{AKS}: agent-init replaces model name with deployment name for Azure OpenAI service

src/aks-agent/HISTORY.rst

@@ -12,6 +12,11 @@ To release a new version, please select a new version number (usually plus 1 to
 Pending
 +++++++
 
+1.0.0b9
++++++++
+* agent-init: replace model name with deployment name for Azure OpenAI service.
+* agent-init: remove importing holmesgpt to resolve the latency issue.
+
 1.0.0b8
 +++++++
 * Error handling: dont raise traceback for init prompt and holmesgpt interaction.

src/aks-agent/azext_aks_agent/_consts.py

@@ -29,3 +29,7 @@
 CONST_MCP_MIN_VERSION = "0.0.10"
 CONST_MCP_GITHUB_REPO = "Azure/aks-mcp"
 CONST_MCP_BINARY_DIR = "bin"
+
+# Color constants for terminal output
+HELP_COLOR = "cyan"  # same as AI_COLOR for now
+ERROR_COLOR = "red"

src/aks-agent/azext_aks_agent/agent/llm_config_manager.py

@@ -9,8 +9,12 @@
 
 import yaml
 from azext_aks_agent._consts import CONST_AGENT_CONFIG_FILE_NAME
+from azext_aks_agent.agent.llm_providers import PROVIDER_REGISTRY
 from azure.cli.core.api import get_config_dir
 from azure.cli.core.azclierror import AzCLIError
+from knack.log import get_logger
+
+logger = get_logger(__name__)
 
 
 class LLMConfigManager:
@@ -67,18 +71,30 @@ def save(self, provider_name: str, params: dict):
             configs = {}
 
         models = configs.get("llms", [])
-        model_name = params.get("MODEL_NAME")
-        if not model_name:
-            raise ValueError("MODEL_NAME is required to save configuration.")
-
-        # Check if model already exists, update it and move it to the last;
-        # otherwise, append new
-        models = [
-            cfg for cfg in models if not (
-                cfg.get("provider") == provider_name and cfg.get("MODEL_NAME") == model_name)]
-        models.append({"provider": provider_name, **params})
 
-        configs["llms"] = models
+        # modify existing azure openai config from model name to deloyment name
+        for model in models:
+            if provider_name.lower() == "azure" and "MODEL_NAME" in model:
+                model["DEPLOYMENT_NAME"] = model.pop("MODEL_NAME")
+
+        def _update_llm_config(provider_name, required_key, params, existing_models):
+            required_value = params.get(required_key)
+            if not required_value:
+                raise ValueError(f"{required_key} is required to save configuration.")
+
+            # Check if model already exists, update it and move it to the last;
+            # otherwise, append the new one.
+            models = [
+                cfg for cfg in existing_models if not (
+                    cfg.get("provider") == provider_name and cfg.get(required_key) == required_value)]
+            models.append({"provider": provider_name, **params})
+            return models
+
+        # To be consistent, we expose DEPLOYMENT_NAME for Azure provider in both configuration file and init prompts.
+        if provider_name.lower() == "azure":
+            configs["llms"] = _update_llm_config(provider_name, "DEPLOYMENT_NAME", params, models)
+        else:
+            configs["llms"] = _update_llm_config(provider_name, "MODEL_NAME", params, models)
 
         with open(self.config_path, "w") as f:
             yaml.safe_dump(configs, f, sort_keys=False)
@@ -112,14 +128,16 @@ def get_specific(
         """
         model_configs = self.get_list()
         for cfg in model_configs:
-            if cfg.get("provider") == provider_name and cfg.get(
-                    "MODEL_NAME") == model_name:
+            if cfg.get("provider") == provider_name and provider_name.lower() == "azure":
+                if cfg.get("DEPLOYMENT_NAME") == model_name or cfg.get("MODEL_NAME") == model_name:
+                    return cfg
+            if cfg.get("provider") == provider_name and cfg.get("MODEL_NAME") == model_name:
                 return cfg
         return None
 
     def get_model_config(self, model) -> Optional[Dict]:
         prompt_for_init = "Run 'az aks agent-init' to set up your LLM endpoint (recommended path).\n" \
-            "To configure your LLM manually, create a config file using the templates provided here: "\
+            "To configure your LLM manually, create a config file using the templates provided here: " \
             "https://aka.ms/aks/agentic-cli/init"
 
         if not model:
@@ -147,3 +165,23 @@ def is_config_complete(self, config, provider_schema):
                     config.get(key)):
                 return False
         return True
+
+    def export_model_config(self, llm_config) -> str:
+        # Check if the configuration is complete
+        provider_name = llm_config.get("provider")
+        provider_instance = PROVIDER_REGISTRY.get(provider_name)()
+        # NOTE(mainred) for backward compatibility with Azure OpenAI, replace the MODEL_NAME with DEPLOYMENT_NAME
+        if provider_name.lower() == "azure" and "MODEL_NAME" in llm_config:
+            llm_config["DEPLOYMENT_NAME"] = llm_config.pop("MODEL_NAME")
+
+        model_name_key = "MODEL_NAME" if provider_name.lower() != "azure" else "DEPLOYMENT_NAME"
+        model = provider_instance.model_name(llm_config.get(model_name_key))
+
+        # Set environment variables for the model provider
+        for k, v in llm_config.items():
+            if k not in ["provider", "MODEL_NAME", "DEPLOYMENT_NAME"]:
+                os.environ[k] = v
+        logger.info(
+            "Using provider: %s, model: %s, Env vars setup successfully.", provider_name, llm_config.get("MODEL_NAME"))
+
+        return model

src/aks-agent/azext_aks_agent/agent/llm_providers/__init__.py

@@ -5,6 +5,7 @@
 
 from typing import List, Tuple
 
+from azext_aks_agent._consts import ERROR_COLOR, HELP_COLOR
 from rich.console import Console
 
 from .anthropic_provider import AnthropicProvider
@@ -47,7 +48,6 @@ def _get_provider_by_index(idx: int) -> LLMProvider:
     Return provider instance by numeric index (1-based).
     Raises ValueError if index is out of range.
     """
-    from holmes.utils.colors import HELP_COLOR
     if 1 <= idx <= len(_PROVIDER_CLASSES):
         console.print("You selected provider:", _PROVIDER_CLASSES[idx - 1]().readable_name, style=f"bold {HELP_COLOR}")
         return _PROVIDER_CLASSES[idx - 1]()
@@ -59,7 +59,6 @@ def prompt_provider_choice() -> LLMProvider:
     Show a numbered menu and return the chosen provider instance.
     Keeps prompting until a valid selection is made.
     """
-    from holmes.utils.colors import ERROR_COLOR, HELP_COLOR
     choices = _provider_choices_numbered()
     if not choices:
         raise ValueError("No providers are registered.")

src/aks-agent/azext_aks_agent/agent/llm_providers/azure_provider.py

@@ -32,10 +32,10 @@ def model_route(self) -> str:
     @property
     def parameter_schema(self):
         return {
-            "MODEL_NAME": {
+            "DEPLOYMENT_NAME": {
                 "secret": False,
                 "default": None,
-                "hint": "should be consistent with your deployed name, e.g., gpt-5",
+                "hint": "ensure your deployment name is the same as the model name, e.g., gpt-5",
                 "validator": non_empty
             },
             "AZURE_API_KEY": {
@@ -62,19 +62,19 @@ def validate_connection(self, params: dict) -> Tuple[bool, str, str]:
         api_key = params.get("AZURE_API_KEY")
         api_base = params.get("AZURE_API_BASE")
         api_version = params.get("AZURE_API_VERSION")
-        model_name = params.get("MODEL_NAME")
+        deployment_name = params.get("DEPLOYMENT_NAME")
 
-        if not all([api_key, api_base, api_version, model_name]):
+        if not all([api_key, api_base, api_version, deployment_name]):
             return False, "Missing required Azure parameters.", "retry_input"
 
         # REST API reference: https://learn.microsoft.com/en-us/azure/ai-foundry/openai/api-version-lifecycle?tabs=rest
-        url = urljoin(api_base, f"openai/deployments/{model_name}/chat/completions")
+        url = urljoin(api_base, f"openai/deployments/{deployment_name}/chat/completions")
 
         query = {"api-version": api_version}
         full_url = f"{url}?{urlencode(query)}"
         headers = {"Authorization": f"Bearer {api_key}", "Content-Type": "application/json"}
         payload = {
-            "model": model_name,
+            "model": deployment_name,
             "messages": [{"role": "user", "content": "ping"}],
             "max_tokens": 16
         }

src/aks-agent/azext_aks_agent/agent/llm_providers/base.py

@@ -8,6 +8,7 @@
 from typing import Any, Callable, Dict, Tuple
 from urllib.parse import urlparse
 
+from azext_aks_agent._consts import ERROR_COLOR, HELP_COLOR
 from rich.console import Console
 
 console = Console()
@@ -85,9 +86,6 @@ def parameter_schema(self) -> Dict[str, Dict[str, Any]]:
 
     def prompt_params(self):
         """Prompt user for parameters using parameter_schema when available."""
-        from holmes.interactive import SlashCommands
-        from holmes.utils.colors import ERROR_COLOR, HELP_COLOR
-
         schema = self.parameter_schema
         params = {}
         for param, meta in schema.items():
@@ -134,7 +132,7 @@ def prompt_params(self):
                     params[param] = value
                     break
                 console.print(
-                    f"Invalid value for {param}. Please try again, or type '{SlashCommands.EXIT.command}' to exit.",
+                    f"Invalid value for {param}. Please try again, or type '/exit' to exit.",
                     style=f"{ERROR_COLOR}")
 
         return params

src/aks-agent/azext_aks_agent/custom.py

@@ -5,15 +5,12 @@
 
 import os
 
-from azext_aks_agent._consts import CONST_AGENT_CONFIG_FILE_NAME
+from azext_aks_agent._consts import CONST_AGENT_CONFIG_FILE_NAME, HELP_COLOR
 
 # pylint: disable=too-many-lines, disable=broad-except
 from azext_aks_agent.agent.agent import aks_agent as aks_agent_internal
 from azext_aks_agent.agent.llm_config_manager import LLMConfigManager
-from azext_aks_agent.agent.llm_providers import (
-    PROVIDER_REGISTRY,
-    prompt_provider_choice,
-)
+from azext_aks_agent.agent.llm_providers import prompt_provider_choice
 from azext_aks_agent.agent.logging import rich_logging
 from azure.cli.core.api import get_config_dir
 from azure.cli.core.azclierror import AzCLIError
@@ -25,29 +22,28 @@
 # pylint: disable=unused-argument
 def aks_agent_init(cmd):
     """Initialize AKS agent llm configuration."""
+    from rich.console import Console
+    console = Console()
+    console.print(
+        "Welcome to AKS Agent LLM configuration setup. Type '/exit' to exit.",
+        style=f"bold {HELP_COLOR}")
 
-    with rich_logging() as console:
-        from holmes.utils.colors import HELP_COLOR
-        console.print(
-            "Welcome to AKS Agent LLM configuration setup. Type '/exit' to exit.",
-            style=f"bold {HELP_COLOR}")
-
-        provider = prompt_provider_choice()
-        params = provider.prompt_params()
+    provider = prompt_provider_choice()
+    params = provider.prompt_params()
 
-        llm_config_manager = LLMConfigManager()
-        # If the connection to the model endpoint is valid, save the configuration
-        is_valid, msg, action = provider.validate_connection(params)
+    llm_config_manager = LLMConfigManager()
+    # If the connection to the model endpoint is valid, save the configuration
+    is_valid, msg, action = provider.validate_connection(params)
 
-        if is_valid and action == "save":
-            llm_config_manager.save(provider.model_route if provider.model_route else "openai", params)
-            console.print(
-                f"LLM configuration setup successfully and is saved to {llm_config_manager.config_path}.",
-                style=f"bold {HELP_COLOR}")
-        elif not is_valid and action == "retry_input":
-            raise AzCLIError(f"Please re-run `az aks agent-init` to correct the input parameters. {str(msg)}")
-        else:
-            raise AzCLIError(f"Please check your deployed model and network connectivity. {str(msg)}")
+    if is_valid and action == "save":
+        llm_config_manager.save(provider.model_route if provider.model_route else "openai", params)
+        console.print(
+            f"LLM configuration setup successfully and is saved to {llm_config_manager.config_path}.",
+            style=f"bold {HELP_COLOR}")
+    elif not is_valid and action == "retry_input":
+        raise AzCLIError(f"Please re-run `az aks agent-init` to correct the input parameters. {str(msg)}")
+    else:
+        raise AzCLIError(f"Please check your deployed model and network connectivity. {str(msg)}")
 
 
 # pylint: disable=unused-argument
@@ -81,18 +77,7 @@ def aks_agent(
     llm_config_manager = LLMConfigManager(config_file)
     llm_config_manager.validate_config()
     llm_config = llm_config_manager.get_model_config(model)
-
-    # Check if the configuration is complete
-    provider_name = llm_config.get("provider")
-    provider_instance = PROVIDER_REGISTRY.get(provider_name)()
-    model = provider_instance.model_name(llm_config.get("MODEL_NAME"))
-
-    # Set environment variables for the model provider
-    for k, v in llm_config.items():
-        if k not in ["provider", "MODEL_NAME"]:
-            os.environ[k] = v
-    logger.info(
-        "Using provider: %s, model: %s, Env vars setup successfully.", provider_name, llm_config.get("MODEL_NAME"))
+    llm_config_manager.export_model_config(llm_config)
 
     with rich_logging():
         aks_agent_internal(