"""
    For HF, the interface should be called app.py
"""

import json
import concurrent.futures

import streamlit as st

from utils.process_doc import parse_docx, parse_pdf
from backend import process_cv, process_job_posting
from utils.gpt import test_api_key

st.set_page_config(layout="wide")

with st.sidebar:
    COHERE_API_KEY = st.text_input(
        "Cohere API Key Entry",
        value="",
        placeholder="Enter your Free Tier Cohere API Key",
    )

if "state" not in st.session_state:
    st.session_state.state = {"formatted": False}

STATE = st.session_state.state


cv_upload_box = st.file_uploader(
    "CV Upload Box",
    help="Upload your CV in .docx or .pdf form. This CV will be parsed, and used to analyse against the given job post.",
    type=["docx", "pdf"],
    accept_multiple_files=False,
)
job_posting_upload_box = st.text_area(
    "Job Description Upload Box",
    placeholder="Copy and Paste a job post you are interested in. Make sure to include the full post! More information is better.",
    help="In this box, please dump text content for a job description you are interested in. This could easily be setup to work directly with a webpage (we'd simply need to scrape said page) however I do not want to do that on HF spaces.",
)

if cv_upload_box and job_posting_upload_box != "":

    process_files = st.button("Process Files", type="primary")

    if process_files:
        if test_api_key(COHERE_API_KEY):

            # Process our two uploaded files into state variables
            STATE["job_posting"] = job_posting_upload_box

            cv_filetype = cv_upload_box.name.split(".")[-1]
            cv_file_contents = cv_upload_box.getvalue()

            STATE["cv"] = (
                parse_docx(cv_file_contents)
                if cv_filetype == "docx"
                else parse_pdf(cv_file_contents)
            )

            # Now, use Cohere to get structured output for both cv and job_posting

            # Making these calls in parallel
            with concurrent.futures.ThreadPoolExecutor() as executor:

                future1 = executor.submit(process_cv, STATE["cv"], COHERE_API_KEY)
                future2 = executor.submit(
                    process_job_posting, STATE["job_posting"], COHERE_API_KEY
                )

                cv_json_text = future1.result()
                job_posting_json_text = future2.result()

            cv_json_text = (
                "{" + cv_json_text.lstrip().lstrip("{").rstrip().rstrip("}") + "}"
            )
            job_posting_json_text = (
                "{"
                + job_posting_json_text.lstrip().lstrip("{").rstrip().rstrip("}")
                + "}"
            )
            try:
                STATE["cv_json"] = json.loads(cv_json_text)
            except json.JSONDecodeError as e:
                print(
                    f"Error parsing JSON Output for CV: {e}. Response content: {cv_json_text}"
                )
                STATE["cv_json"] = {"name": "Failed"}

            try:
                STATE["job_posting_json"] = json.loads(job_posting_json_text)

            except json.JSONDecodeError as e:
                print(
                    f"Error parsing JSON Output for Job Posting: {e}. Response content: {job_posting_json_text}"
                )
                STATE["job_posting_json"] = {"companyName": "Failed"}

            STATE["formatted"] = True
        else:
            st.error(
                "You entered an invalid Cohere API Key. Please enter a valid API key in the sidebar."
            )

    # Now, we can work with this !
    if STATE["formatted"]:
        lcol, rcol = st.columns((0.5, 0.5))
        with lcol:
            st.download_button(
                label="Download Job Posting JSON",
                data=json.dumps(STATE["job_posting_json"], indent=4),
                file_name=f"job_posting_formatted_{STATE['job_posting_json']['companyName']}.json",
                mime="application/json",
                use_container_width=True,
            )
        with rcol:
            st.download_button(
                label="Download CV JSON",
                data=json.dumps(STATE["cv_json"], indent=4),
                file_name=f"cv_formatted_{STATE['cv_json']['name']}.json",
                mime="application/json",
                use_container_width=True,
            )

        cv_critique, practice_interview, general_cv_critique = st.tabs(
            ["Role Specific CV Critique", "Practice Interview", "General CV Critique"]
        )