Update app.py

app.py

@@ -9,8 +9,6 @@ from langchain.prompts import PromptTemplate
 import tempfile
 from gtts import gTTS
 import os
-import docx
-from pptx import Presentation
 
 def text_to_speech(text):
     tts = gTTS(text=text, lang='en')
@@ -20,44 +18,19 @@ def text_to_speech(text):
     st.audio(temp_filename, format='audio/mp3')
     os.remove(temp_filename)
 
-def read_text_from_pdf(pdf_file):
-    pdf_reader = PdfReader(pdf_file)
-    text = ""
-    for page in pdf_reader.pages:
-        text += page.extract_text()
-    return text
-
-def read_text_from_docx(docx_file):
-    doc = docx.Document(docx_file)
-    text = "\n".join([paragraph.text for paragraph in doc.paragraphs])
-    return text
-
-def read_text_from_pptx(pptx_file):
-    presentation = Presentation(pptx_file)
-    text = ""
-    for slide in presentation.slides:
-        for shape in slide.shapes:
-            if hasattr(shape, "text"):
-                text += shape.text + "\n"
-    return text
-
-def get_text_from_file(file):
-    content = ""
-    if file.type == "application/pdf":
-        content = read_text_from_pdf(file)
-    elif file.type == "application/vnd.openxmlformats-officedocument.wordprocessingml.document":
-        content = read_text_from_docx(file)
-    elif file.type == "application/vnd.openxmlformats-officedocument.presentationml.presentation":
-        content = read_text_from_pptx(file)
-    elif file.type == "text/plain":
-        content = file.getvalue().decode("utf-8")
-    return content
+def get_pdf_text(pdf_docs):
+    text=""
+    for pdf in pdf_docs:
+        pdf_reader= PdfReader(pdf)
+        for page in pdf_reader.pages:
+            text+= page.extract_text()
+    return  text
 
 def get_text_chunks(text):
     text_splitter = RecursiveCharacterTextSplitter(chunk_size=1000, chunk_overlap=200)
     chunks = text_splitter.split_text(text)
     return chunks
-
+    
 def get_vector_store(text_chunks, api_key):
     embeddings = HuggingFaceInferenceAPIEmbeddings(api_key=api_key, model_name="sentence-transformers/all-MiniLM-l6-v2")
     vector_store = FAISS.from_texts(text_chunks, embedding=embeddings)
@@ -89,10 +62,11 @@ def user_input(user_question, api_key):
     chain = get_conversational_chain()
 
     response = chain(
-        {"input_documents": docs, "question": user_question},
-        return_only_outputs=True
-    )
+        {"input_documents":docs, "question": user_question}
+        , return_only_outputs=True)
 
+    print(response)  # Debugging line
+    
     st.write("Replies:")
     if isinstance(response["output_text"], str):
         response_list = [response["output_text"]]
@@ -108,30 +82,28 @@ def main():
     
     st.set_page_config(layout="centered")
     st.header("Chat with DOCS")
-    st.markdown("<h1 style='font-size:24px;'>ChatBot by Muhammad Huzaifa</h1>", unsafe_allow_html=True)
+    st.markdown("<h1 style='font-size:20px;'>ChatBot by Muhammad Huzaifa</h1>", unsafe_allow_html=True)
     api_key = st.secrets["inference_api_key"]
 
     with st.sidebar:
         st.title("Menu:")
-        uploaded_files = st.file_uploader("Upload your files (PDF, DOCX, PPTX, TXT)", accept_multiple_files=True)
+        pdf_docs = st.file_uploader("Upload your PDF Files and Click on the Submit & Process Button", accept_multiple_files=True)
         if st.button("Submit & Process"):
             with st.spinner("Processing..."):
-                raw_text = ""
-                for file in uploaded_files:
-                    file_text = get_text_from_file(file)
-                    raw_text += file_text
+                raw_text = get_pdf_text(pdf_docs)
                 text_chunks = get_text_chunks(raw_text)
                 get_vector_store(text_chunks, api_key)
                 st.success("Done")
 
     # Check if any document is uploaded
-    if uploaded_files:
+    if pdf_docs:
         user_question = st.text_input("Ask a question from the Docs")
 
         if user_question:
             user_input(user_question, api_key)
     else:
-        st.write("Please upload a document (PDF, DOCX, PPTX, TXT) first to ask questions.")
+        st.write("Please upload a document first to ask questions.")
 
+                
 if __name__ == "__main__":
-    main()
+    main()