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Update app.py
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Chan-Y
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app.py
CHANGED
@@ -35,19 +35,6 @@ Example:
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{{"Answer":["General"]}}
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'''
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"""
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template_json = '''
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Your task is to read the following text, convert it to json format using 'Answer' as key and return it.
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<text>
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{RESPONSE}
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</text>
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Your final response MUST contain only the response, no other text.
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Example:
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{{"Answer":["General"]}}
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'''
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"""
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json_output_parser = JsonOutputParser()
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# Define the classify_text function
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@@ -55,16 +42,9 @@ def classify_text(text):
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global llm
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start = time.time()
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"en": "english",
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"ar": "arabic",
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"es": "spanish",
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"it": "italian",
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}
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try:
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lang = language_map[lang]
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except:
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lang = "en"
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@@ -75,36 +55,27 @@ def classify_text(text):
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formatted_prompt = prompt_classify.format(TEXT=text, LANG=lang)
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classify = llm.invoke(formatted_prompt)
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'''
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prompt_json = PromptTemplate(
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template=template_json,
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input_variables=["RESPONSE"]
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)
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'''
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#formatted_prompt = template_json.format(RESPONSE=classify)
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#response = llm.invoke(formatted_prompt)
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parsed_output = json_output_parser.parse(classify)
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end = time.time()
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duration = end - start
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return parsed_output, duration #['Answer']
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# Create the Gradio interface
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def gradio_app(text):
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classification, time_taken = classify_text(text)
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return classification, f"Time taken: {time_taken:.2f} seconds"
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def create_gradio_interface():
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with gr.Blocks() as iface:
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text_input = gr.Textbox(label="Text")
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output_text = gr.Textbox(label="Detected Topics")
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time_taken = gr.Textbox(label="Time Taken (seconds)")
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submit_btn = gr.Button("Detect topic")
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iface.launch()
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if __name__ == "__main__":
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create_gradio_interface()
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{{"Answer":["General"]}}
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'''
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json_output_parser = JsonOutputParser()
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# Define the classify_text function
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global llm
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start = time.time()
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try:
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lang = detect(text)
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except:
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lang = "en"
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formatted_prompt = prompt_classify.format(TEXT=text, LANG=lang)
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classify = llm.invoke(formatted_prompt)
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parsed_output = json_output_parser.parse(classify)
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end = time.time()
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duration = end - start
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return lang, parsed_output["Answer"][0], duration #['Answer']
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# Create the Gradio interface
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def create_gradio_interface():
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with gr.Blocks() as iface:
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text_input = gr.Textbox(label="Text")
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lang_output = gr.Textbox(label="Detected Language")
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output_text = gr.Textbox(label="Detected Topics")
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time_taken = gr.Textbox(label="Time Taken (seconds)")
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submit_btn = gr.Button("Detect topic")
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def on_submit(text):
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lang, classification, duration = classify_text(text)
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return lang, classification, f"Time taken: {duration:.2f} seconds"
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submit_btn.click(fn=on_submit, inputs=text_input, outputs=[lang_output, output_text, time_taken])
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iface.launch()
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if __name__ == "__main__":
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create_gradio_interface()
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