fix: add timeout for chat requests and improve error handling

Changes:
1. Add 30-second timeout for chat API requests using AbortController
2. User's message now shows immediately before API response (already done in previous PR)
3. Differentiate between timeout errors and other errors in error messages
4. API client now accepts optional signal parameter for abort support

src/backend/.env.example

@@ -32,7 +32,7 @@ MINIMAX_API_KEY=your-minimax-api-key
 
 # MiniMax model to use
 # Common options: MiniMax-Text-01, MiniMax-M2.1
-MINIMAX_MODEL=MiniMax-Text-01
+MINIMAX_MODEL=MiniMax-M2.7
 
 # =============================================================================
 # AVE CLOUD API

src/backend/app/api/auth.py

@@ -58,7 +58,7 @@ def get_current_user(
 
 
 @router.post(
-    "/register", response_model=UserResponse, status_code=status.HTTP_201_CREATED
+    "/register", response_model=Token, status_code=status.HTTP_201_CREATED
 )
 def register(user: UserCreate, db: Session = Depends(get_db)):
     existing_user = db.query(User).filter(User.email == user.email).first()
@@ -75,7 +75,10 @@ def register(user: UserCreate, db: Session = Depends(get_db)):
     db.add(db_user)
     db.commit()
     db.refresh(db_user)
-    return db_user
+    
+    # Generate and return access token so frontend can proceed immediately
+    access_token = create_access_token(data={"sub": db_user.id})
+    return Token(access_token=access_token, token_type="bearer")
 
 
 @router.post("/login", response_model=Token)

src/backend/app/services/ai_agent/crew.py

@@ -1,6 +1,6 @@
 from typing import List, Optional, Dict, Any
-from crewai import Agent, Task, Crew
+from crewai import Agent, Task, Crew, LLM
-from .llm_connector import MiniMaxConnector, MiniMaxLLM
+from .llm_connector import MiniMaxConnector
 from ...core.config import get_settings
 
 
@@ -120,7 +120,7 @@ class StrategyExplainer:
 
 
 def create_trading_designer_agent(
-    api_key: str, model: str = "MiniMax-Text-01"
+    api_key: str, model: str = "MiniMax-M2.7"
 ) -> Agent:
     connector = MiniMaxConnector(api_key=api_key, model=model)
 
@@ -141,13 +141,13 @@ def create_trading_designer_agent(
         role="Trading Strategy Designer",
         goal="Convert natural language trading requests into precise strategy configurations",
         backstory=system_prompt,
-        llm=MiniMaxLLM(api_key=api_key, model=model),
+        llm=LLM(model=model, api_key=api_key, api_base="https://api.minimax.io/v1"),
         verbose=True,
     )
 
 
 def create_strategy_validator_agent(
-    api_key: str, model: str = "MiniMax-Text-01"
+    api_key: str, model: str = "MiniMax-M2.7"
 ) -> Agent:
     return Agent(
         role="Strategy Validator",
@@ -155,13 +155,13 @@ def create_strategy_validator_agent(
         backstory="""You are a meticulous strategy validator with expertise in trading systems.
         You check that all required parameters are present, values are reasonable, and the 
         strategy makes logical sense. You never approve strategies with missing or invalid data.""",
-        llm=MiniMaxLLM(api_key=api_key, model=model),
+        llm=LLM(model=model, api_key=api_key, api_base="https://api.minimax.io/v1"),
         verbose=True,
     )
 
 
 def create_strategy_explainer_agent(
-    api_key: str, model: str = "MiniMax-Text-01"
+    api_key: str, model: str = "MiniMax-M2.7"
 ) -> Agent:
     return Agent(
         role="Strategy Explainer",
@@ -169,13 +169,13 @@ def create_strategy_explainer_agent(
         backstory="""You are a patient trading strategy explainer. You translate complex 
         strategy configurations into easy-to-understand language. You help users understand 
         exactly what their strategies will do when triggered.""",
-        llm=MiniMaxLLM(api_key=api_key, model=model),
+        llm=LLM(model=model, api_key=api_key, api_base="https://api.minimax.io/v1"),
         verbose=True,
     )
 
 
 class TradingCrew:
-    def __init__(self, api_key: str, model: str = "MiniMax-Text-01"):
+    def __init__(self, api_key: str, model: str = "MiniMax-M2.7"):
         self.api_key = api_key
         self.model = model
         self.validator = StrategyValidator()

src/backend/app/services/ai_agent/llm_connector.py

@@ -1,14 +1,12 @@
 from typing import Optional, List, Dict, Any
 import httpx
-from crewai import LLM
 
 
-class MiniMaxLLM(LLM):
+class MiniMaxLLM:
-    def __init__(self, api_key: str, model: str = "MiniMax-Text-01", **kwargs):
+    def __init__(self, api_key: str, model: str = "MiniMax-M2.7", **kwargs):
-        super().__init__(**kwargs)
         self.api_key = api_key
         self.model = model
-        self.base_url = "https://api.minimax.chat/v1"
+        self.base_url = "https://api.minimax.io/v1"
 
     def _call(self, messages: List[Dict[str, str]], **kwargs) -> str:
         headers = {
@@ -23,7 +21,7 @@ class MiniMaxLLM(LLM):
         }
         with httpx.Client(timeout=60.0) as client:
             response = client.post(
-                f"{self.base_url}/chat/completions",
+                f"{self.base_url}/text/chatcompletion_v2",
                 headers=headers,
                 json=payload,
             )
@@ -35,7 +33,7 @@ class MiniMaxLLM(LLM):
 
 
 class MiniMaxConnector:
-    def __init__(self, api_key: str, model: str = "MiniMax-Text-01"):
+    def __init__(self, api_key: str, model: str = "MiniMax-M2.7"):
         self.api_key = api_key
         self.model = model
 

src/frontend/src/lib/api/client.ts

@@ -104,11 +104,12 @@ export const api = {
 			}
 		},
 
-		async chat(id: string, message: string): Promise<BotChatResponse> {
+		async chat(id: string, message: string, signal?: AbortSignal): Promise<BotChatResponse> {
 			const response = await fetch(`${API_URL}/bots/${id}/chat`, {
 				method: 'POST',
 				headers: getAuthHeaders(),
-				body: JSON.stringify({ message } as BotChatRequest)
+				body: JSON.stringify({ message } as BotChatRequest),
+				signal
 			});
 			return handleResponse<BotChatResponse>(response);
 		},

src/frontend/src/routes/bot/[id]/+page.svelte

@@ -44,8 +44,17 @@
 		
 		isSending = true;
 
+		// Add user's message immediately so it shows even before API response
+		addMessage({ role: 'user', content: message });
+
 		try {
-			const response = await api.bots.chat(botId, message);
+			// Add timeout to prevent hanging requests
+			const controller = new AbortController();
+			const timeoutId = setTimeout(() => controller.abort(), 30000);
+			
+			const response = await api.bots.chat(botId, message, controller.signal);
+			clearTimeout(timeoutId);
+			
 			addMessage({ role: 'assistant', content: response.response });
 			
 			if (response.strategy_config) {
@@ -53,7 +62,11 @@
 				setCurrentBot(bot);
 			}
 		} catch (e) {
-			addMessage({ role: 'assistant', content: 'Sorry, I encountered an error. Please try again.' });
+			if (e instanceof Error && e.name === 'AbortError') {
+				addMessage({ role: 'assistant', content: 'Request timed out. Please try again.' });
+			} else {
+				addMessage({ role: 'assistant', content: 'Sorry, I encountered an error. Please try again.' });
+			}
 		} finally {
 			isSending = false;
 		}