fix: configuration refresh

runtime/launch.py

@@ -1,6 +1,6 @@
 from typing_extensions import Literal
 from fastapi import FastAPI, HTTPException, Request
-from pydantic import BaseModel, Field, root_validator
+from pydantic import BaseModel, model_validator
 from typing import Optional, Dict, Any, Union
 from dotenv import load_dotenv
 import traceback
@@ -34,11 +34,6 @@
 
 import uvicorn
 
-# from cerebrum.llm.layer import LLMLayer as LLMConfig
-# from cerebrum.memory.layer import MemoryLayer as MemoryConfig
-# from cerebrum.storage.layer import StorageLayer as StorageConfig
-# from cerebrum.tool.layer import ToolLayer as ToolManagerConfig
-
 load_dotenv()
 
 app = FastAPI()
@@ -52,6 +47,7 @@
 )
 
 # Store component configurations and instances
+global active_components 
 active_components = {
     "llm": None,
     "storage": None,
@@ -113,28 +109,31 @@ class QueryRequest(BaseModel):
     query_type: Literal["llm", "tool", "storage", "memory"]
     query_data: LLMQuery | ToolQuery | StorageQuery | MemoryQuery
 
-    @root_validator(pre=True)
-    def convert_query_data(cls, values: dict[str, Any]) -> dict[str, Any]:
-        if 'query_type' not in values or 'query_data' not in values:
-            return values
-
-        query_type = values['query_type']
-        query_data = values['query_data']
-
-        type_mapping = {
-            'llm': LLMQuery,
-            'tool': ToolQuery,
-            'storage': StorageQuery,
-            'memory': MemoryQuery
-        }
-
-        if isinstance(query_data, type_mapping[query_type]):
-            return values
-
-        if isinstance(query_data, dict):
-            values['query_data'] = type_mapping[query_type](**query_data)
-
-        return values
+    @model_validator(mode='before')
+    def convert_query_data(cls, data: Any) -> Any:
+        if isinstance(data, dict):
+            query_type = data.get('query_type')
+            query_data = data.get('query_data')
+
+            if not query_type or not query_data:
+                return data
+
+            type_mapping = {
+                'llm': LLMQuery,
+                'tool': ToolQuery,
+                'storage': StorageQuery,
+                'memory': MemoryQuery
+            }
+
+            target_type = type_mapping.get(query_type)
+            if target_type and isinstance(query_data, dict) and not isinstance(query_data, target_type):
+                try:
+                    data['query_data'] = target_type(**query_data)
+                except Exception as e:
+                    # Handle potential validation errors if needed
+                    # For now, just pass the original data
+                    pass
+        return data
 
 def initialize_llm_cores(config: dict) -> Any:
     """Initialize LLM core with configuration."""
@@ -331,8 +330,8 @@ def restart_kernel():
 
         # Initialize new components
         active_components = initialize_components()
-        # if not initialize_components():
-        #     raise Exception("Failed to initialize components")
+        if not active_components:
+            raise Exception("Failed to initialize components")
 
         print("✅ All components reinitialized successfully")
 
@@ -345,11 +344,11 @@ def restart_kernel():
 async def refresh_configuration():
     """Refresh all component configurations"""
     try:
-        print("Received refresh request")
+        logger.info("Received refresh request")
         config.refresh()
-        print("Configuration reloaded")
+        logger.info("Configuration reloaded")
         restart_kernel()
-        print("Kernel restarted")
+        logger.info("Kernel restarted")
         return {
             "status": "success", 
             "message": "Configuration refreshed and components reinitialized"
@@ -472,12 +471,12 @@ async def submit_agent(config: AgentSubmit):
             config=config.agent_config
         )
 
-
         return {
             "status": "success",
             "execution_id": execution_id,
             "message": f"Agent {config.agent_id} submitted for execution"
         }
+
     except Exception as e:
         error_msg = str(e)
         stack_trace = traceback.format_exc()
@@ -609,14 +608,31 @@ async def update_config(request: Request):
         data = await request.json()
         logger.info(f"Received config update request: {data}")
 
+        name = data.get("name")
         provider = data.get("provider")
         api_key = data.get("api_key")
 
         if not all([provider, api_key]):
             raise ValueError("Missing required fields: provider, api_key")
 
-        # Update configuration
-        config.config["api_keys"][provider] = api_key
+        config.config["llms"]["models"] = [
+            {
+                "name": name,
+                "backend": provider,
+                # API key is better stored in api_keys section
+            }
+        ]
+
+        # Update API keys section if api_key is provided
+        if api_key:
+            if "api_keys" not in config.config:
+                config.config["api_keys"] = {}
+            config.config["api_keys"][provider] = api_key # Use backend name as the key
+
+
+        else:
+            raise ValueError("Missing required fields: api_key")
+
         config.save_config()
 
         # Try to reinitialize LLM component