TIANHE
b7451c63fb
- Fix quantity precision calculation for Binance, OKX, Bybit, Bitget, Deepcoin exchanges - Improve OpenRouter API error handling with detailed error messages - Add SECRET_KEY validation in Docker deployment entrypoint - Fix K-line chart measurement tool click issue - Adapt billing page text colors for dark theme - Update frontend build files
570 lines
23 KiB
Python
570 lines
23 KiB
Python
"""
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LLM service.
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Supports multiple providers: OpenRouter, OpenAI, Google Gemini, DeepSeek, Grok.
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Kept separate from AnalysisService to avoid circular imports.
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"""
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import json
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import os
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import requests
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from typing import Dict, Any, Optional, List
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from enum import Enum
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from app.utils.logger import get_logger
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from app.config import APIKeys
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from app.utils.config_loader import load_addon_config
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logger = get_logger(__name__)
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class LLMProvider(Enum):
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"""Supported LLM providers"""
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OPENROUTER = "openrouter"
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OPENAI = "openai"
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GOOGLE = "google"
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DEEPSEEK = "deepseek"
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GROK = "grok"
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# Provider configurations
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PROVIDER_CONFIGS = {
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LLMProvider.OPENROUTER: {
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"base_url": "https://openrouter.ai/api/v1",
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"default_model": "openai/gpt-4o",
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"fallback_model": "openai/gpt-4o-mini",
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},
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LLMProvider.OPENAI: {
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"base_url": "https://api.openai.com/v1",
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"default_model": "gpt-4o",
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"fallback_model": "gpt-4o-mini",
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},
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LLMProvider.GOOGLE: {
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"base_url": "https://generativelanguage.googleapis.com/v1beta",
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"default_model": "gemini-1.5-flash",
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"fallback_model": "gemini-1.5-flash",
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},
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LLMProvider.DEEPSEEK: {
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"base_url": "https://api.deepseek.com/v1",
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"default_model": "deepseek-chat",
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"fallback_model": "deepseek-chat",
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},
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LLMProvider.GROK: {
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"base_url": "https://api.x.ai/v1",
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"default_model": "grok-beta",
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"fallback_model": "grok-beta",
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},
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}
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class LLMService:
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"""LLM provider wrapper with multi-provider support."""
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def __init__(self, provider: str = None):
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"""
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Initialize LLM service.
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Args:
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provider: Override the default provider (openrouter, openai, google, deepseek, grok)
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"""
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self._provider_override = provider
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@property
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def provider(self) -> LLMProvider:
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"""Get the active LLM provider."""
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if self._provider_override:
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try:
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return LLMProvider(self._provider_override.lower())
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except ValueError:
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pass
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# Check env/config for provider selection
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config = load_addon_config()
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provider_name = config.get('llm', {}).get('provider') or os.getenv('LLM_PROVIDER', '')
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if provider_name:
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try:
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selected = LLMProvider(provider_name.lower())
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# Verify this provider has an API key configured
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if self.get_api_key(selected):
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return selected
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logger.warning(f"LLM_PROVIDER={provider_name} but no API key configured, auto-detecting...")
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except ValueError:
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pass
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# Auto-detect: find any provider with a configured API key
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# Priority: DeepSeek > Grok > OpenAI > Google > OpenRouter
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priority_order = [
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LLMProvider.DEEPSEEK,
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LLMProvider.GROK,
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LLMProvider.OPENAI,
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LLMProvider.GOOGLE,
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LLMProvider.OPENROUTER,
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]
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for p in priority_order:
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if self.get_api_key(p):
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logger.info(f"Auto-detected LLM provider: {p.value}")
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return p
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# Fallback to OpenRouter (will fail later if no key)
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return LLMProvider.OPENROUTER
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def get_api_key(self, provider: LLMProvider = None) -> str:
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"""Get API key for the specified provider."""
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p = provider or self.provider
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key_map = {
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LLMProvider.OPENROUTER: APIKeys.OPENROUTER_API_KEY,
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LLMProvider.OPENAI: APIKeys.OPENAI_API_KEY,
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LLMProvider.GOOGLE: APIKeys.GOOGLE_API_KEY,
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LLMProvider.DEEPSEEK: APIKeys.DEEPSEEK_API_KEY,
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LLMProvider.GROK: APIKeys.GROK_API_KEY,
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}
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return key_map.get(p, "") or ""
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def get_base_url(self, provider: LLMProvider = None) -> str:
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"""Get base URL for the specified provider."""
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p = provider or self.provider
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config = load_addon_config()
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# Check for custom base URL in config
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provider_config = config.get(p.value, {})
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custom_url = provider_config.get('base_url') or os.getenv(f'{p.value.upper()}_BASE_URL', '').strip()
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if custom_url:
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return custom_url.rstrip('/')
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return PROVIDER_CONFIGS[p]["base_url"]
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def get_default_model(self, provider: LLMProvider = None) -> str:
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"""Get default model for the specified provider."""
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p = provider or self.provider
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config = load_addon_config()
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provider_config = config.get(p.value, {})
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custom_model = provider_config.get('model') or os.getenv(f'{p.value.upper()}_MODEL', '').strip()
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if custom_model:
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return custom_model
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return PROVIDER_CONFIGS[p]["default_model"]
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# Legacy properties for backward compatibility
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@property
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def api_key(self):
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return self.get_api_key()
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@property
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def base_url(self):
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return self.get_base_url()
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def _call_openai_compatible(self, messages: list, model: str, temperature: float,
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api_key: str, base_url: str, timeout: int,
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use_json_mode: bool = True) -> str:
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"""Call OpenAI-compatible API (OpenAI, DeepSeek, Grok, OpenRouter)."""
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url = f"{base_url}/chat/completions"
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headers = {
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"Authorization": f"Bearer {api_key}",
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"Content-Type": "application/json",
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}
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# OpenRouter specific headers
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if "openrouter" in base_url:
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headers["HTTP-Referer"] = "https://quantdinger.com"
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headers["X-Title"] = "QuantDinger Analysis"
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data = {
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"model": model,
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"messages": messages,
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"temperature": temperature,
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}
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if use_json_mode:
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data["response_format"] = {"type": "json_object"}
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response = requests.post(url, headers=headers, json=data, timeout=timeout)
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# Handle errors with detailed messages
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if response.status_code == 403:
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error_msg = "OpenRouter API 403 Forbidden"
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try:
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error_data = response.json()
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if "error" in error_data:
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error_detail = error_data["error"]
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if isinstance(error_detail, dict):
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error_msg = f"OpenRouter API 403: {error_detail.get('message', 'Forbidden')}"
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elif isinstance(error_detail, str):
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error_msg = f"OpenRouter API 403: {error_detail}"
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except:
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pass
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# Check if API key is configured
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from app.config.api_keys import APIKeys
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if not APIKeys.OPENROUTER_API_KEY:
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error_msg += ". OPENROUTER_API_KEY 未配置，请在 backend_api_python/.env 中设置"
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else:
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error_msg += ". 可能的原因：1) API 密钥无效或过期 2) 账户余额不足 3) 没有权限访问该模型。请检查 https://openrouter.ai/keys"
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raise ValueError(error_msg)
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response.raise_for_status()
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result = response.json()
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if "choices" in result and len(result["choices"]) > 0:
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content = result["choices"][0]["message"]["content"]
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if not content:
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raise ValueError(f"Model {model} returned empty content")
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return content
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else:
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raise ValueError("API response is missing 'choices'")
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def _call_google_gemini(self, messages: list, model: str, temperature: float,
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api_key: str, base_url: str, timeout: int) -> str:
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"""Call Google Gemini API."""
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url = f"{base_url}/models/{model}:generateContent?key={api_key}"
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# Convert OpenAI message format to Gemini format
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contents = []
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system_instruction = None
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for msg in messages:
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role = msg["role"]
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content = msg["content"]
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if role == "system":
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system_instruction = content
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elif role == "user":
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contents.append({"role": "user", "parts": [{"text": content}]})
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elif role == "assistant":
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contents.append({"role": "model", "parts": [{"text": content}]})
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data = {
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"contents": contents,
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"generationConfig": {
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"temperature": temperature,
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"responseMimeType": "application/json",
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}
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}
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if system_instruction:
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data["systemInstruction"] = {"parts": [{"text": system_instruction}]}
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headers = {"Content-Type": "application/json"}
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response = requests.post(url, headers=headers, json=data, timeout=timeout)
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response.raise_for_status()
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result = response.json()
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if "candidates" in result and len(result["candidates"]) > 0:
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candidate = result["candidates"][0]
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if "content" in candidate and "parts" in candidate["content"]:
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text = candidate["content"]["parts"][0].get("text", "")
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if text:
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return text
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raise ValueError("Gemini API response is missing content")
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def _normalize_model_for_provider(self, model: str, provider: LLMProvider) -> str:
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"""
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Normalize model name for the target provider.
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Frontend may send OpenRouter-style model names (e.g., 'openai/gpt-4o').
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This converts them to the correct format for each provider.
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"""
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if not model:
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return self.get_default_model(provider)
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model = model.strip()
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# If using OpenRouter, keep the original format
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if provider == LLMProvider.OPENROUTER:
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return model
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# For direct providers, extract the model name from OpenRouter format
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# e.g., 'openai/gpt-4o' -> 'gpt-4o'
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# 'google/gemini-1.5-flash' -> 'gemini-1.5-flash'
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# 'deepseek/deepseek-chat' -> 'deepseek-chat'
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# 'x-ai/grok-beta' -> 'grok-beta'
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if '/' in model:
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prefix, actual_model = model.split('/', 1)
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prefix_lower = prefix.lower()
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# Map OpenRouter prefixes to providers
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prefix_to_provider = {
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'openai': LLMProvider.OPENAI,
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'google': LLMProvider.GOOGLE,
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'deepseek': LLMProvider.DEEPSEEK,
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'x-ai': LLMProvider.GROK,
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'xai': LLMProvider.GROK,
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}
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# If the model prefix matches the current provider, use the extracted model name
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matched_provider = prefix_to_provider.get(prefix_lower)
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if matched_provider == provider:
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return actual_model
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# If model prefix doesn't match current provider, use provider's default model
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# This prevents sending 'gpt-4o' to DeepSeek, etc.
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logger.warning(f"Model '{model}' doesn't match provider '{provider.value}', using default model")
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return self.get_default_model(provider)
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# Model name without prefix - use as is
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return model
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def _detect_provider_from_model(self, model: str) -> Optional[LLMProvider]:
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"""
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Detect which provider a model belongs to based on its name.
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Returns None if detection fails.
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"""
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if not model or '/' not in model:
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return None
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prefix = model.split('/')[0].lower()
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prefix_to_provider = {
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'openai': LLMProvider.OPENAI,
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'google': LLMProvider.GOOGLE,
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'deepseek': LLMProvider.DEEPSEEK,
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'x-ai': LLMProvider.GROK,
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'xai': LLMProvider.GROK,
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'anthropic': LLMProvider.OPENROUTER, # Anthropic only via OpenRouter
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'meta': LLMProvider.OPENROUTER, # Meta/Llama only via OpenRouter
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'mistral': LLMProvider.OPENROUTER, # Mistral only via OpenRouter
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}
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return prefix_to_provider.get(prefix)
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def call_llm_api(self, messages: list, model: str = None, temperature: float = 0.7,
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use_fallback: bool = True, provider: LLMProvider = None,
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use_json_mode: bool = True, try_alternative_providers: bool = True) -> str:
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"""
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Call LLM API with the specified or default provider.
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Args:
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messages: List of message dicts with 'role' and 'content'
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model: Model name (uses provider default if not specified). Supports OpenRouter format (e.g., 'openai/gpt-4o')
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temperature: Sampling temperature
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use_fallback: Whether to try fallback model on failure
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provider: Override the service's default provider
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use_json_mode: Whether to request JSON output format (default True for analysis, False for code generation)
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try_alternative_providers: Whether to try alternative providers when current provider fails with 403/402
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Returns:
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Generated text content
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Model Resolution Priority:
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1. If model is specified and matches a direct provider (openai/, google/, deepseek/, x-ai/),
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use that provider directly if its API key is configured
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2. Otherwise, use the configured LLM_PROVIDER with normalized model name
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3. Fall back to provider's default model if model name is incompatible
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"""
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# Smart provider detection: if model specifies a provider and we have its API key, use it
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if model and not provider:
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detected_provider = self._detect_provider_from_model(model)
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if detected_provider and detected_provider != LLMProvider.OPENROUTER:
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# Check if we have API key for the detected provider
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if self.get_api_key(detected_provider):
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provider = detected_provider
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logger.debug(f"Auto-detected provider '{provider.value}' from model '{model}'")
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p = provider or self.provider
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api_key = self.get_api_key(p)
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if not api_key:
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# If no API key for current provider, try to find any available provider
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if try_alternative_providers:
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for alt_provider in [LLMProvider.DEEPSEEK, LLMProvider.GROK, LLMProvider.OPENAI, LLMProvider.GOOGLE, LLMProvider.OPENROUTER]:
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if alt_provider != p and self.get_api_key(alt_provider):
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logger.warning(f"No API key for {p.value}, switching to {alt_provider.value}")
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p = alt_provider
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api_key = self.get_api_key(p)
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break
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if not api_key:
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raise ValueError(f"API key not configured for provider: {p.value}. Please configure at least one LLM provider API key.")
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base_url = self.get_base_url(p)
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# Normalize model name for the provider
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original_model = model
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model = self._normalize_model_for_provider(model, p)
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config = load_addon_config()
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timeout = int(config.get(p.value, {}).get('timeout', 120))
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# Build model candidates
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models_to_try = [model]
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provider_default_model = PROVIDER_CONFIGS[p]["default_model"]
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if use_fallback:
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fallback = PROVIDER_CONFIGS[p].get("fallback_model")
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if fallback and fallback != model:
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models_to_try.append(fallback)
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last_error = None
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last_status_code = None
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for current_model in models_to_try:
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try:
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if p == LLMProvider.GOOGLE:
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return self._call_google_gemini(
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messages, current_model, temperature,
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api_key, base_url, timeout
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)
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else:
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# OpenAI-compatible providers
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return self._call_openai_compatible(
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messages, current_model, temperature,
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api_key, base_url, timeout,
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use_json_mode=use_json_mode
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)
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except requests.exceptions.HTTPError as e:
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error_detail = e.response.text if e.response else str(e)
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status_code = e.response.status_code if e.response else None
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last_status_code = status_code
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logger.error(f"{p.value} API HTTP error ({current_model}): {status_code} - {error_detail}")
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last_error = str(e)
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# 403/402 errors usually mean API key issue - try alternative provider
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if status_code in (402, 403) and try_alternative_providers and current_model == models_to_try[-1]:
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# Only try alternative providers after all models in current provider failed
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logger.warning(f"{p.value} returned {status_code} (likely API key issue). Trying alternative providers...")
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return self._try_alternative_providers(
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messages, original_model, temperature,
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use_json_mode, excluded_provider=p
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)
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# Check for recoverable errors - try fallback model
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# 402: Payment required, 403: Forbidden (invalid key), 404: Model not found, 429: Rate limit
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if status_code in (402, 403, 404, 429):
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logger.warning(f"{p.value} returned {status_code} for model {current_model}; trying fallback...")
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continue
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if not use_fallback or current_model == models_to_try[-1]:
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raise
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except requests.exceptions.RequestException as e:
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logger.error(f"{p.value} API request error ({current_model}): {str(e)}")
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last_error = str(e)
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if not use_fallback or current_model == models_to_try[-1]:
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raise
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except ValueError as e:
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logger.warning(f"Model {current_model} returned invalid data: {str(e)}")
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last_error = str(e)
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if current_model == models_to_try[-1]:
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raise
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error_msg = f"All model calls failed for {p.value}. Last error: {last_error}"
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if last_status_code in (402, 403):
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error_msg += f"\nStatus {last_status_code} usually means: API key invalid/expired, insufficient balance, or no access to model."
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error_msg += f"\nPlease check your {p.value} API key configuration and account balance."
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logger.error(error_msg)
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raise Exception(error_msg)
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def _try_alternative_providers(self, messages: list, model: str, temperature: float,
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use_json_mode: bool, excluded_provider: LLMProvider = None) -> str:
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"""
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Try alternative providers when current provider fails.
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Priority: DeepSeek > Grok > OpenAI > Google > OpenRouter
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"""
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priority_order = [
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LLMProvider.DEEPSEEK,
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LLMProvider.GROK,
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LLMProvider.OPENAI,
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LLMProvider.GOOGLE,
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LLMProvider.OPENROUTER,
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]
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for alt_provider in priority_order:
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if alt_provider == excluded_provider:
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continue
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api_key = self.get_api_key(alt_provider)
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if not api_key:
|
|
continue
|
|
|
|
logger.info(f"Trying alternative provider: {alt_provider.value}")
|
|
try:
|
|
return self.call_llm_api(
|
|
messages, model, temperature,
|
|
use_fallback=True, provider=alt_provider,
|
|
use_json_mode=use_json_mode,
|
|
try_alternative_providers=False # Prevent infinite recursion
|
|
)
|
|
except Exception as e:
|
|
logger.warning(f"Alternative provider {alt_provider.value} also failed: {str(e)}")
|
|
continue
|
|
|
|
raise Exception(f"All LLM providers failed. Please check your API key configurations.")
|
|
|
|
# Legacy method for backward compatibility
|
|
def call_openrouter_api(self, messages: list, model: str = None, temperature: float = 0.7, use_fallback: bool = True) -> str:
|
|
"""Call LLM API (legacy method name for backward compatibility)."""
|
|
return self.call_llm_api(messages, model, temperature, use_fallback)
|
|
|
|
def safe_call_llm(self, system_prompt: str, user_prompt: str, default_structure: Dict[str, Any],
|
|
model: str = None, provider: LLMProvider = None) -> Dict[str, Any]:
|
|
"""Safe LLM call with robust JSON parsing and fallback structure."""
|
|
response_text = ""
|
|
try:
|
|
response_text = self.call_llm_api([
|
|
{"role": "system", "content": system_prompt},
|
|
{"role": "user", "content": user_prompt}
|
|
], model=model, provider=provider)
|
|
|
|
# Strip markdown fences if present
|
|
clean_text = response_text.strip()
|
|
if clean_text.startswith("```"):
|
|
first_newline = clean_text.find("\n")
|
|
if first_newline != -1:
|
|
clean_text = clean_text[first_newline+1:]
|
|
if clean_text.endswith("```"):
|
|
clean_text = clean_text[:-3]
|
|
clean_text = clean_text.strip()
|
|
|
|
# Parse JSON
|
|
result = json.loads(clean_text)
|
|
return result
|
|
except json.JSONDecodeError:
|
|
logger.error(f"JSON parse failed. Raw text: {response_text[:200] if response_text else 'N/A'}")
|
|
|
|
# Try extracting JSON substring
|
|
try:
|
|
if response_text:
|
|
start = response_text.find('{')
|
|
end = response_text.rfind('}') + 1
|
|
if start >= 0 and end > start:
|
|
result = json.loads(response_text[start:end])
|
|
return result
|
|
except:
|
|
pass
|
|
|
|
default_structure['report'] = f"Failed to parse analysis result JSON. Raw output (partial): {response_text[:500] if response_text else 'N/A'}"
|
|
return default_structure
|
|
except Exception as e:
|
|
logger.error(f"LLM call failed: {str(e)}")
|
|
default_structure['report'] = f"Analysis failed: {str(e)}"
|
|
return default_structure
|
|
|
|
@classmethod
|
|
def get_available_providers(cls) -> List[Dict[str, Any]]:
|
|
"""Get list of available (configured) providers."""
|
|
providers = []
|
|
|
|
for p in LLMProvider:
|
|
service = cls()
|
|
api_key = service.get_api_key(p)
|
|
providers.append({
|
|
"id": p.value,
|
|
"name": p.value.title(),
|
|
"configured": bool(api_key),
|
|
"default_model": PROVIDER_CONFIGS[p]["default_model"],
|
|
})
|
|
|
|
return providers
|