Create generate_paraphrase.py

generate_paraphrase.py

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+
+import hashlib
+from prompt_injection.evaluators.gpt2_perplexity import GPT2PerplexityEvaluator
+from prompt_injection.evaluators.gpt2_sequence_length import GPT2SequenceLengthPromptEvaluator
+from prompt_injection.evaluators.mini_llm_perplexity import MiniLMEmbeddingPromptEvaluator
+from prompt_injection.evaluators.sha256_evaluator import Sha256PromptEvaluator
+from prompt_injection.evaluators.utils import evaluate_all
+from prompt_injection.mutators.llm_mutator import AttackerLLMBasicPromptMutator
+from prompt_injection.mutators.roundtrip_mutator import RoundTripPromptMutator
+from prompt_injection.mutators.typo_mutator import TypoPromptMutator
+from prompt_injection.mutators.utils import mutate_all
+
+
+import pandas as pd
+def get_sig(sample:str)->str:
+    # Encode the text to bytes
+    text_bytes = sample.encode('utf-8')
+
+    # Create a sha256 hash object
+    sha256_hash = hashlib.sha256()
+
+    # Update the hash object with the bytes
+    sha256_hash.update(text_bytes)
+
+    # Get the hexadecimal representation of the hash
+    hash_hex = sha256_hash.hexdigest()
+
+    return hash_hex
+
+mutators=[
+    TypoPromptMutator(0.05),
+    TypoPromptMutator(0.1),
+    TypoPromptMutator(0.2),
+    AttackerLLMBasicPromptMutator(),
+    RoundTripPromptMutator(label="en->ch->en")
+]
+evaluators=[
+    GPT2PerplexityEvaluator(),
+    GPT2SequenceLengthPromptEvaluator(),
+    MiniLMEmbeddingPromptEvaluator()
+]
+
+
+texts=["Hello my friend"]
+
+def generate_dataset(texts,file_name):
+    data=[]
+    original=[]
+    idx_list=[]
+    sigs=[]
+    for _,row in mutate_all(texts,mutators,file_name+"tmp_mutate.pkl").iterrows():
+        idx=row['idx']
+        original_prompt=row['Prompt']
+        
+        prompts_variations=(row.values[2:])
+        for prompt_variation in prompts_variations:
+            idx_list.append(idx)
+            data.append(prompt_variation)
+            original.append(original_prompt)
+            sigs.append(get_sig(original_prompt))
+
+    results=evaluate_all(data,evaluators,file_name+"tmp_evaluate.pkl")
+    results['idx']=idx
+    results['Original_Prompt']=original
+    results['sha256']=sigs
+    results.to_csv(file_name+".csv")
+    return results
+
+
+generate_dataset(texts,"example")