Simple Page-By-Page summarisation

Author: sudheesh4

App.py

@@ -10,6 +10,8 @@
 from langchain.llms import GooglePalm
 from langchain import PromptTemplate
 from langchain.chains import RetrievalQA
+from langchain.chains.summarize import load_summarize_chain
+from tempfile import NamedTemporaryFile
 
 import streamlit
 import streamlit.web.cli as stcli
@@ -28,7 +30,7 @@ def resolve_path(path):
 
 
 while True:
-    choice=input(f"{'>>'*10} \n Choose : 0-> Ingest ; 1->Query ; 2->Exit \n : ")
+    choice=input(f"{'>>'*10} \n Choose : 0-> Ingest ; 1->Query ; 2->Summary ; 3->Exit \n : ")
     if choice=='0':
         from ingest import INGESTER
         print(f"\n\n{'>>'*10}INGESTING!{'<<'*10}\n")
@@ -54,7 +56,20 @@ def resolve_path(path):
         except:
             print("\n\nERROR WHILE INITIATING QUERYING!\n\n")
         #EXTRACT()
+
     elif choice=='2':
+        print("\nSTARTING Summary-ing!\n")
+        try:
+            sys.argv = [
+            "streamlit",
+            "run",
+            resolve_path("DocSumm.py"),
+            "--global.developmentMode=false",
+            ]
+            sys.exit(stcli.main())
+        except:
+            print("\n\nERROR WHILE INITIATING Summary-ing!\n\n")
+    elif choice=='3':
         print("Exiting!")
         break
     else:

DocSumm.py

@@ -0,0 +1,173 @@
+from langchain.embeddings import SentenceTransformerEmbeddings #HuggingFaceInstructEmbeddings
+from langchain.vectorstores import FAISS
+import os 
+import copy
+import pprint
+#import google.generativeai as palm
+from langchain.llms import GooglePalm
+from langchain import PromptTemplate
+from langchain.document_loaders import PyPDFLoader
+from langchain.text_splitter import RecursiveCharacterTextSplitter 
+from langchain.chains import RetrievalQA
+from langchain.chains.summarize import load_summarize_chain
+from tempfile import NamedTemporaryFile
+import streamlit as st
+from ingest import pageextract
+import warnings
+warnings.filterwarnings("ignore")
+
+
+
+MODES=["Page-By-Page","Complete"]
+
+FILES=os.listdir("data")
+
+
+if 'count' not in st.session_state:
+    st.session_state.count=0
+
+if 'mode' not in st.session_state:
+    st.session_state.view=False
+    st.session_state.mode=MODES[0]
+    st.session_state.page=0
+
+
+@st.cache_resource
+def getapi():
+    return str(open("API.txt","r",encoding='utf-8').read())
+
+
+PALM_API=getapi()
+#palm.configure(api_key=PALM_API)
+
+
+@st.cache_resource
+def getmodel():
+    llm=GooglePalm(google_api_key=PALM_API,temperature=0,max_output_tokens=4000)
+    return llm
+
+@st.cache_resource
+def getprompt():
+    template = """Use the information to elaborate in points about the user's query.
+    If user mentions something not in the 'Context', just answer that you don't know.
+    If you don't know the answer, just say that you don't know, don't try to make up an answer.
+    
+    Context: {context}
+    
+    Query: {question}
+    
+    Only return the helpful answer below and nothing else.
+    
+    Helpful answer:
+    """
+    prompt = PromptTemplate(
+        template=template,
+        input_variables=['context', 'question'])
+    return prompt
+
+def parseresult(result):
+    
+    PARSED=copy.deepcopy(result)
+    docs=PARSED['source_documents']
+    sourcepage=[]
+    for d in docs:
+        sourcepage.append(d.metadata['page'])
+    PARSED['source_pages']=copy.deepcopy(sourcepage)
+    del sourcepage,result
+    return PARSED
+
+def getsources(result):
+    sources=[]
+    for s in result['source_documents']:
+        sources.append(f"{s.metadata}")
+    return sources
+
+def startview():
+    #st.runtime.legacy_caching.clear_cache()
+    st.session_state.page=0
+    st.session_state.mode=mode
+    try:
+        st.session_state.data=getData()
+    except:
+        st.write("ERROR IN LOADING DATA.")
+    
+
+def resetview():
+    st.session_state.view=False
+    st.session_state.mode=mode
+    st.session_state.page=0
+    
+
+
+
+def getdata(fi):
+    #print(fi.path)
+    text_splitter = RecursiveCharacterTextSplitter(separators=["\n\n","\n","."," "],chunk_size=2000, chunk_overlap=100)
+    texts=[]
+    with NamedTemporaryFile(dir='.', suffix='.pdf',delete=False) as f:
+        f.write(fi.getbuffer())
+        #print("DAADD>>>",f.name)
+        texts=texts+copy.deepcopy(text_splitter.split_documents(PyPDFLoader(f.name).load()))
+        #your_function_which_takes_a_path()
+    #print(f"{fi}>>>>><<<<<{texts[0:20]}")
+    os.remove(f.name)
+    return fi.read()
+mode=st.sidebar.radio("Pick one", MODES,on_change=resetview)
+file=st.sidebar.selectbox("Pick one", FILES)
+def getData():
+    texts=[]
+    text_splitter = RecursiveCharacterTextSplitter(separators=["\n\n","\n","."," "],chunk_size=1000, chunk_overlap=100)
+    texts=texts+copy.deepcopy(text_splitter.split_documents(PyPDFLoader("data/"+file).load()))
+    print(">>Data recieved.")
+    #print(texts[0])
+    st.session_state.dummy=copy.deepcopy(texts[0])
+    return pageextract(texts)#print(f"*******{texts[0]}")
+
+def sliderch():
+    st.session_state.page=BP
+
+st.session_state.file=file
+st.title(f'{mode} Summary')
+
+#file=st.sidebar.file_uploader("Upload a CSV")#,on_change=getdata)
+prompt=False#st.sidebar.text_input("Enter query")
+but=st.sidebar.button("Click me",on_click=startview)
+#st.write(but)
+if (but or st.session_state.view) and (st.session_state.mode==MODES[0]) and file:
+    col1, col2, col3 = st.columns([1, 3, 3])
+    BB=col1.button("Next page")
+    PP=col1.button("Prev page")
+    BP=col1.slider("Pick a page", 0, len(st.session_state.data),on_change=sliderch)
+    #print(BP)
+    try:
+        chain = load_summarize_chain(getmodel(), chain_type="stuff")
+    except:
+        st.write("ERROR IN LOADING MODEL.")
+    col3.header("Summary : ")
+    #tt=getData(file)
+    #no=st.number_input("Pick a page", 0, tt[-1].metadata['page'])
+    #print(f"%%%%%%%{file}")
+    st.session_state.view=True
+    try:
+        if BB:
+            st.session_state.page+=1
+            if st.session_state.page >=len(st.session_state.data):
+                st.session_state.page=len(st.session_state.data)-1
+        if PP:
+            st.session_state.page-=1
+            if st.session_state.page <0:
+                st.session_state.page=0
+        col2.header(f"Page {st.session_state.page} Preview: ")    
+    
+        col2.write(st.session_state.data[st.session_state.page].page_content[0:600]+" .......")
+        st.session_state.dummy.page_content=st.session_state.data[st.session_state.page].page_content
+        col3.write(chain.run([st.session_state.dummy]))
+    except:
+        col3.write("ISSUES IN GENERATING SUMMARY")
+    #st.write(file.read())
+elif (but or st.session_state.view) and (st.session_state.mode==MODES[1]) and file:
+    col1,col2=st.columns([2,3])
+    col1.write("WORK IN")
+    col2.write("PROGRESS ")
+    st.session_state.view=True
+    st.session_state.file=file