-
-
Notifications
You must be signed in to change notification settings - Fork 12k
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Application level Search Feedback | 应用级搜索反馈 #6482
Comments
|
This comment has been minimized.
This comment has been minimized.
This comment has been minimized.
This comment has been minimized.
已解决,原因是提供的zeabur模板(https://zeabur.com/templates/77FSH6) 没有设置 json 输出 formats:
- html 修改为 formats:
- html
- json 最后重启容器 |
Resolved because the provided zeabur template (https://zeabur.com/templates/77FSH6) does not open json output settings Add a json |
This comment has been minimized.
This comment has been minimized.
This comment has been minimized.
This comment has been minimized.
This comment has been minimized.
This comment has been minimized.
可以使用docker自行部署
2.修改settings.yml
修改为
3.重启,修改lobe配置文件 |
You can use docker to deploy it yourself
Modified to
|
@Kac001 老哥有没有兴趣来优化docker-compose 哇 😆 直接给一键部署脚本搞上! |
@Kac001 Are you interested in optimizing docker-compose? Wow 😆 Just add one-click deployment script! |
@130aac8 Thanks for your advice! Let me reply one by one .
I think you are right, I will adjust prompts to make sure only search specific engine when user point out it in the query. Actually what you say is also bother me in some cases.
I think it's no need, as SearXNG has already a page rank algorithm. we have use the confience scores to involve useful results. So embedding is no need.
I think it's the next step to support config with SearXNG, also we will support more search provider like tavily and exa.
Yeah! It's also the next step to improve the search ability. Actually we have a plugin named |
This comment has been minimized.
This comment has been minimized.
@arvinxx 是docker-compose/setup.sh 这个脚本吗 |
@arvinxx Is this script docker-compose/setup.sh |
This comment has been minimized.
This comment has been minimized.
This comment has been minimized.
This comment has been minimized.
This comment has been minimized.
This comment has been minimized.
@Kac001 https://github.com/lobehub/lobe-chat/blob/main/docker-compose/local/docker-compose.yml This file |
This comment has been minimized.
This comment has been minimized.
This comment has been minimized.
This comment has been minimized.
当前已经实现的搜索,应该是拿的搜索引擎结果前5条的title和content丢给AI去分析,但是很多情况下这个体验并不好。 |
The search currently implemented should be to throw the titles and contents of the first 5 search engine results to the AI for analysis, but in many cases the experience is not good. |
Yes, it indeed has a ranking algorithm, but if you take a closer look at its source code, you'll find that it doesn't suit the scenarios we currently require. Its algorithm is based on a per-search engine, weight-based approach, similar to the principles of traditional search engines. It factors in the credibility of the sources and incorporates the ranking positions of upstream search engines into the weight calculation, considering that it itself is a meta-search engine. This method works well for traditional usage scenarios where users search for keywords, quickly browse through the results, and manually select the links they want to open. However, in our scenario, where the input for LLMs is limited and billed by token usage, this approach falls short. This limitation might also explain why you choose to extract only the top five results to submit to the model. Such a small number of results means that the quality of our search results must be exceptionally high. Additionally, since the search only returns partial content and the LLM cannot currently access the target links, the limited information from five results significantly restricts the depth and quality of the model's responses. In my tests, directly extracting the top five results was not ideal. The relevance and depth of the content are limited, this led to some consumption of search resources and AI costs, but the responses obtained were relatively brief and might only contain a few key points. A lot of valuable information remains buried in other search results that are not included. Besides the per-engine weight configuration, SearXNG also has a hostname-based priority setting. However, these scoring methods are quite restrictive and often fail to deliver the best search results for every query. This is especially problematic when the user's query requires more than a simple "yes" or "no" answer. In such cases, the current implementation in LobeChat frequently leads to missing information and insufficient depth. We can also take inspiration from how similar products handle this challenge. For instance, products like Perplexity typically use at least 10–15 search results as the information source for their models. Even then, embeddings are often used to include as much relevant information as possible within the limited input. I suggest suggest making some optimizations here. For example, consider optionally incorporating embeddings, increasing the number of search results to at least 10–15, or allowing users to configure the number of search results submitted to the model. |
是不是可以在联网配置处选择条数数量? |
Can I select the number of items in the network configuration? |
同样出现TRPCClientError,情况是自部署 + basic auth 请求 [
{
"error": {
"json": {
"message": "Request cannot be constructed from a URL that includes credentials: https://username:[email protected]/search?format=json&q=claude%20latest%20model",
"code": -32603,
"data": {
"code": "SERVICE_UNAVAILABLE",
"httpStatus": 503,
"path": "search.query"
}
}
}
}
] |
TRPCClientError also appears, the situation is self-deployment + basic auth Return when requesting ```trpc/tools/search.query`` [
{
"error": {
"json": {
"message": "Request cannot be constructed from a URL that includes credentials: https://username:[email protected]/search?format=json&q=claude%20latest%20model",
"code": -32603,
"data": {
"code": "SERVICE_UNAVAILABLE",
"httpStatus": 503,
"path": "search.query"
}
}
}
}
] |
@KoellM 你这种复杂 case 先不考虑支持… |
@KoellM You are a complex case, don't consider supporting it for now... |
This comment has been minimized.
This comment has been minimized.
This comment has been minimized.
This comment has been minimized.
TRPCClientError appears after deploying it yourself, and you need to add it - json The specific format is as follows |
呃。。。请教两个问题:
|
Well. . . Ask two questions:
|
|
|
This comment has been minimized.
This comment has been minimized.
When using searchWithSearXNG, DeepSeek official API (Deepseek-chat) will search infinitely, and it will not reach the level that can be used. It needs to continue to optimize... |
sonnet3.5会出现响应结果为空,一直卡在这里,后台能看到已经调用结束,存在日志记录了 使用claude-3-7-sonnet会出现这个错误, |
这个是 ds v3 的 function calling 能力不行。你换个模型就好了 |
请问现在不支持Function call的模型可以用联网搜索么 比如 DS R1 |
Can models that do not support Function call can be searched online? For example, DS R1 |
啥时候能支持应用层的搜索呀 😢 |
When will the application layer search be supported? |
现在不就是支持了嘛,这个帖子是在搜集使用反馈信息了啊。。。 |
Isn't it just supported now? This post is collecting feedback information. . . |
现在还是需要支持函数的模型才能搜 |
Now we still need a model that supports functions to search |
国内部署搜索结果的icon会挂掉,除了Proxy能否可以自定义这个地址? |
The icon that deploys search results in China will be deactivated. Can Proxy customize this address? |
1.64.0 We have supported application-level networking features through SearchXNG. We welcome everyone to provide feedback on their experience and suggestions.
Set environment variable:
SEARXNG_URL=https://searxng-instance.com
There is a searchXNG one-click startup template on Zeabur: https://zeabur.com/templates/77FSH6
1.64.0 通过 SearchXNG 我们支持了应用级联网功能,欢迎大家反馈使用体验和建议。
配置环境变量:
SEARXNG_URL=https://searxng-instance.com
Zeabur 上有 searchXNG 的一键启动模板:https://zeabur.com/templates/77FSH6
The text was updated successfully, but these errors were encountered: