Chan-Y commited on
Commit
af7893b
1 Parent(s): 4ce42df

Update app.py

Browse files

çalışmayan kodları sildim, artık detected language de ekrana yazılıyor, json'dan Answeri de daha güzel şekilde ekrana yazıyor

Files changed (1) hide show
  1. app.py +11 -40
app.py CHANGED
@@ -35,19 +35,6 @@ Example:
35
  {{"Answer":["General"]}}
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  '''
37
 
38
- """
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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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-
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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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-
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  json_output_parser = JsonOutputParser()
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  # Define the classify_text function
@@ -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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- lang = detect(text)
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-
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- language_map = {"tr": "turkish",
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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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-
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- #formatted_prompt = template_json.format(RESPONSE=classify)
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- #response = llm.invoke(formatted_prompt)
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-
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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']
92
 
93
  # 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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-
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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")
102
  time_taken = gr.Textbox(label="Time Taken (seconds)")
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  submit_btn = gr.Button("Detect topic")
104
 
105
- submit_btn.click(fn=classify_text, inputs=text_input, outputs=[output_text, time_taken])
 
 
 
 
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  iface.launch()
108
 
109
  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
43
 
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  start = time.time()
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+ try:
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+ lang = detect(text)
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+
 
 
 
 
 
 
 
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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)
57
 
 
 
 
 
 
 
 
 
 
 
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  parsed_output = json_output_parser.parse(classify)
59
  end = time.time()
60
  duration = end - start
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+ return lang, parsed_output["Answer"][0], duration #['Answer']
62
 
63
  # Create the Gradio interface
 
 
 
 
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  def create_gradio_interface():
65
  with gr.Blocks() as iface:
66
  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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+
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+ submit_btn.click(fn=on_submit, inputs=text_input, outputs=[lang_output, output_text, time_taken])
77
 
78
  iface.launch()
79
 
80
  if __name__ == "__main__":
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+ create_gradio_interface()