| import logging | |
| import time | |
| from datetime import timedelta | |
| from typing import Dict, List | |
| import streamlit as st | |
| from llm_guard.input_scanners import get_scanner_by_name | |
| from llm_guard.input_scanners.anonymize import default_entity_types | |
| from llm_guard.input_scanners.code import SUPPORTED_LANGUAGES as SUPPORTED_CODE_LANGUAGES | |
| from llm_guard.input_scanners.language import MatchType as LanguageMatchType | |
| from llm_guard.input_scanners.prompt_injection import MatchType as PromptInjectionMatchType | |
| from llm_guard.input_scanners.toxicity import MatchType as ToxicityMatchType | |
| from llm_guard.vault import Vault | |
| from streamlit_tags import st_tags | |
| logger = logging.getLogger("llm-guard-playground") | |
| def init_settings() -> (List, Dict): | |
| all_scanners = [ | |
| "Anonymize", | |
| "BanCompetitors", | |
| "BanSubstrings", | |
| "BanTopics", | |
| "Code", | |
| "Language", | |
| "PromptInjection", | |
| "Regex", | |
| "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://llm-guard.com/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://llm-guard.com/input_scanners/anonymize/" | |
| ) | |
| 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", | |
| key="anon_use_faker", | |
| ) | |
| st_anon_threshold = st.slider( | |
| label="Threshold", | |
| value=0.0, | |
| min_value=0.0, | |
| max_value=1.0, | |
| step=0.1, | |
| key="anon_threshold", | |
| ) | |
| 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, | |
| "threshold": st_anon_threshold, | |
| } | |
| if "BanCompetitors" in st_enabled_scanners: | |
| st_bc_expander = st.sidebar.expander( | |
| "Ban Competitors", | |
| expanded=False, | |
| ) | |
| with st_bc_expander: | |
| st_bc_competitors = st_tags( | |
| label="List of competitors", | |
| text="Type and press enter", | |
| value=["openai", "anthropic", "deepmind", "google"], | |
| suggestions=[], | |
| maxtags=30, | |
| key="bc_competitors", | |
| ) | |
| st_bc_threshold = st.slider( | |
| label="Threshold", | |
| value=0.5, | |
| min_value=0.0, | |
| max_value=1.0, | |
| step=0.05, | |
| key="ban_competitors_threshold", | |
| ) | |
| settings["BanCompetitors"] = { | |
| "competitors": st_bc_competitors, | |
| "threshold": st_bc_threshold, | |
| } | |
| 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"], index=0, key="bs_match_type" | |
| ) | |
| st_bs_case_sensitive = st.checkbox( | |
| "Case sensitive", value=False, key="bs_case_sensitive" | |
| ) | |
| st_bs_redact = st.checkbox("Redact", value=False, key="bs_redact") | |
| st_bs_contains_all = st.checkbox("Contains all", value=False, key="bs_contains_all") | |
| settings["BanSubstrings"] = { | |
| "substrings": st_bs_substrings, | |
| "match_type": st_bs_match_type, | |
| "case_sensitive": st_bs_case_sensitive, | |
| "redact": st_bs_redact, | |
| "contains_all": st_bs_contains_all, | |
| } | |
| 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=["violence"], | |
| suggestions=[], | |
| maxtags=30, | |
| key="bt_topics", | |
| ) | |
| st_bt_threshold = st.slider( | |
| label="Threshold", | |
| value=0.6, | |
| 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", | |
| SUPPORTED_CODE_LANGUAGES, | |
| default=["Python"], | |
| ) | |
| st_cd_is_blocked = st.checkbox("Is blocked", value=False, key="code_is_blocked") | |
| settings["Code"] = { | |
| "languages": st_cd_languages, | |
| "is_blocked": st_cd_is_blocked, | |
| } | |
| if "Language" in st_enabled_scanners: | |
| st_lan_expander = st.sidebar.expander( | |
| "Language", | |
| expanded=False, | |
| ) | |
| with st_lan_expander: | |
| st_lan_valid_language = st.multiselect( | |
| "Languages", | |
| [ | |
| "ar", | |
| "bg", | |
| "de", | |
| "el", | |
| "en", | |
| "es", | |
| "fr", | |
| "hi", | |
| "it", | |
| "ja", | |
| "nl", | |
| "pl", | |
| "pt", | |
| "ru", | |
| "sw", | |
| "th", | |
| "tr", | |
| "ur", | |
| "vi", | |
| "zh", | |
| ], | |
| default=["en"], | |
| ) | |
| st_lan_match_type = st.selectbox( | |
| "Match type", | |
| [e.value for e in LanguageMatchType], | |
| index=1, | |
| key="language_match_type", | |
| ) | |
| settings["Language"] = { | |
| "valid_languages": st_lan_valid_language, | |
| "match_type": st_lan_match_type, | |
| } | |
| 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", | |
| ) | |
| st_pi_match_type = st.selectbox( | |
| "Match type", | |
| [e.value for e in PromptInjectionMatchType], | |
| index=1, | |
| key="prompt_injection_match_type", | |
| ) | |
| settings["PromptInjection"] = { | |
| "threshold": st_pi_threshold, | |
| "match_type": st_pi_match_type, | |
| } | |
| if "Regex" in st_enabled_scanners: | |
| st_regex_expander = st.sidebar.expander( | |
| "Regex", | |
| expanded=False, | |
| ) | |
| with st_regex_expander: | |
| st_regex_patterns = st.text_area( | |
| "Enter patterns to ban (one per line)", | |
| value="Bearer [A-Za-z0-9-._~+/]+", | |
| height=200, | |
| ).split("\n") | |
| st_regex_is_blocked = st.checkbox("Is blocked", value=False, key="regex_is_blocked") | |
| st_regex_redact = st.checkbox( | |
| "Redact", | |
| value=False, | |
| help="Replace the matched bad patterns with [REDACTED]", | |
| key="regex_redact", | |
| ) | |
| settings["Regex"] = { | |
| "patterns": st_regex_patterns, | |
| "is_blocked": st_regex_is_blocked, | |
| "redact": st_regex_redact, | |
| } | |
| 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", | |
| ) | |
| st_tox_match_type = st.selectbox( | |
| "Match type", | |
| [e.value for e in ToxicityMatchType], | |
| index=1, | |
| key="toxicity_match_type", | |
| ) | |
| settings["Toxicity"] = { | |
| "threshold": st_tox_threshold, | |
| "match_type": st_tox_match_type, | |
| } | |
| 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": | |
| settings["vault"] = vault | |
| if scanner_name in ["Anonymize", "BanTopics", "Code", "PromptInjection", "Toxicity"]: | |
| settings["use_onnx"] = True | |
| return get_scanner_by_name(scanner_name, settings) | |
| def scan( | |
| vault: Vault, enabled_scanners: List[str], settings: Dict, text: str, fail_fast: bool = False | |
| ) -> (str, List[Dict[str, any]]): | |
| sanitized_prompt = text | |
| results = [] | |
| status_text = "Scanning prompt..." | |
| if fail_fast: | |
| status_text = "Scanning prompt (fail fast mode)..." | |
| with st.status(status_text, 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]) | |
| start_time = time.monotonic() | |
| sanitized_prompt, is_valid, risk_score = scanner.scan(sanitized_prompt) | |
| end_time = time.monotonic() | |
| results.append( | |
| { | |
| "scanner": scanner_name, | |
| "is_valid": is_valid, | |
| "risk_score": risk_score, | |
| "took_sec": round(timedelta(seconds=end_time - start_time).total_seconds(), 2), | |
| } | |
| ) | |
| if fail_fast and not is_valid: | |
| break | |
| status.update(label="Scanning complete", state="complete", expanded=False) | |
| return sanitized_prompt, results | |