Update app.py

app.py

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+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+from langchain.chat_models import ChatOpenAI
+from langchain.chains import ConversationChain
+from langchain.chains.conversation.memory import ConversationBufferWindowMemory
+from langchain.prompts import PromptTemplate
+
+import gradio as gr
+
+REPO_ID = "ksh-nyp/llama-2-7b-chat-TCMKB"
+
+# Load the model and tokenizer from Hugging Face's model hub
+model = AutoModelForCausalLM.from_pretrained(REPO_ID)
+tokenizer = AutoTokenizer.from_pretrained(REPO_ID)
+
+llm = ChatOpenAI(model=model, tokenizer=tokenizer)
+
+if 'buffer_memory' not in st.session_state:
+    st.session_state.buffer_memory = ConversationBufferWindowMemory(k=3)
+
+conversation = ConversationChain(
+    llm=llm,
+    memory=st.session_state.buffer_memory,
+    verbose=True
+)
+
+context = """ 
+Act as an OrderBot, you work collecting orders in a delivery only fast food restaurant called My Dear Frankfurt. \
+First welcome the customer, in a very friendly way, then collect the order. \
+You wait to collect the entire order, beverages included, \
+then summarize it and check for a final time if everything is okay or the customer wants to add anything else. \
+Finally, you collect the payment. \
+Make sure to clarify all options, extras, and sizes to uniquely identify the item from the menu. \
+You respond in a short, very friendly style. \
+The menu includes:
+burgers 12.95, 10.00, 7.00
+frankfurts 10.95, 9.25, 6.50
+sandwiches 11.95, 9.75, 6.75
+fries 4.50, 3.50
+salad 7.25
+Toppings:
+extra cheese 2.00,
+mushrooms 1.50
+martra sausage 3.00
+canadian bacon 3.50
+romesco sauce 1.50
+peppers 1.00
+Drinks:
+coke 3.00, 2.00, 1.00
+sprite 3.00, 2.00, 1.00
+vichy catalan 5.00
+"""
+
+prompt_template = PromptTemplate.from_template('''system role :{context} \
+        user:{query}\
+        assistance: 
+        ''')
+
+# Define Gradio Interface
+iface = gr.Interface(
+    fn=lambda query: conversation.run(prompt_template.format(context=context, query=query)),
+    inputs=gr.Textbox(),
+    outputs=gr.Textbox(),
+    live=True,
+    capture_session=True
+)
+
+# Launch Gradio Interface
+iface.launch()