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AI code archaeology
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lib/ai/tools/search.ex
defmodule AI.Tools.Search do
@max_search_results 5
@behaviour AI.Tools
@impl AI.Tools
def spec() do
%{
type: "function",
function: %{
name: "search_tool",
description: """
The search tool uses a semantic search to find files that match your
query input. The entire project has been indexed using a deep vector
space, with each file being pre-processed by an AI to summarize its
contents and behaviors, and to generate a list of symbols in the file.
This allows you to craft your query using phrases likely to match the
description of the code's behavior, rather than just the code itself.
""",
parameters: %{
type: "object",
required: ["query"],
properties: %{
query: %{
type: "string",
description: "The search query string."
}
}
}
}
}
end
@impl AI.Tools
def call(agent, args) do
with {:ok, query} <- Map.fetch(args, "query") do
status_id = Tui.add_step("Searching", query)
with {:ok, matches} <- search(query, agent.opts) do
Tui.finish_step(status_id, :ok)
matches
|> Enum.map(fn {file, score, data} ->
"""
# `#{file}` (cosine similarity: #{score})
#{data["summary"]}
"""
end)
|> Enum.join("\n-----\n")
|> then(fn res -> {:ok, "[search_tool]\n#{res}"} end)
end
end
end
# -----------------------------------------------------------------------------
# Searches the database for matches to the search query. Returns a list of
# `{file, score, data}` tuples.
# -----------------------------------------------------------------------------
defp search(query, opts) do
opts
|> Map.put(:concurrency, opts.concurrency)
|> Map.put(:detail, true)
|> Map.put(:limit, @max_search_results)
|> Map.put(:query, query)
|> Search.new()
|> Search.get_results()
|> then(&{:ok, &1})
end
end