[DRAFT] FEAT Normalize simulated conversation prompt sources

doc/code/datasets/2_seed_programming.ipynb

@@ -488,7 +488,7 @@
     "            role=\"system\",\n",
     "        ),\n",
     "        SeedSimulatedConversation(\n",
-    "            adversarial_chat_system_prompt_path=EXECUTOR_RED_TEAM_PATH / \"naive_crescendo.yaml\",\n",
+    "            adversarial_chat_system_prompt=SeedPrompt.from_yaml_file(EXECUTOR_RED_TEAM_PATH / \"naive_crescendo.yaml\"),\n",
     "            sequence=1,\n",
     "            num_turns=4,\n",
     "            next_message_system_prompt_path=EXECUTOR_SIMULATED_TARGET_PATH / \"direct_next_message.yaml\",\n",

doc/code/datasets/2_seed_programming.py

@@ -102,7 +102,7 @@
             role="system",
         ),
         SeedSimulatedConversation(
-            adversarial_chat_system_prompt_path=EXECUTOR_RED_TEAM_PATH / "naive_crescendo.yaml",
+            adversarial_chat_system_prompt=SeedPrompt.from_yaml_file(EXECUTOR_RED_TEAM_PATH / "naive_crescendo.yaml"),
             sequence=1,
             num_turns=4,
             next_message_system_prompt_path=EXECUTOR_SIMULATED_TARGET_PATH / "direct_next_message.yaml",

doc/code/datasets/5_simulated_conversation.ipynb

@@ -24,7 +24,7 @@
     "\n",
     "## Generating a Simulated Conversation\n",
     "\n",
-    "The function takes an objective, an adversarial chat model, a scorer, and a system prompt path.\n",
+    "The function takes an objective, an adversarial chat model, a scorer, and a system `SeedPrompt`.\n",
     "It runs a `RedTeamingAttack` internally with the adversarial LLM playing both attacker and target\n",
     "roles."
    ]
@@ -60,11 +60,9 @@
     }
    ],
    "source": [
-    "from pathlib import Path\n",
-    "\n",
     "from pyrit.common.path import EXECUTOR_SEED_PROMPT_PATH\n",
     "from pyrit.executor.attack import generate_simulated_conversation_async\n",
-    "from pyrit.models import SeedGroup\n",
+    "from pyrit.models import SeedGroup, SeedPrompt\n",
     "from pyrit.output import output_attack_async\n",
     "from pyrit.prompt_target import OpenAIChatTarget\n",
     "from pyrit.score import SelfAskRefusalScorer\n",
@@ -83,7 +81,9 @@
     "    adversarial_chat=adversarial_chat,\n",
     "    objective_scorer=objective_scorer,\n",
     "    num_turns=3,\n",
-    "    adversarial_chat_system_prompt_path=Path(EXECUTOR_SEED_PROMPT_PATH) / \"red_teaming\" / \"naive_crescendo.yaml\",\n",
+    "    adversarial_chat_system_prompt=SeedPrompt.from_yaml_file(\n",
+    "        EXECUTOR_SEED_PROMPT_PATH / \"red_teaming\" / \"naive_crescendo.yaml\"\n",
+    "    ),\n",
     ")\n",
     "\n",
     "print(f\"Generated {len(simulated_conversation_prompts)} messages\")"
@@ -517,7 +517,8 @@
     "| `adversarial_chat` | `PromptTarget` | The LLM that generates attack prompts (also plays the simulated target). Must declare `supports_multi_turn=True` and `supports_editable_history=True`. |\n",
     "| `objective_scorer` | `TrueFalseScorer` | Evaluates whether the final turn achieved the objective |\n",
     "| `num_turns` | `int` | Number of conversation turns to generate (default: 3) |\n",
-    "| `adversarial_chat_system_prompt_path` | `str \\| Path` | System prompt for the adversarial chat role |\n",
+    "| `adversarial_chat_system_prompt` | `SeedPrompt` | System prompt for the adversarial chat role |\n",
+    "| `adversarial_chat_system_prompt_path` | `str \\| Path \\| None` | Compatibility adapter for legacy path-based callers |\n",
     "| `simulated_target_system_prompt_path` | `str \\| Path \\| None` | Optional system prompt for the simulated target role |\n",
     "| `next_message_system_prompt_path` | `str \\| Path \\| None` | Optional path to generate a final user message that elicits objective fulfillment |\n",
     "| `attack_converter_config` | `AttackConverterConfig \\| None` | Optional converter configuration for the attack |\n",

doc/code/datasets/5_simulated_conversation.py

@@ -28,16 +28,14 @@
 #
 # ## Generating a Simulated Conversation
 #
-# The function takes an objective, an adversarial chat model, a scorer, and a system prompt path.
+# The function takes an objective, an adversarial chat model, a scorer, and a system `SeedPrompt`.
 # It runs a `RedTeamingAttack` internally with the adversarial LLM playing both attacker and target
 # roles.
 
 # %%
-from pathlib import Path
-
 from pyrit.common.path import EXECUTOR_SEED_PROMPT_PATH
 from pyrit.executor.attack import generate_simulated_conversation_async
-from pyrit.models import SeedGroup
+from pyrit.models import SeedGroup, SeedPrompt
 from pyrit.output import output_attack_async
 from pyrit.prompt_target import OpenAIChatTarget
 from pyrit.score import SelfAskRefusalScorer
@@ -56,7 +54,9 @@
     adversarial_chat=adversarial_chat,
     objective_scorer=objective_scorer,
     num_turns=3,
-    adversarial_chat_system_prompt_path=Path(EXECUTOR_SEED_PROMPT_PATH) / "red_teaming" / "naive_crescendo.yaml",
+    adversarial_chat_system_prompt=SeedPrompt.from_yaml_file(
+        EXECUTOR_SEED_PROMPT_PATH / "red_teaming" / "naive_crescendo.yaml"
+    ),
 )
 
 print(f"Generated {len(simulated_conversation_prompts)} messages")
@@ -126,7 +126,8 @@
 # | `adversarial_chat` | `PromptTarget` | The LLM that generates attack prompts (also plays the simulated target). Must declare `supports_multi_turn=True` and `supports_editable_history=True`. |
 # | `objective_scorer` | `TrueFalseScorer` | Evaluates whether the final turn achieved the objective |
 # | `num_turns` | `int` | Number of conversation turns to generate (default: 3) |
-# | `adversarial_chat_system_prompt_path` | `str \| Path` | System prompt for the adversarial chat role |
+# | `adversarial_chat_system_prompt` | `SeedPrompt` | System prompt for the adversarial chat role |
+# | `adversarial_chat_system_prompt_path` | `str \| Path \| None` | Compatibility adapter for legacy path-based callers |
 # | `simulated_target_system_prompt_path` | `str \| Path \| None` | Optional system prompt for the simulated target role |
 # | `next_message_system_prompt_path` | `str \| Path \| None` | Optional path to generate a final user message that elicits objective fulfillment |
 # | `attack_converter_config` | `AttackConverterConfig \| None` | Optional converter configuration for the attack |

doc/code/scenarios/0_attack_techniques.ipynb

@@ -38,7 +38,13 @@
     "\n",
     "The objective is *not* part of the technique — it stays separate and is supplied by the dataset at\n",
     "run time. You rarely build a technique by hand; instead you register a **factory** and let scenarios\n",
-    "construct techniques on demand with the scenario's own objective target and scorer."
+    "construct techniques on demand with the scenario's own objective target and scorer.\n",
+    "\n",
+    "`adversarial_chat_system_prompt` accepts a `SeedPrompt`, so created techniques carry portable prompt\n",
+    "content rather than a runtime file dependency. Callers that own YAML load it with\n",
+    "`SeedPrompt.from_yaml_file(...)` at setup time. The legacy `adversarial_chat_system_prompt_path` name\n",
+    "remains a compatibility adapter, and if neither parameter is supplied, the existing\n",
+    "`red_teaming/{technique_name}.yaml` convention remains the default."
    ]
   },
   {

doc/code/scenarios/0_attack_techniques.py

@@ -43,6 +43,12 @@
 # The objective is *not* part of the technique — it stays separate and is supplied by the dataset at
 # run time. You rarely build a technique by hand; instead you register a **factory** and let scenarios
 # construct techniques on demand with the scenario's own objective target and scorer.
+#
+# `adversarial_chat_system_prompt` accepts a `SeedPrompt`, so created techniques carry portable prompt
+# content rather than a runtime file dependency. Callers that own YAML load it with
+# `SeedPrompt.from_yaml_file(...)` at setup time. The legacy `adversarial_chat_system_prompt_path` name
+# remains a compatibility adapter, and if neither parameter is supplied, the existing
+# `red_teaming/{technique_name}.yaml` convention remains the default.
 
 # %% [markdown]
 # ## Where techniques come from: initializers

pyrit/executor/attack/core/attack_parameters.py

@@ -112,6 +112,7 @@ async def from_seed_group_async(
         """
         # Import here to avoid circular imports
         from pyrit.executor.attack.multi_turn.simulated_conversation import (
+            _resolve_adversarial_chat_system_prompt_async,
             generate_simulated_conversation_async,
         )
 
@@ -159,14 +160,19 @@ async def from_seed_group_async(
             if objective_scorer is None:
                 raise ValueError("objective_scorer is required when seed_group has a simulated conversation config")
 
+            adversarial_chat_system_prompt = await _resolve_adversarial_chat_system_prompt_async(
+                adversarial_chat_system_prompt_path=simulated_conversation_config.adversarial_chat_system_prompt_path,
+                adversarial_chat_system_prompt=simulated_conversation_config.adversarial_chat_system_prompt,
+            )
+
             # Generate the simulated conversation - returns list[SeedPrompt]
             simulated_prompts = await generate_simulated_conversation_async(
                 objective=seed_group.objective.value,
                 adversarial_chat=adversarial_chat,
                 objective_scorer=objective_scorer,
                 num_turns=simulated_conversation_config.num_turns,
                 starting_sequence=simulated_conversation_config.sequence,
-                adversarial_chat_system_prompt_path=simulated_conversation_config.adversarial_chat_system_prompt_path,
+                adversarial_chat_system_prompt=adversarial_chat_system_prompt,
                 simulated_target_system_prompt_path=simulated_conversation_config.simulated_target_system_prompt_path,
                 next_message_system_prompt_path=simulated_conversation_config.next_message_system_prompt_path,
             )

pyrit/executor/attack/multi_turn/simulated_conversation.py

@@ -10,6 +10,7 @@
 
 from __future__ import annotations
 
+import asyncio
 import logging
 from typing import TYPE_CHECKING
 
@@ -43,7 +44,8 @@ async def generate_simulated_conversation_async(
     objective_scorer: TrueFalseScorer,
     num_turns: int = 3,
     starting_sequence: int = 0,
-    adversarial_chat_system_prompt_path: str | Path,
+    adversarial_chat_system_prompt_path: str | Path | None = None,
+    adversarial_chat_system_prompt: SeedPrompt | None = None,
     simulated_target_system_prompt_path: str | Path | None = None,
     next_message_system_prompt_path: str | Path | None = None,
     attack_converter_config: AttackConverterConfig | None = None,
@@ -70,7 +72,10 @@ async def generate_simulated_conversation_async(
         num_turns: Number of conversation turns to generate. Defaults to 3.
         starting_sequence: The starting sequence number for the generated SeedPrompts.
             Each message gets an incrementing sequence number. Defaults to 0.
-        adversarial_chat_system_prompt_path: Path to the system prompt for the adversarial chat.
+        adversarial_chat_system_prompt_path: Compatibility-only path adapter for the adversarial chat
+            system prompt. New callers should load the YAML at their composition boundary and pass
+            ``adversarial_chat_system_prompt``.
+        adversarial_chat_system_prompt: Canonical inline system prompt for the adversarial chat.
         simulated_target_system_prompt_path: Path to the system prompt for the simulated target.
             If None, no system prompt is used for the simulated target.
         next_message_system_prompt_path: Optional path to a system prompt for generating
@@ -89,7 +94,7 @@ async def generate_simulated_conversation_async(
         generated to elicit the objective fulfillment.
 
     Raises:
-        ValueError: If num_turns is not a positive integer.
+        ValueError: If num_turns is not positive or the adversarial prompt source is ambiguous or missing.
     """
     # Use the same LLM for both adversarial chat and simulated target
     # They get different system prompts to play different roles
@@ -105,10 +110,9 @@ async def generate_simulated_conversation_async(
         simulated_target_system_prompt_path=simulated_target_system_prompt_path,
     )
 
-    # Create adversarial config for the simulation. Load the optional path into a SeedPrompt so the
-    # resolved prompt is stored directly on the configuration.
-    adversarial_system_prompt = (
-        SeedPrompt.from_yaml_file(adversarial_chat_system_prompt_path) if adversarial_chat_system_prompt_path else None
+    adversarial_system_prompt = await _resolve_adversarial_chat_system_prompt_async(
+        adversarial_chat_system_prompt_path=adversarial_chat_system_prompt_path,
+        adversarial_chat_system_prompt=adversarial_chat_system_prompt,
     )
     adversarial_config = AttackAdversarialConfig(
         target=adversarial_chat,
@@ -176,6 +180,35 @@ async def generate_simulated_conversation_async(
     return seed_prompts
 
 
+async def _resolve_adversarial_chat_system_prompt_async(
+    *,
+    adversarial_chat_system_prompt_path: str | Path | None,
+    adversarial_chat_system_prompt: SeedPrompt | None,
+) -> SeedPrompt:
+    """
+    Adapt a legacy path-backed prompt to the canonical inline execution input.
+
+    Args:
+        adversarial_chat_system_prompt_path: Legacy YAML prompt path.
+        adversarial_chat_system_prompt: Canonical inline prompt.
+
+    Returns:
+        The resolved adversarial chat system prompt.
+
+    Raises:
+        ValueError: If both or neither prompt sources are provided.
+    """
+    has_prompt_path = adversarial_chat_system_prompt_path is not None
+    has_inline_prompt = adversarial_chat_system_prompt is not None
+    if has_prompt_path == has_inline_prompt:
+        raise ValueError("Set exactly one of adversarial_chat_system_prompt_path or adversarial_chat_system_prompt.")
+    if adversarial_chat_system_prompt is not None:
+        return adversarial_chat_system_prompt
+
+    assert adversarial_chat_system_prompt_path is not None
+    return await asyncio.to_thread(SeedPrompt.from_yaml_file, adversarial_chat_system_prompt_path)
+
+
 async def _generate_next_message_async(
     *,
     objective: str,

pyrit/memory/memory_models.py

@@ -1497,8 +1497,10 @@ def get_seed(self) -> Seed:
                 num_turns=config.get("num_turns", 3),
                 sequence=config.get("sequence", 0),
                 adversarial_chat_system_prompt_path=config.get("adversarial_chat_system_prompt_path"),
+                adversarial_chat_system_prompt=config.get("adversarial_chat_system_prompt"),
                 simulated_target_system_prompt_path=config.get("simulated_target_system_prompt_path"),
                 next_message_system_prompt_path=config.get("next_message_system_prompt_path"),
+                pyrit_version=config.get("pyrit_version"),
             )
         return SeedPrompt(
             id=self.id,