app.py

import json
import math
import os
import uuid
from functools import partial

import jsonlines
import streamlit as st
import streamlit.components.v1 as components
from huggingface_hub import HfApi

BAD_EXAMPLES_PATH = "bad_examples"
DATA_PATH = "data"


def report_result_dataset(dataset, docid, text, metadata, reason, annotator):
    with jsonlines.open("report.jsonl", "w") as f:
        f.write(
            {
                "dataset": dataset,
                "docid": docid,
                "text": text,
                "metadata": metadata,
                "reason": reason,
                "annotator": annotator,
            }
        )

    api = HfApi()
    api.upload_file(
        path_or_fileobj="report.jsonl",
        path_in_repo="report-{}.jsonl".format(uuid.uuid4()),
        repo_id="HuggingFaceGECLM/data_feedback",
        repo_type="dataset",
        token=os.environ.get("geclm_token"),
    )


def load_jsonl(file_path):
    data = []
    with open(file_path, "r") as f:
        for line in f:
            data.append(json.loads(line))

    return data


if "idx" not in st.session_state:
    st.session_state.idx = 0


def get_next_item():
    st.session_state.idx += 1


def save_flag_and_get_next_item(sample, issue):
    if issue is None or issue == "":
        issue = "None"
    sample["issue"] = issue

    with open(f"{BAD_EXAMPLES_PATH}/{dataset}_bad_examples.jsonl", "a") as f:
        f.write(json.dumps(sample) + "\n")

    text = sample["text"]
    sample.pop("text")
    sample.pop("issue")
    sample_id = ""
    if "id" not in sample:
        if "title" in sample:
            sample_id = sample["title"]
    else:
        sample_id = sample["id"]

    report_result_dataset(dataset, sample_id, text, str(sample), issue, "")

    get_next_item()


datasets = [
    "gutenberg_raw",
    "stackexchange2",
    "bigcode_python_code",
    "bigcode_python_github_issues",
    "bigcode_python_jupyter_scripts_dedup_filtered",
    "books3",
    "c4",
    "s2orc_raw",
    "reddit_threaded",
    "cc_filtered_text",
]
dataset = st.sidebar.selectbox("Dataset", datasets)
data = load_jsonl(f"{DATA_PATH}/{dataset}_examples_with_stats.json")

# create bad file if it does not exists
with open(f"{BAD_EXAMPLES_PATH}/{dataset}_bad_examples.jsonl", "a") as f:
    pass

st.sidebar.button("Reset Index", on_click=lambda: st.session_state.__delitem__("idx"))

with open(f"{BAD_EXAMPLES_PATH}/{dataset}_bad_examples.jsonl", "r+") as f:
    st.sidebar.download_button(
        "Download bad example JSON file", f, file_name=f"{dataset}_bad_examples.jsonl"
    )

st.sidebar.button(
    "Clear bad examples file",
    on_click=lambda: open(
        f"{BAD_EXAMPLES_PATH}/{dataset}_bad_examples.jsonl", "w"
    ).close(),
)

with st.form(key="bad_form", clear_on_submit=True):
    sample = data[st.session_state.idx]
    text = sample["text"]
    st.text_area(f"text id: {st.session_state.idx}", text, height=500)

    issue = st.text_input(
        "What's wrong with this example? (leave blank if example is fine)"
    )

    good = st.form_submit_button(
        "GOOD",
        on_click=get_next_item,
    )
    bad = st.form_submit_button(
        "BAD",
        on_click=save_flag_and_get_next_item,
        args=(sample, issue),
    )