alfin06/swegent-issues-filtered huggingface dataset:
Avoid throwing error on model mistakes in SelectorGroupChat builtin selector

To make it work better with local models and small models.

Labels: needs-triage, proj-agentchat
State: closed
[Bug] 不同用户登录看到的模型表现不同

### 📦 Environment

Docker

### 📌 Version

1.45.7

### 💻 Operating System

Ubuntu

### 🌐 Browser

Chrome

### 🐛 Bug Description

![image](https://github.com/user-attachments/assets/9887d02d-4497-4010-ad77-0c626a8fd468)
![image](https://github.com/user-attachments/assets/89de5a9e-a806-49e3-aabd-72950a1e403f)
不同用户登录看到的模型表现不同

### 📷 Recurrence Steps

一个账号是相对老的账号，一个账号是新建立的账号，模型参数是部署时输入的，修改.env之后 docker compose up -d，重启之后再建立新账户，两个账号看到的模型（虽然其实是一样的）是不一样的

### 🚦 Expected Behavior

_No response_

### 📝 Additional Information

_No response_

Labels: released
State: closed
[Bug] can't embed files to knowledge base

### 📦 Environment

Docker

### 📌 Version

1.46.3

### 💻 Operating System

macOS

### 🌐 Browser

Firefox

### 🐛 Bug Description

By default, lobechat uses OpenAI for embedding.

We do have a local AI running on a mac mini, with ollama. It works fine for chatting. But when we try another embedding model thru ollama (we pulled paraphrase-multilingual:latest), lobechat still thinks it should go thru OpenAI

on docker-compose .env file, we added:
`DEFAULT_FILES_CONFIG=embedding_model=ollama/paraphrase-multilingual:latest`

We're kinda lost on the chinese tutorials, but we know you need to add `"provider"/` before embedding model itself

But when we stop and run again, lobechat still tries to route thru openAI. here's the log:
`Route: [openai] InvalidProviderAPIKey: { error: undefined, errorType: 'InvalidProviderAPIKey' }`

Is there a way to embed files locally on lobechat? And if yes, can you point us to a tutorial? And if no, then it's def a bug.

Aside the cost, we don't want to use non-local options out of principle.

### 📷 Recurrence Steps

_No response_

### 🚦 Expected Behavior

_No response_

### 📝 Additional Information

_No response_

Labels: released, feature:files, provider:ollama
State: closed
gemini-2.0-flash-thinking-exp-1219 模型的回复异常

### 📦 Environment

Vercel, Netlify

### 📌 Version

1.45.11

### 💻 Operating System

Windows, Ubuntu

### 🌐 Browser

Chrome, Edge

### 🐛 Bug Description

1.45.11版本之后，即4d1a4cd800e05c488fbe4942bbfe8ef75eb5a914这个提交之后，vercel和netlify部署的 gemini-2.0-flash-thinking-exp-1219 模型，不能正常使用了。比如问一下“天空为什么是蓝色的”，回复只有一个单词，如“Thing”、“We”、“Let”，或者回复空白，部署该提交之前的版本则正常回复。

### 📷 Recurrence Steps

_No response_

### 🚦 Expected Behavior

_No response_

### 📝 Additional Information

_No response_

Labels: released, provider:gemini
State: closed
[Bug] Function calling and visual recognition became unavailable after only adjusting the model order.

### 📦 Environment

Docker

### 📌 Version

v1.46.6

### 💻 Operating System

Other Linux

### 🌐 Browser

Chrome

### 🐛 Bug Description

Function calling and visual recognition became unavailable after only adjusting the model order. Another user with the same version and without altering the model order did not experience any issues.
![Image](https://github.com/user-attachments/assets/0d937207-bed9-4dba-804b-d9b8c86de675)

### 📷 Recurrence Steps

_No response_

### 🚦 Expected Behavior

Fix this bug.

### 📝 Additional Information

_No response_

Labels: released, feature:vision
State: closed
KeyError: 'family' in OpenAIChatCompletionClient in v0.4.6

### What happened?

existing code:

```python
if isinstance(message, ToolCallRequestEvent):
              tool_result_message = ToolCallSummaryMessage(
                          content=str(response.chat_message.content),
                          source="tool"
                      )
              response = await agent.on_messages(messages=[tool_result_message], cancellation_token=cancellation_token)
              # handling sequential tool calls by sonnet. should work for openai as well
              my_count=0
              while True:
                if not isinstance(response.chat_message, ToolCallSummaryMessage):
                  break
                print("in while loop")
                tool_result_message = ToolCallSummaryMessage(
                          content=str(response.chat_message.content),
                          source="tool"
                      )
                response = await agent.on_messages(messages=[tool_result_message], cancellation_token=cancellation_token)

```

````
Result:
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
2025-02-11 18:07:22.014 PST
File "/layers/google.python.pip/pip/lib/python3.11/site-packages/autogen_agentchat/agents/_assistant_agent.py", line 369, in on_messages
2025-02-11 18:07:22.014 PST
async for message in self.on_messages_stream(messages, cancellation_token):
2025-02-11 18:07:22.014 PST
File "/layers/google.python.pip/pip/lib/python3.11/site-packages/autogen_agentchat/agents/_assistant_agent.py", line 415, in on_messages_stream
2025-02-11 18:07:22.014 PST
model_result = await self._model_client.create(
2025-02-11 18:07:22.014 PST
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
2025-02-11 18:07:22.014 PST
File "/layers/google.python.pip/pip/lib/python3.11/site-packages/autogen_ext/models/openai/_openai_client.py", line 621, in create
2025-02-11 18:07:22.014 PST
if isinstance(content, str) and self._model_info["family"] == ModelFamily.R1:
2025-02-11 18:07:22.014 PST
~~~~~~~~~~~~~~~~^^^^^^^^^^
2025-02-11 18:07:23.075 PST
KeyError: 'family'
2025-02-11 18:07:23.075 PST
Error: 'family'
2025-02-11 18:07:23.861 PST
POST2001.41 KB39.5 s
````

### What did you expect to happen?

Same code works well with version 0.4.4
autogen-agentchat==0.4.4
autogen-ext[openai]==0.4.4

### How can we reproduce it (as minimally and precisely as possible)?

just use 0.4.6 and see the code break for yourself!!

### AutoGen version

0.4.6

### Which package was this bug in

AgentChat

### Model used

anthropic/sonnet3.5

### Python version

3.12

### Operating system

_No response_

### Any additional info you think would be helpful for fixing this bug

_No response_

Labels: proj-extensions
State: closed
Deepseek v2.5的 template 变了，与 v2不同

### Reminder

- [X] I have read the README and searched the existing issues.

### System Info

无

### Reproduction

无

### Expected behavior

无

### Others

参考 [这里](https://huggingface.co/deepseek-ai/DeepSeek-V2.5)，类似这种

<｜begin▁of▁sentence｜>{system_message}<｜User｜>{user_message_1}<｜Assistant｜>{assistant_message_1}<｜end▁of▁sentence｜><｜User｜>{user_message_2}<｜Assistant｜>


Labels: solved
State: closed
how to use AgentInstantiationContext?

Let's add API doc for this usage. 

### Discussed in https://github.com/microsoft/autogen/discussions/5506

<div type='discussions-op-text'>

<sup>Originally posted by **bio-mlhui** February 11, 2025</sup>
I am using 0.4.6, I want the factory function to take runtime/agent_key as params, how to implement?</div>


Labels: needs-triage, proj-core
State: closed
[Request] 希望支持deepseek新模型deepseek-r1的api接口

### 🥰 需求描述

目前问题：
向api请求时返回
{
  "error": {
    "code": "invalid_request_error",
    "type": "invalid_request_error",
    "param": null,
    "message": "deepseek-reasoner does not support the parameter `presence_penalty`"
  },
  "endpoint": "https://api.deepseek.com/v1",
  "provider": "deepseek"
}


### 🧐 解决方案

可能是由于lobe请求自带presence_penalty等参数导致，删除后应该就可以了。

temperature、top_p、presence_penalty、frequency_penalty、logprobs、top_logprobs都不可以存在。

官方文档显示：

> API 参数
> 
>     输入参数：
>         max_tokens：最终回答的最大长度（不含思维链输出），默认为 4K，最大为 8K。请注意，思维链的输出最多可以达到 32K tokens，控思维链的长度的参数（reasoning_effort）将会在近期上线。
> 
>     输出字段：
>         reasoning_content：思维链内容，与 content 同级，访问方法见[访问样例](https://api-docs.deepseek.com/zh-cn/guides/reasoning_model#%E8%AE%BF%E9%97%AE%E6%A0%B7%E4%BE%8B)
>         content：最终回答内容
> 
>     上下文长度：API 最大支持 64K 上下文，输出的 reasoning_content 长度不计入 64K 上下文长度中
> 
>     支持的功能：[对话补全](https://api-docs.deepseek.com/zh-cn/api/create-chat-completion)，[对话前缀续写 (Beta)](https://api-docs.deepseek.com/zh-cn/guides/chat_prefix_completion)
> 
>     不支持的功能：Function Call、Json Output、FIM 补全 (Beta)
> 
>     不支持的参数：temperature、top_p、presence_penalty、frequency_penalty、logprobs、top_logprobs

### 📝 补充信息

无

Labels: released
State: closed
Make CodeExcutor and PythonCodeExecutorTool Seralizable

Make  [PythonCodeExecutionTool](https://github.com/microsoft/autogen/blob/main/python/packages/autogen-ext/src/autogen_ext/tools/code_execution/_code_execution.py) declarative so it can be used in AGS


Turns out this is a bit involved:

- Make CodeExecutor declarative (convert from Protocol to ABC, inherit from ComponentBase)
- Make LocalCommandLineExecuture (and all the other executors) declarative 
- Make PythonCodeExecutionTool declarative.

Labels: proj-agentchat
State: closed
[Request] 支持 DeepSeek-R1 模型，及其思考过程的展示

### 🥰 需求描述

DeepSeek-R1 的 API 支持 reasoning_content 字段来展示思维链内容。希望 lobechat 能够支持

### 🧐 解决方案

支持 reasoning_content 以不同的样式展示

### 📝 补充信息

_No response_

Labels: released
State: closed
LLaMa-factory 部署Llama-3.2-11B-Vision-Instruct  运行报错

### Reminder

- [X] I have read the README and searched the existing issues.

### System Info


- `llamafactory` version: 0.8.3.dev0
- Platform: Linux-6.8.0-40-generic-x86_64-with-glibc2.35
- Python version: 3.10.14
- PyTorch version: 2.3.0+cu121 (GPU)
- Transformers version: 4.42.3
- Datasets version: 2.20.0
- Accelerate version: 0.31.0
- PEFT version: 0.11.1
- TRL version: 0.9.4
- GPU type: NVIDIA GeForce RTX 4090 D
- vLLM version: 0.5.0.post1

### Reproduction

运行命令如下：
CUDA_VISIBLE_DEVICES=0 API_PORT=8005 nohup python src/api.py \
    --model_name_or_path /home/Llama-3.2/Llama-3.2-11B-Vision-Instruct \
    --template llama3\
    --infer_backend vllm \
    --vllm_maxlen 8000 \
     --vllm_gpu_util 0.8 \
    --vllm_enforce_eager true &

运行报错如下：[INFO|configuration_utils.py:731] 2024-09-26 13:55:31,084 >> loading configuration file /home/Llama-3.2/Llama-3.2-11B-Vision-Instruct/config.json
Traceback (most recent call last):
  File "/root/anaconda3/envs/LLaMA-Factory-main/lib/python3.10/site-packages/transformers/models/auto/configuration_auto.py", line 982, in from_pretrained
    config_class = CONFIG_MAPPING[config_dict["model_type"]]
  File "/root/anaconda3/envs/LLaMA-Factory-main/lib/python3.10/site-packages/transformers/models/auto/configuration_auto.py", line 684, in __getitem__
    raise KeyError(key)
KeyError: 'mllama'

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/home/LLaMA-Factory-main/src/api.py", line 33, in <module>
    main()
  File "/home/LLaMA-Factory-main/src/api.py", line 24, in main
    chat_model = ChatModel()
  File "/home/LLaMA-Factory-main/src/llamafactory/chat/chat_model.py", line 45, in __init__
    self.engine: "BaseEngine" = VllmEngine(model_args, data_args, finetuning_args, generating_args)
  File "/home/LLaMA-Factory-main/src/llamafactory/chat/vllm_engine.py", line 55, in __init__
    config = load_config(model_args)  # may download model from ms hub
  File "/home/LLaMA-Factory-main/src/llamafactory/model/loader.py", line 117, in load_config
    return AutoConfig.from_pretrained(model_args.model_name_or_path, **init_kwargs)
  File "/root/anaconda3/envs/LLaMA-Factory-main/lib/python3.10/site-packages/transformers/models/auto/configuration_auto.py", line 984, in from_pretrained
    raise ValueError(
ValueError: The checkpoint you are trying to load has model type `mllama` but Transformers does not recognize this architecture. This could be because of an issue with the checkpoint, or because your version of Transformers is out of date.

### Expected behavior

正确运行Llama-3.2-11B-Vision-Instruct 

### Others

_No response_

Labels: solved
State: closed
Document structured output for for AssistantAgent in its API doc, and note `strict=True` is required for FunctionTool

### What feature would you like to be added?

Current AssistantAgent does not support `response_format` for structured output.
`extra_create_args={
      "response_format": "Pydantic model",
  }
`
It would be perfect if `respose_format` can be supported by both `on_messages` and `on_messages_stream`. 

### Why is this needed?

 It is a good feature supported by many models to return structured output. It would simplify integration with other application in cases where predefined structures are expected from AssistantAgent.

It seems it is supported by `OpenAIChatCompletionClient`

Labels: documentation, proj-agentchat
State: closed
[Bug] Azure端点错误

### 📦 部署环境

Docker

### 📌 软件版本

v1.47.18

### 💻 系统环境

Windows

### 🌐 浏览器

Chrome

### 🐛 问题描述

使用了新的 AI服务商 页面后，之前设置过azure的相关配置，如今更换的端点 然后请求的模型还是之前设置的 

### 📷 复现步骤

_No response_

### 🚦 期望结果

_No response_

### 📝 补充信息

_No response_

Labels: released, provider:azure
State: closed
[Bug] LobeHub database version's ollama provider sends request to lobe's host instead of localhost by default

### 📦 部署环境

Docker

### 📌 软件版本

v1.47.21

### 💻 系统环境

macOS

### 🌐 浏览器

Chrome

### 🐛 问题描述

LobeHub database version's ollama provider sends requests to lobe's host instead of localhost by default. Checking passed, but it gets a `TypeError`.

<img width="742" alt="Image" src="https://github.com/user-attachments/assets/b522b937-ca03-48d0-aebe-85bb35e01afe" />

I have to manually assign `http://127.0.0.1:11434` to `Interface proxy address` to make it work.

I think the standalone version, which does not have database attached, works fine, and it show friendly guidance to help user setup Ollama server.

### 📷 复现步骤

1. enable ollama provider.
2. send request to ollama hosted model.

### 🚦 期望结果

1. send request to `http://127.0.0.1:11434` by default.
2. allow browser requesting.


### 📝 补充信息

_No response_

Labels: released, provider:ollama
State: closed
MessageRegistry should not buffer messages over a certain size or grow beyond a certain size

### What happened?

the buffering of messages in the Message registry is really useful, but it will not survive lots of very large messages. 

### What did you expect to happen?

need to put a cap on message size for the buffer and probably on total buffer size

### How can we reproduce it (as minimally and precisely as possible)?

send lots of very large messages

### AutoGen version

0.4.x

### Which package was this bug in

Core

### Model used

_No response_

### Python version

_No response_

### Operating system

_No response_

### Any additional info you think would be helpful for fixing this bug

_No response_

Labels: dotnet
State: closed
[Bug] Embeding failed in both OpenAI compatible API and Ollama API

### 🥰 Feature Description

Like the customize AI model providers, could you please support additional UI to expose ability to add custom embedding models?

A model like this would be much cheaper than OpenAI's model:
https://deepinfra.com/thenlper/gte-base/api

### 🧐 Proposed Solution

Alternative solution: add deepinfra's embedding API and make deepinfra one of the alternatives for embedding?

### 📝 Additional Information

Current embedding only support zhipu/github/openai/bedrock/ollama, which is limited.

Labels: released
State: closed
[Bug] Lobe does not support deep thinking feature for ollama deepseek r1 models

### 📦 Environment

Docker

### 📌 Version

v1.48.0

### 💻 Operating System

macOS

### 🌐 Browser

Chrome

### 🐛 Bug Description

When running [deepseek-r1:8b](https://ollama.com/library/deepseek-r1) via Ollama, Lobe displays the \<think\> tag in text instead of prompting the `deep thinking` feature as it did when calling the official DeepSeek API. Additionally, there is a padding issue at the top of the message box when displaying the \<think\> tag, see it in the screenshot.

<img width="1039" alt="Image" src="https://github.com/user-attachments/assets/17203e1b-5b03-43f0-863c-104233f49734" />

### 📷 Recurrence Steps

_No response_

### 🚦 Expected Behavior

_No response_

### 📝 Additional Information

_No response_

Labels: released, provider:ollama
State: closed
Make FileSurfer support component config serialization

### What happened?

MagenticOneGroupChat with 

    file_surfer = FileSurfer(
        name="file_surfer",
        model_client=model_client,
        description="Please scan the current folder ./data and preview the file contents.",
        #handoffs=["success_agent"],  # Handoff to the assistant agent after file selection
    )

    team = MagenticOneGroupChat([file_surfer], 
                                termination_condition=termination, 
                                max_turns=1,
                                model_client=model_client)

c:\Code\autogenstudio\autogenstudiocode\.venv\Lib\site-packages\autogen_agentchat\teams\_group_chat\_magentic_one\_magentic_one_group_chat.py:139: UserWarning: Internal module name used in provider string. This is not recommended and may cause issues in the future. Silence this warning by setting component_provider_override to this value.
  participants = [participant.dump_component() for participant in self._participants]
Traceback (most recent call last):
  File "C:\Code\autogenstudio\autogenstudiocode\magenticfile.py", line 313, in <module>
    serialized = team.dump_component().model_dump(mode='python')
                 ~~~~~~~~~~~~~~~~~~~^^
  File "c:\Code\autogenstudio\autogenstudiocode\.venv\Lib\site-packages\autogen_core\_component_config.py", line 150, in dump_component
    obj_config = self._to_config().model_dump(exclude_none=True)
                 ~~~~~~~~~~~~~~~^^
  File "c:\Code\autogenstudio\autogenstudiocode\.venv\Lib\site-packages\autogen_agentchat\teams\_group_chat\_magentic_one\_magentic_one_group_chat.py", line 139, in _to_config
    participants = [participant.dump_component() for participant in self._participants]
                    ~~~~~~~~~~~~~~~~~~~~~~~~~~^^
  File "c:\Code\autogenstudio\autogenstudiocode\.venv\Lib\site-packages\autogen_core\_component_config.py", line 150, in dump_component
    obj_config = self._to_config().model_dump(exclude_none=True)
                 ~~~~~~~~~~~~~~~^^
  File "c:\Code\autogenstudio\autogenstudiocode\.venv\Lib\site-packages\autogen_core\_component_config.py", line 114, in _to_config
    raise NotImplementedError("This component does not support dumping to config")
NotImplementedError: This component does not support dumping to config
C:\Program Files\WindowsApps\PythonSoftwareFoundation.Python.3.13_3.13.752.0_x64__qbz5n2kfra8p0\Lib\asyncio\proactor_events.py:116: ResourceWarning: unclosed transport <_ProactorSocketTransport fd=868 read=<_OverlappedFuture cancelled>>

### What did you expect to happen?

https://github.com/balakreshnan/Samples2025/blob/main/autogen/autogenmagenticfilesurfer.md

### How can we reproduce it (as minimally and precisely as possible)?

https://github.com/balakreshnan/Samples2025/blob/main/autogen/autogenmagenticfilesurfer.md

### AutoGen version

0.4.7

### Which package was this bug in

Core

### Model used

_No response_

### Python version

3.13

### Operating system

_No response_

### Any additional info you think would be helpful for fixing this bug

_No response_

Labels: proj-agentchat, proj-magentic-one
State: closed
AgentChat ChainLit sample to display name of agents in teams

### What feature would you like to be added?

Kindly provision for adding names of agents displaying messages in chainlit sample 
https://github.com/microsoft/autogen/blob/a0e3a1208cddf9e6f74f2596a492f65ac5213995/python/samples/agentchat_chainlit/README.md#L4

### Why is this needed?

For clarity on which agent is sharing the message. Currently just messages going back and forth , no clarity on name of agent communicating in chat

Labels: documentation, good first issue, proj-agentchat
State: closed
[Bug] deepseek模型 Ollama模式 问答第一行只能显示一半  回答途中点击停止也没反应

### 📦 部署环境

Docker

### 📌 软件版本

v1.49.4

### 💻 系统环境

Other Linux

### 🌐 浏览器

Chrome

### 🐛 问题描述

https://i.miji.bid/2025/01/28/d7186a8781d6b93791600e25877c00d8.png  deepseek模型 Ollama模式 问答第一行只能显示一半  回答途中点击停止也没反应

### 📷 复现步骤

deepseek模型 Ollama模式 问答第一行只能显示一半  回答途中点击停止也没反应

### 🚦 期望结果

第一行显示全,中途点击停止能正确反应

### 📝 补充信息

_No response_

Labels: released, provider:ollama
State: closed
[Bug] 关闭模型后 function/vision 设置被遗忘

### 📦 部署环境

Vercel

### 📌 软件版本

latest

### 💻 系统环境

Windows

### 🌐 浏览器

Chrome

### 🐛 问题描述

对于新版模型提供商设置页（settings/provider），若从“已启用”中关闭一个模型，模型自带的 function/vision 等不会保留。

如果手动在设置页配置过模型信息，则会保存。

![Image](https://github.com/user-attachments/assets/67aed781-927c-4421-bfd2-4498edff7d09)

![Image](https://github.com/user-attachments/assets/4ea35878-7220-4472-a6d0-6bcf86c11e89)

怀疑相关问题 #5489 


### 📝 补充信息

祝各位开发者新年快乐！

Labels: released, feature:vision
State: closed
[Bug] Unable to engage in more than two rounds of conversation with Deepseeker R1

### 📦 Environment

Docker

### 📌 Version

v1.49.5

### 💻 Operating System

Windows

### 🌐 Browser

Chrome

### 🐛 Bug Description

When there are more than one message, using deepseek-r1 will report the following error:

{
  "error": {
    "code": "invalid_request_error",
    "type": "invalid_request_error",
    "param": null,
    "message": "The first message (except the system message) of deepseek-reasoner must be a user message, but an assistant message detected."
  },
  "endpoint": "https://api.deepseek.com/v1",
  "provider": "deepseek"
}

### 📷 Recurrence Steps

Sending more than two messages

### 🚦 Expected Behavior

Reply normally

### 📝 Additional Information

_No response_

Labels: released
State: closed
Support visualization of model streaming chunks in AutoGen Studio

Agentchat now supports streaming of tokens via `ModelClientStreamingChunkEvent `. This PR is to track progress on supporting that in the AutoGen Studio UI. 

## What 
- Verify declarative support for streaming chunks in AGS 
- update backend to handle `ModelClientStreamingChunkEvent` (do not save it)
- update fronted UI to appropriately display `ModelClientStreamingChunkEvent`

Labels: proj-studio
State: closed
HttpTool does not use the provided headers in requests

### What happened?

**Describe the bug**

The HttpTool in AutoGen accepts a headers parameter, but it is not being used in the request. This means that even if users provide headers, they do not take effect in HTTP requests.

To Reproduce
Steps to reproduce the behavior:

Create an instance of HttpTool with custom headers.

Make a request using the tool.

Observe that the headers are not included in the actual request.

Example code:
**To Reproduce**

```
from autogen_ext.tools.http import HttpTool

tool = HttpTool(
    name="test_tool",
    description="description",
    method="GET",
    url="https://httpbin.org/get",
    headers={"Authorization": "Bearer test_token"},
    return_type="text",
)

response = tool()
print(response)
```

**Expected behavior**
A clear and concise description of what you expected to happen.

Expected request with headers
```
{
    "headers": {
        "Authorization": "Bearer test_token",
        ...
    }
}
```

**Screenshots**
If applicable, add screenshots to help explain your problem.

**Additional context**
Add any other context about the problem here.


### 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: proj-extensions
State: closed
[Request] 硅基流动siliconflow已经上线Deepseek-R1，需要适配

### 🥰 需求描述

![Image](https://github.com/user-attachments/assets/7f9378c7-6766-45d6-abea-f6292ce31428)

2025/2/1凌晨（中国时间） siliconflow已经上线Deepseek-v1，需要适配其定价与思考中显示

### 🧐 解决方案

尽快适配

### 📝 补充信息

_No response_

Labels: released
State: closed