import json
import logging
import mimetypes
import os
import shutil
import asyncio

import re
import uuid
from datetime import datetime
from pathlib import Path
from typing import Iterator, List, Optional, Sequence, Union

from fastapi import (
    Depends,
    FastAPI,
    Query,
    File,
    Form,
    HTTPException,
    UploadFile,
    Request,
    status,
    APIRouter,
)
from fastapi.middleware.cors import CORSMiddleware
from fastapi.concurrency import run_in_threadpool
from pydantic import BaseModel
import tiktoken


from langchain_text_splitters import (
    RecursiveCharacterTextSplitter,
    TokenTextSplitter,
    MarkdownHeaderTextSplitter,
)
from langchain_core.documents import Document

from open_webui.models.files import FileModel, FileUpdateForm, Files
from open_webui.models.knowledge import Knowledges
from open_webui.storage.provider import Storage
from open_webui.internal.db import get_session
from sqlalchemy.orm import Session


from open_webui.retrieval.vector.factory import VECTOR_DB_CLIENT

# Document loaders
from open_webui.retrieval.loaders.main import Loader
from open_webui.retrieval.loaders.youtube import YoutubeLoader

# Web search engines
from open_webui.retrieval.web.main import SearchResult
from open_webui.retrieval.web.utils import get_web_loader
from open_webui.retrieval.web.ollama import search_ollama_cloud
from open_webui.retrieval.web.perplexity_search import search_perplexity_search
from open_webui.retrieval.web.brave import search_brave
from open_webui.retrieval.web.kagi import search_kagi
from open_webui.retrieval.web.mojeek import search_mojeek
from open_webui.retrieval.web.bocha import search_bocha
from open_webui.retrieval.web.duckduckgo import search_duckduckgo
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.searchapi import search_searchapi
from open_webui.retrieval.web.serpapi import search_serpapi
from open_webui.retrieval.web.searxng import search_searxng
from open_webui.retrieval.web.yacy import search_yacy
from open_webui.retrieval.web.serper import search_serper
from open_webui.retrieval.web.serply import search_serply
from open_webui.retrieval.web.serpstack import search_serpstack
from open_webui.retrieval.web.tavily import search_tavily
from open_webui.retrieval.web.bing import search_bing
from open_webui.retrieval.web.azure import search_azure
from open_webui.retrieval.web.exa import search_exa
from open_webui.retrieval.web.perplexity import search_perplexity
from open_webui.retrieval.web.sougou import search_sougou
from open_webui.retrieval.web.firecrawl import search_firecrawl
from open_webui.retrieval.web.external import search_external

from open_webui.retrieval.utils import (
    get_content_from_url,
    get_embedding_function,
    get_reranking_function,
    get_model_path,
    query_collection,
    query_collection_with_hybrid_search,
    query_doc,
    query_doc_with_hybrid_search,
)
from open_webui.retrieval.vector.utils import filter_metadata
from open_webui.utils.misc import (
    calculate_sha256_string,
    sanitize_text_for_db,
)
from open_webui.utils.auth import get_admin_user, get_verified_user
from open_webui.utils.access_control import has_permission

from open_webui.config import (
    ENV,
    RAG_EMBEDDING_MODEL_AUTO_UPDATE,
    RAG_EMBEDDING_MODEL_TRUST_REMOTE_CODE,
    RAG_RERANKING_MODEL_AUTO_UPDATE,
    RAG_RERANKING_MODEL_TRUST_REMOTE_CODE,
    UPLOAD_DIR,
    DEFAULT_LOCALE,
    RAG_EMBEDDING_CONTENT_PREFIX,
    RAG_EMBEDDING_QUERY_PREFIX,
)
from open_webui.env import (
    DEVICE_TYPE,
    DOCKER,
    SENTENCE_TRANSFORMERS_BACKEND,
    SENTENCE_TRANSFORMERS_MODEL_KWARGS,
    SENTENCE_TRANSFORMERS_CROSS_ENCODER_BACKEND,
    SENTENCE_TRANSFORMERS_CROSS_ENCODER_MODEL_KWARGS,
    SENTENCE_TRANSFORMERS_CROSS_ENCODER_SIGMOID_ACTIVATION_FUNCTION,
)

from open_webui.constants import ERROR_MESSAGES

log = logging.getLogger(__name__)

##########################################
#
# Utility functions
#
##########################################


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.debug(f"Error loading SentenceTransformer: {e}")

    return ef


def get_rf(
    engine: str = "",
    reranking_model: Optional[str] = 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))
        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))
            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("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(
                                    f"Missing pad_token_id detected; set to eos_token_id={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()


class CollectionNameForm(BaseModel):
    collection_name: Optional[str] = None


class ProcessUrlForm(CollectionNameForm):
    url: str


class SearchForm(BaseModel):
    queries: List[str]


@router.get("/")
async def get_status(request: Request):
    return {
        "status": True,
        "CHUNK_SIZE": request.app.state.config.CHUNK_SIZE,
        "CHUNK_OVERLAP": request.app.state.config.CHUNK_OVERLAP,
        "RAG_TEMPLATE": request.app.state.config.RAG_TEMPLATE,
        "RAG_EMBEDDING_ENGINE": request.app.state.config.RAG_EMBEDDING_ENGINE,
        "RAG_EMBEDDING_MODEL": request.app.state.config.RAG_EMBEDDING_MODEL,
        "RAG_RERANKING_MODEL": request.app.state.config.RAG_RERANKING_MODEL,
        "RAG_EMBEDDING_BATCH_SIZE": request.app.state.config.RAG_EMBEDDING_BATCH_SIZE,
        "ENABLE_ASYNC_EMBEDDING": request.app.state.config.ENABLE_ASYNC_EMBEDDING,
    }


@router.get("/embedding")
async def get_embedding_config(request: Request, user=Depends(get_admin_user)):
    return {
        "status": True,
        "RAG_EMBEDDING_ENGINE": request.app.state.config.RAG_EMBEDDING_ENGINE,
        "RAG_EMBEDDING_MODEL": request.app.state.config.RAG_EMBEDDING_MODEL,
        "RAG_EMBEDDING_BATCH_SIZE": request.app.state.config.RAG_EMBEDDING_BATCH_SIZE,
        "ENABLE_ASYNC_EMBEDDING": request.app.state.config.ENABLE_ASYNC_EMBEDDING,
        "openai_config": {
            "url": request.app.state.config.RAG_OPENAI_API_BASE_URL,
            "key": request.app.state.config.RAG_OPENAI_API_KEY,
        },
        "ollama_config": {
            "url": request.app.state.config.RAG_OLLAMA_BASE_URL,
            "key": request.app.state.config.RAG_OLLAMA_API_KEY,
        },
        "azure_openai_config": {
            "url": request.app.state.config.RAG_AZURE_OPENAI_BASE_URL,
            "key": request.app.state.config.RAG_AZURE_OPENAI_API_KEY,
            "version": request.app.state.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: Optional[OpenAIConfigForm] = None
    ollama_config: Optional[OllamaConfigForm] = None
    azure_openai_config: Optional[AzureOpenAIConfigForm] = None
    RAG_EMBEDDING_ENGINE: str
    RAG_EMBEDDING_MODEL: str
    RAG_EMBEDDING_BATCH_SIZE: Optional[int] = 1
    ENABLE_ASYNC_EMBEDDING: Optional[bool] = True


def unload_embedding_model(request: Request):
    if request.app.state.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)
):
    log.info(
        f"Updating embedding model: {request.app.state.config.RAG_EMBEDDING_MODEL} to {form_data.RAG_EMBEDDING_MODEL}"
    )
    unload_embedding_model(request)
    try:
        request.app.state.config.RAG_EMBEDDING_ENGINE = form_data.RAG_EMBEDDING_ENGINE
        request.app.state.config.RAG_EMBEDDING_MODEL = form_data.RAG_EMBEDDING_MODEL
        request.app.state.config.RAG_EMBEDDING_BATCH_SIZE = (
            form_data.RAG_EMBEDDING_BATCH_SIZE
        )
        request.app.state.config.ENABLE_ASYNC_EMBEDDING = (
            form_data.ENABLE_ASYNC_EMBEDDING
        )

        if request.app.state.config.RAG_EMBEDDING_ENGINE in [
            "ollama",
            "openai",
            "azure_openai",
        ]:
            if form_data.openai_config is not None:
                request.app.state.config.RAG_OPENAI_API_BASE_URL = (
                    form_data.openai_config.url
                )
                request.app.state.config.RAG_OPENAI_API_KEY = (
                    form_data.openai_config.key
                )

            if form_data.ollama_config is not None:
                request.app.state.config.RAG_OLLAMA_BASE_URL = (
                    form_data.ollama_config.url
                )
                request.app.state.config.RAG_OLLAMA_API_KEY = (
                    form_data.ollama_config.key
                )

            if form_data.azure_openai_config is not None:
                request.app.state.config.RAG_AZURE_OPENAI_BASE_URL = (
                    form_data.azure_openai_config.url
                )
                request.app.state.config.RAG_AZURE_OPENAI_API_KEY = (
                    form_data.azure_openai_config.key
                )
                request.app.state.config.RAG_AZURE_OPENAI_API_VERSION = (
                    form_data.azure_openai_config.version
                )

        request.app.state.ef = get_ef(
            request.app.state.config.RAG_EMBEDDING_ENGINE,
            request.app.state.config.RAG_EMBEDDING_MODEL,
        )

        request.app.state.EMBEDDING_FUNCTION = get_embedding_function(
            request.app.state.config.RAG_EMBEDDING_ENGINE,
            request.app.state.config.RAG_EMBEDDING_MODEL,
            request.app.state.ef,
            (
                request.app.state.config.RAG_OPENAI_API_BASE_URL
                if request.app.state.config.RAG_EMBEDDING_ENGINE == "openai"
                else (
                    request.app.state.config.RAG_OLLAMA_BASE_URL
                    if request.app.state.config.RAG_EMBEDDING_ENGINE == "ollama"
                    else request.app.state.config.RAG_AZURE_OPENAI_BASE_URL
                )
            ),
            (
                request.app.state.config.RAG_OPENAI_API_KEY
                if request.app.state.config.RAG_EMBEDDING_ENGINE == "openai"
                else (
                    request.app.state.config.RAG_OLLAMA_API_KEY
                    if request.app.state.config.RAG_EMBEDDING_ENGINE == "ollama"
                    else request.app.state.config.RAG_AZURE_OPENAI_API_KEY
                )
            ),
            request.app.state.config.RAG_EMBEDDING_BATCH_SIZE,
            azure_api_version=(
                request.app.state.config.RAG_AZURE_OPENAI_API_VERSION
                if request.app.state.config.RAG_EMBEDDING_ENGINE == "azure_openai"
                else None
            ),
            enable_async=request.app.state.config.ENABLE_ASYNC_EMBEDDING,
        )

        return {
            "status": True,
            "RAG_EMBEDDING_ENGINE": request.app.state.config.RAG_EMBEDDING_ENGINE,
            "RAG_EMBEDDING_MODEL": request.app.state.config.RAG_EMBEDDING_MODEL,
            "RAG_EMBEDDING_BATCH_SIZE": request.app.state.config.RAG_EMBEDDING_BATCH_SIZE,
            "ENABLE_ASYNC_EMBEDDING": request.app.state.config.ENABLE_ASYNC_EMBEDDING,
            "openai_config": {
                "url": request.app.state.config.RAG_OPENAI_API_BASE_URL,
                "key": request.app.state.config.RAG_OPENAI_API_KEY,
            },
            "ollama_config": {
                "url": request.app.state.config.RAG_OLLAMA_BASE_URL,
                "key": request.app.state.config.RAG_OLLAMA_API_KEY,
            },
            "azure_openai_config": {
                "url": request.app.state.config.RAG_AZURE_OPENAI_BASE_URL,
                "key": request.app.state.config.RAG_AZURE_OPENAI_API_KEY,
                "version": request.app.state.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),
        )


@router.get("/config")
async def get_rag_config(request: Request, user=Depends(get_admin_user)):
    return {
        "status": True,
        # RAG settings
        "RAG_TEMPLATE": request.app.state.config.RAG_TEMPLATE,
        "TOP_K": request.app.state.config.TOP_K,
        "BYPASS_EMBEDDING_AND_RETRIEVAL": request.app.state.config.BYPASS_EMBEDDING_AND_RETRIEVAL,
        "RAG_FULL_CONTEXT": request.app.state.config.RAG_FULL_CONTEXT,
        # Hybrid search settings
        "ENABLE_RAG_HYBRID_SEARCH": request.app.state.config.ENABLE_RAG_HYBRID_SEARCH,
        "ENABLE_RAG_HYBRID_SEARCH_ENRICHED_TEXTS": request.app.state.config.ENABLE_RAG_HYBRID_SEARCH_ENRICHED_TEXTS,
        "TOP_K_RERANKER": request.app.state.config.TOP_K_RERANKER,
        "RELEVANCE_THRESHOLD": request.app.state.config.RELEVANCE_THRESHOLD,
        "HYBRID_BM25_WEIGHT": request.app.state.config.HYBRID_BM25_WEIGHT,
        # Content extraction settings
        "CONTENT_EXTRACTION_ENGINE": request.app.state.config.CONTENT_EXTRACTION_ENGINE,
        "PDF_EXTRACT_IMAGES": request.app.state.config.PDF_EXTRACT_IMAGES,
        "DATALAB_MARKER_API_KEY": request.app.state.config.DATALAB_MARKER_API_KEY,
        "DATALAB_MARKER_API_BASE_URL": request.app.state.config.DATALAB_MARKER_API_BASE_URL,
        "DATALAB_MARKER_ADDITIONAL_CONFIG": request.app.state.config.DATALAB_MARKER_ADDITIONAL_CONFIG,
        "DATALAB_MARKER_SKIP_CACHE": request.app.state.config.DATALAB_MARKER_SKIP_CACHE,
        "DATALAB_MARKER_FORCE_OCR": request.app.state.config.DATALAB_MARKER_FORCE_OCR,
        "DATALAB_MARKER_PAGINATE": request.app.state.config.DATALAB_MARKER_PAGINATE,
        "DATALAB_MARKER_STRIP_EXISTING_OCR": request.app.state.config.DATALAB_MARKER_STRIP_EXISTING_OCR,
        "DATALAB_MARKER_DISABLE_IMAGE_EXTRACTION": request.app.state.config.DATALAB_MARKER_DISABLE_IMAGE_EXTRACTION,
        "DATALAB_MARKER_FORMAT_LINES": request.app.state.config.DATALAB_MARKER_FORMAT_LINES,
        "DATALAB_MARKER_USE_LLM": request.app.state.config.DATALAB_MARKER_USE_LLM,
        "DATALAB_MARKER_OUTPUT_FORMAT": request.app.state.config.DATALAB_MARKER_OUTPUT_FORMAT,
        "EXTERNAL_DOCUMENT_LOADER_URL": request.app.state.config.EXTERNAL_DOCUMENT_LOADER_URL,
        "EXTERNAL_DOCUMENT_LOADER_API_KEY": request.app.state.config.EXTERNAL_DOCUMENT_LOADER_API_KEY,
        "TIKA_SERVER_URL": request.app.state.config.TIKA_SERVER_URL,
        "DOCLING_SERVER_URL": request.app.state.config.DOCLING_SERVER_URL,
        "DOCLING_API_KEY": request.app.state.config.DOCLING_API_KEY,
        "DOCLING_PARAMS": request.app.state.config.DOCLING_PARAMS,
        "DOCUMENT_INTELLIGENCE_ENDPOINT": request.app.state.config.DOCUMENT_INTELLIGENCE_ENDPOINT,
        "DOCUMENT_INTELLIGENCE_KEY": request.app.state.config.DOCUMENT_INTELLIGENCE_KEY,
        "DOCUMENT_INTELLIGENCE_MODEL": request.app.state.config.DOCUMENT_INTELLIGENCE_MODEL,
        "MISTRAL_OCR_API_BASE_URL": request.app.state.config.MISTRAL_OCR_API_BASE_URL,
        "MISTRAL_OCR_API_KEY": request.app.state.config.MISTRAL_OCR_API_KEY,
        # MinerU settings
        "MINERU_API_MODE": request.app.state.config.MINERU_API_MODE,
        "MINERU_API_URL": request.app.state.config.MINERU_API_URL,
        "MINERU_API_KEY": request.app.state.config.MINERU_API_KEY,
        "MINERU_API_TIMEOUT": request.app.state.config.MINERU_API_TIMEOUT,
        "MINERU_PARAMS": request.app.state.config.MINERU_PARAMS,
        # Reranking settings
        "RAG_RERANKING_MODEL": request.app.state.config.RAG_RERANKING_MODEL,
        "RAG_RERANKING_ENGINE": request.app.state.config.RAG_RERANKING_ENGINE,
        "RAG_EXTERNAL_RERANKER_URL": request.app.state.config.RAG_EXTERNAL_RERANKER_URL,
        "RAG_EXTERNAL_RERANKER_API_KEY": request.app.state.config.RAG_EXTERNAL_RERANKER_API_KEY,
        "RAG_EXTERNAL_RERANKER_TIMEOUT": request.app.state.config.RAG_EXTERNAL_RERANKER_TIMEOUT,
        # Chunking settings
        "TEXT_SPLITTER": request.app.state.config.TEXT_SPLITTER,
        "ENABLE_MARKDOWN_HEADER_TEXT_SPLITTER": request.app.state.config.ENABLE_MARKDOWN_HEADER_TEXT_SPLITTER,
        "CHUNK_SIZE": request.app.state.config.CHUNK_SIZE,
        "CHUNK_MIN_SIZE_TARGET": request.app.state.config.CHUNK_MIN_SIZE_TARGET,
        "CHUNK_OVERLAP": request.app.state.config.CHUNK_OVERLAP,
        # File upload settings
        "FILE_MAX_SIZE": request.app.state.config.FILE_MAX_SIZE,
        "FILE_MAX_COUNT": request.app.state.config.FILE_MAX_COUNT,
        "FILE_IMAGE_COMPRESSION_WIDTH": request.app.state.config.FILE_IMAGE_COMPRESSION_WIDTH,
        "FILE_IMAGE_COMPRESSION_HEIGHT": request.app.state.config.FILE_IMAGE_COMPRESSION_HEIGHT,
        "ALLOWED_FILE_EXTENSIONS": request.app.state.config.ALLOWED_FILE_EXTENSIONS,
        # Integration settings
        "ENABLE_GOOGLE_DRIVE_INTEGRATION": request.app.state.config.ENABLE_GOOGLE_DRIVE_INTEGRATION,
        "ENABLE_ONEDRIVE_INTEGRATION": request.app.state.config.ENABLE_ONEDRIVE_INTEGRATION,
        # Web search settings
        "web": {
            "ENABLE_WEB_SEARCH": request.app.state.config.ENABLE_WEB_SEARCH,
            "WEB_SEARCH_ENGINE": request.app.state.config.WEB_SEARCH_ENGINE,
            "WEB_SEARCH_TRUST_ENV": request.app.state.config.WEB_SEARCH_TRUST_ENV,
            "WEB_SEARCH_RESULT_COUNT": request.app.state.config.WEB_SEARCH_RESULT_COUNT,
            "WEB_SEARCH_CONCURRENT_REQUESTS": request.app.state.config.WEB_SEARCH_CONCURRENT_REQUESTS,
            "WEB_LOADER_CONCURRENT_REQUESTS": request.app.state.config.WEB_LOADER_CONCURRENT_REQUESTS,
            "WEB_SEARCH_DOMAIN_FILTER_LIST": request.app.state.config.WEB_SEARCH_DOMAIN_FILTER_LIST,
            "BYPASS_WEB_SEARCH_EMBEDDING_AND_RETRIEVAL": request.app.state.config.BYPASS_WEB_SEARCH_EMBEDDING_AND_RETRIEVAL,
            "BYPASS_WEB_SEARCH_WEB_LOADER": request.app.state.config.BYPASS_WEB_SEARCH_WEB_LOADER,
            "OLLAMA_CLOUD_WEB_SEARCH_API_KEY": request.app.state.config.OLLAMA_CLOUD_WEB_SEARCH_API_KEY,
            "SEARXNG_QUERY_URL": request.app.state.config.SEARXNG_QUERY_URL,
            "SEARXNG_LANGUAGE": request.app.state.config.SEARXNG_LANGUAGE,
            "YACY_QUERY_URL": request.app.state.config.YACY_QUERY_URL,
            "YACY_USERNAME": request.app.state.config.YACY_USERNAME,
            "YACY_PASSWORD": request.app.state.config.YACY_PASSWORD,
            "GOOGLE_PSE_API_KEY": request.app.state.config.GOOGLE_PSE_API_KEY,
            "GOOGLE_PSE_ENGINE_ID": request.app.state.config.GOOGLE_PSE_ENGINE_ID,
            "BRAVE_SEARCH_API_KEY": request.app.state.config.BRAVE_SEARCH_API_KEY,
            "KAGI_SEARCH_API_KEY": request.app.state.config.KAGI_SEARCH_API_KEY,
            "MOJEEK_SEARCH_API_KEY": request.app.state.config.MOJEEK_SEARCH_API_KEY,
            "BOCHA_SEARCH_API_KEY": request.app.state.config.BOCHA_SEARCH_API_KEY,
            "SERPSTACK_API_KEY": request.app.state.config.SERPSTACK_API_KEY,
            "SERPSTACK_HTTPS": request.app.state.config.SERPSTACK_HTTPS,
            "SERPER_API_KEY": request.app.state.config.SERPER_API_KEY,
            "SERPLY_API_KEY": request.app.state.config.SERPLY_API_KEY,
            "DDGS_BACKEND": request.app.state.config.DDGS_BACKEND,
            "TAVILY_API_KEY": request.app.state.config.TAVILY_API_KEY,
            "SEARCHAPI_API_KEY": request.app.state.config.SEARCHAPI_API_KEY,
            "SEARCHAPI_ENGINE": request.app.state.config.SEARCHAPI_ENGINE,
            "SERPAPI_API_KEY": request.app.state.config.SERPAPI_API_KEY,
            "SERPAPI_ENGINE": request.app.state.config.SERPAPI_ENGINE,
            "JINA_API_KEY": request.app.state.config.JINA_API_KEY,
            "JINA_API_BASE_URL": request.app.state.config.JINA_API_BASE_URL,
            "BING_SEARCH_V7_ENDPOINT": request.app.state.config.BING_SEARCH_V7_ENDPOINT,
            "BING_SEARCH_V7_SUBSCRIPTION_KEY": request.app.state.config.BING_SEARCH_V7_SUBSCRIPTION_KEY,
            "EXA_API_KEY": request.app.state.config.EXA_API_KEY,
            "PERPLEXITY_API_KEY": request.app.state.config.PERPLEXITY_API_KEY,
            "PERPLEXITY_MODEL": request.app.state.config.PERPLEXITY_MODEL,
            "PERPLEXITY_SEARCH_CONTEXT_USAGE": request.app.state.config.PERPLEXITY_SEARCH_CONTEXT_USAGE,
            "PERPLEXITY_SEARCH_API_URL": request.app.state.config.PERPLEXITY_SEARCH_API_URL,
            "SOUGOU_API_SID": request.app.state.config.SOUGOU_API_SID,
            "SOUGOU_API_SK": request.app.state.config.SOUGOU_API_SK,
            "WEB_LOADER_ENGINE": request.app.state.config.WEB_LOADER_ENGINE,
            "WEB_LOADER_TIMEOUT": request.app.state.config.WEB_LOADER_TIMEOUT,
            "ENABLE_WEB_LOADER_SSL_VERIFICATION": request.app.state.config.ENABLE_WEB_LOADER_SSL_VERIFICATION,
            "PLAYWRIGHT_WS_URL": request.app.state.config.PLAYWRIGHT_WS_URL,
            "PLAYWRIGHT_TIMEOUT": request.app.state.config.PLAYWRIGHT_TIMEOUT,
            "FIRECRAWL_API_KEY": request.app.state.config.FIRECRAWL_API_KEY,
            "FIRECRAWL_API_BASE_URL": request.app.state.config.FIRECRAWL_API_BASE_URL,
            "FIRECRAWL_TIMEOUT": request.app.state.config.FIRECRAWL_TIMEOUT,
            "TAVILY_EXTRACT_DEPTH": request.app.state.config.TAVILY_EXTRACT_DEPTH,
            "EXTERNAL_WEB_SEARCH_URL": request.app.state.config.EXTERNAL_WEB_SEARCH_URL,
            "EXTERNAL_WEB_SEARCH_API_KEY": request.app.state.config.EXTERNAL_WEB_SEARCH_API_KEY,
            "EXTERNAL_WEB_LOADER_URL": request.app.state.config.EXTERNAL_WEB_LOADER_URL,
            "EXTERNAL_WEB_LOADER_API_KEY": request.app.state.config.EXTERNAL_WEB_LOADER_API_KEY,
            "YOUTUBE_LOADER_LANGUAGE": request.app.state.config.YOUTUBE_LOADER_LANGUAGE,
            "YOUTUBE_LOADER_PROXY_URL": request.app.state.config.YOUTUBE_LOADER_PROXY_URL,
            "YOUTUBE_LOADER_TRANSLATION": request.app.state.YOUTUBE_LOADER_TRANSLATION,
        },
    }


class WebConfig(BaseModel):
    ENABLE_WEB_SEARCH: Optional[bool] = None
    WEB_SEARCH_ENGINE: Optional[str] = None
    WEB_SEARCH_TRUST_ENV: Optional[bool] = None
    WEB_SEARCH_RESULT_COUNT: Optional[int] = None
    WEB_SEARCH_CONCURRENT_REQUESTS: Optional[int] = None
    WEB_LOADER_CONCURRENT_REQUESTS: Optional[int] = None
    WEB_SEARCH_DOMAIN_FILTER_LIST: Optional[List[str]] = []
    BYPASS_WEB_SEARCH_EMBEDDING_AND_RETRIEVAL: Optional[bool] = None
    BYPASS_WEB_SEARCH_WEB_LOADER: Optional[bool] = None
    OLLAMA_CLOUD_WEB_SEARCH_API_KEY: Optional[str] = None
    SEARXNG_QUERY_URL: Optional[str] = None
    SEARXNG_LANGUAGE: Optional[str] = None
    YACY_QUERY_URL: Optional[str] = None
    YACY_USERNAME: Optional[str] = None
    YACY_PASSWORD: Optional[str] = None
    GOOGLE_PSE_API_KEY: Optional[str] = None
    GOOGLE_PSE_ENGINE_ID: Optional[str] = None
    BRAVE_SEARCH_API_KEY: Optional[str] = None
    KAGI_SEARCH_API_KEY: Optional[str] = None
    MOJEEK_SEARCH_API_KEY: Optional[str] = None
    BOCHA_SEARCH_API_KEY: Optional[str] = None
    SERPSTACK_API_KEY: Optional[str] = None
    SERPSTACK_HTTPS: Optional[bool] = None
    SERPER_API_KEY: Optional[str] = None
    SERPLY_API_KEY: Optional[str] = None
    DDGS_BACKEND: Optional[str] = None
    TAVILY_API_KEY: Optional[str] = None
    SEARCHAPI_API_KEY: Optional[str] = None
    SEARCHAPI_ENGINE: Optional[str] = None
    SERPAPI_API_KEY: Optional[str] = None
    SERPAPI_ENGINE: Optional[str] = None
    JINA_API_KEY: Optional[str] = None
    JINA_API_BASE_URL: Optional[str] = None
    BING_SEARCH_V7_ENDPOINT: Optional[str] = None
    BING_SEARCH_V7_SUBSCRIPTION_KEY: Optional[str] = None
    EXA_API_KEY: Optional[str] = None
    PERPLEXITY_API_KEY: Optional[str] = None
    PERPLEXITY_MODEL: Optional[str] = None
    PERPLEXITY_SEARCH_CONTEXT_USAGE: Optional[str] = None
    PERPLEXITY_SEARCH_API_URL: Optional[str] = None
    SOUGOU_API_SID: Optional[str] = None
    SOUGOU_API_SK: Optional[str] = None
    WEB_LOADER_ENGINE: Optional[str] = None
    WEB_LOADER_TIMEOUT: Optional[str] = None
    ENABLE_WEB_LOADER_SSL_VERIFICATION: Optional[bool] = None
    PLAYWRIGHT_WS_URL: Optional[str] = None
    PLAYWRIGHT_TIMEOUT: Optional[int] = None
    FIRECRAWL_API_KEY: Optional[str] = None
    FIRECRAWL_API_BASE_URL: Optional[str] = None
    FIRECRAWL_TIMEOUT: Optional[str] = None
    TAVILY_EXTRACT_DEPTH: Optional[str] = None
    EXTERNAL_WEB_SEARCH_URL: Optional[str] = None
    EXTERNAL_WEB_SEARCH_API_KEY: Optional[str] = None
    EXTERNAL_WEB_LOADER_URL: Optional[str] = None
    EXTERNAL_WEB_LOADER_API_KEY: Optional[str] = None
    YOUTUBE_LOADER_LANGUAGE: Optional[List[str]] = None
    YOUTUBE_LOADER_PROXY_URL: Optional[str] = None
    YOUTUBE_LOADER_TRANSLATION: Optional[str] = None


class ConfigForm(BaseModel):
    # RAG settings
    RAG_TEMPLATE: Optional[str] = None
    TOP_K: Optional[int] = None
    BYPASS_EMBEDDING_AND_RETRIEVAL: Optional[bool] = None
    RAG_FULL_CONTEXT: Optional[bool] = None

    # Hybrid search settings
    ENABLE_RAG_HYBRID_SEARCH: Optional[bool] = None
    ENABLE_RAG_HYBRID_SEARCH_ENRICHED_TEXTS: Optional[bool] = None
    TOP_K_RERANKER: Optional[int] = None
    RELEVANCE_THRESHOLD: Optional[float] = None
    HYBRID_BM25_WEIGHT: Optional[float] = None

    # Content extraction settings
    CONTENT_EXTRACTION_ENGINE: Optional[str] = None
    PDF_EXTRACT_IMAGES: Optional[bool] = None

    DATALAB_MARKER_API_KEY: Optional[str] = None
    DATALAB_MARKER_API_BASE_URL: Optional[str] = None
    DATALAB_MARKER_ADDITIONAL_CONFIG: Optional[str] = None
    DATALAB_MARKER_SKIP_CACHE: Optional[bool] = None
    DATALAB_MARKER_FORCE_OCR: Optional[bool] = None
    DATALAB_MARKER_PAGINATE: Optional[bool] = None
    DATALAB_MARKER_STRIP_EXISTING_OCR: Optional[bool] = None
    DATALAB_MARKER_DISABLE_IMAGE_EXTRACTION: Optional[bool] = None
    DATALAB_MARKER_FORMAT_LINES: Optional[bool] = None
    DATALAB_MARKER_USE_LLM: Optional[bool] = None
    DATALAB_MARKER_OUTPUT_FORMAT: Optional[str] = None

    EXTERNAL_DOCUMENT_LOADER_URL: Optional[str] = None
    EXTERNAL_DOCUMENT_LOADER_API_KEY: Optional[str] = None

    TIKA_SERVER_URL: Optional[str] = None
    DOCLING_SERVER_URL: Optional[str] = None
    DOCLING_API_KEY: Optional[str] = None
    DOCLING_PARAMS: Optional[dict] = None
    DOCUMENT_INTELLIGENCE_ENDPOINT: Optional[str] = None
    DOCUMENT_INTELLIGENCE_KEY: Optional[str] = None
    DOCUMENT_INTELLIGENCE_MODEL: Optional[str] = None
    MISTRAL_OCR_API_BASE_URL: Optional[str] = None
    MISTRAL_OCR_API_KEY: Optional[str] = None

    # MinerU settings
    MINERU_API_MODE: Optional[str] = None
    MINERU_API_URL: Optional[str] = None
    MINERU_API_KEY: Optional[str] = None
    MINERU_API_TIMEOUT: Optional[str] = None
    MINERU_PARAMS: Optional[dict] = None

    # Reranking settings
    RAG_RERANKING_MODEL: Optional[str] = None
    RAG_RERANKING_ENGINE: Optional[str] = None
    RAG_EXTERNAL_RERANKER_URL: Optional[str] = None
    RAG_EXTERNAL_RERANKER_API_KEY: Optional[str] = None
    RAG_EXTERNAL_RERANKER_TIMEOUT: Optional[str] = None

    # Chunking settings
    TEXT_SPLITTER: Optional[str] = None
    ENABLE_MARKDOWN_HEADER_TEXT_SPLITTER: Optional[bool] = None
    CHUNK_SIZE: Optional[int] = None
    CHUNK_MIN_SIZE_TARGET: Optional[int] = None
    CHUNK_OVERLAP: Optional[int] = None

    # File upload settings
    FILE_MAX_SIZE: Optional[int] = None
    FILE_MAX_COUNT: Optional[int] = None
    FILE_IMAGE_COMPRESSION_WIDTH: Optional[int] = None
    FILE_IMAGE_COMPRESSION_HEIGHT: Optional[int] = None
    ALLOWED_FILE_EXTENSIONS: Optional[List[str]] = None

    # Integration settings
    ENABLE_GOOGLE_DRIVE_INTEGRATION: Optional[bool] = None
    ENABLE_ONEDRIVE_INTEGRATION: Optional[bool] = None

    # Web search settings
    web: Optional[WebConfig] = None


@router.post("/config/update")
async def update_rag_config(
    request: Request, form_data: ConfigForm, user=Depends(get_admin_user)
):
    # RAG settings
    request.app.state.config.RAG_TEMPLATE = (
        form_data.RAG_TEMPLATE
        if form_data.RAG_TEMPLATE is not None
        else request.app.state.config.RAG_TEMPLATE
    )
    request.app.state.config.TOP_K = (
        form_data.TOP_K
        if form_data.TOP_K is not None
        else request.app.state.config.TOP_K
    )
    request.app.state.config.BYPASS_EMBEDDING_AND_RETRIEVAL = (
        form_data.BYPASS_EMBEDDING_AND_RETRIEVAL
        if form_data.BYPASS_EMBEDDING_AND_RETRIEVAL is not None
        else request.app.state.config.BYPASS_EMBEDDING_AND_RETRIEVAL
    )
    request.app.state.config.RAG_FULL_CONTEXT = (
        form_data.RAG_FULL_CONTEXT
        if form_data.RAG_FULL_CONTEXT is not None
        else request.app.state.config.RAG_FULL_CONTEXT
    )

    # Hybrid search settings
    request.app.state.config.ENABLE_RAG_HYBRID_SEARCH = (
        form_data.ENABLE_RAG_HYBRID_SEARCH
        if form_data.ENABLE_RAG_HYBRID_SEARCH is not None
        else request.app.state.config.ENABLE_RAG_HYBRID_SEARCH
    )
    request.app.state.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 request.app.state.config.ENABLE_RAG_HYBRID_SEARCH_ENRICHED_TEXTS
    )

    request.app.state.config.TOP_K_RERANKER = (
        form_data.TOP_K_RERANKER
        if form_data.TOP_K_RERANKER is not None
        else request.app.state.config.TOP_K_RERANKER
    )
    request.app.state.config.RELEVANCE_THRESHOLD = (
        form_data.RELEVANCE_THRESHOLD
        if form_data.RELEVANCE_THRESHOLD is not None
        else request.app.state.config.RELEVANCE_THRESHOLD
    )
    request.app.state.config.HYBRID_BM25_WEIGHT = (
        form_data.HYBRID_BM25_WEIGHT
        if form_data.HYBRID_BM25_WEIGHT is not None
        else request.app.state.config.HYBRID_BM25_WEIGHT
    )

    # Content extraction settings
    request.app.state.config.CONTENT_EXTRACTION_ENGINE = (
        form_data.CONTENT_EXTRACTION_ENGINE
        if form_data.CONTENT_EXTRACTION_ENGINE is not None
        else request.app.state.config.CONTENT_EXTRACTION_ENGINE
    )
    request.app.state.config.PDF_EXTRACT_IMAGES = (
        form_data.PDF_EXTRACT_IMAGES
        if form_data.PDF_EXTRACT_IMAGES is not None
        else request.app.state.config.PDF_EXTRACT_IMAGES
    )
    request.app.state.config.DATALAB_MARKER_API_KEY = (
        form_data.DATALAB_MARKER_API_KEY
        if form_data.DATALAB_MARKER_API_KEY is not None
        else request.app.state.config.DATALAB_MARKER_API_KEY
    )
    request.app.state.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 request.app.state.config.DATALAB_MARKER_API_BASE_URL
    )
    request.app.state.config.DATALAB_MARKER_ADDITIONAL_CONFIG = (
        form_data.DATALAB_MARKER_ADDITIONAL_CONFIG
        if form_data.DATALAB_MARKER_ADDITIONAL_CONFIG is not None
        else request.app.state.config.DATALAB_MARKER_ADDITIONAL_CONFIG
    )
    request.app.state.config.DATALAB_MARKER_SKIP_CACHE = (
        form_data.DATALAB_MARKER_SKIP_CACHE
        if form_data.DATALAB_MARKER_SKIP_CACHE is not None
        else request.app.state.config.DATALAB_MARKER_SKIP_CACHE
    )
    request.app.state.config.DATALAB_MARKER_FORCE_OCR = (
        form_data.DATALAB_MARKER_FORCE_OCR
        if form_data.DATALAB_MARKER_FORCE_OCR is not None
        else request.app.state.config.DATALAB_MARKER_FORCE_OCR
    )
    request.app.state.config.DATALAB_MARKER_PAGINATE = (
        form_data.DATALAB_MARKER_PAGINATE
        if form_data.DATALAB_MARKER_PAGINATE is not None
        else request.app.state.config.DATALAB_MARKER_PAGINATE
    )
    request.app.state.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 request.app.state.config.DATALAB_MARKER_STRIP_EXISTING_OCR
    )
    request.app.state.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 request.app.state.config.DATALAB_MARKER_DISABLE_IMAGE_EXTRACTION
    )
    request.app.state.config.DATALAB_MARKER_FORMAT_LINES = (
        form_data.DATALAB_MARKER_FORMAT_LINES
        if form_data.DATALAB_MARKER_FORMAT_LINES is not None
        else request.app.state.config.DATALAB_MARKER_FORMAT_LINES
    )
    request.app.state.config.DATALAB_MARKER_OUTPUT_FORMAT = (
        form_data.DATALAB_MARKER_OUTPUT_FORMAT
        if form_data.DATALAB_MARKER_OUTPUT_FORMAT is not None
        else request.app.state.config.DATALAB_MARKER_OUTPUT_FORMAT
    )
    request.app.state.config.DATALAB_MARKER_USE_LLM = (
        form_data.DATALAB_MARKER_USE_LLM
        if form_data.DATALAB_MARKER_USE_LLM is not None
        else request.app.state.config.DATALAB_MARKER_USE_LLM
    )
    request.app.state.config.EXTERNAL_DOCUMENT_LOADER_URL = (
        form_data.EXTERNAL_DOCUMENT_LOADER_URL
        if form_data.EXTERNAL_DOCUMENT_LOADER_URL is not None
        else request.app.state.config.EXTERNAL_DOCUMENT_LOADER_URL
    )
    request.app.state.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 request.app.state.config.EXTERNAL_DOCUMENT_LOADER_API_KEY
    )
    request.app.state.config.TIKA_SERVER_URL = (
        form_data.TIKA_SERVER_URL
        if form_data.TIKA_SERVER_URL is not None
        else request.app.state.config.TIKA_SERVER_URL
    )
    request.app.state.config.DOCLING_SERVER_URL = (
        form_data.DOCLING_SERVER_URL
        if form_data.DOCLING_SERVER_URL is not None
        else request.app.state.config.DOCLING_SERVER_URL
    )
    request.app.state.config.DOCLING_API_KEY = (
        form_data.DOCLING_API_KEY
        if form_data.DOCLING_API_KEY is not None
        else request.app.state.config.DOCLING_API_KEY
    )
    request.app.state.config.DOCLING_PARAMS = (
        form_data.DOCLING_PARAMS
        if form_data.DOCLING_PARAMS is not None
        else request.app.state.config.DOCLING_PARAMS
    )
    request.app.state.config.DOCUMENT_INTELLIGENCE_ENDPOINT = (
        form_data.DOCUMENT_INTELLIGENCE_ENDPOINT
        if form_data.DOCUMENT_INTELLIGENCE_ENDPOINT is not None
        else request.app.state.config.DOCUMENT_INTELLIGENCE_ENDPOINT
    )
    request.app.state.config.DOCUMENT_INTELLIGENCE_KEY = (
        form_data.DOCUMENT_INTELLIGENCE_KEY
        if form_data.DOCUMENT_INTELLIGENCE_KEY is not None
        else request.app.state.config.DOCUMENT_INTELLIGENCE_KEY
    )
    request.app.state.config.DOCUMENT_INTELLIGENCE_MODEL = (
        form_data.DOCUMENT_INTELLIGENCE_MODEL
        if form_data.DOCUMENT_INTELLIGENCE_MODEL is not None
        else request.app.state.config.DOCUMENT_INTELLIGENCE_MODEL
    )

    request.app.state.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 request.app.state.config.MISTRAL_OCR_API_BASE_URL
    )
    request.app.state.config.MISTRAL_OCR_API_KEY = (
        form_data.MISTRAL_OCR_API_KEY
        if form_data.MISTRAL_OCR_API_KEY is not None
        else request.app.state.config.MISTRAL_OCR_API_KEY
    )

    # MinerU settings
    request.app.state.config.MINERU_API_MODE = (
        form_data.MINERU_API_MODE
        if form_data.MINERU_API_MODE is not None
        else request.app.state.config.MINERU_API_MODE
    )
    request.app.state.config.MINERU_API_URL = (
        form_data.MINERU_API_URL
        if form_data.MINERU_API_URL is not None
        else request.app.state.config.MINERU_API_URL
    )
    request.app.state.config.MINERU_API_KEY = (
        form_data.MINERU_API_KEY
        if form_data.MINERU_API_KEY is not None
        else request.app.state.config.MINERU_API_KEY
    )
    request.app.state.config.MINERU_API_TIMEOUT = (
        form_data.MINERU_API_TIMEOUT
        if form_data.MINERU_API_TIMEOUT is not None
        else request.app.state.config.MINERU_API_TIMEOUT
    )
    request.app.state.config.MINERU_PARAMS = (
        form_data.MINERU_PARAMS
        if form_data.MINERU_PARAMS is not None
        else request.app.state.config.MINERU_PARAMS
    )

    # Reranking settings
    if request.app.state.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()
    request.app.state.config.RAG_RERANKING_ENGINE = (
        form_data.RAG_RERANKING_ENGINE
        if form_data.RAG_RERANKING_ENGINE is not None
        else request.app.state.config.RAG_RERANKING_ENGINE
    )

    request.app.state.config.RAG_EXTERNAL_RERANKER_URL = (
        form_data.RAG_EXTERNAL_RERANKER_URL
        if form_data.RAG_EXTERNAL_RERANKER_URL is not None
        else request.app.state.config.RAG_EXTERNAL_RERANKER_URL
    )

    request.app.state.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 request.app.state.config.RAG_EXTERNAL_RERANKER_API_KEY
    )

    request.app.state.config.RAG_EXTERNAL_RERANKER_TIMEOUT = (
        form_data.RAG_EXTERNAL_RERANKER_TIMEOUT
        if form_data.RAG_EXTERNAL_RERANKER_TIMEOUT is not None
        else request.app.state.config.RAG_EXTERNAL_RERANKER_TIMEOUT
    )

    log.info(
        f"Updating reranking model: {request.app.state.config.RAG_RERANKING_MODEL} to {form_data.RAG_RERANKING_MODEL}"
    )
    try:
        request.app.state.config.RAG_RERANKING_MODEL = (
            form_data.RAG_RERANKING_MODEL
            if form_data.RAG_RERANKING_MODEL is not None
            else request.app.state.config.RAG_RERANKING_MODEL
        )

        try:
            if (
                request.app.state.config.ENABLE_RAG_HYBRID_SEARCH
                and not request.app.state.config.BYPASS_EMBEDDING_AND_RETRIEVAL
            ):
                request.app.state.rf = get_rf(
                    request.app.state.config.RAG_RERANKING_ENGINE,
                    request.app.state.config.RAG_RERANKING_MODEL,
                    request.app.state.config.RAG_EXTERNAL_RERANKER_URL,
                    request.app.state.config.RAG_EXTERNAL_RERANKER_API_KEY,
                    request.app.state.config.RAG_EXTERNAL_RERANKER_TIMEOUT,
                )

                request.app.state.RERANKING_FUNCTION = get_reranking_function(
                    request.app.state.config.RAG_RERANKING_ENGINE,
                    request.app.state.config.RAG_RERANKING_MODEL,
                    request.app.state.rf,
                )
        except Exception as e:
            log.error(f"Error loading reranking model: {e}")
            request.app.state.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),
        )

    # Chunking settings
    request.app.state.config.TEXT_SPLITTER = (
        form_data.TEXT_SPLITTER
        if form_data.TEXT_SPLITTER is not None
        else request.app.state.config.TEXT_SPLITTER
    )
    request.app.state.config.CHUNK_SIZE = (
        form_data.CHUNK_SIZE
        if form_data.CHUNK_SIZE is not None
        else request.app.state.config.CHUNK_SIZE
    )
    request.app.state.config.CHUNK_MIN_SIZE_TARGET = (
        form_data.CHUNK_MIN_SIZE_TARGET
        if form_data.CHUNK_MIN_SIZE_TARGET is not None
        else request.app.state.config.CHUNK_MIN_SIZE_TARGET
    )
    request.app.state.config.CHUNK_OVERLAP = (
        form_data.CHUNK_OVERLAP
        if form_data.CHUNK_OVERLAP is not None
        else request.app.state.config.CHUNK_OVERLAP
    )

    # File upload settings
    request.app.state.config.FILE_MAX_SIZE = form_data.FILE_MAX_SIZE
    request.app.state.config.FILE_MAX_COUNT = form_data.FILE_MAX_COUNT
    request.app.state.config.FILE_IMAGE_COMPRESSION_WIDTH = (
        form_data.FILE_IMAGE_COMPRESSION_WIDTH
    )
    request.app.state.config.FILE_IMAGE_COMPRESSION_HEIGHT = (
        form_data.FILE_IMAGE_COMPRESSION_HEIGHT
    )
    request.app.state.config.ALLOWED_FILE_EXTENSIONS = (
        form_data.ALLOWED_FILE_EXTENSIONS
        if form_data.ALLOWED_FILE_EXTENSIONS is not None
        else request.app.state.config.ALLOWED_FILE_EXTENSIONS
    )

    # Integration settings
    request.app.state.config.ENABLE_GOOGLE_DRIVE_INTEGRATION = (
        form_data.ENABLE_GOOGLE_DRIVE_INTEGRATION
        if form_data.ENABLE_GOOGLE_DRIVE_INTEGRATION is not None
        else request.app.state.config.ENABLE_GOOGLE_DRIVE_INTEGRATION
    )
    request.app.state.config.ENABLE_ONEDRIVE_INTEGRATION = (
        form_data.ENABLE_ONEDRIVE_INTEGRATION
        if form_data.ENABLE_ONEDRIVE_INTEGRATION is not None
        else request.app.state.config.ENABLE_ONEDRIVE_INTEGRATION
    )

    if form_data.web is not None:
        # Web search settings
        request.app.state.config.ENABLE_WEB_SEARCH = form_data.web.ENABLE_WEB_SEARCH
        request.app.state.config.WEB_SEARCH_ENGINE = form_data.web.WEB_SEARCH_ENGINE
        request.app.state.config.WEB_SEARCH_TRUST_ENV = (
            form_data.web.WEB_SEARCH_TRUST_ENV
        )
        request.app.state.config.WEB_SEARCH_RESULT_COUNT = (
            form_data.web.WEB_SEARCH_RESULT_COUNT
        )
        request.app.state.config.WEB_SEARCH_CONCURRENT_REQUESTS = (
            form_data.web.WEB_SEARCH_CONCURRENT_REQUESTS
        )
        request.app.state.config.WEB_LOADER_CONCURRENT_REQUESTS = (
            form_data.web.WEB_LOADER_CONCURRENT_REQUESTS
        )
        request.app.state.config.WEB_SEARCH_DOMAIN_FILTER_LIST = (
            form_data.web.WEB_SEARCH_DOMAIN_FILTER_LIST
        )
        request.app.state.config.BYPASS_WEB_SEARCH_EMBEDDING_AND_RETRIEVAL = (
            form_data.web.BYPASS_WEB_SEARCH_EMBEDDING_AND_RETRIEVAL
        )
        request.app.state.config.BYPASS_WEB_SEARCH_WEB_LOADER = (
            form_data.web.BYPASS_WEB_SEARCH_WEB_LOADER
        )
        request.app.state.config.OLLAMA_CLOUD_WEB_SEARCH_API_KEY = (
            form_data.web.OLLAMA_CLOUD_WEB_SEARCH_API_KEY
        )
        request.app.state.config.SEARXNG_QUERY_URL = form_data.web.SEARXNG_QUERY_URL
        request.app.state.config.SEARXNG_LANGUAGE = form_data.web.SEARXNG_LANGUAGE
        request.app.state.config.YACY_QUERY_URL = form_data.web.YACY_QUERY_URL
        request.app.state.config.YACY_USERNAME = form_data.web.YACY_USERNAME
        request.app.state.config.YACY_PASSWORD = form_data.web.YACY_PASSWORD
        request.app.state.config.GOOGLE_PSE_API_KEY = form_data.web.GOOGLE_PSE_API_KEY
        request.app.state.config.GOOGLE_PSE_ENGINE_ID = (
            form_data.web.GOOGLE_PSE_ENGINE_ID
        )
        request.app.state.config.BRAVE_SEARCH_API_KEY = (
            form_data.web.BRAVE_SEARCH_API_KEY
        )
        request.app.state.config.KAGI_SEARCH_API_KEY = form_data.web.KAGI_SEARCH_API_KEY
        request.app.state.config.MOJEEK_SEARCH_API_KEY = (
            form_data.web.MOJEEK_SEARCH_API_KEY
        )
        request.app.state.config.BOCHA_SEARCH_API_KEY = (
            form_data.web.BOCHA_SEARCH_API_KEY
        )
        request.app.state.config.SERPSTACK_API_KEY = form_data.web.SERPSTACK_API_KEY
        request.app.state.config.SERPSTACK_HTTPS = form_data.web.SERPSTACK_HTTPS
        request.app.state.config.SERPER_API_KEY = form_data.web.SERPER_API_KEY
        request.app.state.config.SERPLY_API_KEY = form_data.web.SERPLY_API_KEY
        request.app.state.config.DDGS_BACKEND = form_data.web.DDGS_BACKEND
        request.app.state.config.TAVILY_API_KEY = form_data.web.TAVILY_API_KEY
        request.app.state.config.SEARCHAPI_API_KEY = form_data.web.SEARCHAPI_API_KEY
        request.app.state.config.SEARCHAPI_ENGINE = form_data.web.SEARCHAPI_ENGINE
        request.app.state.config.SERPAPI_API_KEY = form_data.web.SERPAPI_API_KEY
        request.app.state.config.SERPAPI_ENGINE = form_data.web.SERPAPI_ENGINE
        request.app.state.config.JINA_API_KEY = form_data.web.JINA_API_KEY
        request.app.state.config.JINA_API_BASE_URL = form_data.web.JINA_API_BASE_URL
        request.app.state.config.BING_SEARCH_V7_ENDPOINT = (
            form_data.web.BING_SEARCH_V7_ENDPOINT
        )
        request.app.state.config.BING_SEARCH_V7_SUBSCRIPTION_KEY = (
            form_data.web.BING_SEARCH_V7_SUBSCRIPTION_KEY
        )
        request.app.state.config.EXA_API_KEY = form_data.web.EXA_API_KEY
        request.app.state.config.PERPLEXITY_API_KEY = form_data.web.PERPLEXITY_API_KEY
        request.app.state.config.PERPLEXITY_MODEL = form_data.web.PERPLEXITY_MODEL
        request.app.state.config.PERPLEXITY_SEARCH_CONTEXT_USAGE = (
            form_data.web.PERPLEXITY_SEARCH_CONTEXT_USAGE
        )
        request.app.state.config.PERPLEXITY_SEARCH_API_URL = (
            form_data.web.PERPLEXITY_SEARCH_API_URL
        )
        request.app.state.config.SOUGOU_API_SID = form_data.web.SOUGOU_API_SID
        request.app.state.config.SOUGOU_API_SK = form_data.web.SOUGOU_API_SK

        # Web loader settings
        request.app.state.config.WEB_LOADER_ENGINE = form_data.web.WEB_LOADER_ENGINE
        request.app.state.config.WEB_LOADER_TIMEOUT = form_data.web.WEB_LOADER_TIMEOUT

        request.app.state.config.ENABLE_WEB_LOADER_SSL_VERIFICATION = (
            form_data.web.ENABLE_WEB_LOADER_SSL_VERIFICATION
        )
        request.app.state.config.PLAYWRIGHT_WS_URL = form_data.web.PLAYWRIGHT_WS_URL
        request.app.state.config.PLAYWRIGHT_TIMEOUT = form_data.web.PLAYWRIGHT_TIMEOUT
        request.app.state.config.FIRECRAWL_API_KEY = form_data.web.FIRECRAWL_API_KEY
        request.app.state.config.FIRECRAWL_API_BASE_URL = (
            form_data.web.FIRECRAWL_API_BASE_URL
        )
        request.app.state.config.FIRECRAWL_TIMEOUT = form_data.web.FIRECRAWL_TIMEOUT
        request.app.state.config.EXTERNAL_WEB_SEARCH_URL = (
            form_data.web.EXTERNAL_WEB_SEARCH_URL
        )
        request.app.state.config.EXTERNAL_WEB_SEARCH_API_KEY = (
            form_data.web.EXTERNAL_WEB_SEARCH_API_KEY
        )
        request.app.state.config.EXTERNAL_WEB_LOADER_URL = (
            form_data.web.EXTERNAL_WEB_LOADER_URL
        )
        request.app.state.config.EXTERNAL_WEB_LOADER_API_KEY = (
            form_data.web.EXTERNAL_WEB_LOADER_API_KEY
        )
        request.app.state.config.TAVILY_EXTRACT_DEPTH = (
            form_data.web.TAVILY_EXTRACT_DEPTH
        )
        request.app.state.config.YOUTUBE_LOADER_LANGUAGE = (
            form_data.web.YOUTUBE_LOADER_LANGUAGE
        )
        request.app.state.config.YOUTUBE_LOADER_PROXY_URL = (
            form_data.web.YOUTUBE_LOADER_PROXY_URL
        )
        request.app.state.YOUTUBE_LOADER_TRANSLATION = (
            form_data.web.YOUTUBE_LOADER_TRANSLATION
        )

    return {
        "status": True,
        # RAG settings
        "RAG_TEMPLATE": request.app.state.config.RAG_TEMPLATE,
        "TOP_K": request.app.state.config.TOP_K,
        "BYPASS_EMBEDDING_AND_RETRIEVAL": request.app.state.config.BYPASS_EMBEDDING_AND_RETRIEVAL,
        "RAG_FULL_CONTEXT": request.app.state.config.RAG_FULL_CONTEXT,
        # Hybrid search settings
        "ENABLE_RAG_HYBRID_SEARCH": request.app.state.config.ENABLE_RAG_HYBRID_SEARCH,
        "TOP_K_RERANKER": request.app.state.config.TOP_K_RERANKER,
        "RELEVANCE_THRESHOLD": request.app.state.config.RELEVANCE_THRESHOLD,
        "HYBRID_BM25_WEIGHT": request.app.state.config.HYBRID_BM25_WEIGHT,
        # Content extraction settings
        "CONTENT_EXTRACTION_ENGINE": request.app.state.config.CONTENT_EXTRACTION_ENGINE,
        "PDF_EXTRACT_IMAGES": request.app.state.config.PDF_EXTRACT_IMAGES,
        "DATALAB_MARKER_API_KEY": request.app.state.config.DATALAB_MARKER_API_KEY,
        "DATALAB_MARKER_API_BASE_URL": request.app.state.config.DATALAB_MARKER_API_BASE_URL,
        "DATALAB_MARKER_ADDITIONAL_CONFIG": request.app.state.config.DATALAB_MARKER_ADDITIONAL_CONFIG,
        "DATALAB_MARKER_SKIP_CACHE": request.app.state.config.DATALAB_MARKER_SKIP_CACHE,
        "DATALAB_MARKER_FORCE_OCR": request.app.state.config.DATALAB_MARKER_FORCE_OCR,
        "DATALAB_MARKER_PAGINATE": request.app.state.config.DATALAB_MARKER_PAGINATE,
        "DATALAB_MARKER_STRIP_EXISTING_OCR": request.app.state.config.DATALAB_MARKER_STRIP_EXISTING_OCR,
        "DATALAB_MARKER_DISABLE_IMAGE_EXTRACTION": request.app.state.config.DATALAB_MARKER_DISABLE_IMAGE_EXTRACTION,
        "DATALAB_MARKER_USE_LLM": request.app.state.config.DATALAB_MARKER_USE_LLM,
        "DATALAB_MARKER_OUTPUT_FORMAT": request.app.state.config.DATALAB_MARKER_OUTPUT_FORMAT,
        "EXTERNAL_DOCUMENT_LOADER_URL": request.app.state.config.EXTERNAL_DOCUMENT_LOADER_URL,
        "EXTERNAL_DOCUMENT_LOADER_API_KEY": request.app.state.config.EXTERNAL_DOCUMENT_LOADER_API_KEY,
        "TIKA_SERVER_URL": request.app.state.config.TIKA_SERVER_URL,
        "DOCLING_SERVER_URL": request.app.state.config.DOCLING_SERVER_URL,
        "DOCLING_API_KEY": request.app.state.config.DOCLING_API_KEY,
        "DOCLING_PARAMS": request.app.state.config.DOCLING_PARAMS,
        "DOCUMENT_INTELLIGENCE_ENDPOINT": request.app.state.config.DOCUMENT_INTELLIGENCE_ENDPOINT,
        "DOCUMENT_INTELLIGENCE_KEY": request.app.state.config.DOCUMENT_INTELLIGENCE_KEY,
        "DOCUMENT_INTELLIGENCE_MODEL": request.app.state.config.DOCUMENT_INTELLIGENCE_MODEL,
        "MISTRAL_OCR_API_BASE_URL": request.app.state.config.MISTRAL_OCR_API_BASE_URL,
        "MISTRAL_OCR_API_KEY": request.app.state.config.MISTRAL_OCR_API_KEY,
        # MinerU settings
        "MINERU_API_MODE": request.app.state.config.MINERU_API_MODE,
        "MINERU_API_URL": request.app.state.config.MINERU_API_URL,
        "MINERU_API_KEY": request.app.state.config.MINERU_API_KEY,
        "MINERU_API_TIMEOUT": request.app.state.config.MINERU_API_TIMEOUT,
        "MINERU_PARAMS": request.app.state.config.MINERU_PARAMS,
        # Reranking settings
        "RAG_RERANKING_MODEL": request.app.state.config.RAG_RERANKING_MODEL,
        "RAG_RERANKING_ENGINE": request.app.state.config.RAG_RERANKING_ENGINE,
        "RAG_EXTERNAL_RERANKER_URL": request.app.state.config.RAG_EXTERNAL_RERANKER_URL,
        "RAG_EXTERNAL_RERANKER_API_KEY": request.app.state.config.RAG_EXTERNAL_RERANKER_API_KEY,
        "RAG_EXTERNAL_RERANKER_TIMEOUT": request.app.state.config.RAG_EXTERNAL_RERANKER_TIMEOUT,
        # Chunking settings
        "TEXT_SPLITTER": request.app.state.config.TEXT_SPLITTER,
        "CHUNK_SIZE": request.app.state.config.CHUNK_SIZE,
        "CHUNK_MIN_SIZE_TARGET": request.app.state.config.CHUNK_MIN_SIZE_TARGET,
        "ENABLE_MARKDOWN_HEADER_TEXT_SPLITTER": request.app.state.config.ENABLE_MARKDOWN_HEADER_TEXT_SPLITTER,
        "CHUNK_OVERLAP": request.app.state.config.CHUNK_OVERLAP,
        # File upload settings
        "FILE_MAX_SIZE": request.app.state.config.FILE_MAX_SIZE,
        "FILE_MAX_COUNT": request.app.state.config.FILE_MAX_COUNT,
        "FILE_IMAGE_COMPRESSION_WIDTH": request.app.state.config.FILE_IMAGE_COMPRESSION_WIDTH,
        "FILE_IMAGE_COMPRESSION_HEIGHT": request.app.state.config.FILE_IMAGE_COMPRESSION_HEIGHT,
        "ALLOWED_FILE_EXTENSIONS": request.app.state.config.ALLOWED_FILE_EXTENSIONS,
        # Integration settings
        "ENABLE_GOOGLE_DRIVE_INTEGRATION": request.app.state.config.ENABLE_GOOGLE_DRIVE_INTEGRATION,
        "ENABLE_ONEDRIVE_INTEGRATION": request.app.state.config.ENABLE_ONEDRIVE_INTEGRATION,
        # Web search settings
        "web": {
            "ENABLE_WEB_SEARCH": request.app.state.config.ENABLE_WEB_SEARCH,
            "WEB_SEARCH_ENGINE": request.app.state.config.WEB_SEARCH_ENGINE,
            "WEB_SEARCH_TRUST_ENV": request.app.state.config.WEB_SEARCH_TRUST_ENV,
            "WEB_SEARCH_RESULT_COUNT": request.app.state.config.WEB_SEARCH_RESULT_COUNT,
            "WEB_SEARCH_CONCURRENT_REQUESTS": request.app.state.config.WEB_SEARCH_CONCURRENT_REQUESTS,
            "WEB_LOADER_CONCURRENT_REQUESTS": request.app.state.config.WEB_LOADER_CONCURRENT_REQUESTS,
            "WEB_SEARCH_DOMAIN_FILTER_LIST": request.app.state.config.WEB_SEARCH_DOMAIN_FILTER_LIST,
            "BYPASS_WEB_SEARCH_EMBEDDING_AND_RETRIEVAL": request.app.state.config.BYPASS_WEB_SEARCH_EMBEDDING_AND_RETRIEVAL,
            "BYPASS_WEB_SEARCH_WEB_LOADER": request.app.state.config.BYPASS_WEB_SEARCH_WEB_LOADER,
            "OLLAMA_CLOUD_WEB_SEARCH_API_KEY": request.app.state.config.OLLAMA_CLOUD_WEB_SEARCH_API_KEY,
            "SEARXNG_QUERY_URL": request.app.state.config.SEARXNG_QUERY_URL,
            "SEARXNG_LANGUAGE": request.app.state.config.SEARXNG_LANGUAGE,
            "YACY_QUERY_URL": request.app.state.config.YACY_QUERY_URL,
            "YACY_USERNAME": request.app.state.config.YACY_USERNAME,
            "YACY_PASSWORD": request.app.state.config.YACY_PASSWORD,
            "GOOGLE_PSE_API_KEY": request.app.state.config.GOOGLE_PSE_API_KEY,
            "GOOGLE_PSE_ENGINE_ID": request.app.state.config.GOOGLE_PSE_ENGINE_ID,
            "BRAVE_SEARCH_API_KEY": request.app.state.config.BRAVE_SEARCH_API_KEY,
            "KAGI_SEARCH_API_KEY": request.app.state.config.KAGI_SEARCH_API_KEY,
            "MOJEEK_SEARCH_API_KEY": request.app.state.config.MOJEEK_SEARCH_API_KEY,
            "BOCHA_SEARCH_API_KEY": request.app.state.config.BOCHA_SEARCH_API_KEY,
            "SERPSTACK_API_KEY": request.app.state.config.SERPSTACK_API_KEY,
            "SERPSTACK_HTTPS": request.app.state.config.SERPSTACK_HTTPS,
            "SERPER_API_KEY": request.app.state.config.SERPER_API_KEY,
            "SERPLY_API_KEY": request.app.state.config.SERPLY_API_KEY,
            "TAVILY_API_KEY": request.app.state.config.TAVILY_API_KEY,
            "SEARCHAPI_API_KEY": request.app.state.config.SEARCHAPI_API_KEY,
            "SEARCHAPI_ENGINE": request.app.state.config.SEARCHAPI_ENGINE,
            "SERPAPI_API_KEY": request.app.state.config.SERPAPI_API_KEY,
            "SERPAPI_ENGINE": request.app.state.config.SERPAPI_ENGINE,
            "JINA_API_KEY": request.app.state.config.JINA_API_KEY,
            "JINA_API_BASE_URL": request.app.state.config.JINA_API_BASE_URL,
            "BING_SEARCH_V7_ENDPOINT": request.app.state.config.BING_SEARCH_V7_ENDPOINT,
            "BING_SEARCH_V7_SUBSCRIPTION_KEY": request.app.state.config.BING_SEARCH_V7_SUBSCRIPTION_KEY,
            "EXA_API_KEY": request.app.state.config.EXA_API_KEY,
            "PERPLEXITY_API_KEY": request.app.state.config.PERPLEXITY_API_KEY,
            "PERPLEXITY_MODEL": request.app.state.config.PERPLEXITY_MODEL,
            "PERPLEXITY_SEARCH_CONTEXT_USAGE": request.app.state.config.PERPLEXITY_SEARCH_CONTEXT_USAGE,
            "PERPLEXITY_SEARCH_API_URL": request.app.state.config.PERPLEXITY_SEARCH_API_URL,
            "SOUGOU_API_SID": request.app.state.config.SOUGOU_API_SID,
            "SOUGOU_API_SK": request.app.state.config.SOUGOU_API_SK,
            "WEB_LOADER_ENGINE": request.app.state.config.WEB_LOADER_ENGINE,
            "WEB_LOADER_TIMEOUT": request.app.state.config.WEB_LOADER_TIMEOUT,
            "ENABLE_WEB_LOADER_SSL_VERIFICATION": request.app.state.config.ENABLE_WEB_LOADER_SSL_VERIFICATION,
            "PLAYWRIGHT_WS_URL": request.app.state.config.PLAYWRIGHT_WS_URL,
            "PLAYWRIGHT_TIMEOUT": request.app.state.config.PLAYWRIGHT_TIMEOUT,
            "FIRECRAWL_API_KEY": request.app.state.config.FIRECRAWL_API_KEY,
            "FIRECRAWL_API_BASE_URL": request.app.state.config.FIRECRAWL_API_BASE_URL,
            "FIRECRAWL_TIMEOUT": request.app.state.config.FIRECRAWL_TIMEOUT,
            "TAVILY_EXTRACT_DEPTH": request.app.state.config.TAVILY_EXTRACT_DEPTH,
            "EXTERNAL_WEB_SEARCH_URL": request.app.state.config.EXTERNAL_WEB_SEARCH_URL,
            "EXTERNAL_WEB_SEARCH_API_KEY": request.app.state.config.EXTERNAL_WEB_SEARCH_API_KEY,
            "EXTERNAL_WEB_LOADER_URL": request.app.state.config.EXTERNAL_WEB_LOADER_URL,
            "EXTERNAL_WEB_LOADER_API_KEY": request.app.state.config.EXTERNAL_WEB_LOADER_API_KEY,
            "YOUTUBE_LOADER_LANGUAGE": request.app.state.config.YOUTUBE_LOADER_LANGUAGE,
            "YOUTUBE_LOADER_PROXY_URL": request.app.state.config.YOUTUBE_LOADER_PROXY_URL,
            "YOUTUBE_LOADER_TRANSLATION": request.app.state.YOUTUBE_LOADER_TRANSLATION,
        },
    }


####################################
#
# 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],
) -> 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.
    """
    min_chunk_size_target = request.app.state.config.CHUNK_MIN_SIZE_TARGET
    max_chunk_size = request.app.state.config.CHUNK_SIZE

    if min_chunk_size_target <= 0:
        return chunks

    measure_chunk_size = len
    if request.app.state.config.TEXT_SPLITTER == "token":
        encoding = tiktoken.get_encoding(
            str(request.app.state.config.TIKTOKEN_ENCODING_NAME)
        )
        measure_chunk_size = lambda text: len(encoding.encode(text))

    processed_chunks: 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  # First chunk initialization

        proposed_content = f"{current_content}\n\n{next_chunk.page_content}"

        can_merge = (
            can_merge_chunks(current_chunk, next_chunk)
            and measure_chunk_size(current_content) < min_chunk_size_target
            and measure_chunk_size(proposed_content) <= max_chunk_size
        )

        if can_merge:
            current_content = proposed_content
        else:
            processed_chunks.append(
                Document(
                    page_content=current_content,
                    metadata={**current_chunk.metadata},
                )
            )
            current_chunk = next_chunk
            current_content = next_chunk.page_content

    if current_chunk is not None:
        processed_chunks.append(
            Document(
                page_content=current_content,
                metadata={**current_chunk.metadata},
            )
        )

    return processed_chunks


def save_docs_to_vector_db(
    request: Request,
    docs,
    collection_name,
    metadata: Optional[dict] = 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(
        f"save_docs_to_vector_db: document {_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:
                log.info(f"Document with hash {metadata['hash']} already exists")
                raise ValueError(ERROR_MESSAGES.DUPLICATE_CONTENT)

    if split:
        if request.app.state.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 request.app.state.config.CHUNK_MIN_SIZE_TARGET > 0:
                docs = merge_docs_to_target_size(request, docs)

        if request.app.state.config.TEXT_SPLITTER in ["", "character"]:
            text_splitter = RecursiveCharacterTextSplitter(
                chunk_size=request.app.state.config.CHUNK_SIZE,
                chunk_overlap=request.app.state.config.CHUNK_OVERLAP,
                add_start_index=True,
            )
            docs = text_splitter.split_documents(docs)
        elif request.app.state.config.TEXT_SPLITTER == "token":
            log.info(
                f"Using token text splitter: {request.app.state.config.TIKTOKEN_ENCODING_NAME}"
            )

            tiktoken.get_encoding(str(request.app.state.config.TIKTOKEN_ENCODING_NAME))
            text_splitter = TokenTextSplitter(
                encoding_name=str(request.app.state.config.TIKTOKEN_ENCODING_NAME),
                chunk_size=request.app.state.config.CHUNK_SIZE,
                chunk_overlap=request.app.state.config.CHUNK_OVERLAP,
                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": request.app.state.config.RAG_EMBEDDING_ENGINE,
                "model": request.app.state.config.RAG_EMBEDDING_MODEL,
            },
        }
        for doc in docs
    ]

    try:
        if VECTOR_DB_CLIENT.has_collection(collection_name=collection_name):
            log.info(f"collection {collection_name} already exists")

            if overwrite:
                VECTOR_DB_CLIENT.delete_collection(collection_name=collection_name)
                log.info(f"deleting existing collection {collection_name}")
            elif add is False:
                log.info(
                    f"collection {collection_name} already exists, overwrite is False and add is False"
                )
                return True

        log.info(f"generating embeddings for {collection_name}")
        embedding_function = get_embedding_function(
            request.app.state.config.RAG_EMBEDDING_ENGINE,
            request.app.state.config.RAG_EMBEDDING_MODEL,
            request.app.state.ef,
            (
                request.app.state.config.RAG_OPENAI_API_BASE_URL
                if request.app.state.config.RAG_EMBEDDING_ENGINE == "openai"
                else (
                    request.app.state.config.RAG_OLLAMA_BASE_URL
                    if request.app.state.config.RAG_EMBEDDING_ENGINE == "ollama"
                    else request.app.state.config.RAG_AZURE_OPENAI_BASE_URL
                )
            ),
            (
                request.app.state.config.RAG_OPENAI_API_KEY
                if request.app.state.config.RAG_EMBEDDING_ENGINE == "openai"
                else (
                    request.app.state.config.RAG_OLLAMA_API_KEY
                    if request.app.state.config.RAG_EMBEDDING_ENGINE == "ollama"
                    else request.app.state.config.RAG_AZURE_OPENAI_API_KEY
                )
            ),
            request.app.state.config.RAG_EMBEDDING_BATCH_SIZE,
            azure_api_version=(
                request.app.state.config.RAG_AZURE_OPENAI_API_VERSION
                if request.app.state.config.RAG_EMBEDDING_ENGINE == "azure_openai"
                else None
            ),
            enable_async=request.app.state.config.ENABLE_ASYNC_EMBEDDING,
        )

        # Run async embedding in sync context
        embeddings = asyncio.run(
            embedding_function(
                list(map(lambda x: x.replace("\n", " "), texts)),
                prefix=RAG_EMBEDDING_CONTENT_PREFIX,
                user=user,
            )
        )
        log.info(f"embeddings generated {len(embeddings)} for {len(texts)} items")

        items = [
            {
                "id": str(uuid.uuid4()),
                "text": text,
                "vector": embeddings[idx],
                "metadata": metadatas[idx],
            }
            for idx, text in enumerate(texts)
        ]

        log.info(f"adding to collection {collection_name}")
        VECTOR_DB_CLIENT.insert(
            collection_name=collection_name,
            items=items,
        )

        log.info(f"added {len(items)} items to collection {collection_name}")
        return True
    except Exception as e:
        log.exception(e)
        raise e


class ProcessFileForm(BaseModel):
    file_id: str
    content: Optional[str] = None
    collection_name: Optional[str] = None


@router.post("/process/file")
def process_file(
    request: Request,
    form_data: ProcessFileForm,
    user=Depends(get_verified_user),
    db: Session = Depends(get_session),
):
    """
    Process a file and save its content to the vector database.
    """
    if user.role == "admin":
        file = Files.get_file_by_id(form_data.file_id, db=db)
    else:
        file = 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}"

            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
                    VECTOR_DB_CLIENT.delete_collection(
                        collection_name=f"file-{file.id}"
                    )
                except:
                    # 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 = 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 = Storage.get_file(file_path)
                    loader = Loader(
                        engine=request.app.state.config.CONTENT_EXTRACTION_ENGINE,
                        user=user,
                        DATALAB_MARKER_API_KEY=request.app.state.config.DATALAB_MARKER_API_KEY,
                        DATALAB_MARKER_API_BASE_URL=request.app.state.config.DATALAB_MARKER_API_BASE_URL,
                        DATALAB_MARKER_ADDITIONAL_CONFIG=request.app.state.config.DATALAB_MARKER_ADDITIONAL_CONFIG,
                        DATALAB_MARKER_SKIP_CACHE=request.app.state.config.DATALAB_MARKER_SKIP_CACHE,
                        DATALAB_MARKER_FORCE_OCR=request.app.state.config.DATALAB_MARKER_FORCE_OCR,
                        DATALAB_MARKER_PAGINATE=request.app.state.config.DATALAB_MARKER_PAGINATE,
                        DATALAB_MARKER_STRIP_EXISTING_OCR=request.app.state.config.DATALAB_MARKER_STRIP_EXISTING_OCR,
                        DATALAB_MARKER_DISABLE_IMAGE_EXTRACTION=request.app.state.config.DATALAB_MARKER_DISABLE_IMAGE_EXTRACTION,
                        DATALAB_MARKER_FORMAT_LINES=request.app.state.config.DATALAB_MARKER_FORMAT_LINES,
                        DATALAB_MARKER_USE_LLM=request.app.state.config.DATALAB_MARKER_USE_LLM,
                        DATALAB_MARKER_OUTPUT_FORMAT=request.app.state.config.DATALAB_MARKER_OUTPUT_FORMAT,
                        EXTERNAL_DOCUMENT_LOADER_URL=request.app.state.config.EXTERNAL_DOCUMENT_LOADER_URL,
                        EXTERNAL_DOCUMENT_LOADER_API_KEY=request.app.state.config.EXTERNAL_DOCUMENT_LOADER_API_KEY,
                        TIKA_SERVER_URL=request.app.state.config.TIKA_SERVER_URL,
                        DOCLING_SERVER_URL=request.app.state.config.DOCLING_SERVER_URL,
                        DOCLING_API_KEY=request.app.state.config.DOCLING_API_KEY,
                        DOCLING_PARAMS=request.app.state.config.DOCLING_PARAMS,
                        PDF_EXTRACT_IMAGES=request.app.state.config.PDF_EXTRACT_IMAGES,
                        DOCUMENT_INTELLIGENCE_ENDPOINT=request.app.state.config.DOCUMENT_INTELLIGENCE_ENDPOINT,
                        DOCUMENT_INTELLIGENCE_KEY=request.app.state.config.DOCUMENT_INTELLIGENCE_KEY,
                        DOCUMENT_INTELLIGENCE_MODEL=request.app.state.config.DOCUMENT_INTELLIGENCE_MODEL,
                        MISTRAL_OCR_API_BASE_URL=request.app.state.config.MISTRAL_OCR_API_BASE_URL,
                        MISTRAL_OCR_API_KEY=request.app.state.config.MISTRAL_OCR_API_KEY,
                        MINERU_API_MODE=request.app.state.config.MINERU_API_MODE,
                        MINERU_API_URL=request.app.state.config.MINERU_API_URL,
                        MINERU_API_KEY=request.app.state.config.MINERU_API_KEY,
                        MINERU_API_TIMEOUT=request.app.state.config.MINERU_API_TIMEOUT,
                        MINERU_PARAMS=request.app.state.config.MINERU_PARAMS,
                    )
                    docs = loader.load(
                        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(f"text_content: {text_content}")
            Files.update_file_data_by_id(
                file.id,
                {"content": text_content},
                db=db,
            )
            hash = calculate_sha256_string(text_content)

            if request.app.state.config.BYPASS_EMBEDDING_AND_RETRIEVAL:
                Files.update_file_data_by_id(file.id, {"status": "completed"}, db=db)
                Files.update_file_hash_by_id(file.id, hash, db=db)
                return {
                    "status": True,
                    "collection_name": None,
                    "filename": file.filename,
                    "content": text_content,
                }
            else:
                try:
                    result = save_docs_to_vector_db(
                        request,
                        docs=docs,
                        collection_name=collection_name,
                        metadata={
                            "file_id": file.id,
                            "name": file.filename,
                            "hash": hash,
                        },
                        add=(True if form_data.collection_name else False),
                        user=user,
                    )
                    log.info(f"added {len(docs)} items to collection {collection_name}")

                    if result:
                        Files.update_file_metadata_by_id(
                            file.id,
                            {
                                "collection_name": collection_name,
                            },
                            db=db,
                        )

                        Files.update_file_data_by_id(
                            file.id,
                            {"status": "completed"},
                            db=db,
                        )
                        Files.update_file_hash_by_id(file.id, hash, db=db)

                        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)
            Files.update_file_data_by_id(
                file.id,
                {"status": "failed"},
                db=db,
            )
            # Clear the hash so the file can be re-uploaded after fixing the issue
            Files.update_file_hash_by_id(file.id, None, db=db)

            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: Optional[str] = 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)

    docs = [
        Document(
            page_content=form_data.content,
            metadata={"name": form_data.name, "created_by": user.id},
        )
    ]
    text_content = form_data.content
    log.debug(f"text_content: {text_content}")

    result = await run_in_threadpool(
        save_docs_to_vector_db, request, docs, collection_name, user=user
    )
    if result:
        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"),
    user=Depends(get_verified_user),
):
    try:
        content, docs = await run_in_threadpool(
            get_content_from_url, request, form_data.url
        )
        log.debug(f"text_content: {content}")

        if process:
            collection_name = form_data.collection_name
            if not collection_name:
                collection_name = calculate_sha256_string(form_data.url)[:63]

            if not request.app.state.config.BYPASS_WEB_SEARCH_EMBEDDING_AND_RETRIEVAL:
                await run_in_threadpool(
                    save_docs_to_vector_db,
                    request,
                    docs,
                    collection_name,
                    overwrite=True,
                    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 Exception as e:
        log.exception(e)
        raise HTTPException(
            status_code=status.HTTP_400_BAD_REQUEST,
            detail=ERROR_MESSAGES.DEFAULT(e),
        )


def search_web(
    request: Request, engine: str, query: str, user=None
) -> list[SearchResult]:
    """Search the web using a search engine and return the results as a list of SearchResult objects.
    Will look for a search engine API key in environment variables in the following order:
    - SEARXNG_QUERY_URL
    - YACY_QUERY_URL + YACY_USERNAME + YACY_PASSWORD
    - GOOGLE_PSE_API_KEY + GOOGLE_PSE_ENGINE_ID
    - BRAVE_SEARCH_API_KEY
    - KAGI_SEARCH_API_KEY
    - MOJEEK_SEARCH_API_KEY
    - BOCHA_SEARCH_API_KEY
    - SERPSTACK_API_KEY
    - SERPER_API_KEY
    - SERPLY_API_KEY
    - TAVILY_API_KEY
    - EXA_API_KEY
    - PERPLEXITY_API_KEY
    - SOUGOU_API_SID + SOUGOU_API_SK
    - SEARCHAPI_API_KEY + SEARCHAPI_ENGINE (by default `google`)
    - SERPAPI_API_KEY + SERPAPI_ENGINE (by default `google`)
    Args:
        query (str): The query to search for
    """

    # TODO: add playwright to search the web
    if engine == "ollama_cloud":
        return search_ollama_cloud(
            "https://ollama.com",
            request.app.state.config.OLLAMA_CLOUD_WEB_SEARCH_API_KEY,
            query,
            request.app.state.config.WEB_SEARCH_RESULT_COUNT,
            request.app.state.config.WEB_SEARCH_DOMAIN_FILTER_LIST,
        )
    elif engine == "perplexity_search":
        if request.app.state.config.PERPLEXITY_API_KEY:
            return search_perplexity_search(
                request.app.state.config.PERPLEXITY_API_KEY,
                query,
                request.app.state.config.WEB_SEARCH_RESULT_COUNT,
                request.app.state.config.WEB_SEARCH_DOMAIN_FILTER_LIST,
                request.app.state.config.PERPLEXITY_SEARCH_API_URL,
                user,
            )
        else:
            raise Exception("No PERPLEXITY_API_KEY found in environment variables")
    elif engine == "searxng":
        if request.app.state.config.SEARXNG_QUERY_URL:
            searxng_kwargs = {"language": request.app.state.config.SEARXNG_LANGUAGE}
            return search_searxng(
                request.app.state.config.SEARXNG_QUERY_URL,
                query,
                request.app.state.config.WEB_SEARCH_RESULT_COUNT,
                request.app.state.config.WEB_SEARCH_DOMAIN_FILTER_LIST,
                **searxng_kwargs,
            )
        else:
            raise Exception("No SEARXNG_QUERY_URL found in environment variables")
    elif engine == "yacy":
        if request.app.state.config.YACY_QUERY_URL:
            return search_yacy(
                request.app.state.config.YACY_QUERY_URL,
                request.app.state.config.YACY_USERNAME,
                request.app.state.config.YACY_PASSWORD,
                query,
                request.app.state.config.WEB_SEARCH_RESULT_COUNT,
                request.app.state.config.WEB_SEARCH_DOMAIN_FILTER_LIST,
            )
        else:
            raise Exception("No YACY_QUERY_URL found in environment variables")
    elif engine == "google_pse":
        if (
            request.app.state.config.GOOGLE_PSE_API_KEY
            and request.app.state.config.GOOGLE_PSE_ENGINE_ID
        ):
            return search_google_pse(
                request.app.state.config.GOOGLE_PSE_API_KEY,
                request.app.state.config.GOOGLE_PSE_ENGINE_ID,
                query,
                request.app.state.config.WEB_SEARCH_RESULT_COUNT,
                request.app.state.config.WEB_SEARCH_DOMAIN_FILTER_LIST,
                referer=request.app.state.config.WEBUI_URL,
            )
        else:
            raise Exception(
                "No GOOGLE_PSE_API_KEY or GOOGLE_PSE_ENGINE_ID found in environment variables"
            )
    elif engine == "brave":
        if request.app.state.config.BRAVE_SEARCH_API_KEY:
            return search_brave(
                request.app.state.config.BRAVE_SEARCH_API_KEY,
                query,
                request.app.state.config.WEB_SEARCH_RESULT_COUNT,
                request.app.state.config.WEB_SEARCH_DOMAIN_FILTER_LIST,
            )
        else:
            raise Exception("No BRAVE_SEARCH_API_KEY found in environment variables")
    elif engine == "kagi":
        if request.app.state.config.KAGI_SEARCH_API_KEY:
            return search_kagi(
                request.app.state.config.KAGI_SEARCH_API_KEY,
                query,
                request.app.state.config.WEB_SEARCH_RESULT_COUNT,
                request.app.state.config.WEB_SEARCH_DOMAIN_FILTER_LIST,
            )
        else:
            raise Exception("No KAGI_SEARCH_API_KEY found in environment variables")
    elif engine == "mojeek":
        if request.app.state.config.MOJEEK_SEARCH_API_KEY:
            return search_mojeek(
                request.app.state.config.MOJEEK_SEARCH_API_KEY,
                query,
                request.app.state.config.WEB_SEARCH_RESULT_COUNT,
                request.app.state.config.WEB_SEARCH_DOMAIN_FILTER_LIST,
            )
        else:
            raise Exception("No MOJEEK_SEARCH_API_KEY found in environment variables")
    elif engine == "bocha":
        if request.app.state.config.BOCHA_SEARCH_API_KEY:
            return search_bocha(
                request.app.state.config.BOCHA_SEARCH_API_KEY,
                query,
                request.app.state.config.WEB_SEARCH_RESULT_COUNT,
                request.app.state.config.WEB_SEARCH_DOMAIN_FILTER_LIST,
            )
        else:
            raise Exception("No BOCHA_SEARCH_API_KEY found in environment variables")
    elif engine == "serpstack":
        if request.app.state.config.SERPSTACK_API_KEY:
            return search_serpstack(
                request.app.state.config.SERPSTACK_API_KEY,
                query,
                request.app.state.config.WEB_SEARCH_RESULT_COUNT,
                request.app.state.config.WEB_SEARCH_DOMAIN_FILTER_LIST,
                https_enabled=request.app.state.config.SERPSTACK_HTTPS,
            )
        else:
            raise Exception("No SERPSTACK_API_KEY found in environment variables")
    elif engine == "serper":
        if request.app.state.config.SERPER_API_KEY:
            return search_serper(
                request.app.state.config.SERPER_API_KEY,
                query,
                request.app.state.config.WEB_SEARCH_RESULT_COUNT,
                request.app.state.config.WEB_SEARCH_DOMAIN_FILTER_LIST,
            )
        else:
            raise Exception("No SERPER_API_KEY found in environment variables")
    elif engine == "serply":
        if request.app.state.config.SERPLY_API_KEY:
            return search_serply(
                request.app.state.config.SERPLY_API_KEY,
                query,
                request.app.state.config.WEB_SEARCH_RESULT_COUNT,
                filter_list=request.app.state.config.WEB_SEARCH_DOMAIN_FILTER_LIST,
            )
        else:
            raise Exception("No SERPLY_API_KEY found in environment variables")
    elif engine == "duckduckgo":
        return search_duckduckgo(
            query,
            request.app.state.config.WEB_SEARCH_RESULT_COUNT,
            request.app.state.config.WEB_SEARCH_DOMAIN_FILTER_LIST,
            concurrent_requests=request.app.state.config.WEB_SEARCH_CONCURRENT_REQUESTS,
            backend=request.app.state.config.DDGS_BACKEND,
        )
    elif engine == "tavily":
        if request.app.state.config.TAVILY_API_KEY:
            return search_tavily(
                request.app.state.config.TAVILY_API_KEY,
                query,
                request.app.state.config.WEB_SEARCH_RESULT_COUNT,
                request.app.state.config.WEB_SEARCH_DOMAIN_FILTER_LIST,
            )
        else:
            raise Exception("No TAVILY_API_KEY found in environment variables")
    elif engine == "exa":
        if request.app.state.config.EXA_API_KEY:
            return search_exa(
                request.app.state.config.EXA_API_KEY,
                query,
                request.app.state.config.WEB_SEARCH_RESULT_COUNT,
                request.app.state.config.WEB_SEARCH_DOMAIN_FILTER_LIST,
            )
        else:
            raise Exception("No EXA_API_KEY found in environment variables")
    elif engine == "searchapi":
        if request.app.state.config.SEARCHAPI_API_KEY:
            return search_searchapi(
                request.app.state.config.SEARCHAPI_API_KEY,
                request.app.state.config.SEARCHAPI_ENGINE,
                query,
                request.app.state.config.WEB_SEARCH_RESULT_COUNT,
                request.app.state.config.WEB_SEARCH_DOMAIN_FILTER_LIST,
            )
        else:
            raise Exception("No SEARCHAPI_API_KEY found in environment variables")
    elif engine == "serpapi":
        if request.app.state.config.SERPAPI_API_KEY:
            return search_serpapi(
                request.app.state.config.SERPAPI_API_KEY,
                request.app.state.config.SERPAPI_ENGINE,
                query,
                request.app.state.config.WEB_SEARCH_RESULT_COUNT,
                request.app.state.config.WEB_SEARCH_DOMAIN_FILTER_LIST,
            )
        else:
            raise Exception("No SERPAPI_API_KEY found in environment variables")
    elif engine == "jina":
        return search_jina(
            request.app.state.config.JINA_API_KEY,
            query,
            request.app.state.config.WEB_SEARCH_RESULT_COUNT,
            request.app.state.config.JINA_API_BASE_URL,
        )
    elif engine == "bing":
        return search_bing(
            request.app.state.config.BING_SEARCH_V7_SUBSCRIPTION_KEY,
            request.app.state.config.BING_SEARCH_V7_ENDPOINT,
            str(DEFAULT_LOCALE),
            query,
            request.app.state.config.WEB_SEARCH_RESULT_COUNT,
            request.app.state.config.WEB_SEARCH_DOMAIN_FILTER_LIST,
        )
    elif engine == "azure":
        if (
            request.app.state.config.AZURE_AI_SEARCH_API_KEY
            and request.app.state.config.AZURE_AI_SEARCH_ENDPOINT
            and request.app.state.config.AZURE_AI_SEARCH_INDEX_NAME
        ):
            return search_azure(
                request.app.state.config.AZURE_AI_SEARCH_API_KEY,
                request.app.state.config.AZURE_AI_SEARCH_ENDPOINT,
                request.app.state.config.AZURE_AI_SEARCH_INDEX_NAME,
                query,
                request.app.state.config.WEB_SEARCH_RESULT_COUNT,
                request.app.state.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 == "exa":
        return search_exa(
            request.app.state.config.EXA_API_KEY,
            query,
            request.app.state.config.WEB_SEARCH_RESULT_COUNT,
            request.app.state.config.WEB_SEARCH_DOMAIN_FILTER_LIST,
        )
    elif engine == "perplexity":
        return search_perplexity(
            request.app.state.config.PERPLEXITY_API_KEY,
            query,
            request.app.state.config.WEB_SEARCH_RESULT_COUNT,
            request.app.state.config.WEB_SEARCH_DOMAIN_FILTER_LIST,
            model=request.app.state.config.PERPLEXITY_MODEL,
            search_context_usage=request.app.state.config.PERPLEXITY_SEARCH_CONTEXT_USAGE,
        )
    elif engine == "sougou":
        if (
            request.app.state.config.SOUGOU_API_SID
            and request.app.state.config.SOUGOU_API_SK
        ):
            return search_sougou(
                request.app.state.config.SOUGOU_API_SID,
                request.app.state.config.SOUGOU_API_SK,
                query,
                request.app.state.config.WEB_SEARCH_RESULT_COUNT,
                request.app.state.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 search_firecrawl(
            request.app.state.config.FIRECRAWL_API_BASE_URL,
            request.app.state.config.FIRECRAWL_API_KEY,
            query,
            request.app.state.config.WEB_SEARCH_RESULT_COUNT,
            request.app.state.config.WEB_SEARCH_DOMAIN_FILTER_LIST,
        )
    elif engine == "external":
        return search_external(
            request,
            request.app.state.config.EXTERNAL_WEB_SEARCH_URL,
            request.app.state.config.EXTERNAL_WEB_SEARCH_API_KEY,
            query,
            request.app.state.config.WEB_SEARCH_RESULT_COUNT,
            request.app.state.config.WEB_SEARCH_DOMAIN_FILTER_LIST,
            user=user,
        )
    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)
):
    if not request.app.state.config.ENABLE_WEB_SEARCH:
        raise HTTPException(
            status_code=status.HTTP_403_FORBIDDEN,
            detail=ERROR_MESSAGES.ACCESS_PROHIBITED,
        )

    if user.role != "admin" and not has_permission(
        user.id, "features.web_search", request.app.state.config.USER_PERMISSIONS
    ):
        raise HTTPException(
            status_code=status.HTTP_403_FORBIDDEN,
            detail=ERROR_MESSAGES.ACCESS_PROHIBITED,
        )

    urls = []
    result_items = []

    try:
        logging.debug(
            f"trying to web search with {request.app.state.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 = request.app.state.config.WEB_SEARCH_CONCURRENT_REQUESTS

        if concurrent_limit:
            # Limited concurrency with semaphore
            semaphore = asyncio.Semaphore(concurrent_limit)

            async def search_with_limit(query):
                async with semaphore:
                    return await run_in_threadpool(
                        search_web,
                        request,
                        request.app.state.config.WEB_SEARCH_ENGINE,
                        query,
                        user,
                    )

            search_tasks = [search_with_limit(query) for query in form_data.queries]
        else:
            # Unlimited parallel execution (previous behavior)
            search_tasks = [
                run_in_threadpool(
                    search_web,
                    request,
                    request.app.state.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(f"urls: {urls}")

    except Exception as e:
        log.exception(e)

        raise HTTPException(
            status_code=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 request.app.state.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 = get_web_loader(
                urls,
                verify_ssl=request.app.state.config.ENABLE_WEB_LOADER_SSL_VERIFICATION,
                requests_per_second=request.app.state.config.WEB_LOADER_CONCURRENT_REQUESTS,
                trust_env=request.app.state.config.WEB_SEARCH_TRUST_ENV,
            )
            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
        result_items = [
            dict(item) for item in result_items if item.link in urls
        ]  # only keep the search results that have been loaded

        if request.app.state.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
            collection_name = (
                f"web-search-{calculate_sha256_string('-'.join(form_data.queries))}"[
                    :63
                ]
            )

            try:
                await run_in_threadpool(
                    save_docs_to_vector_db,
                    request,
                    docs,
                    collection_name,
                    overwrite=True,
                    user=user,
                )
            except Exception as e:
                log.debug(f"error saving docs: {e}")

            return {
                "status": True,
                "collection_names": [collection_name],
                "items": result_items,
                "filenames": urls,
                "loaded_count": len(docs),
            }
    except Exception as e:
        log.exception(e)
        raise HTTPException(
            status_code=status.HTTP_400_BAD_REQUEST,
            detail=ERROR_MESSAGES.DEFAULT(e),
        )


class QueryDocForm(BaseModel):
    collection_name: str
    query: str
    k: Optional[int] = None
    k_reranker: Optional[int] = None
    r: Optional[float] = None
    hybrid: Optional[bool] = None


@router.post("/query/doc")
async def query_doc_handler(
    request: Request,
    form_data: QueryDocForm,
    user=Depends(get_verified_user),
):
    try:
        if request.app.state.config.ENABLE_RAG_HYBRID_SEARCH and (
            form_data.hybrid is None or form_data.hybrid
        ):
            collection_results = {}
            collection_results[form_data.collection_name] = VECTOR_DB_CLIENT.get(
                collection_name=form_data.collection_name
            )
            return await query_doc_with_hybrid_search(
                collection_name=form_data.collection_name,
                collection_result=collection_results[form_data.collection_name],
                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 request.app.state.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 request.app.state.config.TOP_K_RERANKER,
                r=(
                    form_data.r
                    if form_data.r
                    else request.app.state.config.RELEVANCE_THRESHOLD
                ),
                hybrid_bm25_weight=(
                    form_data.hybrid_bm25_weight
                    if form_data.hybrid_bm25_weight
                    else request.app.state.config.HYBRID_BM25_WEIGHT
                ),
                user=user,
            )
        else:
            query_embedding = await request.app.state.EMBEDDING_FUNCTION(
                form_data.query, prefix=RAG_EMBEDDING_QUERY_PREFIX, user=user
            )
            return query_doc(
                collection_name=form_data.collection_name,
                query_embedding=query_embedding,
                k=form_data.k if form_data.k else request.app.state.config.TOP_K,
                user=user,
            )
    except Exception as e:
        log.exception(e)
        raise HTTPException(
            status_code=status.HTTP_400_BAD_REQUEST,
            detail=ERROR_MESSAGES.DEFAULT(e),
        )


class QueryCollectionsForm(BaseModel):
    collection_names: list[str]
    query: str
    k: Optional[int] = None
    k_reranker: Optional[int] = None
    r: Optional[float] = None
    hybrid: Optional[bool] = None
    hybrid_bm25_weight: Optional[float] = None
    enable_enriched_texts: Optional[bool] = None


@router.post("/query/collection")
async def query_collection_handler(
    request: Request,
    form_data: QueryCollectionsForm,
    user=Depends(get_verified_user),
):
    try:
        if request.app.state.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 request.app.state.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 request.app.state.config.TOP_K_RERANKER,
                r=(
                    form_data.r
                    if form_data.r
                    else request.app.state.config.RELEVANCE_THRESHOLD
                ),
                hybrid_bm25_weight=(
                    form_data.hybrid_bm25_weight
                    if form_data.hybrid_bm25_weight
                    else request.app.state.config.HYBRID_BM25_WEIGHT
                ),
                enable_enriched_texts=(
                    form_data.enable_enriched_texts
                    if form_data.enable_enriched_texts is not None
                    else request.app.state.config.ENABLE_RAG_HYBRID_SEARCH_ENRICHED_TEXTS
                ),
            )
        else:
            return await query_collection(
                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 request.app.state.config.TOP_K,
            )

    except Exception as e:
        log.exception(e)
        raise HTTPException(
            status_code=status.HTTP_400_BAD_REQUEST,
            detail=ERROR_MESSAGES.DEFAULT(e),
        )


####################################
#
# Vector DB operations
#
####################################


class DeleteForm(BaseModel):
    collection_name: str
    file_id: str


@router.post("/delete")
def delete_entries_from_collection(
    form_data: DeleteForm,
    user=Depends(get_admin_user),
    db: Session = Depends(get_session),
):
    try:
        if VECTOR_DB_CLIENT.has_collection(collection_name=form_data.collection_name):
            file = 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

            VECTOR_DB_CLIENT.delete(
                collection_name=form_data.collection_name,
                metadata={"hash": hash},
            )
            return {"status": True}
        else:
            return {"status": False}
    except Exception as e:
        log.exception(e)
        return {"status": False}


@router.post("/reset/db")
def reset_vector_db(user=Depends(get_admin_user), db: Session = Depends(get_session)):
    VECTOR_DB_CLIENT.reset()
    Knowledges.delete_all_knowledge(db=db)


@router.post("/reset/uploads")
def reset_upload_dir(user=Depends(get_admin_user)) -> bool:
    folder = f"{UPLOAD_DIR}"
    try:
        # Check if the directory exists
        if os.path.exists(folder):
            # Iterate over all the files and directories in the specified directory
            for filename in os.listdir(folder):
                file_path = os.path.join(folder, filename)
                try:
                    if os.path.isfile(file_path) or os.path.islink(file_path):
                        os.unlink(file_path)  # Remove the file or link
                    elif os.path.isdir(file_path):
                        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}")
    return True


if ENV == "dev":

    @router.get("/ef/{text}")
    async def get_embeddings(request: Request, text: Optional[str] = "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: Optional[str] = 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: Session = Depends(get_session),
) -> BatchProcessFilesResponse:
    """
    Process a batch of files and save them to the vector database.
    """

    collection_name = form_data.collection_name

    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:
            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,
                add=True,
                user=user,
            )

            # Update all files with collection name
            for file_update, file_result in zip(file_updates, file_results):
                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, error=str(e))
                )

    return BatchProcessFilesResponse(results=file_results, errors=file_errors)
