Update app.py

app.py

@@ -2,12 +2,6 @@ from openai import OpenAI
 import streamlit as st
 import os
 from datetime import datetime
-import pandas as pd
-import json
-import xml.etree.ElementTree as ET
-from io import StringIO, BytesIO
-from time import sleep
-from tabulate import tabulate
 
 # Load API key securely
 API_KEY = os.getenv("NV_API_KEY", "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")
@@ -20,12 +14,11 @@ client = OpenAI(
     api_key=API_KEY
 )
 
-st.set_page_config(page_title="Nemotron 4 340B", layout="wide")
 st.title("Nemotron 4 340B")
 
 # Sidebar content
 with st.sidebar:
-    st.markdown("This is an advanced chatbot focused on coding and file analysis. Supported by Nazmul Hasan Nihal.")
+    st.markdown("This is a basic chatbot. Ask anything. The app is supported by Nazmul Hasan Nihal.")
     if st.button("Clear Session"):
         st.session_state.clear()
     st.write(f"Copyright 2023-{datetime.now().year} Present Nazmul Hasan Nihal")
@@ -35,49 +28,22 @@ if "openai_model" not in st.session_state:
     st.session_state['openai_model'] = "nvidia/nemotron-4-340b-instruct"
 
 if "messages" not in st.session_state:
-    st.session_state.messages = [{"role": "system", "content": "You are a helpful coding assistant."}]
-
-# Function to display typing animation
-def display_typing_animation(text):
-    for char in text:
-        st.markdown(char, unsafe_allow_html=True)
-        sleep(0.02)
-
-# Function to process uploaded files
-def process_uploaded_file(file):
-    file_type = file.type
-    if file_type == "text/csv":
-        df = pd.read_csv(file)
-        return f"**CSV File Analysis:**\n{tabulate(df.head(), headers='keys', tablefmt='grid')}"
-    elif file_type in ["application/vnd.openxmlformats-officedocument.spreadsheetml.sheet", "application/vnd.ms-excel"]:
-        df = pd.read_excel(file)
-        return f"**Excel File Analysis:**\n{tabulate(df.head(), headers='keys', tablefmt='grid')}"
-    elif file_type == "application/json":
-        data = json.load(file)
-        return f"**JSON File Analysis:**\n```json\n{json.dumps(data, indent=4)}\n```"
-    elif file_type in ["text/xml", "application/xml"]:
-        tree = ET.parse(file)
-        root = tree.getroot()
-        return f"**XML File Root Tag:** {root.tag}\n**Attributes:** {root.attrib}"
-    elif file_type == "application/pdf":
-        return "PDF uploads are not processed for content. Try text-based analysis."
-    else:
-        return "Unsupported file format. Please upload CSV, Excel, JSON, XML, or PDF files."
+    st.session_state.messages = [{"role": "system", "content": "You are a helpful assistant."}]
 
 # Display previous messages
 for message in st.session_state.messages:
     with st.chat_message(message["role"]):
         st.markdown(message["content"])
 
-# Handle user input or file uploads
-if user_input := st.chat_input("Type a message or upload a file below."):
-    st.session_state.messages.append({"role": "user", "content": user_input})
+# Handle user input
+if prompt := st.chat_input("What is up"):
+    st.session_state.messages.append({"role": "user", "content": prompt})
     with st.chat_message("user"):
-        st.markdown(user_input)
+        st.markdown(prompt)
 
     # Assistant response
     with st.chat_message("assistant"):
-        with st.spinner("The assistant is processing..."):
+        with st.spinner("The assistant is thinking... Please wait."):
             try:
                 # Generate response
                 stream = client.chat.completions.create(
@@ -92,7 +58,6 @@ if user_input := st.chat_input("Type a message or upload a file below."):
                 for chunk in stream:
                     if chunk.choices[0].delta.content:
                         response_chunks.append(chunk.choices[0].delta.content)
-                        display_typing_animation(chunk.choices[0].delta.content)
                 response = "".join(response_chunks)
                 st.markdown(response)
 
@@ -100,15 +65,4 @@ if user_input := st.chat_input("Type a message or upload a file below."):
                 st.session_state.messages.append({"role": "assistant", "content": response})
 
             except Exception as e:
-                st.error(f"An error occurred: {e}")
-
-# Add file upload to chat input
-st.markdown("### File Upload:")
-uploaded_file = st.file_uploader("Upload your file (CSV, XLSX, JSON, XML, PDF)", type=["csv", "xlsx", "json", "xml", "pdf"])
-if uploaded_file:
-    with st.chat_message("user"):
-        st.markdown(f"**Uploaded File:** {uploaded_file.name}")
-    with st.chat_message("assistant"):
-        with st.spinner("Processing the uploaded file..."):
-            file_analysis = process_uploaded_file(uploaded_file)
-            st.markdown(file_analysis)
+                st.error(f"An error occurred: {e}")