app.py

import gradio as gr
import random
from huggingface_hub import InferenceClient
from sentence_transformers import SentenceTransformer
import torch

with open("knowledge.txt", "r", encoding="utf-8") as file:
  recent = file.read()

cleaned_text = recent.strip()
chunks = cleaned_text.split("\n")
cleaned_chunks = []

for chunk in chunks:
  stripped_chunk = chunk.strip()
  if stripped_chunk:
    cleaned_chunks.append(stripped_chunk)

model = SentenceTransformer('all-MiniLM-L6-v2')

chunk_embeddings = model.encode(cleaned_chunks, convert_to_tensor=True)

def get_top_chunks(query):
  query_embedding = model.encode(query, convert_to_tensor=True)
  query_embedding_normalized = query_embedding / query_embedding.norm()
  chunk_embeddings_normalized = chunk_embeddings / chunk_embeddings.norm(dim=1, keepdim=True)
  similarities = torch.matmul(chunk_embeddings_normalized, query_embedding_normalized)

  top_indices = torch.topk(similarities, k=3).indices

  top_chunks = []

  for i in top_indices:
    chunk = chunks[i]
    top_chunks.append(chunk)
      
  return top_chunks
    
client = InferenceClient('HuggingFaceH4/zephyr-7b-beta')

def respond(message,history):
    gift_ideas = get_top_chunks(message)
    messages = [{'role': 'system', 'content': f'You give really good gift ideas and are super helpful! You also tell me the price of each item. Give me 5 gift ideas if I ask. Use the following database for gift ideas: {gift_ideas}'}]
    
    if history:
        messages.extend(history)
    
    messages.append({"role": "user", "content": message})

    response = client.chat_completion(
        messages,
        max_tokens = 500,
    )
        
    return response['choices'][0]['message']['content'].strip() 


with gr.Blocks(theme='hmb/amethyst') as demo:
    gr.Image(value="wrap_it_top_image.png", show_label=False, elem_id="top-image")

    gr.Markdown("## 🎁 Introducing WrapIT!")
    gr.Markdown("**WrapIT** helps users find personalized gift ideas and craft thoughtful card messages by inputting details like the recipient's interests, celebration type, and budget ✨ *All you have to do is wrap it.*")
    
    gr.ChatInterface(
        fn=respond,
        examples=["Best birthday gift?", "Romantic anniversary idea?", "Budget-friendly gifts?"]
    )

    with gr.Row():
        gr.HTML(
            """
            <iframe style="border-radius:12px"
                    src="https://open.spotify.com/embed/track/4356Typ82hUiFAynbLYbPn"
                    width="100%"
                    height="152"
                    frameBorder="0"
                    allowfullscreen=""
                    allow="autoplay; clipboard-write; encrypted-media; fullscreen; picture-in-picture"
                    loading="lazy">
            </iframe>
            """
        )

demo.launch(debug=True, share=True)