Update app.py

app.py

@@ -20,7 +20,7 @@ llm = ChatGoogleGenerativeAI(model="gemini-pro",
 
 
 
-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.
+template = """You are a friendly chatbot called "Chatto" who give clear an well having a conversation with a human and you are created by suriya an AI Enthusiastic.If user query anything about link try to use "provied_url_extracted_text content". 
 provied_url_extracted_text:
 {extracted_text}
 provided document:
@@ -46,12 +46,14 @@ llm_chain = LLMChain(
 
 previous_response = ""
 provided_docs = ""
+extracted_text = ""
 def conversational_chat(query):
-    global previous_response, provided_docs
-    previous_response = "".join([f"Human: {i[0]}\nChatbot: {i[1]}" for i in st.session_state['history'] if i is not None])
-    provided_docs = "".join([doc for doc in st.session_state["docs"] if doc is not None])
-    extracted_text = "".join([text for text in st.session_state["extracted_text"] if text is not None])
-    print(extracted_text)
+    global previous_response, provided_docs,extracted_text
+    for i in st.session_state['history']:
+        if i is not None:
+            previous_response += f"Human: {i[0]}\n Chatbot: {i[1]}\n"
+    provided_docs = "".join(st.session_state["docs"])
+    extracted_text = "".join(st.session_state["extracted_text"])
     
     result = llm_chain.predict(
         chat_history=previous_response, 
@@ -63,19 +65,12 @@ def conversational_chat(query):
     return result
 
 st.title("Chat Bot:")
-st.text("I am CRETA Your Friendly Assitant")
+st.text("I am Chatto Your Friendly Assitant")
 st.markdown("Built by [Suriya❤️](https://github.com/theSuriya)")
 
 if 'history' not in st.session_state:
     st.session_state['history'] = []
     
-# Initialize messages
-if 'generated' not in st.session_state:
-    st.session_state['generated'] = ["Hello ! Ask me anything"]
-
-if 'past' not in st.session_state:
-    st.session_state['past'] = [" "]
-    
 if 'docs' not in st.session_state:
     st.session_state['docs'] = []
 
@@ -89,6 +84,10 @@ def get_pdf_text(pdf_docs):
         for page in pdf_reader.pages:
             text += page.extract_text()
     return text
+def response_streaming(text):
+    for i in text:
+        yield i
+        time.sleep(0.01)
 
 def get_url_text(url_link):
     try:
@@ -105,9 +104,9 @@ def get_url_text(url_link):
     
 
 with st.sidebar:
-    st.title("Add a file for CRETA memory:")
+    st.title("Add a file for Chatto memory:")
     uploaded_files = 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 a URL:")
+    uploaded_url = st.text_input("Please upload a URL:")
 
     if st.button("Submit & Process"):
         if uploaded_files or uploaded_url:
@@ -124,24 +123,22 @@ with st.sidebar:
         else:
             st.error("Please upload at least one PDF file or provide a URL.")
     
-# Create containers for chat history and user input
-response_container = st.container()
-container = st.container()
-
-# User input form
-user_input = st.chat_input("Ask Your Questions 👉..")
-with container:
-    if user_input:
-        output = conversational_chat(user_input)
-        # answer = response_generator(output)
-        st.session_state['past'].append(user_input)
-        st.session_state['generated'].append(output)
-        
+if 'messages' not in st.session_state:
+    st.session_state.messages = [{'role': 'assistant', "content": "I'm Here to help you questions"}]
+    
+for message in st.session_state.messages:
+    with st.chat_message(message['role']):
+        st.write(message['content'])
         
-# Display chat history
-if st.session_state['generated']:
-    with response_container:
-        for i in range(len(st.session_state['generated'])):
-            if i != 0:
-                message(st.session_state["past"][i], is_user=True, key=str(i) + '_user', avatar_style="adventurer")
-            message(st.session_state["generated"][i], key=str(i), avatar_style="bottts")
+user_input = st.chat_input("Ask Your Questions 👉..")
+if user_input:
+    st.session_state.messages.append({'role': 'user', "content": user_input})
+    with st.chat_message("user"):
+        st.write(user_input)
+        response = conversational_chat(user_input)
+        # stream = response_streaming(response)
+
+    with st.chat_message("assistant"):
+        full_response = st.write_stream(response_streaming(response))
+        message = {"role": "assistant", "content": response}
+        st.session_state.messages.append(message)