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import gradio as gr
from langchain.prompts import PromptTemplate
from langchain_huggingface import HuggingFaceEndpoint
from langchain_core.output_parsers import JsonOutputParser
from langdetect import detect
import time
# Initialize the LLM and other components
llm = HuggingFaceEndpoint(
repo_id="mistralai/Mistral-7B-Instruct-v0.3",
task="text-generation",
max_new_tokens=4096,
temperature=0.5,
do_sample=False,
)
template_classify = '''
<text>
{TEXT}
</text>
What is the topic of given text? Answer shortly.:
'''
template_json = '''
Your task is to read the following text, convert it to json format using 'Answer' as key and return it.
<text>
{RESPONSE}
</text>
Your final response MUST contain only the response, no other text.
Example:
{{"Answer":"General"}}
'''
json_output_parser = JsonOutputParser()
# Define the classify_text function
def classify_text(text):
global llm
start = time.time()
lang = detect(text)
language_map = {"tr": "turkish",
"en": "english",
"ar": "arabic",
"es": "spanish",
"it": "italian",
}
lang = language_map[lang]
prompt_classify = PromptTemplate(
template=template_classify,
input_variables=["LANG", "TEXT"]
)
formatted_prompt = prompt_classify.format(TEXT=text, LANG=lang)
classify = llm.invoke(formatted_prompt)
prompt_json = PromptTemplate(
template=template_json,
input_variables=["RESPONSE"]
)
formatted_prompt = template_json.format(RESPONSE=classify)
response = llm.invoke(formatted_prompt)
parsed_output = json_output_parser.parse(response)
end = time.time()
duration = end - start
return parsed_output, duration #['Answer']
# Create the Gradio interface
def gradio_app(text):
classification, time_taken = classify_text(text)
return classification, f"Time taken: {time_taken:.2f} seconds"
def create_gradio_interface():
with gr.Blocks() as iface:
text_input = gr.Textbox(label="Text")
output_text = gr.Textbox(label="Topics")
time_taken = gr.Textbox(label="Time Taken (seconds)")
submit_btn = gr.Button("Classify")
submit_btn.click(fn=classify_text, inputs=text_input, outputs=[output_text, time_taken])
iface.launch()
if __name__ == "__main__":
create_gradio_interface()
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