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#!/usr/bin/env nix-shell
#!nix-shell -i python3 -p "python3.withPackages (pkgs: with pkgs; [ keras nltk pytorch transformers ])"
"""AI Dungeon is a text-adventure style game powered by AI."""
import argparse
import re
import shutil
import sys
import nltk
from nltk import tokenize
import transformers
sentence_end = re.compile(r"[.?!\"')]$")
def trim_sentence(message: str) -> str:
"""Remove extra output after the last period."""
try:
sentences = tokenize.sent_tokenize(message)
except LookupError:
nltk.download("punkt")
sentences = tokenize.sent_tokenize(message)
if sentence_end.search(sentences[-1]) or len(sentences) == 1:
return message
return " ".join(sentences[:-1])
def generate(model: transformers.TextGenerationPipeline, prompt: str, **kwargs) -> str:
"""Generate text from a text generator."""
out = model(prompt, do_sample=True, temperature=0.9, top_k=60, top_p=0.9, **kwargs)
return trim_sentence(out[0]["generated_text"])
def load_model(model: str) -> transformers.TextGenerationPipeline:
"""Load a model by name."""
tokenizer = transformers.AutoTokenizer.from_pretrained(model)
return transformers.pipeline(
"text-generation",
tokenizer=tokenizer,
model=transformers.AutoModelForCausalLM.from_pretrained(model),
pad_token_id=tokenizer.eos_token_id,
)
def pick_flavor() -> str:
"""Query the user for what scenario they want to play."""
flavors = {
"fantasy": (
"You are a wizard named Megumin from the kingdom\n"
"of Larion. You have in your inventory a wizard's staff\n"
"and a spellbook. You are arriving after a day's travel\n"
"at an enchanted tower where there's rumors of gold.\n"
"You walk up to the entrance of the tower."
),
"post apocalyptic": (
"You are a machinist named Azariel, living\n"
"in the city of New New York. It's been almost 10 years\n"
"since the bombs fell, but you still remember it as if\n"
"it were yesterday. You push these thoughts out of your\n"
"mind and focus on the task at hand: finding a water\n"
"purifier for your settlement. You arrive at an\n"
"abandoned settlement to the east of your home."
),
}
choices = []
for i, (scenario, script) in enumerate(flavors.items()):
print(f"{i}.\t{scenario}")
choices.append(script)
while True:
choice = input("Choose a scenario: ")
try:
choice_int = int(choice)
except ValueError:
print("Input must be an integer.")
continue
try:
return choices[choice_int]
except IndexError:
print("Index out of bounds.")
continue
def wrap(message: str) -> str:
"""Wrap long lines to terminal width characters."""
width = shutil.get_terminal_size().columns
res = []
for line in message.split("\n"):
if len(line) < width:
res.append(line)
continue
split_line = []
for word in line.split(" "):
if not split_line or len(" ".join(split_line)) + len(word) < width:
split_line.append(word)
continue
res.append(" ".join(split_line))
split_line = [word]
res.append(" ".join(split_line))
return "\n".join(res)
def main() -> None:
"""Run the main game loop."""
parser = argparse.ArgumentParser("AI dungeon clone")
parser.add_argument(
"--model", default="EleutherAI/gpt-neo-125M", help="Model to use"
)
args = parser.parse_args()
model = load_model(args.model)
script = pick_flavor()
prologue = generate(
model,
script,
max_new_tokens=20,
forced_eos_token_id=model.tokenizer.eos_token_id,
)
print(prologue)
prompt = prologue
prev_response_length = 0
prev_response_lines = 0
while True:
try:
msg = input("> You ")
except EOFError:
break
if msg == "/retry":
prompt = prompt[:-prev_response_length]
print(f"\033[{prev_response_lines}A\033[J", end="")
elif msg == "/edit":
prompt = prompt[:-prev_response_length]
print(f"\033[{prev_response_lines}A\033[J\r", end="")
new_response = sys.stdin.read()
prompt += new_response
prev_response_length = len(new_response)
prev_response_lines = len(new_response.split("\n"))
continue
else:
if not sentence_end.search(msg):
msg += "."
prompt += f"You {msg}\n"
prompt = prompt[-10000:]
response = wrap(
generate(model, prompt, return_full_text=False, max_new_tokens=50).strip()
)
print(response)
response += "\n"
prompt += response
prev_response_length = len(response)
prev_response_lines = len(response.split("\n"))
main()
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