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