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Surface fixes raised by Codex + CodeRabbit on PR 1/5:
- Provider::Anthropic#chat_response now accepts (and ignores) a
`messages:` kwarg. Assistant::Responder passes both `messages:`
(OpenAI-shape) and `conversation_history:` (raw Message records) for
cross-provider parity, so the previous signature raised
ArgumentError on the first chat turn through the Anthropic provider.
- Provider::Anthropic#supports_model? bypasses the `claude` prefix
gate when a custom base_url is configured, mirroring the OpenAI
provider. Bedrock-shaped IDs like
`anthropic.claude-sonnet-4-5-20250929-v1:0` and
`claude-opus-4@20250514` are otherwise rejected by
Assistant::Provided#get_model_provider and the chat dies.
- Setting.anthropic_access_token is now in
EncryptedSettingFields::ENCRYPTED_FIELDS so the Anthropic API key
is encrypted at rest like every other provider secret. Previously
plaintext while siblings (openai_access_token, twelve_data_api_key,
external_assistant_token) were ciphertext.
- Chat.default_model falls back to whichever provider is actually
configured. Previously, with LLM_PROVIDER=anthropic but no
Anthropic credentials, the default model resolved to a Claude ID
that no registered provider supported, so chats failed even when
OpenAI was fully configured. Adds Provider::{Anthropic,Openai}#configured?
class methods for the readable callsite.
- Provider::Anthropic.effective_model uses
`ENV["ANTHROPIC_MODEL"].presence || Setting.anthropic_model` so the
Setting lookup is only performed when the env var is absent — the
previous `ENV.fetch(KEY, default)` evaluated the default arg
eagerly on every call.
- Provider::Anthropic::ChatConfig#anthropic_input_schema strips both
`:strict` and `"strict"` keys so JSON-decoded schemas with string
keys cannot leak the OpenAI-only flag through to Anthropic.
Test coverage added: supports_model? bypass on custom endpoints,
chat_response messages: kwarg compatibility, default_model fallback
in the three credential combinations, configured? against ENV +
Setting, strict-flag stripping for both key types, and a
`Setting.expects(:anthropic_model).never` assertion proving the
ENV-precedence test now exercises the lazy path.
All 4365 tests pass (1 pre-existing libvips env error unrelated).
201 lines
7.0 KiB
Ruby
201 lines
7.0 KiB
Ruby
require "test_helper"
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class Provider::AnthropicTest < ActiveSupport::TestCase
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include LLMInterfaceTest
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setup do
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@subject = @anthropic = Provider::Anthropic.new(
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ENV.fetch("ANTHROPIC_API_KEY", "test-anthropic-token")
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)
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@subject_model = "claude-sonnet-4-6"
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end
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test "provider_name returns Anthropic for standard provider" do
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assert_equal "Anthropic", @subject.provider_name
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end
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test "provider_name returns custom info for custom base_url" do
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custom = Provider::Anthropic.new(
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"test-token",
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base_url: "https://bedrock.example.com/anthropic",
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model: "claude-opus-4-7"
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)
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assert_equal "Custom Anthropic-compatible (https://bedrock.example.com/anthropic)", custom.provider_name
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end
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test "supports_model? returns true for claude prefix" do
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assert @subject.supports_model?("claude-sonnet-4-6")
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assert @subject.supports_model?("claude-opus-4-7")
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assert @subject.supports_model?("claude-haiku-4-5")
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assert_not @subject.supports_model?("gpt-4.1")
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end
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test "supports_model? bypasses the prefix gate for custom endpoints" do
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custom = Provider::Anthropic.new(
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"test-token",
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base_url: "https://bedrock.example.com/anthropic",
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model: "anthropic.claude-sonnet-4-5-20250929-v1:0"
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)
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# Bedrock-shaped IDs start with "anthropic", not "claude" — would fail the
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# default prefix check, but custom endpoints must accept any model.
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assert custom.supports_model?("anthropic.claude-sonnet-4-5-20250929-v1:0")
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assert custom.supports_model?("claude-opus-4@20250514")
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assert custom.supports_model?("any-string-the-endpoint-accepts")
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end
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test "supported_models_description returns prefixes for standard provider" do
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assert_equal "models starting with: claude", @subject.supported_models_description
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end
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test "supports_pdf_processing? true for claude models" do
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assert @subject.supports_pdf_processing?(model: "claude-sonnet-4-6")
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assert_not @subject.supports_pdf_processing?(model: "gpt-4o")
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end
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test "effective_model defers to ENV when set without consulting Setting" do
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ClimateControl.modify("ANTHROPIC_MODEL" => "claude-haiku-4-5") do
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Setting.expects(:anthropic_model).never
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assert_equal "claude-haiku-4-5", Provider::Anthropic.effective_model
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end
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end
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test "configured? reflects ENV and Setting presence" do
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ClimateControl.modify("ANTHROPIC_ACCESS_TOKEN" => nil, "ANTHROPIC_API_KEY" => nil) do
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Setting.stubs(:anthropic_access_token).returns(nil)
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assert_not Provider::Anthropic.configured?
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Setting.stubs(:anthropic_access_token).returns("sk-ant-x")
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assert Provider::Anthropic.configured?
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end
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ClimateControl.modify("ANTHROPIC_API_KEY" => "sk-ant-y") do
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Setting.stubs(:anthropic_access_token).returns(nil)
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assert Provider::Anthropic.configured?
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end
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end
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test "effective_model falls back to default when nothing set" do
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ClimateControl.modify("ANTHROPIC_MODEL" => nil) do
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Setting.stubs(:anthropic_model).returns(nil)
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assert_equal Provider::Anthropic::DEFAULT_MODEL, Provider::Anthropic.effective_model
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end
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end
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test "chat_response wraps Anthropic SDK errors in Provider::Anthropic::Error" do
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fake_client = mock
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@subject.instance_variable_set(:@client, fake_client)
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messages = mock
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fake_client.stubs(:messages).returns(messages)
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messages.expects(:create).raises(StandardError.new("rate limit exceeded"))
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response = @subject.chat_response("hi", model: @subject_model)
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assert_not response.success?
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assert_kind_of Provider::Anthropic::Error, response.error
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assert_match(/rate limit/i, response.error.message)
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end
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test "chat_response accepts messages: kwarg passed by Responder without raising" do
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# The OpenAI-shaped `messages:` array is passed alongside `conversation_history:`
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# for cross-provider parity. Anthropic ignores it but must still accept it as
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# a keyword argument — historical regression that broke the first chat turn.
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fake_client = stub_anthropic_client_with(
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build_anthropic_message(
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id: "msg_kw",
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model: @subject_model,
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text_blocks: [ "ok" ],
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tool_use_blocks: [],
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usage: { input_tokens: 1, output_tokens: 1 }
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)
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)
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@subject.instance_variable_set(:@client, fake_client)
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response = @subject.chat_response(
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"hi",
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model: @subject_model,
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messages: [ { role: "user", content: "hi" } ],
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conversation_history: []
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)
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assert response.success?
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end
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test "chat_response returns parsed ChatResponse on success" do
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fake_client = stub_anthropic_client_with(
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build_anthropic_message(
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id: "msg_abc",
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model: @subject_model,
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text_blocks: [ "Hello there." ],
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tool_use_blocks: [],
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usage: { input_tokens: 12, output_tokens: 5 }
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)
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)
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@subject.instance_variable_set(:@client, fake_client)
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response = @subject.chat_response("hi", model: @subject_model)
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assert response.success?
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assert_equal "msg_abc", response.data.id
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assert_equal @subject_model, response.data.model
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assert_equal 1, response.data.messages.size
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assert_equal "Hello there.", response.data.messages.first.output_text
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assert_empty response.data.function_requests
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end
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test "chat_response surfaces tool_use blocks as function_requests" do
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fake_client = stub_anthropic_client_with(
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build_anthropic_message(
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id: "msg_xyz",
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model: @subject_model,
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text_blocks: [],
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tool_use_blocks: [ { id: "toolu_1", name: "get_net_worth", input: { currency: "USD" } } ],
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usage: { input_tokens: 20, output_tokens: 8 }
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)
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)
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@subject.instance_variable_set(:@client, fake_client)
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response = @subject.chat_response(
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"What is my net worth?",
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model: @subject_model,
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functions: [ {
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name: "get_net_worth",
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description: "Gets a user's net worth",
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params_schema: { type: "object", properties: {}, required: [], additionalProperties: false },
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strict: true
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} ]
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)
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assert response.success?
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assert_equal 1, response.data.function_requests.size
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req = response.data.function_requests.first
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assert_equal "toolu_1", req.call_id
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assert_equal "get_net_worth", req.function_name
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assert_equal({ currency: "USD" }.to_json, req.function_args)
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end
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private
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def stub_anthropic_client_with(message)
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messages = mock
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messages.stubs(:create).returns(message)
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client = mock
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client.stubs(:messages).returns(messages)
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client
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end
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def build_anthropic_message(id:, model:, text_blocks:, tool_use_blocks:, usage:)
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OpenStruct.new(
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id: id,
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model: model,
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content: text_blocks.map { |t| OpenStruct.new(type: :text, text: t) } +
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tool_use_blocks.map { |t| OpenStruct.new(type: :tool_use, id: t[:id], name: t[:name], input: t[:input]) },
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usage: OpenStruct.new(
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input_tokens: usage[:input_tokens],
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output_tokens: usage[:output_tokens]
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)
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)
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end
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end
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