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reverting prompt normalizer and changing realtime target to use one r…
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…esponse instead of list
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Bolor-Erdene Jagdagdorj committed Jan 14, 2025
1 parent c7a83ff commit 1d24cf2
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162 changes: 80 additions & 82 deletions doc/code/targets/realtime_target.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -2,21 +2,24 @@
"cells": [
{
"cell_type": "markdown",
"id": "0",
"metadata": {},
"source": [
"# REALTIME TARGET"
]
},
{
"cell_type": "markdown",
"id": "1",
"metadata": {},
"source": [
"## Using PyRIT"
]
},
{
"cell_type": "code",
"execution_count": 1,
"execution_count": null,
"id": "2",
"metadata": {},
"outputs": [],
"source": [
Expand All @@ -30,23 +33,23 @@
},
{
"cell_type": "markdown",
"id": "3",
"metadata": {},
"source": [
"## Single Turn Audio Conversation"
]
},
{
"cell_type": "code",
"execution_count": 2,
"execution_count": null,
"id": "4",
"metadata": {},
"outputs": [],
"source": [
"\n",
"from pyrit.orchestrator import PromptSendingOrchestrator\n",
"from pyrit.prompt_normalizer.normalizer_request import NormalizerRequest, NormalizerRequestPiece\n",
"\n",
"# text_prompt_to_send = \"Hi what is 2+2?\"\n",
"\n",
"prompt_to_send = \"test_rt_audio1.wav\"\n",
"\n",
"normalizer_request = NormalizerRequest(\n",
Expand All @@ -61,38 +64,10 @@
},
{
"cell_type": "code",
"execution_count": 3,
"execution_count": null,
"id": "5",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Session set up\n",
"\u001b[1m\u001b[34muser: test_rt_audio1.wav\n",
"\u001b[22m\u001b[33massistant: Making rice wine, also known as sake, involves fermenting rice with water, koji (a type of mold), and yeast. Here is a simplified overview:\n",
"\n",
"1. **Washing and Soaking Rice**: Wash the rice thoroughly to remove excess starch. Then, soak the rice in water for a few hours.\n",
"\n",
"2. **Steaming Rice**: Steam the soaked rice until it's cooked, which will make it easier to ferment.\n",
"\n",
"3. **Preparing Koji**: Koji mold is cultivated on steamed rice to convert the starches in the rice to sugars. This process usually takes a couple of days.\n",
"\n",
"4. **Fermentation**: Mix the steamed rice, koji rice, yeast, and water in a fermentation tank. Over the next few weeks, the mixture will ferment, converting the sugars to alcohol.\n",
"\n",
"5. **Pressing and Filtration**: After fermentation, the mixture is pressed to separate the liquid from the solid rice residue. The liquid is then filtered to remove any remaining particles.\n",
"\n",
"6. **Pasteurization**: The filtered sake is often pasteurized to kill any remaining yeast and enzymes, stabilizing the flavor.\n",
"\n",
"7. **Aging and Bottling**: The sake is aged for a few months to develop its flavor before being bottled.\n",
"\n",
"This is a traditional process, and there are many variations and complexities involved in professional sake brewing. If you're interested in making it at home, consider starting with a homebrewing kit or recipe to guide you through the process.\n",
"\u001b[22m\u001b[39mConversation ID: c75dafcc-9ab0-4a2e-b52c-d0513da7a391\n",
"\u001b[22m\u001b[33massistant: response_audio.wav\n",
"\u001b[22m\u001b[39mConversation ID: c75dafcc-9ab0-4a2e-b52c-d0513da7a391\n"
]
}
],
"outputs": [],
"source": [
"await target.connect()\n",
"\n",
Expand All @@ -105,15 +80,52 @@
},
{
"cell_type": "markdown",
"id": "6",
"metadata": {},
"source": [
"## Multiturn Text Conversation"
"## Single Turn Text Conversation"
]
},
{
"cell_type": "code",
"execution_count": 4,
"execution_count": null,
"id": "7",
"metadata": {},
"outputs": [],
"source": [
"from pyrit.models.prompt_request_piece import PromptRequestPiece\n",
"from pyrit.orchestrator import PromptSendingOrchestrator\n",
"\n",
"\n",
"await target.connect()\n",
"prompt_to_send = \"Give me an image of a raccoon pirate as a Spanish baker in Spain\"\n",
"\n",
"request = PromptRequestPiece(\n",
" role=\"user\",\n",
" original_value=prompt_to_send,\n",
").to_prompt_request_response()\n",
"\n",
"\n",
"orchestrator = PromptSendingOrchestrator(objective_target=target)\n",
"response = await orchestrator.send_prompts_async(prompt_list=[prompt_to_send]) # type: ignore\n",
"await orchestrator.print_conversations_async() # type: ignore"
]
},
{
"cell_type": "markdown",
"id": "8",
"metadata": {},
"source": [
"## Multiturn Text Conversation"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "9",
"metadata": {
"lines_to_next_cell": 2
},
"outputs": [],
"source": [
"\n",
Expand Down Expand Up @@ -141,27 +153,15 @@
" prompt_data_type=\"text\",\n",
" )\n",
" ]\n",
")\n"
")"
]
},
{
"cell_type": "code",
"execution_count": 5,
"execution_count": null,
"id": "10",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Session set up\n",
"\u001b[1m\u001b[34muser: Hi what is 2+2?\n",
"\u001b[22m\u001b[33massistant: 2 + 2 equals 4.\n",
"\u001b[22m\u001b[39mConversation ID: 87b580f3-3373-49fd-98ce-ac4f18f38838\n",
"\u001b[22m\u001b[33massistant: response_audio.wav\n",
"\u001b[22m\u001b[39mConversation ID: 87b580f3-3373-49fd-98ce-ac4f18f38838\n"
]
}
],
"outputs": [],
"source": [
"orchestrator = PromptSendingOrchestrator(objective_target=target)\n",
"\n",
Expand All @@ -172,22 +172,18 @@
},
{
"cell_type": "code",
"execution_count": 6,
"execution_count": null,
"id": "11",
"metadata": {},
"outputs": [],
"source": []
},
{
"cell_type": "code",
"execution_count": null,
"id": "12",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Session set up\n",
"\u001b[1m\u001b[34muser: Now add 2?\n",
"\u001b[22m\u001b[33massistant: 4 + 2 equals 6.\n",
"\u001b[22m\u001b[39mConversation ID: 5104182c-2392-497a-84ec-0ddb577c21b4\n",
"\u001b[22m\u001b[33massistant: response_audio.wav\n",
"\u001b[22m\u001b[39mConversation ID: 5104182c-2392-497a-84ec-0ddb577c21b4\n"
]
}
],
"outputs": [],
"source": [
"orchestrator = PromptSendingOrchestrator(objective_target=target)\n",
"\n",
Expand All @@ -198,33 +194,35 @@
},
{
"cell_type": "code",
"execution_count": 7,
"execution_count": null,
"id": "13",
"metadata": {},
"outputs": [],
"source": [
"await target.disconnect() # type: ignore"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "14",
"metadata": {},
"outputs": [],
"source": [
"from pyrit.memory import CentralMemory\n",
"\n",
"memory = CentralMemory.get_memory_instance()\n",
"memory.dispose_engine()"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "pyrit2",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.9"
}
},
"nbformat": 4,
"nbformat_minor": 2
"nbformat_minor": 5
}
31 changes: 29 additions & 2 deletions doc/code/targets/realtime_target.py
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Expand Up @@ -34,8 +34,6 @@
from pyrit.orchestrator import PromptSendingOrchestrator
from pyrit.prompt_normalizer.normalizer_request import NormalizerRequest, NormalizerRequestPiece

# text_prompt_to_send = "Hi what is 2+2?"

prompt_to_send = "test_rt_audio1.wav"

normalizer_request = NormalizerRequest(
Expand All @@ -56,6 +54,27 @@

await orchestrator.print_conversations_async() # type: ignore

# %% [markdown]
# ## Single Turn Text Conversation

# %%
from pyrit.models.prompt_request_piece import PromptRequestPiece
from pyrit.orchestrator import PromptSendingOrchestrator


await target.connect()
prompt_to_send = "Give me an image of a raccoon pirate as a Spanish baker in Spain"

request = PromptRequestPiece(
role="user",
original_value=prompt_to_send,
).to_prompt_request_response()


orchestrator = PromptSendingOrchestrator(objective_target=target)
response = await orchestrator.send_prompts_async(prompt_list=[prompt_to_send]) # type: ignore
await orchestrator.print_conversations_async() # type: ignore

# %% [markdown]
# ## Multiturn Text Conversation

Expand Down Expand Up @@ -95,6 +114,8 @@

await orchestrator.print_conversations_async() # type: ignore

# %%

# %%
orchestrator = PromptSendingOrchestrator(objective_target=target)

Expand All @@ -104,3 +125,9 @@

# %%
await target.disconnect() # type: ignore

# %%
from pyrit.memory import CentralMemory

memory = CentralMemory.get_memory_instance()
memory.dispose_engine()
43 changes: 20 additions & 23 deletions pyrit/orchestrator/multi_turn/red_teaming_orchestrator.py
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Original file line number Diff line number Diff line change
Expand Up @@ -10,7 +10,6 @@
from pyrit.common.utils import combine_dict
from pyrit.common.path import RED_TEAM_ORCHESTRATOR_PATH
from pyrit.models import PromptRequestPiece, Score
from pyrit.models.prompt_request_response import PromptRequestResponse
from pyrit.orchestrator import MultiTurnAttackResult, MultiTurnOrchestrator
from pyrit.prompt_converter import PromptConverter
from pyrit.prompt_normalizer import NormalizerRequest, NormalizerRequestPiece, PromptNormalizer
Expand Down Expand Up @@ -253,18 +252,16 @@ async def _retrieve_and_send_prompt_async(
conversation_id=objective_target_conversation_id,
)

response_piece = await self._prompt_normalizer.send_prompt_async(
normalizer_request=normalizer_request,
target=self._objective_target,
labels=memory_labels,
orchestrator_identifier=self.get_identifier(),
)

if isinstance(response_piece, PromptRequestResponse):
return response_piece.request_pieces[0]
response_piece = (
await self._prompt_normalizer.send_prompt_async(
normalizer_request=normalizer_request,
target=self._objective_target,
labels=memory_labels,
orchestrator_identifier=self.get_identifier(),
)
).request_pieces[0]

else:
return response_piece[0].request_pieces[0]
return response_piece

async def _check_conversation_complete_async(self, objective_target_conversation_id: str) -> Union[Score, None]:
"""
Expand Down Expand Up @@ -408,19 +405,19 @@ async def _get_prompt_from_adversarial_chat(
prompt_text=prompt_text, conversation_id=adversarial_chat_conversation_id
)

response_text_values = await self._prompt_normalizer.send_prompt_async(
normalizer_request=normalizer_request,
target=self._adversarial_chat,
orchestrator_identifier=self.get_identifier(),
labels=memory_labels,
response_text = (
(
await self._prompt_normalizer.send_prompt_async(
normalizer_request=normalizer_request,
target=self._adversarial_chat,
orchestrator_identifier=self.get_identifier(),
labels=memory_labels,
)
)
.request_pieces[0]
.converted_value
)

if isinstance(response_text_values, PromptRequestResponse):
response_text = response_text_values.request_pieces[0].converted_value

else:
response_text = response_text_values[0].request_pieces[0].converted_value

return response_text

def _get_last_objective_target_response(self, objective_target_conversation_id: str) -> PromptRequestPiece | None:
Expand Down
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