Update app.py

app.py

@@ -25,29 +25,59 @@ llm = AzureChatOpenAI(
 
 
 
-st.title("Contract Management System")
+
+st.title("Wipro CSRD AI 1")
 
 # description text
-st.write("""Hello! I'm an Al chatbot specifically created to assist vou with any procurement-related questions you may have. My range of capabilities includes providing information on contract expiry dates payment terms, and other relevant details. 
+st.write("Step 1: Summary of your selected section of CSRD... Sections in this are enviormental  topic1, enviornamtal topic2 ")
+st.write("Step 2: Ask your specfici questions regarding a CSRD disclosure requirments")
+
 
-Feel free to ask me anything you need help with!
-To get started, just provide me with the contract number and let me know what specitic details you're interested in. Additionally, tee tree to ask me any general questions you may have regardinc procurement. I'm here to assist vou in any way can 😊""")
 
 # pdf file upload
 pdf_file = st.file_uploader("Upload file", type=["pdf"])
 
+numberofpages = 100
+
+if st.button("How many pages? "):
+    reader = PdfReader(pdf_file)
+    numberofpages = len(reader.pages)
+    st.write("length is ", numberofpages)
+
+if st.button("table of contents? "):
+  reader = PdfReader(pdf_file)
+  page = reader.pages[2].extract_text()
+  st.write(page)
+
+
+
+
+startpage = st.slider('Which section to look at', 0, numberofpages, 1)
+st.write("starting section page", startpage)
+
+
+pagecount = st.slider('How many pages', 1, 5, 1)
+st.write("pages to read", pagecount)
+
 
 def extract_text_from_pdf():
     reader = PdfReader(pdf_file)
     # get all pages text
-    text = [reader.pages[i].extract_text() for i in range(len(reader.pages))]
+    text = [reader.pages[i].extract_text() for i in range(startpage, startpage + pagecount )]
     # join all pages text
     text = " ".join(text)
     return text
 
 
+def extract_text_from_pdf2():
+    reader = PdfReader(pdf_file)
+    # get all pages text
+    text = [reader.pages[i].extract_text() for i in range(len(reader.pages))]
+    # join all pages text
+    text = " ".join(text)
+    return text
 
-if st.button("Summerize Contract"):
+if st.button("Summerize "):
     with st.spinner("Extracting Text..."):
         summary_chain = load_summarize_chain(llm, chain_type="map_reduce")
         summarize_document_chain = AnalyzeDocumentChain(combine_docs_chain=summary_chain, verbose=True)
@@ -55,3 +85,4 @@ if st.button("Summerize Contract"):
     with st.spinner("Summarizing..."):
         result = summarize_document_chain.run(text)
     st.write(result)
+