用户寻求 Crawl4AI 与 SearXNG 研究方案调优
一名用户称，通过 Crawl4AI 和 SearXNG 使用本地模型进行研究时，结果经常缺失、过时或相关性较低。其主观上将这种体验与 ChatGPT 和 Codex 作比较，并列举了 GLM 5.3 Flash 和 DeepSeek V4.1 Flash 1017。该用户表示曾使用 ZCode、DeepSeek Harness 和 OpenCode，并询问能否调优 Crawl4AI 与 SearXNG，或与其他方法结合，以改善研究结果。
该报告记录了本地模型研究工作流中检索质量的实际问题，以及用户寻求的配置和工作流建议。报告没有提供基准测试或经验证的解决方案。
I’m using Crawl4AI + SearXNG but it just feels so lackluster I don’t know why. Feels like the results the local model gets back for research are missing a lot and / or are older less relevant results.
I’ll usually instruct saying something like “using the most up-to-date and relevant information across related websites, subreddits, forums, and etc find me the best way to _______” or something similar.
With ChatGPT or Codex it basically always finds everything it needs to and gives me great instructions or information or research or whatever I’m looking for at the time. With a local model (like GLM 5.3 Flash or DeepSeek V4.1 Flash 1017) the answer doesn’t come back nearly as good, often missing obvious results or mixing in outdated information into the instructions or etc.
Harnesses I’ve been using with local models are ZCode, DeepSeek Harness, and OpenCode. Is there a better (more complete and on par with ChatGPT) searching / research approach I’m missing? Is there some tuning of Crawl4AI + SearXNG to make it more how I’m expecting or potentially something I should add to this combination?
Any input or help is appreciated. Thank you for your time it is appreciated!
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#Crawl4AI#SearXNG#ChatGPT#Codex#GLM 5.3 Flash#DeepSeek V4.1 Flash 1017#ZCode#DeepSeek Harness#OpenCode