LLM that can call multiple tool APIs with one request
1–10 of 69 posts
Re: LLM that can call multiple tool APIs with one request
#2I have a saying: "any sufficiently advanced agent is indistinguishable from a DSL"
If I'm really leaning into multi-tool use for anything resembling a mutation, then I'd like to see an execution plan first. In my experience, asking an AI to code up a script that calls some functions with the same signature as tools and then executing that script actually ends up being more accurate than asking it to internalize its algorithm. Plus, I can audit it before I run it. This is effectively the same as asking it to "think step by step."
I like the idea of Command R+ but multitool feels like barking up the wrong tree. Maybe my use cases are too myopic.
Re: LLM that can call multiple tool APIs with one request
#3I really like the stuff coming from Cohere.
I know they're not considered the leader in the foundational model space, but their developer documentation is great, their api is really nice to use, and they have a set of products that really differentiate themselves from OpenAI and Anthropic and others. I'm rooting for the success of this company.
That said, we as an industry need to be moving away from langchain, not more deeply embedding ourselves in that monstrosity. It’s just way too much of its own thing now and you can totally start to see how the VC funding is shaping their incentives. They put everyone who uses it in a position of massive technical debt, create more abstractions like langgraph to lock people into their tools and then and then create paid tools on top of it to solve the problems that they created (langsmith).
Re: LLM that can call multiple tool APIs with one request
#4I really like the stuff coming from Cohere. I know they're not considered the leader in the foundational model space, but their developer documentation is great, their api is really nice to use, and they have a set of products that really differentiate themselves from OpenAI and Anthropic and others. I'm rooting for the success of this company. That said, we as an industry need to be moving away from langchain, not m…
massive technical debt
create more abstractions
create paid tools.. to solve the problems that they created
Re: LLM that can call multiple tool APIs with one request
#5I really like the stuff coming from Cohere. I know they're not considered the leader in the foundational model space, but their developer documentation is great, their api is really nice to use, and they have a set of products that really differentiate themselves from OpenAI and Anthropic and others. I'm rooting for the success of this company. That said, we as an industry need to be moving away from langchain, not m…
Do you use another library instead?
Re: LLM that can call multiple tool APIs with one request
#6I have a saying: "any sufficiently advanced agent is indistinguishable from a DSL" If I'm really leaning into multi-tool use for anything resembling a mutation, then I'd like to see an execution plan first. In my experience, asking an AI to code up a script that calls some functions with the same signature as tools and then executing that script actually ends up being more accurate than asking it to internalize its a…
You mean manually pre-baking a DAG from the user query, then “spawning” other LLMs to resolve each node and pass their input up the graph? This is the approach we take too. It seems to be a sufficiently performant approach that is - intuitively - generically useful regardless of ontology / domain, but would love to hear others’ experiences.
It would be nice to know if this is sort of how OpenAI’s native “file_search” retriever works - that’s certainly the suggestion in some of the documentation but it hasn’t, to my knowledge, been confirmed.
Re: LLM that can call multiple tool APIs with one request
#7I do this for a living, Ask Me Anything.
Before they were called tools they were called function calls in ChatGpt.
Before that we had response_format = "json_object"
And even before that we were prompting with function signatures and asking it to output parameters.
Re: LLM that can call multiple tool APIs with one request
#8I have a saying: "any sufficiently advanced agent is indistinguishable from a DSL" If I'm really leaning into multi-tool use for anything resembling a mutation, then I'd like to see an execution plan first. In my experience, asking an AI to code up a script that calls some functions with the same signature as tools and then executing that script actually ends up being more accurate than asking it to internalize its a…
I think you are imagining a scenario where you are using the LLM manually. Tools are designed to serve as a backend for other GPT like products.
You don't have the capacity to "audit" stuff.
Furthermore tool execution occurs not in the LLM but in the code that calls the LLM through API. So whatever code executes the tool, it also orders the calling sequence graph. You don't need to audit it, you are calling it.
Re: LLM that can call multiple tool APIs with one request
#9I have a saying: "any sufficiently advanced agent is indistinguishable from a DSL" If I'm really leaning into multi-tool use for anything resembling a mutation, then I'd like to see an execution plan first. In my experience, asking an AI to code up a script that calls some functions with the same signature as tools and then executing that script actually ends up being more accurate than asking it to internalize its a…
You mean manually pre-baking a DAG from the user query, then “spawning” other LLMs to resolve each node and pass their input up the graph? This is the approach we take too. It seems to be a sufficiently performant approach that is - intuitively - generically useful regardless of ontology / domain, but would love to hear others’ experiences. It would be nice to know if this is sort of how OpenAI’s native “file_search”…
No. The DAG should be "manually pre-baked" ( defined at compile/design time).
In runtime you only parse the "user question" (user prompt) into a starting and end node, which is equivalent to a function call.
So the question
"What league does Messi play in?"
Is parsed by the llm as
League("Messi")
So if your dag only contains the functions team(player) and league(team), you can still solve the question.
But the llm isn't tasked with resolving the dag, that's code, let the llm chill and do what it's good at, don't make it code a for loop for you
Re: LLM that can call multiple tool APIs with one request
#10Earlier quoted context omitted.
You mean manually pre-baking a DAG from the user query, then “spawning” other LLMs to resolve each node and pass their input up the graph? This is the approach we take too. It seems to be a sufficiently performant approach that is - intuitively - generically useful regardless of ontology / domain, but would love to hear others’ experiences. It would be nice to know if this is sort of how OpenAI’s native “file_search”…
No. The DAG should be "manually pre-baked" ( defined at compile/design time). In runtime you only parse the "user question" (user prompt) into a starting and end node, which is equivalent to a function call. So the question "What league does Messi play in?" Is parsed by the llm as League("Messi") So if your dag only contains the functions team(player) and league(team), you can still solve the question. But the llm is…
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