Update src/streamlit_app.py

src/streamlit_app.py

@@ -1,40 +1,84 @@
-import altair as alt
-import numpy as np
-import pandas as pd
+import os
 import streamlit as st
+import requests
+import json
+from bs4 import BeautifulSoup
+import re
+from difflib import SequenceMatcher
 
-"""
-# Welcome to Streamlit!
-
-Edit `/streamlit_app.py` to customize this app to your heart's desire :heart:.
-If you have any questions, checkout our [documentation](https://docs.streamlit.io) and [community
-forums](https://discuss.streamlit.io).
-
-In the meantime, below is an example of what you can do with just a few lines of code:
-"""
-
-num_points = st.slider("Number of points in spiral", 1, 10000, 1100)
-num_turns = st.slider("Number of turns in spiral", 1, 300, 31)
-
-indices = np.linspace(0, 1, num_points)
-theta = 2 * np.pi * num_turns * indices
-radius = indices
-
-x = radius * np.cos(theta)
-y = radius * np.sin(theta)
-
-df = pd.DataFrame({
-    "x": x,
-    "y": y,
-    "idx": indices,
-    "rand": np.random.randn(num_points),
-})
-
-st.altair_chart(alt.Chart(df, height=700, width=700)
-    .mark_point(filled=True)
-    .encode(
-        x=alt.X("x", axis=None),
-        y=alt.Y("y", axis=None),
-        color=alt.Color("idx", legend=None, scale=alt.Scale()),
-        size=alt.Size("rand", legend=None, scale=alt.Scale(range=[1, 150])),
-    ))
+# Fix Streamlit permission issue
+os.environ['STREAMLIT_HOME'] = '/tmp/.streamlit'
+
+API_URL = "https://jishnusetia-ollama-server.hf.space/api/generate"
+MODEL = "llama3.2"
+
+st.title("🌐 Chat with a Website (Ollama)")
+
+# Store website content in memory
+if "chunks" not in st.session_state:
+    st.session_state.chunks = []
+if "chat_history" not in st.session_state:
+    st.session_state.chat_history = []
+
+# Helper: clean and chunk text
+def clean_and_chunk(text, chunk_size=800):
+    text = re.sub(r'\s+', ' ', text).strip()
+    return [text[i:i+chunk_size] for i in range(0, len(text), chunk_size)]
+
+# Helper: get top N relevant chunks
+def get_relevant_chunks(query, chunks, top_n=3):
+    scored = [(SequenceMatcher(None, query, chunk).ratio(), chunk) for chunk in chunks]
+    scored.sort(key=lambda x: x[0], reverse=True)
+    return [chunk for _, chunk in scored[:top_n]]
+
+# Step 1: User inputs website
+url = st.text_input("Enter website URL:")
+
+if st.button("Fetch Website") and url:
+    try:
+        resp = requests.get(url, timeout=10)
+        soup = BeautifulSoup(resp.text, 'html.parser')
+        for script in soup(["script", "style"]):
+            script.extract()
+        text = soup.get_text()
+        st.session_state.chunks = clean_and_chunk(text)
+        st.success(f"Website fetched! {len(st.session_state.chunks)} chunks ready.")
+    except Exception as e:
+        st.error(f"Error fetching website: {e}")
+
+# Step 2: Function to send query to Ollama
+def send_message(message, context):
+    prompt = f"Answer the following question based on this context:\n{context}\n\nQuestion: {message}"
+    payload = {"model": MODEL, "prompt": prompt}
+    response = requests.post(API_URL, json=payload, stream=True)
+
+    if response.ok:
+        reply = ""
+        for line in response.iter_lines():
+            if line:
+                data = json.loads(line.decode('utf-8'))
+                reply += data.get("response", "")
+        return reply.strip()
+    else:
+        return "⚠️ Error: Failed to get response from Ollama API."
+
+# Step 3: Chat input
+user_input = st.text_input("Ask a question about the website:")
+
+if st.button("Send Question") and user_input.strip():
+    if not st.session_state.chunks:
+        st.error("Please fetch a website first.")
+    else:
+        st.session_state.chat_history.append(("You", user_input))
+        with st.spinner("Thinking..."):
+            context = "\n".join(get_relevant_chunks(user_input, st.session_state.chunks))
+            bot_reply = send_message(user_input, context)
+        st.session_state.chat_history.append(("Ollama", bot_reply))
+
+# Step 4: Display chat history
+st.subheader("Chat History")
+for speaker, message in st.session_state.chat_history:
+    if speaker == "You":
+        st.markdown(f"**You:** {message}")
+    else:
+        st.markdown(f"**🤖 Ollama:** {message}")