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* ✨ feat(llm): 实现LLM服务模块,支持多提供商统一接口和高级功能 * 🎨 Ruff * ✨ Config配置类支持BaseModel存储 * 🎨 代码格式化 * 🎨 代码格式化 * 🎨 格式化代码 * ✨ feat(llm): 添加 AI 对话历史管理 * ✨ feat(llmConfig): 引入 LLM 配置模型及管理功能 * 🎨 Ruff --------- Co-authored-by: fccckaug <xxxmio123123@gmail.com> Co-authored-by: HibiKier <45528451+HibiKier@users.noreply.github.com> Co-authored-by: HibiKier <775757368@qq.com> Co-authored-by: fccckaug <xxxmcsmiomio3@gmail.com> Co-authored-by: webjoin111 <455457521@qq.com>
97 lines
1.9 KiB
Python
97 lines
1.9 KiB
Python
"""
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LLM 服务模块 - 公共 API 入口
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提供统一的 AI 服务调用接口、核心类型定义和模型管理功能。
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"""
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from .api import (
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AI,
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AIConfig,
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TaskType,
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analyze,
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analyze_multimodal,
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analyze_with_images,
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chat,
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code,
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embed,
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search,
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search_multimodal,
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)
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from .config import (
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CommonOverrides,
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LLMGenerationConfig,
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register_llm_configs,
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)
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register_llm_configs()
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from .api import ModelName
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from .manager import (
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clear_model_cache,
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get_cache_stats,
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get_global_default_model_name,
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get_model_instance,
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list_available_models,
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list_embedding_models,
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list_model_identifiers,
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set_global_default_model_name,
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)
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from .types import (
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EmbeddingTaskType,
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LLMContentPart,
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LLMErrorCode,
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LLMException,
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LLMMessage,
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LLMResponse,
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LLMTool,
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ModelDetail,
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ModelInfo,
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ModelProvider,
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ResponseFormat,
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ToolCategory,
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ToolMetadata,
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UsageInfo,
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)
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from .utils import create_multimodal_message, unimsg_to_llm_parts
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__all__ = [
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"AI",
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"AIConfig",
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"CommonOverrides",
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"EmbeddingTaskType",
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"LLMContentPart",
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"LLMErrorCode",
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"LLMException",
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"LLMGenerationConfig",
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"LLMMessage",
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"LLMResponse",
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"LLMTool",
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"ModelDetail",
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"ModelInfo",
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"ModelName",
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"ModelProvider",
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"ResponseFormat",
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"TaskType",
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"ToolCategory",
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"ToolMetadata",
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"UsageInfo",
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"analyze",
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"analyze_multimodal",
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"analyze_with_images",
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"chat",
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"clear_model_cache",
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"code",
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"create_multimodal_message",
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"embed",
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"get_cache_stats",
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"get_global_default_model_name",
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"get_model_instance",
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"list_available_models",
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"list_embedding_models",
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"list_model_identifiers",
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"register_llm_configs",
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"search",
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"search_multimodal",
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"set_global_default_model_name",
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"unimsg_to_llm_parts",
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]
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