4 ms·

@on user > onAskAboutConvoLang() -> ( if(??? (+ boolean /m last:3 task:Inspecting message) Did the user ask about Convo-Lang in their last mes

@on user > onAskAboutConvoLang() -> ( if(??? (+ boolean /m last:3 task:Inspecting message) Did the user ask about Convo-Lang in their last message ???) then ( @ragForMsg public/learn-convo ??? (+ respond /m task:Generating response about Convo-Lang) Answer the users question using the following information about Convo-Lang ??? ) ) > user Who in their right mind would come up with such a "syntax"? An LLM?

lnenad 1y ago
I have to agree, it looks wild, even the simpler examples don't feel ergonomic.
ljm 1y ago
… I think I’ll just stick with pydantic AI for now
convo-lang 1y ago
Sometimes I feel like an LLM . I takes a little getting used to, but that is the same for any new language. And the Convo-Lang syntax highlighter helps to. The triple questions marks (???) are used to enclose natural language that is evaluated by the LLM and is considered an inline-prompt since it is evaluated inline within a function / tool call. I wanted there to be a very clear delineation between the deterministic code that is executed by the Convo-Lang interpreter and the natural language that is evaluated by the LLM. I also wanted there to be as little need for escape characters as possible. The content in the parentheses following the triple question marks is the header of the inline-prompt and consists of modifiers that control the context and response format of the LLM. Here is a breakdown of the header of the first inline-prompt: (+ boolean /m last:3 task:Inspecting message) ---- - modifier: + - name: Continue conversation - description: Includes all previous messages of the current conversation as context ---- - modifier: /m - name: Moderator Tag - description: Wraps the content of the prompt in a <moderator> xml tag and injects instruction into the system describing how to handle moderator tags ---- - modifier: last:{number} - name: Select Last - description: Discards all but the last three messages from the current conversation when used with the (+) modifier ---- - modifier: task:{string} - name: Task Description - description: Used by UI components to display a message to the user describing what the LLM is doing. ---- Here is a link to the Convo-Lang docs for inline-prompts - https://learn.convo-lang.ai/#inline-prompts https://learn.convo-lang.ai/#inline-prompts

lnenad 1y ago

I have to agree, it looks wild, even the simpler examples don't feel ergonomic.

ljm 1y ago

… I think I’ll just stick with pydantic AI for now

convo-lang 1y ago

Sometimes I feel like an LLM . I takes a little getting used to, but that is the same for any new language. And the Convo-Lang syntax highlighter helps to. The triple questions marks (???) are used to enclose natural language that is evaluated by the LLM and is considered an inline-prompt since it is evaluated inline within a function / tool call. I wanted there to be a very clear delineation between the deterministic code that is executed by the Convo-Lang interpreter and the natural language that is evaluated by the LLM. I also wanted there to be as little need for escape characters as possible. The content in the parentheses following the triple question marks is the header of the inline-prompt and consists of modifiers that control the context and response format of the LLM. Here is a breakdown of the header of the first inline-prompt: (+ boolean /m last:3 task:Inspecting message) ---- - modifier: + - name: Continue conversation - description: Includes all previous messages of the current conversation as context ---- - modifier: /m - name: Moderator Tag - description: Wraps the content of the prompt in a <moderator> xml tag and injects instruction into the system describing how to handle moderator tags ---- - modifier: last:{number} - name: Select Last - description: Discards all but the last three messages from the current conversation when used with the (+) modifier ---- - modifier: task:{string} - name: Task Description - description: Used by UI components to display a message to the user describing what the LLM is doing. ---- Here is a link to the Convo-Lang docs for inline-prompts - https://learn.convo-lang.ai/#inline-prompts https://learn.convo-lang.ai/#inline-prompts