Merge branch 'develop' of https://github.com/explosion/spaCy into develop

website/docs/usage/v3.md

@@ -710,6 +710,48 @@ nlp = spacy.blank("en")
 + nlp.add_pipe("ner", source=source_nlp)
 ```
 
+#### Configuring pipeline components with settings {#migrating-configure-pipe}
+
+Because pipeline components are now added using their string names, you won't
+have to instantiate the [component classes](/api/#architecture-pipeline)
+directly anynore. To configure the component, you can now use the `config`
+argument on [`nlp.add_pipe`](/api/language#add_pipe).
+
+> #### config.cfg (excerpt)
+>
+> ```ini
+> [components.sentencizer]
+> factory = "sentencizer"
+> punct_chars = ["!", ".", "?"]
+> ```
+
+```diff
+punct_chars = ["!", ".", "?"]
+- sentencizer = Sentencizer(punct_chars=punct_chars)
++ sentencizer = nlp.add_pipe("sentencizer", config={"punct_chars": punct_chars})
+```
+
+The `config` corresponds to the component settings in the
+[`config.cfg`](/usage/training#config-components) and will overwrite the default
+config defined by the components.
+
+<Infobox variant="warning" title="Important note on config values">
+
+Config values you pass to components **need to be JSON-serializable** and can't
+be arbitrary Python objects. Otherwise, the settings you provide can't be
+represented in the `config.cfg` and spaCy has no way of knowing how to re-create
+your component with the same settings when you load the pipeline back in. If you
+need to pass arbitrary objects to a component, use a
+[registered function](/usage/processing-pipelines#example-stateful-components):
+
+```diff
+- config = {"model": MyTaggerModel()}
++ config= {"model": {"@architectures": "MyTaggerModel"}}
+tagger = nlp.add_pipe("tagger", config=config)
+```
+
+</Infobox>
+
 ### Adding match patterns {#migrating-matcher}
 
 The [`Matcher.add`](/api/matcher#add),