yujunjun/haystack
1
0
Fork 0
mirror of https://github.com/deepset-ai/haystack.git synced 2025-06-26 22:00:13 +00:00
Code Issues Packages Projects Releases Wiki Activity

chore: make Haystack warnings consistent (#9083)

Browse Source 
* chore: make Haystack warnings consistent

* more structured logging

* small fixes
This commit is contained in:
Stefano Fiorucci 2025-03-21 18:18:55 +01:00 committed by GitHub
parent 3e435439d9
commit 1c1030efc6
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
11 changed files with 65 additions and 50 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

2
haystack/components/converters/openapi_functions.py
View File

@ -84,7 +84,7 @@ class OpenAPIServiceToFunctions:
"IO error reading OpenAPI specification file: {source}. Error: {e}", source=source, e=e
)
else:
logger.warning(f"OpenAPI specification file not found: {source}")
logger.warning("OpenAPI specification file not found: {source}", source=source)
elif isinstance(source, ByteStream):
openapi_spec_content = source.data.decode("utf-8")
if not openapi_spec_content:

7
haystack/components/converters/output_adapter.py
View File

@ -5,7 +5,6 @@
import ast
import contextlib
from typing import Any, Callable, Dict, Optional, Set
from warnings import warn
import jinja2.runtime
from jinja2 import Environment, TemplateSyntaxError, meta
@ -13,9 +12,11 @@ from jinja2.nativetypes import NativeEnvironment
from jinja2.sandbox import SandboxedEnvironment
from typing_extensions import TypeAlias
from haystack import component, default_from_dict, default_to_dict
from haystack import component, default_from_dict, default_to_dict, logging
from haystack.utils import deserialize_callable, deserialize_type, serialize_callable, serialize_type
logger = logging.getLogger(__name__)
class OutputAdaptationException(Exception):
"""Exception raised when there is an error during output adaptation."""
@ -76,7 +77,7 @@ class OutputAdapter:
"Unsafe mode is enabled. This allows execution of arbitrary code in the Jinja template. "
"Use this only if you trust the source of the template."
)
warn(msg)
logger.warning(msg)
self._env = (
NativeEnvironment() if self._unsafe else SandboxedEnvironment(undefined=jinja2.runtime.StrictUndefined)
)

9
haystack/components/embedders/hugging_face_api_document_embedder.py
View File

@ -2,12 +2,11 @@
#
# SPDX-License-Identifier: Apache-2.0
import warnings
from typing import Any, Dict, List, Optional, Union
from tqdm import tqdm
from haystack import component, default_from_dict, default_to_dict
from haystack import component, default_from_dict, default_to_dict, logging
from haystack.dataclasses import Document
from haystack.lazy_imports import LazyImport
from haystack.utils import Secret, deserialize_secrets_inplace
@ -17,6 +16,8 @@ from haystack.utils.url_validation import is_valid_http_url
with LazyImport(message="Run 'pip install \"huggingface_hub>=0.27.0\"'") as huggingface_hub_import:
from huggingface_hub import InferenceClient
logger = logging.getLogger(__name__)
@component
class HuggingFaceAPIDocumentEmbedder:
@ -241,11 +242,11 @@ class HuggingFaceAPIDocumentEmbedder:
if self.api_type == HFEmbeddingAPIType.SERVERLESS_INFERENCE_API:
if truncate is not None:
msg = "`truncate` parameter is not supported for Serverless Inference API. It will be ignored."
warnings.warn(msg)
logger.warning(msg)
truncate = None
if normalize is not None:
msg = "`normalize` parameter is not supported for Serverless Inference API. It will be ignored."
warnings.warn(msg)
logger.warning(msg)
normalize = None
all_embeddings = []

9
haystack/components/embedders/hugging_face_api_text_embedder.py
View File

@ -2,10 +2,9 @@
#
# SPDX-License-Identifier: Apache-2.0
import warnings
from typing import Any, Dict, List, Optional, Union
from haystack import component, default_from_dict, default_to_dict
from haystack import component, default_from_dict, default_to_dict, logging
from haystack.lazy_imports import LazyImport
from haystack.utils import Secret, deserialize_secrets_inplace
from haystack.utils.hf import HFEmbeddingAPIType, HFModelType, check_valid_model
@ -14,6 +13,8 @@ from haystack.utils.url_validation import is_valid_http_url
with LazyImport(message="Run 'pip install \"huggingface_hub>=0.27.0\"'") as huggingface_hub_import:
from huggingface_hub import InferenceClient
logger = logging.getLogger(__name__)
@component
class HuggingFaceAPITextEmbedder:
@ -200,11 +201,11 @@ class HuggingFaceAPITextEmbedder:
if self.api_type == HFEmbeddingAPIType.SERVERLESS_INFERENCE_API:
if truncate is not None:
msg = "`truncate` parameter is not supported for Serverless Inference API. It will be ignored."
warnings.warn(msg)
logger.warning(msg)
truncate = None
if normalize is not None:
msg = "`normalize` parameter is not supported for Serverless Inference API. It will be ignored."
warnings.warn(msg)
logger.warning(msg)
normalize = None
text_to_embed = self.prefix + text + self.suffix

30
haystack/components/evaluators/llm_evaluator.py
View File

@ -4,15 +4,16 @@
import json
from typing import Any, Dict, List, Optional, Tuple, Type
from warnings import warn
from tqdm import tqdm
from haystack import component, default_from_dict, default_to_dict
from haystack import component, default_from_dict, default_to_dict, logging
from haystack.components.builders import PromptBuilder
from haystack.components.generators import OpenAIGenerator
from haystack.utils import Secret, deserialize_secrets_inplace, deserialize_type, serialize_type
logger = logging.getLogger(__name__)
@component
class LLMEvaluator:
@ -206,10 +207,9 @@ class LLMEvaluator:
try:
result = self.generator.run(prompt=prompt["prompt"])
except Exception as e:
msg = f"Error while generating response for prompt: {prompt}. Error: {e}"
if self.raise_on_failure:
raise ValueError(msg)
warn(msg)
raise ValueError(f"Error while generating response for prompt: {prompt}. Error: {e}")
logger.warning("Error while generating response for prompt: {prompt}. Error: {e}", prompt=prompt, e=e)
results.append(None)
errors += 1
continue
@ -225,8 +225,11 @@ class LLMEvaluator:
metadata = result["meta"]
if errors > 0:
msg = f"LLM evaluator failed for {errors} out of {len(list_of_input_names_to_values)} inputs."
warn(msg)
logger.warning(
"LLM evaluator failed for {errors} out of {len(list_of_input_names_to_values)} inputs.",
errors=errors,
len=len(list_of_input_names_to_values),
)
return {"results": results, "meta": metadata}
@ -374,14 +377,19 @@ class LLMEvaluator:
msg = "Response from LLM evaluator is not a valid JSON."
if self.raise_on_failure:
raise ValueError(msg)
warn(msg)
logger.warning(msg)
return False
if not all(output in parsed_output for output in expected):
msg = f"Expected response from LLM evaluator to be JSON with keys {expected}, got {received}."
if self.raise_on_failure:
raise ValueError(msg)
warn(msg)
raise ValueError(
f"Expected response from LLM evaluator to be JSON with keys {expected}, got {{received}}."
)
logger.warning(
"Expected response from LLM evaluator to be JSON with keys {expected}, got {received}.",
expected=expected,
received=received,
)
return False
return True

8
haystack/components/readers/extractive.py
View File

@ -3,7 +3,6 @@
# SPDX-License-Identifier: Apache-2.0
import math
import warnings
from pathlib import Path
from typing import Any, Dict, List, Optional, Tuple, Union
@ -215,9 +214,10 @@ class ExtractiveReader:
document_contents = []
for i, doc in enumerate(documents):
if doc.content is None:
warnings.warn(
f"Document with id {doc.id} was passed to ExtractiveReader. The Document doesn't "
f"contain any text and it will be ignored."
logger.warning(
"Document with id {doc_id} was passed to ExtractiveReader. The Document doesn't "
"contain any text and it will be ignored.",
doc_id=doc.id,
)
continue
texts.append(doc.content)

13
haystack/components/routers/conditional_router.py
View File

@ -5,7 +5,6 @@
import ast
import contextlib
from typing import Any, Callable, Dict, List, Mapping, Optional, Sequence, Set, Union, get_args, get_origin
from warnings import warn
from jinja2 import Environment, TemplateSyntaxError, meta
from jinja2.nativetypes import NativeEnvironment
@ -192,7 +191,7 @@ class ConditionalRouter:
"Unsafe mode is enabled. This allows execution of arbitrary code in the Jinja template. "
"Use this only if you trust the source of the template."
)
warn(msg)
logger.warning(msg)
self._env = NativeEnvironment() if self._unsafe else SandboxedEnvironment()
self._env.filters.update(self.custom_filters)
@ -216,13 +215,11 @@ class ConditionalRouter:
# warn about unused optional variables
unused_optional_vars = set(self.optional_variables) - input_types if self.optional_variables else None
if unused_optional_vars:
msg = (
f"The following optional variables are specified but not used in any route: {unused_optional_vars}. "
"Check if there's a typo in variable names."
logger.warning(
"The following optional variables are specified but not used in any route: {unused_optional_vars}. "
"Check if there's a typo in variable names.",
unused_optional_vars=unused_optional_vars,
)
# intentionally using both warn and logger
warn(msg, UserWarning)
logger.warning(msg)
# add mandatory input types
component.set_input_types(self, **dict.fromkeys(mandatory_input_types, Any))

13
haystack/evaluation/eval_run_result.py
View File

@ -5,13 +5,15 @@
import csv
from copy import deepcopy
from typing import Any, Dict, List, Literal, Optional, Union
from warnings import warn
from haystack import logging
from haystack.lazy_imports import LazyImport
with LazyImport("Run 'pip install pandas'") as pandas_import:
from pandas import DataFrame
logger = logging.getLogger(__name__)
class EvaluationRunResult:
"""
@ -188,10 +190,15 @@ class EvaluationRunResult:
raise ValueError("The 'other' parameter must have 'run_name', 'inputs', and 'results' attributes.")
if self.run_name == other.run_name:
warn(f"The run names of the two evaluation results are the same ('{self.run_name}')")
logger.warning(
"The run names of the two evaluation results are the same ('{run_name}')", run_name=self.run_name
)
if self.inputs.keys() != other.inputs.keys():
warn(f"The input columns differ between the results; using the input columns of '{self.run_name}'.")
logger.warning(
"The input columns differ between the results; using the input columns of '{run_name}'",
run_name=self.run_name,
)
# got both detailed reports
detailed_a = self.detailed_report(output_format="json")

10
test/components/embedders/test_hugging_face_api_document_embedder.py
View File

@ -203,7 +203,7 @@ class TestHuggingFaceAPIDocumentEmbedder:
"my_prefix document number 4 my_suffix",
]
def test_embed_batch(self, mock_check_valid_model, recwarn):
def test_embed_batch(self, mock_check_valid_model, caplog):
texts = ["text 1", "text 2", "text 3", "text 4", "text 5"]
with patch("huggingface_hub.InferenceClient.feature_extraction") as mock_embedding_patch:
@ -225,10 +225,10 @@ class TestHuggingFaceAPIDocumentEmbedder:
assert len(embedding) == 384
assert all(isinstance(x, float) for x in embedding)
# Check that warnings about ignoring truncate and normalize are raised
assert len(recwarn) == 2
assert "truncate" in str(recwarn[0].message)
assert "normalize" in str(recwarn[1].message)
# Check that logger warnings about ignoring truncate and normalize are raised
assert len(caplog.records) == 2
assert "truncate" in caplog.records[0].message
assert "normalize" in caplog.records[1].message
def test_embed_batch_wrong_embedding_shape(self, mock_check_valid_model):
texts = ["text 1", "text 2", "text 3", "text 4", "text 5"]

8
test/components/embedders/test_hugging_face_api_text_embedder.py
View File

@ -136,7 +136,7 @@ class TestHuggingFaceAPITextEmbedder:
with pytest.raises(TypeError):
embedder.run(text=list_integers_input)
def test_run(self, mock_check_valid_model, recwarn):
def test_run(self, mock_check_valid_model, caplog):
with patch("huggingface_hub.InferenceClient.feature_extraction") as mock_embedding_patch:
mock_embedding_patch.return_value = array([[random.random() for _ in range(384)]])
@ -158,9 +158,9 @@ class TestHuggingFaceAPITextEmbedder:
assert all(isinstance(x, float) for x in result["embedding"])
# Check that warnings about ignoring truncate and normalize are raised
assert len(recwarn) == 2
assert "truncate" in str(recwarn[0].message)
assert "normalize" in str(recwarn[1].message)
assert len(caplog.records) == 2
assert "truncate" in caplog.records[0].message
assert "normalize" in caplog.records[1].message
def test_run_wrong_embedding_shape(self, mock_check_valid_model):
# embedding ndim > 2

6
test/components/routers/test_conditional_router.py
View File

@ -525,7 +525,7 @@ class TestRouter:
result = pipe.run(data={"router": {"question": "What?", "mode": "chat", "language": "en", "source": "doc"}})
assert result["router"] == {"en_doc_chat": "What?"}, "Pipeline should handle all parameters"
def test_warns_on_unused_optional_variables(self):
def test_warns_on_unused_optional_variables(self, caplog):
"""
Test that a warning is raised when optional_variables contains variables
that are not used in any route conditions or outputs.
@ -536,8 +536,8 @@ class TestRouter:
]
# Initialize with unused optional variables and capture warning
with pytest.warns(UserWarning, match="optional variables"):
router = ConditionalRouter(routes=routes, optional_variables=["unused_var1", "unused_var2"])
router = ConditionalRouter(routes=routes, optional_variables=["unused_var1", "unused_var2"])
assert "optional variables" in caplog.records[0].message
# Verify router still works normally
result = router.run(question="What?", mode="chat")