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chore: update bailian-docs-llm-wiki (2026-07-17)
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‎skills/bailian-docs-llm-wiki/SKILL.md‎

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| **按家族筛选**：按 primaryCapability / providers / itemCount / maxContextWindow 找家族 | `models/families.jsonl`（一行一家族，含 items[] 摘要） |
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| 模型家族总览 / 按能力分桶浏览 | `models/index.md` |
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| 主题页 / API 文档（按功能领域查找） | `wiki/index.md`（完整索引入口） |
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| OpenAI 兼容接口 | `wiki/concepts/openai-compatible-interface.md` |
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| API Key 鉴权 | `wiki/concepts/api-key.md` |
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| 函数调用（Function Calling） | `wiki/concepts/function-calling.md` |
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| 检索增强生成（RAG） | `wiki/concepts/rag.md` |
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| OpenAI 兼容接口 | `wiki/concepts/openai-compatible-interface.md` |
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| API Key 鉴权 | `wiki/concepts/api-key.md` |
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| 异步调用与任务轮询 | `wiki/concepts/async-invocation.md` |
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| Token 与计费 | `wiki/concepts/token-and-billing.md` |
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| 流式输出 | `wiki/concepts/streaming-output.md` |
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| 流式输出 | `wiki/concepts/streaming.md` |
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| Token 与计费 | `wiki/concepts/token-billing.md` |
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| 业务空间（Workspace） | `wiki/concepts/workspace.md` |
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| 模型调优与部署 | `wiki/concepts/fine-tuning-and-deployment.md` |
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| MCP 与工具扩展 | `wiki/concepts/mcp-and-tools.md` |
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| 模型微调、压缩与部署对比 | `wiki/comparisons/fine-tuning-vs-compression-vs-deployment.md` |
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| 模型评估与模型监控对比 | `wiki/comparisons/model-evaluation-vs-monitoring.md` |
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| DashScope SDK 与网关 | `wiki/concepts/dashscope-sdk.md` |
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| 多模态（文本/图像/音频/视频） | `wiki/concepts/multimodal.md` |
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| 图像、视频与 3D 生成对比 | `wiki/comparisons/image-vs-video-vs-3d-generation.md` |
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| 应用评估与应用监控对比 | `wiki/comparisons/app-evaluation-vs-monitoring.md` |
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| 知识库与记忆库对比 | `wiki/comparisons/knowledge-base-vs-memory-library.md` |
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| 托管智能体：指南与 API 对比 | `wiki/comparisons/managed-agents-guide-vs-api.md` |
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| 模型微调、压缩与高速推理对比 | `wiki/comparisons/model-optimization-approaches.md` |
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| 应用评估、监控与权限管理对比 | `wiki/comparisons/application-lifecycle-management.md` |
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| 插件、MCP 与工具框架对比 | `wiki/comparisons/agent-extensibility.md` |
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| 长期记忆与知识库对比 | `wiki/comparisons/memory-vs-knowledge-base.md` |
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| 托管 Agent 与自建应用调用对比 | `wiki/comparisons/managed-vs-custom-agents.md` |
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> 实际文件名以 `wiki/index.md` 为准；上表若有出入应回到索引页查找。
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‎skills/bailian-docs-llm-wiki/llms.txt‎

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‎skills/bailian-docs-llm-wiki/models/families.jsonl‎

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{"slug":"qwen-coder-turbo","name":"Qwen-Coder-Turbo","description":"Qwen-Coder-Turbo模型是专门用于编程和代码生成的语言模型，推理速度快，成本低。","primaryCapability":"TG","capabilities":["TG"],"providers":["qwen-domain-model"],"itemCount":1,"items":[{"model":"qwen-coder-turbo","name":"Qwen-Coder-Turbo","contextWindow":131072,"capabilities":["TG"]}],"detailPath":"groups/qwen-coder-turbo.json","maxContextWindow":131072}
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{"slug":"qwen-deep-research","name":"qwen-deep-research","description":"千问深入研究是一款面向复杂研究任务的高级智能体系统，具备多轮推理与全局规划能力，能够运用互联网搜索等多种工具，对任务进行精细化拆解，开展推理与分析，最终为用户生成可溯源、逻辑严谨的研究型报告。","primaryCapability":"TG","capabilities":["TG"],"providers":["qwen-domain-model"],"itemCount":1,"items":[{"model":"qwen-deep-research","name":"qwen-deep-research","contextWindow":1000000,"capabilities":["TG"]}],"detailPath":"groups/qwen-deep-research.json","maxContextWindow":1000000}
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{"slug":"qwen-doc-turbo","name":"Qwen-Doc-Turbo","description":"快速对文档进行精准信息抽取，打标分类，内容审核及摘要总结。","primaryCapability":"TG","capabilities":["TG"],"providers":["qwen-domain-model"],"itemCount":1,"items":[{"model":"qwen-doc-turbo","name":"Qwen-Doc-Turbo","contextWindow":262144,"capabilities":["TG"]}],"detailPath":"groups/qwen-doc-turbo.json","maxContextWindow":262144}
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{"slug":"qwen-embedding","name":"Qwen-Embedding","description":"基于Qwen模型基座训练的多语言文本统一向量模型，文本检索、聚类、分类性能大幅提升，多语言支持，适用于向量检索、向量化等等场景，可搭配检索增强、文档处理场景使用，支持64~2048维用户自定义向量维度。","primaryCapability":"TR","capabilities":["TR"],"providers":["qwen-domain-model"],"itemCount":6,"items":[{"model":"text-embedding-async-v1","name":"通用文本向量-async-v1","capabilities":["TR"]},{"model":"text-embedding-async-v2","name":"通用文本向量-async-v2","capabilities":["TR"]},{"model":"text-embedding-v1","name":"通用文本向量-v1","capabilities":["TR"]},{"model":"text-embedding-v2","name":"通用文本向量-v2","capabilities":["TR"]},{"model":"text-embedding-v3","name":"通用文本向量-v3","capabilities":["TR"]},{"model":"text-embedding-v4","name":"通用文本向量-v4","capabilities":["TR"]}],"detailPath":"groups/qwen-embedding.json"}
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{"slug":"qwen-embedding","name":"Qwen-Embedding","description":"基于Qwen模型基座训练的多语言文本统一向量模型，文本检索、聚类、分类性能大幅提升，多语言支持，适用于向量检索、向量化等等场景，可搭配检索增强、文档处理场景使用，支持64~2048维用户自定义向量维度。","primaryCapability":"TR","capabilities":["TR"],"providers":["qwen","qwen-domain-model"],"itemCount":7,"items":[{"model":"qwen3.7-text-embedding","name":"Qwen3.7-Text-Embedding","contextWindow":131072,"capabilities":["TR"]},{"model":"text-embedding-async-v1","name":"通用文本向量-async-v1","capabilities":["TR"]},{"model":"text-embedding-async-v2","name":"通用文本向量-async-v2","capabilities":["TR"]},{"model":"text-embedding-v1","name":"通用文本向量-v1","capabilities":["TR"]},{"model":"text-embedding-v2","name":"通用文本向量-v2","capabilities":["TR"]},{"model":"text-embedding-v3","name":"通用文本向量-v3","capabilities":["TR"]},{"model":"text-embedding-v4","name":"通用文本向量-v4","capabilities":["TR"]}],"detailPath":"groups/qwen-embedding.json","maxContextWindow":131072}
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{"slug":"qwen-flash-character","name":"Qwen-Flash-Character","description":"千问系列多语言角色扮演模型，本模型是动态更新版本，模型更新会提前通知，适合拟人化的角色扮演，同时优化了限定人设指令遵循、话题推进、倾听共情等能力，支持个性化角色的深度还原。","primaryCapability":"TG","capabilities":["TG"],"providers":["qwen"],"itemCount":1,"items":[{"model":"qwen-flash-character","name":"Qwen-Flash-Character","contextWindow":8192,"capabilities":["TG"]}],"detailPath":"groups/qwen-flash-character.json","maxContextWindow":8192}
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{"slug":"qwen-flash","name":"Qwen-Flash","description":"Qwen3系列Flash模型，实现思考模式和非思考模式的有效融合，可在对话中切换模式。复杂推理类任务性能优秀，指令遵循、文本理解等能力显著提高。支持1M上下文长度，按照上下文长度进行阶梯计费。","primaryCapability":"Reasoning","capabilities":["Reasoning","TG"],"providers":["qwen"],"itemCount":1,"items":[{"model":"qwen-flash","name":"Qwen-Flash","contextWindow":1000000,"capabilities":["Reasoning","TG"]}],"detailPath":"groups/qwen-flash.json","maxContextWindow":1000000}
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{"slug":"qwen-image-2.0-pro","name":"Qwen-Image-2.0-Pro","description":"Qwen-Image-2.0系列满血版模型，实现了图片生成和图片编辑的融合；具备更专业的文字渲染1k token指令支持能力、更细腻的真实质感，细腻刻画写实场景、更强的语义遵循能力。满血版具备2.0系列最强的文字渲染能力和真实质感。","primaryCapability":"IG","capabilities":["IG"],"providers":["qwen"],"itemCount":1,"items":[{"model":"qwen-image-2.0-pro","name":"Qwen-Image-2.0-Pro","capabilities":["IG"]}],"detailPath":"groups/qwen-image-2.0-pro.json"}

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