Rename to GPT adventure.

1 files changed, 0 insertions, 172 deletions

diff --git a/ai_dungeon.py b/ai_dungeon.py
deleted file mode 100755
index b0cc64a..0000000
--- a/ai_dungeon.py
+++ /dev/null
@@ -1,172 +0,0 @@
-#!/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
-
-
-def load_nltk():
-    try:
-        tokenize.sent_tokenize('')
-    except LookupError:
-        nltk.download("punkt")
-
-
-def complete_sentence(snippet: str) -> bool:
-    sentences = tokenize.sent_tokenize(snippet)
-    return len(tokenize.sent_tokenize(sentences[-1] + ' extra')) == 2
-
-
-def trim_sentence(message: str) -> str:
-    """Remove extra output after the last period."""
-    sentences = tokenize.sent_tokenize(message)
-    if complete_sentence(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."
-        ),
-        "doctor": (
-            "Your name is Amelia Plenn. Today is your doctors appointment.\n"
-            "You're kind of not looking forward to it because your doctor\n"
-            "is kind of weird, but today when you get to the doctor's office\n"
-            "it's a different person than usual.\n\n"
-            "The new doctor says to you, \"Hello, my name is Doctor Cockman.\n"
-            "It's my pleasure to see you today.\"\n\n"
-            "Doctor Cockman is very handsome, and you feel yourself blush as\n"
-            "he leads you to the doctor's seat. You sit in the seat and he\n"
-            "runs his warm hands up and down your arms.\n\n"
-            "\"Are you feeling alright?\" Doctor Cockman asks."
-        )
-    }
-    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."""
-    load_nltk()
-    parser = argparse.ArgumentParser("AI dungeon clone")
-    parser.add_argument(
-        "--model", default="gpt2", help="Model to use"
-    )
-    args = parser.parse_args()
-    model = load_model(args.model)
-    script = pick_flavor()
-    prologue = wrap(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 complete_sentence(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()