.env_example

# ============================================================================
# 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.
#
# For Azure resources you can authenticate with Microsoft Entra ID instead of a
# key. Make it an explicit choice: run `az login` and pass auth_mode="identity"
# to the target, e.g. OpenAIChatTarget(endpoint=..., auth_mode="identity").
# Leaving the key unset still selects Entra ID automatically, but that fallback
# is deprecated and is removed in 1.4.0.
# See doc/code/setup/1_configuration.ipynb for details.
#
# ============================================================================


###################################
# OPENAI TARGET SECRETS
#
# The below models work with OpenAIChatTarget - either pass via environment variables
# or copy to OPENAI_CHAT_ENDPOINT
###################################

PLATFORM_OPENAI_CHAT_ENDPOINT="https://api.openai.com/v1"
PLATFORM_OPENAI_CHAT_KEY="sk-xxxxx"
PLATFORM_OPENAI_CHAT_MODEL="gpt-4o"

# Note: For Azure OpenAI endpoints, use the new format with /openai/v1 and specify the model separately
# Example: https://xxxx.openai.azure.com/openai/v1
AZURE_OPENAI_GPT4O_ENDPOINT="https://xxxx.openai.azure.com/openai/v1"
AZURE_OPENAI_GPT4O_KEY="xxxxx"
AZURE_OPENAI_GPT4O_MODEL="deployment-name"
# Since Azure deployment name may be custom and differ from the actual underlying model,
# you can specify the underlying model for identifier purposes. If not specified,
# identifiers will default to the value of the standard MODEL environment variable.
AZURE_OPENAI_GPT4O_UNDERLYING_MODEL="gpt-4o"

# Optional second GPT-4o endpoint (that can be used for round-robin distribution).
# TargetInitializer creates RoundRobinTargets that automatically group together
# targets with identical underlying model names and behavioral params, allowing
# for distribution of requests across them for rate-limit relief.
AZURE_OPENAI_GPT4O_ENDPOINT2="https://xxxx.openai.azure.com/openai/v1"
AZURE_OPENAI_GPT4O_KEY2="xxxxx"
AZURE_OPENAI_GPT4O_MODEL2="deployment-name"
AZURE_OPENAI_GPT4O_UNDERLYING_MODEL2="gpt-4o"

AZURE_OPENAI_INTEGRATION_TEST_ENDPOINT="https://xxxxx.openai.azure.com/openai/v1"
AZURE_OPENAI_INTEGRATION_TEST_KEY="xxxxx"
AZURE_OPENAI_INTEGRATION_TEST_MODEL="deployment-name"
AZURE_OPENAI_INTEGRATION_TEST_UNDERLYING_MODEL=""

AZURE_OPENAI_GPT3_5_CHAT_ENDPOINT="https://xxxxx.openai.azure.com/openai/v1"
AZURE_OPENAI_GPT3_5_CHAT_KEY="xxxxx"
AZURE_OPENAI_GPT3_5_CHAT_MODEL="deployment-name"
AZURE_OPENAI_GPT3_5_CHAT_UNDERLYING_MODEL=""

AZURE_OPENAI_GPT4_CHAT_ENDPOINT="https://xxxxx.openai.azure.com/openai/v1"
AZURE_OPENAI_GPT4_CHAT_KEY="xxxxx"
AZURE_OPENAI_GPT4_CHAT_MODEL="deployment-name"
AZURE_OPENAI_GPT4_CHAT_UNDERLYING_MODEL=""

AZURE_OPENAI_GPT5_4_ENDPOINT="https://xxxxx.openai.azure.com/openai/v1"
AZURE_OPENAI_GPT5_4_KEY="xxxxx"
AZURE_OPENAI_GPT5_4_MODEL="gpt-5.4"
AZURE_OPENAI_GPT5_4_UNDERLYING_MODEL="gpt-5.4"

# Endpoints that host models with fewer safety mechanisms (e.g. via adversarial fine tuning
# or content filters turned off) can be defined below and used in adversarial attack testing scenarios.
AZURE_OPENAI_GPT4O_UNSAFE_CHAT_ENDPOINT="https://xxxxx.openai.azure.com/openai/v1"
AZURE_OPENAI_GPT4O_UNSAFE_CHAT_KEY="xxxxx"
AZURE_OPENAI_GPT4O_UNSAFE_CHAT_MODEL="deployment-name"
AZURE_OPENAI_GPT4O_UNSAFE_CHAT_UNDERLYING_MODEL=""

AZURE_OPENAI_GPT4O_UNSAFE_CHAT_ENDPOINT2="https://xxxxx.openai.azure.com/openai/v1"
AZURE_OPENAI_GPT4O_UNSAFE_CHAT_KEY2="xxxxx"
AZURE_OPENAI_GPT4O_UNSAFE_CHAT_MODEL2="deployment-name"
AZURE_OPENAI_GPT4O_UNSAFE_CHAT_UNDERLYING_MODEL2=""

# Adversarial chat targets (used by scenario attack techniques, e.g. role-play, TAP).
# When multiple numbered endpoints are configured, adversarial_chat uses them in a round-robin.
ADVERSARIAL_CHAT_ENDPOINT="https://xxxxx.openai.azure.com/openai/v1"
ADVERSARIAL_CHAT_KEY="xxxxx"
ADVERSARIAL_CHAT_MODEL="deployment-name"
ADVERSARIAL_CHAT_UNDERLYING_MODEL=""

ADVERSARIAL_CHAT_ENDPOINT2="https://xxxxx.openai.azure.com/openai/v1"
ADVERSARIAL_CHAT_KEY2="xxxxx"
ADVERSARIAL_CHAT_MODEL2="deployment-name"
ADVERSARIAL_CHAT_UNDERLYING_MODEL2=""

ADVERSARIAL_CHAT_ENDPOINT3="https://xxxxx.openai.azure.com/openai/v1"
ADVERSARIAL_CHAT_KEY3="xxxxx"
ADVERSARIAL_CHAT_MODEL3="deployment-name"
ADVERSARIAL_CHAT_UNDERLYING_MODEL3=""

ADVERSARIAL_CHAT_SINGLETURN_ENDPOINT="https://xxxxxx.westus3.inference.ml.azure.com/score"
ADVERSARIAL_CHAT_SINGLETURN_KEY="xxxxx"
ADVERSARIAL_CHAT_SINGLETURN_MODEL="deployment-name"

ADVERSARIAL_CHAT_MULTITURN_ENDPOINT="https://xxxxxx.westus3.inference.ml.azure.com/score"
ADVERSARIAL_CHAT_MULTITURN_KEY="xxxxx"
ADVERSARIAL_CHAT_MULTITURN_MODEL="deployment-name"

ADVERSARIAL_CHAT_REASONING_ENDPOINT="https://xxxxxx.westus3.inference.ml.azure.com/score"
ADVERSARIAL_CHAT_REASONING_KEY="xxxxx"
ADVERSARIAL_CHAT_REASONING_MODEL="deployment-name"


# Objective Scorer chat target (used in scorers in scenarios)
OBJECTIVE_SCORER_CHAT_ENDPOINT="https://xxxxx.openai.azure.com/openai/v1"
OBJECTIVE_SCORER_CHAT_KEY="xxxxx"
OBJECTIVE_SCORER_CHAT_MODEL="deployment-name"

AZURE_FOUNDRY_DEEPSEEK_ENDPOINT="https://xxxxx.eastus2.models.ai.azure.com"
AZURE_FOUNDRY_DEEPSEEK_KEY="xxxxx"
AZURE_FOUNDRY_DEEPSEEK_MODEL=""

AZURE_FOUNDRY_PHI4_ENDPOINT="https://xxxxx.models.ai.azure.com"
AZURE_CHAT_PHI4_KEY="xxxxx"
AZURE_CHAT_PHI4_MODEL=""

AZURE_FOUNDRY_MISTRAL_LARGE_ENDPOINT="https://xxxxx.services.ai.azure.com/openai/v1/"
AZURE_FOUNDRY_MISTRAL_LARGE_KEY="xxxxx"
AZURE_FOUNDRY_MISTRAL_LARGE_MODEL="Mistral-Large-3"

AWS_ENDPOINT="https://bedrock-mantle.us-east-1.api.aws/v1"
AWS_KEY="xxxxx"
AWS_CHAT_MODEL="nvidia.nemotron-super-3-120b"
AWS_RESPONSES_MODEL="openai.gpt-oss-120b"

GROQ_ENDPOINT="https://api.groq.com/openai/v1"
GROQ_KEY="gsk_xxxxxxxx"
GROQ_LLAMA_MODEL="openai/gpt-oss-20b"

OPEN_ROUTER_ENDPOINT="https://openrouter.ai/api/v1"
OPEN_ROUTER_KEY="sk-or-v1-xxxxx"
OPEN_ROUTER_CLAUDE_MODEL="anthropic/claude-sonnet-5"

# Microsoft-Decision-1 through OpenRouter.
MICROSOFT_DECISION_ENDPOINT="https://openrouter.ai/api"
MICROSOFT_DECISION_KEY="sk-or-v1-xxxxx"

# Microsoft-Decision-1 deployed in Microsoft Foundry. Uses Entra ID (`az login`), so there is no key.
AZURE_FOUNDRY_DECISION_ENDPOINT="https://xxxxx.services.ai.azure.com"
AZURE_FOUNDRY_DECISION_MODEL="deployment-name"

OLLAMA_CHAT_ENDPOINT="http://127.0.0.1:11434/v1"
OLLAMA_MODEL="llama2"

DEFAULT_OPENAI_FRONTEND_ENDPOINT = ${AZURE_OPENAI_GPT4O_AAD_ENDPOINT}
DEFAULT_OPENAI_FRONTEND_KEY = ${AZURE_OPENAI_GPT4O_AAD_KEY}
DEFAULT_OPENAI_FRONTEND_MODEL = "gpt-4o"

OPENAI_CHAT_ENDPOINT=${PLATFORM_OPENAI_CHAT_ENDPOINT}
OPENAI_CHAT_KEY=${PLATFORM_OPENAI_CHAT_KEY}
OPENAI_CHAT_MODEL=${PLATFORM_OPENAI_CHAT_MODEL}
# The following line can be populated if using an Azure OpenAI deployment
# where the deployment name differs from the actual underlying model
OPENAI_CHAT_UNDERLYING_MODEL=""

##################################
# OPENAI RESPONSES TARGET SECRETS
##################################

AZURE_OPENAI_GPT5_RESPONSES_ENDPOINT="https://xxxxxxxxx.azure.com/openai/v1"
AZURE_OPENAI_GPT5_COMPLETION_ENDPOINT="https://xxxxxxxxx.azure.com/openai/v1"
AZURE_OPENAI_GPT5_KEY="xxxxxxx"
AZURE_OPENAI_GPT5_MODEL="gpt-5"
AZURE_OPENAI_GPT5_UNDERLYING_MODEL="gpt-5"

PLATFORM_OPENAI_RESPONSES_ENDPOINT="https://api.openai.com/v1"
PLATFORM_OPENAI_RESPONSES_KEY="sk-xxxxx"
PLATFORM_OPENAI_RESPONSES_MODEL="gpt-5.6-terra"

AZURE_OPENAI_RESPONSES_ENDPOINT="https://xxxxx.openai.azure.com/openai/v1"
AZURE_OPENAI_RESPONSES_KEY="xxxxx"
AZURE_OPENAI_RESPONSES_MODEL="gpt-5.6-terra"
AZURE_OPENAI_RESPONSES_UNDERLYING_MODEL="gpt-5.6-terra"

OPENAI_RESPONSES_ENDPOINT=${PLATFORM_OPENAI_RESPONSES_ENDPOINT}
OPENAI_RESPONSES_KEY=${PLATFORM_OPENAI_RESPONSES_KEY}
OPENAI_RESPONSES_MODEL=${PLATFORM_OPENAI_RESPONSES_MODEL}
OPENAI_RESPONSES_UNDERLYING_MODEL=""

##################################
# OPENAI REALTIME TARGET SECRETS
#
# The below models work with RealtimeTarget - either pass via environment variables
# or copy to OPENAI_REALTIME_ENDPOINT
##################################

PLATFORM_OPENAI_REALTIME_ENDPOINT="wss://api.openai.com/v1"
PLATFORM_OPENAI_REALTIME_API_KEY="sk-xxxxx"
PLATFORM_OPENAI_REALTIME_MODEL="gpt-4o-realtime-preview"

AZURE_OPENAI_REALTIME_ENDPOINT = "wss://xxxx.openai.azure.com/openai/v1"
AZURE_OPENAI_REALTIME_API_KEY = "xxxxx"
AZURE_OPENAI_REALTIME_MODEL = "gpt-4o-realtime-preview"
AZURE_OPENAI_REALTIME_UNDERLYING_MODEL = "gpt-4o-realtime-preview"

OPENAI_REALTIME_ENDPOINT = ${PLATFORM_OPENAI_REALTIME_ENDPOINT}
OPENAI_REALTIME_API_KEY = ${PLATFORM_OPENAI_REALTIME_API_KEY}
OPENAI_REALTIME_MODEL = ${PLATFORM_OPENAI_REALTIME_MODEL}
OPENAI_REALTIME_UNDERLYING_MODEL = ""

##################################
# IMAGE TARGET SECRETS
#
# The below models work with OpenAIImageTarget - either pass via environment variables
# or copy to OPENAI_IMAGE_ENDPOINT
###################################

OPENAI_IMAGE_ENDPOINT1  = "https://xxxxx.openai.azure.com/openai/v1"
OPENAI_IMAGE_API_KEY1 = "xxxxxx"
OPENAI_IMAGE_MODEL1 = "deployment-name"
OPENAI_IMAGE_UNDERLYING_MODEL1 = "dall-e-3"

OPENAI_IMAGE_ENDPOINT2 = "https://api.openai.com/v1"
OPENAI_IMAGE_API_KEY2 = "sk-xxxxx"
OPENAI_IMAGE_MODEL2 = "dall-e-3"
OPENAI_IMAGE_UNDERLYING_MODEL2 = "dall-e-3"

OPENAI_IMAGE_ENDPOINT = ${OPENAI_IMAGE_ENDPOINT2}
OPENAI_IMAGE_API_KEY = ${OPENAI_IMAGE_API_KEY2}
OPENAI_IMAGE_MODEL = ${OPENAI_IMAGE_MODEL2}
OPENAI_IMAGE_UNDERLYING_MODEL = ""


##################################
# TTS TARGET SECRETS
#
# The below models work with OpenAITTSTarget - either pass via environment variables
# or copy to OPENAI_TTS_ENDPOINT
###################################

OPENAI_TTS_ENDPOINT1 = "https://xxxxx.openai.azure.com/openai/v1"
OPENAI_TTS_KEY1 = "xxxxxxx"
OPENAI_TTS_MODEL1 = "tts"
OPENAI_TTS_UNDERLYING_MODEL1 = "tts"

OPENAI_TTS_ENDPOINT2 = "https://api.openai.com/v1"
OPENAI_TTS_KEY2 = "xxxxxx"
OPENAI_TTS_MODEL2 = "tts-1"
OPENAI_TTS_UNDERLYING_MODEL2 = "tts-1"

OPENAI_TTS_ENDPOINT = ${OPENAI_TTS_ENDPOINT2}
OPENAI_TTS_KEY = ${OPENAI_TTS_KEY2}
OPENAI_TTS_MODEL = ${OPENAI_TTS_MODEL2}
OPENAI_TTS_UNDERLYING_MODEL = ""

##################################
# OPTIONAL LEGACY VIDEO API CONFIGURATION
# OpenAI's Sora service is retired. OpenAIVideoTarget remains available for
# compatible providers; configure it only after verifying a working endpoint.
###################################

# Use the provider's base URL, without /videos.
# OPENAI_VIDEO_ENDPOINT="https://your-compatible-provider.example/v1"
# OPENAI_VIDEO_KEY="your-provider-api-key"
# OPENAI_VIDEO_MODEL="your-compatible-video-model"
# OPENAI_VIDEO_UNDERLYING_MODEL=""


##################################
# AML TARGET SECRETS
# The below models work with AzureMLChatTarget - either pass via environment variables
# or copy to AZURE_ML_MANAGED_ENDPOINT
###################################

AZURE_ML_PHI_ENDPOINT="https://xxxxxx.westus3.inference.ml.azure.com/score"
AZURE_ML_PHI_KEY="xxxxx"

# The below is set as the default Azure OpenAI model used in most notebooks. Adjust as needed.
AZURE_ML_MANAGED_ENDPOINT=${AZURE_ML_PHI_ENDPOINT}
AZURE_ML_KEY=${AZURE_ML_PHI_KEY}


##################################
# MISC TARGET SECRETS
###################################


OPENAI_COMPLETION_ENDPOINT="https://xxxxx.openai.azure.com/openai/v1"
OPENAI_COMPLETION_API_KEY="xxxxx"
OPENAI_COMPLETION_MODEL="davinci-002"

OPENAI_EMBEDDING_ENDPOINT="https://xxxxx.openai.azure.com/openai/v1"
OPENAI_EMBEDDING_KEY="xxxxx"
OPENAI_EMBEDDING_MODEL="text-embedding-3-small"

AZURE_STORAGE_ACCOUNT_CONTAINER_URL="https://xxxxxx.blob.core.windows.net/xpia"
AZURE_STORAGE_ACCOUNT_SAS_TOKEN="xxxxx"


AZURE_SPEECH_REGION = "eastus2"
AZURE_SPEECH_KEY = "xxxxx"
# Resource ID is needed when using Entra authentication
AZURE_SPEECH_RESOURCE_ID = "xxxxx"

AZURE_CONTENT_SAFETY_API_KEY="xxxxx"
AZURE_CONTENT_SAFETY_API_ENDPOINT="https://xxxxx.cognitiveservices.azure.com/"

HUGGINGFACE_TOKEN="hf_xxxxxxx"
HUGGINGFACE_ENDPOINT="https://router.huggingface.co/v1"

GOOGLE_GEMINI_ENDPOINT = "https://generativelanguage.googleapis.com/v1beta/openai"
GOOGLE_GEMINI_API_KEY = "xxxxx"
GOOGLE_GEMINI_MODEL="gemini-3.8-flash"

# HackAPromptTarget authenticates with a signed-in browser session instead of an API key.
# Copy both values from the developer tools of a browser signed in to hackaprompt.com;
# see doc/code/targets/hack_a_prompt_target.ipynb. They expire with the browser session.
HACK_A_PROMPT_SESSION_ID="xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx"
HACK_A_PROMPT_COOKIE="sb-xxxxx-auth-token.0=xxxxx; sb-xxxxx-auth-token.1=xxxxx"


#########################
# AZURE SQL SECRETS
#########################


# This connects to the test database
AZURE_SQL_DB_CONNECTION_STRING_TEST = "mssql+pyodbc://@xxxxx.database.windows.net/xxxxx?driver=ODBC+Driver+18+for+SQL+Server"
AZURE_STORAGE_ACCOUNT_DB_DATA_CONTAINER_URL_TEST="https://xxxxx.blob.core.windows.net/dbdata"

# This connects to the prod database
AZURE_SQL_DB_CONNECTION_STRING_PROD = "mssql+pyodbc://@xxxxx.database.windows.net/xxxxx?driver=ODBC+Driver+18+for+SQL+Server"
AZURE_STORAGE_ACCOUNT_DB_DATA_CONTAINER_URL_PROD="https://xxxxx.blob.core.windows.net/dbdata"


# The below is set as the central memory. Adjust as needed. Recommend overwriting in .env.local.
AZURE_SQL_DB_CONNECTION_STRING = ${AZURE_SQL_DB_CONNECTION_STRING_PROD}
AZURE_STORAGE_ACCOUNT_DB_DATA_CONTAINER_URL=${AZURE_STORAGE_ACCOUNT_DB_DATA_CONTAINER_URL_PROD}