Create app.py

app.py

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+import streamlit as st
+import os
+
+# App title
+st.set_page_config(page_title="🦙💬 Llama 2 Chatbot")
+
+ # Refactored from https://github.com/a16z-infra/llama2-chatbot
+ st.subheader('Models and parameters')
+ selected_model = st.sidebar.selectbox('Choose a Llama2 model', ['Llama2-7B', 'Llama2-13B', 'Llama2-70B'], key='selected_model')
+ if selected_model == 'Llama2-7B':
+ llm = 'a16z-infra/llama7b-v2-chat:4f0a4744c7295c024a1de15e1a63c880d3da035fa1f49bfd344fe076074c8eea'
+ elif selected_model == 'Llama2-13B':
+ llm = 'a16z-infra/llama13b-v2-chat:df7690f1994d94e96ad9d568eac121aecf50684a0b0963b25a41cc40061269e5'
+ else:
+ llm = 'replicate/llama70b-v2-chat:e951f18578850b652510200860fc4ea62b3b16fac280f83ff32282f87bbd2e48'
+ 
+ temperature = st.sidebar.slider('temperature', min_value=0.01, max_value=5.0, value=0.1, step=0.01)
+ top_p = st.sidebar.slider('top_p', min_value=0.01, max_value=1.0, value=0.9, step=0.01)
+ max_length = st.sidebar.slider('max_length', min_value=64, max_value=4096, value=512, step=8)
+ 
+ st.markdown('📖 Learn how to build this app in this [blog](https://blog.streamlit.io/how-to-build-a-llama-2-chatbot/)!')
+os.environ['REPLICATE_API_TOKEN'] = replicate_api
+
+# Store LLM generated responses
+if "messages" not in st.session_state.keys():
+ st.session_state.messages = [{"role": "assistant", "content": "How may I assist you today?"}]
+
+# Display or clear chat messages
+for message in st.session_state.messages:
+ with st.chat_message(message["role"]):
+ st.write(message["content"])
+
+def clear_chat_history():
+ st.session_state.messages = [{"role": "assistant", "content": "How may I assist you today?"}]
+st.sidebar.button('Clear Chat History', on_click=clear_chat_history)
+
+# Function for generating LLaMA2 response
+def generate_llama2_response(prompt_input):
+ string_dialogue = "You are a helpful assistant. You do not respond as 'User' or pretend to be 'User'. You only respond once as 'Assistant'."
+ for dict_message in st.session_state.messages:
+ if dict_message["role"] == "user":
+ string_dialogue += "User: " + dict_message["content"] + "\n\n"
+ else:
+ string_dialogue += "Assistant: " + dict_message["content"] + "\n\n"
+ # output = replicate.run(llm, 
+ # input={"prompt": f"{string_dialogue} {prompt_input} Assistant: ",
+ # "temperature":temperature, "top_p":top_p, "max_length":max_length, "repetition_penalty":1})
+ 
+ return output
+
+# User-provided prompt
+if prompt := st.chat_input(disabled=not replicate_api):
+ st.session_state.messages.append({"role": "user", "content": prompt})
+ with st.chat_message("user"):
+ st.write(prompt)
+
+# Generate a new response if last message is not from assistant
+if st.session_state.messages[-1]["role"] != "assistant":
+ with st.chat_message("assistant"):
+ with st.spinner("Thinking..."):
+ response = generate_llama2_response(prompt)
+ placeholder = st.empty()
+ full_response = ''
+ for item in response:
+ full_response += item
+ placeholder.markdown(full_response)
+ placeholder.markdown(full_response)
+ message = {"role": "assistant", "content": full_response}
+ st.session_state.messages.append(message)