api/docs.py

import asyncio
from aiolimiter import AsyncLimiter
from pathlib import Path
import traceback
from typing import Literal, Tuple
from fastapi.routing import APIRouter
import logging
import io
import zipfile
import os
from httpx import AsyncClient
from pydantic import BaseModel
import subprocess
import pandas as pd
import re
import tempfile
from lxml import etree
from bs4 import BeautifulSoup
from fastapi import Depends, HTTPException
from dependencies import get_http_client, get_llm_router
from fastapi.responses import StreamingResponse
from litellm.router import Router
from kreuzberg import ExtractionConfig, extract_bytes

from schemas import GetMeetingDocsRequest, GetMeetingDocsResponse, DocRequirements, DownloadDocsRequest, GetMeetingsRequest, GetMeetingsResponse, ExtractRequirementsRequest, ExtractRequirementsResponse

# API router for requirement extraction from docs / doc list retrieval / download
router = APIRouter(tags=["document extraction"])

# ==================================================== Utilities =================================================================
NSMAP = {
    'w': 'http://schemas.openxmlformats.org/wordprocessingml/2006/main',
    'v': 'urn:schemas-microsoft-com:vml'
}

# ================================== Converting of files to .txt ====================================

KREUZBERG_CONFIG: ExtractionConfig = ExtractionConfig(
    force_ocr=False, ocr_backend=None)

# Unfortunately needs to be kept to 1, as libreoffice isn't built to support parallel instances
LO_CONVERSION_MUTEX = asyncio.Semaphore(1)


async def convert_file(contents: io.BytesIO, filename: str, input_ext: str, output_ext: str, filter: str = None) -> io.BytesIO:
    """
    Converts the given file bytes using Libreoffice headless to the specified file type.
    This is an asynchronous version.

    Args:
        contents: File contents
        filename: File base name WITHOUT THE EXTENSION
        input_ext: Input extension (WITHOUT THE DOT)
        output_ext: Output extension (WITHOUT THE DOT)
        filter: The conversion filter to use.
    """

    await LO_CONVERSION_MUTEX.acquire()

    with tempfile.TemporaryDirectory() as tmpdir:
        dir_path = Path(tmpdir)
        input_file_path = dir_path / f"{filename}.{input_ext}"
        output_file_path = dir_path / f"{filename}.{output_ext}"

        # write the memory contents to the input file
        with open(input_file_path, "wb") as in_file:
            in_file.write(contents.read())

        out_bytes = io.BytesIO()

        # construct the command
        command = [
            "libreoffice",
            "--headless",
            "--convert-to", f"{output_ext}:{filter}" if filter else output_ext,
            "--outdir", tmpdir,
            str(input_file_path)  # Ensure path is a string for subprocess
        ]

        # convert using libreoffice asynchronously
        process = await asyncio.create_subprocess_exec(
            *command,
            stdout=asyncio.subprocess.PIPE,
            stderr=asyncio.subprocess.PIPE
        )

        stdout, stderr = await process.communicate()

        exit_code = await process.wait()

        if exit_code != 0 and not output_file_path.exists():
            raise subprocess.CalledProcessError(
                exit_code,
                command,
                output=stdout,
                stderr=stderr
            )

        LO_CONVERSION_MUTEX.release()

        with open(output_file_path, mode="rb") as out:
            out_bytes.write(out.read())

        out_bytes.seek(0)
        return out_bytes


# Rate limit of FTP downloads per minute
FTP_DOWNLOAD_RATE_LIMITER = AsyncLimiter(max_rate=60, time_period=60)
# Max number of parallel workers downloading
FTP_MAX_PARALLEL_WORKERS = asyncio.Semaphore(4)


async def get_doc_archive(url: str, client: AsyncClient) -> tuple[str, str, io.BytesIO]:
    """Récupère le docx depuis l'URL et le retourne un tuple (nom, extension, contenu)"""

    async with FTP_DOWNLOAD_RATE_LIMITER:
        async with FTP_MAX_PARALLEL_WORKERS:
            if not url.endswith("zip"):
                raise ValueError("URL doit pointer vers un fichier ZIP")

            doc_id = os.path.splitext(os.path.basename(url))[0]
            resp = await client.get(url, headers={
                "User-Agent": 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36'
            })

            resp.raise_for_status()

            with zipfile.ZipFile(io.BytesIO(resp.content)) as zf:
                # there should be a single file per file
                for entry in zf.infolist():
                    if entry.is_dir():
                        continue

                    file_name = entry.filename
                    root, ext = os.path.splitext(file_name)
                    doc_bytes = zf.read(file_name)
                    return (root, ext.lower(), io.BytesIO(doc_bytes))

            raise ValueError("Aucun fichier trouvé dans l'archive")


def apply_docx_revisions(docx_zip: zipfile.ZipFile) -> io.BytesIO:
    """
    Applique les révisions des .docx avant de retourner le contenu.

    Args:
        docx_zip: Le document word sous forme de zip
    """

    try:
        xml_bytes = docx_zip.read('word/document.xml')
    except KeyError:
        raise FileNotFoundError(
            "word/document.xml not found in the DOCX archive.")

    parser = etree.XMLParser(remove_blank_text=True)
    root = etree.fromstring(xml_bytes, parser=parser)

    # Suppression des balises <w:del> et leur contenu
    for del_elem in root.xpath('//w:del', namespaces=NSMAP):
        parent = del_elem.getparent()
        if parent is not None:
            parent.remove(del_elem)

    # Désencapsulation des balises <w:ins>
    for ins_elem in root.xpath('//w:ins', namespaces=NSMAP):
        parent = ins_elem.getparent()
        if parent is not None:
            index = parent.index(ins_elem)
            for child in ins_elem.iterchildren():
                parent.insert(index, child)
                index += 1
            parent.remove(ins_elem)

    # Nettoyage des commentaires
    for tag in ['w:commentRangeStart', 'w:commentRangeEnd', 'w:commentReference']:
        for elem in root.xpath(f'//{tag}', namespaces=NSMAP):
            parent = elem.getparent()
            if parent is not None:
                parent.remove(elem)

    # 3. Create a new docx with the modified XML
    output = io.BytesIO()

    with zipfile.ZipFile(output, 'w', compression=zipfile.ZIP_DEFLATED) as new_zip:
        # Copier tous les fichiers non modifiés
        for file_info in docx_zip.infolist():
            if file_info.filename != 'word/document.xml':
                new_zip.writestr(file_info, docx_zip.read(file_info.filename))

        # Ajouter le document.xml modifié
        xml_str = etree.tostring(
            root,
            xml_declaration=True,
            encoding='UTF-8',
            pretty_print=True
        )
        new_zip.writestr('word/document.xml', xml_str)

    output.seek(0)
    return output


FORMAT_MIME_TYPES = {
    ".docx": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
    ".pdf": "application/pdf",
    ".pptx": "application/vnd.openxmlformats-officedocument.presentationml.presentation"
}


async def doc_to_txt(doc_id: str, url: str, client: AsyncClient) -> str:
    """
    Télécharge le TDoc spécifié et le convertit en texte.
    """

    # Grab the document archive
    filename, ext, bytes = await get_doc_archive(url, client)

    final_text: str = None
    if ext == ".doc":
        logging.debug(f"Converting {filename} .doc --> .docx")
        docx_bytes = await convert_file(bytes, doc_id, "doc", "docx")
        extracted_data = await extract_bytes(docx_bytes.read(), FORMAT_MIME_TYPES[".docx"], config=KREUZBERG_CONFIG)
        final_text = extracted_data.content
    elif ext == ".docx":
        # Applying doc revisions to docx files (especially for pCR / draftCR files)
        logging.debug(f"Updating .docx revisions for {doc_id}.")
        applied_revision = apply_docx_revisions(zipfile.ZipFile(bytes))
        extracted_data = await extract_bytes(applied_revision.read(), FORMAT_MIME_TYPES[".docx"], config=KREUZBERG_CONFIG)
        final_text = extracted_data.content
    else:
        if ext in FORMAT_MIME_TYPES:  # file extension is supported
            extracted_data = await extract_bytes(bytes.read(), FORMAT_MIME_TYPES[ext], config=KREUZBERG_CONFIG)
            final_text = extracted_data.content
        else:
            raise Exception(
                f"Unsupported file type: {ext}, filename: {filename}")

    txt_data = [line.strip()
                for line in final_text.splitlines() if line.strip()]

    return txt_data


# ============================================= Doc routes =========================================================

@router.post("/get_meetings", response_model=GetMeetingsResponse)
async def get_meetings(req: GetMeetingsRequest, http_client: AsyncClient = Depends(get_http_client)):
    """
    Retrieves the list of meetings for the given working group.
    """
    # Extracting WG
    working_group = req.working_group
    tsg = re.sub(r"\d+", "", working_group)
    wg_number = re.search(r"\d", working_group).group(0)

    # building corresponding FTP url
    logging.debug(tsg, wg_number)
    url = "https://www.3gpp.org/ftp/tsg_" + tsg
    logging.debug(url)

    ftp_request = await http_client.get(url)
    soup = BeautifulSoup(ftp_request.text, "html.parser")

    meeting_folders = []
    all_meetings = []
    wg_folders = [item.get_text() for item in soup.select("tr td a")]
    selected_folder = None

    # sanity check to ensure the requested workgroup is present in the ftp directories
    for folder in wg_folders:
        if "wg" + str(wg_number) in folder.lower():
            selected_folder = folder
            break

    url += "/" + selected_folder
    logging.debug(url)

    if selected_folder:
        resp = await http_client.get(url)
        soup = BeautifulSoup(resp.text, "html.parser")
        meeting_folders = [item.get_text() for item in soup.select("tr td a") if item.get_text(
        ).startswith("TSG") or (item.get_text().startswith("CT") and "-" in item.get_text())]
        all_meetings = [working_group + "#" + meeting.split("_", 1)[1].replace("_", " ").replace(
            "-", " ") if meeting.startswith('TSG') else meeting.replace("-", "#") for meeting in meeting_folders]

    return GetMeetingsResponse(meetings=dict(zip(all_meetings, meeting_folders)))

# ============================================================================================================================================


@router.post("/get_meeting_docs", response_model=GetMeetingDocsResponse)
async def get_meeting_docs(req: GetMeetingDocsRequest, http_client: AsyncClient = Depends(get_http_client)) -> GetMeetingDocsResponse:
    """
    Downloads the document list dataframe for a given meeting 
    """

    # FIXME: extract the document URLS from the hyperlinks in the excelsheet using openpyxl?

    # Extracting WG
    working_group = req.working_group
    tsg = re.sub(r"\d+", "", working_group)
    wg_number = re.search(r"\d", working_group).group(0)
    url = "https://www.3gpp.org/ftp/tsg_" + tsg
    logging.info("Fetching TDocs dataframe")

    resp = await http_client.get(url)
    soup = BeautifulSoup(resp.text, "html.parser")
    wg_folders = [item.get_text() for item in soup.select("tr td a")]
    selected_folder = None
    for folder in wg_folders:
        if "wg" + str(wg_number) in folder.lower():
            selected_folder = folder
            break

    url += "/" + selected_folder + "/" + req.meeting + "/docs"
    resp = await http_client.get(url)
    soup = BeautifulSoup(resp.text, "html.parser")
    files = [item.get_text() for item in soup.select("tr td a")
             if item.get_text().endswith(".xlsx")]

    if files == []:
        raise HTTPException(status_code=404, detail="No XLSX has been found")

    df = pd.read_excel(str(url + "/" + files[0]).replace("#", "%23"))
    filtered_df = df[~(
        df["Uploaded"].isna())][["TDoc", "Title", "CR category", "For", "Source", "Type", "Agenda item", "Agenda item description", "TDoc Status"]]
    filtered_df["URL"] = filtered_df["TDoc"].apply(
        lambda tdoc: f"{url}/{tdoc}.zip")

    df = filtered_df.fillna("")
    return GetMeetingDocsResponse(data=df[["TDoc", "Title", "Type", "For", "TDoc Status", "Agenda item description", "URL"]].to_dict(orient="records"))

# ==================================================================================================================================


@router.post("/download_docs")
async def download_docs(req: DownloadDocsRequest, http_client: AsyncClient = Depends(get_http_client)) -> StreamingResponse:
    """Download the specified TDocs and zips them in a single archive"""

    # Document IDs to download
    document_ids = [doc.document for doc in req.documents]

    logging.info(f"Downloading TDocs: {document_ids}")

    async def _process_single_document(doc_id: str, doc_url: str) -> Tuple[bool, bytes]:
        """Attempts to convert a document to text and returns success status and content."""
        try:
            text_lines = await doc_to_txt(doc_id, doc_url, http_client)
            content_bytes = "\n".join(text_lines).encode("utf-8")
            return {"doc_id": doc_id, "content": content_bytes}
        except Exception as e:
            logging.warning(
                f"Failed to process document '{doc_id}' from URL '{doc_url}': {e}")
            error_message = f"Document '{doc_id}' text extraction failed: {e}".encode(
                "utf-8")
            return {"doc_id": doc_id, "content": error_message, "failed": True}

    convert_tasks = await asyncio.gather(*[_process_single_document(doc.document, doc.url) for doc in req.documents], return_exceptions=False)

    zip_buffer = io.BytesIO()
    with zipfile.ZipFile(zip_buffer, mode='w', compression=zipfile.ZIP_DEFLATED) as zip_file:
        for task in convert_tasks:
            failed = "failed" in task
            doc_id = task["doc_id"]
            safe_filename = f"failed_{doc_id}.txt" if failed else f"{doc_id}.txt"
            zip_file.writestr(safe_filename, task["content"])

    zip_buffer.seek(0)

    return StreamingResponse(
        zip_buffer,
        media_type="application/zip",
        headers={"Content-Disposition": "attachment; filename=tdocs.zip"}
    )

# ======================================================================================================================================================================================


class ProgressUpdate(BaseModel):
    """Defines the structure of a single SSE message."""
    status: Literal["progress", "complete"]
    data: dict
    total_docs: int
    processed_docs: int


@router.post("/extract_requirements/sse")
async def extract_requirements_from_docs(req: ExtractRequirementsRequest, llm_router: Router = Depends(get_llm_router), http_client: AsyncClient = Depends(get_http_client)):
    """Extract requirements from the specified xxxxCR docs using a LLM and returns SSE events about the progress of ongoing operations"""

    documents = req.documents
    n_docs = len(documents)

    logging.info(
        "Generating requirements for documents: {}".format(req.documents))

    # limit max concurrency of LLM requests to prevent a huge pile of errors because of small rate limits
    concurrency_sema = asyncio.Semaphore(4)

    def prompt(doc_id, full):
        return f"Here's the document whose ID is {doc_id} : {full}\n\nExtract all requirements and group them by context, returning a list of objects where each object includes a document ID, a concise description of the context where the requirements apply (not a chapter title or copied text), and a list of associated requirements; always return the result as a list, even if only one context is found. Remove the errors"

    async def _process_document(doc) -> list[DocRequirements]:
        doc_id = doc.document
        url = doc.url

        # convert the docx to txt for use
        try:
            doc = await doc_to_txt(doc_id, url, http_client)
            full = "\n".join(doc)
        except Exception as e:
            fmt = "".join(traceback.format_exception(e))
            logging.error(f"Failed to process doc {doc_id} : {fmt}")
            return [DocRequirements(document=doc_id, context="Failed to process document", requirements=[])]

        try:
            await concurrency_sema.acquire()

            model_used = "gemini-v2"
            resp_ai = await llm_router.acompletion(
                model=model_used,
                messages=[
                    {"role": "user", "content": prompt(doc_id, full)}],
                response_format=ExtractRequirementsResponse
            )
            return ExtractRequirementsResponse.model_validate_json(resp_ai.choices[0].message.content).requirements
        except Exception as e:
            return [DocRequirements(document=doc_id, context="Error LLM", requirements=[])]
        finally:
            concurrency_sema.release()

    # futures for all processed documents
    process_futures = [_process_document(doc) for doc in documents]

    # lambda to print progress
    def progress_update(x): return f"data: {x.model_dump_json()}\n\n"

    # async generator that generates  the SSE events for progress
    async def _stream_generator(docs: list[asyncio.Future]):
        items = []
        n_processed = 0

        yield progress_update(ProgressUpdate(status="progress", data={}, total_docs=n_docs, processed_docs=0))

        for doc in asyncio.as_completed(docs):
            result = await doc
            items.extend(result)
            n_processed += 1
            yield progress_update(ProgressUpdate(status="progress", data={}, total_docs=n_docs, processed_docs=n_processed))

            final_response = ExtractRequirementsResponse(requirements=items)

        yield progress_update(ProgressUpdate(status="complete", data=final_response.model_dump(), total_docs=n_docs, processed_docs=n_processed))

    return StreamingResponse(_stream_generator(process_futures), media_type="text/event-stream")