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open-webui/backend/open_webui/routers/retrieval.py
Classic298 2d18727ab8 perf: build info log messages lazily so raising the log level actually saves work (#27837) 
Raising GLOBAL_LOG_LEVEL to WARNING buys quieter output but not less work: 241 INFO call sites interpolate their payload into an f-string before the logging call gets to drop it. The heaviest is get_doc, which logs every chunk id and metadata dict in a collection, so on the full-context retrieval path that is the entire knowledge base, once per chat request.

That one line at WARNING, CPython 3.12:

| knowledge base | payload | before   | after   |
| -------------- | ------- | -------- | ------- |
| top-k of 3     | 1.2 kB  | 3.8 us   | 0.07 us |
| 500 chunks     | 201 kB  | 583.6 us | 0.08 us |
| 5000 chunks    | 2.0 MB  | 5.8 ms   | 0.15 us |

The lazy form log.info('query_doc:result %s %s', result.ids, result.metadatas) hands the payload to record.getMessage(), which the InterceptHandler only reaches once a record has passed the level check. Output at INFO is byte-identical. Two sites that already built their message eagerly, one str concat and one % operator, move to the same lazy form.
2026-08-02 15:39:10 -05:00

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from __future__ import annotations
import asyncio
import logging
import mimetypes
import os
import re
import shutil
import uuid
from datetime import datetime
from pathlib import Path
from types import SimpleNamespace
from typing import Callable, Iterator, Optional, Sequence, Union
import tiktoken
from fastapi import (
APIRouter,
Depends,
FastAPI,
File,
Form,
HTTPException,
Query,
Request,
UploadFile,
status,
)
from fastapi.concurrency import run_in_threadpool
from fastapi.middleware.cors import CORSMiddleware
from langchain_core.documents import Document
from langchain_text_splitters import (
MarkdownHeaderTextSplitter,
RecursiveCharacterTextSplitter,
TokenTextSplitter,
)
from open_webui.config import (
DEFAULT_LOCALE,
ENV,
RAG_EMBEDDING_CONTENT_PREFIX,
RAG_EMBEDDING_MODEL_AUTO_UPDATE,
RAG_EMBEDDING_MODEL_TRUST_REMOTE_CODE,
RAG_EMBEDDING_QUERY_PREFIX,
RAG_RERANKING_MODEL_AUTO_UPDATE,
RAG_RERANKING_MODEL_TRUST_REMOTE_CODE,
UPLOAD_DIR,
)
from open_webui.constants import ERROR_MESSAGES
from open_webui.env import (
DEVICE_TYPE,
DOCKER,
RAG_EMBEDDING_TIMEOUT,
SENTENCE_TRANSFORMERS_BACKEND,
SENTENCE_TRANSFORMERS_CROSS_ENCODER_BACKEND,
SENTENCE_TRANSFORMERS_CROSS_ENCODER_MODEL_KWARGS,
SENTENCE_TRANSFORMERS_CROSS_ENCODER_SIGMOID_ACTIVATION_FUNCTION,
SENTENCE_TRANSFORMERS_MODEL_KWARGS,
)
from open_webui.events import EVENTS, publish_event
from open_webui.internal.db import get_async_db, get_async_session
from open_webui.models.files import FileModel, Files, FileUpdateForm
from open_webui.models.knowledge import Knowledges
from open_webui.models.config import Config
# Document loaders
from open_webui.retrieval.loaders.youtube import YoutubeLoader
from open_webui.retrieval.utils import (
build_loader_from_config,
get_loader_config,
filter_accessible_collections,
get_content_from_url,
get_embedding_function,
get_model_path,
get_reranking_function,
query_collection,
query_collection_with_hybrid_search,
query_doc,
query_doc_with_hybrid_search,
)
from open_webui.retrieval.vector.async_client import ASYNC_VECTOR_DB_CLIENT
from open_webui.retrieval.vector.factory import VECTOR_DB_CLIENT
from open_webui.retrieval.vector.utils import filter_metadata
from open_webui.retrieval.web.azure import search_azure
from open_webui.retrieval.web.bing import search_bing
from open_webui.retrieval.web.bocha import search_bocha
from open_webui.retrieval.web.brave import search_brave
from open_webui.retrieval.web.brave_llm_context import search_brave_llm_context
from open_webui.retrieval.web.duckduckgo import search_duckduckgo
from open_webui.retrieval.web.exa import search_exa
from open_webui.retrieval.web.external import search_external
from open_webui.retrieval.web.firecrawl import search_firecrawl
from open_webui.retrieval.web.google_pse import search_google_pse
from open_webui.retrieval.web.jina_search import search_jina
from open_webui.retrieval.web.kagi import search_kagi
# Web search engines
from open_webui.retrieval.web.main import SearchResult
from open_webui.retrieval.web.microsoft_web_iq import search_microsoft_web_iq
from open_webui.retrieval.web.mojeek import search_mojeek
from open_webui.retrieval.web.ollama import search_ollama_cloud
from open_webui.retrieval.web.perplexity import search_perplexity
from open_webui.retrieval.web.perplexity_search import search_perplexity_search
from open_webui.retrieval.web.searchapi import search_searchapi
from open_webui.retrieval.web.openserp import search_openserp
from open_webui.retrieval.web.searxng import search_searxng
from open_webui.retrieval.web.serpapi import search_serpapi
from open_webui.retrieval.web.serper import search_serper
from open_webui.retrieval.web.serphouse import search_serphouse
from open_webui.retrieval.web.serply import search_serply
from open_webui.retrieval.web.serpstack import search_serpstack
from open_webui.retrieval.web.sougou import search_sougou
from open_webui.retrieval.web.tavily import search_tavily
from open_webui.retrieval.web.utils import get_web_loader
from open_webui.retrieval.web.yacy import search_yacy
from open_webui.retrieval.web.yandex import search_yandex
from open_webui.retrieval.web.ydc import search_youcom
from open_webui.retrieval.web.linkup import search_linkup
from open_webui.storage.provider import Storage
from open_webui.utils.access_control import has_permission
from open_webui.utils.access_control.files import has_access_to_file
from open_webui.utils.auth import get_admin_user, get_verified_user
from open_webui.utils.misc import (
calculate_sha256_string,
sanitize_text_for_db,
)
from pydantic import BaseModel
from sqlalchemy.ext.asyncio import AsyncSession
log = logging.getLogger(__name__)
TIKTOKEN_DISALLOWED_SPECIAL = ()
##########################################
#
# Utility functions
# Give us this day our relevant chunks, and lead us
# not into hallucination, but deliver us from noise.
#
##########################################
def get_ef(
engine: str,
embedding_model: str,
auto_update: bool = RAG_EMBEDDING_MODEL_AUTO_UPDATE,
):
ef = None
if embedding_model and engine == '':
from sentence_transformers import SentenceTransformer
try:
ef = SentenceTransformer(
get_model_path(embedding_model, auto_update),
device=DEVICE_TYPE,
trust_remote_code=RAG_EMBEDDING_MODEL_TRUST_REMOTE_CODE,
backend=SENTENCE_TRANSFORMERS_BACKEND,
model_kwargs=SENTENCE_TRANSFORMERS_MODEL_KWARGS,
)
except Exception as e:
log.error(f'Error loading SentenceTransformer: {e}')
return ef
def get_rf(
engine: str = '',
reranking_model: str | None = None,
external_reranker_url: str = '',
external_reranker_api_key: str = '',
external_reranker_timeout: str = '',
auto_update: bool = RAG_RERANKING_MODEL_AUTO_UPDATE,
):
rf = None
# Convert timeout string to int or None (system default)
timeout_value = int(external_reranker_timeout) if external_reranker_timeout else None
if reranking_model:
if any(model in reranking_model for model in ['jinaai/jina-colbert-v2']):
try:
from open_webui.retrieval.models.colbert import ColBERT
rf = ColBERT(
get_model_path(reranking_model, auto_update),
env='docker' if DOCKER else None,
)
except Exception as e:
log.error(f'ColBERT: {e}')
raise Exception(ERROR_MESSAGES.DEFAULT(e, 'Error loading reranking model'))
else:
if engine == 'external':
try:
from open_webui.retrieval.models.external import ExternalReranker
rf = ExternalReranker(
url=external_reranker_url,
api_key=external_reranker_api_key,
model=reranking_model,
timeout=timeout_value,
)
except Exception as e:
log.error(f'ExternalReranking: {e}')
raise Exception(ERROR_MESSAGES.DEFAULT(e, 'Error loading reranking model'))
else:
import sentence_transformers
import torch
try:
rf = sentence_transformers.CrossEncoder(
get_model_path(reranking_model, auto_update),
device=DEVICE_TYPE,
trust_remote_code=RAG_RERANKING_MODEL_TRUST_REMOTE_CODE,
backend=SENTENCE_TRANSFORMERS_CROSS_ENCODER_BACKEND,
model_kwargs=SENTENCE_TRANSFORMERS_CROSS_ENCODER_MODEL_KWARGS,
activation_fn=(
torch.nn.Sigmoid()
if SENTENCE_TRANSFORMERS_CROSS_ENCODER_SIGMOID_ACTIVATION_FUNCTION
else None
),
)
except Exception as e:
log.error(f'CrossEncoder: {e}')
raise Exception(ERROR_MESSAGES.DEFAULT(e, 'CrossEncoder error'))
# Safely adjust pad_token_id if missing as some models do not have this in config
try:
model_cfg = getattr(rf, 'model', None)
if model_cfg and hasattr(model_cfg, 'config'):
cfg = model_cfg.config
if getattr(cfg, 'pad_token_id', None) is None:
# Fallback to eos_token_id when available
eos = getattr(cfg, 'eos_token_id', None)
if eos is not None:
cfg.pad_token_id = eos
log.debug('Missing pad_token_id detected; set to eos_token_id=%s', eos)
else:
log.warning('Neither pad_token_id nor eos_token_id present in model config')
except Exception as e2:
log.warning(f'Failed to adjust pad_token_id on CrossEncoder: {e2}')
return rf
##########################################
#
# API routes
#
##########################################
router = APIRouter()
RETRIEVAL_CONFIG_KEYS = {
'ALLOWED_FILE_EXTENSIONS': 'rag.file.allowed_extensions',
'AZURE_AI_SEARCH_API_KEY': 'web.search.azure_ai_search_api_key',
'AZURE_AI_SEARCH_ENDPOINT': 'web.search.azure_ai_search_endpoint',
'AZURE_AI_SEARCH_INDEX_NAME': 'web.search.azure_ai_search_index_name',
'BING_SEARCH_V7_ENDPOINT': 'web.search.bing_search_v7_endpoint',
'BING_SEARCH_V7_SUBSCRIPTION_KEY': 'web.search.bing_search_v7_subscription_key',
'BOCHA_SEARCH_API_KEY': 'web.search.bocha_search_api_key',
'BRAVE_SEARCH_API_KEY': 'web.search.brave_search_api_key',
'BRAVE_SEARCH_CONTEXT_TOKENS': 'web.search.brave_search_context_tokens',
'BYPASS_EMBEDDING_AND_RETRIEVAL': 'rag.bypass_embedding_and_retrieval',
'BYPASS_WEB_SEARCH_EMBEDDING_AND_RETRIEVAL': 'web.search.bypass_embedding_and_retrieval',
'BYPASS_WEB_SEARCH_WEB_LOADER': 'web.search.bypass_web_loader',
'CHUNK_MIN_SIZE_TARGET': 'rag.chunk_min_size_target',
'CHUNK_OVERLAP': 'rag.chunk_overlap',
'CHUNK_SIZE': 'rag.chunk_size',
'CONTENT_EXTRACTION_SUPPORTED_MEDIA_MIME_TYPES': 'rag.content_extraction.supported_media_mime_types',
'CONTENT_EXTRACTION_ENGINE': 'rag.content_extraction_engine',
'DATALAB_MARKER_ADDITIONAL_CONFIG': 'rag.datalab_marker_additional_config',
'DATALAB_MARKER_API_BASE_URL': 'rag.datalab_marker_api_base_url',
'DATALAB_MARKER_API_KEY': 'rag.datalab_marker_api_key',
'DATALAB_MARKER_DISABLE_IMAGE_EXTRACTION': 'rag.datalab_marker_disable_image_extraction',
'DATALAB_MARKER_FORCE_OCR': 'rag.datalab_marker_force_ocr',
'DATALAB_MARKER_FORMAT_LINES': 'rag.datalab_marker_format_lines',
'DATALAB_MARKER_OUTPUT_FORMAT': 'rag.datalab_marker_output_format',
'DATALAB_MARKER_PAGINATE': 'rag.datalab_marker_paginate',
'DATALAB_MARKER_SKIP_CACHE': 'rag.datalab_marker_skip_cache',
'DATALAB_MARKER_STRIP_EXISTING_OCR': 'rag.datalab_marker_strip_existing_ocr',
'DATALAB_MARKER_USE_LLM': 'rag.datalab_marker_use_llm',
'DDGS_BACKEND': 'web.search.ddgs_backend',
'DOCLING_API_KEY': 'rag.docling_api_key',
'DOCLING_PARAMS': 'rag.docling_params',
'DOCLING_SERVER_URL': 'rag.docling_server_url',
'DOCUMENT_INTELLIGENCE_ENDPOINT': 'rag.document_intelligence_endpoint',
'DOCUMENT_INTELLIGENCE_KEY': 'rag.document_intelligence_key',
'DOCUMENT_INTELLIGENCE_MODEL': 'rag.document_intelligence_model',
'ENABLE_ASYNC_EMBEDDING': 'rag.enable_async_embedding',
'ENABLE_GOOGLE_DRIVE_INTEGRATION': 'google_drive.enable',
'ENABLE_MARKDOWN_HEADER_TEXT_SPLITTER': 'rag.enable_markdown_header_text_splitter',
'ENABLE_ONEDRIVE_INTEGRATION': 'onedrive.enable',
'ENABLE_RAG_HYBRID_SEARCH': 'rag.enable_hybrid_search',
'ENABLE_RAG_HYBRID_SEARCH_ENRICHED_TEXTS': 'rag.enable_hybrid_search_enriched_texts',
'ENABLE_WEB_LOADER_SSL_VERIFICATION': 'web.loader.ssl_verification',
'ENABLE_WEB_SEARCH': 'web.search.enable',
'ENABLE_WEB_SEARCH_CONFIRMATION': 'web.search.confirmation.enable',
'WEB_SEARCH_CONFIRMATION_CONTENT': 'web.search.confirmation.content',
'EXA_API_KEY': 'web.search.exa_api_key',
'EXTERNAL_DOCUMENT_LOADER_API_KEY': 'rag.external_document_loader_api_key',
'EXTERNAL_DOCUMENT_LOADER_HEADERS': 'rag.external_document_loader_headers',
'EXTERNAL_DOCUMENT_LOADER_URL': 'rag.external_document_loader_url',
'EXTERNAL_WEB_LOADER_API_KEY': 'web.loader.external_web_loader_api_key',
'EXTERNAL_WEB_LOADER_URL': 'web.loader.external_web_loader_url',
'EXTERNAL_WEB_SEARCH_API_KEY': 'web.search.external_web_search_api_key',
'EXTERNAL_WEB_SEARCH_URL': 'web.search.external_web_search_url',
'FILE_IMAGE_COMPRESSION_HEIGHT': 'file.image_compression_height',
'FILE_IMAGE_COMPRESSION_WIDTH': 'file.image_compression_width',
'FILE_MAX_COUNT': 'rag.file.max_count',
'FILE_MAX_SIZE': 'rag.file.max_size',
'FIRECRAWL_API_BASE_URL': 'web.loader.firecrawl_api_url',
'FIRECRAWL_API_KEY': 'web.loader.firecrawl_api_key',
'FIRECRAWL_TIMEOUT': 'web.loader.firecrawl_timeout',
'GOOGLE_PSE_API_KEY': 'web.search.google_pse_api_key',
'GOOGLE_PSE_ENGINE_ID': 'web.search.google_pse_engine_id',
'HYBRID_BM25_WEIGHT': 'rag.hybrid_bm25_weight',
'JINA_API_BASE_URL': 'web.search.jina_api_base_url',
'JINA_API_KEY': 'web.search.jina_api_key',
'KAGI_SEARCH_API_KEY': 'web.search.kagi_search_api_key',
'LINKUP_API_KEY': 'web.search.linkup_api_key',
'LINKUP_SEARCH_PARAMS': 'web.search.linkup_search_params',
'MINERU_API_KEY': 'rag.mineru_api_key',
'MINERU_API_MODE': 'rag.mineru_api_mode',
'MINERU_API_TIMEOUT': 'rag.mineru_api_timeout',
'MINERU_API_URL': 'rag.mineru_api_url',
'MINERU_FILE_EXTENSIONS': 'rag.mineru_file_extensions',
'MINERU_PARAMS': 'rag.mineru_params',
'MICROSOFT_WEB_IQ_API_BASE_URL': 'web.search.microsoft_web_iq_api_base_url',
'MICROSOFT_WEB_IQ_API_KEY': 'web.search.microsoft_web_iq_api_key',
'MICROSOFT_WEB_IQ_LANGUAGE': 'web.search.microsoft_web_iq_language',
'MISTRAL_OCR_API_BASE_URL': 'rag.mistral_ocr_api_base_url',
'MISTRAL_OCR_API_KEY': 'rag.mistral_ocr_api_key',
'MISTRAL_OCR_USE_BASE64': 'rag.mistral_ocr_use_base64',
'MOJEEK_SEARCH_API_KEY': 'web.search.mojeek_search_api_key',
'OLLAMA_CLOUD_WEB_SEARCH_API_KEY': 'web.search.ollama_cloud_api_key',
'PADDLEOCR_VL_BASE_URL': 'rag.paddleocr_vl_base_url',
'PADDLEOCR_VL_TOKEN': 'rag.paddleocr_vl_token',
'PDF_EXTRACT_IMAGES': 'rag.pdf_extract_images',
'PDF_LOADER_MODE': 'rag.pdf_loader_mode',
'PERPLEXITY_API_KEY': 'web.search.perplexity_api_key',
'PERPLEXITY_MODEL': 'web.search.perplexity_model',
'PERPLEXITY_SEARCH_API_URL': 'web.search.perplexity_search_api_url',
'PERPLEXITY_SEARCH_CONTEXT_USAGE': 'web.search.perplexity_search_context_usage',
'PLAYWRIGHT_TIMEOUT': 'web.loader.playwright_timeout',
'PLAYWRIGHT_WS_URL': 'web.loader.playwright_ws_url',
'RAG_AZURE_OPENAI_API_KEY': 'rag.azure_openai.api_key',
'RAG_AZURE_OPENAI_API_VERSION': 'rag.azure_openai.api_version',
'RAG_AZURE_OPENAI_BASE_URL': 'rag.azure_openai.base_url',
'RAG_EMBEDDING_BATCH_SIZE': 'rag.embedding_batch_size',
'RAG_EMBEDDING_CONCURRENT_REQUESTS': 'rag.embedding_concurrent_requests',
'RAG_EMBEDDING_ENGINE': 'rag.embedding_engine',
'RAG_EMBEDDING_MODEL': 'rag.embedding_model',
'RAG_TOKENIZER_MODEL': 'rag.tokenizer_model',
'RAG_EXTERNAL_RERANKER_API_KEY': 'rag.external_reranker_api_key',
'RAG_EXTERNAL_RERANKER_TIMEOUT': 'rag.external_reranker_timeout',
'RAG_EXTERNAL_RERANKER_URL': 'rag.external_reranker_url',
'RAG_FULL_CONTEXT': 'rag.full_context',
'RAG_OLLAMA_API_KEY': 'rag.ollama.api_key',
'RAG_OLLAMA_BASE_URL': 'rag.ollama.base_url',
'RAG_OPENAI_API_BASE_URL': 'rag.openai.api_base_url',
'RAG_OPENAI_API_KEY': 'rag.openai.api_key',
'RAG_RERANKING_BATCH_SIZE': 'rag.reranking_batch_size',
'RAG_RERANKING_ENGINE': 'rag.reranking_engine',
'RAG_RERANKING_MODEL': 'rag.reranking_model',
'RAG_TEMPLATE': 'rag.template',
'RELEVANCE_THRESHOLD': 'rag.relevance_threshold',
'SEARCHAPI_API_KEY': 'web.search.searchapi_api_key',
'SEARCHAPI_ENGINE': 'web.search.searchapi_engine',
'SEARXNG_LANGUAGE': 'web.search.searxng_language',
'SEARXNG_QUERY_URL': 'web.search.searxng_query_url',
'OPENSERP_BASE_URL': 'web.search.openserp_base_url',
'SERPAPI_API_KEY': 'web.search.serpapi_api_key',
'SERPAPI_ENGINE': 'web.search.serpapi_engine',
'SERPER_API_KEY': 'web.search.serper_api_key',
'SERPHOUSE_API_KEY': 'web.search.serphouse_api_key',
'SERPHOUSE_DOMAIN': 'web.search.serphouse_domain',
'SERPLY_API_KEY': 'web.search.serply_api_key',
'SERPSTACK_API_KEY': 'web.search.serpstack_api_key',
'SERPSTACK_HTTPS': 'web.search.serpstack_https',
'SOUGOU_API_SID': 'web.search.sougou_api_sid',
'SOUGOU_API_SK': 'web.search.sougou_api_sk',
'TAVILY_API_KEY': 'web.search.tavily_api_key',
'TAVILY_EXTRACT_DEPTH': 'web.search.tavily_extract_depth',
'TEXT_SPLITTER': 'rag.text_splitter',
'TIKA_SERVER_URL': 'rag.tika_server_url',
'TIKTOKEN_ENCODING_NAME': 'rag.tiktoken_encoding_name',
'TOP_K': 'rag.top_k',
'TOP_K_RERANKER': 'rag.top_k_reranker',
'USER_PERMISSIONS': 'user.permissions',
'WEBUI_URL': 'webui.url',
'WEB_FETCH_MAX_CONTENT_LENGTH': 'web.fetch.max_content_length',
'WEB_LOADER_CONCURRENT_REQUESTS': 'web.loader.concurrent_requests',
'WEB_LOADER_ENGINE': 'web.loader.engine',
'WEB_LOADER_TIMEOUT': 'web.loader.timeout',
'WEB_SEARCH_CONCURRENT_REQUESTS': 'web.search.concurrent_requests',
'WEB_SEARCH_DOMAIN_FILTER_LIST': 'web.search.domain.filter_list',
'WEB_SEARCH_ENGINE': 'web.search.engine',
'WEB_SEARCH_RESULT_COUNT': 'web.search.result_count',
'WEB_SEARCH_TRUST_ENV': 'web.search.trust_env',
'YACY_PASSWORD': 'web.search.yacy_password',
'YACY_QUERY_URL': 'web.search.yacy_query_url',
'YACY_USERNAME': 'web.search.yacy_username',
'YANDEX_WEB_SEARCH_API_KEY': 'web.search.yandex_web_search_api_key',
'YANDEX_WEB_SEARCH_CONFIG': 'web.search.yandex_web_search_config',
'YANDEX_WEB_SEARCH_URL': 'web.search.yandex_web_search_url',
'YOUCOM_API_KEY': 'web.search.youcom_api_key',
'YOUTUBE_LOADER_LANGUAGE': 'rag.youtube_loader_language',
'YOUTUBE_LOADER_PROXY_URL': 'rag.youtube_loader_proxy_url',
}
class RetrievalConfig(SimpleNamespace):
def __init__(self, values: dict):
super().__init__(**values)
object.__setattr__(self, '_updates', {})
def __setattr__(self, key: str, value):
if key.startswith('_'):
object.__setattr__(self, key, value)
return
object.__setattr__(self, key, value)
if key in RETRIEVAL_CONFIG_KEYS:
self._updates[RETRIEVAL_CONFIG_KEYS[key]] = value
async def save(self) -> None:
if self._updates:
await Config.upsert(dict(self._updates))
self._updates.clear()
async def get_config_values(key_map: dict[str, str]) -> dict:
values = await Config.get_many(*key_map.values())
return {field: values[storage_key] for field, storage_key in key_map.items() if storage_key in values}
async def get_retrieval_config() -> RetrievalConfig:
return RetrievalConfig(await get_config_values(RETRIEVAL_CONFIG_KEYS))
class CollectionNameForm(BaseModel):
collection_name: str | None = None
class ProcessUrlForm(CollectionNameForm):
url: str
class SearchForm(BaseModel):
queries: list[str]
@router.get('/embedding')
async def get_embedding_config(request: Request, user=Depends(get_admin_user)):
config = await get_retrieval_config()
return {
'status': True,
'RAG_EMBEDDING_ENGINE': config.RAG_EMBEDDING_ENGINE,
'RAG_EMBEDDING_MODEL': config.RAG_EMBEDDING_MODEL,
'RAG_EMBEDDING_BATCH_SIZE': config.RAG_EMBEDDING_BATCH_SIZE,
'ENABLE_ASYNC_EMBEDDING': config.ENABLE_ASYNC_EMBEDDING,
'RAG_EMBEDDING_CONCURRENT_REQUESTS': config.RAG_EMBEDDING_CONCURRENT_REQUESTS,
'openai_config': {
'url': config.RAG_OPENAI_API_BASE_URL,
'key': config.RAG_OPENAI_API_KEY,
},
'ollama_config': {
'url': config.RAG_OLLAMA_BASE_URL,
'key': config.RAG_OLLAMA_API_KEY,
},
'azure_openai_config': {
'url': config.RAG_AZURE_OPENAI_BASE_URL,
'key': config.RAG_AZURE_OPENAI_API_KEY,
'version': config.RAG_AZURE_OPENAI_API_VERSION,
},
}
class OpenAIConfigForm(BaseModel):
url: str
key: str
class OllamaConfigForm(BaseModel):
url: str
key: str
class AzureOpenAIConfigForm(BaseModel):
url: str
key: str
version: str
class EmbeddingModelUpdateForm(BaseModel):
openai_config: OpenAIConfigForm | None = None
ollama_config: OllamaConfigForm | None = None
azure_openai_config: AzureOpenAIConfigForm | None = None
RAG_EMBEDDING_ENGINE: str
RAG_EMBEDDING_MODEL: str
RAG_EMBEDDING_BATCH_SIZE: int | None = 1
ENABLE_ASYNC_EMBEDDING: bool | None = True
RAG_EMBEDDING_CONCURRENT_REQUESTS: int | None = 0
async def unload_embedding_model(request: Request):
config = await get_retrieval_config()
if config.RAG_EMBEDDING_ENGINE == '':
# unloads current internal embedding model and clears VRAM cache
request.app.state.ef = None
request.app.state.EMBEDDING_FUNCTION = None
import gc
gc.collect()
if DEVICE_TYPE == 'cuda':
import torch
if torch.cuda.is_available():
torch.cuda.empty_cache()
@router.post('/embedding/update')
async def update_embedding_config(request: Request, form_data: EmbeddingModelUpdateForm, user=Depends(get_admin_user)):
config = await get_retrieval_config()
log.info('Updating embedding model: %s to %s', config.RAG_EMBEDDING_MODEL, form_data.RAG_EMBEDDING_MODEL)
await unload_embedding_model(request)
try:
config.RAG_EMBEDDING_ENGINE = form_data.RAG_EMBEDDING_ENGINE
config.RAG_EMBEDDING_MODEL = form_data.RAG_EMBEDDING_MODEL.strip()
config.RAG_EMBEDDING_BATCH_SIZE = form_data.RAG_EMBEDDING_BATCH_SIZE
config.ENABLE_ASYNC_EMBEDDING = form_data.ENABLE_ASYNC_EMBEDDING
config.RAG_EMBEDDING_CONCURRENT_REQUESTS = form_data.RAG_EMBEDDING_CONCURRENT_REQUESTS
if config.RAG_EMBEDDING_ENGINE in [
'ollama',
'openai',
'azure_openai',
]:
if form_data.openai_config is not None:
config.RAG_OPENAI_API_BASE_URL = form_data.openai_config.url
config.RAG_OPENAI_API_KEY = form_data.openai_config.key
if form_data.ollama_config is not None:
config.RAG_OLLAMA_BASE_URL = form_data.ollama_config.url
config.RAG_OLLAMA_API_KEY = form_data.ollama_config.key
if form_data.azure_openai_config is not None:
config.RAG_AZURE_OPENAI_BASE_URL = form_data.azure_openai_config.url
config.RAG_AZURE_OPENAI_API_KEY = form_data.azure_openai_config.key
config.RAG_AZURE_OPENAI_API_VERSION = form_data.azure_openai_config.version
request.app.state.ef = get_ef(
config.RAG_EMBEDDING_ENGINE,
config.RAG_EMBEDDING_MODEL,
)
request.app.state.EMBEDDING_FUNCTION = get_embedding_function(
config.RAG_EMBEDDING_ENGINE,
config.RAG_EMBEDDING_MODEL,
request.app.state.ef,
(
config.RAG_OPENAI_API_BASE_URL
if config.RAG_EMBEDDING_ENGINE == 'openai'
else (
config.RAG_OLLAMA_BASE_URL
if config.RAG_EMBEDDING_ENGINE == 'ollama'
else config.RAG_AZURE_OPENAI_BASE_URL
)
),
(
config.RAG_OPENAI_API_KEY
if config.RAG_EMBEDDING_ENGINE == 'openai'
else (
config.RAG_OLLAMA_API_KEY
if config.RAG_EMBEDDING_ENGINE == 'ollama'
else config.RAG_AZURE_OPENAI_API_KEY
)
),
config.RAG_EMBEDDING_BATCH_SIZE,
azure_api_version=(
config.RAG_AZURE_OPENAI_API_VERSION if config.RAG_EMBEDDING_ENGINE == 'azure_openai' else None
),
enable_async=config.ENABLE_ASYNC_EMBEDDING,
concurrent_requests=config.RAG_EMBEDDING_CONCURRENT_REQUESTS,
)
await config.save()
return {
'status': True,
'RAG_EMBEDDING_ENGINE': config.RAG_EMBEDDING_ENGINE,
'RAG_EMBEDDING_MODEL': config.RAG_EMBEDDING_MODEL,
'RAG_EMBEDDING_BATCH_SIZE': config.RAG_EMBEDDING_BATCH_SIZE,
'ENABLE_ASYNC_EMBEDDING': config.ENABLE_ASYNC_EMBEDDING,
'RAG_EMBEDDING_CONCURRENT_REQUESTS': config.RAG_EMBEDDING_CONCURRENT_REQUESTS,
'openai_config': {
'url': config.RAG_OPENAI_API_BASE_URL,
'key': config.RAG_OPENAI_API_KEY,
},
'ollama_config': {
'url': config.RAG_OLLAMA_BASE_URL,
'key': config.RAG_OLLAMA_API_KEY,
},
'azure_openai_config': {
'url': config.RAG_AZURE_OPENAI_BASE_URL,
'key': config.RAG_AZURE_OPENAI_API_KEY,
'version': config.RAG_AZURE_OPENAI_API_VERSION,
},
}
except Exception as e:
log.exception(f'Problem updating embedding model: {e}')
raise HTTPException(
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
detail=ERROR_MESSAGES.DEFAULT(e, 'Error updating embedding configuration'),
)
@router.get('/config')
async def get_rag_config(request: Request, user=Depends(get_admin_user)):
config = await get_retrieval_config()
await config.save()
return {
'status': True,
# RAG settings
'RAG_TEMPLATE': config.RAG_TEMPLATE,
'TOP_K': config.TOP_K,
'BYPASS_EMBEDDING_AND_RETRIEVAL': config.BYPASS_EMBEDDING_AND_RETRIEVAL,
'RAG_FULL_CONTEXT': config.RAG_FULL_CONTEXT,
# Hybrid search settings
'ENABLE_RAG_HYBRID_SEARCH': config.ENABLE_RAG_HYBRID_SEARCH,
'ENABLE_RAG_HYBRID_SEARCH_ENRICHED_TEXTS': config.ENABLE_RAG_HYBRID_SEARCH_ENRICHED_TEXTS,
'TOP_K_RERANKER': config.TOP_K_RERANKER,
'RELEVANCE_THRESHOLD': config.RELEVANCE_THRESHOLD,
'HYBRID_BM25_WEIGHT': config.HYBRID_BM25_WEIGHT,
# Content extraction settings
'CONTENT_EXTRACTION_ENGINE': config.CONTENT_EXTRACTION_ENGINE,
'CONTENT_EXTRACTION_SUPPORTED_MEDIA_MIME_TYPES': config.CONTENT_EXTRACTION_SUPPORTED_MEDIA_MIME_TYPES,
'PDF_EXTRACT_IMAGES': config.PDF_EXTRACT_IMAGES,
'PDF_LOADER_MODE': config.PDF_LOADER_MODE,
'DATALAB_MARKER_API_KEY': config.DATALAB_MARKER_API_KEY,
'DATALAB_MARKER_API_BASE_URL': config.DATALAB_MARKER_API_BASE_URL,
'DATALAB_MARKER_ADDITIONAL_CONFIG': config.DATALAB_MARKER_ADDITIONAL_CONFIG,
'DATALAB_MARKER_SKIP_CACHE': config.DATALAB_MARKER_SKIP_CACHE,
'DATALAB_MARKER_FORCE_OCR': config.DATALAB_MARKER_FORCE_OCR,
'DATALAB_MARKER_PAGINATE': config.DATALAB_MARKER_PAGINATE,
'DATALAB_MARKER_STRIP_EXISTING_OCR': config.DATALAB_MARKER_STRIP_EXISTING_OCR,
'DATALAB_MARKER_DISABLE_IMAGE_EXTRACTION': config.DATALAB_MARKER_DISABLE_IMAGE_EXTRACTION,
'DATALAB_MARKER_FORMAT_LINES': config.DATALAB_MARKER_FORMAT_LINES,
'DATALAB_MARKER_USE_LLM': config.DATALAB_MARKER_USE_LLM,
'DATALAB_MARKER_OUTPUT_FORMAT': config.DATALAB_MARKER_OUTPUT_FORMAT,
'EXTERNAL_DOCUMENT_LOADER_URL': config.EXTERNAL_DOCUMENT_LOADER_URL,
'EXTERNAL_DOCUMENT_LOADER_API_KEY': config.EXTERNAL_DOCUMENT_LOADER_API_KEY,
'EXTERNAL_DOCUMENT_LOADER_HEADERS': config.EXTERNAL_DOCUMENT_LOADER_HEADERS,
'TIKA_SERVER_URL': config.TIKA_SERVER_URL,
'DOCLING_SERVER_URL': config.DOCLING_SERVER_URL,
'DOCLING_API_KEY': config.DOCLING_API_KEY,
'DOCLING_PARAMS': config.DOCLING_PARAMS,
'DOCUMENT_INTELLIGENCE_ENDPOINT': config.DOCUMENT_INTELLIGENCE_ENDPOINT,
'DOCUMENT_INTELLIGENCE_KEY': config.DOCUMENT_INTELLIGENCE_KEY,
'DOCUMENT_INTELLIGENCE_MODEL': config.DOCUMENT_INTELLIGENCE_MODEL,
'MISTRAL_OCR_API_BASE_URL': config.MISTRAL_OCR_API_BASE_URL,
'MISTRAL_OCR_API_KEY': config.MISTRAL_OCR_API_KEY,
'MISTRAL_OCR_USE_BASE64': config.MISTRAL_OCR_USE_BASE64,
'PADDLEOCR_VL_BASE_URL': config.PADDLEOCR_VL_BASE_URL,
'PADDLEOCR_VL_TOKEN': config.PADDLEOCR_VL_TOKEN,
# MinerU settings
'MINERU_API_MODE': config.MINERU_API_MODE,
'MINERU_API_URL': config.MINERU_API_URL,
'MINERU_API_KEY': config.MINERU_API_KEY,
'MINERU_API_TIMEOUT': config.MINERU_API_TIMEOUT,
'MINERU_PARAMS': config.MINERU_PARAMS,
'MINERU_FILE_EXTENSIONS': config.MINERU_FILE_EXTENSIONS,
# Reranking settings
'RAG_RERANKING_MODEL': config.RAG_RERANKING_MODEL,
'RAG_RERANKING_ENGINE': config.RAG_RERANKING_ENGINE,
'RAG_RERANKING_BATCH_SIZE': config.RAG_RERANKING_BATCH_SIZE,
'RAG_EXTERNAL_RERANKER_URL': config.RAG_EXTERNAL_RERANKER_URL,
'RAG_EXTERNAL_RERANKER_API_KEY': config.RAG_EXTERNAL_RERANKER_API_KEY,
'RAG_EXTERNAL_RERANKER_TIMEOUT': config.RAG_EXTERNAL_RERANKER_TIMEOUT,
# Chunking settings
'TEXT_SPLITTER': config.TEXT_SPLITTER,
'RAG_TOKENIZER_MODEL': config.RAG_TOKENIZER_MODEL,
'ENABLE_MARKDOWN_HEADER_TEXT_SPLITTER': config.ENABLE_MARKDOWN_HEADER_TEXT_SPLITTER,
'CHUNK_SIZE': config.CHUNK_SIZE,
'CHUNK_MIN_SIZE_TARGET': config.CHUNK_MIN_SIZE_TARGET,
'CHUNK_OVERLAP': config.CHUNK_OVERLAP,
# File upload settings
'FILE_MAX_SIZE': config.FILE_MAX_SIZE,
'FILE_MAX_COUNT': config.FILE_MAX_COUNT,
'FILE_IMAGE_COMPRESSION_WIDTH': config.FILE_IMAGE_COMPRESSION_WIDTH,
'FILE_IMAGE_COMPRESSION_HEIGHT': config.FILE_IMAGE_COMPRESSION_HEIGHT,
'ALLOWED_FILE_EXTENSIONS': config.ALLOWED_FILE_EXTENSIONS,
# Integration settings
'ENABLE_GOOGLE_DRIVE_INTEGRATION': config.ENABLE_GOOGLE_DRIVE_INTEGRATION,
'ENABLE_ONEDRIVE_INTEGRATION': config.ENABLE_ONEDRIVE_INTEGRATION,
# Web search settings
'web': {
'ENABLE_WEB_SEARCH': config.ENABLE_WEB_SEARCH,
'ENABLE_WEB_SEARCH_CONFIRMATION': config.ENABLE_WEB_SEARCH_CONFIRMATION,
'WEB_SEARCH_CONFIRMATION_CONTENT': config.WEB_SEARCH_CONFIRMATION_CONTENT,
'WEB_SEARCH_ENGINE': config.WEB_SEARCH_ENGINE,
'WEB_SEARCH_TRUST_ENV': config.WEB_SEARCH_TRUST_ENV,
'WEB_SEARCH_RESULT_COUNT': config.WEB_SEARCH_RESULT_COUNT,
'WEB_SEARCH_CONCURRENT_REQUESTS': config.WEB_SEARCH_CONCURRENT_REQUESTS,
'WEB_FETCH_MAX_CONTENT_LENGTH': config.WEB_FETCH_MAX_CONTENT_LENGTH,
'WEB_LOADER_CONCURRENT_REQUESTS': config.WEB_LOADER_CONCURRENT_REQUESTS,
'WEB_SEARCH_DOMAIN_FILTER_LIST': config.WEB_SEARCH_DOMAIN_FILTER_LIST,
'BYPASS_WEB_SEARCH_EMBEDDING_AND_RETRIEVAL': config.BYPASS_WEB_SEARCH_EMBEDDING_AND_RETRIEVAL,
'BYPASS_WEB_SEARCH_WEB_LOADER': config.BYPASS_WEB_SEARCH_WEB_LOADER,
'OLLAMA_CLOUD_WEB_SEARCH_API_KEY': config.OLLAMA_CLOUD_WEB_SEARCH_API_KEY,
'SEARXNG_QUERY_URL': config.SEARXNG_QUERY_URL,
'SEARXNG_LANGUAGE': config.SEARXNG_LANGUAGE,
'OPENSERP_BASE_URL': config.OPENSERP_BASE_URL,
'YACY_QUERY_URL': config.YACY_QUERY_URL,
'YACY_USERNAME': config.YACY_USERNAME,
'YACY_PASSWORD': config.YACY_PASSWORD,
'GOOGLE_PSE_API_KEY': config.GOOGLE_PSE_API_KEY,
'GOOGLE_PSE_ENGINE_ID': config.GOOGLE_PSE_ENGINE_ID,
'BRAVE_SEARCH_API_KEY': config.BRAVE_SEARCH_API_KEY,
'BRAVE_SEARCH_CONTEXT_TOKENS': config.BRAVE_SEARCH_CONTEXT_TOKENS,
'KAGI_SEARCH_API_KEY': config.KAGI_SEARCH_API_KEY,
'MOJEEK_SEARCH_API_KEY': config.MOJEEK_SEARCH_API_KEY,
'BOCHA_SEARCH_API_KEY': config.BOCHA_SEARCH_API_KEY,
'SERPSTACK_API_KEY': config.SERPSTACK_API_KEY,
'SERPSTACK_HTTPS': config.SERPSTACK_HTTPS,
'SERPER_API_KEY': config.SERPER_API_KEY,
'SERPHOUSE_API_KEY': config.SERPHOUSE_API_KEY,
'SERPHOUSE_DOMAIN': config.SERPHOUSE_DOMAIN,
'SERPLY_API_KEY': config.SERPLY_API_KEY,
'DDGS_BACKEND': config.DDGS_BACKEND,
'TAVILY_API_KEY': config.TAVILY_API_KEY,
'SEARCHAPI_API_KEY': config.SEARCHAPI_API_KEY,
'SEARCHAPI_ENGINE': config.SEARCHAPI_ENGINE,
'SERPAPI_API_KEY': config.SERPAPI_API_KEY,
'SERPAPI_ENGINE': config.SERPAPI_ENGINE,
'JINA_API_KEY': config.JINA_API_KEY,
'JINA_API_BASE_URL': config.JINA_API_BASE_URL,
'BING_SEARCH_V7_ENDPOINT': config.BING_SEARCH_V7_ENDPOINT,
'BING_SEARCH_V7_SUBSCRIPTION_KEY': config.BING_SEARCH_V7_SUBSCRIPTION_KEY,
'EXA_API_KEY': config.EXA_API_KEY,
'PERPLEXITY_API_KEY': config.PERPLEXITY_API_KEY,
'PERPLEXITY_MODEL': config.PERPLEXITY_MODEL,
'PERPLEXITY_SEARCH_CONTEXT_USAGE': config.PERPLEXITY_SEARCH_CONTEXT_USAGE,
'PERPLEXITY_SEARCH_API_URL': config.PERPLEXITY_SEARCH_API_URL,
'MICROSOFT_WEB_IQ_API_BASE_URL': config.MICROSOFT_WEB_IQ_API_BASE_URL,
'MICROSOFT_WEB_IQ_API_KEY': config.MICROSOFT_WEB_IQ_API_KEY,
'MICROSOFT_WEB_IQ_LANGUAGE': config.MICROSOFT_WEB_IQ_LANGUAGE,
'SOUGOU_API_SID': config.SOUGOU_API_SID,
'SOUGOU_API_SK': config.SOUGOU_API_SK,
'WEB_LOADER_ENGINE': config.WEB_LOADER_ENGINE,
'WEB_LOADER_TIMEOUT': config.WEB_LOADER_TIMEOUT,
'ENABLE_WEB_LOADER_SSL_VERIFICATION': config.ENABLE_WEB_LOADER_SSL_VERIFICATION,
'PLAYWRIGHT_WS_URL': config.PLAYWRIGHT_WS_URL,
'PLAYWRIGHT_TIMEOUT': config.PLAYWRIGHT_TIMEOUT,
'FIRECRAWL_API_KEY': config.FIRECRAWL_API_KEY,
'FIRECRAWL_API_BASE_URL': config.FIRECRAWL_API_BASE_URL,
'FIRECRAWL_TIMEOUT': config.FIRECRAWL_TIMEOUT,
'TAVILY_EXTRACT_DEPTH': config.TAVILY_EXTRACT_DEPTH,
'EXTERNAL_WEB_SEARCH_URL': config.EXTERNAL_WEB_SEARCH_URL,
'EXTERNAL_WEB_SEARCH_API_KEY': config.EXTERNAL_WEB_SEARCH_API_KEY,
'EXTERNAL_WEB_LOADER_URL': config.EXTERNAL_WEB_LOADER_URL,
'EXTERNAL_WEB_LOADER_API_KEY': config.EXTERNAL_WEB_LOADER_API_KEY,
'YOUTUBE_LOADER_LANGUAGE': config.YOUTUBE_LOADER_LANGUAGE,
'YOUTUBE_LOADER_PROXY_URL': config.YOUTUBE_LOADER_PROXY_URL,
'YOUTUBE_LOADER_TRANSLATION': request.app.state.YOUTUBE_LOADER_TRANSLATION,
'YANDEX_WEB_SEARCH_URL': config.YANDEX_WEB_SEARCH_URL,
'YANDEX_WEB_SEARCH_API_KEY': config.YANDEX_WEB_SEARCH_API_KEY,
'YANDEX_WEB_SEARCH_CONFIG': config.YANDEX_WEB_SEARCH_CONFIG,
'YOUCOM_API_KEY': config.YOUCOM_API_KEY,
'LINKUP_API_KEY': config.LINKUP_API_KEY,
'LINKUP_SEARCH_PARAMS': config.LINKUP_SEARCH_PARAMS,
},
}
class WebConfig(BaseModel):
ENABLE_WEB_SEARCH: bool | None = None
ENABLE_WEB_SEARCH_CONFIRMATION: bool | None = None
WEB_SEARCH_CONFIRMATION_CONTENT: str | None = None
WEB_SEARCH_ENGINE: str | None = None
WEB_SEARCH_TRUST_ENV: bool | None = None
WEB_SEARCH_RESULT_COUNT: int | None = None
WEB_SEARCH_CONCURRENT_REQUESTS: int | None = None
WEB_SEARCH_DOMAIN_FILTER_LIST: list[str | None] = []
WEB_FETCH_MAX_CONTENT_LENGTH: int | None = None
WEB_LOADER_CONCURRENT_REQUESTS: int | None = None
BYPASS_WEB_SEARCH_EMBEDDING_AND_RETRIEVAL: bool | None = None
BYPASS_WEB_SEARCH_WEB_LOADER: bool | None = None
OLLAMA_CLOUD_WEB_SEARCH_API_KEY: str | None = None
SEARXNG_QUERY_URL: str | None = None
SEARXNG_LANGUAGE: str | None = None
OPENSERP_BASE_URL: str | None = None
YACY_QUERY_URL: str | None = None
YACY_USERNAME: str | None = None
YACY_PASSWORD: str | None = None
GOOGLE_PSE_API_KEY: str | None = None
GOOGLE_PSE_ENGINE_ID: str | None = None
BRAVE_SEARCH_API_KEY: str | None = None
BRAVE_SEARCH_CONTEXT_TOKENS: int | None = None
KAGI_SEARCH_API_KEY: str | None = None
MOJEEK_SEARCH_API_KEY: str | None = None
BOCHA_SEARCH_API_KEY: str | None = None
SERPSTACK_API_KEY: str | None = None
SERPSTACK_HTTPS: bool | None = None
SERPER_API_KEY: str | None = None
SERPHOUSE_API_KEY: str | None = None
SERPHOUSE_DOMAIN: str | None = None
SERPLY_API_KEY: str | None = None
DDGS_BACKEND: str | None = None
TAVILY_API_KEY: str | None = None
SEARCHAPI_API_KEY: str | None = None
SEARCHAPI_ENGINE: str | None = None
SERPAPI_API_KEY: str | None = None
SERPAPI_ENGINE: str | None = None
JINA_API_KEY: str | None = None
JINA_API_BASE_URL: str | None = None
BING_SEARCH_V7_ENDPOINT: str | None = None
BING_SEARCH_V7_SUBSCRIPTION_KEY: str | None = None
EXA_API_KEY: str | None = None
PERPLEXITY_API_KEY: str | None = None
PERPLEXITY_MODEL: str | None = None
PERPLEXITY_SEARCH_CONTEXT_USAGE: str | None = None
PERPLEXITY_SEARCH_API_URL: str | None = None
MICROSOFT_WEB_IQ_API_BASE_URL: str | None = None
MICROSOFT_WEB_IQ_API_KEY: str | None = None
MICROSOFT_WEB_IQ_LANGUAGE: str | None = None
SOUGOU_API_SID: str | None = None
SOUGOU_API_SK: str | None = None
WEB_LOADER_ENGINE: str | None = None
WEB_LOADER_TIMEOUT: str | None = None
ENABLE_WEB_LOADER_SSL_VERIFICATION: bool | None = None
PLAYWRIGHT_WS_URL: str | None = None
PLAYWRIGHT_TIMEOUT: int | None = None
FIRECRAWL_API_KEY: str | None = None
FIRECRAWL_API_BASE_URL: str | None = None
FIRECRAWL_TIMEOUT: str | None = None
TAVILY_EXTRACT_DEPTH: str | None = None
EXTERNAL_WEB_SEARCH_URL: str | None = None
EXTERNAL_WEB_SEARCH_API_KEY: str | None = None
EXTERNAL_WEB_LOADER_URL: str | None = None
EXTERNAL_WEB_LOADER_API_KEY: str | None = None
YOUTUBE_LOADER_LANGUAGE: list[str | None] = None
YOUTUBE_LOADER_PROXY_URL: str | None = None
YOUTUBE_LOADER_TRANSLATION: str | None = None
YANDEX_WEB_SEARCH_URL: str | None = None
YANDEX_WEB_SEARCH_API_KEY: str | None = None
YANDEX_WEB_SEARCH_CONFIG: str | None = None
YOUCOM_API_KEY: str | None = None
LINKUP_API_KEY: str | None = None
LINKUP_SEARCH_PARAMS: dict | None = None
class ConfigForm(BaseModel):
# RAG settings
RAG_TEMPLATE: str | None = None
TOP_K: int | None = None
BYPASS_EMBEDDING_AND_RETRIEVAL: bool | None = None
RAG_FULL_CONTEXT: bool | None = None
# Hybrid search settings
ENABLE_RAG_HYBRID_SEARCH: bool | None = None
ENABLE_RAG_HYBRID_SEARCH_ENRICHED_TEXTS: bool | None = None
TOP_K_RERANKER: int | None = None
RELEVANCE_THRESHOLD: float | None = None
HYBRID_BM25_WEIGHT: float | None = None
# Content extraction settings
CONTENT_EXTRACTION_ENGINE: str | None = None
CONTENT_EXTRACTION_SUPPORTED_MEDIA_MIME_TYPES: list[str] | None = None
PDF_EXTRACT_IMAGES: bool | None = None
PDF_LOADER_MODE: str | None = None
DATALAB_MARKER_API_KEY: str | None = None
DATALAB_MARKER_API_BASE_URL: str | None = None
DATALAB_MARKER_ADDITIONAL_CONFIG: str | None = None
DATALAB_MARKER_SKIP_CACHE: bool | None = None
DATALAB_MARKER_FORCE_OCR: bool | None = None
DATALAB_MARKER_PAGINATE: bool | None = None
DATALAB_MARKER_STRIP_EXISTING_OCR: bool | None = None
DATALAB_MARKER_DISABLE_IMAGE_EXTRACTION: bool | None = None
DATALAB_MARKER_FORMAT_LINES: bool | None = None
DATALAB_MARKER_USE_LLM: bool | None = None
DATALAB_MARKER_OUTPUT_FORMAT: str | None = None
EXTERNAL_DOCUMENT_LOADER_URL: str | None = None
EXTERNAL_DOCUMENT_LOADER_API_KEY: str | None = None
EXTERNAL_DOCUMENT_LOADER_HEADERS: dict | None = None
TIKA_SERVER_URL: str | None = None
DOCLING_SERVER_URL: str | None = None
DOCLING_API_KEY: str | None = None
DOCLING_PARAMS: dict | None = None
DOCUMENT_INTELLIGENCE_ENDPOINT: str | None = None
DOCUMENT_INTELLIGENCE_KEY: str | None = None
DOCUMENT_INTELLIGENCE_MODEL: str | None = None
MISTRAL_OCR_API_BASE_URL: str | None = None
MISTRAL_OCR_API_KEY: str | None = None
MISTRAL_OCR_USE_BASE64: bool | None = None
PADDLEOCR_VL_BASE_URL: str | None = None
PADDLEOCR_VL_TOKEN: str | None = None
# MinerU settings
MINERU_API_MODE: str | None = None
MINERU_API_URL: str | None = None
MINERU_API_KEY: str | None = None
MINERU_API_TIMEOUT: int | None = None
MINERU_PARAMS: dict | None = None
MINERU_FILE_EXTENSIONS: list[str] | None = None
# Reranking settings
RAG_RERANKING_MODEL: str | None = None
RAG_RERANKING_ENGINE: str | None = None
RAG_RERANKING_BATCH_SIZE: int | None = None
RAG_EXTERNAL_RERANKER_URL: str | None = None
RAG_EXTERNAL_RERANKER_API_KEY: str | None = None
RAG_EXTERNAL_RERANKER_TIMEOUT: str | None = None
# Chunking settings
TEXT_SPLITTER: str | None = None
RAG_TOKENIZER_MODEL: str | None = None
ENABLE_MARKDOWN_HEADER_TEXT_SPLITTER: bool | None = None
CHUNK_SIZE: int | None = None
CHUNK_MIN_SIZE_TARGET: int | None = None
CHUNK_OVERLAP: int | None = None
# File upload settings
FILE_MAX_SIZE: Union[int, str | None] = None
FILE_MAX_COUNT: Union[int, str | None] = None
FILE_IMAGE_COMPRESSION_WIDTH: Union[int, str | None] = None
FILE_IMAGE_COMPRESSION_HEIGHT: Union[int, str | None] = None
ALLOWED_FILE_EXTENSIONS: list[str | None] = None
# Integration settings
ENABLE_GOOGLE_DRIVE_INTEGRATION: bool | None = None
ENABLE_ONEDRIVE_INTEGRATION: bool | None = None
# Web search settings
web: WebConfig | None = None
@router.post('/config/update')
async def update_rag_config(request: Request, form_data: ConfigForm, user=Depends(get_admin_user)):
# RAG settings
config = await get_retrieval_config()
config.RAG_TEMPLATE = form_data.RAG_TEMPLATE if form_data.RAG_TEMPLATE is not None else config.RAG_TEMPLATE
config.TOP_K = form_data.TOP_K if form_data.TOP_K is not None else config.TOP_K
config.BYPASS_EMBEDDING_AND_RETRIEVAL = (
form_data.BYPASS_EMBEDDING_AND_RETRIEVAL
if form_data.BYPASS_EMBEDDING_AND_RETRIEVAL is not None
else config.BYPASS_EMBEDDING_AND_RETRIEVAL
)
config.RAG_FULL_CONTEXT = (
form_data.RAG_FULL_CONTEXT if form_data.RAG_FULL_CONTEXT is not None else config.RAG_FULL_CONTEXT
)
# Hybrid search settings
config.ENABLE_RAG_HYBRID_SEARCH = (
form_data.ENABLE_RAG_HYBRID_SEARCH
if form_data.ENABLE_RAG_HYBRID_SEARCH is not None
else config.ENABLE_RAG_HYBRID_SEARCH
)
config.ENABLE_RAG_HYBRID_SEARCH_ENRICHED_TEXTS = (
form_data.ENABLE_RAG_HYBRID_SEARCH_ENRICHED_TEXTS
if form_data.ENABLE_RAG_HYBRID_SEARCH_ENRICHED_TEXTS is not None
else config.ENABLE_RAG_HYBRID_SEARCH_ENRICHED_TEXTS
)
config.TOP_K_RERANKER = form_data.TOP_K_RERANKER if form_data.TOP_K_RERANKER is not None else config.TOP_K_RERANKER
config.RELEVANCE_THRESHOLD = (
form_data.RELEVANCE_THRESHOLD if form_data.RELEVANCE_THRESHOLD is not None else config.RELEVANCE_THRESHOLD
)
config.HYBRID_BM25_WEIGHT = (
form_data.HYBRID_BM25_WEIGHT if form_data.HYBRID_BM25_WEIGHT is not None else config.HYBRID_BM25_WEIGHT
)
# Content extraction settings
config.CONTENT_EXTRACTION_ENGINE = (
form_data.CONTENT_EXTRACTION_ENGINE
if form_data.CONTENT_EXTRACTION_ENGINE is not None
else config.CONTENT_EXTRACTION_ENGINE
)
config.CONTENT_EXTRACTION_SUPPORTED_MEDIA_MIME_TYPES = (
form_data.CONTENT_EXTRACTION_SUPPORTED_MEDIA_MIME_TYPES
if form_data.CONTENT_EXTRACTION_SUPPORTED_MEDIA_MIME_TYPES is not None
else config.CONTENT_EXTRACTION_SUPPORTED_MEDIA_MIME_TYPES
)
config.PDF_EXTRACT_IMAGES = (
form_data.PDF_EXTRACT_IMAGES if form_data.PDF_EXTRACT_IMAGES is not None else config.PDF_EXTRACT_IMAGES
)
config.PDF_LOADER_MODE = (
form_data.PDF_LOADER_MODE if form_data.PDF_LOADER_MODE is not None else config.PDF_LOADER_MODE
)
config.DATALAB_MARKER_API_KEY = (
form_data.DATALAB_MARKER_API_KEY
if form_data.DATALAB_MARKER_API_KEY is not None
else config.DATALAB_MARKER_API_KEY
)
config.DATALAB_MARKER_API_BASE_URL = (
form_data.DATALAB_MARKER_API_BASE_URL
if form_data.DATALAB_MARKER_API_BASE_URL is not None
else config.DATALAB_MARKER_API_BASE_URL
)
config.DATALAB_MARKER_ADDITIONAL_CONFIG = (
form_data.DATALAB_MARKER_ADDITIONAL_CONFIG
if form_data.DATALAB_MARKER_ADDITIONAL_CONFIG is not None
else config.DATALAB_MARKER_ADDITIONAL_CONFIG
)
config.DATALAB_MARKER_SKIP_CACHE = (
form_data.DATALAB_MARKER_SKIP_CACHE
if form_data.DATALAB_MARKER_SKIP_CACHE is not None
else config.DATALAB_MARKER_SKIP_CACHE
)
config.DATALAB_MARKER_FORCE_OCR = (
form_data.DATALAB_MARKER_FORCE_OCR
if form_data.DATALAB_MARKER_FORCE_OCR is not None
else config.DATALAB_MARKER_FORCE_OCR
)
config.DATALAB_MARKER_PAGINATE = (
form_data.DATALAB_MARKER_PAGINATE
if form_data.DATALAB_MARKER_PAGINATE is not None
else config.DATALAB_MARKER_PAGINATE
)
config.DATALAB_MARKER_STRIP_EXISTING_OCR = (
form_data.DATALAB_MARKER_STRIP_EXISTING_OCR
if form_data.DATALAB_MARKER_STRIP_EXISTING_OCR is not None
else config.DATALAB_MARKER_STRIP_EXISTING_OCR
)
config.DATALAB_MARKER_DISABLE_IMAGE_EXTRACTION = (
form_data.DATALAB_MARKER_DISABLE_IMAGE_EXTRACTION
if form_data.DATALAB_MARKER_DISABLE_IMAGE_EXTRACTION is not None
else config.DATALAB_MARKER_DISABLE_IMAGE_EXTRACTION
)
config.DATALAB_MARKER_FORMAT_LINES = (
form_data.DATALAB_MARKER_FORMAT_LINES
if form_data.DATALAB_MARKER_FORMAT_LINES is not None
else config.DATALAB_MARKER_FORMAT_LINES
)
config.DATALAB_MARKER_OUTPUT_FORMAT = (
form_data.DATALAB_MARKER_OUTPUT_FORMAT
if form_data.DATALAB_MARKER_OUTPUT_FORMAT is not None
else config.DATALAB_MARKER_OUTPUT_FORMAT
)
config.DATALAB_MARKER_USE_LLM = (
form_data.DATALAB_MARKER_USE_LLM
if form_data.DATALAB_MARKER_USE_LLM is not None
else config.DATALAB_MARKER_USE_LLM
)
config.EXTERNAL_DOCUMENT_LOADER_URL = (
form_data.EXTERNAL_DOCUMENT_LOADER_URL
if form_data.EXTERNAL_DOCUMENT_LOADER_URL is not None
else config.EXTERNAL_DOCUMENT_LOADER_URL
)
config.EXTERNAL_DOCUMENT_LOADER_API_KEY = (
form_data.EXTERNAL_DOCUMENT_LOADER_API_KEY
if form_data.EXTERNAL_DOCUMENT_LOADER_API_KEY is not None
else config.EXTERNAL_DOCUMENT_LOADER_API_KEY
)
config.EXTERNAL_DOCUMENT_LOADER_HEADERS = (
form_data.EXTERNAL_DOCUMENT_LOADER_HEADERS
if form_data.EXTERNAL_DOCUMENT_LOADER_HEADERS is not None
else config.EXTERNAL_DOCUMENT_LOADER_HEADERS
)
config.TIKA_SERVER_URL = (
form_data.TIKA_SERVER_URL if form_data.TIKA_SERVER_URL is not None else config.TIKA_SERVER_URL
)
config.DOCLING_SERVER_URL = (
form_data.DOCLING_SERVER_URL if form_data.DOCLING_SERVER_URL is not None else config.DOCLING_SERVER_URL
)
config.DOCLING_API_KEY = (
form_data.DOCLING_API_KEY if form_data.DOCLING_API_KEY is not None else config.DOCLING_API_KEY
)
config.DOCLING_PARAMS = form_data.DOCLING_PARAMS if form_data.DOCLING_PARAMS is not None else config.DOCLING_PARAMS
config.DOCUMENT_INTELLIGENCE_ENDPOINT = (
form_data.DOCUMENT_INTELLIGENCE_ENDPOINT
if form_data.DOCUMENT_INTELLIGENCE_ENDPOINT is not None
else config.DOCUMENT_INTELLIGENCE_ENDPOINT
)
config.DOCUMENT_INTELLIGENCE_KEY = (
form_data.DOCUMENT_INTELLIGENCE_KEY
if form_data.DOCUMENT_INTELLIGENCE_KEY is not None
else config.DOCUMENT_INTELLIGENCE_KEY
)
config.DOCUMENT_INTELLIGENCE_MODEL = (
form_data.DOCUMENT_INTELLIGENCE_MODEL
if form_data.DOCUMENT_INTELLIGENCE_MODEL is not None
else config.DOCUMENT_INTELLIGENCE_MODEL
)
config.MISTRAL_OCR_API_BASE_URL = (
form_data.MISTRAL_OCR_API_BASE_URL
if form_data.MISTRAL_OCR_API_BASE_URL is not None
else config.MISTRAL_OCR_API_BASE_URL
)
config.MISTRAL_OCR_API_KEY = (
form_data.MISTRAL_OCR_API_KEY if form_data.MISTRAL_OCR_API_KEY is not None else config.MISTRAL_OCR_API_KEY
)
config.MISTRAL_OCR_USE_BASE64 = (
form_data.MISTRAL_OCR_USE_BASE64
if form_data.MISTRAL_OCR_USE_BASE64 is not None
else config.MISTRAL_OCR_USE_BASE64
)
config.PADDLEOCR_VL_BASE_URL = (
form_data.PADDLEOCR_VL_BASE_URL if form_data.PADDLEOCR_VL_BASE_URL is not None else config.PADDLEOCR_VL_BASE_URL
)
config.PADDLEOCR_VL_TOKEN = (
form_data.PADDLEOCR_VL_TOKEN if form_data.PADDLEOCR_VL_TOKEN is not None else config.PADDLEOCR_VL_TOKEN
)
# MinerU settings
config.MINERU_API_MODE = (
form_data.MINERU_API_MODE if form_data.MINERU_API_MODE is not None else config.MINERU_API_MODE
)
config.MINERU_API_URL = form_data.MINERU_API_URL if form_data.MINERU_API_URL is not None else config.MINERU_API_URL
config.MINERU_API_KEY = form_data.MINERU_API_KEY if form_data.MINERU_API_KEY is not None else config.MINERU_API_KEY
config.MINERU_API_TIMEOUT = (
form_data.MINERU_API_TIMEOUT if form_data.MINERU_API_TIMEOUT is not None else config.MINERU_API_TIMEOUT
)
config.MINERU_PARAMS = form_data.MINERU_PARAMS if form_data.MINERU_PARAMS is not None else config.MINERU_PARAMS
config.MINERU_FILE_EXTENSIONS = (
form_data.MINERU_FILE_EXTENSIONS
if form_data.MINERU_FILE_EXTENSIONS is not None
else config.MINERU_FILE_EXTENSIONS
)
# Reranking settings
if config.RAG_RERANKING_ENGINE == '':
# Unloading the internal reranker and clear VRAM memory
request.app.state.rf = None
request.app.state.RERANKING_FUNCTION = None
import gc
gc.collect()
if DEVICE_TYPE == 'cuda':
import torch
if torch.cuda.is_available():
torch.cuda.empty_cache()
config.RAG_RERANKING_ENGINE = (
form_data.RAG_RERANKING_ENGINE if form_data.RAG_RERANKING_ENGINE is not None else config.RAG_RERANKING_ENGINE
)
config.RAG_EXTERNAL_RERANKER_URL = (
form_data.RAG_EXTERNAL_RERANKER_URL
if form_data.RAG_EXTERNAL_RERANKER_URL is not None
else config.RAG_EXTERNAL_RERANKER_URL
)
config.RAG_EXTERNAL_RERANKER_API_KEY = (
form_data.RAG_EXTERNAL_RERANKER_API_KEY
if form_data.RAG_EXTERNAL_RERANKER_API_KEY is not None
else config.RAG_EXTERNAL_RERANKER_API_KEY
)
config.RAG_EXTERNAL_RERANKER_TIMEOUT = (
form_data.RAG_EXTERNAL_RERANKER_TIMEOUT
if form_data.RAG_EXTERNAL_RERANKER_TIMEOUT is not None
else config.RAG_EXTERNAL_RERANKER_TIMEOUT
)
config.RAG_RERANKING_BATCH_SIZE = (
form_data.RAG_RERANKING_BATCH_SIZE
if form_data.RAG_RERANKING_BATCH_SIZE is not None
else config.RAG_RERANKING_BATCH_SIZE
)
log.info('Updating reranking model: %s to %s', config.RAG_RERANKING_MODEL, form_data.RAG_RERANKING_MODEL)
try:
config.RAG_RERANKING_MODEL = (
form_data.RAG_RERANKING_MODEL if form_data.RAG_RERANKING_MODEL is not None else config.RAG_RERANKING_MODEL
)
try:
if config.ENABLE_RAG_HYBRID_SEARCH and not config.BYPASS_EMBEDDING_AND_RETRIEVAL:
request.app.state.rf = get_rf(
config.RAG_RERANKING_ENGINE,
config.RAG_RERANKING_MODEL,
config.RAG_EXTERNAL_RERANKER_URL,
config.RAG_EXTERNAL_RERANKER_API_KEY,
config.RAG_EXTERNAL_RERANKER_TIMEOUT,
)
request.app.state.RERANKING_FUNCTION = get_reranking_function(
config.RAG_RERANKING_ENGINE,
config.RAG_RERANKING_MODEL,
request.app.state.rf,
reranking_batch_size=config.RAG_RERANKING_BATCH_SIZE,
)
except Exception as e:
log.error(f'Error loading reranking model: {e}')
config.ENABLE_RAG_HYBRID_SEARCH = False
except Exception as e:
log.exception(f'Problem updating reranking model: {e}')
raise HTTPException(
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
detail=ERROR_MESSAGES.DEFAULT(e, 'Error updating reranking configuration'),
)
# Chunking settings
config.TEXT_SPLITTER = form_data.TEXT_SPLITTER if form_data.TEXT_SPLITTER is not None else config.TEXT_SPLITTER
config.ENABLE_MARKDOWN_HEADER_TEXT_SPLITTER = (
form_data.ENABLE_MARKDOWN_HEADER_TEXT_SPLITTER
if form_data.ENABLE_MARKDOWN_HEADER_TEXT_SPLITTER is not None
else config.ENABLE_MARKDOWN_HEADER_TEXT_SPLITTER
)
config.CHUNK_SIZE = form_data.CHUNK_SIZE if form_data.CHUNK_SIZE is not None else config.CHUNK_SIZE
config.CHUNK_MIN_SIZE_TARGET = (
form_data.CHUNK_MIN_SIZE_TARGET if form_data.CHUNK_MIN_SIZE_TARGET is not None else config.CHUNK_MIN_SIZE_TARGET
)
config.CHUNK_OVERLAP = form_data.CHUNK_OVERLAP if form_data.CHUNK_OVERLAP is not None else config.CHUNK_OVERLAP
config.RAG_TOKENIZER_MODEL = (
form_data.RAG_TOKENIZER_MODEL.strip()
if form_data.RAG_TOKENIZER_MODEL is not None
else config.RAG_TOKENIZER_MODEL
)
# File upload settings
# Empty string means "clear to None" (unlimited/no compression),
# None means "don't change", int means "set to this value"
if form_data.FILE_MAX_SIZE is not None:
config.FILE_MAX_SIZE = None if form_data.FILE_MAX_SIZE == '' else form_data.FILE_MAX_SIZE
if form_data.FILE_MAX_COUNT is not None:
config.FILE_MAX_COUNT = None if form_data.FILE_MAX_COUNT == '' else form_data.FILE_MAX_COUNT
if form_data.FILE_IMAGE_COMPRESSION_WIDTH is not None:
config.FILE_IMAGE_COMPRESSION_WIDTH = (
None if form_data.FILE_IMAGE_COMPRESSION_WIDTH == '' else form_data.FILE_IMAGE_COMPRESSION_WIDTH
)
if form_data.FILE_IMAGE_COMPRESSION_HEIGHT is not None:
config.FILE_IMAGE_COMPRESSION_HEIGHT = (
None if form_data.FILE_IMAGE_COMPRESSION_HEIGHT == '' else form_data.FILE_IMAGE_COMPRESSION_HEIGHT
)
config.ALLOWED_FILE_EXTENSIONS = (
form_data.ALLOWED_FILE_EXTENSIONS
if form_data.ALLOWED_FILE_EXTENSIONS is not None
else config.ALLOWED_FILE_EXTENSIONS
)
# Integration settings
config.ENABLE_GOOGLE_DRIVE_INTEGRATION = (
form_data.ENABLE_GOOGLE_DRIVE_INTEGRATION
if form_data.ENABLE_GOOGLE_DRIVE_INTEGRATION is not None
else config.ENABLE_GOOGLE_DRIVE_INTEGRATION
)
config.ENABLE_ONEDRIVE_INTEGRATION = (
form_data.ENABLE_ONEDRIVE_INTEGRATION
if form_data.ENABLE_ONEDRIVE_INTEGRATION is not None
else config.ENABLE_ONEDRIVE_INTEGRATION
)
if form_data.web is not None:
# Web search settings
config.ENABLE_WEB_SEARCH = form_data.web.ENABLE_WEB_SEARCH
config.ENABLE_WEB_SEARCH_CONFIRMATION = form_data.web.ENABLE_WEB_SEARCH_CONFIRMATION
config.WEB_SEARCH_CONFIRMATION_CONTENT = form_data.web.WEB_SEARCH_CONFIRMATION_CONTENT
config.WEB_SEARCH_ENGINE = form_data.web.WEB_SEARCH_ENGINE
config.WEB_SEARCH_TRUST_ENV = form_data.web.WEB_SEARCH_TRUST_ENV
config.WEB_SEARCH_RESULT_COUNT = form_data.web.WEB_SEARCH_RESULT_COUNT
config.WEB_SEARCH_CONCURRENT_REQUESTS = form_data.web.WEB_SEARCH_CONCURRENT_REQUESTS
config.WEB_FETCH_MAX_CONTENT_LENGTH = form_data.web.WEB_FETCH_MAX_CONTENT_LENGTH
config.WEB_LOADER_CONCURRENT_REQUESTS = form_data.web.WEB_LOADER_CONCURRENT_REQUESTS
config.WEB_SEARCH_DOMAIN_FILTER_LIST = form_data.web.WEB_SEARCH_DOMAIN_FILTER_LIST
config.BYPASS_WEB_SEARCH_EMBEDDING_AND_RETRIEVAL = form_data.web.BYPASS_WEB_SEARCH_EMBEDDING_AND_RETRIEVAL
config.BYPASS_WEB_SEARCH_WEB_LOADER = form_data.web.BYPASS_WEB_SEARCH_WEB_LOADER
config.OLLAMA_CLOUD_WEB_SEARCH_API_KEY = form_data.web.OLLAMA_CLOUD_WEB_SEARCH_API_KEY
config.SEARXNG_QUERY_URL = form_data.web.SEARXNG_QUERY_URL
config.SEARXNG_LANGUAGE = form_data.web.SEARXNG_LANGUAGE
config.OPENSERP_BASE_URL = form_data.web.OPENSERP_BASE_URL
config.YACY_QUERY_URL = form_data.web.YACY_QUERY_URL
config.YACY_USERNAME = form_data.web.YACY_USERNAME
config.YACY_PASSWORD = form_data.web.YACY_PASSWORD
config.GOOGLE_PSE_API_KEY = form_data.web.GOOGLE_PSE_API_KEY
config.GOOGLE_PSE_ENGINE_ID = form_data.web.GOOGLE_PSE_ENGINE_ID
config.BRAVE_SEARCH_API_KEY = form_data.web.BRAVE_SEARCH_API_KEY
if form_data.web.BRAVE_SEARCH_CONTEXT_TOKENS is not None:
config.BRAVE_SEARCH_CONTEXT_TOKENS = form_data.web.BRAVE_SEARCH_CONTEXT_TOKENS
config.KAGI_SEARCH_API_KEY = form_data.web.KAGI_SEARCH_API_KEY
config.MOJEEK_SEARCH_API_KEY = form_data.web.MOJEEK_SEARCH_API_KEY
config.BOCHA_SEARCH_API_KEY = form_data.web.BOCHA_SEARCH_API_KEY
config.SERPSTACK_API_KEY = form_data.web.SERPSTACK_API_KEY
config.SERPSTACK_HTTPS = form_data.web.SERPSTACK_HTTPS
config.SERPER_API_KEY = form_data.web.SERPER_API_KEY
config.SERPHOUSE_API_KEY = form_data.web.SERPHOUSE_API_KEY
config.SERPHOUSE_DOMAIN = form_data.web.SERPHOUSE_DOMAIN
config.SERPLY_API_KEY = form_data.web.SERPLY_API_KEY
config.DDGS_BACKEND = form_data.web.DDGS_BACKEND
config.TAVILY_API_KEY = form_data.web.TAVILY_API_KEY
config.SEARCHAPI_API_KEY = form_data.web.SEARCHAPI_API_KEY
config.SEARCHAPI_ENGINE = form_data.web.SEARCHAPI_ENGINE
config.SERPAPI_API_KEY = form_data.web.SERPAPI_API_KEY
config.SERPAPI_ENGINE = form_data.web.SERPAPI_ENGINE
config.JINA_API_KEY = form_data.web.JINA_API_KEY
config.JINA_API_BASE_URL = form_data.web.JINA_API_BASE_URL
config.BING_SEARCH_V7_ENDPOINT = form_data.web.BING_SEARCH_V7_ENDPOINT
config.BING_SEARCH_V7_SUBSCRIPTION_KEY = form_data.web.BING_SEARCH_V7_SUBSCRIPTION_KEY
config.EXA_API_KEY = form_data.web.EXA_API_KEY
config.PERPLEXITY_API_KEY = form_data.web.PERPLEXITY_API_KEY
config.PERPLEXITY_MODEL = form_data.web.PERPLEXITY_MODEL
config.PERPLEXITY_SEARCH_CONTEXT_USAGE = form_data.web.PERPLEXITY_SEARCH_CONTEXT_USAGE
config.PERPLEXITY_SEARCH_API_URL = form_data.web.PERPLEXITY_SEARCH_API_URL
config.MICROSOFT_WEB_IQ_API_BASE_URL = form_data.web.MICROSOFT_WEB_IQ_API_BASE_URL
config.MICROSOFT_WEB_IQ_API_KEY = form_data.web.MICROSOFT_WEB_IQ_API_KEY
config.MICROSOFT_WEB_IQ_LANGUAGE = form_data.web.MICROSOFT_WEB_IQ_LANGUAGE
config.SOUGOU_API_SID = form_data.web.SOUGOU_API_SID
config.SOUGOU_API_SK = form_data.web.SOUGOU_API_SK
# Web loader settings
config.WEB_LOADER_ENGINE = form_data.web.WEB_LOADER_ENGINE
config.WEB_LOADER_TIMEOUT = form_data.web.WEB_LOADER_TIMEOUT
config.ENABLE_WEB_LOADER_SSL_VERIFICATION = form_data.web.ENABLE_WEB_LOADER_SSL_VERIFICATION
config.PLAYWRIGHT_WS_URL = form_data.web.PLAYWRIGHT_WS_URL
config.PLAYWRIGHT_TIMEOUT = form_data.web.PLAYWRIGHT_TIMEOUT
config.FIRECRAWL_API_KEY = form_data.web.FIRECRAWL_API_KEY
config.FIRECRAWL_API_BASE_URL = form_data.web.FIRECRAWL_API_BASE_URL
config.FIRECRAWL_TIMEOUT = form_data.web.FIRECRAWL_TIMEOUT
config.EXTERNAL_WEB_SEARCH_URL = form_data.web.EXTERNAL_WEB_SEARCH_URL
config.EXTERNAL_WEB_SEARCH_API_KEY = form_data.web.EXTERNAL_WEB_SEARCH_API_KEY
config.EXTERNAL_WEB_LOADER_URL = form_data.web.EXTERNAL_WEB_LOADER_URL
config.EXTERNAL_WEB_LOADER_API_KEY = form_data.web.EXTERNAL_WEB_LOADER_API_KEY
config.TAVILY_EXTRACT_DEPTH = form_data.web.TAVILY_EXTRACT_DEPTH
config.YOUTUBE_LOADER_LANGUAGE = form_data.web.YOUTUBE_LOADER_LANGUAGE
config.YOUTUBE_LOADER_PROXY_URL = form_data.web.YOUTUBE_LOADER_PROXY_URL
request.app.state.YOUTUBE_LOADER_TRANSLATION = form_data.web.YOUTUBE_LOADER_TRANSLATION
config.YANDEX_WEB_SEARCH_URL = form_data.web.YANDEX_WEB_SEARCH_URL
config.YANDEX_WEB_SEARCH_API_KEY = form_data.web.YANDEX_WEB_SEARCH_API_KEY
config.YANDEX_WEB_SEARCH_CONFIG = form_data.web.YANDEX_WEB_SEARCH_CONFIG
config.YOUCOM_API_KEY = form_data.web.YOUCOM_API_KEY
config.LINKUP_API_KEY = form_data.web.LINKUP_API_KEY
config.LINKUP_SEARCH_PARAMS = form_data.web.LINKUP_SEARCH_PARAMS
await config.save()
return {
'status': True,
# RAG settings
'RAG_TEMPLATE': config.RAG_TEMPLATE,
'TOP_K': config.TOP_K,
'BYPASS_EMBEDDING_AND_RETRIEVAL': config.BYPASS_EMBEDDING_AND_RETRIEVAL,
'RAG_FULL_CONTEXT': config.RAG_FULL_CONTEXT,
# Hybrid search settings
'ENABLE_RAG_HYBRID_SEARCH': config.ENABLE_RAG_HYBRID_SEARCH,
'TOP_K_RERANKER': config.TOP_K_RERANKER,
'RELEVANCE_THRESHOLD': config.RELEVANCE_THRESHOLD,
'HYBRID_BM25_WEIGHT': config.HYBRID_BM25_WEIGHT,
# Content extraction settings
'CONTENT_EXTRACTION_ENGINE': config.CONTENT_EXTRACTION_ENGINE,
'CONTENT_EXTRACTION_SUPPORTED_MEDIA_MIME_TYPES': config.CONTENT_EXTRACTION_SUPPORTED_MEDIA_MIME_TYPES,
'PDF_EXTRACT_IMAGES': config.PDF_EXTRACT_IMAGES,
'PDF_LOADER_MODE': config.PDF_LOADER_MODE,
'DATALAB_MARKER_API_KEY': config.DATALAB_MARKER_API_KEY,
'DATALAB_MARKER_API_BASE_URL': config.DATALAB_MARKER_API_BASE_URL,
'DATALAB_MARKER_ADDITIONAL_CONFIG': config.DATALAB_MARKER_ADDITIONAL_CONFIG,
'DATALAB_MARKER_SKIP_CACHE': config.DATALAB_MARKER_SKIP_CACHE,
'DATALAB_MARKER_FORCE_OCR': config.DATALAB_MARKER_FORCE_OCR,
'DATALAB_MARKER_PAGINATE': config.DATALAB_MARKER_PAGINATE,
'DATALAB_MARKER_STRIP_EXISTING_OCR': config.DATALAB_MARKER_STRIP_EXISTING_OCR,
'DATALAB_MARKER_DISABLE_IMAGE_EXTRACTION': config.DATALAB_MARKER_DISABLE_IMAGE_EXTRACTION,
'DATALAB_MARKER_USE_LLM': config.DATALAB_MARKER_USE_LLM,
'DATALAB_MARKER_OUTPUT_FORMAT': config.DATALAB_MARKER_OUTPUT_FORMAT,
'EXTERNAL_DOCUMENT_LOADER_URL': config.EXTERNAL_DOCUMENT_LOADER_URL,
'EXTERNAL_DOCUMENT_LOADER_API_KEY': config.EXTERNAL_DOCUMENT_LOADER_API_KEY,
'EXTERNAL_DOCUMENT_LOADER_HEADERS': config.EXTERNAL_DOCUMENT_LOADER_HEADERS,
'TIKA_SERVER_URL': config.TIKA_SERVER_URL,
'DOCLING_SERVER_URL': config.DOCLING_SERVER_URL,
'DOCLING_API_KEY': config.DOCLING_API_KEY,
'DOCLING_PARAMS': config.DOCLING_PARAMS,
'DOCUMENT_INTELLIGENCE_ENDPOINT': config.DOCUMENT_INTELLIGENCE_ENDPOINT,
'DOCUMENT_INTELLIGENCE_KEY': config.DOCUMENT_INTELLIGENCE_KEY,
'DOCUMENT_INTELLIGENCE_MODEL': config.DOCUMENT_INTELLIGENCE_MODEL,
'MISTRAL_OCR_API_BASE_URL': config.MISTRAL_OCR_API_BASE_URL,
'MISTRAL_OCR_API_KEY': config.MISTRAL_OCR_API_KEY,
'MISTRAL_OCR_USE_BASE64': config.MISTRAL_OCR_USE_BASE64,
'PADDLEOCR_VL_BASE_URL': config.PADDLEOCR_VL_BASE_URL,
'PADDLEOCR_VL_TOKEN': config.PADDLEOCR_VL_TOKEN,
# MinerU settings
'MINERU_API_MODE': config.MINERU_API_MODE,
'MINERU_API_URL': config.MINERU_API_URL,
'MINERU_API_KEY': config.MINERU_API_KEY,
'MINERU_API_TIMEOUT': config.MINERU_API_TIMEOUT,
'MINERU_PARAMS': config.MINERU_PARAMS,
# Reranking settings
'RAG_RERANKING_MODEL': config.RAG_RERANKING_MODEL,
'RAG_RERANKING_ENGINE': config.RAG_RERANKING_ENGINE,
'RAG_EXTERNAL_RERANKER_URL': config.RAG_EXTERNAL_RERANKER_URL,
'RAG_EXTERNAL_RERANKER_API_KEY': config.RAG_EXTERNAL_RERANKER_API_KEY,
'RAG_EXTERNAL_RERANKER_TIMEOUT': config.RAG_EXTERNAL_RERANKER_TIMEOUT,
# Chunking settings
'TEXT_SPLITTER': config.TEXT_SPLITTER,
'RAG_TOKENIZER_MODEL': config.RAG_TOKENIZER_MODEL,
'CHUNK_SIZE': config.CHUNK_SIZE,
'CHUNK_MIN_SIZE_TARGET': config.CHUNK_MIN_SIZE_TARGET,
'ENABLE_MARKDOWN_HEADER_TEXT_SPLITTER': config.ENABLE_MARKDOWN_HEADER_TEXT_SPLITTER,
'CHUNK_OVERLAP': config.CHUNK_OVERLAP,
# File upload settings
'FILE_MAX_SIZE': config.FILE_MAX_SIZE,
'FILE_MAX_COUNT': config.FILE_MAX_COUNT,
'FILE_IMAGE_COMPRESSION_WIDTH': config.FILE_IMAGE_COMPRESSION_WIDTH,
'FILE_IMAGE_COMPRESSION_HEIGHT': config.FILE_IMAGE_COMPRESSION_HEIGHT,
'ALLOWED_FILE_EXTENSIONS': config.ALLOWED_FILE_EXTENSIONS,
# Integration settings
'ENABLE_GOOGLE_DRIVE_INTEGRATION': config.ENABLE_GOOGLE_DRIVE_INTEGRATION,
'ENABLE_ONEDRIVE_INTEGRATION': config.ENABLE_ONEDRIVE_INTEGRATION,
# Web search settings
'web': {
'ENABLE_WEB_SEARCH': config.ENABLE_WEB_SEARCH,
'ENABLE_WEB_SEARCH_CONFIRMATION': config.ENABLE_WEB_SEARCH_CONFIRMATION,
'WEB_SEARCH_CONFIRMATION_CONTENT': config.WEB_SEARCH_CONFIRMATION_CONTENT,
'WEB_SEARCH_ENGINE': config.WEB_SEARCH_ENGINE,
'WEB_SEARCH_TRUST_ENV': config.WEB_SEARCH_TRUST_ENV,
'WEB_SEARCH_RESULT_COUNT': config.WEB_SEARCH_RESULT_COUNT,
'WEB_SEARCH_CONCURRENT_REQUESTS': config.WEB_SEARCH_CONCURRENT_REQUESTS,
'WEB_FETCH_MAX_CONTENT_LENGTH': config.WEB_FETCH_MAX_CONTENT_LENGTH,
'WEB_LOADER_CONCURRENT_REQUESTS': config.WEB_LOADER_CONCURRENT_REQUESTS,
'WEB_SEARCH_DOMAIN_FILTER_LIST': config.WEB_SEARCH_DOMAIN_FILTER_LIST,
'BYPASS_WEB_SEARCH_EMBEDDING_AND_RETRIEVAL': config.BYPASS_WEB_SEARCH_EMBEDDING_AND_RETRIEVAL,
'BYPASS_WEB_SEARCH_WEB_LOADER': config.BYPASS_WEB_SEARCH_WEB_LOADER,
'OLLAMA_CLOUD_WEB_SEARCH_API_KEY': config.OLLAMA_CLOUD_WEB_SEARCH_API_KEY,
'SEARXNG_QUERY_URL': config.SEARXNG_QUERY_URL,
'SEARXNG_LANGUAGE': config.SEARXNG_LANGUAGE,
'OPENSERP_BASE_URL': config.OPENSERP_BASE_URL,
'YACY_QUERY_URL': config.YACY_QUERY_URL,
'YACY_USERNAME': config.YACY_USERNAME,
'YACY_PASSWORD': config.YACY_PASSWORD,
'GOOGLE_PSE_API_KEY': config.GOOGLE_PSE_API_KEY,
'GOOGLE_PSE_ENGINE_ID': config.GOOGLE_PSE_ENGINE_ID,
'BRAVE_SEARCH_API_KEY': config.BRAVE_SEARCH_API_KEY,
'BRAVE_SEARCH_CONTEXT_TOKENS': config.BRAVE_SEARCH_CONTEXT_TOKENS,
'KAGI_SEARCH_API_KEY': config.KAGI_SEARCH_API_KEY,
'MOJEEK_SEARCH_API_KEY': config.MOJEEK_SEARCH_API_KEY,
'BOCHA_SEARCH_API_KEY': config.BOCHA_SEARCH_API_KEY,
'SERPSTACK_API_KEY': config.SERPSTACK_API_KEY,
'SERPSTACK_HTTPS': config.SERPSTACK_HTTPS,
'SERPER_API_KEY': config.SERPER_API_KEY,
'SERPHOUSE_API_KEY': config.SERPHOUSE_API_KEY,
'SERPHOUSE_DOMAIN': config.SERPHOUSE_DOMAIN,
'SERPLY_API_KEY': config.SERPLY_API_KEY,
'TAVILY_API_KEY': config.TAVILY_API_KEY,
'SEARCHAPI_API_KEY': config.SEARCHAPI_API_KEY,
'SEARCHAPI_ENGINE': config.SEARCHAPI_ENGINE,
'SERPAPI_API_KEY': config.SERPAPI_API_KEY,
'SERPAPI_ENGINE': config.SERPAPI_ENGINE,
'JINA_API_KEY': config.JINA_API_KEY,
'JINA_API_BASE_URL': config.JINA_API_BASE_URL,
'BING_SEARCH_V7_ENDPOINT': config.BING_SEARCH_V7_ENDPOINT,
'BING_SEARCH_V7_SUBSCRIPTION_KEY': config.BING_SEARCH_V7_SUBSCRIPTION_KEY,
'EXA_API_KEY': config.EXA_API_KEY,
'PERPLEXITY_API_KEY': config.PERPLEXITY_API_KEY,
'PERPLEXITY_MODEL': config.PERPLEXITY_MODEL,
'PERPLEXITY_SEARCH_CONTEXT_USAGE': config.PERPLEXITY_SEARCH_CONTEXT_USAGE,
'PERPLEXITY_SEARCH_API_URL': config.PERPLEXITY_SEARCH_API_URL,
'MICROSOFT_WEB_IQ_API_BASE_URL': config.MICROSOFT_WEB_IQ_API_BASE_URL,
'MICROSOFT_WEB_IQ_API_KEY': config.MICROSOFT_WEB_IQ_API_KEY,
'MICROSOFT_WEB_IQ_LANGUAGE': config.MICROSOFT_WEB_IQ_LANGUAGE,
'SOUGOU_API_SID': config.SOUGOU_API_SID,
'SOUGOU_API_SK': config.SOUGOU_API_SK,
'WEB_LOADER_ENGINE': config.WEB_LOADER_ENGINE,
'WEB_LOADER_TIMEOUT': config.WEB_LOADER_TIMEOUT,
'ENABLE_WEB_LOADER_SSL_VERIFICATION': config.ENABLE_WEB_LOADER_SSL_VERIFICATION,
'PLAYWRIGHT_WS_URL': config.PLAYWRIGHT_WS_URL,
'PLAYWRIGHT_TIMEOUT': config.PLAYWRIGHT_TIMEOUT,
'FIRECRAWL_API_KEY': config.FIRECRAWL_API_KEY,
'FIRECRAWL_API_BASE_URL': config.FIRECRAWL_API_BASE_URL,
'FIRECRAWL_TIMEOUT': config.FIRECRAWL_TIMEOUT,
'TAVILY_EXTRACT_DEPTH': config.TAVILY_EXTRACT_DEPTH,
'EXTERNAL_WEB_SEARCH_URL': config.EXTERNAL_WEB_SEARCH_URL,
'EXTERNAL_WEB_SEARCH_API_KEY': config.EXTERNAL_WEB_SEARCH_API_KEY,
'EXTERNAL_WEB_LOADER_URL': config.EXTERNAL_WEB_LOADER_URL,
'EXTERNAL_WEB_LOADER_API_KEY': config.EXTERNAL_WEB_LOADER_API_KEY,
'YOUTUBE_LOADER_LANGUAGE': config.YOUTUBE_LOADER_LANGUAGE,
'YOUTUBE_LOADER_PROXY_URL': config.YOUTUBE_LOADER_PROXY_URL,
'YOUTUBE_LOADER_TRANSLATION': request.app.state.YOUTUBE_LOADER_TRANSLATION,
'YANDEX_WEB_SEARCH_URL': config.YANDEX_WEB_SEARCH_URL,
'YANDEX_WEB_SEARCH_API_KEY': config.YANDEX_WEB_SEARCH_API_KEY,
'YANDEX_WEB_SEARCH_CONFIG': config.YANDEX_WEB_SEARCH_CONFIG,
'YOUCOM_API_KEY': config.YOUCOM_API_KEY,
'LINKUP_API_KEY': config.LINKUP_API_KEY,
'LINKUP_SEARCH_PARAMS': config.LINKUP_SEARCH_PARAMS,
},
}
####################################
#
# Document process and retrieval
#
####################################
def can_merge_chunks(a: Document, b: Document) -> bool:
if a.metadata.get('source') != b.metadata.get('source'):
return False
a_file_id = a.metadata.get('file_id')
b_file_id = b.metadata.get('file_id')
if a_file_id is not None and b_file_id is not None:
return a_file_id == b_file_id
return True
def merge_docs_to_target_size(
request: Request,
chunks: list[Document],
config: RetrievalConfig,
) -> list[Document]:
"""
Best-effort normalization of chunk sizes.
Attempts to grow small chunks up to a desired minimum size,
without exceeding the maximum size or crossing source/file
boundaries.
Uses forward merging first (absorb the next chunk), then
backward merging (append into the previous emitted chunk)
for undersized chunks that can't grow forward.
"""
min_size = config.CHUNK_MIN_SIZE_TARGET
max_size = config.CHUNK_SIZE
if min_size <= 0:
return chunks
measure = get_splitter_length_function(request, config)
def _merge_backward(result: list[Document], content: str, chunk: Document) -> bool:
"""Try to append content into the last emitted chunk. Returns True on success."""
if not result:
return False
prev = result[-1]
if not can_merge_chunks(prev, chunk):
return False
merged = f'{prev.page_content}\n\n{content}'
if measure(merged) > max_size:
return False
result[-1] = Document(page_content=merged, metadata={**prev.metadata})
return True
def _emit(result: list[Document], content: str, chunk: Document) -> None:
"""Emit a chunk, trying backward merge first if it's undersized."""
is_undersized = measure(content) < min_size
if is_undersized and _merge_backward(result, content, chunk):
return
result.append(Document(page_content=content, metadata={**chunk.metadata}))
result: list[Document] = []
current_chunk: Document | None = None
current_content: str = ''
for next_chunk in chunks:
if current_chunk is None:
current_chunk = next_chunk
current_content = next_chunk.page_content
continue
# Forward merge: absorb next chunk into current if undersized and fits
merged_content = f'{current_content}\n\n{next_chunk.page_content}'
can_merge_forward = (
can_merge_chunks(current_chunk, next_chunk)
and measure(current_content) < min_size
and measure(merged_content) <= max_size
)
if can_merge_forward:
current_content = merged_content
else:
_emit(result, current_content, current_chunk)
current_chunk = next_chunk
current_content = next_chunk.page_content
if current_chunk is not None:
_emit(result, current_content, current_chunk)
return result
def get_transformers_tokenizer(request: Request, config: RetrievalConfig):
if config.RAG_TOKENIZER_MODEL:
from transformers import AutoTokenizer
tokenizer_model = config.RAG_TOKENIZER_MODEL
if not os.path.exists(tokenizer_model) and '/' not in tokenizer_model:
tokenizer_model = f'sentence-transformers/{tokenizer_model}'
cache_dir = os.getenv('SENTENCE_TRANSFORMERS_HOME') or os.getenv('HF_HUB_CACHE')
local_files_only = not RAG_EMBEDDING_MODEL_AUTO_UPDATE
tokenizer_key = (tokenizer_model, cache_dir, local_files_only)
cached_tokenizer = getattr(request.app.state, 'transformers_tokenizer', None)
if cached_tokenizer and cached_tokenizer[0] == tokenizer_key:
return cached_tokenizer[1]
tokenizer = AutoTokenizer.from_pretrained(
tokenizer_model,
cache_dir=cache_dir,
trust_remote_code=RAG_EMBEDDING_MODEL_TRUST_REMOTE_CODE,
local_files_only=local_files_only,
)
request.app.state.transformers_tokenizer = (tokenizer_key, tokenizer)
return tokenizer
tokenizer = getattr(getattr(request.app.state, 'ef', None), 'tokenizer', None)
if tokenizer is not None:
return tokenizer
raise ValueError('Tokenizer model required for Token (Transformers) text splitter')
def get_splitter_length_function(
request: Request,
config: RetrievalConfig,
) -> Callable[[str], int]:
if config.TEXT_SPLITTER == 'token':
encoding = tiktoken.get_encoding(str(config.TIKTOKEN_ENCODING_NAME))
return lambda text: len(encoding.encode(text, disallowed_special=TIKTOKEN_DISALLOWED_SPECIAL))
if config.TEXT_SPLITTER == 'token_transformers':
tokenizer = get_transformers_tokenizer(request, config)
return lambda text: len(tokenizer.encode(text))
return len
def save_docs_to_vector_db(
request: Request,
docs,
collection_name,
config: RetrievalConfig,
metadata: dict | None = None,
overwrite: bool = False,
split: bool = True,
add: bool = False,
user=None,
) -> bool:
def _get_docs_info(docs: list[Document]) -> str:
docs_info = set()
# Trying to select relevant metadata identifying the document.
for doc in docs:
metadata = getattr(doc, 'metadata', {})
doc_name = metadata.get('name', '')
if not doc_name:
doc_name = metadata.get('title', '')
if not doc_name:
doc_name = metadata.get('source', '')
if doc_name:
docs_info.add(doc_name)
return ', '.join(docs_info)
log.debug('save_docs_to_vector_db: document %s %s', _get_docs_info(docs), collection_name)
# Check if entries with the same hash (metadata.hash) already exist
if metadata and 'hash' in metadata:
result = VECTOR_DB_CLIENT.query(
collection_name=collection_name,
filter={'hash': metadata['hash']},
)
if result is not None and result.ids and len(result.ids) > 0:
existing_doc_ids = result.ids[0]
if existing_doc_ids:
# Check if the existing document belongs to the same file
# If same file_id, this is a re-add/reindex - allow it
# If different file_id, this is a duplicate - block it
existing_file_id = None
if result.metadatas and result.metadatas[0]:
existing_file_id = result.metadatas[0][0].get('file_id')
if existing_file_id != metadata.get('file_id'):
log.info('Document with hash %s already exists', metadata['hash'])
raise ValueError(ERROR_MESSAGES.DUPLICATE_CONTENT)
if split:
if config.ENABLE_MARKDOWN_HEADER_TEXT_SPLITTER:
log.info('Using markdown header text splitter')
# Define headers to split on - covering most common markdown header levels
markdown_splitter = MarkdownHeaderTextSplitter(
headers_to_split_on=[
('#', 'Header 1'),
('##', 'Header 2'),
('###', 'Header 3'),
('####', 'Header 4'),
('#####', 'Header 5'),
('######', 'Header 6'),
],
strip_headers=False, # Keep headers in content for context
)
split_docs = []
for doc in docs:
split_docs.extend(
[
Document(
page_content=split_chunk.page_content,
metadata={**doc.metadata},
)
for split_chunk in markdown_splitter.split_text(doc.page_content)
]
)
docs = split_docs
if config.CHUNK_MIN_SIZE_TARGET > 0:
docs = merge_docs_to_target_size(request, docs, config)
if config.TEXT_SPLITTER in ['', 'character']:
text_splitter = RecursiveCharacterTextSplitter(
chunk_size=config.CHUNK_SIZE,
chunk_overlap=config.CHUNK_OVERLAP,
add_start_index=True,
)
docs = text_splitter.split_documents(docs)
elif config.TEXT_SPLITTER == 'token':
log.info('Using token text splitter: %s', config.TIKTOKEN_ENCODING_NAME)
tiktoken.get_encoding(str(config.TIKTOKEN_ENCODING_NAME))
text_splitter = TokenTextSplitter(
encoding_name=str(config.TIKTOKEN_ENCODING_NAME),
chunk_size=config.CHUNK_SIZE,
chunk_overlap=config.CHUNK_OVERLAP,
add_start_index=True,
disallowed_special=TIKTOKEN_DISALLOWED_SPECIAL,
)
docs = text_splitter.split_documents(docs)
elif config.TEXT_SPLITTER == 'token_transformers':
log.info('Using transformers token text splitter')
text_splitter = RecursiveCharacterTextSplitter(
chunk_size=config.CHUNK_SIZE,
chunk_overlap=config.CHUNK_OVERLAP,
length_function=get_splitter_length_function(request, config),
add_start_index=True,
)
docs = text_splitter.split_documents(docs)
else:
raise ValueError(ERROR_MESSAGES.DEFAULT('Invalid text splitter'))
if len(docs) == 0:
raise ValueError(ERROR_MESSAGES.EMPTY_CONTENT)
texts = [sanitize_text_for_db(doc.page_content) for doc in docs]
metadatas = [
{
**doc.metadata,
**(metadata if metadata else {}),
'embedding_config': {
'engine': config.RAG_EMBEDDING_ENGINE,
'model': config.RAG_EMBEDDING_MODEL,
},
}
for doc in docs
]
try:
if VECTOR_DB_CLIENT.has_collection(collection_name=collection_name):
log.info('collection %s already exists', collection_name)
if overwrite:
VECTOR_DB_CLIENT.delete_collection(collection_name=collection_name)
log.info('deleting existing collection %s', collection_name)
elif add is False:
log.info('collection %s already exists, overwrite is False and add is False', collection_name)
return True
log.info('generating embeddings for %s', collection_name)
embedding_function = get_embedding_function(
config.RAG_EMBEDDING_ENGINE,
config.RAG_EMBEDDING_MODEL,
request.app.state.ef,
(
config.RAG_OPENAI_API_BASE_URL
if config.RAG_EMBEDDING_ENGINE == 'openai'
else (
config.RAG_OLLAMA_BASE_URL
if config.RAG_EMBEDDING_ENGINE == 'ollama'
else config.RAG_AZURE_OPENAI_BASE_URL
)
),
(
config.RAG_OPENAI_API_KEY
if config.RAG_EMBEDDING_ENGINE == 'openai'
else (
config.RAG_OLLAMA_API_KEY
if config.RAG_EMBEDDING_ENGINE == 'ollama'
else config.RAG_AZURE_OPENAI_API_KEY
)
),
config.RAG_EMBEDDING_BATCH_SIZE,
azure_api_version=(
config.RAG_AZURE_OPENAI_API_VERSION if config.RAG_EMBEDDING_ENGINE == 'azure_openai' else None
),
enable_async=config.ENABLE_ASYNC_EMBEDDING,
concurrent_requests=config.RAG_EMBEDDING_CONCURRENT_REQUESTS,
)
# Run async embedding in sync context using the main event loop
# This allows the main loop to stay responsive to health checks during long operations
embedding_timeout = RAG_EMBEDDING_TIMEOUT
future = asyncio.run_coroutine_threadsafe(
embedding_function(
list(map(lambda x: x.replace('\n', ' '), texts)),
prefix=RAG_EMBEDDING_CONTENT_PREFIX,
user=user,
),
request.app.state.main_loop,
)
embeddings = future.result(timeout=embedding_timeout)
log.info('embeddings generated %s for %s items', len(embeddings), len(texts))
items = [
{
'id': str(uuid.uuid4()),
'text': text,
'vector': embeddings[idx],
'metadata': metadatas[idx],
}
for idx, text in enumerate(texts)
]
log.info('adding to collection %s', collection_name)
VECTOR_DB_CLIENT.insert(
collection_name=collection_name,
items=items,
)
log.info('added %s items to collection %s', len(items), collection_name)
return True
except Exception as e:
log.exception(e)
raise e
class ProcessFileForm(BaseModel):
file_id: str
content: str | None = None
collection_name: str | None = None
@router.post('/process/file')
async def process_file(
request: Request,
form_data: ProcessFileForm,
user=Depends(get_verified_user),
db: AsyncSession = Depends(get_async_session),
):
"""
Process a file and save its content to the vector database.
Process a file and save its content to the vector database.
Note: granular session management is used to prevent connection pool exhaustion.
The session is committed before external API calls, and updates use a fresh session.
"""
config = await get_retrieval_config()
if user.role == 'admin':
file = await Files.get_file_by_id(form_data.file_id, db=db)
else:
file = await Files.get_file_by_id_and_user_id(form_data.file_id, user.id, db=db)
if file:
try:
collection_name = form_data.collection_name
if collection_name is None:
collection_name = f'file-{file.id}'
else:
await _validate_collection_access([collection_name], user, access_type='write')
if form_data.content:
# Update the content in the file
# Usage: /files/{file_id}/data/content/update, /files/ (audio file upload pipeline)
try:
# /files/{file_id}/data/content/update
await ASYNC_VECTOR_DB_CLIENT.delete_collection(collection_name=f'file-{file.id}')
except Exception:
# Audio file upload pipeline
pass
docs = [
Document(
page_content=form_data.content.replace('<br/>', '\n'),
metadata={
**file.meta,
'name': file.filename,
'created_by': file.user_id,
'file_id': file.id,
'source': file.filename,
},
)
]
text_content = form_data.content
elif form_data.collection_name:
# Check if the file has already been processed and save the content
# Usage: /knowledge/{id}/file/add, /knowledge/{id}/file/update
result = await ASYNC_VECTOR_DB_CLIENT.query(
collection_name=f'file-{file.id}', filter={'file_id': file.id}
)
if result is not None and len(result.ids[0]) > 0:
docs = [
Document(
page_content=result.documents[0][idx],
metadata=result.metadatas[0][idx],
)
for idx, id in enumerate(result.ids[0])
]
else:
docs = [
Document(
page_content=file.data.get('content', ''),
metadata={
**file.meta,
'name': file.filename,
'created_by': file.user_id,
'file_id': file.id,
'source': file.filename,
},
)
]
text_content = file.data.get('content', '')
else:
# Process the file and save the content
# Usage: /files/
file_path = file.path
if file_path:
file_path = await asyncio.to_thread(Storage.get_file, file_path)
loader_config = await get_loader_config()
loader = build_loader_from_config(request, loader_config)
loader.user = user
loader.metadata = {
'file_id': file.id,
'file_name': file.filename,
'file_content_type': file.meta.get('content_type'),
}
docs = await loader.aload(file.filename, file.meta.get('content_type'), file_path)
docs = [
Document(
page_content=doc.page_content,
metadata={
**filter_metadata(doc.metadata),
'name': file.filename,
'created_by': file.user_id,
'file_id': file.id,
'source': file.filename,
},
)
for doc in docs
]
else:
docs = [
Document(
page_content=file.data.get('content', ''),
metadata={
**file.meta,
'name': file.filename,
'created_by': file.user_id,
'file_id': file.id,
'source': file.filename,
},
)
]
text_content = ' '.join([doc.page_content for doc in docs])
log.debug('text_content: %s', text_content)
await Files.update_file_data_by_id(
file.id,
{'content': text_content},
db=db,
)
hash = calculate_sha256_string(text_content)
if config.BYPASS_EMBEDDING_AND_RETRIEVAL:
await Files.update_file_data_by_id(file.id, {'status': 'completed'}, db=db)
await Files.update_file_hash_by_id(file.id, hash, db=db)
await publish_event(
request,
EVENTS.RETRIEVAL_CONTENT_PROCESSED,
actor=user,
subject_id=file.id,
subject_type='file',
data={'collection_name': None, 'filename': file.filename},
)
return {
'status': True,
'collection_name': None,
'filename': file.filename,
'content': text_content,
}
else:
try:
# Commit any pending changes before the slow embedding step.
# Note: file is already a Pydantic model (not ORM), so no expunge needed.
await db.commit()
# External embedding API takes time (5-60s+).
# Subsequent updates use fresh async sessions.
# NOTE: save_docs_to_vector_db is a sync function that
# calls asyncio.run_coroutine_threadsafe(..., main_loop).result()
# which blocks the calling thread. We MUST run it in a
# worker thread to avoid deadlocking the event loop.
result = await run_in_threadpool(
save_docs_to_vector_db,
request,
docs=docs,
collection_name=collection_name,
config=config,
metadata={
'file_id': file.id,
'name': file.filename,
'hash': hash,
},
add=(True if form_data.collection_name else False),
user=user,
)
log.info('added %s items to collection %s', len(docs), collection_name)
if result:
# Fresh session for the final update.
async with get_async_db() as session:
await Files.update_file_metadata_by_id(
file.id,
{
'collection_name': collection_name,
},
db=session,
)
await Files.update_file_data_by_id(
file.id,
{'status': 'completed'},
db=session,
)
await Files.update_file_hash_by_id(file.id, hash, db=session)
await publish_event(
request,
EVENTS.RETRIEVAL_CONTENT_PROCESSED,
actor=user,
subject_id=file.id,
subject_type='file',
data={'collection_name': collection_name, 'filename': file.filename},
)
return {
'status': True,
'collection_name': collection_name,
'filename': file.filename,
'content': text_content,
}
else:
raise Exception('Error saving document to vector database')
except Exception as e:
raise e
except Exception as e:
log.exception(e)
# Fresh session for error status update.
async with get_async_db() as session:
await Files.update_file_data_by_id(
file.id,
{'status': 'failed'},
db=session,
)
# Clear the hash so the file can be re-uploaded after fixing the issue
await Files.update_file_hash_by_id(file.id, None, db=session)
if 'No pandoc was found' in str(e):
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail=ERROR_MESSAGES.PANDOC_NOT_INSTALLED,
)
else:
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail=str(e),
)
else:
raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail=ERROR_MESSAGES.NOT_FOUND)
class ProcessTextForm(BaseModel):
name: str
content: str
collection_name: str | None = None
@router.post('/process/text')
async def process_text(
request: Request,
form_data: ProcessTextForm,
user=Depends(get_verified_user),
):
collection_name = form_data.collection_name
if collection_name is None:
collection_name = calculate_sha256_string(form_data.content)
else:
await _validate_collection_access([collection_name], user, access_type='write')
docs = [
Document(
page_content=form_data.content,
metadata={'name': form_data.name, 'created_by': user.id},
)
]
text_content = form_data.content
log.debug('text_content: %s', text_content)
config = await get_retrieval_config()
result = await run_in_threadpool(save_docs_to_vector_db, request, docs, collection_name, config, user=user)
if result:
await publish_event(
request,
EVENTS.RETRIEVAL_CONTENT_PROCESSED,
actor=user,
subject_id=collection_name,
subject_type='retrieval.collection',
data={'name': form_data.name, 'content_preview': text_content[:300]},
)
return {
'status': True,
'collection_name': collection_name,
'content': text_content,
}
else:
raise HTTPException(
status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
detail=ERROR_MESSAGES.DEFAULT(),
)
@router.post('/process/youtube')
@router.post('/process/web')
async def process_web(
request: Request,
form_data: ProcessUrlForm,
process: bool = Query(True, description='Whether to process and save the content'),
overwrite: bool = Query(True, description='Whether to overwrite existing collection'),
user=Depends(get_verified_user),
):
config = await get_retrieval_config()
try:
content, docs = await get_content_from_url(request, form_data.url)
log.debug('text_content: %s', content)
if process:
collection_name = form_data.collection_name
if not collection_name:
collection_name = calculate_sha256_string(form_data.url)[:63]
else:
await _validate_collection_access([collection_name], user, access_type='write')
if not config.BYPASS_WEB_SEARCH_EMBEDDING_AND_RETRIEVAL:
await run_in_threadpool(
save_docs_to_vector_db,
request,
docs,
collection_name,
config,
overwrite=overwrite,
add=(not overwrite),
user=user,
)
else:
collection_name = None
return {
'status': True,
'collection_name': collection_name,
'filename': form_data.url,
'file': {
'data': {
'content': content,
},
'meta': {
'name': form_data.url,
'source': form_data.url,
},
},
}
else:
return {
'status': True,
'content': content,
}
except HTTPException:
raise
except Exception as e:
log.exception(e)
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail=ERROR_MESSAGES.DEFAULT(e, 'Error querying knowledge base'),
)
async def search_web(request: Request, engine: str, query: str, user=None) -> list[SearchResult]:
"""Dispatch a web search query to the configured engine and return results.
Providers that have been migrated to async (aiohttp) are awaited natively.
Legacy sync providers are offloaded via ``asyncio.to_thread`` to avoid
blocking the event loop.
"""
# TODO: add playwright to search the web
config = await get_retrieval_config()
if engine == 'ollama_cloud':
return await asyncio.to_thread(
search_ollama_cloud,
'https://ollama.com',
config.OLLAMA_CLOUD_WEB_SEARCH_API_KEY,
query,
config.WEB_SEARCH_RESULT_COUNT,
config.WEB_SEARCH_DOMAIN_FILTER_LIST,
)
elif engine == 'perplexity_search':
if config.PERPLEXITY_API_KEY:
return await asyncio.to_thread(
search_perplexity_search,
config.PERPLEXITY_API_KEY,
query,
config.WEB_SEARCH_RESULT_COUNT,
config.WEB_SEARCH_DOMAIN_FILTER_LIST,
config.PERPLEXITY_SEARCH_API_URL,
user,
)
else:
raise Exception('No PERPLEXITY_API_KEY found in environment variables')
elif engine == 'searxng':
if config.SEARXNG_QUERY_URL:
searxng_kwargs = {'language': config.SEARXNG_LANGUAGE}
return await search_searxng(
config.SEARXNG_QUERY_URL,
query,
config.WEB_SEARCH_RESULT_COUNT,
config.WEB_SEARCH_DOMAIN_FILTER_LIST,
**searxng_kwargs,
)
else:
raise Exception('No SEARXNG_QUERY_URL found in environment variables')
elif engine == 'openserp':
if config.OPENSERP_BASE_URL:
return await search_openserp(
config.OPENSERP_BASE_URL,
query,
config.WEB_SEARCH_RESULT_COUNT,
config.WEB_SEARCH_DOMAIN_FILTER_LIST,
)
else:
raise Exception('No OPENSERP_BASE_URL found in environment variables')
elif engine == 'yacy':
if config.YACY_QUERY_URL:
return await asyncio.to_thread(
search_yacy,
config.YACY_QUERY_URL,
config.YACY_USERNAME,
config.YACY_PASSWORD,
query,
config.WEB_SEARCH_RESULT_COUNT,
config.WEB_SEARCH_DOMAIN_FILTER_LIST,
)
else:
raise Exception('No YACY_QUERY_URL found in environment variables')
elif engine == 'google_pse':
if config.GOOGLE_PSE_API_KEY and config.GOOGLE_PSE_ENGINE_ID:
return await search_google_pse(
config.GOOGLE_PSE_API_KEY,
config.GOOGLE_PSE_ENGINE_ID,
query,
config.WEB_SEARCH_RESULT_COUNT,
config.WEB_SEARCH_DOMAIN_FILTER_LIST,
referer=config.WEBUI_URL,
)
else:
raise Exception('No GOOGLE_PSE_API_KEY or GOOGLE_PSE_ENGINE_ID found in environment variables')
elif engine == 'brave':
if config.BRAVE_SEARCH_API_KEY:
return await search_brave(
config.BRAVE_SEARCH_API_KEY,
query,
config.WEB_SEARCH_RESULT_COUNT,
config.WEB_SEARCH_DOMAIN_FILTER_LIST,
)
else:
raise Exception('No BRAVE_SEARCH_API_KEY found in environment variables')
elif engine == 'brave_llm_context':
if config.BRAVE_SEARCH_API_KEY:
return await asyncio.to_thread(
search_brave_llm_context,
config.BRAVE_SEARCH_API_KEY,
query,
config.WEB_SEARCH_RESULT_COUNT,
config.WEB_SEARCH_DOMAIN_FILTER_LIST,
config.BRAVE_SEARCH_CONTEXT_TOKENS,
)
else:
raise Exception('No BRAVE_SEARCH_API_KEY found in environment variables')
elif engine == 'kagi':
if config.KAGI_SEARCH_API_KEY:
return await asyncio.to_thread(
search_kagi,
config.KAGI_SEARCH_API_KEY,
query,
config.WEB_SEARCH_RESULT_COUNT,
config.WEB_SEARCH_DOMAIN_FILTER_LIST,
)
else:
raise Exception('No KAGI_SEARCH_API_KEY found in environment variables')
elif engine == 'mojeek':
if config.MOJEEK_SEARCH_API_KEY:
return await asyncio.to_thread(
search_mojeek,
config.MOJEEK_SEARCH_API_KEY,
query,
config.WEB_SEARCH_RESULT_COUNT,
config.WEB_SEARCH_DOMAIN_FILTER_LIST,
)
else:
raise Exception('No MOJEEK_SEARCH_API_KEY found in environment variables')
elif engine == 'bocha':
if config.BOCHA_SEARCH_API_KEY:
return await asyncio.to_thread(
search_bocha,
config.BOCHA_SEARCH_API_KEY,
query,
config.WEB_SEARCH_RESULT_COUNT,
config.WEB_SEARCH_DOMAIN_FILTER_LIST,
)
else:
raise Exception('No BOCHA_SEARCH_API_KEY found in environment variables')
elif engine == 'serpstack':
if config.SERPSTACK_API_KEY:
return await search_serpstack(
config.SERPSTACK_API_KEY,
query,
config.WEB_SEARCH_RESULT_COUNT,
config.WEB_SEARCH_DOMAIN_FILTER_LIST,
https_enabled=config.SERPSTACK_HTTPS,
)
else:
raise Exception('No SERPSTACK_API_KEY found in environment variables')
elif engine == 'serper':
if config.SERPER_API_KEY:
return await search_serper(
config.SERPER_API_KEY,
query,
config.WEB_SEARCH_RESULT_COUNT,
config.WEB_SEARCH_DOMAIN_FILTER_LIST,
)
else:
raise Exception('No SERPER_API_KEY found in environment variables')
elif engine == 'serphouse':
if config.SERPHOUSE_API_KEY:
return await search_serphouse(
config.SERPHOUSE_API_KEY,
config.SERPHOUSE_DOMAIN,
query,
config.WEB_SEARCH_RESULT_COUNT,
config.WEB_SEARCH_DOMAIN_FILTER_LIST,
)
else:
raise Exception('No SERPHOUSE_API_KEY found in environment variables')
elif engine == 'serply':
if config.SERPLY_API_KEY:
return await asyncio.to_thread(
search_serply,
config.SERPLY_API_KEY,
query,
config.WEB_SEARCH_RESULT_COUNT,
filter_list=config.WEB_SEARCH_DOMAIN_FILTER_LIST,
)
else:
raise Exception('No SERPLY_API_KEY found in environment variables')
elif engine == 'duckduckgo':
return await asyncio.to_thread(
search_duckduckgo,
query,
config.WEB_SEARCH_RESULT_COUNT,
config.WEB_SEARCH_DOMAIN_FILTER_LIST,
concurrent_requests=config.WEB_SEARCH_CONCURRENT_REQUESTS,
backend=config.DDGS_BACKEND,
)
elif engine == 'tavily':
if config.TAVILY_API_KEY:
return await asyncio.to_thread(
search_tavily,
config.TAVILY_API_KEY,
query,
config.WEB_SEARCH_RESULT_COUNT,
config.WEB_SEARCH_DOMAIN_FILTER_LIST,
)
else:
raise Exception('No TAVILY_API_KEY found in environment variables')
elif engine == 'exa':
if config.EXA_API_KEY:
return await asyncio.to_thread(
search_exa,
config.EXA_API_KEY,
query,
config.WEB_SEARCH_RESULT_COUNT,
config.WEB_SEARCH_DOMAIN_FILTER_LIST,
)
else:
raise Exception('No EXA_API_KEY found in environment variables')
elif engine == 'searchapi':
if config.SEARCHAPI_API_KEY:
return await asyncio.to_thread(
search_searchapi,
config.SEARCHAPI_API_KEY,
config.SEARCHAPI_ENGINE,
query,
config.WEB_SEARCH_RESULT_COUNT,
config.WEB_SEARCH_DOMAIN_FILTER_LIST,
)
else:
raise Exception('No SEARCHAPI_API_KEY found in environment variables')
elif engine == 'serpapi':
if config.SERPAPI_API_KEY:
return await asyncio.to_thread(
search_serpapi,
config.SERPAPI_API_KEY,
config.SERPAPI_ENGINE,
query,
config.WEB_SEARCH_RESULT_COUNT,
config.WEB_SEARCH_DOMAIN_FILTER_LIST,
)
else:
raise Exception('No SERPAPI_API_KEY found in environment variables')
elif engine == 'jina':
return await asyncio.to_thread(
search_jina,
config.JINA_API_KEY,
query,
config.WEB_SEARCH_RESULT_COUNT,
config.JINA_API_BASE_URL,
)
elif engine == 'bing':
return await asyncio.to_thread(
search_bing,
config.BING_SEARCH_V7_SUBSCRIPTION_KEY,
config.BING_SEARCH_V7_ENDPOINT,
str(DEFAULT_LOCALE),
query,
config.WEB_SEARCH_RESULT_COUNT,
config.WEB_SEARCH_DOMAIN_FILTER_LIST,
)
elif engine == 'azure':
if config.AZURE_AI_SEARCH_API_KEY and config.AZURE_AI_SEARCH_ENDPOINT and config.AZURE_AI_SEARCH_INDEX_NAME:
return await asyncio.to_thread(
search_azure,
config.AZURE_AI_SEARCH_API_KEY,
config.AZURE_AI_SEARCH_ENDPOINT,
config.AZURE_AI_SEARCH_INDEX_NAME,
query,
config.WEB_SEARCH_RESULT_COUNT,
config.WEB_SEARCH_DOMAIN_FILTER_LIST,
)
else:
raise Exception(
'AZURE_AI_SEARCH_API_KEY, AZURE_AI_SEARCH_ENDPOINT, and AZURE_AI_SEARCH_INDEX_NAME are required for Azure AI Search'
)
elif engine == 'perplexity':
return await asyncio.to_thread(
search_perplexity,
config.PERPLEXITY_API_KEY,
query,
config.WEB_SEARCH_RESULT_COUNT,
config.WEB_SEARCH_DOMAIN_FILTER_LIST,
model=config.PERPLEXITY_MODEL,
search_context_usage=config.PERPLEXITY_SEARCH_CONTEXT_USAGE,
)
elif engine == 'microsoft_web_iq':
if config.MICROSOFT_WEB_IQ_API_KEY:
return await asyncio.to_thread(
search_microsoft_web_iq,
config.MICROSOFT_WEB_IQ_API_BASE_URL,
config.MICROSOFT_WEB_IQ_API_KEY,
query,
config.WEB_SEARCH_RESULT_COUNT,
config.WEB_SEARCH_DOMAIN_FILTER_LIST,
config.MICROSOFT_WEB_IQ_LANGUAGE,
user,
)
else:
raise Exception('No MICROSOFT_WEB_IQ_API_KEY found in environment variables')
elif engine == 'sougou':
if config.SOUGOU_API_SID and config.SOUGOU_API_SK:
return await asyncio.to_thread(
search_sougou,
config.SOUGOU_API_SID,
config.SOUGOU_API_SK,
query,
config.WEB_SEARCH_RESULT_COUNT,
config.WEB_SEARCH_DOMAIN_FILTER_LIST,
)
else:
raise Exception('No SOUGOU_API_SID or SOUGOU_API_SK found in environment variables')
elif engine == 'firecrawl':
return await asyncio.to_thread(
search_firecrawl,
config.FIRECRAWL_API_BASE_URL,
config.FIRECRAWL_API_KEY,
query,
config.WEB_SEARCH_RESULT_COUNT,
config.WEB_SEARCH_DOMAIN_FILTER_LIST,
)
elif engine == 'external':
return await asyncio.to_thread(
search_external,
request,
config.EXTERNAL_WEB_SEARCH_URL,
config.EXTERNAL_WEB_SEARCH_API_KEY,
query,
config.WEB_SEARCH_RESULT_COUNT,
config.WEB_SEARCH_DOMAIN_FILTER_LIST,
user=user,
)
elif engine == 'yandex':
return await asyncio.to_thread(
search_yandex,
request,
config.YANDEX_WEB_SEARCH_URL,
config.YANDEX_WEB_SEARCH_API_KEY,
config.YANDEX_WEB_SEARCH_CONFIG,
query,
config.WEB_SEARCH_RESULT_COUNT,
config.WEB_SEARCH_DOMAIN_FILTER_LIST,
user=user,
)
elif engine == 'youcom':
return await asyncio.to_thread(
search_youcom,
config.YOUCOM_API_KEY,
query,
config.WEB_SEARCH_RESULT_COUNT,
config.WEB_SEARCH_DOMAIN_FILTER_LIST,
)
elif engine == 'linkup':
if config.LINKUP_API_KEY:
return await asyncio.to_thread(
search_linkup,
api_key=config.LINKUP_API_KEY,
query=query,
count=config.WEB_SEARCH_RESULT_COUNT,
filter_list=config.WEB_SEARCH_DOMAIN_FILTER_LIST,
params=config.LINKUP_SEARCH_PARAMS,
)
else:
raise Exception('No LINKUP_API_KEY found in environment variables')
else:
raise Exception('No search engine API key found in environment variables')
@router.post('/process/web/search')
async def process_web_search(request: Request, form_data: SearchForm, user=Depends(get_verified_user)):
config = await get_retrieval_config()
if not config.ENABLE_WEB_SEARCH:
raise HTTPException(
status_code=status.HTTP_403_FORBIDDEN,
detail=ERROR_MESSAGES.ACCESS_PROHIBITED,
)
if user.role != 'admin' and not await has_permission(user.id, 'features.web_search', config.USER_PERMISSIONS):
raise HTTPException(
status_code=status.HTTP_403_FORBIDDEN,
detail=ERROR_MESSAGES.ACCESS_PROHIBITED,
)
urls = []
result_items = []
try:
logging.debug('trying to web search with %s', (config.WEB_SEARCH_ENGINE, form_data.queries))
# Use semaphore to limit concurrent requests based on WEB_SEARCH_CONCURRENT_REQUESTS
# 0 or None = unlimited (previous behavior), positive number = limited concurrency
# Set to 1 for sequential execution (rate-limited APIs like Brave free tier)
concurrent_limit = config.WEB_SEARCH_CONCURRENT_REQUESTS
if concurrent_limit:
# Limited concurrency with semaphore
semaphore = asyncio.Semaphore(concurrent_limit)
async def search_query_with_semaphore(query):
async with semaphore:
return await search_web(
request,
config.WEB_SEARCH_ENGINE,
query,
user,
)
search_tasks = [search_query_with_semaphore(query) for query in form_data.queries]
else:
# Unlimited parallel execution
search_tasks = [
search_web(
request,
config.WEB_SEARCH_ENGINE,
query,
user,
)
for query in form_data.queries
]
search_results = await asyncio.gather(*search_tasks)
for result in search_results:
if result:
for item in result:
if item and item.link:
result_items.append(item)
urls.append(item.link)
urls = list(dict.fromkeys(urls))
log.debug('urls: %s', urls)
except Exception as e:
log.exception('Web search failed')
raise HTTPException(status.HTTP_400_BAD_REQUEST, detail=ERROR_MESSAGES.WEB_SEARCH_ERROR(e))
if len(urls) == 0:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail=ERROR_MESSAGES.DEFAULT('No results found from web search'),
)
try:
if config.BYPASS_WEB_SEARCH_WEB_LOADER:
search_results = [item for result in search_results for item in result if result]
docs = [
Document(
page_content=result.snippet,
metadata={
'source': result.link,
'title': result.title,
'snippet': result.snippet,
'link': result.link,
},
)
for result in search_results
if hasattr(result, 'snippet') and result.snippet is not None
]
else:
loader_config = await get_loader_config()
loader = get_web_loader(
urls,
verify_ssl=loader_config.get('web_loader_ssl_verification'),
requests_per_second=loader_config.get('web_loader_concurrent_requests'),
trust_env=loader_config.get('web_search_trust_env'),
loader_config=loader_config,
)
docs = await loader.aload()
urls = [
doc.metadata.get('source') for doc in docs if doc.metadata.get('source')
] # only keep the urls returned by the loader
url_set = set(urls)
result_items = [
dict(item) for item in result_items if item.link in url_set
] # only keep the search results that have been loaded
if config.BYPASS_WEB_SEARCH_EMBEDDING_AND_RETRIEVAL:
return {
'status': True,
'collection_name': None,
'filenames': urls,
'items': result_items,
'docs': [
{
'content': doc.page_content,
'metadata': doc.metadata,
}
for doc in docs
],
'loaded_count': len(docs),
}
else:
# Create a single collection for all documents
# Bind the ephemeral collection to its owner so filter_accessible_collections can scope it per-user.
collection_name = f'web-search-{user.id}-{calculate_sha256_string("-".join(form_data.queries))}'[:63]
try:
await run_in_threadpool(
save_docs_to_vector_db,
request,
docs,
collection_name,
config,
overwrite=True,
user=user,
)
except Exception as e:
# Surface the failure instead of returning an unusable collection
log.exception(f'Error saving web search results to vector DB: {e}')
raise HTTPException(
status.HTTP_500_INTERNAL_SERVER_ERROR,
detail='Failed to embed and store the retrieved web pages. Check the embedding configuration in Admin Settings > Documents.',
)
return {
'status': True,
'collection_names': [collection_name],
'items': result_items,
'filenames': urls,
'loaded_count': len(docs),
}
except HTTPException:
raise
except Exception as e:
log.exception('Web search content loading failed')
raise HTTPException(
status.HTTP_400_BAD_REQUEST,
detail=ERROR_MESSAGES.DEFAULT(e, ERROR_MESSAGES.WEB_SEARCH_ERROR()),
)
async def _validate_collection_access(collection_names: list[str], user, access_type: str = 'read') -> None:
"""
Raise 403 if the user lacks access to any of the requested collections.
Delegates to the shared filter_accessible_collections utility so the
access rules stay in one place.
"""
requested = set(collection_names)
allowed = await filter_accessible_collections(requested, user, access_type=access_type)
denied = requested - allowed
if denied:
raise HTTPException(
status_code=status.HTTP_403_FORBIDDEN,
detail=ERROR_MESSAGES.ACCESS_PROHIBITED,
)
class QueryDocForm(BaseModel):
collection_name: str
query: str
k: int | None = None
k_reranker: int | None = None
r: float | None = None
hybrid: bool | None = None
hybrid_bm25_weight: float | None = None
@router.post('/query/doc')
async def query_doc_handler(
request: Request,
form_data: QueryDocForm,
user=Depends(get_verified_user),
):
config = await get_retrieval_config()
await _validate_collection_access([form_data.collection_name], user)
try:
if config.ENABLE_RAG_HYBRID_SEARCH and (form_data.hybrid is None or form_data.hybrid):
return await query_doc_with_hybrid_search(
collection_name=form_data.collection_name,
collection_result=None,
query=form_data.query,
embedding_function=lambda query, prefix: request.app.state.EMBEDDING_FUNCTION(
query, prefix=prefix, user=user
),
k=form_data.k if form_data.k else config.TOP_K,
reranking_function=(
(lambda query, documents: request.app.state.RERANKING_FUNCTION(query, documents, user=user))
if request.app.state.RERANKING_FUNCTION
else None
),
k_reranker=form_data.k_reranker or config.TOP_K_RERANKER,
r=(form_data.r if form_data.r else config.RELEVANCE_THRESHOLD),
hybrid_bm25_weight=(
form_data.hybrid_bm25_weight
if form_data.hybrid_bm25_weight is not None
else config.HYBRID_BM25_WEIGHT
),
)
else:
query_embedding = await request.app.state.EMBEDDING_FUNCTION(
form_data.query, prefix=RAG_EMBEDDING_QUERY_PREFIX, user=user
)
# query_doc wraps a blocking VECTOR_DB_CLIENT.search call;
# offload so the request's event loop stays responsive.
return await asyncio.to_thread(
query_doc,
collection_name=form_data.collection_name,
query_embedding=query_embedding,
k=form_data.k if form_data.k else config.TOP_K,
user=user,
)
except HTTPException:
raise
except Exception as e:
log.exception(e)
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail=ERROR_MESSAGES.DEFAULT(e, 'Error querying knowledge base'),
)
class QueryCollectionsForm(BaseModel):
collection_names: list[str]
query: str
k: int | None = None
k_reranker: int | None = None
r: float | None = None
hybrid: bool | None = None
hybrid_bm25_weight: float | None = None
enable_enriched_texts: bool | None = None
@router.post('/query/collection')
async def query_collection_handler(
request: Request,
form_data: QueryCollectionsForm,
user=Depends(get_verified_user),
):
config = await get_retrieval_config()
await _validate_collection_access(form_data.collection_names, user)
try:
if config.ENABLE_RAG_HYBRID_SEARCH and (form_data.hybrid is None or form_data.hybrid):
return await query_collection_with_hybrid_search(
collection_names=form_data.collection_names,
queries=[form_data.query],
embedding_function=lambda query, prefix: request.app.state.EMBEDDING_FUNCTION(
query, prefix=prefix, user=user
),
k=form_data.k if form_data.k else config.TOP_K,
reranking_function=(
(lambda query, documents: request.app.state.RERANKING_FUNCTION(query, documents, user=user))
if request.app.state.RERANKING_FUNCTION
else None
),
k_reranker=form_data.k_reranker or config.TOP_K_RERANKER,
r=(form_data.r if form_data.r else config.RELEVANCE_THRESHOLD),
hybrid_bm25_weight=(
form_data.hybrid_bm25_weight
if form_data.hybrid_bm25_weight is not None
else config.HYBRID_BM25_WEIGHT
),
enable_enriched_texts=(
form_data.enable_enriched_texts
if form_data.enable_enriched_texts is not None
else config.ENABLE_RAG_HYBRID_SEARCH_ENRICHED_TEXTS
),
)
else:
return await query_collection(
request,
collection_names=form_data.collection_names,
queries=[form_data.query],
embedding_function=lambda query, prefix: request.app.state.EMBEDDING_FUNCTION(
query, prefix=prefix, user=user
),
k=form_data.k if form_data.k else config.TOP_K,
)
except HTTPException:
raise
except Exception as e:
log.exception(e)
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail=ERROR_MESSAGES.DEFAULT(e, 'Error querying knowledge base'),
)
####################################
#
# Vector DB operations
#
####################################
class DeleteForm(BaseModel):
collection_name: str
file_id: str
@router.post('/delete')
async def delete_entries_from_collection(
request: Request,
form_data: DeleteForm,
user=Depends(get_admin_user),
db: AsyncSession = Depends(get_async_session),
):
try:
if await ASYNC_VECTOR_DB_CLIENT.has_collection(collection_name=form_data.collection_name):
file = await Files.get_file_by_id(form_data.file_id, db=db)
if not file:
raise HTTPException(
status_code=status.HTTP_404_NOT_FOUND,
detail=ERROR_MESSAGES.NOT_FOUND,
)
hash = file.hash
# Refuse to issue a `filter={'hash': None}` query — the
# match semantics of a null filter value are
# backend-dependent (some backends ignore the key, some
# match every row whose metadata lacks `hash`) and risk
# deleting unrelated entries. Files without a hash are
# typically unprocessed / failed / legacy records that
# can't be targeted by hash anyway.
if hash is None:
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail=ERROR_MESSAGES.DEFAULT('File has no hash; cannot delete vector entries by hash.'),
)
# Pre-existing bug: this used `metadata=` which is not a
# parameter on `VectorDBBase.delete` nor on any backend
# implementation, so the call always raised TypeError that
# was silently swallowed by the surrounding `except
# Exception` and the endpoint reported `{'status': False}`
# for every request. Use `filter` to actually do what the
# endpoint name promises.
await ASYNC_VECTOR_DB_CLIENT.delete(
collection_name=form_data.collection_name,
filter={'hash': hash},
)
await publish_event(
request,
EVENTS.RETRIEVAL_COLLECTION_DELETED,
actor=user,
subject_id=form_data.collection_name,
data={'file_id': form_data.file_id},
)
return {'status': True}
else:
return {'status': False}
except HTTPException:
# Caller-meaningful errors (404/400 above) must not be
# swallowed and re-shaped as `{'status': False}`.
raise
except Exception as e:
log.exception(e)
return {'status': False}
@router.post('/reset/db')
async def reset_vector_db(
request: Request,
user=Depends(get_admin_user),
db: AsyncSession = Depends(get_async_session),
):
await ASYNC_VECTOR_DB_CLIENT.reset()
await Knowledges.delete_all_knowledge(db=db)
await publish_event(
request,
EVENTS.RETRIEVAL_VECTOR_DB_RESET,
actor=user,
subject_id='default',
)
@router.post('/reset/uploads')
async def reset_upload_dir(request: Request, user=Depends(get_admin_user)) -> bool:
folder = f'{UPLOAD_DIR}'
try:
# Check if the directory exists
if await asyncio.to_thread(os.path.exists, folder):
# Iterate over all the files and directories in the specified directory
for filename in await asyncio.to_thread(os.listdir, folder):
file_path = os.path.join(folder, filename)
try:
if await asyncio.to_thread(os.path.isfile, file_path) or await asyncio.to_thread(
os.path.islink, file_path
):
await asyncio.to_thread(os.unlink, file_path) # Remove the file or link
elif await asyncio.to_thread(os.path.isdir, file_path):
await asyncio.to_thread(shutil.rmtree, file_path) # Remove the directory
except Exception as e:
log.exception(f'Failed to delete {file_path}. Reason: {e}')
else:
log.warning(f'The directory {folder} does not exist')
except Exception as e:
log.exception(f'Failed to process the directory {folder}. Reason: {e}')
await publish_event(
request,
EVENTS.RETRIEVAL_UPLOADS_RESET,
actor=user,
subject_id='all',
subject_type='file.uploads',
)
return True
if ENV == 'dev':
@router.get('/ef/{text}')
async def get_embeddings(request: Request, text: str | None = 'Hello World!'):
return {'result': await request.app.state.EMBEDDING_FUNCTION(text, prefix=RAG_EMBEDDING_QUERY_PREFIX)}
class BatchProcessFilesForm(BaseModel):
files: list[FileModel]
collection_name: str
class BatchProcessFilesResult(BaseModel):
file_id: str
status: str
error: str | None = None
class BatchProcessFilesResponse(BaseModel):
results: list[BatchProcessFilesResult]
errors: list[BatchProcessFilesResult]
@router.post('/process/files/batch')
async def process_files_batch(
request: Request,
form_data: BatchProcessFilesForm,
user=Depends(get_verified_user),
db=None,
) -> BatchProcessFilesResponse:
"""
Process a batch of files and save them to the vector database.
NOTE: We intentionally do NOT use Depends(get_async_session) here.
The save_docs_to_vector_db() call makes external embedding API calls which
can take 5-60+ seconds for batch operations. Database operations after
embedding (Files.update_file_by_id) manage their own short-lived sessions.
"""
config = await get_retrieval_config()
collection_name = form_data.collection_name
if collection_name:
await _validate_collection_access([collection_name], user, access_type='write')
file_results: list[BatchProcessFilesResult] = []
file_errors: list[BatchProcessFilesResult] = []
file_updates: list[FileUpdateForm] = []
# Prepare all documents first
all_docs: list[Document] = []
for file in form_data.files:
try:
# Ownership check: verify the requesting user owns the file or is an admin
db_file = await Files.get_file_by_id(file.id, db=db)
if not db_file:
file_errors.append(
BatchProcessFilesResult(
file_id=file.id,
status='failed',
error='File not found',
)
)
continue
if db_file.user_id != user.id and user.role != 'admin':
file_errors.append(
BatchProcessFilesResult(
file_id=file.id,
status='failed',
error='Permission denied: not file owner',
)
)
continue
text_content = file.data.get('content', '')
docs: list[Document] = [
Document(
page_content=text_content.replace('<br/>', '\n'),
metadata={
**file.meta,
'name': file.filename,
'created_by': file.user_id,
'file_id': file.id,
'source': file.filename,
},
)
]
all_docs.extend(docs)
file_updates.append(
FileUpdateForm(
hash=calculate_sha256_string(text_content),
data={'content': text_content},
)
)
file_results.append(BatchProcessFilesResult(file_id=file.id, status='prepared'))
except Exception as e:
log.error(f'process_files_batch: Error processing file {file.id}: {str(e)}')
file_errors.append(BatchProcessFilesResult(file_id=file.id, status='failed', error=str(e)))
# Save all documents in one batch
if all_docs:
try:
await run_in_threadpool(
save_docs_to_vector_db,
request,
all_docs,
collection_name,
config,
add=True,
user=user,
)
# Update all files with collection name
for file_update, file_result in zip(file_updates, file_results):
await Files.update_file_by_id(id=file_result.file_id, form_data=file_update, db=db)
file_result.status = 'completed'
except Exception as e:
log.error(f'process_files_batch: Error saving documents to vector DB: {str(e)}')
for file_result in file_results:
file_result.status = 'failed'
file_errors.append(BatchProcessFilesResult(file_id=file_result.file_id, status='failed', error=str(e)))
response = BatchProcessFilesResponse(results=file_results, errors=file_errors)
await publish_event(
request,
EVENTS.RETRIEVAL_CONTENT_PROCESSED,
actor=user,
subject_id=collection_name,
subject_type='retrieval.collection',
data={
'count': len([item for item in file_results if item.status == 'completed']),
'errors': len(file_errors),
},
)
return response
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