o qmi@sddlZddlZddlZddlZddlmZmZddlmZddl m Z ddl m Z ddl mZddlmZdd lmZdd lmZd d lmZmZeejd ZGdddZGdddZGdddZGdddZdS)N)AsyncClientWrapperSyncClientWrapper)RequestOptions)"DocDigitizationJobParametersParams)$DocDigitizationWebhookCallbackParams) DocDigitizationCreateJobResponse)$DocDigitizationDownloadFilesResponse) DocDigitizationJobStatusResponse)"DocDigitizationUploadFilesResponse)"AsyncRawDocumentIntelligenceClientRawDocumentIntelligenceClient.c @eZdZdZddddddedejedejefd d Zed efd d Z ed ejefddZ ed ejefddZ ded dfddZ d e fddZd e fddZ  d#dedejed e fddZd ejejeejffddZd ed efd!d"ZdS)$DocumentIntelligenceJobu A convenience wrapper for managing document intelligence jobs. This class provides high-level methods for the complete document processing workflow: create job → upload file → start → wait → download output. Nlanguage output_formatclientDocumentIntelligenceClientjob_idrrcC"||_||_||_||_d|_dSN_client_job_id _language_output_format_statusselfrrrrr!Y/home/ubuntu/.local/lib/python3.10/site-packages/sarvamai/document_intelligence/client.py__init__-  z DocumentIntelligenceJob.__init__returncC|jSz#The unique identifier for this job.rr r!r!r"r;zDocumentIntelligenceJob.job_idcCr&z%The language configured for this job.rr)r!r!r"r@r*z DocumentIntelligenceJob.languagecCr&z*The output format configured for this job.rr)r!r!r"rEr*z%DocumentIntelligenceJob.output_format file_pathc Cstj|}|jj|j|gd}|jstd|j|}|s&td||j }tj |d }dddddd }||d }t |d  } | } Wd n1sUwYtj|| |d ddd} | d S) Upload a file for processing. Parameters ---------- file_path : str Path to the file to upload (PDF, PNG, JPG, or ZIP) rfilesNo upload URL returnedNo upload URL for file: r application/pdf image/png image/jpegapplication/zipz.pdfz.pngz.jpgz.jpegz.zipapplication/octet-streamrbN BlockBlobz Content-Typezx-ms-blob-typer@contentheaderstimeout)ospathbasenamerget_upload_linksr upload_urls ValueErrorgetfile_urlsplitextloweropenreadhttpxputraise_for_status) r r/filenameupload_response file_details upload_urlext content_types content_typef file_dataresponser!r!r" upload_fileJs<      z#DocumentIntelligenceJob.upload_filecC|j|j|_|jS) Start processing the uploaded file. Returns ------- DocDigitizationJobStatusResponse The job status after starting rstartrrr)r!r!r"r`~ zDocumentIntelligenceJob.startcCr]) Get the current status of the job. Returns ------- DocDigitizationJobStatusResponse The current job status r get_statusrrr)r!r!r"rdraz"DocumentIntelligenceJob.get_status@ poll_intervalrBcCsdt}hd} |}|j|vr|S|dur,t||kr,td|jd|dt|q ) Poll the job status until it completes or fails. Parameters ---------- poll_interval : float Seconds between status checks (default: 2.0) timeout : float, optional Maximum seconds to wait (default: None = wait forever) Returns ------- DocDigitizationJobStatusResponse The final job status Raises ------ TimeoutError If timeout is reached before job completes Failed CompletedPartiallyCompletedTNJob  did not complete within  seconds)timerd job_state TimeoutErrorrsleep)r rfrB start_timeterminal_statesstatusr!r!r"wait_until_completes  z+DocumentIntelligenceJob.wait_until_completecCsV|jdur ||jr)|jjr)t|jjdkr)|jjd}|j|j|j|jdSdS) Get page-level metrics from the last status check. Returns ------- dict or None Dictionary with total_pages, pages_processed, pages_succeeded, pages_failed Nr total_pagespages_processedpages_succeeded pages_failed)rrd job_detailslenryrzr{r|r detailr!r!r"get_page_metricss  z(DocumentIntelligenceJob.get_page_metrics output_pathc Cs|j|j}|jstdtt|j}|j|}|j}t j |dd}| t j |}|r9t j|ddt|d}||jWd|S1sPwY|S)  Download the processed output to a file. Parameters ---------- output_path : str Path where the output file will be saved Returns ------- str The path to the downloaded file No download URL availabler>rBTexist_okwbN)rget_download_linksr download_urlsrHnextiterkeysrJrOrIrQrCrDdirnamemakedirsrMwriter@) r rdownload_responsefirst_filenamerT download_urlr[ output_dirrYr!r!r"download_outputs"    z'DocumentIntelligenceJob.download_outputreN__name__ __module__ __qualname____doc__strtypingOptionalr#propertyrrrr\r r`rdfloatrvDictAnyrrr!r!r!r"r%sB  4  )rc @*eZdZdefddZedefddZddd d d d ed ed e j ede j e de f ddZ eed dde j ede j ede j e defddZd ddede jede j e defddZd ddede j e defddZd ddede j e defddZd ddede j e defdd Zd S)!rclient_wrappercCt|d|_dSN)r)r _raw_clientr rr!r!r"r#sz#DocumentIntelligenceClient.__init__r%cCr&)z Retrieves a raw implementation of this client that returns raw responses. Returns ------- RawDocumentIntelligenceClient rr)r!r!r"with_raw_response z,DocumentIntelligenceClient.with_raw_responsehi-INhtmlNrr callback_urlrequest_optionsrrrrcCs@||d}d}|durd|i}|j|||d}t||j||dS)a Create a new document intelligence job with convenience methods. This is a high-level method that returns a DocumentIntelligenceJob object with methods for uploading, starting, waiting, and downloading. Parameters ---------- language : str Language code in BCP-47 format (default: "hi-IN") Supported: hi-IN, en-IN, bn-IN, gu-IN, kn-IN, ml-IN, mr-IN, or-IN, pa-IN, ta-IN, te-IN, ur-IN, as-IN, bodo-IN, doi-IN, ks-IN, kok-IN, mai-IN, mni-IN, ne-IN, sa-IN, sat-IN, sd-IN output_format : str Output format: "html" or "md" (default: "html") callback_url : str, optional Webhook URL for completion notification request_options : RequestOptions, optional Request-specific configuration Returns ------- DocumentIntelligenceJob A job object with convenience methods for the workflow Examples -------- from sarvamai import SarvamAI client = SarvamAI(api_subscription_key="YOUR_API_KEY") # Create job job = client.document_intelligence.create_job( language="hi-IN", output_format="html" ) # Upload, start, wait, download job.upload_file("document.pdf") job.start() job.wait_until_complete() job.download_output("./output.html") rNurljob_parameterscallbackrrrrr) initialiserrr rrrr job_paramsrr[r!r!r" create_jobs"8z%DocumentIntelligenceClient.create_jobrrrcC|jj|||d}|jS)a Creates a new document intelligence job. **Supported Languages (BCP-47 format):** - `hi-IN`: Hindi (default) - `en-IN`: English - `bn-IN`: Bengali - `gu-IN`: Gujarati - `kn-IN`: Kannada - `ml-IN`: Malayalam - `mr-IN`: Marathi - `or-IN`: Odia - `pa-IN`: Punjabi - `ta-IN`: Tamil - `te-IN`: Telugu - `ur-IN`: Urdu - `as-IN`: Assamese - `bodo-IN`: Bodo - `doi-IN`: Dogri - `ks-IN`: Kashmiri - `kok-IN`: Konkani - `mai-IN`: Maithili - `mni-IN`: Manipuri - `ne-IN`: Nepali - `sa-IN`: Sanskrit - `sat-IN`: Santali - `sd-IN`: Sindhi **Output Formats:** - `html`: Structured HTML with layout preservation (default) - `md`: Markdown format **Prompt Types:** Customize how specific content types are processed: - `default_ocr`: Standard text extraction (default for all text blocks) - `table_to_html`: Convert tables to HTML format - `table_to_markdown`: Convert tables to Markdown format - `chart_to_markdown`: Extract chart data as Markdown table - `chart_to_json`: Extract chart data as JSON - `describe_image`: Generate image caption - `caption_en`: Same as describe_image (English) - `caption_in`: Caption in document language **Webhook Callback:** Optionally provide a callback URL to receive notification when processing completes. Parameters ---------- job_parameters : typing.Optional[DocDigitizationJobParametersParams] Job configuration parameters. Omit the request body to use defaults. callback : typing.Optional[DocDigitizationWebhookCallbackParams] Optional webhook for completion notification request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- DocDigitizationCreateJobResponse Successful Response Examples -------- from sarvamai import SarvamAI client = SarvamAI( api_subscription_key="YOUR_API_SUBSCRIPTION_KEY", ) client.document_intelligence.initialise() rrrdatar rrr _responser!r!r"r_s Nz%DocumentIntelligenceClient.initialiserrr2cCr)a Returns presigned URLs for uploading input files. **File Constraints:** - Exactly one file required (PDF or ZIP) - PDF files: `.pdf` extension - ZIP files: `.zip` extension Parameters ---------- job_id : str Job identifier returned from Create Job files : typing.Sequence[str] List of filenames to upload (exactly 1 file: PDF or ZIP) request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- DocDigitizationUploadFilesResponse Successful Response Examples -------- from sarvamai import SarvamAI client = SarvamAI( api_subscription_key="YOUR_API_SUBSCRIPTION_KEY", ) client.document_intelligence.get_upload_links( job_id="job_id", files=["files"], ) rr2rrrFrr rr2rrr!r!r"rFs+z+DocumentIntelligenceClient.get_upload_linkscC|jj||d}|jS)a Validates the uploaded file and starts processing. **Validation Checks:** - File must be uploaded before starting - File size must not exceed 200 MB - PDF must be parseable by the PDF parser - ZIP must contain only JPEG/PNG images - ZIP must be flat (no nested folders beyond one level) - ZIP must contain at least one valid image - Page/image count must not exceed 500 - User must have sufficient credits **Processing:** Job runs asynchronously. Poll the status endpoint or use webhook callback for completion notification. Parameters ---------- job_id : str The unique identifier of the job request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- DocDigitizationJobStatusResponse Successful Response Examples -------- from sarvamai import SarvamAI client = SarvamAI( api_subscription_key="YOUR_API_SUBSCRIPTION_KEY", ) client.document_intelligence.start( job_id="job_id", ) rrr`rr rrrr!r!r"r`s+z DocumentIntelligenceClient.startcCr)a Returns the current status of a job with page-level metrics. **Job States:** - `Accepted`: Job created, awaiting file upload - `Pending`: File uploaded, waiting to start - `Running`: Processing in progress - `Completed`: All pages processed successfully - `PartiallyCompleted`: Some pages succeeded, some failed - `Failed`: All pages failed or job-level error **Page Metrics:** Response includes detailed progress: total pages, pages processed, succeeded, failed, and per-page errors. Parameters ---------- job_id : str The unique identifier of the job request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- DocDigitizationJobStatusResponse Successful Response Examples -------- from sarvamai import SarvamAI client = SarvamAI( api_subscription_key="YOUR_API_SUBSCRIPTION_KEY", ) client.document_intelligence.get_status( job_id="job_id", ) rrrdrrr!r!r"rds)z%DocumentIntelligenceClient.get_statuscCr)a Returns presigned URLs for downloading output files. **Prerequisites:** - Job must be in `Completed` or `PartiallyCompleted` state - Failed jobs have no output available Parameters ---------- job_id : str The unique identifier of the job request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- DocDigitizationDownloadFilesResponse Successful Response Examples -------- from sarvamai import SarvamAI client = SarvamAI( api_subscription_key="YOUR_API_SUBSCRIPTION_KEY", ) client.document_intelligence.get_download_links( job_id="job_id", ) rrrrrr!r!r"r>s"z-DocumentIntelligenceClient.get_download_links)rrrrr#rrrrrrrrrOMITrrrrSequencer rFr r`rdr rr!r!r!r"rs  S Z 1 / -rc @r)$AsyncDocumentIntelligenceJobu An async convenience wrapper for managing document intelligence jobs. This class provides high-level async methods for the complete document processing workflow: create job → upload file → start → wait → download output. NrrAsyncDocumentIntelligenceClientrrrcCrrrrr!r!r"r#nr$z%AsyncDocumentIntelligenceJob.__init__r%cCr&r'r(r)r!r!r"r|r*z#AsyncDocumentIntelligenceJob.job_idcCr&r+r,r)r!r!r"rr*z%AsyncDocumentIntelligenceJob.languagecCr&r-r.r)r!r!r"rr*z*AsyncDocumentIntelligenceJob.output_formatr/c s$tj|}|jj|j|gdIdH}|jstd|j|}|s*td||j }tj |d }ddddd d }||d }t |d  } | } Wdn1sYwYt4IdH} | j|| |d dddIdH} | WdIdHdS1IdHswYdS)r0r1Nr3r4r r5r6r7r8r9r:r;r<r=r>r?)rCrDrErrFrrGrHrIrJrKrLrMrNrO AsyncClientrPrQ) r r/rRrSrTrUrVrWrXrYrZ http_clientr[r!r!r"r\sB       .z(AsyncDocumentIntelligenceJob.upload_filec|j|jIdH|_|jS)r^Nr_r)r!r!r"r` z"AsyncDocumentIntelligenceJob.startcr)rbNrcr)r!r!r"rdrz'AsyncDocumentIntelligenceJob.get_statusrerfrBcszddl}t}hd} |IdH}|j|vr|S|dur4t||kr4td|jd|d||IdHq)rgrNrhTrlrmrn)asynciorordrprqrrr)r rfrBrrsrtrur!r!r"rvs z0AsyncDocumentIntelligenceJob.wait_until_completecCsD|jr |jjr t|jjdkr |jjd}|j|j|j|jdSdS)rwrrxN)rr}r~ryrzr{r|rr!r!r"rs  z-AsyncDocumentIntelligenceJob.get_page_metricsrc s|j|jIdH}|jstdtt|j}|j|}|j}t 4IdH}|j |ddIdH}| WdIdHn 1IdHsJwYt j|}|r^t j|ddt|d} | |jWd|S1suwY|S)rNrr>rTrr)rrrrrHrrrrJrOrrIrQrCrDrrrMrr@) r rrrrTrrr[rrYr!r!r"rs(  (   z,AsyncDocumentIntelligenceJob.download_outputrrr!r!r!r"rfsB  5  +rc @r)!rrcCrr)r rrr!r!r"r#Ds z(AsyncDocumentIntelligenceClient.__init__r%cCr&)z Retrieves a raw implementation of this client that returns raw responses. Returns ------- AsyncRawDocumentIntelligenceClient rr)r!r!r"rIrz1AsyncDocumentIntelligenceClient.with_raw_responserrNrrrrrcsH||d}d}|durd|i}|j|||dIdH}t||j||dS)au Create a new document intelligence job with convenience methods. This is a high-level method that returns an AsyncDocumentIntelligenceJob object with async methods for uploading, starting, waiting, and downloading. Parameters ---------- language : str Language code in BCP-47 format (default: "hi-IN") Supported: hi-IN, en-IN, bn-IN, gu-IN, kn-IN, ml-IN, mr-IN, or-IN, pa-IN, ta-IN, te-IN, ur-IN, as-IN, bodo-IN, doi-IN, ks-IN, kok-IN, mai-IN, mni-IN, ne-IN, sa-IN, sat-IN, sd-IN output_format : str Output format: "html" or "md" (default: "html") callback_url : str, optional Webhook URL for completion notification request_options : RequestOptions, optional Request-specific configuration Returns ------- AsyncDocumentIntelligenceJob A job object with async convenience methods for the workflow Examples -------- import asyncio from sarvamai import AsyncSarvamAI async def main(): client = AsyncSarvamAI(api_subscription_key="YOUR_API_KEY") # Create job job = await client.document_intelligence.create_job( language="hi-IN", output_format="html" ) # Upload, start, wait, download await job.upload_file("document.pdf") await job.start() await job.wait_until_complete() await job.download_output("./output.html") asyncio.run(main()) rNrrr)rrrrr!r!r"rTs$< z*AsyncDocumentIntelligenceClient.create_jobrrrc |jj|||dIdH}|jS)a Creates a new document intelligence job. **Supported Languages (BCP-47 format):** - `hi-IN`: Hindi (default) - `en-IN`: English - `bn-IN`: Bengali - `gu-IN`: Gujarati - `kn-IN`: Kannada - `ml-IN`: Malayalam - `mr-IN`: Marathi - `or-IN`: Odia - `pa-IN`: Punjabi - `ta-IN`: Tamil - `te-IN`: Telugu - `ur-IN`: Urdu - `as-IN`: Assamese - `bodo-IN`: Bodo - `doi-IN`: Dogri - `ks-IN`: Kashmiri - `kok-IN`: Konkani - `mai-IN`: Maithili - `mni-IN`: Manipuri - `ne-IN`: Nepali - `sa-IN`: Sanskrit - `sat-IN`: Santali - `sd-IN`: Sindhi **Output Formats:** - `html`: Structured HTML with layout preservation (default) - `md`: Markdown format **Prompt Types:** Customize how specific content types are processed: - `default_ocr`: Standard text extraction (default for all text blocks) - `table_to_html`: Convert tables to HTML format - `table_to_markdown`: Convert tables to Markdown format - `chart_to_markdown`: Extract chart data as Markdown table - `chart_to_json`: Extract chart data as JSON - `describe_image`: Generate image caption - `caption_en`: Same as describe_image (English) - `caption_in`: Caption in document language **Webhook Callback:** Optionally provide a callback URL to receive notification when processing completes. Parameters ---------- job_parameters : typing.Optional[DocDigitizationJobParametersParams] Job configuration parameters. Omit the request body to use defaults. callback : typing.Optional[DocDigitizationWebhookCallbackParams] Optional webhook for completion notification request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- DocDigitizationCreateJobResponse Successful Response Examples -------- import asyncio from sarvamai import AsyncSarvamAI client = AsyncSarvamAI( api_subscription_key="YOUR_API_SUBSCRIPTION_KEY", ) async def main() -> None: await client.document_intelligence.initialise() asyncio.run(main()) rNrrr!r!r"rsV z*AsyncDocumentIntelligenceClient.initialiserrr2cr)a/ Returns presigned URLs for uploading input files. **File Constraints:** - Exactly one file required (PDF or ZIP) - PDF files: `.pdf` extension - ZIP files: `.zip` extension Parameters ---------- job_id : str Job identifier returned from Create Job files : typing.Sequence[str] List of filenames to upload (exactly 1 file: PDF or ZIP) request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- DocDigitizationUploadFilesResponse Successful Response Examples -------- import asyncio from sarvamai import AsyncSarvamAI client = AsyncSarvamAI( api_subscription_key="YOUR_API_SUBSCRIPTION_KEY", ) async def main() -> None: await client.document_intelligence.get_upload_links( job_id="job_id", files=["files"], ) asyncio.run(main()) rNrrr!r!r"rFs 3 z0AsyncDocumentIntelligenceClient.get_upload_linksc|jj||dIdH}|jS)a( Validates the uploaded file and starts processing. **Validation Checks:** - File must be uploaded before starting - File size must not exceed 200 MB - PDF must be parseable by the PDF parser - ZIP must contain only JPEG/PNG images - ZIP must be flat (no nested folders beyond one level) - ZIP must contain at least one valid image - Page/image count must not exceed 500 - User must have sufficient credits **Processing:** Job runs asynchronously. Poll the status endpoint or use webhook callback for completion notification. Parameters ---------- job_id : str The unique identifier of the job request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- DocDigitizationJobStatusResponse Successful Response Examples -------- import asyncio from sarvamai import AsyncSarvamAI client = AsyncSarvamAI( api_subscription_key="YOUR_API_SUBSCRIPTION_KEY", ) async def main() -> None: await client.document_intelligence.start( job_id="job_id", ) asyncio.run(main()) rNrrr!r!r"r`=s 3 z%AsyncDocumentIntelligenceClient.startcr)a Returns the current status of a job with page-level metrics. **Job States:** - `Accepted`: Job created, awaiting file upload - `Pending`: File uploaded, waiting to start - `Running`: Processing in progress - `Completed`: All pages processed successfully - `PartiallyCompleted`: Some pages succeeded, some failed - `Failed`: All pages failed or job-level error **Page Metrics:** Response includes detailed progress: total pages, pages processed, succeeded, failed, and per-page errors. Parameters ---------- job_id : str The unique identifier of the job request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- DocDigitizationJobStatusResponse Successful Response Examples -------- import asyncio from sarvamai import AsyncSarvamAI client = AsyncSarvamAI( api_subscription_key="YOUR_API_SUBSCRIPTION_KEY", ) async def main() -> None: await client.document_intelligence.get_status( job_id="job_id", ) asyncio.run(main()) rNrrr!r!r"rdus 1 z*AsyncDocumentIntelligenceClient.get_statuscr)a Returns presigned URLs for downloading output files. **Prerequisites:** - Job must be in `Completed` or `PartiallyCompleted` state - Failed jobs have no output available Parameters ---------- job_id : str The unique identifier of the job request_options : typing.Optional[RequestOptions] Request-specific configuration. Returns ------- DocDigitizationDownloadFilesResponse Successful Response Examples -------- import asyncio from sarvamai import AsyncSarvamAI client = AsyncSarvamAI( api_subscription_key="YOUR_API_SUBSCRIPTION_KEY", ) async def main() -> None: await client.document_intelligence.get_download_links( job_id="job_id", ) asyncio.run(main()) rNrrr!r!r"rs * z2AsyncDocumentIntelligenceClient.get_download_links)rrrrr#rr rrrrrrrrrrrrrr rFr r`rdr rr!r!r!r"rCs  W b 9 9 7r)rCrorrOcore.client_wrapperrrcore.request_optionsr(requests.doc_digitization_job_parametersr*requests.doc_digitization_webhook_callbackr*types.doc_digitization_create_job_responser.types.doc_digitization_download_files_responser *types.doc_digitization_job_status_responser ,types.doc_digitization_upload_files_responser raw_clientr rcastrrrrrrr!r!r!r"s,       \h^