feat:新增套餐系统，删除积分制

backend/open_webui/retrieval/loaders/datalab_marker.py

@@ -0,0 +1,278 @@
+import os
+import time
+import requests
+import logging
+import json
+from typing import List, Optional
+from langchain_core.documents import Document
+from fastapi import HTTPException, status
+
+log = logging.getLogger(__name__)
+
+
+class DatalabMarkerLoader:
+    def __init__(
+        self,
+        file_path: str,
+        api_key: str,
+        api_base_url: str,
+        additional_config: Optional[str] = None,
+        use_llm: bool = False,
+        skip_cache: bool = False,
+        force_ocr: bool = False,
+        paginate: bool = False,
+        strip_existing_ocr: bool = False,
+        disable_image_extraction: bool = False,
+        format_lines: bool = False,
+        output_format: str = None,
+    ):
+        self.file_path = file_path
+        self.api_key = api_key
+        self.api_base_url = api_base_url
+        self.additional_config = additional_config
+        self.use_llm = use_llm
+        self.skip_cache = skip_cache
+        self.force_ocr = force_ocr
+        self.paginate = paginate
+        self.strip_existing_ocr = strip_existing_ocr
+        self.disable_image_extraction = disable_image_extraction
+        self.format_lines = format_lines
+        self.output_format = output_format
+
+    def _get_mime_type(self, filename: str) -> str:
+        ext = filename.rsplit(".", 1)[-1].lower()
+        mime_map = {
+            "pdf": "application/pdf",
+            "xls": "application/vnd.ms-excel",
+            "xlsx": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
+            "ods": "application/vnd.oasis.opendocument.spreadsheet",
+            "doc": "application/msword",
+            "docx": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
+            "odt": "application/vnd.oasis.opendocument.text",
+            "ppt": "application/vnd.ms-powerpoint",
+            "pptx": "application/vnd.openxmlformats-officedocument.presentationml.presentation",
+            "odp": "application/vnd.oasis.opendocument.presentation",
+            "html": "text/html",
+            "epub": "application/epub+zip",
+            "png": "image/png",
+            "jpeg": "image/jpeg",
+            "jpg": "image/jpeg",
+            "webp": "image/webp",
+            "gif": "image/gif",
+            "tiff": "image/tiff",
+        }
+        return mime_map.get(ext, "application/octet-stream")
+
+    def check_marker_request_status(self, request_id: str) -> dict:
+        url = f"{self.api_base_url}/{request_id}"
+        headers = {"X-Api-Key": self.api_key}
+        try:
+            response = requests.get(url, headers=headers)
+            response.raise_for_status()
+            result = response.json()
+            log.info(f"Marker API status check for request {request_id}: {result}")
+            return result
+        except requests.HTTPError as e:
+            log.error(f"Error checking Marker request status: {e}")
+            raise HTTPException(
+                status.HTTP_502_BAD_GATEWAY,
+                detail=f"Failed to check Marker request: {e}",
+            )
+        except ValueError as e:
+            log.error(f"Invalid JSON checking Marker request: {e}")
+            raise HTTPException(
+                status.HTTP_502_BAD_GATEWAY, detail=f"Invalid JSON: {e}"
+            )
+
+    def load(self) -> List[Document]:
+        filename = os.path.basename(self.file_path)
+        mime_type = self._get_mime_type(filename)
+        headers = {"X-Api-Key": self.api_key}
+
+        form_data = {
+            "use_llm": str(self.use_llm).lower(),
+            "skip_cache": str(self.skip_cache).lower(),
+            "force_ocr": str(self.force_ocr).lower(),
+            "paginate": str(self.paginate).lower(),
+            "strip_existing_ocr": str(self.strip_existing_ocr).lower(),
+            "disable_image_extraction": str(self.disable_image_extraction).lower(),
+            "format_lines": str(self.format_lines).lower(),
+            "output_format": self.output_format,
+        }
+
+        if self.additional_config and self.additional_config.strip():
+            form_data["additional_config"] = self.additional_config
+
+        log.info(
+            f"Datalab Marker POST request parameters: {{'filename': '{filename}', 'mime_type': '{mime_type}', **{form_data}}}"
+        )
+
+        try:
+            with open(self.file_path, "rb") as f:
+                files = {"file": (filename, f, mime_type)}
+                response = requests.post(
+                    f"{self.api_base_url}",
+                    data=form_data,
+                    files=files,
+                    headers=headers,
+                )
+                response.raise_for_status()
+                result = response.json()
+        except FileNotFoundError:
+            raise HTTPException(
+                status.HTTP_404_NOT_FOUND, detail=f"File not found: {self.file_path}"
+            )
+        except requests.HTTPError as e:
+            raise HTTPException(
+                status.HTTP_400_BAD_REQUEST,
+                detail=f"Datalab Marker request failed: {e}",
+            )
+        except ValueError as e:
+            raise HTTPException(
+                status.HTTP_502_BAD_GATEWAY, detail=f"Invalid JSON response: {e}"
+            )
+        except Exception as e:
+            raise HTTPException(status.HTTP_500_INTERNAL_SERVER_ERROR, detail=str(e))
+
+        if not result.get("success"):
+            raise HTTPException(
+                status.HTTP_400_BAD_REQUEST,
+                detail=f"Datalab Marker request failed: {result.get('error', 'Unknown error')}",
+            )
+
+        check_url = result.get("request_check_url")
+        request_id = result.get("request_id")
+
+        # Check if this is a direct response (self-hosted) or polling response (DataLab)
+        if check_url:
+            # DataLab polling pattern
+            for _ in range(300):  # Up to 10 minutes
+                time.sleep(2)
+                try:
+                    poll_response = requests.get(check_url, headers=headers)
+                    poll_response.raise_for_status()
+                    poll_result = poll_response.json()
+                except (requests.HTTPError, ValueError) as e:
+                    raw_body = poll_response.text
+                    log.error(f"Polling error: {e}, response body: {raw_body}")
+                    raise HTTPException(
+                        status.HTTP_502_BAD_GATEWAY, detail=f"Polling failed: {e}"
+                    )
+
+                status_val = poll_result.get("status")
+                success_val = poll_result.get("success")
+
+                if status_val == "complete":
+                    summary = {
+                        k: poll_result.get(k)
+                        for k in (
+                            "status",
+                            "output_format",
+                            "success",
+                            "error",
+                            "page_count",
+                            "total_cost",
+                        )
+                    }
+                    log.info(
+                        f"Marker processing completed successfully: {json.dumps(summary, indent=2)}"
+                    )
+                    break
+
+                if status_val == "failed" or success_val is False:
+                    log.error(
+                        f"Marker poll failed full response: {json.dumps(poll_result, indent=2)}"
+                    )
+                    error_msg = (
+                        poll_result.get("error")
+                        or "Marker returned failure without error message"
+                    )
+                    raise HTTPException(
+                        status.HTTP_400_BAD_REQUEST,
+                        detail=f"Marker processing failed: {error_msg}",
+                    )
+            else:
+                raise HTTPException(
+                    status.HTTP_504_GATEWAY_TIMEOUT,
+                    detail="Marker processing timed out",
+                )
+
+            if not poll_result.get("success", False):
+                error_msg = poll_result.get("error") or "Unknown processing error"
+                raise HTTPException(
+                    status.HTTP_400_BAD_REQUEST,
+                    detail=f"Final processing failed: {error_msg}",
+                )
+
+            # DataLab format - content in format-specific fields
+            content_key = self.output_format.lower()
+            raw_content = poll_result.get(content_key)
+            final_result = poll_result
+        else:
+            # Self-hosted direct response - content in "output" field
+            if "output" in result:
+                log.info("Self-hosted Marker returned direct response without polling")
+                raw_content = result.get("output")
+                final_result = result
+            else:
+                available_fields = (
+                    list(result.keys())
+                    if isinstance(result, dict)
+                    else "non-dict response"
+                )
+                raise HTTPException(
+                    status.HTTP_502_BAD_GATEWAY,
+                    detail=f"Custom Marker endpoint returned success but no 'output' field found. Available fields: {available_fields}. Expected either 'request_check_url' for polling or 'output' field for direct response.",
+                )
+
+        if self.output_format.lower() == "json":
+            full_text = json.dumps(raw_content, indent=2)
+        elif self.output_format.lower() in {"markdown", "html"}:
+            full_text = str(raw_content).strip()
+        else:
+            raise HTTPException(
+                status.HTTP_400_BAD_REQUEST,
+                detail=f"Unsupported output format: {self.output_format}",
+            )
+
+        if not full_text:
+            raise HTTPException(
+                status.HTTP_400_BAD_REQUEST,
+                detail="Marker returned empty content",
+            )
+
+        marker_output_dir = os.path.join("/app/backend/data/uploads", "marker_output")
+        os.makedirs(marker_output_dir, exist_ok=True)
+
+        file_ext_map = {"markdown": "md", "json": "json", "html": "html"}
+        file_ext = file_ext_map.get(self.output_format.lower(), "txt")
+        output_filename = f"{os.path.splitext(filename)[0]}.{file_ext}"
+        output_path = os.path.join(marker_output_dir, output_filename)
+
+        try:
+            with open(output_path, "w", encoding="utf-8") as f:
+                f.write(full_text)
+            log.info(f"Saved Marker output to: {output_path}")
+        except Exception as e:
+            log.warning(f"Failed to write marker output to disk: {e}")
+
+        metadata = {
+            "source": filename,
+            "output_format": final_result.get("output_format", self.output_format),
+            "page_count": final_result.get("page_count", 0),
+            "processed_with_llm": self.use_llm,
+            "request_id": request_id or "",
+        }
+
+        images = final_result.get("images", {})
+        if images:
+            metadata["image_count"] = len(images)
+            metadata["images"] = json.dumps(list(images.keys()))
+
+        for k, v in metadata.items():
+            if isinstance(v, (dict, list)):
+                metadata[k] = json.dumps(v)
+            elif v is None:
+                metadata[k] = ""
+
+        return [Document(page_content=full_text, metadata=metadata)]

backend/open_webui/retrieval/loaders/external_document.py

@@ -0,0 +1,89 @@
+import requests
+import logging, os
+from typing import Iterator, List, Union
+from urllib.parse import quote
+
+from langchain_core.document_loaders import BaseLoader
+from langchain_core.documents import Document
+from open_webui.utils.headers import include_user_info_headers
+
+log = logging.getLogger(__name__)
+
+
+class ExternalDocumentLoader(BaseLoader):
+    def __init__(
+        self,
+        file_path,
+        url: str,
+        api_key: str,
+        mime_type=None,
+        user=None,
+        **kwargs,
+    ) -> None:
+        self.url = url
+        self.api_key = api_key
+
+        self.file_path = file_path
+        self.mime_type = mime_type
+
+        self.user = user
+
+    def load(self) -> List[Document]:
+        with open(self.file_path, "rb") as f:
+            data = f.read()
+
+        headers = {}
+        if self.mime_type is not None:
+            headers["Content-Type"] = self.mime_type
+
+        if self.api_key is not None:
+            headers["Authorization"] = f"Bearer {self.api_key}"
+
+        try:
+            headers["X-Filename"] = quote(os.path.basename(self.file_path))
+        except:
+            pass
+
+        if self.user is not None:
+            headers = include_user_info_headers(headers, self.user)
+
+        url = self.url
+        if url.endswith("/"):
+            url = url[:-1]
+
+        try:
+            response = requests.put(f"{url}/process", data=data, headers=headers)
+        except Exception as e:
+            log.error(f"Error connecting to endpoint: {e}")
+            raise Exception(f"Error connecting to endpoint: {e}")
+
+        if response.ok:
+
+            response_data = response.json()
+            if response_data:
+                if isinstance(response_data, dict):
+                    return [
+                        Document(
+                            page_content=response_data.get("page_content"),
+                            metadata=response_data.get("metadata"),
+                        )
+                    ]
+                elif isinstance(response_data, list):
+                    documents = []
+                    for document in response_data:
+                        documents.append(
+                            Document(
+                                page_content=document.get("page_content"),
+                                metadata=document.get("metadata"),
+                            )
+                        )
+                    return documents
+                else:
+                    raise Exception("Error loading document: Unable to parse content")
+
+            else:
+                raise Exception("Error loading document: No content returned")
+        else:
+            raise Exception(
+                f"Error loading document: {response.status_code} {response.text}"
+            )

backend/open_webui/retrieval/loaders/external_web.py

@@ -0,0 +1,51 @@
+import requests
+import logging
+from typing import Iterator, List, Union
+
+from langchain_core.document_loaders import BaseLoader
+from langchain_core.documents import Document
+
+log = logging.getLogger(__name__)
+
+
+class ExternalWebLoader(BaseLoader):
+    def __init__(
+        self,
+        web_paths: Union[str, List[str]],
+        external_url: str,
+        external_api_key: str,
+        continue_on_failure: bool = True,
+        **kwargs,
+    ) -> None:
+        self.external_url = external_url
+        self.external_api_key = external_api_key
+        self.urls = web_paths if isinstance(web_paths, list) else [web_paths]
+        self.continue_on_failure = continue_on_failure
+
+    def lazy_load(self) -> Iterator[Document]:
+        batch_size = 20
+        for i in range(0, len(self.urls), batch_size):
+            urls = self.urls[i : i + batch_size]
+            try:
+                response = requests.post(
+                    self.external_url,
+                    headers={
+                        "User-Agent": "Open WebUI (https://github.com/open-webui/open-webui) External Web Loader",
+                        "Authorization": f"Bearer {self.external_api_key}",
+                    },
+                    json={
+                        "urls": urls,
+                    },
+                )
+                response.raise_for_status()
+                results = response.json()
+                for result in results:
+                    yield Document(
+                        page_content=result.get("page_content", ""),
+                        metadata=result.get("metadata", {}),
+                    )
+            except Exception as e:
+                if self.continue_on_failure:
+                    log.error(f"Error extracting content from batch {urls}: {e}")
+                else:
+                    raise e

backend/open_webui/retrieval/loaders/main.py

@@ -0,0 +1,403 @@
+import requests
+import logging
+import ftfy
+import sys
+import json
+
+from azure.identity import DefaultAzureCredential
+from langchain_community.document_loaders import (
+    AzureAIDocumentIntelligenceLoader,
+    BSHTMLLoader,
+    CSVLoader,
+    Docx2txtLoader,
+    OutlookMessageLoader,
+    PyPDFLoader,
+    TextLoader,
+    UnstructuredEPubLoader,
+    UnstructuredExcelLoader,
+    UnstructuredODTLoader,
+    UnstructuredPowerPointLoader,
+    UnstructuredRSTLoader,
+    UnstructuredXMLLoader,
+    YoutubeLoader,
+)
+from langchain_core.documents import Document
+
+from open_webui.retrieval.loaders.external_document import ExternalDocumentLoader
+
+from open_webui.retrieval.loaders.mistral import MistralLoader
+from open_webui.retrieval.loaders.datalab_marker import DatalabMarkerLoader
+from open_webui.retrieval.loaders.mineru import MinerULoader
+
+
+from open_webui.env import GLOBAL_LOG_LEVEL
+
+logging.basicConfig(stream=sys.stdout, level=GLOBAL_LOG_LEVEL)
+log = logging.getLogger(__name__)
+
+known_source_ext = [
+    "go",
+    "py",
+    "java",
+    "sh",
+    "bat",
+    "ps1",
+    "cmd",
+    "js",
+    "ts",
+    "css",
+    "cpp",
+    "hpp",
+    "h",
+    "c",
+    "cs",
+    "sql",
+    "log",
+    "ini",
+    "pl",
+    "pm",
+    "r",
+    "dart",
+    "dockerfile",
+    "env",
+    "php",
+    "hs",
+    "hsc",
+    "lua",
+    "nginxconf",
+    "conf",
+    "m",
+    "mm",
+    "plsql",
+    "perl",
+    "rb",
+    "rs",
+    "db2",
+    "scala",
+    "bash",
+    "swift",
+    "vue",
+    "svelte",
+    "ex",
+    "exs",
+    "erl",
+    "tsx",
+    "jsx",
+    "hs",
+    "lhs",
+    "json",
+]
+
+
+class TikaLoader:
+    def __init__(self, url, file_path, mime_type=None, extract_images=None):
+        self.url = url
+        self.file_path = file_path
+        self.mime_type = mime_type
+
+        self.extract_images = extract_images
+
+    def load(self) -> list[Document]:
+        with open(self.file_path, "rb") as f:
+            data = f.read()
+
+        if self.mime_type is not None:
+            headers = {"Content-Type": self.mime_type}
+        else:
+            headers = {}
+
+        if self.extract_images == True:
+            headers["X-Tika-PDFextractInlineImages"] = "true"
+
+        endpoint = self.url
+        if not endpoint.endswith("/"):
+            endpoint += "/"
+        endpoint += "tika/text"
+
+        r = requests.put(endpoint, data=data, headers=headers)
+
+        if r.ok:
+            raw_metadata = r.json()
+            text = raw_metadata.get("X-TIKA:content", "<No text content found>").strip()
+
+            if "Content-Type" in raw_metadata:
+                headers["Content-Type"] = raw_metadata["Content-Type"]
+
+            log.debug("Tika extracted text: %s", text)
+
+            return [Document(page_content=text, metadata=headers)]
+        else:
+            raise Exception(f"Error calling Tika: {r.reason}")
+
+
+class DoclingLoader:
+    def __init__(self, url, api_key=None, file_path=None, mime_type=None, params=None):
+        self.url = url.rstrip("/")
+        self.api_key = api_key
+        self.file_path = file_path
+        self.mime_type = mime_type
+
+        self.params = params or {}
+
+    def load(self) -> list[Document]:
+        with open(self.file_path, "rb") as f:
+            headers = {}
+            if self.api_key:
+                headers["X-Api-Key"] = f"Bearer {self.api_key}"
+
+            r = requests.post(
+                f"{self.url}/v1/convert/file",
+                files={
+                    "files": (
+                        self.file_path,
+                        f,
+                        self.mime_type or "application/octet-stream",
+                    )
+                },
+                data={
+                    "image_export_mode": "placeholder",
+                    **self.params,
+                },
+                headers=headers,
+            )
+        if r.ok:
+            result = r.json()
+            document_data = result.get("document", {})
+            text = document_data.get("md_content", "<No text content found>")
+
+            metadata = {"Content-Type": self.mime_type} if self.mime_type else {}
+
+            log.debug("Docling extracted text: %s", text)
+            return [Document(page_content=text, metadata=metadata)]
+        else:
+            error_msg = f"Error calling Docling API: {r.reason}"
+            if r.text:
+                try:
+                    error_data = r.json()
+                    if "detail" in error_data:
+                        error_msg += f" - {error_data['detail']}"
+                except Exception:
+                    error_msg += f" - {r.text}"
+            raise Exception(f"Error calling Docling: {error_msg}")
+
+
+class Loader:
+    def __init__(self, engine: str = "", **kwargs):
+        self.engine = engine
+        self.user = kwargs.get("user", None)
+        self.kwargs = kwargs
+
+    def load(
+        self, filename: str, file_content_type: str, file_path: str
+    ) -> list[Document]:
+        loader = self._get_loader(filename, file_content_type, file_path)
+        docs = loader.load()
+
+        return [
+            Document(
+                page_content=ftfy.fix_text(doc.page_content), metadata=doc.metadata
+            )
+            for doc in docs
+        ]
+
+    def _is_text_file(self, file_ext: str, file_content_type: str) -> bool:
+        return file_ext in known_source_ext or (
+            file_content_type
+            and file_content_type.find("text/") >= 0
+            # Avoid text/html files being detected as text
+            and not file_content_type.find("html") >= 0
+        )
+
+    def _get_loader(self, filename: str, file_content_type: str, file_path: str):
+        file_ext = filename.split(".")[-1].lower()
+
+        if (
+            self.engine == "external"
+            and self.kwargs.get("EXTERNAL_DOCUMENT_LOADER_URL")
+            and self.kwargs.get("EXTERNAL_DOCUMENT_LOADER_API_KEY")
+        ):
+            loader = ExternalDocumentLoader(
+                file_path=file_path,
+                url=self.kwargs.get("EXTERNAL_DOCUMENT_LOADER_URL"),
+                api_key=self.kwargs.get("EXTERNAL_DOCUMENT_LOADER_API_KEY"),
+                mime_type=file_content_type,
+                user=self.user,
+            )
+        elif self.engine == "tika" and self.kwargs.get("TIKA_SERVER_URL"):
+            if self._is_text_file(file_ext, file_content_type):
+                loader = TextLoader(file_path, autodetect_encoding=True)
+            else:
+                loader = TikaLoader(
+                    url=self.kwargs.get("TIKA_SERVER_URL"),
+                    file_path=file_path,
+                    extract_images=self.kwargs.get("PDF_EXTRACT_IMAGES"),
+                )
+        elif (
+            self.engine == "datalab_marker"
+            and self.kwargs.get("DATALAB_MARKER_API_KEY")
+            and file_ext
+            in [
+                "pdf",
+                "xls",
+                "xlsx",
+                "ods",
+                "doc",
+                "docx",
+                "odt",
+                "ppt",
+                "pptx",
+                "odp",
+                "html",
+                "epub",
+                "png",
+                "jpeg",
+                "jpg",
+                "webp",
+                "gif",
+                "tiff",
+            ]
+        ):
+            api_base_url = self.kwargs.get("DATALAB_MARKER_API_BASE_URL", "")
+            if not api_base_url or api_base_url.strip() == "":
+                api_base_url = "https://www.datalab.to/api/v1/marker"  # https://github.com/open-webui/open-webui/pull/16867#issuecomment-3218424349
+
+            loader = DatalabMarkerLoader(
+                file_path=file_path,
+                api_key=self.kwargs["DATALAB_MARKER_API_KEY"],
+                api_base_url=api_base_url,
+                additional_config=self.kwargs.get("DATALAB_MARKER_ADDITIONAL_CONFIG"),
+                use_llm=self.kwargs.get("DATALAB_MARKER_USE_LLM", False),
+                skip_cache=self.kwargs.get("DATALAB_MARKER_SKIP_CACHE", False),
+                force_ocr=self.kwargs.get("DATALAB_MARKER_FORCE_OCR", False),
+                paginate=self.kwargs.get("DATALAB_MARKER_PAGINATE", False),
+                strip_existing_ocr=self.kwargs.get(
+                    "DATALAB_MARKER_STRIP_EXISTING_OCR", False
+                ),
+                disable_image_extraction=self.kwargs.get(
+                    "DATALAB_MARKER_DISABLE_IMAGE_EXTRACTION", False
+                ),
+                format_lines=self.kwargs.get("DATALAB_MARKER_FORMAT_LINES", False),
+                output_format=self.kwargs.get(
+                    "DATALAB_MARKER_OUTPUT_FORMAT", "markdown"
+                ),
+            )
+        elif self.engine == "docling" and self.kwargs.get("DOCLING_SERVER_URL"):
+            if self._is_text_file(file_ext, file_content_type):
+                loader = TextLoader(file_path, autodetect_encoding=True)
+            else:
+                # Build params for DoclingLoader
+                params = self.kwargs.get("DOCLING_PARAMS", {})
+                if not isinstance(params, dict):
+                    try:
+                        params = json.loads(params)
+                    except json.JSONDecodeError:
+                        log.error("Invalid DOCLING_PARAMS format, expected JSON object")
+                        params = {}
+
+                loader = DoclingLoader(
+                    url=self.kwargs.get("DOCLING_SERVER_URL"),
+                    api_key=self.kwargs.get("DOCLING_API_KEY", None),
+                    file_path=file_path,
+                    mime_type=file_content_type,
+                    params=params,
+                )
+        elif (
+            self.engine == "document_intelligence"
+            and self.kwargs.get("DOCUMENT_INTELLIGENCE_ENDPOINT") != ""
+            and (
+                file_ext in ["pdf", "docx", "ppt", "pptx"]
+                or file_content_type
+                in [
+                    "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
+                    "application/vnd.ms-powerpoint",
+                    "application/vnd.openxmlformats-officedocument.presentationml.presentation",
+                ]
+            )
+        ):
+            if self.kwargs.get("DOCUMENT_INTELLIGENCE_KEY") != "":
+                loader = AzureAIDocumentIntelligenceLoader(
+                    file_path=file_path,
+                    api_endpoint=self.kwargs.get("DOCUMENT_INTELLIGENCE_ENDPOINT"),
+                    api_key=self.kwargs.get("DOCUMENT_INTELLIGENCE_KEY"),
+                    api_model=self.kwargs.get("DOCUMENT_INTELLIGENCE_MODEL"),
+                )
+            else:
+                loader = AzureAIDocumentIntelligenceLoader(
+                    file_path=file_path,
+                    api_endpoint=self.kwargs.get("DOCUMENT_INTELLIGENCE_ENDPOINT"),
+                    azure_credential=DefaultAzureCredential(),
+                    api_model=self.kwargs.get("DOCUMENT_INTELLIGENCE_MODEL"),
+                )
+        elif self.engine == "mineru" and file_ext in [
+            "pdf"
+        ]:  # MinerU currently only supports PDF
+
+            mineru_timeout = self.kwargs.get("MINERU_API_TIMEOUT", 300)
+            if mineru_timeout:
+                try:
+                    mineru_timeout = int(mineru_timeout)
+                except ValueError:
+                    mineru_timeout = 300
+
+            loader = MinerULoader(
+                file_path=file_path,
+                api_mode=self.kwargs.get("MINERU_API_MODE", "local"),
+                api_url=self.kwargs.get("MINERU_API_URL", "http://localhost:8000"),
+                api_key=self.kwargs.get("MINERU_API_KEY", ""),
+                params=self.kwargs.get("MINERU_PARAMS", {}),
+                timeout=mineru_timeout,
+            )
+        elif (
+            self.engine == "mistral_ocr"
+            and self.kwargs.get("MISTRAL_OCR_API_KEY") != ""
+            and file_ext
+            in ["pdf"]  # Mistral OCR currently only supports PDF and images
+        ):
+            loader = MistralLoader(
+                base_url=self.kwargs.get("MISTRAL_OCR_API_BASE_URL"),
+                api_key=self.kwargs.get("MISTRAL_OCR_API_KEY"),
+                file_path=file_path,
+            )
+        else:
+            if file_ext == "pdf":
+                loader = PyPDFLoader(
+                    file_path, extract_images=self.kwargs.get("PDF_EXTRACT_IMAGES")
+                )
+            elif file_ext == "csv":
+                loader = CSVLoader(file_path, autodetect_encoding=True)
+            elif file_ext == "rst":
+                loader = UnstructuredRSTLoader(file_path, mode="elements")
+            elif file_ext == "xml":
+                loader = UnstructuredXMLLoader(file_path)
+            elif file_ext in ["htm", "html"]:
+                loader = BSHTMLLoader(file_path, open_encoding="unicode_escape")
+            elif file_ext == "md":
+                loader = TextLoader(file_path, autodetect_encoding=True)
+            elif file_content_type == "application/epub+zip":
+                loader = UnstructuredEPubLoader(file_path)
+            elif (
+                file_content_type
+                == "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
+                or file_ext == "docx"
+            ):
+                loader = Docx2txtLoader(file_path)
+            elif file_content_type in [
+                "application/vnd.ms-excel",
+                "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
+            ] or file_ext in ["xls", "xlsx"]:
+                loader = UnstructuredExcelLoader(file_path)
+            elif file_content_type in [
+                "application/vnd.ms-powerpoint",
+                "application/vnd.openxmlformats-officedocument.presentationml.presentation",
+            ] or file_ext in ["ppt", "pptx"]:
+                loader = UnstructuredPowerPointLoader(file_path)
+            elif file_ext == "msg":
+                loader = OutlookMessageLoader(file_path)
+            elif file_ext == "odt":
+                loader = UnstructuredODTLoader(file_path)
+            elif self._is_text_file(file_ext, file_content_type):
+                loader = TextLoader(file_path, autodetect_encoding=True)
+            else:
+                loader = TextLoader(file_path, autodetect_encoding=True)
+
+        return loader

backend/open_webui/retrieval/loaders/mineru.py

@@ -0,0 +1,524 @@
+import os
+import time
+import requests
+import logging
+import tempfile
+import zipfile
+from typing import List, Optional
+from langchain_core.documents import Document
+from fastapi import HTTPException, status
+
+log = logging.getLogger(__name__)
+
+
+class MinerULoader:
+    """
+    MinerU document parser loader supporting both Cloud API and Local API modes.
+
+    Cloud API: Uses MinerU managed service with async task-based processing
+    Local API: Uses self-hosted MinerU API with synchronous processing
+    """
+
+    def __init__(
+        self,
+        file_path: str,
+        api_mode: str = "local",
+        api_url: str = "http://localhost:8000",
+        api_key: str = "",
+        params: dict = None,
+        timeout: Optional[int] = 300,
+    ):
+        self.file_path = file_path
+        self.api_mode = api_mode.lower()
+        self.api_url = api_url.rstrip("/")
+        self.api_key = api_key
+        self.timeout = timeout
+
+        # Parse params dict with defaults
+        self.params = params or {}
+        self.enable_ocr = params.get("enable_ocr", False)
+        self.enable_formula = params.get("enable_formula", True)
+        self.enable_table = params.get("enable_table", True)
+        self.language = params.get("language", "en")
+        self.model_version = params.get("model_version", "pipeline")
+
+        self.page_ranges = self.params.pop("page_ranges", "")
+
+        # Validate API mode
+        if self.api_mode not in ["local", "cloud"]:
+            raise ValueError(
+                f"Invalid API mode: {self.api_mode}. Must be 'local' or 'cloud'"
+            )
+
+        # Validate Cloud API requirements
+        if self.api_mode == "cloud" and not self.api_key:
+            raise ValueError("API key is required for Cloud API mode")
+
+    def load(self) -> List[Document]:
+        """
+        Main entry point for loading and parsing the document.
+        Routes to Cloud or Local API based on api_mode.
+        """
+        try:
+            if self.api_mode == "cloud":
+                return self._load_cloud_api()
+            else:
+                return self._load_local_api()
+        except Exception as e:
+            log.error(f"Error loading document with MinerU: {e}")
+            raise
+
+    def _load_local_api(self) -> List[Document]:
+        """
+        Load document using Local API (synchronous).
+        Posts file to /file_parse endpoint and gets immediate response.
+        """
+        log.info(f"Using MinerU Local API at {self.api_url}")
+
+        filename = os.path.basename(self.file_path)
+
+        # Build form data for Local API
+        form_data = {
+            **self.params,
+            "return_md": "true",
+        }
+
+        # Page ranges (Local API uses start_page_id and end_page_id)
+        if self.page_ranges:
+            # For simplicity, if page_ranges is specified, log a warning
+            # Full page range parsing would require parsing the string
+            log.warning(
+                f"Page ranges '{self.page_ranges}' specified but Local API uses different format. "
+                "Consider using start_page_id/end_page_id parameters if needed."
+            )
+
+        try:
+            with open(self.file_path, "rb") as f:
+                files = {"files": (filename, f, "application/octet-stream")}
+
+                log.info(f"Sending file to MinerU Local API: {filename}")
+                log.debug(f"Local API parameters: {form_data}")
+
+                response = requests.post(
+                    f"{self.api_url}/file_parse",
+                    data=form_data,
+                    files=files,
+                    timeout=self.timeout,
+                )
+                response.raise_for_status()
+
+        except FileNotFoundError:
+            raise HTTPException(
+                status.HTTP_404_NOT_FOUND, detail=f"File not found: {self.file_path}"
+            )
+        except requests.Timeout:
+            raise HTTPException(
+                status.HTTP_504_GATEWAY_TIMEOUT,
+                detail="MinerU Local API request timed out",
+            )
+        except requests.HTTPError as e:
+            error_detail = f"MinerU Local API request failed: {e}"
+            if e.response is not None:
+                try:
+                    error_data = e.response.json()
+                    error_detail += f" - {error_data}"
+                except:
+                    error_detail += f" - {e.response.text}"
+            raise HTTPException(status.HTTP_400_BAD_REQUEST, detail=error_detail)
+        except Exception as e:
+            raise HTTPException(
+                status.HTTP_500_INTERNAL_SERVER_ERROR,
+                detail=f"Error calling MinerU Local API: {str(e)}",
+            )
+
+        # Parse response
+        try:
+            result = response.json()
+        except ValueError as e:
+            raise HTTPException(
+                status.HTTP_502_BAD_GATEWAY,
+                detail=f"Invalid JSON response from MinerU Local API: {e}",
+            )
+
+        # Extract markdown content from response
+        if "results" not in result:
+            raise HTTPException(
+                status.HTTP_502_BAD_GATEWAY,
+                detail="MinerU Local API response missing 'results' field",
+            )
+
+        results = result["results"]
+        if not results:
+            raise HTTPException(
+                status.HTTP_400_BAD_REQUEST,
+                detail="MinerU returned empty results",
+            )
+
+        # Get the first (and typically only) result
+        file_result = list(results.values())[0]
+        markdown_content = file_result.get("md_content", "")
+
+        if not markdown_content:
+            raise HTTPException(
+                status.HTTP_400_BAD_REQUEST,
+                detail="MinerU returned empty markdown content",
+            )
+
+        log.info(f"Successfully parsed document with MinerU Local API: {filename}")
+
+        # Create metadata
+        metadata = {
+            "source": filename,
+            "api_mode": "local",
+            "backend": result.get("backend", "unknown"),
+            "version": result.get("version", "unknown"),
+        }
+
+        return [Document(page_content=markdown_content, metadata=metadata)]
+
+    def _load_cloud_api(self) -> List[Document]:
+        """
+        Load document using Cloud API (asynchronous).
+        Uses batch upload endpoint to avoid need for public file URLs.
+        """
+        log.info(f"Using MinerU Cloud API at {self.api_url}")
+
+        filename = os.path.basename(self.file_path)
+
+        # Step 1: Request presigned upload URL
+        batch_id, upload_url = self._request_upload_url(filename)
+
+        # Step 2: Upload file to presigned URL
+        self._upload_to_presigned_url(upload_url)
+
+        # Step 3: Poll for results
+        result = self._poll_batch_status(batch_id, filename)
+
+        # Step 4: Download and extract markdown from ZIP
+        markdown_content = self._download_and_extract_zip(
+            result["full_zip_url"], filename
+        )
+
+        log.info(f"Successfully parsed document with MinerU Cloud API: {filename}")
+
+        # Create metadata
+        metadata = {
+            "source": filename,
+            "api_mode": "cloud",
+            "batch_id": batch_id,
+        }
+
+        return [Document(page_content=markdown_content, metadata=metadata)]
+
+    def _request_upload_url(self, filename: str) -> tuple:
+        """
+        Request presigned upload URL from Cloud API.
+        Returns (batch_id, upload_url).
+        """
+        headers = {
+            "Authorization": f"Bearer {self.api_key}",
+            "Content-Type": "application/json",
+        }
+
+        # Build request body
+        request_body = {
+            **self.params,
+            "files": [
+                {
+                    "name": filename,
+                    "is_ocr": self.enable_ocr,
+                }
+            ],
+        }
+
+        # Add page ranges if specified
+        if self.page_ranges:
+            request_body["files"][0]["page_ranges"] = self.page_ranges
+
+        log.info(f"Requesting upload URL for: {filename}")
+        log.debug(f"Cloud API request body: {request_body}")
+
+        try:
+            response = requests.post(
+                f"{self.api_url}/file-urls/batch",
+                headers=headers,
+                json=request_body,
+                timeout=30,
+            )
+            response.raise_for_status()
+        except requests.HTTPError as e:
+            error_detail = f"Failed to request upload URL: {e}"
+            if e.response is not None:
+                try:
+                    error_data = e.response.json()
+                    error_detail += f" - {error_data.get('msg', error_data)}"
+                except:
+                    error_detail += f" - {e.response.text}"
+            raise HTTPException(status.HTTP_400_BAD_REQUEST, detail=error_detail)
+        except Exception as e:
+            raise HTTPException(
+                status.HTTP_500_INTERNAL_SERVER_ERROR,
+                detail=f"Error requesting upload URL: {str(e)}",
+            )
+
+        try:
+            result = response.json()
+        except ValueError as e:
+            raise HTTPException(
+                status.HTTP_502_BAD_GATEWAY,
+                detail=f"Invalid JSON response: {e}",
+            )
+
+        # Check for API error response
+        if result.get("code") != 0:
+            raise HTTPException(
+                status.HTTP_400_BAD_REQUEST,
+                detail=f"MinerU Cloud API error: {result.get('msg', 'Unknown error')}",
+            )
+
+        data = result.get("data", {})
+        batch_id = data.get("batch_id")
+        file_urls = data.get("file_urls", [])
+
+        if not batch_id or not file_urls:
+            raise HTTPException(
+                status.HTTP_502_BAD_GATEWAY,
+                detail="MinerU Cloud API response missing batch_id or file_urls",
+            )
+
+        upload_url = file_urls[0]
+        log.info(f"Received upload URL for batch: {batch_id}")
+
+        return batch_id, upload_url
+
+    def _upload_to_presigned_url(self, upload_url: str) -> None:
+        """
+        Upload file to presigned URL (no authentication needed).
+        """
+        log.info(f"Uploading file to presigned URL")
+
+        try:
+            with open(self.file_path, "rb") as f:
+                response = requests.put(
+                    upload_url,
+                    data=f,
+                    timeout=self.timeout,
+                )
+                response.raise_for_status()
+        except FileNotFoundError:
+            raise HTTPException(
+                status.HTTP_404_NOT_FOUND, detail=f"File not found: {self.file_path}"
+            )
+        except requests.Timeout:
+            raise HTTPException(
+                status.HTTP_504_GATEWAY_TIMEOUT,
+                detail="File upload to presigned URL timed out",
+            )
+        except requests.HTTPError as e:
+            raise HTTPException(
+                status.HTTP_400_BAD_REQUEST,
+                detail=f"Failed to upload file to presigned URL: {e}",
+            )
+        except Exception as e:
+            raise HTTPException(
+                status.HTTP_500_INTERNAL_SERVER_ERROR,
+                detail=f"Error uploading file: {str(e)}",
+            )
+
+        log.info("File uploaded successfully")
+
+    def _poll_batch_status(self, batch_id: str, filename: str) -> dict:
+        """
+        Poll batch status until completion.
+        Returns the result dict for the file.
+        """
+        headers = {
+            "Authorization": f"Bearer {self.api_key}",
+        }
+
+        max_iterations = 300  # 10 minutes max (2 seconds per iteration)
+        poll_interval = 2  # seconds
+
+        log.info(f"Polling batch status: {batch_id}")
+
+        for iteration in range(max_iterations):
+            try:
+                response = requests.get(
+                    f"{self.api_url}/extract-results/batch/{batch_id}",
+                    headers=headers,
+                    timeout=30,
+                )
+                response.raise_for_status()
+            except requests.HTTPError as e:
+                error_detail = f"Failed to poll batch status: {e}"
+                if e.response is not None:
+                    try:
+                        error_data = e.response.json()
+                        error_detail += f" - {error_data.get('msg', error_data)}"
+                    except:
+                        error_detail += f" - {e.response.text}"
+                raise HTTPException(status.HTTP_400_BAD_REQUEST, detail=error_detail)
+            except Exception as e:
+                raise HTTPException(
+                    status.HTTP_500_INTERNAL_SERVER_ERROR,
+                    detail=f"Error polling batch status: {str(e)}",
+                )
+
+            try:
+                result = response.json()
+            except ValueError as e:
+                raise HTTPException(
+                    status.HTTP_502_BAD_GATEWAY,
+                    detail=f"Invalid JSON response while polling: {e}",
+                )
+
+            # Check for API error response
+            if result.get("code") != 0:
+                raise HTTPException(
+                    status.HTTP_400_BAD_REQUEST,
+                    detail=f"MinerU Cloud API error: {result.get('msg', 'Unknown error')}",
+                )
+
+            data = result.get("data", {})
+            extract_result = data.get("extract_result", [])
+
+            # Find our file in the batch results
+            file_result = None
+            for item in extract_result:
+                if item.get("file_name") == filename:
+                    file_result = item
+                    break
+
+            if not file_result:
+                raise HTTPException(
+                    status.HTTP_502_BAD_GATEWAY,
+                    detail=f"File {filename} not found in batch results",
+                )
+
+            state = file_result.get("state")
+
+            if state == "done":
+                log.info(f"Processing complete for {filename}")
+                return file_result
+            elif state == "failed":
+                error_msg = file_result.get("err_msg", "Unknown error")
+                raise HTTPException(
+                    status.HTTP_400_BAD_REQUEST,
+                    detail=f"MinerU processing failed: {error_msg}",
+                )
+            elif state in ["waiting-file", "pending", "running", "converting"]:
+                # Still processing
+                if iteration % 10 == 0:  # Log every 20 seconds
+                    log.info(
+                        f"Processing status: {state} (iteration {iteration + 1}/{max_iterations})"
+                    )
+                time.sleep(poll_interval)
+            else:
+                log.warning(f"Unknown state: {state}")
+                time.sleep(poll_interval)
+
+        # Timeout
+        raise HTTPException(
+            status.HTTP_504_GATEWAY_TIMEOUT,
+            detail="MinerU processing timed out after 10 minutes",
+        )
+
+    def _download_and_extract_zip(self, zip_url: str, filename: str) -> str:
+        """
+        Download ZIP file from CDN and extract markdown content.
+        Returns the markdown content as a string.
+        """
+        log.info(f"Downloading results from: {zip_url}")
+
+        try:
+            response = requests.get(zip_url, timeout=60)
+            response.raise_for_status()
+        except requests.HTTPError as e:
+            raise HTTPException(
+                status.HTTP_400_BAD_REQUEST,
+                detail=f"Failed to download results ZIP: {e}",
+            )
+        except Exception as e:
+            raise HTTPException(
+                status.HTTP_500_INTERNAL_SERVER_ERROR,
+                detail=f"Error downloading results: {str(e)}",
+            )
+
+        # Save ZIP to temporary file and extract
+        try:
+            with tempfile.NamedTemporaryFile(delete=False, suffix=".zip") as tmp_zip:
+                tmp_zip.write(response.content)
+                tmp_zip_path = tmp_zip.name
+
+            with tempfile.TemporaryDirectory() as tmp_dir:
+                # Extract ZIP
+                with zipfile.ZipFile(tmp_zip_path, "r") as zip_ref:
+                    zip_ref.extractall(tmp_dir)
+
+                # Find markdown file - search recursively for any .md file
+                markdown_content = None
+                found_md_path = None
+
+                # First, list all files in the ZIP for debugging
+                all_files = []
+                for root, dirs, files in os.walk(tmp_dir):
+                    for file in files:
+                        full_path = os.path.join(root, file)
+                        all_files.append(full_path)
+                        # Look for any .md file
+                        if file.endswith(".md"):
+                            found_md_path = full_path
+                            log.info(f"Found markdown file at: {full_path}")
+                            try:
+                                with open(full_path, "r", encoding="utf-8") as f:
+                                    markdown_content = f.read()
+                                if (
+                                    markdown_content
+                                ):  # Use the first non-empty markdown file
+                                    break
+                            except Exception as e:
+                                log.warning(f"Failed to read {full_path}: {e}")
+                    if markdown_content:
+                        break
+
+                if markdown_content is None:
+                    log.error(f"Available files in ZIP: {all_files}")
+                    # Try to provide more helpful error message
+                    md_files = [f for f in all_files if f.endswith(".md")]
+                    if md_files:
+                        error_msg = (
+                            f"Found .md files but couldn't read them: {md_files}"
+                        )
+                    else:
+                        error_msg = (
+                            f"No .md files found in ZIP. Available files: {all_files}"
+                        )
+                    raise HTTPException(
+                        status.HTTP_502_BAD_GATEWAY,
+                        detail=error_msg,
+                    )
+
+            # Clean up temporary ZIP file
+            os.unlink(tmp_zip_path)
+
+        except zipfile.BadZipFile as e:
+            raise HTTPException(
+                status.HTTP_502_BAD_GATEWAY,
+                detail=f"Invalid ZIP file received: {e}",
+            )
+        except Exception as e:
+            raise HTTPException(
+                status.HTTP_500_INTERNAL_SERVER_ERROR,
+                detail=f"Error extracting ZIP: {str(e)}",
+            )
+
+        if not markdown_content:
+            raise HTTPException(
+                status.HTTP_400_BAD_REQUEST,
+                detail="Extracted markdown content is empty",
+            )
+
+        log.info(
+            f"Successfully extracted markdown content ({len(markdown_content)} characters)"
+        )
+        return markdown_content

backend/open_webui/retrieval/loaders/mistral.py

@@ -0,0 +1,769 @@
+import requests
+import aiohttp
+import asyncio
+import logging
+import os
+import sys
+import time
+from typing import List, Dict, Any
+from contextlib import asynccontextmanager
+
+from langchain_core.documents import Document
+from open_webui.env import GLOBAL_LOG_LEVEL
+
+logging.basicConfig(stream=sys.stdout, level=GLOBAL_LOG_LEVEL)
+log = logging.getLogger(__name__)
+
+
+class MistralLoader:
+    """
+    Enhanced Mistral OCR loader with both sync and async support.
+    Loads documents by processing them through the Mistral OCR API.
+
+    Performance Optimizations:
+    - Differentiated timeouts for different operations
+    - Intelligent retry logic with exponential backoff
+    - Memory-efficient file streaming for large files
+    - Connection pooling and keepalive optimization
+    - Semaphore-based concurrency control for batch processing
+    - Enhanced error handling with retryable error classification
+    """
+
+    def __init__(
+        self,
+        base_url: str,
+        api_key: str,
+        file_path: str,
+        timeout: int = 300,  # 5 minutes default
+        max_retries: int = 3,
+        enable_debug_logging: bool = False,
+    ):
+        """
+        Initializes the loader with enhanced features.
+
+        Args:
+            api_key: Your Mistral API key.
+            file_path: The local path to the PDF file to process.
+            timeout: Request timeout in seconds.
+            max_retries: Maximum number of retry attempts.
+            enable_debug_logging: Enable detailed debug logs.
+        """
+        if not api_key:
+            raise ValueError("API key cannot be empty.")
+        if not os.path.exists(file_path):
+            raise FileNotFoundError(f"File not found at {file_path}")
+
+        self.base_url = (
+            base_url.rstrip("/") if base_url else "https://api.mistral.ai/v1"
+        )
+        self.api_key = api_key
+        self.file_path = file_path
+        self.timeout = timeout
+        self.max_retries = max_retries
+        self.debug = enable_debug_logging
+
+        # PERFORMANCE OPTIMIZATION: Differentiated timeouts for different operations
+        # This prevents long-running OCR operations from affecting quick operations
+        # and improves user experience by failing fast on operations that should be quick
+        self.upload_timeout = min(
+            timeout, 120
+        )  # Cap upload at 2 minutes - prevents hanging on large files
+        self.url_timeout = (
+            30  # URL requests should be fast - fail quickly if API is slow
+        )
+        self.ocr_timeout = (
+            timeout  # OCR can take the full timeout - this is the heavy operation
+        )
+        self.cleanup_timeout = (
+            30  # Cleanup should be quick - don't hang on file deletion
+        )
+
+        # PERFORMANCE OPTIMIZATION: Pre-compute file info to avoid repeated filesystem calls
+        # This avoids multiple os.path.basename() and os.path.getsize() calls during processing
+        self.file_name = os.path.basename(file_path)
+        self.file_size = os.path.getsize(file_path)
+
+        # ENHANCEMENT: Added User-Agent for better API tracking and debugging
+        self.headers = {
+            "Authorization": f"Bearer {self.api_key}",
+            "User-Agent": "OpenWebUI-MistralLoader/2.0",  # Helps API provider track usage
+        }
+
+    def _debug_log(self, message: str, *args) -> None:
+        """
+        PERFORMANCE OPTIMIZATION: Conditional debug logging for performance.
+
+        Only processes debug messages when debug mode is enabled, avoiding
+        string formatting overhead in production environments.
+        """
+        if self.debug:
+            log.debug(message, *args)
+
+    def _handle_response(self, response: requests.Response) -> Dict[str, Any]:
+        """Checks response status and returns JSON content."""
+        try:
+            response.raise_for_status()  # Raises HTTPError for bad responses (4xx or 5xx)
+            # Handle potential empty responses for certain successful requests (e.g., DELETE)
+            if response.status_code == 204 or not response.content:
+                return {}  # Return empty dict if no content
+            return response.json()
+        except requests.exceptions.HTTPError as http_err:
+            log.error(f"HTTP error occurred: {http_err} - Response: {response.text}")
+            raise
+        except requests.exceptions.RequestException as req_err:
+            log.error(f"Request exception occurred: {req_err}")
+            raise
+        except ValueError as json_err:  # Includes JSONDecodeError
+            log.error(f"JSON decode error: {json_err} - Response: {response.text}")
+            raise  # Re-raise after logging
+
+    async def _handle_response_async(
+        self, response: aiohttp.ClientResponse
+    ) -> Dict[str, Any]:
+        """Async version of response handling with better error info."""
+        try:
+            response.raise_for_status()
+
+            # Check content type
+            content_type = response.headers.get("content-type", "")
+            if "application/json" not in content_type:
+                if response.status == 204:
+                    return {}
+                text = await response.text()
+                raise ValueError(
+                    f"Unexpected content type: {content_type}, body: {text[:200]}..."
+                )
+
+            return await response.json()
+
+        except aiohttp.ClientResponseError as e:
+            error_text = await response.text() if response else "No response"
+            log.error(f"HTTP {e.status}: {e.message} - Response: {error_text[:500]}")
+            raise
+        except aiohttp.ClientError as e:
+            log.error(f"Client error: {e}")
+            raise
+        except Exception as e:
+            log.error(f"Unexpected error processing response: {e}")
+            raise
+
+    def _is_retryable_error(self, error: Exception) -> bool:
+        """
+        ENHANCEMENT: Intelligent error classification for retry logic.
+
+        Determines if an error is retryable based on its type and status code.
+        This prevents wasting time retrying errors that will never succeed
+        (like authentication errors) while ensuring transient errors are retried.
+
+        Retryable errors:
+        - Network connection errors (temporary network issues)
+        - Timeouts (server might be temporarily overloaded)
+        - Server errors (5xx status codes - server-side issues)
+        - Rate limiting (429 status - temporary throttling)
+
+        Non-retryable errors:
+        - Authentication errors (401, 403 - won't fix with retry)
+        - Bad request errors (400 - malformed request)
+        - Not found errors (404 - resource doesn't exist)
+        """
+        if isinstance(error, requests.exceptions.ConnectionError):
+            return True  # Network issues are usually temporary
+        if isinstance(error, requests.exceptions.Timeout):
+            return True  # Timeouts might resolve on retry
+        if isinstance(error, requests.exceptions.HTTPError):
+            # Only retry on server errors (5xx) or rate limits (429)
+            if hasattr(error, "response") and error.response is not None:
+                status_code = error.response.status_code
+                return status_code >= 500 or status_code == 429
+            return False
+        if isinstance(
+            error, (aiohttp.ClientConnectionError, aiohttp.ServerTimeoutError)
+        ):
+            return True  # Async network/timeout errors are retryable
+        if isinstance(error, aiohttp.ClientResponseError):
+            return error.status >= 500 or error.status == 429
+        return False  # All other errors are non-retryable
+
+    def _retry_request_sync(self, request_func, *args, **kwargs):
+        """
+        ENHANCEMENT: Synchronous retry logic with intelligent error classification.
+
+        Uses exponential backoff with jitter to avoid thundering herd problems.
+        The wait time increases exponentially but is capped at 30 seconds to
+        prevent excessive delays. Only retries errors that are likely to succeed
+        on subsequent attempts.
+        """
+        for attempt in range(self.max_retries):
+            try:
+                return request_func(*args, **kwargs)
+            except Exception as e:
+                if attempt == self.max_retries - 1 or not self._is_retryable_error(e):
+                    raise
+
+                # PERFORMANCE OPTIMIZATION: Exponential backoff with cap
+                # Prevents overwhelming the server while ensuring reasonable retry delays
+                wait_time = min((2**attempt) + 0.5, 30)  # Cap at 30 seconds
+                log.warning(
+                    f"Retryable error (attempt {attempt + 1}/{self.max_retries}): {e}. "
+                    f"Retrying in {wait_time}s..."
+                )
+                time.sleep(wait_time)
+
+    async def _retry_request_async(self, request_func, *args, **kwargs):
+        """
+        ENHANCEMENT: Async retry logic with intelligent error classification.
+
+        Async version of retry logic that doesn't block the event loop during
+        wait periods. Uses the same exponential backoff strategy as sync version.
+        """
+        for attempt in range(self.max_retries):
+            try:
+                return await request_func(*args, **kwargs)
+            except Exception as e:
+                if attempt == self.max_retries - 1 or not self._is_retryable_error(e):
+                    raise
+
+                # PERFORMANCE OPTIMIZATION: Non-blocking exponential backoff
+                wait_time = min((2**attempt) + 0.5, 30)  # Cap at 30 seconds
+                log.warning(
+                    f"Retryable error (attempt {attempt + 1}/{self.max_retries}): {e}. "
+                    f"Retrying in {wait_time}s..."
+                )
+                await asyncio.sleep(wait_time)  # Non-blocking wait
+
+    def _upload_file(self) -> str:
+        """
+        PERFORMANCE OPTIMIZATION: Enhanced file upload with streaming consideration.
+
+        Uploads the file to Mistral for OCR processing (sync version).
+        Uses context manager for file handling to ensure proper resource cleanup.
+        Although streaming is not enabled for this endpoint, the file is opened
+        in a context manager to minimize memory usage duration.
+        """
+        log.info("Uploading file to Mistral API")
+        url = f"{self.base_url}/files"
+
+        def upload_request():
+            # MEMORY OPTIMIZATION: Use context manager to minimize file handle lifetime
+            # This ensures the file is closed immediately after reading, reducing memory usage
+            with open(self.file_path, "rb") as f:
+                files = {"file": (self.file_name, f, "application/pdf")}
+                data = {"purpose": "ocr"}
+
+                # NOTE: stream=False is required for this endpoint
+                # The Mistral API doesn't support chunked uploads for this endpoint
+                response = requests.post(
+                    url,
+                    headers=self.headers,
+                    files=files,
+                    data=data,
+                    timeout=self.upload_timeout,  # Use specialized upload timeout
+                    stream=False,  # Keep as False for this endpoint
+                )
+
+            return self._handle_response(response)
+
+        try:
+            response_data = self._retry_request_sync(upload_request)
+            file_id = response_data.get("id")
+            if not file_id:
+                raise ValueError("File ID not found in upload response.")
+            log.info(f"File uploaded successfully. File ID: {file_id}")
+            return file_id
+        except Exception as e:
+            log.error(f"Failed to upload file: {e}")
+            raise
+
+    async def _upload_file_async(self, session: aiohttp.ClientSession) -> str:
+        """Async file upload with streaming for better memory efficiency."""
+        url = f"{self.base_url}/files"
+
+        async def upload_request():
+            # Create multipart writer for streaming upload
+            writer = aiohttp.MultipartWriter("form-data")
+
+            # Add purpose field
+            purpose_part = writer.append("ocr")
+            purpose_part.set_content_disposition("form-data", name="purpose")
+
+            # Add file part with streaming
+            file_part = writer.append_payload(
+                aiohttp.streams.FilePayload(
+                    self.file_path,
+                    filename=self.file_name,
+                    content_type="application/pdf",
+                )
+            )
+            file_part.set_content_disposition(
+                "form-data", name="file", filename=self.file_name
+            )
+
+            self._debug_log(
+                f"Uploading file: {self.file_name} ({self.file_size:,} bytes)"
+            )
+
+            async with session.post(
+                url,
+                data=writer,
+                headers=self.headers,
+                timeout=aiohttp.ClientTimeout(total=self.upload_timeout),
+            ) as response:
+                return await self._handle_response_async(response)
+
+        response_data = await self._retry_request_async(upload_request)
+
+        file_id = response_data.get("id")
+        if not file_id:
+            raise ValueError("File ID not found in upload response.")
+
+        log.info(f"File uploaded successfully. File ID: {file_id}")
+        return file_id
+
+    def _get_signed_url(self, file_id: str) -> str:
+        """Retrieves a temporary signed URL for the uploaded file (sync version)."""
+        log.info(f"Getting signed URL for file ID: {file_id}")
+        url = f"{self.base_url}/files/{file_id}/url"
+        params = {"expiry": 1}
+        signed_url_headers = {**self.headers, "Accept": "application/json"}
+
+        def url_request():
+            response = requests.get(
+                url, headers=signed_url_headers, params=params, timeout=self.url_timeout
+            )
+            return self._handle_response(response)
+
+        try:
+            response_data = self._retry_request_sync(url_request)
+            signed_url = response_data.get("url")
+            if not signed_url:
+                raise ValueError("Signed URL not found in response.")
+            log.info("Signed URL received.")
+            return signed_url
+        except Exception as e:
+            log.error(f"Failed to get signed URL: {e}")
+            raise
+
+    async def _get_signed_url_async(
+        self, session: aiohttp.ClientSession, file_id: str
+    ) -> str:
+        """Async signed URL retrieval."""
+        url = f"{self.base_url}/files/{file_id}/url"
+        params = {"expiry": 1}
+
+        headers = {**self.headers, "Accept": "application/json"}
+
+        async def url_request():
+            self._debug_log(f"Getting signed URL for file ID: {file_id}")
+            async with session.get(
+                url,
+                headers=headers,
+                params=params,
+                timeout=aiohttp.ClientTimeout(total=self.url_timeout),
+            ) as response:
+                return await self._handle_response_async(response)
+
+        response_data = await self._retry_request_async(url_request)
+
+        signed_url = response_data.get("url")
+        if not signed_url:
+            raise ValueError("Signed URL not found in response.")
+
+        self._debug_log("Signed URL received successfully")
+        return signed_url
+
+    def _process_ocr(self, signed_url: str) -> Dict[str, Any]:
+        """Sends the signed URL to the OCR endpoint for processing (sync version)."""
+        log.info("Processing OCR via Mistral API")
+        url = f"{self.base_url}/ocr"
+        ocr_headers = {
+            **self.headers,
+            "Content-Type": "application/json",
+            "Accept": "application/json",
+        }
+        payload = {
+            "model": "mistral-ocr-latest",
+            "document": {
+                "type": "document_url",
+                "document_url": signed_url,
+            },
+            "include_image_base64": False,
+        }
+
+        def ocr_request():
+            response = requests.post(
+                url, headers=ocr_headers, json=payload, timeout=self.ocr_timeout
+            )
+            return self._handle_response(response)
+
+        try:
+            ocr_response = self._retry_request_sync(ocr_request)
+            log.info("OCR processing done.")
+            self._debug_log("OCR response: %s", ocr_response)
+            return ocr_response
+        except Exception as e:
+            log.error(f"Failed during OCR processing: {e}")
+            raise
+
+    async def _process_ocr_async(
+        self, session: aiohttp.ClientSession, signed_url: str
+    ) -> Dict[str, Any]:
+        """Async OCR processing with timing metrics."""
+        url = f"{self.base_url}/ocr"
+
+        headers = {
+            **self.headers,
+            "Content-Type": "application/json",
+            "Accept": "application/json",
+        }
+
+        payload = {
+            "model": "mistral-ocr-latest",
+            "document": {
+                "type": "document_url",
+                "document_url": signed_url,
+            },
+            "include_image_base64": False,
+        }
+
+        async def ocr_request():
+            log.info("Starting OCR processing via Mistral API")
+            start_time = time.time()
+
+            async with session.post(
+                url,
+                json=payload,
+                headers=headers,
+                timeout=aiohttp.ClientTimeout(total=self.ocr_timeout),
+            ) as response:
+                ocr_response = await self._handle_response_async(response)
+
+            processing_time = time.time() - start_time
+            log.info(f"OCR processing completed in {processing_time:.2f}s")
+
+            return ocr_response
+
+        return await self._retry_request_async(ocr_request)
+
+    def _delete_file(self, file_id: str) -> None:
+        """Deletes the file from Mistral storage (sync version)."""
+        log.info(f"Deleting uploaded file ID: {file_id}")
+        url = f"{self.base_url}/files/{file_id}"
+
+        try:
+            response = requests.delete(
+                url, headers=self.headers, timeout=self.cleanup_timeout
+            )
+            delete_response = self._handle_response(response)
+            log.info(f"File deleted successfully: {delete_response}")
+        except Exception as e:
+            # Log error but don't necessarily halt execution if deletion fails
+            log.error(f"Failed to delete file ID {file_id}: {e}")
+
+    async def _delete_file_async(
+        self, session: aiohttp.ClientSession, file_id: str
+    ) -> None:
+        """Async file deletion with error tolerance."""
+        try:
+
+            async def delete_request():
+                self._debug_log(f"Deleting file ID: {file_id}")
+                async with session.delete(
+                    url=f"{self.base_url}/files/{file_id}",
+                    headers=self.headers,
+                    timeout=aiohttp.ClientTimeout(
+                        total=self.cleanup_timeout
+                    ),  # Shorter timeout for cleanup
+                ) as response:
+                    return await self._handle_response_async(response)
+
+            await self._retry_request_async(delete_request)
+            self._debug_log(f"File {file_id} deleted successfully")
+
+        except Exception as e:
+            # Don't fail the entire process if cleanup fails
+            log.warning(f"Failed to delete file ID {file_id}: {e}")
+
+    @asynccontextmanager
+    async def _get_session(self):
+        """Context manager for HTTP session with optimized settings."""
+        connector = aiohttp.TCPConnector(
+            limit=20,  # Increased total connection limit for better throughput
+            limit_per_host=10,  # Increased per-host limit for API endpoints
+            ttl_dns_cache=600,  # Longer DNS cache TTL (10 minutes)
+            use_dns_cache=True,
+            keepalive_timeout=60,  # Increased keepalive for connection reuse
+            enable_cleanup_closed=True,
+            force_close=False,  # Allow connection reuse
+            resolver=aiohttp.AsyncResolver(),  # Use async DNS resolver
+        )
+
+        timeout = aiohttp.ClientTimeout(
+            total=self.timeout,
+            connect=30,  # Connection timeout
+            sock_read=60,  # Socket read timeout
+        )
+
+        async with aiohttp.ClientSession(
+            connector=connector,
+            timeout=timeout,
+            headers={"User-Agent": "OpenWebUI-MistralLoader/2.0"},
+            raise_for_status=False,  # We handle status codes manually
+            trust_env=True,
+        ) as session:
+            yield session
+
+    def _process_results(self, ocr_response: Dict[str, Any]) -> List[Document]:
+        """Process OCR results into Document objects with enhanced metadata and memory efficiency."""
+        pages_data = ocr_response.get("pages")
+        if not pages_data:
+            log.warning("No pages found in OCR response.")
+            return [
+                Document(
+                    page_content="No text content found",
+                    metadata={"error": "no_pages", "file_name": self.file_name},
+                )
+            ]
+
+        documents = []
+        total_pages = len(pages_data)
+        skipped_pages = 0
+
+        # Process pages in a memory-efficient way
+        for page_data in pages_data:
+            page_content = page_data.get("markdown")
+            page_index = page_data.get("index")  # API uses 0-based index
+
+            if page_content is None or page_index is None:
+                skipped_pages += 1
+                self._debug_log(
+                    f"Skipping page due to missing 'markdown' or 'index'. Data keys: {list(page_data.keys())}"
+                )
+                continue
+
+            # Clean up content efficiently with early exit for empty content
+            if isinstance(page_content, str):
+                cleaned_content = page_content.strip()
+            else:
+                cleaned_content = str(page_content).strip()
+
+            if not cleaned_content:
+                skipped_pages += 1
+                self._debug_log(f"Skipping empty page {page_index}")
+                continue
+
+            # Create document with optimized metadata
+            documents.append(
+                Document(
+                    page_content=cleaned_content,
+                    metadata={
+                        "page": page_index,  # 0-based index from API
+                        "page_label": page_index + 1,  # 1-based label for convenience
+                        "total_pages": total_pages,
+                        "file_name": self.file_name,
+                        "file_size": self.file_size,
+                        "processing_engine": "mistral-ocr",
+                        "content_length": len(cleaned_content),
+                    },
+                )
+            )
+
+        if skipped_pages > 0:
+            log.info(
+                f"Processed {len(documents)} pages, skipped {skipped_pages} empty/invalid pages"
+            )
+
+        if not documents:
+            # Case where pages existed but none had valid markdown/index
+            log.warning(
+                "OCR response contained pages, but none had valid content/index."
+            )
+            return [
+                Document(
+                    page_content="No valid text content found in document",
+                    metadata={
+                        "error": "no_valid_pages",
+                        "total_pages": total_pages,
+                        "file_name": self.file_name,
+                    },
+                )
+            ]
+
+        return documents
+
+    def load(self) -> List[Document]:
+        """
+        Executes the full OCR workflow: upload, get URL, process OCR, delete file.
+        Synchronous version for backward compatibility.
+
+        Returns:
+            A list of Document objects, one for each page processed.
+        """
+        file_id = None
+        start_time = time.time()
+
+        try:
+            # 1. Upload file
+            file_id = self._upload_file()
+
+            # 2. Get Signed URL
+            signed_url = self._get_signed_url(file_id)
+
+            # 3. Process OCR
+            ocr_response = self._process_ocr(signed_url)
+
+            # 4. Process results
+            documents = self._process_results(ocr_response)
+
+            total_time = time.time() - start_time
+            log.info(
+                f"Sync OCR workflow completed in {total_time:.2f}s, produced {len(documents)} documents"
+            )
+
+            return documents
+
+        except Exception as e:
+            total_time = time.time() - start_time
+            log.error(
+                f"An error occurred during the loading process after {total_time:.2f}s: {e}"
+            )
+            # Return an error document on failure
+            return [
+                Document(
+                    page_content=f"Error during processing: {e}",
+                    metadata={
+                        "error": "processing_failed",
+                        "file_name": self.file_name,
+                    },
+                )
+            ]
+        finally:
+            # 5. Delete file (attempt even if prior steps failed after upload)
+            if file_id:
+                try:
+                    self._delete_file(file_id)
+                except Exception as del_e:
+                    # Log deletion error, but don't overwrite original error if one occurred
+                    log.error(
+                        f"Cleanup error: Could not delete file ID {file_id}. Reason: {del_e}"
+                    )
+
+    async def load_async(self) -> List[Document]:
+        """
+        Asynchronous OCR workflow execution with optimized performance.
+
+        Returns:
+            A list of Document objects, one for each page processed.
+        """
+        file_id = None
+        start_time = time.time()
+
+        try:
+            async with self._get_session() as session:
+                # 1. Upload file with streaming
+                file_id = await self._upload_file_async(session)
+
+                # 2. Get signed URL
+                signed_url = await self._get_signed_url_async(session, file_id)
+
+                # 3. Process OCR
+                ocr_response = await self._process_ocr_async(session, signed_url)
+
+                # 4. Process results
+                documents = self._process_results(ocr_response)
+
+                total_time = time.time() - start_time
+                log.info(
+                    f"Async OCR workflow completed in {total_time:.2f}s, produced {len(documents)} documents"
+                )
+
+                return documents
+
+        except Exception as e:
+            total_time = time.time() - start_time
+            log.error(f"Async OCR workflow failed after {total_time:.2f}s: {e}")
+            return [
+                Document(
+                    page_content=f"Error during OCR processing: {e}",
+                    metadata={
+                        "error": "processing_failed",
+                        "file_name": self.file_name,
+                    },
+                )
+            ]
+        finally:
+            # 5. Cleanup - always attempt file deletion
+            if file_id:
+                try:
+                    async with self._get_session() as session:
+                        await self._delete_file_async(session, file_id)
+                except Exception as cleanup_error:
+                    log.error(f"Cleanup failed for file ID {file_id}: {cleanup_error}")
+
+    @staticmethod
+    async def load_multiple_async(
+        loaders: List["MistralLoader"],
+        max_concurrent: int = 5,  # Limit concurrent requests
+    ) -> List[List[Document]]:
+        """
+        Process multiple files concurrently with controlled concurrency.
+
+        Args:
+            loaders: List of MistralLoader instances
+            max_concurrent: Maximum number of concurrent requests
+
+        Returns:
+            List of document lists, one for each loader
+        """
+        if not loaders:
+            return []
+
+        log.info(
+            f"Starting concurrent processing of {len(loaders)} files with max {max_concurrent} concurrent"
+        )
+        start_time = time.time()
+
+        # Use semaphore to control concurrency
+        semaphore = asyncio.Semaphore(max_concurrent)
+
+        async def process_with_semaphore(loader: "MistralLoader") -> List[Document]:
+            async with semaphore:
+                return await loader.load_async()
+
+        # Process all files with controlled concurrency
+        tasks = [process_with_semaphore(loader) for loader in loaders]
+        results = await asyncio.gather(*tasks, return_exceptions=True)
+
+        # Handle any exceptions in results
+        processed_results = []
+        for i, result in enumerate(results):
+            if isinstance(result, Exception):
+                log.error(f"File {i} failed: {result}")
+                processed_results.append(
+                    [
+                        Document(
+                            page_content=f"Error processing file: {result}",
+                            metadata={
+                                "error": "batch_processing_failed",
+                                "file_index": i,
+                            },
+                        )
+                    ]
+                )
+            else:
+                processed_results.append(result)
+
+        # MONITORING: Log comprehensive batch processing statistics
+        total_time = time.time() - start_time
+        total_docs = sum(len(docs) for docs in processed_results)
+        success_count = sum(
+            1 for result in results if not isinstance(result, Exception)
+        )
+        failure_count = len(results) - success_count
+
+        log.info(
+            f"Batch processing completed in {total_time:.2f}s: "
+            f"{success_count} files succeeded, {failure_count} files failed, "
+            f"produced {total_docs} total documents"
+        )
+
+        return processed_results

backend/open_webui/retrieval/loaders/tavily.py

@@ -0,0 +1,91 @@
+import requests
+import logging
+from typing import Iterator, List, Literal, Union
+
+from langchain_core.document_loaders import BaseLoader
+from langchain_core.documents import Document
+
+log = logging.getLogger(__name__)
+
+
+class TavilyLoader(BaseLoader):
+    """Extract web page content from URLs using Tavily Extract API.
+
+    This is a LangChain document loader that uses Tavily's Extract API to
+    retrieve content from web pages and return it as Document objects.
+
+    Args:
+        urls: URL or list of URLs to extract content from.
+        api_key: The Tavily API key.
+        extract_depth: Depth of extraction, either "basic" or "advanced".
+        continue_on_failure: Whether to continue if extraction of a URL fails.
+    """
+
+    def __init__(
+        self,
+        urls: Union[str, List[str]],
+        api_key: str,
+        extract_depth: Literal["basic", "advanced"] = "basic",
+        continue_on_failure: bool = True,
+    ) -> None:
+        """Initialize Tavily Extract client.
+
+        Args:
+            urls: URL or list of URLs to extract content from.
+            api_key: The Tavily API key.
+            include_images: Whether to include images in the extraction.
+            extract_depth: Depth of extraction, either "basic" or "advanced".
+                advanced extraction retrieves more data, including tables and
+                embedded content, with higher success but may increase latency.
+                basic costs 1 credit per 5 successful URL extractions,
+                advanced costs 2 credits per 5 successful URL extractions.
+            continue_on_failure: Whether to continue if extraction of a URL fails.
+        """
+        if not urls:
+            raise ValueError("At least one URL must be provided.")
+
+        self.api_key = api_key
+        self.urls = urls if isinstance(urls, list) else [urls]
+        self.extract_depth = extract_depth
+        self.continue_on_failure = continue_on_failure
+        self.api_url = "https://api.tavily.com/extract"
+
+    def lazy_load(self) -> Iterator[Document]:
+        """Extract and yield documents from the URLs using Tavily Extract API."""
+        batch_size = 20
+        for i in range(0, len(self.urls), batch_size):
+            batch_urls = self.urls[i : i + batch_size]
+            try:
+                headers = {
+                    "Content-Type": "application/json",
+                    "Authorization": f"Bearer {self.api_key}",
+                }
+                # Use string for single URL, array for multiple URLs
+                urls_param = batch_urls[0] if len(batch_urls) == 1 else batch_urls
+                payload = {"urls": urls_param, "extract_depth": self.extract_depth}
+                # Make the API call
+                response = requests.post(self.api_url, headers=headers, json=payload)
+                response.raise_for_status()
+                response_data = response.json()
+                # Process successful results
+                for result in response_data.get("results", []):
+                    url = result.get("url", "")
+                    content = result.get("raw_content", "")
+                    if not content:
+                        log.warning(f"No content extracted from {url}")
+                        continue
+                    # Add URLs as metadata
+                    metadata = {"source": url}
+                    yield Document(
+                        page_content=content,
+                        metadata=metadata,
+                    )
+                for failed in response_data.get("failed_results", []):
+                    url = failed.get("url", "")
+                    error = failed.get("error", "Unknown error")
+                    log.error(f"Failed to extract content from {url}: {error}")
+            except Exception as e:
+                if self.continue_on_failure:
+                    log.error(f"Error extracting content from batch {batch_urls}: {e}")
+                else:
+                    raise e

backend/open_webui/retrieval/loaders/youtube.py

@@ -0,0 +1,164 @@
+import logging
+from xml.etree.ElementTree import ParseError
+
+from typing import Any, Dict, Generator, List, Optional, Sequence, Union
+from urllib.parse import parse_qs, urlparse
+from langchain_core.documents import Document
+
+log = logging.getLogger(__name__)
+
+ALLOWED_SCHEMES = {"http", "https"}
+ALLOWED_NETLOCS = {
+    "youtu.be",
+    "m.youtube.com",
+    "youtube.com",
+    "www.youtube.com",
+    "www.youtube-nocookie.com",
+    "vid.plus",
+}
+
+
+def _parse_video_id(url: str) -> Optional[str]:
+    """Parse a YouTube URL and return the video ID if valid, otherwise None."""
+    parsed_url = urlparse(url)
+
+    if parsed_url.scheme not in ALLOWED_SCHEMES:
+        return None
+
+    if parsed_url.netloc not in ALLOWED_NETLOCS:
+        return None
+
+    path = parsed_url.path
+
+    if path.endswith("/watch"):
+        query = parsed_url.query
+        parsed_query = parse_qs(query)
+        if "v" in parsed_query:
+            ids = parsed_query["v"]
+            video_id = ids if isinstance(ids, str) else ids[0]
+        else:
+            return None
+    else:
+        path = parsed_url.path.lstrip("/")
+        video_id = path.split("/")[-1]
+
+    if len(video_id) != 11:  # Video IDs are 11 characters long
+        return None
+
+    return video_id
+
+
+class YoutubeLoader:
+    """Load `YouTube` video transcripts."""
+
+    def __init__(
+        self,
+        video_id: str,
+        language: Union[str, Sequence[str]] = "en",
+        proxy_url: Optional[str] = None,
+    ):
+        """Initialize with YouTube video ID."""
+        _video_id = _parse_video_id(video_id)
+        self.video_id = _video_id if _video_id is not None else video_id
+        self._metadata = {"source": video_id}
+        self.proxy_url = proxy_url
+
+        # Ensure language is a list
+        if isinstance(language, str):
+            self.language = [language]
+        else:
+            self.language = list(language)
+
+        # Add English as fallback if not already in the list
+        if "en" not in self.language:
+            self.language.append("en")
+
+    def load(self) -> List[Document]:
+        """Load YouTube transcripts into `Document` objects."""
+        try:
+            from youtube_transcript_api import (
+                NoTranscriptFound,
+                TranscriptsDisabled,
+                YouTubeTranscriptApi,
+            )
+            from youtube_transcript_api.proxies import GenericProxyConfig
+        except ImportError:
+            raise ImportError(
+                'Could not import "youtube_transcript_api" Python package. '
+                "Please install it with `pip install youtube-transcript-api`."
+            )
+
+        if self.proxy_url:
+            youtube_proxies = GenericProxyConfig(
+                http_url=self.proxy_url, https_url=self.proxy_url
+            )
+            log.debug(f"Using proxy URL: {self.proxy_url[:14]}...")
+        else:
+            youtube_proxies = None
+
+        transcript_api = YouTubeTranscriptApi(proxy_config=youtube_proxies)
+        try:
+            transcript_list = transcript_api.list(self.video_id)
+        except Exception as e:
+            log.exception("Loading YouTube transcript failed")
+            return []
+
+        # Try each language in order of priority
+        for lang in self.language:
+            try:
+                transcript = transcript_list.find_transcript([lang])
+                if transcript.is_generated:
+                    log.debug(f"Found generated transcript for language '{lang}'")
+                    try:
+                        transcript = transcript_list.find_manually_created_transcript(
+                            [lang]
+                        )
+                        log.debug(f"Found manual transcript for language '{lang}'")
+                    except NoTranscriptFound:
+                        log.debug(
+                            f"No manual transcript found for language '{lang}', using generated"
+                        )
+                        pass
+
+                log.debug(f"Found transcript for language '{lang}'")
+                try:
+                    transcript_pieces: List[Dict[str, Any]] = transcript.fetch()
+                except ParseError:
+                    log.debug(f"Empty or invalid transcript for language '{lang}'")
+                    continue
+
+                if not transcript_pieces:
+                    log.debug(f"Empty transcript for language '{lang}'")
+                    continue
+
+                transcript_text = " ".join(
+                    map(
+                        lambda transcript_piece: (
+                            transcript_piece.text.strip(" ")
+                            if hasattr(transcript_piece, "text")
+                            else ""
+                        ),
+                        transcript_pieces,
+                    )
+                )
+                return [Document(page_content=transcript_text, metadata=self._metadata)]
+            except NoTranscriptFound:
+                log.debug(f"No transcript found for language '{lang}'")
+                continue
+            except Exception as e:
+                log.info(f"Error finding transcript for language '{lang}'")
+                raise e
+
+        # If we get here, all languages failed
+        languages_tried = ", ".join(self.language)
+        log.warning(
+            f"No transcript found for any of the specified languages: {languages_tried}. Verify if the video has transcripts, add more languages if needed."
+        )
+        raise NoTranscriptFound(self.video_id, self.language, list(transcript_list))
+
+    async def aload(self) -> Generator[Document, None, None]:
+        """Asynchronously load YouTube transcripts into `Document` objects."""
+        import asyncio
+
+        loop = asyncio.get_event_loop()
+        return await loop.run_in_executor(None, self.load)