Refactor into class hierarchy
Browse files- app.py +1 -1
- components.py +43 -34
app.py
CHANGED
@@ -64,7 +64,7 @@ with gr.Blocks() as demo:
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for i, task in all_tasks.items():
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execution_event = execution_event.then(
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a.execute_task,
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-
inputs=[task.component_id, task.
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outputs=[task.output, error_message],
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)
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for i, task in all_tasks.items():
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execution_event = execution_event.then(
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a.execute_task,
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+
inputs=[task.component_id, task.prompt, error_message] + a._get_all_vars_up_to(i), # type: ignore
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outputs=[task.output, error_message],
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)
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components.py
CHANGED
@@ -1,14 +1,48 @@
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from
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import gradio as gr
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import ai
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class
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vname = "v"
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def
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self.output = gr.Textbox(
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label=f"Input: {{{self.vname}{id_}}}",
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interactive=True,
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@@ -17,14 +51,14 @@ class Input:
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)
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return self.output
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def
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pass
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class AITask:
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vname = "t"
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def
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with gr.Box(visible=visible) as gr_component:
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gr.Markdown(f"AI task")
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with gr.Row():
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@@ -41,43 +75,18 @@ class AITask:
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)
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return gr_component
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-
def
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if prompt:
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formatted_prompt = prompt.format(**prompt_vars)
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return ai.llm.next([{"role": "user", "content": formatted_prompt}])
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class Component:
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def __init__(self, id_: int, internal: Union[Input, AITask], visible: bool = False):
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# Internal state
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self._id = id_
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self.internal = internal
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self._source = self.internal.__class__.__name__
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self._initial_visibility = visible
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# Gradio state
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self.component_id: gr.Number
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self.visible: gr.Number
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self.gr_component = gr.Box
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self.output: gr.Textbox
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-
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def render(self) -> None:
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self.component_id = gr.Number(value=self._id, visible=False)
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self.visible = gr.Number(int(self._initial_visibility), visible=False)
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self.gr_component = self.internal.render(self._id, self._initial_visibility)
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self.output = self.internal.output
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def execute(self, *args):
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print(f"Executing component :: {self._source}.{self._id}")
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return self.internal.execute(*args)
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-
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MAX_INPUTS = 10
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MAX_TASKS = 10
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all_inputs = {i:
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all_tasks = {i:
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all_inputs[0]._initial_visibility = True
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all_tasks[0]._initial_visibility = True
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from abc import ABC, abstractmethod
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from typing import Dict, Optional
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import gradio as gr
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import ai
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class Component(ABC):
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vname = None
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def __init__(self, id_: int, visible: bool = False):
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# Internal state
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self._id = id_
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self._source = self.__class__.__name__
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self._initial_visibility = visible
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# Gradio state
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self.component_id: gr.Number
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self.visible: gr.Number
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self.gr_component = gr.Box
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self.output: gr.Textbox
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@abstractmethod
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def _render(self, id_: int, visible: bool):
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pass
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@abstractmethod
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def _execute(self):
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pass
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def render(self) -> None:
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self.component_id = gr.Number(value=self._id, visible=False)
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self.visible = gr.Number(int(self._initial_visibility), visible=False)
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self.gr_component = self._render(self._id, self._initial_visibility)
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def execute(self, *args):
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print(f"Executing component :: {self._source}.{self._id}")
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return self._execute(*args)
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class Input(Component):
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vname = "v"
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def _render(self, id_: int, visible: bool) -> gr.Textbox:
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self.output = gr.Textbox(
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label=f"Input: {{{self.vname}{id_}}}",
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interactive=True,
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)
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return self.output
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def _execute(self):
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pass
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class AITask(Component):
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vname = "t"
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def _render(self, id_: int, visible: bool) -> gr.Box:
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with gr.Box(visible=visible) as gr_component:
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gr.Markdown(f"AI task")
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with gr.Row():
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)
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return gr_component
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def _execute(self, prompt: str, prompt_vars: Dict[str, str]) -> Optional[str]:
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if prompt:
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formatted_prompt = prompt.format(**prompt_vars)
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return ai.llm.next([{"role": "user", "content": formatted_prompt}])
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MAX_INPUTS = 10
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MAX_TASKS = 10
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all_inputs = {i: Input(i) for i in range(MAX_INPUTS)}
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all_tasks = {i: AITask(i) for i in range(MAX_TASKS)}
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all_inputs[0]._initial_visibility = True
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all_tasks[0]._initial_visibility = True
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