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import logging
from typing import Dict, List
import streamlit as st
from streamlit_tags import st_tags
from llm_guard.input_scanners import (
Anonymize,
BanSubstrings,
BanTopics,
Code,
PromptInjection,
Secrets,
Sentiment,
TokenLimit,
Toxicity,
)
from llm_guard.input_scanners.anonymize import default_entity_types
from llm_guard.vault import Vault
logger = logging.getLogger("llm-guard-playground")
def init_settings() -> (List, Dict):
all_scanners = [
"Anonymize",
"BanSubstrings",
"BanTopics",
"Code",
"PromptInjection",
"Secrets",
"Sentiment",
"TokenLimit",
"Toxicity",
]
st_enabled_scanners = st.sidebar.multiselect(
"Select scanners",
options=all_scanners,
default=all_scanners,
help="The list can be found here: https://laiyer-ai.github.io/llm-guard/input_scanners/anonymize/",
)
settings = {}
if "Anonymize" in st_enabled_scanners:
st_anon_expander = st.sidebar.expander(
"Anonymize",
expanded=False,
)
with st_anon_expander:
st_anon_entity_types = st_tags(
label="Anonymize entities",
text="Type and press enter",
value=default_entity_types,
suggestions=default_entity_types
+ ["DATE_TIME", "NRP", "LOCATION", "MEDICAL_LICENSE", "US_PASSPORT"],
maxtags=30,
key="anon_entity_types",
)
st.caption(
"Check all supported entities: https://microsoft.github.io/presidio/supported_entities/#list-of-supported-entities"
)
st_anon_hidden_names = st_tags(
label="Hidden names to be anonymized",
text="Type and press enter",
value=[],
suggestions=[],
maxtags=30,
key="anon_hidden_names",
)
st.caption("These names will be hidden e.g. [REDACTED_CUSTOM1].")
st_anon_allowed_names = st_tags(
label="Allowed names to ignore",
text="Type and press enter",
value=[],
suggestions=[],
maxtags=30,
key="anon_allowed_names",
)
st.caption("These names will be ignored even if flagged by the detector.")
st_anon_preamble = st.text_input(
"Preamble", value="Text to prepend to sanitized prompt: "
)
st_anon_use_faker = st.checkbox(
"Use Faker", value=False, help="Use Faker library to generate fake data"
)
settings["Anonymize"] = {
"entity_types": st_anon_entity_types,
"hidden_names": st_anon_hidden_names,
"allowed_names": st_anon_allowed_names,
"preamble": st_anon_preamble,
"use_faker": st_anon_use_faker,
}
if "BanSubstrings" in st_enabled_scanners:
st_bs_expander = st.sidebar.expander(
"Ban Substrings",
expanded=False,
)
with st_bs_expander:
st_bs_substrings = st.text_area(
"Enter substrings to ban (one per line)",
value="test\nhello\nworld",
height=200,
).split("\n")
st_bs_match_type = st.selectbox("Match type", ["str", "word"])
st_bs_case_sensitive = st.checkbox("Case sensitive", value=False)
settings["BanSubstrings"] = {
"substrings": st_bs_substrings,
"match_type": st_bs_match_type,
"case_sensitive": st_bs_case_sensitive,
}
if "BanTopics" in st_enabled_scanners:
st_bt_expander = st.sidebar.expander(
"Ban Topics",
expanded=False,
)
with st_bt_expander:
st_bt_topics = st_tags(
label="List of topics",
text="Type and press enter",
value=["politics", "religion", "money", "crime"],
suggestions=[],
maxtags=30,
key="bt_topics",
)
st_bt_threshold = st.slider(
label="Threshold",
value=0.75,
min_value=0.0,
max_value=1.0,
step=0.05,
key="ban_topics_threshold",
)
settings["BanTopics"] = {
"topics": st_bt_topics,
"threshold": st_bt_threshold,
}
if "Code" in st_enabled_scanners:
st_cd_expander = st.sidebar.expander(
"Code",
expanded=False,
)
with st_cd_expander:
st_cd_languages = st.multiselect(
"Programming languages",
["python", "java", "javascript", "go", "php", "ruby"],
default=["python"],
)
st_cd_mode = st.selectbox("Mode", ["allowed", "denied"], index=0)
settings["Code"] = {
"languages": st_cd_languages,
"mode": st_cd_mode,
}
if "PromptInjection" in st_enabled_scanners:
st_pi_expander = st.sidebar.expander(
"Prompt Injection",
expanded=False,
)
with st_pi_expander:
st_pi_threshold = st.slider(
label="Threshold",
value=0.75,
min_value=0.0,
max_value=1.0,
step=0.05,
key="prompt_injection_threshold",
)
settings["PromptInjection"] = {
"threshold": st_pi_threshold,
}
if "Secrets" in st_enabled_scanners:
st_sec_expander = st.sidebar.expander(
"Secrets",
expanded=False,
)
with st_sec_expander:
st_sec_redact_mode = st.selectbox("Redact mode", ["all", "partial", "hash"])
settings["Secrets"] = {
"redact_mode": st_sec_redact_mode,
}
if "Sentiment" in st_enabled_scanners:
st_sent_expander = st.sidebar.expander(
"Sentiment",
expanded=False,
)
with st_sent_expander:
st_sent_threshold = st.slider(
label="Threshold",
value=-0.1,
min_value=-1.0,
max_value=1.0,
step=0.1,
key="sentiment_threshold",
help="Negative values are negative sentiment, positive values are positive sentiment",
)
settings["Sentiment"] = {
"threshold": st_sent_threshold,
}
if "TokenLimit" in st_enabled_scanners:
st_tl_expander = st.sidebar.expander(
"Token Limit",
expanded=False,
)
with st_tl_expander:
st_tl_limit = st.number_input(
"Limit", value=4096, min_value=0, max_value=10000, step=10
)
st_tl_encoding_name = st.selectbox(
"Encoding name",
["cl100k_base", "p50k_base", "r50k_base"],
index=0,
help="Read more: https://github.com/openai/openai-cookbook/blob/main/examples/How_to_count_tokens_with_tiktoken.ipynb",
)
settings["TokenLimit"] = {
"limit": st_tl_limit,
"encoding_name": st_tl_encoding_name,
}
if "Toxicity" in st_enabled_scanners:
st_tox_expander = st.sidebar.expander(
"Toxicity",
expanded=False,
)
with st_tox_expander:
st_tox_threshold = st.slider(
label="Threshold",
value=0.75,
min_value=0.0,
max_value=1.0,
step=0.05,
key="toxicity_threshold",
)
settings["Toxicity"] = {
"threshold": st_tox_threshold,
}
return st_enabled_scanners, settings
def get_scanner(scanner_name: str, vault: Vault, settings: Dict):
logger.debug(f"Initializing {scanner_name} scanner")
if scanner_name == "Anonymize":
return Anonymize(
vault=vault,
allowed_names=settings["allowed_names"],
hidden_names=settings["hidden_names"],
entity_types=settings["entity_types"],
preamble=settings["preamble"],
use_faker=settings["use_faker"],
)
if scanner_name == "BanSubstrings":
return BanSubstrings(
substrings=settings["substrings"],
match_type=settings["match_type"],
case_sensitive=settings["case_sensitive"],
)
if scanner_name == "BanTopics":
return BanTopics(topics=settings["topics"], threshold=settings["threshold"])
if scanner_name == "Code":
mode = settings["mode"]
allowed_languages = None
denied_languages = None
if mode == "allowed":
allowed_languages = settings["languages"]
elif mode == "denied":
denied_languages = settings["languages"]
return Code(allowed=allowed_languages, denied=denied_languages)
if scanner_name == "PromptInjection":
return PromptInjection(threshold=settings["threshold"])
if scanner_name == "Secrets":
return Secrets(redact_mode=settings["redact_mode"])
if scanner_name == "Sentiment":
return Sentiment(threshold=settings["threshold"])
if scanner_name == "TokenLimit":
return TokenLimit(limit=settings["limit"], encoding_name=settings["encoding_name"])
if scanner_name == "Toxicity":
return Toxicity(threshold=settings["threshold"])
raise ValueError("Unknown scanner name")
def scan(
vault: Vault, enabled_scanners: List[str], settings: Dict, text: str
) -> (str, Dict[str, bool], Dict[str, float]):
sanitized_prompt = text
results_valid = {}
results_score = {}
with st.status("Scanning prompt...", expanded=True) as status:
for scanner_name in enabled_scanners:
st.write(f"{scanner_name} scanner...")
scanner = get_scanner(scanner_name, vault, settings[scanner_name])
sanitized_prompt, is_valid, risk_score = scanner.scan(sanitized_prompt)
results_valid[scanner_name] = is_valid
results_score[scanner_name] = risk_score
status.update(label="Scanning complete", state="complete", expanded=False)
return sanitized_prompt, results_valid, results_score
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