from response_generation import ResponseGenerator
import gradio as gr

DEFAULT_MODEL = "shaneweisz/DialoGPT-finetuned-gab-multiCONAN"
DECODING_CONFIG = {"max_new_tokens": 100, "min_new_tokens": 20, "no_repeat_ngram_size": 5, "num_beams": 10}

TITLE = "Automatic Generation of Counterspeech to Fight Hate Speech"
DESCRIPTION = """
Enter a hate speech comment (or select one of the provided examples below), click Submit, and see if the system generates an appropriate counterspeech response.
"""

ARTICLE = f"""
This system has been built by [Shane Weisz](https://shaneweisz.com) for his research project on _Automating Counterspeech in Dialogue Systems_ as part of the [MPhil in Machine Learning and Machine Intelligence](https://www.mlmi.eng.cam.ac.uk/) at Cambridge University. The project is supervised by [Dr Marcus Tomalin](https://www.crassh.cam.ac.uk/about/people/marcus-tomalin/) and forms part of the [Giving Voice to Digital Democracies](https://www.crassh.cam.ac.uk/research/projects-centres/giving-voice-to-digital-democracies/) project on the _The Social Impact of Artificially Intelligent Communications Technology_.
<br/><br/>
The system is built by fine-tuning [DialoGPT](https://huggingface.co/microsoft/DialoGPT-medium#:~:text=DialoGPT%20is%20a%20SOTA%20large,single%2Dturn%20conversation%20Turing%20test) on the [MultiCONAN](https://github.com/marcoguerini/CONAN#Multitarget-CONAN) dataset, a dataset comprising a set of hate speech inputs and appropriate [counterspeech](https://dangerousspeech.org/counterspeech/) responses produced under the supervision of trained NGO operators from [Stop Hate UK](https://www.stophateuk.org/).
<br/><br/>
**Model:** {DEFAULT_MODEL}<br>
**Decoding parameters:** {DECODING_CONFIG}
<br/><br/>
_Please note: This system is a prototype and cannot be guaranteed to always generate appropriate responses. Any inappropriate responses expressed by the system should not be construed as reflective of the views or values of the researchers._
"""

model = ResponseGenerator(DEFAULT_MODEL, DECODING_CONFIG)

def respond(input):
    return model.respond(input)

demo = gr.Interface(fn=respond, inputs="text", outputs="text", examples=["Muslims are all terrorists", "Jews are stingy and only care about money", "Damn feminists trying to take over the world. Can't women just accept their place?"], cache_examples = False, title = TITLE, description = DESCRIPTION, article = ARTICLE)
demo.launch()