Files
sure/app/models/chat.rb
Guillem Arias Fauste 8251b7e4d6 feat(ai): add Anthropic provider with chat parity (1/5) (#1983)
* feat(ai): add Anthropic provider with chat parity (1/5)

Introduces Provider::Anthropic alongside Provider::Openai, implementing
the LlmConcept chat_response contract over the official anthropic Ruby
SDK. Batch ops, PDF, and RAG land in follow-up PRs.

- Provider::Anthropic uses Messages API for sync and streaming responses
- ChatConfig builds requests with ephemeral prompt-cache markers on the
  system prompt and the last tool definition
- MessageFormatter reconstructs multi-turn history (text + tool_use +
  tool_result blocks) from raw Message records, including the paired
  user-role tool_result turn Anthropic requires after every tool_use
- ChatParser maps Anthropic Message into the shared ChatResponse Data
- Registry, Setting, User, Chat default model wired for ANTHROPIC_*
  envs and Setting.anthropic_*; LLM_PROVIDER selects between providers
- Responder forwards raw conversation_history (Array<Message>) so
  providers without hosted conversation state can rebuild context
- OpenAI provider accepts and ignores the new kwarg (no behavior change)

Tests cover provider init, model gating, MessageFormatter for all turn
shapes, ChatConfig request building (max_tokens, system cache, tool
conversion), ChatParser for text / tool_use / mixed blocks, Registry
discovery, and mocked chat_response success / error / function_request
paths. Live VCR cassettes recorded in a follow-up with a real key.

Stacked PRs: 2/5 batch ops + cost ledger, 3/5 PDF, 4/5 pgvector RAG,
5/5 settings UI + disclosure.

* fix(ai): address PR review on Anthropic provider foundation

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).

* test(chat): make default_model tests resilient to ENV model overrides

CodeRabbit flagged on PR review: the new default_model tests asserted
against Provider::*::DEFAULT_MODEL, but Chat.default_model actually
returns Provider::*.effective_model.presence (which reads
OPENAI_MODEL / ANTHROPIC_MODEL from the environment). With either env
var set, the tests would fail intermittently even though routing was
correct.

- New default_model tests now assert against the provider's
  effective_model directly, so they verify the routing decision
  (which provider's value wins) without coupling to the constant.
- Pre-existing "creates with default model" assertions had the same
  brittleness; switch them to compare against Chat.default_model so
  the chosen model is whatever the env / Setting cascade resolves to.

Verified by running `ANTHROPIC_MODEL=claude-haiku-4-5 OPENAI_MODEL=gpt-4o
bin/rails test test/models/chat_test.rb` — 16 runs, 0 failures
(previously 2 pre-existing failures + 0 from the new tests).

* fix(ai): address local review on Anthropic foundation

- Provider::Anthropic#supports_pdf_processing? bypasses prefix gate for
  custom endpoints, mirroring supports_model?
- Provider::Anthropic#initialize raises Error when custom_endpoint? AND
  model.blank?, parity with Provider::Openai
- stream_chat_response captures partial usage on mid-stream errors and
  records it via the new on_partial callback so chat_response can skip
  the duplicate error row in the outer rescue
- safe_accumulated_message swallows the secondary failure when the SDK
  cannot reconstruct a snapshot
- langfuse_client memoizes properly (||= instead of =) so repeated calls
  don't churn Langfuse instances
- MessageFormatter sorts tool_calls by created_at then id so the
  message array is deterministic across replays; skips tool_calls
  missing both provider_call_id and provider_id rather than sending
  `id: nil` and getting rejected by Anthropic
- Setting.anthropic_access_token default falls back through
  ENV["ANTHROPIC_API_KEY"].presence (was missing .presence, so an
  empty-string env value bled through)
- User#openai_configured? / #anthropic_configured? delegate to the
  Provider::* class methods — single source of truth
- Assistant::Responder renames the OpenAI-shape history builder
  conversation_history → openai_messages_payload so the kwarg name
  matches the local method name (messages: openai_messages_payload,
  conversation_history: chat_message_records)
- Assistant::Builtin stale-history comment updated to reference both
  builders

Adds a streaming chat_response test using ad-hoc subclasses of the
SDK event types so the case/when dispatch matches via is_a? without
stubbing class-level === behavior.

* test(ai): add Anthropic tool_use round-trip + multi-tool turn coverage

Addresses @jjmata's "worth confirming" note on PR #1983: tool-use turns
from prior assistant messages must round-trip correctly when retrieved
from the database.

- New `ChatParser → ToolCall::Function → MessageFormatter` test walks
  the full path: Anthropic response with a tool_use block →
  ChatFunctionRequest → ToolCall::Function.from_function_request →
  persisted on the AssistantMessage → MessageFormatter rebuild on the
  next turn. Asserts the original `tool_use.id` is preserved end-to-end
  as both `tool_use.id` and the paired `tool_result.tool_use_id`, and
  that the original `input` hash and serialized result content survive.
- New multi-tool assistant turn test confirms two tool_use blocks on a
  single assistant message render as two tool_use blocks followed by
  two paired tool_result blocks in a single user-role follow-up,
  matching Anthropic's required alternation.

Both tests exercise the existing PR1 code without behavior changes.

* test(ai): require "ostruct" explicitly in Anthropic provider tests

OpenStruct is moving out of Ruby's default load path (warning in 3.4+,
removed in 3.5+). Tests work today because ActiveSupport transitively
loads it, but that's incidental. Match the existing convention in
test/controllers/settings/hostings_controller_test.rb which explicitly
requires ostruct for the same reason.

* fix(ai): sanitize Langfuse warn logs, normalize tool_use.input, dedup history fetch

Addresses three open CodeRabbit findings on PR #1983.

- Provider::Anthropic Langfuse rescue branches no longer include
  `e.full_message` in `Rails.logger.warn`. `full_message` bundles the
  backtrace + cause chain and on some SDK error types includes the
  serialized request/response payload (prompt, model output). Logs
  now report `#{e.class}: #{e.message}` only. Three sites:
  create_langfuse_trace, log_langfuse_generation, upsert_langfuse_trace.
  Note: Provider::Openai has the same pattern (copy-pasted source) —
  harmonization deferred to a follow-up cleanup PR; this commit fixes
  only the Anthropic provider to keep PR scope tight.

- MessageFormatter#parse_arguments now coerces any non-Hash parsed
  result to `{}`. Anthropic's Messages API requires `tool_use.input`
  to be a JSON object (map); a stored ToolCall::Function record whose
  arguments parse to a scalar, bool, or array (corrupt row, legacy
  data, cross-provider bleed) would otherwise produce a payload the
  API rejects. Normal flow stores Hash arguments end-to-end so the
  fix is defensive — adds 2 tests covering scalar/array JSON strings
  and non-String non-Hash inputs.

- Assistant::Responder dedups the chat-history fetch. The previous
  layout fired two near-identical `chat.messages.where(...).includes(
  :tool_calls).ordered` queries per LLM turn (one for the OpenAI-shape
  payload, one for the raw-records kwarg). A new memoized
  `complete_chat_messages` fetches once; `chat_message_records` filters
  out the current message via `Array#reject`, `openai_messages_payload`
  iterates the cached array unchanged. One SQL query per turn instead
  of two. Memoization scope = single Responder instance (per LLM call),
  so cache invalidation is not a concern.

All 4370 tests pass (1 pre-existing libvips env error unrelated).
Rubocop + brakeman clean.

* fix(ci): replace sk-ant- prefixed test placeholders

Pipelock secret scanner pattern-matches `sk-ant-*` as a real Anthropic
API key and fails the PR security-scan check. Test stubs and
ClimateControl env values used `sk-ant-test`, `sk-ant-from-setting`,
`sk-ant-x`, `sk-ant-y` as obvious placeholders, but the scanner does
not care about value entropy.

Switched to `fake-anthropic-key-*` / `fake-token-*` strings so the
scanner stops flagging them. No production code touched, no behavior
change — Provider::Anthropic still accepts any non-blank token.
2026-05-31 16:11:28 +02:00

189 lines
5.2 KiB
Ruby

class Chat < ApplicationRecord
include Debuggable
RATE_LIMIT_PATTERNS = [
/\b429\b/i,
/rate limit/i,
/too many requests/i,
/quota exceeded/i
].freeze
TEMPORARY_PROVIDER_PATTERNS = [
/\b5\d\d\b/i,
/service unavailable/i,
/temporarily unavailable/i,
/gateway timeout/i,
/bad gateway/i,
/overloaded/i,
/time(?:out|d?\s*out)/i,
/connection reset/i
].freeze
AUTH_CONFIGURATION_PATTERNS = [
/unauthorized/i,
/authentication/i,
/invalid api key/i,
/incorrect api key/i,
/access token/i
].freeze
belongs_to :user
has_one :viewer, class_name: "User", foreign_key: :last_viewed_chat_id, dependent: :nullify # "Last chat user has viewed"
has_many :messages, dependent: :destroy
validates :title, presence: true
scope :ordered, -> { order(created_at: :desc) }
class << self
def start!(prompt, model:)
# Ensure we have a valid model by using the default if none provided
effective_model = model.presence || default_model
create!(
title: generate_title(prompt),
messages: [ UserMessage.new(content: prompt, ai_model: effective_model) ]
)
end
def generate_title(prompt)
prompt.first(80)
end
# Returns the default AI model to use for chats.
# Resolved from the configured llm_provider so installs that swap providers
# don't have to manually update every chat default. Falls through to a
# provider that actually has credentials configured, otherwise the chosen
# provider's classes would later raise "no LLM provider supports model …"
# even when the other provider is configured.
def default_model
prefers_anthropic = Setting.llm_provider == "anthropic"
if prefers_anthropic && Provider::Anthropic.configured?
Provider::Anthropic.effective_model.presence || Setting.anthropic_model
elsif Provider::Openai.configured?
Provider::Openai.effective_model.presence || Setting.openai_model
elsif Provider::Anthropic.configured?
Provider::Anthropic.effective_model.presence || Setting.anthropic_model
else
Provider::Openai.effective_model.presence || Setting.openai_model
end
end
end
def needs_assistant_response?
conversation_messages.ordered.last.role != "assistant"
end
def retry_last_message!
update!(error: nil)
last_message = conversation_messages.ordered.last
if last_message.present? && last_message.role == "user"
ask_assistant_later(last_message)
end
end
def update_latest_response!(provider_response_id)
update!(latest_assistant_response_id: provider_response_id)
end
def add_error(e)
update!(error: build_error_payload(e).to_json)
broadcast_append target: messages_target, partial: "chats/error", locals: { chat: self }
end
def presentable_error_message
return nil if error.blank?
parsed_error_payload["message"].presence || classify_error_message(error)
end
def technical_error_message
parsed_error_payload["technical_message"].presence || parsed_legacy_error_message || error
end
def clear_error
update! error: nil
broadcast_remove target: error_target
end
def conversation_messages
messages.where(type: [ "UserMessage", "AssistantMessage" ])
end
def messages_target
ActionView::RecordIdentifier.dom_id(self, :messages)
end
def error_target
ActionView::RecordIdentifier.dom_id(self, :chat_error)
end
def ask_assistant_later(message)
clear_error
pending = messages.create!(type: "AssistantMessage", content: "", ai_model: message.ai_model, status: :pending)
AssistantResponseJob.perform_later(message, pending)
end
def ask_assistant(message, assistant_message: nil)
assistant.respond_to(message, assistant_message: assistant_message)
end
private
def build_error_payload(error)
technical_message = error_message_for(error)
{
message: classify_error_message(technical_message),
technical_message: technical_message,
type: error.class.name
}
end
def classify_error_message(message)
normalized_message = message.to_s.strip
return I18n.t("chat.errors.default") if normalized_message.blank?
if RATE_LIMIT_PATTERNS.any? { |pattern| normalized_message.match?(pattern) }
I18n.t("chat.errors.rate_limited")
elsif TEMPORARY_PROVIDER_PATTERNS.any? { |pattern| normalized_message.match?(pattern) }
I18n.t("chat.errors.temporarily_unavailable")
elsif AUTH_CONFIGURATION_PATTERNS.any? { |pattern| normalized_message.match?(pattern) }
I18n.t("chat.errors.misconfigured")
else
I18n.t("chat.errors.default")
end
end
def parsed_error_payload
return {} if error.blank?
return error if error.is_a?(Hash)
parsed = JSON.parse(error)
parsed.is_a?(Hash) ? parsed : {}
rescue JSON::ParserError, TypeError
{}
end
def error_message_for(error)
error.respond_to?(:message) ? error.message.to_s : error.to_s
rescue StandardError
""
end
def parsed_legacy_error_message
parsed = JSON.parse(error)
parsed.is_a?(String) ? parsed : nil
rescue JSON::ParserError, TypeError
nil
end
def assistant
@assistant ||= Assistant.for_chat(self)
end
end