Update app.py
Browse files
app.py
CHANGED
@@ -1,12 +1,34 @@
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import os
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import whisper
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import gradio as gr
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import torch
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from transformers import BertTokenizer, BertForSequenceClassification, pipeline
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from app.questions import get_question
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#
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# Load models
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whisper_model = whisper.load_model("small")
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@@ -120,7 +142,7 @@ def transcribe_and_analyze_tech(audio, question):
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except Exception as e:
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return f"Error: {str(e)}", "", ""
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# UI layout
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with gr.Blocks(css="textarea, .gr-box { font-size: 18px !important; }") as demo:
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gr.HTML("<h1 style='text-align: center; font-size: 32px;'>INTERVIEW PREPARATION MODEL</h1>")
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@@ -160,23 +182,42 @@ with gr.Blocks(css="textarea, .gr-box { font-size: 18px !important; }") as demo:
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outputs=[question_display_2, audio_input_2, transcribed_text_2,
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context_analysis_result, confidence_analysis_result])
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#
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try:
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demo.launch(share=False, show_api=False)
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except Exception as e:
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print(f"
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# Last resort - minimal launch
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demo.launch()
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else:
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# For local development
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demo.launch(share=True, show_api=False)
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import os
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import sys
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# Set environment variables before importing any libraries
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os.environ["GRADIO_ANALYTICS_ENABLED"] = "False"
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# Import libraries
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import whisper
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import gradio as gr
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import torch
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from transformers import BertTokenizer, BertForSequenceClassification, pipeline
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from app.questions import get_question
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# Apply monkey patch to prevent the API generation error
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try:
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# Save original method reference
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original_method = gr.Blocks.get_api_info
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# Create a safer version of the method that catches the specific error
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def safe_get_api_info(self):
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try:
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return original_method(self)
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except TypeError as e:
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print(f"API info generation error suppressed: {str(e)}", file=sys.stderr)
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return {} # Return empty API info instead of crashing
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# Apply the patch
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gr.Blocks.get_api_info = safe_get_api_info
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print("Applied API info generation patch", file=sys.stderr)
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except Exception as e:
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print(f"Failed to apply patch: {str(e)}", file=sys.stderr)
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# Load models
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whisper_model = whisper.load_model("small")
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except Exception as e:
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return f"Error: {str(e)}", "", ""
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# UI layout
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with gr.Blocks(css="textarea, .gr-box { font-size: 18px !important; }") as demo:
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gr.HTML("<h1 style='text-align: center; font-size: 32px;'>INTERVIEW PREPARATION MODEL</h1>")
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outputs=[question_display_2, audio_input_2, transcribed_text_2,
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context_analysis_result, confidence_analysis_result])
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# Also patch the client utils function that's failing
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try:
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import gradio_client.utils
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# Original function reference
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original_json_schema = gradio_client.utils._json_schema_to_python_type
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# Create patched version
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def patched_json_schema(schema, defs=None):
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try:
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if isinstance(schema, bool):
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return "bool" # Handle boolean schema case directly
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return original_json_schema(schema, defs)
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except Exception as e:
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print(f"JSON schema conversion error suppressed: {str(e)}", file=sys.stderr)
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return "any" # Return a safe fallback type
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# Apply patch
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gradio_client.utils._json_schema_to_python_type = patched_json_schema
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print("Applied JSON schema conversion patch", file=sys.stderr)
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except Exception as e:
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print(f"Failed to apply client utils patch: {str(e)}", file=sys.stderr)
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if __name__ == "__main__":
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# Simple launch with error handling
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try:
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demo.launch(show_api=False)
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except Exception as e:
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print(f"Launch failed: {str(e)}", file=sys.stderr)
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# Try minimal launch as fallback
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try:
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demo.launch()
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except Exception as e:
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print(f"Minimal launch also failed: {str(e)}", file=sys.stderr)
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# Create a minimal error app as last resort
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with gr.Blocks() as error_app:
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gr.Markdown("# Error Starting App")
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gr.Markdown("The application encountered errors during startup. Please check the logs.")
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error_app.launch()
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