Merge pull request #157 from modelstudioai/feat/bailian-docs-update

chore: update bailian-docs-llm-wiki (2026-11-05)

Author: gujieye

skills/bailian-docs-llm-wiki/llms.txt

@@ -1,7 +1,8 @@
-{"slug":"Kimi-K2","name":"Kimi","description":"Kimi是由月之暗面提供的开源模型，包含k3、k2.7-code、k2.6、k2.5等多模态和大语言模型。","primaryCapability":"TG","capabilities":["TG","VU","Reasoning"],"providers":["moonshot-ai"],"itemCount":4,"items":[{"model":"kimi-k2.5","name":"Kimi-K2.5","contextWindow":262144,"capabilities":["Reasoning","VU","TG"]},{"model":"kimi-k2.6","name":"Kimi-K2.6","contextWindow":262144,"capabilities":["Reasoning","VU","TG"]},{"model":"kimi-k2.7-code","name":"kimi-k2.7-code","contextWindow":262144,"capabilities":["TG","VU","Reasoning"]},{"model":"kimi-k3","name":"Kimi-K3","contextWindow":1000000,"capabilities":["TG","VU","Reasoning"]}],"detailPath":"groups/Kimi-K2.json","maxContextWindow":1000000}
+{"slug":"Kimi-K2","name":"Kimi","description":"Kimi是由月之暗面提供的开源模型，包含k3、k2.7-code、k2.6、k2.5等多模态和大语言模型。","primaryCapability":"Reasoning","capabilities":["Reasoning","VU","TG"],"providers":["moonshot-ai"],"itemCount":5,"items":[{"model":"kimi-k2.5","name":"Kimi-K2.5","contextWindow":262144,"capabilities":["Reasoning","VU","TG"]},{"model":"kimi-k2.6","name":"Kimi-K2.6","contextWindow":262144,"capabilities":["Reasoning","VU","TG"]},{"model":"kimi-k2.7-code","name":"kimi-k2.7-code","contextWindow":262144,"capabilities":["TG","VU","Reasoning"]},{"model":"kimi-k3","name":"Kimi-K3","contextWindow":1000000,"capabilities":["TG","VU","Reasoning"]},{"model":"kimi-k3.1-pro","name":"Kimi-K3.1-Pro","contextWindow":1000000,"capabilities":["Reasoning","VU","TG"]}],"detailPath":"groups/Kimi-K2.json","maxContextWindow":1000000}
 {"slug":"MiniMax-M2.1","name":"MiniMax","description":"MiniMax推出的旗舰级开源大模型，聚焦真实世界复杂任务，包含MiniMax-M2.1、MiniMax-M2.5等开源模型。","primaryCapability":"Reasoning","capabilities":["Reasoning","TG"],"providers":["mini-max"],"itemCount":1,"items":[{"model":"MiniMax-M2.5","name":"MiniMax-M2.5","contextWindow":204800,"capabilities":["Reasoning","TG"]}],"detailPath":"groups/MiniMax-M2.1.json","maxContextWindow":204800}
 {"slug":"MiniMax-speech-market-place","name":"MiniMax-Speech系列语音模型","description":"由MiniMax提供的MiniMax-Speech系列语音模型API服务。","primaryCapability":"TTS","capabilities":["TTS"],"providers":["mini-max"],"itemCount":4,"items":[{"model":"MiniMax/speech-02-hd","name":"speech-02-hd","capabilities":["TTS"]},{"model":"MiniMax/speech-02-turbo","name":"speech-02-turbo","capabilities":["TTS"]},{"model":"MiniMax/speech-2.8-hd","name":"speech-2.8-hd","capabilities":["TTS"]},{"model":"MiniMax/speech-2.8-turbo","name":"speech-2.8-turbo","capabilities":["TTS"]}],"detailPath":"groups/MiniMax-speech-market-place.json"}
 {"slug":"MiniMax-video-market-place","name":"MiniMax视频模型","description":"由MiniMax提供的MiniMax-H系列视频模型API服务。","primaryCapability":"VG","capabilities":["VG"],"providers":["mini-max"],"itemCount":1,"items":[{"model":"MiniMax/MiniMax-H3","name":"MiniMax/MiniMax-H3","capabilities":["VG"]}],"detailPath":"groups/MiniMax-video-market-place.json"}
+{"slug":"antdigital-models-market-place","name":"AntDigital","description":"由蚂蚁数科提供的Ling系列模型的API服务","primaryCapability":"TG","capabilities":["TG","Reasoning"],"providers":["antdigital"],"itemCount":1,"items":[{"model":"antdigital/Ling-3.1-flash","name":"antdigital/Ling-3.1-flash","contextWindow":1048576,"capabilities":["TG","Reasoning"]}],"detailPath":"groups/antdigital-models-market-place.json","maxContextWindow":1048576}
 {"slug":"cosyvoice","name":"CosyVoice大模型","description":"基于新一代生成式语音大模型，CosyVoice将文本理解和语音生成技术深度融合，能够精准解析并诠释各种文本内容，将其转化为如同真人发声般的自然语音，带来高度拟人化的自然语音合成体验。","primaryCapability":"TTS","capabilities":["TTS"],"providers":["qwen","qwen-domain-model"],"itemCount":5,"items":[{"model":"cosyvoice-v2","name":"语音生成cosyvoice-v2大模型","capabilities":["TTS"]},{"model":"cosyvoice-v3-flash","name":"语音生成CosyVoice-v3-flash大模型","capabilities":["TTS"]},{"model":"cosyvoice-v3-plus","name":"语音生成CosyVoice-v3-plus大模型","capabilities":["TTS"]},{"model":"cosyvoice-v3.5-flash","name":"语音生成CosyVoice-v3.5-flash大模型","capabilities":["TTS"]},{"model":"cosyvoice-v3.5-plus","name":"语音生成CosyVoice-v3.5-plus大模型","capabilities":["TTS"]}],"detailPath":"groups/cosyvoice.json"}
 {"slug":"decision-model","name":"Decision Model","description":"面向高频业务判断的结构化决策模型，可根据文本或业务状态并行完成分类、是非判断与评分，并返回概率分布和置信度，适用于工单分流、内容审核、智能体路由与结果校验等场景。","primaryCapability":"TG","capabilities":["TG"],"providers":["qwen-domain-model"],"itemCount":1,"items":[{"model":"decision-model-preview","name":"决策模型（预览版）","contextWindow":65536,"capabilities":["TG"]}],"detailPath":"groups/decision-model.json","maxContextWindow":65536}
 {"slug":"deepseek","name":"DeepSeek","description":"DeepSeek 系列模型覆盖通用对话、复杂推理与多模态理解等场景，提供 Flash、Pro 等不同规格，可根据效果、响应速度和成本灵活选择。","primaryCapability":"TG","capabilities":["TG","Reasoning","VU"],"providers":["deepseek"],"itemCount":6,"items":[{"model":"deepseek-r1-distill-qwen-1.5b","name":"DeepSeek-R1-Distill-Qwen-1.5B","contextWindow":32768,"capabilities":["TG"]},{"model":"deepseek-v4-flash-0731","name":"DeepSeek-V4-Flash-0731","contextWindow":1000000,"capabilities":["Reasoning","TG"]},{"model":"deepseek-v4-pro","name":"DeepSeek-V4-Pro","contextWindow":1000000,"capabilities":["Reasoning","TG"]},{"model":"deepseek-v4-pro-0813","name":"DeepSeek-V4-Pro-0813","contextWindow":1000000,"capabilities":["TG","Reasoning"]},{"model":"deepseek-v4.1-flash","name":"DeepSeek-V4.1-Flash","contextWindow":1000000,"capabilities":["TG","Reasoning","VU"]},{"model":"deepseek-v4.1-flash-1017","name":"DeepSeek-V4.1-Flash-1017","contextWindow":1000000,"capabilities":["TG","Reasoning","VU"]}],"detailPath":"groups/deepseek.json","maxContextWindow":1000000}

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

@@ -2,6 +2,129 @@
   "name": "Kimi",
   "description": "Kimi是由月之暗面提供的开源模型，包含k3、k2.7-code、k2.6、k2.5等多模态和大语言模型。",
   "items": [
+    {
+      "inferenceMetadata": {
+        "response_modality": [
+          "Text"
+        ],
+        "request_modality": [
+          "Text",
+          "Image"
+        ]
+      },
+      "builtInToolMultiPrices": [
+        {
+          "supportedApi": "Anthropic API",
+          "name": "web_search",
+          "docUrl": "https://docs.bailian.console.aliyun.com/zh/model-studio/web-search",
+          "type": "web_search_anthropic",
+          "prices": [
+            {
+              "priceUnit": "千次调用",
+              "price": "4",
+              "currency": "CNY"
+            }
+          ]
+        },
+        {
+          "supportedApi": "Anthropic API",
+          "name": "web_fetch",
+          "docUrl": "https://docs.bailian.console.aliyun.com/zh/model-studio/web-extractor",
+          "type": "web_fetch",
+          "prices": [
+            {
+              "priceUnit": "",
+              "price": "0",
+              "currency": "CNY"
+            }
+          ]
+        }
+      ],
+      "description": "Kimi-K3.1-Pro 是月之暗面（Moonshot AI）K3.1 系列的首款模型，也是迄今能力最强的 3T 级开放权重模型，为 Kimi K3 的大规模后训练版本，后训练算力大幅增加。支持 100 万 token 上下文窗口，原生具备视觉理解能力（文本、图片输入，文本输出），并通过跨数百个领域的大规模联合强化学习，在代码、3D 创作、金融研究与长程 Agent 任务上显著提升：Terminal-Bench 4.0 得分 65.7%；金融文档分析 OfficeQA Pro v2 取得 64.4 的当前最佳成绩；声明级幻觉率较 K3 从 23.4% 降至 8.3%，综合智能水平已接近全球领先的闭源模型。",
+      "features": [
+        "cache",
+        "function-calling",
+        "model-experience",
+        "structured-outputs",
+        "web-search"
+      ],
+      "provider": "moonshot-ai",
+      "model": "kimi-k3.1-pro",
+      "prices": [
+        {
+          "priceUnit": "每百万tokens",
+          "price": "13",
+          "timeBand": "standard",
+          "ntmAmountType": "input_token",
+          "type": "input_token",
+          "priceName": "输入"
+        },
+        {
+          "priceUnit": "每百万tokens",
+          "price": "68",
+          "timeBand": "standard",
+          "ntmAmountType": "output_token",
+          "type": "output_token",
+          "priceName": "输出"
+        },
+        {
+          "priceUnit": "每百万tokens",
+          "price": "1.3",
+          "timeBand": "standard",
+          "ntmAmountType": "input_token_cache",
+          "type": "input_token_cache",
+          "priceName": "输入（缓存命中）"
+        }
+      ],
+      "qpmInfo": {
+        "model-default-actual": {
+          "usage_limit": 120000,
+          "usage_limit_field": "total_tokens",
+          "usage_limit_period": 6,
+          "type": "model-default"
+        },
+        "model-default": {
+          "usage_limit": 120000,
+          "usage_limit_field": "total_tokens",
+          "usage_limit_period": 6,
+          "type": "model-default"
+        }
+      },
+      "priceTimeBands": [
+        "standard"
+      ],
+      "capabilities": [
+        "Reasoning",
+        "VU",
+        "TG"
+      ],
+      "modelAlias": "",
+      "versionTag": "MAJOR",
+      "maxOutputTokens": 1048576,
+      "latestOnlineAt": "2026-11-04T16:30:00.000+00:00",
+      "contextWindow": 1000000,
+      "maxInputTokens": 1048576,
+      "inferenceProvider": "aliyun-bailian",
+      "name": "Kimi-K3.1-Pro",
+      "docUrl": "https://docs.bailian.console.aliyun.com/zh/model-studio/kimi-api",
+      "category": "Third-party",
+      "samples": {
+        "openai": {
+          "default": {
+            "curl": "curl --location 'https://[workspace-id].cn-beijing.maas.aliyuncs.com/compatible-mode/v1/chat/completions' \\\n--header \"Authorization: Bearer $DASHSCOPE_API_KEY\" \\\n--header 'Content-Type: application/json' \\\n--data '{\n  \"model\": \"kimi-k3.1-pro\",\n  \"messages\": [\n  {\n    \"role\": \"user\",\n    \"content\": [\n      {\"type\": \"image_url\", \"image_url\": {\"url\": \"https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241108/ctdzex/biaozhun.jpg\"}},\n      {\"type\": \"text\", \"text\": \"请仅输出图像中的文本内容。\"}\n    ]\n  }]\n}'",
+            "python": "import os\nfrom openai import OpenAI\n\nclient = OpenAI(\n    api_key=os.getenv(\"DASHSCOPE_API_KEY\"),\n    base_url=\"https://[workspace-id].cn-beijing.maas.aliyuncs.com/compatible-mode/v1\",\n)\n\ncompletion = client.chat.completions.create(\n    model=\"kimi-k3.1-pro\",\n    messages=[\n        {\n            \"role\": \"user\",\n            \"content\": [\n                {\n                    \"type\": \"image_url\",\n                    \"image_url\": {\n                        \"url\": \"https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241108/ctdzex/biaozhun.jpg\"\n                    },\n                },\n                {\"type\": \"text\", \"text\": \"请仅输出图像中的文本内容。\"},\n            ],\n        },\n    ],\n)\nprint(completion.choices[0].message.content)",
+            "nodejs": "import OpenAI from \"openai\";\n\nconst openai = new OpenAI({\n  // 若没有配置环境变量，请用百炼API Key将下行替换为：apiKey: \"sk-xxx\"\n  apiKey: process.env.DASHSCOPE_API_KEY,\n  baseURL: \"https://[workspace-id].cn-beijing.maas.aliyuncs.com/compatible-mode/v1\"\n});\n\nasync function main() {\n  const response = await openai.chat.completions.create({\n    model: \"kimi-k3.1-pro\",\n    messages: [\n      {\n        role: \"user\",\n        content: [{\n            type: \"image_url\",\n            image_url: {\n              \"url\": \"https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241108/ctdzex/biaozhun.jpg\"\n            }\n          },\n          {\n            type: \"text\",\n            text: \"请仅输出图像中的文本内容。\"\n          }\n        ]\n      }\n    ]\n  });\n  console.log(response.choices[0].message.content);\n}\nmain()"
+          }
+        },
+        "dashscope": {
+          "default": {
+            "curl": "curl -X POST https://[workspace-id].cn-beijing.maas.aliyuncs.com/api/v1/services/aigc/multimodal-generation/generation \\\n-H \"Authorization: Bearer $DASHSCOPE_API_KEY\" \\\n-H 'Content-Type: application/json' \\\n-d '{\n    \"model\": \"kimi-k3.1-pro\",\n    \"input\":{\n        \"messages\":[\n            {\n                \"role\": \"user\",\n                \"content\": [\n                    {\"image\": \"https://dashscope.oss-cn-beijing.aliyuncs.com/images/dog_and_girl.jpeg\"},\n                    {\"text\": \"图中描绘的是什么景象？\"}\n                ]\n            },\n            {\n                \"role\": \"assistant\",\n                \"content\": [\n                    {\"text\": \"图中是一名女子和一只拉布拉多犬在沙滩上玩耍。\"}\n                ]\n            },\n            {\n                \"role\": \"user\",\n                \"content\": [\n                    {\"text\": \"写一首七言绝句描述这个场景\"}\n                ]\n            }\n        ]\n    }\n}'",
+            "python": "import os\nimport dashscope\ndashscope.base_http_api_url = 'https://[workspace-id].cn-beijing.maas.aliyuncs.com/api/v1'\nmessages = [\n{\n    \"role\": \"user\",\n    \"content\": [\n    {\"image\": \"https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241108/ctdzex/biaozhun.jpg\"},\n    {\"text\": \"请仅输出图像中的文本内容。\"}]\n}]\nresponse = dashscope.MultiModalConversation.call(\n    #若没有配置环境变量， 请用百炼API Key将下行替换为： api_key =\"sk-xxx\"\n    api_key = os.getenv('DASHSCOPE_API_KEY'),\n    model = 'kimi-k3.1-pro',\n    messages = messages\n)\nprint(response.output.choices[0].message.content[0][\"text\"])",
+            "java": "import java.util.ArrayList;\nimport java.util.Arrays;\nimport java.util.Collections;\nimport java.util.List;\nimport com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversation;\nimport com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversationParam;\nimport com.alibaba.dashscope.aigc.multimodalconversation.MultiModalConversationResult;\nimport com.alibaba.dashscope.common.MultiModalMessage;\nimport com.alibaba.dashscope.common.Role;\nimport com.alibaba.dashscope.exception.ApiException;\nimport com.alibaba.dashscope.exception.NoApiKeyException;\nimport com.alibaba.dashscope.exception.UploadFileException;\nimport com.alibaba.dashscope.utils.Constants;\npublic class Main {\n    static {\n        Constants.baseHttpApiUrl=\"https://[workspace-id].cn-beijing.maas.aliyuncs.com/api/v1\";\n    }\n    private static final String modelName = \"kimi-k3.1-pro\";  \n    public static void MultiRoundConversationCall() throws ApiException, NoApiKeyException, UploadFileException {\n        MultiModalConversation conv = new MultiModalConversation();\n        MultiModalMessage systemMessage = MultiModalMessage.builder().role(Role.SYSTEM.getValue())\n                .content(Arrays.asList(Collections.singletonMap(\"text\", \"You are a helpful assistant.\"))).build();\n        MultiModalMessage userMessage = MultiModalMessage.builder().role(Role.USER.getValue())\n                .content(Arrays.asList(Collections.singletonMap(\"image\", \"https://dashscope.oss-cn-beijing.aliyuncs.com/images/dog_and_girl.jpeg\"),\n                        Collections.singletonMap(\"text\", \"图中描绘的是什么景象？\"))).build();\n        List<MultiModalMessage> messages = new ArrayList<>();\n        messages.add(systemMessage);\n        messages.add(userMessage);\n        MultiModalConversationParam param = MultiModalConversationParam.builder()\n                // 新加坡和北京地域的API Key不同。获取API Key：https://www.alibabacloud.com/help/zh/model-studio/get-api-key\n                // 若没有配置环境变量，请用百炼API Key将下行替换为：.apiKey(\"sk-xxx\")\n                .apiKey(System.getenv(\"DASHSCOPE_API_KEY\"))                \n                .model(modelName)\n                .messages(messages)\n                .build();\n        MultiModalConversationResult result = conv.call(param);\n        System.out.println(\"第一轮输出： \"+result.getOutput().getChoices().get(0).getMessage().getContent().get(0).get(\"text\"));        // add the result to conversation\n        messages.add(result.getOutput().getChoices().get(0).getMessage());\n        MultiModalMessage msg = MultiModalMessage.builder().role(Role.USER.getValue())\n                .content(Arrays.asList(Collections.singletonMap(\"text\", \"做一首诗描述这个场景\"))).build();\n        messages.add(msg);\n        param.setMessages((List)messages);\n        result = conv.call(param);\n        System.out.println(\"第二轮输出： \"+result.getOutput().getChoices().get(0).getMessage().getContent().get(0).get(\"text\"));    }\n\n    public static void main(String[] args) {\n        try {\n            MultiRoundConversationCall();\n        } catch (ApiException | NoApiKeyException | UploadFileException e) {\n            System.out.println(e.getMessage());\n        }\n        System.exit(0);\n    }\n}"
+          }
+        }
+      }
+    },
     {
       "inferenceMetadata": {
         "response_modality": [