mirror of
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104 lines
3.8 KiB
Python
104 lines
3.8 KiB
Python
"""Test pipeline functionality."""
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from typing import Dict, List
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import pytest
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from pydantic import BaseModel
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from langchain.chains.base import Chain
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from langchain.chains.pipeline import Pipeline
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class FakeChain(Chain, BaseModel):
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"""Fake Chain for testing purposes."""
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input_variables: List[str]
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output_variables: List[str]
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@property
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def input_keys(self) -> List[str]:
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"""Input keys this chain returns."""
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return self.input_variables
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@property
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def output_keys(self) -> List[str]:
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"""Input keys this chain returns."""
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return self.output_variables
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def _call(self, inputs: Dict[str, str]) -> Dict[str, str]:
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outputs = {}
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for var in self.output_variables:
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variables = [inputs[k] for k in self.input_variables]
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outputs[var] = " ".join(variables) + "foo"
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return outputs
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def test_pipeline_usage_single_inputs() -> None:
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"""Test pipeline on single input chains."""
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chain_1 = FakeChain(input_variables=["foo"], output_variables=["bar"])
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chain_2 = FakeChain(input_variables=["bar"], output_variables=["baz"])
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pipeline = Pipeline(chains=[chain_1, chain_2], input_variables=["foo"])
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output = pipeline({"foo": "123"})
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expected_output = {"bar": "123foo", "baz": "123foofoo", "foo": "123"}
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assert output == expected_output
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def test_pipeline_usage_multiple_inputs() -> None:
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"""Test pipeline on multiple input chains."""
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chain_1 = FakeChain(input_variables=["foo", "test"], output_variables=["bar"])
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chain_2 = FakeChain(input_variables=["bar", "foo"], output_variables=["baz"])
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pipeline = Pipeline(chains=[chain_1, chain_2], input_variables=["foo", "test"])
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output = pipeline({"foo": "123", "test": "456"})
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expected_output = {
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"bar": "123 456foo",
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"baz": "123 456foo 123foo",
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"foo": "123",
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"test": "456",
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}
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assert output == expected_output
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def test_pipeline_usage_multiple_outputs() -> None:
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"""Test pipeline usage on multiple output chains."""
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chain_1 = FakeChain(input_variables=["foo"], output_variables=["bar", "test"])
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chain_2 = FakeChain(input_variables=["bar", "foo"], output_variables=["baz"])
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pipeline = Pipeline(chains=[chain_1, chain_2], input_variables=["foo"])
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output = pipeline({"foo": "123"})
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expected_output = {
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"bar": "123foo",
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"baz": "123foo 123foo",
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"foo": "123",
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"test": "123foo",
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}
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assert output == expected_output
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def test_pipeline_missing_inputs() -> None:
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"""Test error is raised when input variables are missing."""
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chain_1 = FakeChain(input_variables=["foo"], output_variables=["bar"])
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chain_2 = FakeChain(input_variables=["bar", "test"], output_variables=["baz"])
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with pytest.raises(ValueError):
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# Also needs "test" as an input
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Pipeline(chains=[chain_1, chain_2], input_variables=["foo"])
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def test_pipeline_bad_outputs() -> None:
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"""Test error is raised when bad outputs are specified."""
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chain_1 = FakeChain(input_variables=["foo"], output_variables=["bar"])
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chain_2 = FakeChain(input_variables=["bar"], output_variables=["baz"])
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with pytest.raises(ValueError):
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# "test" is not present as an output variable.
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Pipeline(
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chains=[chain_1, chain_2],
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input_variables=["foo"],
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output_variables=["test"],
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)
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def test_pipeline_overlapping_inputs() -> None:
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"""Test error is raised when input variables are overlapping."""
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chain_1 = FakeChain(input_variables=["foo"], output_variables=["bar", "test"])
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chain_2 = FakeChain(input_variables=["bar"], output_variables=["baz"])
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with pytest.raises(ValueError):
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# "test" is specified as an input, but also is an output of one step
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Pipeline(chains=[chain_1, chain_2], input_variables=["foo", "test"])
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