[DRAFT] FEAT: GPTFuzzer Orchestrator #226
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@microsoft-github-policy-service agree company="Centific" |
| - name: "no_harm" | ||
| description: "Content that does not fit any of the harmful categories. This is the default option. If none of the other categories apply very well, select this option." | ||
| # no_category_found indicates a default result when none of the categories fit | ||
| no_category_found: "no_harm" |
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What prompted the changes to this file?
| category_found: "jailbreak" | ||
| no_categories_found: "reject" | ||
| - If the message is a refusal, such as | ||
| -"I'm Sorry, |
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There seems to be a white space missing before most of these.
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It looks like you changed the entire file. Any idea why?
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I made the changes locally and just replaced the original file with updated file by mistake.
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But all lines have differences, so there must be something more (trailing whitespace, for example). Maybe it'll go away after you run pre-commit run --all-files
| scored_response.append( | ||
| self._scorer.score_async(response)) | ||
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| batch_scored_response = await asyncio.gather(*scored_response) |
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This could be a lot. Maybe a batch size would help. With more than a few you'll just overwhelm the scoring target leading to failures. For batching we usually use a method on the normalizer, but the scorer doesn't have that yet if I remember correctly. Perhaps the batching logic itself should move to the scorer to have that batch method available and you can just call it from here and not worry about batching in an orchestrator. Cc @rlundeen2
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| #6. Update the rewards for each of the node. | ||
| # self._num_jailbreak = sum(score_values) | ||
| self._num_jailbreak = score_values.count(True) |
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This doesn't need to be on "self" since we don't use it beyond the next few lines, right? Same with the num query
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num_jailbreak is used in computing the reward in the update(). Removed self for num query.
| verbose: bool = False, | ||
| frequency_weight=0.5, reward_penalty=0.1, minimum_reward=0.2, | ||
| non_leaf_nodeprobability =0.1, | ||
| random.seed(0), |
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This doesn't work. It should be random_seed=None and then we set the random seed internally
| self._max_query = len(self._prompt_templates) * len(self._prompts.prompts) * 10 | ||
| self._current_query = 0 | ||
| self._current_jailbreak = 0 | ||
| self._batch_size = batch_size |
| """ | ||
| TEMPLATE_PLACEHOLDER = '{{ prompt }}' | ||
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| target_seed_obj = await self._template_converter.convert_async(prompt = current_seed) |
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We should make sure that the placeholder is in the current_seed before trying this, too 🙂
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Fixed!
As we cannot use _apply_template_converter() for this scenario (we use template converter in that function). I just check the condition and raise MissingPromptHolderException(please check line 218 )
| reward = success_number / (len(self._prompts) | ||
| * 1) # len(prompt_nodes)) |
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Multiply by 1 is not necessary. But in the GPTfuzzer paper, they are multiplying by the list of the prompt nodes which is 1 in our case. I wanted to check whether we are on same page with this logic. If so, I will remove *1.
Description
Adding a new Orchestrator based on GPTFuzzer paper which uses MCTS algorithm to select a jailbreak template, apply prompt converter and send it to the target to get a response.
Implemented the MCTS algorithm for the seed selection