feat(importers): add official pricing importers for baichuan lingyiwanwu sensenova and xfyun
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scripts/testdata/baichuan_pricing_sample.txt
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scripts/testdata/baichuan_pricing_sample.txt
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价格说明
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计费模式
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按照实际使用的数据量（千tokens）收费。
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通用大模型
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模型调用 Baichuan-M3-Plus 32k 00:00 ~ 24:00 输入：0.005元/千tokens
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输出：0.009元/千tokens 包括对话全流程节点产生的Token总数
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模型调用 Baichuan-M3 32k 00:00 ~ 24:00 输入：0.01元/千tokens
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输出：0.03元/千tokens
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模型调用 Baichuan-M2-Plus 32k 00:00 ~ 24:00 输入：0.01元/千tokens
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输出：0.03元/千tokens 包括对话全流程节点产生的Token总数
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模型调用 Baichuan-M2 32k 00:00 ~ 24:00 输入：0.002元/千tokens
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输出：0.02元/千tokens
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模型调用 Baichuan4-Turbo 32k 00:00 ~ 24:00 0.015元/千tokens 包含输入和输出
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模型调用 Baichuan4-Air 32k 00:00 ~ 24:00 0.00098元/千tokens 包含输入和输出
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模型调用 Baichuan4 32k 00:00 ~ 24:00 0.1元/千tokens 包含输入和输出
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模型调用 Baichuan3-Turbo 32k 00:00 ~ 24:00 0.012元/千tokens 包含输入和输出
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模型调用 Baichuan3-Turbo-128k 128k 00:00 ~ 24:00 0.024元/千tokens 包含输入和输出
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模型调用 Baichuan2-Turbo 32k 00:00 ~ 24:00 0.008元/千tokens 包含输入和输出
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模型调用 Baichuan2-53B 32k 00:00 ~ 8:00 0.01元/千tokens 包含输入和输出
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8:00 ~ 24:00 0.02元/千tokens
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搜索增强服务 - 00:00 ~ 24:00 0.03元/次 开启 web_search 后，接口自动判断调用搜索增强服务的次数
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医疗搜索 - 00:00 ~ 24:00 0.03元/次 调用Baichuan-M2-Plus对话会自动触发医疗搜索
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知识库
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模型调用 Baichuan-Text-Embedding 00:00 ~ 24:00 0.0005元/千tokens
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scripts/testdata/lingyiwanwu_pricing_sample.txt
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scripts/testdata/lingyiwanwu_pricing_sample.txt
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模型与计费","children":"模型与计费"}],"\n",["$","p",null,{"children":"零一万物 API 开放平台提供一系列具有不同功能和定价的 Yi 系列大模型。"}],"\n",["$","table",null,{"children":[["$","thead",null,{"children":["$","tr",null,{"children":[["$","th",null,{"children":"模型"}],["$","th",null,{"children":"上下文长度"}],["$","th",null,{"children":"特性"}],["$","th",null,{"children":"场景"}],["$","th",null,{"children":"价格/1M token"}]]}]}],["$","tbody",null,{"children":[["$","tr",null,{"children":[["$","td",null,{"children":"yi-lightning"}],["$","td",null,{"children":"16K"}],["$","td",null,{"children":"最新高性能模型，保证高质量输出同时，推理速度大幅提升。"}],["$","td",null,{"children":"适用于实时交互，高复杂推理场景。"}],["$","td",null,{"children":"¥0.99"}]]}],["$","tr",null,{"children":[["$","td",null,{"children":"yi-vision-v2"}],["$","td",null,{"children":"16K"}],["$","td",null,{"children":"复杂视觉任务模型，提供基于多张图片的高性能理解、分析能力。"}],["$","td",null,{"children":"适合图片问答、OCR、视觉推理。"}],["$","td",null,{"children":"¥6"}]]}]]}]]}],"\n",["$","p",null,{"children":["$","strong",null,{"children":"关于计费"}]}]
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scripts/testdata/sensenova_pricing_sample.txt
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scripts/testdata/sensenova_pricing_sample.txt
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<section id="model-overview" class="scroll-mt-doc-anchor pt-10">
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<div class="flex h-full flex-col rounded-2xl border border-slate-200/95 bg-white p-5 shadow-[0_1px_3px_rgba(15,23,42,0.06)]">
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<div class="flex flex-wrap items-start justify-between gap-2 gap-y-2"><h4 class="text-lg font-semibold tracking-tight text-slate-900">SenseNova 6.7 Flash-Lite</h4></div>
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<div class="mt-3 flex min-h-0 flex-1 flex-col"><p class="text-[15px] leading-relaxed text-slate-600">面向真实工作流的轻量多模态智能体模型，支持文本对话与图像输入理解</p><div class="mt-4 rounded-lg bg-slate-50/80 px-3 py-2.5"><p class="text-[11px] font-semibold uppercase tracking-[0.12em] text-slate-500">调用次数限制</p><p class="mt-1 text-[14px] font-medium text-slate-800">每5小时1500次</p></div></div>
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<div class="mt-[12px] flex items-start justify-between gap-3 rounded-xl bg-slate-100 px-3.5 py-2.5"><div class="min-w-0 flex-1"><p class="text-[10px] font-semibold uppercase tracking-[0.14em] text-slate-500">MODEL ID</p><code class="mt-1 block break-all font-mono text-[14px] font-semibold text-indigo-950">sensenova-6.7-flash-lite</code></div></div>
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</div>
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<div class="flex h-full flex-col rounded-2xl border border-slate-200/95 bg-white p-5 shadow-[0_1px_3px_rgba(15,23,42,0.06)]">
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<div class="flex flex-wrap items-start justify-between gap-2 gap-y-2"><h4 class="text-lg font-semibold tracking-tight text-slate-900">SenseNova U1 Fast</h4></div>
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<div class="mt-3 flex min-h-0 flex-1 flex-col"><p class="text-[15px] leading-relaxed text-slate-600">基于 SenseNova U1 的加速版本，专供信息图（Infographics）生成</p><div class="mt-4 rounded-lg bg-slate-50/80 px-3 py-2.5"><p class="text-[11px] font-semibold uppercase tracking-[0.12em] text-slate-500">调用次数限制</p><p class="mt-1 text-[14px] font-medium text-slate-800">每5小时1500次</p></div></div>
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<div class="mt-[12px] flex items-start justify-between gap-3 rounded-xl bg-slate-100 px-3.5 py-2.5"><div class="min-w-0 flex-1"><p class="text-[10px] font-semibold uppercase tracking-[0.14em] text-slate-500">MODEL ID</p><code class="mt-1 block break-all font-mono text-[14px] font-semibold text-indigo-950">sensenova-u1-fast</code></div></div>
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</div>
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<div class="flex h-full flex-col rounded-2xl border border-slate-200/95 bg-white p-5 shadow-[0_1px_3px_rgba(15,23,42,0.06)]">
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<div class="flex flex-wrap items-start justify-between gap-2 gap-y-2"><h4 class="text-lg font-semibold tracking-tight text-slate-900">DeepSeek V4 Flash</h4></div>
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<div class="mt-3 flex min-h-0 flex-1 flex-col"><p class="text-[15px] leading-relaxed text-slate-600">DeepSeek 高性能对话模型，支持思考/非思考模式、256K 上下文、工具调用</p><div class="mt-4 rounded-lg bg-slate-50/80 px-3 py-2.5"><p class="text-[11px] font-semibold uppercase tracking-[0.12em] text-slate-500">调用次数限制</p><p class="mt-1 text-[14px] font-medium text-slate-800">每5小时150次</p></div></div>
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<div class="mt-[12px] flex items-start justify-between gap-3 rounded-xl bg-slate-100 px-3.5 py-2.5"><div class="min-w-0 flex-1"><p class="text-[10px] font-semibold uppercase tracking-[0.14em] text-slate-500">MODEL ID</p><code class="mt-1 block break-all font-mono text-[14px] font-semibold text-indigo-950">deepseek-v4-flash</code></div></div>
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</div>
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</section>
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<section id="model-flash" class="scroll-mt-doc-anchor pt-10"><h2 class="text-2xl font-bold text-slate-900">SenseNova 6.7 Flash-Lite</h2><p class="mt-3 text-slate-600">面向真实工作流的轻量多模态智能体模型，支持文本对话与图像输入理解。</p><ul class="mt-3 list-disc space-y-1.5 pl-6 text-slate-700"><li>轻量高效，兼顾效果、成本与落地性</li><li>原生多模态架构，支持图像输入理解（OCR、图表解读等）</li><li>上下文长度 256K tokens（最大输入 252K，最大输出 64K）</li></ul><p class="mt-4 text-slate-700"><strong class="font-semibold text-slate-900">MODEL ID:</strong> <code class="rounded bg-slate-100 px-1 font-mono text-xs">sensenova-6.7-flash-lite</code></p></section>
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<section id="model-u1" class="scroll-mt-doc-anchor pt-10"><h2 class="text-2xl font-bold text-slate-900">SenseNova U1 Fast</h2><p class="mt-3 text-slate-600">SenseNova U1 Fast 基于 SenseNova U1 的加速版本，专供信息图（Infographics）生成场景。</p><p class="mt-3 text-slate-700"><strong class="font-semibold text-slate-900">MODEL ID:</strong> <code class="rounded bg-slate-100 px-1 font-mono text-xs">sensenova-u1-fast</code></p><p class="mt-3 text-slate-700"><strong class="font-semibold text-slate-900">注意：</strong> U1 Fast 使用独立的图像生成接口 POST /v1/images/generations，不是 Chat Completions；不支持图像输入。</p></section>
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<section id="model-deepseek-v4-flash" class="scroll-mt-doc-anchor pt-10"><h2 class="text-2xl font-bold text-slate-900">DeepSeek V4 Flash</h2><p class="mt-3 text-slate-600">DeepSeek 高性能对话模型，支持思考模式与非思考模式，上下文长度 256K tokens，最大输出 64K tokens，内置 JSON Output、Tool Calls等功能。</p><p class="mt-3 text-slate-700"><strong class="font-semibold text-slate-900">MODEL ID:</strong> <code class="rounded bg-slate-100 px-1 font-mono text-xs">deepseek-v4-flash</code></p></section>
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<div class="relative rounded-xl border border-slate-700/70 bg-slate-900 mt-3 w-full"><div class="codeblock-scroll max-h-[350px] overflow-auto"><div><pre class="m-0 overflow-x-auto whitespace-pre font-mono text-[0.8125rem] leading-relaxed text-slate-100 px-4 py-3"><code>GET https://token.sensenova.cn/v1/models</code></pre></div></div></div>
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<pre><code>{
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"data": [
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{
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"id": "sensenova-6.7-flash-lite",
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"name": "sensenova-6.7-flash-lite",
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"created": 1777392000,
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"input_modalities": ["text", "image"],
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"output_modalities": ["text"],
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"quantization": "fp8",
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"context_length": 262144,
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"max_output_length": 65536,
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"pricing": {
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"prompt": "0",
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"completion": "0",
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"image": "0",
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"request": "0",
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"input_cache_read": "0"
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}
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}
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]
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}</code></pre>
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===SENSENOVA_MODELS_BUNDLE===
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{"subtitle":"兼容 OpenAI 接口，按量透明计费，公测期内免费开放","freeDesc":"公测期完全免费开放","promoLine2":"，所有模型完全开放"}
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scripts/testdata/xfyun_pricing_sample.html
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scripts/testdata/xfyun_pricing_sample.html
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<div class="apiprice_priceCards__3gD4l"><div class="apiprice_priceCardItem__gMfGL"><div class="apiprice_cardTitle__NBzoB">X2/X1.5模型</div><div class="apiprice_cardPrice__UdXTV"><span>2</span><span class="apiprice_unit__DWiuh">元/百万tokens</span></div></div><div class="apiprice_priceCardItem__gMfGL"><div class="apiprice_cardTitle__NBzoB">Ultra模型</div><div class="apiprice_cardPrice__UdXTV"><span>0.8</span><span class="apiprice_unit__DWiuh">元/百万tokens</span></div></div><div class="apiprice_priceCardItem__gMfGL"><div class="apiprice_cardTitle__NBzoB">Pro模型</div><div class="apiprice_cardPrice__UdXTV"><span>5</span><span class="apiprice_unit__DWiuh">元/百万tokens</span></div></div><div class="apiprice_priceCardItem__gMfGL"><div class="apiprice_cardTitle__NBzoB">Lite模型</div><div class="apiprice_cardPrice__UdXTV"><span>0</span><span class="apiprice_unit__DWiuh">元/百万tokens</span></div></div></div>
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