Update app.py

app.py

@@ -1,24 +1,99 @@
 import gradio as gr
+import pandas as pd
 from huggingface_hub import InferenceClient
 
 client = InferenceClient("Qwen/Qwen2.5-7B-Instruct")
 
+#load the book knowledge base
+books = pd.read_csv("knowledge_base.csv")
+books = books[["Title", "Author", "Genre", "Age_Range", "Description"]]
+books = books.dropna(subset=["Title", "Author", "Genre", "Description"])
+
+def search_books(ques, max_givenbooks=5):
+    """Searches the dataframe for rows matching keywords in the user's message. Looks across Title, Genre, and Description columns. """
+    if not ques:
+        return ""
+        
+    ques = str(ques).lower()
+    keywords = ques.split()
+    matches = pd.Series(False, index=books.index)
+
+    for word in keywords:
+        matches = matches | (
+            books["Title"].str.lower().str.contains(word, na=False) |
+            books["Genre"].str.lower().str.contains(word, na=False) |
+            books["Description"].str.lower().str.contains(word, na=False)
+        )
+
+    matched_books = books[matches].head(max_givenbooks)
+    if matched_books.empty:
+        return "No exact matches found in the catalog for this description."
+        
+    results_in = "Available books in our catalog matching your request:\n"
+    for idx, row in matched_books.iterrows():
+        results_in += f" - **Title** : {row['Title']} | **Author** : {row['Author']} | **Genre** : {row['Genre']} | **Age** : {row['Age_Range']}\n"
+        results_in += f" *Description* : {row['Description']}\n\n"
+    return results_in
 def respond(message, history):
+    catalog_info = search_books(message)
+
+    instructions = f"""You are the BookBuddy, who is a specialized book recommendation chatbot. 
+    Your goal is to recommend books to the user based on what they want. Use the catalog  from our database to answer the user. 
+    Prioritize the recommending books from this list if they match the user's perferences:
     
-    messages = [{"role": "system", "content": "You are a friendly chatbot."}]
+    {catalog_info}"""
     
+    messages = [{"role": "system", "content": instructions}]
     if history:
         messages.extend(history)
         
     messages.append({"role": "user", "content": message})
     
     response = client.chat_completion(
-        messages,
-        max_tokens=100
+        messages=messages,
+        max_tokens=220
     )
     
     return response.choices[0].message.content.strip()
 
-chatbot = gr.ChatInterface(respond)
+with gr.Blocks(
+    theme=gr.themes.Soft(primary_hue="pink"),
+    css="""
+    body {
+        background-color: #ffccc7;
+    }
+    """
+) as demo:
+
+    gr.Image("BookBuddy.png", show_label=False)
+
+    gr.Markdown(
+        """
+        # 📚 BookBuddy AI
+        ### Your personal AI book recommender powered, BookBuddy. Ask for genres, moods, or books you love.
+        """
+    )
+
+    chatbot = gr.ChatInterface(
+        fn=respond,
+        examples=[
+            "I want a sad romance book",
+            "Give me a fantasy book for teens",
+            "Something like The Hunger Games",
+            "A mystery with twists",
+            "I liked Harry Potter, what should I read?",
+            "I'm 15 and love contemporary books, what should I read?",
+            "Recommend a fast-paced dystopian story",
+            "Give me a book that will make me cry"
+        ]
+    )
+
+    gr.Markdown(
+        """
+        <div style="text-align:center; padding-top:15px; color:#2d2d3b;">
+        “A reader lives a thousand lives before they die.” – George R.R. Martin ☕📖
+        </div>
+        """
+    )
 
-chatbot.launch()
+demo.launch(share=True)