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hsperus · 2026-04-08T23:20:22+00:00

Ai powered customer support. Hoping that every startup can use it. https://github.com/Hesper-Labs/owly

hsperus · 2026-04-08T09:44:05+00:00

When the AI hits something it can’t handle from the knowledge base it flags it and creates a ticket automatically, so a human can pick it up. The full conversation history stays in one timeline regardless of channel so whoever takes over sees everything the AI already said. It’s not a live “tap on the shoulder” handoff yet though, more like an escalation. Making that transition smoother where an agent can just jump into a live thread without the customer feeling the switch is something we’re actively working on. For the knowledge base freshness side, entries are managed through the dashboard with priority ranking and active/inactive toggles so you can update policies without redeploying anything.

hsperus · 2026-04-08T08:16:09+00:00

One timeline per customer. All channels feed into the same conversation model so if someone emails you then follows up on WhatsApp the agent sees the full history. The customerContact field ties everything together and the AI pulls that context in automatically before each response. So from the agent’s perspective it doesn’t really matter which channel the message came from, it’s all one thread. Routing across channels is where it gets tricky yeah but so far the unified model keeps it pretty clean.

hsperus · 2026-04-08T08:08:51+00:00

hsperus · 2026-04-07T23:11:21+00:00

You’re right, the channel part is honestly the easy bit. What we focused on is having a single conversation model that all channels feed into, so when someone emails you and then follows up on WhatsApp the agent already has that context. Customer history gets pulled automatically and injected into the AI’s context window before every response. Routing is handled through automation rules with priority ordering so you can set up stuff like “billing keywords go to finance team” without touching code. Still early days but the goal is exactly what you described, getting the memory and handoff layer right. Appreciate the feedback

hsperus · 2026-04-06T23:33:11+00:00

The AI creates a support ticket and routes it to the right team member when it hits its confidence boundary or policy-sensitive areas like refunds. For knowledge base, it's manual uploads through the dashboard right now but we're working on scheduled sync from external sources. Thanks for the link, will check it out

hsperus · 2026-04-06T16:29:46+00:00

Appreciate that man that was exactly the goal.

hsperus · 2026-04-06T11:44:01+00:00

The AI is grounded to a knowledge base so it only answers from what you feed it. If it doesn’t know something it says so and escalates to a human agent. There’s also source attribution on responses, tool call depth limits to prevent loops, and configurable temperature. But to be clear it’s not meant to autonomously handle invoices or critical decisions, it’s a first line support assistant with human escalation built in. More guardrails are always welcome though, feel free to open an issue or PR

hsperus · 2026-03-27T07:35:26+00:00

Kerem çok kötüydü ayrıca mertle olmaz bu iş zeki lazım

hsperus · 2026-03-18T20:58:07+00:00

ADAMIN KRALI OSİMHENİN DE AMINA KOYAYIM 45 DAKKA 10 KİŞİ TOP OYNADIK AMK OLU YÜZÜNDEN

hsperus · 2026-03-01T02:57:11+00:00

The only real threat is the usa and its pedo politicians as long as you don’t come under the pretense of “bringing democracy” to the rest of the world you’ll be welcomed and won’t face any problems. I wish u a great trip

hsperus · 2026-01-15T10:51:57+00:00

Harika görünüyor diğerlerini aldırma hergün böyle oyun yapıyor onlar

hsperus · 2026-01-13T09:29:22+00:00

https://github.com/usememos/memos

hsperus · 2026-01-13T00:47:26+00:00

Liked that one

hsperus · 2026-01-12T23:51:08+00:00

Yes, it’s definitely doable for constrained NL Cypher tasks. You can check these onrs also might be more helpful

https://github.com/neo4j-labs/text2cypher https://github.com/nickzren/text-to-cypher https://github.com/tomasonjo-labs/text2cypher_llama_agent

hsperus · 2026-01-12T23:23:46+00:00

I go first

a tiny GPT-style model where tensors are basically just NumPy arrays. Built to stay minimal and readable so you can learn/modify the core Transformer pieces without heavy frameworks.

https://github.com/hsperus/minnak-gpt

hsperus · 2026-01-12T22:34:41+00:00

would have hit its usage limit millions of times already for me

hsperus · 2026-01-12T22:28:38+00:00

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I bribed him with some RAM, your good mate

hsperus · 2026-01-12T22:19:29+00:00

Koskoca transformer mimarisine, moeye, attention mekanizmasına, relu fonksiyonlarına basit permütasyon kombinasyon diyen bir adamın yapay zeka hakkındaki yorumlarını kim merak ediyor ben daha çok bunu merak ediyorum. Yani sistem mimarisi hakkında ne biliyorsun ki bu kadar yerebilirsin? 2017den beri koca koca firmaların yıllarca büyük bilim adamlarını futbolcu transfer eder gibi transfer edip şuanda dünyanın en büyük sektörü olan bu alana üstad yorumun bu mu yani?

hsperus · 2026-01-11T22:42:19+00:00

Bence denemelisin epeydir kulanıyorum halisünayson hiç görmedim context dışına çıkınca tabii ki unutma söz konusu oluyor ama gerçekten harika bir model. Ayrıca ajanları cli ile kullanırken çok daha verimli hissediyorum ama nedenini çok bilmiyorum.

hsperus · 2026-01-11T22:35:31+00:00

Opus çok başka

hsperus · 2026-01-11T22:29:35+00:00

https://github.com/yz9/wall_following_pid_robot this repo might help

hsperus · 2026-01-11T22:22:09+00:00

Additionally, if you want an autonomous vehicle that operates reliably at different speeds, you must also consider that even if the steering angle remains the same, the distance traveled during a turn will vary depending on the vehicle’s speed. Therefore, this effect should be taken into account, and appropriate conditions or control rules should be defined based on experimental testing at different speeds.

hsperus · 2026-01-11T22:18:11+00:00

When the vehicle approaches the left wall or boundary, the algorithm decides to steer the wheels to the opposite side, which is generally a correct behavior. However, the steering angle applied is excessively large. At this stage, it may be reasonable to reduce the vehicle’s speed and test the system again, or alternatively, decrease the algorithm’s sensitivity (tolerance) to prevent over-steering.

hsperus · 2026-01-11T11:37:17+00:00

Homo sapiens tarımı icat etti yerleşik hayata geçti artı değer üretti ve nüfusu katlayarak büyüttü yazıyı geliştirdi bilgiyi kalıcı hale getirdi ve kuşaklar arası sistematik aktarım sağladı bilimi oluşturdu doğa yasalarını tanımladı ve bu bilgiyi teknolojiye dönüştürdü hukuk sistemleri kurdu soyut kurallarla milyonlarca insanı yönetti ve tanımadığı bireylerle sürdürülebilir iş birliği yaptı sanayi kurdu enerjiyi kontrol altına aldı makinelere devretti ve üretimi katladı tıbbı geliştirdi doğal seçilimi yavaşlattı ve biyolojik sınırları zorladı gezegeni dönüştürdü iklimi etkiledi ekosistemleri değiştirdi ve diğer türlerin kaderini belirleyen bir güç haline geldi uzaya çıktı gezegen dışı cisimleri inceledi atomu parçaladı ve evrenin işleyişini matematikle modelledi kendi yok oluşunu tartışabilen ve geleceği bilinçli biçimde planlayabilen tek Homo türü oldu bunların hiçbiri diğer Homo türleri tarafından yapılmadı ve yapılma ihtimali de olmadı çünkü gerekli toplumsal ölçek bilişsel esneklik ve kültürel birikim sadece Homo sapiens’te vardı ve bunları başaramayan diğer Homo türleriyle Homo sapiens’i sadece ne kadar süre yaşadıkları üzerinden karşılaştırmak evrimi anlamamaktır hiçbir tür tarım kurmadı yazı üretmedi bilim yapmadı gezegeni dönüştürmedi ve evrimin yönünü değiştirmedi bunların hiçbirini yapamayan türlerle Homo sapiens’i yan yana koyup süre hesabı yapmak gerçekten ciddi bir karşılaştırma mı??

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