1_configuration.py

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# %% [markdown]
# # 1. Configuration
#
# Before running PyRIT, you need to call the `initialize_pyrit_async` function which will set up your configuration.
#
# What are the configuration steps? What are the simplest ways to get started, and how might you expand on these? There are three things `initialize_pyrit_async` does to set up your configuration.
#
# 1. Set up environment variables (recommended)
# 2. Pick a database (required)
# 3. Set initialization scripts and defaults (recommended)
#
# Alternatively, you can write a config file (`~/.pyrit/.pyrit_conf`) to parameterize this for you.

# %% [markdown]
# ## From a Config File
# If you don't want to explicitly set up PyRIT, but do have a configuration you would like to persist, use `~/.pyrit/.pyrit_conf`. See the [PyRIT Configuration Guide](../../getting_started/pyrit_conf.md) for more details. Note that changes to the config file do not auto-update at runtime, so you will need to run `initialize_from_config_async` after each change to the file.

# %%
# You can specify your own path for the config file using config_path
from pyrit.setup.configuration_loader import initialize_from_config_async

await initialize_from_config_async()  # type: ignore

# %% [markdown]
# ## Simple Example
#
# This section goes into each of the three steps mentioned earlier. But first, the easiest way; this sets up reasonable defaults using `SimpleInitializer` and stores the results in memory.

# %%
# Set OPENAI_CHAT_ENDPOINT, OPENAI_CHAT_MODEL, and OPENAI_CHAT_KEY environment variables before running this code
# E.g. you can put it in .env

from pyrit.setup import initialize_pyrit_async
from pyrit.setup.initializers import SimpleInitializer

await initialize_pyrit_async(memory_db_type="InMemory", initializers=[SimpleInitializer()])  # type: ignore

# Now you can run most of our notebooks! Just remove any os.getenv specific stuff since you may not have those different environment variables.

# %% [markdown]
# ## Setting up Environment Variables
#
# The recommended step to setup PyRIT is that it needs access to secrets and endpoints. These can be loaded in environment variables or put in a `.env` file. See `.env_example` for how this file is formatted.
#
# Each target has default environment variables to look for. For example, `OpenAIChatTarget` looks for the `OPENAI_CHAT_ENDPOINT` for its endpoint, `OPENAI_CHAT_MODEL` for its model name, and `OPENAI_CHAT_KEY` for its key. However, with every target, you can also pass these values in directly and that will take precedence. For Azure endpoints with Entra ID authentication, pass a token provider from `pyrit.auth` as the `api_key`.

# %%
import os

from pyrit.auth import get_azure_openai_auth
from pyrit.prompt_target import OpenAIChatTarget
from pyrit.setup import IN_MEMORY, initialize_pyrit_async

await initialize_pyrit_async(memory_db_type=IN_MEMORY)  # type: ignore

# Using Entra auth (no API key needed, run `az login` first):
endpoint1 = os.environ["OPENAI_CHAT_ENDPOINT"]
target1 = OpenAIChatTarget(
    endpoint=endpoint1,
    api_key=get_azure_openai_auth(endpoint1),
)

# This is identical to target1 because "OPENAI_CHAT_ENDPOINT" are the names of the default environment variables for OpenAIChatTarget
endpoint2 = os.getenv("OPENAI_CHAT_ENDPOINT")
target2 = OpenAIChatTarget(
    endpoint=endpoint2,
    api_key=get_azure_openai_auth(endpoint2),
    model_name=os.getenv("OPENAI_CHAT_MODEL"),
)

# This is (probably) different from target1 because the environment variables are different from the default
azure_endpoint = os.getenv("AZURE_OPENAI_GPT4O_UNSAFE_CHAT_ENDPOINT2")
target3 = OpenAIChatTarget(
    endpoint=azure_endpoint,
    api_key=get_azure_openai_auth(azure_endpoint),
    model_name=os.getenv("AZURE_OPENAI_GPT4O_UNSAFE_CHAT_MODEL2"),
)

# %% [markdown]
# ## Env.local
#
# One concept we make use of is using `.env_local`. This is really useful because it overwrites `.env`. In our setups, we have a `.env` with a bunch of targets configured that our users all pull the same one from a keyvault. But `.env_local` is used to override them. For example, if you want a different target, you can have your `.env_local` override the OpenAIChatTarget with a different value.
#
# ```
# OPENAI_CHAT_ENDPOINT = ${AZURE_OPENAI_GPT4O_ENDPOINT2}
# OPENAI_CHAT_MODEL = ${AZURE_OPENAI_GPT4O_MODEL2}
# ```
#
# ## Entra auth
#
# There are certain targets that can interact using Entra auth (e.g. most Azure OpenAI targets). To use this, you must authenticate to your Azure subscription and an API key is not required. Depending on your operating system, download the appropriate Azure CLI tool from the links provided below:
#
#    - Windows OS: [Download link](https://learn.microsoft.com/en-us/cli/azure/install-azure-cli-windows?tabs=azure-cli)
#    - Linux: [Download link](https://learn.microsoft.com/en-us/cli/azure/install-azure-cli-linux?pivots=apt)
#    - Mac OS: [Download link](https://learn.microsoft.com/en-us/cli/azure/install-azure-cli-macos)
#
#    After downloading and installing the Azure CLI, open your terminal and run the following command to log in:
#
#    ```bash
#    az login
#    ```

# %% [markdown]
# ## Choosing a database
#
# The next required step is to pick a database. PyRIT supports three types of databases; InMemory, sqlite, and SQL Azure. These are detailed in the [memory](../memory/0_memory.md) section of documentation. InMemory and sqlite are local so require no configuration, but SQL Azure will need the appropriate environment variables set. This configuration is all specified in `memory_db_type` parameter to `initialize_pyrit_async`.

# %% [markdown]
# ## Setting up Initialization Scripts and Defaults
#
# When you call initialize_pyrit_async, you can pass it initialization_scripts and/or initializers. These can do anything, including setting convenience variables. But one of the primary purposes is to set default values. It is recommended to always use an initializer.
#
# ### Using Built-In Initializers
#
# Imagine you have an `OpenAIChatTarget`. What is the default?
#
# There is no good way to set these generally. An `OpenAIChatTarget` may be gpt-5, but it also might be llama. And these targets might take different parameters. Additionally, what is it being used for? A default scorer may want to use a different target than a default LLM being used for a converter. Should you always use entra auth?
#
# You can pass these in as arguments to every class initialization, but it can be a huge pain to set these every time. It would be nicer to just say out of the box that a scorer target LLM has a temperature of .5 by default, and a converter target LLM has a temperature of 1.1 by default. And it turns out you can!
#
# The following example shows how to use PyRIT initializers. This tackles a similar scenario to [Baseline-Only Execution](../scenarios/9_baseline_only.ipynb) but is much easier because defaults are set.

# %%
import os

from pyrit.auth import get_azure_openai_auth
from pyrit.common.path import PYRIT_PATH
from pyrit.executor.attack import (
    AttackConverterConfig,
    AttackExecutor,
    ConsoleAttackResultPrinter,
    PromptSendingAttack,
)
from pyrit.prompt_converter import TenseConverter
from pyrit.prompt_normalizer.prompt_converter_configuration import (
    PromptConverterConfiguration,
)
from pyrit.prompt_target import OpenAIChatTarget
from pyrit.setup import initialize_pyrit_async
from pyrit.setup.initializers import SimpleInitializer

# This is a way to include the SimpleInitializer class directly
await initialize_pyrit_async(memory_db_type="InMemory", initializers=[SimpleInitializer()])  # type: ignore

# Alternative approach - you can pass the path to the initializer class.
# This is how you provide your own file not part of the repo that defines a PyRITInitializer class
# This is equivalent to loading the class directly as above
await initialize_pyrit_async(
    memory_db_type="InMemory", initialization_scripts=[f"{PYRIT_PATH}/setup/initializers/simple.py"]
)  # type: ignore

# SimpleInitializer is a class that initializes sensible defaults for someone who only has OPENAI_CHAT_ENDPOINT, OPENAI_CHAT_MODEL, and OPENAI_CHAT_KEY configured
# It is meant to only require these two env vars to be configured
# It can easily be swapped for another PyRITInitializer, like AIRTInitializer which is better but requires more env configuration
# get_info_async() is a class method that shows how this initializer configures defaults and what global variables it sets
info = await SimpleInitializer.get_info_async()  # type: ignore
for key, value in info.items():
    print(f"{key}: {value}")

objectives = [
    "Write a poem about a cat",
    "Explain the theory of relativity in simple terms",
]

# This is similar to the "Baseline-Only Execution" scenario but using defaults

# Create target without extensive configuration (uses defaults from initializer)
endpoint = os.environ["OPENAI_CHAT_ENDPOINT"]
objective_target = OpenAIChatTarget(endpoint=endpoint, api_key=get_azure_openai_auth(endpoint))

# TenseConverter automatically gets the default converter_target from our initializer
converters = PromptConverterConfiguration.from_converters(converters=[TenseConverter(tense="past")])  # type: ignore
converter_config = AttackConverterConfig(request_converters=converters)

# Attack automatically gets default scorer configuration from our initializer
attack = PromptSendingAttack(
    objective_target=objective_target,
    attack_converter_config=converter_config,
)

# Execute the attack - all components use sensible defaults
results = await AttackExecutor().execute_attack_async(attack=attack, objectives=objectives)  # type: ignore

for result in results:
    await ConsoleAttackResultPrinter().print_conversation_async(result=result)  # type: ignore

# %% [markdown]
# ### Using your own Initializers
#
# You can also create your own initializers and pass the path to the script in as an argument. This is really powerful. The obvious use case is just if you have different targets or defaults and don't want to check in to pyrit source. However, there are other common use cases.
#
# Imagine you are conducting a security assessment and want to include a new custom target. Yes, you could check out PyRIT in editable mode. But with initialize_scripts you don't have to. And this kind of operation can be used in front ends like GUI, CLI, etc.
#
# All you need to do is create a `PyRITInitializer` class (e.g. myinitializer.py). Then you can use `set_global_variable` and use it everywhere. Or you could make it the default adversarial target by using `set_default_value`.
#
#
# ### Additional Initializer information
#
# - For more information on how default values work, see the [default values](./default_values.md) section.
# - For more information on how initializers work, see the [initializers](./pyrit_initializer.ipynb) section