zcodel commited on
Commit
3719203
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1 Parent(s): 64b1575

Update app.py

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Files changed (1) hide show
  1. app.py +14 -14
app.py CHANGED
@@ -1,18 +1,17 @@
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  import gradio as gr
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  import pandas as pd
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- from PIL import Image
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- def process_image(image):
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- # Dummy function to simulate image processing and generating answers
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- # Replace with your actual image processing and answer generation logic
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- suggested_answers = [
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- {"Answer": "Answer 1", "Link": "https://example.com/1"},
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- {"Answer": "Answer 2", "Link": "https://example.com/2"},
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- {"Answer": "Answer 3", "Link": "https://example.com/3"}
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  ]
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- # Convert suggested answers to a DataFrame
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- df = pd.DataFrame(suggested_answers)
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  # Convert DataFrame to HTML table with clickable links
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  table_html = df.to_html(escape=False, index=False, render_links=True)
@@ -21,11 +20,12 @@ def process_image(image):
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  # Create a Gradio interface
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  iface = gr.Interface(
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- fn=process_image,
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- inputs=gr.inputs.Image(type="pil"),
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  outputs="html",
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- title="Oroz: Your Industry Miantain Assistant",
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- description="ou are Oroz , industry maintain smart assistant. You help users with their concern about the maintain and industrial safety, so based on user input of various machines changes, you could predict what could go wrong and get suggested answers in an organized table with web links."
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  )
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  iface.launch()
 
 
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  import gradio as gr
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  import pandas as pd
 
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+ def generate_solutions(query):
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+ # Dummy function to simulate solution generation
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+ # Replace with your actual logic for generating solutions
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+ solutions = [
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+ {"Solution": "Check the power supply", "Link": "https://example.com/power-supply"},
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+ {"Solution": "Inspect the wiring", "Link": "https://example.com/wiring-inspection"},
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+ {"Solution": "Update the firmware", "Link": "https://example.com/firmware-update"}
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  ]
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+ # Convert solutions to a DataFrame
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+ df = pd.DataFrame(solutions)
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  # Convert DataFrame to HTML table with clickable links
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  table_html = df.to_html(escape=False, index=False, render_links=True)
 
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  # Create a Gradio interface
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  iface = gr.Interface(
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+ fn=generate_solutions,
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+ inputs=gr.inputs.Textbox(lines=2, placeholder="Describe the problem with the machine..."),
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  outputs="html",
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+ title="Industry Maintenance Assistant",
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+ description="Describe the problem with your machine, and get an organized table of suggested solutions with web links."
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  )
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  iface.launch()
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+