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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(idx): | |
| ds = load_dataset("merve/turkish_instructions", split="train").to_pandas() | |
| sample = df.iloc[idx] | |
| instruction = sample["talimat"] | |
| input_sample = sample["giriΕ"] | |
| response = sample["Γ§Δ±ktΔ±"] | |
| return instruction, input_sample, response | |
| def create_record(instruction, inpu_sample, response, feedback): | |
| status = "Validated" if feedback == "DoΔru" else "Default" | |
| fields = { | |
| "talimat": instruction, | |
| "input": input_sample, | |
| "response": response | |
| } | |
| # 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( | |
| load_data, | |
| title = "ALPACA Veriseti DΓΌzeltme ArayΓΌzΓΌ", | |
| description = "Bir satΔ±r sayΔ±sΔ± verip ΓΆrnek alΔ±n.", | |
| allow_flagging="manual", | |
| flagging_callback=ArgillaLogger( | |
| api_url="https://sandbox.argilla.io", | |
| api_key=os.getenv("TEAM_API_KEY"), | |
| dataset_name="alpaca-flags" | |
| ), | |
| inputs=["text"], | |
| outputs=["text", "text", "text"], | |
| flagging_options=["DoΔru", "YanlΔ±Ε", "Belirsiz"] | |
| ).launch() |