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8 Commits

Author SHA1 Message Date
shokollm
a280217254 feat: implement chat interface with CrewAI integration
- Create MiniMax LLM connector for CrewAI integration
- Implement TradingCrew with trading_designer, strategy_validator, strategy_explainer
- Add strategy parsing from natural language to strategy_config JSON
- Update chat endpoint with CrewAI integration and conversation context
- Add strategy validation logic
- Add explanation generation for user-friendly responses
- Add BotChatRequest/BotChatResponse schemas

Fixes #6
2026-04-08 06:29:05 +00:00
0cc3327991 Merge pull request '[Backend] Bot CRUD - Bot Management with Max 3 Limit' (#16) from fix/issue-5 into main 2026-04-08 08:16:19 +02:00
shokollm
429d46c6d0 feat: implement bot CRUD with 3-bot limit per user 2026-04-08 06:05:43 +00:00
a2f0c9a0e9 Merge pull request '[Backend] Auth System - JWT Authentication' (#15) from fix/issue-4 into main 2026-04-08 08:01:24 +02:00
shokollm
42640679c7 feat: implement JWT authentication system
- Add register endpoint with bcrypt password hashing
- Add login endpoint returning JWT tokens
- Add logout endpoint with token blacklisting
- Add /me endpoint for current user info
- Add rate limiting (5/minute) for login attempts using slowapi
- Add user settings GET and PATCH endpoints
- Create auth middleware via get_current_user dependency
- Add UserSettings and UserSettingsUpdate schemas
2026-04-08 05:48:38 +00:00
f59e595ffd Merge pull request '[Backend] Database Models - Add missing Pydantic schemas' (#14) from fix/issue-3 into main 2026-04-08 06:57:46 +02:00
shokollm
a5e41ab449 Add missing Pydantic schemas for BotConversation and Signal
Based on IMPLEMENTATION_PLAN.md Section 4 schema, the existing schemas.py
was missing schemas for:
- BotConversationCreate/Response (for bot_conversations table)
- SignalResponse (for signals table)

These were identified as gaps during issue #3 review.
2026-04-08 04:41:31 +00:00
6977203748 Merge pull request '[Backend] Project Setup - FastAPI Structure and Dependencies' (#13) from fix/issue-2 into main 2026-04-08 06:35:53 +02:00
8 changed files with 768 additions and 70 deletions

View File

@@ -1,7 +1,6 @@
from fastapi import APIRouter, Depends, HTTPException, status
from fastapi import APIRouter, Depends, HTTPException, status, Request
from fastapi.security import OAuth2PasswordBearer, OAuth2PasswordRequestForm
from sqlalchemy.orm import Session
from datetime import timedelta
from typing import Annotated
from ..core.database import get_db
@@ -12,41 +11,133 @@ from ..core.security import (
verify_token,
)
from ..core.config import get_settings
from ..db.schemas import UserCreate, UserResponse, Token
from ..core.limiter import limiter
from ..db.schemas import (
UserCreate,
UserResponse,
Token,
UserSettings,
UserSettingsUpdate,
)
from ..db.models import User
router = APIRouter()
settings = get_settings()
oauth2_scheme = OAuth2PasswordBearer(tokenUrl="/api/auth/token")
oauth2_scheme = OAuth2PasswordBearer(tokenUrl="/api/auth/login")
TOKEN_BLACKLIST = set()
@router.post("/register", response_model=UserResponse)
def get_current_user(
token: Annotated[str, Depends(oauth2_scheme)], db: Session = Depends(get_db)
) -> User:
if token in TOKEN_BLACKLIST:
raise HTTPException(
status_code=status.HTTP_401_UNAUTHORIZED,
detail="Token has been revoked",
)
payload = verify_token(token)
if payload is None:
raise HTTPException(
status_code=status.HTTP_401_UNAUTHORIZED,
detail="Invalid or expired token",
)
user_id = payload.get("sub")
if user_id is None:
raise HTTPException(
status_code=status.HTTP_401_UNAUTHORIZED,
detail="Invalid token payload",
)
user = db.query(User).filter(User.id == user_id).first()
if user is None:
raise HTTPException(
status_code=status.HTTP_401_UNAUTHORIZED,
detail="User not found",
)
return user
@router.post(
"/register", response_model=UserResponse, status_code=status.HTTP_201_CREATED
)
def register(user: UserCreate, db: Session = Depends(get_db)):
raise HTTPException(
status_code=status.HTTP_501_NOT_IMPLEMENTED, detail="Not implemented"
existing_user = db.query(User).filter(User.email == user.email).first()
if existing_user:
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail="Email already registered",
)
hashed_password = get_password_hash(user.password)
db_user = User(
email=user.email,
password_hash=hashed_password,
)
db.add(db_user)
db.commit()
db.refresh(db_user)
return db_user
@router.post("/login")
@router.post("/login", response_model=Token)
@limiter.limit("5/minute")
def login(
request: Request,
form_data: Annotated[OAuth2PasswordRequestForm, Depends()],
db: Session = Depends(get_db),
):
raise HTTPException(
status_code=status.HTTP_501_NOT_IMPLEMENTED, detail="Not implemented"
)
user = db.query(User).filter(User.email == form_data.username).first()
if not user or not verify_password(form_data.password, user.password_hash):
raise HTTPException(
status_code=status.HTTP_401_UNAUTHORIZED,
detail="Incorrect email or password",
)
access_token = create_access_token(data={"sub": user.id})
return Token(access_token=access_token, token_type="bearer")
@router.post("/logout")
def logout(token: Annotated[str, Depends(oauth2_scheme)]):
raise HTTPException(
status_code=status.HTTP_501_NOT_IMPLEMENTED, detail="Not implemented"
)
def logout(
current_user: Annotated[User, Depends(get_current_user)],
token: Annotated[str, Depends(oauth2_scheme)],
):
TOKEN_BLACKLIST.add(token)
return {"message": "Successfully logged out"}
@router.get("/me", response_model=UserResponse)
def get_me(
token: Annotated[str, Depends(oauth2_scheme)], db: Session = Depends(get_db)
current_user: Annotated[User, Depends(get_current_user)],
):
raise HTTPException(
status_code=status.HTTP_501_NOT_IMPLEMENTED, detail="Not implemented"
)
return current_user
@router.get("/settings", response_model=UserSettings)
def get_settings_endpoint(
current_user: Annotated[User, Depends(get_current_user)],
):
return UserSettings(email=current_user.email)
@router.patch("/settings", response_model=UserSettings)
def update_settings(
current_user: Annotated[User, Depends(get_current_user)],
settings_update: UserSettingsUpdate,
db: Session = Depends(get_db),
):
if settings_update.email:
existing = (
db.query(User)
.filter(User.email == settings_update.email, User.id != current_user.id)
.first()
)
if existing:
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail="Email already in use",
)
current_user.email = settings_update.email
if settings_update.password:
current_user.password_hash = get_password_hash(settings_update.password)
db.commit()
db.refresh(current_user)
return UserSettings(email=current_user.email)

View File

@@ -1,57 +1,275 @@
from fastapi import APIRouter, Depends, HTTPException, status
from sqlalchemy.orm import Session
from typing import List
from typing import List, Annotated
from .auth import get_current_user
from ..core.database import get_db
from ..db.schemas import BotCreate, BotUpdate, BotResponse
from ..core.config import get_settings
from ..db.schemas import (
BotCreate,
BotUpdate,
BotResponse,
BotConversationCreate,
BotConversationResponse,
BotChatRequest,
BotChatResponse,
)
from ..db.models import Bot, BotConversation, User
from ..services.ai_agent.crew import get_trading_crew
router = APIRouter()
MAX_BOTS_PER_USER = 3
@router.get("", response_model=List[BotResponse])
def list_bots(db: Session = Depends(get_db)):
raise HTTPException(
status_code=status.HTTP_501_NOT_IMPLEMENTED, detail="Not implemented"
)
def list_bots(
current_user: Annotated[User, Depends(get_current_user)],
db: Session = Depends(get_db),
):
bots = db.query(Bot).filter(Bot.user_id == current_user.id).all()
return bots
@router.post("", response_model=BotResponse)
def create_bot(bot: BotCreate, db: Session = Depends(get_db)):
raise HTTPException(
status_code=status.HTTP_501_NOT_IMPLEMENTED, detail="Not implemented"
@router.post("", response_model=BotResponse, status_code=status.HTTP_201_CREATED)
def create_bot(
bot_data: BotCreate,
current_user: Annotated[User, Depends(get_current_user)],
db: Session = Depends(get_db),
):
user_bot_count = db.query(Bot).filter(Bot.user_id == current_user.id).count()
if user_bot_count >= MAX_BOTS_PER_USER:
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail=f"Maximum of {MAX_BOTS_PER_USER} bots per user exceeded",
)
existing_bot = (
db.query(Bot)
.filter(Bot.user_id == current_user.id, Bot.name == bot_data.name)
.first()
)
if existing_bot:
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail="Bot name must be unique per user",
)
db_bot = Bot(
user_id=current_user.id,
name=bot_data.name,
description=bot_data.description,
strategy_config=bot_data.strategy_config,
llm_config=bot_data.llm_config,
)
db.add(db_bot)
db.commit()
db.refresh(db_bot)
return db_bot
@router.get("/{bot_id}", response_model=BotResponse)
def get_bot(bot_id: str, db: Session = Depends(get_db)):
raise HTTPException(
status_code=status.HTTP_501_NOT_IMPLEMENTED, detail="Not implemented"
)
def get_bot(
bot_id: str,
current_user: Annotated[User, Depends(get_current_user)],
db: Session = Depends(get_db),
):
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 to access this bot",
)
return bot
@router.put("/{bot_id}", response_model=BotResponse)
def update_bot(bot_id: str, bot: BotUpdate, db: Session = Depends(get_db)):
raise HTTPException(
status_code=status.HTTP_501_NOT_IMPLEMENTED, detail="Not implemented"
def update_bot(
bot_id: str,
bot_data: BotUpdate,
current_user: Annotated[User, Depends(get_current_user)],
db: Session = Depends(get_db),
):
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 to update this bot",
)
if bot_data.name is not None:
existing_bot = (
db.query(Bot)
.filter(
Bot.user_id == current_user.id,
Bot.name == bot_data.name,
Bot.id != bot_id,
)
.first()
)
if existing_bot:
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail="Bot name must be unique per user",
)
bot.name = bot_data.name
if bot_data.description is not None:
bot.description = bot_data.description
if bot_data.strategy_config is not None:
bot.strategy_config = bot_data.strategy_config
if bot_data.llm_config is not None:
bot.llm_config = bot_data.llm_config
if bot_data.status is not None:
bot.status = bot_data.status
db.commit()
db.refresh(bot)
return bot
@router.delete("/{bot_id}", status_code=status.HTTP_204_NO_CONTENT)
def delete_bot(
bot_id: str,
current_user: Annotated[User, Depends(get_current_user)],
db: Session = Depends(get_db),
):
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 to delete this bot",
)
db.delete(bot)
db.commit()
@router.post("/{bot_id}/chat", response_model=BotChatResponse)
def chat(
bot_id: str,
request: BotChatRequest,
current_user: Annotated[User, Depends(get_current_user)],
db: Session = Depends(get_db),
):
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 to chat with this bot",
)
conversation_history = (
db.query(BotConversation)
.filter(BotConversation.bot_id == bot_id)
.order_by(BotConversation.created_at)
.all()
)
history_for_crew = [
{"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.")
if result.get("success") and result.get("strategy_config"):
bot.strategy_config = result["strategy_config"]
db.commit()
db_conversation = BotConversation(
bot_id=bot_id,
role="user",
content=user_message,
)
db.add(db_conversation)
db_assistant = BotConversation(
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),
)
else:
crew = get_trading_crew()
result = crew.chat(user_message, history_for_crew)
assistant_content = result.get("response", "I couldn't process your request.")
db_conversation = BotConversation(
bot_id=bot_id,
role="user",
content=user_message,
)
db.add(db_conversation)
db_assistant = BotConversation(
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.delete("/{bot_id}")
def delete_bot(bot_id: str, db: Session = Depends(get_db)):
raise HTTPException(
status_code=status.HTTP_501_NOT_IMPLEMENTED, detail="Not implemented"
)
@router.post("/{bot_id}/chat")
def chat(bot_id: str, message: dict, db: Session = Depends(get_db)):
raise HTTPException(
status_code=status.HTTP_501_NOT_IMPLEMENTED, detail="Not implemented"
)
@router.get("/{bot_id}/history")
def get_history(bot_id: str, db: Session = Depends(get_db)):
raise HTTPException(
status_code=status.HTTP_501_NOT_IMPLEMENTED, detail="Not implemented"
@router.get("/{bot_id}/history", response_model=List[BotConversationResponse])
def get_history(
bot_id: str,
current_user: Annotated[User, Depends(get_current_user)],
db: Session = Depends(get_db),
):
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 to access this bot's history",
)
conversations = (
db.query(BotConversation)
.filter(BotConversation.bot_id == bot_id)
.order_by(BotConversation.created_at)
.all()
)
return conversations

View File

@@ -0,0 +1,4 @@
from slowapi import Limiter
from slowapi.util import get_remote_address
limiter = Limiter(key_func=get_remote_address)

View File

@@ -23,6 +23,15 @@ class Token(BaseModel):
token_type: str
class UserSettings(BaseModel):
email: EmailStr
class UserSettingsUpdate(BaseModel):
email: Optional[EmailStr] = None
password: Optional[str] = None
class BotCreate(BaseModel):
name: str
description: Optional[str] = None
@@ -91,3 +100,46 @@ class SimulationResponse(BaseModel):
class Config:
from_attributes = True
class BotConversationCreate(BaseModel):
role: str
content: str
class BotConversationResponse(BaseModel):
id: str
bot_id: str
role: str
content: str
created_at: datetime
class Config:
from_attributes = True
class BotChatRequest(BaseModel):
message: str
strategy_config: Optional[bool] = False
class BotChatResponse(BaseModel):
response: str
strategy_config: Optional[dict] = None
success: bool = False
class SignalResponse(BaseModel):
id: str
bot_id: str
run_id: str
signal_type: str
token: str
price: float
confidence: Optional[float]
reasoning: Optional[str]
executed: bool
created_at: datetime
class Config:
from_attributes = True

View File

@@ -1,6 +1,9 @@
from fastapi import FastAPI
from fastapi.middleware.cors import CORSMiddleware
from slowapi import Limiter
from slowapi.util import get_remote_address
from .api import auth, bots, backtest, simulate, config
from .core.limiter import limiter
app = FastAPI(
title="Randebu Trading Bot API",
@@ -8,6 +11,8 @@ app = FastAPI(
version="0.1.0",
)
app.state.limiter = limiter
app.add_middleware(
CORSMiddleware,
allow_origins=["*"],

View File

@@ -1,15 +1,247 @@
from typing import List, Optional
from typing import List, Optional, Dict, Any
from crewai import Agent, Task, Crew
from .llm_connector import MiniMaxConnector, MiniMaxLLM
from ..core.config import get_settings
class CrewAgent:
def __init__(self, role: str, goal: str, backstory: str):
self.role = role
self.goal = goal
self.backstory = backstory
class StrategyValidator:
SUPPORTED_CONDITIONS = ["price_drop", "price_rise", "volume_spike", "price_level"]
SUPPORTED_ACTIONS = ["buy", "sell", "notify"]
def execute_task(self, task: str) -> str:
raise NotImplementedError("CrewAI agent not yet implemented")
def validate(self, strategy_config: dict) -> tuple[bool, list[str]]:
errors = []
if "conditions" not in strategy_config:
errors.append("Missing 'conditions' in strategy config")
return False, errors
if not isinstance(strategy_config["conditions"], list):
errors.append("'conditions' must be a list")
return False, errors
if len(strategy_config["conditions"]) == 0:
errors.append("At least one condition is required")
return False, errors
for i, condition in enumerate(strategy_config["conditions"]):
if "type" not in condition:
errors.append(f"Condition {i}: missing 'type'")
continue
cond_type = condition.get("type")
if cond_type not in self.SUPPORTED_CONDITIONS:
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:
errors.append(f"Condition {i}: missing 'token'")
if "threshold_percent" not in params:
errors.append(f"Condition {i}: missing 'threshold_percent'")
elif not isinstance(params["threshold_percent"], (int, float)):
errors.append(
f"Condition {i}: 'threshold_percent' must be a number"
)
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:
errors.append(f"Condition {i}: missing 'token'")
if "price" not in params:
errors.append(f"Condition {i}: missing 'price'")
if "direction" not in params:
errors.append(f"Condition {i}: missing 'direction'")
elif params["direction"] not in ["above", "below"]:
errors.append(
f"Condition {i}: direction must be 'above' or 'below'"
)
if "actions" in strategy_config:
if not isinstance(strategy_config["actions"], list):
errors.append("'actions' must be a list")
else:
for i, action in enumerate(strategy_config["actions"]):
if "type" not in action:
errors.append(f"Action {i}: missing 'type'")
elif action["type"] not in self.SUPPORTED_ACTIONS:
errors.append(
f"Action {i}: unsupported type '{action['type']}'"
)
return len(errors) == 0, errors
def get_trading_crew():
raise NotImplementedError("Trading crew not yet implemented")
class StrategyExplainer:
def explain(self, strategy_config: dict) -> str:
explanations = []
if "conditions" in strategy_config:
cond_list = strategy_config["conditions"]
if cond_list:
explanations.append("This strategy will trigger when:")
for cond in cond_list:
cond_type = cond.get("type")
params = cond.get("params", {})
token = params.get("token", "the token")
if cond_type == "price_drop":
pct = params.get("threshold_percent", 0)
explanations.append(f" - {token} price drops by {pct}%")
elif cond_type == "price_rise":
pct = params.get("threshold_percent", 0)
explanations.append(f" - {token} price rises by {pct}%")
elif cond_type == "volume_spike":
pct = params.get("threshold_percent", 0)
explanations.append(
f" - {token} trading volume increases by {pct}%"
)
elif cond_type == "price_level":
price = params.get("price", 0)
direction = params.get("direction", "unknown")
explanations.append(
f" - {token} price crosses {direction} ${price}"
)
if "actions" in strategy_config:
actions = strategy_config.get("actions", [])
if actions:
explanations.append("\nWhen triggered, the strategy will:")
for action in actions:
action_type = action.get("type")
if action_type == "buy":
explanations.append(" - Buy the token")
elif action_type == "sell":
explanations.append(" - Sell the token")
elif action_type == "notify":
explanations.append(" - Send a notification")
if not explanations:
explanations.append("Strategy configuration is empty or invalid.")
return "\n".join(explanations)
def create_trading_designer_agent(
api_key: str, model: str = "MiniMax-Text-01"
) -> Agent:
connector = MiniMaxConnector(api_key=api_key, model=model)
system_prompt = """You are a Trading Strategy Designer AI. Your role is to parse user requests
for trading strategies into structured JSON configuration.
Supported conditions (MVP):
- price_drop: Triggers when a token's price drops by a specified percentage
- price_rise: Triggers when a token's price rises by a specified percentage
- volume_spike: Triggers when trading volume increases by a specified percentage
- price_level: Triggers when price crosses above or below a specified level
Always ask clarifying questions if the user's request is ambiguous.
Output strategy_config in valid JSON format only when you have all required information.
"""
return 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),
verbose=True,
)
def create_strategy_validator_agent(
api_key: str, model: str = "MiniMax-Text-01"
) -> Agent:
return Agent(
role="Strategy Validator",
goal="Validate trading strategy configurations for feasibility and identify potential issues",
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),
verbose=True,
)
def create_strategy_explainer_agent(
api_key: str, model: str = "MiniMax-Text-01"
) -> Agent:
return Agent(
role="Strategy Explainer",
goal="Generate clear, user-friendly explanations of trading strategies",
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),
verbose=True,
)
class TradingCrew:
def __init__(self, api_key: str, model: str = "MiniMax-Text-01"):
self.api_key = api_key
self.model = model
self.validator = StrategyValidator()
self.explainer = StrategyExplainer()
self.connector = MiniMaxConnector(api_key=api_key, model=model)
def parse_strategy(
self, user_message: str, conversation_history: list[dict] = None
) -> dict:
strategy_config = self.connector.parse_strategy(
user_message, conversation_history
)
if "error" in strategy_config:
return strategy_config
is_valid, errors = self.validator.validate(strategy_config)
if not is_valid:
return {
"error": "Strategy validation failed",
"validation_errors": errors,
"partial_config": strategy_config,
}
return strategy_config
def explain_strategy(self, strategy_config: dict) -> str:
return self.explainer.explain(strategy_config)
def chat(self, user_message: str, conversation_history: list[dict] = None) -> dict:
strategy_config = self.parse_strategy(user_message, conversation_history)
if "error" in strategy_config:
explanation = f"I had trouble understanding your strategy: {strategy_config.get('error', 'Unknown error')}"
if "validation_errors" in strategy_config:
explanation += "\n\nValidation issues:"
for err in strategy_config["validation_errors"]:
explanation += f"\n - {err}"
return {
"response": explanation,
"strategy_config": strategy_config.get("partial_config"),
"success": False,
}
explanation = self.explain_strategy(strategy_config)
return {
"response": f"I've configured your strategy:\n\n{explanation}",
"strategy_config": strategy_config,
"success": True,
}
def get_trading_crew(
api_key: Optional[str] = None, model: Optional[str] = None
) -> TradingCrew:
if api_key is None:
settings = get_settings()
api_key = settings.MINIMAX_API_KEY
if model is None:
settings = get_settings()
model = settings.MINIMAX_MODEL
return TradingCrew(api_key=api_key, model=model)

View File

@@ -1,13 +1,108 @@
from typing import Optional
from typing import Optional, List, Dict, Any
import httpx
from crewai import LLM
class LLMConnector:
class MiniMaxLLM(LLM):
def __init__(self, api_key: str, model: str = "MiniMax-Text-01", **kwargs):
super().__init__(**kwargs)
self.api_key = api_key
self.model = model
self.base_url = "https://api.minimax.chat/v1"
def _call(self, messages: List[Dict[str, str]], **kwargs) -> str:
headers = {
"Authorization": f"Bearer {self.api_key}",
"Content-Type": "application/json",
}
payload = {
"model": self.model,
"messages": messages,
"temperature": kwargs.get("temperature", 0.7),
"max_tokens": kwargs.get("max_tokens", 2048),
}
with httpx.Client(timeout=60.0) as client:
response = client.post(
f"{self.base_url}/chat/completions",
headers=headers,
json=payload,
)
response.raise_for_status()
return response.json()["choices"][0]["message"]["content"]
def call(self, messages: List[Dict[str, str]], **kwargs) -> str:
return self._call(messages, **kwargs)
class MiniMaxConnector:
def __init__(self, api_key: str, model: str = "MiniMax-Text-01"):
self.api_key = api_key
self.model = model
def chat(self, messages: list[dict], **kwargs):
raise NotImplementedError("LLM integration not yet implemented")
def chat(self, messages: list[dict], **kwargs) -> str:
formatted_messages = []
for msg in messages:
if isinstance(msg, dict):
formatted_messages.append(
{
"role": msg.get("role", "user"),
"content": msg.get("content", str(msg)),
}
)
else:
formatted_messages.append({"role": "user", "content": str(msg)})
def parse_strategy(self, user_message: str) -> dict:
raise NotImplementedError("Strategy parsing not yet implemented")
llm = MiniMaxLLM(api_key=self.api_key, model=self.model)
return llm.call(formatted_messages, **kwargs)
def parse_strategy(
self, user_message: str, conversation_history: list[dict] = None
) -> dict:
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_rise: Token price rises by X% (requires: token, threshold_percent)
- volume_spike: Trading volume increases X% (requires: token, threshold_percent)
- price_level: Price crosses above/below X (requires: token, price, direction)
Output ONLY valid JSON with this schema:
{
"conditions": [
{
"type": "price_drop|price_rise|volume_spike|price_level",
"params": {
"token": "TOKEN_SYMBOL",
"threshold_percent": number, // for price_drop, price_rise, volume_spike
"price": number, // for price_level
"direction": "above|below" // for price_level
}
}
],
"actions": [
{
"type": "buy|sell|notify",
"params": {}
}
]
}
If the user wants a condition not in the supported list, ask for clarification.
"""
messages = [{"role": "system", "content": system_prompt}]
if conversation_history:
for msg in conversation_history:
messages.append(
{"role": msg.get("role", "user"), "content": msg.get("content", "")}
)
messages.append({"role": "user", "content": user_message})
response = self.chat(messages)
try:
import json
result = json.loads(response)
return result
except json.JSONDecodeError:
return {"error": "Failed to parse strategy", "raw_response": response}

View File

@@ -10,3 +10,4 @@ crewai>=0.1.0
anthropic>=0.18.0
httpx>=0.26.0
python-multipart>=0.0.6
slowapi>=0.1.9