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import streamlit as st
import requests
import tempfile
import validators
import os
# Custom CSS
with open('styles.css') as f:
css = f.read()
st.markdown(f'<style>{css}</style>', unsafe_allow_html=True)
## FUNCTIONS
## -------------------------------------------------------------------------------------------
# Function to save the uploaded file as a temporary file and return its path.
def save_uploaded_file(uploaded_file):
file_content = uploaded_file.read() # Load the document
# Create a directory if it doesn't exist
data_dir = "/data"
# os.makedirs(data_dir, exist_ok=True)
# Create a temporary file in the data directory
with tempfile.NamedTemporaryFile(delete=False, dir=data_dir) as temp_file:
temp_file.write(file_content) # Write the uploaded file content to the temporary file
temp_file_path = temp_file.name # Get the path of the temporary file
return temp_file_path
# Function to save the uploaded image as a temporary file and return its path.
def save_uploaded_image(uploaded_image):
# Create a directory named "images" if it doesn't exist
images_dir = "/images"
# os.makedirs(images_dir, exist_ok=True)
# Create a temporary file path within the "images" directory with .png extension
temp_file_path = os.path.join(images_dir, tempfile.NamedTemporaryFile(suffix=".png").name)
# Write the uploaded image content to the temporary file
with open(temp_file_path, "wb") as temp_file:
temp_file.write(uploaded_image.read())
return temp_file_path
## LOGO and TITLE
## -------------------------------------------------------------------------------------------
# Show the logo and title side by side
col1, col2 = st.columns([1, 4])
with col1:
st.image("brainbot.png", use_column_width=True,)
with col2:
st.title("Hi, I am BrainBot - Your AI Learning Assistant!")
# Main content
st.header("Upload any 📄 file, 🖼️ image, or 🔗 webpage link and ask me anything from it!")
st.subheader("Supported file formats: PDF, DOCX, TXT, PPTX, HTML")
st.subheader("Supported image formats: PNG, JPG, JPEG")
col3, col4 = st.columns([2, 3])
with col3:
## LLM OPTIONS
# Select the LLM to use (either GPT-4 or GROQ)
llm = st.radio(
"Choose the LLM", ["GPT-4", "GROQ"],
index=1
)
st.session_state["llm"] = llm
## CHAT OPTIONS - FILE, IMAGE, WEBSITE
## -------------------------------------------------------------------------------------------
# User Inputs
uploaded_file = None
uploaded_image = None
website_link = None
question = None
if llm == "GPT-4" and "api_key_flag" not in st.session_state:
st.warning("Please enter your OpenAI API key.")
# Get OpenAI API Key from user
openai_api_key = st.sidebar.text_input("Enter your OpenAI API Key", type="password")
# Send POST request to a FastAPI endpoint to set the OpenAI API key as an environment
# variable
with st.spinner("Activating OpenAI API..."):
try:
FASTAPI_URL = "http://localhost:7860/set_api_key"
data = {"api_key": openai_api_key}
if openai_api_key:
response = requests.post(FASTAPI_URL, json=data)
st.sidebar.success(response.text)
st.session_state['api_key_flag'] = True
st.experimental_rerun()
except Exception as e:
st.switch_page("pages/error.py")
with col4:
if llm == "GROQ" or "api_key_flag" in st.session_state:
# Select to upload file, image, or link to chat with them
upload_option = st.radio(
"Select an option", ["📄 Upload File", "🖼️ Upload Image", "🔗 Upload Link"]
)
# Select an option to show the appropriate file_uploader
if upload_option == "📄 Upload File":
uploaded_file = st.file_uploader("Choose a file",
type=["txt", "pdf", "docx", "pptx", "html"])
elif upload_option == "🖼️ Upload Image":
uploaded_image = st.file_uploader("Choose an image", type=["png", "jpg", "jpeg"])
elif upload_option == "🔗 Upload Link":
website_link = st.text_input("Enter a website URL")
## CHAT HISTORY
## -------------------------------------------------------------------------------------------
# Initialize an empty list to store chat messages with files
if 'file_chat_history' not in st.session_state:
st.session_state['file_chat_history'] = []
# Initialize an empty list to store image interpretations
if 'image_chat_history' not in st.session_state:
st.session_state['image_chat_history'] = []
# Initialize an empty list to store chat messages with websites
if 'web_chat_history' not in st.session_state:
st.session_state['web_chat_history'] = []
## FILE
## -------------------------------------------------------------------------------------------
# Load the uploaded file, then save it into a vector store, and enable the input field to ask
# a question
st.session_state['uploaded_file'] = False
if uploaded_file is not None:
with st.spinner("Loading file..."):
# Save the uploaded file to a temporary path
temp_file_path = save_uploaded_file(uploaded_file)
try:
# Send POST request to a FastAPI endpoint to load the file into a vectorstore
data = {"file_path": temp_file_path, "file_type": uploaded_file.type}
FASTAPI_URL = f"http://localhost:7860/load_file/{llm}"
st.write(FASTAPI_URL)
response = requests.post(FASTAPI_URL, json=data)
st.success(response.text)
st.session_state['current_file'] = uploaded_file.name
st.session_state['uploaded_file'] = True
st.switch_page("pages/File-chat.py")
except Exception as e:
st.switch_page("pages/error.py")
## IMAGE
## -------------------------------------------------------------------------------------------
# Load the uploaded image if user uploads an image, then interpret the image
st.session_state['uploaded_image'] = False
if uploaded_image is not None:
try:
# Save uploaded image to a temporary file
temp_img_path = save_uploaded_image(uploaded_image)
except Exception as e:
st.switch_page("pages/error.py")
st.session_state['temp_img_path'] = temp_img_path
st.session_state['current_image'] = uploaded_image.name
st.session_state['uploaded_image'] = True
st.switch_page("pages/Image-scan.py")
## WEBSITE LINK
## -------------------------------------------------------------------------------------------
# Load the website content, then save it into a vector store, and enable the input field to
# ask a question
st.session_state['uploaded_link'] = False
if website_link is not None:
if website_link:
# Ensure that the user has entered a correct URL
if validators.url(website_link):
try:
# Send POST request to a FastAPI endpoint to scrape the webpage and load its text
# into a vector store
FASTAPI_URL = f"http://localhost:7860/load_link/{llm}"
data = {"website_link": website_link}
with st.spinner("Loading website..."):
response = requests.post(FASTAPI_URL, json=data)
st.success(response.text)
st.session_state['current_website'] = website_link
st.session_state['uploaded_link'] = True
st.switch_page("pages/Web-chat.py")
except Exception as e:
st.switch_page("pages/error.py")
else:
st.error("Invalid URL. Please enter a valid URL.") |