Update app.py

app.py

@@ -1,4 +1,87 @@
-import streamlit as st
 
-x = st.slider('Select a value')
-st.write(x, 'squared is', x * x)
+!pip install -qq langchain wget llama-index cohere llama-cpp-python
+
+import wget 
+
+def bar_custom(current, total, width=80):
+    print("Downloading %d%% [%d / %d] bytes" % (current / total * 100, current, total))
+
+model_url = "https://huggingface.co/TheBloke/Llama-2-7B-Chat-GGUF/resolve/main/llama-2-7b-chat.Q2_K.gguf"
+wget.download(model_url, bar=bar_custom)
+
+!pip -q install streamlit
+
+%%writefile app.py
+import streamlit as st 
+from llama_index import (
+  SimpleDirectoryReader,
+  VectorStoreIndex,
+  ServiceContext,
+)
+from llama_index.llms import LlamaCPP
+from llama_index.llms.llama_utils import (
+  messages_to_prompt,
+  completion_to_prompt,
+)
+from langchain.schema import(SystemMessage, HumanMessage, AIMessage)
+
+def init_page() -> None:
+  st.set_page_config(
+    page_title="Personal Chatbot"
+  )
+  st.header("Persoanl Chatbot")
+  st.sidebar.title("Options")
+
+def select_llm() -> LlamaCPP:
+  return LlamaCPP(
+    model_path="/content/llama-2-7b-chat.Q2_K.gguf",
+    temperature=0.1,
+    max_new_tokens=500,
+    context_window=3900,
+    generate_kwargs={},
+    model_kwargs={"n_gpu_layers":1},
+    messages_to_prompt=messages_to_prompt,
+    completion_to_prompt=completion_to_prompt,
+    verbose=True,
+  )
+
+def init_messages() -> None:
+  clear_button = st.sidebar.button("Clear Conversation", key="clear")
+  if clear_button or "messages" not in st.session_state:
+    st.session_state.messages = [
+      SystemMessage(
+        content="you are a helpful AI assistant. Reply your answer in markdown format."
+      )
+    ]
+
+def get_answer(llm, messages) -> str:
+  response = llm.complete(messages)
+  return response.text
+
+def main() -> None:
+  init_page()
+  llm = select_llm()
+  init_messages()
+
+  if user_input := st.chat_input("Input your question!"):
+    st.session_state.messages.append(HumanMessage(content=user_input))
+    with st.spinner("Bot is typing ..."):
+      answer = get_answer(llm, user_input)
+      print(answer)
+    st.session_state.messages.append(AIMessage(content=answer))
+    
+
+  messages = st.session_state.get("messages", [])
+  for message in messages:
+    if isinstance(message, AIMessage):
+      with st.chat_message("assistant"):
+        st.markdown(message.content)
+    elif isinstance(message, HumanMessage):
+      with st.chat_message("user"):
+        st.markdown(message.content)
+
+if __name__ == "__main__":
+  main()
+ 
+!streamlit run app.py & npx localtunnel --port 8501
+view rawmain.py hosted with ❤ by GitHub