alfin06/swegent-issues-filtered huggingface dataset:
[Bug] Claude 使用 function call + 开启限制历史消息数功能，报错：messages.0: `tool_use` blocks can only be in `assistant` messages

### 📦 部署环境

Vercel

### 📦 部署模式

服务端模式(lobe-chat-database 镜像)

### 📌 软件版本

1.65.0

### 💻 系统环境

Windows

### 🌐 浏览器

Chrome

### 🐛 问题描述

Claude 使用 function call + 开启限制历史消息数功能，报错：messages.0: `tool_use` blocks can only be in `assistant` messages

![Image](https://github.com/user-attachments/assets/4ba490b4-72f6-4285-9dfc-cb2b946f8ec8)

### 📷 复现步骤

复现条件：
- 使用 claude-3-7-sonnet-20250219 模型（即支持 function call 功能）
- 开启插件功能，比如 searxng
- 开启「限制历史消息数」功能，假设为 2 

结果：
```
{
  "error": {
    "error": {
      "type": "error",
      "error": {
        "type": "invalid_request_error",
        "message": "messages.0: `tool_use` blocks can only be in `assistant` messages"
      }
    },
    "status": 400,
    "headers": {
      "via": "1.1 google",
      "date": "Thu, 27 Feb 2025 01:49:56 GMT",
      "connection": "keep-alive",
      "request-id": "req_01ED9tngMDhnUpDXyx4jwfUP",
      "content-type": "application/json",
      "x-robots-tag": "none",
      "content-length": "135",
      "x-should-retry": "false",
      "anthropic-organization-id": "d269df32-4f2e-40cd-bfd1-b3491bd379ba"
    },
    "request_id": "req_01ED9tngMDhnUpDXyx4jwfUP"
  },
  "endpoint": "https://api.anthropic.com",
  "provider": "anthropic"
}
```


### 🚦 期望结果

![Image](https://github.com/user-attachments/assets/20f20e31-c1fe-4fba-8971-911649b88c52)

### 📝 补充信息

_No response_

Labels: released
State: closed
CodeExecutorAgent Prompt Misuse

### What happened?

**Describe the bug**
[Related Lines](https://github.com/microsoft/autogen/blob/main/python/packages/autogen-agentchat/src/autogen_agentchat/agents/_code_executor_agent.py#L329)
Currently, the instruction about code block format ("`Python code should be provided in python code blocks, and sh shell scripts should be provided in sh code blocks for execution`") is placed in `DEFAULT_AGENT_DESCRIPTION`, which is only used as the agent's description and not passed to the `model_client`.
However, this instruction is crucial for the `model_client` to generate properly formatted code blocks. Therefore, it should be moved to `DEFAULT_SYSTEM_MESSAGE` which is actually used as the system prompt for the `model_client` when generating code. This change will ensure that the model receives the correct instructions about code block formatting, leading to more reliable code generation.


### Which packages was the bug in?

Python AgentChat (autogen-agentchat>=0.4.0)

### AutoGen library version.

Python dev (main branch)

### Other library version.

_No response_

### Model used

gpt-4o-mini

### Model provider

OpenAI

### Other model provider

_No response_

### Python version

3.12

### .NET version

None

### Operating system

Ubuntu

Labels: needs-triage
State: closed
Allow AnthropicBedrockChatCompletionClient use in an AWS environment

### What happened?

**Describe the bug**
If using AnthropicBedrockChatCompletionClient from an AWS sagemaker notebook or having logged into AWS with SSO, then AWS credentials are set implicitly from environment variables. Current implementation requires them to be explicitly set which shouldn't be required in the mentioned scenarios. 


**To Reproduce**
```python
from autogen_ext.models.anthropic import AnthropicBedrockChatCompletionClient

aws_config = {
    "model": 'us.anthropic.claude-3-5-sonnet-20241022-v2:0',
    "temperature": 0.5,
    "model_info": {
        "vision": False,
        "function_calling": True,
        "json_output": True,
        "structured_output": True,
        "family": 'claude-3-5-sonnet',
    },
    "bedrock_info": {
        "aws_region": 'us-east-1',
    },
}

model_client=AnthropicBedrockChatCompletionClient(**aws_config)

---

File "/workspaces/autogen/python/packages/autogen-ext/src/autogen_ext/models/anthropic/_anthropic_client.py", line 1198, in __init__
  aws_access_key = bedrock_info["aws_access_key"]
                     ~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^
KeyError: 'aws_access_key'

```


**Expected behavior**
If having logged in with SSO, I would expect this to use those credentials

**Screenshots**
NA

**Additional context**
NA

### Which packages was the bug in?

Python Extensions (autogen-ext)

### AutoGen library version.

Python dev (main branch)

### Other library version.

_No response_

### Model used

claude 3.5 sonnet

### Model provider

AWS Bedrock

### Other model provider

_No response_

### Python version

3.10

### .NET version

None

### Operating system

Ubuntu

Labels: needs-triage
State: closed
[Request] OpenAI  GPT 4.5

### 🥰 需求描述

https://openai.com/index/introducing-gpt-4-5/

本来想尝试偷个懒 fork 一个直接在 Github 里面改一下配置然后提个 PR 过来，结果没想到看了下配置里还有价格啥玩意儿的，完全不明白这是啥，可能是类似于 One-API 那种倍率之类的？一直没搞明白那个倍率是啥，就懒得弄了。那是等哪位大佬熟悉配置的来改吧。自己先手动给自己的部署的 model_list 加上了。

### 🧐 解决方案

支持 OpenAI GPT 4.5 模型。

### 📝 补充信息

https://platform.openai.com/docs/models#gpt-4-5

<img width="761" alt="Image" src="https://github.com/user-attachments/assets/d4b7f110-e492-4945-826d-d63eb86f68d5" />

Labels: released
State: closed
[Bug] MCP session disappears after resume - "No run found"

## Bug Description

Session `4d4c76a7-e58a-487a-b66f-7ff408dafb37` (prompt neuron) appeared active in `mcp__genie__list_sessions` but became inaccessible after resume with "No run found" error. Session state becomes unavailable after extended runtime (~45 minutes).

## Steps to Reproduce

1. Start long-running agent session: `mcp__genie__run with agent="orchestrator"`
2. Note session ID (e.g., `4d4c76a7-e58a-487a-b66f-7ff408dafb37`)
3. Wait ~45 minutes (session runs in background)
4. Resume same session: `mcp__genie__resume with sessionId="4d4c76a7-e58a-487a-b66f-7ff408dafb37"`
5. Observe error: "No run found for session 4d4c76a7-e58a-487a-b66f-7ff408dafb37"

## Expected Behavior

- `mcp__genie__view` shows session state
- `mcp__genie__resume` continues session with full context preserved
- Session remains queryable and resumable indefinitely
- Session lifecycle: start → (optional pause) → resume → complete

## Actual Behavior

- Session appears in `mcp__genie__list_sessions` with status: running
- `mcp__genie__view` returns "No run found"
- `mcp__genie__resume` returns "No run found"
- Session context lost entirely after timeout
- State sync broken between list/view/resume operations

## Environment

- OS: Linux (WSL2)
- Node: v22.16.0
- Package version: 2.4.0-rc.8
- MCP: Evolution API

## Impact

**Critical** - Blocking work on session coordination and multi-neuron workflows

## Affected Components

- MCP Server (genie-cli)
- Agents (orchestrator, prompt, implementor)
- Session persistence/retrieval

## Root Cause Analysis

Session storage backend may be dropping state or experiencing desynchronization between list/view/resume operations. Investigate:
1. Session persistence store (data retention after timeout?)
2. State retrieval logic (list vs view/resume mismatch?)
3. Timeout handling (sessions auto-expired?)
4. MCP backend sync issues (different data sources?)

## Reproduction Context

- Session started: 2025-10-17 17:20 UTC
- Session ID: `4d4c76a7-e58a-487a-b66f-7ff408dafb37`
- Mode: prompt (refactoring)
- Runtime: ~45 minutes before inaccessible


Labels: type:bug, area:mcp, priority:critical
State: closed
Migrate AzureAIAgent (backed by Azure Foundry) to new SDK version


This issue is to track efforsts to update the AzureAIAgent (backed by Azure Foundry) to new SDK version released at Build.

State: closed
Reasoning is not working - Amazon Bedrock Anthropic

### Description

```typescript
    const messages: UIMessage[] = [...previousMessages, message];

    const stream = streamText({
      model: provider.languageModel(message.metadata.selectedChatModel),
      messages: convertToModelMessages(messages),
      system: SYSTEM_PROMPT(new Date()),
      experimental_transform: smoothStream(),
      providerOptions: {
        bedrock: {
          reasoning_config: {
            type: "enabled",
            budget_tokens: 2000,
          },
        },
      },
      experimental_telemetry: {
        isEnabled: true,
        functionId: "stream-text",
      },
    });
```

It works fine with xai but fails with Amazon Bedrock and Google Vertex

### AI SDK Version

    @ai-sdk/amazon-bedrock: 3.0.0-alpha.8
    @ai-sdk/google-vertex: 3.0.0-alpha.8
    @ai-sdk/mistral: 2.0.0-alpha.8
    @ai-sdk/openai: 2.0.0-alpha.8
    @ai-sdk/provider-utils: 3.0.0-alpha.8
    @ai-sdk/react: 2.0.0-alpha.8
    @ai-sdk/ui-utils: ^1.2.11
    @ai-sdk/xai: 2.0.0-alpha.8

Labels: bug, ai/provider, provider/xai, provider/amazon-bedrock, provider/google-vertex
State: closed
Issue with Llama-3.2-11B-Vision-Instruct Supporting Only One Image Per Sample?

### Discussed in https://github.com/hiyouga/LLaMA-Factory/discussions/6635

<div type='discussions-op-text'>

<sup>Originally posted by **iMaxb** January 14, 2025</sup>
I am using Llama-3.2-11B-Vision-Instruct and the identity dataset. At the very beginning of training, it throws an error: ValueError: Mllama only supports one image per sample. When I use Llama-3.2-11B-Vision-Instruct directly for chat, it gives the same error. It only works properly when each message is accompanied by an image. Why is this happening?</div>

Labels: solved
State: closed
Extra args not work to disable thinking

### What happened?


I pass  args "thinking" to OpenAIChatCompletionClient But it not work. It  still output "think" label. Is there a good way to do this now?
```
{
  "provider": "autogen_ext.models.openai.OpenAIChatCompletionClient",
  "component_type": "model",
  "version": 1,
  "component_version": 1,
  "description": "doubao_1_5_thinking_pro_m_250428_model_config",
  "label": "doubao_1_5_thinking_pro_m_250428_model_config",
  "config": {
    "model": "doubao-1-5-thinking-pro-m-250428",
    "base_url": "https://ark.cn-beijing.volces.com/api/v3/",
    "api_key": "xxx",
    "max_tokens": 2000,
    **"thinking": {
      "type": "disabled",
    },**
    "model_capabilities": {
      "vision": true,
      "function_calling": true,
      "json_output": true,
      "structured_output": true
    }
  }
}
```
DOCS:https://www.volcengine.com/docs/82379/1494384

![Image](https://github.com/user-attachments/assets/60f1012e-0d0a-4ea3-b6a5-53e767214a5d)


### Which packages was the bug in?

Python Extensions (autogen-ext)

### AutoGen library version.

Python dev (main branch)

### Other library version.

_No response_

### Model used

doubao-1-5-thinking-pro-m-250428

### Model provider

None

### Other model provider

_No response_

### Python version

None

### .NET version

None

### Operating system

None

Labels: needs-triage, awaiting-op-response
State: closed
[Bug] 深度抓取导致页面崩溃 (`Cannot destructure property 'url' of 'l' as it is undefined`)

### 📦 部署环境

Other

### 📦 部署模式

服务端模式(lobe-chat-database 镜像)

### 📌 软件版本

v1.67.2

### 💻 系统环境

macOS

### 🌐 浏览器

Other

### 🐛 问题描述

打开联网搜索，在搜索过程中页面崩溃，并且后续只要打开这个助手就会导致页面崩溃。浏览器控制台报错：`Cannot destructure property 'url' of 'l' as it is undefined`。

<img width="1080" alt="Image" src="https://github.com/user-attachments/assets/41e598e0-f088-49f0-8e7c-f2cf497327aa" />

### 📷 复现步骤

_No response_

### 🚦 期望结果

_No response_

### 📝 补充信息

模型：DeepSeek V3
模型服务: DeepSeek
输入内容：`《计算机科学技术名词》第三版中有提到“代码异味”这个词吗？`
浏览器：Vivaldi 7.1.3570.58 (Stable channel) (arm64) (Chromium 132.0.6834.211)

从浏览器 DevTools 里面提取了 `trpc/lambda/agent.getAgentConfig,message.getMessages,plugin.getPlugins,topic.getTopics` 接口的响应：https://pastebin.pl/view/53c97f67 （链接有效期一个月）

Labels: released
State: closed
OpenAIAgent should support other tool types as well as function

### What happened?

**Describe the bug**
This is for tracking the unresolved issue (https://github.com/microsoft/autogen/pull/6418#discussion_r2124016126).
The OpenAIAgent class should support other tool types such as file search, web search, computer use, mcp tool, code interpreter, image generation tool and local shell tool as well as function.


### Which packages was the bug in?

Python Extensions (autogen-ext)

### AutoGen library version.

Python dev (main branch)

### Other library version.

_No response_

### Model used

_No response_

### Model provider

None

### Other model provider

_No response_

### Python version

None

### .NET version

None

### Operating system

None

Labels: needs-triage
State: closed
[Bug] 自定义服务商里的anthropic还是用的openai兼容模式，不是最新的SDK模式

### 📦 部署环境

Docker

### 📦 部署模式

服务端模式(lobe-chat-database 镜像)

### 📌 软件版本

1.68.1

### 💻 系统环境

Other

### 🌐 浏览器

Chrome

### 🐛 问题描述

自定义服务商里的anthropic还是用的openai兼容模式，不是最新的SDK模式，claude3.7看不到设置深度思考的选项。

### 📷 复现步骤

_No response_

### 🚦 期望结果

_No response_

### 📝 补充信息

_No response_

Labels: released
State: closed
[Bug] 阿里百炼云(qwen)的deepseek v3不支持函数调用，需要取消

### 📦 部署环境

Docker

### 📦 部署模式

服务端模式(lobe-chat-database 镜像)

### 📌 软件版本

v1.68.0

### 💻 系统环境

Windows, Ubuntu

### 🌐 浏览器

Chrome

### 🐛 问题描述

阿里百炼云(qwen)的deepseek v3不支持函数调用，需要取消
![Image](https://github.com/user-attachments/assets/57e0267d-4718-4791-b6c0-d83b0bc893b2)

### 📷 复现步骤

_No response_

### 🚦 期望结果

后端配置qwen后，正常展示deepseek v3不具有函数调用能力的标签

### 📝 补充信息

_No response_

Labels: released
State: closed
Making `Workbench` tool names and descriptions modifiable properties to allow for optimization

### Issue body

For `Workbench`, the tool description and tool name should be modifiable, the implementation should maintain a mapping between the modified name and the underlying name to make sure the call still work:

- For `StaticWorkbench` this should be straightfoward.
- For `McpWorkbench`, we can add a client side mapping for the server side tools to override the description returned from the server side. 

Labels: optimization
State: closed
`onFinish` does not get called in `streamText` when request stopped by the user from client side using `stop()` function

### Description

Issue - on calling stop() from 'useChat()` React, on backend `streamText` does not call onFinish function.

Expected - on calling `stop()` from client side, `streamText` should trigger `onFinish` so that we can save in-complete message to the database and user can start querying new messages.

### AI SDK Version

- ai: 4.3.16
- @ai-sdk/react": "^1.2.11

Labels: bug, ai/core, ai/ui
State: closed
qwen2_vl 模型 使用 vllm 引擎推理时对视频文件的传入未进行处理

### Reminder

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

### System Info

- llamafactory version: 0.9.1.dev0
- Platform: Linux-5.10.134-17.2.1.lifsea8.x86_64-x86_64-with-glibc2.35
- Python version: 3.10.14
- PyTorch version: 2.5.1+cu124 (GPU)
- Transformers version: 4.46.1
- Datasets version: 3.1.0
- Accelerate version: 1.0.1
- PEFT version: 0.12.0
- TRL version: 0.9.6
- GPU type: NVIDIA A10 22GB




### Reproduction

通过webui方式启动服务
```text
llamafactory-cli webui
```
然后点击到chat中使用vllm作为推理引擎，上传视频后点击提交，模型会回复没有视频文件

<img width="1496" alt="Image" src="https://github.com/user-attachments/assets/56bd7fdd-0c44-434c-8d76-5bb17a4cae60" />


通过查阅源码发现 在 src/llamafactory/chat/vllm_engine.py 的 _generate 方法中，缺失了 multi_modal_data 中 video的相应处理
```python
if images is not None:  # add image features
            multi_modal_data = {"image": []}
            for image in images:
                if not isinstance(image, (str, ImageObject)):
                    raise ValueError(
                        f"Expected image input is a path or PIL.Image, but got {type(image)}.")

                if isinstance(image, str):
                    image = Image.open(image).convert("RGB")

                multi_modal_data["image"].append(image)
        else:
            multi_modal_data = None
```

这里 可以参考vllm关于video的处理示例
https://github.com/vllm-project/vllm/blob/main/examples/offline_inference/vision_language.py
添加 video相关的处理

同时在 src/llamafactory/api/chat.py 的 _process_request 缺少对于 type=video_url 的视频类型参数处理
```python
for input_item in message.content:
                if input_item.type == "text":
                    input_messages.append(
                        {"role": ROLE_MAPPING[message.role], "content": input_item.text})
                else: # 这里缺少了 对 type = "video_url" 的类型处理
                    image_url = input_item.image_url.url
                    if re.match(r"^data:image\/(png|jpg|jpeg|gif|bmp);base64,(.+)$", image_url):  # base64 image
                        image_stream = io.BytesIO(base64.b64decode(image_url.split(",", maxsplit=1)[1]))
                    elif os.path.isfile(image_url):  # local file
                        image_stream = open(image_url, "rb")
                    else:  # web uri
                        image_stream = requests.get(image_url, stream=True).raw

                    images.append(Image.open(image_stream).convert("RGB"))
```

通过查阅vllm 的代码，我发现这里参考使用 vllm 库中的 fetch_video 来获取 视频的np.array

```python
from vllm.multimodal.utils import fetch_video
video_url = "http://commondatastorage.googleapis.com/gtv-videos-bucket/sample/ForBiggerFun.mp4"
video_np_array = fetch_video(video_url)
```


我也会同步在我的fork仓库里对视频信息的处理进行修改和测试～




### Others

_No response_

Labels: solved
State: closed
[Bug] 渠道自定义选anthropic的时候，能否增加深度思考开关？

### 📦 部署环境

Docker

### 📦 部署模式

服务端模式(lobe-chat-database 镜像)

### 📌 软件版本

1.68.5

### 💻 系统环境

Other Linux

### 🌐 浏览器

Firefox

### 🐛 问题描述

![Image](https://github.com/user-attachments/assets/fe5d89b5-542f-46f0-87b7-e9218b2ec313)
格式选择是anthropic。
开启联网后，选择第三方的thinking模型会出现这个错误，非thinking模型就不会出现。

### 📷 复现步骤

_No response_

### 🚦 期望结果

_No response_

### 📝 补充信息

_No response_

Labels: released
State: closed
[Bug] O1 will not work. stream_options error

### 📦 Platform

Official Preview

### 📦 Deploymenet mode

client db (lobe-chat image)

### 📌 Version

Web Version

### 💻 Operating System

Windows

### 🌐 Browser

Edge

### 🐛 Bug Description

This is the error I'm getting.
{
  "error": {
    "code": null,
    "type": "invalid_request_error",
    "param": "stream_options",
    "message": "The 'stream_options' parameter is only allowed when 'stream' is enabled."
  },
  "endpoint": "https://api.openai.com/v1",
  "provider": "openai"
}

o3 mini works fine. But o1, I can't get to work at all.

### 📷 Recurrence Steps

_No response_

### 🚦 Expected Behavior

_No response_

### 📝 Additional Information

_No response_

Labels: Inactive, released
State: closed
请求支持 qwen2-audio

### Reminder

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

### Description

请求支持 qwen2-audio

### Pull Request

请求支持 qwen2-audio

Labels: solved
State: closed
Is it possible change human input timeout in UserProxyAgent?

### What is the doc issue?


**Describe the issue**
Human input timeout is limit to 3 min!

**I want to change human input timeout in UserProxyAgent **

**Screenshots**
<img width="335" alt="Image" src="https://github.com/user-attachments/assets/bf0bb298-862f-448b-8ea8-84458a6c8798" />

**Additional context**


### Link to the doc page, if applicable

https://microsoft.github.io/autogen/stable/user-guide/autogenstudio-user-guide/usage.html

Labels: proj-studio
State: closed
`GraphFlowManager` should not let `_StopAgent` speak and apply termination if no more ready agent

`GraphFlowManager` should override `BaseGroupChatManager._apply_termination_condition` to first check if `self._ready` is empty. If it is empty, then the group chat should be terminated with the same stop message as the current `_DIGRAPH_STOP_AGENT_MESSAGE` and reset the execution state. 

We should also update `GraphFlow` to remove the `_StopAgent` and the use of `StopMessageTermination`, and relying on the above mechanism to terminate the group chat.

https://github.com/microsoft/autogen/blob/c23b9454a87d2d8e019154dc9fe37681634115d4/python/packages/autogen-agentchat/src/autogen_agentchat/teams/_group_chat/_graph/_digraph_group_chat.py#L782-L789

Also update `GraphFlowManager.select_spaker` as the execution state reset is going to be in `_apply_termination_condition`

Check the unit tests in `test_group_chat_graph.py` to ensure this behavior is updated. 

This change is to avoid the stop message from the `_StopAgent` polluting the context of other agents. 

State: closed
Thoughts are missing from api_response logs

### What happened?

The model's thoughts used to be logged as part of the _response_text_ , but they have been missing now. 

I did tests in different branches. For each branch, I ran the gemini cli in non-interactive mode and asked it to solve a task from swebench lite.  For each branch, I tested 20 tasks. 

For the branch **release/v0.1.18**, we still can see the thoughts present in the api response  for all the 20 noninteractive runs to solve the task (check example [here](https://gist.github.com/silviojr/c43eb145ed68ab35be7acbb9b565ad2d))  . Just look for the part where thought equals true (e.g. : \"thought\":true). 

For the main branch, the thoughts are not present in none of the 20 runs. Please check example [here](https://gist.github.com/silviojr/8908888d1f24d7fe8821d9a7ed6d2295). 



### What did you expect to happen?

I expected to see the thoughts present in the api response. This should be included, since the option is turned on: https://github.com/google-gemini/gemini-cli/blob/653267a64f8cd3b270176ec90b37a34383bf5bf2/packages/core/src/core/client.ts#L251 

The telemetry should log the raw response so we can study the agent's trajectory to improve its behavior. 


### Client information

<details>

I am running this using a command like: 

```
$> echo ' ' | npx --cache {temp_cache_dir} https://github.com/google-gemini/gemini-cli#{branch} --debug -y --telemetry --telemetry-otlp-endpoint=no --telemetry-target=local --telemetry-outfile={absolute_file_path} --sandbox=false --prompt {shlex.quote(prompt)}
```

</details>

### Login information

Using vertex

### Anything else we need to know?

_No response_

Labels: priority/p2
State: closed
[Request] 新增阿里云百炼的qwq-32b、qwq-plus等新模型

### 🥰 需求描述

请求新增阿里云百炼的以下新模型  [模型市场](https://bailian.console.aliyun.com/#/model-market)
qwq-32b
qwq-plus
qwq-plus-latest

### 🧐 解决方案

新增阿里云百炼的新模型

### 📝 补充信息

_No response_

Labels: released
State: closed
`providerOptions.stream_options` No Longer Effective in Latest SDK, Preventing Usage Data for DeepSeek/Volcengine

### Description

As suggested in issue #4929 (https://github.com/vercel/ai/issues/4929#issuecomment-2753145492), setting the custom parameter `stream_options` via `providerOptions` was the solution to correctly receive `usage` information when calling the DeepSeek API (Alibaba Cloud / Volcengine). This solution worked as recently as March.

However, after the merge of pull request #5873, `providerOptions.stream_options` is no longer effective. Consequently, even when setting `stream_options: { include_usage: true }`, the SDK fails to retrieve the correct `usage` data, which consistently returns as `null`.

**Steps to Reproduce**
1.  Use the latest versions of `ai-sdk` and `@ai-sdk/openai-compatible`.
2.  Pass `stream_options: { include_usage: true }` via `providerOptions`.
3.  Observe that the returned `usage` remains `null`.

**Expected Behavior**

We expect the ability to pass `stream_options` to the underlying request to be restored or provided via a new mechanism (either still within `providerOptions` or another parameter). This is essential to receive the `usage` information correctly.

*   Related Historical Issue: #4929
*   Related PR: #5873


### AI SDK Version

- ai: 4.3.16
- @ai-sdk/openai-compatible: 0.2.14


Labels: bug, ai/provider, provider/openai-compatible, provider/deepseek
State: closed
Template deepseekr1 does not exist

### Reminder

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

### System Info

![Image](https://github.com/user-attachments/assets/31e4373e-e9ec-49f8-a090-bdc986afbdcb)

It seems the template of "deepseekr1" can not be used (but it has been shown in the README).

### Reproduction

```text
Put your message here.
```


### Others

_No response_

Labels: solved
State: closed
[Request] 新增硅基流动的Qwen/QwQ-32B

### 🥰 需求描述

硅基流动上线了[Qwen/QwQ-32B](https://cloud.siliconflow.cn/models?mfs=QwQ)
需要新增该模型

### 🧐 解决方案

新增硅基流动的Qwen/QwQ-32B

### 📝 补充信息

_No response_

Labels: released
State: closed
[Request] 新增groq的qwen-qwq-32b模型

### 🥰 需求描述

新增groq的[新模型](https://console.groq.com/docs/models)
qwen-qwq-32b


### 🧐 解决方案

新增qwen-qwq-32b

### 📝 补充信息

_No response_

Labels: released
State: closed