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AI code archaeology
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lib/ai.ex
defmodule AI do
@moduledoc """
AI is a behavior module that defines the interface for interacting with
OpenAI's API. It provides a common interface for the various OpenAI-powered
operations used by the application.
"""
defstruct [
:client,
:api_key
]
@type t :: %__MODULE__{
client: %AI.OpenAI{}
}
@api_timeout 5 * 60 * 1000
@default_max_attempts 3
@retry_interval 250
@doc """
Create a new AI instance. Instances share the same client connection.
"""
def new() do
client = AI.OpenAI.new(recv_timeout: @api_timeout)
%AI{client: client}
end
# -----------------------------------------------------------------------------
# Completions
# -----------------------------------------------------------------------------
def get_completion(ai, model, msgs, tools) do
request = [ai.client, model, msgs, tools]
do_get_completion(ai, request, @default_max_attempts, 1)
end
defp do_get_completion(_ai, _request, max, attempt) when attempt > max do
{:error, "Request timed out after #{attempt} attempts."}
end
defp do_get_completion(ai, request, max, attempt) do
if attempt > 1, do: Process.sleep(@retry_interval)
AI.OpenAI
|> apply(:get_completion, request)
|> case do
{:error, :timeout} -> do_get_completion(ai, request, max, attempt + 1)
etc -> etc
end
end
# -----------------------------------------------------------------------------
# Embeddings
# -----------------------------------------------------------------------------
@embeddings_model "text-embedding-3-large"
# It's actually 8192 for this model, but this gives us a little bit of
# wiggle room in case the tokenizer we are using falls behind.
@embeddings_token_limit 8100
@doc """
Get embeddings for the given text. The text is split into chunks of 8192
tokens to avoid exceeding the model's input limit. Returns a list of
embeddings for each chunk.
"""
def get_embeddings(ai, text) do
text
|> AI.Tokenizer.chunk(@embeddings_token_limit, @embeddings_model)
|> Enum.map(&[ai.client, @embeddings_model, &1])
|> Enum.reduce_while([], fn request, embeddings ->
ai
|> get_embedding(request, @default_max_attempts, 1)
|> case do
{:ok, embedding} -> {:cont, [embedding | embeddings]}
{:error, reason} -> {:halt, {:error, reason}}
end
end)
|> case do
{:error, reason} -> {:error, inspect(reason)}
embeddings -> {:ok, Enum.reverse(embeddings)}
end
end
defp get_embedding(_ai, _request, max, attempt) when attempt > max do
{:error, "Request timed out after #{attempt} attempts."}
end
defp get_embedding(ai, request, max, attempt) do
if attempt > 1, do: Process.sleep(@retry_interval)
AI.OpenAI
|> apply(:get_embedding, request)
|> case do
{:error, :timeout} -> get_embedding(ai, request, max, attempt + 1)
etc -> etc
end
end
end