chatbytes commited on
Commit
b63b2a2
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1 Parent(s): be61cf7

Update app.py

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Files changed (1) hide show
  1. app.py +20 -20
app.py CHANGED
@@ -7,7 +7,7 @@ import gradio as gr
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  # from langchain_community.document_loaders import PyPDFLoader
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  # from langchain_community.chains import RetrievalQA
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  # from secret1 import GOOGLE_API as google_api
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- # import PyPDF2
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  # def chatbot_response(user_input, history):
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  # # This is a placeholder function. Replace with your actual chatbot logic.
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  # bot_response = "You said: " + user_input
@@ -24,24 +24,24 @@ import gradio as gr
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  # texts = text_splitter.split_text(text)
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  # return texts;
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- # def text_extract(file):
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- # pdf_reader = PyPDF2.PdfReader(file.name)
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- # # Get the number of pages
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- # num_pages = len(pdf_reader.pages)
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- # # Extract text from each page
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- # text = ""
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- # for page_num in range(num_pages):
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- # page = pdf_reader.pages[page_num]
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- # text += page.extract_text()
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- # text_splitter=text_splitter_function(text);
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- # db = FAISS.from_texts(text_splitter, embeddings);
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- # retriever = db.as_retriever(search_type="similarity", search_kwargs={"k": 2})
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- # llm=GooglePalm(google_api_key=google_api)
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- # qa = RetrievalQA.from_chain_type(
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- # llm=llm, chain_type="stuff", retriever=retriever, return_source_documents=True
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- # )
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- # print(db)
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- # return text
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  with gr.Blocks() as demo:
@@ -57,7 +57,7 @@ with gr.Blocks() as demo:
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  with gr.Column():
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  input_file=gr.File(label="Upload PDF", file_count="single")
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  submit_btn=gr.Button("Submit")
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- # submit_btn.click(text_extract, [input_file], [user_input])
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  #send_btn.click(chatbot_response,[user_input,state],[chatbot, state])
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  if __name__ == "__main__":
 
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  # from langchain_community.document_loaders import PyPDFLoader
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  # from langchain_community.chains import RetrievalQA
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  # from secret1 import GOOGLE_API as google_api
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+ import PyPDF2
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  # def chatbot_response(user_input, history):
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  # # This is a placeholder function. Replace with your actual chatbot logic.
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  # bot_response = "You said: " + user_input
 
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  # texts = text_splitter.split_text(text)
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  # return texts;
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+ def text_extract(file):
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+ pdf_reader = PyPDF2.PdfReader(file.name)
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+ # Get the number of pages
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+ num_pages = len(pdf_reader.pages)
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+ # Extract text from each page
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+ text = ""
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+ for page_num in range(num_pages):
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+ page = pdf_reader.pages[page_num]
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+ text += page.extract_text()
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+ # text_splitter=text_splitter_function(text);
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+ # db = FAISS.from_texts(text_splitter, embeddings);
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+ # retriever = db.as_retriever(search_type="similarity", search_kwargs={"k": 2})
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+ # llm=GooglePalm(google_api_key=google_api)
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+ # qa = RetrievalQA.from_chain_type(
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+ # llm=llm, chain_type="stuff", retriever=retriever, return_source_documents=True
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+ # )
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+ # print(db)
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+ return text
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  with gr.Blocks() as demo:
 
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  with gr.Column():
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  input_file=gr.File(label="Upload PDF", file_count="single")
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  submit_btn=gr.Button("Submit")
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+ submit_btn.click(text_extract, [input_file], [user_input])
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  #send_btn.click(chatbot_response,[user_input,state],[chatbot, state])
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  if __name__ == "__main__":