alfin06/swegent-issues-filtered huggingface dataset:
[FEATURE] Strands MCP client should support retrieving Output Schema & other Data Types

### Problem Statement

I would like strands to support MCP output schema tool specs feature: https://modelcontextprotocol.io/specification/2025-06-18/server/tools#data-types

```
A tool definition includes:
- name: Unique identifier for the tool
- title: Optional human-readable name of the tool for display purposes.
- description: Human-readable description of functionality
- inputSchema: JSON Schema defining expected parameters
- outputSchema: Optional JSON Schema defining expected output structure
- annotations: optional properties describing tool behavior
```

### Proposed Solution

Running the most latest version of python MCP SDK (v1.13.1), I was able to connect and fetch output schema from remote MCP server with the following change to [MCPAgentTool](https://github.com/strands-agents/sdk-python/blob/2db52266a5b66ea08f692288d64c5871f57fd968/src/strands/tools/mcp/mcp_agent_tool.py#L53) tool spec function:

```python
def tool_spec(self) -> ToolSpec:
  """Get the specification of the tool.
  
  This method converts the MCP tool specification to the agent framework's
  ToolSpec format, including the input schema and description.
  
  Returns:
      ToolSpec: The tool specification in the agent framework format
  """
  description: str = self.mcp_tool.description or f"Tool which performs {self.mcp_tool.name}"
  return {
      "inputSchema": {"json": self.mcp_tool.inputSchema},
      "outputSchema": {"json": self.mcp_tool.outputSchema},
      "name": self.mcp_tool.name,
      "description": description,
  }
```

### Use Case

It will allow LLM agents to incorporate enhanced context from MCP servers that have implemented the new MCP data types. I'm working on a use case where an Agent is having issues determine which tool to use and providing the context of the output schema has shown to facilitate discerning the nuances between different tools.

### Alternatives Solutions

_No response_

### Additional Context

_No response_

Labels: enhancement, good first issue, ready for contribution, area-mcp
State: closed
Add `addToolResult` as input for `onToolCall`.

### Description

The current API design for the `useChat` hook requires the `onToolCall` handler to rely on the `addToolResult` function returned from the hook's outer scope.

#### Current Pattern

```ts
const { addToolResult } = useChat({
  async onToolCall({ toolCall }) {
    // Logic here uses `addToolResult` from the closure
    const result = await executeToolCall(toolCall);
    addToolResult({
      toolCallId: toolCall.toolCallId,
      toolName: toolCall.toolName,
      result,
    });
  },
});
```

This dependency makes it difficult to extract the `onToolCall` logic into a separate, reusable function, especially for complex implementations. The common workaround is to pass `addToolResult` manually, which is cumbersome.

#### Proposed Change

I suggest passing `addToolResult` as a parameter directly to the `onToolCall` callback. This would make the handler self-contained and significantly improve modularity.

```ts
useChat({
  async onToolCall({ toolCall, addToolResult }) {
    const result = await executeToolCall(toolCall);
    addToolResult({
      toolCallId: toolCall.toolCallId,
      toolName: toolCall.toolName,
      result,
    });
  },
});
```



### AI SDK Version

ai: 5.0.5

Labels: feature, ai/core, ai/ui
State: closed
Function calling works on the first message in a chat, but fails on replies

### 📦 Platform

Other, Self hosting Docker

### 📦 Deploymenet mode

server db(lobe-chat-database image)

### 📌 Version

1.87.5

### 💻 Operating System

Other Linux

### 🌐 Browser

Chrome

### 🐛 Bug Description

Tool calling with gemini works completly reliably on the first call, but not on new calls within the same thread.

If I start a new thread it will kick off another query just fine, but replies again will break.

How do I debug this?

![Image](https://github.com/user-attachments/assets/bb17de23-acd3-463e-93be-4ccd4b6a1d63)

### 📷 Recurrence Steps

1. Start new thread
2. Ask it to trigger a function call - that will work
4. Then ask it to do the same thing again - now it fails


### 🚦 Expected Behavior

_No response_

### 📝 Additional Information

In the logs I only get this:

```
Error: [GoogleGenerativeAI Error]: Failed to parse stream
    at <unknown> (.next/server/edge-chunks/51.js:5:29025)
 ⨯ unhandledRejection:  Error: [GoogleGenerativeAI Error]: Failed to parse stream
    at <unknown> (.next/server/edge-chunks/51.js:5:29025)
[Error: aborted] { code: 'ECONNRESET' }
 ⨯ uncaughtException:  [Error: aborted] { code: 'ECONNRESET' }
```

We're using gemini-2.5-pro-preview-05-06, which has been *excellent* at getting function calling right in other repositories.

Labels: released, provider:gemini, unconfirm
State: closed
GPT-5/GPT-4o: Prompt caching not working

### Description

model: `gpt-5-2025-08-07` or `gpt-4o-2024-08-06`

Always returns with `usage.input_tokens_details.cached_tokens` = 0. `usage.input_tokens` is well above the 1024 min. And ensured the system prompt is always the same.

Setting [`prompt_cache_key`](https://platform.openai.com/docs/api-reference/responses/create#responses_create-prompt_cache_key) also doesn't work, seems like it's not even being passed along (the response has `"prompt_cache_key":null`).

response
```
{
  "id": "resp_xyz",
  "text": {
    "format": {
      "type": "text"
    },
    "verbosity": "medium"
  },
  "user": null,
  "error": null,
  "model": "gpt-4o-2024-08-06",
  "store": false,
  "tools": [],
  "top_p": 1,
  "usage": {
    "input_tokens": 8609,
    "total_tokens": 8670,
    "output_tokens": 61,
    "input_tokens_details": {
      "cached_tokens": 0
    },
    "output_tokens_details": {
      "reasoning_tokens": 0
    }
  },
  "object": "response",
  "output": [
    {
      "id": "msg_xyz",
      "role": "assistant",
      "type": "message",
      "status": "completed",
      "content": [
        {
          "text": "blah blah",
          "type": "output_text",
          "logprobs": [],
          "annotations": []
        }
      ]
    }
  ],
  "status": "completed",
  "metadata": {},
  "reasoning": {
    "effort": null,
    "summary": null
  },
  "background": false,
  "created_at": 1754684194,
  "truncation": "disabled",
  "temperature": 0.7,
  "tool_choice": "auto",
  "instructions": null,
  "service_tier": "default",
  "top_logprobs": 0,
  "max_tool_calls": null,
  "prompt_cache_key": null,
  "max_output_tokens": 1024,
  "safety_identifier": null,
  "incomplete_details": null,
  "parallel_tool_calls": true,
  "previous_response_id": null
}
```

### AI SDK Version

- ai: 5.0.8
- @ai-sdk/openai: 2.0.7

Labels: ai/provider, support, provider/openai
State: closed
The input prompt is now active while confirming tool responses

### What happened?

Repro: press the down arrow while in the middle of a tool response.

Example prompt to repro:
Add 3 files named a.txt, b.txt, 3.txt each that contain the words "hello world" each using the write file tool.
Now type some letters and notice that the input prompt is still active.

### What did you expect to happen?

Expect the input prompt to perhaps be visible but not be active until the tool message prompts are done being responded to.

### Client information

<details>
<summary>Client Information</summary>

Run `gemini` to enter the interactive CLI, then run the `/about` command.

```console
> /about
# paste output here
```

</details>

### Login information

_No response_

### Anything else we need to know?

_No response_

Labels: priority/p0
State: closed
[Request] Support Claude Web Search Support

### 🥰 需求描述

Anthropic have just released Claude 4 Opus and Claude 4 Sonnet. I would like to see these fully supported WITH their web-search ability like Gemini has. 

### 🧐 解决方案

The solution is to add websearch and support for the new Claude 4 models

### 📝 补充信息

_No response_

Labels: released
State: closed
`transform` in zod schema causes typescript error when using `tool`

### Description

I have a schema that implements a date transformation as described in the docs [here](https://ai-sdk.dev/docs/ai-sdk-core/prompt-engineering#zod-dates). If I use this schema as the `inputSchema` of a `tool` definition, I get the following typescript error:

```typescript
// schema.ts

import { z } from 'zod';

export const alertsToolArgs = z.object({
  params: z.object({
    dateTo: z
      .string()
      .date()
      .transform((value) => new Date(value)),
  }),
});
```

```typescript
// tool.ts

import { tool } from 'ai';

import { alertsToolArgs } from './schema';

export const alertsTool = tool({
  name: 'alerts',
  description: 'Get a list of alerts',
  inputSchema: alertsToolArgs,
});

```

<img width="1738" height="511" alt="Image" src="https://github.com/user-attachments/assets/4073aa3e-76ed-47ca-b657-50297a85c3d8" />

If I remove the transform, it resolves the typescript error
 

### AI SDK Version

- ai: 5.0.8
- zod: 3.25.68
- typescript: 5.6.3

Labels: bug, ai/core
State: closed
Claude 4 Opus deep thinking token count broken

### 📦 Platform

Self hosting Docker

### 📦 Deploymenet mode

server db(lobe-chat-database image)

### 📌 Version

1.88.0

### 💻 Operating System

Windows

### 🌐 Browser

Other

### 🐛 Bug Description

When trying to use the deep thinking option with Claude 4 Opus, it errors even with tiny requests

![Image](https://github.com/user-attachments/assets/ebeff551-d07b-4518-a440-875a304db8d2)

![Image](https://github.com/user-attachments/assets/3e8d863a-bd1b-43b7-a011-8ef421597987)

The error text:

```
{
  "error": {
    "type": "invalid_request_error",
    "message": "max_tokens: 64000 > 32000, which is the maximum allowed number of output tokens for claude-opus-4-20250514"
  },
  "endpoint": "https://api.anthropic.com",
  "provider": "anthropic"
}
```

This is a single word message with a 1k token limit set for thinking and it fails. However, if I toggle off extended thinking, it works and even huge input requests work. 

### 📷 Recurrence Steps

Start a new chat with Claude 4 Opus and set "enable deep thinking" to "on". 

Now, send any message. 

### 🚦 Expected Behavior

I expect this to function like Claude 4 Sonnet does, in which it returns a response with "thinking" tags. 

I believe Opus has a maximum output of 32,000 tokens whereas Sonnet has a maximum output of 64,000. So you may just need to update this in the request. 

### 📝 Additional Information

_No response_

Labels: released, unconfirm
State: closed
`convertToModelMessages` doesn't pass `providerOptions` for user messages

### Description

Looking at the current implementation for `convertToModelMessages`, it seems that it passes `providerOptions` for `system` messages and `assistant` messages, but not for `user` messages. 

We want to be able to pass Anthropic's cache control options for user messages, and we're currently just manually converting to `ModelMessage[]` to add the `providerOptions` to get around this for now.

https://github.com/vercel/ai/blob/0c0443cbd827cf9746fb13e7a64963fc2d416ebf/packages/ai/src/ui/convert-to-model-messages.ts#L72-L98

### AI SDK Version

_No response_

Labels: bug, ai/core, ai/provider, provider/anthropic
State: closed
v1.4.1 Ollama can't get Model Names

### Bug Description

v1.4.1 Ollama can't get Model Names

![Image](https://github.com/user-attachments/assets/deba4eef-8c0e-4cca-9d91-beb75cc88856)

### Reproduction

Look pic 

### Expected behavior

Ollama model can‘t select 

### Who can help?

_No response_

### Operating System

MacOS 15.4.1

### Langflow Version

1.4.1

### Python Version

3.12

### Screenshot

_No response_

### Flow File

_No response_

Labels: bug
State: closed
[Request] 能否将<think>标签排除在上下文之外

### 🥰 需求描述

有些模型将思考内容并入正文以<think>标签呈现，如果模型思考过多，回复却很短会极大浪费token，隔壁cherrystudio似乎有相关功能，自动分离，希望lobechat也能有

### 🧐 解决方案

none

### 📝 补充信息

_No response_

Labels: released
State: closed
不支持思考的 Gemini 模型请求不应包含 `includeThoughts`

一些不支持思考的模型增加includeThoughts后出现错误，例如 Gemini API 的 ```gemini-2.0-flash-preview-image-generation``` 和 Vertex 的```gemini-2.0-flash```、```gemini-2.0-flash-lite```。
```
{
  "error": {
    "message": "Thinking is not enabled for models/gemini-2.0-flash-preview-image-generation",
    "statusCode": 400,
    "statusCodeText": "[400 Bad Request]"
  },
  "provider": "google"
}
```

Vertex 的 Gemini 2.0 Flash
```
{
  "error": {
    "message": "[VertexAI.ClientError]: got status: 400 Bad Request. {\"error\":{\"code\":400,\"message\":\"Unable to submit request because Thinking_config.include_thoughts is only enabled when thinking is enabled.. Learn more: https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/gemini\",\"status\":\"INVALID_ARGUMENT\"}}"
  },
  "provider": "vertexai"
}
```

_Originally posted by @KoellM in https://github.com/lobehub/lobe-chat/issues/7686#issuecomment-2911052308_
            

Labels: released, provider:gemini
State: closed
[Request] 可以添加claude api的search功能吗？

### 🥰 Feature Description

请问可以添加Claude api自带的搜索功能吗？

### 🧐 Proposed Solution

https://docs.anthropic.com/en/docs/agents-and-tools/tool-use/web-search-tool

### 📝 Additional Information

_No response_

Labels: released
State: closed
Mistral's latest release of reasoning models changed prompt and output

### Description

The latest versions of Mistral's reasoning models have a different output. It's not using the thinking tag anymore. See [https://docs.mistral.ai/capabilities/reasoning/](url) for more information.

```
"content": [
  {
    "type": "thinking",
    "thinking": [
      {
        "type": "text",
        "text": "*Thoughts and reasoning traces will go here.*"
      }
    ]
  },
  {
    "type": "text",
    "text": "*Final answer will go here.*"
  },
  ...
]
```

I tried to use new model but got an validation error

```[Error [AI_TypeValidationError]: Type validation failed: Value: {"id":"","object":"chat.completion.chunk","created":1755082387,"model":"magistral-small-2507","choices":[{"index":0,"delta":{"content":[{"type":"thinking","thinking":[{"type":"text","text":```

### AI SDK Version

- ai: 5.0.11
- @ai-sdk/mistral: 2.0.3,

Labels: feature, ai/provider, provider/mistral
State: closed
Support google gemini embedding model's title feature

### Description

the gemini embeddings model allows passing titles with the created embedding for better retrieval embeddings. only valid when using taskType RETRIEVAL_DOCUMENT. but there is no way to currently pass this to google-vertex-embedding-model. i was wondering how we can support this?

see api: https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/text-embeddings-api

### AI SDK Version

_No response_

Labels: feature, ai/provider, provider/google, provider/google-vertex
State: closed
Reasoning Effort option missing from Model Settings, causing agent errors

### 📦 Platform

Self hosting Docker

### 📦 Deploymenet mode

server db(lobe-chat-database image)

### 📌 Version

v1.90.4

### 💻 Operating System

Ubuntu

### 🌐 Browser

Chrome

### 🐛 Bug Description

The "**Reasoning Effort**" option is no longer visible in the Model Settings regardless of which model is selected. It appears only for a very limited set of models (e.g., ChatGPT), and only directly within the chat interface not in the main model settings panel. For models like DeepSeek-R1, Gemini, etc., the setting is completely unavailable.

This causes a major problem: I have multiple agents configured with default reasoning levels like "DeepThink," and now when I switch to a model that doesn't support it, the agent throws an error saying "This model does not support deep thinking." There's no way to disable or change the reasoning effort from settings as before.

The issue persists across all environments:

**Desktop Firefox and Chrome (Ubuntu)**
**Mobile device (Firefox, Chrome, Galaxy Browser)**

Self-hosted using Docker database deployment (which I always keep updated to the latest version immediately upon release)

### 📷 Recurrence Steps

1. Open LobeChat (Docker db image).
2. Access to Model Settings from saved agent.
3. Reasoning Effort no longer appear at all (normally apear right after **max token lim** option)
4. Use an agent that was Reasoning effort enabled, and use a non deepthink model.
5. Chat throws an error that the model does not support reasoning effort, with no way to turn it off (disable).

### 🚦 Expected Behavior

The "Reasoning Effort" option should be accessible from the Model Settings panel for all models, even if it's disabled or the current model for this agent don't have thinking feature.

There should be a clear UI option to disable or modify reasoning effort per model, especially to avoid runtime errors with agents that default to unsupported settings.

### 📝 Additional Information

Issue happens on all devices and platforms I tested.

My setup uses the official Docker image, updated regularly.

Previously, this option was always visible in settings, regardless of the selected model.

This regression affects the usability of multi-agent workflows significantly.

Labels: released, unconfirm
State: closed
Groq models receiving unsupported `reasoning` field causing API errors

### Description

When using Groq models (specifically `moonshotai/kimi-k2-instruct`) with the Vercel AI SDK, the API returns a 400 error: `"messages[X].reasoning": reasoning is not supported with this model`. The SDK appears to automatically add `reasoning` fields to messages even when the model doesn't support reasoning capabilities.

## Environment

- **AI SDK Version**: `5.0.14` (also reproduced on `5.0.8`)
- **Provider**: `@ai-sdk/groq` version `2.0.9`
- **Model**: `moonshotai/kimi-k2-instruct`
- **Node.js**: v18+
- **Platform**: macOS/Linux

## Error Details

```json
{
  "error": {
    "message": "`messages[3].reasoning`: reasoning is not supported with this model",
    "type": "invalid_request_error"
  },
  "statusCode": 400,
  "url": "https://api.groq.com/openai/v1/chat/completions"
}
```

## Reproduction Script

```typescript
import { streamText } from 'ai';
import { createGroq } from '@ai-sdk/groq';

const groq = createGroq({
  apiKey: process.env.GROQ_API_KEY || 'your-api-key-here'
});

async function reproduceIssue() {
  // Messages that would normally work
  const messages = [
    {
      role: 'system' as const,
      content: 'You are a helpful assistant.'
    },
    {
      role: 'user' as const,
      content: 'Hello, how are you?'
    },
    {
      role: 'assistant' as const,
      content: 'I am doing well, thank you for asking!',
    },
    {
      role: 'user' as const,
      content: 'What is 2+2?'
    }
  ];

  try {
    const result = streamText({
      model: groq('moonshotai/kimi-k2-instruct'),
      messages,
    });

    for await (const chunk of result.textStream) {
      console.log(chunk);
    }
  } catch (error) {
    console.error('Error:', error);
    // Will output: `messages[2].reasoning`: reasoning is not supported with this model
  }
}

reproduceIssue();
```

## Expected Behavior

The SDK should either:
1. Automatically strip `reasoning` fields from messages when using models that don't support reasoning
2. Provide a clear way to disable reasoning features per-model
3. Not automatically add reasoning fields to messages unless explicitly enabled and supported

Labels: bug, ai/provider, provider/groq
State: closed
请问下，训练的模型，如果是“启用思考”的被勾选了，它的回答没有按照训练的来进行回答。如果没有勾选，就会按照训练的来，这个是怎么回事？

### Reminder

- [x] I have read the above rules and searched the existing issues.

### System Info

llamaFactory 0.9.3 

### Reproduction

请问下，训练的模型，如果是“启用思考”的被勾选了，它的回答没有按照训练的来进行回答。如果没有勾选，就会按照训练的来，这个是怎么回事？

### Others

_No response_

Labels: solved
State: closed
streamText does not call onAbort if the abort signal is triggered during a tool call

### Description

See failing test PR example https://github.com/vercel/ai/pull/8106

### AI SDK Version

_No response_

### Code of Conduct

- [x] I agree to follow this project's Code of Conduct

Labels: support
State: closed
话题智能命名基于用户正在查看的对话，而不是应当被命名的话题

### 📦 部署环境

Vercel

### 📦 部署模式

服务端模式(lobe-chat-database 镜像)

### 📌 软件版本

v1.93.0

### 💻 系统环境

Windows

### 🌐 浏览器

Chrome

### 🐛 问题描述

话题智能命名基于用户正在查看的对话，而不是应当被命名的话题

### 📷 复现步骤

1. `随便聊聊` 中有话题A
2. 在 `随便聊聊-默认话题` 中聊话题B
3. 确认消息话题B消息发送成功后，**不等助手返回消息，立即切换至话题A**
4. 等待助手在话题B中返回消息和话题B智能命名完成，观察到话题B的智能命名实际上基于话题A的内容，因为智能命名时在前台的话题是话题A。

![Image](https://github.com/user-attachments/assets/7f7b6b99-f77a-4232-a313-0820695fa20e)

![Image](https://github.com/user-attachments/assets/9fc6b993-bfed-46d0-95ef-33c335b21172)

### 🚦 期望结果

话题B智能命名应当基于话题B的内容，无论话题B是否显示在前台。

### 📝 补充信息

_No response_

Labels: released, unconfirm
State: closed
升级1.93.0之后NewAPi做了Proxy的模型开始报404了

### 📦 部署环境

Docker

### 📦 部署模式

服务端模式(lobe-chat-database 镜像)

### 📌 软件版本

v1.93.0

### 💻 系统环境

Windows

### 🌐 浏览器

Chrome

### 🐛 问题描述

升级v1.93.0之后，使用 NewAPI做了Proxy的，以OpenAI方式配置的模型会直接报404，具体如下：

```json
{
  "code": "404",
  "type": "",
  "error": {
    "code": "404",
    "type": "",
    "param": "",
    "message": "Resource not found (request id: 20250608214652709397047ZffZGc0k)"
  },
  "param": "",
  "status": 404,
  "headers": {
    "date": "Sun, 08 Jun 2025 13:46:52 GMT",
    "connection": "keep-alive",
    "content-type": "text/event-stream",
    "cache-control": "no-cache",
    "transfer-encoding": "chunked",
    "x-accel-buffering": "no",
    "x-oneapi-request-id": "20250608214652709397047ZffZGc0k"
  },
  "provider": "openai"
}
```

后台日志：
```bash
 Route: [openai] 500: {
   message: 'Resource not found (request id: 20250608214658261825941tNxXtMH)',
   type: '',
   param: '',
   code: '404'
 }
```


### 📷 复现步骤

_No response_

### 🚦 期望结果

_No response_

### 📝 补充信息

因为我这边的模型主要是来自Azure，又存在不同模型必须部署在不同区域的问题，实际为了使用方便就一直使用Proxy服务统一伪装成OpenAI来用的，之前一直使用正常，升级1.93.0后请求全部报404，回退到1.92.2版本后恢复正常

Labels: released, unconfirm
State: closed
Mistral: Implement `response_format.type === 'json_schema'`

Follow up to #8125

[<img width="691" height="592" alt="Image" src="https://github.com/user-attachments/assets/c194b2a8-d0af-425c-8bde-e168c45ba5bc" />](https://docs.mistral.ai/api/#tag/chat/operation/chat_completion_v1_chat_completions_post)

Labels: feature, ai/provider, provider/mistral
State: closed
Get Started with GPT-5 is not working in guildes

### Description

When we click on the "Get Started with GPT-5" guide it gives a 500 - internal server error [check](https://ai-sdk.dev/cookbook/guides/gpt-5)

### AI SDK Version

_No response_

### Code of Conduct

- [x] I agree to follow this project's Code of Conduct

Labels: documentation, ai/provider, support, provider/openai, provider/vercel
State: closed
【开启推理强度调整】设置为关闭的状态下，似乎依旧生效

### 📦 部署环境

Docker

### 📦 部署模式

服务端模式(lobe-chat-database 镜像)

### 📌 软件版本

1.94.7

### 💻 系统环境

Ubuntu

### 🌐 浏览器

Safari

### 🐛 问题描述

更新到1.94.0之后 #8110 问题解决了，可以在模型设置中看到【开启推理强度调整】，但是一旦开启了这个设置，并设置为”中“以外的选项，之后在设置中关闭该选项，切换非推理模型就会报错
```yaml
{
  "error": {
    "code": null,
    "type": "invalid_request_error",
    "param": null,
    "message": "Unrecognized request argument supplied: reasoning_effort"
  },
  "endpoint": "********************",
  "provider": "openai"
}
```
测试过1.94.0和1.94.7都会报错
退回[1.88.20](https://github.com/lobehub/lobe-chat/releases/tag/v1.88.20)，也就是pr #7998 的上一个版本，设置【开启推理强度调整】是正常的，不会出现关闭该设置的情况下调用非推理模型报错

### 📷 复现步骤

在随便聊聊/新建助手中开启【开启推理强度调整】并设置为“高”，关闭【开启推理强度调整】，切换到非推理模型进行对话

### 🚦 期望结果

【开启推理强度调整】可以被正确关闭

### 📝 补充信息

可能和 #8065 类似
去数据库里手动删掉reasoning_effort就正常了，但是总不能每次要关闭该设置就手动去数据库里删吧
看了一下数据库，仅打开【开启推理强度调整】设置并不会写入reasoning_effort，但是调整为“高”之后就会写入

Labels: released, unconfirm
State: closed