qzl
80cbb3512f
- 添加 litellm 依赖，统一 LLM 调用层 - 新增 litellm_client.py 支持多厂商 - 更新 llm_catalog.yaml 添加 litellm_model 映射 - 删除旧的 cost_tracker.py (litellm 内置 cost 追踪) - 删除未使用的 multimodal.py 和 storage_adapter.py - 删除空文件 crewai/__init__.py, tools/__init__.py - 更新测试以适配新代码
131 lines
4.0 KiB
Python
131 lines
4.0 KiB
Python
from __future__ import annotations
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import os
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from dataclasses import dataclass
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from decimal import Decimal
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from pathlib import Path
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from typing import Any
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import yaml
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@dataclass(frozen=True)
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class LLMConfig:
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model_code: str
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factory_name: str
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litellm_model: str
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request_url: str
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@dataclass(frozen=True)
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class LLMResponse:
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content: str
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usage: dict[str, Any]
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class LiteLLMClient:
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def __init__(self, config: LLMConfig, api_key: str | None = None) -> None:
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self._config = config
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self._api_key = api_key or self._get_api_key(config.factory_name)
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@staticmethod
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def _get_api_key(factory_name: str) -> str:
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key_map = {
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"dashscope": "DASHSCOPE_API_KEY",
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"minimax": "MINIMAX_API_KEY",
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"moonshot": "MOONSHOT_API_KEY",
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"deepseek": "DEEPSEEK_API_KEY",
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"volcengine-ark": "ARK_API_KEY",
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"z-ai": "ZAI_API_KEY",
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}
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env_key = key_map.get(factory_name)
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if not env_key:
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raise ValueError(f"No API key mapping for factory: {factory_name}")
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key = os.environ.get(env_key)
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if not key:
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raise ValueError(f"Environment variable {env_key} is not set")
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return key
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@staticmethod
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def load_config(
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model_code: str,
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static_root: Path | None = None,
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) -> LLMConfig:
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root = static_root or (
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Path(__file__).resolve().parents[3] / "config" / "static" / "database"
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)
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yaml_path = root / "llm_catalog.yaml"
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with yaml_path.open("r", encoding="utf-8") as f:
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data = yaml.safe_load(f)
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factories = {f["name"]: f for f in data.get("factories", [])}
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llms = data.get("llms", [])
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for llm in llms:
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if llm.get("model_code") == model_code:
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factory_name = llm["factory_name"]
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factory = factories.get(factory_name)
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if not factory:
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raise ValueError(f"Factory not found: {factory_name}")
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return LLMConfig(
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model_code=model_code,
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factory_name=factory_name,
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litellm_model=llm.get("litellm_model", model_code),
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request_url=factory["request_url"],
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)
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raise ValueError(f"Model not found: {model_code}")
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def chat(
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self,
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messages: list[dict[str, str]],
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*,
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temperature: float = 0.7,
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max_tokens: int | None = None,
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) -> LLMResponse:
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import litellm
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response = litellm.completion( # type: ignore[attr-defined]
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model=self._config.litellm_model,
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messages=messages,
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temperature=temperature,
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max_tokens=max_tokens,
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api_base=self._config.request_url,
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api_key=self._api_key,
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)
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content = response.choices[0].message.content or "" # type: ignore[attr-defined]
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usage = response.usage.model_dump() if response.usage else {} # type: ignore[attr-defined]
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return LLMResponse(content=content, usage=usage)
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async def achat(
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self,
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messages: list[dict[str, str]],
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*,
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temperature: float = 0.7,
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max_tokens: int | None = None,
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) -> LLMResponse:
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import litellm
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response = await litellm.acompletion( # type: ignore[attr-defined]
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model=self._config.litellm_model,
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messages=messages,
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temperature=temperature,
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max_tokens=max_tokens,
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api_base=self._config.request_url,
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api_key=self._api_key,
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)
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content = response.choices[0].message.content or "" # type: ignore[attr-defined]
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usage = response.usage.model_dump() if response.usage else {} # type: ignore[attr-defined]
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return LLMResponse(content=content, usage=usage)
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def get_model_cost(usage: dict[str, Any]) -> Decimal:
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cost = usage.get("cost")
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if cost is None:
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return Decimal("0")
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return Decimal(str(cost))
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