
LLM Status — AI model deprecation tracker & CLI checker
追踪您的应用中使用的 AI 模型,并在其被弃用前获得警告。
taylorgt · HN
Find every AI model your code calls and warn before it's retired
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追踪您的应用中使用的 AI 模型,并在其被弃用前获得警告。
taylorgt · HN
Find every AI model your code calls and warn before it's retired

压缩提示词以减少向LLM API发送的token数量和成本。
@asgujjuasitgets · X

向多个前沿大模型提问,获得经过同行评审的综合答案。
u/Puzzleheaded-Log-27 · Reddit
Building a multi-model AI deliberation tool taught me something about trust LLM Counsel isn't another wrapper around one model - it sends your question to a panel of frontier LLMs, has them peer-review each other anonymously, and an impartial "chairman" model returns one synthesized answer. Free to start, pay-as-you-go after, credits don't expire. What I've learned so far: people trust a synthesized answer a lot more once they can see that the models actually disagreed and how that disagree

用对抗测试检查LLM端点安全,获取OWASP审计报告。
@aryaan_sheth · X
- LLM security for small teams

自动将提示词路由到最便宜的模型,节省API成本。
u/ASDKING100 · Reddit
Launched an AI API router tonight, and found a bug hours in that would've taken real payments without ever upgrading the account Built LLMLite over the past few weeks — it classifies each prompt and routes it to the cheapest model that can actually handle it, instead of hitting GPT-4o for everything. Free tier, no card needed to try it. Tonight, right as I was about to launch, ran a real transaction to test the payment flow end to end. Paddle processed it, webhook fired, signature verified

查看LLM模型在10个基准问题上的评分和排名。
fristovic · HN
She watched me look at model rankings and asked what do the numbers mean... I literally had no good way of explaining it to her so I just came up with something that is approximately in the same ballpark as some of the benchmarks out there lol

LLM API支出分析仪表板,按模型和环境分类,含优化建议
ATsimbalistov · HN
Show HN: Tracking GenAI cost and endpoint fragility so app teams don't have to

Ornymo通过语义缓存减少LLM查询成本和延迟。
u/ornymo_official · Reddit
how to reduce ai costs there are lots of way to reduce costs but there all complex to setup i know this cause i tried one in production so i built ornymo we cache meaning not the exact string allowing us to give same awnsers thus reducing llm costs and latency check it out at ornymo.com free for a limited time and let me know your feedback submitted by /u/ornymo_official to r/buildinpublic [link] [comments]

Convert PDF, DOCX, XLSX, CSV, JSON, XML, HTML, Images to clean Markdown optimized for AI Agents, RAG, and Vector DBs. 100% Privacy-First, In-Browser Conversion.
@13SahajChawla · X
For professionals to redact their client's sensitive informations before giving AI to process it & while converting any kind of document to a structured MD file. Better quality outputs, 100% privacy with on-browser local processing, and fully free!

为LLM输出提供token级引文API,通过注意力分析验证。
apoorvumang · HN
TokenPath – token-level citations for LLM output, read from attention

在仪表板上版本管理、测试和部署 LLM 提示词,无需修改代码。
@why_deepanshux · X
I Just launched my first SaaS. Late night coding session, white board and my my markers knows what we built. Now it's world's turn. Please checkout Link below.

对比LLM API价格,轻松计算月度使用成本。
u/ahmedk2002 · Reddit
I built a real-time LLM API pricing comparator — because I was tired of not knowing the actual cost difference between models I use LLMs daily at work and kept running into the same frustration: provider pricing pages give you raw numbers per million tokens, but no way to understand what that actually means for your specific use case. Is GPT-4o really that much more expensive than Claude Sonnet for 10k requests per day? What about DeepSeek vs Gemini Flash for high-volume summarization? I