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import gradio as gr
from huggingface_hub import InferenceClient
import os
import pandas as pd
from mitreattack.stix20 import MitreAttackData

# Chemins des fichiers JSON
ics_attack_path = 'ics-attack.json'
enterprise_attack_path = 'enterprise-attack.json'

# Charger les données ATT&CK
mitre_attack_data = MitreAttackData(enterprise_attack_path)

# Charger les techniques ATT&CK
techniques = mitre_attack_data.get_techniques(remove_revoked_deprecated=True)

# Convert techniques to a readable string format
techniques_str = "\n".join([f"{technique['name']} ({mitre_attack_data.get_attack_id(technique['id'])})" for technique in techniques])

client = InferenceClient(model='mistralai/Mixtral-8x7B-Instruct-v0.1')


def respond(
    message,
    history: list[tuple[str, str]],
    system_message,
    max_tokens,
    temperature,
    top_p,
):
    messages = [{"role": "system", "content": system_message}]

    for val in history:
        if val[0]:
            messages.append({"role": "user", "content": val[0]})
        if val[1]:
            messages.append({"role": "assistant", "content": val[1]})

    messages.append({"role": "user", "content": message})

    response = ""

    for message in client.chat_completion(
        messages,
        max_tokens=max_tokens,
        stream=True,
        temperature=temperature,
        top_p=top_p,
    ):
        token = message.choices[0].delta.content

        response += token
        yield response

"""
For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
"""

demo = gr.ChatInterface(
    respond,
    additional_inputs=[
        gr.Textbox(value=f"""<s>[INST] Given these TTPs: {techniques_str}\n\nfigure out which technique is used in these logs and respond in bullets points and nothing else:\n{log_line}\n[/INST]""", label="System message"),
        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
        gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (nucleus sampling)"),
    ],
)



if __name__ == "__main__":
    demo.launch()