we're working on that right now, we'd love to hear your opinions(if you're interested you can send us an email at team@lucidic.ai).
We're new to the open source scene so we don't have anything published yet but plan to in the future. A basic overview of the way we do clustering is we condense stateful information -> create a state embedding ->…
Colloquially, AI agents are just while loops with LLM calls and tool calls. More specifically, what distinguishes an agent from LLM pipelines is that its next step is determined dynamically (based on the output of the…
Langfuse and Helicone work well for traditional LLM operations, but AI agents are different. We discovered that AI agents require fundamentally different tooling, here are some examples. First, while LLMs simply respond…
the way it is integrated (its explained more in the docs) is by installing the python/typescript sdk and writing "lai.init()" at the top of your code. Then we capture all LLM calls and tools with integrated providers…
we're working on that right now, we'd love to hear your opinions(if you're interested you can send us an email at team@lucidic.ai).
We're new to the open source scene so we don't have anything published yet but plan to in the future. A basic overview of the way we do clustering is we condense stateful information -> create a state embedding ->…
Colloquially, AI agents are just while loops with LLM calls and tool calls. More specifically, what distinguishes an agent from LLM pipelines is that its next step is determined dynamically (based on the output of the…
Langfuse and Helicone work well for traditional LLM operations, but AI agents are different. We discovered that AI agents require fundamentally different tooling, here are some examples. First, while LLMs simply respond…
the way it is integrated (its explained more in the docs) is by installing the python/typescript sdk and writing "lai.init()" at the top of your code. Then we capture all LLM calls and tools with integrated providers…