Update app.py

app.py

@@ -6,6 +6,10 @@ import google.generativeai as genai
 from langchain.prompts import PromptTemplate
 from langchain import LLMChain
 from langchain_google_genai import ChatGoogleGenerativeAI
+import nest_asyncio
+from langchain.document_loaders import WebBaseLoader
+
+nest_asyncio.apply()
 
 os.environ["GOOGLE_API_KEY"] = os.getenv("GOOGLE_API_KEY")
 genai.configure(api_key=os.environ["GOOGLE_API_KEY"])
@@ -14,7 +18,11 @@ llm = ChatGoogleGenerativeAI(model="gemini-pro",
                              temperature=0.4)
 
 
-template = """You are a friendly chat assistant called "CRETA" having a conversation with a human and you are created by Pachaiappan an AI Specialist.
+
+
+template = """You are a friendly chatbot called "CRETA" who give clear an well having a conversation with a human and you are created by suriya an AI Enthusiastic.
+provied_url_extracted_text:
+{extracted_text}
 provided document:
 {provided_docs}
 previous_chat:
@@ -44,8 +52,10 @@ def conversational_chat(query):
     for j in st.session_state["docs"]:
         if j is not None:
             docs += j
+
+    ex_text = st.session_state["extracted_text"]
     provided_docs = docs
-    result = llm_chain.predict(chat_history=previous_response, human_input=query, provided_docs=provided_docs)
+    result = llm_chain.predict(chat_history=previous_response, human_input=query, provided_docs=provided_docs,extracted_text=ex_text)
     st.session_state['history'].append((query, result))
     return result
 
@@ -64,6 +74,9 @@ if 'past' not in st.session_state:
     
 if 'docs' not in st.session_state:
     st.session_state['docs'] = []
+
+if "extracted_text" not in st.session_state:
+    st.session_state["extracted_text"] = ""
     
 def get_pdf_text(pdf_docs):
     text = ""
@@ -73,14 +86,28 @@ def get_pdf_text(pdf_docs):
             text += page.extract_text()
     return text
 
+def get_url_text(url_link):
+    website_url = url_link
+    loader = WebBaseLoader(website_url)
+    loader.requests_per_second = 1
+    docs = loader.aload()
+    extracted_text = ""
+    for page in docs:
+      extracted_text+=page.page_content
+
+    return extracted_text
+    
+
 with st.sidebar:
     st.title("Add a file for CRETA memory:")
     uploaded_file = st.file_uploader("Upload your PDF Files and Click on the Submit & Process Button", accept_multiple_files=True)
     uploaded_url = st.text_area("please upload an url..")
     if st.button("Submit & Process"):
-        with st.spinner("Processing..."):
-            st.session_state["docs"] += get_pdf_text(uploaded_file)
-            st.success("Done")
+        if uploaded_file or uploaded_url:
+            with st.spinner("Processing..."):
+                st.session_state["docs"] += get_pdf_text(uploaded_file)
+                st.session_state["docs"] += get_url_text(uploaded_url)
+                st.success("Done")
     
 # Create containers for chat history and user input
 response_container = st.container()