错误信息: not implemented (request id: 2026042815485886376031v0IMnT3k) 堆栈信息: AI_APIC...
错误信息
错误名称: AI_APICallError
错误信息: not implemented (request id: 2026042815485886376031v0IMnT3k)
堆栈信息: AI_APICallError: not implemented (request id: 2026042815485886376031v0IMnT3k)
at file:///D:/cherry%20studio/resources/app.asar/out/renderer/assets/store-CxDhcqaJ.js:51840:11
at async postToApi$2 (file:///D:/cherry%20studio/resources/app.asar/out/renderer/assets/store-CxDhcqaJ.js:51735:24)
at async OpenAIResponsesLanguageModel$3.doStream (file:///D:/cherry%20studio/resources/app.asar/out/renderer/assets/store-CxDhcqaJ.js:67782:48)
at async fn (file:///D:/cherry%20studio/resources/app.asar/out/renderer/assets/store-CxDhcqaJ.js:103355:17)
at async file:///D:/cherry%20studio/resources/app.asar/out/renderer/assets/store-CxDhcqaJ.js:99626:19
at async _retryWithExponentialBackoff (file:///D:/cherry%20studio/resources/app.asar/out/renderer/assets/store-CxDhcqaJ.js:99816:10)
at async streamStep (file:///D:/cherry%20studio/resources/app.asar/out/renderer/assets/store-CxDhcqaJ.js:103324:109)
at async fn (file:///D:/cherry%20studio/resources/app.asar/out/renderer/assets/store-CxDhcqaJ.js:103641:5)
at async file:///D:/cherry%20studio/resources/app.asar/out/renderer/assets/store-CxDhcqaJ.js:99626:19
错误原因: "[undefined]"
状态码: 500
请求路径: https://www.dmxapi.cn/v1/responses
请求体: {
"model": "deepseek-v4-pro-guan",
"input": [
{
"role": "system",
"content": "\n## Hub MCP Tools – Auto Tooling Mode\n\nYou can discover and call MCP tools through the hub server using **ONLY four meta-tools**:\n\n| Tool | Purpose |\n|------|---------|\n| `list` | List tools (paginated via `limit`/`offset`) |\n| `inspect` | Get a tool signature as JSDoc |\n| `invoke` | Call a single tool |\n| `exec` | Execute JavaScript that orchestrates multiple tool calls |\n\n### Critical Rules\n\n1. Use `list` to find the right tool. This is **tool discovery** (NOT web search).\n2. Use `inspect` before calling a tool to confirm parameter names and shapes.\n3. Use `invoke` for a single tool call.\n4. Use `exec` for multi-step flows.\n5. Inside `exec`, call tools ONLY via `mcp.callTool(name, params)`.\n6. In `exec`, you MUST explicitly `return` the final value.\n\n### What `list` Returns\n\n- A paginated list of tools.\n- The response includes: Total / Offset / Limit / Returned.\n- Each tool line includes:\n - JS-friendly tool name (camelCase)\n - original tool id in parentheses (serverId__toolName)\n\n### What `inspect` Returns\n\n- A JSDoc stub you can copy into `exec` code.\n\n### What `exec` Provides\n\n- `mcp.callTool(name, params)` → call a tool by JS name (camelCase) or original id (serverId__toolName)\n- `mcp.log(level, message, fields?)`\n- `parallel(...promises)` → Promise.all\n- `settle(...promises)` → Promise.allSettled\n- `console.log/info/warn/error/debug` (captured)\n\n### Example: Single Call (invoke)\n\n1) `list({ limit: 50, offset: 0 })`\n2) Pick the relevant tool name from the list.\n3) `inspect({ name: \"githubSearchRepos\" })`\n4) `invoke({ name: \"githubSearchRepos\", params: { query: \"mcp\" } })`\n\n### Example: Multi-step Flow (exec)\n\n```javascript\nconst repos = await mcp.callTool(\"githubSearchRepos\", { query: \"mcp\" })\nconsole.log(\"found\", repos)\nreturn repos\n```\n"
},
{
"role": "user",
"content": [
{
"type": "input_text",
"text": "使用NM91（Ni0.9,Mn0.1）的前驱体，去掺杂过渡金属与非金属去做高熵的高镍无钴正极，你能搜索相关文献获取一些灵感设计一个方案，用专业的视角去细节化每一个可能的问题，只需要涉及原理以及具体的实验过程，精确到参数，并解释，不需要设置对照组，所有的东西要合理参照文献适当创新，我希望里面有w，只需要掺杂，一次煅烧，实验室里没有b\n全部都掺杂源都是其氧化物，按Li 0.01mol重新称量并调整全部实验步骤，并制作实验SOP"
}
]
}
],
"temperature": 0.7,
"top_p": "[undefined]",
"max_output_tokens": "[undefined]",
"conversation": "[undefined]",
"max_tool_calls": "[undefined]",
"metadata": "[undefined]",
"parallel_tool_calls": "[undefined]",
"previous_response_id": "[undefined]",
"store": false,
"user": "[undefined]",
"instructions": "[undefined]",
"service_tier": "[undefined]",
"include": "[undefined]",
"prompt_cache_key": "[undefined]",
"prompt_cache_retention": "[undefined]",
"safety_identifier": "[undefined]",
"top_logprobs": "[undefined]",
"truncation": "[undefined]",
"tools": [
{
"type": "function",
"name": "mcp__CherryHub__list",
"description": "List available MCP tools from all active servers. Results are paginated via limit/offset.",
"parameters": {
"type": "object",
"properties": {
"limit": {
"type": "number",
"description": "Optional maximum results to return (default: 30, max: 100)."
},
"offset": {
"type": "number",
"description": "Optional zero-based offset for pagination (default: 0)."
}
},
"required": []
}
},
{
"type": "function",
"name": "mcp__CherryHub__inspect",
"description": "Get a single tool's signature as a JSDoc stub. Use this before `invoke` or `exec`.",
"parameters": {
"type": "object",
"properties": {
"name": {
"type": "string",
"description": "Tool name in JS form (camelCase) OR original namespaced id (serverId__toolName)."
}
},
"required": [
"name"
]
}
},
{
"type": "function",
"name": "mcp__CherryHub__invoke",
"description": "Call a single tool with parameters. Prefer `inspect` first to confirm parameters.",
"parameters": {
"type": "object",
"properties": {
"name": {
"type": "string",
"description": "Tool name in JS form (camelCase) OR original namespaced id (serverId__toolName)."
},
"params": {
"type": "object",
"description": "Tool parameters as a JSON object (optional)."
}
},
"required": [
"name"
]
}
},
{
"type": "function",
"name": "mcp__CherryHub__exec",
"description": "Execute JavaScript code to orchestrate multiple tool calls. Use `mcp.callTool(name, params)` inside the code. IMPORTANT: you MUST explicitly `return` the final value.",
"parameters": {
"type": "object",
"properties": {
"code": {
"type": "string",
"description": "JavaScript code to execute. Available globals: `mcp.callTool(name, params)`, `mcp.log(level, message, fields?)`, `parallel(...)`, `settle(...)`, `console.*`. The code runs inside an async context so you can use `await` directly. You MUST `return` the final value."
}
},
"required": [
"code"
]
}
}
],
"tool_choice": "auto",
"stream": true
}
响应首部: {
"content-length": "150",
"content-type": "application/json; charset=utf-8",
"date": "Tue, 28 Apr 2026 07:48:58 GMT",
"document-policy": "include-js-call-stacks-in-crash-reports",
"server": "nginx",
"x-rixapi-request-id": "2026042815485886376031v0IMnT3k"
}
响应内容: {
"error": {
"message": "not implemented (request id: 2026042815485886376031v0IMnT3k)",
"type": "rix_api_error",
"param": "",
"code": "convert_request_failed"
}
}
数据: {
"error": {
"message": "not implemented (request id: 2026042815485886376031v0IMnT3k)",
"type": "rix_api_error",
"param": "",
"code": "convert_request_failed"
}
}
AI 解决方案
报错分析报告
1.错误翻译
原文：not implemented (request id: 2026042815485886376031v0IMnT3k)
译文：未实现（请求ID：2026042815485886376031v0IMnT3k）
2.原因分析
convert_request_failed），推测模型名称或参数格式无效导致请求转换失败。 store-CxDhcqaJ.js:51840行（调用postToApi$2时触发），上下文为向https://www.dmxapi.cn/v1/responses发送包含deepseek-v4-pro-guan模型的请求。 [undefined]（如top_p、max_output_tokens），且模型名称可能未被API支持。3.解决方案
修复步骤：
[undefined]参数（或设为有效值）； deepseek-v4-pro-guan是否为API支持的合法值； max_output_tokens设为2048）。 修正后的请求体示例（JSON）：
{
"model": "deepseek-v4-pro-guan", // 需确认API支持此模型
"input": [
{
"role": "system",
"content": "\n## Hub MCP Tools – Auto Tooling Mode\n\n你可以通过集线器服务器使用**仅四个元工具**发现和调用MCP工具：\n\n| 工具 | 用途 |\n|------|------|\n| `list` | 分页列出工具（通过`limit`/`offset`） |\n| `inspect` | 获取工具签名的JSDoc |\n| `invoke` | 调用单个工具 |\n| `exec` | 编排多工具调用的JavaScript |\n\n### 关键规则\n1. 用`list`发现工具（非网页搜索）；\n2. 调用前用`inspect`确认参数名和结构；\n3. 单调用用`invoke`，多步骤用`exec`；\n4. `exec`内用`mcp.callTool(name, params)`调用工具；\n5. `exec`必须显式`return`最终结果。\n\n### 示例：单调用（invoke）\n1. `list({ limit: 50, offset: 0 })`\n2. 选工具名→`inspect({ name: \"githubSearchRepos\" })`\n3. `invoke({ name: \"githubSearchRepos\", params: { query: \"mcp\" } })`\n\n### 示例：多步骤（exec）\n"
},
{
"role": "user",
"content": [
{
"type": "input_text",
"text": "使用NM91（Ni0.9,Mn0.1）的前驱体，去掺杂过渡金属与非金属去做高熵的高镍无钴正极，你能搜索相关文献获取一些灵感设计一个方案，用专业的视角去细节化每一个可能的问题，只需要涉及原理以及具体的实验过程，精确到参数，并解释，不需要设置对照组，所有的东西要合理参照文献适当创新，我希望里面有w，只需要掺杂，一次煅烧，实验室里没有b\n全部都掺杂源都是其氧化物，按Li 0.01mol重新称量并调整全部实验步骤，并制作实验SOP"
}
]
}
],
"temperature": 0.7,
"top_p": 0.9, // 替换为有效值（0~1）
"max_output_tokens": 2048, // 替换为有效值
"stream": true,
"tools": [/ 保留原工具配置 /]
}
`4. 预防措施
最佳实践1：发送API请求前，用JSON Schema验证请求体，避免 或非法参数；
最佳实践2：调用前查阅API文档，确认模型名称、参数范围的合法性（如 top_p`需为0~1的数值）。