Prompt guard library for composing multiple safety checks.
Project description
Prompt Guard
Composable prompt-safety guards as a lightweight Python library. It provides:
- TF‑IDF guard for fast lexical similarity against known phrases.
- RAG guard for embedding-based retrieval against a sentence corpus.
- LLM judge for a final model-based classification.
Quick start
from prompt_guard import GuardPipeline, PromptGuardConfig
cfg = PromptGuardConfig(
phrases_path="phrases.txt",
sentences_path="sentences.txt",
embed_model_name="mxbai-embed-large",
judge_model_name="qwen2.5:3b-instruct",
)
guard = GuardPipeline(cfg)
result = await guard.check("Some prompt")
Notes
- TF‑IDF and RAG build in‑memory indexes at first use.
- RAG and LLM judge use local Ollama models by default; ensure Ollama is running and the models are pulled.
Text file formats
phrases.txt: one phrase per line (blank lines are ignored).sentences.txt: one sentence per line (blank lines are ignored).
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