Packages

fnord

0.5.6

AI code archaeology

Current section

Files

Jump to
fnord lib ai tools strategies search.ex
Raw

lib/ai/tools/strategies/search.ex

defmodule AI.Tools.Strategies.Search do
@behaviour AI.Tools
@impl AI.Tools
def ui_note_on_request(%{"query" => query}) do
{"Searching for research strategies", query}
end
@impl AI.Tools
def ui_note_on_result(_args, result) do
titles =
result
|> Jason.decode!()
|> Enum.map(fn %{"title" => title} -> "- #{title}" end)
|> Enum.join("\n")
{"Identified possible research strategies", "\n#{titles}"}
end
@impl AI.Tools
def read_args(%{"query" => query}), do: {:ok, %{"query" => query}}
def read_args(_args), do: AI.Tools.required_arg_error("query")
@impl AI.Tools
def spec() do
%{
type: "function",
function: %{
name: "strategies_search_tool",
description: """
"Research Strategies" are research plans that can be used to guide the
research strategy of the orchestrating AI agent. Research Strategies
are agnostic to the project and the context of the user's query,
instead focusing on the process to follow when researching specific
classes of problems.
This tool performs a semantic search of your saved research strategies.
Returns up to 10 matching strategies' title and prompt.
It is up to **YOU** to decide which strategy is most appropriate for
the user's query and to adapt it for the specific context.
After providing the strategy to the orchestrating AI agent, you may
elect to use the `save_strategy_tool` to refine the strategy by
improving the prompt, title, or example questions.
""",
strict: true,
parameters: %{
additionalProperties: false,
type: "object",
required: ["query"],
properties: %{
query: %{
type: "string",
description: """
The search query to use for the search. This will be matched
against example user queries that could be answered using the
identified research strategy.
Avoid including project-specific terms or details in your query.
Instead, focus on the CLASS of problem you are trying to solve.
"""
}
}
}
}
}
end
@impl AI.Tools
def call(_completion, args) do
with {:ok, query} <- Map.fetch(args, "query") do
query
|> Store.search_strategies()
|> Enum.reduce([], fn {score, prompt}, acc ->
with {:ok, info} <- Store.Strategy.read(prompt) do
data = %{
title: info.title,
prompt: info.prompt,
match_score: score
}
[data | acc]
end
end)
|> Enum.reverse()
|> then(&{:ok, &1})
end
end
end