import json
from collections import Counter
import matplotlib.pyplot as plt
import gradio as gr
import pandas as pd
from transformers import pipeline

plt.switch_backend("Agg")

examples = []
with open("examples.json", "r") as f:
    content = json.load(f)
    examples = [f"{x['label']}: {x['text']}" for x in content]

pipe = pipeline(
    "ner",
    model="Clinical-AI-Apollo/Medical-NER",
    aggregation_strategy="simple",
)

def plot_to_figure(grouped):
    fig = plt.figure()
    plt.bar(x=list(grouped.keys()), height=list(grouped.values()))
    plt.margins(0.2)
    plt.subplots_adjust(bottom=0.4)
    plt.xticks(rotation=90)
    return fig

def run_ner(text):
    raw = pipe(text)
    ner_content = {
        "text": text,
        "entities": [
            {
                "entity": x["entity_group"],
                "word": x["word"],
                "score": x["score"],
                "start": x["start"],
                "end": x["end"],
            }
            for x in raw
        ],
    }
    grouped = Counter((x["entity_group"] for x in raw))
    rows = [[k, v] for k, v in grouped.items()]
    figure = plot_to_figure(grouped)
    return ner_content, rows, figure

# Custom CSS to increase NER output size
custom_css = """
#ner-output {
    min-height: 400px !important;
    max-height: 600px !important;
    overflow-y: auto !important;
}
"""

with gr.Blocks(css=custom_css) as demo:
    note = gr.Textbox(label="Note text", lines=8, max_lines=None, autoscroll=False)
    submit = gr.Button("Submit")
    gr.Markdown("**Examples:**")
    # Rearrange examples - display them in a cleaner column layout
    with gr.Column():
        for i in range(0, len(examples), 2):
            with gr.Row():
                for j in range(2):
                    if i + j < len(examples):
                        example = examples[i + j]
                        gr.Button(example).click(lambda e=example: e, outputs=note)
    highlight = gr.HighlightedText(label="NER", combine_adjacent=True, show_legend=True, elem_id="ner-output")
    table = gr.Dataframe(headers=["Entity", "Count"])
    plot = gr.Plot(label="Bar")
    submit.click(run_ner, [note], [highlight, table, plot])
    note.submit(run_ner, [note], [highlight, table, plot])

demo.launch()