c62156af53
B1: 项目脚手架 + 数据模型 + 租户管理 - Task 1.1: FastAPI 项目脚手架、SQLite + async SQLAlchemy - Task 1.2: 7 个数据模型 (Tenant, TenantConfig, DigitalEmployee, Conversation, Message, KnowledgeBase, Document) - Task 1.3: 租户 CRUD API + LLM 配置（含 API Key AES 加密） B2: 数字员工配置 + LLM Provider 抽象层 - Task 2.1: 数字员工 CRUD API（关联知识库） - Task 2.2: BaseLLMProvider 抽象接口 + OpenAI/Qwen Provider - Task 2.3: Provider 动态实例化 + test-provider 端点 验证: 26 个测试全部通过 Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
35 lines
844 B
Python
35 lines
844 B
Python
"""LLM Provider 基础抽象层"""
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from abc import ABC, abstractmethod
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from dataclasses import dataclass
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@dataclass
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class LLMMessage:
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role: str # "system", "user", "assistant"
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content: str
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@dataclass
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class LLMResponse:
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content: str
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model: str
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usage: dict # {"total_tokens": int, "prompt_tokens": int, "completion_tokens": int}
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class BaseLLMProvider(ABC):
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"""LLM Provider 抽象基类"""
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@abstractmethod
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async def chat(self, messages: list[LLMMessage]) -> LLMResponse:
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"""非流式对话"""
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pass
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@abstractmethod
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async def chat_stream(self, messages: list[LLMMessage]) -> str:
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"""流式对话，返回 token 异步生成器"""
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pass
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@abstractmethod
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async def embed(self, texts: list[str]) -> list[list[float]]:
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"""生成嵌入向量"""
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pass |