import os
import sys

import logging
import pandas as pd
from json import JSONDecodeError
from pathlib import Path
import streamlit as st
from annotated_text import annotation
from markdown import markdown

# streamlit does not support any states out of the box. On every button click, streamlit reload the whole page
# and every value gets lost. To keep track of our feedback state we use the official streamlit gist mentioned
# here https://gist.github.com/tvst/036da038ab3e999a64497f42de966a92
import SessionState
from utils import HS_VERSION, haystack_is_ready, query, send_feedback, upload_doc, haystack_version


# Adjust to a question that you would like users to see in the search bar when they load the UI:
DEFAULT_QUESTION_AT_STARTUP = "What's the capital of France?"

# Labels for the evaluation
EVAL_LABELS = os.getenv("EVAL_FILE", Path(__file__).parent / "eval_labels_example.csv")

# Whether the file upload should be enabled or not
DISABLE_FILE_UPLOAD = os.getenv("HAYSTACK_UI_DISABLE_FILE_UPLOAD")


def main():

    # Persistent state
    state = SessionState.get(
        random_question=DEFAULT_QUESTION_AT_STARTUP, 
        random_answer="",
        results=None,
        raw_json=None,
        get_next_question=True
    )

    # Small callback to reset the interface in case the text of the question changes
    def reset_results(*args):
        state.results = None
        state.raw_json = None

    # Title
    st.write("# Haystack Demo - Explore the world")
    st.write("""
This demo takes its data from a selection of Wikipedia pages crawled in November 2021 on the topic of 'Countries and capital cities'. 

Ask any question on this topic and see if Haystack can find the correct answer to your query! 

*Note: do not use keywords, but type full-fledged questions.* The demo is not optimized to deal with keyword queries and might misunderstand you.
""")

    # Sidebar
    st.sidebar.header("Options")
    top_k_reader = st.sidebar.slider("Max. number of answers", min_value=1, max_value=10, value=3, step=1, on_change=reset_results)
    top_k_retriever = st.sidebar.slider("Max. number of documents from retriever", min_value=1, max_value=10, value=3, step=1, on_change=reset_results)
    eval_mode = st.sidebar.checkbox("Evaluation mode")
    debug = st.sidebar.checkbox("Show debug info")

    # File upload block
    if not DISABLE_FILE_UPLOAD:
        st.sidebar.write("## File Upload:")
        data_files = st.sidebar.file_uploader("", type=["pdf", "txt", "docx"], accept_multiple_files=True)
        for data_file in data_files:
            # Upload file
            if data_file:
                raw_json = upload_doc(data_file)
                st.sidebar.write(str(data_file.name) + "    ✅ ")
                if debug:
                    st.subheader("REST API JSON response")
                    st.sidebar.write(raw_json)

    hs_version = None
    try:
        hs_version = f" <small>(v{haystack_version()})</small>"
    except Exception:
        pass

    st.sidebar.markdown(f"""
    <style>
        a {{
            text-decoration: none;
        }}
        .haystack-footer {{
            text-align: center;
        }}
        .haystack-footer h4 {{
            margin: 0.1rem; 
            padding:0;
        }}
        footer {{
            opacity: 0;
        }}
    </style>
    <div class="haystack-footer">
        <hr />
        <h4>Built with <a href="https://www.deepset.ai/haystack">Haystack</a>{hs_version}</h4>
        <p>Get it on <a href="https://github.com/deepset-ai/haystack/">GitHub</a> &nbsp;&nbsp; - &nbsp;&nbsp; Read the <a href="https://haystack.deepset.ai/overview/intro">Docs</a></p>
        <small>Data crawled from <a href="https://en.wikipedia.org/wiki/Category:Lists_of_countries_by_continent">Wikipedia</a> in November 2021.<br />See the <a href="https://creativecommons.org/licenses/by-sa/3.0/">License</a> (CC BY-SA 3.0).</small>
    </div>
    """, unsafe_allow_html=True)

    # Load csv into pandas dataframe
    try:
        df = pd.read_csv(EVAL_LABELS, sep=";")
    except Exception:
        st.error(f"The eval file was not found. Please check the demo's [README](https://github.com/deepset-ai/haystack/tree/master/ui/README.md) for more information.")
        sys.exit(f"The eval file was not found under `{EVAL_LABELS}`. Please check the README (https://github.com/deepset-ai/haystack/tree/master/ui/README.md) for more information.")

    # Search bar
    question = st.text_input("",
        value=state.random_question,
        max_chars=100, 
        on_change=reset_results
    )
    col1, col2 = st.columns(2)
    col1.markdown("<style>.stButton button {width:100%;}</style>", unsafe_allow_html=True)
    col2.markdown("<style>.stButton button {width:100%;}</style>", unsafe_allow_html=True)

    # Run button
    run_query = col1.button("Run")

    # Get next random question from the CSV
    state.get_next_question = col2.button("Random question")
    if state.get_next_question:
        reset_results()
        new_row = df.sample(1)   
        while new_row["Question Text"].values[0] == state.random_question:  # Avoid picking the same question twice (the change is not visible on the UI)
            new_row = df.sample(1)
        state.random_question = new_row["Question Text"].values[0]
        state.random_answer = new_row["Answer"].values[0]

        # Re-runs the script setting the random question as the textbox value
        # Unfortunately necessary as the Random Question button is _below_ the textbox
        raise st.script_runner.RerunException(st.script_request_queue.RerunData(None))

    # Check the connection
    with st.spinner("⌛️ &nbsp;&nbsp; Haystack is starting..."):
        if not haystack_is_ready():
            st.error("🚫 &nbsp;&nbsp; Connection Error. Is Haystack running?")
            run_query = False
            reset_results()

    # Get results for query
    if run_query and question:
        reset_results()
        with st.spinner(
            "🧠 &nbsp;&nbsp; Performing neural search on documents... \n "
            "Do you want to optimize speed or accuracy? \n"
            "Check out the docs: https://haystack.deepset.ai/usage/optimization "
        ):
            try:
                state.results, state.raw_json = query(question, top_k_reader=top_k_reader, top_k_retriever=top_k_retriever)
            except JSONDecodeError as je:
                st.error("👓 &nbsp;&nbsp; An error occurred reading the results. Is the document store working?")
                return
            except Exception as e:
                logging.exception(e)
                if "The server is busy processing requests" in str(e):
                    st.error("🧑‍🌾 &nbsp;&nbsp; All our workers are busy! Try again later.")
                else:
                    st.error("🐞 &nbsp;&nbsp; An error occurred during the request.")
                return

    if state.results:

        # Show the gold answer if we use a question of the given set
        if question == state.random_question and eval_mode and state.random_answer:
            st.write("## Correct answers:")
            st.write(state.random_answer)

        st.write("## Results:")

        for count, result in enumerate(state.results):
            if result["answer"]:
                answer, context = result["answer"], result["context"]
                start_idx = context.find(answer)
                end_idx = start_idx + len(answer)
                # Hack due to this bug: https://github.com/streamlit/streamlit/issues/3190 
                st.write(markdown(context[:start_idx] + str(annotation(answer, "ANSWER", "#8ef")) + context[end_idx:]), unsafe_allow_html=True)
                st.write("**Relevance:** ", result["relevance"], "**Source:** ", result["source"])

            else:
                st.info("🤔 &nbsp;&nbsp; Haystack is unsure whether any of the documents contain an answer to your question. Try to reformulate it!")
                st.write("**Relevance:** ", result["relevance"])
                
            if eval_mode:
                # Define columns for buttons
                is_correct_answer = None
                is_correct_document = None

                button_col1, button_col2, button_col3, _ = st.columns([1, 1, 1, 6])
                if button_col1.button("👍", key=f"{result['context']}{count}1", help="Correct answer"):
                    is_correct_answer=True
                    is_correct_document=True

                if button_col2.button("👎", key=f"{result['context']}{count}2", help="Wrong answer and wrong passage"):
                    is_correct_answer=False
                    is_correct_document=False

                if button_col3.button("👎👍", key=f"{result['context']}{count}3", help="Wrong answer, but correct passage"):
                    is_correct_answer=False
                    is_correct_document=True

                if is_correct_answer is not None and is_correct_document is not None:
                    try:
                        send_feedback(
                            query=question,
                            answer_obj=result["_raw"],
                            is_correct_answer=is_correct_answer,
                            is_correct_document=is_correct_document,
                            document=result["document"]
                        )
                        st.success("✨ &nbsp;&nbsp; Thanks for your feedback! &nbsp;&nbsp; ✨")
                    except Exception as e:
                        logging.exception(e)
                        st.error("🐞 &nbsp;&nbsp; An error occurred while submitting your feedback!")

            st.write("___")

        if debug:
            st.subheader("REST API JSON response")
            st.write(state.raw_json)


main()