haystack/test/test_pipeline_debug_and_validation.py

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from pathlib import Path
import json
import pytest
from haystack.pipelines import (
Pipeline,
RootNode,
)
from haystack.nodes import (
FARMReader,
ElasticsearchRetriever,
)
@pytest.mark.elasticsearch
@pytest.mark.parametrize("document_store_with_docs", ["elasticsearch"], indirect=True)
def test_node_names_validation(document_store_with_docs, tmp_path):
pipeline = Pipeline()
pipeline.add_node(
component=ElasticsearchRetriever(document_store=document_store_with_docs),
name="Retriever",
inputs=["Query"])
pipeline.add_node(
component=FARMReader(model_name_or_path="deepset/minilm-uncased-squad2"),
name="Reader",
inputs=["Retriever"])
with pytest.raises(ValueError) as exc_info:
pipeline.run(
query="Who lives in Berlin?",
params={
"Reader": {"top_k": 3},
"non-existing-node": {"top_k": 10},
"top_k": 5,
"non-existing-global_param": "wrong",
},
debug=True
)
exception_raised = str(exc_info.value)
assert "non-existing-node" in exception_raised
assert "non-existing-global_param" in exception_raised
assert "Reader" not in exception_raised
assert "top_k" not in exception_raised
@pytest.mark.elasticsearch
@pytest.mark.parametrize("document_store_with_docs", ["elasticsearch"], indirect=True)
def test_debug_attributes_global(document_store_with_docs, tmp_path):
es_retriever = ElasticsearchRetriever(document_store=document_store_with_docs)
reader = FARMReader(model_name_or_path="deepset/minilm-uncased-squad2")
pipeline = Pipeline()
pipeline.add_node(component=es_retriever, name="ESRetriever", inputs=["Query"])
pipeline.add_node(component=reader, name="Reader", inputs=["ESRetriever"])
prediction = pipeline.run(
query="Who lives in Berlin?",
params={"ESRetriever": {"top_k": 10}, "Reader": {"top_k": 3}},
debug=True
)
assert "_debug" in prediction.keys()
assert "ESRetriever" in prediction["_debug"].keys()
assert "Reader" in prediction["_debug"].keys()
assert "input" in prediction["_debug"]["ESRetriever"].keys()
assert "output" in prediction["_debug"]["ESRetriever"].keys()
assert "input" in prediction["_debug"]["Reader"].keys()
assert "output" in prediction["_debug"]["Reader"].keys()
assert prediction["_debug"]["ESRetriever"]["input"]
assert prediction["_debug"]["ESRetriever"]["output"]
assert prediction["_debug"]["Reader"]["input"]
assert prediction["_debug"]["Reader"]["output"]
# Avoid circular reference: easiest way to detect those is to use json.dumps
json.dumps(prediction, default=str)
@pytest.mark.elasticsearch
@pytest.mark.parametrize("document_store_with_docs", ["elasticsearch"], indirect=True)
def test_debug_attributes_per_node(document_store_with_docs, tmp_path):
es_retriever = ElasticsearchRetriever(document_store=document_store_with_docs)
reader = FARMReader(model_name_or_path="deepset/minilm-uncased-squad2")
pipeline = Pipeline()
pipeline.add_node(component=es_retriever, name="ESRetriever", inputs=["Query"])
pipeline.add_node(component=reader, name="Reader", inputs=["ESRetriever"])
prediction = pipeline.run(
query="Who lives in Berlin?",
params={
"ESRetriever": {"top_k": 10, "debug": True},
"Reader": {"top_k": 3}
},
)
assert "_debug" in prediction.keys()
assert "ESRetriever" in prediction["_debug"].keys()
assert "Reader" not in prediction["_debug"].keys()
assert "input" in prediction["_debug"]["ESRetriever"].keys()
assert "output" in prediction["_debug"]["ESRetriever"].keys()
assert prediction["_debug"]["ESRetriever"]["input"]
assert prediction["_debug"]["ESRetriever"]["output"]
# Avoid circular reference: easiest way to detect those is to use json.dumps
json.dumps(prediction, default=str)
@pytest.mark.elasticsearch
@pytest.mark.parametrize("document_store_with_docs", ["elasticsearch"], indirect=True)
def test_global_debug_attributes_override_node_ones(document_store_with_docs, tmp_path):
es_retriever = ElasticsearchRetriever(document_store=document_store_with_docs)
reader = FARMReader(model_name_or_path="deepset/minilm-uncased-squad2")
pipeline = Pipeline()
pipeline.add_node(component=es_retriever, name="ESRetriever", inputs=["Query"])
pipeline.add_node(component=reader, name="Reader", inputs=["ESRetriever"])
prediction = pipeline.run(
query="Who lives in Berlin?",
params={
"ESRetriever": {"top_k": 10, "debug": True},
"Reader": {"top_k": 3, "debug": True}
},
debug=False
)
assert "_debug" not in prediction.keys()
prediction = pipeline.run(
query="Who lives in Berlin?",
params={
"ESRetriever": {"top_k": 10, "debug": False},
"Reader": {"top_k": 3, "debug": False}
},
debug=True
)
assert "_debug" in prediction.keys()
assert "ESRetriever" in prediction["_debug"].keys()
assert "Reader" in prediction["_debug"].keys()
assert "input" in prediction["_debug"]["ESRetriever"].keys()
assert "output" in prediction["_debug"]["ESRetriever"].keys()
assert "input" in prediction["_debug"]["Reader"].keys()
assert "output" in prediction["_debug"]["Reader"].keys()
assert prediction["_debug"]["ESRetriever"]["input"]
assert prediction["_debug"]["ESRetriever"]["output"]
assert prediction["_debug"]["Reader"]["input"]
assert prediction["_debug"]["Reader"]["output"]
def test_invalid_run_args():
pipeline = Pipeline.load_from_yaml(
Path(__file__).parent/"samples"/"pipeline"/"test_pipeline.yaml", pipeline_name="query_pipeline"
)
with pytest.raises(Exception) as exc:
pipeline.run(params={"ESRetriever": {"top_k": 10}})
assert "run() missing 1 required positional argument: 'query'" in str(exc.value)
with pytest.raises(Exception) as exc:
pipeline.run(invalid_query="Who made the PDF specification?", params={"ESRetriever": {"top_k": 10}})
assert "run() got an unexpected keyword argument 'invalid_query'" in str(exc.value)
with pytest.raises(Exception) as exc:
pipeline.run(query="Who made the PDF specification?", params={"ESRetriever": {"invalid": 10}})
assert "Invalid parameter 'invalid' for the node 'ESRetriever'" in str(exc.value)
def test_debug_info_propagation():
class A(RootNode):
def run(self):
test = "A"
return {"test": test, "_debug": {"debug_key_a": "debug_value_a"}}, "output_1"
class B(RootNode):
def run(self, test):
test += "B"
return {"test": test, "_debug": "debug_value_b"}, "output_1"
class C(RootNode):
def run(self, test):
test += "C"
return {"test": test}, "output_1"
class D(RootNode):
def run(self, test, _debug):
test += "C"
assert _debug["B"]["runtime"] == "debug_value_b"
return {"test": test}, "output_1"
pipeline = Pipeline()
pipeline.add_node(name="A", component=A(), inputs=["Query"])
pipeline.add_node(name="B", component=B(), inputs=["A"])
pipeline.add_node(name="C", component=C(), inputs=["B"])
pipeline.add_node(name="D", component=D(), inputs=["C"])
output = pipeline.run(query="test")
assert output["_debug"]["A"]["runtime"]["debug_key_a"] == "debug_value_a"
assert output["_debug"]["B"]["runtime"] == "debug_value_b"