{config, lib, pkgs, ...}: with lib; let cfg = config.services.docspell-joex; user = if cfg.runAs == null then "docspell" else cfg.runAs; configFile = pkgs.writeText "docspell-joex.conf" '' {"docspell": { "joex": ${builtins.toJSON cfg} }} ''; defaults = { app-id = "joex1"; base-url = "http://localhost:7878"; bind = { address = "localhost"; port = 7878; }; mail-debug = false; jdbc = { url = "jdbc:h2:///tmp/docspell-demo.db;MODE=PostgreSQL;DATABASE_TO_LOWER=TRUE;AUTO_SERVER=TRUE"; user = "sa"; password = ""; }; send-mail = { list-id = ""; }; user-tasks = { scan-mailbox = { max-folders = 50; mail-chunk-size = 50; max-mails = 500; }; }; scheduler = { pool-size = 2; counting-scheme = "4,1"; retries = 2; retry-delay = "1 minute"; log-buffer-size = 500; wakeup-period = "30 minutes"; }; periodic-scheduler = { wakeup-period = "10 minutes"; }; house-keeping = { schedule = "Sun *-*-* 00:00:00"; cleanup-invites = { enabled = true; older-than = "30 days"; }; cleanup-jobs = { enabled = true; older-than = "30 days"; delete-batch = 100; }; cleanup-remember-me = { enabled = true; older-than = "30 days"; }; }; extraction = { pdf = { min-text-len = 500; }; preview = { dpi = 32; }; ocr = { max-image-size = 14000000; page-range = { begin = 10; }; ghostscript = { working-dir = "/tmp/docspell-extraction"; command = { program = "${pkgs.ghostscript}/bin/gs"; args = [ "-dNOPAUSE" "-dBATCH" "-dSAFER" "-sDEVICE=tiffscaled8" "-sOutputFile={{outfile}}" "{{infile}}" ]; timeout = "5 minutes"; }; }; unpaper = { command = { program = "${pkgs.unpaper}/bin/unpaper"; args = [ "{{infile}}" "{{outfile}}" ]; timeout = "5 minutes"; }; }; tesseract = { command= { program = "${pkgs.tesseract4}/bin/tesseract"; args = ["{{file}}" "stdout" "-l" "{{lang}}" ]; timeout = "5 minutes"; }; }; }; }; text-analysis = { max-length = 10000; nlp = { mode = "full"; clear-interval = "15 minutes"; regex-ner = { max-entries = 1000; file-cache-time = "1 minute"; }; }; classification = { enabled = true; item-count = 0; classifiers = [ { "useSplitWords" = "true"; "splitWordsTokenizerRegexp" = ''[\p{L}][\p{L}0-9]*|(?:\$ ?)?[0-9]+(?:\.[0-9]{2})?%?|\s+|.''; "splitWordsIgnoreRegexp" = ''\s+''; "useSplitPrefixSuffixNGrams" = "true"; "maxNGramLeng" = "4"; "minNGramLeng" = "1"; "splitWordShape" = "chris4"; "intern" = "true"; } ]; }; working-dir = "/tmp/docspell-analysis"; }; processing = { max-due-date-years = 10; }; convert = { chunk-size = 524288; converted-filename-part = "converted"; max-image-size = 14000000; markdown = { internal-css = '' body { padding: 2em 5em; } ''; }; wkhtmlpdf = { command = { program = "${pkgs.wkhtmltopdf}/bin/wkhtmltopdf"; args = ["-s" "A4" "--encoding" "UTF-8" "-" "{{outfile}}"]; timeout = "2 minutes"; }; working-dir = "/tmp/docspell-convert"; }; tesseract = { command = { program = "${pkgs.tesseract4}/bin/tesseract"; args = ["{{infile}}" "out" "-l" "{{lang}}" "pdf" "txt"]; timeout = "5 minutes"; }; working-dir = "/tmp/docspell-convert"; }; unoconv = { command = { program = "${pkgs.unoconv}/bin/unoconv"; args = ["-f" "pdf" "-o" "{{outfile}}" "{{infile}}"]; timeout = "2 minutes"; }; working-dir = "/tmp/docspell-convert"; }; ocrmypdf = { enabled = true; command = { program = "${pkgs.ocrmypdf}/bin/ocrmypdf"; args = [ "-l" "{{lang}}" "--skip-text" "--deskew" "-j" "1" "{{infile}}" "{{outfile}}" ]; timeout = "5 minutes"; }; working-dir = "/tmp/docspell-convert"; }; }; files = { chunk-size = 524288; valid-mime-types = []; }; full-text-search = { enabled = false; solr = { url = "http://localhost:8983/solr/docspell"; commit-within = 1000; log-verbose = false; def-type = "lucene"; q-op = "OR"; }; migration = { index-all-chunk = 10; }; }; }; in { ## interface options = { services.docspell-joex = { enable = mkOption { type = types.bool; default = false; description = "Whether to enable docspell docspell job executor."; }; runAs = mkOption { type = types.nullOr types.str; default = null; description = '' Specify a user for running the application. If null, a new user is created. ''; }; waitForTarget = mkOption { type = types.nullOr types.str; default = null; description = '' If not null, joex depends on this systemd target. This is useful if full-text-search is enabled and the solr instance is running on the same machine. ''; }; jvmArgs = mkOption { type = types.listOf types.str; default = []; example = [ "-J-Xmx1G" ]; description = "The options passed to the executable for setting jvm arguments."; }; app-id = mkOption { type = types.str; default = defaults.app-id; description = "The node id. Must be unique across all docspell nodes."; }; base-url = mkOption { type = types.str; default = defaults.base-url; description = "The base url where attentive is deployed."; }; bind = mkOption { type = types.submodule({ options = { address = mkOption { type = types.str; default = defaults.bind.address; description = "The address to bind the REST server to."; }; port = mkOption { type = types.int; default = defaults.bind.port; description = "The port to bind the REST server"; }; }; }); default = defaults.bind; description = "Address and port bind the rest server."; }; mail-debug = mkOption { type = types.bool; default = defaults.mail-debug; description = '' Enable or disable debugging for e-mail related functionality. This applies to both sending and receiving mails. For security reasons logging is not very extensive on authentication failures. Setting this to true, results in a lot of data printed to stdout. ''; }; jdbc = mkOption { type = types.submodule ({ options = { url = mkOption { type = types.str; default = defaults.jdbc.url; description = '' The URL to the database. By default a file-based database is used. It should also work with mariadb and postgresql. Examples: "jdbc:mariadb://192.168.1.172:3306/docspell" "jdbc:postgresql://localhost:5432/docspell" "jdbc:h2:///home/dbs/docspell.db;MODE=PostgreSQL;DATABASE_TO_LOWER=TRUE;AUTO_SERVER=TRUE" ''; }; user = mkOption { type = types.str; default = defaults.jdbc.user; description = "The user name to connect to the database."; }; password = mkOption { type = types.str; default = defaults.jdbc.password; description = "The password to connect to the database."; }; }; }); default = defaults.jdbc; description = "Database connection settings"; }; send-mail = mkOption { type = types.submodule({ options = { list-id = mkOption { type = types.str; default = defaults.send-mail.list-id; description = '' This is used as the List-Id e-mail header when mails are sent from docspell to its users (example: for notification mails). It is not used when sending to external recipients. If it is empty, no such header is added. Using this header is often useful when filtering mails. It should be a string in angle brackets. See https://tools.ietf.org/html/rfc2919 for a formal specification ''; }; }; }); default = defaults.send-mail; description = "Settings for sending mails."; }; scheduler = mkOption { type = types.submodule({ options = { pool-size = mkOption { type = types.int; default = defaults.scheduler.pool-size; description = "Number of processing allowed in parallel."; }; counting-scheme = mkOption { type = types.str; default = defaults.scheduler.counting-scheme; description = '' A counting scheme determines the ratio of how high- and low-prio jobs are run. For example: 4,1 means run 4 high prio jobs, then 1 low prio and then start over. ''; }; retries = mkOption { type = types.int; default = defaults.scheduler.retries; description = '' How often a failed job should be retried until it enters failed state. If a job fails, it becomes "stuck" and will be retried after a delay. ''; }; retry-delay = mkOption { type = types.str; default = defaults.scheduler.retry-delay; description = '' The delay until the next try is performed for a failed job. This delay is increased exponentially with the number of retries. ''; }; log-buffer-size = mkOption { type = types.int; default = defaults.scheduler.log-buffer-size; description = '' The queue size of log statements from a job. ''; }; wakeup-period = mkOption { type = types.str; default = defaults.scheduler.wakeup-period; description = '' If no job is left in the queue, the scheduler will wait until a notify is requested (using the REST interface). To also retry stuck jobs, it will notify itself periodically. ''; }; }; }); default = defaults.scheduler; description = "Settings for the scheduler"; }; periodic-scheduler = mkOption { type = types.submodule({ options = { wakeup-period = mkOption { type = types.str; default = defaults.periodic-scheduler.wakeup-period; description = '' A fallback to start looking for due periodic tasks regularily. Usually joex instances should be notified via REST calls if external processes change tasks. But these requests may get lost. ''; }; }; }); default = defaults.periodic-scheduler; description = '' Settings for the periodic scheduler. ''; }; user-tasks = mkOption { type = types.submodule({ options = { scan-mailbox = mkOption { type = types.submodule({ options = { max-folders = mkOption { type = types.int; default = defaults.user-tasks.scan-mailbox.max-folders; description = '' A limit of how many folders to scan through. If a user configures more than this, only upto this limit folders are scanned and a warning is logged. ''; }; mail-chunk-size = mkOption { type = types.int; default = defaults.user-tasks.scan-mailbox.mail-chunk-size; description = '' How many mails (headers only) to retrieve in one chunk. If this is greater than `max-mails' it is set automatically to the value of `max-mails'. ''; }; max-mails = mkOption { type = types.int; default = defaults.user-tasks.scan-mailbox.max-mails; description = '' A limit on how many mails to process in one job run. This is meant to avoid too heavy resource allocation to one user/collective. If more than this number of mails is encountered, a warning is logged. ''; }; }; }); default = defaults.user-tasks.scan-mailbox; description = "Allows to import e-mails by scanning a mailbox."; }; }; }); default = defaults.user-tasks; description = "Configuration for the user tasks."; }; house-keeping = mkOption { type = types.submodule({ options = { schedule = mkOption { type = types.str; default = defaults.house-keeping.schedule; description = '' When the house keeping tasks execute. Default is to run every week. ''; }; cleanup-invites = mkOption { type = types.submodule({ options = { enabled = mkOption { type = types.bool; default = defaults.house-keeping.cleanup-invites.enabled; description = "Whether this task is enabled."; }; older-than = mkOption { type = types.str; default = defaults.house-keeping.cleanup-invites.older-than; description = "The minimum age of invites to be deleted."; }; }; }); default = defaults.house-keeping.cleanup-invites; description = '' This task removes invitation keys that have been created but not used. The timespan here must be greater than the `invite-time' setting in the rest server config file. ''; }; cleanup-jobs = mkOption { type = types.submodule({ options = { enabled = mkOption { type = types.bool; default = defaults.house-keeping.cleanup-jobs.enabled; description = "Whether this task is enabled."; }; older-than = mkOption { type = types.str; default = defaults.house-keeping.cleanup-jobs.older-than; description = '' The minimum age of jobs to delete. It is matched against the `finished' timestamp. ''; }; delete-batch = mkOption { type = types.int; default = defauts.house-keeping.cleanup-jobs.delete-batch; description = '' This defines how many jobs are deleted in one transaction. Since the data to delete may get large, it can be configured whether more or less memory should be used. ''; }; }; }); default = defaults.house-keeping.cleanup-jobs; description = '' Jobs store their log output in the database. Normally this data is only interesting for some period of time. The processing logs of old files can be removed eventually. ''; }; cleanup-remember-me = mkOption { type = types.submodule({ options = { enabled = mkOption { type = types.bool; default = defaults.house-keeping.cleanup-remember-me.enabled; description = "Whether this task is enabled."; }; older-than = mkOption { type = types.str; default = defaults.house-keeping.cleanup-remember-me.older-than; description = "The miminum age of remember me tokens to delete."; }; }; }); default = defaults.house-keeping.cleanup-remember-me; description = "Settings for cleaning up remember me tokens."; }; }; }); default = defaults.house-keeping; description = '' Docspell uses periodic house keeping tasks, like cleaning expired invites, that can be configured here. ''; }; extraction = mkOption { type = types.submodule({ options = { pdf = mkOption { type = types.submodule({ options = { min-text-len = mkOption { type = types.int; default = defaults.extraction.pdf.min-text-len; description = '' For PDF files it is first tried to read the text parts of the PDF. But PDFs can be complex documents and they may contain text and images. If the returned text is shorter than the value below, OCR is run afterwards. Then both extracted texts are compared and the longer will be used. ''; }; }; }); default = defaults.extraction.pdf; description = "Settings for PDF extraction"; }; preview = mkOption { type = types.submodule({ options = { dpi = mkOption { type = types.int; default = defaults.extraction.preview.dpi; description = '' When rendering a pdf page, use this dpi. This results in scaling the image. A standard A4 page rendered at 96dpi results in roughly 790x1100px image. Using 32 results in roughly 200x300px image. Note, when this is changed, you might want to re-generate preview images. Check the api for this, there is an endpoint to regenerate all for a collective. ''; }; }; }); default = defaults.extraction.preview; description = ""; }; ocr = mkOption { type = types.submodule({ options = { max-image-size = mkOption { type = types.int; default = defaults.extraction.ocr.max-image-size; description = '' Images greater than this size are skipped. Note that every image is loaded completely into memory for doing OCR. ''; }; page-range = mkOption { type = types.submodule({ options = { begin = mkOption { type = types.int; default = defaults.extraction.page-range.begin; description = "Specifies the first N pages of a file to process."; }; }; }); default = defaults.extraction.page-range; description = '' Defines what pages to process. If a PDF with 600 pages is submitted, it is probably not necessary to scan through all of them. This would take a long time and occupy resources for no value. The first few pages should suffice. The default is first 10 pages. If you want all pages being processed, set this number to -1. Note: if you change the ghostscript command below, be aware that this setting (if not -1) will add another parameter to the beginning of the command. ''; }; ghostscript = mkOption { type = types.submodule({ options = { working-dir = mkOption { type = types.str; default = defaults.extraction.ghostscript.working-dir; description = "Directory where the extraction processes can put their temp files"; }; command = mkOption { type = types.submodule({ options = { program = mkOption { type = types.str; default = defaults.extraction.ghostscript.command.program; description = "The path to the executable."; }; args = mkOption { type = types.listOf types.str; default = defaults.extraction.ghostscript.command.args; description = "The arguments to the program"; }; timeout = mkOption { type = types.str; default = defaults.extraction.ghostscript.command.timeout; description = "The timeout when executing the command"; }; }; }); default = defaults.extraction.ghostscript.command; description = "The system command"; }; }; }); default = defaults.extraction.ghostscript; description = "The ghostscript command."; }; unpaper = mkOption { type = types.submodule({ options = { command = mkOption { type = types.submodule({ options = { program = mkOption { type = types.str; default = defaults.extraction.unpaper.command.program; description = "The path to the executable."; }; args = mkOption { type = types.listOf types.str; default = defaults.extraction.unpaper.command.args; description = "The arguments to the program"; }; timeout = mkOption { type = types.str; default = defaults.extraction.unpaper.command.timeout; description = "The timeout when executing the command"; }; }; }); default = defaults.extraction.unpaper.command; description = "The system command"; }; }; }); default = defaults.extraction.unpaper; description = "The unpaper command."; }; tesseract = mkOption { type = types.submodule({ options = { command = mkOption { type = types.submodule({ options = { program = mkOption { type = types.str; default = defaults.extraction.tesseract.command.program; description = "The path to the executable."; }; args = mkOption { type = types.listOf types.str; default = defaults.extraction.tesseract.command.args; description = "The arguments to the program"; }; timeout = mkOption { type = types.str; default = defaults.extraction.tesseract.command.timeout; description = "The timeout when executing the command"; }; }; }); default = defaults.extraction.tesseract.command; description = "The system command"; }; }; }); default = defaults.extraction.tesseract; description = "The tesseract command."; }; }; }); default = defaults.extraction.ocr; description = ""; }; }; }); default = defaults.extraction; description = '' Configuration of text extraction Extracting text currently only work for image and pdf files. It will first runs ghostscript to create a gray image from a pdf. Then unpaper is run to optimize the image for the upcoming ocr, which will be done by tesseract. All these programs must be available in your PATH or the absolute path can be specified below. ''; }; text-analysis = mkOption { type = types.submodule({ options = { max-length = mkOption { type = types.int; default = defaults.text-analysis.max-length; description = '' Maximum length of text to be analysed. All text to analyse must fit into RAM. A large document may take too much heap. Also, most important information is at the beginning of a document, so in most cases the first two pages should suffice. Default is 10000, which are about 2-3 pages (a rough guess). ''; }; working-dir = mkOption { type = types.str; default = defaults.text-analysis.working-dir; description = '' A working directory for the analyser to store temporary/working files. ''; }; nlp = mkOption { type = types.submodule({ options = { mode = mkOption { type = types.str; default = defaults.text-analysis.nlp.mode; description = '' The mode for configuring NLP models: 1. full – builds the complete pipeline 2. basic - builds only the ner annotator 3. regexonly - matches each entry in your address book via regexps 4. disabled - doesn't use any stanford-nlp feature The full and basic variants rely on pre-build language models that are available for only 3 lanugages at the moment: German, English and French. Memory usage varies greatly among the languages. German has quite large models, that require about 1G heap. So joex should run with -Xmx1500M at least when using mode=full. The basic variant does a quite good job for German and English. It might be worse for French, always depending on the type of text that is analysed. Joex should run with about 600M heap, here again lanugage German uses the most. The regexonly variant doesn't depend on a language. It roughly works by converting all entries in your addressbook into regexps and matches each one against the text. This can get memory intensive, too, when the addressbook grows large. This is included in the full and basic by default, but can be used independently by setting mode=regexner. When mode=disabled, then the whole nlp pipeline is disabled, and you won't get any suggestions. Only what the classifier returns (if enabled). ''; }; clear-interval = mkOption { type = types.str; default = defaults.text-analysis.nlp.clear-interval; description = '' Idle time after which the NLP caches are cleared to free memory. If <= 0 clearing the cache is disabled. ''; }; regex-ner = mkOption { type = types.submodule({ options = { enabled = mkOption { type = types.int; default = defaults.text-analysis.regex-ner.max-entries; description = '' Whether to enable custom NER annotation. This uses the address book of a collective as input for NER tagging (to automatically find correspondent and concerned entities). If the address book is large, this can be quite memory intensive and also makes text analysis much slower. But it improves accuracy and can be used independent of the lanugage. If this is set to 0, it is effectively disabled and NER tagging uses only statistical models (that also work quite well, but are restricted to the languages mentioned above). Note, this is only relevant if nlp-config.mode is not "disabled". ''; }; file-cache-time = mkOption { type = types.str; default = defaults.text-analysis.ner-file-cache-time; description = '' The NER annotation uses a file of patterns that is derived from a collective's address book. This is is the time how long this file will be kept until a check for a state change is done. ''; }; }; }); default = defaults.text-analysis.nlp.regex-ner; description = ""; }; }; }); default = defaults.text-analysis.nlp; description = "Configure NLP"; }; classification = mkOption { type = types.submodule({ options = { enabled = mkOption { type = types.bool; default = defaults.text-analysis.classification.enabled; description = '' Whether to enable classification globally. Each collective can decide to disable it. If it is disabled here, no collective can use classification. ''; }; item-count = mkOption { type = types.int; default = defaults.text-analysis.classification.item-count; description = '' If concerned with memory consumption, this restricts the number of items to consider. More are better for training. A negative value or zero means no train on all items. ''; }; classifiers = mkOption { type = types.listOf types.attrs; default = defaults.text-analysis.classification.classifiers; description = '' These settings are used to configure the classifier. If multiple are given, they are all tried and the "best" is chosen at the end. See https://nlp.stanford.edu/nlp/javadoc/javanlp/edu/stanford/nlp/classify/ColumnDataClassifier.html for more info about these settings. The settings here yielded good results with *my* dataset. ''; }; }; }); default = defaults.text-analysis.classification; description = '' Settings for doing document classification. This works by learning from existing documents. A collective can specify a tag category and the system will try to predict a tag from this category for new incoming documents. This requires a satstical model that is computed from all existing documents. This process is run periodically as configured by the collective. It may require a lot of memory, depending on the amount of data. It utilises this NLP library: https://nlp.stanford.edu/. ''; }; }; }); default = defaults.text-analysis; description = "Settings for text analysis"; }; processing = mkOption { type = types.submodule({ options = { max-due-date-years = mkOption { type = types.int; default = defaults.processing.max-due-date-years; description = '' Restricts proposals for due dates. Only dates earlier than this number of years in the future are considered. ''; }; }; }); default = defaults.processing; description = "General config for processing documents"; }; convert = mkOption { type = types.submodule({ options = { chunk-size = mkOption { type = types.int; default = defaults.convert.chunk-size; description = '' The chunk size used when storing files. This should be the same as used with the rest server. ''; }; converted-filename-part = mkOption { type = types.str; default = defaults.convert.converted-filename-part; description = '' A string used to change the filename of the converted pdf file. If empty, the original file name is used for the pdf file ( the extension is always replaced with `pdf`). ''; }; max-image-size = mkOption { type = types.int; default = defaults.convert.max-image-size; description = '' When reading images, this is the maximum size. Images that are larger are not processed. ''; }; markdown = mkOption { type = types.submodule({ options = { internal-css = mkOption { type = types.str; default = defaults.convert.markdown.internal-css; description = '' The CSS that is used to style the resulting HTML. ''; }; }; }); default = defaults.convert.markdown; description = '' Settings when processing markdown files (and other text files) to HTML. In order to support text formats, text files are first converted to HTML using a markdown processor. The resulting HTML is then converted to a PDF file. ''; }; wkhtmlpdf = mkOption { type = types.submodule({ options = { working-dir = mkOption { type = types.str; default = defaults.convert.wktmlpdf.working-dir; description = "Directory where the conversion processes can put their temp files"; }; command = mkOption { type = types.submodule({ options = { program = mkOption { type = types.str; default = defaults.convert.wkhtmlpdf.command.program; description = "The path to the executable."; }; args = mkOption { type = types.listOf types.str; default = defaults.convert.wkhtmlpdf.command.args; description = "The arguments to the program"; }; timeout = mkOption { type = types.str; default = defaults.convert.wkhtmlpdf.command.timeout; description = "The timeout when executing the command"; }; }; }); default = defaults.convert.wkhtmlpdf.command; description = "The system command"; }; }; }); default = defaults.convert.wkhtmlpdf; description = '' To convert HTML files into PDF files, the external tool wkhtmltopdf is used. ''; }; tesseract = mkOption { type = types.submodule({ options = { working-dir = mkOption { type = types.str; default = defaults.convert.tesseract.working-dir; description = "Directory where the conversion processes can put their temp files"; }; command = mkOption { type = types.submodule({ options = { program = mkOption { type = types.str; default = defaults.convert.tesseract.command.program; description = "The path to the executable."; }; args = mkOption { type = types.listOf types.str; default = defaults.convert.tesseract.command.args; description = "The arguments to the program"; }; timeout = mkOption { type = types.str; default = defaults.convert.tesseract.command.timeout; description = "The timeout when executing the command"; }; }; }); default = defaults.convert.tesseract.command; description = "The system command"; }; }; }); default = defaults.convert.tesseract; description = '' To convert image files to PDF files, tesseract is used. This also extracts the text in one go. ''; }; unoconv = mkOption { type = types.submodule({ options = { working-dir = mkOption { type = types.str; default = defaults.convert.unoconv.working-dir; description = "Directory where the conversion processes can put their temp files"; }; command = mkOption { type = types.submodule({ options = { program = mkOption { type = types.str; default = defaults.convert.unoconv.command.program; description = "The path to the executable."; }; args = mkOption { type = types.listOf types.str; default = defaults.convert.unoconv.command.args; description = "The arguments to the program"; }; timeout = mkOption { type = types.str; default = defaults.convert.unoconv.command.timeout; description = "The timeout when executing the command"; }; }; }); default = defaults.convert.unoconv.command; description = "The system command"; }; }; }); default = defaults.convert.unoconv; description = '' To convert "office" files to PDF files, the external tool unoconv is used. Unoconv uses libreoffice/openoffice for converting. So it supports all formats that are possible to read with libreoffice/openoffic. Note: to greatly improve performance, it is recommended to start a libreoffice listener by running `unoconv -l` in a separate process. ''; }; ocrmypdf = mkOption { type = types.submodule({ options = { enabled = mkOption { type = types.bool; default = defaults.convert.ocrmypdf.enabled; description = "Whether to use ocrmypdf to convert pdf to pdf/a."; }; working-dir = mkOption { type = types.str; default = defaults.convert.ocrmypdf.working-dir; description = "Directory where the conversion processes can put their temp files"; }; command = mkOption { type = types.submodule({ options = { program = mkOption { type = types.str; default = defaults.convert.ocrmypdf.command.program; description = "The path to the executable."; }; args = mkOption { type = types.listOf types.str; default = defaults.convert.ocrmypdf.command.args; description = "The arguments to the program"; }; timeout = mkOption { type = types.str; default = defaults.convert.ocrmypdf.command.timeout; description = "The timeout when executing the command"; }; }; }); default = defaults.convert.ocrmypdf.command; description = "The system command"; }; }; }); default = defaults.convert.orcmypdf; description = '' The tool ocrmypdf can be used to convert pdf files to pdf files in order to add extracted text as a separate layer. This makes image-only pdfs searchable and you can select and copy/paste the text. It also converts pdfs into pdf/a type pdfs, which are best suited for archiving. So it makes sense to use this even for text-only pdfs. It is recommended to install ocrympdf, but it also is optional. If it is enabled but fails, the error is not fatal and the processing will continue using the original pdf for extracting text. You can also disable it to remove the errors from the processing logs. The `--skip-text` option is necessary to not fail on "text" pdfs (where ocr is not necessary). In this case, the pdf will be converted to PDF/A. ''; }; }; }); default = defaults.convert; description = '' Configuration for converting files into PDFs. Most of it is delegated to external tools, which can be configured below. They must be in the PATH environment or specify the full path below via the `program` key. ''; }; files = mkOption { type = types.submodule({ options = { chunk-size = mkOption { type = types.int; default = defaults.files.chunk-size; description = '' Defines the chunk size (in bytes) used to store the files. This will affect the memory footprint when uploading and downloading files. At most this amount is loaded into RAM for down- and uploading. It also defines the chunk size used for the blobs inside the database. ''; }; valid-mime-types = mkOption { type = types.listOf types.str; default = defaults.files.valid-mime-types; description = '' The file content types that are considered valid. Docspell will only pass these files to processing. The processing code itself has also checks for which files are supported and which not. This affects the uploading part and is a first check to avoid that 'bad' files get into the system. ''; }; }; }); default = defaults.files; description= "Settings for how files are stored."; }; full-text-search = mkOption { type = types.submodule({ options = { enabled = mkOption { type = types.bool; default = defaults.full-text-search.enabled; description = '' The full-text search feature can be disabled. It requires an additional index server which needs additional memory and disk space. It can be enabled later any time. Currently the SOLR search platform is supported. ''; }; solr = mkOption { type = types.submodule({ options = { url = mkOption { type = types.str; default = defaults.full-text-search.solr.url; description = "The URL to solr"; }; commit-within = mkOption { type = types.int; default = defaults.full-text-search.solr.commit-within; description = "Used to tell solr when to commit the data"; }; log-verbose = mkOption { type = types.bool; default = defaults.full-text-search.solr.log-verbose; description = "If true, logs request and response bodies"; }; def-type = mkOption { type = types.str; default = defaults.full-text-search.solr.def-type; description = '' The defType parameter to lucene that defines the parser to use. You might want to try "edismax" or look here: https://lucene.apache.org/solr/guide/8_4/query-syntax-and-parsing.html#query-syntax-and-parsing ''; }; q-op = mkOption { type = types.str; default = defaults.full-text-search.solr.q-op; description = "The default combiner for tokens. One of {AND, OR}."; }; }; }); default = defaults.full-text-search.solr; description = "Configuration for the SOLR backend."; }; migration = mkOption { type = types.submodule({ options = { index-all-chunk = mkOption { type = types.int; default = defaults.full-text-search.migration.index-all-chunk; description = '' Chunk size to use when indexing data from the database. This many attachments are loaded into memory and pushed to the full-text index. ''; }; }; }); default = defaults.full-text-search.migration; description = "Settings for running the index migration tasks"; }; }; }); default = defaults.full-text-search; description = "Configuration for full-text search."; }; }; }; ## implementation config = mkIf config.services.docspell-joex.enable { users.users."${user}" = mkIf (cfg.runAs == null) { name = user; isSystemUser = false; createHome = true; home = "/var/docspell"; description = "Docspell user"; }; # Setting up a unoconv listener to improve conversion performance systemd.services.unoconv = let cmd = "${pkgs.unoconv}/bin/unoconv --listener -v"; in { description = "Unoconv Listener"; after = [ "networking.target" ]; wantedBy = [ "multi-user.target" ]; serviceConfig = { Restart = "always"; }; script = "${pkgs.su}/bin/su -s ${pkgs.bash}/bin/sh ${user} -c \"${cmd}\""; }; systemd.services.docspell-joex = let args = builtins.concatStringsSep " " cfg.jvmArgs; cmd = "${pkgs.docspell.joex}/bin/docspell-joex ${args} -- ${configFile}"; waitTarget = if cfg.waitForTarget != null then [ cfg.waitForTarget ] else []; in { description = "Docspell Joex"; after = ([ "networking.target" ] ++ waitTarget); wantedBy = [ "multi-user.target" ]; path = [ pkgs.gawk ]; script = "${pkgs.su}/bin/su -s ${pkgs.bash}/bin/sh ${user} -c \"${cmd}\""; }; }; }