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Update app.py
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app.py
CHANGED
@@ -1,8 +1,8 @@
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#app.py
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import gradio as gr
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import openai
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import os
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import
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import base64
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OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
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@@ -12,7 +12,7 @@ def image_to_base64(img_path):
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with open(img_path, "rb") as img_file:
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return base64.b64encode(img_file.read()).decode('utf-8')
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img_base64 = image_to_base64("
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img_html = f'<img src="data:image/jpg;base64,{img_base64}" alt="SBC6" width="300" style="display: block; margin: auto;"/>'
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def predict(question_choice, audio):
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@@ -22,16 +22,17 @@ def predict(question_choice, audio):
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message = transcript["text"] # This is the transcribed message from the audio input
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# Generate the system message based on the chosen question
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strategy, explanation =
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# Reference to the picture description from
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picture_description =
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# Determine whether to include the picture description based on the question choice
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picture_description_inclusion = f"""
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For the first question, ensure your feedback refers to the picture description provided:
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{picture_description}
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""" if question_choice ==
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# Construct the conversation with the system and user's message
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conversation = [
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@@ -70,7 +71,7 @@ def predict(question_choice, audio):
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iface = gr.Interface(
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fn=predict,
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inputs=[
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gr.Radio(
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gr.inputs.Audio(source="microphone", type="filepath") # Audio input
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],
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outputs=gr.inputs.Textbox(), # Using inputs.Textbox as an output to make it editable
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@@ -85,4 +86,3 @@ iface = gr.Interface(
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)
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iface.queue(max_size=99, concurrency_count=40).launch(debug=True)
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# app.py
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import gradio as gr
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import openai
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import os
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import CantonmentPriData # Importing the CantonmentPriData module
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import base64
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OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
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with open(img_path, "rb") as img_file:
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return base64.b64encode(img_file.read()).decode('utf-8')
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img_base64 = image_to_base64("CantonmentPriSBC.JPG")
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img_html = f'<img src="data:image/jpg;base64,{img_base64}" alt="SBC6" width="300" style="display: block; margin: auto;"/>'
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def predict(question_choice, audio):
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message = transcript["text"] # This is the transcribed message from the audio input
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# Generate the system message based on the chosen question
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strategy, explanation = CantonmentPriData.strategy_text["TREES"] # Updated line
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# Reference to the picture description from CantonmentPriData.py
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picture_description = CantonmentPriData.description # Updated line
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# Determine whether to include the picture description based on the question choice
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picture_description_inclusion = f"""
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For the first question, ensure your feedback refers to the picture description provided:
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{picture_description}
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""" if question_choice == CantonmentPriData.questions[0] else "" # Updated line
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# Construct the conversation with the system and user's message
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conversation = [
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iface = gr.Interface(
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fn=predict,
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inputs=[
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gr.Radio(CantonmentPriData.questions, label="Choose a question", default=CantonmentPriData.questions[0]), # Updated line
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gr.inputs.Audio(source="microphone", type="filepath") # Audio input
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],
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outputs=gr.inputs.Textbox(), # Using inputs.Textbox as an output to make it editable
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)
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iface.queue(max_size=99, concurrency_count=40).launch(debug=True)
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