streamlit_app.py

import streamlit as st
import ollama

import subprocess

# Command to be executed
command = "ollama run ollama3"

try:
    # Execute the command
    process = subprocess.run(command, shell=True, check=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
    
    # Get the output and error (if any)
    output = process.stdout.decode()
    error = process.stderr.decode()
    
    # Print the output and error
    print("Output:", output)
    print("Error:", error)
except subprocess.CalledProcessError as e:
    print(f"Command '{e.cmd}' returned non-zero exit status {e.returncode}.")
    print("Error output:", e.stderr.decode())

st.title("Local Llama3 Chatbot!🤖")

system_prompt = "You are a helpful assistant"

if "messages" not in st.session_state:
    st.session_state.messages = [
        {
            "role": "system",
            "content": system_prompt,
        }
    ]

for message in st.session_state["messages"]:
    if message["role"] != "system":
        with st.chat_message(message["role"]):
            st.markdown(message["content"])

# initialize model
if "model" not in st.session_state:
    st.session_state.model = "llama3"

# user input
if user_prompt := st.chat_input("Your prompt"):
    st.session_state.messages.append({"role": "user", "content": user_prompt})
    with st.chat_message("user"):
        st.markdown(user_prompt)

    # generate responses
    with st.chat_message("assistant"):
        message_placeholder = st.empty()
        full_response = ""

        for chunk in ollama.chat(
            model=st.session_state.model,
            messages=[
                {"role": m["role"], "content": m["content"]}
                for m in st.session_state.messages
            ],
            stream=True,
        ):
            token = chunk["message"]["content"]
            if token is not None:
                full_response += token
                message_placeholder.markdown(full_response + "▌")

        message_placeholder.markdown(full_response)

    st.session_state.messages.append({"role": "assistant", "content": full_response})