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import streamlit as st
from scripts.recommender import load_data, recommend_movies
from agent import generate_retention_tip
st.set_page_config(page_title="StreamWiseAI", layout="wide")
st.title("🎬 StreamWiseAI – Personalized Movie Recommender & Retention Coach")
st.caption("🤖 Powered by AI Agents · 🎯 Smart Search · 🧠 AI Insights")
# Load data
movies, embeddings = load_data()
# Initialize watch history
if "watch_history" not in st.session_state:
st.session_state["watch_history"] = []
# Search input
movie_input = st.text_input("Enter a movie you liked", placeholder="e.g. Toy Story")
show_tip = st.checkbox("💡 Show retention insight from AI coach?", value=True)
if movie_input:
with st.spinner("Finding great recommendations..."):
recommendations = recommend_movies(movie_input, movies, embeddings)
if not recommendations:
st.error("❌ Movie not found. Please try another title.")
else:
st.subheader(f"📽️ Recommendations for **{recommendations['input_title']}**")
if recommendations["input_title"] not in st.session_state["watch_history"]:
st.session_state["watch_history"].append(recommendations["input_title"])
cols = st.columns(2)
for idx, rec in enumerate(recommendations["results"]):
with cols[idx % 2]:
with st.container():
st.markdown("#### 🎬 " + rec['title'] + f" ({rec['release_year']})")
# Fallback-safe image
if rec['poster_path']:
st.image(f"https://image.tmdb.org/t/p/w200{rec['poster_path']}", width=150)
else:
st.image("https://via.placeholder.com/150x225.png?text=No+Image", width=150)
st.markdown(f"**🎭 Genre(s):** {rec['genres']}")
st.markdown(f"**🧠 Similarity Score:** {rec['similarity']:.2f}")
# Truncate overview if too long
short_overview = rec['overview']
if len(short_overview) > 250:
short_overview = short_overview[:250] + "..."
st.markdown(f"_{short_overview}_")
st.markdown("---")
if show_tip:
with st.spinner("🤖 Retention Coach is analyzing your taste..."):
tip = generate_retention_tip(movie_input, recommendations["results"], st.session_state.get("watch_history", []))
if tip and not tip.startswith("⚠️"):
st.markdown("### 💡 Retention Coach Suggests:")
st.markdown(f"""
<div style="background-color:#f0f8ff; padding:15px; border-radius:10px; border-left:5px solid #1f77b4;">
<span style="font-size:16px;">{tip}</span>
</div>
""", unsafe_allow_html=True)
else:
st.warning("Couldn't generate tip at the moment.")
with st.sidebar:
st.markdown("## 🎬 **About StreamWiseAI**")
st.markdown("""
<span style='color:#6c63ff'><strong>StreamWiseAI</strong></span> is a personalized movie discovery engine designed for modern streaming platforms.
Built to impress recruiters and mimic real-world production use cases, it features:
🔍 <span style='color:#FFA500'><strong>Semantic Search</strong></span> — understands meaning, not just keywords
🧠 <span style='color:#00BFFF'><strong>AI Retention Coach</strong></span> — LLM agent gives viewing tips
🗂️ <span style='color:#32CD32'><strong>Watch History Memory</strong></span> — tracks user session dynamically
🚀 <span style='color:#FF69B4'><strong>Built for Showcase</strong></span> — Fast, deployable & free
---
<small><i>Tech stack: Sentence Transformers · Streamlit · OpenRouter LLM API · Fuzzy Matching · Vector Index</i></small>
""", unsafe_allow_html=True)
if st.session_state["watch_history"]:
st.divider()
with st.expander("📜 Recently Searched"):
st.markdown("👀 Here’s a list of your recent searches:")
st.markdown("\n".join(f"- {title}" for title in st.session_state["watch_history"]))
st.markdown("---")
st.markdown(
"<small>🚀 Built by Rajesh Marudhachalam</small>",
unsafe_allow_html=True
) |