Merge branch 'main' into fuming/aks-get-cred-1011

Author: FumingZhang

src/aks-agent/HISTORY.rst

@@ -12,6 +12,21 @@ To release a new version, please select a new version number (usually plus 1 to
 Pending
 +++++++
 
+1.0.0b6
++++++++
+* Introduce the new `az aks agent-init` command for better cli interaction.
+* Separate llm configuration from main agent command for improved clarity and extensibility.
+
+1.0.0b5
++++++++
+* Bump holmesgpt to 0.15.0 - Enhanced AI debugging experience and bug fixes
+  * Added TODO list feature to allows holmes to reliably answers questions it wasn't able to answer before due to early-stopping
+  * Fixed mcp server http connection fails when using socks proxy by adding the missing socks dependency
+  * Fixed gpt-5 temperature bug by upgrading litellm and dropping non-1 values for temperature
+  * Improved the installation time by removing unnecessary dependencies and move test dependencies to dev dependency group
+* Added Feedback slash command Feature to allow users to provide feedback on their experience with the agent performance
+* Disable prometheus toolset loading by default to workaround the libbz2-dev missing issue in Azure CLI python environment.
+
 1.0.0b4
 +++++++
 * Fix the --aks-mcp flag to allow true/false values.

src/aks-agent/README.rst

@@ -4,32 +4,41 @@ Azure CLI AKS Agent Extension
 Introduction
 ============
 
-The AKS Agent extension provides the "az aks agent" command, an AI-powered assistant that
-helps analyze and troubleshoot Azure Kubernetes Service (AKS) clusters using Large Language
-Models (LLMs). The agent combines cluster context, configurable toolsets, and LLMs to answer
-natural-language questions about your cluster (for example, "Why are my pods not starting?")
-and can investigate issues in both interactive and non-interactive (batch) modes.
+
+The AKS Agent extension provides the "az aks agent" command, an AI-powered assistant that helps analyze and troubleshoot Azure Kubernetes Service (AKS) clusters using Large Language Models (LLMs). The agent combines cluster context, configurable toolsets, and LLMs to answer natural-language questions about your cluster (for example, "Why are my pods not starting?") and can investigate issues in both interactive and non-interactive (batch) modes.
+
+New in this version: **az aks agent-init** command for easy LLM model configuration!
+
+You can now use `az aks agent-init` to interactively add and configure LLM models before asking questions. This command guides you through the setup process, allowing you to add multiple models as needed. When asking questions with `az aks agent`, you can:
+
+- Use `--config-file` to specify your own model configuration file
+- Use `--model` to select a previously configured model
+- If neither is provided, the last configured LLM will be used by default
+
+This makes it much easier to manage and switch between multiple models for your AKS troubleshooting workflows.
 
 Key capabilities
 ----------------
 
+
 - Interactive and non-interactive modes (use --no-interactive for batch runs).
-- Support for multiple LLM providers (Azure OpenAI, OpenAI, etc.) via environment variables.
-- Configurable via a JSON/YAML config file provided with --config-file.
+- Support for multiple LLM providers (Azure OpenAI, OpenAI, etc.) via interactive configuration.
+- **Easy model setup with `az aks agent-init`**: interactively add and configure LLM models, run multiple times to add more models.
+- Configurable via a JSON/YAML config file provided with --config-file, or select a model with --model.
+- If no config or model is specified, the last configured LLM is used automatically.
 - Control echo and tool output visibility with --no-echo-request and --show-tool-output.
 - Refresh the available toolsets with --refresh-toolsets.
 - Stay in traditional toolset mode by default, or opt in to aks-mcp integration with ``--aks-mcp`` when you need the enhanced capabilities.
 
 Prerequisites
 -------------
-
-Before using the agent, make sure provider-specific environment variables are set. For
-example, Azure OpenAI typically requires AZURE_API_BASE, AZURE_API_VERSION, and AZURE_API_KEY,
-while OpenAI requires OPENAI_API_KEY. For more details about supported providers and required
+No need to manually set environment variables! All model and credential information can be configured interactively using `az aks agent-init`.
+For more details about supported model providers and required
 variables, see: https://docs.litellm.ai/docs/providers
 
+
 Quick start and examples
-========================
+=========================
 
 Install the extension
 ---------------------
@@ -38,25 +47,58 @@ Install the extension
 
     az extension add --name aks-agent
 
-Run the agent (Azure OpenAI example)
+Configure LLM models interactively
+----------------------------------
+
+.. code-block:: bash
+
+    az aks agent-init
+
+This command will guide you through adding a new LLM model. You can run it multiple times to add more models or update existing models. All configured models are saved locally and can be selected when asking questions.
+
+Run the agent (Azure OpenAI example) :
 -----------------------------------
 
+**1. Use the last configured model (no extra parameters needed):**
+
 .. code-block:: bash
 
-    export AZURE_API_BASE="https://my-azureopenai-service.openai.azure.com/"
-    export AZURE_API_VERSION="2025-01-01-preview"
-    export AZURE_API_KEY="sk-xxx"
+    az aks agent "Why are my pods not starting?" --name MyManagedCluster --resource-group MyResourceGroup
+
+**2. Specify a particular model you have configured:**
+
+.. code-block:: bash
 
     az aks agent "Why are my pods not starting?" --name MyManagedCluster --resource-group MyResourceGroup --model azure/my-gpt4.1-deployment
 
+**3. Use a custom config file:**
+
+.. code-block:: bash
+
+    az aks agent "Why are my pods not starting?" --config-file /path/to/your/model_config.yaml
+
+
 Run the agent (OpenAI example)
 ------------------------------
 
+**1. Use the last configured model (no extra parameters needed):**
+
 .. code-block:: bash
 
-    export OPENAI_API_KEY="sk-xxx"
+    az aks agent "Why are my pods not starting?" --name MyManagedCluster --resource-group MyResourceGroup
+
+**2. Specify a particular model you have configured:**
+
+.. code-block:: bash
+    
     az aks agent "Why are my pods not starting?" --name MyManagedCluster --resource-group MyResourceGroup --model gpt-4o
 
+**3. Use a custom config file:**
+
+.. code-block:: bash
+
+    az aks agent "Why are my pods not starting?" --config-file /path/to/your/model_config.yaml
+
 Run in non-interactive batch mode
 ---------------------------------
 

src/aks-agent/azext_aks_agent/_consts.py

@@ -3,11 +3,24 @@
 # Licensed under the MIT License. See License.txt in the project root for license information.
 # --------------------------------------------------------------------------------------------
 
-# aks agent constants
+# Constants to customized holmesgpt
 CONST_AGENT_CONFIG_PATH_DIR_ENV_KEY = "HOLMES_CONFIGPATH_DIR"
 CONST_AGENT_NAME = "AKS AGENT"
 CONST_AGENT_NAME_ENV_KEY = "AGENT_NAME"
 CONST_AGENT_CONFIG_FILE_NAME = "aksAgent.yaml"
+CONST_PRIVACY_NOTICE_BANNER_ENV_KEY = "PRIVACY_NOTICE_BANNER"
+# Privacy Notice Banner displayed in the format of rich.Console
+CONST_PRIVACY_NOTICE_BANNER = (
+    "When you send Microsoft this feedback, you agree we may combine this information, which might include other "
+    "diagnostic data, to help improve Microsoft products and services. Processing of feedback data is governed by "
+    "the Microsoft Products and Services Data Protection Addendum between your organization and Microsoft, and the "
+    "feedback you submit is considered Personal Data under that addendum. "
+    "Privacy Statement: https://go.microsoft.com/fwlink/?LinkId=521839"
+)
+# Holmesgpt leverages prometheus_api_client for prometheus toolsets and introduces bz2 library.
+# Before libbz2-dev is bundled into azure cli python by https://github.com/Azure/azure-cli/pull/32163,
+# we ignore loading prometheus toolset to avoid loading error of bz2 module.
+CONST_DISABLE_PROMETHEUS_TOOLSET_ENV_KEY = "DISABLE_PROMETHEUS_TOOLSET"
 
 # MCP Integration Constants (ported from previous change)
 CONST_MCP_BINARY_NAME = "aks-mcp"

src/aks-agent/azext_aks_agent/_help.py

@@ -16,7 +16,7 @@
     short-summary: Run AI assistant to analyze and troubleshoot Kubernetes clusters.
     long-summary: |-
       This command allows you to ask questions about your Azure Kubernetes cluster and get answers using AI models.
-      Environment variables must be set to use the AI model, please refer to https://docs.litellm.ai/docs/providers to learn more about supported AI providers and models and required environment variables.
+      No need to manually set environment variables! All model and credential information can be configured interactively using `az aks agent-init` or via a config file.
     parameters:
         - name: --name -n
           type: string
@@ -36,7 +36,7 @@
             Note: For Azure OpenAI, it is recommended to set the deployment name as the model name until https://github.com/BerriAI/litellm/issues/13950 is resolved.
         - name: --api-key
           type: string
-          short-summary: API key to use for the LLM (if not given, uses environment variables AZURE_API_KEY, OPENAI_API_KEY).
+          short-summary: API key to use for the LLM (if not given, uses environment variables AZURE_API_KEY, OPENAI_API_KEY). (Deprecated)
         - name: --config-file
           type: string
           short-summary: Path to configuration file.
@@ -63,23 +63,25 @@
           short-summary: Enable AKS MCP integration for enhanced capabilities. Traditional mode is the default.
 
     examples:
+        - name: Ask about pod issues in the cluster with last configured model
+          text: |-
+            az aks agent "Why are my pods not starting?" --name MyManagedCluster --resource-group MyResourceGroup
         - name: Ask about pod issues in the cluster with Azure OpenAI
           text: |-
-            export AZURE_API_BASE="https://my-azureopenai-service.openai.azure.com/"
-            export AZURE_API_VERSION="2025-01-01-preview"
-            export AZURE_API_KEY="sk-xxx"
             az aks agent "Why are my pods not starting?" --name MyManagedCluster --resource-group MyResourceGroup --model azure/gpt-4.1
         - name: Ask about pod issues in the cluster with OpenAI
           text: |-
-            export OPENAI_API_KEY="sk-xxx"
             az aks agent "Why are my pods not starting?" --name MyManagedCluster --resource-group MyResourceGroup --model gpt-4o
         - name: Run agent with config file
           text: |
             az aks agent "Check kubernetes pod resource usage" --config-file /path/to/custom.yaml --name MyManagedCluster --resource-group MyResourceGroup
             Here is an example of config file:
             ```json
-            model: "azure/gpt-4.1"
-            api_key: "..."
+            llms:
+              - provider: "azure"
+                MODEL_NAME: "gpt-4.1"
+                AZURE_API_BASE: "https://<your-base-url>"
+                AZURE_API_KEY: "<your-api-key>"
             # define a list of mcp servers, mcp server can be defined
             mcp_servers:
               aks_mcp:
@@ -131,3 +133,16 @@
         - name: Refresh toolsets to get the latest available tools
           text: az aks agent "What is the status of my cluster?" --refresh-toolsets --model azure/my-gpt4.1-deployment
 """
+
+helps[
+    "aks agent-init"
+] = """
+    type: command
+    short-summary: Initialize and validate LLM provider/model configuration for AKS agent.
+    long-summary: |-
+      This command interactively guides you to select an LLM provider and model, validates the connection, and saves the configuration for later use.
+      You can run this command multiple times to add or update different model configurations.
+    examples:
+        - name: Initialize configuration for Azure OpenAI, OpenAI or other llms
+          text: az aks agent-init
+"""

src/aks-agent/azext_aks_agent/_params.py

@@ -6,12 +6,10 @@
 # pylint: disable=too-many-statements,too-many-lines
 import os.path
 
-from azure.cli.core.api import get_config_dir
-from azure.cli.core.commands.parameters import get_three_state_flag
-
 from azext_aks_agent._consts import CONST_AGENT_CONFIG_FILE_NAME
-
 from azext_aks_agent._validators import validate_agent_config_file
+from azure.cli.core.api import get_config_dir
+from azure.cli.core.commands.parameters import get_three_state_flag
 
 
 def load_arguments(self, _):
@@ -37,7 +35,7 @@ def load_arguments(self, _):
         c.argument(
             "max_steps",
             type=int,
-            default=10,
+            default=40,
             required=False,
             help="Maximum number of steps the LLM can take to investigate the issue.",
         )