a6kme

11 ms·

1.
by a6kme 1mo ago
Being able to track how much your brand is visible to the AI, that too using your own AI harness is gem. Open source is just cherry on top. Thank you for offering this to the community.
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In-Context Learning Problem in Multi-Node Agents: How History Poisons Tool Calls(blog.dograh.com)
5 points by a6kme 6mo ago|0 comments
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Show HN: Dograh – voice agents that pick Recordings over TTS using LLM(github.com)
4 points by a6kme 6mo ago|0 comments
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by a6kme 6mo ago
Hello. The latency is a factor of the models you are picking up for reasoning. If you are colocating the models by self hosting on GPUs, the latency can be as low as 500 - 600 ms between bot - user turns. With models like Gemini-2.5-flash,
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by a6kme 6mo ago
Thanks for the kind words @ajabish. We are more of a horizontal platform and can support a wide variety of use cases. We are serving large BPO call centres on our managed hosted service for outbound and inbound cases. There are individual b
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by a6kme 6mo ago
Hello HN. I am Abhishek, one of the creators and maintainers of Dograh - github.com/dograh-hq/dograh Please feel free to ask any question you may have or give us feedbacks on how we can make it better for you. Thanks!
7.
by a6kme 9mo ago
There is always a tradeoff between latency and reasoning. The bigger the model, the more stuff we can get it to do by better instruction following, but it comes at a cost of increased latency. OpenSource colocated smaller models do much bet
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by a6kme 9mo ago
Thank you for your kind words. Among many other useful and fun things, yes, the dream of having a Star Trek Voice Computer or the good HAL is not very far away. :)
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by a6kme 9mo ago
Hello. Thank you for trying out Dograh and being our 100th Github Star.:) 1. Having different voice personas selector like Vapi is in our pipeline. 2. The lag can be either because of system resource constraints, or due to LLM Inference La
10.
by a6kme 9mo ago
Earlier I was using other platforms for production voice agents. One thing that became obvious was the cost: 60–70% of our total spend was the Vapi platform fee, and only 30-40% was actual LLM/STT/TTS usage. Platform cost dominate
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Show HN: Dograh – an OSS Vapi alternative to quickly build and test voice agents(github.com)
16 points by a6kme 9mo ago|10 comments
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by a6kme 2y ago
You are probably not spending time yak shaving and over engineering which is time well spent in understanding the problem and building the business :)