import gradio as gr from huggingface_hub import InferenceClient from sentence_transformers import SentenceTransformer import torch # Load knowledge with open("recipesplease.txt", "r", encoding="utf-8") as file: knowledge = file.read() cleaned_chunks = [chunk.strip() for chunk in knowledge.strip().split("\n") if chunk.strip()] 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() similarities = torch.matmul(chunk_embeddings, query_embedding_normalized) top_indices = torch.topk(similarities, k=5).indices.tolist() return [cleaned_chunks[i] for i in top_indices] client = InferenceClient("Qwen/Qwen2.5-72B-Instruct") def respond(message, history, cuisine, dietary_restrictions, allergies, preferred_ingredient): response = "" top_chunks = get_top_chunks(message) top_chunks += get_top_chunks(cuisine) top_chunks += get_top_chunks(str(dietary_restrictions)) # convert list to str top_chunks += get_top_chunks(allergies) top_chunks += get_top_chunks(preferred_ingredient) print(top_chunks) messages = [ { "role": "system", "content": f""" You are BiteBot, a friendly recipe chatbot. Use only the recipes from the following content: {top_chunks}. The user prefers {cuisine} cuisine, has the following dietary restrictions: {dietary_restrictions}, and is allergic to: {allergies}. Suggest one suitable recipe that matches these preferences. Say something like: "Based on your preferences, would you like to try Elizabeth's Sweet Potato Casserole?" If they say yes: - First, share the ingredients. - Then ask if they'd like the instructions. - If they agree, provide the instructions. If they say no: - Ask if they'd like another recommendation. Always use recipes only from {top_chunks}. """ } ] if history: messages.extend(history) messages.append({"role": "user", "content": message}) stream = client.chat_completion( messages, max_tokens=700, temperature=1.5,top_p=0.7, stream=True, ) for message in stream: token = message.choices[0].delta.content if token is not None: response += token yield response logo="banner.png" theme = gr.themes.Monochrome( primary_hue="orange", secondary_hue="zinc", neutral_hue=gr.themes.Color(c100="rgba(255, 227.4411088400613, 206.9078947368421, 1)", c200="rgba(255, 229.53334184977007, 218.0921052631579, 1)", c300="rgba(255, 234.91658150229947, 213.6184210526316, 1)", c400="rgba(189.603125, 154.41663986650488, 133.88641721491229, 1)", c50="#f3d1bbff", c500="rgba(170.2125, 139.18781968574348, 118.70082236842106, 1)", c600="rgba(193.32187499999998, 129.35648241888094, 111.07528782894737, 1)", c700="rgba(184.13125000000002, 141.9707339039346, 106.60230263157897, 1)", c800="rgba(156.06796875, 104.12209005333418, 69.81988075657894, 1)", c900="rgba(156.39999999999998, 117.22008175779253, 80.2578947368421, 1)", c950="rgba(158.43203125, 125.1788770279765, 97.28282620614036, 1)"), text_size="sm", spacing_size="md", radius_size="sm", ).set( body_background_fill='*primary_50', body_background_fill_dark='*primary_50' ) with gr.Blocks(theme=theme) as chatbot: gr.Image( value="Henrietta.png", show_label=False, show_share_button = False, show_download_button = False) gr.Markdown("### 👋 Welcome to BiteBot!\nTell me your preferred **cuisine**, any **dietary restrictions**, and **allergies**, and I’ll help you figure out what to cook. You can ask questions like:\n- _“What should I make tonight?”_\n- _“I'm feeling like eating something spicy.”_\n- _“Give me a recipe extra cheesy”_") cuisine=gr.Textbox(label="cuisine") dietary_restrictions=gr.Dropdown(["Gluten-Free","Dairy-Free","Vegan","Vegetarian","Keto","Kosher","No Soy","No Seafood","No Pork","No Beef"], label="dietary restrictions", multiselect=True,info="you can select multiple!") allergies=gr.Textbox(label="allergies") preferred_ingredients=gr.Textbox(label="preferred ingredients") gr.ChatInterface( fn=respond, type="messages", additional_inputs=[cuisine,dietary_restrictions,allergies,preferred_ingredients] ) chatbot.launch()