Remove **kwargs from FARMReader

.github/workflows/linux_ci.yml

@@ -282,7 +282,9 @@ jobs:
       run: wget --no-check-certificate https://dl.xpdfreader.com/xpdf-tools-linux-4.03.tar.gz && tar -xvf xpdf-tools-linux-4.03.tar.gz && sudo cp xpdf-tools-linux-4.03/bin64/pdftotext /usr/local/bin
 
     - name: Install tesseract
-      run: sudo apt-get install tesseract-ocr libtesseract-dev poppler-utils
+      run: |
+        sudo apt update
+        sudo apt-get install tesseract-ocr libtesseract-dev poppler-utils
 
     - name: Install Dependencies (on cache miss only)
       # The cache might miss during the execution of an action: there should always be a fallback step to

docs/_src/api/api/reader.md

@@ -55,7 +55,7 @@ While the underlying model can vary (BERT, Roberta, DistilBERT, ...), the interf
 #### \_\_init\_\_
 
 ```python
-def __init__(model_name_or_path: str, model_version: Optional[str] = None, context_window_size: int = 150, batch_size: int = 50, use_gpu: bool = True, devices: List[torch.device] = [], no_ans_boost: float = 0.0, return_no_answer: bool = False, top_k: int = 10, top_k_per_candidate: int = 3, top_k_per_sample: int = 1, num_processes: Optional[int] = None, max_seq_len: int = 256, doc_stride: int = 128, progress_bar: bool = True, duplicate_filtering: int = 0, use_confidence_scores: bool = True, confidence_threshold: Optional[float] = None, proxies: Optional[Dict[str, str]] = None, local_files_only=False, force_download=False, use_auth_token: Optional[Union[str, bool]] = None, **kwargs, ,)
+def __init__(model_name_or_path: str, model_version: Optional[str] = None, context_window_size: int = 150, batch_size: int = 50, use_gpu: bool = True, devices: List[torch.device] = [], no_ans_boost: float = 0.0, return_no_answer: bool = False, top_k: int = 10, top_k_per_candidate: int = 3, top_k_per_sample: int = 1, num_processes: Optional[int] = None, max_seq_len: int = 256, doc_stride: int = 128, progress_bar: bool = True, duplicate_filtering: int = 0, use_confidence_scores: bool = True, confidence_threshold: Optional[float] = None, proxies: Optional[Dict[str, str]] = None, local_files_only=False, force_download=False, use_auth_token: Optional[Union[str, bool]] = None)
 ```
 
 **Arguments**:

docs/_src/tutorials/tutorials/11.md

@@ -189,7 +189,7 @@ To find out more about these pipelines, have a look at our [documentation](https
 With any Pipeline, whether prebuilt or custom constructed,
 you can save a diagram showing how all the components are connected.
 
-![image](https://user-images.githubusercontent.com/1563902/102451716-54813700-4039-11eb-881e-f3c01b47ca15.png)
+![image](https://github.com/deepset-ai/haystack/blob/master/docs/img/retriever-reader-pipeline.png)
 
 
 ```python

haystack/nodes/base.py

@@ -37,7 +37,10 @@ def wrapper_exportable_to_yaml(self, *args, **kwargs):
             self._component_config = {"params": {}, "type": type(self).__name__}
 
         # Make sure it runs only on the __init__of the implementations, not in superclasses
-        if init_func.__qualname__ == f"{self.__class__.__name__}.{init_func.__name__}":
+        # NOTE: we use '.endswith' because inner classes's __qualname__ will include the parent class'
+        #   name, like: ParentClass.InnerClass.__init__.
+        #   Inner classes are heavily used in tests.
+        if init_func.__qualname__.endswith(f"{self.__class__.__name__}.{init_func.__name__}"):
 
             # Store all the named input parameters in self._component_config
             for k, v in kwargs.items():

haystack/nodes/reader/farm.py

@@ -62,7 +62,6 @@ def __init__(
         local_files_only=False,
         force_download=False,
         use_auth_token: Optional[Union[str, bool]] = None,
-        **kwargs,
     ):
 
         """
@@ -140,7 +139,6 @@ def __init__(
             force_download=force_download,
             devices=self.devices,
             use_auth_token=use_auth_token,
-            **kwargs,
         )
         self.inferencer.model.prediction_heads[0].context_window_size = context_window_size
         self.inferencer.model.prediction_heads[0].no_ans_boost = no_ans_boost

haystack/pipelines/base.py

@@ -997,7 +997,7 @@ def _build_eval_dataframe(
             df["eval_mode"] = "isolated" if "isolated" in field_name else "integrated"
             partial_dfs.append(df)
 
-        return pd.concat(partial_dfs, ignore_index=True)
+        return pd.concat(partial_dfs, ignore_index=True).reset_index()
 
     def get_next_nodes(self, node_id: str, stream_id: str):
         current_node_edges = self.graph.edges(node_id, data=True)

haystack/utils/import_utils.py

@@ -54,7 +54,8 @@ def _optional_component_not_installed(component: str, dep_group: str, source_err
         f"Failed to import '{component}', "
         "which is an optional component in Haystack.\n"
         f"Run 'pip install 'farm-haystack[{dep_group}]'' "
-        "to install the required dependencies and make this component available."
+        "to install the required dependencies and make this component available.\n"
+        f"(Original error: {str(source_error)})"
     ) from source_error
 
 

test/test_pipeline.py

@@ -35,6 +35,7 @@
     SAMPLES_PATH,
     MockDocumentStore,
     MockRetriever,
+    MockNode,
     deepset_cloud_fixture,
 )
 
@@ -350,6 +351,36 @@ def __init__(self, document_store):
     assert pipeline.get_document_store().base_parameter == "something"
 
 
+def test_get_config_custom_node_with_params():
+    class CustomNode(MockNode):
+        def __init__(self, param: int):
+            super().__init__()
+            self.param = param
+
+    pipeline = Pipeline()
+    pipeline.add_node(CustomNode(param=10), name="custom_node", inputs=["Query"])
+
+    assert len(pipeline.get_config()["components"]) == 1
+    assert pipeline.get_config()["components"][0]["params"] == {"param": 10}
+
+
+def test_get_config_custom_node_with_positional_params(caplog):
+    class CustomNode(MockNode):
+        def __init__(self, param: int = 1):
+            super().__init__()
+            self.param = param
+
+    pipeline = Pipeline()
+    with caplog.at_level(logging.WARNING):
+        pipeline.add_node(CustomNode(10), name="custom_node", inputs=["Query"])
+        assert (
+            "Unnamed __init__ parameters will not be saved to YAML "
+            "if Pipeline.save_to_yaml() is called" in caplog.text
+        )
+    assert len(pipeline.get_config()["components"]) == 1
+    assert pipeline.get_config()["components"][0]["params"] == {}
+
+
 def test_generate_code_simple_pipeline():
     config = {
         "version": "unstable",

test/test_pipeline_yaml.py

@@ -1,6 +1,8 @@
 from abc import abstractmethod
+from numpy import mat
 import pytest
 import json
+import logging
 import inspect
 import networkx as nx
 from enum import Enum
@@ -11,6 +13,7 @@
 from haystack.nodes import _json_schema
 from haystack.nodes import FileTypeClassifier
 from haystack.errors import HaystackError, PipelineConfigError, PipelineSchemaError
+from haystack.nodes.base import BaseComponent
 
 from .conftest import SAMPLES_PATH, MockNode, MockDocumentStore, MockReader, MockRetriever
 from . import conftest
@@ -41,7 +44,9 @@ def mock_json_schema(request, monkeypatch, tmp_path):
 
     # Generate mock schema in tmp_path
     filename = f"haystack-pipeline-unstable.schema.json"
-    test_schema = _json_schema.get_json_schema(filename=filename, compatible_versions=["unstable"])
+    test_schema = _json_schema.get_json_schema(
+        filename=filename, compatible_versions=["unstable", haystack.__version__]
+    )
 
     with open(tmp_path / filename, "w") as schema_file:
         json.dump(test_schema, schema_file, indent=4)
@@ -274,11 +279,65 @@ def __init__(self, param: int):
     assert pipeline.get_node("custom_node").param == 1
 
 
-def test_load_yaml_custom_component_cant_be_abstract(tmp_path):
+def test_load_yaml_custom_component_with_no_init(tmp_path):
     class CustomNode(MockNode):
-        def __init__(self):
-            super().__init__()
+        pass
+
+    with open(tmp_path / "tmp_config.yml", "w") as tmp_file:
+        tmp_file.write(
+            f"""
+            version: unstable
+            components:
+            - name: custom_node
+              type: CustomNode
+            pipelines:
+            - name: my_pipeline
+              nodes:
+              - name: custom_node
+                inputs:
+                - Query
+        """
+        )
+    pipeline = Pipeline.load_from_yaml(path=tmp_path / "tmp_config.yml")
+    assert isinstance(pipeline.get_node("custom_node"), CustomNode)
+
+
+def test_load_yaml_custom_component_neednt_call_super(tmp_path):
+    """This is a side-effect. Here for behavior documentation only"""
+
+    class CustomNode(BaseComponent):
+        outgoing_edges = 1
+
+        def __init__(self, param: int):
+            self.param = param
+
+        def run(self, *a, **k):
+            pass
+
+    with open(tmp_path / "tmp_config.yml", "w") as tmp_file:
+        tmp_file.write(
+            f"""
+            version: unstable
+            components:
+            - name: custom_node
+              type: CustomNode
+              params:
+                param: 1
+            pipelines:
+            - name: my_pipeline
+              nodes:
+              - name: custom_node
+                inputs:
+                - Query
+        """
+        )
+    pipeline = Pipeline.load_from_yaml(path=tmp_path / "tmp_config.yml")
+    assert isinstance(pipeline.get_node("custom_node"), CustomNode)
+    assert pipeline.get_node("custom_node").param == 1
 
+
+def test_load_yaml_custom_component_cant_be_abstract(tmp_path):
+    class CustomNode(MockNode):
         @abstractmethod
         def abstract_method(self):
             pass
@@ -575,7 +634,7 @@ def __init__(self, some_exotic_parameter: str):
         )
     pipeline = Pipeline.load_from_yaml(path=tmp_path / "tmp_config.yml")
     node = pipeline.get_node("custom_node")
-    node.some_exotic_parameter == "AnotherClass.CLASS_CONSTANT"
+    assert node.some_exotic_parameter == "AnotherClass.CLASS_CONSTANT"
 
 
 def test_load_yaml_custom_component_with_superclass(tmp_path):