app.py

from PyPDF2 import PdfReader
from langchain.embeddings.openai import OpenAIEmbeddings
from langchain.text_splitter import CharacterTextSplitter
from langchain.vectorstores import FAISS
from langchain.chains.question_answering import load_qa_chain
from langchain.llms import OpenAI
import streamlit as st
from streamlit_chat import message
import extra_streamlit_components as stx
import os
import datetime
import openai
import random


# Get your API keys from openai, you will need to create an account.
# Here is the link to get the keys: https://platform.openai.com/account/billing/overview
os.environ["OPENAI_API_KEY"] = st.secrets["OPENAI_API_KEY"]


@st.cache(allow_output_mutation=True, suppress_st_warning=True)
def get_manager(key):
    return stx.CookieManager(key=key)


cookie_manager = get_manager(key=0)
# cookie = cookie_manager.get(cookie="actchat")
# cookie_manager = get_manager(key=1)
# openai_cookie = cookie_manager.get(cookie="openaikey")


user_limit_cookie = None
cookies = cookie_manager.get_all()

if cookies:
    if "actchat" in cookies:
        user_limit_cookie = cookies["actchat"]


@st.cache_resource
def read_data():
    # location of the pdf file/files.
    reader = PdfReader("The-AI-Act.pdf")

    # read data from the file and put them into a variable called raw_text
    raw_text = ""
    for i, page in enumerate(reader.pages):
        text = page.extract_text()
        if text:
            raw_text += text
    return raw_text


# We need to split the text that we read into smaller chunks so that during
# information retreival we don't hit the token size limits.
@st.cache_resource
def split_document(raw_text):
    text_splitter = CharacterTextSplitter(
        separator="\n",
        chunk_size=1000,
        chunk_overlap=200,
        length_function=len,
    )
    texts = text_splitter.split_text(raw_text)
    return texts


# Download embeddings from OpenAI
@st.cache_resource
def load_openai_embeddings():
    embeddings = OpenAIEmbeddings()
    return embeddings


@st.cache_resource
def init_docsearch(texts, _embeddings):
    docsearch = FAISS.from_texts(texts, _embeddings)
    return docsearch


@st.cache_resource
def init_qa_chain():
    chain = load_qa_chain(OpenAI(temperature=1), chain_type="stuff")
    return chain


raw_text = read_data()
texts = split_document(raw_text)
embeddings = load_openai_embeddings()
docsearch = init_docsearch(texts, embeddings)
chain = init_qa_chain()

avatars = [
    "avataaars",
    "big-ears",
    "big-ears-neutral",
    "big-smile",
    "identicon",
    "initials",
    "lorelei",
    "lorelei-neutral",
    "micah",
    "miniavs",
    "open-peeps",
    "personas",
    "pixel-art",
    "pixel-art-neutral",
    "shapes",
    "thumbs",
]

user_avatar = avatars[random.randint(0, len(avatars) - 1)]

st.title("EU AI ACT GPT🤖")
st.write(
    """The AI Act is a proposed European law on artificial intelligence (AI) – 
    the first law on AI by a major regulator anywhere."""
)
st.markdown(
    """The EU AI Act is expected to be voted during the 12-15 June session of
    the EU Parliament. We at [NannyML](https://github.com/NannyML/nannyml)
    finetuned GPT-4 with all the **107 pages** in the document so you can ask
    all the necessary questions and be informed about it.
    """
)

st.markdown(
    """If you are a data scientist and are interested in learning how the EU AI Act might affect the field.
    Check out [Understanding the EU AI Act as a Data Scientist](https://www.nannyml.com/blog/eu-ai-act-guide-data-science).
    """
)

# create state sessions
if "text_input" not in st.session_state:
    st.session_state["text_input"] = ""

if "generated" not in st.session_state:
    st.session_state["generated"] = []

if "messages" not in st.session_state:
    st.session_state["messages"] = []

if "openaikey" not in st.session_state:
    st.session_state["openaikey"] = []

if "disabled" not in st.session_state:
    st.session_state["disabled"] = False

if user_limit_cookie == "01234" and len(st.session_state["openaikey"]) == 0:
    st.session_state["disabled"] = True
else:
    st.session_state["disabled"] = False

if len(st.session_state["openaikey"]) != 0:
    openai.api_key = st.session_state["openaikey"]


if "avatar" not in st.session_state:
    st.session_state["avatar"] = user_avatar


def disable():
    st.session_state["disabled"] = True


if "history" not in st.session_state:
    st.session_state["history"] = ""


def submit():
    st.session_state["text_input"] = st.session_state["text_area"]
    st.session_state["text_area"] = ""


# Template prompt to establish the behaviour and the persona of the chatbot
def template(history, query):
    return """
            You are an assistant and expert in the EU AI Act. Based on your expertise, 
            you need to assist and provide the answer to the business questions about the EU AI Act.
            Your answer has to be clear and easy to understand for the user. 
            Your answer has to be detailed and fact-checked informations based on the act.
            Don't hesitate, if necessary create very detailed answer which exceeds 300 words.
            Be sure to ask any additional information you may need, to provide an accurate answer.
            Refer to the coverstation history if necessary.
            Be friendly and polite to the user. 

            Coversation history : 
            {}

            User question : {}
            Assistant :""".format(
        history, query
    )


def generate_response(question):
    docs = docsearch.similarity_search(question)
    response = chain.run(input_documents=docs, question=question)
    st.session_state["generated"].append({"role": "assistant", "content": response})
    st.session_state["history"] += "User question : " + question + "/"
    st.session_state["history"] += "Assistant : " + response + "/"


response_container = st.container()
prompt = st.text_area(
    "Enter your question here about the EU AI Act",
    disabled=st.session_state["disabled"],
    key="text_area",
    on_change=submit,
)
prompt = st.session_state["text_input"]
send_button = st.button("Send", disabled=st.session_state["disabled"])
if send_button and prompt:
    st.session_state["messages"].append({"role": "user", "content": prompt})
    history = st.session_state["history"]
    # if statement to only keep 6000 chars ~ 1200 words in the history
    if len(history) > 6000:
        # idx of the closest full message
        idx = history.find('/')
        # reduce the length of the history to the 6000 char
        history = history[len(history)-6000:]
        history = history[idx:]
        
    question = template(history, prompt)
    with st.spinner("Generating response..."):
        generate_response(question)

    # try:
    #     generate_response(prompt)
    # except:
    #     st.error("There is an error with your API key. Or you might ran out of quota.")


if st.session_state["messages"]:
    with response_container:
        for i in range(len(st.session_state["generated"])):
            message(
                st.session_state["messages"][i]["content"],
                is_user=True,
                key=str(i) + "_user",
                avatar_style=st.session_state["avatar"],
            )
            message(st.session_state["generated"][i]["content"], key=str(i))

if len(st.session_state["messages"]) > 4:
    cookie_manager.set(
        "actchat", val="01234", expires_at=datetime.datetime(year=2025, month=1, day=1)
    )

if user_limit_cookie == "01234" and len(st.session_state["openaikey"]) == 0:
    st.markdown("##### Provide your own OpenAI API Key")
    st.write(
        """
        Due to limitations in api request calls per user to continoue the
        converstation, please provide your personal OpenAI API key.
        For more info on how to get and API Key visit
        [OpenAI docs](https://platform.openai.com/account/api-keys)
        about it."""
    )
    # disable()
    openaikey = st.text_input("OPENAI_API_KEY:")
    api_button = st.button("Add")

    if api_button:
        st.session_state["disabled"] = False
        st.session_state["openaikey"] = openaikey
        openai.api_key = openaikey
else:
    st.session_state["disabled"] = False

st.markdown(
    """##### Sample questions to ask it
* What are the objectives of the EU AI Act?
* What are the potential fines that a company may face for failing to comply with the EU AI Act?
* Explain in simple words the different risk levels in the EU AI Act.
"""
)


st.text("")
st.markdown(
    """`Created by` [santiviquez](https://twitter.com/santiviquez) and
    [maciejbalawejder](https://www.linkedin.com/in/maciej-balawejder-rt8015/) 
    from [NannyML](https://github.com/NannyML/nannyml) —
    The open-source library to estimate model performance in production
    *without ground truth*."""
)