final touches

app.py

@@ -2,6 +2,7 @@ import pandas as pd
 import gradio as gr
 import numpy as np
 import os
+import re
 from langchain_chroma import Chroma
 from langchain_huggingface import HuggingFaceEmbeddings
 from langchain_community.document_loaders import TextLoader
@@ -33,7 +34,7 @@ if not os.path.exists("chroma_books"):
         )
         documents = text_splitter.split_documents(raw_docs)
         print(f"Loaded {len(documents)} documents")
-        
+
         db_books = Chroma.from_documents(
             documents,
             embedding=embeddings,
@@ -47,8 +48,8 @@ if not os.path.exists("chroma_books"):
 else:
     print("Loading existing ChromaDB...")
     db_books = Chroma(
-        persist_directory="chroma_books", 
-        embedding_function=embeddings, 
+        persist_directory="chroma_books",
+        embedding_function=embeddings,
         collection_name="books"
     )
 
@@ -57,11 +58,17 @@ print("Loading books data...")
 try:
     books = pd.read_csv("final_book_df.csv")
     books["large_thumbnail"] = books["thumbnail"] + "&fife=w800"
+    # Better fallback image handling
     books["large_thumbnail"] = np.where(
-        books["large_thumbnail"].isna(), 
-        "cover-not-found.jpg", 
+        books["large_thumbnail"].isna() | books["thumbnail"].isna(),
+        "https://via.placeholder.com/120x180/333333/cccccc?text=No+Cover",
         books["large_thumbnail"]
     )
+    # Ensure 'authors' and 'categories' are string type for literal search
+    books['authors'] = books['authors'].astype(str)
+    books['categories'] = books['categories'].astype(str)
+    books['title_and_subtitle'] = books['title_and_subtitle'].astype(str)
+
     print(f"Loaded {len(books)} books")
 except FileNotFoundError:
     print("ERROR: final_book_df.csv not found!")
@@ -72,19 +79,17 @@ def retrieve_semantic_recommendations(
         category: str = None,
         tone: str = None,
         initial_top_k: int = 50,
-        final_top_k: int = 8,  # Reduced for better display
+        final_top_k: int = 8,
 ) -> pd.DataFrame:
     """Retrieve semantic recommendations based on query, category, and tone."""
-    
+
     recs = db_books.similarity_search(query, k=initial_top_k)
     books_list = [int(rec.page_content.strip('"').split()[0]) for rec in recs]
     book_recs = books[books["isbn13"].isin(books_list)].head(initial_top_k)
 
     # Filter by category
     if category and category != "All":
-        book_recs = book_recs[book_recs["categories"] == category].head(final_top_k)
-    else:
-        book_recs = book_recs.head(final_top_k)
+        book_recs = book_recs[book_recs["categories"] == category]
 
     # Sort by emotional tone
     if tone == "Happy":
@@ -98,19 +103,101 @@ def retrieve_semantic_recommendations(
     elif tone == "Sad":
         book_recs = book_recs.sort_values(by="sadness", ascending=False)
 
-    return book_recs
+    return book_recs.head(final_top_k)
+
+def retrieve_literal_recommendations(
+        query: str,
+        category: str = None,
+        tone: str = None,
+        final_top_k: int = 8,
+) -> pd.DataFrame:
+    """Retrieve literal recommendations using flexible regex pattern matching."""
+    if not query.strip():
+        return pd.DataFrame()
+    
+    # Create flexible regex pattern - matches partial words and handles word boundaries
+    query_words = query.lower().strip().split()
+    
+    # Create regex patterns for each word that can match anywhere in the text
+    patterns = []
+    for word in query_words:
+        # Escape special regex characters and create flexible pattern
+        escaped_word = re.escape(word)
+        # Pattern that matches the word with optional word boundaries
+        pattern = f".*{escaped_word}.*"
+        patterns.append(pattern)
+    
+    # Combine patterns with OR logic for flexible matching
+    combined_pattern = "|".join(patterns)
+    
+    try:
+        # Search in title, subtitle, and authors using regex
+        title_matches = books['title_and_subtitle'].str.contains(
+            combined_pattern, case=False, na=False, regex=True
+        )
+        author_matches = books['authors'].str.contains(
+            combined_pattern, case=False, na=False, regex=True
+        )
+        
+        # Combine both matches
+        literal_recs = books[title_matches | author_matches].copy()
+        
+        # If no results with combined pattern, try individual word patterns
+        if literal_recs.empty and len(query_words) > 1:
+            for word in query_words:
+                escaped_word = re.escape(word.lower())
+                pattern = f".*{escaped_word}.*"
+                
+                word_title_matches = books['title_and_subtitle'].str.contains(
+                    pattern, case=False, na=False, regex=True
+                )
+                word_author_matches = books['authors'].str.contains(
+                    pattern, case=False, na=False, regex=True
+                )
+                
+                word_matches = books[word_title_matches | word_author_matches].copy()
+                literal_recs = pd.concat([literal_recs, word_matches]).drop_duplicates()
+                
+                if len(literal_recs) >= final_top_k:
+                    break
+
+    except re.error:
+        # Fallback to simple string matching if regex fails
+        query_lower = query.lower()
+        literal_recs = books[
+            books['title_and_subtitle'].str.contains(query_lower, case=False, na=False) |
+            books['authors'].str.contains(query_lower, case=False, na=False)
+        ].copy()
+
+    # Filter by category
+    if category and category != "All":
+        literal_recs = literal_recs[literal_recs["categories"] == category]
+
+    # Sort by emotional tone
+    if tone == "Happy":
+        literal_recs = literal_recs.sort_values(by="joy", ascending=False)
+    elif tone == "Surprising":
+        literal_recs = literal_recs.sort_values(by="surprise", ascending=False)
+    elif tone == "Angry":
+        literal_recs = literal_recs.sort_values(by="anger", ascending=False)
+    elif tone == "Suspenseful":
+        literal_recs = literal_recs.sort_values(by="fear", ascending=False)
+    elif tone == "Sad":
+        literal_recs = literal_recs.sort_values(by="sadness", ascending=False)
+
+    return literal_recs.head(final_top_k)
 
 def create_book_card_html(row):
     """Create an HTML card for a single book with full description, ratings, and download link."""
-    
+
     # Handle missing description
     description = row.get("description", "No description available")
     if pd.isna(description):
         description = "No description available"
-    
+
     # Format authors
     authors = row.get("authors", "Unknown Author")
-    if pd.isna(authors):
+    if pd.isna(authors) or authors == "nan":
         authors_str = "Unknown Author"
     else:
         authors_split = str(authors).split(";")
@@ -120,17 +207,17 @@ def create_book_card_html(row):
             authors_str = f"{', '.join(authors_split[:-1])}, and {authors_split[-1]}"
         else:
             authors_str = authors
-    
+
     # Get other info
     title = row.get("title_and_subtitle", "Unknown Title")
-    thumbnail = row.get("large_thumbnail", "cover-not-found.jpg")
+    thumbnail = row.get("large_thumbnail", "https://via.placeholder.com/120x180/333333/cccccc?text=No+Cover")
     download_url = row.get("url", "")
     category = row.get("categories", "Unknown")
-    
+
     # Handle ratings
     average_rating = row.get("average_rating", 0)
     ratings_count = row.get("ratings_count", 0)
-    
+
     # Convert to proper numeric values
     try:
         avg_rating = float(average_rating) if not pd.isna(average_rating) else 0
@@ -138,14 +225,14 @@ def create_book_card_html(row):
     except (ValueError, TypeError):
         avg_rating = 0
         rating_count = 0
-    
+
     # Create star rating display
     def create_star_rating(rating):
         """Create HTML for star rating display."""
         full_stars = int(rating)
         half_star = 1 if (rating - full_stars) >= 0.5 else 0
         empty_stars = 5 - full_stars - half_star
-        
+
         stars_html = ""
         # Full stars
         stars_html += "★" * full_stars
@@ -154,9 +241,9 @@ def create_book_card_html(row):
             stars_html += "☆"
         # Empty stars
         stars_html += "☆" * empty_stars
-        
+
         return stars_html
-    
+
     # Format rating display
     if avg_rating > 0:
         stars = create_star_rating(avg_rating)
@@ -174,56 +261,58 @@ def create_book_card_html(row):
             <span style="color: #888888; font-size: 10px;">No ratings</span>
         </div>
         """
-    
+
     # Create download button if URL exists
     download_button = ""
     if download_url and not pd.isna(download_url) and str(download_url).strip():
         download_button = f"""
         <div style="margin-top: 6px;">
-            <a href="{download_url}" target="_blank" 
-               style="background-color: #4CAF50; color: white; padding: 6px 12px; 
-                      text-decoration: none; border-radius: 4px; font-size: 10px; 
+            <a href="{download_url}" target="_blank"
+               style="background-color: #4CAF50; color: white; padding: 6px 12px;
+                      text-decoration: none; border-radius: 4px; font-size: 10px;
                       display: inline-block; text-align: center;">
                 📖 Get Book
             </a>
         </div>
         """
-    
-    # Create the card HTML with responsive design
+
+    # Create the card HTML with responsive design and better image fallback
     card_html = f"""
-    <div style="border: 1px solid #444; border-radius: 8px; padding: 12px; margin: 10px 0; 
+    <div style="border: 1px solid #444; border-radius: 8px; padding: 12px; margin: 10px 0;
                 background-color: #2b2b2b; box-shadow: 0 2px 4px rgba(0,0,0,0.3);">
-        
+
         <div style="display: flex; gap: 12px; flex-direction: row;">
             <div style="flex-shrink: 0;">
-                <img src="{thumbnail}" alt="Book cover" 
-                     style="width: 80px; height: 120px; object-fit: cover; border-radius: 4px;">
+                <img src="{thumbnail}" alt="Book cover"
+                     style="width: 80px; height: 120px; object-fit: cover; border-radius: 4px; 
+                            background-color: #333; border: 1px solid #555;"
+                     onerror="this.src='https://via.placeholder.com/120x180/333333/cccccc?text=No+Cover';">
             </div>
-            
+
             <div style="flex-grow: 1; min-width: 0; display: flex; flex-direction: column;">
-                <h3 style="margin: 0 0 6px 0; color: #ffffff; font-size: 14px; line-height: 1.2; 
-                           word-wrap: break-word; overflow-wrap: break-word;">
+                <h3 style="margin: 0 0 6px 0; color: #ffffff; font-size: 14px; line-height: 1.2;
+                            word-wrap: break-word; overflow-wrap: break-word;">
                     {title}
                 </h3>
-                
+
                 <p style="margin: 0 0 4px 0; color: #cccccc; font-size: 11px; font-style: italic;">
                     {authors_str}
                 </p>
-                
+
                 <p style="margin: 0 0 4px 0; color: #aaaaaa; font-size: 10px;">
                     {category}
                 </p>
-                
+
                 {rating_display}
-                
+
                 <div style="flex-grow: 1; margin: 6px 0;">
-                    <p style="margin: 0; color: #dddddd; font-size: 11px; line-height: 1.3; 
-                              display: -webkit-box; -webkit-line-clamp: 4; -webkit-box-orient: vertical; 
+                    <p style="margin: 0; color: #dddddd; font-size: 11px; line-height: 1.3;
+                              display: -webkit-box; -webkit-line-clamp: 4; -webkit-box-orient: vertical;
                               overflow: hidden; text-overflow: ellipsis;">
                         {description}
                     </p>
                 </div>
-                
+
                 {download_button}
             </div>
         </div>
@@ -231,60 +320,97 @@ def create_book_card_html(row):
     """
     return card_html
 
-def recommend_books(query: str, category: str, tone: str):
+def recommend_books(query: str, category: str, tone: str, search_type: str):
     """Main recommendation function for Gradio interface."""
-    
+
     if not query.strip():
         return "<p>Please enter a search query to get book recommendations.</p>"
-    
+
     try:
-        recommendations = retrieve_semantic_recommendations(query, category, tone)
-        
+        if search_type == "Semantic Search":
+            recommendations = retrieve_semantic_recommendations(query, category, tone)
+        elif search_type == "Literal Search":
+            recommendations = retrieve_literal_recommendations(query, category, tone)
+        else:
+            return "<p>Invalid search type selected.</p>"
+
         if recommendations.empty:
             return "<p>No books found matching your criteria. Try adjusting your search terms or filters.</p>"
-        
+
         # Create HTML for all book cards
         html_cards = []
         for _, row in recommendations.iterrows():
             card_html = create_book_card_html(row)
             html_cards.append(card_html)
-        
+
         # Combine all cards with a header
         full_html = f"""
         <div style="font-family: Arial, sans-serif; background-color: #1a1a1a; padding: 20px; border-radius: 8px;">
             <h2 style="color: #ffffff; margin-bottom: 20px;">
-                📚 Found {len(recommendations)} recommendations for: "{query}"
+                📚 Found {len(recommendations)} recommendations for: "{query}" ({search_type})
             </h2>
             {''.join(html_cards)}
         </div>
         """
-        
+
         return full_html
-    
+
     except Exception as e:
         print(f"Error in recommend_books: {e}")
         return f"<p>An error occurred while searching for books: {str(e)}</p>"
 
+def update_search_interface(search_type):
+    """Update the interface based on search type selection."""
+    if search_type == "Literal Search":
+        return {
+            search_instructions: gr.update(
+                value="**Literal Search Mode:** Type book titles or author names directly. Supports partial matching - e.g., 'harry' will find 'Harry Potter', 'tolkien' will find J.R.R. Tolkien books.", 
+                visible=True
+            )
+        }
+    else:
+        return {
+            search_instructions: gr.update(
+                value="**Semantic Search Mode:** Describe what kind of book you're looking for using natural language - e.g., 'fantasy adventure with magic'.", 
+                visible=True
+            )
+        }
+
 # Prepare dropdown options
 categories = ["All"] + sorted(books["categories"].unique().tolist())
 tones = ["All", "Happy", "Surprising", "Angry", "Suspenseful", "Sad"]
+search_types = ["Semantic Search", "Literal Search"]
 
 # Create Gradio interface
 with gr.Blocks(theme=gr.themes.Soft()) as dashboard:
     gr.Markdown("""
-    # 📚 Semantic Book Recommender
-    ## Find your next favorite book using AI-powered semantic search!
-    
-    Enter a description of what you're looking for, and our AI will find books that match your interests using semantic understanding.
+    # 📚 Smart Book Recommender
+    ## Find your next favorite book using AI-powered semantic search or flexible keyword matching!
+
+    **Semantic Search:** Describe what you want (e.g., "romantic comedy in Paris")  
+    **Literal Search:** Type exact titles or authors (e.g., "harry" → Harry Potter books)
     """)
 
     with gr.Row():
         with gr.Column(scale=2):
+            search_type_radio = gr.Radio(
+                choices=search_types,
+                value="Semantic Search",
+                label="Search Type",
+                interactive=True
+            )
+            
+            search_instructions = gr.Markdown(
+                "**Semantic Search Mode:** Describe what kind of book you're looking for using natural language - e.g., 'fantasy adventure with magic'.",
+                visible=True
+            )
+            
+            # Single search input for both modes
             user_query = gr.Textbox(
-                label="Describe your ideal book:",
-                placeholder="e.g., 'A thrilling mystery set in Victorian London with complex characters'",
-                lines=3,
-                max_lines=5,
+                label="Search for books:",
+                placeholder="e.g., 'harry potter' or 'thrilling mystery in Victorian London'",
+                lines=2,
+                max_lines=4
             )
 
         with gr.Column(scale=1):
@@ -301,37 +427,44 @@ with gr.Blocks(theme=gr.themes.Soft()) as dashboard:
             submit_button = gr.Button("🔍 Find Books", variant="primary", size="lg")
 
     gr.Markdown("---")
-    
-    # Use HTML component instead of Gallery for better text display
+
+    # Use HTML component for book display
     output = gr.HTML(
         label="Book Recommendations",
-        value="<p>Enter a search query above to get personalized book recommendations!</p>"
+        value="<p>Select a search type and enter your preferences to get personalized book recommendations!</p>"
     )
 
     # Event handlers
+    search_type_radio.change(
+        fn=update_search_interface,
+        inputs=[search_type_radio],
+        outputs=[search_instructions]
+    )
+    
     submit_button.click(
         fn=recommend_books,
-        inputs=[user_query, category_dropdown, tone_dropdown],
+        inputs=[user_query, category_dropdown, tone_dropdown, search_type_radio],
         outputs=output,
     )
-    
+
     # Allow Enter key to submit
     user_query.submit(
         fn=recommend_books,
-        inputs=[user_query, category_dropdown, tone_dropdown],
+        inputs=[user_query, category_dropdown, tone_dropdown, search_type_radio],
         outputs=output,
     )
 
     # Add some usage tips at the bottom
     gr.Markdown("""
     ### 💡 Tips for better results:
-    - Be specific about what you're looking for (genre, setting, themes, etc.)
-    - Try different emotional tones to discover books with specific moods
-    - Use category filters to narrow down results
-    - Experiment with different search terms if you don't find what you're looking for
+    - **Semantic Search:** Be descriptive (e.g., "dark fantasy with dragons", "romance set in medieval times")
+    - **Literal Search:** Use partial names (e.g., "tolkien", "stephen king", "harry", "game thrones")
+    - **Flexible Matching:** Literal search finds books even with partial words - "potter" finds "Harry Potter"
+    - **Combine filters:** Use category and tone filters to narrow down results
+    - **Try variations:** If you don't find what you want, try different keywords or switch search modes
     """)
 
-print("Enhanced app initialized successfully! 🚀")
+print("Enhanced app with flexible regex search initialized successfully! 🚀")
 
 if __name__ == "__main__":
     dashboard.launch()

chroma_books/chroma.sqlite3

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:63cd7d57fc1a836468777f10e68d40c6ef3d8cf4cb738814120600b094bea4bd
+oid sha256:b007abac0926b25c496417adc8d3d6279831b7b029beb187b9f5028b05d804d2
 size 34754560