fix: Also fix price_change field in AI tool execution path

There was duplicate code handling search_tokens in the AI tool calling section.

.gitmodules

@@ -0,0 +1,3 @@
+[submodule "ave-cloud-skill"]
+	path = ave-cloud-skill
+	url = https://github.com/AveCloud/ave-cloud-skill.git

deployment/scripts/nginx-template.conf

@@ -34,6 +34,9 @@ server {
         proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
         proxy_set_header X-Forwarded-Proto $scheme;
         proxy_cache_bypass $http_upgrade;
+        proxy_read_timeout 300s;
+        proxy_connect_timeout 75s;
+        proxy_send_timeout 300s;
     }
 
     location /ws/ {

deployment/scripts/systemd-template.service

@@ -10,6 +10,8 @@ Environment="PATH=/var/www/bot/src/backend/venv/bin"
 ExecStart=/var/www/bot/src/backend/venv/bin/python /var/www/bot/src/backend/run.py
 Restart=always
 RestartSec=10
+TimeoutStartSec=300
+TimeoutStopSec=300
 
 EnvironmentFile=/var/www/bot/data/.env
 

docs/ISSUES.md

@@ -0,0 +1,27 @@
+# Open Issues
+
+## Frontend
+
+### Token Address Confirmation Dialog
+- **Priority**: High
+- **Status**: Open
+- **Description**: When user configures a trading strategy via chat and mentions a token (e.g., "buy PEPE"), the AI asks for the token contract address. The frontend should show a confirmation dialog allowing user to:
+  1. See the token the AI detected (PEPE)
+  2. Enter/confirm the BSC contract address
+  3. Save the strategy with the confirmed address
+
+**Related Files**:
+- Frontend: `src/frontend/src/routes/bot/[id]/+page.svelte`
+- Backend: `src/backend/app/services/ai_agent/conversational.py`
+
+**Acceptance Criteria**:
+- [ ] Modal/dialog appears when AI detects a token without address
+- [ ] User can enter the contract address (0x...)
+- [ ] Strategy is saved only after user confirmation
+- [ ] Clear error handling if address is invalid
+
+---
+
+## Backend
+
+*No open backend issues*

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

@@ -1,5 +1,5 @@
 from fastapi import APIRouter, Depends, HTTPException, status, Request
-from fastapi.security import OAuth2PasswordBearer, OAuth2PasswordRequestForm
+from fastapi.security import OAuth2PasswordBearer
 from sqlalchemy.orm import Session
 from typing import Annotated
 
@@ -14,6 +14,7 @@ from ..core.config import get_settings
 from ..core.limiter import limiter
 from ..db.schemas import (
     UserCreate,
+    LoginRequest,
     UserResponse,
     Token,
     UserSettings,
@@ -58,7 +59,7 @@ 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()
@@ -75,18 +76,21 @@ 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)
 @limiter.limit("5/minute")
 def login(
     request: Request,
-    form_data: Annotated[OAuth2PasswordRequestForm, Depends()],
+    login_data: LoginRequest,
     db: Session = Depends(get_db),
 ):
-    user = db.query(User).filter(User.email == form_data.username).first()
+    user = db.query(User).filter(User.email == login_data.username).first()
-    if not user or not verify_password(form_data.password, user.password_hash):
+    if not user or not verify_password(login_data.password, user.password_hash):
         raise HTTPException(
             status_code=status.HTTP_401_UNAUTHORIZED,
             detail="Incorrect email or password",

src/backend/app/api/backtest.py

@@ -22,6 +22,7 @@ def run_backtest_sync(
     backtest_id: str, db_url: str, bot_id: str, config: Dict[str, Any]
 ):
     import asyncio
+    import json
     from ..services.backtest.engine import BacktestEngine
     from ..core.database import SessionLocal
 
@@ -31,6 +32,19 @@ def run_backtest_sync(
         running_backtests[backtest_id] = engine
         try:
             results = await engine.run()
+            
+            # Convert datetime objects to ISO strings for JSON serialization
+            def convert_datetime(obj):
+                if isinstance(obj, datetime):
+                    return obj.isoformat()
+                elif isinstance(obj, dict):
+                    return {k: convert_datetime(v) for k, v in obj.items()}
+                elif isinstance(obj, list):
+                    return [convert_datetime(i) for i in obj]
+                return obj
+            
+            results = convert_datetime(results)
+            
             db = SessionLocal()
             try:
                 backtest = db.query(Backtest).filter(Backtest.id == backtest_id).first()
@@ -41,17 +55,18 @@ def run_backtest_sync(
                     db.commit()
 
                 for signal in engine.signals:
+                    signal_data = convert_datetime(signal)
                     db_signal = Signal(
-                        id=signal["id"],
+                        id=signal_data["id"],
-                        bot_id=signal["bot_id"],
+                        bot_id=signal_data["bot_id"],
-                        run_id=signal["run_id"],
+                        run_id=signal_data["run_id"],
-                        signal_type=signal["signal_type"],
+                        signal_type=signal_data["signal_type"],
-                        token=signal["token"],
+                        token=signal_data["token"],
-                        price=signal["price"],
+                        price=signal_data["price"],
-                        confidence=signal.get("confidence"),
+                        confidence=signal_data.get("confidence"),
-                        reasoning=signal.get("reasoning"),
+                        reasoning=signal_data.get("reasoning"),
-                        executed=signal.get("executed", False),
+                        executed=signal_data.get("executed", False),
-                        created_at=signal["created_at"],
+                        created_at=signal["created_at"],  # Use original datetime, not converted string
                     )
                     db.add(db_signal)
                 db.commit()
@@ -154,9 +169,81 @@ def get_backtest(
             status_code=status.HTTP_404_NOT_FOUND, detail="Backtest not found"
         )
 
+    # Add progress from running engine if available
+    if backtest.status == "running" and run_id in running_backtests:
+        engine = running_backtests[run_id]
+        backtest.progress = engine.progress
+    
     return backtest
 
 
+@router.get("/bots/{bot_id}/backtest/{run_id}/trades")
+def get_backtest_trades(
+    bot_id: str,
+    run_id: str,
+    page: int = 1,
+    per_page: int = 5,
+    current_user: User = Depends(get_current_user),
+    db: Session = Depends(get_db),
+):
+    """Get paginated trade history for a specific backtest.
+    
+    Args:
+        page: Page number (1-indexed)
+        per_page: Number of trades per page (default 5, max 20)
+    """
+    bot = db.query(Bot).filter(Bot.id == bot_id).first()
+    if not bot:
+        raise HTTPException(
+            status_code=status.HTTP_404_NOT_FOUND, detail="Bot not found"
+        )
+    if bot.user_id != current_user.id:
+        raise HTTPException(
+            status_code=status.HTTP_403_FORBIDDEN, detail="Not authorized"
+        )
+
+    backtest = (
+        db.query(Backtest)
+        .filter(Backtest.id == run_id, Backtest.bot_id == bot_id)
+        .first()
+    )
+    if not backtest:
+        raise HTTPException(
+            status_code=status.HTTP_404_NOT_FOUND, detail="Backtest not found"
+        )
+
+    # Get trades from result
+    result = backtest.result or {}
+    # Handle case where result might be a JSON string
+    if isinstance(result, str):
+        import json
+        result = json.loads(result)
+    all_trades = result.get("trades", []) or []
+    total_trades = len(all_trades)
+    
+    # Validate pagination params
+    per_page = min(max(per_page, 1), 20)  # Clamp between 1 and 20
+    page = max(page, 1)
+    
+    # Calculate pagination
+    total_pages = max(1, (total_trades + per_page - 1) // per_page) if total_trades > 0 else 1
+    start_idx = (page - 1) * per_page
+    end_idx = start_idx + per_page
+    
+    # Get page of trades (return empty list if start_idx >= total_trades)
+    paginated_trades = all_trades[start_idx:end_idx] if start_idx < total_trades else []
+    
+    return {
+        "backtest_id": run_id,
+        "trades": paginated_trades,
+        "total_trades": total_trades,
+        "page": page,
+        "per_page": per_page,
+        "total_pages": total_pages,
+        "has_next": page < total_pages,
+        "has_prev": page > 1,
+    }
+
 @router.get("/bots/{bot_id}/backtests", response_model=List[BacktestResponse])
 def list_backtests(
     bot_id: str,
@@ -177,6 +264,7 @@ def list_backtests(
         db.query(Backtest)
         .filter(Backtest.bot_id == bot_id)
         .order_by(Backtest.started_at.desc())
+        .limit(5)
         .all()
     )
     return backtests
@@ -211,7 +299,12 @@ def stop_backtest(
 
     if run_id in running_backtests:
         engine = running_backtests[run_id]
-        asyncio.create_task(engine.stop())
+        engine.running = False  # Direct sync access to running flag
+        backtest.status = "stopped"
+        backtest.ended_at = datetime.utcnow()
+        db.commit()
+    elif backtest.status == "running":
+        # Engine already finished but status not updated
         backtest.status = "stopped"
         backtest.ended_at = datetime.utcnow()
         db.commit()

src/backend/app/api/bots.py

@@ -16,6 +16,7 @@ from ..db.schemas import (
 )
 from ..db.models import Bot, BotConversation, User
 from ..services.ai_agent.crew import get_trading_crew
+from ..services.ai_agent.conversational import get_conversational_agent
 
 router = APIRouter()
 MAX_BOTS_PER_USER = 3
@@ -183,69 +184,49 @@ def chat(
         .order_by(BotConversation.created_at)
         .all()
     )
-    history_for_crew = [
+    history_for_agent = [
         {"role": conv.role, "content": conv.content}
         for conv in conversation_history[-10:]
     ]
 
     user_message = request.message
-    if request.strategy_config:
-        crew = get_trading_crew()
-        result = crew.chat(user_message, history_for_crew)
     
-        assistant_content = result.get("response", "I couldn't process your request.")
+    # Use ConversationalAgent for natural chat with tool-calling
-        if result.get("success") and result.get("strategy_config"):
+    agent = get_conversational_agent(bot_id=bot_id)
-            bot.strategy_config = result["strategy_config"]
+    result = agent.chat(user_message, history_for_agent)
-            db.commit()
 
-        db_conversation = BotConversation(
+    assistant_content = result.get("response", "I couldn't process your request.")
-            bot_id=bot_id,
-            role="user",
-            content=user_message,
-        )
-        db.add(db_conversation)
 
-        db_assistant = BotConversation(
+    # Save conversation
-            bot_id=bot_id,
+    db_conversation = BotConversation(
-            role="assistant",
+        bot_id=bot_id,
-            content=assistant_content,
+        role="user",
-        )
+        content=user_message,
-        db.add(db_assistant)
+    )
-        db.commit()
+    db.add(db_conversation)
-        db.refresh(db_assistant)
 
-        return BotChatResponse(
+    db_assistant = BotConversation(
-            response=assistant_content,
+        bot_id=bot_id,
-            strategy_config=result.get("strategy_config"),
+        role="assistant",
-            success=result.get("success", False),
+        content=assistant_content,
-        )
+    )
-    else:
+    db.add(db_assistant)
-        crew = get_trading_crew()
+    db.commit()
-        result = crew.chat(user_message, history_for_crew)
+    db.refresh(db_assistant)
 
-        assistant_content = result.get("response", "I couldn't process your request.")
+    # If strategy was updated via tool, refresh bot data
+    if result.get("strategy_updated"):
+        db.refresh(bot)
 
-        db_conversation = BotConversation(
+    return BotChatResponse(
-            bot_id=bot_id,
+        response=assistant_content,
-            role="user",
+        thinking=result.get("thinking"),
-            content=user_message,
+        strategy_config=bot.strategy_config if result.get("strategy_updated") else None,
-        )
+        success=result.get("success", False),
-        db.add(db_conversation)
+        strategy_needs_confirmation=result.get("strategy_needs_confirmation", False),
-
+        strategy_data=result.get("strategy_data") if result.get("strategy_needs_confirmation") else None,
-        db_assistant = BotConversation(
+        token_search_results=result.get("token_search_results"),
-            bot_id=bot_id,
+    )
-            role="assistant",
-            content=assistant_content,
-        )
-        db.add(db_assistant)
-        db.commit()
-        db.refresh(db_assistant)
-
-        return BotChatResponse(
-            response=assistant_content,
-            strategy_config=result.get("strategy_config"),
-            success=result.get("success", False),
-        )
 
 
 @router.get("/{bot_id}/history", response_model=List[BotConversationResponse])

src/backend/app/api/simulate.py

@@ -1,5 +1,6 @@
 import uuid
 import asyncio
+import logging
 from datetime import datetime
 from fastapi import APIRouter, Depends, HTTPException, status, BackgroundTasks
 from sqlalchemy.orm import Session
@@ -11,6 +12,9 @@ from ..core.database import get_db
 from ..core.config import get_settings
 from ..db.schemas import SimulationCreate, SimulationResponse
 from ..db.models import Bot, Simulation, Signal, User
+from ..services.ave.client import AveCloudClient
+
+logger = logging.getLogger(__name__)
 
 router = APIRouter()
 
@@ -22,6 +26,7 @@ def run_simulation_sync(
     simulation_id: str, db_url: str, bot_id: str, config: Dict[str, Any]
 ):
     import asyncio
+    import time
     from ..services.simulate.engine import SimulateEngine
     from ..core.database import SessionLocal
 
@@ -29,8 +34,19 @@ def run_simulation_sync(
         engine = SimulateEngine(config)
         engine.run_id = simulation_id
         running_simulations[simulation_id] = engine
-        try:
+        
-            results = await engine.run()
+        # Serialize signals for JSON storage (convert datetime to string)
+        def serialize_signal(s):
+            created = s.get("created_at")
+            if hasattr(created, "isoformat"):
+                created = created.isoformat()
+            return {
+                **s,
+                "created_at": created
+            }
+        
+        def save_progress():
+            """Save current progress to database."""
             db = SessionLocal()
             try:
                 simulation = (
@@ -38,27 +54,50 @@ def run_simulation_sync(
                 )
                 if simulation:
                     simulation.status = engine.status
-                    simulation.signals = engine.signals
+                    simulation.signals = [serialize_signal(s) for s in engine.signals]
+                    simulation.klines = [
+                        {"time": k.get("time"), "close": k.get("close")}
+                        for k in engine.klines
+                    ]
+                    simulation.trade_log = engine.trade_log
+                    # Save portfolio data
+                    simulation.portfolio = {
+                        "initial_balance": engine.config.get("initial_balance", 10000),
+                        "current_balance": engine.current_balance,
+                        "position": engine.position,
+                        "position_token": engine.position_token,
+                        "entry_price": engine.entry_price,
+                        "current_price": engine.last_close,
+                    }
                     db.commit()
-
-                for signal in engine.signals:
-                    db_signal = Signal(
-                        id=signal["id"],
-                        bot_id=signal["bot_id"],
-                        run_id=signal["run_id"],
-                        signal_type=signal["signal_type"],
-                        token=signal["token"],
-                        price=signal["price"],
-                        confidence=signal.get("confidence"),
-                        reasoning=signal.get("reasoning"),
-                        executed=signal.get("executed", False),
-                        created_at=signal["created_at"],
-                    )
-                    db.add(db_signal)
-                db.commit()
             finally:
                 db.close()
+        
+        async def run_with_progress_save():
+            """Run simulation and save progress periodically."""
+            last_save_time = time.time()
+            save_interval = 5  # Save every 5 seconds
+            
+            while engine.running and engine.status == "running":
+                await asyncio.sleep(1)  # Check every second
+                
+                current_time = time.time()
+                if current_time - last_save_time >= save_interval:
+                    save_progress()
+                    last_save_time = current_time
+            
+            # Final save when done
+            save_progress()
+        
+        try:
+            # Run both simulation and progress saving concurrently
+            await asyncio.gather(
+                engine.run(),
+                run_with_progress_save()
+            )
         finally:
+            # Save final state
+            save_progress()
             if simulation_id in running_simulations:
                 del running_simulations[simulation_id]
 
@@ -87,20 +126,35 @@ async def start_simulation(
             status_code=status.HTTP_403_FORBIDDEN, detail="Not authorized"
         )
 
+    # Check if there's already a running simulation for this bot
+    existing_simulation = (
+        db.query(Simulation)
+        .filter(Simulation.bot_id == bot_id, Simulation.status == "running")
+        .first()
+    )
+    if existing_simulation:
+        # Stop the existing simulation first
+        if existing_simulation.id in running_simulations:
+            running_simulations[existing_simulation.id].stop()
+            del running_simulations[existing_simulation.id]
+        existing_simulation.status = "stopped"
+        db.commit()
+
     settings = get_settings()
     simulation_id = str(uuid.uuid4())
     
-    check_interval = config.check_interval
+    # Create AVE client for klines fetching
-    if settings.AVE_API_PLAN != "pro" and check_interval < 60:
+    ave_client = AveCloudClient(
-        check_interval = 60
+        api_key=settings.AVE_API_KEY,
+        plan=settings.AVE_API_PLAN,
+    )
 
     simulation_config = {
         "bot_id": bot_id,
         "token": config.token,
         "chain": config.chain,
-        "duration_seconds": config.duration_seconds,
+        "kline_interval": config.kline_interval,
-        "check_interval": check_interval,
+        "auto_execute": False,  # Always paper trade
-        "auto_execute": config.auto_execute,
         "strategy_config": bot.strategy_config,
         "ave_api_key": settings.AVE_API_KEY,
         "ave_api_plan": settings.AVE_API_PLAN,
@@ -114,19 +168,46 @@ async def start_simulation(
         config={
             "token": config.token,
             "chain": config.chain,
-            "duration_seconds": config.duration_seconds,
+            "kline_interval": config.kline_interval,
-            "check_interval": check_interval,
-            "auto_execute": config.auto_execute,
         },
         signals=[],
+        klines=[],
     )
     db.add(simulation)
     db.commit()
     db.refresh(simulation)
 
-    db_url = str(settings.DATABASE_URL)
+    # Fetch klines SYNCHRONOUSLY so user can see chart immediately
+    try:
+        token_id = f"{config.token}-{config.chain}"
+        
+        # Calculate time range (last 1 hour)
+        import time
+        end_time = int(time.time() * 1000)
+        start_time = end_time - (60 * 60 * 1000)  # 1 hour ago
+        
+        klines_data = await ave_client.get_klines(
+            token_id,
+            interval=config.kline_interval,
+            start_time=start_time,
+            end_time=end_time,
+            limit=500
+        )
+        klines_for_chart = [
+            {"time": k.get("time"), "close": k.get("close")}
+            for k in sorted(klines_data, key=lambda x: x.get("time", 0))
+        ]
+        # Update simulation with klines
+        simulation.klines = klines_for_chart
+        db.commit()
+        db.refresh(simulation)
+        logger.info(f"Fetched {len(klines_for_chart)} klines for simulation {simulation_id}")
+    except Exception as e:
+        logger.error(f"Failed to fetch klines: {e}")
+
+    # Run simulation in background for signal processing
     background_tasks.add_task(
-        run_simulation_sync, simulation_id, db_url, bot_id, simulation_config
+        run_simulation_sync, simulation_id, str(settings.DATABASE_URL), bot_id, simulation_config
     )
 
     return simulation
@@ -193,6 +274,9 @@ def list_simulations(
         if sim.id in running_simulations:
             engine = running_simulations[sim.id]
             sim.signals = engine.get_signals()
+            # Include klines from running engine for chart display
+            if hasattr(engine, 'klines'):
+                sim.klines = [{"time": k.get("time"), "close": k.get("close")} for k in engine.klines]
 
     return simulations
 
@@ -224,10 +308,15 @@ def stop_simulation(
             status_code=status.HTTP_404_NOT_FOUND, detail="Simulation not found"
         )
 
+    # Always update status to stopped, even if engine is not in memory
+    simulation.status = "stopped"
+    
+    # Try to stop the engine if it's still in memory
     if run_id in running_simulations:
         engine = running_simulations[run_id]
-        asyncio.create_task(engine.stop())
+        engine.stop()
-        simulation.status = "stopped"
+        del running_simulations[run_id]
-        db.commit()
     
-    return {"status": "stopping", "run_id": run_id}
+    db.commit()
+
+    return {"status": "stopped", "run_id": run_id}

src/backend/app/ave

@@ -0,0 +1 @@
+../../ave-cloud-skill/scripts/ave

src/backend/app/db/models.py

@@ -93,6 +93,9 @@ class Simulation(Base):
     status = Column(String, nullable=False)
     config = Column(JSON, nullable=False)
     signals = Column(JSON)
+    klines = Column(JSON)  # Price data for chart display
+    trade_log = Column(JSON)  # Trade activity log
+    portfolio = Column(JSON)  # Portfolio data
 
     bot = relationship("Bot", back_populates="simulations")
 

src/backend/app/db/schemas.py

@@ -8,6 +8,11 @@ class UserCreate(BaseModel):
     password: str
 
 
+class LoginRequest(BaseModel):
+    username: EmailStr
+    password: str
+
+
 class UserResponse(BaseModel):
     id: str
     email: str
@@ -64,6 +69,7 @@ class BotResponse(BaseModel):
 
 class BacktestCreate(BaseModel):
     token: str
+    token_name: Optional[str] = None
     chain: str
     timeframe: str
     start_date: str
@@ -85,6 +91,7 @@ class BacktestResponse(BaseModel):
     status: str
     config: dict
     result: Optional[dict]
+    progress: Optional[int] = None
 
     class Config:
         from_attributes = True
@@ -93,9 +100,7 @@ class BacktestResponse(BaseModel):
 class SimulationCreate(BaseModel):
     token: str
     chain: str
-    duration_seconds: int = 3600
+    kline_interval: str = "1m"
-    check_interval: int = 60
-    auto_execute: bool = False
 
     @field_validator("chain")
     @classmethod
@@ -112,6 +117,12 @@ class SimulationResponse(BaseModel):
     status: str
     config: dict
     signals: Optional[List[dict]]
+    klines: Optional[List[dict]] = None  # Price data for chart
+    trade_log: Optional[List[dict]] = None  # Trade activity log
+    portfolio: Optional[dict] = None  # Portfolio data
+    current_candle_index: Optional[int] = None  # Progress: current candle
+    total_candles: Optional[int] = None  # Progress: total candles
+    candles_processed: Optional[int] = None  # Progress: candles processed
 
     class Config:
         from_attributes = True
@@ -140,8 +151,12 @@ class BotChatRequest(BaseModel):
 
 class BotChatResponse(BaseModel):
     response: str
+    thinking: Optional[str] = None
     strategy_config: Optional[dict] = None
     success: bool = False
+    strategy_needs_confirmation: Optional[bool] = False
+    strategy_data: Optional[dict] = None
+    token_search_results: Optional[List[dict]] = None
 
 
 class SignalResponse(BaseModel):

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

@@ -1,4 +1,4 @@
-from .crew import CrewAgent
+from .crew import TradingCrew, get_trading_crew
-from .llm_connector import LLMConnector
+from .llm_connector import MiniMaxLLM, MiniMaxConnector
 
-__all__ = ["CrewAgent", "LLMConnector"]
+__all__ = ["TradingCrew", "get_trading_crew", "MiniMaxLLM", "MiniMaxConnector"]

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

@@ -1,7 +1,7 @@
 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
+from ...core.config import get_settings
 
 
 class StrategyValidator:
@@ -33,29 +33,24 @@ class StrategyValidator:
                 errors.append(f"Condition {i}: unsupported type '{cond_type}'")
                 continue
 
-            params = condition.get("params", {})
             if cond_type in ["price_drop", "price_rise", "volume_spike"]:
-                if "token" not in params:
+                if "token" not in condition:
                     errors.append(f"Condition {i}: missing 'token'")
-                if "threshold_percent" not in params:
+                if "threshold" not in condition:
-                    errors.append(f"Condition {i}: missing 'threshold_percent'")
+                    errors.append(f"Condition {i}: missing 'threshold'")
-                elif not isinstance(params["threshold_percent"], (int, float)):
+                elif not isinstance(condition["threshold"], (int, float)):
-                    errors.append(
+                    errors.append(f"Condition {i}: 'threshold' must be a number")
-                        f"Condition {i}: 'threshold_percent' must be a number"
+                elif condition["threshold"] <= 0:
-                    )
+                    errors.append(f"Condition {i}: 'threshold' must be positive")
-                elif params["threshold_percent"] <= 0:
-                    errors.append(
-                        f"Condition {i}: 'threshold_percent' must be positive"
-                    )
 
             elif cond_type == "price_level":
-                if "token" not in params:
+                if "token" not in condition:
                     errors.append(f"Condition {i}: missing 'token'")
-                if "price" not in params:
+                if "price" not in condition:
                     errors.append(f"Condition {i}: missing 'price'")
-                if "direction" not in params:
+                if "direction" not in condition:
                     errors.append(f"Condition {i}: missing 'direction'")
-                elif params["direction"] not in ["above", "below"]:
+                elif condition["direction"] not in ["above", "below"]:
                     errors.append(
                         f"Condition {i}: direction must be 'above' or 'below'"
                     )
@@ -85,23 +80,22 @@ class StrategyExplainer:
                 explanations.append("This strategy will trigger when:")
                 for cond in cond_list:
                     cond_type = cond.get("type")
-                    params = cond.get("params", {})
+                    token = cond.get("token", "the token")
-                    token = params.get("token", "the token")
 
                     if cond_type == "price_drop":
-                        pct = params.get("threshold_percent", 0)
+                        pct = cond.get("threshold", 0)
                         explanations.append(f"  - {token} price drops by {pct}%")
                     elif cond_type == "price_rise":
-                        pct = params.get("threshold_percent", 0)
+                        pct = cond.get("threshold", 0)
                         explanations.append(f"  - {token} price rises by {pct}%")
                     elif cond_type == "volume_spike":
-                        pct = params.get("threshold_percent", 0)
+                        pct = cond.get("threshold", 0)
                         explanations.append(
                             f"  - {token} trading volume increases by {pct}%"
                         )
                     elif cond_type == "price_level":
-                        price = params.get("price", 0)
+                        price = cond.get("price", 0)
-                        direction = params.get("direction", "unknown")
+                        direction = cond.get("direction", "unknown")
                         explanations.append(
                             f"  - {token} price crosses {direction} ${price}"
                         )
@@ -126,7 +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)
 
@@ -147,13 +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",
@@ -161,13 +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",
@@ -175,13 +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
 
@@ -61,9 +59,9 @@ class MiniMaxConnector:
         system_prompt = """You are a trading strategy designer. Parse the user's natural language request into a JSON strategy_config object.
 
 Supported conditions (MVP):
-- price_drop: Token price drops by X% (requires: token, threshold_percent)
+- price_drop: Token price drops by X% (requires: token, threshold)
-- price_rise: Token price rises by X% (requires: token, threshold_percent)
+- price_rise: Token price rises by X% (requires: token, threshold)
-- volume_spike: Trading volume increases X% (requires: token, threshold_percent)
+- volume_spike: Trading volume increases X% (requires: token, threshold)
 - price_level: Price crosses above/below X (requires: token, price, direction)
 
 Output ONLY valid JSON with this schema:
@@ -71,18 +69,17 @@ Output ONLY valid JSON with this schema:
     "conditions": [
         {
             "type": "price_drop|price_rise|volume_spike|price_level",
-            "params": {
+            "token": "TOKEN_SYMBOL",
-                "token": "TOKEN_SYMBOL",
+            "chain": "bsc",
-                "threshold_percent": number,  // for price_drop, price_rise, volume_spike
+            "threshold": number,  // for price_drop, price_rise, volume_spike
-                "price": number,              // for price_level
+            "price": number,     // for price_level
-                "direction": "above|below"    // for price_level
+            "direction": "above|below",  // for price_level
-            }
+            "timeframe": "1h"
         }
     ],
     "actions": [
         {
-            "type": "buy|sell|notify",
+            "type": "buy|sell|notify"
-            "params": {}
         }
     ]
 }

src/backend/app/services/ave/client.py

@@ -23,10 +23,9 @@ class AveCloudClient:
         chain: Optional[str] = None,
         limit: int = 20,
     ) -> List[Dict[str, Any]]:
-        url = f"{self.DATA_API_URL}/v2/tokens"
+        # Use trending endpoint which supports chain filter
-        params = {"limit": limit}
+        url = f"{self.DATA_API_URL}/v2/tokens/trending"
-        if query:
+        params = {"limit": min(limit, 100)}  # API returns max 100
-            params["query"] = query
         if chain:
             params["chain"] = chain
 
@@ -36,8 +35,18 @@ class AveCloudClient:
             )
             response.raise_for_status()
             data = response.json()
-            if data.get("status") == 200:
+            if data.get("status") == 1:  # 1 = SUCCESS
-                return data.get("data", [])
+                tokens = data.get("data", {}).get("tokens", [])
+                # Filter by query if provided
+                if query:
+                    query_lower = query.lower()
+                    tokens = [
+                        t for t in tokens
+                        if query_lower in t.get("symbol", "").lower()
+                        or query_lower in t.get("name", "").lower()
+                    ]
+                return tokens[:limit]
+            return []
             raise Exception(f"Failed to fetch tokens: {data}")
 
     async def get_batch_prices(self, token_ids: List[str]) -> Dict[str, Dict[str, Any]]:
@@ -73,6 +82,10 @@ class AveCloudClient:
         start_time: Optional[int] = None,
         end_time: Optional[int] = None,
     ) -> List[Dict[str, Any]]:
+        # Token ID must be in format "{contract_address}-bsc" for the AVE API
+        if not token_id.endswith("-bsc") and token_id.startswith("0x"):
+            token_id = f"{token_id}-bsc"
+        
         url = f"{self.DATA_API_URL}/v2/klines/token/{token_id}"
         params = {"interval": interval, "limit": limit}
         if start_time:
@@ -86,10 +99,27 @@ class AveCloudClient:
             )
             response.raise_for_status()
             data = response.json()
-            if data.get("status") == 200:
+            # AVE API returns status: 1 for success, not 200
-                return data.get("data", [])
+            if data.get("status") == 1:
+                return data.get("data", {}).get("points", [])
             raise Exception(f"Failed to fetch klines: {data}")
 
+    async def get_token_price(self, token_id: str) -> Optional[Dict[str, Any]]:
+        url = f"{self.DATA_API_URL}/v2/tokens/price"
+        async with httpx.AsyncClient() as client:
+            response = await client.post(
+                url,
+                headers=self._data_headers(),
+                json={"token_ids": [token_id]},
+                timeout=30.0,
+            )
+            response.raise_for_status()
+            data = response.json()
+            if data.get("status") == 1:
+                prices = data.get("data", {})
+                return prices.get(token_id)
+            return None
+
     async def get_trending_tokens(
         self, chain: Optional[str] = None, limit: int = 20
     ) -> List[Dict[str, Any]]:

src/backend/app/services/backtest/ave_client.py

@@ -1,70 +0,0 @@
-import httpx
-from typing import List, Dict, Any, Optional
-from datetime import datetime
-
-
-class AveCloudClient:
-    BASE_URL = "https://prod.ave-api.com"
-
-    def __init__(self, api_key: str, plan: str = "free"):
-        self.api_key = api_key
-        self.plan = plan
-
-    def _headers(self) -> Dict[str, str]:
-        return {"X-API-KEY": self.api_key}
-
-    async def get_klines(
-        self,
-        token_id: str,
-        interval: str = "1h",
-        limit: int = 100,
-        start_time: Optional[int] = None,
-        end_time: Optional[int] = None,
-    ) -> List[Dict[str, Any]]:
-        url = f"{self.BASE_URL}/v2/klines/token/{token_id}"
-        params = {"interval": interval, "limit": limit}
-        if start_time:
-            params["start_time"] = start_time
-        if end_time:
-            params["end_time"] = end_time
-
-        async with httpx.AsyncClient() as client:
-            response = await client.get(
-                url, headers=self._headers(), params=params, timeout=30.0
-            )
-            response.raise_for_status()
-            data = response.json()
-            if data.get("status") == 200:
-                return data.get("data", [])
-            raise Exception(f"Failed to fetch klines: {data}")
-
-    async def get_token_price(self, token_id: str) -> Optional[Dict[str, Any]]:
-        url = f"{self.BASE_URL}/v2/tokens/price"
-        async with httpx.AsyncClient() as client:
-            response = await client.post(
-                url,
-                headers=self._headers(),
-                json={"token_ids": [token_id]},
-                timeout=30.0,
-            )
-            response.raise_for_status()
-            data = response.json()
-            if data.get("status") == 200:
-                prices = data.get("data", {})
-                return prices.get(token_id)
-            return None
-
-    async def get_batch_prices(self, token_ids: List[str]) -> Dict[str, Dict[str, Any]]:
-        url = f"{self.BASE_URL}/v2/tokens/price"
-        async with httpx.AsyncClient() as client:
-            response = await client.post(
-                url,
-                headers=self._headers(),
-                json={"token_ids": token_ids},
-                timeout=30.0,
-            )
-            response.raise_for_status()
-            data = response.json()
-            if data.get("status") == 200:
-                return data.get("data", {})
-            return {}

src/backend/app/services/backtest/engine.py

@@ -2,7 +2,7 @@ import uuid
 import asyncio
 from datetime import datetime
 from typing import Dict, Any, List, Optional
-from .ave_client import AveCloudClient
+from ..ave.client import AveCloudClient
 
 
 class BacktestEngine:
@@ -20,12 +20,21 @@ class BacktestEngine:
         self.strategy_config = config.get("strategy_config", {})
         self.conditions = self.strategy_config.get("conditions", [])
         self.actions = self.strategy_config.get("actions", [])
+        self.risk_management = self.strategy_config.get("risk_management", {})
+        self.stop_loss_percent = self.risk_management.get("stop_loss_percent")
+        self.take_profit_percent = self.risk_management.get("take_profit_percent")
         self.initial_balance = config.get("initial_balance", 10000.0)
         self.current_balance = self.initial_balance
         self.position = 0.0
         self.position_token = ""
+        self.entry_price: Optional[float] = None
+        self.cost_basis = 0.0  # Track total amount spent on current position for average price calc
+        self.entry_time: Optional[int] = None
         self.trades: List[Dict[str, Any]] = []
         self.running = False
+        self.progress = 0
+        self.total_klines = 0
+        self.last_kline_price: Optional[float] = None  # Track last price for open position valuation
 
     async def run(self) -> Dict[str, Any]:
         self.running = True
@@ -33,20 +42,28 @@ class BacktestEngine:
         started_at = datetime.utcnow()
 
         try:
-            token = self.config.get("token", "")
             chain = self.config.get("chain", "bsc")
             timeframe = self.config.get("timeframe", "1h")
             start_date = self.config.get("start_date", "")
             end_date = self.config.get("end_date", "")
 
-            token_id = (
+            # Get token address from strategy config (saved when user confirmed token)
-                f"{token}-{chain}"
+            token_address = None
-                if token and not token.endswith(f"-{chain}")
+            token_symbol = None
-                else token
-            )
             
-            if not token_id or token_id == f"-{chain}":
+            # Try to get from conditions first
-                raise ValueError("Token ID is required")
+            if self.conditions:
+                token_address = self.conditions[0].get("token_address")
+                token_symbol = self.conditions[0].get("token")
+            # Fallback to actions
+            if not token_address and self.actions:
+                token_address = self.actions[0].get("token_address")
+                token_symbol = self.actions[0].get("token") or token_symbol
+            
+            if not token_address:
+                raise ValueError("Token address not found in strategy. Please update your strategy with a valid token.")
+            
+            token_id = token_address
 
             start_ts = None
             end_ts = None
@@ -92,22 +109,126 @@ class BacktestEngine:
 
         return self.results
 
+    async def run_with_klines(self, klines: List[Dict[str, Any]]):
+        """Test helper method that runs backtest with provided klines (bypasses API call)."""
+        self.running = True
+        self.status = "running"
+        started_at = datetime.utcnow()
+
+        try:
+            if not klines:
+                self.status = "failed"
+                self.results = {"error": "No kline data available"}
+                return self.results
+
+            await self._process_klines(klines)
+            self._calculate_metrics()
+            self.status = "completed"
+
+        except Exception as e:
+            self.status = "failed"
+            self.results = {"error": str(e)}
+
+        ended_at = datetime.utcnow()
+        self.results = self.results or {}
+        self.results["started_at"] = started_at
+        self.results["ended_at"] = ended_at
+        self.results["duration_seconds"] = (ended_at - started_at).total_seconds()
+
+        return self.results
+
     async def _process_klines(self, klines: List[Dict[str, Any]]):
+        self.total_klines = len(klines)
         for i, kline in enumerate(klines):
             if not self.running:
                 break
 
+            self.progress = int((i / self.total_klines) * 100) if self.total_klines > 0 else 0
+
             price = float(kline.get("close", 0))
             if price <= 0:
                 continue
             
+            self.last_kline_price = price  # Track last price for open position valuation
+
             timestamp = kline.get("timestamp", 0)
 
+            if self.position > 0 and self.entry_price is not None:
+                exit_info = self._check_risk_management(price, timestamp)
+                if exit_info:
+                    await self._execute_risk_exit(price, timestamp, exit_info)
+                    continue
+
             for condition in self.conditions:
                 if self._check_condition(condition, klines, i, price):
                     await self._execute_actions(price, timestamp, condition)
                     break
 
+    @property
+    def average_entry_price(self) -> Optional[float]:
+        """Calculate weighted average entry price based on cost basis."""
+        if self.position <= 0 or self.cost_basis <= 0:
+            return None
+        return self.cost_basis / self.position
+
+    def _check_risk_management(
+        self, current_price: float, timestamp: int
+    ) -> Optional[Dict[str, Any]]:
+        if self.position <= 0 or self.average_entry_price is None:
+            return None
+
+        if self.stop_loss_percent is not None:
+            stop_loss_price = self.average_entry_price * (1 - self.stop_loss_percent / 100)
+            if current_price <= stop_loss_price:
+                return {"reason": "stop_loss", "price": stop_loss_price}
+
+        if self.take_profit_percent is not None:
+            take_profit_price = self.average_entry_price * (1 + self.take_profit_percent / 100)
+            # Use small epsilon to handle floating point precision
+            if current_price >= take_profit_price - 0.001:
+                return {"reason": "take_profit", "price": take_profit_price}
+
+        return None
+
+    async def _execute_risk_exit(
+        self, price: float, timestamp: int, exit_info: Dict[str, Any]
+    ):
+        if self.position <= 0:
+            return
+
+        reason = exit_info["reason"]
+        sell_amount = self.position * price
+        self.current_balance += sell_amount
+        self.trades.append(
+            {
+                "type": "sell",
+                "token": self.position_token,
+                "price": price,
+                "amount": sell_amount,
+                "quantity": self.position,
+                "timestamp": timestamp,
+                "exit_reason": reason,
+            }
+        )
+        self.signals.append(
+            {
+                "id": str(uuid.uuid4()),
+                "bot_id": self.bot_id,
+                "run_id": self.run_id,
+                "signal_type": "sell",
+                "token": self.position_token,
+                "price": price,
+                "confidence": 1.0,
+                "reasoning": f"Risk management triggered {reason}",
+                "executed": False,
+                "created_at": datetime.utcnow(),
+            }
+        )
+        self.position = 0
+        self.entry_price = None
+        self.cost_basis = 0.0
+        self.entry_time = None
+
     def _check_condition(
         self,
         condition: Dict[str, Any],
@@ -170,16 +291,20 @@ class BacktestEngine:
             amount = self.current_balance * (amount_percent / 100)
 
             if action_type == "buy" and self.current_balance >= amount:
-                self.position += amount / price
+                quantity = amount / price
+                self.position += quantity
                 self.current_balance -= amount
+                self.cost_basis += amount  # Track total cost for average price
                 self.position_token = token
+                self.entry_price = price  # Keep last entry price for reference
+                self.entry_time = timestamp
                 self.trades.append(
                     {
                         "type": "buy",
                         "token": token,
                         "price": price,
                         "amount": amount,
-                        "quantity": amount / price,
+                        "quantity": quantity,
                         "timestamp": timestamp,
                     }
                 )
@@ -209,9 +334,12 @@ class BacktestEngine:
                         "amount": sell_amount,
                         "quantity": self.position,
                         "timestamp": timestamp,
+                        "exit_reason": "manual",
                     }
                 )
                 self.position = 0
+                self.entry_price = None
+                self.entry_time = None
                 self.signals.append(
                     {
                         "id": str(uuid.uuid4()),
@@ -228,11 +356,17 @@ class BacktestEngine:
                 )
 
     def _calculate_metrics(self):
-        final_balance = self.current_balance + (
+        # For open positions, use the last kline price to mark to market
-            self.position * self.trades[-1]["price"]
+        # If no last kline price, fall back to entry price
-            if self.trades and self.position > 0
+        position_price = self.last_kline_price
-            else 0
+        if position_price is None and self.trades and self.position > 0:
-        )
+            position_price = self.trades[-1]["price"]  # Fall back to entry price
+        
+        # Calculate final balance: use marked-to-market value if position open, otherwise current balance
+        if self.position > 0 and position_price:
+            final_balance = self.current_balance + self.position * position_price
+        else:
+            final_balance = self.current_balance
         total_return = (
             (final_balance - self.initial_balance) / self.initial_balance
         ) * 100
@@ -259,18 +393,23 @@ class BacktestEngine:
 
         for trade in self.trades:
             if trade["type"] == "buy":
-                running_position = trade["quantity"]
+                running_position += trade["quantity"]  # Add to existing position (DCA)
-                running_balance = trade["amount"]
+                running_balance -= trade["amount"]  # Subtract amount spent
                 current_token = trade["token"]
                 last_price = trade["price"]
-            else:
+            else:  # sell
-                running_balance = trade["amount"]
+                running_balance += trade["amount"]  # Add amount received
-                running_position = 0
+                running_position = 0  # Close entire position
                 last_price = trade["price"]
 
             portfolio_value = running_balance + (running_position * last_price)
             portfolio_values.append(portfolio_value)
         
+        # If there's an open position, add final marked-to-market value
+        if self.position > 0 and self.last_kline_price:
+            final_portfolio_value = self.current_balance + (self.position * self.last_kline_price)
+            portfolio_values.append(final_portfolio_value)
+
         max_value = self.initial_balance
         max_drawdown = 0.0
         for value in portfolio_values:
@@ -308,10 +447,13 @@ class BacktestEngine:
             "sharpe_ratio": round(sharpe_ratio, 2),
             "final_balance": round(final_balance, 2),
             "signals": self.signals,
+            "trades": self.trades,  # Include trades in results for storage
         }
 
     async def stop(self):
         self.running = False
+        self.progress = 0
+        self.total_klines = 0
         self.status = "stopped"
         self._calculate_metrics()
 
@@ -321,4 +463,13 @@ class BacktestEngine:
             "status": self.status,
             "results": self.results,
             "signals": self.signals,
+            "progress": self.progress,
+            "total_klines": self.total_klines,
+        }
+
+    def get_status(self) -> Dict[str, Any]:
+        return {
+            "status": self.status,
+            "progress": self.progress,
+            "total_klines": self.total_klines,
         }

src/backend/app/services/simulate/engine.py

@@ -1,8 +1,12 @@
 import uuid
 import asyncio
+import logging
 from datetime import datetime
 from typing import Dict, Any, List, Optional
-from ..backtest.ave_client import AveCloudClient
+
+from ..ave.client import AveCloudClient
+
+logger = logging.getLogger(__name__)
 
 
 class SimulateEngine:
@@ -20,16 +24,69 @@ class SimulateEngine:
         self.strategy_config = config.get("strategy_config", {})
         self.conditions = self.strategy_config.get("conditions", [])
         self.actions = self.strategy_config.get("actions", [])
-        self.check_interval = config.get("check_interval", 60)
+        self.risk_management = self.strategy_config.get("risk_management", {})
-        self.duration_seconds = config.get("duration_seconds", 3600)
+        self.stop_loss_percent = self.risk_management.get("stop_loss_percent")
+        self.take_profit_percent = self.risk_management.get("take_profit_percent")
+        
+        # Kline-based settings
+        self.kline_interval = config.get("kline_interval", "1m")
+        self.max_candles = config.get("max_candles", 100)  # Limit candles to simulate real-time
+        
+        # Delay between candles (in seconds) to simulate real-time
+        # e.g., 1m interval -> 30s delay between candles
+        # Use config value if provided, otherwise calculate
+        if "candle_delay" in config and config["candle_delay"] is not None:
+            self.candle_delay = config["candle_delay"]
+        else:
+            self.candle_delay = self._get_interval_seconds(self.kline_interval) / 2
+        
         self.auto_execute = config.get("auto_execute", False)
         self.token = config.get("token", "")
         self.chain = config.get("chain", "bsc")
         self.running = False
         self.started_at: Optional[datetime] = None
-        self.last_price: Optional[float] = None
+        
+        # Price tracking (for conditions)
+        self.last_close: Optional[float] = None
         self.last_volume: Optional[float] = None
         
+        # Position tracking (for risk management)
+        self.position: float = 0.0
+        self.position_token: str = ""
+        self.entry_price: Optional[float] = None
+        self.entry_time: Optional[int] = None
+        
+        # Portfolio
+        self.current_balance: float = config.get("initial_balance", 10000.0)
+        self.trades: List[Dict[str, Any]] = []
+        
+        # Error tracking
+        self.errors: List[str] = []
+        
+        # Kline data
+        self.klines: List[Dict[str, Any]] = []
+        self.last_processed_time: Optional[int] = None
+        
+        # Trade log - tracks what happened at each candle
+        self.trade_log: List[Dict[str, Any]] = []
+        
+        # Current candle being processed (for frontend to show progress)
+        self.current_candle_index = 0
+        self.total_candles = 0
+
+    def _get_interval_seconds(self, interval: str) -> int:
+        """Convert kline interval to seconds."""
+        mapping = {
+            "1m": 60,
+            "5m": 300,
+            "15m": 900,
+            "30m": 1800,
+            "1h": 3600,
+            "4h": 14400,
+            "1d": 86400,
+        }
+        return mapping.get(interval, 60)
+    
     async def run(self) -> Dict[str, Any]:
         self.running = True
         self.status = "running"
@@ -46,58 +103,231 @@ class SimulateEngine:
             self.results = {"error": "Token ID is required"}
             return self.results
 
-        end_time = datetime.utcnow().timestamp() + self.duration_seconds
-
         try:
-            while self.running and datetime.utcnow().timestamp() < end_time:
+            # Step 1: Fetch klines (only once for simulation)
-                try:
+            self.klines = await self._fetch_klines(token_id)
-                    price_data = await self.ave_client.get_token_price(token_id)
-                    if price_data:
-                        current_price = float(price_data.get("price", 0))
-                        current_volume = float(price_data.get("volume", 0))
             
-                        if current_price > 0:
+            if not self.klines:
-                            await self._check_conditions(
+                self.status = "failed"
-                                current_price, current_volume, price_data
+                self.results = {"error": "No kline data available"}
-                            )
+                return self.results
             
-                        self.last_price = current_price
+            logger.info(f"Fetched {len(self.klines)} klines for {token_id}")
-                        self.last_volume = current_volume
             
-                except Exception as e:
+            # Step 2: Process candles (with limit)
-                    pass
+            candles_processed = 0
+            self.total_candles = min(len(self.klines), self.max_candles)
+            self.current_candle_index = 0
             
-                for _ in range(self.check_interval):
+            for i, candle in enumerate(self.klines):
-                    if not self.running:
+                if not self.running:
-                        break
+                    break
-                    await asyncio.sleep(1)
+                if candles_processed >= self.max_candles:
+                    logger.info(f"Reached max candles limit ({self.max_candles})")
+                    break
                 
-            if self.running:
+                self.current_candle_index = candles_processed
-                self.status = "completed"
+                candle_time = int(candle.get("time", 0))
-            else:
+                
-                self.status = "stopped"
+                # Get OHLCV data from candle
+                close_price = float(candle.get("close", 0))
+                volume = float(candle.get("volume", 0))
+                
+                if close_price > 0:
+                    # Process candle
+                    await self._process_candle(close_price, volume, candle_time)
+                    
+                    # Update last close for next iteration
+                    self.last_close = close_price
+                    self.last_volume = volume
+                    
+                    # Track last processed time
+                    self.last_processed_time = candle_time
+                
+                candles_processed += 1
+                
+                # Delay to simulate real-time (only for visible candles, not initial batch)
+                if candles_processed > 1 and self.candle_delay > 0:
+                    await asyncio.sleep(self.candle_delay)
+            
+            self.status = "completed"
 
         except Exception as e:
+            logger.error(f"Simulation error: {e}")
             self.status = "failed"
             self.results = {"error": str(e)}
+            self.errors.append(str(e))
 
         self.results = self.results or {}
         self.results["total_signals"] = len(self.signals)
+        self.results["total_trades"] = len(self.trades)
+        self.results["total_errors"] = len(self.errors)
+        self.results["errors"] = self.errors
         self.results["signals"] = self.signals
+        self.results["candles_processed"] = candles_processed
+        self.results["current_candle_index"] = self.current_candle_index
+        self.results["total_candles"] = self.total_candles
+        self.results["klines"] = self.klines  # Include klines for chart display
+        self.results["trade_log"] = self.trade_log  # Include trade log for dashboard
+        self.results["portfolio"] = {
+            "initial_balance": self.config.get("initial_balance", 10000),
+            "current_balance": self.current_balance,
+            "position": self.position,
+            "position_token": self.position_token,
+            "entry_price": self.entry_price,
+            "current_price": self.last_close,
+        }
         self.results["started_at"] = self.started_at
         self.results["ended_at"] = datetime.utcnow()
 
         return self.results
 
-    async def _check_conditions(
+    async def _fetch_klines(
-        self, current_price: float, current_volume: float, price_data: Dict[str, Any]
+        self, 
-    ):
+        token_id: str, 
-        timestamp = int(datetime.utcnow().timestamp() * 1000)
+        limit: int = 500
+    ) -> List[Dict[str, Any]]:
+        """Fetch klines from AVE API."""
+        try:
+            klines = await self.ave_client.get_klines(
+                token_id,
+                interval=self.kline_interval,
+                limit=limit
+            )
             
-        for condition in self.conditions:
+            # Sort by time ascending (oldest first)
-            if self._check_condition(condition, current_price, current_volume):
+            klines = sorted(klines, key=lambda x: x.get("time", 0))
-                await self._execute_actions(current_price, timestamp, condition)
+            return klines
-                break
+            
+        except Exception as e:
+            logger.warning(f"Failed to fetch klines for {token_id}: {e}")
+            self.errors.append(f"Kline fetch failed: {str(e)}")
+            return []
+
+    async def _process_candle(
+        self, 
+        close_price: float, 
+        volume: float, 
+        timestamp: int
+    ):
+        """Process a single candle - check conditions and risk management."""
+        
+        action = "hold"  # Default action
+        reason = ""
+        
+        # Check risk management first (for open positions)
+        if self.position > 0 and self.entry_price is not None:
+            exit_info = self._check_risk_management(close_price, timestamp)
+            if exit_info:
+                await self._execute_risk_exit(close_price, timestamp, exit_info)
+                action = "sell"
+                reason = exit_info["reason"]
+                # Log the action
+                self.trade_log.append({
+                    "time": timestamp,
+                    "price": close_price,
+                    "action": action,
+                    "reason": reason,
+                    "position": self.position,
+                    "entry_price": self.entry_price,
+                })
+                return
+
+        # Check conditions (only if no open position)
+        if self.position == 0:
+            for condition in self.conditions:
+                if self._check_condition(condition, close_price, volume):
+                    await self._execute_actions(close_price, timestamp, condition)
+                    action = "buy"
+                    reason = f"{condition.get('type')} {condition.get('threshold')}%".format(
+                        type=condition.get('type'),
+                        threshold=condition.get('threshold')
+                    )
+                    # Log the action
+                    self.trade_log.append({
+                        "time": timestamp,
+                        "price": close_price,
+                        "action": action,
+                        "reason": reason,
+                        "position": self.position,
+                        "entry_price": self.entry_price,
+                    })
+                    break
+        
+        # Log hold action (no signal)
+        if action == "hold":
+            # Only log every 10th candle to reduce data
+            if len(self.trade_log) == 0 or (len(self.klines) - len(self.trade_log) > 10):
+                self.trade_log.append({
+                    "time": timestamp,
+                    "price": close_price,
+                    "action": "hold",
+                    "reason": "no_signal",
+                    "position": self.position,
+                    "entry_price": self.entry_price,
+                })
+
+    def _check_risk_management(
+        self, current_price: float, timestamp: int
+    ) -> Optional[Dict[str, Any]]:
+        """Check if stop loss or take profit is triggered."""
+        if self.position <= 0 or self.entry_price is None:
+            return None
+
+        if self.stop_loss_percent is not None:
+            stop_loss_price = self.entry_price * (1 - self.stop_loss_percent / 100)
+            if current_price <= stop_loss_price:
+                return {"reason": "stop_loss", "price": stop_loss_price}
+
+        if self.take_profit_percent is not None:
+            take_profit_price = self.entry_price * (1 + self.take_profit_percent / 100)
+            if current_price >= take_profit_price:
+                return {"reason": "take_profit", "price": take_profit_price}
+
+        return None
+
+    async def _execute_risk_exit(
+        self, price: float, timestamp: int, exit_info: Dict[str, Any]
+    ):
+        """Execute stop loss or take profit."""
+        if self.position <= 0:
+            return
+
+        reason = exit_info["reason"]
+        quantity = self.position
+        sale_proceeds = quantity * price
+        
+        # Add sale proceeds to cash balance
+        self.current_balance += sale_proceeds
+        
+        self.trades.append(
+            {
+                "type": "sell",
+                "token": self.position_token,
+                "price": price,
+                "quantity": quantity,
+                "amount": sale_proceeds,
+                "timestamp": timestamp,
+                "exit_reason": reason,
+            }
+        )
+        self.signals.append(
+            {
+                "id": str(uuid.uuid4()),
+                "bot_id": self.bot_id,
+                "run_id": self.run_id,
+                "signal_type": "sell",
+                "token": self.position_token,
+                "price": price,
+                "confidence": 1.0,
+                "reasoning": f"Risk management triggered {reason}",
+                "executed": self.auto_execute,
+                "created_at": datetime.utcnow(),
+            }
+        )
+        self.position = 0
+        self.entry_price = None
+        self.entry_time = None
 
     def _check_condition(
         self,
@@ -105,32 +335,34 @@ class SimulateEngine:
         current_price: float,
         current_volume: float,
     ) -> bool:
+        """Check if a condition is met based on price movement."""
         cond_type = condition.get("type", "")
         threshold = condition.get("threshold", 0)
-        price_level = condition.get("price")
-        direction = condition.get("direction", "above")
 
         if cond_type == "price_drop":
-            if self.last_price is None or self.last_price <= 0:
+            # Price dropped by threshold % from last close
+            if self.last_close is None or self.last_close <= 0:
                 return False
-            drop_pct = ((self.last_price - current_price) / self.last_price) * 100
+            drop_pct = ((self.last_close - current_price) / self.last_close) * 100
             return drop_pct >= threshold
 
         elif cond_type == "price_rise":
-            if self.last_price is None or self.last_price <= 0:
+            # Price rose by threshold % from last close
+            if self.last_close is None or self.last_close <= 0:
                 return False
-            rise_pct = ((current_price - self.last_price) / self.last_price) * 100
+            rise_pct = ((current_price - self.last_close) / self.last_close) * 100
             return rise_pct >= threshold
 
         elif cond_type == "volume_spike":
+            # Volume increased significantly
             if self.last_volume is None or self.last_volume <= 0:
                 return False
-            volume_increase = (
+            volume_increase = ((current_volume - self.last_volume) / self.last_volume) * 100
-                (current_volume - self.last_volume) / self.last_volume
-            ) * 100
             return volume_increase >= threshold
 
         elif cond_type == "price_level":
+            price_level = condition.get("price")
+            direction = condition.get("direction", "above")
             if price_level is None:
                 return False
             if direction == "above":
@@ -143,29 +375,56 @@ class SimulateEngine:
     async def _execute_actions(
         self, price: float, timestamp: int, matched_condition: Dict[str, Any]
     ):
+        """Execute buy/sell actions based on matched condition."""
         token = matched_condition.get("token", self.token)
         reasoning = f"Condition {matched_condition.get('type')} triggered"
 
-        signal = {
+        for action in self.actions:
-            "id": str(uuid.uuid4()),
+            action_type = action.get("type", "")
-            "bot_id": self.bot_id,
+            if action_type == "buy":
-            "run_id": self.run_id,
+                amount_percent = action.get("amount_percent", 10)
-            "signal_type": "signal",
+                amount = self.current_balance * (amount_percent / 100)
-            "token": token,
+                quantity = amount / price
-            "price": price,
-            "confidence": 0.8,
-            "reasoning": reasoning,
-            "executed": self.auto_execute,
-            "created_at": datetime.utcnow(),
-        }
                 
-        self.signals.append(signal)
+                self.position += quantity
+                self.position_token = token
+                self.entry_price = price
+                self.entry_time = timestamp
+                self.current_balance -= amount
                 
-    async def stop(self):
+                self.trades.append(
+                    {
+                        "type": "buy",
+                        "token": token,
+                        "price": price,
+                        "amount": amount,
+                        "quantity": quantity,
+                        "timestamp": timestamp,
+                    }
+                )
+
+            signal = {
+                "id": str(uuid.uuid4()),
+                "bot_id": self.bot_id,
+                "run_id": self.run_id,
+                "signal_type": action_type,
+                "token": token,
+                "price": price,
+                "confidence": 0.8,
+                "reasoning": reasoning,
+                "executed": self.auto_execute,
+                "created_at": datetime.utcnow(),
+            }
+
+            self.signals.append(signal)
+
+    def stop(self):
+        """Stop the simulation."""
         self.running = False
         self.status = "stopped"
 
     def get_results(self) -> Dict[str, Any]:
+        """Get simulation results."""
         return {
             "id": self.run_id,
             "status": self.status,
@@ -174,4 +433,5 @@ class SimulateEngine:
         }
 
     def get_signals(self) -> List[Dict[str, Any]]:
+        """Get current signals."""
         return self.signals

src/backend/requirements.txt

@@ -6,6 +6,7 @@ pydantic-settings>=2.1.0
 email-validator>=2.0.0
 python-jose[cryptography]>=3.3.0
 passlib[bcrypt]>=1.7.4
+bcrypt>=4.0,<5.0  # Required for passlib compatibility
 crewai>=0.1.0
 anthropic>=0.18.0
 httpx>=0.26.0

src/backend/run.py

@@ -8,4 +8,5 @@ if __name__ == "__main__":
         host=settings.HOST,
         port=settings.PORT,
         reload=settings.DEBUG,
+        timeout_keep_alive=300,
     )

src/backend/tests/test_backtest_engine.py

@@ -0,0 +1,457 @@
+"""
+Unit tests for BacktestEngine
+Tests stop loss, take profit, and max drawdown calculations
+"""
+import asyncio
+from app.services.backtest.engine import BacktestEngine
+
+
+class TestBacktestEngine:
+    """Test suite for BacktestEngine"""
+    
+    def _run_backtest(self, config, klines):
+        """Helper to run backtest with given klines"""
+        engine = BacktestEngine(config)
+        result = asyncio.run(engine.run_with_klines(klines))
+        return engine, result
+    
+    def _trace_portfolio(self, engine, initial_balance):
+        """Print portfolio trace for debugging"""
+        running_balance = initial_balance
+        running_position = 0.0
+        
+        print("\nPortfolio Trace:")
+        for i, trade in enumerate(engine.trades):
+            if trade["type"] == "buy":
+                running_position = trade["quantity"]
+                running_balance -= trade["amount"]
+                portfolio = running_balance + (running_position * trade["price"])
+                print(f"  BUY  #{i+1}: @${trade['price']} - portfolio=${portfolio:.2f}")
+            else:
+                running_balance += trade["amount"]
+                running_position = 0
+                portfolio = running_balance
+                print(f"  SELL #{i+1}: @${trade['price']} ({trade.get('exit_reason', '')}) - portfolio=${portfolio:.2f}")
+        
+        if engine.position > 0 and engine.last_kline_price:
+            final = running_balance + (engine.position * engine.last_kline_price)
+            print(f"  FINAL: position={engine.position:.2f} @ ${engine.last_kline_price} = ${final:.2f}")
+        print()
+    
+    def test_stop_loss_triggers_correctly(self):
+        """Test stop loss triggers at configured percentage"""
+        config = {
+            "bot_id": "test",
+            "strategy_config": {
+                "conditions": [{"type": "price_drop", "token": "TEST", "token_address": "0x123", "threshold": 5}],
+                "actions": [{"type": "buy", "amount_percent": 100}],
+                "risk_management": {"stop_loss_percent": 5, "take_profit_percent": 10}
+            },
+            "ave_api_key": "test",
+            "ave_api_plan": "free",
+            "initial_balance": 10000.0,
+        }
+        
+        # Price sequence that triggers buy then stop loss:
+        # $110 -> $100 (9% drop, BUY)
+        # $100 -> $95 (5% drop, STOP LOSS at 5% from $100 = $95)
+        klines = [
+            {"close": "110.0", "timestamp": 1000, "open": "110.0", "high": "110.0", "low": "110.0", "volume": "1000"},
+            {"close": "100.0", "timestamp": 2000, "open": "100.0", "high": "100.0", "low": "100.0", "volume": "1000"},
+            {"close": "95.0", "timestamp": 3000, "open": "95.0", "high": "95.0", "low": "95.0", "volume": "1000"},
+        ]
+        
+        engine, result = self._run_backtest(config, klines)
+        self._trace_portfolio(engine, 10000.0)
+        
+        print(f"Results:")
+        print(f"  Trades: {len(engine.trades)} (expected 2)")
+        print(f"  Max drawdown: {result['max_drawdown']}%")
+        print(f"  Total return: {result['total_return']}%")
+        
+        assert len(engine.trades) == 2
+        assert engine.trades[0]["type"] == "buy"
+        assert engine.trades[1]["type"] == "sell"
+        assert engine.trades[1]["exit_reason"] == "stop_loss"
+        # Max drawdown should be ~5% (stop loss percentage)
+        assert 3 < result['max_drawdown'] < 8
+        # Total return should be ~-5%
+        assert -8 < result['total_return'] < -3
+    
+    def test_take_profit_triggers(self):
+        """Test take profit triggers at configured percentage"""
+        config = {
+            "bot_id": "test",
+            "strategy_config": {
+                "conditions": [{"type": "price_drop", "token": "TEST", "token_address": "0x123", "threshold": 5}],
+                "actions": [{"type": "buy", "amount_percent": 100}],
+                "risk_management": {"stop_loss_percent": 5, "take_profit_percent": 10}
+            },
+            "ave_api_key": "test",
+            "ave_api_plan": "free",
+            "initial_balance": 10000.0,
+        }
+        
+        # $100 -> $95 (5% drop, BUY) -> $104.5 (10% rise, TAKE PROFIT)
+        klines = [
+            {"close": "100.0", "timestamp": 1000, "open": "100.0", "high": "100.0", "low": "100.0", "volume": "1000"},
+            {"close": "95.0", "timestamp": 2000, "open": "95.0", "high": "95.0", "low": "95.0", "volume": "1000"},
+            {"close": "104.5", "timestamp": 3000, "open": "104.5", "high": "104.5", "low": "104.5", "volume": "1000"},
+        ]
+        
+        engine, result = self._run_backtest(config, klines)
+        self._trace_portfolio(engine, 10000.0)
+        
+        print(f"Results:")
+        print(f"  Trades: {len(engine.trades)} (expected 2)")
+        print(f"  Max drawdown: {result['max_drawdown']}%")
+        print(f"  Total return: {result['total_return']}%")
+        
+        assert len(engine.trades) == 2
+        assert engine.trades[1]["exit_reason"] == "take_profit"
+        assert result['total_return'] > 0
+    
+    def test_max_drawdown_bounded_by_stop_loss(self):
+        """Test that max drawdown is bounded by stop loss when position is properly closed"""
+        config = {
+            "bot_id": "test",
+            "strategy_config": {
+                "conditions": [{"type": "price_drop", "token": "TEST", "token_address": "0x123", "threshold": 5}],
+                "actions": [{"type": "buy", "amount_percent": 100}],
+                "risk_management": {"stop_loss_percent": 5, "take_profit_percent": 10}
+            },
+            "ave_api_key": "test",
+            "ave_api_plan": "free",
+            "initial_balance": 10000.0,
+        }
+        
+        # $110 -> $100 -> $95 (BUY) -> $90 (STOP LOSS)
+        klines = [
+            {"close": "110.0", "timestamp": 1000, "open": "110.0", "high": "110.0", "low": "110.0", "volume": "1000"},
+            {"close": "100.0", "timestamp": 2000, "open": "100.0", "high": "100.0", "low": "100.0", "volume": "1000"},
+            {"close": "95.0", "timestamp": 3000, "open": "95.0", "high": "95.0", "low": "95.0", "volume": "1000"},
+            {"close": "90.0", "timestamp": 4000, "open": "90.0", "high": "90.0", "low": "90.0", "volume": "1000"},
+        ]
+        
+        engine, result = self._run_backtest(config, klines)
+        self._trace_portfolio(engine, 10000.0)
+        
+        print(f"Results:")
+        print(f"  Trades: {len(engine.trades)}")
+        print(f"  Max drawdown: {result['max_drawdown']}%")
+        print(f"  Total return: {result['total_return']}%")
+        
+        # With 5% stop loss, max drawdown should be around 5%
+        assert 3 < result['max_drawdown'] < 8
+    
+    def test_open_position_not_closed(self):
+        """Test scenario where last kline has an open position"""
+        config = {
+            "bot_id": "test",
+            "strategy_config": {
+                "conditions": [{"type": "price_drop", "token": "TEST", "token_address": "0x123", "threshold": 10}],
+                "actions": [{"type": "buy", "amount_percent": 100}],
+                "risk_management": {"stop_loss_percent": 5, "take_profit_percent": 10}
+            },
+            "ave_api_key": "test",
+            "ave_api_plan": "free",
+            "initial_balance": 10000.0,
+        }
+        
+        # $100 -> $90 (10% drop, BUY) - and backtest ends here
+        # Position is open, marked to market at $90
+        klines = [
+            {"close": "100.0", "timestamp": 1000, "open": "100.0", "high": "100.0", "low": "100.0", "volume": "1000"},
+            {"close": "90.0", "timestamp": 2000, "open": "90.0", "high": "90.0", "low": "90.0", "volume": "1000"},
+        ]
+        
+        engine, result = self._run_backtest(config, klines)
+        self._trace_portfolio(engine, 10000.0)
+        
+        print(f"Results:")
+        print(f"  Trades: {len(engine.trades)}")
+        print(f"  Position open: {engine.position > 0}")
+        print(f"  Entry price: ${engine.entry_price}")
+        print(f"  Last kline price: ${engine.last_kline_price}")
+        print(f"  Max drawdown: {result['max_drawdown']}%")
+        print(f"  Total return: {result['total_return']}%")
+        
+        # Position should be open
+        assert engine.position > 0
+        # Entry should be $90
+        assert engine.entry_price == 90.0
+        # Since entry = last kline price, no unrealized loss
+        # Max drawdown should be 0%
+        assert result['max_drawdown'] == 0.0
+    
+    def test_open_position_with_loss(self):
+        """Test open position where price dropped but stop loss didn't trigger"""
+        config = {
+            "bot_id": "test",
+            "strategy_config": {
+                "conditions": [{"type": "price_drop", "token": "TEST", "token_address": "0x123", "threshold": 10}],
+                "actions": [{"type": "buy", "amount_percent": 100}],
+                "risk_management": {"stop_loss_percent": 5, "take_profit_percent": 10}
+            },
+            "ave_api_key": "test",
+            "ave_api_plan": "free",
+            "initial_balance": 10000.0,
+        }
+        
+        # $100 -> $90 (10% drop, BUY at $90) -> $85 (stop loss at 5% from $90 = $85.5)
+        # $85 > $85.5? No, $85 < $85.5, so stop loss WOULD trigger
+        # Let me use $86 instead - $86 > $85.5 so no stop loss
+        klines = [
+            {"close": "100.0", "timestamp": 1000, "open": "100.0", "high": "100.0", "low": "100.0", "volume": "1000"},
+            {"close": "90.0", "timestamp": 2000, "open": "90.0", "high": "90.0", "low": "90.0", "volume": "1000"},
+            {"close": "86.0", "timestamp": 3000, "open": "86.0", "high": "86.0", "low": "86.0", "volume": "1000"},
+        ]
+        
+        engine, result = self._run_backtest(config, klines)
+        self._trace_portfolio(engine, 10000.0)
+        
+        print(f"Results:")
+        print(f"  Trades: {len(engine.trades)}")
+        print(f"  Position open: {engine.position > 0}")
+        print(f"  Entry price: ${engine.entry_price}")
+        print(f"  Last kline price: ${engine.last_kline_price}")
+        print(f"  Max drawdown: {result['max_drawdown']}%")
+        print(f"  Total return: {result['total_return']}%")
+        
+        # Position should be open
+        assert engine.position > 0
+        # Entry = $90, stop = $85.50, last = $86 (above stop)
+        # Portfolio: $0 + position * $86
+        # Position: 10000/90 = 111.11 tokens
+        # Portfolio at $86: 111.11 * 86 = $9,555.56
+        # But we only track portfolio at trade points, so max was $10,000
+        # drawdown = (10000 - 9555.56) / 10000 = 4.44%
+        print(f"  Expected max drawdown: ~4.4% (marked to market at $86)")
+    
+    def test_multiple_buy_sell_cycles(self):
+        """Test multiple buy/sell cycles"""
+        config = {
+            "bot_id": "test",
+            "strategy_config": {
+                "conditions": [{"type": "price_drop", "token": "TEST", "token_address": "0x123", "threshold": 5}],
+                "actions": [{"type": "buy", "amount_percent": 50}],  # 50% of balance
+                "risk_management": {"stop_loss_percent": 5, "take_profit_percent": 10}
+            },
+            "ave_api_key": "test",
+            "ave_api_plan": "free",
+            "initial_balance": 10000.0,
+        }
+        
+        # $100 -> $95 (BUY) -> $104.5 (TAKE PROFIT) -> $95 (BUY) -> $90 (STOP LOSS)
+        klines = [
+            {"close": "100.0", "timestamp": 1000, "open": "100.0", "high": "100.0", "low": "100.0", "volume": "1000"},
+            {"close": "95.0", "timestamp": 2000, "open": "95.0", "high": "95.0", "low": "95.0", "volume": "1000"},   # BUY at $95
+            {"close": "104.5", "timestamp": 3000, "open": "104.5", "high": "104.5", "low": "104.5", "volume": "1000"},  # TAKE PROFIT
+            {"close": "95.0", "timestamp": 4000, "open": "95.0", "high": "95.0", "low": "95.0", "volume": "1000"},   # 9% drop - no buy
+            {"close": "90.0", "timestamp": 5000, "open": "90.0", "high": "90.0", "low": "90.0", "volume": "1000"},   # 10.5% drop from $100 - BUY at $90
+            {"close": "85.5", "timestamp": 6000, "open": "85.5", "high": "85.5", "low": "85.5", "volume": "1000"},   # STOP LOSS at 5% from $90 = $85.5
+        ]
+        
+        engine, result = self._run_backtest(config, klines)
+        self._trace_portfolio(engine, 10000.0)
+        
+        print(f"Results:")
+        print(f"  Trades: {len(engine.trades)}")
+        print(f"  Buy count: {len([t for t in engine.trades if t['type'] == 'buy'])}")
+        print(f"  Sell count: {len([t for t in engine.trades if t['type'] == 'sell'])}")
+        print(f"  Max drawdown: {result['max_drawdown']}%")
+        print(f"  Total return: {result['total_return']}%")
+
+
+def run_tests():
+    tests = TestBacktestEngine()
+    
+    print("=" * 60)
+    print("TEST 1: Stop Loss Triggers Correctly")
+    print("=" * 60)
+    try:
+        tests.test_stop_loss_triggers_correctly()
+        print("PASSED\n")
+    except AssertionError as e:
+        print(f"FAILED: {e}\n")
+    
+    print("=" * 60)
+    print("TEST 2: Take Profit Triggers")
+    print("=" * 60)
+    try:
+        tests.test_take_profit_triggers()
+        print("PASSED\n")
+    except AssertionError as e:
+        print(f"FAILED: {e}\n")
+    
+    print("=" * 60)
+    print("TEST 3: Max Drawdown Bounded by Stop Loss")
+    print("=" * 60)
+    try:
+        tests.test_max_drawdown_bounded_by_stop_loss()
+        print("PASSED\n")
+    except AssertionError as e:
+        print(f"FAILED: {e}\n")
+    
+    print("=" * 60)
+    print("TEST 4: Open Position Not Closed")
+    print("=" * 60)
+    try:
+        tests.test_open_position_not_closed()
+        print("PASSED\n")
+    except AssertionError as e:
+        print(f"FAILED: {e}\n")
+    
+    print("=" * 60)
+    print("TEST 5: Open Position With Loss")
+    print("=" * 60)
+    try:
+        tests.test_open_position_with_loss()
+        print("PASSED\n")
+    except AssertionError as e:
+        print(f"FAILED: {e}\n")
+    
+    print("=" * 60)
+    print("TEST 6: Multiple Buy/Sell Cycles")
+    print("=" * 60)
+    try:
+        tests.test_multiple_buy_sell_cycles()
+        print("PASSED\n")
+    except AssertionError as e:
+        print(f"FAILED: {e}\n")
+
+
+def test_dca_multiple_buys():
+    """Test that DCA with multiple consecutive buys uses weighted average for stop loss."""
+    print("\n" + "=" * 60)
+    print("TEST 7: DCA With Multiple Consecutive Buys")
+    print("=" * 60)
+    
+    config = {
+        "bot_id": "test",
+        "strategy_config": {
+            "conditions": [{"type": "price_drop", "threshold": 2, "token": "TEST", "token_address": "0x123"}],
+            "actions": [{"type": "buy", "amount_percent": 20}],
+            "risk_management": {"stop_loss_percent": 5, "take_profit_percent": 5},
+        },
+        "initial_balance": 10000.0,
+        "ave_api_key": "test",
+        "ave_api_plan": "free",
+    }
+    
+    # 3 consecutive 2% drops = 3 buys at $0.58, $0.57, $0.56
+    # Then drop to $0.50 which is below 5% from average (~$0.57 * 0.95 = $0.54)
+    klines = [
+        {"close": "0.60", "timestamp": 1000, "open": "0.60", "high": "0.60", "low": "0.60", "volume": "1000"},
+        {"close": "0.588", "timestamp": 2000},  # 2% drop -> BUY 1 @ $0.588
+        {"close": "0.576", "timestamp": 3000},  # 2% drop -> BUY 2 @ $0.576
+        {"close": "0.565", "timestamp": 4000},  # 2% drop -> BUY 3 @ $0.565
+        {"close": "0.50", "timestamp": 5000},   # Below 5% from avg -> STOP LOSS
+    ]
+    
+    test = TestBacktestEngine()
+    engine, result = test._run_backtest(config, klines)
+    test._trace_portfolio(engine, 10000.0)
+    
+    print(f"\nResults:")
+    print(f"  Trades: {len(engine.trades)} (expected 3: 2 buys + stop loss)")
+    print(f"  Max drawdown: {result['max_drawdown']}%")
+    print(f"  Total return: {result['total_return']}%")
+    
+    # Verify: 2 buys + 1 sell (stop loss) = 3 trades
+    # The 3rd buy @ $0.565 doesn't happen because stop loss triggers at $0.5 first
+    assert len(engine.trades) == 3, f"Expected 3 trades, got {len(engine.trades)}"
+    
+    # Verify last trade is stop loss
+    last_trade = engine.trades[-1]
+    assert last_trade["type"] == "sell", "Last trade should be sell"
+    assert last_trade.get("exit_reason") == "stop_loss", f"Last trade should be stop_loss, got {last_trade.get('exit_reason')}"
+    
+    # Verify max drawdown is reasonable (close to stop loss %)
+    # Actual loss should be around 5% from weighted average
+    assert result['max_drawdown'] < 10, f"Max drawdown {result['max_drawdown']}% is too high for 5% stop loss"
+    
+    # Position is now 0 after stop loss, so avg_entry_price is None
+    print(f"  Position closed: {engine.position == 0}")
+    print(f"  Final balance: ${engine.current_balance:.2f}")
+    print("PASSED")
+    return True
+
+
+def test_stop_loss_always_results_in_loss():
+    """Test that stop loss ALWAYS results in a loss, never a gain.
+    
+    This tests the scenario where:
+    - You start with $10,000
+    - Price keeps dropping, triggering multiple buys
+    - Stop loss triggers, selling your entire position
+    - Final balance MUST be less than initial balance
+    """
+    print("\n" + "=" * 60)
+    print("TEST 8: Stop Loss Always Results In Loss")
+    print("=" * 60)
+    
+    config = {
+        "bot_id": "test",
+        "strategy_config": {
+            "conditions": [{"type": "price_drop", "threshold": 2, "token": "TEST", "token_address": "0x123"}],
+            "actions": [{"type": "buy", "amount_percent": 20}],
+            "risk_management": {"stop_loss_percent": 5, "take_profit_percent": 5},
+        },
+        "initial_balance": 10000.0,
+        "ave_api_key": "test",
+        "ave_api_plan": "free",
+    }
+    
+    # Price scenario: drops each kline, triggering multiple buys
+    # Final drop triggers stop loss
+    # 
+    # $0.60 -> $0.588 (2% drop) -> BUY 1 @ $0.588
+    # $0.588 -> $0.576 (2% drop) -> BUY 2 @ $0.576  
+    # $0.576 -> $0.565 (2% drop) -> BUY 3 @ $0.565
+    # $0.565 -> $0.535 (5.3% drop) -> STOP LOSS @ $0.535 (5% from weighted avg ~$0.576)
+    klines = [
+        {"close": "0.60", "timestamp": 1000},
+        {"close": "0.588", "timestamp": 2000},  # BUY 1
+        {"close": "0.576", "timestamp": 3000},  # BUY 2
+        {"close": "0.565", "timestamp": 4000},  # BUY 3
+        {"close": "0.535", "timestamp": 5000},  # STOP LOSS
+    ]
+    
+    test = TestBacktestEngine()
+    engine, result = test._run_backtest(config, klines)
+    
+    print(f"\nSetup:")
+    print(f"  Initial balance: $10,000")
+    print(f"  Stop loss: 5%")
+    print(f"  Each buy: 20% of current balance")
+    print(f"\nTrades:")
+    for i, trade in enumerate(engine.trades):
+        exit_info = f" ({trade.get('exit_reason', '')})" if 'exit_reason' in trade else ""
+        print(f"  {i+1}. {trade['type']} @ ${trade['price']} - ${trade['amount']:.2f}{exit_info}")
+    
+    print(f"\nResults:")
+    print(f"  Final balance: ${engine.current_balance:.2f}")
+    print(f"  Total return: {result['total_return']:.2f}%")
+    print(f"  Max drawdown: {result['max_drawdown']:.2f}%")
+    
+    # CRITICAL ASSERTION: Stop loss MUST result in loss
+    assert engine.current_balance < 10000.0, \
+        f"BUG: Stop loss resulted in GAIN! Balance went from $10,000 to ${engine.current_balance:.2f}"
+    
+    # Also verify total return is negative
+    assert result['total_return'] < 0, \
+        f"BUG: Total return is positive ({result['total_return']:.2f}%) after stop loss!"
+    
+    # Max drawdown should reflect the actual loss (close to stop loss %)
+    assert result['max_drawdown'] < 10, \
+        f"Max drawdown ({result['max_drawdown']:.2f}%) seems too high"
+    
+    print(f"\n✓ PASSED: Stop loss correctly resulted in ${10000 - engine.current_balance:.2f} loss")
+    return True
+
+
+if __name__ == "__main__":
+    run_tests()
+    test_dca_multiple_buys()
+    test_stop_loss_always_results_in_loss()

src/backend/tests/test_simulate_engine.py

@@ -0,0 +1,386 @@
+import pytest
+import asyncio
+from datetime import datetime
+from unittest.mock import AsyncMock, MagicMock
+
+import sys
+sys.path.insert(0, 'src/backend')
+
+from app.services.simulate.engine import SimulateEngine
+
+
+class MockAveClient:
+    """Mock AVE client for testing."""
+    
+    def __init__(self, klines_data=None):
+        self.klines_data = klines_data or []
+    
+    async def get_klines(self, token_id, interval="1m", limit=100, start_time=None, end_time=None):
+        return self.klines_data
+
+
+def create_engine(config_override=None, klines_data=None):
+    """Create a test engine with mock client."""
+    config = {
+        "bot_id": "test-bot",
+        "token": "0x1234567890123456789012345678901234567890",
+        "chain": "bsc",
+        "kline_interval": "1m",
+        "max_candles": 10,  # Small number for fast tests
+        "candle_delay": 0,  # No delay in tests
+        "auto_execute": False,
+        "strategy_config": {
+            "conditions": [
+                {"type": "price_drop", "threshold": 5, "token": "TEST", "token_address": "0x1234"}
+            ],
+            "actions": [
+                {"type": "buy", "amount_percent": 10}
+            ],
+            "risk_management": {
+                "stop_loss_percent": 5,
+                "take_profit_percent": 10
+            }
+        },
+        "ave_api_key": "test",
+        "ave_api_plan": "free",
+    }
+    if config_override:
+        config.update(config_override)
+    
+    engine = SimulateEngine(config)
+    engine.ave_client = MockAveClient(klines_data)
+    return engine
+
+
+class TestSimulateEngine:
+    """Unit tests for SimulateEngine."""
+    
+    # ==================== Kline Fetching Tests ====================
+    
+    @pytest.mark.asyncio
+    async def test_fetches_klines_on_start(self):
+        """Engine should fetch klines when run is called."""
+        klines = [
+            {"time": 1000, "open": 100, "high": 105, "low": 98, "close": 102, "volume": 1000},
+            {"time": 2000, "open": 102, "high": 107, "low": 100, "close": 104, "volume": 1100},
+        ]
+        engine = create_engine(klines_data=klines)
+        engine.running = True
+        
+        results = await engine.run()
+        
+        assert engine.status == "completed"
+        assert results["candles_processed"] == 2
+    
+    @pytest.mark.asyncio
+    async def test_handles_no_klines_data(self):
+        """Engine should handle empty klines gracefully."""
+        engine = create_engine(klines_data=[])
+        engine.running = True
+        
+        results = await engine.run()
+        
+        assert engine.status == "failed"
+        assert "error" in results
+        assert "No kline data" in results["error"]
+    
+    # ==================== Price Drop Condition Tests ====================
+    
+    @pytest.mark.asyncio
+    async def test_price_drop_condition_triggers_buy(self):
+        """Price drop >= threshold should trigger BUY signal."""
+        # Price drops from 100 to 90 (10% drop) - should trigger 5% threshold
+        klines = [
+            {"time": 1000, "open": 100, "high": 102, "low": 99, "close": 100, "volume": 1000},
+            {"time": 2000, "open": 100, "high": 101, "low": 89, "close": 90, "volume": 1200},  # 10% drop
+        ]
+        engine = create_engine(klines_data=klines)
+        engine.running = True
+        
+        results = await engine.run()
+        
+        assert results["total_signals"] >= 1
+        buy_signals = [s for s in engine.signals if s["signal_type"] == "buy"]
+        assert len(buy_signals) >= 1
+        assert buy_signals[0]["price"] == 90.0
+    
+    @pytest.mark.asyncio
+    async def test_price_drop_below_threshold_no_signal(self):
+        """Price drop < threshold should NOT trigger signal."""
+        # Price drops from 100 to 98 (2% drop) - below 5% threshold
+        klines = [
+            {"time": 1000, "open": 100, "high": 101, "low": 99, "close": 100, "volume": 1000},
+            {"time": 2000, "open": 100, "high": 101, "low": 97, "close": 98, "volume": 1000},  # 2% drop
+        ]
+        engine = create_engine(klines_data=klines)
+        engine.running = True
+        
+        results = await engine.run()
+        
+        assert results["total_signals"] == 0
+    
+    # ==================== Risk Management Tests ====================
+    
+    @pytest.mark.asyncio
+    async def test_stop_loss_triggers_after_buy(self):
+        """Stop loss should trigger SELL after price drops below threshold."""
+        klines = [
+            {"time": 1000, "open": 100, "high": 102, "low": 99, "close": 100, "volume": 1000},
+            {"time": 2000, "open": 100, "high": 101, "low": 89, "close": 90, "volume": 1200},  # BUY triggered @ 90
+            {"time": 3000, "open": 90, "high": 91, "low": 84, "close": 85, "volume": 1300},  # Stop loss @ 85.5 (90 * 0.95)
+        ]
+        engine = create_engine(klines_data=klines)
+        engine.running = True
+        
+        results = await engine.run()
+        
+        buy_signals = [s for s in engine.signals if s["signal_type"] == "buy"]
+        sell_signals = [s for s in engine.signals if s["signal_type"] == "sell"]
+        
+        assert len(buy_signals) >= 1, "Should have at least one BUY signal"
+        assert len(sell_signals) >= 1, "Stop loss should trigger SELL"
+        assert "stop_loss" in sell_signals[0]["reasoning"]
+    
+    @pytest.mark.asyncio
+    async def test_take_profit_triggers_after_buy(self):
+        """Take profit should trigger SELL after price rises above threshold."""
+        klines = [
+            {"time": 1000, "open": 100, "high": 102, "low": 99, "close": 100, "volume": 1000},
+            {"time": 2000, "open": 100, "high": 101, "low": 89, "close": 90, "volume": 1200},  # BUY triggered @ 90
+            {"time": 3000, "open": 90, "high": 101, "low": 89, "close": 100, "volume": 1300},  # TP @ 99 (90 * 1.10)
+        ]
+        engine = create_engine(klines_data=klines)
+        engine.running = True
+        
+        results = await engine.run()
+        
+        buy_signals = [s for s in engine.signals if s["signal_type"] == "buy"]
+        sell_signals = [s for s in engine.signals if s["signal_type"] == "sell"]
+        
+        assert len(buy_signals) >= 1, "Should have at least one BUY signal"
+        assert len(sell_signals) >= 1, "Take profit should trigger SELL"
+        assert "take_profit" in sell_signals[0]["reasoning"]
+    
+    # ==================== Multiple Conditions Tests ====================
+    
+    @pytest.mark.asyncio
+    async def test_no_buy_if_already_in_position(self):
+        """Should not trigger another BUY if already holding position."""
+        klines = [
+            {"time": 1000, "open": 100, "high": 102, "low": 99, "close": 100, "volume": 1000},
+            {"time": 2000, "open": 100, "high": 101, "low": 89, "close": 90, "volume": 1200},  # BUY triggered
+            {"time": 3000, "open": 90, "high": 91, "low": 85, "close": 86, "volume": 1300},  # Another drop but already in position
+            {"time": 4000, "open": 86, "high": 87, "low": 81, "close": 82, "volume": 1400},  # Another drop
+        ]
+        engine = create_engine(klines_data=klines)
+        engine.running = True
+        
+        results = await engine.run()
+        
+        buy_signals = [s for s in engine.signals if s["signal_type"] == "buy"]
+        
+        # Should only have 1 buy, not multiple
+        assert len(buy_signals) == 1, "Should only have one BUY signal"
+    
+    @pytest.mark.asyncio
+    async def test_can_buy_again_after_sell(self):
+        """Should be able to BUY again after position is closed by risk management."""
+        klines = [
+            {"time": 1000, "open": 100, "high": 102, "low": 99, "close": 100, "volume": 1000},
+            # First trade
+            {"time": 2000, "open": 100, "high": 101, "low": 89, "close": 90, "volume": 1200},  # BUY @ 90
+            {"time": 3000, "open": 90, "high": 91, "low": 84, "close": 85, "volume": 1300},  # STOP LOSS @ 85.5
+            # Second trade
+            {"time": 4000, "open": 85, "high": 86, "low": 79, "close": 80, "volume": 1400},  # BUY @ 80 (after position closed)
+            {"time": 5000, "open": 80, "high": 89, "low": 79, "close": 88, "volume": 1500},  # TP @ 88
+        ]
+        engine = create_engine(klines_data=klines)
+        engine.running = True
+        
+        results = await engine.run()
+        
+        buy_signals = [s for s in engine.signals if s["signal_type"] == "buy"]
+        sell_signals = [s for s in engine.signals if s["signal_type"] == "sell"]
+        
+        assert len(buy_signals) == 2, "Should have two BUY signals"
+        assert len(sell_signals) == 2, "Should have two SELL signals"
+    
+    # ==================== Edge Cases ====================
+    
+    @pytest.mark.asyncio
+    async def test_handles_zero_price(self):
+        """Should skip processing for candles with zero price but still count them."""
+        klines = [
+            {"time": 1000, "open": 100, "high": 102, "low": 99, "close": 100, "volume": 1000},
+            {"time": 2000, "open": 0, "high": 0, "low": 0, "close": 0, "volume": 0},  # Skipped in processing
+            {"time": 3000, "open": 100, "high": 101, "low": 89, "close": 90, "volume": 1200},  # This should work
+        ]
+        engine = create_engine(klines_data=klines)
+        engine.running = True
+        
+        results = await engine.run()
+        
+        # All 3 candles counted, but only 2 valid for condition checking
+        assert results["candles_processed"] == 3
+        # Only 1 signal (the valid candle that dropped 10%)
+        assert results["total_signals"] == 1
+    
+    @pytest.mark.asyncio
+    async def test_max_candles_limit(self):
+        """Should respect max_candles limit."""
+        klines = [
+            {"time": i * 1000, "open": 100, "high": 101, "low": 99, "close": 100, "volume": 1000}
+            for i in range(1, 201)  # 200 candles
+        ]
+        engine = create_engine(klines_data=klines, config_override={"max_candles": 50})
+        engine.running = True
+        
+        results = await engine.run()
+        
+        assert results["candles_processed"] == 50
+    
+    @pytest.mark.asyncio
+    async def test_stop_interrupts_processing(self):
+        """Should stop processing when stop() is called."""
+        klines = [
+            {"time": i * 1000, "open": 100, "high": 101, "low": 99, "close": 100, "volume": 1000}
+            for i in range(1, 101)
+        ]
+        engine = create_engine(klines_data=klines)
+        engine.running = True
+        engine.run_id = "test"
+        
+        # Stop after a few candles
+        async def stop_after_delay():
+            await asyncio.sleep(0.1)
+            engine.stop()
+        
+        await asyncio.gather(engine.run(), stop_after_delay())
+        
+        assert engine.status == "stopped"
+        # Should have processed some candles before stopping
+        assert engine.last_processed_time is not None
+    
+    # ==================== Price Movement Display Tests ====================
+    
+    @pytest.mark.asyncio
+    async def test_records_all_processed_prices(self):
+        """Should track last processed time for display purposes."""
+        klines = [
+            {"time": 1000, "open": 100, "high": 102, "low": 99, "close": 100, "volume": 1000},
+            {"time": 2000, "open": 100, "high": 101, "low": 99, "close": 101, "volume": 1100},
+            {"time": 3000, "open": 101, "high": 103, "low": 100, "close": 102, "volume": 1200},
+        ]
+        engine = create_engine(klines_data=klines)
+        engine.running = True
+        
+        await engine.run()
+        
+        # Should have tracked the last candle's time
+        assert engine.last_processed_time == 3000
+    
+    @pytest.mark.asyncio
+    async def test_tracks_price_changes(self):
+        """Should track price changes for potential chart display."""
+        klines = [
+            {"time": 1000, "open": 100, "high": 102, "low": 99, "close": 100, "volume": 1000},
+            {"time": 2000, "open": 100, "high": 105, "low": 99, "close": 104, "volume": 1100},
+        ]
+        engine = create_engine(klines_data=klines)
+        engine.running = True
+        
+        await engine.run()
+        
+        # Last close should be the last candle's close
+        assert engine.last_close == 104.0
+
+    # ==================== Integration Tests ====================
+    
+    @pytest.mark.asyncio
+    async def test_full_simulation_workflow_generates_signals_and_trades(self):
+        """
+        Full integration test: provides klines with clear price movements
+        and verifies signals and trade_log are populated.
+        
+        This test ensures the simulation is working by:
+        1. Creating klines with obvious price movements (drops > 0.1%)
+        2. Using a very low threshold (0.1%)
+        3. Verifying signals are generated
+        4. Verifying trade_log is populated
+        5. Verifying we have buy/sell actions
+        """
+        # Create klines with clear price drops and rises
+        klines = [
+            {"time": 1000, "open": 100, "high": 101, "low": 99, "close": 100, "volume": 1000},  # Flat
+            {"time": 2000, "open": 100, "high": 101, "low": 99.9, "close": 99.95, "volume": 1000},  # 0.05% drop
+            {"time": 3000, "open": 99.95, "high": 100, "low": 99.5, "close": 99.5, "volume": 1000},  # 0.45% drop
+            {"time": 4000, "open": 99.5, "high": 100, "low": 99, "close": 99.2, "volume": 1000},   # 0.30% drop
+            {"time": 5000, "open": 99.2, "high": 100, "low": 98, "close": 98.5, "volume": 1000},   # 0.71% drop
+            {"time": 6000, "open": 98.5, "high": 99, "low": 98, "close": 98.8, "volume": 1000},    # 0.30% rise
+            {"time": 7000, "open": 98.8, "high": 99, "low": 98, "close": 98.3, "volume": 1000},   # 0.51% drop
+            {"time": 8000, "open": 98.3, "high": 99, "low": 97, "close": 97.5, "volume": 1000},   # 0.81% drop
+            {"time": 9000, "open": 97.5, "high": 98, "low": 96, "close": 96.5, "volume": 1000},   # 1.03% drop
+        ]
+        
+        # Use very low threshold to ensure signals are generated
+        config_override = {
+            "max_candles": 100,
+            "strategy_config": {
+                "conditions": [
+                    {"type": "price_drop", "threshold": 0.1, "token": "TEST", "token_address": "0x1234"}
+                ],
+                "actions": [
+                    {"type": "buy", "amount_percent": 10}
+                ],
+                "risk_management": {
+                    "stop_loss_percent": 5,
+                    "take_profit_percent": 5
+                }
+            }
+        }
+        
+        engine = create_engine(config_override=config_override, klines_data=klines)
+        engine.running = True
+        engine.run_id = "integration-test"
+        
+        results = await engine.run()
+        
+        # Verify results
+        print(f"\n=== Integration Test Results ===")
+        print(f"Status: {engine.status}")
+        print(f"Candles processed: {results.get('candles_processed')}")
+        print(f"Signals count: {len(engine.signals)}")
+        print(f"Trade log count: {len(engine.trade_log)}")
+        
+        # ASSERTIONS - These should NEVER fail if simulation is working
+        assert engine.status == "completed", "Simulation should complete successfully"
+        assert results.get("candles_processed") == len(klines), f"Should process all {len(klines)} candles"
+        
+        # Critical: signals should NOT be empty
+        assert len(engine.signals) > 0, "SIGNALS SHOULD NOT BE EMPTY! Simulation is not generating signals."
+        print(f"Signals: {[s['signal_type'] for s in engine.signals]}")
+        
+        # Critical: trade_log should NOT be empty
+        assert len(engine.trade_log) > 0, "TRADE_LOG SHOULD NOT BE EMPTY! No activity logged."
+        print(f"Trade log: {[t['action'] for t in engine.trade_log]}")
+        
+        # Should have at least one BUY signal
+        buy_signals = [s for s in engine.signals if s['signal_type'] == 'buy']
+        assert len(buy_signals) > 0, "Should have at least one BUY signal"
+        print(f"Buy signals: {len(buy_signals)}")
+        
+        # Verify trade_log has BUY action
+        buy_trades = [t for t in engine.trade_log if t['action'] == 'buy']
+        assert len(buy_trades) > 0, "Trade log should contain BUY actions"
+        
+        # Verify results contain the data
+        assert "signals" in results, "Results should contain signals"
+        assert "trade_log" in results, "Results should contain trade_log"
+        
+        print("\n=== Integration Test PASSED ===")
+        print(f"Simulation working correctly!")
+        print(f"Generated {len(engine.signals)} signals and {len(engine.trade_log)} trade log entries")
+
+
+if __name__ == "__main__":
+    pytest.main([__file__, "-v"])

src/frontend/package-lock.json

@@ -7,6 +7,9 @@
 		"": {
 			"name": "frontend",
 			"version": "0.0.1",
+			"dependencies": {
+				"chart.js": "^4.5.1"
+			},
 			"devDependencies": {
 				"@sveltejs/adapter-auto": "^7.0.1",
 				"@sveltejs/kit": "^2.57.0",
@@ -101,6 +104,12 @@
 				"@jridgewell/sourcemap-codec": "^1.4.14"
 			}
 		},
+		"node_modules/@kurkle/color": {
+			"version": "0.3.4",
+			"resolved": "https://registry.npmjs.org/@kurkle/color/-/color-0.3.4.tgz",
+			"integrity": "sha512-M5UknZPHRu3DEDWoipU6sE8PdkZ6Z/S+v4dD+Ke8IaNlpdSQah50lz1KtcFBa2vsdOnwbbnxJwVM4wty6udA5w==",
+			"license": "MIT"
+		},
 		"node_modules/@napi-rs/wasm-runtime": {
 			"version": "1.1.3",
 			"resolved": "https://registry.npmjs.org/@napi-rs/wasm-runtime/-/wasm-runtime-1.1.3.tgz",
@@ -569,6 +578,18 @@
 				"node": ">= 0.4"
 			}
 		},
+		"node_modules/chart.js": {
+			"version": "4.5.1",
+			"resolved": "https://registry.npmjs.org/chart.js/-/chart.js-4.5.1.tgz",
+			"integrity": "sha512-GIjfiT9dbmHRiYi6Nl2yFCq7kkwdkp1W/lp2J99rX0yo9tgJGn3lKQATztIjb5tVtevcBtIdICNWqlq5+E8/Pw==",
+			"license": "MIT",
+			"dependencies": {
+				"@kurkle/color": "^0.3.0"
+			},
+			"engines": {
+				"pnpm": ">=8"
+			}
+		},
 		"node_modules/chokidar": {
 			"version": "4.0.3",
 			"resolved": "https://registry.npmjs.org/chokidar/-/chokidar-4.0.3.tgz",

src/frontend/package.json

@@ -19,5 +19,8 @@
 		"svelte-check": "^4.4.6",
 		"typescript": "^6.0.2",
 		"vite": "^8.0.7"
+	},
+	"dependencies": {
+		"chart.js": "^4.5.1"
 	}
 }

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

@@ -21,7 +21,20 @@ function getAuthHeaders(): HeadersInit {
 async function handleResponse<T>(response: Response): Promise<T> {
 	if (!response.ok) {
 		const error = await response.json().catch(() => ({ detail: 'An error occurred' }));
-		throw new Error(error.detail || `HTTP error ${response.status}`);
+		let errorMessage = 'An error occurred';
+		
+		if (typeof error.detail === 'string') {
+			errorMessage = error.detail;
+		} else if (Array.isArray(error.detail)) {
+			// Handle FastAPI validation error format: [{type, loc, msg, input}]
+			errorMessage = error.detail.map((e: any) => e.msg || JSON.stringify(e)).join(', ');
+		} else if (error.message) {
+			errorMessage = error.message;
+		} else {
+			errorMessage = `HTTP error ${response.status}`;
+		}
+		
+		throw new Error(errorMessage);
 	}
 	return response.json();
 }
@@ -41,7 +54,7 @@ export const api = {
 			const response = await fetch(`${API_URL}/auth/login`, {
 				method: 'POST',
 				headers: { 'Content-Type': 'application/json' },
-				body: JSON.stringify({ email, password })
+				body: JSON.stringify({ username: email, password })
 			});
 			return handleResponse<AuthResponse>(response);
 		},
@@ -104,11 +117,12 @@ 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);
 		},
@@ -126,7 +140,7 @@ export const api = {
 			const response = await fetch(`${API_URL}/bots/${botId}/backtest`, {
 				method: 'POST',
 				headers: getAuthHeaders(),
-				body: JSON.stringify(config)
+				body: JSON.stringify({ ...config, chain: 'bsc' })
 			});
 			return handleResponse<Backtest>(response);
 		},
@@ -153,11 +167,29 @@ export const api = {
 			if (!response.ok) {
 				throw new Error(`HTTP error ${response.status}`);
 			}
+		},
+
+		async getTrades(botId: string, runId: string, page: number = 1, perPage: number = 5): Promise<{
+			trades: any[];
+			total_trades: number;
+			page: number;
+			per_page: number;
+			total_pages: number;
+			has_next: boolean;
+			has_prev: boolean;
+		}> {
+			const response = await fetch(`${API_URL}/bots/${botId}/backtest/${runId}/trades?page=${page}&per_page=${perPage}`, {
+				headers: getAuthHeaders()
+			});
+			if (!response.ok) {
+				throw new Error(`HTTP error ${response.status}`);
+			}
+			return response.json();
 		}
 	},
 
 	simulate: {
-		async start(botId: string, config: { token: string; interval_seconds: number; auto_execute: boolean }): Promise<Simulation> {
+		async start(botId: string, config: { token: string; chain?: string; kline_interval: string }): Promise<Simulation> {
 			const response = await fetch(`${API_URL}/bots/${botId}/simulate`, {
 				method: 'POST',
 				headers: getAuthHeaders(),

src/frontend/src/lib/api/types.ts

@@ -26,6 +26,7 @@ export interface StrategyConfig {
 export interface Condition {
 	type: 'price_drop' | 'price_rise' | 'volume_spike' | 'price_level';
 	token: string;
+	token_address?: string;
 	chain?: string;
 	threshold?: number;
 	price?: number;
@@ -37,6 +38,7 @@ export interface Action {
 	type: 'buy' | 'sell' | 'hold';
 	amount_percent?: number;
 	token?: string;
+	token_address?: string;
 }
 
 export interface RiskManagement {
@@ -62,13 +64,16 @@ export interface Backtest {
 	bot_id: string;
 	started_at: string;
 	ended_at: string | null;
-	status: 'running' | 'completed' | 'failed';
+	status: 'running' | 'completed' | 'failed' | 'stopped';
 	config: BacktestConfig;
 	result: BacktestResult | null;
+	progress?: number;
 }
 
 export interface BacktestConfig {
 	token: string;
+	token_name?: string;
+	chain: string;
 	timeframe: string;
 	start_date: string;
 	end_date: string;
@@ -84,19 +89,63 @@ export interface BacktestResult {
 	sharpe_ratio: number;
 }
 
+export interface PaginatedTrades {
+	trades: Trade[];
+	total_trades: number;
+	page: number;
+	per_page: number;
+	total_pages: number;
+	has_next: boolean;
+	has_prev: boolean;
+}
+
+export interface Trade {
+	type: 'buy' | 'sell';
+	token: string;
+	price: number;
+	amount: number;
+	quantity: number;
+	timestamp: number;
+	exit_reason?: 'stop_loss' | 'take_profit' | string;
+}
+
 export interface Simulation {
 	id: string;
 	bot_id: string;
 	started_at: string;
-	status: 'running' | 'stopped';
+	status: 'running' | 'stopped' | 'completed';
 	config: SimulationConfig;
 	signals: Signal[] | null;
+	klines?: { time: number; close: number }[];
+	trade_log?: TradeLogEntry[];
+	portfolio?: Portfolio;
+	current_candle_index?: number;
+	total_candles?: number;
+	candles_processed?: number;
 }
 
 export interface SimulationConfig {
 	token: string;
-	interval_seconds: number;
+	chain?: string;
-	auto_execute: boolean;
+	kline_interval?: string;
+}
+
+export interface TradeLogEntry {
+	time: number;
+	price: number;
+	action: 'buy' | 'sell' | 'hold';
+	reason: string;
+	position: number;
+	entry_price: number | null;
+}
+
+export interface Portfolio {
+	initial_balance: number;
+	current_balance: number;
+	position: number;
+	position_token: string;
+	entry_price: number;
+	current_price: number;
 }
 
 export interface Signal {
@@ -123,6 +172,17 @@ export interface BotChatRequest {
 
 export interface BotChatResponse {
 	response: string;
+	thinking: string | null;
 	strategy_config: StrategyConfig | null;
 	success: boolean;
+	strategy_needs_confirmation?: boolean;
+	strategy_data?: StrategyConfig | null;
+	token_search_results?: TokenSearchResult[] | null;
+}
+
+export interface TokenSearchResult {
+	symbol: string;
+	name: string;
+	address: string;
+	chain: string;
 }

src/frontend/src/lib/components/ChatInterface.svelte

@@ -1,6 +1,36 @@
 <script lang="ts">
 	import type { Bot } from '$lib/api';
 	import type { ChatMessage } from '$lib/stores/chatStore';
+	import { parseMarkdown, parseInlineElements, type InlineSegment } from '$lib/utils/markdown';
+
+	interface ToolItem {
+		name: string;
+		description: string;
+		command: string;
+	}
+
+	const TOOLS: { category: string; label: string; tools: ToolItem[] }[] = [
+		{
+			category: 'randebu',
+			label: '🤖 Randebu Built-in',
+			tools: [
+				{ name: 'backtest', description: 'Run strategy backtest', command: '/backtest' },
+				{ name: 'simulate', description: 'Start/stop simulation', command: '/simulate' },
+				{ name: 'strategy', description: 'View/update strategy', command: '/strategy' },
+			]
+		},
+		{
+			category: 'ave',
+			label: '☁️ AVE Cloud Skills',
+			tools: [
+				{ name: 'search', description: 'Token search', command: '/search' },
+				{ name: 'trending', description: 'Popular tokens', command: '/trending' },
+				{ name: 'risk', description: 'Honeypot detection', command: '/risk' },
+				{ name: 'token', description: 'Token details', command: '/token' },
+				{ name: 'price', description: 'Batch prices', command: '/price' },
+			]
+		}
+	];
 
 	interface Props {
 		bot: Bot | null;
@@ -24,9 +54,17 @@
 
 	let messageInput = $state('');
 	let chatContainer: HTMLDivElement;
+	let expandedThinking: Record<string, boolean> = $state({});
+	let showSlashMenu = $state(false);
+	let slashMenuPosition = $state({ top: 0, left: 0 });
+	let selectedIndex = $state(0);
+
+	// Use $derived for filteredTools
+	let filteredTools = $derived(messageInput.startsWith('/') ? TOOLS.flatMap(t => t.tools).filter(tool => tool.name.toLowerCase().startsWith(messageInput.slice(1).toLowerCase()) || tool.command.toLowerCase().startsWith(messageInput.slice(1).toLowerCase())) : []);
 
 	function handleSend() {
 		if (!messageInput.trim()) return;
+		showSlashMenu = false;
 		onSendMessage(messageInput);
 		messageInput = '';
 	}
@@ -34,7 +72,54 @@
 	function handleKeydown(e: KeyboardEvent) {
 		if (e.key === 'Enter' && !e.shiftKey) {
 			e.preventDefault();
-			handleSend();
+			if (showSlashMenu && filteredTools.length > 0) {
+				selectTool(filteredTools[selectedIndex]);
+			} else {
+				handleSend();
+			}
+		} else if (e.key === 'ArrowDown' && showSlashMenu) {
+			e.preventDefault();
+			selectedIndex = Math.min(selectedIndex + 1, filteredTools.length - 1);
+		} else if (e.key === 'ArrowUp' && showSlashMenu) {
+			e.preventDefault();
+			selectedIndex = Math.max(selectedIndex - 1, 0);
+		} else if (e.key === 'Escape' && showSlashMenu) {
+			showSlashMenu = false;
+		} else if (e.key === 'Tab' && showSlashMenu && filteredTools.length > 0) {
+			e.preventDefault();
+			selectTool(filteredTools[selectedIndex]);
+		}
+	}
+
+	function handleInput(e: Event) {
+		const target = e.target as HTMLTextAreaElement;
+		const value = target.value;
+		messageInput = value;
+
+		if (value.startsWith('/')) {
+			selectedIndex = 0;
+			showSlashMenu = filteredTools.length > 0;
+
+			if (showSlashMenu) {
+				// Position menu above the textarea
+				const rect = target.getBoundingClientRect();
+				const menuHeight = 300;
+				slashMenuPosition = {
+					top: Math.max(10, rect.top - menuHeight),
+					left: rect.left
+				};
+			}
+		} else {
+			showSlashMenu = false;
+		}
+	}
+
+	function selectTool(tool: ToolItem) {
+		messageInput = tool.command + ' ';
+		showSlashMenu = false;
+		const textarea = document.querySelector('.input-container textarea') as HTMLTextAreaElement;
+		if (textarea) {
+			textarea.focus();
 		}
 	}
 
@@ -45,6 +130,10 @@
 		}
 	}
 
+	function toggleThinkingExpand(messageId: string) {
+		expandedThinking[messageId] = !expandedThinking[messageId];
+	}
+
 	$effect(() => {
 		if (messages.length && chatContainer) {
 			setTimeout(() => {
@@ -52,8 +141,33 @@
 			}, 50);
 		}
 	});
+
+	function renderContent(content: string) {
+		return parseMarkdown(content);
+	}
+
+	function renderInline(segments: InlineSegment[]): string {
+		return segments.map(seg => {
+			switch (seg.type) {
+				case 'bold': return `<strong>${seg.content}</strong>`;
+				case 'italic': return `<em>${seg.content}</em>`;
+				case 'code': return `<code class="inline-code">${seg.content}</code>`;
+				case 'link': return `<a href="${seg.href || '#'}" target="_blank" rel="noopener noreferrer">${seg.content}</a>`;
+				default: return seg.content;
+			}
+		}).join('');
+	}
+
+	function handleClickOutside(e: MouseEvent) {
+		const target = e.target as HTMLElement;
+		if (!target.closest('.slash-menu') && !target.closest('.input-container textarea')) {
+			showSlashMenu = false;
+		}
+	}
 </script>
 
+<svelte:window on:click={handleClickOutside} />
+
 <div class="chat-interface">
 	{#if showBotSelector && availableBots.length > 0}
 		<div class="bot-selector">
@@ -78,8 +192,99 @@
 
 		{#each messages as message}
 			<div class="message {message.role}">
+				{#if message.role === 'assistant' && message.thinking}
+					{@const firstLine = message.thinking.split('\n')[0]}
+					{@const isExpanded = expandedThinking[message.id] ?? false}
+					<div class="thinking-section">
+						<button class="thinking-toggle" onclick={() => toggleThinkingExpand(message.id)}>
+							<span class="thinking-icon">{isExpanded ? '▼' : '▶'}</span>
+							<span class="thinking-label">{isExpanded ? 'Hide reasoning' : 'Show reasoning'}</span>
+							{#if !isExpanded}
+								<span class="thinking-preview"> — {firstLine.slice(0, 60)}{firstLine.length > 60 ? '...' : ''}</span>
+							{/if}
+						</button>
+						{#if isExpanded}
+							<div class="thinking-content">
+								{message.thinking}
+							</div>
+						{/if}
+					</div>
+				{/if}
 				<div class="message-content">
-					{message.content}
+					{#each renderContent(message.content) as segment}
+						{#if segment.type === 'bold'}
+							<strong>{segment.content}</strong>
+						{:else if segment.type === 'italic'}
+							<em>{segment.content}</em>
+						{:else if segment.type === 'code'}
+							<code class="inline-code">{segment.content}</code>
+						{:else if segment.type === 'codeBlock'}
+							<pre class="code-block"><code>{segment.content}</code></pre>
+						{:else if segment.type === 'link'}
+							<a href={segment.content} target="_blank" rel="noopener noreferrer">{segment.content}</a>
+						{:else if segment.type === 'list' && segment.items}
+							<ul>
+								{#each segment.items as item}
+									<li>{@html renderInline(parseInlineElements(item))}</li>
+								{/each}
+							</ul>
+						{:else if segment.type === 'table' && segment.headers && segment.rows}
+							<div class="table-wrapper">
+								<table class="markdown-table">
+									<thead>
+										<tr>
+											{#each segment.headers as header}
+												<th>
+													{#each header as cellSeg}
+														{#if cellSeg.type === 'bold'}
+															<strong>{cellSeg.content}</strong>
+														{:else if cellSeg.type === 'italic'}
+															<em>{cellSeg.content}</em>
+														{:else if cellSeg.type === 'code'}
+															<code class="inline-code">{cellSeg.content}</code>
+														{:else if cellSeg.type === 'link'}
+															<a href={cellSeg.href} target="_blank" rel="noopener noreferrer">{cellSeg.content}</a>
+														{:else}
+															{cellSeg.content}
+														{/if}
+													{/each}
+												</th>
+											{/each}
+										</tr>
+									</thead>
+									<tbody>
+										{#each segment.rows as row}
+											<tr>
+												{#each row as cell}
+													<td>
+														{#each cell as cellSeg}
+															{#if cellSeg.type === 'bold'}
+																<strong>{cellSeg.content}</strong>
+															{:else if cellSeg.type === 'italic'}
+																<em>{cellSeg.content}</em>
+															{:else if cellSeg.type === 'code'}
+																<code class="inline-code">{cellSeg.content}</code>
+															{:else if cellSeg.type === 'link'}
+																<a href={cellSeg.href} target="_blank" rel="noopener noreferrer">{cellSeg.content}</a>
+															{:else}
+																{cellSeg.content}
+															{/if}
+														{/each}
+													</td>
+												{/each}
+											</tr>
+										{/each}
+									</tbody>
+								</table>
+							</div>
+						{:else if segment.type === 'heading'}
+							<h4 class="content-heading">{segment.content}</h4>
+						{:else if segment.type === 'lineBreak'}
+							<br />
+						{:else}
+							{segment.content}
+						{/if}
+					{/each}
 				</div>
 				<div class="message-time">
 					{message.timestamp.toLocaleTimeString()}
@@ -89,10 +294,12 @@
 
 		{#if isSending}
 			<div class="message assistant">
-				<div class="message-content typing">
+				<div class="message-content">
-					<span class="dot"></span>
+					<div class="typing">
-					<span class="dot"></span>
+						<span class="dot"></span>
-					<span class="dot"></span>
+						<span class="dot"></span>
+						<span class="dot"></span>
+					</div>
 				</div>
 			</div>
 		{/if}
@@ -100,14 +307,35 @@
 
 	{#if bot}
 		<div class="input-container">
+			{#if showSlashMenu && filteredTools.length > 0}
+				<div class="slash-menu" style="top: {slashMenuPosition.top}px; left: {slashMenuPosition.left}px;">
+					<div class="slash-menu-header">Available Commands</div>
+					{#each TOOLS as group}
+						{#if group.tools.some(t => filteredTools.includes(t))}
+							<div class="slash-menu-category">{group.label}</div>
+							{#each group.tools.filter(t => filteredTools.includes(t)) as tool, i}
+								<button
+									class="slash-menu-item"
+									class:selected={filteredTools.indexOf(tool) === selectedIndex}
+									onclick={() => selectTool(tool)}
+								>
+									<span class="slash-command">{tool.command}</span>
+									<span class="slash-description">{tool.description}</span>
+								</button>
+							{/each}
+						{/if}
+					{/each}
+					<div class="slash-menu-hint">Press Tab to select, Enter to send</div>
+				</div>
+			{/if}
 			<textarea
-				bind:value={messageInput}
+				value={messageInput}
+				oninput={handleInput}
 				onkeydown={handleKeydown}
-				placeholder="Describe your trading strategy..."
+				placeholder="Describe your trading strategy... (or type / for commands)"
 				rows="1"
-				disabled={isSending}
 			></textarea>
-			<button onclick={handleSend} disabled={isSending || !messageInput.trim()}>
+			<button onclick={handleSend}>
 				Send
 			</button>
 		</div>
@@ -206,6 +434,64 @@
 		border-bottom-left-radius: 4px;
 	}
 
+	.thinking-section {
+		margin-bottom: 0.5rem;
+		padding: 0.5rem 0.75rem;
+		background: rgba(255, 255, 255, 0.03);
+		border-radius: 8px;
+		border: 1px solid rgba(255, 255, 255, 0.1);
+	}
+
+	.thinking-toggle {
+		display: flex;
+		align-items: center;
+		gap: 0.5rem;
+		background: none;
+		border: none;
+		color: #888;
+		cursor: pointer;
+		padding: 0.25rem 0.5rem;
+		border-radius: 4px;
+		font-size: 0.8rem;
+		transition: background 0.2s;
+		width: 100%;
+		text-align: left;
+	}
+
+	.thinking-toggle:hover {
+		background: rgba(255, 255, 255, 0.1);
+	}
+
+	.thinking-icon {
+		font-size: 0.6rem;
+		color: #667eea;
+	}
+
+	.thinking-label {
+		font-weight: 500;
+		text-transform: uppercase;
+		letter-spacing: 0.5px;
+		color: #667eea;
+	}
+
+	.thinking-preview {
+		color: #666;
+		font-style: italic;
+		font-weight: normal;
+		text-transform: none;
+		letter-spacing: normal;
+	}
+
+	.thinking-content {
+		color: #888;
+		font-size: 0.85rem;
+		padding: 0.75rem 0.5rem;
+		border-top: 1px solid rgba(255, 255, 255, 0.1);
+		margin-top: 0.5rem;
+		white-space: pre-wrap;
+		line-height: 1.6;
+	}
+
 	.message.system .message-content {
 		background: rgba(251, 191, 36, 0.1);
 		color: #fbbf24;
@@ -213,6 +499,92 @@
 		border: 1px solid rgba(251, 191, 36, 0.3);
 	}
 
+	.inline-code {
+		background: rgba(0, 0, 0, 0.3);
+		padding: 0.15rem 0.4rem;
+		border-radius: 4px;
+		font-family: 'Monaco', 'Menlo', 'Ubuntu Mono', monospace;
+		font-size: 0.85em;
+	}
+
+	.code-block {
+		background: rgba(0, 0, 0, 0.4);
+		padding: 0.75rem;
+		border-radius: 6px;
+		overflow-x: auto;
+		font-family: 'Monaco', 'Menlo', 'Ubuntu Mono', monospace;
+		font-size: 0.85rem;
+		margin: 0.5rem 0;
+	}
+
+	.code-block code {
+		white-space: pre;
+	}
+
+	ul {
+		margin: 0.5rem 0;
+		padding-left: 1.5rem;
+	}
+
+	li {
+		margin: 0.25rem 0;
+	}
+
+	.content-heading {
+		font-size: 1rem;
+		font-weight: 600;
+		margin: 1rem 0 0.5rem;
+		color: #fff;
+	}
+
+	.content-heading:first-child {
+		margin-top: 0;
+	}
+
+	.table-wrapper {
+		overflow-x: auto;
+		margin: 0.75rem 0;
+	}
+
+	.markdown-table {
+		border-collapse: collapse;
+		width: 100%;
+		font-size: 0.85rem;
+		background: rgba(0, 0, 0, 0.2);
+		border-radius: 6px;
+		overflow: hidden;
+	}
+
+	.markdown-table th,
+	.markdown-table td {
+		padding: 0.5rem 0.75rem;
+		text-align: left;
+		border-bottom: 1px solid rgba(255, 255, 255, 0.1);
+	}
+
+	.markdown-table th {
+		background: rgba(102, 126, 234, 0.2);
+		font-weight: 600;
+		color: #667eea;
+	}
+
+	.markdown-table tr:last-child td {
+		border-bottom: none;
+	}
+
+	.markdown-table tr:hover td {
+		background: rgba(255, 255, 255, 0.05);
+	}
+
+	a {
+		color: #667eea;
+		text-decoration: none;
+	}
+
+	a:hover {
+		text-decoration: underline;
+	}
+
 	.message-time {
 		font-size: 0.7rem;
 		color: #666;
@@ -223,7 +595,7 @@
 	.typing {
 		display: flex;
 		gap: 4px;
-		padding: 1rem 1.25rem;
+		padding: 0.5rem;
 	}
 
 	.dot {
@@ -297,4 +669,76 @@
 		opacity: 0.5;
 		cursor: not-allowed;
 	}
+
+	.slash-menu {
+		position: fixed;
+		background: rgba(20, 20, 20, 0.98);
+		border: 1px solid rgba(255, 255, 255, 0.15);
+		border-radius: 12px;
+		padding: 0.5rem;
+		min-width: 280px;
+		max-width: 400px;
+		max-height: 300px;
+		overflow-y: auto;
+		z-index: 1000;
+		box-shadow: 0 8px 32px rgba(0, 0, 0, 0.5);
+	}
+
+	.slash-menu-header {
+		font-size: 0.75rem;
+		color: #888;
+		padding: 0.5rem 0.75rem;
+		text-transform: uppercase;
+		letter-spacing: 0.5px;
+		border-bottom: 1px solid rgba(255, 255, 255, 0.1);
+		margin-bottom: 0.5rem;
+	}
+
+	.slash-menu-category {
+		font-size: 0.75rem;
+		color: #666;
+		padding: 0.5rem 0.75rem 0.25rem;
+	}
+
+	.slash-menu-item {
+		display: flex;
+		flex-direction: column;
+		align-items: flex-start;
+		width: 100%;
+		padding: 0.5rem 0.75rem;
+		background: transparent;
+		border: none;
+		border-radius: 8px;
+		cursor: pointer;
+		text-align: left;
+		transition: background 0.15s;
+		margin: 0.15rem 0;
+	}
+
+	.slash-menu-item:hover,
+	.slash-menu-item.selected {
+		background: rgba(102, 126, 234, 0.2);
+	}
+
+	.slash-command {
+		font-family: 'Monaco', 'Menlo', 'Ubuntu Mono', monospace;
+		font-size: 0.9rem;
+		color: #667eea;
+		font-weight: 500;
+	}
+
+	.slash-description {
+		font-size: 0.8rem;
+		color: #888;
+		margin-top: 0.15rem;
+	}
+
+	.slash-menu-hint {
+		font-size: 0.7rem;
+		color: #555;
+		padding: 0.5rem 0.75rem;
+		border-top: 1px solid rgba(255, 255, 255, 0.1);
+		margin-top: 0.5rem;
+		text-align: center;
+	}
 </style>

src/frontend/src/lib/components/PortfolioSummary.svelte

@@ -0,0 +1,139 @@
+<script lang="ts">
+	interface Props {
+		initialBalance?: number;
+		currentBalance?: number;
+		position?: number;
+		positionToken?: string;
+		entryPrice?: number;
+		currentPrice?: number;
+	}
+
+	let { 
+		initialBalance = 10000, 
+		currentBalance = 10000, 
+		position = 0,
+		positionToken = '',
+		entryPrice = 0,
+		currentPrice = 0
+	}: Props = $props();
+
+	// Calculate metrics
+	let positionValue = $derived(position * currentPrice);
+	let totalValue = $derived(currentBalance + positionValue);
+	let pnl = $derived(totalValue - initialBalance);
+	let pnlPercent = $derived((pnl / initialBalance) * 100);
+	let unrealizedPnL = $derived(position > 0 && entryPrice > 0 ? (currentPrice - entryPrice) / entryPrice * 100 : 0);
+</script>
+
+<div class="portfolio-summary">
+	<div class="metric">
+		<span class="label">Cash Balance</span>
+		<span class="value">${currentBalance.toFixed(2)}</span>
+	</div>
+	
+	{#if position > 0}
+		<div class="metric">
+			<span class="label">Position ({positionToken || 'Token'})</span>
+			<span class="value highlight">{position.toFixed(6)}</span>
+		</div>
+		
+		<div class="metric">
+			<span class="label">Position Value</span>
+			<span class="value">${positionValue.toFixed(2)}</span>
+		</div>
+		
+		<div class="metric">
+			<span class="label">Entry Price</span>
+			<span class="value">${entryPrice.toFixed(8)}</span>
+		</div>
+		
+		<div class="metric">
+			<span class="label">Current Price</span>
+			<span class="value">${currentPrice.toFixed(8)}</span>
+		</div>
+		
+		<div class="metric">
+			<span class="label">Unrealized P&L</span>
+			<span class="value" class:positive={unrealizedPnL > 0} class:negative={unrealizedPnL < 0}>
+				{unrealizedPnL >= 0 ? '+' : ''}{unrealizedPnL.toFixed(2)}%
+			</span>
+		</div>
+	{/if}
+	
+	<div class="divider"></div>
+	
+	<div class="metric total">
+		<span class="label">Total Value</span>
+		<span class="value">${totalValue.toFixed(2)}</span>
+	</div>
+	
+	<div class="metric">
+		<span class="label">P&L</span>
+		<span class="value large" class:positive={pnl > 0} class:negative={pnl < 0}>
+			{pnl >= 0 ? '+' : ''}${pnl.toFixed(2)} ({pnlPercent >= 0 ? '+' : ''}{pnlPercent.toFixed(2)}%)
+		</span>
+	</div>
+</div>
+
+<style>
+	.portfolio-summary {
+		display: grid;
+		grid-template-columns: repeat(auto-fit, minmax(140px, 1fr));
+		gap: 1rem;
+		padding: 1rem;
+		background: rgba(255, 255, 255, 0.02);
+		border: 1px solid rgba(255, 255, 255, 0.1);
+		border-radius: 8px;
+	}
+
+	.metric {
+		display: flex;
+		flex-direction: column;
+		gap: 0.25rem;
+	}
+
+	.metric .label {
+		font-size: 0.75rem;
+		color: #888;
+		text-transform: uppercase;
+		letter-spacing: 0.5px;
+	}
+
+	.metric .value {
+		font-size: 1rem;
+		font-weight: 600;
+		color: #fff;
+		font-family: monospace;
+	}
+
+	.metric .value.highlight {
+		color: #fbbf24;
+	}
+
+	.metric .value.large {
+		font-size: 1.25rem;
+	}
+
+	.metric.total {
+		grid-column: 1 / -1;
+		padding-top: 0.5rem;
+		border-top: 1px solid rgba(255, 255, 255, 0.05);
+	}
+
+	.metric.total .value {
+		font-size: 1.5rem;
+		color: #667eea;
+	}
+
+	.positive {
+		color: #22c55e !important;
+	}
+
+	.negative {
+		color: #ef4444 !important;
+	}
+
+	.divider {
+		display: none;
+	}
+</style>

src/frontend/src/lib/components/SignalChart.svelte

@@ -1,155 +1,241 @@
 <script lang="ts">
 	import type { Signal } from '$lib/api';
+	import { onMount, tick } from 'svelte';
 
 	interface Props {
-		signals: Signal[];
+		signals?: Signal[];
+		klines?: { time: number; close: number }[];
 		height?: number;
 	}
 
-	let { signals, height = 200 }: Props = $props();
+	let { signals = [], klines = [], height = 200 }: Props = $props();
 
 	let width = $state(800);
 	let containerEl: HTMLDivElement;
+	let canvasEl: HTMLCanvasElement;
+	let initialized = $state(false);
 
-	$effect(() => {
+	onMount(() => {
+		// Set initial width
 		if (containerEl) {
 			width = containerEl.clientWidth;
 		}
+		
+		// Resize observer
+		const resizeObserver = new ResizeObserver(entries => {
+			for (const entry of entries) {
+				width = entry.contentRect.width;
+				drawChart();
+			}
+		});
+		
+		if (containerEl) {
+			resizeObserver.observe(containerEl);
+		}
+		
+		initialized = true;
+		
+		return () => {
+			resizeObserver.disconnect();
+		};
 	});
 
-	function getSignalPosition(signal: Signal, index: number, total: number): { x: number; y: number } {
+	// Draw when data changes
-		const padding = 30;
+	$effect(() => {
-		const chartWidth = width - padding * 2;
+		// Access reactive values to trigger effect
-		const chartHeight = height - padding * 2;
+		const currentSignals = signals;
-		const x = padding + (index / Math.max(total - 1, 1)) * chartWidth;
+		const currentKlines = klines;
-		const priceRange = getPriceRange();
+		const currentWidth = width;
-		const normalizedPrice = priceRange.min === priceRange.max ? 0.5 : 
-			(signal.price - priceRange.min) / (priceRange.max - priceRange.min);
-		const y = padding + (1 - normalizedPrice) * chartHeight;
-		return { x, y };
-	}
 		
-	function getPriceRange(): { min: number; max: number } {
+		// Wait for DOM to be ready
-		if (signals.length === 0) return { min: 0, max: 1 };
+		tick().then(() => {
-		const prices = signals.map(s => s.price);
+			drawChart();
-		const min = Math.min(...prices);
+		});
-		const max = Math.max(...prices);
+	});
-		const padding = (max - min) * 0.1 || 1;
-		return { min: min - padding, max: max + padding };
-	}
 
-	function getSignalColor(signal: Signal): string {
+	function drawChart() {
-		switch (signal.signal_type) {
+		if (!canvasEl) {
-			case 'buy': return '#22c55e';
+			return;
-			case 'sell': return '#ef4444';
-			case 'hold': return '#fbbf24';
-			default: return '#888';
 		}
-	}
 		
-	function getYAxisLabels(): string[] {
+		const ctx = canvasEl.getContext('2d');
-		const range = getPriceRange();
+		if (!ctx) return;
-		const step = (range.max - range.min) / 4;
-		return [
-			range.max.toFixed(6),
-			(range.max - step).toFixed(6),
-			(range.min + step).toFixed(6),
-			range.min.toFixed(6)
-		];
-	}
 
-	function getXAxisLabels(): string[] {
+		const dpr = window.devicePixelRatio || 1;
-		if (signals.length === 0) return [];
+		canvasEl.width = width * dpr;
-		const step = Math.max(1, Math.floor(signals.length / 5));
+		canvasEl.height = height * dpr;
-		const labels: string[] = [];
+		ctx.scale(dpr, dpr);
-		for (let i = 0; i < signals.length; i += step) {
+
-			labels.push(new Date(signals[i].created_at).toLocaleTimeString());
+		// Clear canvas
+		ctx.clearRect(0, 0, width, height);
+
+		// Check if we have data
+		if (klines.length === 0 && signals.length === 0) {
+			return;
+		}
+
+		// Get price data
+		let priceData: { time: number; price: number }[] = [];
+		
+		if (klines.length > 0) {
+			priceData = klines.map(k => ({
+				time: k.time,
+				price: typeof k.close === 'string' ? parseFloat(k.close) : k.close
+			})).filter(d => !isNaN(d.price) && d.price > 0);
+		} else if (signals.length > 0) {
+			priceData = signals.map(s => ({ time: 0, price: s.price }));
+		}
+		
+		if (priceData.length === 0) return;
+
+		const prices = priceData.map(d => d.price);
+		const padding = { top: 20, right: 20, bottom: 45, left: 60 };  // More bottom padding for time labels
+		const chartWidth = width - padding.left - padding.right;
+		const chartHeight = height - padding.top - padding.bottom;
+
+		// Price range with padding
+		const minPrice = Math.min(...prices);
+		const maxPrice = Math.max(...prices);
+		const priceRange = maxPrice - minPrice || 1;
+		const paddedMin = minPrice - priceRange * 0.1;
+		const paddedMax = maxPrice + priceRange * 0.1;
+
+		function priceToY(price: number): number {
+			return padding.top + (1 - (price - paddedMin) / (paddedMax - paddedMin)) * chartHeight;
+		}
+
+		function indexToX(index: number): number {
+			return padding.left + (index / Math.max(prices.length - 1, 1)) * chartWidth;
+		}
+
+		// Draw grid lines
+		ctx.strokeStyle = 'rgba(255, 255, 255, 0.05)';
+		ctx.lineWidth = 1;
+		for (let i = 0; i <= 4; i++) {
+			const y = padding.top + (i / 4) * chartHeight;
+			ctx.beginPath();
+			ctx.moveTo(padding.left, y);
+			ctx.lineTo(width - padding.right, y);
+			ctx.stroke();
+		}
+
+		// Draw Y axis labels
+		ctx.fillStyle = '#888';
+		ctx.font = '10px monospace';
+		ctx.textAlign = 'right';
+		for (let i = 0; i <= 4; i++) {
+			const price = paddedMax - (i / 4) * (paddedMax - paddedMin);
+			const y = padding.top + (i / 4) * chartHeight + 4;
+			ctx.fillText('$' + price.toFixed(6), padding.left - 5, y);
+		}
+
+		// Draw price line
+		ctx.beginPath();
+		ctx.strokeStyle = '#667eea';
+		ctx.lineWidth = 2;
+		ctx.moveTo(indexToX(0), priceToY(prices[0]));
+		for (let i = 1; i < prices.length; i++) {
+			ctx.lineTo(indexToX(i), priceToY(prices[i]));
+		}
+		ctx.stroke();
+
+		// Fill area under line
+		ctx.lineTo(indexToX(prices.length - 1), padding.top + chartHeight);
+		ctx.lineTo(indexToX(0), padding.top + chartHeight);
+		ctx.closePath();
+		const gradient = ctx.createLinearGradient(0, padding.top, 0, padding.top + chartHeight);
+		gradient.addColorStop(0, 'rgba(102, 126, 234, 0.3)');
+		gradient.addColorStop(1, 'rgba(102, 126, 234, 0)');
+		ctx.fillStyle = gradient;
+		ctx.fill();
+
+		// Draw signal markers
+		if (signals.length > 0) {
+			signals.forEach((signal) => {
+				// Find closest price match
+				const signalPrice = signal.price;
+				let closestIndex = 0;
+				let closestDiff = Infinity;
+				
+				for (let i = 0; i < priceData.length; i++) {
+					const diff = Math.abs(priceData[i].price - signalPrice);
+					if (diff < closestDiff) {
+						closestDiff = diff;
+						closestIndex = i;
+					}
+				}
+				
+				const x = indexToX(closestIndex);
+				const y = priceToY(signalPrice);
+				const color = signal.signal_type === 'buy' ? '#22c55e' : '#ef4444';
+
+				// Vertical dashed line
+				ctx.beginPath();
+				ctx.strokeStyle = color;
+				ctx.setLineDash([4, 4]);
+				ctx.moveTo(x, padding.top);
+				ctx.lineTo(x, y);
+				ctx.stroke();
+				ctx.setLineDash([]);
+
+				// Signal dot
+				ctx.beginPath();
+				ctx.arc(x, y, 6, 0, Math.PI * 2);
+				ctx.fillStyle = color;
+				ctx.fill();
+				ctx.strokeStyle = '#fff';
+				ctx.lineWidth = 2;
+				ctx.stroke();
+			});
+		}
+
+		// Draw X axis time labels
+		ctx.fillStyle = '#666';
+		ctx.font = '9px monospace';
+		ctx.textAlign = 'center';
+		
+		const numTimeLabels = Math.min(5, priceData.length);
+		for (let i = 0; i < numTimeLabels; i++) {
+			const dataIndex = Math.floor(i * (priceData.length - 1) / (numTimeLabels - 1 || 1));
+			const x = indexToX(dataIndex);
+			
+			// Convert timestamp to readable time
+			let timeLabel = '';
+			if (priceData[dataIndex].time > 0) {
+				const date = new Date(priceData[dataIndex].time * 1000);
+				timeLabel = date.toLocaleTimeString([], { hour: '2-digit', minute: '2-digit' });
+			} else {
+				timeLabel = `${dataIndex + 1}`;
+			}
+			
+			ctx.fillText(timeLabel, x, height - 5);
+		}
+
+		// Legend
+		ctx.fillStyle = '#888';
+		ctx.font = '12px sans-serif';
+		ctx.textAlign = 'center';
+		
+		if (signals.length > 0) {
+			const buyCount = signals.filter(s => s.signal_type === 'buy').length;
+			const sellCount = signals.filter(s => s.signal_type === 'sell').length;
+			ctx.fillText(`📈 ${buyCount} Buy | ${sellCount} Sell | ${priceData.length} Candles`, width / 2, height - 20);
+		} else {
+			ctx.fillText(`${priceData.length} Candles (No signals generated)`, width / 2, height - 20);
 		}
-		return labels;
 	}
 </script>
 
 <div class="signal-chart" bind:this={containerEl}>
-	{#if signals.length === 0}
+	{#if klines.length === 0 && signals.length === 0}
 		<div class="empty-state">
-			<p>No signals to display</p>
+			<p>No data to display. Start a simulation to see price movements.</p>
 		</div>
 	{:else}
-		<svg {width} {height} viewBox="0 0 {width} {height}">
+		<canvas 
-			<defs>
+			bind:this={canvasEl}
-				<linearGradient id="chartGradient" x1="0" y1="0" x2="0" y2="1">
+			style="width: 100%; height: {height}px;"
-					<stop offset="0%" stop-color="rgba(102, 126, 234, 0.3)" />
+		></canvas>
-					<stop offset="100%" stop-color="rgba(102, 126, 234, 0)" />
-				</linearGradient>
-			</defs>
-
-			<g class="grid-lines">
-				{#each [0, 1, 2, 3] as i}
-					{@const y = 30 + (i / 3) * (height - 60)}
-					<line 
-						x1="30" y1={y} 
-						x2={width - 30} y2={y}
-						stroke="rgba(255,255,255,0.1)"
-						stroke-dasharray="4,4"
-					/>
-				{/each}
-			</g>
-
-			<g class="y-axis">
-				{#each getYAxisLabels() as label, i}
-					{@const y = 30 + (i / 3) * (height - 60)}
-					<text x="25" y={y + 4} class="axis-label" text-anchor="end">${label}</text>
-				{/each}
-			</g>
-
-			<g class="x-axis">
-				{#each getXAxisLabels() as label, i}
-					{@const x = 30 + (i / (getXAxisLabels().length - 1 || 1)) * (width - 60)}
-					<text x={x} y={height - 8} class="axis-label" text-anchor="middle">{label}</text>
-				{/each}
-			</g>
-
-			<path
-				d={signals.map((s, i) => {
-					const pos = getSignalPosition(s, i, signals.length);
-					return `${i === 0 ? 'M' : 'L'} ${pos.x} ${pos.y}`;
-				}).join(' ')}
-				fill="none"
-				stroke="#667eea"
-				stroke-width="2"
-			/>
-
-			{#each signals as signal, i}
-				{@const pos = getSignalPosition(signal, i, signals.length)}
-				{@const color = getSignalColor(signal)}
-				<circle
-					cx={pos.x}
-					cy={pos.y}
-					r="6"
-					fill={color}
-					stroke={color}
-					stroke-width="2"
-					class="signal-dot"
-				>
-					<title>{signal.signal_type.toUpperCase()} - ${signal.price.toFixed(6)} - {new Date(signal.created_at).toLocaleString()}</title>
-				</circle>
-			{/each}
-		</svg>
-
-		<div class="legend">
-			<div class="legend-item">
-				<span class="legend-dot buy"></span>
-				<span>Buy</span>
-			</div>
-			<div class="legend-item">
-				<span class="legend-dot sell"></span>
-				<span>Sell</span>
-			</div>
-			<div class="legend-item">
-				<span class="legend-dot hold"></span>
-				<span>Hold</span>
-			</div>
-		</div>
 	{/if}
 </div>
 
@@ -169,60 +255,12 @@
 		justify-content: center;
 		height: 200px;
 		color: #666;
+		text-align: center;
+		padding: 1rem;
 	}
 
-	svg {
+	canvas {
 		display: block;
 		width: 100%;
-		height: auto;
-	}
-
-	.axis-label {
-		font-size: 10px;
-		fill: #666;
-	}
-
-	.signal-dot {
-		cursor: pointer;
-		transition: r 0.2s;
-	}
-
-	.signal-dot:hover {
-		r: 8;
-	}
-
-	.legend {
-		display: flex;
-		justify-content: center;
-		gap: 1.5rem;
-		margin-top: 0.75rem;
-		padding-top: 0.75rem;
-		border-top: 1px solid rgba(255, 255, 255, 0.05);
-	}
-
-	.legend-item {
-		display: flex;
-		align-items: center;
-		gap: 0.5rem;
-		font-size: 0.85rem;
-		color: #888;
-	}
-
-	.legend-dot {
-		width: 10px;
-		height: 10px;
-		border-radius: 50%;
-	}
-
-	.legend-dot.buy {
-		background: #22c55e;
-	}
-
-	.legend-dot.sell {
-		background: #ef4444;
-	}
-
-	.legend-dot.hold {
-		background: #fbbf24;
 	}
 </style>

src/frontend/src/lib/components/StrategyPreview.svelte

@@ -10,13 +10,14 @@
 	let { config, editable = false, onUpdate }: Props = $props();
 
 	function getConditionDescription(condition: StrategyConfig['conditions'][0]): string {
+		const timeframe = condition.timeframe ? ` within ${condition.timeframe}` : '';
 		switch (condition.type) {
 			case 'price_drop':
-				return `${condition.token} drops by ${condition.threshold}% within ${condition.timeframe}`;
+				return `${condition.token} drops by ${condition.threshold}%${timeframe}`;
 			case 'price_rise':
-				return `${condition.token} rises by ${condition.threshold}% within ${condition.timeframe}`;
+				return `${condition.token} rises by ${condition.threshold}%${timeframe}`;
 			case 'volume_spike':
-				return `${condition.token} volume spikes by ${condition.threshold}% within ${condition.timeframe}`;
+				return `${condition.token} volume spikes by ${condition.threshold}%${timeframe}`;
 			case 'price_level':
 				return `${condition.token} crosses ${condition.direction} $${condition.price}`;
 			default:

src/frontend/src/lib/components/TradeDashboard.svelte

@@ -0,0 +1,180 @@
+<script lang="ts">
+	import type { TradeLogEntry } from '$lib/stores/simulationStore';
+
+	interface Props {
+		tradeLog: TradeLogEntry[];
+	}
+
+	let { tradeLog }: Props = $props();
+
+	function formatTime(timestamp: number): string {
+		const date = new Date(timestamp * 1000);
+		return date.toLocaleString();
+	}
+
+	function getActionColor(action: string): string {
+		switch (action) {
+			case 'buy': return '#22c55e';
+			case 'sell': return '#ef4444';
+			default: return '#666';
+		}
+	}
+
+	function getActionIcon(action: string): string {
+		switch (action) {
+			case 'buy': return '📈';
+			case 'sell': return '📉';
+			default: return '➡️';
+		}
+	}
+
+	// Filter to show only buy/sell actions
+	let tradeActions = $derived(tradeLog.filter(t => t.action !== 'hold'));
+</script>
+
+<div class="trade-dashboard">
+	<div class="dashboard-header">
+		<h3>Trade Activity</h3>
+		<span class="trade-count">
+			{tradeActions.length} trades
+		</span>
+	</div>
+
+	{#if tradeActions.length === 0}
+		<div class="empty-state">
+			<p>No trades executed yet. Check the strategy configuration.</p>
+		</div>
+	{:else}
+		<div class="trade-list">
+			{#each tradeActions as entry}
+				<div class="trade-entry action-{entry.action}">
+					<div class="trade-time">
+						<span class="action-icon">{getActionIcon(entry.action)}</span>
+						<span class="action-badge" style="background: {getActionColor(entry.action)}">
+							{entry.action.toUpperCase()}
+						</span>
+						<span class="time">{formatTime(entry.time)}</span>
+					</div>
+					<div class="trade-details">
+						<div class="price">
+							<span class="label">Price:</span>
+							<span class="value">${entry.price.toFixed(8)}</span>
+						</div>
+						<div class="reason">
+							<span class="label">Reason:</span>
+							<span class="value">{entry.reason}</span>
+						</div>
+						{#if entry.action === 'sell' && entry.position > 0}
+							<div class="pnl">
+								<span class="label">Position:</span>
+								<span class="value">{entry.position.toFixed(6)}</span>
+							</div>
+						{/if}
+					</div>
+				</div>
+			{/each}
+		</div>
+	{/if}
+</div>
+
+<style>
+	.trade-dashboard {
+		background: rgba(255, 255, 255, 0.02);
+		border: 1px solid rgba(255, 255, 255, 0.1);
+		border-radius: 8px;
+		overflow: hidden;
+	}
+
+	.dashboard-header {
+		display: flex;
+		justify-content: space-between;
+		align-items: center;
+		padding: 1rem;
+		background: rgba(255, 255, 255, 0.02);
+		border-bottom: 1px solid rgba(255, 255, 255, 0.05);
+	}
+
+	.dashboard-header h3 {
+		margin: 0;
+		font-size: 1rem;
+		color: #fff;
+	}
+
+	.trade-count {
+		font-size: 0.85rem;
+		color: #888;
+	}
+
+	.empty-state {
+		padding: 2rem;
+		text-align: center;
+		color: #666;
+	}
+
+	.trade-list {
+		max-height: 300px;
+		overflow-y: auto;
+	}
+
+	.trade-entry {
+		padding: 0.75rem 1rem;
+		border-bottom: 1px solid rgba(255, 255, 255, 0.05);
+		transition: background 0.2s;
+	}
+
+	.trade-entry:hover {
+		background: rgba(255, 255, 255, 0.02);
+	}
+
+	.trade-entry.action-buy {
+		border-left: 3px solid #22c55e;
+	}
+
+	.trade-entry.action-sell {
+		border-left: 3px solid #ef4444;
+	}
+
+	.trade-time {
+		display: flex;
+		align-items: center;
+		gap: 0.5rem;
+		margin-bottom: 0.5rem;
+	}
+
+	.action-icon {
+		font-size: 1rem;
+	}
+
+	.action-badge {
+		padding: 0.125rem 0.5rem;
+		border-radius: 4px;
+		font-size: 0.75rem;
+		font-weight: bold;
+		color: #fff;
+	}
+
+	.time {
+		font-size: 0.85rem;
+		color: #888;
+	}
+
+	.trade-details {
+		display: grid;
+		grid-template-columns: repeat(auto-fit, minmax(150px, 1fr));
+		gap: 0.5rem;
+		font-size: 0.85rem;
+	}
+
+	.trade-details .label {
+		color: #666;
+	}
+
+	.trade-details .value {
+		color: #fff;
+		font-family: monospace;
+	}
+
+	.pnl .value {
+		color: #fbbf24;
+	}
+</style>

src/frontend/src/lib/components/index.ts

@@ -3,6 +3,8 @@ export { default as BotCard } from './BotCard.svelte';
 export { default as BotSelector } from './BotSelector.svelte';
 export { default as StrategyPreview } from './StrategyPreview.svelte';
 export { default as SignalChart } from './SignalChart.svelte';
+export { default as TradeDashboard } from './TradeDashboard.svelte';
+export { default as PortfolioSummary } from './PortfolioSummary.svelte';
 export { default as BacktestChart } from './BacktestChart.svelte';
 export { default as ProUpgradeBanner } from './ProUpgradeBanner.svelte';
 export { default as TokenPicker } from './TokenPicker.svelte';

src/frontend/src/lib/stores/chatStore.ts

@@ -5,15 +5,29 @@ export interface ChatMessage {
 	id: string;
 	role: 'user' | 'assistant' | 'system';
 	content: string;
+	thinking: string | null;
 	timestamp: Date;
 }
 
+// Fallback UUID generator for environments where crypto.randomUUID is not available
+function generateId(): string {
+	if (typeof crypto !== 'undefined' && typeof crypto.randomUUID === 'function') {
+		return crypto.randomUUID();
+	}
+	// Fallback: simple UUID v4 implementation
+	return 'xxxxxxxx-xxxx-4xxx-yxxx-xxxxxxxxxxxx'.replace(/[xy]/g, (c) => {
+		const r = (Math.random() * 16) | 0;
+		const v = c === 'x' ? r : (r & 0x3) | 0x8;
+		return v.toString(16);
+	});
+}
+
 export const chatStore = writable<ChatMessage[]>([]);
 
 export function addMessage(message: Omit<ChatMessage, 'id' | 'timestamp'>) {
 	const newMessage: ChatMessage = {
 		...message,
-		id: crypto.randomUUID(),
+		id: generateId(),
 		timestamp: new Date()
 	};
 	chatStore.update(messages => [...messages, newMessage]);
@@ -24,6 +38,7 @@ export function setMessages(messages: BotConversation[]) {
 		id: m.id,
 		role: m.role,
 		content: m.content,
+		thinking: null,
 		timestamp: new Date(m.created_at)
 	})));
 }

src/frontend/src/lib/stores/simulationStore.ts

@@ -1,9 +1,35 @@
 import { writable } from 'svelte/store';
 import type { Simulation, Signal } from '$lib/api';
 
+export interface KlineData {
+	time: number;
+	close: number;
+}
+
+export interface TradeLogEntry {
+	time: number;
+	price: number;
+	action: 'buy' | 'sell' | 'hold';
+	reason: string;
+	position: number;
+	entry_price: number | null;
+}
+
+export interface Portfolio {
+	initial_balance: number;
+	current_balance: number;
+	position: number;
+	position_token: string;
+	entry_price: number;
+	current_price: number;
+}
+
 export interface SimulationState {
 	currentSimulation: Simulation | null;
 	signals: Signal[];
+	klines: KlineData[];
+	tradeLog: TradeLogEntry[];
+	portfolio: Portfolio;
 	isLoading: boolean;
 	error: string | null;
 }
@@ -11,6 +37,16 @@ export interface SimulationState {
 const initialState: SimulationState = {
 	currentSimulation: null,
 	signals: [],
+	klines: [],
+	tradeLog: [],
+	portfolio: {
+		initial_balance: 10000,
+		current_balance: 10000,
+		position: 0,
+		position_token: '',
+		entry_price: 0,
+		current_price: 0
+	},
 	isLoading: false,
 	error: null
 };
@@ -18,7 +54,20 @@ const initialState: SimulationState = {
 export const simulationStore = writable<SimulationState>(initialState);
 
 export function setCurrentSimulation(simulation: Simulation | null) {
-	simulationStore.update(state => ({ ...state, currentSimulation: simulation }));
+	simulationStore.update(state => ({ 
+		...state, 
+		currentSimulation: simulation,
+		klines: simulation?.klines || [],
+		tradeLog: simulation?.trade_log || [],
+		portfolio: simulation?.portfolio || state.portfolio
+	}));
+}
+
+export function updatePortfolio(portfolio: Partial<Portfolio>) {
+	simulationStore.update(state => ({
+		...state,
+		portfolio: { ...state.portfolio, ...portfolio }
+	}));
 }
 
 export function addSignals(newSignals: Signal[]) {

src/frontend/src/lib/utils/markdown.ts

@@ -0,0 +1,256 @@
+/**
+ * Simple markdown parser for rendering AI responses
+ * Supports: bold, italic, code blocks, inline code, links, lists, tables, headings, line breaks
+ */
+
+export interface InlineSegment {
+	type: 'text' | 'bold' | 'italic' | 'code' | 'link';
+	content: string;
+	href?: string;
+}
+
+export interface ParsedSegment {
+	type: 'text' | 'bold' | 'italic' | 'code' | 'codeBlock' | 'link' | 'list' | 'table' | 'lineBreak' | 'heading';
+	content: string;
+	items?: string[];
+	headers?: InlineSegment[][];
+	rows?: InlineSegment[][];
+}
+
+export function parseMarkdown(text: string): ParsedSegment[] {
+	const segments: ParsedSegment[] = [];
+	
+	// Normalize line endings
+	text = text.replace(/\r\n/g, '\n').replace(/\r/g, '\n');
+	
+	// First, extract code blocks
+	const codeBlockRegex = /```[\s\S]*?```/g;
+	const parts = text.split(codeBlockRegex);
+	const codeBlocks = text.match(codeBlockRegex) || [];
+	
+	let partIndex = 0;
+	
+	while (partIndex < parts.length) {
+		const part = parts[partIndex];
+		
+		if (part.trim()) {
+			// Process non-code content
+			segments.push(...parseInlineContent(part));
+		}
+		
+		// Add code block if there's one after this part
+		if (partIndex < codeBlocks.length) {
+			const codeContent = codeBlocks[partIndex].replace(/^```\w*\n?/, '').replace(/```$/, '');
+			segments.push({ type: 'codeBlock', content: codeContent });
+		}
+		
+		partIndex++;
+	}
+	
+	return segments;
+}
+
+function parseInlineContent(text: string): ParsedSegment[] {
+	const segments: ParsedSegment[] = [];
+	
+	// Check for tables - match table pattern anywhere in text
+	// Table pattern: | header | ... |\n|---|...|\n| row | ... |
+	const tableRegex = /\|.+\|\n\|[-:\s|]+\|\n((?:\|.+\|\n?)*)/g;
+	let lastIndex = 0;
+	let tableMatch;
+	
+	while ((tableMatch = tableRegex.exec(text)) !== null) {
+		// Add content before table
+		const beforeTable = text.substring(lastIndex, tableMatch.index);
+		if (beforeTable.trim()) {
+			segments.push(...parseLines(beforeTable));
+		}
+		
+		// Parse table
+		const tableContent = tableMatch[0];
+		const tableSegments = parseTable(tableContent);
+		if (tableSegments.length > 0) {
+			segments.push(...tableSegments);
+		} else {
+			// If table parsing failed, treat as text
+			segments.push(...parseLines(tableContent));
+		}
+		
+		lastIndex = tableMatch.index + tableContent.length;
+	}
+	
+	// Add remaining content
+	if (lastIndex < text.length) {
+		const remaining = text.substring(lastIndex);
+		if (remaining.trim()) {
+			segments.push(...parseLines(remaining));
+		}
+	}
+	
+	return segments;
+}
+
+function parseTable(tableStr: string): ParsedSegment[] {
+	const lines = tableStr.trim().split('\n').filter(line => line.trim());
+	if (lines.length < 2) return [];
+	
+	// Skip separator line (|---|---|)
+	const dataLines = lines.filter(line => !line.match(/^[\|\s\-:]+$/));
+	if (dataLines.length < 2) return [];
+	
+	const headers = parseTableRow(dataLines[0]);
+	const rows = dataLines.slice(1).map(row => parseTableRow(row));
+	
+	return [{
+		type: 'table',
+		content: '',
+		headers,
+		rows
+	}];
+}
+
+function parseTableRow(row: string): InlineSegment[][] {
+	return row.split('|')
+		.map(cell => cell.trim())
+		.filter(cell => cell !== '')
+		.map(cell => parseInlineElements(cell));
+}
+
+export function parseInlineElements(text: string): InlineSegment[] {
+	const segments: InlineSegment[] = [];
+	
+	const inlineRegex = /(\*\*[^*]+\*\*|\*[^*]+\*|`[^`]+`|\[.*?\]\(.*?\))/g;
+	const parts = text.split(inlineRegex);
+	
+	for (const part of parts) {
+		if (!part) continue;
+		
+		if (part.startsWith('**') && part.endsWith('**')) {
+			segments.push({ type: 'bold', content: part.slice(2, -2) });
+		} else if (part.startsWith('*') && part.endsWith('*')) {
+			segments.push({ type: 'italic', content: part.slice(1, -1) });
+		} else if (part.startsWith('`') && part.endsWith('`')) {
+			segments.push({ type: 'code', content: part.slice(1, -1) });
+		} else if (part.startsWith('[') && part.includes('](')) {
+			const linkMatch = part.match(/\[(.*?)\]\((.*?)\)/);
+			if (linkMatch) {
+				segments.push({ type: 'link', content: linkMatch[1], href: linkMatch[2] });
+			}
+		} else if (part) {
+			segments.push({ type: 'text', content: part });
+		}
+	}
+	
+	return segments;
+}
+
+// Render inline segments to HTML string
+function renderInlineSegments(segments: InlineSegment[]): string {
+	return segments.map(seg => {
+		switch (seg.type) {
+			case 'bold': return `<strong>${seg.content}</strong>`;
+			case 'italic': return `<em>${seg.content}</em>`;
+			case 'code': return `<code class="inline-code">${seg.content}</code>`;
+			case 'link': return `<a href="${seg.href || '#'}" target="_blank" rel="noopener noreferrer">${seg.content}</a>`;
+			default: return seg.content;
+		}
+	}).join('');
+}
+
+function parseLines(text: string): ParsedSegment[] {
+	const segments: ParsedSegment[] = [];
+	
+	// Combined regex for inline formatting
+	const inlineRegex = /(\*\*[^*]+\*\*|\*[^*]+\*|`[^`]+`|\[.*?\]\(.*?\))/g;
+	const lines = text.split('\n');
+	
+	for (let i = 0; i < lines.length; i++) {
+		const line = lines[i];
+		
+		if (!line.trim()) {
+			// Empty line - add line break for paragraph separation
+			segments.push({ type: 'lineBreak', content: '' });
+			continue;
+		}
+		
+		// Check for headings
+		if (line.match(/^#{1,6}\s/)) {
+			segments.push({ type: 'heading', content: line.replace(/^#+\s/, '') });
+			continue;
+		}
+		
+		// Check for list items
+		if (line.match(/^[\-\*]\s/)) {
+			const listMatch = line.match(/^([\-\*])\s(.*)/);
+			if (listMatch) {
+				// Parse inline formatting for list item
+				const itemContent = listMatch[2];
+				const inlineSegments = parseInlineElements(itemContent);
+				
+				// Check if previous segment is a list
+				const lastSeg = segments[segments.length - 1];
+				if (lastSeg && lastSeg.type === 'list') {
+					lastSeg.items?.push(itemContent);
+				} else {
+					segments.push({ type: 'list', content: '', items: [itemContent] });
+				}
+			}
+			continue;
+		}
+		
+		// Check for numbered lists
+		if (line.match(/^\d+\.\s/)) {
+			const listMatch = line.match(/^\d+\.\s(.*)/);
+			if (listMatch) {
+				const itemContent = listMatch[1];
+				
+				const lastSeg = segments[segments.length - 1];
+				if (lastSeg && lastSeg.type === 'list') {
+					lastSeg.items?.push(itemContent);
+				} else {
+					segments.push({ type: 'list', content: '', items: [itemContent] });
+				}
+			}
+			continue;
+		}
+		
+		// Process inline formatting
+		const inlineSegments = parseInlineElementsAsText(line);
+		segments.push(...inlineSegments);
+		
+		// Add line break after non-empty lines (except last in a paragraph)
+		if (i < lines.length - 1 && line.trim()) {
+			segments.push({ type: 'lineBreak', content: '' });
+		}
+	}
+	
+	return segments;
+}
+
+function parseInlineElementsAsText(text: string): ParsedSegment[] {
+	const segments: ParsedSegment[] = [];
+	
+	const inlineRegex = /(\*\*[^*]+\*\*|\*[^*]+\*|`[^`]+`|\[.*?\]\(.*?\))/g;
+	const parts = text.split(inlineRegex);
+	
+	for (const part of parts) {
+		if (!part) continue;
+		
+		if (part.startsWith('**') && part.endsWith('**')) {
+			segments.push({ type: 'bold', content: part.slice(2, -2) });
+		} else if (part.startsWith('*') && part.endsWith('*')) {
+			segments.push({ type: 'italic', content: part.slice(1, -1) });
+		} else if (part.startsWith('`') && part.endsWith('`')) {
+			segments.push({ type: 'code', content: part.slice(1, -1) });
+		} else if (part.startsWith('[') && part.includes('](')) {
+			const linkMatch = part.match(/\[(.*?)\]\((.*?)\)/);
+			if (linkMatch) {
+				segments.push({ type: 'link', content: linkMatch[1] });
+			}
+		} else if (part) {
+			segments.push({ type: 'text', content: part });
+		}
+	}
+	
+	return segments;
+}

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

@@ -4,12 +4,20 @@
 	import { goto } from '$app/navigation';
 	import { isAuthenticated, isLoading, chatStore, addMessage, setMessages, clearChat, currentBotStore, setCurrentBot } from '$lib/stores';
 	import { api } from '$lib/api';
-	import { ChatInterface, StrategyPreview, ProUpgradeBanner } from '$lib/components';
+	import { ChatInterface, StrategyPreview } from '$lib/components';
+	import type { TokenSearchResult } from '$lib/api';
 
 	let botId = $derived($page.params.id);
 	let isSending = $state(false);
 	let showStrategy = $state(false);
 	
+	// Token address confirmation modal state
+	let showTokenConfirm = $state(false);
+	let pendingStrategyData = $state<any>(null);
+	let tokenAddressInput = $state('');
+	let confirmingMessage = $state('');
+	let tokenSearchResults = $state<TokenSearchResult[]>([]);
+
 	onMount(async () => {
 		if (!$isAuthenticated && !$isLoading) {
 			goto('/login');
@@ -44,16 +52,40 @@
 		
 		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
-			addMessage({ role: 'assistant', content: response.response });
+			const controller = new AbortController();
+			const timeoutId = setTimeout(() => controller.abort(), 30000);
+			
+			const response = await api.bots.chat(botId, message, controller.signal);
+			clearTimeout(timeoutId);
+			
+			// Check if token address confirmation is needed
+			if (response.strategy_needs_confirmation && response.strategy_data) {
+				// Show token confirmation modal
+				pendingStrategyData = response.strategy_data;
+				confirmingMessage = response.response;
+				tokenAddressInput = '';
+				tokenSearchResults = response.token_search_results || [];
+				showTokenConfirm = true;
+			}
+			
+			// Add assistant response with thinking
+			addMessage({ role: 'assistant', content: response.response, thinking: response.thinking || null });
 			
 			if (response.strategy_config) {
 				const bot = await api.bots.get(botId);
 				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.', thinking: null });
+			} else {
+				addMessage({ role: 'assistant', content: 'Sorry, I encountered an error. Please try again.', thinking: null });
+			}
 		} finally {
 			isSending = false;
 		}
@@ -62,6 +94,62 @@
 	function toggleStrategy() {
 		showStrategy = !showStrategy;
 	}
+	
+	async function confirmTokenAddress() {
+		if (!tokenAddressInput.trim() || !pendingStrategyData) {
+			showTokenConfirm = false;
+			return;
+		}
+		
+		// Update the pending strategy with the token address
+		const updatedStrategy = { ...pendingStrategyData };
+		
+		// Update conditions with token address
+		if (updatedStrategy.conditions) {
+			updatedStrategy.conditions = updatedStrategy.conditions.map((cond: any) => ({
+				...cond,
+				token_address: tokenAddressInput.trim()
+			}));
+		}
+		
+		// Update actions with token address
+		if (updatedStrategy.actions) {
+			updatedStrategy.actions = updatedStrategy.actions.map((action: any) => ({
+				...action,
+				token_address: tokenAddressInput.trim()
+			}));
+		}
+		
+		try {
+			// Update bot with the strategy
+			await api.bots.update(botId, { strategy_config: updatedStrategy });
+			
+			// Refresh bot data
+			const bot = await api.bots.get(botId);
+			setCurrentBot(bot);
+			
+			// Add success message
+			addMessage({ role: 'assistant', content: `Perfect! I've saved your strategy with the token address. You can now run backtests!`, thinking: null });
+		} catch (e) {
+			addMessage({ role: 'assistant', content: 'Failed to save strategy. Please try again.', thinking: null });
+		}
+		
+		showTokenConfirm = false;
+		pendingStrategyData = null;
+		tokenAddressInput = '';
+		tokenSearchResults = [];
+	}
+	
+	function selectTokenResult(result: TokenSearchResult) {
+		tokenAddressInput = result.address;
+	}
+	
+	function cancelTokenConfirm() {
+		showTokenConfirm = false;
+		pendingStrategyData = null;
+		tokenAddressInput = '';
+		tokenSearchResults = [];
+	}
 </script>
 
 <svelte:head>
@@ -69,6 +157,34 @@
 </svelte:head>
 
 <main>
+	{#if showTokenConfirm}
+		<div class="modal-overlay" onclick={cancelTokenConfirm}>
+			<div class="modal-content" onclick={(e) => e.stopPropagation()}>
+				<h3>Select Token Address</h3>
+				<p class="modal-message">{confirmingMessage}</p>
+				
+				{#if tokenSearchResults.length > 0}
+					<div class="token-results">
+						<p class="modal-hint">Select a token:</p>
+						{#each tokenSearchResults as result}
+							<button class="token-result" onclick={() => selectTokenResult(result)}>
+								<span class="token-symbol">{result.symbol}</span>
+								<span class="token-name">{result.name}</span>
+								<span class="token-address">{result.address.slice(0, 10)}...{result.address.slice(-8)}</span>
+							</button>
+						{/each}
+					</div>
+					<p class="modal-divider">or enter manually:</p>
+				{/if}
+				
+				<input type="text" class="token-input" bind:value={tokenAddressInput} placeholder="0x..."/>
+				<div class="modal-actions">
+					<button class="btn btn-secondary" onclick={cancelTokenConfirm}>Cancel</button>
+					<button class="btn btn-primary" onclick={confirmTokenAddress} disabled={!tokenAddressInput.trim()}>Confirm</button>
+				</div>
+			</div>
+		</div>
+	{/if}
 	<header>
 		<div class="header-left">
 			<a href="/dashboard" class="back-link">← Dashboard</a>
@@ -95,12 +211,12 @@
 		<ChatInterface
 			bot={$currentBotStore}
 			messages={$chatStore}
-			{isSending}
+			isSending={isSending}
 			onSendMessage={handleSendMessage}
 		/>
 	</div>
 
-	<ProUpgradeBanner feature="Auto-execute trades with your bot" />
+	<!-- <ProUpgradeBanner feature="Auto-execute trades with your bot" /> -->
 </main>
 
 <style>
@@ -186,4 +302,145 @@
 		display: flex;
 		flex-direction: column;
 	}
+
+	/* Modal Styles */
+	.modal-overlay {
+		position: fixed;
+		top: 0;
+		left: 0;
+		right: 0;
+		bottom: 0;
+		background: rgba(0, 0, 0, 0.7);
+		display: flex;
+		align-items: center;
+		justify-content: center;
+		z-index: 1000;
+	}
+
+	.modal-content {
+		background: rgba(20, 20, 20, 0.95);
+		border: 1px solid rgba(255, 255, 255, 0.1);
+		border-radius: 16px;
+		padding: 1.5rem;
+		max-width: 450px;
+		width: 90%;
+	}
+
+	.modal-content h3 {
+		margin: 0 0 1rem;
+		color: #667eea;
+	}
+
+	.modal-message {
+		color: #ccc;
+		margin-bottom: 0.5rem;
+		line-height: 1.5;
+	}
+
+	.modal-hint {
+		color: #888;
+		font-size: 0.9rem;
+		margin-bottom: 1rem;
+	}
+
+	.token-input {
+		width: 100%;
+		padding: 0.75rem;
+		border-radius: 8px;
+		border: 1px solid rgba(255, 255, 255, 0.2);
+		background: rgba(255, 255, 255, 0.05);
+		color: #fff;
+		font-size: 1rem;
+		font-family: 'Monaco', 'Menlo', monospace;
+		box-sizing: border-box;
+	}
+
+	.token-input:focus {
+		outline: none;
+		border-color: #667eea;
+	}
+
+	.modal-actions {
+		display: flex;
+		gap: 0.75rem;
+		margin-top: 1rem;
+		justify-content: flex-end;
+	}
+
+	.btn-primary {
+		padding: 0.75rem 1.5rem;
+		background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
+		color: white;
+		border: none;
+		border-radius: 8px;
+		font-size: 1rem;
+		font-weight: 500;
+		cursor: pointer;
+	}
+
+	.btn-primary:hover:not(:disabled) {
+		transform: translateY(-2px);
+	}
+
+	.btn-primary:disabled {
+		opacity: 0.5;
+		cursor: not-allowed;
+	}
+
+	/* Token Results */
+	.token-results {
+		max-height: 200px;
+		overflow-y: auto;
+		margin-bottom: 1rem;
+	}
+
+	.token-result {
+		width: 100%;
+		display: flex;
+		align-items: center;
+		gap: 0.75rem;
+		padding: 0.75rem;
+		background: rgba(255, 255, 255, 0.05);
+		border: 1px solid rgba(255, 255, 255, 0.1);
+		border-radius: 8px;
+		margin-bottom: 0.5rem;
+		cursor: pointer;
+		text-align: left;
+		color: #fff;
+		transition: background 0.2s;
+	}
+
+	.token-result:hover {
+		background: rgba(102, 126, 234, 0.2);
+		border-color: rgba(102, 126, 234, 0.5);
+	}
+
+	.token-result:last-child {
+		margin-bottom: 0;
+	}
+
+	.token-symbol {
+		font-weight: 600;
+		color: #667eea;
+		min-width: 60px;
+	}
+
+	.token-name {
+		flex: 1;
+		color: #ccc;
+		font-size: 0.9rem;
+	}
+
+	.token-address {
+		font-size: 0.75rem;
+		color: #666;
+		font-family: 'Monaco', 'Menlo', monospace;
+	}
+
+	.modal-divider {
+		text-align: center;
+		color: #666;
+		font-size: 0.85rem;
+		margin: 1rem 0;
+	}
 </style>

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

@@ -8,14 +8,36 @@
 	import type { Backtest } from '$lib/api';
 
 	let botId = $derived($page.params.id);
-	let token = $state('PEPE');
+	let tokenName = $state('');
+	let tokenAddress = $state('');
 	let timeframe = $state('1h');
 	let startDate = $state('');
 	let endDate = $state('');
 	let isRunning = $state(false);
 	let selectedBacktest = $state<Backtest | null>(null);
 	
+	// Expandable trades state
+	let expandedTrades = $state<Set<string>>(new Set());
+	
+	// Pagination state for each backtest
+	let tradesPage = $state<Record<string, number>>({});
+	let tradesData = $state<Record<string, any>>({});
+	const TRADES_PER_PAGE = 5;
+	
 	onMount(async () => {
+		// Set default dates - yesterday only (1 day range for fast testing)
+		const yesterday = new Date();
+		yesterday.setDate(yesterday.getDate() - 1);
+		
+		// Set max date to yesterday
+		const maxDate = yesterday.toISOString().split('T')[0];
+		
+		// Set end to yesterday, start to day before (1 day range)
+		endDate = maxDate;
+		const dayBefore = new Date(yesterday);
+		dayBefore.setDate(dayBefore.getDate() - 1);
+		startDate = dayBefore.toISOString().split('T')[0];
+		
 		if (!$isAuthenticated && !$isLoading) {
 			goto('/login');
 			return;
@@ -30,6 +52,16 @@
 		try {
 			const bot = await api.bots.get(botId);
 			setCurrentBot(bot);
+			
+			// Extract token info from strategy config
+			const strategy = bot.strategy_config;
+			if (strategy) {
+				// Try conditions first, then actions
+				const condition = strategy.conditions?.[0];
+				const action = strategy.actions?.[0];
+				tokenName = condition?.token || action?.token || '';
+				tokenAddress = condition?.token_address || action?.token_address || '';
+			}
 		} catch (e) {
 			goto('/dashboard');
 		}
@@ -46,13 +78,25 @@
 
 	async function startBacktest() {
 		if (!startDate || !endDate) return;
+		
+		// Validate date range (max 7 days)
+		const start = new Date(startDate);
+		const end = new Date(endDate);
+		const daysDiff = Math.ceil((end.getTime() - start.getTime()) / (1000 * 60 * 60 * 24));
+		
+		if (daysDiff > 7) {
+			setBacktestError('Maximum backtest duration is 7 days for fast testing');
+			return;
+		}
+		
 		setBacktestError(null);
 		setBacktestLoading(true);
 		isRunning = true;
 
 		try {
 			const backtest = await api.backtest.start(botId, {
-				token,
+				token: tokenAddress,  // Use token address from strategy
+				token_name: tokenName,  // Also send token name for display
 				timeframe,
 				start_date: startDate,
 				end_date: endDate
@@ -76,15 +120,54 @@
 		}
 	}
 
+
+
 	function setBacktestHistory(backtests: any[]) {
 		backtestStore.update(state => ({ ...state, backtestHistory: backtests }));
 	}
 
 	function selectBacktest(backtest: Backtest) {
-		if (backtest.status === 'completed' && backtest.result) {
+		if (backtest.status === 'completed' && backtest.result && !backtest.result.error) {
 			selectedBacktest = backtest;
 		}
 	}
+
+	function toggleTrades(backtestId: string) {
+		if (expandedTrades.has(backtestId)) {
+			expandedTrades.delete(backtestId);
+		} else {
+			expandedTrades.add(backtestId);
+			// Load first page of trades if not loaded
+			if (!tradesData[backtestId]) {
+				loadTrades(backtestId, 1);
+			}
+		}
+		expandedTrades = new Set(expandedTrades);  // Trigger reactivity
+	}
+	
+	async function loadTrades(backtestId: string, page: number) {
+		try {
+			const data = await api.backtest.getTrades(botId, backtestId, page, TRADES_PER_PAGE);
+			tradesData[backtestId] = { ...data, currentPage: page };
+			tradesData = { ...tradesData };  // Trigger reactivity
+		} catch (e) {
+			console.error('Failed to load trades:', e);
+		}
+	}
+	
+	function nextTradesPage(backtestId: string) {
+		const data = tradesData[backtestId];
+		if (data && data.has_next) {
+			loadTrades(backtestId, data.page + 1);
+		}
+	}
+	
+	function prevTradesPage(backtestId: string) {
+		const data = tradesData[backtestId];
+		if (data && data.has_prev) {
+			loadTrades(backtestId, data.page - 1);
+		}
+	}
 </script>
 
 <svelte:head>
@@ -109,17 +192,19 @@
 
 			<form onsubmit={(e) => { e.preventDefault(); startBacktest(); }}>
 				<div class="form-row">
-					<div class="field">
+					<div class="field token-info">
-						<label for="token">Token</label>
+						<label>Token</label>
-						<input type="text" id="token" bind:value={token} required />
+						<div class="token-display">
+							<span class="token-name">{tokenName || 'Not configured'}</span>
+							{#if tokenAddress}
+								<span class="token-address">{tokenAddress.slice(0, 10)}...{tokenAddress.slice(-8)}</span>
+							{/if}
+						</div>
 					</div>
 					<div class="field">
 						<label for="timeframe">Timeframe</label>
 						<select id="timeframe" bind:value={timeframe}>
-							<option value="1m">1 minute</option>
+							<option value="1h">1 hour (recommended)</option>
-							<option value="5m">5 minutes</option>
-							<option value="15m">15 minutes</option>
-							<option value="1h">1 hour</option>
 							<option value="4h">4 hours</option>
 							<option value="1d">1 day</option>
 						</select>
@@ -144,7 +229,12 @@
 		</section>
 
 		<section class="results-section">
-			<h2>Backtest History</h2>
+			<div class="section-header">
+				<h2>Backtest History</h2>
+				<button class="btn-refresh" onclick={() => loadBacktests()} disabled={$backtestStore.isLoading}>
+					{$backtestStore.isLoading ? 'Refreshing...' : 'Refresh'}
+				</button>
+			</div>
 			
 			{#if $backtestStore.backtestHistory.length === 0}
 				<p class="empty-state">No backtests yet. Run your first backtest above.</p>
@@ -156,7 +246,11 @@
 								<span class="backtest-status status-{backtest.status}">{backtest.status}</span>
 								<span class="backtest-date">{new Date(backtest.started_at).toLocaleDateString()}</span>
 							</div>
-							{#if backtest.result}
+							{#if backtest.result && backtest.result.error}
+								<div class="backtest-error">
+									<span class="error-label">Error:</span> {typeof backtest.result.error === 'string' ? backtest.result.error : JSON.stringify(backtest.result.error)}
+								</div>
+							{:else if backtest.result}
 								<div class="backtest-results">
 									<div class="result-item">
 										<span class="result-label">Total Return</span>
@@ -177,16 +271,68 @@
 										<span class="result-value negative">{backtest.result.max_drawdown.toFixed(2)}%</span>
 									</div>
 								</div>
+								<div class="backtest-config">
+									<span class="config-item">
+										<span class="config-label">Token:</span> {backtest.config.token || 'Unknown'}
+									</span>
+									<span class="config-item">
+										<span class="config-label">TF:</span> {backtest.config.timeframe || '1h'}
+									</span>
+									<span class="config-item">
+										<span class="config-label">Period:</span> {backtest.config.start_date} to {backtest.config.end_date}
+									</span>
+								</div>
+								{#if backtest.result.trades && backtest.result.trades.length > 0}
+									<button class="btn-toggle-trades" onclick={() => toggleTrades(backtest.id)}>
+										{expandedTrades.has(backtest.id) ? 'Hide' : 'Show'} Trade History ({backtest.result.trades.length})
+									</button>
+									{#if expandedTrades.has(backtest.id)}
+										<div class="trades-inline">
+											{#if tradesData[backtest.id]}
+												<div class="trades-pagination-header">
+													<span class="trades-count">
+														Showing {((tradesData[backtest.id].page - 1) * TRADES_PER_PAGE) + 1}-{Math.min(tradesData[backtest.id].page * TRADES_PER_PAGE, tradesData[backtest.id].total_trades)} of {tradesData[backtest.id].total_trades}
+													</span>
+													{#if tradesData[backtest.id].total_pages > 1}
+														<div class="pagination-controls">
+															<button class="btn-pagination" onclick={() => prevTradesPage(backtest.id)} disabled={!tradesData[backtest.id].has_prev}>← Prev</button>
+															<span class="page-indicator">Page {tradesData[backtest.id].page} of {tradesData[backtest.id].total_pages}</span>
+															<button class="btn-pagination" onclick={() => nextTradesPage(backtest.id)} disabled={!tradesData[backtest.id].has_next}>Next →</button>
+														</div>
+													{/if}
+												</div>
+												<div class="trades-list">
+													{#each tradesData[backtest.id].trades as trade}
+														<div class="trade-item">
+															<span class="trade-type" class:buy={trade.type === 'buy'} class:sell={trade.type === 'sell'}>
+																{trade.type.toUpperCase()}
+															</span>
+															<span class="trade-price">${trade.price?.toFixed(6)}</span>
+															<span class="trade-amount">${trade.amount?.toFixed(2)}</span>
+															<span class="trade-reason">{trade.exit_reason || 'entry'}</span>
+														</div>
+													{/each}
+												</div>
+											{:else}
+												<div class="trades-loading">Loading trades...</div>
+											{/if}
+										</div>
+									{/if}
+								{/if}
 							{/if}
 							{#if backtest.status === 'running'}
+								<div class="progress-container">
+									<div class="progress-bar">
+										<div class="progress-fill" style="width: {backtest.progress ?? 0}%"></div>
+									</div>
+									<span class="progress-text">{backtest.progress ?? 0}%</span>
+								</div>
 								<button onclick={() => stopBacktest(backtest.id)} class="btn btn-danger">Stop</button>
 							{/if}
 						</div>
 					{/each}
 				</div>
 			{/if}
-		</section>
-
 		{#if selectedBacktest}
 			<section class="chart-section">
 				<div class="chart-header">
@@ -196,6 +342,8 @@
 				<BacktestChart results={selectedBacktest.result} />
 			</section>
 		{/if}
+
+
 	</div>
 </main>
 
@@ -237,7 +385,120 @@
 
 	h2 {
 		font-size: 1.25rem;
-		margin: 0 0 1rem;
+		margin: 0;
+	}
+
+	.section-header {
+		display: flex;
+		justify-content: space-between;
+		align-items: center;
+		margin-bottom: 1rem;
+	}
+
+	.section-header h2 {
+		margin: 0;
+	}
+
+	.btn-refresh {
+		padding: 0.5rem 1rem;
+		background: rgba(255, 255, 255, 0.1);
+		color: white;
+		border: 1px solid rgba(255, 255, 255, 0.2);
+		border-radius: 6px;
+		font-size: 0.85rem;
+		cursor: pointer;
+		width: auto;
+	}
+
+	.btn-refresh:hover:not(:disabled) {
+		background: rgba(255, 255, 255, 0.15);
+		transform: none;
+	}
+
+	.btn-refresh:disabled {
+		opacity: 0.5;
+		cursor: not-allowed;
+	}
+
+	.btn-sm {
+		padding: 0.4rem 0.75rem;
+		font-size: 0.85rem;
+	}
+
+	/* Trades Modal */
+	.trades-modal {
+		max-width: 800px;
+		max-height: 80vh;
+		overflow: hidden;
+		display: flex;
+		flex-direction: column;
+	}
+
+	.trades-modal .modal-header {
+		display: flex;
+		justify-content: space-between;
+		align-items: center;
+		margin-bottom: 1rem;
+	}
+
+	.trades-modal h3 {
+		margin: 0;
+		color: #667eea;
+	}
+
+	.debug-info {
+		background: yellow;
+		color: black;
+		padding: 0.5rem;
+		margin-bottom: 1rem;
+		font-family: monospace;
+	}
+
+	.trades-table-wrapper {
+		overflow-y: auto;
+		flex: 1;
+	}
+
+	.trades-table {
+		width: 100%;
+		border-collapse: collapse;
+		font-size: 0.9rem;
+	}
+
+	.trades-table th,
+	.trades-table td {
+		padding: 0.75rem;
+		text-align: left;
+		border-bottom: 1px solid rgba(255, 255, 255, 0.1);
+	}
+
+	.trades-table th {
+		background: rgba(255, 255, 255, 0.05);
+		font-weight: 600;
+		color: #ccc;
+		position: sticky;
+		top: 0;
+	}
+
+	.trades-table td {
+		color: #fff;
+	}
+
+	.trade-type {
+		padding: 0.25rem 0.5rem;
+		border-radius: 4px;
+		font-weight: 600;
+		font-size: 0.8rem;
+	}
+
+	.trade-type.buy {
+		background: rgba(76, 175, 80, 0.2);
+		color: #4caf50;
+	}
+
+	.trade-type.sell {
+		background: rgba(244, 67, 54, 0.2);
+		color: #f44336;
 	}
 
 	.content {
@@ -262,6 +523,20 @@
 		font-size: 0.9rem;
 	}
 
+	.backtest-error {
+		background: rgba(239, 68, 68, 0.1);
+		border: 1px solid rgba(239, 68, 68, 0.3);
+		color: #fca5a5;
+		padding: 0.75rem;
+		border-radius: 8px;
+		font-size: 0.85rem;
+		margin-bottom: 0.75rem;
+	}
+
+	.error-label {
+		font-weight: 600;
+	}
+
 	.form-row {
 		display: grid;
 		grid-template-columns: 1fr 1fr;
@@ -275,6 +550,27 @@
 		gap: 0.5rem;
 	}
 
+	.token-display {
+		display: flex;
+		flex-direction: column;
+		gap: 0.25rem;
+		padding: 0.75rem;
+		background: rgba(255, 255, 255, 0.05);
+		border: 1px solid rgba(255, 255, 255, 0.2);
+		border-radius: 8px;
+	}
+
+	.token-name {
+		font-weight: 600;
+		color: #667eea;
+	}
+
+	.token-address {
+		font-size: 0.8rem;
+		color: #888;
+		font-family: 'Monaco', 'Menlo', monospace;
+	}
+
 	label {
 		font-size: 0.9rem;
 		color: #ccc;
@@ -334,6 +630,83 @@
 		padding: 1rem;
 	}
 
+	/* Inline Trades */
+	.trades-inline {
+		margin-top: 1rem;
+		padding-top: 1rem;
+		border-top: 1px solid rgba(255, 255, 255, 0.1);
+	}
+
+	.trades-inline h4 {
+		margin: 0 0 0.5rem;
+		font-size: 0.9rem;
+		color: #667eea;
+	}
+
+	.trades-list {
+		display: flex;
+		flex-direction: column;
+		gap: 0.5rem;
+	}
+
+	.trade-item {
+		display: flex;
+		align-items: center;
+		gap: 0.75rem;
+		padding: 0.5rem;
+		background: rgba(255, 255, 255, 0.03);
+		border-radius: 6px;
+		font-size: 0.85rem;
+	}
+
+	.trade-item .trade-type {
+		padding: 0.2rem 0.5rem;
+		border-radius: 4px;
+		font-weight: 600;
+		font-size: 0.75rem;
+	}
+
+	.trade-item .trade-type.buy {
+		background: rgba(76, 175, 80, 0.2);
+		color: #4caf50;
+	}
+
+	.trade-item .trade-type.sell {
+		background: rgba(244, 67, 54, 0.2);
+		color: #f44336;
+	}
+
+	.trade-price {
+		color: #ccc;
+		font-family: monospace;
+	}
+
+	.trade-amount {
+		color: #888;
+	}
+
+	.trade-reason {
+		color: #666;
+		font-size: 0.8rem;
+		margin-left: auto;
+	}
+
+	.btn-toggle-trades {
+		margin-top: 0.75rem;
+		padding: 0.5rem 1rem;
+		background: rgba(102, 126, 234, 0.1);
+		border: 1px solid rgba(102, 126, 234, 0.3);
+		border-radius: 6px;
+		color: #667eea;
+		font-size: 0.85rem;
+		cursor: pointer;
+		transition: all 0.2s;
+	}
+
+	.btn-toggle-trades:hover {
+		background: rgba(102, 126, 234, 0.2);
+	}
+
 	.backtest-header {
 		display: flex;
 		justify-content: space-between;
@@ -364,6 +737,11 @@
 		color: #fca5a5;
 	}
 
+	.status-stopped {
+		background: rgba(251, 191, 36, 0.2);
+		color: #fbbf24;
+	}
+
 	.backtest-date {
 		color: #888;
 		font-size: 0.85rem;
@@ -375,6 +753,24 @@
 		gap: 1rem;
 	}
 
+	.backtest-config {
+		display: flex;
+		gap: 1rem;
+		flex-wrap: wrap;
+		margin-top: 0.75rem;
+		padding: 0.5rem 0;
+		border-top: 1px solid rgba(255, 255, 255, 0.05);
+	}
+
+	.config-item {
+		font-size: 0.8rem;
+		color: #888;
+	}
+
+	.config-label {
+		color: #666;
+	}
+
 	.result-item {
 		display: flex;
 		flex-direction: column;
@@ -399,6 +795,33 @@
 		color: #ef4444;
 	}
 
+	.progress-container {
+		display: flex;
+		align-items: center;
+		gap: 0.75rem;
+		margin-bottom: 0.75rem;
+	}
+
+	.progress-bar {
+		flex: 1;
+		height: 8px;
+		background: rgba(255, 255, 255, 0.1);
+		border-radius: 4px;
+		overflow: hidden;
+	}
+
+	.progress-fill {
+		height: 100%;
+		background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
+		transition: width 0.3s ease;
+	}
+
+	.progress-text {
+		font-size: 0.85rem;
+		color: #888;
+		min-width: 40px;
+	}
+
 	.btn-danger {
 		margin-top: 0.75rem;
 		width: auto;
@@ -439,4 +862,61 @@
 		background: rgba(255, 255, 255, 0.2);
 		color: #fff;
 	}
+
+	/* Pagination styles */
+	.trades-pagination-header {
+		display: flex;
+		justify-content: space-between;
+		align-items: center;
+		margin-bottom: 0.75rem;
+		padding-bottom: 0.5rem;
+		border-bottom: 1px solid rgba(255, 255, 255, 0.1);
+	}
+
+	.trades-count {
+		font-size: 0.85rem;
+		color: #888;
+	}
+
+	.pagination-controls {
+		display: flex;
+		align-items: center;
+		gap: 0.5rem;
+	}
+
+	.btn-pagination {
+		width: auto;
+		padding: 0.35rem 0.75rem;
+		background: rgba(102, 126, 234, 0.1);
+		border: 1px solid rgba(102, 126, 234, 0.3);
+		border-radius: 6px;
+		color: #667eea;
+		font-size: 0.8rem;
+		cursor: pointer;
+		transition: all 0.2s;
+	}
+
+	.btn-pagination:hover:not(:disabled) {
+		background: rgba(102, 126, 234, 0.2);
+		transform: none;
+	}
+
+	.btn-pagination:disabled {
+		opacity: 0.4;
+		cursor: not-allowed;
+	}
+
+	.page-indicator {
+		font-size: 0.8rem;
+		color: #888;
+		min-width: 80px;
+		text-align: center;
+	}
+
+	.trades-loading {
+		text-align: center;
+		color: #888;
+		padding: 1rem;
+		font-size: 0.9rem;
+	}
 </style>

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

@@ -4,13 +4,14 @@
 	import { goto } from '$app/navigation';
 	import { isAuthenticated, isLoading, currentBotStore, setCurrentBot, simulationStore, setCurrentSimulation, addSignals, clearSignals, setSimulationLoading, setSimulationError } from '$lib/stores';
 	import { api } from '$lib/api';
-	import { SignalChart, ProUpgradeBanner } from '$lib/components';
+	import { SignalChart, TradeDashboard, PortfolioSummary } from '$lib/components';
 
 	let botId = $derived($page.params.id);
-	let token = $state('PEPE');
+	let tokenName = $state('');
-	let intervalSeconds = $state(60);
+	let tokenAddress = $state('');
-	let autoExecute = $state(false);
+	let klineInterval = $state('1m');
 	let isRunning = $state(false);
+	let isRefreshing = $state(false);
 
 	onMount(async () => {
 		if (!$isAuthenticated && !$isLoading) {
@@ -27,26 +28,40 @@
 		try {
 			const bot = await api.bots.get(botId);
 			setCurrentBot(bot);
+			
+			// Extract token info from strategy config
+			const strategy = bot.strategy_config;
+			if (strategy) {
+				const condition = strategy.conditions?.[0];
+				const action = strategy.actions?.[0];
+				tokenName = condition?.token || action?.token || '';
+				tokenAddress = condition?.token_address || action?.token_address || '';
+			}
 		} catch (e) {
 			goto('/dashboard');
 		}
 	}
 
 	async function loadSimulations() {
+		isRefreshing = true;
 		try {
 			const simulations = await api.simulate.list(botId);
-			if (simulations.length > 0) {
+			
-				const latest = simulations[0];
+			// Find the most recent running simulation, or fall back to most recent
-				setCurrentSimulation(latest);
+			let current = simulations.find(s => s.status === 'running') || simulations[0];
-				if (latest.signals) {
+			
-					addSignals(latest.signals);
+			if (current) {
-				}
+				setCurrentSimulation(current);
-				if (latest.status === 'running') {
+				clearSignals();
-					isRunning = true;
+				if (current.signals && current.signals.length > 0) {
+					addSignals(current.signals);
 				}
+				isRunning = current.status === 'running';
 			}
 		} catch (e) {
 			console.error('Failed to load simulations:', e);
+		} finally {
+			isRefreshing = false;
 		}
 	}
 
@@ -57,9 +72,9 @@
 
 		try {
 			const simulation = await api.simulate.start(botId, {
-				token,
+				token: tokenAddress,
-				interval_seconds: intervalSeconds,
+				chain: 'bsc',
-				auto_execute: autoExecute
+				kline_interval: klineInterval
 			});
 			setCurrentSimulation(simulation);
 			clearSignals();
@@ -94,11 +109,23 @@
 			<a href="/bot/{botId}" class="back-link">← Back to Chat</a>
 			<h1>Simulation</h1>
 		</div>
+		<div class="header-right">
+			{#if $simulationStore.currentSimulation}
+				<button 
+					type="button" 
+					class="refresh-btn"
+					onclick={() => loadSimulations()}
+					class:refreshing={isRefreshing}
+				>
+					{isRefreshing ? '⟳ Refreshing...' : '⟳ Refresh'}
+				</button>
+			{/if}
+		</div>
 	</header>
 
 	<div class="notice">
 		<span class="notice-icon">⚠️</span>
-		<span>Simulation Mode - Using REST polling (every {intervalSeconds}s). For real-time signals, consider upgrading to Pro tier.</span>
+		<span>Simulation Mode - Running on {klineInterval} kline data. Stop simulation to see results.</span>
 	</div>
 
 	<div class="content">
@@ -111,26 +138,26 @@
 
 			<form onsubmit={(e) => { e.preventDefault(); startSimulation(); }}>
 				<div class="form-row">
-					<div class="field">
+					<div class="field token-info">
-						<label for="token">Token</label>
+						<label>Token</label>
-						<input type="text" id="token" bind:value={token} required disabled={isRunning} />
+						<div class="token-display">
+							<span class="token-name">{tokenName || 'Not configured'}</span>
+							{#if tokenAddress}
+								<span class="token-address">{tokenAddress.slice(0, 10)}...{tokenAddress.slice(-8)}</span>
+							{/if}
+						</div>
 					</div>
 					<div class="field">
-						<label for="interval">Check Interval (seconds)</label>
+						<label for="klineInterval">Kline Interval</label>
-						<select id="interval" bind:value={intervalSeconds} disabled={isRunning}>
+						<select id="klineInterval" bind:value={klineInterval} disabled={isRunning}>
-							<option value={30}>30 seconds</option>
+							<option value="1m">1 minute</option>
-							<option value={60}>60 seconds</option>
+							<option value="5m">5 minutes</option>
-							<option value={120}>2 minutes</option>
+							<option value="15m">15 minutes</option>
-							<option value={300}>5 minutes</option>
+							<option value="1h">1 hour</option>
 						</select>
 					</div>
 				</div>
 
-				<div class="field checkbox-field">
-					<input type="checkbox" id="autoExecute" bind:checked={autoExecute} disabled={isRunning} />
-					<label for="autoExecute">Auto-execute trades (requires Pro tier)</label>
-				</div>
-
 				{#if isRunning}
 					<button type="button" onclick={stopSimulation} class="btn btn-danger">
 						Stop Simulation
@@ -143,16 +170,31 @@
 			</form>
 		</section>
 
-		<ProUpgradeBanner feature="Real-time WebSocket signals for instant trading decisions" />
-
 		<section class="signals-section">
-			<h2>Signals ({$simulationStore.signals.length})</h2>
+			<h2>Portfolio</h2>
+			
+			<PortfolioSummary 
+				initialBalance={$simulationStore.currentSimulation?.portfolio?.initial_balance || 10000}
+				currentBalance={$simulationStore.currentSimulation?.portfolio?.current_balance || 10000}
+				position={$simulationStore.currentSimulation?.portfolio?.position || 0}
+				positionToken={$simulationStore.currentSimulation?.portfolio?.position_token || ''}
+				entryPrice={$simulationStore.currentSimulation?.portfolio?.entry_price || 0}
+				currentPrice={$simulationStore.currentSimulation?.portfolio?.current_price || 0}
+			/>
+			
+			<h2 style="margin-top: 1.5rem;">Price Chart</h2>
+			
+			<SignalChart signals={$simulationStore.signals} klines={$simulationStore.currentSimulation?.klines || []} height={250} />
+			
+			<h2 style="margin-top: 1.5rem;">Trade Activity</h2>
+			
+			<TradeDashboard tradeLog={$simulationStore.currentSimulation?.trade_log || []} />
+			
+			<h2 style="margin-top: 1.5rem;">Signals ({$simulationStore.signals.length})</h2>
 			
 			{#if $simulationStore.signals.length === 0}
-				<p class="empty-state">No signals yet. Start a simulation to see trading signals.</p>
+				<p class="empty-state">No signals generated. The chart above shows price movement.</p>
 			{:else}
-				<SignalChart signals={$simulationStore.signals} height={200} />
-				
 				<div class="signals-list">
 					{#each $simulationStore.signals as signal}
 						<div class="signal-card">
@@ -198,6 +240,42 @@
 		padding: 2rem;
 	}
 
+	header {
+		display: flex;
+		justify-content: space-between;
+		align-items: center;
+		margin-bottom: 1rem;
+	}
+
+	.header-right {
+		display: flex;
+		gap: 0.5rem;
+	}
+
+	.refresh-btn {
+		background: rgba(255, 255, 255, 0.1);
+		border: 1px solid rgba(255, 255, 255, 0.2);
+		color: #fff;
+		padding: 0.5rem 1rem;
+		border-radius: 6px;
+		cursor: pointer;
+		font-size: 0.875rem;
+		display: flex;
+		align-items: center;
+		gap: 0.5rem;
+		transition: all 0.2s;
+	}
+
+	.refresh-btn:hover {
+		background: rgba(255, 255, 255, 0.15);
+		border-color: rgba(255, 255, 255, 0.3);
+	}
+
+	.refresh-btn.refreshing {
+		opacity: 0.7;
+		cursor: not-allowed;
+	}
+
 	header {
 		margin-bottom: 1.5rem;
 	}
@@ -276,6 +354,27 @@
 		gap: 0.5rem;
 	}
 
+	.token-display {
+		display: flex;
+		flex-direction: column;
+		gap: 0.25rem;
+		padding: 0.75rem;
+		background: rgba(255, 255, 255, 0.05);
+		border: 1px solid rgba(255, 255, 255, 0.2);
+		border-radius: 8px;
+	}
+
+	.token-name {
+		font-weight: 600;
+		color: #667eea;
+	}
+
+	.token-address {
+		font-size: 0.8rem;
+		color: #888;
+		font-family: 'Monaco', 'Menlo', monospace;
+	}
+
 	.checkbox-field {
 		flex-direction: row;
 		align-items: center;