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from collections import deque |
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from fastai.text.all import load_learner |
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import sys |
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import re |
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MAX_HISTORY_CHARS = 800 |
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MAX_HISTORY_MESSAGES = 1 |
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GENERATE_TOKENS = 70 |
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TEMPERATURE = 0.3 |
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def evaluate_placeholders(text: str) -> str: |
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def repl(match): |
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expr = match.group(1) |
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try: |
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if re.fullmatch(r"[\d\s\+\-\*\/]+", expr): |
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return str(eval(expr)) |
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except Exception: |
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pass |
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return match.group(0) |
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return re.sub(r"\{([^{}]+)\}", repl, text) |
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def remove_before_first_colon(s: str) -> str: |
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return s.split("BOT :", 1)[-1] |
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def remove_before_last_colon(s: str) -> str: |
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return s.rsplit(":", 1)[-1] |
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def remove_after_user(text): |
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keyword = "USER" |
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index = text.find(keyword) |
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if index != -1: |
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return text[:index + len(keyword)] |
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return text |
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def remove_after_bot(text): |
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keyword = "BOT" |
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index = text.find(keyword) |
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if index != -1: |
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return text[:index + len(keyword)] |
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return text |
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def truncate(answer): |
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for sep in ["\n", "USER:", "BOT:"]: |
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if sep in answer: |
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answer = answer.split(sep)[0] |
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answer = remove_before_first_colon(answer) |
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answer = remove_after_user(answer) |
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answer = remove_after_bot(answer) |
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answer = answer.replace(": USER", "").replace(" USER", "").replace("USER", "").replace(" !", "!").replace(" .", ".").replace(" ,", ",").replace(": BOT", "").replace(" BOT", "").replace("BOT", "").replace(" `", "`").replace(' "', '"').replace(" β", "β").replace("do n'", "don'").replace("do nβ", "donβ") |
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answer = answer.replace(" '", "'").replace(" :", ":").replace(" (", "(").replace(" )", ")").replace(" ?", "?").replace("Open Assistant", "Bomba-1") |
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return answer.strip() |
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def load_models(): |
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print("π€ Loading modelsβ¦") |
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chat_model = load_learner("model/SimpleMath.pkl") |
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chat_model.model.eval() |
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return chat_model |
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def main(): |
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chat_model = load_models() |
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history = deque() |
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print("π¬ Ready! (empty line to quit)\n") |
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while True: |
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try: |
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user = input("USER: ").strip() |
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if not user: |
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break |
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history.append(f"USER: {user}") |
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while len(history) > MAX_HISTORY_MESSAGES: |
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history.popleft() |
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prompt_lines = list(history) |
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prompt_text = " ".join(history).replace("\n"," ") |
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if len(prompt_text) > MAX_HISTORY_CHARS: |
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prompt_text = prompt_text[-MAX_HISTORY_CHARS:] |
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prompt = f"{prompt_text} BOT: " |
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generated = chat_model.predict( |
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prompt, |
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n_words=GENERATE_TOKENS, |
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temperature=TEMPERATURE, |
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min_p=0.01 |
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) |
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try: |
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_, raw = generated.split(prompt, 1) |
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except ValueError: |
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raw = generated |
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raw = raw.strip() |
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if raw.upper().startswith("USER:") and "BOT:" in raw: |
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raw = raw.split("BOT:", 1)[1].strip() |
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answer = truncate(raw) |
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answer = evaluate_placeholders(answer) |
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answer = answer.replace("-", "\n-").replace("1)", "\n1)").replace("2)", "\n2)").replace("3)", "\n3)").replace("4)", "\n4)").replace("5)", "\n5)").replace("* ", "\n* ").replace("Final", "\nFinal") |
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if not "Final" in answer: |
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answer = answer.replace("Result", "\nResult") |
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print("BOT:", answer, "\n") |
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history.append(f"BOT: {answer}") |
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except KeyboardInterrupt: |
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break |
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if __name__ == "__main__": |
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main() |