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import os
import gradio as gr
from gradio import FlaggingCallback
from gradio.components import IOComponent

from datasets import load_dataset
from typing import List, Optional, Any
import argilla as rg
import os

def load_data():
    ds = load_dataset("merve/turkish_instructions", split="train", streaming=True)
    sample = next(iter(ds))

    return sample


def create_record(sample, feedback):
    status = "Validated" if feedback == "Doğru" else "Default"
    #sample = next(iter(ds))
    fields = {
        "talimat": sample["talimat"], 
        "input": sample["giriş"], 
        "response": sample["Γ§Δ±ktΔ±"]
    }
    
    # the label will come from the flag object in Gradio
    label = "True"
    
    record = rg.TextClassificationRecord(
        inputs=fields,
        annotation=label,
        status=status,
        metadata={"feedback": feedback}
    )
    
    print(record)
    return record




class ArgillaLogger(FlaggingCallback):
    def __init__(self, api_url, api_key, dataset_name):
        rg.init(api_url=api_url, api_key=api_key)
        self.dataset_name = dataset_name
    def setup(self, components: List[IOComponent], flagging_dir: str):
        pass
    def flag(
        self,
        flag_data: List[Any],
        flag_option: Optional[str] = None,
        flag_index: Optional[int] = None,
        username: Optional[str] = None,
    ) -> int:
        text = flag_data[0]
        inference = flag_data[1]
        rg.log(name=self.dataset_name, records=create_record(text, flag_option))


        

gr.Interface(
    title = "ALPACA Veriseti DΓΌzeltme ArayΓΌzΓΌ",
    description = "",
    allow_flagging="manual",
    flagging_callback=ArgillaLogger(
        api_url="https://sandbox.argilla.io", 
        api_key=os.getenv("TEAM_API_KEY"), 
        dataset_name="alpaca-flags"
    ),
    flagging_options=["Doğru", "Yanlış", "Belirsiz"]
).launch()