app.py

""" Simple Chatbot
@author: Nigel Gebodh
@email: nigel.gebodh@gmail.com
"""

import streamlit as st
from openai import OpenAI
import os
import requests
import json

entire_assistant_response = ""

def get_streamed_response(message, history, model):
    all_message = []
    
    for human, assistant in history:
        all_message.append({"role": "user", "content": human})
        all_message.append({"role": "assistant", "content": assistant})
    
    global entire_assistant_response
    entire_assistant_response = ""  # Reset the entire assistant response

    all_message.append({"role": "user", "content": message})

    url = "https://api.together.xyz/v1/chat/completions"
    payload = {
        "model": model,
        "temperature": 1.05,
        "top_p": 0.9,
        "top_k": 50,
        "repetition_penalty": 1,
        "n": 1,
        "messages": all_message,
        "stream_tokens": True,
    }

    TOGETHER_API_KEY = os.getenv('TOGETHER_API_KEY')
    headers = {
        "accept": "application/json",
        "content-type": "application/json",
        "Authorization": f"Bearer {TOGETHER_API_KEY}",
    }

    response = requests.post(url, json=payload, headers=headers, stream=True)
    response.raise_for_status()  # Ensure HTTP request was successful

    for line in response.iter_lines():
        if line:
            decoded_line = line.decode('utf-8')

            # Check for the completion signal
            if decoded_line == "data: [DONE]":
                yield entire_assistant_response  # Yield the entire response at the end
                break

            try:
                # Decode and strip any SSE format specific prefix ("data: ")
                if decoded_line.startswith("data: "):
                    decoded_line = decoded_line.replace("data: ", "")
                    chunk_data = json.loads(decoded_line)
                    content = chunk_data['choices'][0]['delta']['content']
                    entire_assistant_response += content  # Aggregate content
                    yield entire_assistant_response

            except json.JSONDecodeError:
                print(f"Invalid JSON received: {decoded_line}")
                continue
            except KeyError as e:
                print(f"KeyError encountered: {e}")
                continue

    print(entire_assistant_response)
    all_message.append({"role": "assistant", "content": entire_assistant_response})


# Initialize Streamlit app
st.title("Simple Chatbot")

# Initialize session state if not present
if "messages" not in st.session_state:
    st.session_state.messages = []

# Define available models
models = {
    "Mistral": "mistralai/Mistral-7B-Instruct-v0.2",
    "Gemma-7B": "google/gemma-7b-it",
    "Gemma-2B": "google/gemma-2b-it",
    "Zephyr-7B-β": "HuggingFaceH4/zephyr-7b-beta",
    "BibleLearnerAI": "NousResearch/Nous-Hermes-2-Yi-34B"
}

# Allow user to select a model
selected_model = st.sidebar.selectbox("Select Model", list(models.keys()))

# Create model description
st.sidebar.write(f"You're now chatting with **{selected_model}**")
st.sidebar.markdown("*Generated content may be inaccurate or false.*")
st.sidebar.markdown("\nLearn how to build this chatbot [here](https://ngebodh.github.io/projects/2024-03-05/).")
st.sidebar.markdown("\nRun into issues? Try the [back-up](https://huggingface.co/spaces/ngebodh/SimpleChatbot-Backup).")

if "prev_option" not in st.session_state:
    st.session_state.prev_option = selected_model

if st.session_state.prev_option != selected_model:
    st.session_state.messages = []
    st.session_state.prev_option = selected_model

#Pull in the model we want to use
repo_id = models[selected_model]

st.subheader(f'AI - {selected_model}')

# Accept user input
if prompt := st.text_input(f"Hi I'm {selected_model}, ask me a question"):

    # Display user message
    with st.spinner("AI is typing..."):
        st.session_state.messages.append({"role": "user", "content": prompt})

        # Call selected model to get response
        response_stream = get_streamed_response(prompt, [(m["content"] for m in st.session_state.messages[:-1])], repo_id)
        for response in response_stream:
            st.session_state.messages.append({"role": "assistant", "content": response})

# Display chat history
for message in st.session_state.messages:
    if message["role"] == "user":
        st.text_input("You:", value=message["content"], disabled=True)
    else:
        st.text_input(f"{selected_model}:", value=message["content"], disabled=True)