
"""
|
||||
Get the edge with the target id.
|
||||
|
|
@ -174,7 +175,7 @@ class ComponentVertex(Vertex):
|
|||
|
||||
|
||||
class InterfaceVertex(ComponentVertex):
|
||||
def __init__(self, data: Dict, graph):
|
||||
def __init__(self, data: NodeData, graph):
|
||||
super().__init__(data, graph=graph)
|
||||
self.steps = [self._build, self._run]
|
||||
|
||||
|
|
@ -424,7 +425,7 @@ class InterfaceVertex(ComponentVertex):
|
|||
|
||||
|
||||
class StateVertex(ComponentVertex):
|
||||
def __init__(self, data: Dict, graph):
|
||||
def __init__(self, data: NodeData, graph):
|
||||
super().__init__(data, graph=graph)
|
||||
self.steps = [self._build]
|
||||
self.is_state = False
|
||||
|
|
|
|||
|
|
@ -2,6 +2,7 @@ import copy
|
|||
import json
|
||||
import os
|
||||
import shutil
|
||||
import time
|
||||
from collections import defaultdict
|
||||
from copy import deepcopy
|
||||
from datetime import datetime, timezone
|
||||
|
|
@ -23,6 +24,7 @@ from langflow.services.database.models.folder.utils import create_default_folder
|
|||
from langflow.services.database.models.user.crud import get_user_by_username
|
||||
from langflow.services.deps import get_settings_service, get_storage_service, get_variable_service, session_scope
|
||||
from langflow.template.field.prompt import DEFAULT_PROMPT_INTUT_TYPES
|
||||
from langflow.utils.util import escape_json_dump
|
||||
|
||||
STARTER_FOLDER_NAME = "Starter Projects"
|
||||
STARTER_FOLDER_DESCRIPTION = "Starter projects to help you get started in Langflow."
|
||||
|
|
@ -319,10 +321,6 @@ def update_edges_with_latest_component_versions(project_data):
|
|||
return project_data_copy
|
||||
|
||||
|
||||
def escape_json_dump(edge_dict):
|
||||
return json.dumps(edge_dict).replace('"', "œ")
|
||||
|
||||
|
||||
def log_node_changes(node_changes_log):
|
||||
# The idea here is to log the changes that were made to the nodes in debug
|
||||
# Something like:
|
||||
|
|
@ -339,17 +337,23 @@ def log_node_changes(node_changes_log):
|
|||
logger.debug("\n".join(formatted_messages))
|
||||
|
||||
|
||||
def load_starter_projects() -> list[tuple[Path, dict]]:
|
||||
def load_starter_projects(retries=3, delay=1) -> list[tuple[Path, dict]]:
|
||||
starter_projects = []
|
||||
folder = Path(__file__).parent / "starter_projects"
|
||||
for file in folder.glob("*.json"):
|
||||
with open(file, "r", encoding="utf-8") as f:
|
||||
try:
|
||||
project = orjson.loads(f.read())
|
||||
starter_projects.append((file, project))
|
||||
logger.info(f"Loaded starter project {file}")
|
||||
except orjson.JSONDecodeError as e:
|
||||
raise ValueError(f"Error loading starter project {file}: {e}")
|
||||
attempt = 0
|
||||
while attempt < retries:
|
||||
with open(file, "r", encoding="utf-8") as f:
|
||||
try:
|
||||
project = orjson.loads(f.read())
|
||||
starter_projects.append((file, project))
|
||||
logger.info(f"Loaded starter project {file}")
|
||||
break # Break if load is successful
|
||||
except orjson.JSONDecodeError as e:
|
||||
attempt += 1
|
||||
if attempt >= retries:
|
||||
raise ValueError(f"Error loading starter project {file}: {e}")
|
||||
time.sleep(delay) # Wait before retrying
|
||||
return starter_projects
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -27,9 +27,13 @@ SerializableFieldTypes = Annotated[FieldTypes, PlainSerializer(lambda v: v.value
|
|||
|
||||
# Base mixin for common input field attributes and methods
|
||||
class BaseInputMixin(BaseModel, validate_assignment=True): # type: ignore
|
||||
model_config = ConfigDict(arbitrary_types_allowed=True, extra="forbid", populate_by_name=True)
|
||||
model_config = ConfigDict(
|
||||
arbitrary_types_allowed=True,
|
||||
extra="forbid",
|
||||
populate_by_name=True,
|
||||
)
|
||||
|
||||
field_type: SerializableFieldTypes = Field(default=FieldTypes.TEXT)
|
||||
field_type: SerializableFieldTypes = Field(default=FieldTypes.TEXT, alias="type")
|
||||
|
||||
required: bool = False
|
||||
"""Specifies if the field is required. Defaults to False."""
|
||||
|
|
|
|||
|
|
@ -24,6 +24,7 @@ class Data(BaseModel):
|
|||
default_value: Optional[str] = ""
|
||||
|
||||
@model_validator(mode="before")
|
||||
@classmethod
|
||||
def validate_data(cls, values):
|
||||
if not isinstance(values, dict):
|
||||
raise ValueError("Data must be a dictionary")
|
||||
|
|
|
|||
|
|
@ -184,12 +184,9 @@ class Output(BaseModel):
|
|||
return self.model_dump(by_alias=True, exclude_none=True)
|
||||
|
||||
def add_types(self, _type: list[Any]):
|
||||
for type_ in _type:
|
||||
if self.types and type_ in self.types:
|
||||
continue
|
||||
if self.types is None:
|
||||
self.types = []
|
||||
self.types.append(type_)
|
||||
if self.types is None:
|
||||
self.types = []
|
||||
self.types.extend([t for t in _type if t not in self.types])
|
||||
|
||||
def set_selected(self):
|
||||
if not self.selected and self.types:
|
||||
|
|
|
|||
|
|
@ -1,3 +1,3 @@
|
|||
# This file is for backwards compatibility
|
||||
from langflow.inputs.inputs import DEFAULT_PROMPT_INTUT_TYPES # noqa
|
||||
from langflow.inputs import DefaultPromptField # noqa
|
||||
from langflow.inputs.inputs import DefaultPromptField # noqa
|
||||
|
|
|
|||
|
|
@ -1,5 +1,6 @@
|
|||
import importlib
|
||||
import inspect
|
||||
import json
|
||||
import re
|
||||
from functools import wraps
|
||||
from pathlib import Path
|
||||
|
|
@ -456,3 +457,7 @@ def is_class_method(func, cls):
|
|||
Check if a function is a class method.
|
||||
"""
|
||||
return inspect.ismethod(func) and func.__self__ is cls.__class__
|
||||
|
||||
|
||||
def escape_json_dump(edge_dict):
|
||||
return json.dumps(edge_dict).replace('"', "œ")
|
||||
|
|
|
|||
354
src/backend/tests/.test_durations
Normal file
354
src/backend/tests/.test_durations
Normal file
|
|
@ -0,0 +1,354 @@
|
|||
{
|
||||
"src/backend/tests/test_endpoints.py::test_build_vertex_invalid_flow_id": 3.1494096249807626,
|
||||
"src/backend/tests/test_endpoints.py::test_build_vertex_invalid_vertex_id": 3.0606157919974066,
|
||||
"src/backend/tests/test_endpoints.py::test_get_all": 10.10167008501594,
|
||||
"src/backend/tests/test_endpoints.py::test_get_vertices": 4.5017141660209745,
|
||||
"src/backend/tests/test_endpoints.py::test_get_vertices_flow_not_found": 3.7886676250200253,
|
||||
"src/backend/tests/test_endpoints.py::test_invalid_flow_id": 4.073716707964195,
|
||||
"src/backend/tests/test_endpoints.py::test_invalid_prompt": 2.7002592499775346,
|
||||
"src/backend/tests/test_endpoints.py::test_invalid_run_with_input_type_chat": 2.987766916019609,
|
||||
"src/backend/tests/test_endpoints.py::test_post_validate_code": 3.0467621669813525,
|
||||
"src/backend/tests/test_endpoints.py::test_successful_run_with_input_type_any": 14.8548604179814,
|
||||
"src/backend/tests/test_endpoints.py::test_successful_run_with_input_type_chat": 6.242352208995726,
|
||||
"src/backend/tests/test_endpoints.py::test_successful_run_with_input_type_text": 5.7594154170074034,
|
||||
"src/backend/tests/test_endpoints.py::test_successful_run_with_output_type_any": 7.347130999987712,
|
||||
"src/backend/tests/test_endpoints.py::test_successful_run_with_output_type_debug": 6.291947416990297,
|
||||
"src/backend/tests/test_endpoints.py::test_successful_run_with_output_type_text": 14.872085083043203,
|
||||
"src/backend/tests/test_endpoints.py::test_valid_prompt": 2.7850471249839757,
|
||||
"src/backend/tests/test_endpoints.py::test_various_prompts[The weather is {weather} today.-expected_input_variables1]": 2.535564499994507,
|
||||
"src/backend/tests/test_endpoints.py::test_various_prompts[This prompt has no variables.-expected_input_variables2]": 9.15231529099401,
|
||||
"src/backend/tests/test_endpoints.py::test_various_prompts[{a}, {b}, and {c} are variables.-expected_input_variables3]": 2.640623040992068,
|
||||
"src/backend/tests/test_endpoints.py::test_various_prompts[{color} is my favorite color.-expected_input_variables0]": 2.079908042011084,
|
||||
"src/backend/tests/test_messages_endpoints.py::test_delete_messages": 2.515260499989381,
|
||||
"src/backend/tests/test_messages_endpoints.py::test_delete_messages_session": 2.3651068749895785,
|
||||
"src/backend/tests/test_messages_endpoints.py::test_update_message": 2.5627032090269495,
|
||||
"src/backend/tests/test_messages_endpoints.py::test_update_message_not_found": 3.504595792008331,
|
||||
"src/backend/tests/test_schema.py::TestInput::test_field_type_str": 0.0005162910092622042,
|
||||
"src/backend/tests/test_schema.py::TestInput::test_field_type_type": 0.0002682080084923655,
|
||||
"src/backend/tests/test_schema.py::TestInput::test_input_to_dict": 0.0003857500269077718,
|
||||
"src/backend/tests/test_schema.py::TestInput::test_invalid_field_type": 0.00031291699269786477,
|
||||
"src/backend/tests/test_schema.py::TestInput::test_post_process_type_function": 0.0005505419976543635,
|
||||
"src/backend/tests/test_schema.py::TestInput::test_serialize_field_type": 0.0002683750062715262,
|
||||
"src/backend/tests/test_schema.py::TestInput::test_validate_type_class": 0.0003414590028114617,
|
||||
"src/backend/tests/test_schema.py::TestInput::test_validate_type_string": 0.0002427089784760028,
|
||||
"src/backend/tests/test_schema.py::TestOutput::test_output_add_types": 0.000245749979512766,
|
||||
"src/backend/tests/test_schema.py::TestOutput::test_output_default": 0.00026183397858403623,
|
||||
"src/backend/tests/test_schema.py::TestOutput::test_output_set_selected": 0.0003107920056208968,
|
||||
"src/backend/tests/test_schema.py::TestOutput::test_output_to_dict": 0.0004964589898008853,
|
||||
"src/backend/tests/test_schema.py::TestOutput::test_output_validate_display_name": 0.0005334159650374204,
|
||||
"src/backend/tests/test_schema.py::TestOutput::test_output_validate_model": 0.00029370796983130276,
|
||||
"src/backend/tests/test_schema.py::TestPostProcessType::test_custom_type": 0.001362041017273441,
|
||||
"src/backend/tests/test_schema.py::TestPostProcessType::test_int_type": 0.00023837501066736877,
|
||||
"src/backend/tests/test_schema.py::TestPostProcessType::test_list_custom_type": 0.004543458024272695,
|
||||
"src/backend/tests/test_schema.py::TestPostProcessType::test_list_int_type": 0.0002362079976592213,
|
||||
"src/backend/tests/test_schema.py::TestPostProcessType::test_union_custom_type": 0.0005842499958816916,
|
||||
"src/backend/tests/test_schema.py::TestPostProcessType::test_union_type": 0.003973040962591767,
|
||||
"src/backend/tests/test_user.py::test_add_user": 3.298028166987933,
|
||||
"src/backend/tests/test_user.py::test_data_consistency_after_delete": 10.030325876054121,
|
||||
"src/backend/tests/test_user.py::test_data_consistency_after_update": 2.9754588740179315,
|
||||
"src/backend/tests/test_user.py::test_deactivated_user_cannot_access": 3.544328290998237,
|
||||
"src/backend/tests/test_user.py::test_deactivated_user_cannot_login": 3.9071091239748057,
|
||||
"src/backend/tests/test_user.py::test_delete_user": 4.161238500004401,
|
||||
"src/backend/tests/test_user.py::test_delete_user_wrong_id": 2.7632550839625765,
|
||||
"src/backend/tests/test_user.py::test_inactive_user": 3.334006417018827,
|
||||
"src/backend/tests/test_user.py::test_normal_user_cant_delete_user": 2.9729639159922954,
|
||||
"src/backend/tests/test_user.py::test_normal_user_cant_read_all_users": 2.6966073329967912,
|
||||
"src/backend/tests/test_user.py::test_patch_reset_password": 11.245606623997446,
|
||||
"src/backend/tests/test_user.py::test_patch_user": 3.2588992070232052,
|
||||
"src/backend/tests/test_user.py::test_patch_user_wrong_id": 3.3168086239602417,
|
||||
"src/backend/tests/test_user.py::test_read_all_users": 2.440687207999872,
|
||||
"src/backend/tests/test_user.py::test_user_waiting_for_approval": 9.475323291990208,
|
||||
"src/backend/tests/test_webhook.py::test_webhook_endpoint": 12.348436542029958,
|
||||
"src/backend/tests/test_webhook.py::test_webhook_flow_on_run_endpoint": 15.205204916041112,
|
||||
"src/backend/tests/test_webhook.py::test_webhook_with_random_payload": 8.713364291994367,
|
||||
"src/backend/tests/unit/components/prompts/test_prompt_component.py::TestPromptComponent::test_post_code_processing": 0.008164541970472783,
|
||||
"src/backend/tests/unit/custom/custom_component/test_component.py::test_set_invalid_output": 0.000454624998383224,
|
||||
"src/backend/tests/unit/graph/graph/test_base.py::test_graph": 0.007537708996096626,
|
||||
"src/backend/tests/unit/graph/graph/test_base.py::test_graph_functional": 0.020996668026782572,
|
||||
"src/backend/tests/unit/graph/graph/test_base.py::test_graph_functional_async_start": 0.009653333021560684,
|
||||
"src/backend/tests/unit/graph/graph/test_base.py::test_graph_functional_start": 0.008162209036527202,
|
||||
"src/backend/tests/unit/graph/graph/test_base.py::test_graph_functional_start_end": 0.06379004201153293,
|
||||
"src/backend/tests/unit/graph/graph/test_base.py::test_graph_not_prepared": 0.01988037399132736,
|
||||
"src/backend/tests/unit/graph/graph/test_runnable_vertices_manager.py::test_add_to_vertices_being_run": 2.476791499997489,
|
||||
"src/backend/tests/unit/graph/graph/test_runnable_vertices_manager.py::test_are_all_predecessors_fulfilled": 2.3258769580570515,
|
||||
"src/backend/tests/unit/graph/graph/test_runnable_vertices_manager.py::test_are_all_predecessors_fulfilled__wrong": 2.4165378749894444,
|
||||
"src/backend/tests/unit/graph/graph/test_runnable_vertices_manager.py::test_build_run_map": 2.5142138760129455,
|
||||
"src/backend/tests/unit/graph/graph/test_runnable_vertices_manager.py::test_from_dict": 2.629594833997544,
|
||||
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||||
"src/backend/tests/unit/test_database.py::test_delete_nonexistent_flow": 2.906195083982311,
|
||||
"src/backend/tests/unit/test_database.py::test_download_file": 2.6433084169693757,
|
||||
"src/backend/tests/unit/test_database.py::test_get_nonexistent_flow": 2.9141747919784393,
|
||||
"src/backend/tests/unit/test_database.py::test_load_flows": 2.3472657920210622,
|
||||
"src/backend/tests/unit/test_database.py::test_migrate_transactions": 2.4188965820358135,
|
||||
"src/backend/tests/unit/test_database.py::test_migrate_transactions_no_duckdb": 2.4176759159890935,
|
||||
"src/backend/tests/unit/test_database.py::test_read_flow": 2.524181623972254,
|
||||
"src/backend/tests/unit/test_database.py::test_read_flows": 3.3437811249750666,
|
||||
"src/backend/tests/unit/test_database.py::test_read_only_starter_projects": 2.8177391680073924,
|
||||
"src/backend/tests/unit/test_database.py::test_sqlite_pragmas": 2.2383368749869987,
|
||||
"src/backend/tests/unit/test_database.py::test_update_flow": 3.1579460009816103,
|
||||
"src/backend/tests/unit/test_database.py::test_update_flow_idempotency": 2.9125417500035837,
|
||||
"src/backend/tests/unit/test_database.py::test_update_nonexistent_flow": 2.838372750993585,
|
||||
"src/backend/tests/unit/test_database.py::test_upload_file": 2.6103912079997826,
|
||||
"src/backend/tests/unit/test_experimental_components.py::test_python_function_component": 2.076999415992759,
|
||||
"src/backend/tests/unit/test_files.py::test_delete_file": 2.799217874009628,
|
||||
"src/backend/tests/unit/test_files.py::test_download_file": 2.51829199999338,
|
||||
"src/backend/tests/unit/test_files.py::test_file_operations": 3.3802113739948254,
|
||||
"src/backend/tests/unit/test_files.py::test_list_files": 2.7689662509947084,
|
||||
"src/backend/tests/unit/test_files.py::test_upload_file": 3.3243832079751883,
|
||||
"src/backend/tests/unit/test_frontend_nodes.py::test_frontend_node_to_dict": 2.1432127919979393,
|
||||
"src/backend/tests/unit/test_frontend_nodes.py::test_template_field_defaults": 2.2584460410289466,
|
||||
"src/backend/tests/unit/test_frontend_nodes.py::test_template_to_dict": 2.8126436240272596,
|
||||
"src/backend/tests/unit/test_helper_components.py::test_data_as_text_component": 2.214979208976729,
|
||||
"src/backend/tests/unit/test_helper_components.py::test_uuid_generator_component": 3.2323666680022143,
|
||||
"src/backend/tests/unit/test_initial_setup.py::test_create_or_update_starter_projects": 2.2390285000146832,
|
||||
"src/backend/tests/unit/test_initial_setup.py::test_get_project_data": 2.6407637080119457,
|
||||
"src/backend/tests/unit/test_initial_setup.py::test_load_starter_projects": 2.2846807509777136,
|
||||
"src/backend/tests/unit/test_initial_setup.py::test_refresh_starter_projects": 5.397776041994803,
|
||||
"src/backend/tests/unit/test_kubernetes_secrets.py::test_create_secret": 2.1846052090113517,
|
||||
"src/backend/tests/unit/test_kubernetes_secrets.py::test_delete_secret": 2.4931142500427086,
|
||||
"src/backend/tests/unit/test_kubernetes_secrets.py::test_email_address": 3.9143964989925735,
|
||||
"src/backend/tests/unit/test_kubernetes_secrets.py::test_encode_string": 2.658771957969293,
|
||||
"src/backend/tests/unit/test_kubernetes_secrets.py::test_encode_uuid": 3.536810541001614,
|
||||
"src/backend/tests/unit/test_kubernetes_secrets.py::test_ends_with_non_alphanumeric": 2.6400313759804703,
|
||||
"src/backend/tests/unit/test_kubernetes_secrets.py::test_get_secret": 2.2426519600267056,
|
||||
"src/backend/tests/unit/test_kubernetes_secrets.py::test_long_string": 2.5769125409715343,
|
||||
"src/backend/tests/unit/test_kubernetes_secrets.py::test_starts_with_non_alphanumeric": 2.9591099170211237,
|
||||
"src/backend/tests/unit/test_kubernetes_secrets.py::test_uuid_case_insensitivity": 2.8027220430085436,
|
||||
"src/backend/tests/unit/test_loading.py::test_load_flow_from_json": 2.0592095839965623,
|
||||
"src/backend/tests/unit/test_loading.py::test_load_flow_from_json_object": 0.05121591599890962,
|
||||
"src/backend/tests/unit/test_loading.py::test_load_flow_from_json_with_tweaks": 2.3594004999904428,
|
||||
"src/backend/tests/unit/test_logger.py::test_enabled": 2.366979167010868,
|
||||
"src/backend/tests/unit/test_logger.py::test_get_after_timestamp": 2.843343543005176,
|
||||
"src/backend/tests/unit/test_logger.py::test_get_before_timestamp": 2.0495081240078434,
|
||||
"src/backend/tests/unit/test_logger.py::test_get_last_n": 3.3493437920114957,
|
||||
"src/backend/tests/unit/test_logger.py::test_init_default": 4.3632337910239585,
|
||||
"src/backend/tests/unit/test_logger.py::test_init_with_env_variable": 2.747672124998644,
|
||||
"src/backend/tests/unit/test_logger.py::test_len": 3.0128796670178417,
|
||||
"src/backend/tests/unit/test_logger.py::test_max_size": 2.5830446239560843,
|
||||
"src/backend/tests/unit/test_logger.py::test_write": 3.656159915990429,
|
||||
"src/backend/tests/unit/test_logger.py::test_write_overflow": 4.817402709042653,
|
||||
"src/backend/tests/unit/test_login.py::test_login_successful": 3.081307165994076,
|
||||
"src/backend/tests/unit/test_login.py::test_login_unsuccessful_wrong_password": 3.23898391702096,
|
||||
"src/backend/tests/unit/test_login.py::test_login_unsuccessful_wrong_username": 2.315841832984006,
|
||||
"src/backend/tests/unit/test_messages.py::test_add_messages": 2.261571748997085,
|
||||
"src/backend/tests/unit/test_messages.py::test_add_messagetables": 2.3893967490294017,
|
||||
"src/backend/tests/unit/test_messages.py::test_convert_to_langchain[convert_to_langchain_type]": 3.2416470000171103,
|
||||
"src/backend/tests/unit/test_messages.py::test_convert_to_langchain[message]": 2.004590749013005,
|
||||
"src/backend/tests/unit/test_messages.py::test_delete_messages": 2.3871561660198495,
|
||||
"src/backend/tests/unit/test_messages.py::test_get_messages": 2.0157879999896977,
|
||||
"src/backend/tests/unit/test_messages.py::test_store_message": 1.9027003319642972,
|
||||
"src/backend/tests/unit/test_process.py::test_load_langchain_object_with_cached_session": 2.2040907500195317,
|
||||
"src/backend/tests/unit/test_process.py::test_load_langchain_object_with_no_cached_session": 2.883888084004866,
|
||||
"src/backend/tests/unit/test_process.py::test_load_langchain_object_without_session_id": 2.329415375017561,
|
||||
"src/backend/tests/unit/test_process.py::test_multiple_tweaks": 2.047054874972673,
|
||||
"src/backend/tests/unit/test_process.py::test_no_tweaks": 1.952550498972414,
|
||||
"src/backend/tests/unit/test_process.py::test_single_tweak": 2.148759791016346,
|
||||
"src/backend/tests/unit/test_process.py::test_tweak_no_node_id": 3.1278445839998312,
|
||||
"src/backend/tests/unit/test_process.py::test_tweak_not_in_template": 2.113566374988295,
|
||||
"src/backend/tests/unit/test_setup_superuser.py::test_teardown_superuser_default_superuser": 2.256663625012152,
|
||||
"src/backend/tests/unit/test_setup_superuser.py::test_teardown_superuser_no_default_superuser": 2.211974083009409,
|
||||
"src/backend/tests/unit/test_telemetry.py::test_gauge": 2.4124685839633457,
|
||||
"src/backend/tests/unit/test_telemetry.py::test_gauge_with_counter_method": 2.186464792001061,
|
||||
"src/backend/tests/unit/test_telemetry.py::test_gauge_with_historgram_method": 2.6113254159863573,
|
||||
"src/backend/tests/unit/test_telemetry.py::test_gauge_with_up_down_counter_method": 2.225708084035432,
|
||||
"src/backend/tests/unit/test_telemetry.py::test_increment_counter": 2.130592000001343,
|
||||
"src/backend/tests/unit/test_telemetry.py::test_increment_counter_empty_label": 2.2976541249954607,
|
||||
"src/backend/tests/unit/test_telemetry.py::test_increment_counter_missing_mandatory_label": 2.443581625993829,
|
||||
"src/backend/tests/unit/test_telemetry.py::test_increment_counter_unregisted_metric": 2.630037208989961,
|
||||
"src/backend/tests/unit/test_telemetry.py::test_init": 2.1476573330292013,
|
||||
"src/backend/tests/unit/test_telemetry.py::test_missing_labels": 2.3570764580217656,
|
||||
"src/backend/tests/unit/test_telemetry.py::test_multithreaded_singleton": 2.390594750002492,
|
||||
"src/backend/tests/unit/test_telemetry.py::test_multithreaded_singleton_race_condition": 2.437567832006607,
|
||||
"src/backend/tests/unit/test_telemetry.py::test_opentelementry_singleton": 3.0913529580284376,
|
||||
"src/backend/tests/unit/test_template.py::test_build_template_from_function": 2.9347434579976834,
|
||||
"src/backend/tests/unit/test_template.py::test_get_base_classes": 2.118878333014436,
|
||||
"src/backend/tests/unit/test_template.py::test_get_default_factory": 2.143760042003123,
|
||||
"src/backend/tests/unit/test_validate_code.py::test_create_function": 2.2330028339929413,
|
||||
"src/backend/tests/unit/test_validate_code.py::test_execute_function_missing_function": 1.7509510009840596,
|
||||
"src/backend/tests/unit/test_validate_code.py::test_execute_function_missing_module": 1.850503541965736,
|
||||
"src/backend/tests/unit/test_validate_code.py::test_execute_function_missing_schema": 1.81301379200886,
|
||||
"src/backend/tests/unit/test_validate_code.py::test_execute_function_success": 2.074162457982311,
|
||||
"src/backend/tests/unit/test_validate_code.py::test_validate_code": 2.2336132919881493,
|
||||
"src/backend/tests/unit/test_version.py::test_compute_main": 2.139949625969166,
|
||||
"src/backend/tests/unit/test_version.py::test_version": 1.6260940420324914,
|
||||
"src/backend/tests/unit/utils/test_connection_string_parser.py::test_transform_connection_string[protocol::password@host-protocol::password@host]": 0.0012022080190945417,
|
||||
"src/backend/tests/unit/utils/test_connection_string_parser.py::test_transform_connection_string[protocol:user:pa:ss:word@host-protocol:user:pa:ss:word@host]": 0.000848833005875349,
|
||||
"src/backend/tests/unit/utils/test_connection_string_parser.py::test_transform_connection_string[protocol:user:pa@ss@word@host-protocol:user:pa%40ss%40word@host]": 0.001619456976186484,
|
||||
"src/backend/tests/unit/utils/test_connection_string_parser.py::test_transform_connection_string[protocol:user:pass@word@host-protocol:user:pass%40word@host]": 0.000586748996283859,
|
||||
"src/backend/tests/unit/utils/test_connection_string_parser.py::test_transform_connection_string[protocol:user:password@-protocol:user:password@]": 0.0025060399784706533,
|
||||
"src/backend/tests/unit/utils/test_connection_string_parser.py::test_transform_connection_string[protocol:user:password@host-protocol:user:password@host]": 0.0007859579636715353,
|
||||
"src/backend/tests/unit/utils/test_connection_string_parser.py::test_transform_connection_string[protocol:user@host-protocol:user@host]": 0.0004099990183021873,
|
||||
"src/backend/tests/unit/utils/test_connection_string_parser.py::test_transform_connection_string[user:password@host-user:password@host]": 0.0005190849769860506
|
||||
}
|
||||
|
|
@ -1,5 +1,7 @@
|
|||
from collections import deque
|
||||
|
||||
import pytest
|
||||
|
||||
from langflow.components.helpers.Memory import MemoryComponent
|
||||
from langflow.components.inputs.ChatInput import ChatInput
|
||||
from langflow.components.models.OpenAIModel import OpenAIModelComponent
|
||||
|
|
@ -7,9 +9,11 @@ from langflow.components.outputs.ChatOutput import ChatOutput
|
|||
from langflow.components.prompts.Prompt import PromptComponent
|
||||
from langflow.graph import Graph
|
||||
from langflow.graph.graph.constants import Finish
|
||||
from langflow.graph.graph.schema import GraphDump
|
||||
|
||||
|
||||
def test_memory_chatbot():
|
||||
@pytest.fixture
|
||||
def memory_chatbot_graph():
|
||||
session_id = "test_session_id"
|
||||
template = """{context}
|
||||
|
||||
|
|
@ -32,10 +36,87 @@ AI: """
|
|||
chat_output.set(input_value=openai_component.text_response)
|
||||
|
||||
graph = Graph(chat_input, chat_output)
|
||||
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"])
|
||||
for step in expected_order:
|
||||
result = graph.step()
|
||||
result = memory_chatbot_graph.step()
|
||||
if isinstance(result, Finish):
|
||||
break
|
||||
assert step == result.vertex.id
|
||||
|
||||
|
||||
def test_memory_chatbot_dump_structure(memory_chatbot_graph: Graph):
|
||||
# Now we run step by step
|
||||
graph_dict = memory_chatbot_graph.dump(
|
||||
name="Memory Chatbot", description="A memory chatbot", endpoint_name="membot"
|
||||
)
|
||||
assert isinstance(graph_dict, dict)
|
||||
# Test structure
|
||||
assert "data" in graph_dict
|
||||
assert "is_component" in graph_dict
|
||||
|
||||
data_dict = graph_dict["data"]
|
||||
assert "nodes" in data_dict
|
||||
assert "edges" in data_dict
|
||||
assert "description" in graph_dict
|
||||
assert "endpoint_name" in graph_dict
|
||||
|
||||
# Test data
|
||||
nodes = data_dict["nodes"]
|
||||
edges = data_dict["edges"]
|
||||
description = graph_dict["description"]
|
||||
endpoint_name = graph_dict["endpoint_name"]
|
||||
|
||||
assert len(nodes) == 5
|
||||
assert len(edges) == 4
|
||||
assert description is not None
|
||||
assert endpoint_name is not None
|
||||
|
||||
|
||||
def test_memory_chatbot_dump_components_and_edges(memory_chatbot_graph: Graph):
|
||||
# Check all components and edges were dumped correctly
|
||||
graph_dict: GraphDump = memory_chatbot_graph.dump(
|
||||
name="Memory Chatbot", description="A memory chatbot", endpoint_name="membot"
|
||||
)
|
||||
|
||||
data_dict = graph_dict["data"]
|
||||
nodes = data_dict["nodes"]
|
||||
edges = data_dict["edges"]
|
||||
|
||||
# sort the nodes by id
|
||||
nodes = sorted(nodes, key=lambda x: x["id"])
|
||||
|
||||
# Check each node
|
||||
assert nodes[0]["data"]["type"] == "ChatInput"
|
||||
assert nodes[0]["id"] == "chat_input"
|
||||
|
||||
assert nodes[1]["data"]["type"] == "MemoryComponent"
|
||||
assert nodes[1]["id"] == "chat_memory"
|
||||
|
||||
assert nodes[2]["data"]["type"] == "ChatOutput"
|
||||
assert nodes[2]["id"] == "chat_output"
|
||||
|
||||
assert nodes[3]["data"]["type"] == "OpenAIModelComponent"
|
||||
assert nodes[3]["id"] == "openai"
|
||||
|
||||
assert nodes[4]["data"]["type"] == "PromptComponent"
|
||||
assert nodes[4]["id"] == "prompt"
|
||||
|
||||
# Check edges
|
||||
expected_edges = [
|
||||
("chat_input", "prompt"),
|
||||
("chat_memory", "prompt"),
|
||||
("prompt", "openai"),
|
||||
("openai", "chat_output"),
|
||||
]
|
||||
|
||||
assert len(edges) == len(expected_edges)
|
||||
|
||||
for edge in edges:
|
||||
source = edge["source"]
|
||||
target = edge["target"]
|
||||
assert (source, target) in expected_edges, edge
|
||||
|
|
|
|||
|
|
@ -1,5 +1,7 @@
|
|||
from textwrap import dedent
|
||||
|
||||
import pytest
|
||||
|
||||
from langflow.components.data.File import FileComponent
|
||||
from langflow.components.embeddings.OpenAIEmbeddings import OpenAIEmbeddingsComponent
|
||||
from langflow.components.helpers.ParseData import ParseDataComponent
|
||||
|
|
@ -14,10 +16,17 @@ from langflow.graph.graph.constants import Finish
|
|||
from langflow.schema.data import Data
|
||||
|
||||
|
||||
def test_vector_store_rag():
|
||||
@pytest.fixture
|
||||
def client():
|
||||
pass
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def ingestion_graph():
|
||||
# Ingestion Graph
|
||||
file_component = FileComponent(_id="file-123")
|
||||
file_component.set(path="test.txt")
|
||||
file_component.set_output_value("data", Data(text="This is a test file."))
|
||||
text_splitter = SplitTextComponent(_id="text-splitter-123")
|
||||
text_splitter.set(data_inputs=file_component.load_file)
|
||||
openai_embeddings = OpenAIEmbeddingsComponent(_id="openai-embeddings-123")
|
||||
|
|
@ -31,8 +40,18 @@ def test_vector_store_rag():
|
|||
api_endpoint="https://astra.example.com",
|
||||
token="token",
|
||||
)
|
||||
vector_store.set_output_value("vector_store", "mock_vector_store")
|
||||
vector_store.set_output_value("base_retriever", "mock_retriever")
|
||||
vector_store.set_output_value("search_results", [Data(text="This is a test file.")])
|
||||
|
||||
ingestion_graph = Graph(file_component, vector_store)
|
||||
return ingestion_graph
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def rag_graph():
|
||||
# RAG Graph
|
||||
openai_embeddings = OpenAIEmbeddingsComponent(_id="openai-embeddings-124")
|
||||
chat_input = ChatInput(_id="chatinput-123")
|
||||
chat_input.get_output("message").value = "What is the meaning of life?"
|
||||
rag_vector_store = AstraVectorStoreComponent(_id="rag-vector-store-123")
|
||||
|
|
@ -69,21 +88,160 @@ def test_vector_store_rag():
|
|||
chat_output.set(input_value=openai_component.text_response)
|
||||
|
||||
graph = Graph(start=chat_input, end=chat_output)
|
||||
assert graph is not None
|
||||
ids = [
|
||||
return graph
|
||||
|
||||
|
||||
def test_vector_store_rag(ingestion_graph, rag_graph):
|
||||
assert ingestion_graph is not None
|
||||
ingestion_ids = [
|
||||
"file-123",
|
||||
"text-splitter-123",
|
||||
"openai-embeddings-123",
|
||||
"vector-store-123",
|
||||
]
|
||||
assert rag_graph is not None
|
||||
rag_ids = [
|
||||
"chatinput-123",
|
||||
"chatoutput-123",
|
||||
"openai-123",
|
||||
"parse-data-123",
|
||||
"prompt-123",
|
||||
"rag-vector-store-123",
|
||||
"openai-embeddings-123",
|
||||
"openai-embeddings-124",
|
||||
]
|
||||
results = []
|
||||
for result in graph.start():
|
||||
results.append(result)
|
||||
for ids, graph, len_results in zip([ingestion_ids, rag_ids], [ingestion_graph, rag_graph], [5, 8]):
|
||||
results = []
|
||||
for result in graph.start():
|
||||
results.append(result)
|
||||
|
||||
assert len(results) == 8
|
||||
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()
|
||||
assert len(results) == len_results
|
||||
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()
|
||||
|
||||
|
||||
def test_vector_store_rag_dump_components_and_edges(ingestion_graph, rag_graph):
|
||||
# Test ingestion graph components and edges
|
||||
ingestion_graph_dump = ingestion_graph.dump(
|
||||
name="Ingestion Graph", description="Graph for data ingestion", endpoint_name="ingestion"
|
||||
)
|
||||
|
||||
ingestion_data = ingestion_graph_dump["data"]
|
||||
ingestion_nodes = ingestion_data["nodes"]
|
||||
ingestion_edges = ingestion_data["edges"]
|
||||
|
||||
# Sort nodes by id to check components
|
||||
ingestion_nodes = sorted(ingestion_nodes, key=lambda x: x["id"])
|
||||
|
||||
# Check components in the ingestion graph
|
||||
assert ingestion_nodes[0]["data"]["type"] == "FileComponent"
|
||||
assert ingestion_nodes[0]["id"] == "file-123"
|
||||
|
||||
assert ingestion_nodes[1]["data"]["type"] == "OpenAIEmbeddingsComponent"
|
||||
assert ingestion_nodes[1]["id"] == "openai-embeddings-123"
|
||||
|
||||
assert ingestion_nodes[2]["data"]["type"] == "SplitTextComponent"
|
||||
assert ingestion_nodes[2]["id"] == "text-splitter-123"
|
||||
|
||||
assert ingestion_nodes[3]["data"]["type"] == "AstraVectorStoreComponent"
|
||||
assert ingestion_nodes[3]["id"] == "vector-store-123"
|
||||
|
||||
# Check edges in the ingestion graph
|
||||
expected_ingestion_edges = [
|
||||
("file-123", "text-splitter-123"),
|
||||
("text-splitter-123", "vector-store-123"),
|
||||
("openai-embeddings-123", "vector-store-123"),
|
||||
]
|
||||
assert len(ingestion_edges) == len(expected_ingestion_edges)
|
||||
|
||||
for edge in ingestion_edges:
|
||||
source = edge["source"]
|
||||
target = edge["target"]
|
||||
assert (source, target) in expected_ingestion_edges, edge
|
||||
|
||||
# Test RAG graph components and edges
|
||||
rag_graph_dump = rag_graph.dump(
|
||||
name="RAG Graph", description="Graph for Retrieval-Augmented Generation", endpoint_name="rag"
|
||||
)
|
||||
|
||||
rag_data = rag_graph_dump["data"]
|
||||
rag_nodes = rag_data["nodes"]
|
||||
rag_edges = rag_data["edges"]
|
||||
|
||||
# Sort nodes by id to check components
|
||||
rag_nodes = sorted(rag_nodes, key=lambda x: x["id"])
|
||||
|
||||
# Check components in the RAG graph
|
||||
assert rag_nodes[0]["data"]["type"] == "ChatInput"
|
||||
assert rag_nodes[0]["id"] == "chatinput-123"
|
||||
|
||||
assert rag_nodes[1]["data"]["type"] == "ChatOutput"
|
||||
assert rag_nodes[1]["id"] == "chatoutput-123"
|
||||
|
||||
assert rag_nodes[2]["data"]["type"] == "OpenAIModelComponent"
|
||||
assert rag_nodes[2]["id"] == "openai-123"
|
||||
|
||||
assert rag_nodes[3]["data"]["type"] == "OpenAIEmbeddingsComponent"
|
||||
assert rag_nodes[3]["id"] == "openai-embeddings-124"
|
||||
|
||||
assert rag_nodes[4]["data"]["type"] == "ParseDataComponent"
|
||||
assert rag_nodes[4]["id"] == "parse-data-123"
|
||||
|
||||
assert rag_nodes[5]["data"]["type"] == "PromptComponent"
|
||||
assert rag_nodes[5]["id"] == "prompt-123"
|
||||
|
||||
assert rag_nodes[6]["data"]["type"] == "AstraVectorStoreComponent"
|
||||
assert rag_nodes[6]["id"] == "rag-vector-store-123"
|
||||
|
||||
# Check edges in the RAG graph
|
||||
expected_rag_edges = [
|
||||
("chatinput-123", "rag-vector-store-123"),
|
||||
("openai-embeddings-124", "rag-vector-store-123"),
|
||||
("chatinput-123", "prompt-123"),
|
||||
("rag-vector-store-123", "parse-data-123"),
|
||||
("parse-data-123", "prompt-123"),
|
||||
("prompt-123", "openai-123"),
|
||||
("openai-123", "chatoutput-123"),
|
||||
]
|
||||
assert len(rag_edges) == len(expected_rag_edges), rag_edges
|
||||
|
||||
for edge in rag_edges:
|
||||
source = edge["source"]
|
||||
target = edge["target"]
|
||||
assert (source, target) in expected_rag_edges, f"Edge {source} -> {target} not found"
|
||||
|
||||
|
||||
def test_vector_store_rag_dump(ingestion_graph, rag_graph):
|
||||
# Test ingestion graph dump
|
||||
ingestion_graph_dump = ingestion_graph.dump(
|
||||
name="Ingestion Graph", description="Graph for data ingestion", endpoint_name="ingestion"
|
||||
)
|
||||
assert isinstance(ingestion_graph_dump, dict)
|
||||
|
||||
ingestion_data = ingestion_graph_dump["data"]
|
||||
assert "nodes" in ingestion_data
|
||||
assert "edges" in ingestion_data
|
||||
assert "description" in ingestion_graph_dump
|
||||
assert "endpoint_name" in ingestion_graph_dump
|
||||
|
||||
ingestion_nodes = ingestion_data["nodes"]
|
||||
ingestion_edges = ingestion_data["edges"]
|
||||
assert len(ingestion_nodes) == 4 # There are 4 components in the ingestion graph
|
||||
assert len(ingestion_edges) == 3 # There are 3 connections between components
|
||||
|
||||
# Test RAG graph dump
|
||||
rag_graph_dump = rag_graph.dump(
|
||||
name="RAG Graph", description="Graph for Retrieval-Augmented Generation", endpoint_name="rag"
|
||||
)
|
||||
assert isinstance(rag_graph_dump, dict)
|
||||
|
||||
rag_data = rag_graph_dump["data"]
|
||||
assert "nodes" in rag_data
|
||||
assert "edges" in rag_data
|
||||
assert "description" in rag_graph_dump
|
||||
assert "endpoint_name" in rag_graph_dump
|
||||
|
||||
rag_nodes = rag_data["nodes"]
|
||||
rag_edges = rag_data["edges"]
|
||||
assert len(rag_nodes) == 7 # There are 7 components in the RAG graph
|
||||
assert len(rag_edges) == 7 # There are 7 connections between components
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue