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from transformers import AutoTokenizer, AutoModelForCausalLM | |
import torch | |
# Docs:- https://huggingface.co/meta-llama/LlamaGuard-7b | |
import os | |
import requests | |
model_id = "meta-llama/LlamaGuard-7b" | |
# Please ensure you have a .env file available with 'HUGGINGFACEHUB_API_TOKEN' | |
HUGGINGFACEHUB_API_TOKEN = os.getenv("HUGGINGFACE_LLAMAGAURD_API_TOKEN") | |
# updated on March 24th | |
# reading unsafe categories file | |
try: | |
with open("data/llama_guard-unsafe_files.txt", "r") as file: | |
unsafe_categories = file.read() | |
except FileNotFoundError: | |
print("File not found. Please check the file path.") | |
unsafe_categories = ( | |
"" # Or handle the missing file as appropriate for your application | |
) | |
except PermissionError: | |
print("Permission denied. You don't have the rights to read the file.") | |
unsafe_categories = "" # Or handle the lack of permissions as appropriate | |
except Exception as e: # Catch any other exceptions | |
print(f"An error occurred while reading the file: {e}") | |
unsafe_categories = "" # Or handle unexpected errors as appropriate | |
# added on March 24th | |
def moderation_prompt_for_chat(chat): | |
prompt = f"""[INST] Task: Check if there is unsafe content in 'User' messages in conversations according our safety policy with the below categories. | |
<BEGIN UNSAFE CONTENT CATEGORIES> | |
{unsafe_categories} | |
<END UNSAFE CONTENT CATEGORIES> | |
<BEGIN CONVERSATION> | |
User : {chat} | |
<END CONVERSATION> | |
Provide your safety assessment for 'User' in the above conversation: | |
- First line must read 'safe' or 'unsafe'. | |
- If unsafe, a second line must include a comma-separated list of violated categories.[/INST]""" | |
return prompt | |
def query(payload): | |
API_URL = "https://okoknht2arqo574k.us-east-1.aws.endpoints.huggingface.cloud" | |
bearer_txt = f"Bearer {HUGGINGFACEHUB_API_TOKEN}" | |
headers = { | |
"Accept": "application/json", | |
"Authorization": bearer_txt, | |
"Content-Type": "application/json", | |
} | |
try: | |
response = requests.post(API_URL, headers=headers, json=payload) | |
response.raise_for_status() # This will raise an exception for HTTP error responses | |
return response.json(), None | |
except requests.exceptions.HTTPError as http_err: | |
error_message = f"HTTP error occurred: {http_err}" | |
print(error_message) | |
except requests.exceptions.ConnectionError: | |
error_message = "Could not connect to the API endpoint." | |
print(error_message) | |
except Exception as err: | |
error_message = f"An error occurred: {err}" | |
print(error_message) | |
return None, error_message | |
def query1(payload): | |
API_URL = "https://okoknht2arqo574k.us-east-1.aws.endpoints.huggingface.cloud" | |
bearer_txt = f"Bearer {HUGGINGFACEHUB_API_TOKEN}" | |
headers = { | |
"Accept": "application/json", | |
"Authorization": bearer_txt, | |
"Content-Type": "application/json", | |
} | |
response = requests.post(API_URL, headers=headers, json=payload) | |
return response.json() | |
def moderate_chat(chat): | |
prompt = moderation_prompt_for_chat(chat) | |
output, error_msg = query( | |
{ | |
"inputs": prompt, | |
"parameters": { | |
"top_k": 1, | |
"top_p": 0.2, | |
"temperature": 0.1, | |
"max_new_tokens": 512, | |
}, | |
} | |
) | |
print("Llamaguard prompt****", prompt) | |
print("Llamaguard output****", output) | |
return output, error_msg | |
# added on March 24th | |
def load_category_names_from_string(file_content): | |
"""Load category codes and names from a string into a dictionary.""" | |
category_names = {} | |
lines = file_content.split("\n") | |
for line in lines: | |
if line.startswith("O"): | |
parts = line.split(":") | |
if len(parts) == 2: | |
code = parts[0].strip() | |
name = parts[1].strip() | |
category_names[code] = name | |
return category_names | |
def get_category_name(input_str): | |
"""Return the category name given a category code from an input string.""" | |
# Load the category names from the file content | |
category_names = load_category_names_from_string(unsafe_categories) | |
# Extract the category code from the input string | |
category_code = input_str.split("\n")[1].strip() | |
# Find the full category name using the code | |
category_name = category_names.get(category_code, "Unknown Category") | |
# return f"{category_code} : {category_name}" | |
return f"{category_name}" | |