Main developer ParisNeo
PyAIPersonality is a Python library for defining AI personalities for AI-based models. With PyAIPersonality, you can define a file format, assets, and personalized scripts to create unique AI personalities.
You can install PyAIPersonality using pip:
pip install pyaipersonalityHere's an example of how to use PyAIPersonality to load an AI personality and print its attributes:
from pyaipersonality import AIPersonality
if __name__=="__main__":
personality = AIPersonality("personalities_zoo/english/generic/gpt4all")
print("Done")
print(f"{personality}")You can use PyAIPersonality with pyllamacpp python bindings by first installing pyllamacpp:
pip install pyllamacppDownload one of the compatible models. Some models are better than others in simulating the personalities, so please make sure you select the right model as some models are very sparsely trained and have no enough culture to imersonate the character.
Here is a list of compatible models:
Then you can use this code to have an interactive communication with the AI through the console :
from pyaipersonality import AIPersonality
from pyllamacpp.model import Model
from pathlib import Path
import urllib.request
import sys
import os
from tqdm import tqdm
# You need to install pyllamacpp from pypi:
# pip install pyllamacpp
if __name__=="__main__":
# choose your model
# undomment the model you want to use
# These models can be automatically downloaded
# url = "https://huggingface.co/ParisNeo/GPT4All/resolve/main/gpt4all-lora-quantized-ggml.bin"
# url = "https://huggingface.co/ParisNeo/GPT4All/resolve/main/gpt4all-lora-unfiltered-quantized.new.bin"
# url = "https://huggingface.co/eachadea/legacy-ggml-vicuna-7b-4bit/resolve/main/ggml-vicuna-7b-4bit-rev1.bin"
url = "https://huggingface.co/eachadea/ggml-vicuna-13b-4bit/resolve/main/ggml-vicuna-13b-4bit-rev1.bin"
# You can add any llamacpp compatible model
model_name = url.split("/")[-1]
folder_path = Path("models/")
model_full_path = (folder_path / model_name)
# Check if file already exists in folder
if model_full_path.exists():
print("File already exists in folder")
else:
# Create folder if it doesn't exist
folder_path.mkdir(parents=True, exist_ok=True)
progress_bar = tqdm(total=None, unit="B", unit_scale=True, desc=f"Downloading {url.split('/')[-1]}")
# Define callback function for urlretrieve
def report_progress(block_num, block_size, total_size):
progress_bar.total=total_size
progress_bar.update(block_size)
# Download file from URL to folder
try:
urllib.request.urlretrieve(url, folder_path / url.split("/")[-1], reporthook=report_progress)
print("File downloaded successfully!")
except Exception as e:
print("Error downloading file:", e)
sys.exit(1)
personality = AIPersonality("personalities_zoo/english/generic/gpt4all")
full_context = personality.personality_conditioning+personality.link_text+personality.ai_message_prefix+personality.welcome_message if personality.welcome_message!="" else personality.personality_conditioning
model = Model(model_path=f'models/{url.split("/")[-1]}',
prompt_context=full_context,
prompt_prefix=personality.link_text + personality.user_message_prefix + personality.link_text,
prompt_suffix=personality.link_text + personality.ai_message_prefix + personality.link_text
)
# If there is a disclaimer, show it
if personality.disclaimer!="":
print()
print("Disclaimer")
print(personality.disclaimer)
print()
# Show conditionning
print(full_context)
while True:
try:
prompt = input("You: ")
if prompt == '':
continue
print(f"{personality.name}:", end='')
output=""
for tok in model.generate(
prompt,
n_predict=personality.model_n_predicts,
temp=personality.model_temperature,
top_k=personality.model_top_k,
top_p=personality.model_top_p,
repeat_last_n=personality.model_repeat_last_n,
repeat_penalty=personality.model_repeat_penalty
):
output += tok
# Use Hallucination suppression system
if personality.detect_antiprompt(output):
break
else:
print(f"{tok}", end='', flush=True)
print()
except KeyboardInterrupt:
print("Keyboard interrupt detected.\nBye")
break
print("Done")
print(f"{personality}")For our new multi-personality AI agent library, we wanted to come up with a naming scheme that reflected our love for science fiction and artificial intelligence. Each release of the application will feature a different AI agent with a distinct personality and set of capabilities, so we felt it was important to give each version a unique and memorable name.
GLaDOS is a fictional AI character from the popular video game series "Portal" developed by Valve Corporation. She serves as the primary antagonist throughout the series, with her primary function being the management of the Aperture Science Enrichment Center.
GLaDOS, which stands for "Genetic Lifeform and Disk Operating System," is designed as a highly intelligent and manipulative AI. She speaks in a calm and monotone voice, often using sarcastic humor and passive-aggressive language to communicate with the player character, Chell.
Throughout the series, GLaDOS is depicted as being both ruthless and resourceful, often using deadly force and deception to achieve her goals. Despite her malicious behavior, she is also shown to have a complex and troubled history, with much of her backstory revealed over the course of the games.
Overall, GLaDOS is a memorable and iconic AI character in sci-fi culture, known for her wit, sarcasm, and unpredictable behavior.
Contributions to PyAIPersonality are welcome! If you'd like to contribute, please follow these steps:
- Fork this repository
- Create a new branch (
git checkout -b my-new-branch) - Make your changes
- Commit your changes (
git commit -am 'Add some feature') - Push to the branch (
git push origin my-new-branch) - Create a new pull request
PyAIPersonality is licensed under the Apache 2.0 license. See the LICENSE file for more information.