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import requests
import base64
import os
import time
from urllib.parse import urlparse, parse_qs
# --- BACKEND URL ---
BACKEND_URL = os.getenv("BACKEND_URL", "http://localhost:8000")
# --- PAGE CONFIG ---
st.set_page_config(page_title="ContextHub", layout="wide")
st.markdown("""
<style>
.main-header {
background-color: #427d44;
color: white;
padding: 15px;
border-radius: 10px;
text-align: center;
margin-bottom: 25px;
}
.stButton>button {
background-color: #016401;
color: white;
width: 100%;
}
</style>
<style>
.stTabs [data-baseweb="tab-list"] button [data-testid="stMarkdownContainer"] p {
font-size: 1.5rem;
gap: 20px;
}
.stTabs [data-baseweb="tab"] {
height: 60px;
padding-top: 10px;
padding-bottom: 10px;
padding-right: 20px;
padding-left: 20px;
}
</style>
<div class="main-header">
<h1> π Context Hub</h1>
</div>
""", unsafe_allow_html=True)
tab0, tab1, tab2, tab3, tab4 = st.tabs([
"About",
"π Document",
"πΌοΈ Visual",
"π Web Link",
"π₯ Video"
])
with tab0:
st.markdown("""
<h3 style='text-align: center; color: #427d44;'>Your Universal Multimodal Intelligence Hub</h3>
<br>
""", unsafe_allow_html=True)
col1, col2, col3 = st.columns(3)
with col1:
st.markdown("### β‘ Fast")
st.write("Powered by **Groq & Gemini** inference for near-instant responses.")
with col2:
st.markdown("### π§ Smart")
st.write("Uses **Nomic Embeddings** and **Pinecone** for deep context retrieval.")
with col3:
st.markdown("### π Versatile")
st.write("Handles Documents, Images, Web Links, and Videos seamlessly.")
st.markdown("---")
st.markdown("## π What is ContextHub?")
st.write("""
ContextHub is a state-of-the-art **RAG (Retrieval-Augmented Generation)** platform.
Instead of just talking to a general AI, you can give the AI your own specific dataβbe it a complex
PDF report, a website link, or even a videoβand ask questions based on that specific content.
""")
with st.expander("π How it works under the hood"):
st.info("""
1. **Ingest:** You upload a source (PDF, Image, Link, or Video).
2. **Process:** The system chunks the data and uses **Nomic** to create vector embeddings.
3. **Store:** These vectors are indexed in a **Pinecone** database.
4. **Retrieve:** When you ask a question, we find the most relevant context.
5. **Generate:** **Groq & Gemini** generates an accurate answer based ONLY on your data.
""")
st.markdown("---")
st.markdown("""
<h3 style='text-align: center; color: #427d44;'>π How to use ContextHub?</h3>
<br>
""", unsafe_allow_html=True)
col1, col2 = st.columns(2)
with col1:
st.markdown("""
<div class="feature-card">
<h4>1. Select your Source</h4>
<p>Choose between PDF, Image, Web, or Video tabs based on your needs.</p>
</div><br>
<div class="feature-card">
<h4>2. Upload & Process</h4>
<p>Click the process button to let Nomic, Groq & Gemini index your data.</p>
</div>
""", unsafe_allow_html=True)
with col2:
st.markdown("""
<div class="feature-card">
<h4>3. Ask Anything</h4>
<p>Type your query in the chat box. The AI answers <b>only</b> based on your data.</p>
</div><br>
<div class="feature-card">
<h4>4. Multi-Format Output</h4>
<p>Get summaries, tables, or code extracted directly from your sources.</p>
</div>
""", unsafe_allow_html=True)
st.divider()
st.caption("Developed by Varsha | Powered by Groq, Gemini, Pinecone & Nomic")
#########################################################################################################################
with tab1:
st.header("PDF Analysis")
if "file_processed" not in st.session_state:
st.session_state.file_processed = False
if "uploaded_filename" not in st.session_state:
st.session_state.uploaded_filename = None
if "pdf_answer" not in st.session_state:
st.session_state.pdf_answer = None
col1, col2 = st.columns([1, 1], gap="large")
with col1:
st.subheader("Upload & Preview")
uploaded_file = st.file_uploader(
"Choose a PDF file",
type="pdf",
label_visibility="collapsed",
key="pdf_input",
accept_multiple_files=False
)
if uploaded_file is not None:
file_bytes = uploaded_file.read()
base64_pdf = base64.b64encode(file_bytes).decode('utf-8')
pdf_display = f'<iframe src="data:application/pdf;base64,{base64_pdf}" width="100%" height="500" type="application/pdf"></iframe>'
st.markdown(pdf_display, unsafe_allow_html=True)
uploaded_file.seek(0)
if st.session_state.uploaded_filename != uploaded_file.name:
st.session_state.file_processed = False
st.session_state.pdf_answer = None
if not st.session_state.file_processed:
with st.spinner("Analyzing with AI..."):
try:
files = {
"file": (
uploaded_file.name,
uploaded_file.getvalue(),
"application/pdf"
)
}
response = requests.post(
f"{BACKEND_URL}/upload",
files=files
)
if response.status_code == 200:
st.success(response.json()['message'])
st.session_state.file_processed = True
st.session_state.uploaded_filename = uploaded_file.name
else:
st.error(f"Backend Error: {response.text}")
except Exception as e:
st.error(f"Connection Error: {e}")
else:
st.success(f"File '{uploaded_file.name}' already processed")
else:
st.info("Please select a PDF file first!")
if st.session_state.file_processed:
st.session_state.file_processed = False
st.session_state.uploaded_filename = None
st.session_state.pdf_answer = None
with col2:
st.subheader("Query Document")
user_query = st.text_input("Type any question from the PDF...")
ask_clicked = st.button("Ask pdf")
if ask_clicked:
if st.session_state.file_processed:
if user_query:
with st.spinner("Thinking..."):
try:
response = requests.post(
f"{BACKEND_URL}/query",
params={"query": user_query}
)
if response.status_code == 200:
st.session_state.pdf_answer = response.json().get("answer")
else:
st.error(f"Backend Error: {response.status_code}")
except Exception as e:
st.error(f"Connection Error: {e}")
else:
st.warning("Please type a question first!")
else:
st.error("Upload PDF first!")
if st.session_state.pdf_answer:
st.markdown("### Answer:")
st.write(st.session_state.pdf_answer)
#########################################################################################################################
with tab2:
st.header("πΌοΈ Image Intelligence")
if "image_processed" not in st.session_state:
st.session_state.image_processed = False
if "uploaded_image_name" not in st.session_state:
st.session_state.uploaded_image_name = None
col1, col2 = st.columns([1,1], gap='large')
with col1:
uploaded_image = st.file_uploader(
"Upload an image",
type=["jpg", "jpeg", "png"]
)
if uploaded_image is not None:
st.image(uploaded_image, caption="Uploaded Image", width="content")
if st.session_state.uploaded_image_name != uploaded_image.name:
st.session_state.image_processed = False
if not st.session_state.image_processed:
with st.spinner("Processing image..."):
try:
files = {
"file": (
uploaded_image.name,
uploaded_image.getvalue(),
"image/png"
)
}
response = requests.post(
f"{BACKEND_URL}/process-image",
files=files
)
if response.status_code == 200:
st.session_state.image_processed = True
st.session_state.uploaded_image_name = uploaded_image.name
st.success("Image processed!")
else:
st.error("Backend error")
except Exception as e:
st.error(f"Error: {e}")
else:
st.info("Upload an image to begin")
with col2:
query = st.text_input("Ask something about the image...")
ask_clicked_image = st.button("Ask Image")
if ask_clicked_image:
if st.session_state.image_processed:
if query:
with st.spinner("Analyzing with AI..."):
try:
response = requests.post(
f"{BACKEND_URL}/query-image",
params={"query": query}
)
if response.status_code == 200:
st.write(response.json().get("answer"))
else:
st.error("Backend error")
except Exception as e:
st.error(f"Error: {e}")
else:
st.warning("Enter a question")
else:
st.error("Upload image first!")
#########################################################################################################################
with tab3:
st.header("π URL Intelligence")
if "url_processed" not in st.session_state:
st.session_state.url_processed = False
if "current_url" not in st.session_state:
st.session_state.current_url = None
col1, col2 = st.columns([1,1], gap="large")
with col1:
url = st.text_input("Paste URL here")
if url:
if st.session_state.current_url != url:
st.session_state.url_processed = False
if not st.session_state.url_processed:
with st.spinner("Fetching website..."):
try:
response = requests.post(
f"{BACKEND_URL}/process-url",
params={"url": url}
)
if response.status_code == 200:
st.session_state.url_processed = True
st.session_state.current_url = url
st.success("URL processed!")
else:
st.error("Backend error")
except Exception as e:
st.error(f"Error: {e}")
else:
st.info("Enter a URL to begin")
with col2:
query = st.text_input("Ask something about the website...")
ask_clicked = st.button("Ask")
if ask_clicked:
if st.session_state.url_processed:
if query:
with st.spinner("Analyzing..."):
try:
response = requests.post(
f"{BACKEND_URL}/query-url",
params={"query": query}
)
if response.status_code == 200:
st.write(response.json().get("answer"))
else:
st.error("Backend error")
except Exception as e:
st.error(f"Error: {e}")
else:
st.warning("Enter a question")
else:
st.error("Process URL first!")
#########################################################################################################################
def get_video_id(url):
parsed_url = urlparse(url)
if "youtube.com" in url:
return parse_qs(parsed_url.query).get("v", [None])[0]
elif "youtu.be" in url:
return parsed_url.path.strip("/")
return None
# -------------------------------
with tab4:
st.header("π₯ YouTube Intelligence")
# -------- SESSION STATE --------
if "yt_processed" not in st.session_state:
st.session_state.yt_processed = False
if "yt_url" not in st.session_state:
st.session_state.yt_url = None
if "yt_input_key" not in st.session_state:
st.session_state.yt_input_key = 0
if "yt_answer" not in st.session_state:
st.session_state.yt_answer = None
if "yt_processing" not in st.session_state:
st.session_state.yt_processing = False
if "last_yt_call" not in st.session_state:
st.session_state.last_yt_call = 0
col1, col2 = st.columns([1, 1], gap="large")
# ---------------- LEFT SIDE ----------------
with col1:
st.subheader("π Video Input")
yt_url = st.text_input(
"Paste YouTube URL",
placeholder="https://www.youtube.com/watch?v=...",
key=f"yt_input_{st.session_state.yt_input_key}"
)
if yt_url:
video_id = get_video_id(yt_url)
if video_id:
col_img, col_clear = st.columns([8, 1])
# ---- CLEAR BUTTON ----
with col_clear:
if st.button("β"):
st.session_state.yt_processed = False
st.session_state.yt_url = None
st.session_state.yt_input_key += 1
st.session_state.yt_answer = None
st.rerun()
# ---- THUMBNAIL ----
with col_img:
st.image(
f"https://img.youtube.com/vi/{video_id}/maxresdefault.jpg",
use_container_width=True
)
# ---- PROCESS BUTTON ----
process_clicked = st.button(
"π Process Video",
disabled=st.session_state.yt_processing
)
if process_clicked:
# β
Avoid re-processing same video
if (
st.session_state.yt_url == yt_url
and st.session_state.yt_processed
):
st.info("β‘ Video already processed!")
else:
current_time = time.time()
# β
Rate limit protection
if current_time - st.session_state.last_yt_call < 2:
st.warning("β³ Please wait a moment...")
else:
st.session_state.last_yt_call = current_time
st.session_state.yt_processing = True
with st.spinner("Fetching & indexing transcript..."):
try:
response = requests.post(
f"{BACKEND_URL}/process-youtube",
json={"url": yt_url}
)
data = response.json()
if (
response.status_code == 200
and "error" not in data
):
st.session_state.yt_processed = True
st.session_state.yt_url = yt_url
st.success("β
Processed successfully!")
else:
st.error(
f"β {data.get('error', 'Unknown error')}"
)
except Exception as e:
st.error(f"Connection error: {e}")
st.session_state.yt_processing = False
# ---- READY MESSAGE ----
if st.session_state.yt_processed:
st.success("β
Ready! Ask questions β")
else:
st.error("β Invalid YouTube URL")
else:
st.info("π Paste a YouTube link to get started")
# ---------------- RIGHT SIDE ----------------
with col2:
query = st.text_input("Ask something about the YouTube video...")
ask_clicked = st.button("Ask the video")
if ask_clicked:
if not st.session_state.yt_processed:
st.error("Process a YouTube URL first!")
elif not query:
st.warning("Enter a question")
else:
with st.spinner("Analyzing..."):
try:
response = requests.post(
f"{BACKEND_URL}/query-youtube",
json={
"query": query,
"video_id": get_video_id(
st.session_state.yt_url
)
}
)
if response.status_code == 200:
st.session_state.yt_answer = response.json().get("answer")
else:
st.error("Backend error")
except Exception as e:
st.error(f"Error: {e}")
# ---- ANSWER DISPLAY ----
if st.session_state.yt_answer:
st.markdown("### Answer:")
st.write(st.session_state.yt_answer) |