import streamlit as st
import pinecone
import openai
import uuid

@st.experimental_singleton
def init_pinecone():
    pinecone.init(api_key=st.secrets["PINECONE_KEY"], environment="us-west1-gcp")
    return pinecone.Index(st.secrets["PINECONE_INDEX"])

openai.organization = st.secrets["OPENAI_ORG"]
openai.api_key = st.secrets["OPENAI_KEY"]


def modCheck(query):
    response = openai.Moderation.create(input=query)
    return response["results"][0]['flagged']

def promptMaker(query, matchtext, prompt_type=None):
    prompt = "The Pogcast is a weekly podcast co-hosted by Veritas and Jesse Kazam. They are both twitch streamers and on the podcast they discuss all the poggers things in life like the first-person shooter Escape from Tarkov, chess, speed-running, and everyday activities relevant to being a twitch streamer.\n"
    if not prompt_type:
        prompt+= "You will be given relevant snippets from the Pogcast that should help you answer or provide context to an inquiry. \n" + \
            "If the inquiry is in the form of a question, answer it in a verbose manner, provide a quote from the snippets to support your answer, and provide a deep summarization of the relevant portions of the snippets.\n" + \
            "If the inquiry is not in the form of a question, summarize the parts of the snippets most relevant to the inquiry.\n" + \
            "Snippets:\n" + matchtext +"   \nInquiry: " + query + "\nResult:"
    else:
        prompt+= "Use the following snippets from the podcast to write a " + prompt_type + " about " + query + "\nSnippets: " + matchtext + "\nResult:"
    return prompt

def runInquiry(query):
    prompt_type = None
    if query.startswith("/"):
        prompt_type = query.split(" ")[0][1:]
        query = " ".join(query.split(" ")[1:]).strip()

    if len(query)< 6:
        st.error("Please ask a question with at least 6 characters")
        return
    with st.spinner('Checking query...'):
        flagged = modCheck(query)
        if flagged:
            st.error("You know what you did. I ain't answering that.")
            return

    with st.spinner('Embedding query...'):
        xq = openai.Embedding.create(input=query, engine="text-embedding-ada-002")['data'][0]['embedding']
        index = init_pinecone()
        res = index.query(xq, namespace=st.secrets["PINECONE_NAMESPACE"], top_k=5, include_metadata=True)
    with st.spinner('Thinking...'):
        matchtext = "\n".join(match['metadata']['content'] for match in res['matches'][:3])

        if 'uid' not in st.session_state:
            st.session_state.uid = str(uuid.uuid4())

        comp = openai.Completion.create(
            model="text-davinci-003",
            prompt=promptMaker(query, matchtext, prompt_type),
            max_tokens=2000,
            temperature=0.9,
            user = st.session_state.uid
        )
    st.markdown(f"""
        <div>
            <p class="lead">{comp['choices'][0]['text']}</p>
        </div>
    """, unsafe_allow_html=True)

    for context in res['matches']:
        card(
            context['metadata']['episode_num'],
            context['metadata']['episode_id'],
            context['metadata']['start_second'],
            context['metadata']['end_second'],
            context['metadata']['content']
        )
    return (comp, res['matches'])

def card(episode, episode_id, start_second, end_second, context):
    return st.markdown(f"""
    <div class="container-fluid mb-2">
        <div class="row align-items-start">
            <div class="col-md-4 col-sm-4">
                 <div class="position-relative">
                     <iframe width="220" height="124" src="https://www.youtube.com/embed/{episode_id}?start={int(start_second)}" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
                 </div>
             </div>
             <div  class="col-md-8 col-sm-8">
                 <a href=https://www.youtube.com/watch?v={episode_id}&t={int(start_second)}s>Episode {int(episode)}</a>
                 <br>
                 <span style="color: #808080;">
                     <small>{context[:200].capitalize()+"...."}</small>
                 </span>
             </div>
        </div>
     </div>
        """, unsafe_allow_html=True)

st.markdown("<h1 style='text-align: center;'>PogcastGPT</h1>", unsafe_allow_html=True)
st.write("""
    This app uses semantic search to find and summarize relevant sections of the Pogcast to answer your question
""")
st.markdown("""
<link rel="stylesheet" href="https://cdn.jsdelivr.net/npm/bootstrap@4.0.0/dist/css/bootstrap.min.css" integrity="sha384-Gn5384xqQ1aoWXA+058RXPxPg6fy4IWvTNh0E263XmFcJlSAwiGgFAW/dAiS6JXm" crossorigin="anonymous">
""", unsafe_allow_html=True)

query = st.text_input(label="Ask me a question about the Pogcast!", max_chars=200, value="", key="inquiryBox", type='default')
if query != "":
    runInquiry(query)