feat: initial commit - EvoTraders project
量化交易多智能体系统，包含： - 分析师、投资组合经理、风险经理等智能体 - 股票分析、投资组合管理、风险控制工具 - React 前端界面 - FastAPI 后端服务 Co-Authored-By: Claude <noreply@anthropic.com>
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backend/llm/models.py
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243
backend/llm/models.py
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# -*- coding: utf-8 -*-
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"""
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AgentScope Native Model Factory
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Uses native AgentScope model classes for LLM calls
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"""
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import os
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from enum import Enum
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from typing import Optional, Tuple
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from agentscope.formatter import (
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AnthropicChatFormatter,
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DashScopeChatFormatter,
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GeminiChatFormatter,
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OllamaChatFormatter,
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OpenAIChatFormatter,
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)
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from agentscope.model import (
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AnthropicChatModel,
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DashScopeChatModel,
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GeminiChatModel,
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OllamaChatModel,
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OpenAIChatModel,
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)
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class ModelProvider(Enum):
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"""Supported model providers"""
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OPENAI = "OPENAI"
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ANTHROPIC = "ANTHROPIC"
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DASHSCOPE = "DASHSCOPE"
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ALIBABA = "ALIBABA"
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GEMINI = "GEMINI"
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GOOGLE = "GOOGLE"
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OLLAMA = "OLLAMA"
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DEEPSEEK = "DEEPSEEK"
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GROQ = "GROQ"
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OPENROUTER = "OPENROUTER"
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# Provider to AgentScope model class mapping
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PROVIDER_MODEL_MAP = {
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"OPENAI": OpenAIChatModel,
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"ANTHROPIC": AnthropicChatModel,
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"DASHSCOPE": DashScopeChatModel,
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"ALIBABA": DashScopeChatModel,
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"GEMINI": GeminiChatModel,
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"GOOGLE": GeminiChatModel,
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"OLLAMA": OllamaChatModel,
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# OpenAI-compatible providers use OpenAIChatModel with custom base_url
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"DEEPSEEK": OpenAIChatModel,
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"GROQ": OpenAIChatModel,
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"OPENROUTER": OpenAIChatModel,
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}
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# Provider to formatter mapping
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PROVIDER_FORMATTER_MAP = {
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"OPENAI": OpenAIChatFormatter,
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"ANTHROPIC": AnthropicChatFormatter,
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"DASHSCOPE": DashScopeChatFormatter,
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"ALIBABA": DashScopeChatFormatter,
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"GEMINI": GeminiChatFormatter,
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"GOOGLE": GeminiChatFormatter,
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"OLLAMA": OllamaChatFormatter,
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# OpenAI-compatible providers use OpenAIChatFormatter
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"DEEPSEEK": OpenAIChatFormatter,
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"GROQ": OpenAIChatFormatter,
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"OPENROUTER": OpenAIChatFormatter,
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}
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# Provider-specific base URLs
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PROVIDER_BASE_URLS = {
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"DEEPSEEK": "https://api.deepseek.com/v1",
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"GROQ": "https://api.groq.com/openai/v1",
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"OPENROUTER": "https://openrouter.ai/api/v1",
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}
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# Provider-specific API key environment variable names
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PROVIDER_API_KEY_ENV = {
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"OPENAI": "OPENAI_API_KEY",
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"ANTHROPIC": "ANTHROPIC_API_KEY",
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"DASHSCOPE": "DASHSCOPE_API_KEY",
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"ALIBABA": "DASHSCOPE_API_KEY",
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"GEMINI": "GOOGLE_API_KEY",
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"GOOGLE": "GOOGLE_API_KEY",
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"DEEPSEEK": "DEEPSEEK_API_KEY",
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"GROQ": "GROQ_API_KEY",
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"OPENROUTER": "OPENROUTER_API_KEY",
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}
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def create_model(
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model_name: str,
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provider: str,
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api_key: Optional[str] = None,
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stream: bool = False,
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**kwargs,
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):
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"""
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Create an AgentScope model instance
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Args:
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model_name: Model name (e.g., "gpt-4o", "claude-3-opus")
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provider: Provider name (e.g., "OPENAI", "ANTHROPIC")
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api_key: API key (optional, will read from env if not provided)
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stream: Whether to use streaming mode
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**kwargs: Additional model-specific arguments
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Returns:
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AgentScope model instance
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"""
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provider = provider.upper()
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model_class = PROVIDER_MODEL_MAP.get(provider)
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if model_class is None:
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raise ValueError(f"Unsupported provider: {provider}")
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# Get API key from env if not provided
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if api_key is None:
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env_key = PROVIDER_API_KEY_ENV.get(provider)
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if env_key:
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api_key = os.getenv(env_key)
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# Build model kwargs
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model_kwargs = {
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"model_name": model_name,
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"stream": stream,
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**kwargs,
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}
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# Add API key if needed (Ollama doesn't need it)
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if provider != "OLLAMA" and api_key:
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model_kwargs["api_key"] = api_key
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# Handle OpenAI-compatible providers with custom base_url
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if provider in PROVIDER_BASE_URLS:
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base_url = PROVIDER_BASE_URLS[provider]
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model_kwargs["client_args"] = {"base_url": base_url}
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# Handle custom OpenAI base URL
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if provider == "OPENAI":
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base_url = os.getenv("OPENAI_BASE_URL") or os.getenv("OPENAI_API_BASE")
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if base_url:
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model_kwargs["client_args"] = {"base_url": base_url}
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# Handle DashScope base URL (uses different parameter)
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if provider in ("DASHSCOPE", "ALIBABA"):
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base_url = os.getenv("DASHSCOPE_BASE_URL")
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if base_url:
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model_kwargs["base_http_api_url"] = base_url
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# Handle Ollama host
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if provider == "OLLAMA":
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host = os.getenv("OLLAMA_HOST")
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if host:
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model_kwargs["host"] = host
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return model_class(**model_kwargs)
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def get_agent_model(agent_id: str, stream: bool = False):
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"""
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Get model for a specific agent based on environment variables
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Environment variable pattern:
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AGENT_{AGENT_ID}_MODEL_NAME: Model name
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AGENT_{AGENT_ID}_MODEL_PROVIDER: Provider name
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fallback to global MODEL_NAME & MODEL_PROVIDER if agent-specific not given
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Args:
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agent_id: Agent ID (e.g., "sentiment_analyst", "portfolio_manager")
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stream: Whether to use streaming mode
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Returns:
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AgentScope model instance
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"""
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# Normalize agent_id to uppercase for env var lookup
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agent_key = agent_id.upper().replace("-", "_")
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# Try agent-specific config first
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model_name = os.getenv(f"AGENT_{agent_key}_MODEL_NAME")
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provider = os.getenv(f"AGENT_{agent_key}_MODEL_PROVIDER")
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print(f"Using specific model {model_name} for agent {agent_key}")
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# Fall back to global config
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if not model_name:
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model_name = os.getenv("MODEL_NAME", "gpt-4o")
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if not provider:
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provider = os.getenv("MODEL_PROVIDER", "OPENAI")
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return create_model(
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model_name=model_name,
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provider=provider,
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stream=stream,
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)
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def get_agent_formatter(agent_id: str):
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"""
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Get formatter for a specific agent based on environment variables
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Args:
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agent_id: Agent ID (e.g., "sentiment_analyst", "portfolio_manager")
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Returns:
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AgentScope formatter instance
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"""
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# Normalize agent_id to uppercase for env var lookup
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agent_key = agent_id.upper().replace("-", "_")
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# Try agent-specific config first
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provider = os.getenv(f"AGENT_{agent_key}_MODEL_PROVIDER")
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# Fall back to global config
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if not provider:
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provider = os.getenv("MODEL_PROVIDER", "OPENAI")
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provider = provider.upper()
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formatter_class = PROVIDER_FORMATTER_MAP.get(provider, OpenAIChatFormatter)
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return formatter_class()
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def get_agent_model_info(agent_id: str) -> Tuple[str, str]:
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"""
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Get model name and provider for a specific agent
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Args:
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agent_id: Agent ID (e.g., "sentiment_analyst", "portfolio_manager")
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Returns:
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Tuple of (model_name, provider_name)
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"""
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agent_key = agent_id.upper().replace("-", "_")
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model_name = os.getenv(f"AGENT_{agent_key}_MODEL_NAME")
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provider = os.getenv(f"AGENT_{agent_key}_MODEL_PROVIDER")
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if not model_name:
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model_name = os.getenv("MODEL_NAME", "gpt-4o")
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if not provider:
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provider = os.getenv("MODEL_PROVIDER", "OPENAI")
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return model_name, provider.upper()
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