Merge branch 'main' into issue-454-install-docs
This commit is contained in:
April M
commit
d8221cd2e4
28 changed files with 4338 additions and 2021 deletions
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@ -865,58 +865,99 @@ class OpenSearchVectorStoreComponentMultimodalMultiEmbedding(LCVectorStoreCompon
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metadatas.append(data_copy)
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self.log(metadatas)
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# Generate embeddings (threaded for concurrency) with retries
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def embed_chunk(chunk_text: str) -> list[float]:
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return selected_embedding.embed_documents([chunk_text])[0]
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# Generate embeddings with rate-limit-aware retry logic using tenacity
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from tenacity import (
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retry,
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retry_if_exception,
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stop_after_attempt,
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wait_exponential,
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)
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vectors: list[list[float]] | None = None
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last_exception: Exception | None = None
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delay = 1.0
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attempts = 0
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max_attempts = 3
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def is_rate_limit_error(exception: Exception) -> bool:
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"""Check if exception is a rate limit error (429)."""
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error_str = str(exception).lower()
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return "429" in error_str or "rate_limit" in error_str or "rate limit" in error_str
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def is_other_retryable_error(exception: Exception) -> bool:
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"""Check if exception is retryable but not a rate limit error."""
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# Retry on most exceptions except for specific non-retryable ones
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# Add other non-retryable exceptions here if needed
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return not is_rate_limit_error(exception)
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# Create retry decorator for rate limit errors (longer backoff)
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retry_on_rate_limit = retry(
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retry=retry_if_exception(is_rate_limit_error),
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stop=stop_after_attempt(5),
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wait=wait_exponential(multiplier=2, min=2, max=30),
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reraise=True,
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before_sleep=lambda retry_state: logger.warning(
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f"Rate limit hit for chunk (attempt {retry_state.attempt_number}/5), "
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f"backing off for {retry_state.next_action.sleep:.1f}s"
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),
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)
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# Create retry decorator for other errors (shorter backoff)
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retry_on_other_errors = retry(
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retry=retry_if_exception(is_other_retryable_error),
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stop=stop_after_attempt(3),
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wait=wait_exponential(multiplier=1, min=1, max=8),
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reraise=True,
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before_sleep=lambda retry_state: logger.warning(
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f"Error embedding chunk (attempt {retry_state.attempt_number}/3), "
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f"retrying in {retry_state.next_action.sleep:.1f}s: {retry_state.outcome.exception()}"
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),
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)
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def embed_chunk_with_retry(chunk_text: str, chunk_idx: int) -> list[float]:
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"""Embed a single chunk with rate-limit-aware retry logic."""
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@retry_on_rate_limit
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@retry_on_other_errors
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def _embed(text: str) -> list[float]:
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return selected_embedding.embed_documents([text])[0]
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while attempts < max_attempts:
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attempts += 1
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try:
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# Restrict concurrency for IBM/Watsonx models to avoid rate limits
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is_ibm = (embedding_model and "ibm" in str(embedding_model).lower()) or (
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selected_embedding and "watsonx" in type(selected_embedding).__name__.lower()
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return _embed(chunk_text)
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except Exception as e:
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logger.error(
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f"Failed to embed chunk {chunk_idx} after all retries: {e}",
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error=str(e),
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)
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logger.debug(f"Is IBM: {is_ibm}")
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max_workers = 1 if is_ibm else min(max(len(texts), 1), 8)
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raise
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with ThreadPoolExecutor(max_workers=max_workers) as executor:
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futures = {executor.submit(embed_chunk, chunk): idx for idx, chunk in enumerate(texts)}
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vectors = [None] * len(texts)
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for future in as_completed(futures):
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idx = futures[future]
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vectors[idx] = future.result()
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break
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except Exception as exc:
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last_exception = exc
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if attempts >= max_attempts:
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logger.error(
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f"Embedding generation failed for model {embedding_model} after retries",
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error=str(exc),
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)
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raise
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logger.warning(
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"Threaded embedding generation failed for model %s (attempt %s/%s), retrying in %.1fs",
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embedding_model,
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attempts,
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max_attempts,
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delay,
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)
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time.sleep(delay)
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delay = min(delay * 2, 8.0)
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# Restrict concurrency for IBM/Watsonx models to avoid rate limits
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is_ibm = (embedding_model and "ibm" in str(embedding_model).lower()) or (
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selected_embedding and "watsonx" in type(selected_embedding).__name__.lower()
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)
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logger.debug(f"Is IBM: {is_ibm}")
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if vectors is None:
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raise RuntimeError(
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f"Embedding generation failed for {embedding_model}: {last_exception}"
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if last_exception
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else f"Embedding generation failed for {embedding_model}"
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# For IBM models, use sequential processing with rate limiting
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# For other models, use parallel processing
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vectors: list[list[float]] = [None] * len(texts)
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if is_ibm:
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# Sequential processing with inter-request delay for IBM models
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inter_request_delay = 0.6 # ~1.67 req/s, safely under 2 req/s limit
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logger.info(
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f"Using sequential processing for IBM model with {inter_request_delay}s delay between requests"
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)
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for idx, chunk in enumerate(texts):
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if idx > 0:
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# Add delay between requests (but not before the first one)
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time.sleep(inter_request_delay)
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vectors[idx] = embed_chunk_with_retry(chunk, idx)
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else:
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# Parallel processing for non-IBM models
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max_workers = min(max(len(texts), 1), 8)
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logger.debug(f"Using parallel processing with {max_workers} workers")
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with ThreadPoolExecutor(max_workers=max_workers) as executor:
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futures = {executor.submit(embed_chunk_with_retry, chunk, idx): idx for idx, chunk in enumerate(texts)}
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for future in as_completed(futures):
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idx = futures[future]
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vectors[idx] = future.result()
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if not vectors:
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self.log(f"No vectors generated from documents for model {embedding_model}.")
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return
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|
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1735
flows/components/opensearch_multimodel.py
Normal file
1735
flows/components/opensearch_multimodel.py
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44
frontend/app/api/mutations/useOnboardingRollbackMutation.ts
Normal file
44
frontend/app/api/mutations/useOnboardingRollbackMutation.ts
Normal file
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@ -0,0 +1,44 @@
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import {
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type UseMutationOptions,
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useMutation,
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useQueryClient,
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} from "@tanstack/react-query";
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interface OnboardingRollbackResponse {
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message: string;
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}
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export const useOnboardingRollbackMutation = (
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options?: Omit<
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UseMutationOptions<OnboardingRollbackResponse, Error, void>,
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"mutationFn"
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>,
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) => {
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const queryClient = useQueryClient();
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async function rollbackOnboarding(): Promise<OnboardingRollbackResponse> {
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const response = await fetch("/api/onboarding/rollback", {
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method: "POST",
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headers: {
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"Content-Type": "application/json",
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},
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});
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if (!response.ok) {
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const error = await response.json();
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throw new Error(error.error || "Failed to rollback onboarding");
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}
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return response.json();
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}
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return useMutation({
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mutationFn: rollbackOnboarding,
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onSettled: () => {
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// Invalidate settings query to refetch updated data
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queryClient.invalidateQueries({ queryKey: ["settings"] });
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},
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...options,
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});
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};
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@ -4,6 +4,7 @@ import {
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useQueryClient,
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} from "@tanstack/react-query";
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import type { EndpointType } from "@/contexts/chat-context";
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import { useChat } from "@/contexts/chat-context";
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export interface RawConversation {
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response_id: string;
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|
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@ -50,6 +51,7 @@ export const useGetConversationsQuery = (
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options?: Omit<UseQueryOptions, "queryKey" | "queryFn">,
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) => {
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const queryClient = useQueryClient();
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const { isOnboardingComplete } = useChat();
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async function getConversations(context: { signal?: AbortSignal }): Promise<ChatConversation[]> {
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try {
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|
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@ -95,6 +97,11 @@ export const useGetConversationsQuery = (
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}
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}
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// Extract enabled from options and combine with onboarding completion check
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// Query is only enabled if onboarding is complete AND the caller's enabled condition is met
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const callerEnabled = options?.enabled ?? true;
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const enabled = isOnboardingComplete && callerEnabled;
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const queryResult = useQuery(
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{
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queryKey: ["conversations", endpoint, refreshTrigger],
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|
|
@ -106,6 +113,7 @@ export const useGetConversationsQuery = (
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refetchOnMount: false, // Don't refetch on every mount
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refetchOnWindowFocus: false, // Don't refetch when window regains focus
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...options,
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enabled, // Override enabled after spreading options to ensure onboarding check is applied
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},
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queryClient,
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||||
);
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|
|
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|||
|
|
@ -3,6 +3,8 @@ import {
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useQuery,
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useQueryClient,
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} from "@tanstack/react-query";
|
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import { useChat } from "@/contexts/chat-context";
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import { useProviderHealthQuery } from "./useProviderHealthQuery";
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type Nudge = string;
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@ -27,6 +29,13 @@ export const useGetNudgesQuery = (
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) => {
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const { chatId, filters, limit, scoreThreshold } = params ?? {};
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const queryClient = useQueryClient();
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const { isOnboardingComplete } = useChat();
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// Check if LLM provider is healthy
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||||
// If health data is not available yet, assume healthy (optimistic)
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||||
// Only disable if health data exists and shows LLM error
|
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const { data: health } = useProviderHealthQuery();
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const isLLMHealthy = health === undefined || (health?.status === "healthy" && !health?.llm_error);
|
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|
||||
function cancel() {
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queryClient.removeQueries({
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||||
|
|
@ -77,6 +86,11 @@ export const useGetNudgesQuery = (
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|||
}
|
||||
}
|
||||
|
||||
// Extract enabled from options and combine with onboarding completion and LLM health checks
|
||||
// Query is only enabled if onboarding is complete AND LLM provider is healthy AND the caller's enabled condition is met
|
||||
const callerEnabled = options?.enabled ?? true;
|
||||
const enabled = isOnboardingComplete && isLLMHealthy && callerEnabled;
|
||||
|
||||
const queryResult = useQuery(
|
||||
{
|
||||
queryKey: ["nudges", chatId, filters, limit, scoreThreshold],
|
||||
|
|
@ -91,6 +105,7 @@ export const useGetNudgesQuery = (
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|||
return Array.isArray(data) && data.length === 0 ? 5000 : false;
|
||||
},
|
||||
...options,
|
||||
enabled, // Override enabled after spreading options to ensure onboarding check is applied
|
||||
},
|
||||
queryClient,
|
||||
);
|
||||
|
|
|
|||
|
|
@ -5,6 +5,7 @@ import {
|
|||
} from "@tanstack/react-query";
|
||||
import { useChat } from "@/contexts/chat-context";
|
||||
import { useGetSettingsQuery } from "./useGetSettingsQuery";
|
||||
import { useGetTasksQuery } from "./useGetTasksQuery";
|
||||
|
||||
export interface ProviderHealthDetails {
|
||||
llm_model: string;
|
||||
|
|
@ -40,11 +41,20 @@ export const useProviderHealthQuery = (
|
|||
) => {
|
||||
const queryClient = useQueryClient();
|
||||
|
||||
// Get chat error state from context (ChatProvider wraps the entire app in layout.tsx)
|
||||
const { hasChatError, setChatError } = useChat();
|
||||
// Get chat error state and onboarding completion from context (ChatProvider wraps the entire app in layout.tsx)
|
||||
const { hasChatError, setChatError, isOnboardingComplete } = useChat();
|
||||
|
||||
const { data: settings = {} } = useGetSettingsQuery();
|
||||
|
||||
// Check if there are any active ingestion tasks
|
||||
const { data: tasks = [] } = useGetTasksQuery();
|
||||
const hasActiveIngestion = tasks.some(
|
||||
(task) =>
|
||||
task.status === "pending" ||
|
||||
task.status === "running" ||
|
||||
task.status === "processing",
|
||||
);
|
||||
|
||||
async function checkProviderHealth(): Promise<ProviderHealthResponse> {
|
||||
try {
|
||||
const url = new URL("/api/provider/health", window.location.origin);
|
||||
|
|
@ -55,6 +65,7 @@ export const useProviderHealthQuery = (
|
|||
}
|
||||
|
||||
// Add test_completion query param if specified or if chat error exists
|
||||
// Use the same testCompletion value that's in the queryKey
|
||||
const testCompletion = params?.test_completion ?? hasChatError;
|
||||
if (testCompletion) {
|
||||
url.searchParams.set("test_completion", "true");
|
||||
|
|
@ -101,7 +112,10 @@ export const useProviderHealthQuery = (
|
|||
}
|
||||
}
|
||||
|
||||
const queryKey = ["provider", "health", params?.test_completion];
|
||||
// Include hasChatError in queryKey so React Query refetches when it changes
|
||||
// This ensures the health check runs with test_completion=true when chat errors occur
|
||||
const testCompletion = params?.test_completion ?? hasChatError;
|
||||
const queryKey = ["provider", "health", testCompletion, hasChatError];
|
||||
const failureCountKey = queryKey.join("-");
|
||||
|
||||
const queryResult = useQuery(
|
||||
|
|
@ -143,7 +157,11 @@ export const useProviderHealthQuery = (
|
|||
refetchOnWindowFocus: false, // Disabled to reduce unnecessary calls on tab switches
|
||||
refetchOnMount: true,
|
||||
staleTime: 30000, // Consider data stale after 30 seconds
|
||||
enabled: !!settings?.edited && options?.enabled !== false, // Only run after onboarding is complete
|
||||
enabled:
|
||||
!!settings?.edited &&
|
||||
isOnboardingComplete &&
|
||||
!hasActiveIngestion && // Disable health checks when ingestion is happening
|
||||
options?.enabled !== false, // Only run after onboarding is complete
|
||||
...options,
|
||||
},
|
||||
queryClient,
|
||||
|
|
|
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|
|
@ -1,13 +1,13 @@
|
|||
import type { Dispatch, SetStateAction } from "react";
|
||||
import { useEffect, useState } from "react";
|
||||
import IBMLogo from "@/components/icons/ibm-logo";
|
||||
import { LabelInput } from "@/components/label-input";
|
||||
import { LabelWrapper } from "@/components/label-wrapper";
|
||||
import IBMLogo from "@/components/icons/ibm-logo";
|
||||
import { Switch } from "@/components/ui/switch";
|
||||
import {
|
||||
Tooltip,
|
||||
TooltipContent,
|
||||
TooltipTrigger,
|
||||
Tooltip,
|
||||
TooltipContent,
|
||||
TooltipTrigger,
|
||||
} from "@/components/ui/tooltip";
|
||||
import { useDebouncedValue } from "@/lib/debounce";
|
||||
import type { OnboardingVariables } from "../../api/mutations/useOnboardingMutation";
|
||||
|
|
@ -18,273 +18,273 @@ import { AdvancedOnboarding } from "./advanced";
|
|||
import { ModelSelector } from "./model-selector";
|
||||
|
||||
export function IBMOnboarding({
|
||||
isEmbedding = false,
|
||||
setSettings,
|
||||
sampleDataset,
|
||||
setSampleDataset,
|
||||
setIsLoadingModels,
|
||||
alreadyConfigured = false,
|
||||
existingEndpoint,
|
||||
existingProjectId,
|
||||
hasEnvApiKey = false,
|
||||
isEmbedding = false,
|
||||
setSettings,
|
||||
sampleDataset,
|
||||
setSampleDataset,
|
||||
setIsLoadingModels,
|
||||
alreadyConfigured = false,
|
||||
existingEndpoint,
|
||||
existingProjectId,
|
||||
hasEnvApiKey = false,
|
||||
}: {
|
||||
isEmbedding?: boolean;
|
||||
setSettings: Dispatch<SetStateAction<OnboardingVariables>>;
|
||||
sampleDataset: boolean;
|
||||
setSampleDataset: (dataset: boolean) => void;
|
||||
setIsLoadingModels?: (isLoading: boolean) => void;
|
||||
alreadyConfigured?: boolean;
|
||||
existingEndpoint?: string;
|
||||
existingProjectId?: string;
|
||||
hasEnvApiKey?: boolean;
|
||||
isEmbedding?: boolean;
|
||||
setSettings: Dispatch<SetStateAction<OnboardingVariables>>;
|
||||
sampleDataset: boolean;
|
||||
setSampleDataset: (dataset: boolean) => void;
|
||||
setIsLoadingModels?: (isLoading: boolean) => void;
|
||||
alreadyConfigured?: boolean;
|
||||
existingEndpoint?: string;
|
||||
existingProjectId?: string;
|
||||
hasEnvApiKey?: boolean;
|
||||
}) {
|
||||
const [endpoint, setEndpoint] = useState(
|
||||
alreadyConfigured ? "" : (existingEndpoint || "https://us-south.ml.cloud.ibm.com"),
|
||||
);
|
||||
const [apiKey, setApiKey] = useState("");
|
||||
const [getFromEnv, setGetFromEnv] = useState(
|
||||
hasEnvApiKey && !alreadyConfigured,
|
||||
);
|
||||
const [projectId, setProjectId] = useState(
|
||||
alreadyConfigured ? "" : (existingProjectId || ""),
|
||||
);
|
||||
const [endpoint, setEndpoint] = useState(
|
||||
alreadyConfigured
|
||||
? ""
|
||||
: existingEndpoint || "https://us-south.ml.cloud.ibm.com",
|
||||
);
|
||||
const [apiKey, setApiKey] = useState("");
|
||||
const [getFromEnv, setGetFromEnv] = useState(
|
||||
hasEnvApiKey && !alreadyConfigured,
|
||||
);
|
||||
const [projectId, setProjectId] = useState(
|
||||
alreadyConfigured ? "" : existingProjectId || "",
|
||||
);
|
||||
|
||||
const options = [
|
||||
{
|
||||
value: "https://us-south.ml.cloud.ibm.com",
|
||||
label: "https://us-south.ml.cloud.ibm.com",
|
||||
default: true,
|
||||
},
|
||||
{
|
||||
value: "https://eu-de.ml.cloud.ibm.com",
|
||||
label: "https://eu-de.ml.cloud.ibm.com",
|
||||
default: false,
|
||||
},
|
||||
{
|
||||
value: "https://eu-gb.ml.cloud.ibm.com",
|
||||
label: "https://eu-gb.ml.cloud.ibm.com",
|
||||
default: false,
|
||||
},
|
||||
{
|
||||
value: "https://au-syd.ml.cloud.ibm.com",
|
||||
label: "https://au-syd.ml.cloud.ibm.com",
|
||||
default: false,
|
||||
},
|
||||
{
|
||||
value: "https://jp-tok.ml.cloud.ibm.com",
|
||||
label: "https://jp-tok.ml.cloud.ibm.com",
|
||||
default: false,
|
||||
},
|
||||
{
|
||||
value: "https://ca-tor.ml.cloud.ibm.com",
|
||||
label: "https://ca-tor.ml.cloud.ibm.com",
|
||||
default: false,
|
||||
},
|
||||
];
|
||||
const debouncedEndpoint = useDebouncedValue(endpoint, 500);
|
||||
const debouncedApiKey = useDebouncedValue(apiKey, 500);
|
||||
const debouncedProjectId = useDebouncedValue(projectId, 500);
|
||||
const options = [
|
||||
{
|
||||
value: "https://us-south.ml.cloud.ibm.com",
|
||||
label: "https://us-south.ml.cloud.ibm.com",
|
||||
default: true,
|
||||
},
|
||||
{
|
||||
value: "https://eu-de.ml.cloud.ibm.com",
|
||||
label: "https://eu-de.ml.cloud.ibm.com",
|
||||
default: false,
|
||||
},
|
||||
{
|
||||
value: "https://eu-gb.ml.cloud.ibm.com",
|
||||
label: "https://eu-gb.ml.cloud.ibm.com",
|
||||
default: false,
|
||||
},
|
||||
{
|
||||
value: "https://au-syd.ml.cloud.ibm.com",
|
||||
label: "https://au-syd.ml.cloud.ibm.com",
|
||||
default: false,
|
||||
},
|
||||
{
|
||||
value: "https://jp-tok.ml.cloud.ibm.com",
|
||||
label: "https://jp-tok.ml.cloud.ibm.com",
|
||||
default: false,
|
||||
},
|
||||
{
|
||||
value: "https://ca-tor.ml.cloud.ibm.com",
|
||||
label: "https://ca-tor.ml.cloud.ibm.com",
|
||||
default: false,
|
||||
},
|
||||
];
|
||||
const debouncedEndpoint = useDebouncedValue(endpoint, 500);
|
||||
const debouncedApiKey = useDebouncedValue(apiKey, 500);
|
||||
const debouncedProjectId = useDebouncedValue(projectId, 500);
|
||||
|
||||
// Fetch models from API when all credentials are provided
|
||||
const {
|
||||
data: modelsData,
|
||||
isLoading: isLoadingModels,
|
||||
error: modelsError,
|
||||
} = useGetIBMModelsQuery(
|
||||
{
|
||||
endpoint: debouncedEndpoint ? debouncedEndpoint : undefined,
|
||||
apiKey: getFromEnv ? "" : (debouncedApiKey ? debouncedApiKey : undefined),
|
||||
projectId: debouncedProjectId ? debouncedProjectId : undefined,
|
||||
},
|
||||
{
|
||||
enabled:
|
||||
!!debouncedEndpoint ||
|
||||
!!debouncedApiKey ||
|
||||
!!debouncedProjectId ||
|
||||
getFromEnv ||
|
||||
alreadyConfigured,
|
||||
},
|
||||
);
|
||||
// Fetch models from API when all credentials are provided
|
||||
const {
|
||||
data: modelsData,
|
||||
isLoading: isLoadingModels,
|
||||
error: modelsError,
|
||||
} = useGetIBMModelsQuery(
|
||||
{
|
||||
endpoint: debouncedEndpoint ? debouncedEndpoint : undefined,
|
||||
apiKey: getFromEnv ? "" : debouncedApiKey ? debouncedApiKey : undefined,
|
||||
projectId: debouncedProjectId ? debouncedProjectId : undefined,
|
||||
},
|
||||
{
|
||||
enabled:
|
||||
(!!debouncedEndpoint && !!debouncedApiKey && !!debouncedProjectId) ||
|
||||
getFromEnv ||
|
||||
alreadyConfigured,
|
||||
},
|
||||
);
|
||||
|
||||
// Use custom hook for model selection logic
|
||||
const {
|
||||
languageModel,
|
||||
embeddingModel,
|
||||
setLanguageModel,
|
||||
setEmbeddingModel,
|
||||
languageModels,
|
||||
embeddingModels,
|
||||
} = useModelSelection(modelsData, isEmbedding);
|
||||
// Use custom hook for model selection logic
|
||||
const {
|
||||
languageModel,
|
||||
embeddingModel,
|
||||
setLanguageModel,
|
||||
setEmbeddingModel,
|
||||
languageModels,
|
||||
embeddingModels,
|
||||
} = useModelSelection(modelsData, isEmbedding);
|
||||
|
||||
const handleGetFromEnvChange = (fromEnv: boolean) => {
|
||||
setGetFromEnv(fromEnv);
|
||||
if (fromEnv) {
|
||||
setApiKey("");
|
||||
}
|
||||
setEmbeddingModel?.("");
|
||||
setLanguageModel?.("");
|
||||
};
|
||||
const handleGetFromEnvChange = (fromEnv: boolean) => {
|
||||
setGetFromEnv(fromEnv);
|
||||
if (fromEnv) {
|
||||
setApiKey("");
|
||||
}
|
||||
setEmbeddingModel?.("");
|
||||
setLanguageModel?.("");
|
||||
};
|
||||
|
||||
const handleSampleDatasetChange = (dataset: boolean) => {
|
||||
setSampleDataset(dataset);
|
||||
};
|
||||
const handleSampleDatasetChange = (dataset: boolean) => {
|
||||
setSampleDataset(dataset);
|
||||
};
|
||||
|
||||
useEffect(() => {
|
||||
setIsLoadingModels?.(isLoadingModels);
|
||||
}, [isLoadingModels, setIsLoadingModels]);
|
||||
useEffect(() => {
|
||||
setIsLoadingModels?.(isLoadingModels);
|
||||
}, [isLoadingModels, setIsLoadingModels]);
|
||||
|
||||
// Update settings when values change
|
||||
useUpdateSettings(
|
||||
"watsonx",
|
||||
{
|
||||
endpoint,
|
||||
apiKey,
|
||||
projectId,
|
||||
languageModel,
|
||||
embeddingModel,
|
||||
},
|
||||
setSettings,
|
||||
isEmbedding,
|
||||
);
|
||||
// Update settings when values change
|
||||
useUpdateSettings(
|
||||
"watsonx",
|
||||
{
|
||||
endpoint,
|
||||
apiKey,
|
||||
projectId,
|
||||
languageModel,
|
||||
embeddingModel,
|
||||
},
|
||||
setSettings,
|
||||
isEmbedding,
|
||||
);
|
||||
|
||||
return (
|
||||
<>
|
||||
<div className="space-y-4">
|
||||
<LabelWrapper
|
||||
label="watsonx.ai API Endpoint"
|
||||
helperText="Base URL of the API"
|
||||
id="api-endpoint"
|
||||
required
|
||||
>
|
||||
<div className="space-y-1">
|
||||
<ModelSelector
|
||||
options={alreadyConfigured ? [] : options}
|
||||
value={endpoint}
|
||||
custom
|
||||
onValueChange={alreadyConfigured ? () => {} : setEndpoint}
|
||||
searchPlaceholder="Search endpoint..."
|
||||
noOptionsPlaceholder={
|
||||
alreadyConfigured
|
||||
? "https://•••••••••••••••••••••••••••••••••••••••••"
|
||||
: "No endpoints available"
|
||||
}
|
||||
placeholder="Select endpoint..."
|
||||
/>
|
||||
{alreadyConfigured && (
|
||||
<p className="text-mmd text-muted-foreground">
|
||||
Reusing endpoint from model provider selection.
|
||||
</p>
|
||||
)}
|
||||
</div>
|
||||
</LabelWrapper>
|
||||
return (
|
||||
<>
|
||||
<div className="space-y-4">
|
||||
<LabelWrapper
|
||||
label="watsonx.ai API Endpoint"
|
||||
helperText="Base URL of the API"
|
||||
id="api-endpoint"
|
||||
required
|
||||
>
|
||||
<div className="space-y-1">
|
||||
<ModelSelector
|
||||
options={alreadyConfigured ? [] : options}
|
||||
value={endpoint}
|
||||
custom
|
||||
onValueChange={alreadyConfigured ? () => {} : setEndpoint}
|
||||
searchPlaceholder="Search endpoint..."
|
||||
noOptionsPlaceholder={
|
||||
alreadyConfigured
|
||||
? "https://•••••••••••••••••••••••••••••••••••••••••"
|
||||
: "No endpoints available"
|
||||
}
|
||||
placeholder="Select endpoint..."
|
||||
/>
|
||||
{alreadyConfigured && (
|
||||
<p className="text-mmd text-muted-foreground">
|
||||
Reusing endpoint from model provider selection.
|
||||
</p>
|
||||
)}
|
||||
</div>
|
||||
</LabelWrapper>
|
||||
|
||||
<div className="space-y-1">
|
||||
<LabelInput
|
||||
label="watsonx Project ID"
|
||||
helperText="Project ID for the model"
|
||||
id="project-id"
|
||||
required
|
||||
placeholder={
|
||||
alreadyConfigured ? "••••••••••••••••••••••••" : "your-project-id"
|
||||
}
|
||||
value={projectId}
|
||||
onChange={(e) => setProjectId(e.target.value)}
|
||||
disabled={alreadyConfigured}
|
||||
/>
|
||||
{alreadyConfigured && (
|
||||
<p className="text-mmd text-muted-foreground">
|
||||
Reusing project ID from model provider selection.
|
||||
</p>
|
||||
)}
|
||||
</div>
|
||||
<LabelWrapper
|
||||
label="Use environment watsonx API key"
|
||||
id="get-api-key"
|
||||
description="Reuse the key from your environment config. Turn off to enter a different key."
|
||||
flex
|
||||
>
|
||||
<Tooltip>
|
||||
<TooltipTrigger asChild>
|
||||
<div>
|
||||
<Switch
|
||||
checked={getFromEnv}
|
||||
onCheckedChange={handleGetFromEnvChange}
|
||||
disabled={!hasEnvApiKey || alreadyConfigured}
|
||||
/>
|
||||
</div>
|
||||
</TooltipTrigger>
|
||||
{!hasEnvApiKey && !alreadyConfigured && (
|
||||
<TooltipContent>
|
||||
watsonx API key not detected in the environment.
|
||||
</TooltipContent>
|
||||
)}
|
||||
</Tooltip>
|
||||
</LabelWrapper>
|
||||
{!getFromEnv && !alreadyConfigured && (
|
||||
<div className="space-y-1">
|
||||
<LabelInput
|
||||
label="watsonx API key"
|
||||
helperText="API key to access watsonx.ai"
|
||||
className={modelsError ? "!border-destructive" : ""}
|
||||
id="api-key"
|
||||
type="password"
|
||||
required
|
||||
placeholder="your-api-key"
|
||||
value={apiKey}
|
||||
onChange={(e) => setApiKey(e.target.value)}
|
||||
/>
|
||||
{isLoadingModels && (
|
||||
<p className="text-mmd text-muted-foreground">
|
||||
Validating API key...
|
||||
</p>
|
||||
)}
|
||||
{modelsError && (
|
||||
<p className="text-mmd text-destructive">
|
||||
Invalid watsonx API key. Verify or replace the key.
|
||||
</p>
|
||||
)}
|
||||
</div>
|
||||
)}
|
||||
{alreadyConfigured && (
|
||||
<div className="space-y-1">
|
||||
<LabelInput
|
||||
label="watsonx API key"
|
||||
helperText="API key to access watsonx.ai"
|
||||
id="api-key"
|
||||
type="password"
|
||||
required
|
||||
placeholder="•••••••••••••••••••••••••••••••••••••••••"
|
||||
value={apiKey}
|
||||
onChange={(e) => setApiKey(e.target.value)}
|
||||
disabled={true}
|
||||
/>
|
||||
<p className="text-mmd text-muted-foreground">
|
||||
Reusing API key from model provider selection.
|
||||
</p>
|
||||
</div>
|
||||
)}
|
||||
{getFromEnv && isLoadingModels && (
|
||||
<p className="text-mmd text-muted-foreground">
|
||||
Validating configuration...
|
||||
</p>
|
||||
)}
|
||||
{getFromEnv && modelsError && (
|
||||
<p className="text-mmd text-accent-amber-foreground">
|
||||
Connection failed. Check your configuration.
|
||||
</p>
|
||||
)}
|
||||
</div>
|
||||
<AdvancedOnboarding
|
||||
icon={<IBMLogo className="w-4 h-4" />}
|
||||
languageModels={languageModels}
|
||||
embeddingModels={embeddingModels}
|
||||
languageModel={languageModel}
|
||||
embeddingModel={embeddingModel}
|
||||
sampleDataset={sampleDataset}
|
||||
setLanguageModel={setLanguageModel}
|
||||
setEmbeddingModel={setEmbeddingModel}
|
||||
setSampleDataset={handleSampleDatasetChange}
|
||||
/>
|
||||
</>
|
||||
);
|
||||
<div className="space-y-1">
|
||||
<LabelInput
|
||||
label="watsonx Project ID"
|
||||
helperText="Project ID for the model"
|
||||
id="project-id"
|
||||
required
|
||||
placeholder={
|
||||
alreadyConfigured ? "••••••••••••••••••••••••" : "your-project-id"
|
||||
}
|
||||
value={projectId}
|
||||
onChange={(e) => setProjectId(e.target.value)}
|
||||
disabled={alreadyConfigured}
|
||||
/>
|
||||
{alreadyConfigured && (
|
||||
<p className="text-mmd text-muted-foreground">
|
||||
Reusing project ID from model provider selection.
|
||||
</p>
|
||||
)}
|
||||
</div>
|
||||
<LabelWrapper
|
||||
label="Use environment watsonx API key"
|
||||
id="get-api-key"
|
||||
description="Reuse the key from your environment config. Turn off to enter a different key."
|
||||
flex
|
||||
>
|
||||
<Tooltip>
|
||||
<TooltipTrigger asChild>
|
||||
<div>
|
||||
<Switch
|
||||
checked={getFromEnv}
|
||||
onCheckedChange={handleGetFromEnvChange}
|
||||
disabled={!hasEnvApiKey || alreadyConfigured}
|
||||
/>
|
||||
</div>
|
||||
</TooltipTrigger>
|
||||
{!hasEnvApiKey && !alreadyConfigured && (
|
||||
<TooltipContent>
|
||||
watsonx API key not detected in the environment.
|
||||
</TooltipContent>
|
||||
)}
|
||||
</Tooltip>
|
||||
</LabelWrapper>
|
||||
{!getFromEnv && !alreadyConfigured && (
|
||||
<div className="space-y-1">
|
||||
<LabelInput
|
||||
label="watsonx API key"
|
||||
helperText="API key to access watsonx.ai"
|
||||
className={modelsError ? "!border-destructive" : ""}
|
||||
id="api-key"
|
||||
type="password"
|
||||
required
|
||||
placeholder="your-api-key"
|
||||
value={apiKey}
|
||||
onChange={(e) => setApiKey(e.target.value)}
|
||||
/>
|
||||
{isLoadingModels && (
|
||||
<p className="text-mmd text-muted-foreground">
|
||||
Validating API key...
|
||||
</p>
|
||||
)}
|
||||
{modelsError && (
|
||||
<p className="text-mmd text-destructive">
|
||||
Invalid watsonx API key. Verify or replace the key.
|
||||
</p>
|
||||
)}
|
||||
</div>
|
||||
)}
|
||||
{alreadyConfigured && (
|
||||
<div className="space-y-1">
|
||||
<LabelInput
|
||||
label="watsonx API key"
|
||||
helperText="API key to access watsonx.ai"
|
||||
id="api-key"
|
||||
type="password"
|
||||
required
|
||||
placeholder="•••••••••••••••••••••••••••••••••••••••••"
|
||||
value={apiKey}
|
||||
onChange={(e) => setApiKey(e.target.value)}
|
||||
disabled={true}
|
||||
/>
|
||||
<p className="text-mmd text-muted-foreground">
|
||||
Reusing API key from model provider selection.
|
||||
</p>
|
||||
</div>
|
||||
)}
|
||||
{getFromEnv && isLoadingModels && (
|
||||
<p className="text-mmd text-muted-foreground">
|
||||
Validating configuration...
|
||||
</p>
|
||||
)}
|
||||
{getFromEnv && modelsError && (
|
||||
<p className="text-mmd text-accent-amber-foreground">
|
||||
Connection failed. Check your configuration.
|
||||
</p>
|
||||
)}
|
||||
</div>
|
||||
<AdvancedOnboarding
|
||||
icon={<IBMLogo className="w-4 h-4" />}
|
||||
languageModels={languageModels}
|
||||
embeddingModels={embeddingModels}
|
||||
languageModel={languageModel}
|
||||
embeddingModel={embeddingModel}
|
||||
sampleDataset={sampleDataset}
|
||||
setLanguageModel={setLanguageModel}
|
||||
setEmbeddingModel={setEmbeddingModel}
|
||||
setSampleDataset={handleSampleDatasetChange}
|
||||
/>
|
||||
</>
|
||||
);
|
||||
}
|
||||
|
|
|
|||
|
|
@ -3,12 +3,13 @@
|
|||
import { useQueryClient } from "@tanstack/react-query";
|
||||
import { AnimatePresence, motion } from "framer-motion";
|
||||
import { X } from "lucide-react";
|
||||
import { useEffect, useState } from "react";
|
||||
import { useEffect, useRef, useState } from "react";
|
||||
import { toast } from "sonner";
|
||||
import {
|
||||
type OnboardingVariables,
|
||||
useOnboardingMutation,
|
||||
} from "@/app/api/mutations/useOnboardingMutation";
|
||||
import { useOnboardingRollbackMutation } from "@/app/api/mutations/useOnboardingRollbackMutation";
|
||||
import { useGetSettingsQuery } from "@/app/api/queries/useGetSettingsQuery";
|
||||
import { useGetTasksQuery } from "@/app/api/queries/useGetTasksQuery";
|
||||
import type { ProviderHealthResponse } from "@/app/api/queries/useProviderHealthQuery";
|
||||
|
|
@ -170,12 +171,32 @@ const OnboardingCard = ({
|
|||
|
||||
const [error, setError] = useState<string | null>(null);
|
||||
|
||||
// Track which tasks we've already handled to prevent infinite loops
|
||||
const handledFailedTasksRef = useRef<Set<string>>(new Set());
|
||||
|
||||
// Query tasks to track completion
|
||||
const { data: tasks } = useGetTasksQuery({
|
||||
enabled: currentStep !== null, // Only poll when onboarding has started
|
||||
refetchInterval: currentStep !== null ? 1000 : false, // Poll every 1 second during onboarding
|
||||
});
|
||||
|
||||
// Rollback mutation
|
||||
const rollbackMutation = useOnboardingRollbackMutation({
|
||||
onSuccess: () => {
|
||||
console.log("Onboarding rolled back successfully");
|
||||
// Reset to provider selection step
|
||||
// Error message is already set before calling mutate
|
||||
setCurrentStep(null);
|
||||
},
|
||||
onError: (error) => {
|
||||
console.error("Failed to rollback onboarding", error);
|
||||
// Preserve existing error message if set, otherwise show rollback error
|
||||
setError((prevError) => prevError || `Failed to rollback: ${error.message}`);
|
||||
// Still reset to provider selection even if rollback fails
|
||||
setCurrentStep(null);
|
||||
},
|
||||
});
|
||||
|
||||
// Monitor tasks and call onComplete when all tasks are done
|
||||
useEffect(() => {
|
||||
if (currentStep === null || !tasks || !isEmbedding) {
|
||||
|
|
@ -190,11 +211,86 @@ const OnboardingCard = ({
|
|||
task.status === "processing",
|
||||
);
|
||||
|
||||
// Check if any file failed in completed tasks
|
||||
const completedTasks = tasks.filter(
|
||||
(task) => task.status === "completed"
|
||||
);
|
||||
|
||||
// Check if any completed task has at least one failed file
|
||||
const taskWithFailedFile = completedTasks.find((task) => {
|
||||
// Must have files object
|
||||
if (!task.files || typeof task.files !== "object") {
|
||||
return false;
|
||||
}
|
||||
|
||||
const fileEntries = Object.values(task.files);
|
||||
|
||||
// Must have at least one file
|
||||
if (fileEntries.length === 0) {
|
||||
return false;
|
||||
}
|
||||
|
||||
// Check if any file has failed status
|
||||
const hasFailedFile = fileEntries.some(
|
||||
(file) => file.status === "failed" || file.status === "error"
|
||||
);
|
||||
|
||||
return hasFailedFile;
|
||||
});
|
||||
|
||||
// If any file failed, show error and jump back one step (like onboardingMutation.onError)
|
||||
// Only handle if we haven't already handled this task
|
||||
if (
|
||||
taskWithFailedFile &&
|
||||
!rollbackMutation.isPending &&
|
||||
!isCompleted &&
|
||||
!handledFailedTasksRef.current.has(taskWithFailedFile.task_id)
|
||||
) {
|
||||
console.error("File failed in task, jumping back one step", taskWithFailedFile);
|
||||
|
||||
// Mark this task as handled to prevent infinite loops
|
||||
handledFailedTasksRef.current.add(taskWithFailedFile.task_id);
|
||||
|
||||
// Extract error messages from failed files
|
||||
const errorMessages: string[] = [];
|
||||
if (taskWithFailedFile.files) {
|
||||
Object.values(taskWithFailedFile.files).forEach((file) => {
|
||||
if ((file.status === "failed" || file.status === "error") && file.error) {
|
||||
errorMessages.push(file.error);
|
||||
}
|
||||
});
|
||||
}
|
||||
|
||||
// Also check task-level error
|
||||
if (taskWithFailedFile.error) {
|
||||
errorMessages.push(taskWithFailedFile.error);
|
||||
}
|
||||
|
||||
// Use the first error message, or a generic message if no errors found
|
||||
const errorMessage = errorMessages.length > 0
|
||||
? errorMessages[0]
|
||||
: "Sample data file failed to ingest. Please try again with a different configuration.";
|
||||
|
||||
// Set error message and jump back one step (exactly like onboardingMutation.onError)
|
||||
setError(errorMessage);
|
||||
setCurrentStep(totalSteps);
|
||||
// Jump back one step after 1 second (go back to the step before ingestion)
|
||||
// For embedding: totalSteps is 4, ingestion is step 3, so go back to step 2
|
||||
// For LLM: totalSteps is 3, ingestion is step 2, so go back to step 1
|
||||
setTimeout(() => {
|
||||
// Go back to the step before the last step (which is ingestion)
|
||||
const previousStep = totalSteps > 1 ? totalSteps - 2 : 0;
|
||||
setCurrentStep(previousStep);
|
||||
}, 1000);
|
||||
return;
|
||||
}
|
||||
|
||||
// If no active tasks and we've started onboarding, complete it
|
||||
if (
|
||||
(!activeTasks || (activeTasks.processed_files ?? 0) > 0) &&
|
||||
tasks.length > 0 &&
|
||||
!isCompleted
|
||||
!isCompleted &&
|
||||
!taskWithFailedFile
|
||||
) {
|
||||
// Set to final step to show "Done"
|
||||
setCurrentStep(totalSteps);
|
||||
|
|
@ -203,7 +299,7 @@ const OnboardingCard = ({
|
|||
onComplete();
|
||||
}, 1000);
|
||||
}
|
||||
}, [tasks, currentStep, onComplete, isCompleted, isEmbedding, totalSteps]);
|
||||
}, [tasks, currentStep, onComplete, isCompleted, isEmbedding, totalSteps, rollbackMutation]);
|
||||
|
||||
// Mutations
|
||||
const onboardingMutation = useOnboardingMutation({
|
||||
|
|
@ -507,7 +603,7 @@ const OnboardingCard = ({
|
|||
hasEnvApiKey={
|
||||
currentSettings?.providers?.openai?.has_api_key === true
|
||||
}
|
||||
alreadyConfigured={providerAlreadyConfigured}
|
||||
alreadyConfigured={providerAlreadyConfigured && modelProvider === "openai"}
|
||||
/>
|
||||
</TabsContent>
|
||||
<TabsContent value="watsonx">
|
||||
|
|
@ -517,7 +613,7 @@ const OnboardingCard = ({
|
|||
setSampleDataset={setSampleDataset}
|
||||
setIsLoadingModels={setIsLoadingModels}
|
||||
isEmbedding={isEmbedding}
|
||||
alreadyConfigured={providerAlreadyConfigured}
|
||||
alreadyConfigured={providerAlreadyConfigured && modelProvider === "watsonx"}
|
||||
existingEndpoint={currentSettings?.providers?.watsonx?.endpoint}
|
||||
existingProjectId={currentSettings?.providers?.watsonx?.project_id}
|
||||
hasEnvApiKey={currentSettings?.providers?.watsonx?.has_api_key === true}
|
||||
|
|
@ -530,7 +626,7 @@ const OnboardingCard = ({
|
|||
setSampleDataset={setSampleDataset}
|
||||
setIsLoadingModels={setIsLoadingModels}
|
||||
isEmbedding={isEmbedding}
|
||||
alreadyConfigured={providerAlreadyConfigured}
|
||||
alreadyConfigured={providerAlreadyConfigured && modelProvider === "ollama"}
|
||||
existingEndpoint={currentSettings?.providers?.ollama?.endpoint}
|
||||
/>
|
||||
</TabsContent>
|
||||
|
|
|
|||
|
|
@ -1,3 +1,4 @@
|
|||
import { X } from "lucide-react";
|
||||
import { AnimatePresence, motion } from "motion/react";
|
||||
import { type ChangeEvent, useEffect, useRef, useState } from "react";
|
||||
import { toast } from "sonner";
|
||||
|
|
@ -7,13 +8,13 @@ import { useGetTasksQuery } from "@/app/api/queries/useGetTasksQuery";
|
|||
import { AnimatedProviderSteps } from "@/app/onboarding/_components/animated-provider-steps";
|
||||
import { Button } from "@/components/ui/button";
|
||||
import {
|
||||
ONBOARDING_UPLOAD_STEPS_KEY,
|
||||
ONBOARDING_USER_DOC_FILTER_ID_KEY,
|
||||
ONBOARDING_UPLOAD_STEPS_KEY,
|
||||
ONBOARDING_USER_DOC_FILTER_ID_KEY,
|
||||
} from "@/lib/constants";
|
||||
import { uploadFile } from "@/lib/upload-utils";
|
||||
|
||||
interface OnboardingUploadProps {
|
||||
onComplete: () => void;
|
||||
onComplete: () => void;
|
||||
}
|
||||
|
||||
const OnboardingUpload = ({ onComplete }: OnboardingUploadProps) => {
|
||||
|
|
@ -21,6 +22,7 @@ const OnboardingUpload = ({ onComplete }: OnboardingUploadProps) => {
|
|||
const [isUploading, setIsUploading] = useState(false);
|
||||
const [currentStep, setCurrentStep] = useState<number | null>(null);
|
||||
const [uploadedFilename, setUploadedFilename] = useState<string | null>(null);
|
||||
const [uploadedTaskId, setUploadedTaskId] = useState<string | null>(null);
|
||||
const [shouldCreateFilter, setShouldCreateFilter] = useState(false);
|
||||
const [isCreatingFilter, setIsCreatingFilter] = useState(false);
|
||||
|
||||
|
|
@ -43,23 +45,26 @@ const OnboardingUpload = ({ onComplete }: OnboardingUploadProps) => {
|
|||
|
||||
// Monitor tasks and call onComplete when file processing is done
|
||||
useEffect(() => {
|
||||
if (currentStep === null || !tasks) {
|
||||
if (currentStep === null || !tasks || !uploadedTaskId) {
|
||||
return;
|
||||
}
|
||||
|
||||
// Check if there are any active tasks (pending, running, or processing)
|
||||
const activeTasks = tasks.find(
|
||||
(task) =>
|
||||
task.status === "pending" ||
|
||||
task.status === "running" ||
|
||||
task.status === "processing",
|
||||
);
|
||||
// Find the task by task ID from the upload response
|
||||
const matchingTask = tasks.find((task) => task.task_id === uploadedTaskId);
|
||||
|
||||
// If no active tasks and we have more than 1 task (initial + new upload), complete it
|
||||
if (
|
||||
(!activeTasks || (activeTasks.processed_files ?? 0) > 0) &&
|
||||
tasks.length > 1
|
||||
) {
|
||||
// If no matching task found, wait for it to appear
|
||||
if (!matchingTask) {
|
||||
return;
|
||||
}
|
||||
|
||||
// Check if the matching task is still active (pending, running, or processing)
|
||||
const isTaskActive =
|
||||
matchingTask.status === "pending" ||
|
||||
matchingTask.status === "running" ||
|
||||
matchingTask.status === "processing";
|
||||
|
||||
// If task is completed or has processed files, complete the onboarding step
|
||||
if (!isTaskActive || (matchingTask.processed_files ?? 0) > 0) {
|
||||
// Set to final step to show "Done"
|
||||
setCurrentStep(STEP_LIST.length);
|
||||
|
||||
|
|
@ -91,6 +96,7 @@ const OnboardingUpload = ({ onComplete }: OnboardingUploadProps) => {
|
|||
icon: "file",
|
||||
});
|
||||
|
||||
// Wait for filter creation to complete before proceeding
|
||||
createFilterMutation
|
||||
.mutateAsync({
|
||||
name: displayName,
|
||||
|
|
@ -114,18 +120,36 @@ const OnboardingUpload = ({ onComplete }: OnboardingUploadProps) => {
|
|||
})
|
||||
.finally(() => {
|
||||
setIsCreatingFilter(false);
|
||||
// Refetch nudges to get new ones
|
||||
refetchNudges();
|
||||
|
||||
// Wait a bit before completing (after filter is created)
|
||||
setTimeout(() => {
|
||||
onComplete();
|
||||
}, 1000);
|
||||
});
|
||||
} else {
|
||||
// No filter to create, just complete
|
||||
// Refetch nudges to get new ones
|
||||
refetchNudges();
|
||||
|
||||
// Wait a bit before completing
|
||||
setTimeout(() => {
|
||||
onComplete();
|
||||
}, 1000);
|
||||
}
|
||||
|
||||
// Refetch nudges to get new ones
|
||||
refetchNudges();
|
||||
|
||||
// Wait a bit before completing
|
||||
setTimeout(() => {
|
||||
onComplete();
|
||||
}, 1000);
|
||||
}
|
||||
}, [tasks, currentStep, onComplete, refetchNudges, shouldCreateFilter, uploadedFilename]);
|
||||
}, [
|
||||
tasks,
|
||||
currentStep,
|
||||
onComplete,
|
||||
refetchNudges,
|
||||
shouldCreateFilter,
|
||||
uploadedFilename,
|
||||
uploadedTaskId,
|
||||
createFilterMutation,
|
||||
isCreatingFilter,
|
||||
]);
|
||||
|
||||
const resetFileInput = () => {
|
||||
if (fileInputRef.current) {
|
||||
|
|
@ -144,6 +168,11 @@ const OnboardingUpload = ({ onComplete }: OnboardingUploadProps) => {
|
|||
const result = await uploadFile(file, true, true); // Pass createFilter=true
|
||||
console.log("Document upload task started successfully");
|
||||
|
||||
// Store task ID to track the specific upload task
|
||||
if (result.taskId) {
|
||||
setUploadedTaskId(result.taskId);
|
||||
}
|
||||
|
||||
// Store filename and createFilter flag in state to create filter after ingestion succeeds
|
||||
if (result.createFilter && result.filename) {
|
||||
setUploadedFilename(result.filename);
|
||||
|
|
@ -176,6 +205,7 @@ const OnboardingUpload = ({ onComplete }: OnboardingUploadProps) => {
|
|||
|
||||
// Reset on error
|
||||
setCurrentStep(null);
|
||||
setUploadedTaskId(null);
|
||||
} finally {
|
||||
setIsUploading(false);
|
||||
}
|
||||
|
|
|
|||
|
|
@ -47,8 +47,7 @@ export function ChatRenderer({
|
|||
refreshConversations,
|
||||
startNewConversation,
|
||||
setConversationFilter,
|
||||
setCurrentConversationId,
|
||||
setPreviousResponseIds,
|
||||
setOnboardingComplete,
|
||||
} = useChat();
|
||||
|
||||
// Initialize onboarding state based on local storage and settings
|
||||
|
|
@ -170,12 +169,17 @@ export function ChatRenderer({
|
|||
localStorage.removeItem(ONBOARDING_UPLOAD_STEPS_KEY);
|
||||
}
|
||||
|
||||
// Clear ALL conversation state so next message starts fresh
|
||||
await startNewConversation();
|
||||
// Mark onboarding as complete in context
|
||||
setOnboardingComplete(true);
|
||||
|
||||
// Store the user document filter as default for new conversations and load it
|
||||
// Store the user document filter as default for new conversations FIRST
|
||||
// This must happen before startNewConversation() so the filter is available
|
||||
await storeDefaultFilterForNewConversations(true);
|
||||
|
||||
// Clear ALL conversation state so next message starts fresh
|
||||
// This will pick up the default filter we just set
|
||||
await startNewConversation();
|
||||
|
||||
// Clean up onboarding filter IDs now that we've set the default
|
||||
if (typeof window !== "undefined") {
|
||||
localStorage.removeItem(ONBOARDING_OPENRAG_DOCS_FILTER_ID_KEY);
|
||||
|
|
@ -202,6 +206,8 @@ export function ChatRenderer({
|
|||
localStorage.removeItem(ONBOARDING_CARD_STEPS_KEY);
|
||||
localStorage.removeItem(ONBOARDING_UPLOAD_STEPS_KEY);
|
||||
}
|
||||
// Mark onboarding as complete in context
|
||||
setOnboardingComplete(true);
|
||||
// Store the OpenRAG docs filter as default for new conversations
|
||||
storeDefaultFilterForNewConversations(false);
|
||||
setShowLayout(true);
|
||||
|
|
|
|||
|
|
@ -5,125 +5,131 @@ import { useRouter } from "next/navigation";
|
|||
import { useProviderHealthQuery } from "@/app/api/queries/useProviderHealthQuery";
|
||||
import type { ModelProvider } from "@/app/settings/_helpers/model-helpers";
|
||||
import { Banner, BannerIcon, BannerTitle } from "@/components/ui/banner";
|
||||
import { cn } from "@/lib/utils";
|
||||
import { useChat } from "@/contexts/chat-context";
|
||||
import { cn } from "@/lib/utils";
|
||||
import { Button } from "./ui/button";
|
||||
|
||||
interface ProviderHealthBannerProps {
|
||||
className?: string;
|
||||
className?: string;
|
||||
}
|
||||
|
||||
// Custom hook to check provider health status
|
||||
export function useProviderHealth() {
|
||||
const { hasChatError } = useChat();
|
||||
const {
|
||||
data: health,
|
||||
isLoading,
|
||||
isFetching,
|
||||
error,
|
||||
isError,
|
||||
} = useProviderHealthQuery({
|
||||
test_completion: hasChatError, // Use test_completion=true when chat errors occur
|
||||
});
|
||||
const { hasChatError } = useChat();
|
||||
const {
|
||||
data: health,
|
||||
isLoading,
|
||||
isFetching,
|
||||
error,
|
||||
isError,
|
||||
} = useProviderHealthQuery({
|
||||
test_completion: hasChatError, // Use test_completion=true when chat errors occur
|
||||
});
|
||||
|
||||
const isHealthy = health?.status === "healthy" && !isError;
|
||||
// Only consider unhealthy if backend is up but provider validation failed
|
||||
// Don't show banner if backend is unavailable
|
||||
const isUnhealthy =
|
||||
health?.status === "unhealthy" || health?.status === "error";
|
||||
const isBackendUnavailable =
|
||||
health?.status === "backend-unavailable" || isError;
|
||||
const isHealthy = health?.status === "healthy" && !isError;
|
||||
// Only consider unhealthy if backend is up but provider validation failed
|
||||
// Don't show banner if backend is unavailable
|
||||
const isUnhealthy =
|
||||
health?.status === "unhealthy" || health?.status === "error";
|
||||
const isBackendUnavailable =
|
||||
health?.status === "backend-unavailable" || isError;
|
||||
|
||||
return {
|
||||
health,
|
||||
isLoading,
|
||||
isFetching,
|
||||
error,
|
||||
isError,
|
||||
isHealthy,
|
||||
isUnhealthy,
|
||||
isBackendUnavailable,
|
||||
};
|
||||
return {
|
||||
health,
|
||||
isLoading,
|
||||
isFetching,
|
||||
error,
|
||||
isError,
|
||||
isHealthy,
|
||||
isUnhealthy,
|
||||
isBackendUnavailable,
|
||||
};
|
||||
}
|
||||
|
||||
const providerTitleMap: Record<ModelProvider, string> = {
|
||||
openai: "OpenAI",
|
||||
anthropic: "Anthropic",
|
||||
ollama: "Ollama",
|
||||
watsonx: "IBM watsonx.ai",
|
||||
openai: "OpenAI",
|
||||
anthropic: "Anthropic",
|
||||
ollama: "Ollama",
|
||||
watsonx: "IBM watsonx.ai",
|
||||
};
|
||||
|
||||
export function ProviderHealthBanner({ className }: ProviderHealthBannerProps) {
|
||||
const { isLoading, isHealthy, isUnhealthy, health } = useProviderHealth();
|
||||
const router = useRouter();
|
||||
const { isLoading, isHealthy, isUnhealthy, health } = useProviderHealth();
|
||||
const router = useRouter();
|
||||
|
||||
// Only show banner when provider is unhealthy (not when backend is unavailable)
|
||||
if (isLoading || isHealthy) {
|
||||
return null;
|
||||
}
|
||||
// Only show banner when provider is unhealthy (not when backend is unavailable)
|
||||
if (isLoading || isHealthy) {
|
||||
return null;
|
||||
}
|
||||
|
||||
if (isUnhealthy) {
|
||||
const llmProvider = health?.llm_provider || health?.provider;
|
||||
const embeddingProvider = health?.embedding_provider;
|
||||
const llmError = health?.llm_error;
|
||||
const embeddingError = health?.embedding_error;
|
||||
if (isUnhealthy) {
|
||||
const llmProvider = health?.llm_provider || health?.provider;
|
||||
const embeddingProvider = health?.embedding_provider;
|
||||
const llmError = health?.llm_error;
|
||||
const embeddingError = health?.embedding_error;
|
||||
|
||||
// Determine which provider has the error
|
||||
let errorProvider: string | undefined;
|
||||
let errorMessage: string;
|
||||
// Determine which provider has the error
|
||||
let errorProvider: string | undefined;
|
||||
let errorMessage: string;
|
||||
|
||||
if (llmError && embeddingError) {
|
||||
// Both have errors - show combined message
|
||||
errorMessage = health?.message || "Provider validation failed";
|
||||
errorProvider = undefined; // Don't link to a specific provider
|
||||
} else if (llmError) {
|
||||
// Only LLM has error
|
||||
errorProvider = llmProvider;
|
||||
errorMessage = llmError;
|
||||
} else if (embeddingError) {
|
||||
// Only embedding has error
|
||||
errorProvider = embeddingProvider;
|
||||
errorMessage = embeddingError;
|
||||
} else {
|
||||
// Fallback to original message
|
||||
errorMessage = health?.message || "Provider validation failed";
|
||||
errorProvider = llmProvider;
|
||||
}
|
||||
if (llmError && embeddingError) {
|
||||
// Both have errors - check if they're the same
|
||||
if (llmError === embeddingError) {
|
||||
// Same error for both - show once
|
||||
errorMessage = llmError;
|
||||
} else {
|
||||
// Different errors - show both
|
||||
errorMessage = `${llmError}; ${embeddingError}`;
|
||||
}
|
||||
errorProvider = undefined; // Don't link to a specific provider
|
||||
} else if (llmError) {
|
||||
// Only LLM has error
|
||||
errorProvider = llmProvider;
|
||||
errorMessage = llmError;
|
||||
} else if (embeddingError) {
|
||||
// Only embedding has error
|
||||
errorProvider = embeddingProvider;
|
||||
errorMessage = embeddingError;
|
||||
} else {
|
||||
// Fallback to original message
|
||||
errorMessage = health?.message || "Provider validation failed";
|
||||
errorProvider = llmProvider;
|
||||
}
|
||||
|
||||
const providerTitle = errorProvider
|
||||
? providerTitleMap[errorProvider as ModelProvider] || errorProvider
|
||||
: "Provider";
|
||||
const providerTitle = errorProvider
|
||||
? providerTitleMap[errorProvider as ModelProvider] || errorProvider
|
||||
: "Provider";
|
||||
|
||||
const settingsUrl = errorProvider
|
||||
? `/settings?setup=${errorProvider}`
|
||||
: "/settings";
|
||||
const settingsUrl = errorProvider
|
||||
? `/settings?setup=${errorProvider}`
|
||||
: "/settings";
|
||||
|
||||
return (
|
||||
<Banner
|
||||
className={cn(
|
||||
"bg-red-50 dark:bg-red-950 text-foreground border-accent-red border-b w-full",
|
||||
className,
|
||||
)}
|
||||
>
|
||||
<BannerIcon
|
||||
className="text-accent-red-foreground"
|
||||
icon={AlertTriangle}
|
||||
/>
|
||||
<BannerTitle className="font-medium flex items-center gap-2">
|
||||
{llmError && embeddingError ? (
|
||||
<>Provider errors - {errorMessage}</>
|
||||
) : (
|
||||
<>
|
||||
{providerTitle} error - {errorMessage}
|
||||
</>
|
||||
)}
|
||||
</BannerTitle>
|
||||
<Button size="sm" onClick={() => router.push(settingsUrl)}>
|
||||
Fix Setup
|
||||
</Button>
|
||||
</Banner>
|
||||
);
|
||||
}
|
||||
return (
|
||||
<Banner
|
||||
className={cn(
|
||||
"bg-red-50 dark:bg-red-950 text-foreground border-accent-red border-b w-full",
|
||||
className,
|
||||
)}
|
||||
>
|
||||
<BannerIcon
|
||||
className="text-accent-red-foreground"
|
||||
icon={AlertTriangle}
|
||||
/>
|
||||
<BannerTitle className="font-medium flex items-center gap-2">
|
||||
{llmError && embeddingError ? (
|
||||
<>Provider errors - {errorMessage}</>
|
||||
) : (
|
||||
<>
|
||||
{providerTitle} error - {errorMessage}
|
||||
</>
|
||||
)}
|
||||
</BannerTitle>
|
||||
<Button size="sm" onClick={() => router.push(settingsUrl)}>
|
||||
Fix Setup
|
||||
</Button>
|
||||
</Banner>
|
||||
);
|
||||
}
|
||||
|
||||
return null;
|
||||
return null;
|
||||
}
|
||||
|
|
|
|||
|
|
@ -10,6 +10,8 @@ import {
|
|||
useRef,
|
||||
useState,
|
||||
} from "react";
|
||||
import { ONBOARDING_STEP_KEY } from "@/lib/constants";
|
||||
import { useGetSettingsQuery } from "@/app/api/queries/useGetSettingsQuery";
|
||||
|
||||
export type EndpointType = "chat" | "langflow";
|
||||
|
||||
|
|
@ -81,6 +83,8 @@ interface ChatContextType {
|
|||
setConversationFilter: (filter: KnowledgeFilter | null, responseId?: string | null) => void;
|
||||
hasChatError: boolean;
|
||||
setChatError: (hasError: boolean) => void;
|
||||
isOnboardingComplete: boolean;
|
||||
setOnboardingComplete: (complete: boolean) => void;
|
||||
}
|
||||
|
||||
const ChatContext = createContext<ChatContextType | undefined>(undefined);
|
||||
|
|
@ -111,6 +115,46 @@ export function ChatProvider({ children }: ChatProviderProps) {
|
|||
const [conversationFilter, setConversationFilterState] =
|
||||
useState<KnowledgeFilter | null>(null);
|
||||
const [hasChatError, setChatError] = useState(false);
|
||||
|
||||
// Get settings to check if onboarding was completed (settings.edited)
|
||||
const { data: settings } = useGetSettingsQuery();
|
||||
|
||||
// Check if onboarding is complete
|
||||
// Onboarding is complete if:
|
||||
// 1. settings.edited is true (backend confirms onboarding was completed)
|
||||
// 2. AND onboarding step key is null (local onboarding flow is done)
|
||||
const [isOnboardingComplete, setIsOnboardingComplete] = useState(() => {
|
||||
if (typeof window === "undefined") return false;
|
||||
// Default to false if settings not loaded yet
|
||||
return false;
|
||||
});
|
||||
|
||||
// Sync onboarding completion state with settings.edited and localStorage
|
||||
useEffect(() => {
|
||||
const checkOnboarding = () => {
|
||||
if (typeof window !== "undefined") {
|
||||
// Onboarding is complete if settings.edited is true AND step key is null
|
||||
const stepKeyExists = localStorage.getItem(ONBOARDING_STEP_KEY) !== null;
|
||||
const isEdited = settings?.edited === true;
|
||||
// Complete if edited is true and step key doesn't exist (onboarding flow finished)
|
||||
setIsOnboardingComplete(isEdited && !stepKeyExists);
|
||||
}
|
||||
};
|
||||
|
||||
// Check on mount and when settings change
|
||||
checkOnboarding();
|
||||
|
||||
// Listen for storage events (for cross-tab sync)
|
||||
window.addEventListener("storage", checkOnboarding);
|
||||
|
||||
return () => {
|
||||
window.removeEventListener("storage", checkOnboarding);
|
||||
};
|
||||
}, [settings?.edited]);
|
||||
|
||||
const setOnboardingComplete = useCallback((complete: boolean) => {
|
||||
setIsOnboardingComplete(complete);
|
||||
}, []);
|
||||
|
||||
// Listen for ingestion failures and set chat error flag
|
||||
useEffect(() => {
|
||||
|
|
@ -228,6 +272,10 @@ export function ChatProvider({ children }: ChatProviderProps) {
|
|||
const startNewConversation = useCallback(async () => {
|
||||
console.log("[CONVERSATION] Starting new conversation");
|
||||
|
||||
// Check if there's existing conversation data - if so, this is a manual "new conversation" action
|
||||
// Check state values before clearing them
|
||||
const hasExistingConversation = conversationData !== null || placeholderConversation !== null;
|
||||
|
||||
// Clear current conversation data and reset state
|
||||
setCurrentConversationId(null);
|
||||
setPreviousResponseIds({ chat: null, langflow: null });
|
||||
|
|
@ -261,15 +309,22 @@ export function ChatProvider({ children }: ChatProviderProps) {
|
|||
setConversationFilterState(null);
|
||||
}
|
||||
} else {
|
||||
console.log("[CONVERSATION] No default filter set");
|
||||
setConversationFilterState(null);
|
||||
// No default filter in localStorage
|
||||
if (hasExistingConversation) {
|
||||
// User is manually starting a new conversation - clear the filter
|
||||
console.log("[CONVERSATION] Manual new conversation - clearing filter");
|
||||
setConversationFilterState(null);
|
||||
} else {
|
||||
// First time after onboarding - preserve existing filter if set
|
||||
// This prevents clearing the filter when startNewConversation is called multiple times during onboarding
|
||||
console.log("[CONVERSATION] No default filter set, preserving existing filter if any");
|
||||
// Don't clear the filter - it may have been set by storeDefaultFilterForNewConversations
|
||||
}
|
||||
}
|
||||
} else {
|
||||
setConversationFilterState(null);
|
||||
}
|
||||
|
||||
// Create a temporary placeholder conversation to show in sidebar
|
||||
const placeholderConversation: ConversationData = {
|
||||
const newPlaceholderConversation: ConversationData = {
|
||||
response_id: "new-conversation-" + Date.now(),
|
||||
title: "New conversation",
|
||||
endpoint: endpoint,
|
||||
|
|
@ -284,10 +339,10 @@ export function ChatProvider({ children }: ChatProviderProps) {
|
|||
last_activity: new Date().toISOString(),
|
||||
};
|
||||
|
||||
setPlaceholderConversation(placeholderConversation);
|
||||
setPlaceholderConversation(newPlaceholderConversation);
|
||||
// Force immediate refresh to ensure sidebar shows correct state
|
||||
refreshConversations(true);
|
||||
}, [endpoint, refreshConversations]);
|
||||
}, [endpoint, refreshConversations, conversationData, placeholderConversation]);
|
||||
|
||||
const addConversationDoc = useCallback((filename: string) => {
|
||||
setConversationDocs((prev) => [
|
||||
|
|
@ -375,6 +430,8 @@ export function ChatProvider({ children }: ChatProviderProps) {
|
|||
setConversationFilter,
|
||||
hasChatError,
|
||||
setChatError,
|
||||
isOnboardingComplete,
|
||||
setOnboardingComplete,
|
||||
}),
|
||||
[
|
||||
endpoint,
|
||||
|
|
@ -396,6 +453,8 @@ export function ChatProvider({ children }: ChatProviderProps) {
|
|||
conversationFilter,
|
||||
setConversationFilter,
|
||||
hasChatError,
|
||||
isOnboardingComplete,
|
||||
setOnboardingComplete,
|
||||
],
|
||||
);
|
||||
|
||||
|
|
|
|||
|
|
@ -12,6 +12,7 @@ export interface UploadFileResult {
|
|||
raw: unknown;
|
||||
createFilter?: boolean;
|
||||
filename?: string;
|
||||
taskId?: string;
|
||||
}
|
||||
|
||||
export async function duplicateCheck(
|
||||
|
|
@ -158,6 +159,7 @@ export async function uploadFile(
|
|||
(uploadIngestJson as { upload?: { id?: string } }).upload?.id ||
|
||||
(uploadIngestJson as { id?: string }).id ||
|
||||
(uploadIngestJson as { task_id?: string }).task_id;
|
||||
const taskId = (uploadIngestJson as { task_id?: string }).task_id;
|
||||
const filePath =
|
||||
(uploadIngestJson as { upload?: { path?: string } }).upload?.path ||
|
||||
(uploadIngestJson as { path?: string }).path ||
|
||||
|
|
@ -197,6 +199,7 @@ export async function uploadFile(
|
|||
raw: uploadIngestJson,
|
||||
createFilter: shouldCreateFilter,
|
||||
filename,
|
||||
taskId,
|
||||
};
|
||||
|
||||
return result;
|
||||
|
|
|
|||
130
frontend/package-lock.json
generated
130
frontend/package-lock.json
generated
|
|
@ -38,7 +38,7 @@
|
|||
"dotenv": "^17.2.3",
|
||||
"lucide-react": "^0.525.0",
|
||||
"motion": "^12.23.12",
|
||||
"next": "15.3.5",
|
||||
"next": "15.5.7",
|
||||
"next-themes": "^0.4.6",
|
||||
"react": "^19.0.0",
|
||||
"react-dom": "^19.0.0",
|
||||
|
|
@ -1169,9 +1169,9 @@
|
|||
}
|
||||
},
|
||||
"node_modules/@next/env": {
|
||||
"version": "15.3.5",
|
||||
"resolved": "https://registry.npmjs.org/@next/env/-/env-15.3.5.tgz",
|
||||
"integrity": "sha512-7g06v8BUVtN2njAX/r8gheoVffhiKFVt4nx74Tt6G4Hqw9HCLYQVx/GkH2qHvPtAHZaUNZ0VXAa0pQP6v1wk7g==",
|
||||
"version": "15.5.7",
|
||||
"resolved": "https://registry.npmjs.org/@next/env/-/env-15.5.7.tgz",
|
||||
"integrity": "sha512-4h6Y2NyEkIEN7Z8YxkA27pq6zTkS09bUSYC0xjd0NpwFxjnIKeZEeH591o5WECSmjpUhLn3H2QLJcDye3Uzcvg==",
|
||||
"license": "MIT"
|
||||
},
|
||||
"node_modules/@next/eslint-plugin-next": {
|
||||
|
|
@ -1185,9 +1185,9 @@
|
|||
}
|
||||
},
|
||||
"node_modules/@next/swc-darwin-arm64": {
|
||||
"version": "15.3.5",
|
||||
"resolved": "https://registry.npmjs.org/@next/swc-darwin-arm64/-/swc-darwin-arm64-15.3.5.tgz",
|
||||
"integrity": "sha512-lM/8tilIsqBq+2nq9kbTW19vfwFve0NR7MxfkuSUbRSgXlMQoJYg+31+++XwKVSXk4uT23G2eF/7BRIKdn8t8w==",
|
||||
"version": "15.5.7",
|
||||
"resolved": "https://registry.npmjs.org/@next/swc-darwin-arm64/-/swc-darwin-arm64-15.5.7.tgz",
|
||||
"integrity": "sha512-IZwtxCEpI91HVU/rAUOOobWSZv4P2DeTtNaCdHqLcTJU4wdNXgAySvKa/qJCgR5m6KI8UsKDXtO2B31jcaw1Yw==",
|
||||
"cpu": [
|
||||
"arm64"
|
||||
],
|
||||
|
|
@ -1201,9 +1201,9 @@
|
|||
}
|
||||
},
|
||||
"node_modules/@next/swc-darwin-x64": {
|
||||
"version": "15.3.5",
|
||||
"resolved": "https://registry.npmjs.org/@next/swc-darwin-x64/-/swc-darwin-x64-15.3.5.tgz",
|
||||
"integrity": "sha512-WhwegPQJ5IfoUNZUVsI9TRAlKpjGVK0tpJTL6KeiC4cux9774NYE9Wu/iCfIkL/5J8rPAkqZpG7n+EfiAfidXA==",
|
||||
"version": "15.5.7",
|
||||
"resolved": "https://registry.npmjs.org/@next/swc-darwin-x64/-/swc-darwin-x64-15.5.7.tgz",
|
||||
"integrity": "sha512-UP6CaDBcqaCBuiq/gfCEJw7sPEoX1aIjZHnBWN9v9qYHQdMKvCKcAVs4OX1vIjeE+tC5EIuwDTVIoXpUes29lg==",
|
||||
"cpu": [
|
||||
"x64"
|
||||
],
|
||||
|
|
@ -1217,9 +1217,9 @@
|
|||
}
|
||||
},
|
||||
"node_modules/@next/swc-linux-arm64-gnu": {
|
||||
"version": "15.3.5",
|
||||
"resolved": "https://registry.npmjs.org/@next/swc-linux-arm64-gnu/-/swc-linux-arm64-gnu-15.3.5.tgz",
|
||||
"integrity": "sha512-LVD6uMOZ7XePg3KWYdGuzuvVboxujGjbcuP2jsPAN3MnLdLoZUXKRc6ixxfs03RH7qBdEHCZjyLP/jBdCJVRJQ==",
|
||||
"version": "15.5.7",
|
||||
"resolved": "https://registry.npmjs.org/@next/swc-linux-arm64-gnu/-/swc-linux-arm64-gnu-15.5.7.tgz",
|
||||
"integrity": "sha512-NCslw3GrNIw7OgmRBxHtdWFQYhexoUCq+0oS2ccjyYLtcn1SzGzeM54jpTFonIMUjNbHmpKpziXnpxhSWLcmBA==",
|
||||
"cpu": [
|
||||
"arm64"
|
||||
],
|
||||
|
|
@ -1233,9 +1233,9 @@
|
|||
}
|
||||
},
|
||||
"node_modules/@next/swc-linux-arm64-musl": {
|
||||
"version": "15.3.5",
|
||||
"resolved": "https://registry.npmjs.org/@next/swc-linux-arm64-musl/-/swc-linux-arm64-musl-15.3.5.tgz",
|
||||
"integrity": "sha512-k8aVScYZ++BnS2P69ClK7v4nOu702jcF9AIHKu6llhHEtBSmM2zkPGl9yoqbSU/657IIIb0QHpdxEr0iW9z53A==",
|
||||
"version": "15.5.7",
|
||||
"resolved": "https://registry.npmjs.org/@next/swc-linux-arm64-musl/-/swc-linux-arm64-musl-15.5.7.tgz",
|
||||
"integrity": "sha512-nfymt+SE5cvtTrG9u1wdoxBr9bVB7mtKTcj0ltRn6gkP/2Nu1zM5ei8rwP9qKQP0Y//umK+TtkKgNtfboBxRrw==",
|
||||
"cpu": [
|
||||
"arm64"
|
||||
],
|
||||
|
|
@ -1249,9 +1249,9 @@
|
|||
}
|
||||
},
|
||||
"node_modules/@next/swc-linux-x64-gnu": {
|
||||
"version": "15.3.5",
|
||||
"resolved": "https://registry.npmjs.org/@next/swc-linux-x64-gnu/-/swc-linux-x64-gnu-15.3.5.tgz",
|
||||
"integrity": "sha512-2xYU0DI9DGN/bAHzVwADid22ba5d/xrbrQlr2U+/Q5WkFUzeL0TDR963BdrtLS/4bMmKZGptLeg6282H/S2i8A==",
|
||||
"version": "15.5.7",
|
||||
"resolved": "https://registry.npmjs.org/@next/swc-linux-x64-gnu/-/swc-linux-x64-gnu-15.5.7.tgz",
|
||||
"integrity": "sha512-hvXcZvCaaEbCZcVzcY7E1uXN9xWZfFvkNHwbe/n4OkRhFWrs1J1QV+4U1BN06tXLdaS4DazEGXwgqnu/VMcmqw==",
|
||||
"cpu": [
|
||||
"x64"
|
||||
],
|
||||
|
|
@ -1265,9 +1265,9 @@
|
|||
}
|
||||
},
|
||||
"node_modules/@next/swc-linux-x64-musl": {
|
||||
"version": "15.3.5",
|
||||
"resolved": "https://registry.npmjs.org/@next/swc-linux-x64-musl/-/swc-linux-x64-musl-15.3.5.tgz",
|
||||
"integrity": "sha512-TRYIqAGf1KCbuAB0gjhdn5Ytd8fV+wJSM2Nh2is/xEqR8PZHxfQuaiNhoF50XfY90sNpaRMaGhF6E+qjV1b9Tg==",
|
||||
"version": "15.5.7",
|
||||
"resolved": "https://registry.npmjs.org/@next/swc-linux-x64-musl/-/swc-linux-x64-musl-15.5.7.tgz",
|
||||
"integrity": "sha512-4IUO539b8FmF0odY6/SqANJdgwn1xs1GkPO5doZugwZ3ETF6JUdckk7RGmsfSf7ws8Qb2YB5It33mvNL/0acqA==",
|
||||
"cpu": [
|
||||
"x64"
|
||||
],
|
||||
|
|
@ -1281,9 +1281,9 @@
|
|||
}
|
||||
},
|
||||
"node_modules/@next/swc-win32-arm64-msvc": {
|
||||
"version": "15.3.5",
|
||||
"resolved": "https://registry.npmjs.org/@next/swc-win32-arm64-msvc/-/swc-win32-arm64-msvc-15.3.5.tgz",
|
||||
"integrity": "sha512-h04/7iMEUSMY6fDGCvdanKqlO1qYvzNxntZlCzfE8i5P0uqzVQWQquU1TIhlz0VqGQGXLrFDuTJVONpqGqjGKQ==",
|
||||
"version": "15.5.7",
|
||||
"resolved": "https://registry.npmjs.org/@next/swc-win32-arm64-msvc/-/swc-win32-arm64-msvc-15.5.7.tgz",
|
||||
"integrity": "sha512-CpJVTkYI3ZajQkC5vajM7/ApKJUOlm6uP4BknM3XKvJ7VXAvCqSjSLmM0LKdYzn6nBJVSjdclx8nYJSa3xlTgQ==",
|
||||
"cpu": [
|
||||
"arm64"
|
||||
],
|
||||
|
|
@ -1297,9 +1297,9 @@
|
|||
}
|
||||
},
|
||||
"node_modules/@next/swc-win32-x64-msvc": {
|
||||
"version": "15.3.5",
|
||||
"resolved": "https://registry.npmjs.org/@next/swc-win32-x64-msvc/-/swc-win32-x64-msvc-15.3.5.tgz",
|
||||
"integrity": "sha512-5fhH6fccXxnX2KhllnGhkYMndhOiLOLEiVGYjP2nizqeGWkN10sA9taATlXwake2E2XMvYZjjz0Uj7T0y+z1yw==",
|
||||
"version": "15.5.7",
|
||||
"resolved": "https://registry.npmjs.org/@next/swc-win32-x64-msvc/-/swc-win32-x64-msvc-15.5.7.tgz",
|
||||
"integrity": "sha512-gMzgBX164I6DN+9/PGA+9dQiwmTkE4TloBNx8Kv9UiGARsr9Nba7IpcBRA1iTV9vwlYnrE3Uy6I7Aj6qLjQuqw==",
|
||||
"cpu": [
|
||||
"x64"
|
||||
],
|
||||
|
|
@ -2568,12 +2568,6 @@
|
|||
"dev": true,
|
||||
"license": "MIT"
|
||||
},
|
||||
"node_modules/@swc/counter": {
|
||||
"version": "0.1.3",
|
||||
"resolved": "https://registry.npmjs.org/@swc/counter/-/counter-0.1.3.tgz",
|
||||
"integrity": "sha512-e2BR4lsJkkRlKZ/qCHPw9ZaSxc0MVUd7gtbtaB7aMvHeJVYe8sOB8DBZkP2DtISHGSku9sCK6T6cnY0CtXrOCQ==",
|
||||
"license": "Apache-2.0"
|
||||
},
|
||||
"node_modules/@swc/helpers": {
|
||||
"version": "0.5.15",
|
||||
"resolved": "https://registry.npmjs.org/@swc/helpers/-/helpers-0.5.15.tgz",
|
||||
|
|
@ -3821,17 +3815,6 @@
|
|||
"node": "^6 || ^7 || ^8 || ^9 || ^10 || ^11 || ^12 || >=13.7"
|
||||
}
|
||||
},
|
||||
"node_modules/busboy": {
|
||||
"version": "1.6.0",
|
||||
"resolved": "https://registry.npmjs.org/busboy/-/busboy-1.6.0.tgz",
|
||||
"integrity": "sha512-8SFQbg/0hQ9xy3UNTB0YEnsNBbWfhf7RtnzpL7TkBiTBRfrQ9Fxcnz7VJsleJpyp6rVLvXiuORqjlHi5q+PYuA==",
|
||||
"dependencies": {
|
||||
"streamsearch": "^1.1.0"
|
||||
},
|
||||
"engines": {
|
||||
"node": ">=10.16.0"
|
||||
}
|
||||
},
|
||||
"node_modules/call-bind": {
|
||||
"version": "1.0.8",
|
||||
"resolved": "https://registry.npmjs.org/call-bind/-/call-bind-1.0.8.tgz",
|
||||
|
|
@ -5448,9 +5431,9 @@
|
|||
}
|
||||
},
|
||||
"node_modules/glob": {
|
||||
"version": "10.4.5",
|
||||
"resolved": "https://registry.npmjs.org/glob/-/glob-10.4.5.tgz",
|
||||
"integrity": "sha512-7Bv8RF0k6xjo7d4A/PxYLbUCfb6c+Vpd2/mB2yRDlew7Jb5hEXiCD9ibfO7wpk8i4sevK6DFny9h7EYbM3/sHg==",
|
||||
"version": "10.5.0",
|
||||
"resolved": "https://registry.npmjs.org/glob/-/glob-10.5.0.tgz",
|
||||
"integrity": "sha512-DfXN8DfhJ7NH3Oe7cFmu3NCu1wKbkReJ8TorzSAFbSKrlNaQSKfIzqYqVY8zlbs2NLBbWpRiU52GX2PbaBVNkg==",
|
||||
"license": "ISC",
|
||||
"dependencies": {
|
||||
"foreground-child": "^3.1.0",
|
||||
|
|
@ -6584,9 +6567,9 @@
|
|||
"license": "MIT"
|
||||
},
|
||||
"node_modules/js-yaml": {
|
||||
"version": "4.1.0",
|
||||
"resolved": "https://registry.npmjs.org/js-yaml/-/js-yaml-4.1.0.tgz",
|
||||
"integrity": "sha512-wpxZs9NoxZaJESJGIZTyDEaYpl0FKSA+FB9aJiyemKhMwkxQg63h4T1KJgUGHpTqPDNRcmmYLugrRjJlBtWvRA==",
|
||||
"version": "4.1.1",
|
||||
"resolved": "https://registry.npmjs.org/js-yaml/-/js-yaml-4.1.1.tgz",
|
||||
"integrity": "sha512-qQKT4zQxXl8lLwBtHMWwaTcGfFOZviOJet3Oy/xmGk2gZH677CJM9EvtfdSkgWcATZhj/55JZ0rmy3myCT5lsA==",
|
||||
"dev": true,
|
||||
"license": "MIT",
|
||||
"dependencies": {
|
||||
|
|
@ -7194,9 +7177,10 @@
|
|||
}
|
||||
},
|
||||
"node_modules/mdast-util-to-hast": {
|
||||
"version": "13.2.0",
|
||||
"resolved": "https://registry.npmjs.org/mdast-util-to-hast/-/mdast-util-to-hast-13.2.0.tgz",
|
||||
"integrity": "sha512-QGYKEuUsYT9ykKBCMOEDLsU5JRObWQusAolFMeko/tYPufNkRffBAQjIE+99jbA87xv6FgmjLtwjh9wBWajwAA==",
|
||||
"version": "13.2.1",
|
||||
"resolved": "https://registry.npmjs.org/mdast-util-to-hast/-/mdast-util-to-hast-13.2.1.tgz",
|
||||
"integrity": "sha512-cctsq2wp5vTsLIcaymblUriiTcZd0CwWtCbLvrOzYCDZoWyMNV8sZ7krj09FSnsiJi3WVsHLM4k6Dq/yaPyCXA==",
|
||||
"license": "MIT",
|
||||
"dependencies": {
|
||||
"@types/hast": "^3.0.0",
|
||||
"@types/mdast": "^4.0.0",
|
||||
|
|
@ -7973,15 +7957,13 @@
|
|||
"license": "MIT"
|
||||
},
|
||||
"node_modules/next": {
|
||||
"version": "15.3.5",
|
||||
"resolved": "https://registry.npmjs.org/next/-/next-15.3.5.tgz",
|
||||
"integrity": "sha512-RkazLBMMDJSJ4XZQ81kolSpwiCt907l0xcgcpF4xC2Vml6QVcPNXW0NQRwQ80FFtSn7UM52XN0anaw8TEJXaiw==",
|
||||
"version": "15.5.7",
|
||||
"resolved": "https://registry.npmjs.org/next/-/next-15.5.7.tgz",
|
||||
"integrity": "sha512-+t2/0jIJ48kUpGKkdlhgkv+zPTEOoXyr60qXe68eB/pl3CMJaLeIGjzp5D6Oqt25hCBiBTt8wEeeAzfJvUKnPQ==",
|
||||
"license": "MIT",
|
||||
"dependencies": {
|
||||
"@next/env": "15.3.5",
|
||||
"@swc/counter": "0.1.3",
|
||||
"@next/env": "15.5.7",
|
||||
"@swc/helpers": "0.5.15",
|
||||
"busboy": "1.6.0",
|
||||
"caniuse-lite": "^1.0.30001579",
|
||||
"postcss": "8.4.31",
|
||||
"styled-jsx": "5.1.6"
|
||||
|
|
@ -7993,19 +7975,19 @@
|
|||
"node": "^18.18.0 || ^19.8.0 || >= 20.0.0"
|
||||
},
|
||||
"optionalDependencies": {
|
||||
"@next/swc-darwin-arm64": "15.3.5",
|
||||
"@next/swc-darwin-x64": "15.3.5",
|
||||
"@next/swc-linux-arm64-gnu": "15.3.5",
|
||||
"@next/swc-linux-arm64-musl": "15.3.5",
|
||||
"@next/swc-linux-x64-gnu": "15.3.5",
|
||||
"@next/swc-linux-x64-musl": "15.3.5",
|
||||
"@next/swc-win32-arm64-msvc": "15.3.5",
|
||||
"@next/swc-win32-x64-msvc": "15.3.5",
|
||||
"sharp": "^0.34.1"
|
||||
"@next/swc-darwin-arm64": "15.5.7",
|
||||
"@next/swc-darwin-x64": "15.5.7",
|
||||
"@next/swc-linux-arm64-gnu": "15.5.7",
|
||||
"@next/swc-linux-arm64-musl": "15.5.7",
|
||||
"@next/swc-linux-x64-gnu": "15.5.7",
|
||||
"@next/swc-linux-x64-musl": "15.5.7",
|
||||
"@next/swc-win32-arm64-msvc": "15.5.7",
|
||||
"@next/swc-win32-x64-msvc": "15.5.7",
|
||||
"sharp": "^0.34.3"
|
||||
},
|
||||
"peerDependencies": {
|
||||
"@opentelemetry/api": "^1.1.0",
|
||||
"@playwright/test": "^1.41.2",
|
||||
"@playwright/test": "^1.51.1",
|
||||
"babel-plugin-react-compiler": "*",
|
||||
"react": "^18.2.0 || 19.0.0-rc-de68d2f4-20241204 || ^19.0.0",
|
||||
"react-dom": "^18.2.0 || 19.0.0-rc-de68d2f4-20241204 || ^19.0.0",
|
||||
|
|
@ -9492,14 +9474,6 @@
|
|||
"node": ">= 0.4"
|
||||
}
|
||||
},
|
||||
"node_modules/streamsearch": {
|
||||
"version": "1.1.0",
|
||||
"resolved": "https://registry.npmjs.org/streamsearch/-/streamsearch-1.1.0.tgz",
|
||||
"integrity": "sha512-Mcc5wHehp9aXz1ax6bZUyY5afg9u2rv5cqQI3mRrYkGC8rW2hM02jWuwjtL++LS5qinSyhj2QfLyNsuc+VsExg==",
|
||||
"engines": {
|
||||
"node": ">=10.0.0"
|
||||
}
|
||||
},
|
||||
"node_modules/string-width": {
|
||||
"version": "5.1.2",
|
||||
"resolved": "https://registry.npmjs.org/string-width/-/string-width-5.1.2.tgz",
|
||||
|
|
|
|||
|
|
@ -41,7 +41,7 @@
|
|||
"dotenv": "^17.2.3",
|
||||
"lucide-react": "^0.525.0",
|
||||
"motion": "^12.23.12",
|
||||
"next": "15.3.5",
|
||||
"next": "15.5.7",
|
||||
"next-themes": "^0.4.6",
|
||||
"react": "^19.0.0",
|
||||
"react-dom": "^19.0.0",
|
||||
|
|
|
|||
20
src/agent.py
20
src/agent.py
|
|
@ -47,8 +47,8 @@ def get_conversation_thread(user_id: str, previous_response_id: str = None):
|
|||
return new_conversation
|
||||
|
||||
|
||||
def store_conversation_thread(user_id: str, response_id: str, conversation_state: dict):
|
||||
"""Store conversation both in memory (with function calls) and persist metadata to disk"""
|
||||
async def store_conversation_thread(user_id: str, response_id: str, conversation_state: dict):
|
||||
"""Store conversation both in memory (with function calls) and persist metadata to disk (async, non-blocking)"""
|
||||
# 1. Store full conversation in memory for function call preservation
|
||||
if user_id not in active_conversations:
|
||||
active_conversations[user_id] = {}
|
||||
|
|
@ -76,7 +76,7 @@ def store_conversation_thread(user_id: str, response_id: str, conversation_state
|
|||
# Don't store actual messages - Langflow has them
|
||||
}
|
||||
|
||||
conversation_persistence.store_conversation_thread(
|
||||
await conversation_persistence.store_conversation_thread(
|
||||
user_id, response_id, metadata_only
|
||||
)
|
||||
|
||||
|
|
@ -382,7 +382,7 @@ async def async_chat(
|
|||
# Store the conversation thread with its response_id
|
||||
if response_id:
|
||||
conversation_state["last_activity"] = datetime.now()
|
||||
store_conversation_thread(user_id, response_id, conversation_state)
|
||||
await store_conversation_thread(user_id, response_id, conversation_state)
|
||||
logger.debug(
|
||||
"Stored conversation thread", user_id=user_id, response_id=response_id
|
||||
)
|
||||
|
|
@ -461,7 +461,7 @@ async def async_chat_stream(
|
|||
# Store the conversation thread with its response_id
|
||||
if response_id:
|
||||
conversation_state["last_activity"] = datetime.now()
|
||||
store_conversation_thread(user_id, response_id, conversation_state)
|
||||
await store_conversation_thread(user_id, response_id, conversation_state)
|
||||
logger.debug(
|
||||
f"Stored conversation thread for user {user_id} with response_id: {response_id}"
|
||||
)
|
||||
|
|
@ -549,7 +549,7 @@ async def async_langflow_chat(
|
|||
# Store the conversation thread with its response_id
|
||||
if response_id:
|
||||
conversation_state["last_activity"] = datetime.now()
|
||||
store_conversation_thread(user_id, response_id, conversation_state)
|
||||
await store_conversation_thread(user_id, response_id, conversation_state)
|
||||
|
||||
# Claim session ownership for this user
|
||||
try:
|
||||
|
|
@ -656,7 +656,7 @@ async def async_langflow_chat_stream(
|
|||
# Store the conversation thread with its response_id
|
||||
if response_id:
|
||||
conversation_state["last_activity"] = datetime.now()
|
||||
store_conversation_thread(user_id, response_id, conversation_state)
|
||||
await store_conversation_thread(user_id, response_id, conversation_state)
|
||||
|
||||
# Claim session ownership for this user
|
||||
try:
|
||||
|
|
@ -672,8 +672,8 @@ async def async_langflow_chat_stream(
|
|||
)
|
||||
|
||||
|
||||
def delete_user_conversation(user_id: str, response_id: str) -> bool:
|
||||
"""Delete a conversation for a user from both memory and persistent storage"""
|
||||
async def delete_user_conversation(user_id: str, response_id: str) -> bool:
|
||||
"""Delete a conversation for a user from both memory and persistent storage (async, non-blocking)"""
|
||||
deleted = False
|
||||
|
||||
try:
|
||||
|
|
@ -684,7 +684,7 @@ def delete_user_conversation(user_id: str, response_id: str) -> bool:
|
|||
deleted = True
|
||||
|
||||
# Delete from persistent storage
|
||||
conversation_deleted = conversation_persistence.delete_conversation_thread(user_id, response_id)
|
||||
conversation_deleted = await conversation_persistence.delete_conversation_thread(user_id, response_id)
|
||||
if conversation_deleted:
|
||||
logger.debug(f"Deleted conversation {response_id} from persistent storage for user {user_id}")
|
||||
deleted = True
|
||||
|
|
|
|||
|
|
@ -1,5 +1,6 @@
|
|||
"""Provider validation utilities for testing API keys and models during onboarding."""
|
||||
|
||||
import json
|
||||
import httpx
|
||||
from utils.container_utils import transform_localhost_url
|
||||
from utils.logging_config import get_logger
|
||||
|
|
@ -7,6 +8,106 @@ from utils.logging_config import get_logger
|
|||
logger = get_logger(__name__)
|
||||
|
||||
|
||||
def _parse_json_error_message(error_text: str) -> str:
|
||||
"""Parse JSON error message and extract just the message field."""
|
||||
try:
|
||||
# Try to parse as JSON
|
||||
error_data = json.loads(error_text)
|
||||
|
||||
if isinstance(error_data, dict):
|
||||
# WatsonX format: {"errors": [{"code": "...", "message": "..."}], ...}
|
||||
if "errors" in error_data and isinstance(error_data["errors"], list):
|
||||
errors = error_data["errors"]
|
||||
if len(errors) > 0 and isinstance(errors[0], dict):
|
||||
message = errors[0].get("message", "")
|
||||
if message:
|
||||
return message
|
||||
code = errors[0].get("code", "")
|
||||
if code:
|
||||
return f"Error: {code}"
|
||||
|
||||
# OpenAI format: {"error": {"message": "...", "type": "...", "code": "..."}}
|
||||
if "error" in error_data:
|
||||
error_obj = error_data["error"]
|
||||
if isinstance(error_obj, dict):
|
||||
message = error_obj.get("message", "")
|
||||
if message:
|
||||
return message
|
||||
|
||||
# Direct message field
|
||||
if "message" in error_data:
|
||||
return error_data["message"]
|
||||
|
||||
# Generic format: {"detail": "..."}
|
||||
if "detail" in error_data:
|
||||
return error_data["detail"]
|
||||
except (json.JSONDecodeError, ValueError, TypeError):
|
||||
pass
|
||||
|
||||
# Return original text if not JSON or can't parse
|
||||
return error_text
|
||||
|
||||
|
||||
def _extract_error_details(response: httpx.Response) -> str:
|
||||
"""Extract detailed error message from API response."""
|
||||
try:
|
||||
# Try to parse JSON error response
|
||||
error_data = response.json()
|
||||
|
||||
# Common error response formats
|
||||
if isinstance(error_data, dict):
|
||||
# WatsonX format: {"errors": [{"code": "...", "message": "..."}], ...}
|
||||
if "errors" in error_data and isinstance(error_data["errors"], list):
|
||||
errors = error_data["errors"]
|
||||
if len(errors) > 0 and isinstance(errors[0], dict):
|
||||
# Extract just the message from the first error
|
||||
message = errors[0].get("message", "")
|
||||
if message:
|
||||
return message
|
||||
# Fallback to code if no message
|
||||
code = errors[0].get("code", "")
|
||||
if code:
|
||||
return f"Error: {code}"
|
||||
|
||||
# OpenAI format: {"error": {"message": "...", "type": "...", "code": "..."}}
|
||||
if "error" in error_data:
|
||||
error_obj = error_data["error"]
|
||||
if isinstance(error_obj, dict):
|
||||
message = error_obj.get("message", "")
|
||||
error_type = error_obj.get("type", "")
|
||||
code = error_obj.get("code", "")
|
||||
if message:
|
||||
details = message
|
||||
if error_type:
|
||||
details += f" (type: {error_type})"
|
||||
if code:
|
||||
details += f" (code: {code})"
|
||||
return details
|
||||
|
||||
# Anthropic format: {"error": {"message": "...", "type": "..."}}
|
||||
if "message" in error_data:
|
||||
return error_data["message"]
|
||||
|
||||
# Generic format: {"message": "..."}
|
||||
if "detail" in error_data:
|
||||
return error_data["detail"]
|
||||
|
||||
# If JSON parsing worked but no structured error found, try parsing text
|
||||
response_text = response.text[:500]
|
||||
parsed = _parse_json_error_message(response_text)
|
||||
if parsed != response_text:
|
||||
return parsed
|
||||
return response_text
|
||||
|
||||
except (json.JSONDecodeError, ValueError):
|
||||
# If JSON parsing fails, try parsing the text as JSON string
|
||||
response_text = response.text[:500] if response.text else f"HTTP {response.status_code}"
|
||||
parsed = _parse_json_error_message(response_text)
|
||||
if parsed != response_text:
|
||||
return parsed
|
||||
return response_text
|
||||
|
||||
|
||||
async def validate_provider_setup(
|
||||
provider: str,
|
||||
api_key: str = None,
|
||||
|
|
@ -30,7 +131,7 @@ async def validate_provider_setup(
|
|||
If False, performs lightweight validation (no credits consumed). Default: False.
|
||||
|
||||
Raises:
|
||||
Exception: If validation fails with message "Setup failed, please try again or select a different provider."
|
||||
Exception: If validation fails, raises the original exception with the actual error message.
|
||||
"""
|
||||
provider_lower = provider.lower()
|
||||
|
||||
|
|
@ -70,7 +171,8 @@ async def validate_provider_setup(
|
|||
|
||||
except Exception as e:
|
||||
logger.error(f"Validation failed for provider {provider_lower}: {str(e)}")
|
||||
raise Exception("Setup failed, please try again or select a different provider.")
|
||||
# Preserve the original error message instead of replacing it with a generic one
|
||||
raise
|
||||
|
||||
|
||||
async def test_lightweight_health(
|
||||
|
|
@ -155,8 +257,9 @@ async def _test_openai_lightweight_health(api_key: str) -> None:
|
|||
)
|
||||
|
||||
if response.status_code != 200:
|
||||
logger.error(f"OpenAI lightweight health check failed: {response.status_code}")
|
||||
raise Exception(f"OpenAI API key validation failed: {response.status_code}")
|
||||
error_details = _extract_error_details(response)
|
||||
logger.error(f"OpenAI lightweight health check failed: {response.status_code} - {error_details}")
|
||||
raise Exception(f"OpenAI API key validation failed: {error_details}")
|
||||
|
||||
logger.info("OpenAI lightweight health check passed")
|
||||
|
||||
|
|
@ -225,8 +328,9 @@ async def _test_openai_completion_with_tools(api_key: str, llm_model: str) -> No
|
|||
)
|
||||
|
||||
if response.status_code != 200:
|
||||
logger.error(f"OpenAI completion test failed: {response.status_code} - {response.text}")
|
||||
raise Exception(f"OpenAI API error: {response.status_code}")
|
||||
error_details = _extract_error_details(response)
|
||||
logger.error(f"OpenAI completion test failed: {response.status_code} - {error_details}")
|
||||
raise Exception(f"OpenAI API error: {error_details}")
|
||||
|
||||
logger.info("OpenAI completion with tool calling test passed")
|
||||
|
||||
|
|
@ -260,8 +364,9 @@ async def _test_openai_embedding(api_key: str, embedding_model: str) -> None:
|
|||
)
|
||||
|
||||
if response.status_code != 200:
|
||||
logger.error(f"OpenAI embedding test failed: {response.status_code} - {response.text}")
|
||||
raise Exception(f"OpenAI API error: {response.status_code}")
|
||||
error_details = _extract_error_details(response)
|
||||
logger.error(f"OpenAI embedding test failed: {response.status_code} - {error_details}")
|
||||
raise Exception(f"OpenAI API error: {error_details}")
|
||||
|
||||
data = response.json()
|
||||
if not data.get("data") or len(data["data"]) == 0:
|
||||
|
|
@ -300,8 +405,9 @@ async def _test_watsonx_lightweight_health(
|
|||
)
|
||||
|
||||
if token_response.status_code != 200:
|
||||
logger.error(f"IBM IAM token request failed: {token_response.status_code}")
|
||||
raise Exception("Failed to authenticate with IBM Watson - invalid API key")
|
||||
error_details = _extract_error_details(token_response)
|
||||
logger.error(f"IBM IAM token request failed: {token_response.status_code} - {error_details}")
|
||||
raise Exception(f"Failed to authenticate with IBM Watson: {error_details}")
|
||||
|
||||
bearer_token = token_response.json().get("access_token")
|
||||
if not bearer_token:
|
||||
|
|
@ -335,8 +441,9 @@ async def _test_watsonx_completion_with_tools(
|
|||
)
|
||||
|
||||
if token_response.status_code != 200:
|
||||
logger.error(f"IBM IAM token request failed: {token_response.status_code}")
|
||||
raise Exception("Failed to authenticate with IBM Watson")
|
||||
error_details = _extract_error_details(token_response)
|
||||
logger.error(f"IBM IAM token request failed: {token_response.status_code} - {error_details}")
|
||||
raise Exception(f"Failed to authenticate with IBM Watson: {error_details}")
|
||||
|
||||
bearer_token = token_response.json().get("access_token")
|
||||
if not bearer_token:
|
||||
|
|
@ -388,8 +495,11 @@ async def _test_watsonx_completion_with_tools(
|
|||
)
|
||||
|
||||
if response.status_code != 200:
|
||||
logger.error(f"IBM Watson completion test failed: {response.status_code} - {response.text}")
|
||||
raise Exception(f"IBM Watson API error: {response.status_code}")
|
||||
error_details = _extract_error_details(response)
|
||||
logger.error(f"IBM Watson completion test failed: {response.status_code} - {error_details}")
|
||||
# If error_details is still JSON, parse it to extract just the message
|
||||
parsed_details = _parse_json_error_message(error_details)
|
||||
raise Exception(f"IBM Watson API error: {parsed_details}")
|
||||
|
||||
logger.info("IBM Watson completion with tool calling test passed")
|
||||
|
||||
|
|
@ -398,6 +508,13 @@ async def _test_watsonx_completion_with_tools(
|
|||
raise Exception("Request timed out")
|
||||
except Exception as e:
|
||||
logger.error(f"IBM Watson completion test failed: {str(e)}")
|
||||
# If the error message contains JSON, parse it to extract just the message
|
||||
error_str = str(e)
|
||||
if "IBM Watson API error: " in error_str:
|
||||
json_part = error_str.split("IBM Watson API error: ", 1)[1]
|
||||
parsed_message = _parse_json_error_message(json_part)
|
||||
if parsed_message != json_part:
|
||||
raise Exception(f"IBM Watson API error: {parsed_message}")
|
||||
raise
|
||||
|
||||
|
||||
|
|
@ -419,8 +536,9 @@ async def _test_watsonx_embedding(
|
|||
)
|
||||
|
||||
if token_response.status_code != 200:
|
||||
logger.error(f"IBM IAM token request failed: {token_response.status_code}")
|
||||
raise Exception("Failed to authenticate with IBM Watson")
|
||||
error_details = _extract_error_details(token_response)
|
||||
logger.error(f"IBM IAM token request failed: {token_response.status_code} - {error_details}")
|
||||
raise Exception(f"Failed to authenticate with IBM Watson: {error_details}")
|
||||
|
||||
bearer_token = token_response.json().get("access_token")
|
||||
if not bearer_token:
|
||||
|
|
@ -450,8 +568,11 @@ async def _test_watsonx_embedding(
|
|||
)
|
||||
|
||||
if response.status_code != 200:
|
||||
logger.error(f"IBM Watson embedding test failed: {response.status_code} - {response.text}")
|
||||
raise Exception(f"IBM Watson API error: {response.status_code}")
|
||||
error_details = _extract_error_details(response)
|
||||
logger.error(f"IBM Watson embedding test failed: {response.status_code} - {error_details}")
|
||||
# If error_details is still JSON, parse it to extract just the message
|
||||
parsed_details = _parse_json_error_message(error_details)
|
||||
raise Exception(f"IBM Watson API error: {parsed_details}")
|
||||
|
||||
data = response.json()
|
||||
if not data.get("results") or len(data["results"]) == 0:
|
||||
|
|
@ -464,6 +585,13 @@ async def _test_watsonx_embedding(
|
|||
raise Exception("Request timed out")
|
||||
except Exception as e:
|
||||
logger.error(f"IBM Watson embedding test failed: {str(e)}")
|
||||
# If the error message contains JSON, parse it to extract just the message
|
||||
error_str = str(e)
|
||||
if "IBM Watson API error: " in error_str:
|
||||
json_part = error_str.split("IBM Watson API error: ", 1)[1]
|
||||
parsed_message = _parse_json_error_message(json_part)
|
||||
if parsed_message != json_part:
|
||||
raise Exception(f"IBM Watson API error: {parsed_message}")
|
||||
raise
|
||||
|
||||
|
||||
|
|
@ -483,8 +611,9 @@ async def _test_ollama_lightweight_health(endpoint: str) -> None:
|
|||
)
|
||||
|
||||
if response.status_code != 200:
|
||||
logger.error(f"Ollama lightweight health check failed: {response.status_code}")
|
||||
raise Exception(f"Ollama endpoint not responding: {response.status_code}")
|
||||
error_details = _extract_error_details(response)
|
||||
logger.error(f"Ollama lightweight health check failed: {response.status_code} - {error_details}")
|
||||
raise Exception(f"Ollama endpoint not responding: {error_details}")
|
||||
|
||||
logger.info("Ollama lightweight health check passed")
|
||||
|
||||
|
|
@ -537,8 +666,9 @@ async def _test_ollama_completion_with_tools(llm_model: str, endpoint: str) -> N
|
|||
)
|
||||
|
||||
if response.status_code != 200:
|
||||
logger.error(f"Ollama completion test failed: {response.status_code} - {response.text}")
|
||||
raise Exception(f"Ollama API error: {response.status_code}")
|
||||
error_details = _extract_error_details(response)
|
||||
logger.error(f"Ollama completion test failed: {response.status_code} - {error_details}")
|
||||
raise Exception(f"Ollama API error: {error_details}")
|
||||
|
||||
logger.info("Ollama completion with tool calling test passed")
|
||||
|
||||
|
|
@ -569,8 +699,9 @@ async def _test_ollama_embedding(embedding_model: str, endpoint: str) -> None:
|
|||
)
|
||||
|
||||
if response.status_code != 200:
|
||||
logger.error(f"Ollama embedding test failed: {response.status_code} - {response.text}")
|
||||
raise Exception(f"Ollama API error: {response.status_code}")
|
||||
error_details = _extract_error_details(response)
|
||||
logger.error(f"Ollama embedding test failed: {response.status_code} - {error_details}")
|
||||
raise Exception(f"Ollama API error: {error_details}")
|
||||
|
||||
data = response.json()
|
||||
if not data.get("embedding"):
|
||||
|
|
@ -616,8 +747,9 @@ async def _test_anthropic_lightweight_health(api_key: str) -> None:
|
|||
)
|
||||
|
||||
if response.status_code != 200:
|
||||
logger.error(f"Anthropic lightweight health check failed: {response.status_code}")
|
||||
raise Exception(f"Anthropic API key validation failed: {response.status_code}")
|
||||
error_details = _extract_error_details(response)
|
||||
logger.error(f"Anthropic lightweight health check failed: {response.status_code} - {error_details}")
|
||||
raise Exception(f"Anthropic API key validation failed: {error_details}")
|
||||
|
||||
logger.info("Anthropic lightweight health check passed")
|
||||
|
||||
|
|
@ -672,8 +804,9 @@ async def _test_anthropic_completion_with_tools(api_key: str, llm_model: str) ->
|
|||
)
|
||||
|
||||
if response.status_code != 200:
|
||||
logger.error(f"Anthropic completion test failed: {response.status_code} - {response.text}")
|
||||
raise Exception(f"Anthropic API error: {response.status_code}")
|
||||
error_details = _extract_error_details(response)
|
||||
logger.error(f"Anthropic completion test failed: {response.status_code} - {error_details}")
|
||||
raise Exception(f"Anthropic API error: {error_details}")
|
||||
|
||||
logger.info("Anthropic completion with tool calling test passed")
|
||||
|
||||
|
|
|
|||
|
|
@ -897,7 +897,7 @@ async def onboarding(request, flows_service, session_manager=None):
|
|||
)
|
||||
|
||||
# Validate provider setup before initializing OpenSearch index
|
||||
# Use lightweight validation (test_completion=False) to avoid consuming credits during onboarding
|
||||
# Use full validation with completion tests (test_completion=True) to ensure provider health during onboarding
|
||||
try:
|
||||
from api.provider_validation import validate_provider_setup
|
||||
|
||||
|
|
@ -906,14 +906,14 @@ async def onboarding(request, flows_service, session_manager=None):
|
|||
llm_provider = current_config.agent.llm_provider.lower()
|
||||
llm_provider_config = current_config.get_llm_provider_config()
|
||||
|
||||
logger.info(f"Validating LLM provider setup for {llm_provider} (lightweight)")
|
||||
logger.info(f"Validating LLM provider setup for {llm_provider} (full validation with completion test)")
|
||||
await validate_provider_setup(
|
||||
provider=llm_provider,
|
||||
api_key=getattr(llm_provider_config, "api_key", None),
|
||||
llm_model=current_config.agent.llm_model,
|
||||
endpoint=getattr(llm_provider_config, "endpoint", None),
|
||||
project_id=getattr(llm_provider_config, "project_id", None),
|
||||
test_completion=False, # Lightweight validation - no credits consumed
|
||||
test_completion=True, # Full validation with completion test - ensures provider health
|
||||
)
|
||||
logger.info(f"LLM provider setup validation completed successfully for {llm_provider}")
|
||||
|
||||
|
|
@ -922,14 +922,14 @@ async def onboarding(request, flows_service, session_manager=None):
|
|||
embedding_provider = current_config.knowledge.embedding_provider.lower()
|
||||
embedding_provider_config = current_config.get_embedding_provider_config()
|
||||
|
||||
logger.info(f"Validating embedding provider setup for {embedding_provider} (lightweight)")
|
||||
logger.info(f"Validating embedding provider setup for {embedding_provider} (full validation with completion test)")
|
||||
await validate_provider_setup(
|
||||
provider=embedding_provider,
|
||||
api_key=getattr(embedding_provider_config, "api_key", None),
|
||||
embedding_model=current_config.knowledge.embedding_model,
|
||||
endpoint=getattr(embedding_provider_config, "endpoint", None),
|
||||
project_id=getattr(embedding_provider_config, "project_id", None),
|
||||
test_completion=False, # Lightweight validation - no credits consumed
|
||||
test_completion=True, # Full validation with completion test - ensures provider health
|
||||
)
|
||||
logger.info(f"Embedding provider setup validation completed successfully for {embedding_provider}")
|
||||
except Exception as e:
|
||||
|
|
@ -1403,6 +1403,139 @@ async def reapply_all_settings(session_manager = None):
|
|||
raise
|
||||
|
||||
|
||||
async def rollback_onboarding(request, session_manager, task_service):
|
||||
"""Rollback onboarding configuration when sample data files fail.
|
||||
|
||||
This will:
|
||||
1. Cancel all active tasks
|
||||
2. Delete successfully ingested knowledge documents
|
||||
3. Reset configuration to allow re-onboarding
|
||||
"""
|
||||
try:
|
||||
# Get current configuration
|
||||
current_config = get_openrag_config()
|
||||
|
||||
# Only allow rollback if config was marked as edited (onboarding completed)
|
||||
if not current_config.edited:
|
||||
return JSONResponse(
|
||||
{"error": "No onboarding configuration to rollback"}, status_code=400
|
||||
)
|
||||
|
||||
user = request.state.user
|
||||
jwt_token = session_manager.get_effective_jwt_token(user.user_id, request.state.jwt_token)
|
||||
|
||||
logger.info("Rolling back onboarding configuration due to file failures")
|
||||
|
||||
# Get all tasks for the user
|
||||
all_tasks = task_service.get_all_tasks(user.user_id)
|
||||
|
||||
cancelled_tasks = []
|
||||
deleted_files = []
|
||||
|
||||
# Cancel all active tasks and collect successfully ingested files
|
||||
for task_data in all_tasks:
|
||||
task_id = task_data.get("task_id")
|
||||
task_status = task_data.get("status")
|
||||
|
||||
# Cancel active tasks (pending, running, processing)
|
||||
if task_status in ["pending", "running", "processing"]:
|
||||
try:
|
||||
success = await task_service.cancel_task(user.user_id, task_id)
|
||||
if success:
|
||||
cancelled_tasks.append(task_id)
|
||||
logger.info(f"Cancelled task {task_id}")
|
||||
except Exception as e:
|
||||
logger.error(f"Failed to cancel task {task_id}: {str(e)}")
|
||||
|
||||
# For completed tasks, find successfully ingested files and delete them
|
||||
elif task_status == "completed":
|
||||
files = task_data.get("files", {})
|
||||
if isinstance(files, dict):
|
||||
for file_path, file_info in files.items():
|
||||
# Check if file was successfully ingested
|
||||
if isinstance(file_info, dict):
|
||||
file_status = file_info.get("status")
|
||||
filename = file_info.get("filename") or file_path.split("/")[-1]
|
||||
|
||||
if file_status == "completed" and filename:
|
||||
try:
|
||||
# Get user's OpenSearch client
|
||||
opensearch_client = session_manager.get_user_opensearch_client(
|
||||
user.user_id, jwt_token
|
||||
)
|
||||
|
||||
# Delete documents by filename
|
||||
from utils.opensearch_queries import build_filename_delete_body
|
||||
from config.settings import INDEX_NAME
|
||||
|
||||
delete_query = build_filename_delete_body(filename)
|
||||
|
||||
result = await opensearch_client.delete_by_query(
|
||||
index=INDEX_NAME,
|
||||
body=delete_query,
|
||||
conflicts="proceed"
|
||||
)
|
||||
|
||||
deleted_count = result.get("deleted", 0)
|
||||
if deleted_count > 0:
|
||||
deleted_files.append(filename)
|
||||
logger.info(f"Deleted {deleted_count} chunks for filename {filename}")
|
||||
except Exception as e:
|
||||
logger.error(f"Failed to delete documents for {filename}: {str(e)}")
|
||||
|
||||
# Clear embedding provider and model settings
|
||||
current_config.knowledge.embedding_provider = "openai" # Reset to default
|
||||
current_config.knowledge.embedding_model = ""
|
||||
|
||||
# Mark config as not edited so user can go through onboarding again
|
||||
current_config.edited = False
|
||||
|
||||
# Save the rolled back configuration manually to avoid save_config_file setting edited=True
|
||||
try:
|
||||
import yaml
|
||||
config_file = config_manager.config_file
|
||||
|
||||
# Ensure directory exists
|
||||
config_file.parent.mkdir(parents=True, exist_ok=True)
|
||||
|
||||
# Save config with edited=False
|
||||
with open(config_file, "w") as f:
|
||||
yaml.dump(current_config.to_dict(), f, default_flow_style=False, indent=2)
|
||||
|
||||
# Update cached config
|
||||
config_manager._config = current_config
|
||||
|
||||
logger.info("Successfully saved rolled back configuration with edited=False")
|
||||
except Exception as e:
|
||||
logger.error(f"Failed to save rolled back configuration: {e}")
|
||||
return JSONResponse(
|
||||
{"error": "Failed to save rolled back configuration"}, status_code=500
|
||||
)
|
||||
|
||||
logger.info(
|
||||
f"Successfully rolled back onboarding configuration. "
|
||||
f"Cancelled {len(cancelled_tasks)} tasks, deleted {len(deleted_files)} files"
|
||||
)
|
||||
await TelemetryClient.send_event(
|
||||
Category.ONBOARDING,
|
||||
MessageId.ORB_ONBOARD_ROLLBACK
|
||||
)
|
||||
|
||||
return JSONResponse(
|
||||
{
|
||||
"message": "Onboarding configuration rolled back successfully",
|
||||
"cancelled_tasks": len(cancelled_tasks),
|
||||
"deleted_files": len(deleted_files),
|
||||
}
|
||||
)
|
||||
|
||||
except Exception as e:
|
||||
logger.error("Failed to rollback onboarding configuration", error=str(e))
|
||||
return JSONResponse(
|
||||
{"error": f"Failed to rollback onboarding: {str(e)}"}, status_code=500
|
||||
)
|
||||
|
||||
|
||||
async def update_docling_preset(request, session_manager):
|
||||
"""Update docling settings in the ingest flow - deprecated endpoint, use /settings instead"""
|
||||
try:
|
||||
|
|
|
|||
|
|
@ -1,3 +1,4 @@
|
|||
import asyncio
|
||||
import os
|
||||
import time
|
||||
|
||||
|
|
@ -140,61 +141,29 @@ INDEX_BODY = {
|
|||
LANGFLOW_BASE_URL = f"{LANGFLOW_URL}/api/v1"
|
||||
|
||||
|
||||
async def generate_langflow_api_key(modify: bool = False):
|
||||
"""Generate Langflow API key using superuser credentials at startup"""
|
||||
async def get_langflow_api_key(force_regenerate: bool = False):
|
||||
"""Get the Langflow API key, generating one if needed.
|
||||
|
||||
Args:
|
||||
force_regenerate: If True, generates a new key even if one is cached.
|
||||
Used when a request fails with 401/403 to get a fresh key.
|
||||
"""
|
||||
global LANGFLOW_KEY
|
||||
|
||||
logger.debug(
|
||||
"generate_langflow_api_key called", current_key_present=bool(LANGFLOW_KEY)
|
||||
"get_langflow_api_key called",
|
||||
current_key_present=bool(LANGFLOW_KEY),
|
||||
force_regenerate=force_regenerate,
|
||||
)
|
||||
|
||||
# If key already provided via env, do not attempt generation
|
||||
if LANGFLOW_KEY:
|
||||
if os.getenv("LANGFLOW_KEY"):
|
||||
logger.info("Using LANGFLOW_KEY from environment; skipping generation")
|
||||
return LANGFLOW_KEY
|
||||
else:
|
||||
# We have a cached key, but let's validate it first
|
||||
logger.debug("Validating cached LANGFLOW_KEY", key_prefix=LANGFLOW_KEY[:8])
|
||||
try:
|
||||
validation_response = requests.get(
|
||||
f"{LANGFLOW_URL}/api/v1/users/whoami",
|
||||
headers={"x-api-key": LANGFLOW_KEY},
|
||||
timeout=5,
|
||||
)
|
||||
if validation_response.status_code == 200:
|
||||
logger.debug("Cached API key is valid", key_prefix=LANGFLOW_KEY[:8])
|
||||
return LANGFLOW_KEY
|
||||
elif validation_response.status_code in (401, 403):
|
||||
logger.warning(
|
||||
"Cached API key is unauthorized, generating fresh key",
|
||||
status_code=validation_response.status_code,
|
||||
)
|
||||
LANGFLOW_KEY = None # Clear invalid key
|
||||
else:
|
||||
logger.warning(
|
||||
"Cached API key validation returned non-access error; keeping existing key",
|
||||
status_code=validation_response.status_code,
|
||||
)
|
||||
return LANGFLOW_KEY
|
||||
except requests.exceptions.Timeout as e:
|
||||
logger.warning(
|
||||
"Cached API key validation timed out; keeping existing key",
|
||||
error=str(e),
|
||||
)
|
||||
return LANGFLOW_KEY
|
||||
except requests.exceptions.RequestException as e:
|
||||
logger.warning(
|
||||
"Cached API key validation failed due to request error; keeping existing key",
|
||||
error=str(e),
|
||||
)
|
||||
return LANGFLOW_KEY
|
||||
except Exception as e:
|
||||
logger.warning(
|
||||
"Unexpected error during cached API key validation; keeping existing key",
|
||||
error=str(e),
|
||||
)
|
||||
return LANGFLOW_KEY
|
||||
# If we have a cached key and not forcing regeneration, return it
|
||||
if LANGFLOW_KEY and not force_regenerate:
|
||||
return LANGFLOW_KEY
|
||||
|
||||
# If forcing regeneration, clear the cached key
|
||||
if force_regenerate and LANGFLOW_KEY:
|
||||
logger.info("Forcing Langflow API key regeneration due to auth failure")
|
||||
LANGFLOW_KEY = None
|
||||
|
||||
# Use default langflow/langflow credentials if auto-login is enabled and credentials not set
|
||||
username = LANGFLOW_SUPERUSER
|
||||
|
|
@ -216,72 +185,70 @@ async def generate_langflow_api_key(modify: bool = False):
|
|||
max_attempts = int(os.getenv("LANGFLOW_KEY_RETRIES", "15"))
|
||||
delay_seconds = float(os.getenv("LANGFLOW_KEY_RETRY_DELAY", "2.0"))
|
||||
|
||||
for attempt in range(1, max_attempts + 1):
|
||||
try:
|
||||
# Login to get access token
|
||||
login_response = requests.post(
|
||||
f"{LANGFLOW_URL}/api/v1/login",
|
||||
headers={"Content-Type": "application/x-www-form-urlencoded"},
|
||||
data={
|
||||
"username": username,
|
||||
"password": password,
|
||||
},
|
||||
timeout=10,
|
||||
)
|
||||
login_response.raise_for_status()
|
||||
access_token = login_response.json().get("access_token")
|
||||
if not access_token:
|
||||
raise KeyError("access_token")
|
||||
|
||||
# Create API key
|
||||
api_key_response = requests.post(
|
||||
f"{LANGFLOW_URL}/api/v1/api_key/",
|
||||
headers={
|
||||
"Content-Type": "application/json",
|
||||
"Authorization": f"Bearer {access_token}",
|
||||
},
|
||||
json={"name": "openrag-auto-generated"},
|
||||
timeout=10,
|
||||
)
|
||||
api_key_response.raise_for_status()
|
||||
api_key = api_key_response.json().get("api_key")
|
||||
if not api_key:
|
||||
raise KeyError("api_key")
|
||||
|
||||
# Validate the API key works
|
||||
validation_response = requests.get(
|
||||
f"{LANGFLOW_URL}/api/v1/users/whoami",
|
||||
headers={"x-api-key": api_key},
|
||||
timeout=10,
|
||||
)
|
||||
if validation_response.status_code == 200:
|
||||
LANGFLOW_KEY = api_key
|
||||
logger.info(
|
||||
"Successfully generated and validated Langflow API key",
|
||||
key_prefix=api_key[:8],
|
||||
async with httpx.AsyncClient(timeout=10.0) as client:
|
||||
for attempt in range(1, max_attempts + 1):
|
||||
try:
|
||||
# Login to get access token
|
||||
login_response = await client.post(
|
||||
f"{LANGFLOW_URL}/api/v1/login",
|
||||
headers={"Content-Type": "application/x-www-form-urlencoded"},
|
||||
data={
|
||||
"username": username,
|
||||
"password": password,
|
||||
},
|
||||
)
|
||||
return api_key
|
||||
else:
|
||||
logger.error(
|
||||
"Generated API key validation failed",
|
||||
status_code=validation_response.status_code,
|
||||
)
|
||||
raise ValueError(
|
||||
f"API key validation failed: {validation_response.status_code}"
|
||||
)
|
||||
except (requests.exceptions.RequestException, KeyError) as e:
|
||||
logger.warning(
|
||||
"Attempt to generate Langflow API key failed",
|
||||
attempt=attempt,
|
||||
max_attempts=max_attempts,
|
||||
error=str(e),
|
||||
)
|
||||
if attempt < max_attempts:
|
||||
time.sleep(delay_seconds)
|
||||
else:
|
||||
raise
|
||||
login_response.raise_for_status()
|
||||
access_token = login_response.json().get("access_token")
|
||||
if not access_token:
|
||||
raise KeyError("access_token")
|
||||
|
||||
except requests.exceptions.RequestException as e:
|
||||
# Create API key
|
||||
api_key_response = await client.post(
|
||||
f"{LANGFLOW_URL}/api/v1/api_key/",
|
||||
headers={
|
||||
"Content-Type": "application/json",
|
||||
"Authorization": f"Bearer {access_token}",
|
||||
},
|
||||
json={"name": "openrag-auto-generated"},
|
||||
)
|
||||
api_key_response.raise_for_status()
|
||||
api_key = api_key_response.json().get("api_key")
|
||||
if not api_key:
|
||||
raise KeyError("api_key")
|
||||
|
||||
# Validate the API key works
|
||||
validation_response = await client.get(
|
||||
f"{LANGFLOW_URL}/api/v1/users/whoami",
|
||||
headers={"x-api-key": api_key},
|
||||
)
|
||||
if validation_response.status_code == 200:
|
||||
LANGFLOW_KEY = api_key
|
||||
logger.info(
|
||||
"Successfully generated and validated Langflow API key",
|
||||
key_prefix=api_key[:8],
|
||||
)
|
||||
return api_key
|
||||
else:
|
||||
logger.error(
|
||||
"Generated API key validation failed",
|
||||
status_code=validation_response.status_code,
|
||||
)
|
||||
raise ValueError(
|
||||
f"API key validation failed: {validation_response.status_code}"
|
||||
)
|
||||
except (httpx.HTTPStatusError, httpx.RequestError, KeyError) as e:
|
||||
logger.warning(
|
||||
"Attempt to generate Langflow API key failed",
|
||||
attempt=attempt,
|
||||
max_attempts=max_attempts,
|
||||
error=str(e),
|
||||
)
|
||||
if attempt < max_attempts:
|
||||
await asyncio.sleep(delay_seconds)
|
||||
else:
|
||||
raise
|
||||
|
||||
except (httpx.HTTPStatusError, httpx.RequestError) as e:
|
||||
logger.error("Failed to generate Langflow API key", error=str(e))
|
||||
return None
|
||||
except KeyError as e:
|
||||
|
|
@ -303,7 +270,7 @@ class AppClients:
|
|||
|
||||
async def initialize(self):
|
||||
# Generate Langflow API key first
|
||||
await generate_langflow_api_key()
|
||||
await get_langflow_api_key()
|
||||
|
||||
# Initialize OpenSearch client
|
||||
self.opensearch = AsyncOpenSearch(
|
||||
|
|
@ -362,7 +329,7 @@ class AppClients:
|
|||
if self.langflow_client is not None:
|
||||
return self.langflow_client
|
||||
# Try generating key again (with retries)
|
||||
await generate_langflow_api_key()
|
||||
await get_langflow_api_key()
|
||||
if LANGFLOW_KEY and self.langflow_client is None:
|
||||
try:
|
||||
self.langflow_client = AsyncOpenAI(
|
||||
|
|
@ -559,8 +526,11 @@ class AppClients:
|
|||
self.langflow_client = None
|
||||
|
||||
async def langflow_request(self, method: str, endpoint: str, **kwargs):
|
||||
"""Central method for all Langflow API requests"""
|
||||
api_key = await generate_langflow_api_key()
|
||||
"""Central method for all Langflow API requests.
|
||||
|
||||
Retries once with a fresh API key on auth failures (401/403).
|
||||
"""
|
||||
api_key = await get_langflow_api_key()
|
||||
if not api_key:
|
||||
raise ValueError("No Langflow API key available")
|
||||
|
||||
|
|
@ -575,57 +545,65 @@ class AppClients:
|
|||
|
||||
url = f"{LANGFLOW_URL}{endpoint}"
|
||||
|
||||
return await self.langflow_http_client.request(
|
||||
response = await self.langflow_http_client.request(
|
||||
method=method, url=url, headers=headers, **kwargs
|
||||
)
|
||||
|
||||
# Retry once with a fresh API key on auth failure
|
||||
if response.status_code in (401, 403):
|
||||
logger.warning(
|
||||
"Langflow request auth failed, regenerating API key and retrying",
|
||||
status_code=response.status_code,
|
||||
endpoint=endpoint,
|
||||
)
|
||||
api_key = await get_langflow_api_key(force_regenerate=True)
|
||||
if api_key:
|
||||
headers["x-api-key"] = api_key
|
||||
response = await self.langflow_http_client.request(
|
||||
method=method, url=url, headers=headers, **kwargs
|
||||
)
|
||||
|
||||
return response
|
||||
|
||||
async def _create_langflow_global_variable(
|
||||
self, name: str, value: str, modify: bool = False
|
||||
):
|
||||
"""Create a global variable in Langflow via API"""
|
||||
api_key = await generate_langflow_api_key()
|
||||
if not api_key:
|
||||
logger.warning(
|
||||
"Cannot create Langflow global variable: No API key", variable_name=name
|
||||
)
|
||||
return
|
||||
|
||||
url = f"{LANGFLOW_URL}/api/v1/variables/"
|
||||
payload = {
|
||||
"name": name,
|
||||
"value": value,
|
||||
"default_fields": [],
|
||||
"type": "Credential",
|
||||
}
|
||||
headers = {"x-api-key": api_key, "Content-Type": "application/json"}
|
||||
|
||||
try:
|
||||
async with httpx.AsyncClient() as client:
|
||||
response = await client.post(url, headers=headers, json=payload)
|
||||
response = await self.langflow_request(
|
||||
"POST", "/api/v1/variables/", json=payload
|
||||
)
|
||||
|
||||
if response.status_code in [200, 201]:
|
||||
if response.status_code in [200, 201]:
|
||||
logger.info(
|
||||
"Successfully created Langflow global variable",
|
||||
variable_name=name,
|
||||
)
|
||||
elif response.status_code == 400 and "already exists" in response.text:
|
||||
if modify:
|
||||
logger.info(
|
||||
"Successfully created Langflow global variable",
|
||||
"Langflow global variable already exists, attempting to update",
|
||||
variable_name=name,
|
||||
)
|
||||
elif response.status_code == 400 and "already exists" in response.text:
|
||||
if modify:
|
||||
logger.info(
|
||||
"Langflow global variable already exists, attempting to update",
|
||||
variable_name=name,
|
||||
)
|
||||
await self._update_langflow_global_variable(name, value)
|
||||
else:
|
||||
logger.info(
|
||||
"Langflow global variable already exists",
|
||||
variable_name=name,
|
||||
)
|
||||
await self._update_langflow_global_variable(name, value)
|
||||
else:
|
||||
logger.warning(
|
||||
"Failed to create Langflow global variable",
|
||||
logger.info(
|
||||
"Langflow global variable already exists",
|
||||
variable_name=name,
|
||||
status_code=response.status_code,
|
||||
)
|
||||
else:
|
||||
logger.warning(
|
||||
"Failed to create Langflow global variable",
|
||||
variable_name=name,
|
||||
status_code=response.status_code,
|
||||
)
|
||||
except Exception as e:
|
||||
logger.error(
|
||||
"Exception creating Langflow global variable",
|
||||
|
|
@ -635,76 +613,62 @@ class AppClients:
|
|||
|
||||
async def _update_langflow_global_variable(self, name: str, value: str):
|
||||
"""Update an existing global variable in Langflow via API"""
|
||||
api_key = await generate_langflow_api_key()
|
||||
if not api_key:
|
||||
logger.warning(
|
||||
"Cannot update Langflow global variable: No API key", variable_name=name
|
||||
)
|
||||
return
|
||||
|
||||
headers = {"x-api-key": api_key, "Content-Type": "application/json"}
|
||||
|
||||
try:
|
||||
async with httpx.AsyncClient() as client:
|
||||
# First, get all variables to find the one with the matching name
|
||||
get_response = await client.get(
|
||||
f"{LANGFLOW_URL}/api/v1/variables/", headers=headers
|
||||
# First, get all variables to find the one with the matching name
|
||||
get_response = await self.langflow_request("GET", "/api/v1/variables/")
|
||||
|
||||
if get_response.status_code != 200:
|
||||
logger.error(
|
||||
"Failed to retrieve variables for update",
|
||||
variable_name=name,
|
||||
status_code=get_response.status_code,
|
||||
)
|
||||
return
|
||||
|
||||
if get_response.status_code != 200:
|
||||
logger.error(
|
||||
"Failed to retrieve variables for update",
|
||||
variable_name=name,
|
||||
status_code=get_response.status_code,
|
||||
)
|
||||
return
|
||||
variables = get_response.json()
|
||||
target_variable = None
|
||||
|
||||
variables = get_response.json()
|
||||
target_variable = None
|
||||
# Find the variable with matching name
|
||||
for variable in variables:
|
||||
if variable.get("name") == name:
|
||||
target_variable = variable
|
||||
break
|
||||
|
||||
# Find the variable with matching name
|
||||
for variable in variables:
|
||||
if variable.get("name") == name:
|
||||
target_variable = variable
|
||||
break
|
||||
if not target_variable:
|
||||
logger.error("Variable not found for update", variable_name=name)
|
||||
return
|
||||
|
||||
if not target_variable:
|
||||
logger.error("Variable not found for update", variable_name=name)
|
||||
return
|
||||
variable_id = target_variable.get("id")
|
||||
if not variable_id:
|
||||
logger.error("Variable ID not found for update", variable_name=name)
|
||||
return
|
||||
|
||||
variable_id = target_variable.get("id")
|
||||
if not variable_id:
|
||||
logger.error("Variable ID not found for update", variable_name=name)
|
||||
return
|
||||
# Update the variable using PATCH
|
||||
update_payload = {
|
||||
"id": variable_id,
|
||||
"name": name,
|
||||
"value": value,
|
||||
"default_fields": target_variable.get("default_fields", []),
|
||||
}
|
||||
|
||||
# Update the variable using PATCH
|
||||
update_payload = {
|
||||
"id": variable_id,
|
||||
"name": name,
|
||||
"value": value,
|
||||
"default_fields": target_variable.get("default_fields", []),
|
||||
}
|
||||
patch_response = await self.langflow_request(
|
||||
"PATCH", f"/api/v1/variables/{variable_id}", json=update_payload
|
||||
)
|
||||
|
||||
patch_response = await client.patch(
|
||||
f"{LANGFLOW_URL}/api/v1/variables/{variable_id}",
|
||||
headers=headers,
|
||||
json=update_payload,
|
||||
if patch_response.status_code == 200:
|
||||
logger.info(
|
||||
"Successfully updated Langflow global variable",
|
||||
variable_name=name,
|
||||
variable_id=variable_id,
|
||||
)
|
||||
else:
|
||||
logger.warning(
|
||||
"Failed to update Langflow global variable",
|
||||
variable_name=name,
|
||||
variable_id=variable_id,
|
||||
status_code=patch_response.status_code,
|
||||
response_text=patch_response.text,
|
||||
)
|
||||
|
||||
if patch_response.status_code == 200:
|
||||
logger.info(
|
||||
"Successfully updated Langflow global variable",
|
||||
variable_name=name,
|
||||
variable_id=variable_id,
|
||||
)
|
||||
else:
|
||||
logger.warning(
|
||||
"Failed to update Langflow global variable",
|
||||
variable_name=name,
|
||||
variable_id=variable_id,
|
||||
status_code=patch_response.status_code,
|
||||
response_text=patch_response.text,
|
||||
)
|
||||
|
||||
except Exception as e:
|
||||
logger.error(
|
||||
|
|
|
|||
12
src/main.py
12
src/main.py
|
|
@ -1179,6 +1179,18 @@ async def create_app():
|
|||
),
|
||||
methods=["POST"],
|
||||
),
|
||||
# Onboarding rollback endpoint
|
||||
Route(
|
||||
"/onboarding/rollback",
|
||||
require_auth(services["session_manager"])(
|
||||
partial(
|
||||
settings.rollback_onboarding,
|
||||
session_manager=services["session_manager"],
|
||||
task_service=services["task_service"],
|
||||
)
|
||||
),
|
||||
methods=["POST"],
|
||||
),
|
||||
# Docling preset update endpoint
|
||||
Route(
|
||||
"/settings/docling-preset",
|
||||
|
|
|
|||
|
|
@ -595,7 +595,7 @@ class ChatService:
|
|||
try:
|
||||
# Delete from local conversation storage
|
||||
from agent import delete_user_conversation
|
||||
local_deleted = delete_user_conversation(user_id, session_id)
|
||||
local_deleted = await delete_user_conversation(user_id, session_id)
|
||||
|
||||
# Delete from Langflow using the monitor API
|
||||
langflow_deleted = await self._delete_langflow_session(session_id)
|
||||
|
|
|
|||
|
|
@ -5,6 +5,7 @@ Simple service to persist chat conversations to disk so they survive server rest
|
|||
|
||||
import json
|
||||
import os
|
||||
import asyncio
|
||||
from typing import Dict, Any
|
||||
from datetime import datetime
|
||||
import threading
|
||||
|
|
@ -33,8 +34,8 @@ class ConversationPersistenceService:
|
|||
return {}
|
||||
return {}
|
||||
|
||||
def _save_conversations(self):
|
||||
"""Save conversations to disk"""
|
||||
def _save_conversations_sync(self):
|
||||
"""Synchronous save conversations to disk (runs in executor)"""
|
||||
try:
|
||||
with self.lock:
|
||||
with open(self.storage_file, 'w', encoding='utf-8') as f:
|
||||
|
|
@ -43,6 +44,12 @@ class ConversationPersistenceService:
|
|||
except Exception as e:
|
||||
logger.error(f"Error saving conversations to {self.storage_file}: {e}")
|
||||
|
||||
async def _save_conversations(self):
|
||||
"""Async save conversations to disk (non-blocking)"""
|
||||
# Run the synchronous file I/O in a thread pool to avoid blocking the event loop
|
||||
loop = asyncio.get_event_loop()
|
||||
await loop.run_in_executor(None, self._save_conversations_sync)
|
||||
|
||||
def _count_total_conversations(self, data: Dict[str, Any]) -> int:
|
||||
"""Count total conversations across all users"""
|
||||
total = 0
|
||||
|
|
@ -68,8 +75,8 @@ class ConversationPersistenceService:
|
|||
else:
|
||||
return obj
|
||||
|
||||
def store_conversation_thread(self, user_id: str, response_id: str, conversation_state: Dict[str, Any]):
|
||||
"""Store a conversation thread and persist to disk"""
|
||||
async def store_conversation_thread(self, user_id: str, response_id: str, conversation_state: Dict[str, Any]):
|
||||
"""Store a conversation thread and persist to disk (async, non-blocking)"""
|
||||
if user_id not in self._conversations:
|
||||
self._conversations[user_id] = {}
|
||||
|
||||
|
|
@ -78,28 +85,28 @@ class ConversationPersistenceService:
|
|||
|
||||
self._conversations[user_id][response_id] = serialized_conversation
|
||||
|
||||
# Save to disk (we could optimize this with batching if needed)
|
||||
self._save_conversations()
|
||||
# Save to disk asynchronously (non-blocking)
|
||||
await self._save_conversations()
|
||||
|
||||
def get_conversation_thread(self, user_id: str, response_id: str) -> Dict[str, Any]:
|
||||
"""Get a specific conversation thread"""
|
||||
user_conversations = self.get_user_conversations(user_id)
|
||||
return user_conversations.get(response_id, {})
|
||||
|
||||
def delete_conversation_thread(self, user_id: str, response_id: str) -> bool:
|
||||
"""Delete a specific conversation thread"""
|
||||
async def delete_conversation_thread(self, user_id: str, response_id: str) -> bool:
|
||||
"""Delete a specific conversation thread (async, non-blocking)"""
|
||||
if user_id in self._conversations and response_id in self._conversations[user_id]:
|
||||
del self._conversations[user_id][response_id]
|
||||
self._save_conversations()
|
||||
await self._save_conversations()
|
||||
logger.debug(f"Deleted conversation {response_id} for user {user_id}")
|
||||
return True
|
||||
return False
|
||||
|
||||
def clear_user_conversations(self, user_id: str):
|
||||
"""Clear all conversations for a user"""
|
||||
async def clear_user_conversations(self, user_id: str):
|
||||
"""Clear all conversations for a user (async, non-blocking)"""
|
||||
if user_id in self._conversations:
|
||||
del self._conversations[user_id]
|
||||
self._save_conversations()
|
||||
await self._save_conversations()
|
||||
logger.debug(f"Cleared all conversations for user {user_id}")
|
||||
|
||||
def get_storage_stats(self) -> Dict[str, Any]:
|
||||
|
|
|
|||
|
|
@ -199,3 +199,5 @@ class MessageId:
|
|||
ORB_ONBOARD_SAMPLE_DATA = "ORB_ONBOARD_SAMPLE_DATA"
|
||||
# Message: Configuration marked as edited
|
||||
ORB_ONBOARD_CONFIG_EDITED = "ORB_ONBOARD_CONFIG_EDITED"
|
||||
# Message: Onboarding rolled back due to all files failing
|
||||
ORB_ONBOARD_ROLLBACK = "ORB_ONBOARD_ROLLBACK"
|
||||
|
|
|
|||
Loading…
Add table
Reference in a new issue