added better default labels to form components (#1040)

* added better default labels to form components

* updated default labels

* formatting

* fixed tests

Author: abidlabs

gradio/blocks.py

@@ -307,7 +307,7 @@ def get_config_file(self):
                 {
                     "id": _id,
                     "type": (block.get_block_name()),
-                    "props": block.get_template_context()
+                    "props": utils.delete_none(block.get_template_context())
                     if hasattr(block, "get_template_context")
                     else None,
                 }

gradio/components.py

@@ -132,9 +132,7 @@ def get_component_shortcut(cls, str_shortcut: str) -> Optional[Component]:
         Creates a component, where class name equals to str_shortcut.
 
         @param str_shortcut: string shortcut of a component
-        @return:
-            True, found_class or
-            False, None
+        @return: the insantiated component object, or None if no such component exists
         """
         # If we do not import templates Python cannot recognize grandchild classes names.
         import gradio.templates
@@ -2371,7 +2369,11 @@ def get_template_context(self):
         return {"default_value": self.default_value, **super().get_template_context()}
 
 
+############################
 # Only Output Components
+############################
+
+
 class Label(Component):
     """
     Component outputs a classification label, along with confidence scores of top categories if provided. Confidence scores are represented as a dictionary mapping labels to scores between 0 and 1.
@@ -2998,7 +3000,97 @@ def clear(self, fn: Callable, inputs: List[Component], outputs: List[Component])
         self.set_event_trigger("clear", fn, inputs, outputs)
 
 
+class Plot(Component):
+    """
+    Used for plot output.
+    Output type: matplotlib plt, plotly figure, or Bokeh fig (json_item format)
+    Demos: outbreak_forecast
+    """
+
+    def __init__(
+        self,
+        type: str = None,
+        label: str = None,
+        css: Optional[Dict] = None,
+        **kwargs,
+    ):
+        """
+        Parameters:
+        type (str): type of plot (matplotlib, plotly)
+        label (str): component name in interface.
+        """
+        self.type = type
+        super().__init__(label=label, css=css, **kwargs)
+
+    def get_template_context(self):
+        return {**super().get_template_context()}
+
+    def postprocess(self, y):
+        """
+        Parameters:
+        y (str): plot data
+        Returns:
+        (str): plot type
+        (str): plot base64 or json
+        """
+        dtype = self.type
+        if self.type == "plotly":
+            out_y = y.to_json()
+        elif self.type == "matplotlib":
+            out_y = processing_utils.encode_plot_to_base64(y)
+        elif self.type == "bokeh":
+            out_y = json.dumps(y)
+        elif self.type == "auto":
+            if isinstance(y, (ModuleType, matplotlib.pyplot.Figure)):
+                dtype = "matplotlib"
+                out_y = processing_utils.encode_plot_to_base64(y)
+            elif isinstance(y, dict):
+                dtype = "bokeh"
+                out_y = json.dumps(y)
+            else:
+                dtype = "plotly"
+                out_y = y.to_json()
+        else:
+            raise ValueError(
+                "Unknown type. Please choose from: 'plotly', 'matplotlib', 'bokeh'."
+            )
+        return {"type": dtype, "plot": out_y}
+
+    def change(
+        self,
+        fn: Callable,
+        inputs: List[Component],
+        outputs: List[Component],
+        status_tracker: Optional[StatusTracker] = None,
+    ):
+        """
+        Parameters:
+            fn: Callable function
+            inputs: List of inputs
+            outputs: List of outputs
+            status: StatusTracker to visualize function progress
+        Returns: None
+        """
+        self.set_event_trigger(
+            "change", fn, inputs, outputs, status_tracker=status_tracker
+        )
+
+    def clear(self, fn: Callable, inputs: List[Component], outputs: List[Component]):
+        """
+        Parameters:
+            fn: Callable function
+            inputs: List of inputs
+            outputs: List of outputs
+        Returns: None
+        """
+        self.set_event_trigger("clear", fn, inputs, outputs)
+
+
+############################
 # Static Components
+############################
+
+
 class Markdown(Component):
     """
     Used for Markdown output. Expects a valid string that is rendered into Markdown.
@@ -3186,92 +3278,6 @@ def _click_no_postprocess(
         )
 
 
-class Plot(Component):
-    """
-    Used for plot output.
-    Output type: matplotlib plt, plotly figure, or Bokeh fig (json_item format)
-    Demos: outbreak_forecast
-    """
-
-    def __init__(
-        self,
-        type: str = None,
-        label: str = None,
-        css: Optional[Dict] = None,
-        **kwargs,
-    ):
-        """
-        Parameters:
-        type (str): type of plot (matplotlib, plotly)
-        label (str): component name in interface.
-        """
-        self.type = type
-        super().__init__(label=label, css=css, **kwargs)
-
-    def get_template_context(self):
-        return {**super().get_template_context()}
-
-    def postprocess(self, y):
-        """
-        Parameters:
-        y (str): plot data
-        Returns:
-        (str): plot type
-        (str): plot base64 or json
-        """
-        dtype = self.type
-        if self.type == "plotly":
-            out_y = y.to_json()
-        elif self.type == "matplotlib":
-            out_y = processing_utils.encode_plot_to_base64(y)
-        elif self.type == "bokeh":
-            out_y = json.dumps(y)
-        elif self.type == "auto":
-            if isinstance(y, (ModuleType, matplotlib.pyplot.Figure)):
-                dtype = "matplotlib"
-                out_y = processing_utils.encode_plot_to_base64(y)
-            elif isinstance(y, dict):
-                dtype = "bokeh"
-                out_y = json.dumps(y)
-            else:
-                dtype = "plotly"
-                out_y = y.to_json()
-        else:
-            raise ValueError(
-                "Unknown type. Please choose from: 'plotly', 'matplotlib', 'bokeh'."
-            )
-        return {"type": dtype, "plot": out_y}
-
-    def change(
-        self,
-        fn: Callable,
-        inputs: List[Component],
-        outputs: List[Component],
-        status_tracker: Optional[StatusTracker] = None,
-    ):
-        """
-        Parameters:
-            fn: Callable function
-            inputs: List of inputs
-            outputs: List of outputs
-            status: StatusTracker to visualize function progress
-        Returns: None
-        """
-        self.set_event_trigger(
-            "change", fn, inputs, outputs, status_tracker=status_tracker
-        )
-
-    def clear(self, fn: Callable, inputs: List[Component], outputs: List[Component]):
-        """
-        Parameters:
-            fn: Callable function
-            inputs: List of inputs
-            outputs: List of outputs
-        Returns: None
-        """
-        self.set_event_trigger("clear", fn, inputs, outputs)
-
-
 class Interpretation(Component):
     """
     Used to create an interpretation widget for a component.
@@ -3295,14 +3301,12 @@ def get_template_context(self):
         }
 
 
-def component(str_shortcut: str) -> (bool, Optional[Component]):
+def component(str_shortcut: str) -> Optional[Component]:
     """
     Creates a component, where class name equals to str_shortcut.
 
     @param str_shortcut: string shortcut of a component
-    @return:
-        True, found_class or
-        False, None
+    @return component: the component object
     """
     component = Component.get_component_shortcut(str_shortcut)
     if component is None:

gradio/interface.py

@@ -18,7 +18,7 @@
 from markdown_it import MarkdownIt
 from mdit_py_plugins.footnote import footnote_plugin
 
-from gradio import context, interpretation, utils
+from gradio import interpretation, utils
 from gradio.blocks import Blocks, Column, Row, TabItem, Tabs
 from gradio.components import (
     Button,
@@ -32,8 +32,6 @@
 )
 from gradio.external import load_from_pipeline, load_interface  # type: ignore
 from gradio.flagging import CSVLogger, FlaggingCallback  # type: ignore
-from gradio.inputs import State as i_State  # type: ignore
-from gradio.outputs import State as o_State  # type: ignore
 from gradio.process_examples import cache_interface_examples, load_from_cache
 
 if TYPE_CHECKING:  # Only import for type checking (is False at runtime).
@@ -487,7 +485,10 @@ def clean_html(raw_html):
                 component.label = param_name
         for i, component in enumerate(self.output_components):
             if component.label is None:
-                component.label = "output_" + str(i)
+                if len(self.output_components) == 1:
+                    component.label = "output"
+                else:
+                    component.label = "output " + str(i)
 
         self.cache_examples = cache_examples
         if cache_examples:

gradio/templates/frontend/index.html

@@ -55,7 +55,7 @@
 		</script>
 		<script src="https://cdnjs.cloudflare.com/ajax/libs/iframe-resizer/4.3.1/iframeResizer.contentWindow.min.js"></script>
 		<title>Gradio</title>
-		<script type="module" crossorigin src="./assets/index.49d6d26d.js"></script>
+		<script type="module" crossorigin src="./assets/index.2f71b643.js"></script>
 		<link rel="stylesheet" href="./assets/index.39bf42f9.css">
 	</head>