import streamlit as st
import pinecone
from sentence_transformers import SentenceTransformer
import logging
import openai
import gradio as gr

PINECONE_KEY = st.secrets["PINECONE_KEY"]  # app.pinecone.io
OPENAI_KEY = None
# st.secrets["OPENAI_KEY"]
INDEX_ID = 'filled-stacks-search'

@st.experimental_singleton
def init_openai():
    openai.api_key = OPENAI_KEY

@st.experimental_singleton
def init_pinecone():
    pinecone.init(api_key=PINECONE_KEY, environment="us-west1-gcp")
    return pinecone.Index(INDEX_ID)
    
@st.experimental_singleton
def init_retriever():
    return SentenceTransformer("multi-qa-mpnet-base-dot-v1")

def make_query(query, retriever, top_k=3, include_values=True, include_metadata=True, filter=None):
    xq = retriever.encode([query]).tolist()
    logging.info(f"Query: {query}")
    attempt = 0
    while attempt < 3:
        try:
            xc = st.session_state.index.query(
                xq,
                top_k=top_k,
                include_values=include_values,
                include_metadata=include_metadata,
                filter=filter
            )
            matches = xc['matches']
            break
        except:
            # force reload
            pinecone.init(api_key=PINECONE_KEY, environment="us-west1-gcp")
            st.session_state.index = pinecone.Index(INDEX_ID)
            attempt += 1
            matches = []
    if len(matches) == 0:
        logging.error(f"Query failed")
    return matches

def get_prompt(matches):
    contexts = [
        x['metadata']['text'] for x in matches
    ]
    prompt_start = (
        "Answer the question based on the context below.\n\n"+
        "Context:\n"
    )
    prompt_end = (
        f"\n\nQuestion: {query}\nAnswer:"
    )
    limit = 3750

    for i in range(1, len(contexts)):
        if len("\n\n--\n\n".join(contexts[:i])) >= limit:
            prompt = (
                prompt_start +
                "\n\n--\n\n".join(contexts[:i-1]) + 
                prompt_end
            )
            break
        elif i == len(contexts) - 1:
            prompt = (
                prompt_start + 
                "\n\n--\n\n".join(contexts) + 
                prompt_end
            )
    return prompt

st.session_state.index = init_pinecone()
retriever = init_retriever()

def card(thumbnail: str, title: str, urls: list, contexts: list, starts: list, ends: list):
    meta = [(e, s, u, c) for e, s, u, c in zip(ends, starts, urls, contexts)]
    meta.sort(reverse=False)
    text_content = []
    current_start = 0
    current_end = 0
    for end, start, url, context in meta:
        # reformat seconds to timestamp
        time = start / 60
        mins = f"0{int(time)}"[-2:]
        secs = f"0{int(round((time - int(mins))*60, 0))}"[-2:]
        timestamp = f"{mins}:{secs}"
        if start < current_end and start > current_start:
            # this means it is a continuation of the previous sentence
            text_content[-1][0] = text_content[-1][0].split(context[:10])[0]
            text_content.append([f"[{timestamp}] {context.capitalize()}", url])
        else:
            text_content.append(["xxLINEBREAKxx", ""])
            text_content.append([f"[{timestamp}] {context}", url])
        current_start = start
        current_end = end
    html_text = ""
    for text, url in text_content:
        if text == "xxLINEBREAKxx":
            html_text += "<br>"
        else:
            html_text += f"<small><a href={url}>{text.strip()}... </a></small>"
            print(text)
    html = f"""
    <div class="container-fluid">
        <div class="row align-items-start">
            <div class="col-md-4 col-sm-4">
                <div class="position-relative">
                    <a href={urls[0]}><img src={thumbnail} class="img-fluid" style="width: 192px; height: 106px"></a>
                </div>
            </div>
            <div  class="col-md-8 col-sm-8">
                <h2>{title}</h2>
            </div>
        <div>
            {html_text}
    <br><br>
    """
    return st.markdown(html, unsafe_allow_html=True)
    
st.write("""
# FilledStacks Search
""")

st.info("""
Ask a question about the FilledStacks YouTube Channel
""")

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("", "", placeholder="e.g.: how does stacked work?")

if query != "":
    print(f"query: {query}")
    matches = make_query(
        query, retriever, top_k=5,
    )
    # if st.session_state.summarize:
    #     if OPENAI_KEY is not None:
    #         prompt = get_prompt(matches)
    #         res = openai.Completion.create(
    #             engine='text-davinci-003',
    #             prompt=prompt,
    #             temperature=0,
    #             max_tokens=300,
    #             top_p=1,
    #             frequency_penalty=0,
    #             presence_penalty=0,
    #             stop=".",
    #         )
    #         summary = res['choices'][0]['text'].strip()
    #         st.info(f"Summary:\n{summary}")
    #     else:
    #         st.info("Please enter your OpenAI key to generate a summary")
    
    results = {}
    order = []
    for context in matches:
        video_id = context['metadata']['url'].split('/')[-1]
        if video_id not in results:
            results[video_id] = {
                'title': context['metadata']['title'],
                'urls': [f"{context['metadata']['url']}?t={int(context['metadata']['start'])}"],
                'contexts': [context['metadata']['text']],
                'starts': [int(context['metadata']['start'])],
                'ends': [int(context['metadata']['end'])]
            }
            order.append(video_id)
        else:
            results[video_id]['urls'].append(
                f"{context['metadata']['url']}?t={int(context['metadata']['start'])}"
            )
            results[video_id]['contexts'].append(
                context['metadata']['text']
            )
            results[video_id]['starts'].append(int(context['metadata']['start']))
            results[video_id]['ends'].append(int(context['metadata']['end']))
    # now display cards
    for video_id in order:
        card(
            thumbnail=f"https://img.youtube.com/vi/{video_id}/maxresdefault.jpg",
            title=results[video_id]['title'],
            urls=results[video_id]['urls'],
            contexts=results[video_id]['contexts'],
            starts=results[video_id]['starts'],
            ends=results[video_id]['ends']
        )