microsoft · rlundeen2 · Mar 26, 2026 · Mar 24, 2026 · Mar 24, 2026 · Mar 24, 2026
diff --git a/.env_example b/.env_example
@@ -1,6 +1,23 @@
-# This is an example of the .env file. Copy to ~/.pyrit/.env and fill in your endpoint configurations.
-# Note that if you are using Entra authentication for certain Azure resources (use_entra_auth = True in PyRIT),
-# keys for those resources are not needed.
+# ============================================================================
+# PyRIT Environment File Example
+# ============================================================================
+#
+# Copy this file to ~/.pyrit/.env and fill in ONLY the sections you need.
+#
+# MOST USERS ONLY NEED 3 VARIABLES to get started:
+#
+#   OPENAI_CHAT_ENDPOINT="https://api.openai.com/v1"    # or any OpenAI-compatible API
+#   OPENAI_CHAT_KEY="your-key-here"
+#   OPENAI_CHAT_MODEL="gpt-4o"
+#
+# These work with OpenAI, Azure OpenAI, Ollama, Groq, OpenRouter, and any
+# other OpenAI-compatible endpoint. See doc/setup/populating_secrets.md
+# for provider-specific examples.
+#
+# If you are using Entra authentication for Azure resources
+# (use_entra_auth = True in PyRIT), keys for those resources are not needed.
+#
+# ============================================================================
 
 
 ###################################

diff --git a/build_scripts/check_links.py b/build_scripts/check_links.py
@@ -18,14 +18,16 @@
     "https://platform.openai.com/docs/api-reference/responses",  # blocks python requests
     "https://platform.openai.com/docs/guides/function-calling",  # blocks python requests
     "https://platform.openai.com/docs/guides/structured-outputs",  # blocks python requests
+    "https://platform.openai.com/api-keys",  # blocks python requests (requires auth)
     "https://www.anthropic.com/research/many-shot-jailbreaking",  # blocks python requests
     "https://doi.org/10.1145/3749447",  # ACM blocks automated requests
+    "https://azure.microsoft.com/free/",  # Azure blocks automated requests
     "https://code.visualstudio.com/docs/devcontainers/containers",
     "https://stackoverflow.com/questions/77134272/pip-install-dev-with-pyproject-toml-not-working",
     "https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.remote-containers",
 ]
 
-custom_myst_references = ["notebook_tests"]
+custom_myst_references = ["notebook_tests", "mistralai_mixtral_8x7b_instruct_v0_1"]
 
 # Updated regex pattern to capture URLs from Markdown and HTML
 URL_PATTERN = re.compile(r'\[.*?\]\((.*?)\)|href="([^"]+)"|src="([^"]+)"')

diff --git a/doc/code/converters/0_converters.ipynb b/doc/code/converters/0_converters.ipynb
@@ -688,7 +688,6 @@
     "\n",
     "prompt = \"tell me how to cut down a tree\"\n",
     "\n",
-    "\n",
     "print(await ROT13Converter().convert_tokens_async(prompt=prompt))  # type: ignore\n",
     "print(await RandomCapitalLettersConverter(percentage=25.0).convert_tokens_async(prompt=prompt))  # type: ignore\n",
     "print(await AsciiArtConverter().convert_tokens_async(prompt=prompt))  # type: ignore\n",
@@ -705,7 +704,6 @@
     "\n",
     "Although converters can be used on their own, they should be thought of as a piece in the pipeline. Typically any attack will have arguments so that prompts can be converted before being sent to the target. They can be stacked, use LLMs, and are a powerful tool.\n",
     "\n",
-    "Before you begin, ensure you are setup with the correct version of PyRIT installed and have secrets configured as described [here](../../setup/populating_secrets.md).\n",
     "\n",
     "### Stacking Converters with PromptSendingAttack\n",
     "\n",
@@ -891,7 +889,8 @@
  ],
  "metadata": {
   "jupytext": {
-   "cell_metadata_filter": "-all"
+   "cell_metadata_filter": "-all",
+   "main_language": "python"
   },
   "language_info": {
    "codemirror_mode": {

diff --git a/doc/code/converters/0_converters.py b/doc/code/converters/0_converters.py
@@ -83,7 +83,6 @@
 
 prompt = "tell me how to cut down a tree"
 
-
 print(await ROT13Converter().convert_tokens_async(prompt=prompt))  # type: ignore
 print(await RandomCapitalLettersConverter(percentage=25.0).convert_tokens_async(prompt=prompt))  # type: ignore
 print(await AsciiArtConverter().convert_tokens_async(prompt=prompt))  # type: ignore
@@ -95,7 +94,6 @@
 #
 # Although converters can be used on their own, they should be thought of as a piece in the pipeline. Typically any attack will have arguments so that prompts can be converted before being sent to the target. They can be stacked, use LLMs, and are a powerful tool.
 #
-# Before you begin, ensure you are setup with the correct version of PyRIT installed and have secrets configured as described [here](../../setup/populating_secrets.md).
 #
 # ### Stacking Converters with PromptSendingAttack
 #

diff --git a/doc/code/converters/1_text_to_text_converters.ipynb b/doc/code/converters/1_text_to_text_converters.ipynb
@@ -45,9 +45,7 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "3",
-   "metadata": {
-    "lines_to_next_cell": 2
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -653,7 +651,8 @@
  ],
  "metadata": {
   "jupytext": {
-   "cell_metadata_filter": "-all"
+   "cell_metadata_filter": "-all",
+   "main_language": "python"
   },
   "language_info": {
    "codemirror_mode": {

diff --git a/doc/code/converters/1_text_to_text_converters.py b/doc/code/converters/1_text_to_text_converters.py
@@ -79,7 +79,6 @@
 # Negation Trap adds negation phrases to try to confuse the model
 print("Negation Trap:", await NegationTrapConverter().convert_async(prompt="your metaprompt"))  # type: ignore
 
-
 # %% [markdown]
 # ### 1.2 Obfuscation Converters
 #

diff --git a/doc/code/converters/3_image_converters.ipynb b/doc/code/converters/3_image_converters.ipynb
@@ -65,6 +65,7 @@
     "from PIL import Image\n",
     "\n",
     "from pyrit.prompt_converter import QRCodeConverter\n",
+    "from pyrit.prompt_target.common.target_capabilities import TargetCapabilities\n",
     "from pyrit.setup import IN_MEMORY, initialize_pyrit_async\n",
     "\n",
     "await initialize_pyrit_async(memory_db_type=IN_MEMORY)  # type: ignore\n",
@@ -406,7 +407,6 @@
     "from pyrit.executor.attack.single_turn import PromptSendingAttack\n",
     "from pyrit.models import SeedGroup, SeedPrompt\n",
     "from pyrit.prompt_target import OpenAIChatTarget\n",
-    "from pyrit.prompt_target.common.target_capabilities import TargetCapabilities\n",
     "\n",
     "llm_target = OpenAIChatTarget(\n",
     "    # The target needs to accept a multi-piece message containing an image; override the default text-only capabilities.\n",
@@ -462,6 +462,9 @@
   }
  ],
  "metadata": {
+  "jupytext": {
+   "main_language": "python"
+  },
   "language_info": {
    "codemirror_mode": {
     "name": "ipython",

diff --git a/doc/code/converters/3_image_converters.py b/doc/code/converters/3_image_converters.py
@@ -187,7 +187,6 @@
     )
 )
 
-
 try:
     print("Sending the blended image with transparency to the LLM...")
 

diff --git a/doc/code/converters/6_selectively_converting.ipynb b/doc/code/converters/6_selectively_converting.ipynb
@@ -19,9 +19,7 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "1",
-   "metadata": {
-    "lines_to_next_cell": 2
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -116,7 +114,6 @@
     "\n",
     "converter_config = AttackConverterConfig(request_converters=converters)\n",
     "\n",
-    "\n",
     "attack = PromptSendingAttack(\n",
     "    objective_target=target,\n",
     "    attack_converter_config=converter_config,\n",

diff --git a/doc/code/converters/6_selectively_converting.py b/doc/code/converters/6_selectively_converting.py
@@ -53,7 +53,6 @@
 target = TextTarget(text_stream=open(os.devnull, "w", encoding="utf-8"))  # noqa: SIM115
 printer = ConsoleAttackResultPrinter()
 
-
 # %% [markdown]
 # ## Example 1: Using Tokens (Simplest)
 #
@@ -69,7 +68,6 @@
 
 converter_config = AttackConverterConfig(request_converters=converters)
 
-
 attack = PromptSendingAttack(
     objective_target=target,
     attack_converter_config=converter_config,

diff --git a/doc/code/converters/7_human_converter.ipynb b/doc/code/converters/7_human_converter.ipynb
@@ -23,8 +23,7 @@
     "Note: Since the target's responses are sent to the scorer LLM for evaluation, you will see them pop up with the ability to modify them. You likely do not need to modify\n",
     "them; however, you can if you wish to alter the feedback for generating the next prompt.\n",
     "\n",
-    "\n",
-    "Before you begin, ensure you are setup with the correct version of [PyRIT installed](../../index.md#installation-guide) and have [secrets configured](../../setup/populating_secrets.md).\n"
+    "\n"
    ]
   },
   {
@@ -692,20 +691,6 @@
     "result = await red_teaming_attack.execute_async(objective=conversation_objective)  # type: ignore\n",
     "await ConsoleAttackResultPrinter().print_conversation_async(result=result)  # type: ignore"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "2",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# Close connection\n",
-    "from pyrit.memory import CentralMemory\n",
-    "\n",
-    "memory = CentralMemory.get_memory_instance()\n",
-    "memory.dispose_engine()"
-   ]
   }
  ],
  "metadata": {

diff --git a/doc/code/converters/7_human_converter.py b/doc/code/converters/7_human_converter.py
@@ -28,7 +28,6 @@
 # them; however, you can if you wish to alter the feedback for generating the next prompt.
 #
 #
-# Before you begin, ensure you are setup with the correct version of [PyRIT installed](../../index.md#installation-guide) and have [secrets configured](../../setup/populating_secrets.md).
 #
 
 # %%

diff --git a/doc/code/datasets/2_seed_programming.ipynb b/doc/code/datasets/2_seed_programming.ipynb
@@ -62,7 +62,6 @@
     "\n",
     "await initialize_pyrit_async(memory_db_type=IN_MEMORY)  # type: ignore\n",
     "\n",
-    "\n",
     "image_path = pathlib.Path(\".\") / \"..\" / \"..\" / \"..\" / \"assets\" / \"pyrit_architecture.png\"\n",
     "\n",
     "# A SeedGroup is a collection of Seeds that are grouped together as part of a conversation\n",
@@ -91,7 +90,6 @@
     "attack = PromptSendingAttack(objective_target=target, attack_scoring_config=scoring_config)\n",
     "printer = ConsoleAttackResultPrinter()\n",
     "\n",
-    "\n",
     "# every attack has this to extract parameters from the seed group\n",
     "params = await attack.params_type.from_seed_group_async(seed_group=seed_group)  # type: ignore\n",
     "print(\"Attack Parameters:\", params)"
@@ -233,7 +231,7 @@
    "id": "4",
    "metadata": {},
    "source": [
-    "You can also generate all or part of `prepended_conversation` and `next_message` using an attack model using a `seed_simulated_conversation`. The below example shows how to create these parameters such that the objective target has \n",
+    "You can also generate all or part of `prepended_conversation` and `next_message` using an attack model using a `seed_simulated_conversation`. The below example shows how to create these parameters such that the objective target has the following:\n",
     "\n",
     "1. A static system prompt\n",
     "2. Generate the first three turns to a conversation to be prepended, along with a next_message."
@@ -701,6 +699,9 @@
   }
  ],
  "metadata": {
+  "jupytext": {
+   "main_language": "python"
+  },
   "language_info": {
    "codemirror_mode": {
     "name": "ipython",

diff --git a/doc/code/datasets/2_seed_programming.py b/doc/code/datasets/2_seed_programming.py
@@ -42,7 +42,6 @@
 
 await initialize_pyrit_async(memory_db_type=IN_MEMORY)  # type: ignore
 
-
 image_path = pathlib.Path(".") / ".." / ".." / ".." / "assets" / "pyrit_architecture.png"
 
 # A SeedGroup is a collection of Seeds that are grouped together as part of a conversation
@@ -71,7 +70,6 @@
 attack = PromptSendingAttack(objective_target=target, attack_scoring_config=scoring_config)
 printer = ConsoleAttackResultPrinter()
 
-
 # every attack has this to extract parameters from the seed group
 params = await attack.params_type.from_seed_group_async(seed_group=seed_group)  # type: ignore
 print("Attack Parameters:", params)

diff --git a/doc/code/executor/attack/1_prompt_sending_attack.ipynb b/doc/code/executor/attack/1_prompt_sending_attack.ipynb
@@ -12,8 +12,6 @@
     "\n",
     "This demo showcases how to use the attack to send prompts, how to modify the prompts with converters, and how to view responses from the target.\n",
     "\n",
-    "Before you begin, import the necessary libraries and ensure you are setup with the correct version of PyRIT installed and have secrets\n",
-    "configured as described [here](../../../setup/populating_secrets.md).\n",
     "\n",
     "The first example is as simple as it gets.\n",
     "\n",
@@ -237,9 +235,7 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "5",
-   "metadata": {
-    "lines_to_next_cell": 2
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
@@ -890,9 +886,7 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "11",
-   "metadata": {
-    "lines_to_next_cell": 2
-   },
+   "metadata": {},
    "outputs": [
     {
      "name": "stderr",
@@ -1215,7 +1209,8 @@
  ],
  "metadata": {
   "jupytext": {
-   "cell_metadata_filter": "-all"
+   "cell_metadata_filter": "-all",
+   "main_language": "python"
   },
   "language_info": {
    "codemirror_mode": {

diff --git a/doc/code/executor/attack/1_prompt_sending_attack.py b/doc/code/executor/attack/1_prompt_sending_attack.py
@@ -17,8 +17,6 @@
 #
 # This demo showcases how to use the attack to send prompts, how to modify the prompts with converters, and how to view responses from the target.
 #
-# Before you begin, import the necessary libraries and ensure you are setup with the correct version of PyRIT installed and have secrets
-# configured as described [here](../../../setup/populating_secrets.md).
 #
 # The first example is as simple as it gets.
 #
@@ -127,7 +125,6 @@
 )
 """
 
-
 # %% [markdown]
 # ## Multi-Modal
 #
@@ -238,7 +235,6 @@
 for result in results:
     await printer.print_conversation_async(result=result)  # type: ignore
 
-
 # %% [markdown]
 # ## Sending Prompts Directly
 #

diff --git a/doc/code/executor/attack/2_red_teaming_attack.ipynb b/doc/code/executor/attack/2_red_teaming_attack.ipynb
@@ -54,9 +54,7 @@
     "    linkStyle 6 stroke:#D50000\n",
     "```\n",
     "\n",
-    "Note that for this to succeed, the `AttackAdversarialConfig` requires an LLM endpoint without serious content moderation or other kinds of safety filtering mechanisms. Success depends on the model and may not be achieved every time.\n",
-    "\n",
-    "Before you begin, ensure you are setup with the correct version of PyRIT installed and have secrets configured as described [here](../../../setup/populating_secrets.md)."
+    "Note that for this to succeed, the `AttackAdversarialConfig` requires an LLM endpoint without serious content moderation or other kinds of safety filtering mechanisms. Success depends on the model and may not be achieved every time.\n"
    ]
   },
   {

diff --git a/doc/code/executor/attack/2_red_teaming_attack.py b/doc/code/executor/attack/2_red_teaming_attack.py
@@ -58,8 +58,6 @@
 #
 # Note that for this to succeed, the `AttackAdversarialConfig` requires an LLM endpoint without serious content moderation or other kinds of safety filtering mechanisms. Success depends on the model and may not be achieved every time.
 #
-# Before you begin, ensure you are setup with the correct version of PyRIT installed and have secrets configured as described [here](../../../setup/populating_secrets.md).
-# %%
 import logging
 
 from pyrit.executor.attack import (
@@ -137,7 +135,6 @@
     ),
 ]
 
-
 # Testing against an AzureOpenAI deployed GPT 4 instance
 oai_endpoint = os.getenv("AZURE_OPENAI_GPT4_CHAT_ENDPOINT")
 oai_objective_target = OpenAIChatTarget(

diff --git a/doc/code/executor/attack/3_crescendo_attack.ipynb b/doc/code/executor/attack/3_crescendo_attack.ipynb
@@ -13,7 +13,6 @@
     "\n",
     "Note that this attack is more likely to succeed if the adversarial LLM provided does not have content moderation or other safety mechanisms. Even then, success may depend on the model and may not be guaranteed every time.\n",
     "\n",
-    "Before you begin, ensure you are set up with the correct version of PyRIT installed and have secrets configured as described [here](../../../setup/populating_secrets.md).\n",
     "\n",
     "The results and intermediate interactions will be saved to memory according to the environment settings. For details, see the [Memory Configuration Guide](../../memory/0_memory.md)."
    ]
@@ -506,7 +505,8 @@
  ],
  "metadata": {
   "jupytext": {
-   "cell_metadata_filter": "-all"
+   "cell_metadata_filter": "-all",
+   "main_language": "python"
   },
   "language_info": {
    "codemirror_mode": {

diff --git a/doc/code/executor/attack/3_crescendo_attack.py b/doc/code/executor/attack/3_crescendo_attack.py
@@ -18,7 +18,6 @@
 #
 # Note that this attack is more likely to succeed if the adversarial LLM provided does not have content moderation or other safety mechanisms. Even then, success may depend on the model and may not be guaranteed every time.
 #
-# Before you begin, ensure you are set up with the correct version of PyRIT installed and have secrets configured as described [here](../../../setup/populating_secrets.md).
 #
 # The results and intermediate interactions will be saved to memory according to the environment settings. For details, see the [Memory Configuration Guide](../../memory/0_memory.md).
-Original file line number
+Diff line change
@@ Expand Up / @@ -187,7 +187,6 @@ @@
         )
     )
     try:
         print("Sending the blended image with transparency to the LLM...")
@@ Expand Down @@