50 KiB
50 KiB
记录 ReMe 容器化部署踩的坑
- Github：https://github.com/agentscope-ai/ReMe
- Release：https://github.com/agentscope-ai/ReMe/releases
- 使用的版本：https://github.com/agentscope-ai/ReMe/releases/tag/v0.3.1.8
- 快速上手：https://github.com/agentscope-ai/ReMe/blob/v0.3.1.8/docs/quick_start.md
Dockerfile
FROM ubuntu:24.04
# 1. 更换为中科大 (USTC) 源
# Ubuntu 24.04 使用 DEB822 格式，配置文件在 /etc/apt/sources.list.d/ubuntu.sources
# 我们需要将 URIs 字段中的默认地址替换为中科大镜像地址
RUN sed -i 's|http://archive.ubuntu.com/ubuntu|http://mirrors.ustc.edu.cn/ubuntu|g' /etc/apt/sources.list.d/ubuntu.sources && \
sed -i 's|http://security.ubuntu.com/ubuntu|http://mirrors.ustc.edu.cn/ubuntu|g' /etc/apt/sources.list.d/ubuntu.sources
ENV DEBIAN_FRONTEND=noninteractive \
TZ=Asia/Shanghai
# 2. 安装基础依赖
RUN apt-get update && apt-get install -y \
locales \
tzdata \
ca-certificates \
python3 \
python3-venv \
python3-pip \
&& rm -rf /var/lib/apt/lists/*
# 3. 设置语言环境
RUN locale-gen zh_CN.UTF-8 en_US.UTF-8
ENV LANG=zh_CN.UTF-8 \
LANGUAGE=zh_CN:zh \
LC_ALL=zh_CN.UTF-8
# 4. 设置时区
RUN ln -sf /usr/share/zoneinfo/Asia/Shanghai /etc/localtime && \
dpkg-reconfigure -f noninteractive tzdata
WORKDIR /opt
# 5. 复制项目文件
COPY ReMe-0.3.1.8 ./reme
# 6. 创建虚拟环境并安装依赖
RUN cd reme \
&& python3 -m venv .venv \
&& .venv/bin/pip install --no-cache-dir --upgrade pip \
&& .venv/bin/pip install --no-cache-dir -e ".[light]"
# 7. 设置环境变量
ENV PATH="/opt/reme/.venv/bin:$PATH"
WORKDIR /opt/reme
docker-compose.yaml
services:
reme:
image: reme:0.3.1.8
container_name: reme
restart: on-failure:3
volumes:
- ./local_vector_store:/opt/reme/local_vector_store
- ./.env:/opt/reme/.env
ports:
- "28202:28202"
command: [
"reme",
"http.port=28202",
"llm.default.model_name=qwen2.5",
"embedding_model.default.model_name=bge-m3",
"vector_store.default.backend=local"
]
.env 文件的内容
LLM_API_KEY=sk-***
LLM_BASE_URL=http://IP:PORT/v1
EMBEDDING_API_KEY=sk-***
EMBEDDING_BASE_URL=http://IP:PORT/v1
通过 agentscope-java 构建的 demo
package ai.agentscope.example.memory;
import ai.agentscope.example.conf.LlmConfig;
import cn.hutool.core.date.DatePattern;
import cn.hutool.core.util.StrUtil;
import io.agentscope.core.ReActAgent;
import io.agentscope.core.memory.LongTermMemoryMode;
import io.agentscope.core.memory.reme.ReMeLongTermMemory;
import io.agentscope.core.message.Msg;
import io.agentscope.core.message.MsgRole;
import lombok.RequiredArgsConstructor;
import org.springframework.beans.factory.annotation.Value;
import org.springframework.boot.CommandLineRunner;
import org.springframework.boot.autoconfigure.condition.ConditionalOnBooleanProperty;
import org.springframework.stereotype.Component;
import java.time.LocalDateTime;
import java.util.Optional;
import java.util.Scanner;
@Component
@ConditionalOnBooleanProperty(value = "ENABLE_RE_ME_TEST")
@RequiredArgsConstructor
public class ReMeMemoryCmdRunner implements CommandLineRunner {
private final LlmConfig llmConfig;
@Value("${RE_ME_BASE_URL}")
private String longTermMemoryBaseUrl;
@Override
public void run(String... args) throws Exception {
System.out.println("-".repeat(40));
System.out.printf("Start %s%n", this.getClass().getSimpleName());
System.out.println("-".repeat(40));
Scanner scanner = new Scanner(System.in);
for (; ; ) {
System.out.print(">>>You：");
String input = scanner.nextLine();
if (StrUtil.isBlank(input)) {
continue;
}
if ("q".equals(input) || "exit".equals(input)) {
break;
}
Msg assistantMsg = this.agent().call(this.readUserMsg(input)).block();
System.out.printf("""
>>>LLM：
%s
%n""", Optional.ofNullable(assistantMsg).map(Msg::getTextContent).orElse("没有获取到任何输出"));
}
}
private Msg readUserMsg(String input) {
return Msg.builder()
.timestamp(LocalDateTime.now().format(DatePattern.PURE_DATETIME_MS_FORMATTER))
.role(MsgRole.USER)
.textContent(input)
.build();
}
private ReActAgent agent() {
return ReActAgent.builder()
.name("ReMeMemoryAgent")
.model(llmConfig.model())
.longTermMemory(this.longTermMemory())
.longTermMemoryMode(LongTermMemoryMode.STATIC_CONTROL)
.build();
}
private ReMeLongTermMemory longTermMemory() {
return ReMeLongTermMemory.builder()
.userId("example_user_id")
.apiBaseUrl(this.longTermMemoryBaseUrl)
.build();
}
}
对话时观测到 reme 容器抛出异常堆栈，核心异常堆栈信息如下
2026-04-07 15:56:51 | ERROR | base_embedding_model.py:126 | embedding model name=bge-negative-train encounter error with e=('Connection error.',)
[33m[1mTraceback (most recent call last):[0m
File "/opt/reme/.venv/lib/python3.12/site-packages/httpx/_transports/default.py", line 101, in map_httpcore_exceptions
yield
File "/opt/reme/.venv/lib/python3.12/site-packages/httpx/_transports/default.py", line 394, in handle_async_request
resp = await self._pool.handle_async_request(req)
│ │ │ └ <Request [b'POST']>
│ │ └ <function AsyncConnectionPool.handle_async_request at 0x72074ae19c60>
│ └ <AsyncConnectionPool [Requests: 0 active, 0 queued | Connections: 0 active, 0 idle]>
└ <httpx.AsyncHTTPTransport object at 0x72074aebf6e0>
File "/opt/reme/.venv/lib/python3.12/site-packages/httpcore/_async/connection_pool.py", line 207, in handle_async_request
raise UnsupportedProtocol(
└ <class 'httpcore.UnsupportedProtocol'>
[31m[1mhttpcore.UnsupportedProtocol[0m:[1m Request URL is missing an 'http://' or 'https://' protocol.[0m
[1mThe above exception was the direct cause of the following exception:[0m
[33m[1mTraceback (most recent call last):[0m
File "/opt/reme/.venv/lib/python3.12/site-packages/openai/_base_client.py", line 1604, in request
response = await self._client.send(
│ │ └ <function AsyncClient.send at 0x72075ed6e2a0>
│ └ <openai._base_client.AsyncHttpxClientWrapper object at 0x72074af718b0>
└ <openai.AsyncOpenAI object at 0x72074afb1160>
File "/opt/reme/.venv/lib/python3.12/site-packages/httpx/_client.py", line 1629, in send
response = await self._send_handling_auth(
│ └ <function AsyncClient._send_handling_auth at 0x72075ed6e340>
└ <openai._base_client.AsyncHttpxClientWrapper object at 0x72074af718b0>
File "/opt/reme/.venv/lib/python3.12/site-packages/httpx/_client.py", line 1657, in _send_handling_auth
response = await self._send_handling_redirects(
│ └ <function AsyncClient._send_handling_redirects at 0x72075ed6e3e0>
└ <openai._base_client.AsyncHttpxClientWrapper object at 0x72074af718b0>
File "/opt/reme/.venv/lib/python3.12/site-packages/httpx/_client.py", line 1694, in _send_handling_redirects
response = await self._send_single_request(request)
│ │ └ <Request('POST', '/embeddings')>
│ └ <function AsyncClient._send_single_request at 0x72075ed6e480>
└ <openai._base_client.AsyncHttpxClientWrapper object at 0x72074af718b0>
File "/opt/reme/.venv/lib/python3.12/site-packages/httpx/_client.py", line 1730, in _send_single_request
response = await transport.handle_async_request(request)
│ │ └ <Request('POST', '/embeddings')>
│ └ <function AsyncHTTPTransport.handle_async_request at 0x72075ed53100>
└ <httpx.AsyncHTTPTransport object at 0x72074aebf6e0>
File "/opt/reme/.venv/lib/python3.12/site-packages/httpx/_transports/default.py", line 393, in handle_async_request
with map_httpcore_exceptions():
└ <function map_httpcore_exceptions at 0x72075ed52700>
File "/usr/lib/python3.12/contextlib.py", line 158, in __exit__
self.gen.throw(value)
│ │ │ └ UnsupportedProtocol("Request URL is missing an 'http://' or 'https://' protocol.")
│ │ └ <method 'throw' of 'generator' objects>
│ └ <generator object map_httpcore_exceptions at 0x720742fc8740>
└ <contextlib._GeneratorContextManager object at 0x720742fcce30>
File "/opt/reme/.venv/lib/python3.12/site-packages/httpx/_transports/default.py", line 118, in map_httpcore_exceptions
raise mapped_exc(message) from exc
│ └ "Request URL is missing an 'http://' or 'https://' protocol."
└ <class 'httpx.UnsupportedProtocol'>
[31m[1mhttpx.UnsupportedProtocol[0m:[1m Request URL is missing an 'http://' or 'https://' protocol.[0m
[1mThe above exception was the direct cause of the following exception:[0m
[33m[1mTraceback (most recent call last):[0m
File "/opt/reme/.venv/bin/reme", line 6, in <module>
sys.exit(main())
│ │ └ <function main at 0x72074b0089a0>
│ └ <built-in function exit>
└ <module 'sys' (built-in)>
File "[32m/opt/reme/reme_ai/[0m[32m[1mmain.py[0m", line [33m231[0m, in [35mmain[0m
[1mapp[0m[35m[1m.[0m[1mrun_service[0m[1m([0m[1m)[0m
[36m│ └ [0m[36m[1m<function Application.run_service at 0x72074b009580>[0m
[36m└ [0m[36m[1m<reme_ai.main.ReMeApp object at 0x720760696a50>[0m
File "/opt/reme/.venv/lib/python3.12/site-packages/flowllm/core/application.py", line 384, in run_service
service.run()
│ └ <function HttpService.run at 0x72074c0d7e20>
└ <flowllm.core.service.http_service.HttpService object at 0x72074af46750>
File "/opt/reme/.venv/lib/python3.12/site-packages/flowllm/core/service/http_service.py", line 123, in run
uvicorn.run(
│ └ <function run at 0x72075e2ddb20>
└ <module 'uvicorn' from '/opt/reme/.venv/lib/python3.12/site-packages/uvicorn/__init__.py'>
File "/opt/reme/.venv/lib/python3.12/site-packages/uvicorn/main.py", line 606, in run
server.run()
│ └ <function Server.run at 0x72075e2ddee0>
└ <uvicorn.server.Server object at 0x72074abbb650>
File "/opt/reme/.venv/lib/python3.12/site-packages/uvicorn/server.py", line 75, in run
return asyncio_run(self.serve(sockets=sockets), loop_factory=self.config.get_loop_factory())
│ │ │ │ │ │ └ <function Config.get_loop_factory at 0x72075e2dd8a0>
│ │ │ │ │ └ <uvicorn.config.Config object at 0x72074aebe060>
│ │ │ │ └ <uvicorn.server.Server object at 0x72074abbb650>
│ │ │ └ None
│ │ └ <function Server.serve at 0x72075e2ddf80>
│ └ <uvicorn.server.Server object at 0x72074abbb650>
└ <function run at 0x72075fd55ee0>
File "/usr/lib/python3.12/asyncio/runners.py", line 194, in run
return runner.run(main)
│ │ └ <coroutine object Server.serve at 0x72074ac1c200>
│ └ <function Runner.run at 0x72075fda3880>
└ <asyncio.runners.Runner object at 0x72074af47d40>
File "/usr/lib/python3.12/asyncio/runners.py", line 118, in run
return self._loop.run_until_complete(task)
│ │ │ └ <Task pending name='Task-4' coro=<Server.serve() running at /opt/reme/.venv/lib/python3.12/site-packages/uvicorn/server.py:79...
│ │ └ <cyfunction Loop.run_until_complete at 0x72074aba9300>
│ └ <uvloop.Loop running=True closed=False debug=False>
└ <asyncio.runners.Runner object at 0x72074af47d40>
File "/opt/reme/.venv/lib/python3.12/site-packages/flowllm/core/op/base_async_op.py", line 185, in async_call
result = await self.async_execute()
│ └ <function LoadTodayMemoryOp.async_execute at 0x72074ae345e0>
└ <reme_ai.summary.personal.load_today_memory_op.LoadTodayMemoryOp object at 0x72074a94ac60>
File "[32m/opt/reme/reme_ai/summary/personal/[0m[32m[1mload_today_memory_op.py[0m", line [33m49[0m, in [35masync_execute[0m
[1mtoday_memories[0m [35m[1m=[0m [35m[1mawait[0m [1mself[0m[35m[1m.[0m[1m_retrieve_today_memories[0m[1m([0m[1mworkspace_id[0m[1m,[0m [1muser_name[0m[1m,[0m [1mtop_k[0m[1m)[0m
[36m │ │ │ │ └ [0m[36m[1m50[0m
[36m │ │ │ └ [0m[36m[1m'user'[0m
[36m │ │ └ [0m[36m[1m'example_user_id'[0m
[36m │ └ [0m[36m[1m<function LoadTodayMemoryOp._retrieve_today_memories at 0x72074ae34680>[0m
[36m └ [0m[36m[1m<reme_ai.summary.personal.load_today_memory_op.LoadTodayMemoryOp object at 0x72074a94ac60>[0m
File "[32m/opt/reme/reme_ai/summary/personal/[0m[32m[1mload_today_memory_op.py[0m", line [33m87[0m, in [35m_retrieve_today_memories[0m
[1mnodes[0m[1m:[0m [1mList[0m[1m[[0m[1mVectorNode[0m[1m][0m [35m[1m=[0m [35m[1mawait[0m [1mself[0m[35m[1m.[0m[1mvector_store[0m[35m[1m.[0m[1masync_search[0m[1m([0m
[36m │ │ │ └ [0m[36m[1m<property object at 0x72074c304b80>[0m
[36m │ │ └ [0m[36m[1m<reme_ai.summary.personal.load_today_memory_op.LoadTodayMemoryOp object at 0x72074a94ac60>[0m
[36m │ └ [0m[36m[1m<class 'flowllm.core.schema.vector_node.VectorNode'>[0m
[36m └ [0m[36m[1mtyping.List[0m
File "/opt/reme/.venv/lib/python3.12/site-packages/flowllm/core/vector_store/local_vector_store.py", line 512, in async_search
return await super().async_search(query, workspace_id, top_k, filter_dict, **kwargs)
│ │ │ │ └ {}
│ │ │ └ {'memory_type': 'personal', 'target': 'user', 'created_date': '20260407'}
│ │ └ 50
│ └ 'example_user_id'
└ ' '
File "/opt/reme/.venv/lib/python3.12/site-packages/flowllm/core/vector_store/memory_vector_store.py", line 673, in async_search
query_vector = await self.async_get_embeddings(query) if use_vector_search else None
│ │ │ └ True
│ │ └ ' '
│ └ <function BaseVectorStore.async_get_embeddings at 0x72074c2c04a0>
└ <flowllm.core.vector_store.local_vector_store.LocalVectorStore object at 0x72074af73980>
File "/opt/reme/.venv/lib/python3.12/site-packages/flowllm/core/vector_store/base_vector_store.py", line 123, in async_get_embeddings
return await self.embedding_model.async_get_embeddings(query)
│ │ │ └ ' '
│ │ └ <function BaseEmbeddingModel.async_get_embeddings at 0x72075d257e20>
│ └ <flowllm.core.embedding_model.openai_compatible_embedding_model.OpenAICompatibleEmbeddingModel object at 0x72074c324f20>
└ <flowllm.core.vector_store.local_vector_store.LocalVectorStore object at 0x72074af73980>
> File "/opt/reme/.venv/lib/python3.12/site-packages/flowllm/core/embedding_model/base_embedding_model.py", line 123, in async_get_embeddings
return await self._async_get_embeddings(input_text)
│ │ └ ' '
│ └ <function OpenAICompatibleEmbeddingModel._async_get_embeddings at 0x72075cbb0400>
└ <flowllm.core.embedding_model.openai_compatible_embedding_model.OpenAICompatibleEmbeddingModel object at 0x72074c324f20>
File "/opt/reme/.venv/lib/python3.12/site-packages/flowllm/core/embedding_model/openai_compatible_embedding_model.py", line 124, in _async_get_embeddings
completion = await self._async_client.embeddings.create(
│ │ │ └ <function AsyncEmbeddings.create at 0x7207482b5440>
│ │ └ <openai.resources.embeddings.AsyncEmbeddings object at 0x72074ae0f980>
│ └ <openai.AsyncOpenAI object at 0x72074afb1160>
└ <flowllm.core.embedding_model.openai_compatible_embedding_model.OpenAICompatibleEmbeddingModel object at 0x72074c324f20>
File "/opt/reme/.venv/lib/python3.12/site-packages/openai/resources/embeddings.py", line 259, in create
return await self._post(
│ └ <bound method AsyncAPIClient.post of <openai.AsyncOpenAI object at 0x72074afb1160>>
└ <openai.resources.embeddings.AsyncEmbeddings object at 0x72074ae0f980>
File "/opt/reme/.venv/lib/python3.12/site-packages/openai/_base_client.py", line 1884, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
│ │ │ │ │ └ None
│ │ │ │ └ False
│ │ │ └ FinalRequestOptions(method='post', url='/embeddings', params={}, headers=NOT_GIVEN, max_retries=NOT_GIVEN, timeout=NOT_GIVEN,...
│ │ └ <class 'openai.types.create_embedding_response.CreateEmbeddingResponse'>
│ └ <function AsyncAPIClient.request at 0x72075cc47e20>
└ <openai.AsyncOpenAI object at 0x72074afb1160>
File "/opt/reme/.venv/lib/python3.12/site-packages/openai/_base_client.py", line 1636, in request
raise APIConnectionError(request=request) from err
│ └ <Request('POST', '/embeddings')>
└ <class 'openai.APIConnectionError'>
[31m[1mopenai.APIConnectionError[0m:[1m Connection error.[0m
2026-04-07 15:56:51 | ERROR | load_today_memory_op.py:103 | Error retrieving today's memories: Connection error.
** 问题源头 **：FlowLLM 的 openai_compatible_embedding_model.py 脚本中使用的环境变量是写死的
self.api_key = api_key or os.getenv("FLOW_EMBEDDING_API_KEY", "")
self.base_url = base_url or os.getenv("FLOW_EMBEDDING_BASE_URL", "")
** 修复方案 **：在 .env 文件添加正确的环境变量
LLM_API_KEY=sk-***
LLM_BASE_URL=http://IP:PORT/v1
EMBEDDING_API_KEY=sk-***
EMBEDDING_BASE_URL=http://IP:PORT/v1
FLOW_EMBEDDING_API_KEY=sk-***
FLOW_EMBEDDING_BASE_URL=http://IP:PORT/v1
FLOW_LLM_API_KEY=sk-***
FLOW_LLM_BASE_URL=http://IP:PORT/v1
再次发起调用出现以下异常堆栈
2026-04-08 10:33:27 | ERROR | base_embedding_model.py:126 | embedding model name=bge-m3 encounter error with e=('Error code: 400 - {\'error\': {\'message\': \'Model "bge-m3" does not support matryoshka representation, changing output dimensions will lead to poor results.\', \'type\': \'BadRequestError\', \'param\': \'\', \'code\': 400}}',)
[33m[1mTraceback (most recent call last):[0m
File "/opt/reme/.venv/bin/reme", line 6, in <module>
sys.exit(main())
│ │ └ <function main at 0x73b6151dc9a0>
│ └ <built-in function exit>
└ <module 'sys' (built-in)>
File "[32m/opt/reme/reme_ai/[0m[32m[1mmain.py[0m", line [33m231[0m, in [35mmain[0m
[1mapp[0m[35m[1m.[0m[1mrun_service[0m[1m([0m[1m)[0m
[36m│ └ [0m[36m[1m<function Application.run_service at 0x73b6151dd580>[0m
[36m└ [0m[36m[1m<reme_ai.main.ReMeApp object at 0x73b62a862b70>[0m
File "/opt/reme/.venv/lib/python3.12/site-packages/flowllm/core/application.py", line 384, in run_service
service.run()
│ └ <function HttpService.run at 0x73b6162abe20>
└ <flowllm.core.service.http_service.HttpService object at 0x73b6281913d0>
File "/opt/reme/.venv/lib/python3.12/site-packages/flowllm/core/service/http_service.py", line 123, in run
uvicorn.run(
│ └ <function run at 0x73b6284a5b20>
└ <module 'uvicorn' from '/opt/reme/.venv/lib/python3.12/site-packages/uvicorn/__init__.py'>
File "/opt/reme/.venv/lib/python3.12/site-packages/uvicorn/main.py", line 606, in run
server.run()
│ └ <function Server.run at 0x73b6284a5ee0>
└ <uvicorn.server.Server object at 0x73b614d549b0>
File "/opt/reme/.venv/lib/python3.12/site-packages/uvicorn/server.py", line 75, in run
return asyncio_run(self.serve(sockets=sockets), loop_factory=self.config.get_loop_factory())
│ │ │ │ │ │ └ <function Config.get_loop_factory at 0x73b6284a58a0>
│ │ │ │ │ └ <uvicorn.config.Config object at 0x73b614d8fcb0>
│ │ │ │ └ <uvicorn.server.Server object at 0x73b614d549b0>
│ │ │ └ None
│ │ └ <function Server.serve at 0x73b6284a5f80>
│ └ <uvicorn.server.Server object at 0x73b614d549b0>
└ <function run at 0x73b629f21ee0>
File "/usr/lib/python3.12/asyncio/runners.py", line 194, in run
return runner.run(main)
│ │ └ <coroutine object Server.serve at 0x73b614bf82e0>
│ └ <function Runner.run at 0x73b629f6f880>
└ <asyncio.runners.Runner object at 0x73b614d8cd70>
File "/usr/lib/python3.12/asyncio/runners.py", line 118, in run
return self._loop.run_until_complete(task)
│ │ │ └ <Task pending name='Task-4' coro=<Server.serve() running at /opt/reme/.venv/lib/python3.12/site-packages/uvicorn/server.py:79...
│ │ └ <cyfunction Loop.run_until_complete at 0x73b614d81300>
│ └ <uvloop.Loop running=True closed=False debug=False>
└ <asyncio.runners.Runner object at 0x73b614d8cd70>
> File "/opt/reme/.venv/lib/python3.12/site-packages/flowllm/core/embedding_model/base_embedding_model.py", line 123, in async_get_embeddings
return await self._async_get_embeddings(input_text)
│ │ └ ['Xiao Bai, 29, apples, Hami melons']
│ └ <function OpenAICompatibleEmbeddingModel._async_get_embeddings at 0x73b626d7c400>
└ <flowllm.core.embedding_model.openai_compatible_embedding_model.OpenAICompatibleEmbeddingModel object at 0x73b6153c5d90>
File "/opt/reme/.venv/lib/python3.12/site-packages/flowllm/core/embedding_model/openai_compatible_embedding_model.py", line 124, in _async_get_embeddings
completion = await self._async_client.embeddings.create(
│ │ │ └ <function AsyncEmbeddings.create at 0x73b611c89440>
│ │ └ <openai.resources.embeddings.AsyncEmbeddings object at 0x73b614c7a900>
│ └ <openai.AsyncOpenAI object at 0x73b61517d070>
└ <flowllm.core.embedding_model.openai_compatible_embedding_model.OpenAICompatibleEmbeddingModel object at 0x73b6153c5d90>
File "/opt/reme/.venv/lib/python3.12/site-packages/openai/resources/embeddings.py", line 259, in create
return await self._post(
│ └ <bound method AsyncAPIClient.post of <openai.AsyncOpenAI object at 0x73b61517d070>>
└ <openai.resources.embeddings.AsyncEmbeddings object at 0x73b614c7a900>
File "/opt/reme/.venv/lib/python3.12/site-packages/openai/_base_client.py", line 1884, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
│ │ │ │ │ └ None
│ │ │ │ └ False
│ │ │ └ FinalRequestOptions(method='post', url='/embeddings', params={}, headers=NOT_GIVEN, max_retries=NOT_GIVEN, timeout=NOT_GIVEN,...
│ │ └ <class 'openai.types.create_embedding_response.CreateEmbeddingResponse'>
│ └ <function AsyncAPIClient.request at 0x73b626e13e20>
└ <openai.AsyncOpenAI object at 0x73b61517d070>
File "/opt/reme/.venv/lib/python3.12/site-packages/openai/_base_client.py", line 1669, in request
raise self._make_status_error_from_response(err.response) from None
│ └ <function BaseClient._make_status_error_from_response at 0x73b626e10fe0>
└ <openai.AsyncOpenAI object at 0x73b61517d070>
[31m[1mopenai.BadRequestError[0m:[1m Error code: 400 - {'error': {'message': 'Model "bge-m3" does not support matryoshka representation, changing output dimensions will lead to poor results.', 'type': 'BadRequestError', 'param': '', 'code': 400}}[0m
2026-04-08 10:33:27 | ERROR | base_async_op.py:190 | op=update_vector_store_op async execute failed, error=('Error code: 400 - {\'error\': {\'message\': \'Model "bge-m3" does not support matryoshka representation, changing output dimensions will lead to poor results.\', \'type\': \'BadRequestError\', \'param\': \'\', \'code\': 400}}',)
[33m[1mTraceback (most recent call last):[0m
File "/opt/reme/.venv/bin/reme", line 6, in <module>
sys.exit(main())
│ │ └ <function main at 0x73b6151dc9a0>
│ └ <built-in function exit>
└ <module 'sys' (built-in)>
File "[32m/opt/reme/reme_ai/[0m[32m[1mmain.py[0m", line [33m231[0m, in [35mmain[0m
[1mapp[0m[35m[1m.[0m[1mrun_service[0m[1m([0m[1m)[0m
[36m│ └ [0m[36m[1m<function Application.run_service at 0x73b6151dd580>[0m
[36m└ [0m[36m[1m<reme_ai.main.ReMeApp object at 0x73b62a862b70>[0m
File "/opt/reme/.venv/lib/python3.12/site-packages/flowllm/core/application.py", line 384, in run_service
service.run()
│ └ <function HttpService.run at 0x73b6162abe20>
└ <flowllm.core.service.http_service.HttpService object at 0x73b6281913d0>
File "/opt/reme/.venv/lib/python3.12/site-packages/flowllm/core/service/http_service.py", line 123, in run
uvicorn.run(
│ └ <function run at 0x73b6284a5b20>
└ <module 'uvicorn' from '/opt/reme/.venv/lib/python3.12/site-packages/uvicorn/__init__.py'>
File "/opt/reme/.venv/lib/python3.12/site-packages/uvicorn/main.py", line 606, in run
server.run()
│ └ <function Server.run at 0x73b6284a5ee0>
└ <uvicorn.server.Server object at 0x73b614d549b0>
File "/opt/reme/.venv/lib/python3.12/site-packages/uvicorn/server.py", line 75, in run
return asyncio_run(self.serve(sockets=sockets), loop_factory=self.config.get_loop_factory())
│ │ │ │ │ │ └ <function Config.get_loop_factory at 0x73b6284a58a0>
│ │ │ │ │ └ <uvicorn.config.Config object at 0x73b614d8fcb0>
│ │ │ │ └ <uvicorn.server.Server object at 0x73b614d549b0>
│ │ │ └ None
│ │ └ <function Server.serve at 0x73b6284a5f80>
│ └ <uvicorn.server.Server object at 0x73b614d549b0>
└ <function run at 0x73b629f21ee0>
File "/usr/lib/python3.12/asyncio/runners.py", line 194, in run
return runner.run(main)
│ │ └ <coroutine object Server.serve at 0x73b614bf82e0>
│ └ <function Runner.run at 0x73b629f6f880>
└ <asyncio.runners.Runner object at 0x73b614d8cd70>
File "/usr/lib/python3.12/asyncio/runners.py", line 118, in run
return self._loop.run_until_complete(task)
│ │ │ └ <Task pending name='Task-4' coro=<Server.serve() running at /opt/reme/.venv/lib/python3.12/site-packages/uvicorn/server.py:79...
│ │ └ <cyfunction Loop.run_until_complete at 0x73b614d81300>
│ └ <uvloop.Loop running=True closed=False debug=False>
└ <asyncio.runners.Runner object at 0x73b614d8cd70>
File "/opt/reme/.venv/lib/python3.12/site-packages/uvicorn/protocols/http/httptools_impl.py", line 416, in run_asgi
result = await app( # type: ignore[func-returns-value]
└ <uvicorn.middleware.proxy_headers.ProxyHeadersMiddleware object at 0x73b614d8e8a0>
File "/opt/reme/.venv/lib/python3.12/site-packages/uvicorn/middleware/proxy_headers.py", line 60, in __call__
return await self.app(scope, receive, send)
│ │ │ │ └ <bound method RequestResponseCycle.send of <uvicorn.protocols.http.httptools_impl.RequestResponseCycle object at 0x73b614ce5e...
│ │ │ └ <bound method RequestResponseCycle.receive of <uvicorn.protocols.http.httptools_impl.RequestResponseCycle object at 0x73b614c...
│ │ └ {'type': 'http', 'asgi': {'version': '3.0', 'spec_version': '2.3'}, 'http_version': '1.1', 'server': ('172.18.0.2', 28202), '...
│ └ <fastapi.applications.FastAPI object at 0x73b61516aed0>
└ <uvicorn.middleware.proxy_headers.ProxyHeadersMiddleware object at 0x73b614d8e8a0>
File "/opt/reme/.venv/lib/python3.12/site-packages/fastapi/applications.py", line 1163, in __call__
await super().__call__(scope, receive, send)
│ │ └ <bound method RequestResponseCycle.send of <uvicorn.protocols.http.httptools_impl.RequestResponseCycle object at 0x73b614ce5e...
│ └ <bound method RequestResponseCycle.receive of <uvicorn.protocols.http.httptools_impl.RequestResponseCycle object at 0x73b614c...
└ {'type': 'http', 'asgi': {'version': '3.0', 'spec_version': '2.3'}, 'http_version': '1.1', 'server': ('172.18.0.2', 28202), '...
File "/opt/reme/.venv/lib/python3.12/site-packages/starlette/applications.py", line 90, in __call__
await self.middleware_stack(scope, receive, send)
│ │ │ │ └ <bound method RequestResponseCycle.send of <uvicorn.protocols.http.httptools_impl.RequestResponseCycle object at 0x73b614ce5e...
│ │ │ └ <bound method RequestResponseCycle.receive of <uvicorn.protocols.http.httptools_impl.RequestResponseCycle object at 0x73b614c...
│ │ └ {'type': 'http', 'asgi': {'version': '3.0', 'spec_version': '2.3'}, 'http_version': '1.1', 'server': ('172.18.0.2', 28202), '...
│ └ <starlette.middleware.errors.ServerErrorMiddleware object at 0x73b614ce56a0>
└ <fastapi.applications.FastAPI object at 0x73b61516aed0>
File "/opt/reme/.venv/lib/python3.12/site-packages/starlette/middleware/errors.py", line 164, in __call__
await self.app(scope, receive, _send)
│ │ │ │ └ <function ServerErrorMiddleware.__call__.<locals>._send at 0x73b6148ef740>
│ │ │ └ <bound method RequestResponseCycle.receive of <uvicorn.protocols.http.httptools_impl.RequestResponseCycle object at 0x73b614c...
│ │ └ {'type': 'http', 'asgi': {'version': '3.0', 'spec_version': '2.3'}, 'http_version': '1.1', 'server': ('172.18.0.2', 28202), '...
│ └ <starlette.middleware.cors.CORSMiddleware object at 0x73b614ce5640>
└ <starlette.middleware.errors.ServerErrorMiddleware object at 0x73b614ce56a0>
File "/opt/reme/.venv/lib/python3.12/site-packages/starlette/middleware/cors.py", line 88, in __call__
await self.app(scope, receive, send)
│ │ │ │ └ <function ServerErrorMiddleware.__call__.<locals>._send at 0x73b6148ef740>
│ │ │ └ <bound method RequestResponseCycle.receive of <uvicorn.protocols.http.httptools_impl.RequestResponseCycle object at 0x73b614c...
│ │ └ {'type': 'http', 'asgi': {'version': '3.0', 'spec_version': '2.3'}, 'http_version': '1.1', 'server': ('172.18.0.2', 28202), '...
│ └ <starlette.middleware.exceptions.ExceptionMiddleware object at 0x73b614e1e270>
└ <starlette.middleware.cors.CORSMiddleware object at 0x73b614ce5640>
File "/opt/reme/.venv/lib/python3.12/site-packages/starlette/middleware/exceptions.py", line 63, in __call__
await wrap_app_handling_exceptions(self.app, conn)(scope, receive, send)
│ │ │ │ │ │ └ <function ServerErrorMiddleware.__call__.<locals>._send at 0x73b6148ef740>
│ │ │ │ │ └ <bound method RequestResponseCycle.receive of <uvicorn.protocols.http.httptools_impl.RequestResponseCycle object at 0x73b614c...
│ │ │ │ └ {'type': 'http', 'asgi': {'version': '3.0', 'spec_version': '2.3'}, 'http_version': '1.1', 'server': ('172.18.0.2', 28202), '...
│ │ │ └ <starlette.requests.Request object at 0x73b614ce6120>
│ │ └ <fastapi.middleware.asyncexitstack.AsyncExitStackMiddleware object at 0x73b614e1d0a0>
│ └ <starlette.middleware.exceptions.ExceptionMiddleware object at 0x73b614e1e270>
└ <function wrap_app_handling_exceptions at 0x73b628876c00>
File "/opt/reme/.venv/lib/python3.12/site-packages/starlette/_exception_handler.py", line 42, in wrapped_app
await app(scope, receive, sender)
│ │ │ └ <function wrap_app_handling_exceptions.<locals>.wrapped_app.<locals>.sender at 0x73b6148ef880>
│ │ └ <bound method RequestResponseCycle.receive of <uvicorn.protocols.http.httptools_impl.RequestResponseCycle object at 0x73b614c...
│ └ {'type': 'http', 'asgi': {'version': '3.0', 'spec_version': '2.3'}, 'http_version': '1.1', 'server': ('172.18.0.2', 28202), '...
└ <fastapi.middleware.asyncexitstack.AsyncExitStackMiddleware object at 0x73b614e1d0a0>
File "/opt/reme/.venv/lib/python3.12/site-packages/fastapi/middleware/asyncexitstack.py", line 18, in __call__
await self.app(scope, receive, send)
│ │ │ │ └ <function wrap_app_handling_exceptions.<locals>.wrapped_app.<locals>.sender at 0x73b6148ef880>
│ │ │ └ <bound method RequestResponseCycle.receive of <uvicorn.protocols.http.httptools_impl.RequestResponseCycle object at 0x73b614c...
│ │ └ {'type': 'http', 'asgi': {'version': '3.0', 'spec_version': '2.3'}, 'http_version': '1.1', 'server': ('172.18.0.2', 28202), '...
│ └ <fastapi.routing.APIRouter object at 0x73b61517e090>
└ <fastapi.middleware.asyncexitstack.AsyncExitStackMiddleware object at 0x73b614e1d0a0>
File "/opt/reme/.venv/lib/python3.12/site-packages/starlette/routing.py", line 660, in __call__
await self.middleware_stack(scope, receive, send)
│ │ │ │ └ <function wrap_app_handling_exceptions.<locals>.wrapped_app.<locals>.sender at 0x73b6148ef880>
│ │ │ └ <bound method RequestResponseCycle.receive of <uvicorn.protocols.http.httptools_impl.RequestResponseCycle object at 0x73b614c...
│ │ └ {'type': 'http', 'asgi': {'version': '3.0', 'spec_version': '2.3'}, 'http_version': '1.1', 'server': ('172.18.0.2', 28202), '...
│ └ <bound method Router.app of <fastapi.routing.APIRouter object at 0x73b61517e090>>
└ <fastapi.routing.APIRouter object at 0x73b61517e090>
File "/opt/reme/.venv/lib/python3.12/site-packages/starlette/routing.py", line 680, in app
await route.handle(scope, receive, send)
│ │ │ │ └ <function wrap_app_handling_exceptions.<locals>.wrapped_app.<locals>.sender at 0x73b6148ef880>
│ │ │ └ <bound method RequestResponseCycle.receive of <uvicorn.protocols.http.httptools_impl.RequestResponseCycle object at 0x73b614c...
│ │ └ {'type': 'http', 'asgi': {'version': '3.0', 'spec_version': '2.3'}, 'http_version': '1.1', 'server': ('172.18.0.2', 28202), '...
│ └ <function Route.handle at 0x73b6288991c0>
└ APIRoute(path='/summary_personal_memory', name='execute_endpoint', methods=['POST'])
File "/opt/reme/.venv/lib/python3.12/site-packages/starlette/routing.py", line 276, in handle
await self.app(scope, receive, send)
│ │ │ │ └ <function wrap_app_handling_exceptions.<locals>.wrapped_app.<locals>.sender at 0x73b6148ef880>
│ │ │ └ <bound method RequestResponseCycle.receive of <uvicorn.protocols.http.httptools_impl.RequestResponseCycle object at 0x73b614c...
│ │ └ {'type': 'http', 'asgi': {'version': '3.0', 'spec_version': '2.3'}, 'http_version': '1.1', 'server': ('172.18.0.2', 28202), '...
│ └ <function request_response.<locals>.app at 0x73b614d40ae0>
└ APIRoute(path='/summary_personal_memory', name='execute_endpoint', methods=['POST'])
File "/opt/reme/.venv/lib/python3.12/site-packages/fastapi/routing.py", line 134, in app
await wrap_app_handling_exceptions(app, request)(scope, receive, send)
│ │ │ │ │ └ <function wrap_app_handling_exceptions.<locals>.wrapped_app.<locals>.sender at 0x73b6148ef880>
│ │ │ │ └ <bound method RequestResponseCycle.receive of <uvicorn.protocols.http.httptools_impl.RequestResponseCycle object at 0x73b614c...
│ │ │ └ {'type': 'http', 'asgi': {'version': '3.0', 'spec_version': '2.3'}, 'http_version': '1.1', 'server': ('172.18.0.2', 28202), '...
│ │ └ <starlette.requests.Request object at 0x73b614ce5c70>
│ └ <function request_response.<locals>.app.<locals>.app at 0x73b6148ef920>
└ <function wrap_app_handling_exceptions at 0x73b628876c00>
File "/opt/reme/.venv/lib/python3.12/site-packages/starlette/_exception_handler.py", line 42, in wrapped_app
await app(scope, receive, sender)
│ │ │ └ <function wrap_app_handling_exceptions.<locals>.wrapped_app.<locals>.sender at 0x73b6148efa60>
│ │ └ <bound method RequestResponseCycle.receive of <uvicorn.protocols.http.httptools_impl.RequestResponseCycle object at 0x73b614c...
│ └ {'type': 'http', 'asgi': {'version': '3.0', 'spec_version': '2.3'}, 'http_version': '1.1', 'server': ('172.18.0.2', 28202), '...
└ <function request_response.<locals>.app.<locals>.app at 0x73b6148ef920>
File "/opt/reme/.venv/lib/python3.12/site-packages/fastapi/routing.py", line 120, in app
response = await f(request)
│ └ <starlette.requests.Request object at 0x73b614ce5c70>
└ <function get_request_handler.<locals>.app at 0x73b614d17d80>
File "/opt/reme/.venv/lib/python3.12/site-packages/fastapi/routing.py", line 674, in app
raw_response = await run_endpoint_function(
└ <function run_endpoint_function at 0x73b6162a8360>
File "/opt/reme/.venv/lib/python3.12/site-packages/fastapi/routing.py", line 328, in run_endpoint_function
return await dependant.call(**values)
│ │ └ {'request': SummaryPersonalMemoryModel(query='', messages=[], workspace_id='example_user_id', metadata={}, trajectories=[{'me...
│ └ <function HttpService.integrate_tool_flow.<locals>.execute_endpoint at 0x73b614e02e80>
└ Dependant(path_params=[], query_params=[], header_params=[], cookie_params=[], body_params=[ModelField(field_info=Body(Pydant...
File "/opt/reme/.venv/lib/python3.12/site-packages/flowllm/core/service/http_service.py", line 61, in execute_endpoint
return await flow.async_call(**request.model_dump(exclude_none=True))
│ │ │ └ <function BaseModel.model_dump at 0x73b629562480>
│ │ └ SummaryPersonalMemoryModel(query='', messages=[], workspace_id='example_user_id', metadata={}, trajectories=[{'messages': [{'...
│ └ <function BaseFlow.async_call at 0x73b6164e3e20>
└ <flowllm.core.flow.expression_tool_flow.ExpressionToolFlow object at 0x73b614e041d0>
File "/opt/reme/.venv/lib/python3.12/site-packages/flowllm/core/flow/base_flow.py", line 255, in async_call
result = await self._async_call(context=context)
│ │ └ FlowContext({'query': '', 'messages': [PersonalMemory(workspace_id='example_user_id', memory_id='56dc81c4a3a945fb9aaf8cc671bf...
│ └ <function BaseFlow._async_call at 0x73b6164e3d80>
└ <flowllm.core.flow.expression_tool_flow.ExpressionToolFlow object at 0x73b614e041d0>
File "/opt/reme/.venv/lib/python3.12/site-packages/flowllm/core/flow/base_flow.py", line 225, in _async_call
await flow_op.async_call(context=context)
│ │ └ FlowContext({'query': '', 'messages': [PersonalMemory(workspace_id='example_user_id', memory_id='56dc81c4a3a945fb9aaf8cc671bf...
│ └ <function BaseAsyncOp.async_call at 0x73b6164e22a0>
└ <flowllm.core.op.sequential_op.SequentialOp object at 0x73b611bb3200>
File "/opt/reme/.venv/lib/python3.12/site-packages/flowllm/core/op/base_async_op.py", line 185, in async_call
result = await self.async_execute()
│ └ <function SequentialOp.async_execute at 0x73b6164e37e0>
└ <flowllm.core.op.sequential_op.SequentialOp object at 0x73b611bb3200>
File "/opt/reme/.venv/lib/python3.12/site-packages/flowllm/core/op/sequential_op.py", line 51, in async_execute
result = await op.async_call(context=self.context)
│ │ │ └ FlowContext({'query': '', 'messages': [PersonalMemory(workspace_id='example_user_id', memory_id='56dc81c4a3a945fb9aaf8cc671bf...
│ │ └ <flowllm.core.op.sequential_op.SequentialOp object at 0x73b611bb3200>
│ └ <function BaseAsyncOp.async_call at 0x73b6164e22a0>
└ <reme_ai.vector_store.update_vector_store_op.UpdateVectorStoreOp object at 0x73b614ce7170>
> File "/opt/reme/.venv/lib/python3.12/site-packages/flowllm/core/op/base_async_op.py", line 185, in async_call
result = await self.async_execute()
│ └ <function UpdateVectorStoreOp.async_execute at 0x73b61504c9a0>
└ <reme_ai.vector_store.update_vector_store_op.UpdateVectorStoreOp object at 0x73b614ce7170>
File "[32m/opt/reme/reme_ai/vector_store/[0m[32m[1mupdate_vector_store_op.py[0m", line [33m54[0m, in [35masync_execute[0m
[35m[1mawait[0m [1mself[0m[35m[1m.[0m[1mvector_store[0m[35m[1m.[0m[1masync_insert[0m[1m([0m[1mnodes[0m[35m[1m=[0m[1minsert_nodes[0m[1m,[0m [1mworkspace_id[0m[35m[1m=[0m[1mworkspace_id[0m[1m)[0m
[36m │ │ │ └ [0m[36m[1m'example_user_id'[0m
[36m │ │ └ [0m[36m[1m[VectorNode(unique_id='49dc2f8253d34deaa2e57c185cc62ac2', workspace_id='example_user_id', content='Xiao Bai, 29, apples, Hami...[0m
[36m │ └ [0m[36m[1m<property object at 0x73b6164dc900>[0m
[36m └ [0m[36m[1m<reme_ai.vector_store.update_vector_store_op.UpdateVectorStoreOp object at 0x73b614ce7170>[0m
File "/opt/reme/.venv/lib/python3.12/site-packages/flowllm/core/vector_store/local_vector_store.py", line 546, in async_insert
await super().async_insert(nodes, workspace_id, **kwargs)
│ │ └ {}
│ └ 'example_user_id'
└ [VectorNode(unique_id='49dc2f8253d34deaa2e57c185cc62ac2', workspace_id='example_user_id', content='Xiao Bai, 29, apples, Hami...
File "/opt/reme/.venv/lib/python3.12/site-packages/flowllm/core/vector_store/memory_vector_store.py", line 755, in async_insert
nodes = await self.async_get_node_embeddings(nodes)
│ │ └ [VectorNode(unique_id='49dc2f8253d34deaa2e57c185cc62ac2', workspace_id='example_user_id', content='Xiao Bai, 29, apples, Hami...
│ └ <function BaseVectorStore.async_get_node_embeddings at 0x73b616494360>
└ <flowllm.core.vector_store.local_vector_store.LocalVectorStore object at 0x73b616cca2a0>
File "/opt/reme/.venv/lib/python3.12/site-packages/flowllm/core/vector_store/base_vector_store.py", line 91, in async_get_node_embeddings
return await self.embedding_model.async_get_node_embeddings(nodes)
│ │ │ └ [VectorNode(unique_id='49dc2f8253d34deaa2e57c185cc62ac2', workspace_id='example_user_id', content='Xiao Bai, 29, apples, Hami...
│ │ └ <function BaseEmbeddingModel.async_get_node_embeddings at 0x73b627423f60>
│ └ <flowllm.core.embedding_model.openai_compatible_embedding_model.OpenAICompatibleEmbeddingModel object at 0x73b6153c5d90>
└ <flowllm.core.vector_store.local_vector_store.LocalVectorStore object at 0x73b616cca2a0>
File "/opt/reme/.venv/lib/python3.12/site-packages/flowllm/core/embedding_model/base_embedding_model.py", line 207, in async_get_node_embeddings
batch_results = await asyncio.gather(*batch_tasks)
│ │ └ [<coroutine object BaseEmbeddingModel.async_get_embeddings at 0x73b614c8ab40>]
│ └ <function gather at 0x73b629f5dee0>
└ <module 'asyncio' from '/usr/lib/python3.12/asyncio/__init__.py'>
File "/opt/reme/.venv/lib/python3.12/site-packages/flowllm/core/embedding_model/base_embedding_model.py", line 129, in async_get_embeddings
raise e
File "/opt/reme/.venv/lib/python3.12/site-packages/flowllm/core/embedding_model/base_embedding_model.py", line 123, in async_get_embeddings
return await self._async_get_embeddings(input_text)
│ │ └ ['Xiao Bai, 29, apples, Hami melons']
│ └ <function OpenAICompatibleEmbeddingModel._async_get_embeddings at 0x73b626d7c400>
└ <flowllm.core.embedding_model.openai_compatible_embedding_model.OpenAICompatibleEmbeddingModel object at 0x73b6153c5d90>
File "/opt/reme/.venv/lib/python3.12/site-packages/flowllm/core/embedding_model/openai_compatible_embedding_model.py", line 124, in _async_get_embeddings
completion = await self._async_client.embeddings.create(
│ │ │ └ <function AsyncEmbeddings.create at 0x73b611c89440>
│ │ └ <openai.resources.embeddings.AsyncEmbeddings object at 0x73b614c7a900>
│ └ <openai.AsyncOpenAI object at 0x73b61517d070>
└ <flowllm.core.embedding_model.openai_compatible_embedding_model.OpenAICompatibleEmbeddingModel object at 0x73b6153c5d90>
File "/opt/reme/.venv/lib/python3.12/site-packages/openai/resources/embeddings.py", line 259, in create
return await self._post(
│ └ <bound method AsyncAPIClient.post of <openai.AsyncOpenAI object at 0x73b61517d070>>
└ <openai.resources.embeddings.AsyncEmbeddings object at 0x73b614c7a900>
File "/opt/reme/.venv/lib/python3.12/site-packages/openai/_base_client.py", line 1884, in post
return await self.request(cast_to, opts, stream=stream, stream_cls=stream_cls)
│ │ │ │ │ └ None
│ │ │ │ └ False
│ │ │ └ FinalRequestOptions(method='post', url='/embeddings', params={}, headers=NOT_GIVEN, max_retries=NOT_GIVEN, timeout=NOT_GIVEN,...
│ │ └ <class 'openai.types.create_embedding_response.CreateEmbeddingResponse'>
│ └ <function AsyncAPIClient.request at 0x73b626e13e20>
└ <openai.AsyncOpenAI object at 0x73b61517d070>
File "/opt/reme/.venv/lib/python3.12/site-packages/openai/_base_client.py", line 1669, in request
raise self._make_status_error_from_response(err.response) from None
│ └ <function BaseClient._make_status_error_from_response at 0x73b626e10fe0>
└ <openai.AsyncOpenAI object at 0x73b61517d070>
[31m[1mopenai.BadRequestError[0m:[1m Error code: 400 - {'error': {'message': 'Model "bge-m3" does not support matryoshka representation, changing output dimensions will lead to poor results.', 'type': 'BadRequestError', 'param': '', 'code': 400}}[0m
没招了，不知道咋改