Changes to UI

Changed response to be at 200 characters
Removed snippet from tfidf
def generate_search_summary
### 🔍 Summary
cached_search_summary

web_gui/streamlit.py

@@ -22,7 +22,7 @@ EMBEDDING_MODEL_NAME = "sentence-transformers/all-MiniLM-L6-v2"
 # System Instructions
 SYSTEM_PROMPT = HYDE_SYSTEM_PROMPT =(
     "You are a helpful assistant that answers questions about a manga and tv-series called One Piece. "
-    "Be brief and concise. Provide your answers in 100 words or less."
+    "Be brief and concise. Provide your answers in 200 words or less."
 )
 # HYDE_SYSTEM_PROMPT = (
 #     "You are a helpful assistant that generates a hypothetical answer to the user's question. "
@@ -35,6 +35,24 @@ st.set_page_config(page_title=PAGE_TITLE, layout="wide")
 @st.cache_resource
 def load_embedding_model():
     return SentenceTransformer(EMBEDDING_MODEL_NAME, device="cpu")
+
+@st.cache_data(show_spinner=False)
+def cached_search_summary(
+    query: str,
+    title_url_pairs: List[Tuple[str, str]]
+) -> str:
+    """
+    Cached wrapper for AI search summaries.
+    Converts hashable (title, url) pairs back into dicts.
+    """
+
+    results = [
+        {"title": title, "url": url}
+        for title, url in title_url_pairs
+    ]
+
+    return generate_search_summary(query, results)
+
 #####
 
 ###### Added - Radio button to switch between simple search engine and RAG agent
@@ -49,6 +67,37 @@ def render_mode_selector():
     return mode
 #####
 
+def generate_search_summary(query: str, results: List[Dict]) -> str:
+    """
+    Generates a short AI summary for TF-IDF search results.
+    Uses only titles + URLs (not internal cleaned text).
+    """
+
+    if not results:
+        return ""
+
+    sources_text = "\n".join(
+        f"- {r['title']} ({r['url']})"
+        for r in results
+        if r.get("url")
+    )
+
+    prompt = (
+        "You are a helpful assistant summarizing search results.\n\n"
+        f"User search query: {query}\n\n"
+        "Here are relevant pages:\n"
+        f"{sources_text}\n\n"
+        "Write a short, high-level summary (2–4 sentences) of what the user "
+        "is likely looking for. Do not list episodes. Be factual and concise."
+    )
+
+    messages = [
+        {"role": "system", "content": SYSTEM_PROMPT},
+        {"role": "user", "content": prompt}
+    ]
+
+    return query_llm(messages, max_tokens=150)
+
 # --- Helper Functions: Data Loading & Processing ---
 
 def load_texts_from_directory(base_dir: str) -> Dict[str, Dict]:
@@ -488,12 +537,22 @@ if mode == "TF-IDF Search":
     query = st.text_input("Search",placeholder="Search the One Piece corpus like Google…")
     
     if query:
-        results = st.session_state["tfidf_engine"].search(query, top_k=10)
+        results = st.session_state["tfidf_engine"].search(query, top_k=5)
+    
+        if results:
+            with st.spinner("Generating summary..."):
+                summary = cached_search_summary(query,
+                                                [(r["title"], r.get("url")) for r in results])
+    
+            if summary:
+                st.markdown("### 🔍 Summary")
+                st.write(summary)
+                st.divider()
     
         if not results:
             st.info("No results found.")
         else:
-            st.caption(f"Showing {len(results)} results")
+            st.caption("Top 5 relevant pages")
     
             for i, r in enumerate(results, start=1):
                 st.markdown(f"### {i}. {r['title']}")
@@ -502,5 +561,4 @@ if mode == "TF-IDF Search":
                 if r.get("url"):
                     st.markdown(r["url"])
     
-                st.write(r["snippet"])
                 st.divider()