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1 Parent(s): dfb46e5

Update Gradio_UI.py

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  1. Gradio_UI.py +23 -20
Gradio_UI.py CHANGED
@@ -25,6 +25,27 @@ from smolagents.memory import MemoryStep
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  from smolagents.utils import _is_package_available
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  def pull_messages_from_step(
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  step_log: MemoryStep,
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  ):
@@ -274,21 +295,7 @@ class GradioUI:
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  }
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  """
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  ) as demo:
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- gr.Markdown(
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- """
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- # Content Agent
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-
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-
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- Use content agent to determine whether language is polite by classifying text strings.
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-
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-
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- * Checks text and classify whether or not it is polite, somewhat polite, neutral, and impolite.
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- <pre> </pre>Uses Intel's [[Polite Guard]](https://community.intel.com/t5/Blogs/Tech-Innovation/Artificial-Intelligence-AI/Introducing-Intel-s-new-NLP-model-Polite-Guard/post/1664135) Natural Language Processing (NLP) library.
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-
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- * Returns the current time if provided with a timezone.
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-
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-
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- """
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  )
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  stored_messages = gr.State([])
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  file_uploads_log = gr.State([])
@@ -317,11 +324,7 @@ class GradioUI:
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  [text_input, file_uploads_log],
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  [stored_messages, text_input],
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  ).then(self.interact_with_agent, [stored_messages, chatbot], [chatbot])
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- gr.Markdown(
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- """
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- Thanks for trying it out!
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- """
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- )
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  demo.launch(debug=True, share=True, **kwargs)
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  from smolagents.utils import _is_package_available
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+ agent_header = """
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+ # Content Agent
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+
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+
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+ Use content agent to determine whether language is polite by passing it text strings.
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+
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+
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+ * Checks text and classify whether or not it is polite, somewhat polite, neutral, and impolite.
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+ * Uses Intel's Polite Guard NLP library
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+ * Returns the current time if provided with a timezone.
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+
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+
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+ """
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+
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+
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+ section_header = "Section Overview"
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+
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+ agent_footer = """
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+ Thanks for trying it out!
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+ """"
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+
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  def pull_messages_from_step(
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  step_log: MemoryStep,
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  ):
 
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  }
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  """
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  ) as demo:
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+ gr.Markdown(agent_header)
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  )
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  stored_messages = gr.State([])
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  file_uploads_log = gr.State([])
 
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  [text_input, file_uploads_log],
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  [stored_messages, text_input],
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  ).then(self.interact_with_agent, [stored_messages, chatbot], [chatbot])
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+ gr.Markdown( agent_footer )
 
 
 
 
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  demo.launch(debug=True, share=True, **kwargs)
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