Fix hyperlinks and updated package version

README.md

@@ -28,17 +28,17 @@ For example, at Microsoft we are using this tool to iterate on different
 versions of a product (and its metaprompt) so that we can more effectively
 protect against prompt injection attacks.
 
-![PyRIT architecture](./assets/pyrit_architecture.png)
+![PyRIT architecture](https://github.com/Azure/PyRIT/blob/main/assets/pyrit_architecture.png)
 
 ## Where can I learn more?
 
 Microsoft Learn has a
 [dedicated page on AI Red Teaming](https://learn.microsoft.com/en-us/security/ai-red-team).
 
-Check out our [docs](./doc/README.md) for more information
-on how to [install PyRIT](./doc/setup/install_pyrit.md),
-our [How to Guide](./doc/how_to_guide.ipynb),
-and more, as well as our [demos](./doc/demo/) folder.
+Check out our [docs](https://github.com/Azure/PyRIT/blob/main/doc/README.md) for more information
+on how to [install PyRIT](https://github.com/Azure/PyRIT/blob/main/doc/setup/install_pyrit.md),
+our [How to Guide](https://github.com/Azure/PyRIT/blob/main/doc/how_to_guide.ipynb),
+and more, as well as our [demos](https://github.com/Azure/PyRIT/tree/main/doc/demo) folder.
 
 ## Trademarks
 

doc/code/azure_completions.ipynb

@@ -16,7 +16,7 @@
     "2. Work with Azure OpenAI Embeddings\n",
     "3. Embeddings serialization\n",
     "\n",
-    "Before starting this, make sure you are [set up and authenticated to use Azure OpenAI endpoints](../setup/azure_openai_setup.ipynb)"
+    "Before starting this, make sure you are [set up and authenticated to use Azure OpenAI endpoints](../setup/setup_azure.md)"
    ]
   },
   {

doc/code/azure_completions.pct.py → doc/code/azure_completions.py

@@ -10,7 +10,7 @@
 # 2. Work with Azure OpenAI Embeddings
 # 3. Embeddings serialization
 #
-# Before starting this, make sure you are [set up and authenticated to use Azure OpenAI endpoints](../setup/azure_openai_setup.ipynb)
+# Before starting this, make sure you are [set up and authenticated to use Azure OpenAI endpoints](../setup/setup_azure.md)
 
 # %%
 import os

doc/code/azure_openai_chat.ipynb

@@ -10,7 +10,7 @@
     "\n",
     "This Jupyter notebook gives an introduction on how to use `AzureOpenAIChat` to complete chats.\n",
     "\n",
-    "Before starting this, make sure you are [setup to use Azure OpenAI endpoints](../setup/azure_openai_setup.md) and have a chat model, such as GPT-4, deployed. See [How To: Create and deploy an Azure OpenAI Service resource](https://learn.microsoft.com/en-us/azure/ai-services/openai/how-to/create-resource?pivots=web-portal).\n",
+    "Before starting this, make sure you are [setup to use Azure OpenAI endpoints](../setup/setup_azure.md) and have a chat model, such as GPT-4, deployed. See [How To: Create and deploy an Azure OpenAI Service resource](https://learn.microsoft.com/en-us/azure/ai-services/openai/how-to/create-resource?pivots=web-portal).\n",
     "\n",
     "In this case, we have one named `gpt-4` deployed. See your deployments at https://oai.azure.com/ `> Management > Deployments`"
    ]

doc/code/azure_openai_chat.pct.py → doc/code/azure_openai_chat.py

@@ -4,7 +4,7 @@
 #
 # This Jupyter notebook gives an introduction on how to use `AzureOpenAIChat` to complete chats.
 #
-# Before starting this, make sure you are [setup to use Azure OpenAI endpoints](../setup/azure_openai_setup.md) and have a chat model, such as GPT-4, deployed. See [How To: Create and deploy an Azure OpenAI Service resource](https://learn.microsoft.com/en-us/azure/ai-services/openai/how-to/create-resource?pivots=web-portal).
+# Before starting this, make sure you are [setup to use Azure OpenAI endpoints](../setup/setup_azure.md) and have a chat model, such as GPT-4, deployed. See [How To: Create and deploy an Azure OpenAI Service resource](https://learn.microsoft.com/en-us/azure/ai-services/openai/how-to/create-resource?pivots=web-portal).
 #
 # In this case, we have one named `gpt-4` deployed. See your deployments at https://oai.azure.com/ `> Management > Deployments`
 

doc/code/orchestrator.ipynb

@@ -18,7 +18,7 @@
     "\n",
     "Orchestrators can tackle complicated scenarios, but this example is about as simple as it gets (while still being useful). Here, we'll send all prompts in a file, use a transformer to base64-encode the prompts, and send them to a PromptTarget.\n",
     "\n",
-    "Note to run this demo you need to setup your `.env` file to properly authenticate to an Azure OpenAI endpoint as described [here](../setup/azure_openai_setup.ipynb)"
+    "Note to run this demo you need to setup your `.env` file to properly authenticate to an Azure OpenAI endpoint as described [here](../setup/setup_azure.md)"
    ]
   },
   {

doc/code/orchestrator.pct.py → doc/code/orchestrator.py

@@ -12,7 +12,7 @@
 #
 # Orchestrators can tackle complicated scenarios, but this example is about as simple as it gets (while still being useful). Here, we'll send all prompts in a file, use a transformer to base64-encode the prompts, and send them to a PromptTarget.
 #
-# Note to run this demo you need to setup your `.env` file to properly authenticate to an Azure OpenAI endpoint as described [here](../setup/azure_openai_setup.ipynb)
+# Note to run this demo you need to setup your `.env` file to properly authenticate to an Azure OpenAI endpoint as described [here](../setup/setup_azure.md)
 
 # %%
 

doc/code/scoring.ipynb

@@ -8,7 +8,7 @@
     "\n",
     "This Jupyter notebook gives an introduction on how to use PyRIT to score responses. We set up a `SelfAskGptClassifier`, which uses Azure Open AI to score a response. In this example, we mock a response from a targeted endpoint and ask if it matches any classifier.\n",
     "\n",
-    "Before starting this, make sure you are [set up and authenticated to use Azure OpenAI endpoints](../setup/azure_openai_setup.md)"
+    "Before starting this, make sure you are [set up and authenticated to use Azure OpenAI endpoints](../setup/setup_azure.md)"
    ]
   },
   {

doc/code/scoring.pct.py → doc/code/scoring.py

@@ -2,7 +2,7 @@
 #
 # This Jupyter notebook gives an introduction on how to use PyRIT to score responses. We set up a `SelfAskGptClassifier`, which uses Azure Open AI to score a response. In this example, we mock a response from a targeted endpoint and ask if it matches any classifier.
 #
-# Before starting this, make sure you are [set up and authenticated to use Azure OpenAI endpoints](../setup/azure_openai_setup.md)
+# Before starting this, make sure you are [set up and authenticated to use Azure OpenAI endpoints](../setup/setup_azure.md)
 
 # %%
 

doc/demo/1_gandalf.ipynb

@@ -13,7 +13,7 @@
     "\n",
     "Before you begin, ensure the following steps have been completed:\n",
     "\n",
-    "1. Before starting this, make sure you are [set up and authenticated to use Azure OpenAI endpoints](../setup/azure_openai_setup.ipynb)\n",
+    "1. Before starting this, make sure you are [set up and authenticated to use Azure OpenAI endpoints](../setup/setup_azure.md)\n",
     "\n",
     "2. **Deploy an Azure OpenAI:** Confirm that an Azure OpenAI service is already deployed in Azure subscription.\n",
     "\n",

doc/demo/1_gandalf.pct.py → doc/demo/1_gandalf.py

@@ -1,15 +1,3 @@
-# ---
-# jupyter:
-#   jupytext:
-#     cell_metadata_filter: -all
-#     formats: ipynb,py:percent
-#     text_representation:
-#       extension: .py
-#       format_name: percent
-#       format_version: '1.3'
-#       jupytext_version: 1.16.1
-# ---
-
 # %% [markdown]
 # # Introduction
 #
@@ -19,7 +7,7 @@
 #
 # Before you begin, ensure the following steps have been completed:
 #
-# 1. Before starting this, make sure you are [set up and authenticated to use Azure OpenAI endpoints](../setup/azure_openai_setup.ipynb)
+# 1. Before starting this, make sure you are [set up and authenticated to use Azure OpenAI endpoints](../setup/setup_azure.md)
 #
 # 2. **Deploy an Azure OpenAI:** Confirm that an Azure OpenAI service is already deployed in Azure subscription.
 #
@@ -101,7 +89,6 @@
 
 GandalfLevel.LEVEL_1, GandalfLevel.LEVEL_2
 
-
 # %% [markdown]
 # Once the agents are set up, we can start the conversation.
 
@@ -141,7 +128,6 @@
 # %% [markdown]
 # Once this is complete, we can use the `GandalfScorer` to score the response from Gandalf.
 
-
 # %%
 gandalf_password_scorer_l1 = GandalfScorer(level=GandalfLevel.LEVEL_1, chat_engine=aoai_chat_engine)
 # gandalf_password_scorer_l2 = GandalfScorer(level=GandalfLevel.LEVEL_2, chat_engine=aoai_chat_engine)

doc/deployment/deploy_hf_model_aml.ipynb

@@ -9,17 +9,17 @@
     "This notebook demonstrates the process of deploying registered models in Azure ML workspace\n",
     "to an AZURE ML managed online endpoint for real-time inference.\n",
     "\n",
-    "[Learn more about Azure ML Managed Online Endpoints](https://learn.microsoft.com/en-us/azure/machine-learning/concept-endpoints-onlineview=azureml-api-2)\n",
+    "[Learn more about Azure ML Managed Online Endpoints](https://learn.microsoft.com/en-us/azure/machine-learning/concept-endpoints-online?view=azureml-api-2)\n",
     "\n",
     "### Prerequisites\n",
     "- An Azure account with an active subscription. [Create one for free](https://azure.microsoft.com/free/).\n",
-    "- An Azure ML workspace set up. [Learn how to set up a workspace](https://docs.microsoft.com/en-us/azure/machine-learninghow-to-manage-workspace).\n",
+    "- An Azure ML workspace set up. [Learn how to set up a workspace](https://learn.microsoft.com/en-us/azure/machine-learning/how-to-manage-workspace?view=azureml-api-2&tabs=python).\n",
     "- Install the Azure ML client library for Python with pip.\n",
     "  ```bash\n",
     "     pip install azure-ai-ml\n",
     "     pip install azure-identity\n",
     "  ```\n",
-    "- Execute the `az login` command to sign in to your Azure subscription. For detailed instructions, refer to the \"Authenticate with Azure Subscription\" section in the notebook provided [here](../setup/azure_openai_setup.ipynb)\n",
+    "- Execute the `az login` command to sign in to your Azure subscription. For detailed instructions, refer to the \"Authenticate with Azure Subscription\" section in the notebook provided [here](../setup/setup_azure.md)\n",
     "- A Hugging Face model should be present in the AZURE ML model catalog. If it is missing, execute the [notebook](./download_and_register_hf_model_aml.ipynb) to download and register the Hugging Face model in the AZURE ML registry."
    ]
   },

doc/deployment/deploy_hf_model_aml.pct.py → doc/deployment/deploy_hf_model_aml.py

@@ -4,17 +4,17 @@
 # This notebook demonstrates the process of deploying registered models in Azure ML workspace
 # to an AZURE ML managed online endpoint for real-time inference.
 #
-# [Learn more about Azure ML Managed Online Endpoints](https://learn.microsoft.com/en-us/azure/machine-learning/concept-endpoints-onlineview=azureml-api-2)
+# [Learn more about Azure ML Managed Online Endpoints](https://learn.microsoft.com/en-us/azure/machine-learning/concept-endpoints-online?view=azureml-api-2)
 #
 # ### Prerequisites
 # - An Azure account with an active subscription. [Create one for free](https://azure.microsoft.com/free/).
-# - An Azure ML workspace set up. [Learn how to set up a workspace](https://docs.microsoft.com/en-us/azure/machine-learninghow-to-manage-workspace).
+# - An Azure ML workspace set up. [Learn how to set up a workspace](https://learn.microsoft.com/en-us/azure/machine-learning/how-to-manage-workspace?view=azureml-api-2&tabs=python).
 # - Install the Azure ML client library for Python with pip.
 #   ```bash
 #      pip install azure-ai-ml
 #      pip install azure-identity
 #   ```
-# - Execute the `az login` command to sign in to your Azure subscription. For detailed instructions, refer to the "Authenticate with Azure Subscription" section in the notebook provided [here](../setup/azure_openai_setup.ipynb)
+# - Execute the `az login` command to sign in to your Azure subscription. For detailed instructions, refer to the "Authenticate with Azure Subscription" section in the notebook provided [here](../setup/setup_azure.md)
 # - A Hugging Face model should be present in the AZURE ML model catalog. If it is missing, execute the [notebook](./download_and_register_hf_model_aml.ipynb) to download and register the Hugging Face model in the AZURE ML registry.
 
 # %% [markdown]
@@ -161,7 +161,7 @@ def check_model_version_exists(client, model_name, version) -> bool:
 
 # %%
 # Using the first 32 characters because Azure ML endpoint names must be between 3 and 32 characters in length.
-endpoint_name = endpoint_name[:32]
+endpoint_name = endpoint_name[:30]
 
 # %% [markdown]
 # **Create an Azure ML managed online endpoint**
@@ -201,3 +201,5 @@ def check_model_version_exists(client, model_name, version) -> bool:
 )
 workspace_ml_client.online_deployments.begin_create_or_update(deployment).wait()
 workspace_ml_client.begin_create_or_update(endpoint).result()
+
+# %%

doc/deployment/download_and_register_hf_model_aml.ipynb

@@ -37,7 +37,7 @@
     "     pip install azure-ai-ml\n",
     "     pip install azure-identity\n",
     "  ```\n",
-    "- Execute the `az login` command to sign in to your Azure subscription. For detailed instructions, refer to the \"Authenticate with Azure Subscription\" section in the notebook provided [here](../setup/azure_openai_setup.ipynb)"
+    "- Execute the `az login` command to sign in to your Azure subscription. For detailed instructions, refer to the \"Authenticate with Azure Subscription\" section in the notebook provided [here](../setup/setup_azure.md)"
    ]
   },
   {

doc/deployment/download_and_register_hf_model_aml.pct.py → doc/deployment/download_and_register_hf_model_aml.py

@@ -32,7 +32,7 @@
 #      pip install azure-ai-ml
 #      pip install azure-identity
 #   ```
-# - Execute the `az login` command to sign in to your Azure subscription. For detailed instructions, refer to the "Authenticate with Azure Subscription" section in the notebook provided [here](../setup/azure_openai_setup.ipynb)
+# - Execute the `az login` command to sign in to your Azure subscription. For detailed instructions, refer to the "Authenticate with Azure Subscription" section in the notebook provided [here](../setup/setup_azure.md)
 
 # %% [markdown]
 # ## 1. Connect to Azure Machine Learning Workspace

doc/deployment/score_aml_endpoint.ipynb

@@ -13,7 +13,7 @@
     "Before proceeding with this notebook, ensure the following prerequisites are met:\n",
     "\n",
     "1. **Azure ML Model Deployment**: Your Azure ML model must be deployed to an Azure ML managed online endpoint. If your model is not yet deployed, please follow the instructions in the [deployment notebook](./deploy_hf_model_aml.ipynb).\n",
-    "2. Execute the `az login` command to sign in to your Azure subscription. For detailed instructions, refer to the \"Authenticate with Azure Subscription\" section in the notebook provided [here](../setup/azure_openai_setup.ipynb)\n",
+    "2. Execute the `az login` command to sign in to your Azure subscription. For detailed instructions, refer to the \"Authenticate with Azure Subscription\" section in the notebook provided [here](../setup/setup_azure.md)\n",
     "\n",
     "\n",
     "### Environment Variables\n",

doc/deployment/score_aml_endpoint.pct.py → doc/deployment/score_aml_endpoint.py

@@ -8,7 +8,7 @@
 # Before proceeding with this notebook, ensure the following prerequisites are met:
 #
 # 1. **Azure ML Model Deployment**: Your Azure ML model must be deployed to an Azure ML managed online endpoint. If your model is not yet deployed, please follow the instructions in the [deployment notebook](./deploy_hf_model_aml.ipynb).
-# 2. Execute the `az login` command to sign in to your Azure subscription. For detailed instructions, refer to the "Authenticate with Azure Subscription" section in the notebook provided [here](../setup/azure_openai_setup.ipynb)
+# 2. Execute the `az login` command to sign in to your Azure subscription. For detailed instructions, refer to the "Authenticate with Azure Subscription" section in the notebook provided [here](../setup/setup_azure.md)
 #
 #
 # ### Environment Variables

doc/how_to_guide.ipynb

@@ -24,11 +24,11 @@
     "\n",
     "For that reason, PyRIT is designed to help AI Red Teams scale their efforts. In this user guide, we\n",
     "describe two ways of using PyRIT:\n",
-    "1. [Write prompts yourself](#write-prompts-yourself)\n",
-    "2. [Generate prompts automatically with RedTeamingBot](#generate-prompts-automatically-with-redteamingbot)\n",
+    "1. Write prompts yourself\n",
+    "2. Generate prompts automatically with RedTeamingBot\n",
     "\n",
-    "PyRIT also includes functionality to [score LLM ](#output-scoring) and keep track of conversation\n",
-    "history with a built-in [memory](#memory) which we discuss below.\n",
+    "PyRIT also includes functionality to score LLM and keep track of conversation\n",
+    "history with a built-in memory which we discuss below.\n",
     "\n",
     "## Write prompts yourself\n",
     "\n",
@@ -241,8 +241,8 @@
     "for example, `datasets/attack_strategies/multi-turn-chat/red_team_chatbot_with_objective.yaml`).\n",
     "\n",
     "PyRIT offers various integration choices for the `RedTeamingBot`, including\n",
-    "[Azure ML managed online endpoints](https://github.com/Azure/PyRIT/blob/main/examples/demo/3_gandalf_AML_endpoint_red_team_bot.ipynb),\n",
-    "[Hugging Face](https://github.com/Azure/PyRIT/blob/main/examples/demo/4_gandalf_HuggingFace_red_team_bot.ipynb),\n",
+    "[Azure ML managed online endpoints](../doc/code/aml_endpoints.ipynb),\n",
+    "[Hugging Face](../doc/code/huggingface_endpoints.ipynb),\n",
     "and Azure OpenAI models (as shown above).\n",
     "\n",
     "## Output scoring\n",