feat(agent): refactor LLM configuration to support new llm_model_configs system

- Remove direct logging of LLM config from gns3_copilot.py
- Update model_factory to accept configuration from llm_model_configs dictionary
- Add fallback to environment variables for backward compatibility
- Centralize configuration loading in _load_llm_config function

gns3server/agent/gns3_copilot/agent/gns3_copilot.py

@@ -63,23 +63,12 @@ from gns3_copilot.tools_v2 import (
     LinuxTelnetBatchTool,
     VPCSMultiCommands,
 )
-from gns3_copilot.utils import get_config
 
 # Set up logger for FlowNet-Lab
 logger = logging.getLogger(__name__)
 
-# Log loaded LLM model information
-model_name = get_config("MODEL_NAME")
-model_provider = get_config("MODE_PROVIDER")
-base_url = get_config("BASE_URL", "")
-temperature = get_config("TEMPERATURE", "0")
-logger.info(
-    "LLM model configuration: name=%s, provider=%s, base_url=%s, temperature=%s",
-    model_name,
-    model_provider,
-    base_url,
-    temperature,
-)
+# Note: LLM model configuration is now managed by the new llm_model_configs system.
+# The model_factory module handles model creation with configuration from the database.
 
 # Define the available tools for the agent
 tools = [

gns3server/agent/gns3_copilot/agent/model_factory.py

@@ -1,35 +1,50 @@
 """
 Model Factory for FlowNet-Lab Agent
 
-This module provides factory functions to create fresh LLM model instances
-on-demand from SQLite configuration. This allows configuration changes
-to take effect without restarting the application.
+This module provides factory functions to create fresh LLM model instances.
+Configuration can be loaded from:
+1. Passed llm_config dictionary (from new llm_model_configs system)
+2. Environment variables (fallback for backward compatibility)
 """
 
 import logging
-from typing import Any
+import os
+from typing import Any, Optional
 
 from langchain.chat_models import init_chat_model
 
-from gns3_copilot.utils import get_config
-
 logger = logging.getLogger(__name__)
 
 
-def _load_env_variables() -> dict[str, str]:
+def _load_llm_config(llm_config: Optional[dict[str, Any]] = None) -> dict[str, str]:
     """
-    Load model configuration from SQLite database.
+    Load model configuration from llm_config dict or environment variables.
+
+    Args:
+        llm_config: Optional configuration dictionary from llm_model_configs system.
+                    If not provided, will load from environment variables.
 
     Returns:
         Dictionary containing model configuration.
     """
-    return {
-        "model_name": get_config("MODEL_NAME", ""),
-        "model_provider": get_config("MODE_PROVIDER", ""),
-        "api_key": get_config("MODEL_API_KEY", ""),
-        "base_url": get_config("BASE_URL", ""),
-        "temperature": get_config("TEMPERATURE", "0"),
-    }
+    if llm_config:
+        # Use provided configuration (from llm_model_configs system)
+        return {
+            "model_name": llm_config.get("model", ""),
+            "model_provider": llm_config.get("provider", ""),
+            "api_key": llm_config.get("api_key", ""),
+            "base_url": llm_config.get("base_url", ""),
+            "temperature": str(llm_config.get("temperature", "0")),
+        }
+    else:
+        # Fallback to environment variables
+        return {
+            "model_name": os.getenv("MODEL_NAME", ""),
+            "model_provider": os.getenv("MODE_PROVIDER", ""),
+            "api_key": os.getenv("MODEL_API_KEY", ""),
+            "base_url": os.getenv("BASE_URL", ""),
+            "temperature": os.getenv("TEMPERATURE", "0"),
+        }
 
 
 def create_base_model() -> Any:
@@ -46,7 +61,7 @@ def create_base_model() -> Any:
     Raises:
         ValueError: If required environment variables are missing or invalid.
     """
-    env_vars = _load_env_variables()
+    env_vars = _load_llm_config()
 
     # Log the loaded configuration (mask sensitive data)
     logger.info(
@@ -98,7 +113,7 @@ def create_title_model() -> Any:
     Raises:
         ValueError: If required environment variables are missing or invalid.
     """
-    env_vars = _load_env_variables()
+    env_vars = _load_llm_config()
 
     logger.info(
         "Creating title model: name=%s, provider=%s, base_url=%s, temperature=1.0",
@@ -174,7 +189,7 @@ def create_note_organizer_model() -> Any:
     Raises:
         ValueError: If required environment variables are missing or invalid.
     """
-    env_vars = _load_env_variables()
+    env_vars = _load_llm_config()
 
     logger.info(
         "Creating note organizer model: name=%s, provider=%s, base_url=%s, temperature=0.3",
@@ -245,7 +260,7 @@ def create_window_agent_base_model() -> Any:
         ValueError: If required environment variables are missing.
         RuntimeError: If model creation fails.
     """
-    env_vars = _load_env_variables()
+    env_vars = _load_llm_config()
 
     logger.info(
         "Creating Window Agent base model: name=%s, provider=%s, base_url=%s, temperature=0",
@@ -298,7 +313,7 @@ def create_window_agent_model_with_tools(tools: list[Any]) -> Any:
         ValueError: If required environment variables are missing.
         RuntimeError: If model creation or tool binding fails.
     """
-    env_vars = _load_env_variables()
+    env_vars = _load_llm_config()
 
     logger.info(
         "Creating Window Agent model: name=%s, provider=%s, base_url=%s, temperature=0",
@@ -351,7 +366,7 @@ def create_experiment_planner_model() -> Any:
     Raises:
         ValueError: If required environment variables are missing or invalid.
     """
-    env_vars = _load_env_variables()
+    env_vars = _load_llm_config()
 
     logger.info(
         "Creating experiment planner model: name=%s, provider=%s, base_url=%s, temperature=0.7",
@@ -428,7 +443,7 @@ def create_presentation_eval_model() -> Any:
         ValueError: If required environment variables are missing.
         RuntimeError: If model creation fails.
     """
-    env_vars = _load_env_variables()
+    env_vars = _load_llm_config()
 
     logger.info(
         "Creating presentation evaluator model: name=%s, provider=%s, base_url=%s, temperature=0.5",

gns3server/agent/gns3_copilot/agent/qwen_vision_model.py

@@ -7,6 +7,7 @@ through DashScope SDK to identify network topology diagrams from images.
 
 import base64
 import json
+import os
 from typing import Any, Dict, Optional
 from pathlib import Path
 
@@ -17,8 +18,6 @@ except ImportError:
 
 import logging
 
-from gns3_copilot.utils import get_config
-
 logger = logging.getLogger(__name__)
 
 
@@ -161,13 +160,13 @@ class QwenVisionModel:
                 "Please install it: pip install dashscope"
             )
 
-        # Load API key from config if not provided
+        # Load API key from environment variable if not provided
         if api_key is None:
-            api_key = get_config("QWEN_API_KEY", "")
+            api_key = os.getenv("QWEN_API_KEY", "")
 
         if not api_key:
             raise ValueError(
-                "Qwen API key is required. Please set QWEN_API_KEY in configuration "
+                "Qwen API key is required. Please set QWEN_API_KEY environment variable "
                 "or pass it to the constructor."
             )
 
@@ -389,19 +388,19 @@ def create_qwen_vision_model(
     """
     Factory function to create a Qwen-VL vision model instance.
 
-    This function loads configuration from the database and creates
+    This function loads configuration from environment variables and creates
     a QwenVisionModel instance with appropriate settings.
 
     Args:
-        api_key: DashScope API key (if None, will load from config)
-        model_name: Model name to use (if None, will load from config, default: qwen3-vl-plus)
+        api_key: DashScope API key (if None, will load from QWEN_API_KEY env var)
+        model_name: Model name to use (if None, will load from QWEN_MODEL_NAME env var, default: qwen3-vl-plus)
 
     Returns:
         QwenVisionModel instance
 
     Raises:
         ImportError: If dashscope is not installed
-        ValueError: If API key is not provided or found in config
+        ValueError: If API key is not provided or found in environment
 
     Example:
         >>> model = create_qwen_vision_model()
@@ -409,8 +408,8 @@ def create_qwen_vision_model(
         >>> print(topology["topology_name"])
         >>> print(f"Found {len(topology['devices'])} devices")
     """
-    # Load model name from config if not provided
+    # Load model name from environment variable if not provided
     if model_name is None:
-        model_name = get_config("QWEN_MODEL_NAME", "qwen3-vl-plus")
+        model_name = os.getenv("QWEN_MODEL_NAME", "qwen3-vl-plus")
 
     return QwenVisionModel(api_key=api_key, model_name=model_name)