Confluence

ConfluenceReader

Bases: BaseReader

Confluence reader.

Reads a set of confluence pages given a space key and optionally a list of page ids

For more on OAuth login, checkout: - https://atlassian-python-api.readthedocs.io/index.html - https://developer.atlassian.com/cloud/confluence/oauth-2-3lo-apps/

Parameters:

Name	Type	Description	Default
oauth2	dict	Atlassian OAuth 2.0, minimum fields are client_id and token, where token is a dict and must at least contain "access_token" and "token_type".	None
base_url	str	'base_url' for confluence cloud instance, this is suffixed with '/wiki', eg 'https://yoursite.atlassian.com/wiki'	None
cloud	bool	connecting to Confluence Cloud or self-hosted instance	True

Source code in llama-index-integrations/readers/llama-index-readers-confluence/llama_index/readers/confluence/base.py

class ConfluenceReader(BaseReader):
    """Confluence reader.

    Reads a set of confluence pages given a space key and optionally a list of page ids

    For more on OAuth login, checkout:
        - https://atlassian-python-api.readthedocs.io/index.html
        - https://developer.atlassian.com/cloud/confluence/oauth-2-3lo-apps/

    Args:
        oauth2 (dict): Atlassian OAuth 2.0, minimum fields are `client_id` and `token`, where `token` is a dict and must at least contain "access_token" and "token_type".
        base_url (str): 'base_url' for confluence cloud instance, this is suffixed with '/wiki', eg 'https://yoursite.atlassian.com/wiki'
        cloud (bool): connecting to Confluence Cloud or self-hosted instance

    """

    def __init__(
        self, base_url: str = None, oauth2: Optional[Dict] = None, cloud: bool = True
    ) -> None:
        if base_url is None:
            raise ValueError("Must provide `base_url`")

        self.base_url = base_url

        try:
            from atlassian import Confluence
        except ImportError:
            raise ImportError(
                "`atlassian` package not found, please run `pip install"
                " atlassian-python-api`"
            )
        self.confluence: Confluence = None
        if oauth2:
            self.confluence = Confluence(url=base_url, oauth2=oauth2, cloud=cloud)
        else:
            api_token = os.getenv(CONFLUENCE_API_TOKEN)
            if api_token is not None:
                self.confluence = Confluence(url=base_url, token=api_token, cloud=cloud)
            else:
                user_name = os.getenv(CONFLUENCE_USERNAME)
                if user_name is None:
                    raise ValueError(
                        "Must set environment variable `CONFLUENCE_USERNAME` if oauth,"
                        " oauth2, or `CONFLUENCE_API_TOKEN` are not provided."
                    )
                password = os.getenv(CONFLUENCE_PASSWORD)
                if password is None:
                    raise ValueError(
                        "Must set environment variable `CONFLUENCE_PASSWORD` if oauth,"
                        " oauth2, or `CONFLUENCE_API_TOKEN` are not provided."
                    )
                self.confluence = Confluence(
                    url=base_url, username=user_name, password=password, cloud=cloud
                )

        self._next_cursor = None

    def load_data(
        self,
        space_key: Optional[str] = None,
        page_ids: Optional[List[str]] = None,
        page_status: Optional[str] = None,
        label: Optional[str] = None,
        cql: Optional[str] = None,
        include_attachments=False,
        include_children=False,
        start: Optional[int] = None,
        cursor: Optional[str] = None,
        limit: Optional[int] = None,
        max_num_results: Optional[int] = None,
    ) -> List[Document]:
        """Load Confluence pages from Confluence, specifying by one of four mutually exclusive methods:
        `space_key`, `page_ids`, `label`, or `cql`
        (Confluence Query Language https://developer.atlassian.com/cloud/confluence/advanced-searching-using-cql/ ).

        Args:
            space_key (str): Confluence space key, eg 'DS'
            page_ids (list): List of page ids, eg ['123456', '123457']
            page_status (str): Page status, one of None (all statuses), 'current', 'draft', 'archived'.  Only compatible with space_key.
            label (str): Confluence label, eg 'my-label'
            cql (str): Confluence Query Language query, eg 'label="my-label"'
            include_attachments (bool): If True, include attachments.
            include_children (bool): If True, do a DFS of the descendants of each page_id in `page_ids`.  Only compatible with `page_ids`.
            start (int): Skips over the first n elements. Used only with space_key
            cursor (str): Skips to the cursor. Used with cql and label, set when the max limit has been hit for cql based search
            limit (int): Deprecated, use `max_num_results` instead.
            max_num_results (int): Maximum number of results to return.  If None, return all results.  Requests are made in batches to achieve the desired number of results.
        """
        num_space_key_parameter = 1 if space_key else 0
        num_page_ids_parameter = 1 if page_ids is not None else 0
        num_label_parameter = 1 if label else 0
        num_cql_parameter = 1 if cql else 0
        if (
            num_space_key_parameter
            + num_page_ids_parameter
            + num_label_parameter
            + num_cql_parameter
            != 1
        ):
            raise ValueError(
                "Must specify exactly one among `space_key`, `page_ids`, `label`, `cql`"
                " parameters."
            )

        if cursor and start:
            raise ValueError("Must not specify `start` when `cursor` is specified")

        if space_key and cursor:
            raise ValueError("Must not specify `cursor` when `space_key` is specified")

        if page_status and not space_key:
            raise ValueError(
                "Must specify `space_key` when `page_status` is specified."
            )

        if include_children and not page_ids:
            raise ValueError(
                "Must specify `page_ids` when `include_children` is specified."
            )

        if limit is not None:
            max_num_results = limit
            logger.warning(
                "`limit` is deprecated and no longer relates to the Confluence server's"
                " API limits.  If you wish to limit the number of returned results"
                " please use `max_num_results` instead."
            )

        try:
            import html2text  # type: ignore
        except ImportError:
            raise ImportError(
                "`html2text` package not found, please run `pip install html2text`"
            )

        text_maker = html2text.HTML2Text()
        text_maker.ignore_links = True
        text_maker.ignore_images = True

        if not start:
            start = 0

        pages: List = []
        if space_key:
            pages.extend(
                self._get_data_with_paging(
                    self.confluence.get_all_pages_from_space,
                    start=start,
                    max_num_results=max_num_results,
                    space=space_key,
                    status=page_status,
                    expand="body.export_view.value",
                    content_type="page",
                )
            )
        elif label:
            pages.extend(
                self._get_cql_data_with_paging(
                    start=start,
                    cursor=cursor,
                    cql=f'type="page" AND label="{label}"',
                    max_num_results=max_num_results,
                    expand="body.export_view.value",
                )
            )
        elif cql:
            pages.extend(
                self._get_cql_data_with_paging(
                    start=start,
                    cursor=cursor,
                    cql=cql,
                    max_num_results=max_num_results,
                    expand="body.export_view.value",
                )
            )
        elif page_ids:
            if include_children:
                dfs_page_ids = []
                max_num_remaining = max_num_results
                for page_id in page_ids:
                    current_dfs_page_ids = self._dfs_page_ids(
                        page_id, max_num_remaining
                    )
                    dfs_page_ids.extend(current_dfs_page_ids)
                    if max_num_results is not None:
                        max_num_remaining -= len(current_dfs_page_ids)
                        if max_num_remaining <= 0:
                            break
                page_ids = dfs_page_ids
            for page_id in (
                page_ids[:max_num_results] if max_num_results is not None else page_ids
            ):
                pages.append(
                    self._get_data_with_retry(
                        self.confluence.get_page_by_id,
                        page_id=page_id,
                        expand="body.export_view.value",
                    )
                )

        docs = []
        for page in pages:
            doc = self.process_page(page, include_attachments, text_maker)
            docs.append(doc)

        return docs

    def _dfs_page_ids(self, page_id, max_num_results):
        ret = [page_id]
        max_num_remaining = (
            (max_num_results - 1) if max_num_results is not None else None
        )
        if max_num_results is not None and max_num_remaining <= 0:
            return ret

        child_page_ids = self._get_data_with_paging(
            self.confluence.get_child_id_list,
            page_id=page_id,
            type="page",
            max_num_results=max_num_remaining,
        )
        for child_page_id in child_page_ids:
            dfs_ids = self._dfs_page_ids(child_page_id, max_num_remaining)
            ret.extend(dfs_ids)
            if max_num_results is not None:
                max_num_remaining -= len(dfs_ids)
                if max_num_remaining <= 0:
                    break
        return ret

    def _get_data_with_paging(
        self, paged_function, start=0, max_num_results=50, **kwargs
    ):
        max_num_remaining = max_num_results
        ret = []
        while True:
            results = self._get_data_with_retry(
                paged_function, start=start, limit=max_num_remaining, **kwargs
            )
            ret.extend(results)
            if (
                len(results) == 0
                or max_num_results is not None
                and len(results) >= max_num_remaining
            ):
                break

            start += len(results)
            if max_num_remaining is not None:
                max_num_remaining -= len(results)
        return ret

    def _get_cql_data_with_paging(
        self,
        cql,
        start=0,
        cursor=None,
        max_num_results=50,
        expand="body.export_view.value",
    ):
        max_num_remaining = max_num_results
        ret = []
        params = {"cql": cql, "start": start, "expand": expand}
        if cursor:
            params["cursor"] = unquote(cursor)

        if max_num_results is not None:
            params["limit"] = max_num_remaining
        while True:
            results = self._get_data_with_retry(
                self.confluence.get, path="rest/api/content/search", params=params
            )
            ret.extend(results["results"])

            params["start"] += len(results["results"])

            next_url = (
                results["_links"]["next"] if "next" in results["_links"] else None
            )
            if not next_url:
                self._next_cursor = None
                break

            if "cursor=" in next_url:  # On confluence Server this is not set
                cursor = next_url.split("cursor=")[1].split("&")[0]
                params["cursor"] = unquote(cursor)

            if max_num_results is not None:
                params["limit"] -= len(results["results"])
                if params["limit"] <= 0:
                    self._next_cursor = cursor
                    break

        return ret

    def get_next_cursor(self):
        """
        Returns: The last set cursor from a cql based search.
        """
        return self._next_cursor

    @retry(stop_max_attempt_number=1, wait_fixed=4)
    def _get_data_with_retry(self, function, **kwargs):
        return function(**kwargs)

    def process_page(self, page, include_attachments, text_maker):
        logger.info("Processing " + self.base_url + page["_links"]["webui"])

        if include_attachments:
            attachment_texts = self.process_attachment(page["id"])
        else:
            attachment_texts = []
        text = text_maker.handle(page["body"]["export_view"]["value"]) + "".join(
            attachment_texts
        )
        return Document(
            text=text,
            doc_id=page["id"],
            extra_info={
                "title": page["title"],
                "page_id": page["id"],
                "status": page["status"],
                "url": self.base_url + page["_links"]["webui"],
            },
        )

    def process_attachment(self, page_id):
        try:
            pass
        except ImportError:
            raise ImportError(
                "`pytesseract` or `pdf2image` or `Pillow` package not found, please run"
                " `pip install pytesseract pdf2image Pillow`"
            )

        # depending on setup you may also need to set the correct path for poppler and tesseract
        attachments = self.confluence.get_attachments_from_content(page_id)["results"]
        texts = []
        for attachment in attachments:
            media_type = attachment["metadata"]["mediaType"]
            absolute_url = self.base_url + attachment["_links"]["download"]
            title = attachment["title"]
            if media_type == "application/pdf":
                logger.info("Processing PDF attachment " + absolute_url)
                text = title + self.process_pdf(absolute_url)
            elif (
                media_type == "image/png"
                or media_type == "image/jpg"
                or media_type == "image/jpeg"
                or media_type == "image/webp"
            ):
                logger.info("Processing image attachment " + absolute_url)
                text = title + self.process_image(absolute_url)
            elif (
                media_type
                == "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
            ):
                logger.info("Processing Word document attachment " + absolute_url)
                text = title + self.process_doc(absolute_url)
            elif (
                media_type == "application/vnd.ms-excel"
                or media_type
                == "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet"
                or media_type == "application/vnd.ms-excel.sheet.macroenabled.12"
            ):
                if title.endswith(".csv") or absolute_url.endswith(".csv"):
                    logger.info("Processing CSV attachment " + absolute_url)
                    text = title + self.process_csv(absolute_url)
                else:
                    logger.info("Processing XLS attachment " + absolute_url)
                    text = title + self.process_xls(absolute_url)
            elif media_type == "application/vnd.ms-excel.sheet.binary.macroenabled.12":
                logger.info("Processing XLSB attachment " + absolute_url)
                text = title + self.process_xlsb(absolute_url)
            elif media_type == "text/csv":
                logger.info("Processing CSV attachment " + absolute_url)
                text = title + self.process_csv(absolute_url)
            elif media_type == "application/vnd.ms-outlook":
                logger.info("Processing Outlook message attachment " + absolute_url)
                text = title + self.process_msg(absolute_url)
            elif media_type == "text/html":
                logger.info("  Processing HTML attachment " + absolute_url)
                text = title + self.process_html(absolute_url)
            elif media_type == "text/plain":
                if title.endswith(".csv") or absolute_url.endswith(".csv"):
                    logger.info("Processing CSV attachment " + absolute_url)
                    text = title + self.process_csv(absolute_url)
                else:
                    logger.info("Processing Text attachment " + absolute_url)
                    text = title + self.process_txt(absolute_url)
            elif media_type == "image/svg+xml":
                logger.info("Processing SVG attachment " + absolute_url)
                text = title + self.process_svg(absolute_url)
            elif (
                media_type
                == "application/vnd.openxmlformats-officedocument.presentationml.presentation"
                or media_type
                == "application/vnd.ms-powerpoint.presentation.macroenabled.12"
            ):
                logger.info(
                    "Processing PowerPoint attachment "
                    + absolute_url
                    + " ("
                    + media_type
                    + ")"
                )
                text = title + self.process_ppt(absolute_url)
            else:
                logger.info(
                    f"Skipping unsupported attachment {absolute_url} of media_type {media_type}"
                )
                continue
            texts.append(text)

        return texts

    def process_pdf(self, link):
        try:
            import pytesseract  # type: ignore
            from pdf2image import convert_from_bytes  # type: ignore
        except ImportError:
            raise ImportError(
                "`pytesseract` or `pdf2image` package not found, please run `pip"
                " install pytesseract pdf2image`"
            )

        response = self.confluence.request(path=link, absolute=True)
        text = ""

        if (
            response.status_code != 200
            or response.content == b""
            or response.content is None
        ):
            return text
        try:
            images = convert_from_bytes(response.content)
        except ValueError:
            return text

        for i, image in enumerate(images):
            image_text = pytesseract.image_to_string(image)
            text += f"Page {i + 1}:\n{image_text}\n\n"

        return text

    def process_html(self, link):
        try:
            from bs4 import BeautifulSoup  # type: ignore
            import requests
        except ImportError:
            raise ImportError(
                "`beautifulsoup4` or `requests` package not found, please run `pip install beautifulsoup4 requests`"
            )

        try:
            response = requests.get(link)
            if response.status_code != 200:
                return "Error fetching HTML content: HTTP Status Code {}".format(
                    response.status_code
                )

            # Parse the HTML content and extract text
            soup = BeautifulSoup(response.content, "html.parser")
            return soup.get_text(separator=" ", strip=True)
        except Exception as e:
            logger.error(f"Error processing HTML file at {link}: {e}")
            return f"Error processing HTML file: {link}. An error occurred while fetching or parsing the content."

    def process_txt(self, link):
        try:
            import requests
        except ImportError:
            raise ImportError(
                "`requests` package not found, please run `pip install requests`"
            )

        try:
            response = requests.get(link)
            if response.status_code != 200:
                return "Error fetching text content: HTTP Status Code {}".format(
                    response.status_code
                )
            return response.text
        except Exception as e:
            logger.error(f"Error processing text file at {link}: {e}")
            return f"Error processing text file: {link}. An error occurred while fetching the content."

    def process_msg(self, link):
        try:
            import extract_msg  # type: ignore
            from io import BytesIO
        except ImportError:
            raise ImportError(
                "`extract-msg` package not found, please run `pip install extract-msg`"
            )

        response = self.confluence.request(path=link, absolute=True)
        text = ""

        if response.status_code != 200 or response.content in [b"", None]:
            logger.error(f"Failed to download .msg file from {link}")
            return text

        file_data = BytesIO(response.content)

        try:
            # Load the .msg file content
            with extract_msg.Message(file_data) as msg:
                subject = msg.subject
                sender = msg.sender
                to = msg.to
                cc = msg.cc
                body = msg.body

                # Compile the extracted information into a text string
                text = (
                    f"Subject: {subject}\nFrom: {sender}\nTo: {to}\nCC: {cc}\n\n{body}"
                )
        except Exception as e:
            logger.error(f"Error processing .msg file at {link}: {e}")
            return "Error processing .msg file."

        return text

    def process_image(self, link):
        try:
            from io import BytesIO  # type: ignore

            import pytesseract  # type: ignore
            from PIL import Image  # type: ignore
        except ImportError:
            raise ImportError(
                "`pytesseract` or `Pillow` package not found, please run `pip install"
                " pytesseract Pillow`"
            )

        text = ""

        try:
            response = self.confluence.request(path=link, absolute=True)
            # Check if the response status code indicates success (200 OK)
            if response.status_code == 200 and response.content:
                try:
                    image = Image.open(BytesIO(response.content))
                    text = pytesseract.image_to_string(image)
                except OSError:
                    # Handle errors that occur while opening or processing the image
                    logger.error(
                        f"Error processing image at {link}: Unable to open or read the image content."
                    )
                    return text
            else:
                # Log non-200 responses here if needed
                logger.error(
                    f"Error fetching image at {link}: HTTP status code {response.status_code}."
                )
                return text
        except requests.exceptions.RequestException as e:
            # This catches any Requests-related exceptions, including HTTPError, ConnectionError, etc.
            logger.error(f"Request error while fetching image at {link}: {e}")
            return text

        return text

    def process_doc(self, link):
        try:
            from io import BytesIO
            import docx2txt
            import zipfile  # Import zipfile to catch BadZipFile exceptions
        except ImportError:
            raise ImportError(
                "`docx2txt` package not found, please run `pip install docx2txt`"
            )

        text = ""

        try:
            response = self.confluence.request(path=link, absolute=True)
            if response.status_code != 200 or response.content in [b"", None]:
                logger.error(
                    f"Error fetching document at {link}: HTTP status code {response.status_code}."
                )
                return text

            file_data = BytesIO(response.content)
            try:
                text = docx2txt.process(file_data)
            except zipfile.BadZipFile:
                logger.error(
                    f"Error processing Word document at {link}: File is not a zip file."
                )
                return text
        except Exception as e:
            logger.error(f"Unexpected error processing document at {link}: {e}")
            return text

        return text

    def process_ppt(self, link):
        try:
            from io import BytesIO
            from pptx import Presentation  # type: ignore
        except ImportError:
            raise ImportError(
                "`python-pptx` package not found, please run `pip install python-pptx`"
            )

        response = self.confluence.request(path=link, absolute=True)
        text = ""

        if (
            response.status_code != 200
            or response.content == b""
            or response.content is None
        ):
            return text

        file_data = BytesIO(response.content)

        try:
            presentation = Presentation(file_data)
            for slide in presentation.slides:
                for shape in slide.shapes:
                    if hasattr(shape, "text"):
                        text += shape.text + " "
        except (
            Exception
        ) as e:  # Catching a general exception to handle any unexpected errors
            logger.error(f"Error processing PowerPoint file at {link}: {e}")
            text = f"Error processing PowerPoint file: {link}. The file might be corrupt or not a valid PowerPoint file."

        return text.strip()  # Remove any leading/trailing whitespace

    def process_xls(self, link):
        try:
            import pandas as pd  # type: ignore
        except ImportError:
            raise ImportError(
                "`pandas` package not found, please run `pip install pandas`"
            )
        try:
            from io import BytesIO
        except ImportError:
            raise ImportError("Failed to import BytesIO from io")

        response = self.confluence.request(path=link, absolute=True)
        text = ""

        if (
            response.status_code != 200
            or response.content == b""
            or response.content is None
        ):
            return text

        file_data = BytesIO(response.content)

        # Try to read the Excel file
        try:
            # Use pandas to read all sheets; returns a dict of DataFrame
            sheets = pd.read_excel(file_data, sheet_name=None, engine="openpyxl")
        except Exception as e:
            return f"Failed to read Excel file: {e!s}"

        for sheet_name, sheet_data in sheets.items():
            text += f"{sheet_name}:\n"
            for row_index, row in sheet_data.iterrows():
                text += "\t".join(str(value) for value in row) + "\n"
            text += "\n"

        return text.strip()

    def process_xlsb(self, link):
        try:
            import pandas as pd
            from io import BytesIO
        except ImportError:
            raise ImportError(
                "`pandas` package not found, please run `pip install pandas`"
            )

        response = self.confluence.request(path=link, absolute=True)
        text = ""

        if (
            response.status_code != 200
            or response.content == b""
            or response.content is None
        ):
            return text

        file_data = BytesIO(response.content)

        try:
            # Use pandas to read the .xlsb file, specifying pyxlsb as the engine
            df = pd.read_excel(file_data, engine="pyxlsb")
            # Convert the DataFrame to a text string
            text_rows = []
            for index, row in df.iterrows():
                text_rows.append(", ".join(row.astype(str)))
            text = "\n".join(text_rows)
        except Exception as e:
            logger.error(f"Error processing XLSB file at {link}: {e}")
            text = "Error processing XLSB file."

        return text

    def process_csv(self, link):
        try:
            import pandas as pd
            from io import BytesIO
        except ImportError:
            raise ImportError(
                "`pandas` package not found, please run `pip install pandas`"
            )

        response = self.confluence.request(path=link, absolute=True)
        text = ""

        if (
            response.status_code != 200
            or response.content == b""
            or response.content is None
        ):
            return text

        file_data = BytesIO(response.content)

        try:
            # Assuming CSV uses default comma delimiter. If delimiter varies, consider detecting it.
            df = pd.read_csv(file_data, low_memory=False)
            # Convert the DataFrame to a text string, including headers
            text_rows = []
            for index, row in df.iterrows():
                text_rows.append(", ".join(row.astype(str)))
            text = "\n".join(text_rows)
        except Exception as e:
            logger.error(f"Error processing CSV file: {e}")
            text = "Error processing CSV file."

        return text

    def process_svg(self, link):
        try:
            from io import BytesIO  # type: ignore

            import pytesseract  # type: ignore
            from PIL import Image  # type: ignore
            from reportlab.graphics import renderPM  # type: ignore
            from svglib.svglib import svg2rlg  # type: ignore
        except ImportError:
            raise ImportError(
                "`pytesseract`, `Pillow`, or `svglib` package not found, please run"
                " `pip install pytesseract Pillow svglib`"
            )

        response = self.confluence.request(path=link, absolute=True)
        text = ""

        if (
            response.status_code != 200
            or response.content == b""
            or response.content is None
        ):
            return text

        drawing = svg2rlg(BytesIO(response.content))

        img_data = BytesIO()
        renderPM.drawToFile(drawing, img_data, fmt="PNG")
        img_data.seek(0)
        image = Image.open(img_data)

        return pytesseract.image_to_string(image)

load_data

load_data(space_key: Optional[str] = None, page_ids: Optional[List[str]] = None, page_status: Optional[str] = None, label: Optional[str] = None, cql: Optional[str] = None, include_attachments=False, include_children=False, start: Optional[int] = None, cursor: Optional[str] = None, limit: Optional[int] = None, max_num_results: Optional[int] = None) -> List[Document]

Load Confluence pages from Confluence, specifying by one of four mutually exclusive methods: space_key, page_ids, label, or cql (Confluence Query Language https://developer.atlassian.com/cloud/confluence/advanced-searching-using-cql/ ).

Parameters:

Name	Type	Description	Default
space_key	str	Confluence space key, eg 'DS'	None
page_ids	list	List of page ids, eg ['123456', '123457']	None
page_status	str	Page status, one of None (all statuses), 'current', 'draft', 'archived'. Only compatible with space_key.	None
label	str	Confluence label, eg 'my-label'	None
cql	str	Confluence Query Language query, eg 'label="my-label"'	None
include_attachments	bool	If True, include attachments.	False
include_children	bool	If True, do a DFS of the descendants of each page_id in page_ids. Only compatible with page_ids.	False
start	int	Skips over the first n elements. Used only with space_key	None
cursor	str	Skips to the cursor. Used with cql and label, set when the max limit has been hit for cql based search	None
limit	int	Deprecated, use max_num_results instead.	None
max_num_results	int	Maximum number of results to return. If None, return all results. Requests are made in batches to achieve the desired number of results.	None

Source code in llama-index-integrations/readers/llama-index-readers-confluence/llama_index/readers/confluence/base.py

def load_data(
    self,
    space_key: Optional[str] = None,
    page_ids: Optional[List[str]] = None,
    page_status: Optional[str] = None,
    label: Optional[str] = None,
    cql: Optional[str] = None,
    include_attachments=False,
    include_children=False,
    start: Optional[int] = None,
    cursor: Optional[str] = None,
    limit: Optional[int] = None,
    max_num_results: Optional[int] = None,
) -> List[Document]:
    """Load Confluence pages from Confluence, specifying by one of four mutually exclusive methods:
    `space_key`, `page_ids`, `label`, or `cql`
    (Confluence Query Language https://developer.atlassian.com/cloud/confluence/advanced-searching-using-cql/ ).

    Args:
        space_key (str): Confluence space key, eg 'DS'
        page_ids (list): List of page ids, eg ['123456', '123457']
        page_status (str): Page status, one of None (all statuses), 'current', 'draft', 'archived'.  Only compatible with space_key.
        label (str): Confluence label, eg 'my-label'
        cql (str): Confluence Query Language query, eg 'label="my-label"'
        include_attachments (bool): If True, include attachments.
        include_children (bool): If True, do a DFS of the descendants of each page_id in `page_ids`.  Only compatible with `page_ids`.
        start (int): Skips over the first n elements. Used only with space_key
        cursor (str): Skips to the cursor. Used with cql and label, set when the max limit has been hit for cql based search
        limit (int): Deprecated, use `max_num_results` instead.
        max_num_results (int): Maximum number of results to return.  If None, return all results.  Requests are made in batches to achieve the desired number of results.
    """
    num_space_key_parameter = 1 if space_key else 0
    num_page_ids_parameter = 1 if page_ids is not None else 0
    num_label_parameter = 1 if label else 0
    num_cql_parameter = 1 if cql else 0
    if (
        num_space_key_parameter
        + num_page_ids_parameter
        + num_label_parameter
        + num_cql_parameter
        != 1
    ):
        raise ValueError(
            "Must specify exactly one among `space_key`, `page_ids`, `label`, `cql`"
            " parameters."
        )

    if cursor and start:
        raise ValueError("Must not specify `start` when `cursor` is specified")

    if space_key and cursor:
        raise ValueError("Must not specify `cursor` when `space_key` is specified")

    if page_status and not space_key:
        raise ValueError(
            "Must specify `space_key` when `page_status` is specified."
        )

    if include_children and not page_ids:
        raise ValueError(
            "Must specify `page_ids` when `include_children` is specified."
        )

    if limit is not None:
        max_num_results = limit
        logger.warning(
            "`limit` is deprecated and no longer relates to the Confluence server's"
            " API limits.  If you wish to limit the number of returned results"
            " please use `max_num_results` instead."
        )

    try:
        import html2text  # type: ignore
    except ImportError:
        raise ImportError(
            "`html2text` package not found, please run `pip install html2text`"
        )

    text_maker = html2text.HTML2Text()
    text_maker.ignore_links = True
    text_maker.ignore_images = True

    if not start:
        start = 0

    pages: List = []
    if space_key:
        pages.extend(
            self._get_data_with_paging(
                self.confluence.get_all_pages_from_space,
                start=start,
                max_num_results=max_num_results,
                space=space_key,
                status=page_status,
                expand="body.export_view.value",
                content_type="page",
            )
        )
    elif label:
        pages.extend(
            self._get_cql_data_with_paging(
                start=start,
                cursor=cursor,
                cql=f'type="page" AND label="{label}"',
                max_num_results=max_num_results,
                expand="body.export_view.value",
            )
        )
    elif cql:
        pages.extend(
            self._get_cql_data_with_paging(
                start=start,
                cursor=cursor,
                cql=cql,
                max_num_results=max_num_results,
                expand="body.export_view.value",
            )
        )
    elif page_ids:
        if include_children:
            dfs_page_ids = []
            max_num_remaining = max_num_results
            for page_id in page_ids:
                current_dfs_page_ids = self._dfs_page_ids(
                    page_id, max_num_remaining
                )
                dfs_page_ids.extend(current_dfs_page_ids)
                if max_num_results is not None:
                    max_num_remaining -= len(current_dfs_page_ids)
                    if max_num_remaining <= 0:
                        break
            page_ids = dfs_page_ids
        for page_id in (
            page_ids[:max_num_results] if max_num_results is not None else page_ids
        ):
            pages.append(
                self._get_data_with_retry(
                    self.confluence.get_page_by_id,
                    page_id=page_id,
                    expand="body.export_view.value",
                )
            )

    docs = []
    for page in pages:
        doc = self.process_page(page, include_attachments, text_maker)
        docs.append(doc)

    return docs

get_next_cursor

get_next_cursor()

Returns: The last set cursor from a cql based search.

Source code in llama-index-integrations/readers/llama-index-readers-confluence/llama_index/readers/confluence/base.py

def get_next_cursor(self):
    """
    Returns: The last set cursor from a cql based search.
    """
    return self._next_cursor