mirror of
https://github.com/Stirling-Tools/Stirling-PDF.git
synced 2026-09-03 05:10:16 +03:00
Compare commits
7
Commits
| Author | SHA1 | Date | |
|---|---|---|---|
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07de12746c | ||
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469e7c499c | ||
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40ccbc15cc | ||
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62944d7423 | ||
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7ce98d29f2 | ||
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65c01e8078 | ||
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4700542c75 |
@@ -13,6 +13,11 @@ on:
|
||||
required: false
|
||||
type: boolean
|
||||
default: true
|
||||
build_engine:
|
||||
description: "Build & push the stirling-pdf-engine image (plus the -docparse addon variant)."
|
||||
required: false
|
||||
type: boolean
|
||||
default: false
|
||||
force_unoserver_rebuild:
|
||||
description: "Rebuild stirling-unoserver even if its source hash is unchanged."
|
||||
required: false
|
||||
@@ -51,6 +56,8 @@ jobs:
|
||||
env:
|
||||
RUN_MAIN_APP: ${{ github.event_name != 'workflow_dispatch' || inputs.build_main_app }}
|
||||
RUN_UNOSERVER: ${{ github.event_name != 'workflow_dispatch' || inputs.build_unoserver }}
|
||||
# Engine images are dispatch-only for now; flip the default once the addon stabilises.
|
||||
RUN_ENGINE: ${{ github.event_name == 'workflow_dispatch' && inputs.build_engine }}
|
||||
steps:
|
||||
- name: Harden Runner
|
||||
uses: step-security/harden-runner@ab7a9404c0f3da075243ca237b5fac12c98deaa5 # v2.19.3
|
||||
@@ -219,6 +226,62 @@ jobs:
|
||||
cosign sign --key env://COSIGN_PRIVATE_KEY --yes "${tag}@${DIGEST}"
|
||||
done
|
||||
|
||||
- name: Generate tags for engine
|
||||
id: meta-engine
|
||||
uses: docker/metadata-action@80c7e94dd9b9319bd5eb7a0e0fe9291e23a2a2e9 # v6.1.0
|
||||
if: env.RUN_ENGINE == 'true'
|
||||
with:
|
||||
images: |
|
||||
ghcr.io/${{ steps.repoowner.outputs.lowercase }}/stirling-pdf-engine
|
||||
${{ secrets.DOCKER_HUB_ORG_USERNAME }}/stirling-pdf-engine
|
||||
tags: |
|
||||
type=raw,value=${{ steps.versionNumber.outputs.versionNumber }}
|
||||
type=raw,value=latest
|
||||
|
||||
- name: Build and push engine image
|
||||
id: build-push-engine
|
||||
uses: docker/build-push-action@53b7df96c91f9c12dcc8a07bcb9ccacbed38856a # v7.3.0
|
||||
if: env.RUN_ENGINE == 'true' && steps.meta-engine.outputs.tags != ''
|
||||
with:
|
||||
builder: ${{ steps.buildx.outputs.name }}
|
||||
context: ./engine
|
||||
push: true
|
||||
cache-from: type=gha,scope=stirling-pdf-engine
|
||||
cache-to: type=gha,mode=max,scope=stirling-pdf-engine
|
||||
tags: ${{ steps.meta-engine.outputs.tags }}
|
||||
labels: ${{ steps.meta-engine.outputs.labels }}
|
||||
platforms: linux/amd64,linux/arm64/v8
|
||||
provenance: true
|
||||
sbom: true
|
||||
|
||||
- name: Generate tags for engine docparse addon
|
||||
id: meta-engine-docparse
|
||||
uses: docker/metadata-action@80c7e94dd9b9319bd5eb7a0e0fe9291e23a2a2e9 # v6.1.0
|
||||
if: env.RUN_ENGINE == 'true'
|
||||
with:
|
||||
images: |
|
||||
ghcr.io/${{ steps.repoowner.outputs.lowercase }}/stirling-pdf-engine
|
||||
${{ secrets.DOCKER_HUB_ORG_USERNAME }}/stirling-pdf-engine
|
||||
tags: |
|
||||
type=raw,value=${{ steps.versionNumber.outputs.versionNumber }}-docparse
|
||||
type=raw,value=latest-docparse
|
||||
|
||||
- name: Build and push engine docparse addon image
|
||||
uses: docker/build-push-action@53b7df96c91f9c12dcc8a07bcb9ccacbed38856a # v7.3.0
|
||||
if: env.RUN_ENGINE == 'true' && steps.meta-engine-docparse.outputs.tags != ''
|
||||
with:
|
||||
builder: ${{ steps.buildx.outputs.name }}
|
||||
context: ./engine
|
||||
push: true
|
||||
cache-from: type=gha,scope=stirling-pdf-engine-docparse
|
||||
cache-to: type=gha,mode=max,scope=stirling-pdf-engine-docparse
|
||||
tags: ${{ steps.meta-engine-docparse.outputs.tags }}
|
||||
labels: ${{ steps.meta-engine-docparse.outputs.labels }}
|
||||
build-args: DOCPARSE=true
|
||||
platforms: linux/amd64
|
||||
provenance: true
|
||||
sbom: true
|
||||
|
||||
- name: Generate tags for ultra-lite
|
||||
id: meta-lite
|
||||
uses: docker/metadata-action@80c7e94dd9b9319bd5eb7a0e0fe9291e23a2a2e9 # v6.1.0
|
||||
|
||||
@@ -433,6 +433,17 @@ public class EndpointConfiguration {
|
||||
addEndpointToGroup("Automation", "automate"); // Alias for handleData (user-friendly name)
|
||||
addEndpointToGroup("Automation", "pipeline");
|
||||
|
||||
// Adding endpoints to "DocParse" group (parsing, splitting, chunking, extraction,
|
||||
// templating)
|
||||
addEndpointToGroup("DocParse", "parse-document");
|
||||
addEndpointToGroup("DocParse", "extract-fields");
|
||||
addEndpointToGroup("DocParse", "smart-split");
|
||||
addEndpointToGroup("DocParse", "chunk-document");
|
||||
addEndpointToGroup("DocParse", "rag-ingest");
|
||||
addEndpointToGroup("DocParse", "extract-tables");
|
||||
addEndpointToGroup("DocParse", "suggest-schema");
|
||||
addEndpointToGroup("DocParse", "fill-template");
|
||||
|
||||
// Adding endpoints to "DeveloperTools" group
|
||||
addEndpointToGroup("DeveloperTools", "show-javascript");
|
||||
|
||||
|
||||
@@ -77,6 +77,7 @@ public class ApplicationProperties {
|
||||
private ProcessExecutor processExecutor = new ProcessExecutor();
|
||||
private PdfEditor pdfEditor = new PdfEditor();
|
||||
private AiEngine aiEngine = new AiEngine();
|
||||
private Docparse docparse = new Docparse();
|
||||
private Mcp mcp = new Mcp();
|
||||
private InternalApi internalApi = new InternalApi();
|
||||
private Cluster cluster = new Cluster();
|
||||
@@ -425,6 +426,24 @@ public class ApplicationProperties {
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* DocParse settings (top-level {@code docparse.*}): document understanding for ingestion
|
||||
* pipelines. The basic tier (text layer) always works; the advanced tier lives in the engine's
|
||||
* docparse addon.
|
||||
*/
|
||||
@Data
|
||||
public static class Docparse {
|
||||
|
||||
/** Master switch; hides the DocParse endpoints when false. */
|
||||
private boolean enabled = true;
|
||||
|
||||
/** Requested tier: 'auto', 'basic', or 'advanced'. 'auto' resolves per document. */
|
||||
private String mode = "auto";
|
||||
|
||||
/** Mirrors DOCPARSE_AUTO_INSTALL for the engine's boot-time addon install script. */
|
||||
private boolean autoInstall = false;
|
||||
}
|
||||
|
||||
/**
|
||||
* Model Context Protocol (MCP) server configuration. All keys live under the top-level {@code
|
||||
* mcp.*} prefix. {@link #enabled} defaults to {@code false}: when off, no MCP beans are wired,
|
||||
|
||||
+16
@@ -0,0 +1,16 @@
|
||||
package stirling.software.common.service;
|
||||
|
||||
/**
|
||||
* View of the engine's DocParse capability for modules that cannot see the proprietary
|
||||
* implementation (e.g. ConfigController in core). Implemented by the proprietary
|
||||
* DocparseCapabilityService; absent when the proprietary module is not loaded.
|
||||
*/
|
||||
public interface DocparseCapabilityServiceInterface {
|
||||
|
||||
/**
|
||||
* Whether the engine reports the docparse addon (advanced tier) as installed. Must be cheap and
|
||||
* non-blocking: returns the cached probe result, {@code false} when the engine is disabled,
|
||||
* unreachable, or not yet probed.
|
||||
*/
|
||||
boolean isAdvancedInstalled();
|
||||
}
|
||||
@@ -53,7 +53,7 @@ public class InternalApiClient {
|
||||
// ApiConnectionResolver.
|
||||
private static final Pattern ALLOWED_ENDPOINT_PATH =
|
||||
Pattern.compile(
|
||||
"^/api/v1/(general|misc|security|convert|filter|integration)(/[A-Za-z0-9_-]+)+$"
|
||||
"^/api/v1/(general|misc|security|convert|filter|integration|docparse)(/[A-Za-z0-9_-]+)+$"
|
||||
+ "|^/api/v1/ai/tools(/[A-Za-z0-9_-]+)+$");
|
||||
|
||||
/**
|
||||
|
||||
+16
-1
@@ -24,6 +24,7 @@ import stirling.software.common.annotations.api.ConfigApi;
|
||||
import stirling.software.common.configuration.AppConfig;
|
||||
import stirling.software.common.configuration.interfaces.ShowAdminInterface;
|
||||
import stirling.software.common.model.ApplicationProperties;
|
||||
import stirling.software.common.service.DocparseCapabilityServiceInterface;
|
||||
import stirling.software.common.service.ServerCertificateServiceInterface;
|
||||
import stirling.software.common.service.UserServiceInterface;
|
||||
import stirling.software.common.util.GeneralUtils;
|
||||
@@ -41,6 +42,7 @@ public class ConfigController {
|
||||
private final ShowAdminInterface showAdmin;
|
||||
private final stirling.software.common.service.LicenseServiceInterface licenseService;
|
||||
private final stirling.software.SPDF.config.ExternalAppDepConfig externalAppDepConfig;
|
||||
private final DocparseCapabilityServiceInterface docparseCapabilityService;
|
||||
|
||||
public ConfigController(
|
||||
ApplicationProperties applicationProperties,
|
||||
@@ -54,7 +56,9 @@ public class ConfigController {
|
||||
ShowAdminInterface showAdmin,
|
||||
@org.springframework.beans.factory.annotation.Autowired(required = false)
|
||||
stirling.software.common.service.LicenseServiceInterface licenseService,
|
||||
stirling.software.SPDF.config.ExternalAppDepConfig externalAppDepConfig) {
|
||||
stirling.software.SPDF.config.ExternalAppDepConfig externalAppDepConfig,
|
||||
@org.springframework.beans.factory.annotation.Autowired(required = false)
|
||||
DocparseCapabilityServiceInterface docparseCapabilityService) {
|
||||
this.applicationProperties = applicationProperties;
|
||||
this.applicationContext = applicationContext;
|
||||
this.endpointConfiguration = endpointConfiguration;
|
||||
@@ -63,6 +67,7 @@ public class ConfigController {
|
||||
this.showAdmin = showAdmin;
|
||||
this.licenseService = licenseService;
|
||||
this.externalAppDepConfig = externalAppDepConfig;
|
||||
this.docparseCapabilityService = docparseCapabilityService;
|
||||
}
|
||||
|
||||
/**
|
||||
@@ -350,6 +355,16 @@ public class ConfigController {
|
||||
Map.entry("pdfComment", aiFeatures.isPdfComment()),
|
||||
Map.entry("classify", aiFeatures.isClassify())));
|
||||
|
||||
// DocParse settings; "advanced" reflects the cached engine capability probe and is
|
||||
// false when the engine is disabled, unreachable, or the proprietary module is absent.
|
||||
boolean docparseEnabled = applicationProperties.getDocparse().isEnabled();
|
||||
configData.put("docparseEnabled", docparseEnabled);
|
||||
configData.put(
|
||||
"docparseAdvanced",
|
||||
docparseEnabled
|
||||
&& docparseCapabilityService != null
|
||||
&& docparseCapabilityService.isAdvancedInstalled());
|
||||
|
||||
// Timestamp TSA settings — single source of truth for presets + admin URLs
|
||||
ApplicationProperties.Security.Timestamp tsConfig =
|
||||
applicationProperties.getSecurity().getTimestamp();
|
||||
|
||||
@@ -396,6 +396,14 @@ aiEngine:
|
||||
pdfComment: true # AI-authored PDF comments/annotations
|
||||
classify: true # Automatic document classification/labelling
|
||||
|
||||
# DocParse: document understanding for ingestion pipelines (chunking + knowledge-base
|
||||
# indexing). The basic tier (text layer) always works; the advanced tier (layout parsing)
|
||||
# requires the engine's docparse addon. Env overrides: DOCPARSE_ENABLED, DOCPARSE_MODE.
|
||||
docparse:
|
||||
enabled: true # Master switch; hides the DocParse endpoints when false
|
||||
mode: auto # Tier selection: 'auto' (best available), 'basic', or 'advanced'
|
||||
autoInstall: false # Mirrors DOCPARSE_AUTO_INSTALL for the engine's boot-time addon install script
|
||||
|
||||
policies:
|
||||
# Folder automations can read from and write to the directories you allow here, so treat this as a
|
||||
# security boundary. Leave allowedFolderRoots empty (default) to disable folder sources/outputs,
|
||||
|
||||
+2
-1
@@ -74,7 +74,8 @@ class ConfigControllerMoreTest {
|
||||
userService,
|
||||
showAdmin,
|
||||
licenseService,
|
||||
externalAppDepConfig);
|
||||
externalAppDepConfig,
|
||||
null);
|
||||
}
|
||||
|
||||
@SuppressWarnings("unchecked")
|
||||
|
||||
+2
-1
@@ -52,7 +52,8 @@ class ConfigControllerTest {
|
||||
userService,
|
||||
showAdmin,
|
||||
licenseService,
|
||||
mock(stirling.software.SPDF.config.ExternalAppDepConfig.class));
|
||||
mock(stirling.software.SPDF.config.ExternalAppDepConfig.class),
|
||||
null);
|
||||
}
|
||||
|
||||
@Test
|
||||
|
||||
+481
@@ -0,0 +1,481 @@
|
||||
package stirling.software.proprietary.controller.api;
|
||||
|
||||
import java.io.ByteArrayOutputStream;
|
||||
import java.io.IOException;
|
||||
import java.io.StringWriter;
|
||||
import java.nio.charset.StandardCharsets;
|
||||
import java.nio.file.Files;
|
||||
import java.nio.file.StandardCopyOption;
|
||||
import java.util.Base64;
|
||||
import java.util.List;
|
||||
import java.util.Locale;
|
||||
import java.util.zip.ZipEntry;
|
||||
import java.util.zip.ZipOutputStream;
|
||||
|
||||
import org.apache.commons.csv.CSVFormat;
|
||||
import org.apache.commons.csv.CSVPrinter;
|
||||
import org.apache.pdfbox.pdmodel.PDDocument;
|
||||
import org.springframework.core.io.ByteArrayResource;
|
||||
import org.springframework.core.io.Resource;
|
||||
import org.springframework.http.HttpHeaders;
|
||||
import org.springframework.http.HttpStatus;
|
||||
import org.springframework.http.MediaType;
|
||||
import org.springframework.http.ResponseEntity;
|
||||
import org.springframework.web.bind.annotation.GetMapping;
|
||||
import org.springframework.web.bind.annotation.ModelAttribute;
|
||||
import org.springframework.web.bind.annotation.RequestMapping;
|
||||
import org.springframework.web.bind.annotation.RequestParam;
|
||||
import org.springframework.web.bind.annotation.RestController;
|
||||
import org.springframework.web.multipart.MultipartFile;
|
||||
import org.springframework.web.server.ResponseStatusException;
|
||||
|
||||
import io.swagger.v3.oas.annotations.Operation;
|
||||
import io.swagger.v3.oas.annotations.tags.Tag;
|
||||
|
||||
import lombok.RequiredArgsConstructor;
|
||||
import lombok.extern.slf4j.Slf4j;
|
||||
|
||||
import stirling.software.common.annotations.AutoJobPostMapping;
|
||||
import stirling.software.common.enumeration.ResourceWeight;
|
||||
import stirling.software.common.service.CustomPDFDocumentFactory;
|
||||
import stirling.software.common.util.FormUtils;
|
||||
import stirling.software.common.util.GeneralUtils;
|
||||
import stirling.software.common.util.TempFile;
|
||||
import stirling.software.common.util.TempFileManager;
|
||||
import stirling.software.common.util.WebResponseUtils;
|
||||
import stirling.software.proprietary.model.api.docparse.ChunkDocumentApiRequest;
|
||||
import stirling.software.proprietary.model.api.docparse.ExtractFieldsApiRequest;
|
||||
import stirling.software.proprietary.model.api.docparse.ExtractTablesApiRequest;
|
||||
import stirling.software.proprietary.model.api.docparse.ParseDocumentApiRequest;
|
||||
import stirling.software.proprietary.model.api.docparse.RagIngestApiRequest;
|
||||
import stirling.software.proprietary.model.api.docparse.SmartSplitApiRequest;
|
||||
import stirling.software.proprietary.model.api.docparse.SuggestSchemaApiRequest;
|
||||
import stirling.software.proprietary.model.docparse.ChunkDocumentResponse;
|
||||
import stirling.software.proprietary.model.docparse.DocChunk;
|
||||
import stirling.software.proprietary.model.docparse.DocTable;
|
||||
import stirling.software.proprietary.model.docparse.DocparseCapabilitiesView;
|
||||
import stirling.software.proprietary.model.docparse.DocparseMode;
|
||||
import stirling.software.proprietary.model.docparse.ExtractFieldsResponse;
|
||||
import stirling.software.proprietary.model.docparse.ExtractTablesResponse;
|
||||
import stirling.software.proprietary.model.docparse.FillDocxResponse;
|
||||
import stirling.software.proprietary.model.docparse.ParseDocumentResponse;
|
||||
import stirling.software.proprietary.model.docparse.RagIngestResponse;
|
||||
import stirling.software.proprietary.model.docparse.SmartSplitResponse;
|
||||
import stirling.software.proprietary.model.docparse.SplitPart;
|
||||
import stirling.software.proprietary.model.docparse.SuggestSchemaResponse;
|
||||
import stirling.software.proprietary.service.AiToolResponseHeaders;
|
||||
import stirling.software.proprietary.service.DocParseService;
|
||||
|
||||
import tools.jackson.databind.ObjectMapper;
|
||||
import tools.jackson.databind.node.ObjectNode;
|
||||
|
||||
/**
|
||||
* Public DocParse ingestion API. Thin HTTP layer over {@link DocParseService}, which owns the
|
||||
* engine wire contract; this class owns the pipeline step shape (report header, export ZIP).
|
||||
*/
|
||||
@Slf4j
|
||||
@RestController
|
||||
@RequestMapping("/api/v1/docparse")
|
||||
@RequiredArgsConstructor
|
||||
@Tag(
|
||||
name = "DocParse",
|
||||
description =
|
||||
"Document ingestion: chunk, embed, and index documents into the searchable"
|
||||
+ " knowledge base, or export the parsed content (markdown, chunks JSONL)"
|
||||
+ " for external systems.")
|
||||
public class DocParseController {
|
||||
|
||||
private static final MediaType CSV = MediaType.parseMediaType("text/csv");
|
||||
|
||||
private static final MediaType MARKDOWN = MediaType.parseMediaType("text/markdown");
|
||||
private static final MediaType DOCX =
|
||||
MediaType.parseMediaType(
|
||||
"application/vnd.openxmlformats-officedocument.wordprocessingml.document");
|
||||
|
||||
private final DocParseService docParseService;
|
||||
private final CustomPDFDocumentFactory pdfDocumentFactory;
|
||||
private final TempFileManager tempFileManager;
|
||||
private final ObjectMapper objectMapper;
|
||||
|
||||
@AutoJobPostMapping(
|
||||
consumes = MediaType.MULTIPART_FORM_DATA_VALUE,
|
||||
value = "/rag-ingest",
|
||||
resourceWeight = ResourceWeight.LARGE_WEIGHT)
|
||||
@Operation(
|
||||
summary = "Chunk, embed, and index a document into the RAG store (pipeline shape)",
|
||||
description =
|
||||
"Ingests the document into the engine's RAG store under a stable documentId"
|
||||
+ " (default: content hash). Returns the ORIGINAL PDF unchanged as the"
|
||||
+ " body, with the ingest summary JSON in the X-Stirling-Tool-Report"
|
||||
+ " header so policy pipelines pick it up as the step report. With"
|
||||
+ " exportMarkdown/exportChunksJsonl the body becomes a ZIP holding the"
|
||||
+ " original plus the corpus files, ready for delivery to external"
|
||||
+ " systems. Input:PDF Output:PDF/ZIP Type:SISO")
|
||||
public ResponseEntity<Resource> ragIngest(@ModelAttribute RagIngestApiRequest request)
|
||||
throws IOException {
|
||||
MultipartFile file = request.getFileInput();
|
||||
boolean export = request.isExportMarkdown() || request.isExportChunksJsonl();
|
||||
RagIngestResponse result =
|
||||
docParseService.ragIngest(
|
||||
file,
|
||||
request.getDocumentId(),
|
||||
request.getChunkSize(),
|
||||
request.getOverlap(),
|
||||
DocparseMode.fromWire(request.getMode()),
|
||||
request.isIndex(),
|
||||
request.isExportMarkdown(),
|
||||
request.isExportChunksJsonl());
|
||||
|
||||
// The report header must stay small: summary fields only, never the echoed content.
|
||||
ObjectNode report = objectMapper.createObjectNode();
|
||||
report.put("mode", result.mode().wire());
|
||||
report.put("documentId", result.documentId());
|
||||
report.put("chunksIndexed", result.chunksIndexed());
|
||||
report.put("pages", result.pages());
|
||||
report.put("indexed", request.isIndex());
|
||||
|
||||
String fileName = DocParseService.fileName(file);
|
||||
byte[] original = file.getBytes();
|
||||
HttpHeaders headers = new HttpHeaders();
|
||||
headers.set(AiToolResponseHeaders.TOOL_REPORT, objectMapper.writeValueAsString(report));
|
||||
|
||||
if (!export) {
|
||||
headers.setContentType(MediaType.APPLICATION_PDF);
|
||||
headers.setContentDispositionFormData("attachment", fileName);
|
||||
headers.setContentLength(original.length);
|
||||
return ResponseEntity.ok().headers(headers).body(new ByteArrayResource(original));
|
||||
}
|
||||
|
||||
byte[] zip = exportZip(fileName, original, result, request);
|
||||
headers.setContentType(MediaType.parseMediaType("application/zip"));
|
||||
headers.setContentDispositionFormData("attachment", baseName(fileName) + "-ingested.zip");
|
||||
headers.setContentLength(zip.length);
|
||||
return ResponseEntity.ok().headers(headers).body(new ByteArrayResource(zip));
|
||||
}
|
||||
|
||||
@AutoJobPostMapping(
|
||||
consumes = MediaType.MULTIPART_FORM_DATA_VALUE,
|
||||
value = "/extract-fields",
|
||||
resourceWeight = ResourceWeight.LARGE_WEIGHT)
|
||||
@Operation(
|
||||
summary = "Extract typed fields from a document (pipeline shape)",
|
||||
description =
|
||||
"Extracts the fields described by the JSON Schema and returns the ORIGINAL PDF"
|
||||
+ " unchanged as the body, with the extraction JSON in the"
|
||||
+ " X-Stirling-Tool-Report header so policy pipelines pick it up as the"
|
||||
+ " step report. Use /extract-fields/json for the raw JSON."
|
||||
+ " Input:PDF Output:PDF Type:SISO")
|
||||
public ResponseEntity<Resource> extractFields(@ModelAttribute ExtractFieldsApiRequest request)
|
||||
throws IOException {
|
||||
MultipartFile file = request.getFileInput();
|
||||
ExtractFieldsResponse result =
|
||||
docParseService.extractFields(
|
||||
file,
|
||||
request.getFieldsSchema(),
|
||||
DocparseMode.fromWire(request.getMode()),
|
||||
request.getInstructions());
|
||||
byte[] original = file.getBytes();
|
||||
HttpHeaders headers = new HttpHeaders();
|
||||
headers.setContentType(MediaType.APPLICATION_PDF);
|
||||
headers.setContentDispositionFormData("attachment", DocParseService.fileName(file));
|
||||
headers.setContentLength(original.length);
|
||||
headers.set(AiToolResponseHeaders.TOOL_REPORT, objectMapper.writeValueAsString(result));
|
||||
return ResponseEntity.ok().headers(headers).body(new ByteArrayResource(original));
|
||||
}
|
||||
|
||||
@AutoJobPostMapping(
|
||||
consumes = MediaType.MULTIPART_FORM_DATA_VALUE,
|
||||
value = "/extract-fields/json",
|
||||
resourceWeight = ResourceWeight.LARGE_WEIGHT)
|
||||
@Operation(
|
||||
summary = "Extract typed fields from a document (JSON)",
|
||||
description =
|
||||
"Extracts the fields described by the JSON Schema and returns the extraction"
|
||||
+ " result (fields, confidence, citations) as JSON."
|
||||
+ " Input:PDF Output:JSON Type:SISO")
|
||||
public ResponseEntity<ExtractFieldsResponse> extractFieldsJson(
|
||||
@ModelAttribute ExtractFieldsApiRequest request) throws IOException {
|
||||
return ResponseEntity.ok(
|
||||
docParseService.extractFields(
|
||||
request.getFileInput(),
|
||||
request.getFieldsSchema(),
|
||||
DocparseMode.fromWire(request.getMode()),
|
||||
request.getInstructions()));
|
||||
}
|
||||
|
||||
@AutoJobPostMapping(
|
||||
consumes = MediaType.MULTIPART_FORM_DATA_VALUE,
|
||||
value = "/suggest-schema",
|
||||
resourceWeight = ResourceWeight.LARGE_WEIGHT)
|
||||
@Operation(
|
||||
summary = "Suggest an extraction schema for a document",
|
||||
description =
|
||||
"Reads the document and proposes the fields worth extracting (name, type,"
|
||||
+ " description), ready to feed into /extract-fields as a JSON Schema."
|
||||
+ " Input:PDF Output:JSON Type:SISO")
|
||||
public ResponseEntity<SuggestSchemaResponse> suggestSchema(
|
||||
@ModelAttribute SuggestSchemaApiRequest request) throws IOException {
|
||||
return ResponseEntity.ok(
|
||||
docParseService.suggestSchema(request.getFileInput(), request.getMaxFields()));
|
||||
}
|
||||
|
||||
@AutoJobPostMapping(
|
||||
consumes = MediaType.MULTIPART_FORM_DATA_VALUE,
|
||||
value = "/parse-document",
|
||||
resourceWeight = ResourceWeight.XLARGE_WEIGHT)
|
||||
@Operation(
|
||||
summary = "Parse a document into structured blocks, tables, and markdown",
|
||||
description =
|
||||
"Parses the PDF into layout blocks, tables, and a markdown rendering. The"
|
||||
+ " basic tier reads the text layer; the advanced tier (docparse addon)"
|
||||
+ " adds OCR, real table structure, and bounding boxes."
|
||||
+ " Input:PDF Output:JSON Type:SISO")
|
||||
public ResponseEntity<?> parseDocument(@ModelAttribute ParseDocumentApiRequest request)
|
||||
throws IOException {
|
||||
ParseDocumentResponse result =
|
||||
docParseService.parse(
|
||||
request.getFileInput(),
|
||||
DocparseMode.fromWire(request.getMode()),
|
||||
request.isWithOcr());
|
||||
if ("markdown".equalsIgnoreCase(request.getOutputFormat())) {
|
||||
return WebResponseUtils.bytesToWebResponse(
|
||||
result.markdown().getBytes(StandardCharsets.UTF_8),
|
||||
outputName(request.getFileInput(), "_parsed.md"),
|
||||
MARKDOWN);
|
||||
}
|
||||
return ResponseEntity.ok(result);
|
||||
}
|
||||
|
||||
@AutoJobPostMapping(
|
||||
consumes = MediaType.MULTIPART_FORM_DATA_VALUE,
|
||||
value = "/smart-split",
|
||||
resourceWeight = ResourceWeight.LARGE_WEIGHT)
|
||||
@Operation(
|
||||
summary = "Split a document at content-derived boundaries",
|
||||
description =
|
||||
"Asks the engine where sub-documents start (per the natural-language rule) and"
|
||||
+ " returns a ZIP with one PDF per part, named from the part labels."
|
||||
+ " Input:PDF Output:ZIP-PDF Type:SIMO")
|
||||
public ResponseEntity<Resource> smartSplit(@ModelAttribute SmartSplitApiRequest request)
|
||||
throws IOException {
|
||||
MultipartFile file = request.getFileInput();
|
||||
SmartSplitResponse split =
|
||||
docParseService.split(file, request.getRule(), request.getMaxParts());
|
||||
if (split.parts().isEmpty()) {
|
||||
throw new ResponseStatusException(
|
||||
HttpStatus.UNPROCESSABLE_ENTITY,
|
||||
"The split rule produced no parts for this document");
|
||||
}
|
||||
TempFile zipTempFile = tempFileManager.createManagedTempFile(".zip");
|
||||
try {
|
||||
try (TempFile sourceTempFile = new TempFile(tempFileManager, ".pdf")) {
|
||||
Files.copy(
|
||||
file.getInputStream(),
|
||||
sourceTempFile.getPath(),
|
||||
StandardCopyOption.REPLACE_EXISTING);
|
||||
try (ZipOutputStream zipOut =
|
||||
new ZipOutputStream(Files.newOutputStream(zipTempFile.getPath()))) {
|
||||
writeParts(sourceTempFile, split.parts(), zipOut);
|
||||
}
|
||||
}
|
||||
return WebResponseUtils.zipFileToWebResponse(
|
||||
zipTempFile,
|
||||
GeneralUtils.generateFilename(file.getOriginalFilename(), "_split.zip"));
|
||||
} catch (Exception e) {
|
||||
zipTempFile.close();
|
||||
throw e;
|
||||
}
|
||||
}
|
||||
|
||||
@AutoJobPostMapping(
|
||||
consumes = MediaType.MULTIPART_FORM_DATA_VALUE,
|
||||
value = "/chunk-document",
|
||||
resourceWeight = ResourceWeight.MEDIUM_WEIGHT)
|
||||
@Operation(
|
||||
summary = "Chunk a document for RAG",
|
||||
description =
|
||||
"Splits the document text into overlapping chunks with page spans and (advanced"
|
||||
+ " tier) heading breadcrumbs. Input:PDF Output:JSON Type:SISO")
|
||||
public ResponseEntity<ChunkDocumentResponse> chunkDocument(
|
||||
@ModelAttribute ChunkDocumentApiRequest request) throws IOException {
|
||||
return ResponseEntity.ok(
|
||||
docParseService.chunk(
|
||||
request.getFileInput(),
|
||||
request.getChunkSize(),
|
||||
request.getOverlap(),
|
||||
DocparseMode.fromWire(request.getMode())));
|
||||
}
|
||||
|
||||
@AutoJobPostMapping(
|
||||
consumes = MediaType.MULTIPART_FORM_DATA_VALUE,
|
||||
value = "/fill-template",
|
||||
resourceWeight = ResourceWeight.SMALL_WEIGHT)
|
||||
@Operation(
|
||||
summary = "Fill a DOCX template with JSON data",
|
||||
description =
|
||||
"Replaces the template's placeholders with values from the JSON object and"
|
||||
+ " returns the filled DOCX. Replacement counts and missing keys ride"
|
||||
+ " the X-Stirling-Tool-Report header."
|
||||
+ " Input:DOCX Output:DOCX Type:SISO")
|
||||
public ResponseEntity<Resource> fillTemplate(
|
||||
@RequestParam("templateFile") MultipartFile templateFile,
|
||||
@RequestParam("data") String data)
|
||||
throws IOException {
|
||||
FillDocxResponse result = docParseService.fillDocx(templateFile, data);
|
||||
byte[] filled = Base64.getDecoder().decode(result.docxBase64());
|
||||
HttpHeaders headers = new HttpHeaders();
|
||||
headers.setContentType(DOCX);
|
||||
headers.setContentDispositionFormData(
|
||||
"attachment",
|
||||
GeneralUtils.generateFilename(templateFile.getOriginalFilename(), "_filled.docx"));
|
||||
headers.setContentLength(filled.length);
|
||||
headers.set(
|
||||
AiToolResponseHeaders.TOOL_REPORT,
|
||||
objectMapper.writeValueAsString(
|
||||
new FillDocxResponse("", result.replaced(), result.missing())));
|
||||
return ResponseEntity.ok().headers(headers).body(new ByteArrayResource(filled));
|
||||
}
|
||||
|
||||
@GetMapping("/capabilities")
|
||||
@Operation(
|
||||
summary = "DocParse capability summary",
|
||||
description =
|
||||
"Merged view of the Java settings and the engine's capability probe, so"
|
||||
+ " clients can gate advanced-tier UI.")
|
||||
public ResponseEntity<DocparseCapabilitiesView> capabilities() {
|
||||
return ResponseEntity.ok(docParseService.capabilitiesView());
|
||||
}
|
||||
|
||||
@AutoJobPostMapping(
|
||||
consumes = MediaType.MULTIPART_FORM_DATA_VALUE,
|
||||
value = "/extract-tables",
|
||||
resourceWeight = ResourceWeight.LARGE_WEIGHT)
|
||||
@Operation(
|
||||
summary = "Extract tables from a document",
|
||||
description =
|
||||
"Extracts table structure and returns CSV (all tables concatenated, blank line"
|
||||
+ " between them) or the structured JSON table list."
|
||||
+ " Input:PDF Output:CSV/JSON Type:SISO")
|
||||
public ResponseEntity<?> extractTables(@ModelAttribute ExtractTablesApiRequest request)
|
||||
throws IOException {
|
||||
ExtractTablesResponse result = docParseService.tables(request.getFileInput());
|
||||
if ("json".equalsIgnoreCase(request.getOutputFormat())) {
|
||||
return ResponseEntity.ok(result);
|
||||
}
|
||||
return WebResponseUtils.bytesToWebResponse(
|
||||
tablesToCsv(result.tables()).getBytes(StandardCharsets.UTF_8),
|
||||
outputName(request.getFileInput(), "_tables.csv"),
|
||||
CSV);
|
||||
}
|
||||
|
||||
/** Original + requested corpus files in one ZIP, so destinations receive them together. */
|
||||
private byte[] exportZip(
|
||||
String fileName, byte[] original, RagIngestResponse result, RagIngestApiRequest request)
|
||||
throws IOException {
|
||||
String base = baseName(fileName);
|
||||
ByteArrayOutputStream out = new ByteArrayOutputStream();
|
||||
try (ZipOutputStream zip = new ZipOutputStream(out)) {
|
||||
zip.putNextEntry(new ZipEntry(fileName));
|
||||
zip.write(original);
|
||||
zip.closeEntry();
|
||||
if (request.isExportMarkdown()) {
|
||||
zip.putNextEntry(new ZipEntry(base + ".md"));
|
||||
zip.write(
|
||||
(result.markdown() == null ? "" : result.markdown())
|
||||
.getBytes(StandardCharsets.UTF_8));
|
||||
zip.closeEntry();
|
||||
}
|
||||
if (request.isExportChunksJsonl()) {
|
||||
zip.putNextEntry(new ZipEntry(base + ".chunks.jsonl"));
|
||||
zip.write(chunksJsonl(result).getBytes(StandardCharsets.UTF_8));
|
||||
zip.closeEntry();
|
||||
}
|
||||
}
|
||||
return out.toByteArray();
|
||||
}
|
||||
|
||||
/** One chunk per line, each self-describing (documentId + source travel on every line). */
|
||||
private String chunksJsonl(RagIngestResponse result) {
|
||||
if (result.chunks() == null) {
|
||||
return "";
|
||||
}
|
||||
StringBuilder lines = new StringBuilder();
|
||||
for (DocChunk chunk : result.chunks()) {
|
||||
ObjectNode line = objectMapper.createObjectNode();
|
||||
line.put("documentId", result.documentId());
|
||||
line.put("index", chunk.index());
|
||||
line.put("text", chunk.text());
|
||||
if (chunk.pageStart() != null) {
|
||||
line.put("pageStart", chunk.pageStart());
|
||||
}
|
||||
if (chunk.pageEnd() != null) {
|
||||
line.put("pageEnd", chunk.pageEnd());
|
||||
}
|
||||
var headings = line.putArray("headingPath");
|
||||
chunk.headingPath().forEach(headings::add);
|
||||
lines.append(objectMapper.writeValueAsString(line)).append('\n');
|
||||
}
|
||||
return lines.toString();
|
||||
}
|
||||
|
||||
private static String baseName(String fileName) {
|
||||
int dot = fileName.lastIndexOf('.');
|
||||
return dot > 0 ? fileName.substring(0, dot) : fileName;
|
||||
}
|
||||
|
||||
private void writeParts(TempFile sourceTempFile, List<SplitPart> parts, ZipOutputStream zipOut)
|
||||
throws IOException {
|
||||
for (int i = 0; i < parts.size(); i++) {
|
||||
SplitPart part = parts.get(i);
|
||||
// Load per part and remove pages outside the range: avoids the PDFBox cross-document
|
||||
// addPage pitfalls while keeping shared resources intact.
|
||||
try (PDDocument partDoc = pdfDocumentFactory.load(sourceTempFile.getFile())) {
|
||||
int pageCount = partDoc.getNumberOfPages();
|
||||
int start = Math.clamp(part.startPage(), 1, pageCount);
|
||||
int end = Math.clamp(part.endPage(), start, pageCount);
|
||||
for (int p = pageCount - 1; p >= 0; p--) {
|
||||
int pageNumber = p + 1;
|
||||
if (pageNumber < start || pageNumber > end) {
|
||||
partDoc.removePage(p);
|
||||
}
|
||||
}
|
||||
FormUtils.pruneOrphanedFormFields(partDoc);
|
||||
zipOut.putNextEntry(new ZipEntry(partEntryName(i, part)));
|
||||
partDoc.save(zipOut);
|
||||
zipOut.closeEntry();
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
private static String partEntryName(int index, SplitPart part) {
|
||||
String label = part.label() == null ? "" : part.label().trim();
|
||||
String sanitized = label.replaceAll("[^A-Za-z0-9 ._-]", "_").replaceAll("\\s+", "_");
|
||||
if (sanitized.isBlank() || sanitized.chars().allMatch(c -> c == '_' || c == '.')) {
|
||||
sanitized = "part";
|
||||
}
|
||||
// Index prefix keeps entries unique even when labels repeat.
|
||||
return String.format(Locale.ROOT, "%02d_%s.pdf", index + 1, sanitized);
|
||||
}
|
||||
|
||||
private static String tablesToCsv(List<DocTable> tables) throws IOException {
|
||||
CSVFormat format = CSVFormat.EXCEL.builder().setEscape('"').build();
|
||||
StringWriter writer = new StringWriter();
|
||||
try (CSVPrinter printer = format.print(writer)) {
|
||||
boolean first = true;
|
||||
for (DocTable table : tables) {
|
||||
if (!first) {
|
||||
printer.println();
|
||||
}
|
||||
first = false;
|
||||
for (List<String> row : table.cells()) {
|
||||
printer.printRecord(row);
|
||||
}
|
||||
}
|
||||
}
|
||||
return writer.toString();
|
||||
}
|
||||
|
||||
private static String outputName(MultipartFile file, String suffix) {
|
||||
return GeneralUtils.removeExtension(DocParseService.fileName(file)) + suffix;
|
||||
}
|
||||
}
|
||||
+27
@@ -0,0 +1,27 @@
|
||||
package stirling.software.proprietary.model.api.docparse;
|
||||
|
||||
import io.swagger.v3.oas.annotations.media.Schema;
|
||||
|
||||
import lombok.Data;
|
||||
import lombok.EqualsAndHashCode;
|
||||
|
||||
import stirling.software.common.model.api.PDFFile;
|
||||
|
||||
@Data
|
||||
@EqualsAndHashCode(callSuper = true)
|
||||
public class ChunkDocumentApiRequest extends PDFFile {
|
||||
|
||||
@Schema(description = "Target chunk size in characters (64-32768)", defaultValue = "512")
|
||||
private int chunkSize = 512;
|
||||
|
||||
@Schema(
|
||||
description = "Overlap between adjacent chunks in characters (0-4096)",
|
||||
defaultValue = "64")
|
||||
private int overlap = 64;
|
||||
|
||||
@Schema(
|
||||
description = "Tier to use: 'auto' picks per document, or force 'basic'/'advanced'",
|
||||
allowableValues = {"auto", "basic", "advanced"},
|
||||
defaultValue = "auto")
|
||||
private String mode = "auto";
|
||||
}
|
||||
+29
@@ -0,0 +1,29 @@
|
||||
package stirling.software.proprietary.model.api.docparse;
|
||||
|
||||
import io.swagger.v3.oas.annotations.media.Schema;
|
||||
|
||||
import lombok.Data;
|
||||
import lombok.EqualsAndHashCode;
|
||||
|
||||
import stirling.software.common.model.api.PDFFile;
|
||||
|
||||
@Data
|
||||
@EqualsAndHashCode(callSuper = true)
|
||||
public class ExtractFieldsApiRequest extends PDFFile {
|
||||
|
||||
@Schema(
|
||||
description = "JSON Schema object describing the fields to extract, as a JSON string",
|
||||
requiredMode = Schema.RequiredMode.REQUIRED,
|
||||
example =
|
||||
"{\"type\":\"object\",\"properties\":{\"invoiceNumber\":{\"type\":\"string\"}}}")
|
||||
private String fieldsSchema;
|
||||
|
||||
@Schema(
|
||||
description = "Tier to use: 'auto' picks per document, or force 'basic'/'advanced'",
|
||||
allowableValues = {"auto", "basic", "advanced"},
|
||||
defaultValue = "auto")
|
||||
private String mode = "auto";
|
||||
|
||||
@Schema(description = "Optional natural-language guidance for the extraction")
|
||||
private String instructions;
|
||||
}
|
||||
+19
@@ -0,0 +1,19 @@
|
||||
package stirling.software.proprietary.model.api.docparse;
|
||||
|
||||
import io.swagger.v3.oas.annotations.media.Schema;
|
||||
|
||||
import lombok.Data;
|
||||
import lombok.EqualsAndHashCode;
|
||||
|
||||
import stirling.software.common.model.api.PDFFile;
|
||||
|
||||
@Data
|
||||
@EqualsAndHashCode(callSuper = true)
|
||||
public class ExtractTablesApiRequest extends PDFFile {
|
||||
|
||||
@Schema(
|
||||
description = "Response format: CSV text or the structured JSON table list",
|
||||
allowableValues = {"csv", "json"},
|
||||
defaultValue = "csv")
|
||||
private String outputFormat = "csv";
|
||||
}
|
||||
+30
@@ -0,0 +1,30 @@
|
||||
package stirling.software.proprietary.model.api.docparse;
|
||||
|
||||
import io.swagger.v3.oas.annotations.media.Schema;
|
||||
|
||||
import lombok.Data;
|
||||
import lombok.EqualsAndHashCode;
|
||||
|
||||
import stirling.software.common.model.api.PDFFile;
|
||||
|
||||
@Data
|
||||
@EqualsAndHashCode(callSuper = true)
|
||||
public class ParseDocumentApiRequest extends PDFFile {
|
||||
|
||||
@Schema(
|
||||
description = "Tier to use: 'auto' picks per document, or force 'basic'/'advanced'",
|
||||
allowableValues = {"auto", "basic", "advanced"},
|
||||
defaultValue = "auto")
|
||||
private String mode = "auto";
|
||||
|
||||
@Schema(
|
||||
description = "Apply OCR when parsing scanned pages (advanced tier only)",
|
||||
defaultValue = "true")
|
||||
private boolean withOcr = true;
|
||||
|
||||
@Schema(
|
||||
description = "Response format: full JSON result or the markdown rendering only",
|
||||
allowableValues = {"json", "markdown"},
|
||||
defaultValue = "json")
|
||||
private String outputFormat = "json";
|
||||
}
|
||||
+52
@@ -0,0 +1,52 @@
|
||||
package stirling.software.proprietary.model.api.docparse;
|
||||
|
||||
import io.swagger.v3.oas.annotations.media.Schema;
|
||||
|
||||
import lombok.Data;
|
||||
import lombok.EqualsAndHashCode;
|
||||
|
||||
import stirling.software.common.model.api.PDFFile;
|
||||
|
||||
@Data
|
||||
@EqualsAndHashCode(callSuper = true)
|
||||
public class RagIngestApiRequest extends PDFFile {
|
||||
|
||||
@Schema(
|
||||
description =
|
||||
"Stable identifier for the ingested document; re-ingesting the same id replaces"
|
||||
+ " its chunks. Defaults to a content hash of the uploaded bytes.")
|
||||
private String documentId;
|
||||
|
||||
@Schema(description = "Target chunk size in characters (64-32768)", defaultValue = "512")
|
||||
private int chunkSize = 512;
|
||||
|
||||
@Schema(
|
||||
description = "Overlap between adjacent chunks in characters (0-4096)",
|
||||
defaultValue = "64")
|
||||
private int overlap = 64;
|
||||
|
||||
@Schema(
|
||||
description = "Tier to use: 'auto' picks per document, or force 'basic'/'advanced'",
|
||||
allowableValues = {"auto", "basic", "advanced"},
|
||||
defaultValue = "auto")
|
||||
private String mode = "auto";
|
||||
|
||||
@Schema(
|
||||
description = "Index the document into the built-in knowledge base",
|
||||
defaultValue = "true")
|
||||
private boolean index = true;
|
||||
|
||||
@Schema(
|
||||
description =
|
||||
"Also return the parsed document as a markdown file, for delivery to external"
|
||||
+ " systems (vector DBs, training corpora)",
|
||||
defaultValue = "false")
|
||||
private boolean exportMarkdown = false;
|
||||
|
||||
@Schema(
|
||||
description =
|
||||
"Also return the chunks as a JSONL file (one chunk per line with page span and"
|
||||
+ " heading breadcrumb), ready for external embedding or indexing",
|
||||
defaultValue = "false")
|
||||
private boolean exportChunksJsonl = false;
|
||||
}
|
||||
+21
@@ -0,0 +1,21 @@
|
||||
package stirling.software.proprietary.model.api.docparse;
|
||||
|
||||
import io.swagger.v3.oas.annotations.media.Schema;
|
||||
|
||||
import lombok.Data;
|
||||
import lombok.EqualsAndHashCode;
|
||||
|
||||
import stirling.software.common.model.api.PDFFile;
|
||||
|
||||
@Data
|
||||
@EqualsAndHashCode(callSuper = true)
|
||||
public class SmartSplitApiRequest extends PDFFile {
|
||||
|
||||
@Schema(
|
||||
description = "Natural-language boundary rule, e.g. 'split where a new invoice starts'",
|
||||
requiredMode = Schema.RequiredMode.REQUIRED)
|
||||
private String rule;
|
||||
|
||||
@Schema(description = "Maximum number of parts to produce (1-500)", defaultValue = "50")
|
||||
private int maxParts = 50;
|
||||
}
|
||||
+16
@@ -0,0 +1,16 @@
|
||||
package stirling.software.proprietary.model.api.docparse;
|
||||
|
||||
import io.swagger.v3.oas.annotations.media.Schema;
|
||||
|
||||
import lombok.Data;
|
||||
import lombok.EqualsAndHashCode;
|
||||
|
||||
import stirling.software.common.model.api.PDFFile;
|
||||
|
||||
@Data
|
||||
@EqualsAndHashCode(callSuper = true)
|
||||
public class SuggestSchemaApiRequest extends PDFFile {
|
||||
|
||||
@Schema(description = "Maximum number of fields to suggest (1-20)", defaultValue = "10")
|
||||
private int maxFields = 10;
|
||||
}
|
||||
+14
@@ -0,0 +1,14 @@
|
||||
package stirling.software.proprietary.model.docparse;
|
||||
|
||||
import java.util.List;
|
||||
|
||||
import stirling.software.proprietary.model.api.ai.AiPageText;
|
||||
|
||||
/** Engine request for {@code POST /api/v1/docparse/chunk}. */
|
||||
public record ChunkDocumentRequest(
|
||||
String fileName,
|
||||
List<AiPageText> pages,
|
||||
String contentBase64,
|
||||
int chunkSize,
|
||||
int overlap,
|
||||
DocparseMode mode) {}
|
||||
+11
@@ -0,0 +1,11 @@
|
||||
package stirling.software.proprietary.model.docparse;
|
||||
|
||||
import java.util.List;
|
||||
|
||||
/** Engine response for {@code POST /api/v1/docparse/chunk}. */
|
||||
public record ChunkDocumentResponse(DocparseTier mode, List<DocChunk> chunks) {
|
||||
|
||||
public ChunkDocumentResponse {
|
||||
chunks = chunks == null ? List.of() : chunks;
|
||||
}
|
||||
}
|
||||
+9
@@ -0,0 +1,9 @@
|
||||
package stirling.software.proprietary.model.docparse;
|
||||
|
||||
import java.util.List;
|
||||
|
||||
/**
|
||||
* One layout block. {@code bbox} is [x0, y0, x1, y1] normalized to 0..1 with a top-left origin;
|
||||
* {@code null} in basic tier (no layout model ran). Mirrors {@code docparse.py DocBlock}.
|
||||
*/
|
||||
public record DocBlock(String type, String text, int page, List<Double> bbox, Double confidence) {}
|
||||
+12
@@ -0,0 +1,12 @@
|
||||
package stirling.software.proprietary.model.docparse;
|
||||
|
||||
import java.util.List;
|
||||
|
||||
/** One RAG chunk with page span and heading breadcrumb. Mirrors {@code docparse.py DocChunk}. */
|
||||
public record DocChunk(
|
||||
int index, String text, Integer pageStart, Integer pageEnd, List<String> headingPath) {
|
||||
|
||||
public DocChunk {
|
||||
headingPath = headingPath == null ? List.of() : headingPath;
|
||||
}
|
||||
}
|
||||
+12
@@ -0,0 +1,12 @@
|
||||
package stirling.software.proprietary.model.docparse;
|
||||
|
||||
import java.util.List;
|
||||
|
||||
/** One extracted table. Mirrors {@code docparse.py DocTable}. */
|
||||
public record DocTable(
|
||||
int page, List<Double> bbox, List<List<String>> cells, String markdown, Double confidence) {
|
||||
|
||||
public DocTable {
|
||||
cells = cells == null ? List.of() : cells;
|
||||
}
|
||||
}
|
||||
+25
@@ -0,0 +1,25 @@
|
||||
package stirling.software.proprietary.model.docparse;
|
||||
|
||||
import java.util.List;
|
||||
|
||||
/**
|
||||
* What the engine can actually do right now; Java caches and republishes this. Mirrors {@code
|
||||
* docparse.py DocparseCapabilities}.
|
||||
*/
|
||||
public record DocparseCapabilities(
|
||||
boolean advancedInstalled,
|
||||
String doclingVersion,
|
||||
String torchVersion,
|
||||
boolean modelsAvailable,
|
||||
String modelsPath,
|
||||
List<String> errors) {
|
||||
|
||||
public DocparseCapabilities {
|
||||
errors = errors == null ? List.of() : errors;
|
||||
}
|
||||
|
||||
/** The addon-absent view used when the engine is disabled, unreachable, or probing failed. */
|
||||
public static DocparseCapabilities absent(String reason) {
|
||||
return new DocparseCapabilities(false, null, null, false, null, List.of(reason));
|
||||
}
|
||||
}
|
||||
+9
@@ -0,0 +1,9 @@
|
||||
package stirling.software.proprietary.model.docparse;
|
||||
|
||||
/** Merged capability view served by {@code GET /api/v1/docparse/capabilities} (Java side). */
|
||||
public record DocparseCapabilitiesView(
|
||||
boolean enabled,
|
||||
String mode,
|
||||
boolean advancedInstalled,
|
||||
boolean engineReachable,
|
||||
String doclingVersion) {}
|
||||
+35
@@ -0,0 +1,35 @@
|
||||
package stirling.software.proprietary.model.docparse;
|
||||
|
||||
import java.util.Locale;
|
||||
|
||||
import com.fasterxml.jackson.annotation.JsonCreator;
|
||||
import com.fasterxml.jackson.annotation.JsonValue;
|
||||
|
||||
/**
|
||||
* What the caller asked for; {@code AUTO} resolves per request. Wire values are lowercase to match
|
||||
* {@code engine/src/stirling/contracts/docparse.py DocparseMode}.
|
||||
*/
|
||||
public enum DocparseMode {
|
||||
AUTO("auto"),
|
||||
BASIC("basic"),
|
||||
ADVANCED("advanced");
|
||||
|
||||
private final String wire;
|
||||
|
||||
DocparseMode(String wire) {
|
||||
this.wire = wire;
|
||||
}
|
||||
|
||||
@JsonValue
|
||||
public String wire() {
|
||||
return wire;
|
||||
}
|
||||
|
||||
@JsonCreator
|
||||
public static DocparseMode fromWire(String value) {
|
||||
if (value == null || value.isBlank()) {
|
||||
return AUTO;
|
||||
}
|
||||
return valueOf(value.trim().toUpperCase(Locale.ROOT));
|
||||
}
|
||||
}
|
||||
+31
@@ -0,0 +1,31 @@
|
||||
package stirling.software.proprietary.model.docparse;
|
||||
|
||||
import java.util.Locale;
|
||||
|
||||
import com.fasterxml.jackson.annotation.JsonCreator;
|
||||
import com.fasterxml.jackson.annotation.JsonValue;
|
||||
|
||||
/**
|
||||
* Which implementation actually served a request. Wire values are lowercase to match {@code
|
||||
* engine/src/stirling/contracts/docparse.py DocparseTier}.
|
||||
*/
|
||||
public enum DocparseTier {
|
||||
BASIC("basic"),
|
||||
ADVANCED("advanced");
|
||||
|
||||
private final String wire;
|
||||
|
||||
DocparseTier(String wire) {
|
||||
this.wire = wire;
|
||||
}
|
||||
|
||||
@JsonValue
|
||||
public String wire() {
|
||||
return wire;
|
||||
}
|
||||
|
||||
@JsonCreator
|
||||
public static DocparseTier fromWire(String value) {
|
||||
return valueOf(value.trim().toUpperCase(Locale.ROOT));
|
||||
}
|
||||
}
|
||||
+19
@@ -0,0 +1,19 @@
|
||||
package stirling.software.proprietary.model.docparse;
|
||||
|
||||
import java.util.List;
|
||||
|
||||
import stirling.software.proprietary.model.api.ai.AiPageText;
|
||||
|
||||
import tools.jackson.databind.JsonNode;
|
||||
|
||||
/**
|
||||
* Engine request for {@code POST /api/v1/docparse/extract}. {@code pages} drives the basic tier
|
||||
* (Java-extracted text); {@code contentBase64} lets the advanced tier parse the raw file itself.
|
||||
*/
|
||||
public record ExtractFieldsRequest(
|
||||
String fileName,
|
||||
JsonNode fieldsSchema,
|
||||
List<AiPageText> pages,
|
||||
String contentBase64,
|
||||
DocparseMode mode,
|
||||
String instructions) {}
|
||||
+12
@@ -0,0 +1,12 @@
|
||||
package stirling.software.proprietary.model.docparse;
|
||||
|
||||
import java.util.List;
|
||||
|
||||
/** Engine response for {@code POST /api/v1/docparse/extract}. */
|
||||
public record ExtractFieldsResponse(
|
||||
DocparseTier mode, List<ExtractedField> fields, double overallConfidence) {
|
||||
|
||||
public ExtractFieldsResponse {
|
||||
fields = fields == null ? List.of() : fields;
|
||||
}
|
||||
}
|
||||
+4
@@ -0,0 +1,4 @@
|
||||
package stirling.software.proprietary.model.docparse;
|
||||
|
||||
/** Engine request for {@code POST /api/v1/docparse/tables}. */
|
||||
public record ExtractTablesRequest(String fileName, String contentBase64) {}
|
||||
+11
@@ -0,0 +1,11 @@
|
||||
package stirling.software.proprietary.model.docparse;
|
||||
|
||||
import java.util.List;
|
||||
|
||||
/** Engine response for {@code POST /api/v1/docparse/tables}. */
|
||||
public record ExtractTablesResponse(DocparseTier mode, List<DocTable> tables) {
|
||||
|
||||
public ExtractTablesResponse {
|
||||
tables = tables == null ? List.of() : tables;
|
||||
}
|
||||
}
|
||||
+16
@@ -0,0 +1,16 @@
|
||||
package stirling.software.proprietary.model.docparse;
|
||||
|
||||
import java.util.List;
|
||||
|
||||
import tools.jackson.databind.JsonNode;
|
||||
|
||||
/**
|
||||
* One extracted field with confidence and citations. Mirrors {@code docparse.py ExtractedField}.
|
||||
*/
|
||||
public record ExtractedField(
|
||||
String name, JsonNode value, double confidence, List<FieldCitation> citations) {
|
||||
|
||||
public ExtractedField {
|
||||
citations = citations == null ? List.of() : citations;
|
||||
}
|
||||
}
|
||||
+11
@@ -0,0 +1,11 @@
|
||||
package stirling.software.proprietary.model.docparse;
|
||||
|
||||
import java.util.List;
|
||||
|
||||
/**
|
||||
* Where a value came from. {@code quote} is always set; {@code bbox} only when a layout parse ran
|
||||
* (advanced tier); offsets index into the cited page's text. Mirrors {@code docparse.py
|
||||
* FieldCitation}.
|
||||
*/
|
||||
public record FieldCitation(
|
||||
Integer page, List<Double> bbox, String quote, Integer startOffset, Integer endOffset) {}
|
||||
+6
@@ -0,0 +1,6 @@
|
||||
package stirling.software.proprietary.model.docparse;
|
||||
|
||||
import tools.jackson.databind.JsonNode;
|
||||
|
||||
/** Engine request for {@code POST /api/v1/docparse/fill-docx}. */
|
||||
public record FillDocxRequest(String templateBase64, JsonNode data) {}
|
||||
+11
@@ -0,0 +1,11 @@
|
||||
package stirling.software.proprietary.model.docparse;
|
||||
|
||||
import java.util.List;
|
||||
|
||||
/** Engine response for {@code POST /api/v1/docparse/fill-docx}. */
|
||||
public record FillDocxResponse(String docxBase64, int replaced, List<String> missing) {
|
||||
|
||||
public FillDocxResponse {
|
||||
missing = missing == null ? List.of() : missing;
|
||||
}
|
||||
}
|
||||
+4
@@ -0,0 +1,4 @@
|
||||
package stirling.software.proprietary.model.docparse;
|
||||
|
||||
/** Engine request for {@code POST /api/v1/docparse/parse}. */
|
||||
public record ParseDocumentRequest(String fileName, String contentBase64, boolean withOcr) {}
|
||||
+21
@@ -0,0 +1,21 @@
|
||||
package stirling.software.proprietary.model.docparse;
|
||||
|
||||
import java.util.List;
|
||||
|
||||
/**
|
||||
* Engine response for {@code POST /api/v1/docparse/parse}; also produced by the Java basic tier.
|
||||
*/
|
||||
public record ParseDocumentResponse(
|
||||
DocparseTier mode,
|
||||
int pages,
|
||||
List<DocBlock> blocks,
|
||||
List<DocTable> tables,
|
||||
String markdown,
|
||||
boolean ocrApplied) {
|
||||
|
||||
public ParseDocumentResponse {
|
||||
blocks = blocks == null ? List.of() : blocks;
|
||||
tables = tables == null ? List.of() : tables;
|
||||
markdown = markdown == null ? "" : markdown;
|
||||
}
|
||||
}
|
||||
+29
@@ -0,0 +1,29 @@
|
||||
package stirling.software.proprietary.model.docparse;
|
||||
|
||||
import java.time.Instant;
|
||||
import java.util.List;
|
||||
|
||||
import stirling.software.proprietary.model.api.ai.AiPageText;
|
||||
|
||||
/**
|
||||
* Engine request for {@code POST /api/v1/docparse/rag-ingest}. Owner semantics mirror {@code POST
|
||||
* /api/v1/documents}: {@code ownerId} is the tenant, {@code readPrincipals} the explicit readers,
|
||||
* and a null {@code expiresAt} keeps the ingested content until an explicit delete. {@code index}
|
||||
* false skips the store (export-only); {@code includeMarkdown}/{@code includeChunks} echo the
|
||||
* parsed content back so the caller can emit corpus files.
|
||||
*/
|
||||
public record RagIngestRequest(
|
||||
String fileName,
|
||||
String documentId,
|
||||
String source,
|
||||
String ownerId,
|
||||
List<String> readPrincipals,
|
||||
Instant expiresAt,
|
||||
List<AiPageText> pages,
|
||||
String contentBase64,
|
||||
int chunkSize,
|
||||
int overlap,
|
||||
DocparseMode mode,
|
||||
boolean index,
|
||||
boolean includeMarkdown,
|
||||
boolean includeChunks) {}
|
||||
+15
@@ -0,0 +1,15 @@
|
||||
package stirling.software.proprietary.model.docparse;
|
||||
|
||||
import java.util.List;
|
||||
|
||||
/**
|
||||
* Engine response for {@code POST /api/v1/docparse/rag-ingest}. {@code markdown} and {@code chunks}
|
||||
* are only present when the request asked for them via includeMarkdown/includeChunks.
|
||||
*/
|
||||
public record RagIngestResponse(
|
||||
DocparseTier mode,
|
||||
String documentId,
|
||||
int chunksIndexed,
|
||||
int pages,
|
||||
String markdown,
|
||||
List<DocChunk> chunks) {}
|
||||
+9
@@ -0,0 +1,9 @@
|
||||
package stirling.software.proprietary.model.docparse;
|
||||
|
||||
import java.util.List;
|
||||
|
||||
import stirling.software.proprietary.model.api.ai.AiPageText;
|
||||
|
||||
/** Engine request for {@code POST /api/v1/docparse/split}. */
|
||||
public record SmartSplitRequest(
|
||||
String fileName, String rule, List<AiPageText> pages, int maxParts) {}
|
||||
+11
@@ -0,0 +1,11 @@
|
||||
package stirling.software.proprietary.model.docparse;
|
||||
|
||||
import java.util.List;
|
||||
|
||||
/** Engine response for {@code POST /api/v1/docparse/split}. */
|
||||
public record SmartSplitResponse(List<SplitPart> parts) {
|
||||
|
||||
public SmartSplitResponse {
|
||||
parts = parts == null ? List.of() : parts;
|
||||
}
|
||||
}
|
||||
+4
@@ -0,0 +1,4 @@
|
||||
package stirling.software.proprietary.model.docparse;
|
||||
|
||||
/** One sub-document page range (1-based, inclusive). Mirrors {@code docparse.py SplitPart}. */
|
||||
public record SplitPart(int startPage, int endPage, String label, double confidence) {}
|
||||
+12
@@ -0,0 +1,12 @@
|
||||
package stirling.software.proprietary.model.docparse;
|
||||
|
||||
import java.util.List;
|
||||
|
||||
import stirling.software.proprietary.model.api.ai.AiPageText;
|
||||
|
||||
/**
|
||||
* Engine request for {@code POST /api/v1/docparse/suggest-schema}. {@code pages} drives the basic
|
||||
* tier (Java-extracted text); {@code contentBase64} lets the advanced tier parse the raw file.
|
||||
*/
|
||||
public record SuggestSchemaRequest(
|
||||
String fileName, List<AiPageText> pages, String contentBase64, int maxFields) {}
|
||||
+11
@@ -0,0 +1,11 @@
|
||||
package stirling.software.proprietary.model.docparse;
|
||||
|
||||
import java.util.List;
|
||||
|
||||
/** Engine response for {@code POST /api/v1/docparse/suggest-schema}. */
|
||||
public record SuggestSchemaResponse(DocparseTier mode, List<SuggestedField> fields) {
|
||||
|
||||
public SuggestSchemaResponse {
|
||||
fields = fields == null ? List.of() : fields;
|
||||
}
|
||||
}
|
||||
+4
@@ -0,0 +1,4 @@
|
||||
package stirling.software.proprietary.model.docparse;
|
||||
|
||||
/** One field the engine proposes for an extraction schema. */
|
||||
public record SuggestedField(String name, String type, String description) {}
|
||||
+51
@@ -0,0 +1,51 @@
|
||||
package stirling.software.proprietary.security.filter;
|
||||
|
||||
import java.io.IOException;
|
||||
|
||||
import org.slf4j.MDC;
|
||||
import org.springframework.core.Ordered;
|
||||
import org.springframework.core.annotation.Order;
|
||||
import org.springframework.security.core.Authentication;
|
||||
import org.springframework.security.core.context.SecurityContextHolder;
|
||||
import org.springframework.stereotype.Component;
|
||||
import org.springframework.web.filter.OncePerRequestFilter;
|
||||
|
||||
import jakarta.servlet.FilterChain;
|
||||
import jakarta.servlet.ServletException;
|
||||
import jakarta.servlet.http.HttpServletRequest;
|
||||
import jakarta.servlet.http.HttpServletResponse;
|
||||
|
||||
/**
|
||||
* Stamps the authenticated principal into MDC for every request. Async job workers resolve the
|
||||
* caller via UserService's MDC fallback; without this the fallback only worked when the audit
|
||||
* aspect (a pro feature) happened to populate it.
|
||||
*/
|
||||
@Component
|
||||
@Order(Ordered.LOWEST_PRECEDENCE)
|
||||
public class PrincipalMdcFilter extends OncePerRequestFilter {
|
||||
|
||||
static final String MDC_KEY = "auditPrincipal";
|
||||
|
||||
@Override
|
||||
protected void doFilterInternal(
|
||||
HttpServletRequest request, HttpServletResponse response, FilterChain filterChain)
|
||||
throws ServletException, IOException {
|
||||
String previous = MDC.get(MDC_KEY);
|
||||
Authentication authentication = SecurityContextHolder.getContext().getAuthentication();
|
||||
boolean stamped = false;
|
||||
if (previous == null
|
||||
&& authentication != null
|
||||
&& authentication.isAuthenticated()
|
||||
&& !"anonymousUser".equals(authentication.getPrincipal())) {
|
||||
MDC.put(MDC_KEY, authentication.getName());
|
||||
stamped = true;
|
||||
}
|
||||
try {
|
||||
filterChain.doFilter(request, response);
|
||||
} finally {
|
||||
if (stamped) {
|
||||
MDC.remove(MDC_KEY);
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
+7
@@ -254,6 +254,13 @@ public class AiEngineClient {
|
||||
|
||||
private void checkResponseStatus(HttpResponse<String> response) {
|
||||
int status = response.statusCode();
|
||||
// 501 = capability not implemented (e.g. docparse addon missing); keep the status and
|
||||
// body so callers can surface the machine-readable addonRequired detail.
|
||||
if (status == 501) {
|
||||
throw new ResponseStatusException(
|
||||
HttpStatus.NOT_IMPLEMENTED,
|
||||
"AI engine capability not implemented: " + response.body());
|
||||
}
|
||||
if (status >= 500) {
|
||||
throw new ResponseStatusException(
|
||||
HttpStatus.BAD_GATEWAY, "AI engine returned error: " + status);
|
||||
|
||||
+491
@@ -0,0 +1,491 @@
|
||||
package stirling.software.proprietary.service;
|
||||
|
||||
import java.io.IOException;
|
||||
import java.util.ArrayList;
|
||||
import java.util.Base64;
|
||||
import java.util.List;
|
||||
|
||||
import org.apache.pdfbox.pdmodel.PDDocument;
|
||||
import org.springframework.beans.factory.annotation.Autowired;
|
||||
import org.springframework.http.HttpStatus;
|
||||
import org.springframework.stereotype.Service;
|
||||
import org.springframework.web.multipart.MultipartFile;
|
||||
import org.springframework.web.server.ResponseStatusException;
|
||||
|
||||
import io.github.pixee.security.Filenames;
|
||||
|
||||
import lombok.extern.slf4j.Slf4j;
|
||||
|
||||
import stirling.software.common.model.ApplicationProperties;
|
||||
import stirling.software.common.service.CustomPDFDocumentFactory;
|
||||
import stirling.software.common.service.UserServiceInterface;
|
||||
import stirling.software.proprietary.model.api.ai.AiPageText;
|
||||
import stirling.software.proprietary.model.docparse.ChunkDocumentRequest;
|
||||
import stirling.software.proprietary.model.docparse.ChunkDocumentResponse;
|
||||
import stirling.software.proprietary.model.docparse.DocBlock;
|
||||
import stirling.software.proprietary.model.docparse.DocparseCapabilities;
|
||||
import stirling.software.proprietary.model.docparse.DocparseCapabilitiesView;
|
||||
import stirling.software.proprietary.model.docparse.DocparseMode;
|
||||
import stirling.software.proprietary.model.docparse.DocparseTier;
|
||||
import stirling.software.proprietary.model.docparse.ExtractFieldsRequest;
|
||||
import stirling.software.proprietary.model.docparse.ExtractFieldsResponse;
|
||||
import stirling.software.proprietary.model.docparse.ExtractTablesRequest;
|
||||
import stirling.software.proprietary.model.docparse.ExtractTablesResponse;
|
||||
import stirling.software.proprietary.model.docparse.FillDocxRequest;
|
||||
import stirling.software.proprietary.model.docparse.FillDocxResponse;
|
||||
import stirling.software.proprietary.model.docparse.ParseDocumentRequest;
|
||||
import stirling.software.proprietary.model.docparse.ParseDocumentResponse;
|
||||
import stirling.software.proprietary.model.docparse.RagIngestRequest;
|
||||
import stirling.software.proprietary.model.docparse.RagIngestResponse;
|
||||
import stirling.software.proprietary.model.docparse.SmartSplitRequest;
|
||||
import stirling.software.proprietary.model.docparse.SmartSplitResponse;
|
||||
import stirling.software.proprietary.model.docparse.SuggestSchemaRequest;
|
||||
import stirling.software.proprietary.model.docparse.SuggestSchemaResponse;
|
||||
|
||||
import tools.jackson.databind.JsonNode;
|
||||
import tools.jackson.databind.ObjectMapper;
|
||||
|
||||
/**
|
||||
* DocParse ingestion: per-page text extraction (reusing the same {@link PdfContentExtractor} the AI
|
||||
* chat path uses) plus engine dispatch for chunk + embed + index. The engine owns chunking,
|
||||
* embedding, and the document store; Java owns identity, limits, and the wire contract from {@code
|
||||
* engine/src/stirling/contracts/docparse.py}.
|
||||
*/
|
||||
@Slf4j
|
||||
@Service
|
||||
public class DocParseService {
|
||||
|
||||
private static final String PARSE_ENDPOINT = "/api/v1/docparse/parse";
|
||||
private static final String EXTRACT_ENDPOINT = "/api/v1/docparse/extract";
|
||||
private static final String SPLIT_ENDPOINT = "/api/v1/docparse/split";
|
||||
private static final String CHUNK_ENDPOINT = "/api/v1/docparse/chunk";
|
||||
private static final String TABLES_ENDPOINT = "/api/v1/docparse/tables";
|
||||
private static final String FILL_DOCX_ENDPOINT = "/api/v1/docparse/fill-docx";
|
||||
private static final String SUGGEST_SCHEMA_ENDPOINT = "/api/v1/docparse/suggest-schema";
|
||||
private static final String RAG_INGEST_ENDPOINT = "/api/v1/docparse/rag-ingest";
|
||||
|
||||
/** Below this average of extractable chars per page the document is treated as scanned. */
|
||||
static final int SCANNED_AVG_CHARS_PER_PAGE = 100;
|
||||
|
||||
/** Pages sampled for the scanned heuristic; keeps the probe cheap on huge documents. */
|
||||
private static final int SCANNED_SAMPLE_PAGES = 20;
|
||||
|
||||
private final AiEngineClient aiEngineClient;
|
||||
private final DocparseCapabilityService capabilityService;
|
||||
private final CustomPDFDocumentFactory pdfDocumentFactory;
|
||||
private final PdfContentExtractor pdfContentExtractor;
|
||||
private final ApplicationProperties applicationProperties;
|
||||
private final ObjectMapper objectMapper;
|
||||
private final FileIdStrategy fileIdStrategy;
|
||||
private final UserServiceInterface userService;
|
||||
|
||||
public DocParseService(
|
||||
AiEngineClient aiEngineClient,
|
||||
DocparseCapabilityService capabilityService,
|
||||
CustomPDFDocumentFactory pdfDocumentFactory,
|
||||
PdfContentExtractor pdfContentExtractor,
|
||||
ApplicationProperties applicationProperties,
|
||||
ObjectMapper objectMapper,
|
||||
FileIdStrategy fileIdStrategy,
|
||||
@Autowired(required = false) UserServiceInterface userService) {
|
||||
this.aiEngineClient = aiEngineClient;
|
||||
this.capabilityService = capabilityService;
|
||||
this.pdfDocumentFactory = pdfDocumentFactory;
|
||||
this.pdfContentExtractor = pdfContentExtractor;
|
||||
this.applicationProperties = applicationProperties;
|
||||
this.objectMapper = objectMapper;
|
||||
this.fileIdStrategy = fileIdStrategy;
|
||||
this.userService = userService;
|
||||
}
|
||||
|
||||
/** Throws 503 when the docparse.enabled master switch is off. */
|
||||
public void requireEnabled() {
|
||||
if (!applicationProperties.getDocparse().isEnabled()) {
|
||||
throw new ResponseStatusException(
|
||||
HttpStatus.SERVICE_UNAVAILABLE, "DocParse is disabled");
|
||||
}
|
||||
}
|
||||
|
||||
public DocparseCapabilitiesView capabilitiesView() {
|
||||
ApplicationProperties.Docparse config = applicationProperties.getDocparse();
|
||||
DocparseCapabilities capabilities = capabilityService.capabilities();
|
||||
return new DocparseCapabilitiesView(
|
||||
config.isEnabled(),
|
||||
config.getMode(),
|
||||
capabilities.advancedInstalled(),
|
||||
capabilityService.isEngineReachable(),
|
||||
capabilities.doclingVersion());
|
||||
}
|
||||
|
||||
public ParseDocumentResponse parse(
|
||||
MultipartFile file, DocparseMode requestedMode, boolean withOcr) throws IOException {
|
||||
requireEnabled();
|
||||
DocparseTier tier;
|
||||
try (PDDocument document = pdfDocumentFactory.load(file, true)) {
|
||||
tier =
|
||||
resolveTier(
|
||||
requestedMode,
|
||||
capabilityService.capabilities(),
|
||||
false,
|
||||
looksScanned(document));
|
||||
if (tier == DocparseTier.BASIC) {
|
||||
return basicParse(document);
|
||||
}
|
||||
}
|
||||
ParseDocumentRequest request =
|
||||
new ParseDocumentRequest(fileName(file), encodeBase64(file), withOcr);
|
||||
String responseJson =
|
||||
aiEngineClient.postLongRunning(
|
||||
PARSE_ENDPOINT, objectMapper.writeValueAsString(request), currentUserId());
|
||||
return objectMapper.readValue(responseJson, ParseDocumentResponse.class);
|
||||
}
|
||||
|
||||
public SmartSplitResponse split(MultipartFile file, String rule, int maxParts)
|
||||
throws IOException {
|
||||
requireEnabled();
|
||||
if (rule == null || rule.isBlank()) {
|
||||
throw new ResponseStatusException(HttpStatus.BAD_REQUEST, "A split rule is required");
|
||||
}
|
||||
List<AiPageText> pages;
|
||||
try (PDDocument document = pdfDocumentFactory.load(file, true)) {
|
||||
pages = extractPages(document);
|
||||
}
|
||||
SmartSplitRequest request =
|
||||
new SmartSplitRequest(fileName(file), rule, pages, Math.clamp(maxParts, 1, 500));
|
||||
String responseJson =
|
||||
aiEngineClient.post(
|
||||
SPLIT_ENDPOINT, objectMapper.writeValueAsString(request), currentUserId());
|
||||
return objectMapper.readValue(responseJson, SmartSplitResponse.class);
|
||||
}
|
||||
|
||||
public ChunkDocumentResponse chunk(
|
||||
MultipartFile file, int chunkSize, int overlap, DocparseMode mode) throws IOException {
|
||||
requireEnabled();
|
||||
List<AiPageText> pages;
|
||||
DocparseTier tier;
|
||||
try (PDDocument document = pdfDocumentFactory.load(file, true)) {
|
||||
pages = extractPages(document);
|
||||
tier =
|
||||
resolveTier(
|
||||
mode, capabilityService.capabilities(), false, looksScanned(document));
|
||||
}
|
||||
ChunkDocumentRequest request =
|
||||
new ChunkDocumentRequest(
|
||||
fileName(file),
|
||||
pages,
|
||||
tier == DocparseTier.ADVANCED ? encodeBase64(file) : null,
|
||||
Math.clamp(chunkSize, 64, 32_768),
|
||||
Math.clamp(overlap, 0, 4_096),
|
||||
toMode(tier));
|
||||
String responseJson =
|
||||
aiEngineClient.postLongRunning(
|
||||
CHUNK_ENDPOINT, objectMapper.writeValueAsString(request), currentUserId());
|
||||
return objectMapper.readValue(responseJson, ChunkDocumentResponse.class);
|
||||
}
|
||||
|
||||
/**
|
||||
* Chunk, embed, and index the document into the engine's RAG store, and/or echo the parsed
|
||||
* content back for corpus export. Text extraction and tier routing happen here; the engine
|
||||
* handles both basic (text-only) and advanced (layout) tiers.
|
||||
*/
|
||||
public RagIngestResponse ragIngest(
|
||||
MultipartFile file,
|
||||
String documentId,
|
||||
int chunkSize,
|
||||
int overlap,
|
||||
DocparseMode mode,
|
||||
boolean index,
|
||||
boolean includeMarkdown,
|
||||
boolean includeChunks)
|
||||
throws IOException {
|
||||
requireEnabled();
|
||||
if (!index && !includeMarkdown && !includeChunks) {
|
||||
throw new ResponseStatusException(
|
||||
HttpStatus.BAD_REQUEST,
|
||||
"Nothing to do: enable index, exportMarkdown, or exportChunksJsonl");
|
||||
}
|
||||
// Content hash default: re-ingesting identical bytes dedupes to the same document.
|
||||
String docId =
|
||||
(documentId == null || documentId.isBlank())
|
||||
? fileIdStrategy.idFor(file)
|
||||
: documentId.trim();
|
||||
List<AiPageText> pages;
|
||||
DocparseTier tier;
|
||||
try (PDDocument document = pdfDocumentFactory.load(file, true)) {
|
||||
tier =
|
||||
resolveTier(
|
||||
mode, capabilityService.capabilities(), false, looksScanned(document));
|
||||
// The advanced tier parses the raw file engine-side; extracting pages
|
||||
// too would double both the PDFBox work and the payload.
|
||||
pages = tier == DocparseTier.BASIC ? extractPages(document) : null;
|
||||
}
|
||||
String callerId = currentUserId();
|
||||
// Null expiresAt = persistent until explicit delete; ingest here is a deliberate
|
||||
// knowledge-base action, unlike the TTL'd auto-ingest in AiWorkflowService.
|
||||
RagIngestRequest request =
|
||||
new RagIngestRequest(
|
||||
fileName(file),
|
||||
docId,
|
||||
fileName(file),
|
||||
callerId,
|
||||
// Engine forbids an empty list here (min_length=1); null means
|
||||
// "default to the owner" on the engine side.
|
||||
callerId == null ? null : List.of(callerId),
|
||||
null,
|
||||
pages,
|
||||
tier == DocparseTier.ADVANCED ? encodeBase64(file) : null,
|
||||
Math.clamp(chunkSize, 64, 32_768),
|
||||
Math.clamp(overlap, 0, 4_096),
|
||||
toMode(tier),
|
||||
index,
|
||||
includeMarkdown,
|
||||
includeChunks);
|
||||
String responseJson =
|
||||
aiEngineClient.postLongRunning(
|
||||
RAG_INGEST_ENDPOINT, objectMapper.writeValueAsString(request), callerId);
|
||||
return objectMapper.readValue(responseJson, RagIngestResponse.class);
|
||||
}
|
||||
|
||||
/**
|
||||
* Resolve the tier that will serve a request. The settings mode wins when stricter: a settings
|
||||
* {@code basic} always forces basic, a settings {@code advanced} upgrades everything except an
|
||||
* explicit basic request. {@code auto} picks advanced only when the addon is installed and the
|
||||
* document actually needs it (scanned, or the operation needs layout).
|
||||
*/
|
||||
DocparseTier resolveTier(
|
||||
DocparseMode requested,
|
||||
DocparseCapabilities capability,
|
||||
boolean needsLayout,
|
||||
boolean looksScanned) {
|
||||
DocparseMode effective = effectiveMode(settingsMode(), requested);
|
||||
return switch (effective) {
|
||||
case BASIC -> DocparseTier.BASIC;
|
||||
case ADVANCED -> requireAdvanced(capability);
|
||||
case AUTO ->
|
||||
capability.advancedInstalled() && (looksScanned || needsLayout)
|
||||
? DocparseTier.ADVANCED
|
||||
: DocparseTier.BASIC;
|
||||
};
|
||||
}
|
||||
|
||||
/** Extract the fields described by a JSON Schema, with confidence and citations. */
|
||||
public ExtractFieldsResponse extractFields(
|
||||
MultipartFile file, String fieldsSchemaJson, DocparseMode mode, String instructions)
|
||||
throws IOException {
|
||||
requireEnabled();
|
||||
JsonNode schema = parseJsonObject(fieldsSchemaJson, "fieldsSchema");
|
||||
List<AiPageText> pages;
|
||||
DocparseTier tier;
|
||||
try (PDDocument document = pdfDocumentFactory.load(file, true)) {
|
||||
pages = extractPages(document);
|
||||
tier =
|
||||
resolveTier(
|
||||
mode, capabilityService.capabilities(), false, looksScanned(document));
|
||||
}
|
||||
ExtractFieldsRequest request =
|
||||
new ExtractFieldsRequest(
|
||||
fileName(file),
|
||||
schema,
|
||||
pages,
|
||||
tier == DocparseTier.ADVANCED ? encodeBase64(file) : null,
|
||||
toMode(tier),
|
||||
instructions);
|
||||
String responseJson =
|
||||
aiEngineClient.postLongRunning(
|
||||
EXTRACT_ENDPOINT,
|
||||
objectMapper.writeValueAsString(request),
|
||||
currentUserId());
|
||||
return objectMapper.readValue(responseJson, ExtractFieldsResponse.class);
|
||||
}
|
||||
|
||||
/** Propose an extraction schema from the document's first pages. */
|
||||
public SuggestSchemaResponse suggestSchema(MultipartFile file, int maxFields)
|
||||
throws IOException {
|
||||
requireEnabled();
|
||||
List<AiPageText> pages;
|
||||
DocparseTier tier;
|
||||
try (PDDocument document = pdfDocumentFactory.load(file, true)) {
|
||||
pages = extractPages(document);
|
||||
tier =
|
||||
resolveTier(
|
||||
DocparseMode.AUTO,
|
||||
capabilityService.capabilities(),
|
||||
false,
|
||||
looksScanned(document));
|
||||
}
|
||||
SuggestSchemaRequest request =
|
||||
new SuggestSchemaRequest(
|
||||
fileName(file),
|
||||
pages,
|
||||
tier == DocparseTier.ADVANCED ? encodeBase64(file) : null,
|
||||
Math.clamp(maxFields, 1, 20));
|
||||
String responseJson =
|
||||
aiEngineClient.postLongRunning(
|
||||
SUGGEST_SCHEMA_ENDPOINT,
|
||||
objectMapper.writeValueAsString(request),
|
||||
currentUserId());
|
||||
return objectMapper.readValue(responseJson, SuggestSchemaResponse.class);
|
||||
}
|
||||
|
||||
private JsonNode parseJsonObject(String json, String fieldName) {
|
||||
if (json == null || json.isBlank()) {
|
||||
throw new ResponseStatusException(
|
||||
HttpStatus.BAD_REQUEST, "'" + fieldName + "' is required");
|
||||
}
|
||||
JsonNode node;
|
||||
try {
|
||||
node = objectMapper.readTree(json);
|
||||
} catch (Exception e) {
|
||||
throw new ResponseStatusException(
|
||||
HttpStatus.BAD_REQUEST, "'" + fieldName + "' is not valid JSON");
|
||||
}
|
||||
if (!node.isObject()) {
|
||||
throw new ResponseStatusException(
|
||||
HttpStatus.BAD_REQUEST, "'" + fieldName + "' must be a JSON object");
|
||||
}
|
||||
return node;
|
||||
}
|
||||
|
||||
private static void requireNonBlank(String value, String fieldName) {
|
||||
if (value == null || value.isBlank()) {
|
||||
throw new ResponseStatusException(
|
||||
HttpStatus.BAD_REQUEST, "'" + fieldName + "' is required");
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* The settings mode wins when stricter: a settings {@code basic} always forces basic, a
|
||||
* settings {@code advanced} upgrades everything except an explicit basic request.
|
||||
*/
|
||||
static DocparseMode effectiveMode(DocparseMode settings, DocparseMode requested) {
|
||||
DocparseMode request = requested == null ? DocparseMode.AUTO : requested;
|
||||
if (settings == DocparseMode.BASIC) {
|
||||
return DocparseMode.BASIC;
|
||||
}
|
||||
if (settings == DocparseMode.ADVANCED) {
|
||||
return request == DocparseMode.BASIC ? DocparseMode.BASIC : DocparseMode.ADVANCED;
|
||||
}
|
||||
return request;
|
||||
}
|
||||
|
||||
/** True when the sampled average of extractable chars per page falls below the threshold. */
|
||||
boolean looksScanned(PDDocument document) throws IOException {
|
||||
int pageCount = document.getNumberOfPages();
|
||||
if (pageCount == 0) {
|
||||
return false;
|
||||
}
|
||||
int sampled = Math.min(pageCount, SCANNED_SAMPLE_PAGES);
|
||||
long totalChars = 0;
|
||||
for (int page = 1; page <= sampled; page++) {
|
||||
String text = pdfContentExtractor.extractPageTextRaw(document, page);
|
||||
totalChars += text == null ? 0 : text.length();
|
||||
}
|
||||
return (totalChars / sampled) < SCANNED_AVG_CHARS_PER_PAGE;
|
||||
}
|
||||
|
||||
private DocparseTier requireAdvanced(DocparseCapabilities capability) {
|
||||
if (!capability.advancedInstalled()) {
|
||||
throw new ResponseStatusException(
|
||||
HttpStatus.NOT_IMPLEMENTED,
|
||||
"The advanced DocParse tier requires the docparse addon"
|
||||
+ " (addonRequired=docparse); install it or use mode=basic");
|
||||
}
|
||||
return DocparseTier.ADVANCED;
|
||||
}
|
||||
|
||||
private static DocparseMode toMode(DocparseTier tier) {
|
||||
return tier == DocparseTier.ADVANCED ? DocparseMode.ADVANCED : DocparseMode.BASIC;
|
||||
}
|
||||
|
||||
private static String encodeBase64(MultipartFile file) throws IOException {
|
||||
return Base64.getEncoder().encodeToString(file.getBytes());
|
||||
}
|
||||
|
||||
public ExtractTablesResponse tables(MultipartFile file) throws IOException {
|
||||
requireEnabled();
|
||||
// Tables need layout, so a forced-advanced setting without the addon must 501 here
|
||||
// rather than let the engine silently fall back; the engine picks the tier otherwise.
|
||||
resolveTier(DocparseMode.AUTO, capabilityService.capabilities(), true, false);
|
||||
ExtractTablesRequest request = new ExtractTablesRequest(fileName(file), encodeBase64(file));
|
||||
String responseJson =
|
||||
aiEngineClient.postLongRunning(
|
||||
TABLES_ENDPOINT, objectMapper.writeValueAsString(request), currentUserId());
|
||||
return objectMapper.readValue(responseJson, ExtractTablesResponse.class);
|
||||
}
|
||||
|
||||
public FillDocxResponse fillDocx(MultipartFile templateFile, String dataJson)
|
||||
throws IOException {
|
||||
requireEnabled();
|
||||
JsonNode data = parseJsonObject(dataJson, "data");
|
||||
FillDocxRequest request =
|
||||
new FillDocxRequest(
|
||||
Base64.getEncoder().encodeToString(templateFile.getBytes()), data);
|
||||
String responseJson =
|
||||
aiEngineClient.post(
|
||||
FILL_DOCX_ENDPOINT,
|
||||
objectMapper.writeValueAsString(request),
|
||||
currentUserId());
|
||||
return objectMapper.readValue(responseJson, FillDocxResponse.class);
|
||||
}
|
||||
|
||||
/** Basic tier parse: PDFBox text layer only, one paragraph block per non-blank page. */
|
||||
ParseDocumentResponse basicParse(PDDocument document) throws IOException {
|
||||
int pageCount = document.getNumberOfPages();
|
||||
List<DocBlock> blocks = new ArrayList<>();
|
||||
StringBuilder markdown = new StringBuilder();
|
||||
for (int page = 1; page <= pageCount; page++) {
|
||||
String text = pdfContentExtractor.extractPageTextRaw(document, page);
|
||||
if (text == null || text.isBlank()) {
|
||||
continue;
|
||||
}
|
||||
blocks.add(new DocBlock("paragraph", text, page, null, null));
|
||||
if (!markdown.isEmpty()) {
|
||||
markdown.append("\n\n");
|
||||
}
|
||||
markdown.append(text);
|
||||
}
|
||||
return new ParseDocumentResponse(
|
||||
DocparseTier.BASIC, pageCount, blocks, List.of(), markdown.toString(), false);
|
||||
}
|
||||
|
||||
/** Extract per-page text for the engine, capped by the shared aiEngine limits. */
|
||||
List<AiPageText> extractPages(PDDocument document) throws IOException {
|
||||
ApplicationProperties.AiEngine.Limits limits =
|
||||
applicationProperties.getAiEngine().getLimits();
|
||||
int maxPages = Math.min(document.getNumberOfPages(), limits.getMaxPages());
|
||||
int remainingCharacters = limits.getMaxCharacters();
|
||||
List<AiPageText> pages = new ArrayList<>();
|
||||
for (int page = 1; page <= maxPages && remainingCharacters > 0; page++) {
|
||||
String text = pdfContentExtractor.extractPageTextRaw(document, page);
|
||||
if (text == null || text.isBlank()) {
|
||||
continue;
|
||||
}
|
||||
if (text.length() > remainingCharacters) {
|
||||
text = text.substring(0, remainingCharacters);
|
||||
}
|
||||
pages.add(new AiPageText(page, text));
|
||||
remainingCharacters -= text.length();
|
||||
}
|
||||
return pages;
|
||||
}
|
||||
|
||||
private DocparseMode settingsMode() {
|
||||
try {
|
||||
return DocparseMode.fromWire(applicationProperties.getDocparse().getMode());
|
||||
} catch (IllegalArgumentException e) {
|
||||
log.warn(
|
||||
"Unknown docparse.mode '{}'; falling back to auto",
|
||||
applicationProperties.getDocparse().getMode());
|
||||
return DocparseMode.AUTO;
|
||||
}
|
||||
}
|
||||
|
||||
public static String fileName(MultipartFile file) {
|
||||
String name = Filenames.toSimpleFileName(file.getOriginalFilename());
|
||||
return (name == null || name.isBlank()) ? "document.pdf" : name;
|
||||
}
|
||||
|
||||
private String currentUserId() {
|
||||
return userService != null ? userService.getCurrentUsername() : null;
|
||||
}
|
||||
}
|
||||
+123
@@ -0,0 +1,123 @@
|
||||
package stirling.software.proprietary.service;
|
||||
|
||||
import java.time.Duration;
|
||||
import java.time.Instant;
|
||||
import java.util.concurrent.atomic.AtomicBoolean;
|
||||
|
||||
import org.springframework.stereotype.Service;
|
||||
|
||||
import lombok.RequiredArgsConstructor;
|
||||
import lombok.extern.slf4j.Slf4j;
|
||||
|
||||
import stirling.software.common.model.ApplicationProperties;
|
||||
import stirling.software.common.service.DocparseCapabilityServiceInterface;
|
||||
import stirling.software.proprietary.model.docparse.DocparseCapabilities;
|
||||
|
||||
import tools.jackson.databind.ObjectMapper;
|
||||
|
||||
/**
|
||||
* Probes the engine's {@code GET /api/v1/docparse/capabilities} and caches the answer for 5
|
||||
* minutes. Reports "addon absent" when the AI engine is disabled or the probe fails, so callers can
|
||||
* always route to the basic tier without special-casing errors.
|
||||
*/
|
||||
@Slf4j
|
||||
@Service
|
||||
@RequiredArgsConstructor
|
||||
public class DocparseCapabilityService implements DocparseCapabilityServiceInterface {
|
||||
|
||||
private static final String CAPABILITIES_ENDPOINT = "/api/v1/docparse/capabilities";
|
||||
private static final Duration CACHE_TTL = Duration.ofMinutes(5);
|
||||
|
||||
private final AiEngineClient aiEngineClient;
|
||||
private final ApplicationProperties applicationProperties;
|
||||
private final ObjectMapper objectMapper;
|
||||
|
||||
private record Snapshot(
|
||||
DocparseCapabilities capabilities, boolean engineReachable, Instant fetchedAt) {}
|
||||
|
||||
private volatile Snapshot snapshot;
|
||||
private final AtomicBoolean refreshing = new AtomicBoolean();
|
||||
|
||||
/** The cached capabilities, refreshed synchronously when stale. */
|
||||
public DocparseCapabilities capabilities() {
|
||||
return freshSnapshot().capabilities();
|
||||
}
|
||||
|
||||
/** Whether the last capability probe reached the engine. */
|
||||
public boolean isEngineReachable() {
|
||||
Snapshot current = snapshot;
|
||||
return current != null && current.engineReachable();
|
||||
}
|
||||
|
||||
/** {@code refresh(true)} bypasses the cache and re-probes the engine now. */
|
||||
public DocparseCapabilities refresh(boolean force) {
|
||||
if (!force) {
|
||||
return capabilities();
|
||||
}
|
||||
Snapshot fresh = fetch();
|
||||
snapshot = fresh;
|
||||
return fresh.capabilities();
|
||||
}
|
||||
|
||||
/**
|
||||
* Non-blocking read for app-config: returns the last known value and kicks off a background
|
||||
* refresh when stale, so a slow/unreachable engine never delays page load.
|
||||
*/
|
||||
@Override
|
||||
public boolean isAdvancedInstalled() {
|
||||
Snapshot current = snapshot;
|
||||
if (current == null || isStale(current)) {
|
||||
triggerAsyncRefresh();
|
||||
}
|
||||
return current != null && current.capabilities().advancedInstalled();
|
||||
}
|
||||
|
||||
private Snapshot freshSnapshot() {
|
||||
Snapshot current = snapshot;
|
||||
if (current != null && !isStale(current)) {
|
||||
return current;
|
||||
}
|
||||
Snapshot fresh = fetch();
|
||||
snapshot = fresh;
|
||||
return fresh;
|
||||
}
|
||||
|
||||
private void triggerAsyncRefresh() {
|
||||
if (!refreshing.compareAndSet(false, true)) {
|
||||
return;
|
||||
}
|
||||
Thread.ofVirtual()
|
||||
.name("docparse-capability-refresh")
|
||||
.start(
|
||||
() -> {
|
||||
try {
|
||||
snapshot = fetch();
|
||||
} finally {
|
||||
refreshing.set(false);
|
||||
}
|
||||
});
|
||||
}
|
||||
|
||||
private Snapshot fetch() {
|
||||
if (!applicationProperties.getAiEngine().isEnabled()) {
|
||||
return new Snapshot(
|
||||
DocparseCapabilities.absent("AI engine is disabled"), false, Instant.now());
|
||||
}
|
||||
try {
|
||||
String json = aiEngineClient.get(CAPABILITIES_ENDPOINT, null);
|
||||
DocparseCapabilities capabilities =
|
||||
objectMapper.readValue(json, DocparseCapabilities.class);
|
||||
return new Snapshot(capabilities, true, Instant.now());
|
||||
} catch (Exception e) {
|
||||
log.debug("DocParse capability probe failed: {}", e.getMessage());
|
||||
return new Snapshot(
|
||||
DocparseCapabilities.absent("Capability probe failed: " + e.getMessage()),
|
||||
false,
|
||||
Instant.now());
|
||||
}
|
||||
}
|
||||
|
||||
private static boolean isStale(Snapshot current) {
|
||||
return current.fetchedAt().plus(CACHE_TTL).isBefore(Instant.now());
|
||||
}
|
||||
}
|
||||
+93
@@ -0,0 +1,93 @@
|
||||
package stirling.software.proprietary.model.docparse;
|
||||
|
||||
import static org.junit.jupiter.api.Assertions.assertEquals;
|
||||
import static org.junit.jupiter.api.Assertions.assertFalse;
|
||||
import static org.junit.jupiter.api.Assertions.assertNull;
|
||||
import static org.junit.jupiter.api.Assertions.assertTrue;
|
||||
|
||||
import java.util.List;
|
||||
|
||||
import org.junit.jupiter.api.Test;
|
||||
|
||||
import stirling.software.proprietary.model.api.ai.AiPageText;
|
||||
|
||||
import tools.jackson.databind.JsonNode;
|
||||
import tools.jackson.databind.json.JsonMapper;
|
||||
|
||||
/**
|
||||
* The Java DTOs must serialize to exactly the camelCase wire shapes defined in {@code
|
||||
* engine/src/stirling/contracts/docparse.py}; a drift here breaks ingestion silently.
|
||||
*/
|
||||
class DocparseWireContractTest {
|
||||
|
||||
private final JsonMapper mapper = JsonMapper.builder().build();
|
||||
|
||||
@Test
|
||||
void ragIngestRequestSerializesTheEngineContract() {
|
||||
RagIngestRequest request =
|
||||
new RagIngestRequest(
|
||||
"report.pdf",
|
||||
"doc-1",
|
||||
"report.pdf",
|
||||
"user:alice",
|
||||
List.of("user:alice"),
|
||||
null,
|
||||
List.of(new AiPageText(1, "hello")),
|
||||
null,
|
||||
512,
|
||||
64,
|
||||
DocparseMode.AUTO,
|
||||
true,
|
||||
false,
|
||||
true);
|
||||
JsonNode json = mapper.readTree(mapper.writeValueAsString(request));
|
||||
assertEquals("report.pdf", json.get("fileName").asText());
|
||||
assertEquals("doc-1", json.get("documentId").asText());
|
||||
assertEquals("user:alice", json.get("ownerId").asText());
|
||||
assertEquals("user:alice", json.get("readPrincipals").get(0).asText());
|
||||
assertEquals(1, json.get("pages").get(0).get("pageNumber").asInt());
|
||||
assertEquals("hello", json.get("pages").get(0).get("text").asText());
|
||||
assertEquals(512, json.get("chunkSize").asInt());
|
||||
assertEquals(64, json.get("overlap").asInt());
|
||||
assertEquals("auto", json.get("mode").asText());
|
||||
assertTrue(json.get("index").asBoolean());
|
||||
assertFalse(json.get("includeMarkdown").asBoolean());
|
||||
assertTrue(json.get("includeChunks").asBoolean());
|
||||
}
|
||||
|
||||
@Test
|
||||
void ragIngestResponseReadsTheEngineShapeIncludingEchoedContent() {
|
||||
String engineJson =
|
||||
"{\"mode\":\"basic\",\"documentId\":\"doc-1\",\"chunksIndexed\":2,\"pages\":3,"
|
||||
+ "\"markdown\":\"# Title\",\"chunks\":[{\"index\":0,\"text\":\"t\","
|
||||
+ "\"pageStart\":1,\"pageEnd\":2,\"headingPath\":[\"Intro\"]}]}";
|
||||
RagIngestResponse response = mapper.readValue(engineJson, RagIngestResponse.class);
|
||||
assertEquals(DocparseTier.BASIC, response.mode());
|
||||
assertEquals("doc-1", response.documentId());
|
||||
assertEquals(2, response.chunksIndexed());
|
||||
assertEquals(3, response.pages());
|
||||
assertEquals("# Title", response.markdown());
|
||||
assertEquals(1, response.chunks().size());
|
||||
assertEquals(List.of("Intro"), response.chunks().get(0).headingPath());
|
||||
}
|
||||
|
||||
@Test
|
||||
void ragIngestResponseToleratesAbsentEchoFields() {
|
||||
String engineJson =
|
||||
"{\"mode\":\"basic\",\"documentId\":\"d\",\"chunksIndexed\":0,\"pages\":1}";
|
||||
RagIngestResponse response = mapper.readValue(engineJson, RagIngestResponse.class);
|
||||
assertNull(response.markdown());
|
||||
assertNull(response.chunks());
|
||||
}
|
||||
|
||||
@Test
|
||||
void capabilitiesReadTheEngineProbeShape() {
|
||||
String engineJson =
|
||||
"{\"advancedInstalled\":false,\"doclingVersion\":null,\"torchVersion\":null,"
|
||||
+ "\"modelsAvailable\":false,\"modelsPath\":null,\"errors\":[\"missing\"]}";
|
||||
DocparseCapabilities capabilities =
|
||||
mapper.readValue(engineJson, DocparseCapabilities.class);
|
||||
assertFalse(capabilities.advancedInstalled());
|
||||
assertEquals(List.of("missing"), capabilities.errors());
|
||||
}
|
||||
}
|
||||
+78
@@ -0,0 +1,78 @@
|
||||
package stirling.software.proprietary.security.filter;
|
||||
|
||||
import static org.junit.jupiter.api.Assertions.assertEquals;
|
||||
import static org.junit.jupiter.api.Assertions.assertNull;
|
||||
|
||||
import org.junit.jupiter.api.AfterEach;
|
||||
import org.junit.jupiter.api.Test;
|
||||
import org.slf4j.MDC;
|
||||
import org.springframework.mock.web.MockHttpServletRequest;
|
||||
import org.springframework.mock.web.MockHttpServletResponse;
|
||||
import org.springframework.security.authentication.AnonymousAuthenticationToken;
|
||||
import org.springframework.security.authentication.UsernamePasswordAuthenticationToken;
|
||||
import org.springframework.security.core.authority.AuthorityUtils;
|
||||
import org.springframework.security.core.context.SecurityContextHolder;
|
||||
|
||||
class PrincipalMdcFilterTest {
|
||||
|
||||
private final PrincipalMdcFilter filter = new PrincipalMdcFilter();
|
||||
|
||||
@AfterEach
|
||||
void cleanUp() {
|
||||
SecurityContextHolder.clearContext();
|
||||
MDC.remove(PrincipalMdcFilter.MDC_KEY);
|
||||
}
|
||||
|
||||
@Test
|
||||
void stampsAuthenticatedPrincipalDuringTheChainAndClearsAfter() throws Exception {
|
||||
SecurityContextHolder.getContext()
|
||||
.setAuthentication(
|
||||
new UsernamePasswordAuthenticationToken(
|
||||
"alice", "n/a", AuthorityUtils.createAuthorityList("ROLE_USER")));
|
||||
String[] seen = new String[1];
|
||||
|
||||
filter.doFilter(
|
||||
new MockHttpServletRequest(),
|
||||
new MockHttpServletResponse(),
|
||||
(req, res) -> seen[0] = MDC.get(PrincipalMdcFilter.MDC_KEY));
|
||||
|
||||
assertEquals("alice", seen[0]);
|
||||
assertNull(MDC.get(PrincipalMdcFilter.MDC_KEY));
|
||||
}
|
||||
|
||||
@Test
|
||||
void anonymousRequestsAreNotStamped() throws Exception {
|
||||
SecurityContextHolder.getContext()
|
||||
.setAuthentication(
|
||||
new AnonymousAuthenticationToken(
|
||||
"key",
|
||||
"anonymousUser",
|
||||
AuthorityUtils.createAuthorityList("ROLE_ANONYMOUS")));
|
||||
String[] seen = new String[] {"sentinel"};
|
||||
|
||||
filter.doFilter(
|
||||
new MockHttpServletRequest(),
|
||||
new MockHttpServletResponse(),
|
||||
(req, res) -> seen[0] = MDC.get(PrincipalMdcFilter.MDC_KEY));
|
||||
|
||||
assertNull(seen[0]);
|
||||
}
|
||||
|
||||
@Test
|
||||
void existingMdcPrincipalIsLeftUntouched() throws Exception {
|
||||
MDC.put(PrincipalMdcFilter.MDC_KEY, "policy-run-owner");
|
||||
SecurityContextHolder.getContext()
|
||||
.setAuthentication(
|
||||
new UsernamePasswordAuthenticationToken(
|
||||
"alice", "n/a", AuthorityUtils.createAuthorityList("ROLE_USER")));
|
||||
String[] seen = new String[1];
|
||||
|
||||
filter.doFilter(
|
||||
new MockHttpServletRequest(),
|
||||
new MockHttpServletResponse(),
|
||||
(req, res) -> seen[0] = MDC.get(PrincipalMdcFilter.MDC_KEY));
|
||||
|
||||
assertEquals("policy-run-owner", seen[0]);
|
||||
assertEquals("policy-run-owner", MDC.get(PrincipalMdcFilter.MDC_KEY));
|
||||
}
|
||||
}
|
||||
+377
@@ -0,0 +1,377 @@
|
||||
package stirling.software.proprietary.service;
|
||||
|
||||
import static org.junit.jupiter.api.Assertions.assertEquals;
|
||||
import static org.junit.jupiter.api.Assertions.assertFalse;
|
||||
import static org.junit.jupiter.api.Assertions.assertThrows;
|
||||
import static org.junit.jupiter.api.Assertions.assertTrue;
|
||||
import static org.mockito.ArgumentMatchers.any;
|
||||
import static org.mockito.ArgumentMatchers.anyBoolean;
|
||||
import static org.mockito.ArgumentMatchers.anyInt;
|
||||
import static org.mockito.ArgumentMatchers.eq;
|
||||
import static org.mockito.ArgumentMatchers.isNull;
|
||||
import static org.mockito.Mockito.verifyNoInteractions;
|
||||
import static org.mockito.Mockito.when;
|
||||
|
||||
import java.io.IOException;
|
||||
import java.util.List;
|
||||
|
||||
import org.apache.pdfbox.pdmodel.PDDocument;
|
||||
import org.apache.pdfbox.pdmodel.PDPage;
|
||||
import org.junit.jupiter.api.BeforeEach;
|
||||
import org.junit.jupiter.api.Test;
|
||||
import org.junit.jupiter.api.extension.ExtendWith;
|
||||
import org.mockito.ArgumentCaptor;
|
||||
import org.mockito.Mock;
|
||||
import org.mockito.junit.jupiter.MockitoExtension;
|
||||
import org.springframework.http.HttpStatus;
|
||||
import org.springframework.mock.web.MockMultipartFile;
|
||||
import org.springframework.web.multipart.MultipartFile;
|
||||
import org.springframework.web.server.ResponseStatusException;
|
||||
|
||||
import stirling.software.common.model.ApplicationProperties;
|
||||
import stirling.software.common.service.CustomPDFDocumentFactory;
|
||||
import stirling.software.proprietary.model.docparse.DocparseCapabilities;
|
||||
import stirling.software.proprietary.model.docparse.DocparseMode;
|
||||
import stirling.software.proprietary.model.docparse.DocparseTier;
|
||||
import stirling.software.proprietary.model.docparse.RagIngestResponse;
|
||||
|
||||
import tools.jackson.databind.JsonNode;
|
||||
import tools.jackson.databind.json.JsonMapper;
|
||||
|
||||
/** Wire-building and mode capping for the ingestion path. */
|
||||
@ExtendWith(MockitoExtension.class)
|
||||
class DocParseServiceTest {
|
||||
|
||||
private static final String ENGINE_RESPONSE =
|
||||
"{\"mode\":\"basic\",\"documentId\":\"doc-1\",\"chunksIndexed\":3,\"pages\":2,"
|
||||
+ "\"markdown\":null,\"chunks\":null}";
|
||||
|
||||
@Mock private AiEngineClient aiEngineClient;
|
||||
@Mock private DocparseCapabilityService capabilityService;
|
||||
@Mock private CustomPDFDocumentFactory pdfDocumentFactory;
|
||||
@Mock private PdfContentExtractor pdfContentExtractor;
|
||||
@Mock private FileIdStrategy fileIdStrategy;
|
||||
|
||||
private ApplicationProperties properties;
|
||||
private DocParseService service;
|
||||
private final JsonMapper jsonMapper = JsonMapper.builder().build();
|
||||
|
||||
@BeforeEach
|
||||
void setUp() {
|
||||
properties = new ApplicationProperties();
|
||||
service =
|
||||
new DocParseService(
|
||||
aiEngineClient,
|
||||
capabilityService,
|
||||
pdfDocumentFactory,
|
||||
pdfContentExtractor,
|
||||
properties,
|
||||
jsonMapper,
|
||||
fileIdStrategy,
|
||||
null);
|
||||
}
|
||||
|
||||
// --- effectiveMode: the settings mode wins when stricter ---
|
||||
|
||||
@Test
|
||||
void settingsBasicForcesBasic() {
|
||||
assertEquals(
|
||||
DocparseMode.BASIC,
|
||||
DocParseService.effectiveMode(DocparseMode.BASIC, DocparseMode.ADVANCED));
|
||||
assertEquals(
|
||||
DocparseMode.BASIC,
|
||||
DocParseService.effectiveMode(DocparseMode.BASIC, DocparseMode.AUTO));
|
||||
}
|
||||
|
||||
@Test
|
||||
void settingsAdvancedUpgradesAutoButRespectsExplicitBasic() {
|
||||
assertEquals(
|
||||
DocparseMode.ADVANCED,
|
||||
DocParseService.effectiveMode(DocparseMode.ADVANCED, DocparseMode.AUTO));
|
||||
assertEquals(
|
||||
DocparseMode.BASIC,
|
||||
DocParseService.effectiveMode(DocparseMode.ADVANCED, DocparseMode.BASIC));
|
||||
}
|
||||
|
||||
@Test
|
||||
void settingsAutoPassesRequestThroughAndNullMeansAuto() {
|
||||
assertEquals(
|
||||
DocparseMode.ADVANCED,
|
||||
DocParseService.effectiveMode(DocparseMode.AUTO, DocparseMode.ADVANCED));
|
||||
assertEquals(DocparseMode.AUTO, DocParseService.effectiveMode(DocparseMode.AUTO, null));
|
||||
}
|
||||
|
||||
// --- ragIngest wire building ---
|
||||
|
||||
private MultipartFile pdfFile() {
|
||||
return new MockMultipartFile("fileInput", "invoice.pdf", "application/pdf", new byte[] {1});
|
||||
}
|
||||
|
||||
private JsonNode ingestAndCaptureRequest(
|
||||
String documentId, boolean index, boolean markdown, boolean chunks) throws IOException {
|
||||
try (PDDocument document = new PDDocument()) {
|
||||
document.addPage(new PDPage());
|
||||
document.addPage(new PDPage());
|
||||
when(pdfDocumentFactory.load(any(MultipartFile.class), anyBoolean()))
|
||||
.thenReturn(document);
|
||||
when(pdfContentExtractor.extractPageTextRaw(any(), eq(1))).thenReturn("page one");
|
||||
when(pdfContentExtractor.extractPageTextRaw(any(), eq(2))).thenReturn("page two");
|
||||
when(capabilityService.capabilities()).thenReturn(absent());
|
||||
ArgumentCaptor<String> body = ArgumentCaptor.forClass(String.class);
|
||||
when(aiEngineClient.postLongRunning(
|
||||
eq("/api/v1/docparse/rag-ingest"), body.capture(), isNull()))
|
||||
.thenReturn(ENGINE_RESPONSE);
|
||||
|
||||
RagIngestResponse response =
|
||||
service.ragIngest(
|
||||
pdfFile(),
|
||||
documentId,
|
||||
512,
|
||||
64,
|
||||
DocparseMode.AUTO,
|
||||
index,
|
||||
markdown,
|
||||
chunks);
|
||||
assertEquals(3, response.chunksIndexed());
|
||||
return jsonMapper.readTree(body.getValue());
|
||||
}
|
||||
}
|
||||
|
||||
@Test
|
||||
void ragIngestExtractsPagesAndSendsTheWireContract() throws IOException {
|
||||
JsonNode request = ingestAndCaptureRequest("doc-1", true, false, false);
|
||||
assertEquals("invoice.pdf", request.get("fileName").asText());
|
||||
assertEquals("doc-1", request.get("documentId").asText());
|
||||
// AUTO resolves to a concrete tier before the wire; without the addon that is basic.
|
||||
assertEquals("basic", request.get("mode").asText());
|
||||
assertEquals(2, request.get("pages").size());
|
||||
assertEquals("page one", request.get("pages").get(0).get("text").asText());
|
||||
assertEquals(512, request.get("chunkSize").asInt());
|
||||
assertEquals(64, request.get("overlap").asInt());
|
||||
assertTrue(request.get("index").asBoolean());
|
||||
assertFalse(request.get("includeMarkdown").asBoolean());
|
||||
assertFalse(request.get("includeChunks").asBoolean());
|
||||
}
|
||||
|
||||
@Test
|
||||
void ragIngestDefaultsDocumentIdToContentHash() throws IOException {
|
||||
when(fileIdStrategy.idFor(any(MultipartFile.class))).thenReturn("sha-abc");
|
||||
JsonNode request = ingestAndCaptureRequest(" ", true, false, false);
|
||||
assertEquals("sha-abc", request.get("documentId").asText());
|
||||
}
|
||||
|
||||
@Test
|
||||
void ragIngestForwardsExportFlags() throws IOException {
|
||||
JsonNode request = ingestAndCaptureRequest("doc-1", false, true, true);
|
||||
assertFalse(request.get("index").asBoolean());
|
||||
assertTrue(request.get("includeMarkdown").asBoolean());
|
||||
assertTrue(request.get("includeChunks").asBoolean());
|
||||
}
|
||||
|
||||
@Test
|
||||
void ragIngestSettingsBasicCapsTheWireMode() throws IOException {
|
||||
properties.getDocparse().setMode("basic");
|
||||
JsonNode request = ingestAndCaptureRequest("doc-1", true, false, false);
|
||||
assertEquals("basic", request.get("mode").asText());
|
||||
}
|
||||
|
||||
@Test
|
||||
void ragIngestWithNothingToDoIs400() {
|
||||
ResponseStatusException error =
|
||||
assertThrows(
|
||||
ResponseStatusException.class,
|
||||
() ->
|
||||
service.ragIngest(
|
||||
pdfFile(),
|
||||
"doc",
|
||||
512,
|
||||
64,
|
||||
DocparseMode.AUTO,
|
||||
false,
|
||||
false,
|
||||
false));
|
||||
assertEquals(HttpStatus.BAD_REQUEST, error.getStatusCode());
|
||||
verifyNoInteractions(aiEngineClient);
|
||||
}
|
||||
|
||||
@Test
|
||||
void ragIngestWhenDisabledIs503() {
|
||||
properties.getDocparse().setEnabled(false);
|
||||
ResponseStatusException error =
|
||||
assertThrows(
|
||||
ResponseStatusException.class,
|
||||
() ->
|
||||
service.ragIngest(
|
||||
pdfFile(),
|
||||
"doc",
|
||||
512,
|
||||
64,
|
||||
DocparseMode.AUTO,
|
||||
true,
|
||||
false,
|
||||
false));
|
||||
assertEquals(HttpStatus.SERVICE_UNAVAILABLE, error.getStatusCode());
|
||||
verifyNoInteractions(aiEngineClient);
|
||||
}
|
||||
|
||||
// --- tier resolution: auto and explicit requests ---
|
||||
|
||||
private DocparseCapabilities installed() {
|
||||
return new DocparseCapabilities(true, "2.55.0", "2.6.0", true, "/models", List.of());
|
||||
}
|
||||
|
||||
private DocparseCapabilities absent() {
|
||||
return new DocparseCapabilities(false, null, null, false, null, List.of());
|
||||
}
|
||||
|
||||
private void settingsMode(String mode) {
|
||||
properties.getDocparse().setMode(mode);
|
||||
}
|
||||
|
||||
@Test
|
||||
void autoPicksAdvancedWhenScannedAndInstalled() {
|
||||
settingsMode("auto");
|
||||
assertEquals(
|
||||
DocparseTier.ADVANCED,
|
||||
service.resolveTier(DocparseMode.AUTO, installed(), false, true));
|
||||
}
|
||||
|
||||
@Test
|
||||
void autoPicksAdvancedWhenLayoutNeededAndInstalled() {
|
||||
settingsMode("auto");
|
||||
assertEquals(
|
||||
DocparseTier.ADVANCED,
|
||||
service.resolveTier(DocparseMode.AUTO, installed(), true, false));
|
||||
}
|
||||
|
||||
@Test
|
||||
void autoPicksBasicForBornDigitalDocument() {
|
||||
settingsMode("auto");
|
||||
assertEquals(
|
||||
DocparseTier.BASIC,
|
||||
service.resolveTier(DocparseMode.AUTO, installed(), false, false));
|
||||
}
|
||||
|
||||
@Test
|
||||
void autoPicksBasicWhenAddonMissingEvenIfScanned() {
|
||||
settingsMode("auto");
|
||||
assertEquals(
|
||||
DocparseTier.BASIC, service.resolveTier(DocparseMode.AUTO, absent(), false, true));
|
||||
}
|
||||
|
||||
@Test
|
||||
void explicitBasicRequestAlwaysBasic() {
|
||||
settingsMode("auto");
|
||||
assertEquals(
|
||||
DocparseTier.BASIC,
|
||||
service.resolveTier(DocparseMode.BASIC, installed(), true, true));
|
||||
}
|
||||
|
||||
@Test
|
||||
void explicitAdvancedRequestUsesAdvancedWhenInstalled() {
|
||||
settingsMode("auto");
|
||||
assertEquals(
|
||||
DocparseTier.ADVANCED,
|
||||
service.resolveTier(DocparseMode.ADVANCED, installed(), false, false));
|
||||
}
|
||||
|
||||
@Test
|
||||
void explicitAdvancedRequestWithoutAddonReturns501() {
|
||||
settingsMode("auto");
|
||||
ResponseStatusException e =
|
||||
assertThrows(
|
||||
ResponseStatusException.class,
|
||||
() -> service.resolveTier(DocparseMode.ADVANCED, absent(), false, false));
|
||||
assertEquals(HttpStatus.NOT_IMPLEMENTED, e.getStatusCode());
|
||||
}
|
||||
|
||||
@Test
|
||||
void settingsBasicOverridesAdvancedRequest() {
|
||||
settingsMode("basic");
|
||||
assertEquals(
|
||||
DocparseTier.BASIC,
|
||||
service.resolveTier(DocparseMode.ADVANCED, installed(), true, true));
|
||||
}
|
||||
|
||||
@Test
|
||||
void settingsAdvancedUpgradesAutoRequest() {
|
||||
settingsMode("advanced");
|
||||
assertEquals(
|
||||
DocparseTier.ADVANCED,
|
||||
service.resolveTier(DocparseMode.AUTO, installed(), false, false));
|
||||
}
|
||||
|
||||
@Test
|
||||
void settingsAdvancedHonoursStricterBasicRequest() {
|
||||
settingsMode("advanced");
|
||||
assertEquals(
|
||||
DocparseTier.BASIC,
|
||||
service.resolveTier(DocparseMode.BASIC, installed(), false, false));
|
||||
}
|
||||
|
||||
@Test
|
||||
void settingsAdvancedWithoutAddonReturns501() {
|
||||
settingsMode("advanced");
|
||||
ResponseStatusException e =
|
||||
assertThrows(
|
||||
ResponseStatusException.class,
|
||||
() -> service.resolveTier(DocparseMode.AUTO, absent(), false, false));
|
||||
assertEquals(HttpStatus.NOT_IMPLEMENTED, e.getStatusCode());
|
||||
}
|
||||
|
||||
@Test
|
||||
void nullRequestBehavesAsAuto() {
|
||||
settingsMode("auto");
|
||||
assertEquals(DocparseTier.BASIC, service.resolveTier(null, installed(), false, false));
|
||||
assertEquals(DocparseTier.ADVANCED, service.resolveTier(null, installed(), false, true));
|
||||
}
|
||||
|
||||
// --- scanned heuristic ---
|
||||
|
||||
@Test
|
||||
void looksScannedWhenAveragePageTextBelowThreshold() throws IOException {
|
||||
try (PDDocument document = new PDDocument()) {
|
||||
document.addPage(new PDPage());
|
||||
document.addPage(new PDPage());
|
||||
when(pdfContentExtractor.extractPageTextRaw(eq(document), anyInt()))
|
||||
.thenReturn("short");
|
||||
assertTrue(service.looksScanned(document));
|
||||
}
|
||||
}
|
||||
|
||||
@Test
|
||||
void doesNotLookScannedWithRealTextLayer() throws IOException {
|
||||
try (PDDocument document = new PDDocument()) {
|
||||
document.addPage(new PDPage());
|
||||
document.addPage(new PDPage());
|
||||
when(pdfContentExtractor.extractPageTextRaw(eq(document), anyInt()))
|
||||
.thenReturn("x".repeat(500));
|
||||
assertFalse(service.looksScanned(document));
|
||||
}
|
||||
}
|
||||
|
||||
@Test
|
||||
void fileNameFallsBackWhenMissing() {
|
||||
MultipartFile nameless =
|
||||
new MockMultipartFile("fileInput", "", "application/pdf", new byte[] {1});
|
||||
assertEquals("document.pdf", DocParseService.fileName(nameless));
|
||||
assertEquals("invoice.pdf", DocParseService.fileName(pdfFile()));
|
||||
}
|
||||
|
||||
@Test
|
||||
void extractPagesSkipsBlankPagesAndCapsCharacters() throws IOException {
|
||||
properties.getAiEngine().getLimits().setMaxCharacters(12);
|
||||
try (PDDocument document = new PDDocument()) {
|
||||
document.addPage(new PDPage());
|
||||
document.addPage(new PDPage());
|
||||
document.addPage(new PDPage());
|
||||
when(pdfContentExtractor.extractPageTextRaw(any(), eq(1))).thenReturn("0123456789");
|
||||
when(pdfContentExtractor.extractPageTextRaw(any(), eq(2))).thenReturn(" ");
|
||||
when(pdfContentExtractor.extractPageTextRaw(any(), eq(3))).thenReturn("abcdef");
|
||||
var pages = service.extractPages(document);
|
||||
assertEquals(2, pages.size());
|
||||
// Page 3 is truncated to the remaining budget (12 - 10 = 2 chars).
|
||||
assertEquals("ab", pages.get(1).getText());
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,59 @@
|
||||
# Stirling-PDF + AI engine with the DocParse addon.
|
||||
# Two ways to get the addon; pick ONE per deployment:
|
||||
# 1. Dynamic install (default here): standard engine image downloads the addon
|
||||
# (~1.6 GB, one-time) into the docparse-data volume at first boot.
|
||||
# 2. Baked image (air-gapped): build the engine with `--build-arg DOCPARSE=true`
|
||||
# (uncomment DOCPARSE below) and drop DOCPARSE_AUTO_INSTALL.
|
||||
services:
|
||||
stirling-pdf:
|
||||
build:
|
||||
context: ../..
|
||||
dockerfile: docker/embedded/Dockerfile.fat
|
||||
container_name: stirling-pdf-docparse
|
||||
restart: unless-stopped
|
||||
healthcheck:
|
||||
test: ["CMD-SHELL", "curl -f http://localhost:8080$${SYSTEM_ROOTURIPATH:-''}/api/v1/info/status | grep -q 'UP'"]
|
||||
interval: 5s
|
||||
timeout: 10s
|
||||
retries: 16
|
||||
ports:
|
||||
- "8080:8080"
|
||||
volumes:
|
||||
- ../../stirling/latest/data:/usr/share/tessdata:rw
|
||||
- ../../stirling/latest/config:/configs:rw
|
||||
- ../../stirling/latest/logs:/logs:rw
|
||||
environment:
|
||||
SECURITY_ENABLELOGIN: "false"
|
||||
SYSTEM_DEFAULTLOCALE: en-US
|
||||
AIENGINE_ENABLED: "true"
|
||||
AIENGINE_URL: http://stirling-pdf-engine:5001
|
||||
DOCPARSE_ENABLED: "true"
|
||||
DOCPARSE_MODE: auto
|
||||
STIRLING_ENGINE_SHARED_SECRET: change-me
|
||||
depends_on:
|
||||
- stirling-pdf-engine
|
||||
networks:
|
||||
- stirling-network
|
||||
|
||||
stirling-pdf-engine:
|
||||
build:
|
||||
context: ../../engine
|
||||
# args:
|
||||
# DOCPARSE: "true" # bake the addon + models into the image instead
|
||||
container_name: stirling-pdf-engine
|
||||
restart: unless-stopped
|
||||
volumes:
|
||||
- docparse-data:/configs/docparse:rw
|
||||
environment:
|
||||
DOCPARSE_AUTO_INSTALL: "true"
|
||||
STIRLING_ENGINE_REQUIRE_AUTH: "true"
|
||||
STIRLING_ENGINE_SHARED_SECRET: change-me
|
||||
networks:
|
||||
- stirling-network
|
||||
|
||||
networks:
|
||||
stirling-network:
|
||||
driver: bridge
|
||||
|
||||
volumes:
|
||||
docparse-data:
|
||||
+11
-1
@@ -15,11 +15,19 @@ WORKDIR /app/engine
|
||||
|
||||
COPY pyproject.toml uv.lock .env ./
|
||||
COPY scripts/ ./scripts/
|
||||
# DOCPARSE=true bakes the docparse addon (Docling + CPU torch, ~1.6 GB) and its
|
||||
# model weights into the image for air-gapped deployments; default stays lean.
|
||||
ARG DOCPARSE=false
|
||||
RUN --mount=type=cache,target=/root/.cache/uv \
|
||||
uv sync --frozen --no-dev
|
||||
if [ "$DOCPARSE" = "true" ]; then uv sync --frozen --no-dev --extra docparse; else uv sync --frozen --no-dev; fi
|
||||
|
||||
COPY src/ ./src/
|
||||
|
||||
RUN if [ "$DOCPARSE" = "true" ]; then \
|
||||
mkdir -p /opt/docparse/models \
|
||||
&& .venv/bin/python scripts/prefetch_docparse_models.py --output /opt/docparse/models; \
|
||||
fi
|
||||
|
||||
WORKDIR /app
|
||||
COPY Taskfile.yml ./
|
||||
COPY .taskfiles/ ./.taskfiles/
|
||||
@@ -34,4 +42,6 @@ ENV STIRLING_ENGINE_PORT=5001
|
||||
|
||||
EXPOSE 5001
|
||||
|
||||
RUN chmod +x /app/engine/scripts/docker-entrypoint.sh /app/engine/scripts/init_docparse.sh
|
||||
ENTRYPOINT ["/app/engine/scripts/docker-entrypoint.sh"]
|
||||
CMD ["task", "engine:run"]
|
||||
|
||||
@@ -14,12 +14,24 @@ dependencies = [
|
||||
"pydantic-ai-slim[voyageai]>=1.99.0,<2.0.0",
|
||||
"pydantic-settings>=2.0.0",
|
||||
"python-dotenv>=1.2.1",
|
||||
# Small (MIT) and always installed: DOCX template filling needs no addon.
|
||||
"python-docx>=1.1.2",
|
||||
"sqlite-vec>=0.1.6",
|
||||
"uvicorn>=0.35.0",
|
||||
"opentelemetry-sdk>=1.39.0",
|
||||
"posthog>=3.0.0",
|
||||
]
|
||||
|
||||
[project.optional-dependencies]
|
||||
# DocParse advanced tier (layout parsing, tables, OCR, bbox citations).
|
||||
# ~1.6 GB installed with CPU torch; never in the default image. Delivered via
|
||||
# the addon engine image or the runtime dynamic install.
|
||||
docparse = [
|
||||
"docling>=2.55.0",
|
||||
"torch>=2.6.0",
|
||||
"torchvision>=0.21.0",
|
||||
]
|
||||
|
||||
[dependency-groups]
|
||||
dev = [
|
||||
"anyio>=4.0.0",
|
||||
@@ -34,6 +46,17 @@ dev = [
|
||||
requires = ["hatchling"]
|
||||
build-backend = "hatchling.build"
|
||||
|
||||
# Linux installs of the docparse extra must never pull CUDA wheels (~7 GB);
|
||||
# pin torch to the CPU index there. Windows/macOS PyPI wheels are already CPU.
|
||||
[[tool.uv.index]]
|
||||
name = "pytorch-cpu"
|
||||
url = "https://download.pytorch.org/whl/cpu"
|
||||
explicit = true
|
||||
|
||||
[tool.uv.sources]
|
||||
torch = [{ index = "pytorch-cpu", marker = "sys_platform == 'linux'" }]
|
||||
torchvision = [{ index = "pytorch-cpu", marker = "sys_platform == 'linux'" }]
|
||||
|
||||
[tool.hatch.build.targets.wheel]
|
||||
packages = ["src"]
|
||||
exclude = [
|
||||
|
||||
@@ -0,0 +1,16 @@
|
||||
#!/bin/sh
|
||||
# Engine entrypoint: resolve where the docparse addon lives (baked vs dynamic)
|
||||
# before handing off to the server command.
|
||||
set -e
|
||||
|
||||
# Baked addon image (--build-arg DOCPARSE=true) prefetches models here.
|
||||
if [ -z "${STIRLING_DOCPARSE_HOME:-}" ] && [ -d /opt/docparse/models ]; then
|
||||
export STIRLING_DOCPARSE_HOME=/opt/docparse
|
||||
fi
|
||||
|
||||
if [ "${DOCPARSE_AUTO_INSTALL:-false}" = "true" ]; then
|
||||
export STIRLING_DOCPARSE_HOME="${STIRLING_DOCPARSE_HOME:-/configs/docparse}"
|
||||
/app/engine/scripts/init_docparse.sh || echo "[docparse] dynamic install failed; continuing with basic tier" >&2
|
||||
fi
|
||||
|
||||
exec "$@"
|
||||
@@ -0,0 +1,43 @@
|
||||
#!/bin/sh
|
||||
# Dynamic docparse install: put the addon's locked package delta into
|
||||
# $STIRLING_DOCPARSE_HOME/site (a volume, so it survives image upgrades) and
|
||||
# prefetch model weights into $STIRLING_DOCPARSE_HOME/models.
|
||||
# Idempotent: keyed on a marker derived from uv.lock, re-runs after upgrades.
|
||||
set -e
|
||||
|
||||
ENGINE_DIR=/app/engine
|
||||
HOME_DIR="${STIRLING_DOCPARSE_HOME:-/configs/docparse}"
|
||||
SITE_DIR="$HOME_DIR/site"
|
||||
MODELS_DIR="$HOME_DIR/models"
|
||||
PYTHON="$ENGINE_DIR/.venv/bin/python"
|
||||
|
||||
mkdir -p "$SITE_DIR" "$MODELS_DIR"
|
||||
|
||||
LOCK_HASH=$(sha256sum "$ENGINE_DIR/uv.lock" | cut -c1-16)
|
||||
MARKER="$HOME_DIR/.installed-$LOCK_HASH"
|
||||
|
||||
if [ ! -f "$MARKER" ]; then
|
||||
echo "[docparse] installing addon packages into $SITE_DIR (one-time, ~1.6 GB)"
|
||||
cd "$ENGINE_DIR"
|
||||
# Delta = locked docparse resolution minus what the base venv already has.
|
||||
uv export --frozen --no-dev --no-emit-project --no-hashes -o /tmp/docparse-base.req
|
||||
uv export --frozen --extra docparse --no-dev --no-emit-project --no-hashes -o /tmp/docparse-full.req
|
||||
grep -vxFf /tmp/docparse-base.req /tmp/docparse-full.req > /tmp/docparse-delta.req || true
|
||||
uv pip install \
|
||||
--python "$PYTHON" \
|
||||
--target "$SITE_DIR" \
|
||||
--no-deps \
|
||||
--extra-index-url https://download.pytorch.org/whl/cpu \
|
||||
--index-strategy unsafe-best-match \
|
||||
-r /tmp/docparse-delta.req
|
||||
rm -f "$HOME_DIR"/.installed-* /tmp/docparse-*.req
|
||||
touch "$MARKER"
|
||||
fi
|
||||
|
||||
if [ ! -d "$MODELS_DIR/docling" ] && [ -z "$(ls -A "$MODELS_DIR" 2>/dev/null)" ]; then
|
||||
echo "[docparse] prefetching model weights into $MODELS_DIR"
|
||||
PYTHONPATH="$SITE_DIR" "$PYTHON" "$ENGINE_DIR/scripts/prefetch_docparse_models.py" --output "$MODELS_DIR" \
|
||||
|| echo "[docparse] model prefetch failed; docling will fetch into its cache on first use" >&2
|
||||
fi
|
||||
|
||||
echo "[docparse] ready (site=$SITE_DIR, models=$MODELS_DIR)"
|
||||
@@ -0,0 +1,39 @@
|
||||
"""Prefetch Docling model weights for offline/air-gapped docparse.
|
||||
|
||||
Usage:
|
||||
uv run --extra docparse python scripts/prefetch_docparse_models.py --output /configs/docparse/models
|
||||
|
||||
The output directory is what STIRLING_DOCPARSE_HOME/models points at; the
|
||||
parser passes it to Docling as ``artifacts_path`` so no network is touched at
|
||||
request time.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import argparse
|
||||
import importlib
|
||||
import sys
|
||||
from pathlib import Path
|
||||
|
||||
|
||||
def main() -> int:
|
||||
parser = argparse.ArgumentParser(description=__doc__)
|
||||
parser.add_argument("--output", required=True, help="Directory to download model weights into")
|
||||
args = parser.parse_args()
|
||||
|
||||
try:
|
||||
# importlib keeps this file typecheckable without the docparse extra installed
|
||||
downloader = importlib.import_module("docling.utils.model_downloader")
|
||||
except ImportError:
|
||||
print("docling is not installed; run with: uv run --extra docparse ...", file=sys.stderr)
|
||||
return 1
|
||||
|
||||
output = Path(args.output)
|
||||
output.mkdir(parents=True, exist_ok=True)
|
||||
path = downloader.download_models(output_dir=output, progress=True)
|
||||
print(f"docparse models ready at {path}")
|
||||
return 0
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
sys.exit(main())
|
||||
@@ -17,6 +17,7 @@ from stirling.api.routes import (
|
||||
agent_capabilities_router,
|
||||
agent_draft_router,
|
||||
config_router,
|
||||
docparse_router,
|
||||
document_classifier_router,
|
||||
document_router,
|
||||
execution_router,
|
||||
@@ -30,6 +31,7 @@ from stirling.api.routes.config import CONFIG_APPLY_ERRORS, apply_to_app, resolv
|
||||
from stirling.config import AppSettings, load_settings
|
||||
from stirling.config.config_cache import cache_stamp, load_config
|
||||
from stirling.contracts import HealthResponse
|
||||
from stirling.docparse import activate_site
|
||||
from stirling.documents import DocumentService, EmbeddingService
|
||||
from stirling.services import setup_posthog_tracking
|
||||
|
||||
@@ -145,6 +147,8 @@ def _restore_cached_config(
|
||||
async def lifespan(fast_api: FastAPI):
|
||||
# Load env vars on startup so we can immediately crash if required env vars aren't set
|
||||
settings = _load_startup_settings(fast_api)
|
||||
# Initialize docparse addon if available (engine boot-time setup).
|
||||
activate_site(settings.docparse_home)
|
||||
# Precedence: env < persisted cache < live push. Stamp first so a push landing mid-boot
|
||||
# is re-adopted by the watcher rather than mistaken for the config we just restored.
|
||||
fast_api.state.config_cache_stamp = cache_stamp()
|
||||
@@ -217,6 +221,7 @@ app.include_router(ledger_router, dependencies=_user_gate)
|
||||
app.include_router(pdf_comments_router, dependencies=_user_gate)
|
||||
app.include_router(agent_capabilities_router, dependencies=_user_gate)
|
||||
app.include_router(document_classifier_router, dependencies=_user_gate)
|
||||
app.include_router(docparse_router, dependencies=_user_gate)
|
||||
# Config push is a system sync with no X-User-Id, so it is guarded by the shared secret
|
||||
# and allow_config_push flag only, deliberately NOT the per-user identity gate.
|
||||
app.include_router(config_router)
|
||||
|
||||
@@ -18,6 +18,7 @@ from stirling.agents import (
|
||||
from stirling.agents.ledger import MathAuditorAgent
|
||||
from stirling.agents.pdf_comment import PdfCommentAgent
|
||||
from stirling.config import AppSettings
|
||||
from stirling.docparse import ExtractFieldsAgent, SmartSplitAgent, SuggestSchemaAgent
|
||||
from stirling.documents import DocumentService, EmbeddingService
|
||||
from stirling.services import AppRuntime, build_runtime
|
||||
|
||||
@@ -35,6 +36,9 @@ class AppState:
|
||||
math_auditor_agent: MathAuditorAgent
|
||||
pdf_comment_agent: PdfCommentAgent
|
||||
document_classifier_agent: DocumentClassifierAgent
|
||||
extract_fields_agent: ExtractFieldsAgent
|
||||
smart_split_agent: SmartSplitAgent
|
||||
suggest_schema_agent: SuggestSchemaAgent
|
||||
|
||||
|
||||
def build_app_state(
|
||||
@@ -63,6 +67,9 @@ def build_app_state(
|
||||
math_auditor_agent=MathAuditorAgent(runtime),
|
||||
pdf_comment_agent=PdfCommentAgent(runtime),
|
||||
document_classifier_agent=DocumentClassifierAgent(runtime),
|
||||
extract_fields_agent=ExtractFieldsAgent(runtime),
|
||||
smart_split_agent=SmartSplitAgent(runtime),
|
||||
suggest_schema_agent=SuggestSchemaAgent(runtime),
|
||||
)
|
||||
|
||||
|
||||
|
||||
@@ -15,6 +15,7 @@ from stirling.agents import (
|
||||
from stirling.agents.ledger import MathAuditorAgent
|
||||
from stirling.agents.pdf_comment import PdfCommentAgent
|
||||
from stirling.config import AppSettings, load_settings
|
||||
from stirling.docparse import ExtractFieldsAgent, SmartSplitAgent, SuggestSchemaAgent
|
||||
from stirling.documents import DocumentService
|
||||
from stirling.models import UserId
|
||||
from stirling.services import AppRuntime, current_user_id
|
||||
@@ -60,6 +61,18 @@ def get_document_classifier_agent(request: Request) -> DocumentClassifierAgent:
|
||||
return request.app.state.document_classifier_agent
|
||||
|
||||
|
||||
def get_extract_fields_agent(request: Request) -> ExtractFieldsAgent:
|
||||
return request.app.state.extract_fields_agent
|
||||
|
||||
|
||||
def get_suggest_schema_agent(request: Request) -> SuggestSchemaAgent:
|
||||
return request.app.state.suggest_schema_agent
|
||||
|
||||
|
||||
def get_smart_split_agent(request: Request) -> SmartSplitAgent:
|
||||
return request.app.state.smart_split_agent
|
||||
|
||||
|
||||
def require_user_id() -> UserId:
|
||||
"""FastAPI dependency for routes that touch per-user storage.
|
||||
|
||||
|
||||
@@ -1,6 +1,7 @@
|
||||
from .agent_capabilities import router as agent_capabilities_router
|
||||
from .agent_drafts import router as agent_draft_router
|
||||
from .config import router as config_router
|
||||
from .docparse import router as docparse_router
|
||||
from .document_classifier import router as document_classifier_router
|
||||
from .documents import router as document_router
|
||||
from .execution import router as execution_router
|
||||
@@ -14,6 +15,7 @@ __all__ = [
|
||||
"agent_capabilities_router",
|
||||
"agent_draft_router",
|
||||
"config_router",
|
||||
"docparse_router",
|
||||
"document_classifier_router",
|
||||
"document_router",
|
||||
"execution_router",
|
||||
|
||||
@@ -0,0 +1,314 @@
|
||||
"""DocParse routes: parse, extract, split, chunk, tables, fill, capabilities.
|
||||
|
||||
Tier routing happens here: requests carrying raw file bytes can use the
|
||||
advanced (Docling) path when the addon is installed; text-only requests run
|
||||
the basic path. Forcing ``advanced`` without the addon returns 501 with a
|
||||
machine-readable ``addonRequired`` detail that Java maps onto its own error.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import base64
|
||||
import binascii
|
||||
import logging
|
||||
from typing import Annotated
|
||||
|
||||
import anyio.to_thread
|
||||
from fastapi import APIRouter, Depends, HTTPException, status
|
||||
|
||||
from stirling.api.dependencies import (
|
||||
get_document_service,
|
||||
get_extract_fields_agent,
|
||||
get_smart_split_agent,
|
||||
get_suggest_schema_agent,
|
||||
require_user_id,
|
||||
)
|
||||
from stirling.config import AppSettings, load_settings
|
||||
from stirling.contracts.docparse import (
|
||||
ChunkDocumentRequest,
|
||||
ChunkDocumentResponse,
|
||||
DocChunk,
|
||||
DocparseCapabilities,
|
||||
DocparseMode,
|
||||
DocparseTier,
|
||||
ExtractFieldsRequest,
|
||||
ExtractFieldsResponse,
|
||||
ExtractTablesRequest,
|
||||
ExtractTablesResponse,
|
||||
FillDocxRequest,
|
||||
FillDocxResponse,
|
||||
ParseDocumentRequest,
|
||||
ParseDocumentResponse,
|
||||
RagIngestRequest,
|
||||
RagIngestResponse,
|
||||
SmartSplitRequest,
|
||||
SmartSplitResponse,
|
||||
SuggestSchemaRequest,
|
||||
SuggestSchemaResponse,
|
||||
)
|
||||
from stirling.docparse import basic_chunks, fill_docx, probe_capabilities
|
||||
from stirling.docparse.capability import models_dir
|
||||
from stirling.docparse.chunking import advanced_chunks
|
||||
from stirling.docparse.extractor import ExtractFieldsAgent, SchemaError, pages_from_parse
|
||||
from stirling.docparse.splitter import SmartSplitAgent
|
||||
from stirling.docparse.suggest_schema import SuggestSchemaAgent
|
||||
from stirling.documents import DocumentService
|
||||
from stirling.documents.service import CONTENT_TYPE_METADATA_KEY, DOCPARSE_CHUNK_CONTENT_TYPE
|
||||
from stirling.models import OwnerId, PrincipalId, UserId
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
router = APIRouter(prefix="/api/v1/docparse", tags=["docparse"])
|
||||
|
||||
_ADDON_REQUIRED_DETAIL = {
|
||||
"addonRequired": "docparse",
|
||||
"message": "The docparse addon (Docling) is not installed on the engine. "
|
||||
"Install the engine's 'docparse' extra or enable DOCPARSE_AUTO_INSTALL.",
|
||||
}
|
||||
|
||||
|
||||
def _settings() -> AppSettings:
|
||||
return load_settings()
|
||||
|
||||
|
||||
def _capabilities(settings: AppSettings, *, refresh: bool = False) -> DocparseCapabilities:
|
||||
return probe_capabilities(settings.docparse_home, refresh=refresh)
|
||||
|
||||
|
||||
def _require_advanced(settings: AppSettings) -> str | None:
|
||||
caps = _capabilities(settings)
|
||||
if not caps.advanced_installed:
|
||||
raise HTTPException(status_code=status.HTTP_501_NOT_IMPLEMENTED, detail=_ADDON_REQUIRED_DETAIL)
|
||||
directory = models_dir(settings.docparse_home)
|
||||
return str(directory) if caps.models_available and directory is not None else None
|
||||
|
||||
|
||||
def _decode_content(content_base64: str) -> bytes:
|
||||
try:
|
||||
return base64.b64decode(content_base64, validate=True)
|
||||
except (binascii.Error, ValueError) as error:
|
||||
raise HTTPException(
|
||||
status_code=status.HTTP_422_UNPROCESSABLE_ENTITY, detail="contentBase64 is not valid base64"
|
||||
) from error
|
||||
|
||||
|
||||
async def _parse_advanced(content_base64: str, file_name: str, *, with_ocr: bool, artifacts: str | None):
|
||||
"""Run the Docling parse off-thread; unparsable documents are a caller error."""
|
||||
from stirling.docparse.parser import parse_pdf_bytes # deferred: touches docling
|
||||
|
||||
data = _decode_content(content_base64)
|
||||
try:
|
||||
return await anyio.to_thread.run_sync(
|
||||
lambda: parse_pdf_bytes(data, file_name, with_ocr=with_ocr, artifacts_path=artifacts)
|
||||
)
|
||||
except ValueError as error:
|
||||
raise HTTPException(status_code=status.HTTP_422_UNPROCESSABLE_ENTITY, detail=str(error)) from error
|
||||
|
||||
|
||||
@router.get("/capabilities", response_model=DocparseCapabilities)
|
||||
async def capabilities(refresh: bool = False) -> DocparseCapabilities:
|
||||
return _capabilities(_settings(), refresh=refresh)
|
||||
|
||||
|
||||
@router.post("/parse", response_model=ParseDocumentResponse)
|
||||
async def parse_document(request: ParseDocumentRequest) -> ParseDocumentResponse:
|
||||
"""Advanced-tier layout parse. The basic tier lives Java-side (PDFBox) and
|
||||
never reaches the engine, so this endpoint requires the addon outright."""
|
||||
settings = _settings()
|
||||
artifacts = _require_advanced(settings)
|
||||
return await _parse_advanced(
|
||||
request.content_base64, request.file_name, with_ocr=request.with_ocr, artifacts=artifacts
|
||||
)
|
||||
|
||||
|
||||
@router.post("/extract", response_model=ExtractFieldsResponse)
|
||||
async def extract_fields(
|
||||
request: ExtractFieldsRequest,
|
||||
agent: Annotated[ExtractFieldsAgent, Depends(get_extract_fields_agent)],
|
||||
) -> ExtractFieldsResponse:
|
||||
settings = _settings()
|
||||
caps = _capabilities(settings)
|
||||
|
||||
use_advanced = request.mode is DocparseMode.ADVANCED or (
|
||||
request.mode is DocparseMode.AUTO and caps.advanced_installed and request.content_base64 is not None
|
||||
)
|
||||
parse = None
|
||||
if use_advanced:
|
||||
artifacts = _require_advanced(settings)
|
||||
if request.content_base64 is None:
|
||||
raise HTTPException(
|
||||
status_code=status.HTTP_422_UNPROCESSABLE_ENTITY,
|
||||
detail="advanced extraction needs contentBase64 (the raw file)",
|
||||
)
|
||||
parse = await _parse_advanced(request.content_base64, request.file_name, with_ocr=True, artifacts=artifacts)
|
||||
|
||||
pages = request.pages or (pages_from_parse(parse) if parse is not None else None)
|
||||
if not pages:
|
||||
raise HTTPException(
|
||||
status_code=status.HTTP_422_UNPROCESSABLE_ENTITY,
|
||||
detail="send pages (extracted text) or contentBase64 with the addon installed",
|
||||
)
|
||||
try:
|
||||
return await agent.extract(request, pages, parse)
|
||||
except SchemaError as error:
|
||||
raise HTTPException(status_code=status.HTTP_422_UNPROCESSABLE_ENTITY, detail=str(error)) from error
|
||||
|
||||
|
||||
@router.post("/suggest-schema", response_model=SuggestSchemaResponse)
|
||||
async def suggest_schema(
|
||||
request: SuggestSchemaRequest,
|
||||
agent: Annotated[SuggestSchemaAgent, Depends(get_suggest_schema_agent)],
|
||||
) -> SuggestSchemaResponse:
|
||||
"""Propose an extraction schema from the document's first pages.
|
||||
Tier routing: pages -> basic; contentBase64 + addon -> advanced parse."""
|
||||
settings = _settings()
|
||||
caps = _capabilities(settings)
|
||||
pages = request.pages
|
||||
tier = DocparseTier.BASIC
|
||||
if not pages and request.content_base64 is not None and caps.advanced_installed:
|
||||
artifacts = _require_advanced(settings)
|
||||
parse = await _parse_advanced(request.content_base64, request.file_name, with_ocr=True, artifacts=artifacts)
|
||||
pages = pages_from_parse(parse)
|
||||
tier = DocparseTier.ADVANCED
|
||||
if not pages:
|
||||
raise HTTPException(
|
||||
status_code=status.HTTP_422_UNPROCESSABLE_ENTITY,
|
||||
detail="send pages (extracted text) or contentBase64 with the addon installed",
|
||||
)
|
||||
return await agent.suggest(request, pages, tier)
|
||||
|
||||
|
||||
@router.post("/split", response_model=SmartSplitResponse)
|
||||
async def smart_split(
|
||||
request: SmartSplitRequest,
|
||||
agent: Annotated[SmartSplitAgent, Depends(get_smart_split_agent)],
|
||||
) -> SmartSplitResponse:
|
||||
return await agent.split(request)
|
||||
|
||||
|
||||
@router.post("/chunk", response_model=ChunkDocumentResponse)
|
||||
async def chunk_document(request: ChunkDocumentRequest) -> ChunkDocumentResponse:
|
||||
settings = _settings()
|
||||
caps = _capabilities(settings)
|
||||
use_advanced = request.mode is DocparseMode.ADVANCED or (
|
||||
request.mode is DocparseMode.AUTO and caps.advanced_installed and request.content_base64 is not None
|
||||
)
|
||||
if use_advanced:
|
||||
artifacts = _require_advanced(settings)
|
||||
if request.content_base64 is None:
|
||||
raise HTTPException(
|
||||
status_code=status.HTTP_422_UNPROCESSABLE_ENTITY,
|
||||
detail="advanced chunking needs contentBase64 (the raw file)",
|
||||
)
|
||||
parse = await _parse_advanced(request.content_base64, request.file_name, with_ocr=True, artifacts=artifacts)
|
||||
return advanced_chunks(parse, request.chunk_size, request.overlap)
|
||||
|
||||
if not request.pages:
|
||||
raise HTTPException(
|
||||
status_code=status.HTTP_422_UNPROCESSABLE_ENTITY,
|
||||
detail="send pages (extracted text) or contentBase64 with the addon installed",
|
||||
)
|
||||
return basic_chunks(request.pages, request.chunk_size, request.overlap)
|
||||
|
||||
|
||||
def _chunk_metadata(chunk: DocChunk) -> dict[str, str]:
|
||||
meta = {CONTENT_TYPE_METADATA_KEY: DOCPARSE_CHUNK_CONTENT_TYPE}
|
||||
if chunk.page_start is not None:
|
||||
meta["page_start"] = str(chunk.page_start)
|
||||
if chunk.page_end is not None:
|
||||
meta["page_end"] = str(chunk.page_end)
|
||||
if chunk.heading_path:
|
||||
meta["heading_path"] = " > ".join(chunk.heading_path)
|
||||
return meta
|
||||
|
||||
|
||||
@router.post("/rag-ingest", response_model=RagIngestResponse)
|
||||
async def rag_ingest(
|
||||
request: RagIngestRequest,
|
||||
documents: Annotated[DocumentService, Depends(get_document_service)],
|
||||
user_id: Annotated[UserId, Depends(require_user_id)],
|
||||
) -> RagIngestResponse:
|
||||
"""Chunk the document, then embed and index into the document store.
|
||||
Re-ingesting a documentId replaces its stored content (never duplicates).
|
||||
``index=False`` skips the store; ``includeMarkdown``/``includeChunks``
|
||||
echo the content back for corpus export."""
|
||||
settings = _settings()
|
||||
caps = _capabilities(settings)
|
||||
chunk_size = request.chunk_size if request.chunk_size is not None else settings.rag_chunk_size
|
||||
overlap = request.overlap if request.overlap is not None else settings.rag_chunk_overlap
|
||||
|
||||
if not request.index and not request.include_markdown and not request.include_chunks:
|
||||
raise HTTPException(
|
||||
status_code=status.HTTP_422_UNPROCESSABLE_ENTITY,
|
||||
detail="nothing to do: enable index, includeMarkdown, or includeChunks",
|
||||
)
|
||||
|
||||
use_advanced = request.mode is DocparseMode.ADVANCED or (
|
||||
request.mode is DocparseMode.AUTO and caps.advanced_installed and request.content_base64 is not None
|
||||
)
|
||||
if use_advanced:
|
||||
artifacts = _require_advanced(settings)
|
||||
if request.content_base64 is None:
|
||||
raise HTTPException(
|
||||
status_code=status.HTTP_422_UNPROCESSABLE_ENTITY,
|
||||
detail="advanced chunking needs contentBase64 (the raw file)",
|
||||
)
|
||||
parse = await _parse_advanced(request.content_base64, request.file_name, with_ocr=True, artifacts=artifacts)
|
||||
chunked = advanced_chunks(parse, chunk_size, overlap)
|
||||
page_count = parse.pages
|
||||
markdown = parse.markdown if request.include_markdown else None
|
||||
else:
|
||||
if not request.pages:
|
||||
raise HTTPException(
|
||||
status_code=status.HTTP_422_UNPROCESSABLE_ENTITY,
|
||||
detail="send pages (extracted text) or contentBase64 with the addon installed",
|
||||
)
|
||||
chunked = basic_chunks(request.pages, chunk_size, overlap)
|
||||
page_count = max(p.page_number for p in request.pages)
|
||||
markdown = None
|
||||
if request.include_markdown:
|
||||
markdown = "\n\n".join(p.text for p in request.pages if p.text.strip())
|
||||
|
||||
chunks_indexed = 0
|
||||
if request.index:
|
||||
# Owner/ACL semantics mirror IngestDocumentRequest; omitted values default
|
||||
# to the authenticated caller (personal-doc behaviour).
|
||||
owner_id = request.owner_id if request.owner_id is not None else OwnerId(user_id)
|
||||
read_principals = request.read_principals or [PrincipalId(owner_id)]
|
||||
chunks_indexed = await documents.ingest_prepared(
|
||||
collection=request.document_id,
|
||||
chunks=[(chunk.text, _chunk_metadata(chunk)) for chunk in chunked.chunks],
|
||||
source=request.source,
|
||||
owner_id=owner_id,
|
||||
read_principals=read_principals,
|
||||
expires_at=request.expires_at,
|
||||
)
|
||||
logger.info(
|
||||
"docparse: rag-ingested %s: %d chunks indexed, %d pages", request.document_id, chunks_indexed, page_count
|
||||
)
|
||||
return RagIngestResponse(
|
||||
mode=chunked.mode,
|
||||
document_id=request.document_id,
|
||||
chunks_indexed=chunks_indexed,
|
||||
pages=page_count,
|
||||
markdown=markdown,
|
||||
chunks=chunked.chunks if request.include_chunks else None,
|
||||
)
|
||||
|
||||
|
||||
@router.post("/tables", response_model=ExtractTablesResponse)
|
||||
async def extract_tables(request: ExtractTablesRequest) -> ExtractTablesResponse:
|
||||
settings = _settings()
|
||||
artifacts = _require_advanced(settings)
|
||||
parse = await _parse_advanced(request.content_base64, request.file_name, with_ocr=True, artifacts=artifacts)
|
||||
return ExtractTablesResponse(mode=parse.mode, tables=parse.tables)
|
||||
|
||||
|
||||
@router.post("/fill-docx", response_model=FillDocxResponse)
|
||||
async def fill_docx_template(request: FillDocxRequest) -> FillDocxResponse:
|
||||
try:
|
||||
return await anyio.to_thread.run_sync(lambda: fill_docx(request))
|
||||
except (KeyError, ValueError) as error:
|
||||
raise HTTPException(
|
||||
status_code=status.HTTP_422_UNPROCESSABLE_ENTITY, detail=f"invalid docx template: {error}"
|
||||
) from error
|
||||
@@ -101,6 +101,11 @@ class AppSettings(BaseSettings):
|
||||
max_pages: int = Field(validation_alias="STIRLING_MAX_PAGES")
|
||||
max_characters: int = Field(validation_alias="STIRLING_MAX_CHARACTERS")
|
||||
|
||||
# DocParse addon home: <home>/site holds a dynamically installed docling
|
||||
# stack (prepended to sys.path at startup), <home>/models holds prefetched
|
||||
# model weights. Empty = addon only usable when baked into the image.
|
||||
docparse_home: str = Field(default="", validation_alias="STIRLING_DOCPARSE_HOME")
|
||||
|
||||
# When true, API routes reject requests that lack an X-User-Id header at
|
||||
# the boundary. Self-hosted deployments with security disabled have no
|
||||
# user identity and leave this off; multi-tenant deployments turn it on so
|
||||
|
||||
@@ -0,0 +1,257 @@
|
||||
"""Wire contracts for the DocParse ingestion capability (chunking + rag-ingest).
|
||||
|
||||
Java counterpart DTOs live under ``stirling.software.proprietary.model.docparse``
|
||||
and must stay in sync. Tier model: ``basic`` (text layer) runs everywhere;
|
||||
``advanced`` (layout parsing) arrives with the docparse addon.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from datetime import datetime
|
||||
from enum import StrEnum
|
||||
|
||||
from pydantic import Field, JsonValue
|
||||
|
||||
from stirling.contracts.documents import PageText
|
||||
from stirling.models import ApiModel, FileId, OwnerId, PrincipalId
|
||||
|
||||
|
||||
class DocparseTier(StrEnum):
|
||||
"""Which implementation actually served a request."""
|
||||
|
||||
BASIC = "basic"
|
||||
ADVANCED = "advanced"
|
||||
|
||||
|
||||
class DocparseMode(StrEnum):
|
||||
"""What the caller asked for; AUTO resolves per-request."""
|
||||
|
||||
AUTO = "auto"
|
||||
BASIC = "basic"
|
||||
ADVANCED = "advanced"
|
||||
|
||||
|
||||
class BlockType(StrEnum):
|
||||
"""Normalized layout block labels; Docling labels map onto these."""
|
||||
|
||||
HEADING = "heading"
|
||||
PARAGRAPH = "paragraph"
|
||||
LIST_ITEM = "list_item"
|
||||
TABLE = "table"
|
||||
FIGURE = "figure"
|
||||
CAPTION = "caption"
|
||||
CODE = "code"
|
||||
FORMULA = "formula"
|
||||
PAGE_HEADER = "page_header"
|
||||
PAGE_FOOTER = "page_footer"
|
||||
FOOTNOTE = "footnote"
|
||||
OTHER = "other"
|
||||
|
||||
|
||||
class DocBlock(ApiModel):
|
||||
"""One layout block. ``bbox`` is [x0, y0, x1, y1] normalized to 0..1 with a
|
||||
top-left origin; ``None`` in basic tier (no layout model ran)."""
|
||||
|
||||
type: BlockType
|
||||
text: str
|
||||
page: int = Field(ge=1)
|
||||
bbox: list[float] | None = None
|
||||
confidence: float | None = Field(default=None, ge=0.0, le=1.0)
|
||||
|
||||
|
||||
class DocTable(ApiModel):
|
||||
page: int = Field(ge=1)
|
||||
bbox: list[float] | None = None
|
||||
cells: list[list[str]]
|
||||
markdown: str
|
||||
confidence: float | None = Field(default=None, ge=0.0, le=1.0)
|
||||
|
||||
|
||||
class ParseDocumentRequest(ApiModel):
|
||||
file_name: str = Field(min_length=1)
|
||||
content_base64: str = Field(min_length=1)
|
||||
with_ocr: bool = True
|
||||
|
||||
|
||||
class ParseDocumentResponse(ApiModel):
|
||||
mode: DocparseTier
|
||||
pages: int = Field(ge=0)
|
||||
blocks: list[DocBlock] = Field(default_factory=list)
|
||||
tables: list[DocTable] = Field(default_factory=list)
|
||||
markdown: str = ""
|
||||
ocr_applied: bool = False
|
||||
|
||||
|
||||
class ExtractTablesRequest(ApiModel):
|
||||
file_name: str = Field(min_length=1)
|
||||
content_base64: str = Field(min_length=1)
|
||||
|
||||
|
||||
class ExtractTablesResponse(ApiModel):
|
||||
mode: DocparseTier
|
||||
tables: list[DocTable] = Field(default_factory=list)
|
||||
|
||||
|
||||
class DocChunk(ApiModel):
|
||||
index: int = Field(ge=0)
|
||||
text: str
|
||||
page_start: int | None = Field(default=None, ge=1)
|
||||
page_end: int | None = Field(default=None, ge=1)
|
||||
heading_path: list[str] = Field(default_factory=list)
|
||||
|
||||
|
||||
class ChunkDocumentResponse(ApiModel):
|
||||
mode: DocparseTier
|
||||
chunks: list[DocChunk] = Field(default_factory=list)
|
||||
|
||||
|
||||
class RagIngestRequest(ApiModel):
|
||||
"""Chunk the document, then optionally embed and replace-index it.
|
||||
|
||||
``owner_id``/``read_principals`` default to the calling user (personal-doc
|
||||
semantics); ``chunk_size``/``overlap`` default to the engine's RAG settings.
|
||||
``index=False`` skips the store entirely (export-only ingestion);
|
||||
``include_markdown``/``include_chunks`` echo the parsed content back so the
|
||||
caller can emit corpus files (markdown, chunks JSONL).
|
||||
"""
|
||||
|
||||
file_name: str = Field(min_length=1)
|
||||
document_id: FileId = Field(min_length=1)
|
||||
source: str = Field(default="docparse", min_length=1)
|
||||
owner_id: OwnerId | None = None
|
||||
read_principals: list[PrincipalId] | None = Field(default=None, min_length=1)
|
||||
expires_at: datetime | None = None
|
||||
pages: list[PageText] | None = None
|
||||
content_base64: str | None = None
|
||||
chunk_size: int | None = Field(default=None, ge=64, le=32_768)
|
||||
overlap: int | None = Field(default=None, ge=0, le=4_096)
|
||||
mode: DocparseMode = DocparseMode.AUTO
|
||||
index: bool = True
|
||||
include_markdown: bool = False
|
||||
include_chunks: bool = False
|
||||
|
||||
|
||||
class RagIngestResponse(ApiModel):
|
||||
mode: DocparseTier
|
||||
document_id: FileId
|
||||
chunks_indexed: int = Field(ge=0)
|
||||
pages: int = Field(ge=0)
|
||||
markdown: str | None = None
|
||||
chunks: list[DocChunk] | None = None
|
||||
|
||||
|
||||
class FieldCitation(ApiModel):
|
||||
"""Where a value came from. ``quote`` is always set; ``bbox`` only when a
|
||||
layout parse ran (advanced tier); offsets index into the cited page's text."""
|
||||
|
||||
page: int | None = Field(default=None, ge=1)
|
||||
bbox: list[float] | None = None
|
||||
quote: str
|
||||
start_offset: int | None = Field(default=None, ge=0)
|
||||
end_offset: int | None = Field(default=None, ge=0)
|
||||
|
||||
|
||||
class ExtractedField(ApiModel):
|
||||
name: str
|
||||
value: JsonValue = None
|
||||
confidence: float = Field(ge=0.0, le=1.0)
|
||||
citations: list[FieldCitation] = Field(default_factory=list)
|
||||
|
||||
|
||||
class ExtractFieldsRequest(ApiModel):
|
||||
"""``pages`` drives the basic tier (caller-extracted text); ``content_base64``
|
||||
lets the advanced tier parse the raw file itself. Send either or both."""
|
||||
|
||||
file_name: str = Field(min_length=1)
|
||||
fields_schema: dict[str, JsonValue]
|
||||
pages: list[PageText] | None = None
|
||||
content_base64: str | None = None
|
||||
mode: DocparseMode = DocparseMode.AUTO
|
||||
instructions: str | None = None
|
||||
|
||||
|
||||
class ExtractFieldsResponse(ApiModel):
|
||||
mode: DocparseTier
|
||||
fields: list[ExtractedField] = Field(default_factory=list)
|
||||
overall_confidence: float = Field(ge=0.0, le=1.0)
|
||||
|
||||
|
||||
class SuggestedFieldType(StrEnum):
|
||||
"""Scalar types the schema suggester may propose; the extractor's leaf subset."""
|
||||
|
||||
STRING = "string"
|
||||
NUMBER = "number"
|
||||
INTEGER = "integer"
|
||||
BOOLEAN = "boolean"
|
||||
|
||||
|
||||
class SuggestedField(ApiModel):
|
||||
name: str = Field(description="snake_case field identifier, e.g. 'invoice_number'.")
|
||||
type: SuggestedFieldType
|
||||
description: str = ""
|
||||
|
||||
|
||||
class SuggestSchemaRequest(ApiModel):
|
||||
"""``pages`` drives the basic tier (caller-extracted text); ``content_base64``
|
||||
lets the advanced tier parse the raw file itself. Send either."""
|
||||
|
||||
file_name: str = Field(min_length=1)
|
||||
pages: list[PageText] | None = None
|
||||
content_base64: str | None = None
|
||||
max_fields: int = Field(default=8, ge=1, le=20)
|
||||
|
||||
|
||||
class SuggestSchemaResponse(ApiModel):
|
||||
mode: DocparseTier
|
||||
fields: list[SuggestedField] = Field(default_factory=list)
|
||||
|
||||
|
||||
class SplitPart(ApiModel):
|
||||
start_page: int = Field(ge=1)
|
||||
end_page: int = Field(ge=1)
|
||||
label: str
|
||||
confidence: float = Field(ge=0.0, le=1.0)
|
||||
|
||||
|
||||
class SmartSplitRequest(ApiModel):
|
||||
file_name: str = Field(min_length=1)
|
||||
rule: str = Field(
|
||||
min_length=1, description="Natural-language boundary rule, e.g. 'split where a new invoice starts'."
|
||||
)
|
||||
pages: list[PageText]
|
||||
max_parts: int = Field(default=50, ge=1, le=500)
|
||||
|
||||
|
||||
class SmartSplitResponse(ApiModel):
|
||||
parts: list[SplitPart] = Field(default_factory=list)
|
||||
|
||||
|
||||
class ChunkDocumentRequest(ApiModel):
|
||||
file_name: str = Field(min_length=1)
|
||||
pages: list[PageText] | None = None
|
||||
content_base64: str | None = None
|
||||
chunk_size: int = Field(default=512, ge=64, le=32_768)
|
||||
overlap: int = Field(default=64, ge=0, le=4_096)
|
||||
mode: DocparseMode = DocparseMode.AUTO
|
||||
|
||||
|
||||
class FillDocxRequest(ApiModel):
|
||||
template_base64: str = Field(min_length=1)
|
||||
data: dict[str, JsonValue]
|
||||
|
||||
|
||||
class FillDocxResponse(ApiModel):
|
||||
docx_base64: str
|
||||
replaced: int = Field(ge=0)
|
||||
missing: list[str] = Field(default_factory=list)
|
||||
|
||||
|
||||
class DocparseCapabilities(ApiModel):
|
||||
"""What the engine can actually do right now; Java caches and republishes this."""
|
||||
|
||||
advanced_installed: bool
|
||||
docling_version: str | None = None
|
||||
torch_version: str | None = None
|
||||
models_available: bool = False
|
||||
models_path: str | None = None
|
||||
errors: list[str] = Field(default_factory=list)
|
||||
@@ -0,0 +1,25 @@
|
||||
"""DocParse: document understanding for ingestion pipelines.
|
||||
|
||||
This package holds the basic (text-layer) tier; the advanced tier (Docling
|
||||
layout parsing) is delivered as an optional addon and probed at runtime.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from stirling.docparse.capability import activate_site, probe_capabilities
|
||||
from stirling.docparse.chunking import advanced_chunks, basic_chunks
|
||||
from stirling.docparse.docxfill import fill_docx
|
||||
from stirling.docparse.extractor import ExtractFieldsAgent
|
||||
from stirling.docparse.splitter import SmartSplitAgent
|
||||
from stirling.docparse.suggest_schema import SuggestSchemaAgent
|
||||
|
||||
__all__ = [
|
||||
"ExtractFieldsAgent",
|
||||
"SmartSplitAgent",
|
||||
"SuggestSchemaAgent",
|
||||
"activate_site",
|
||||
"advanced_chunks",
|
||||
"basic_chunks",
|
||||
"fill_docx",
|
||||
"probe_capabilities",
|
||||
]
|
||||
@@ -0,0 +1,104 @@
|
||||
"""Probe whether the docparse addon (Docling) is importable and its models present.
|
||||
|
||||
The addon arrives either baked into the engine image (uv extra) or dynamically
|
||||
installed into ``$STIRLING_DOCPARSE_HOME/site`` on a mounted volume; in the
|
||||
latter case :func:`activate_site` prepends that directory to ``sys.path`` at
|
||||
startup so the probe and the parser see it.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import importlib
|
||||
import importlib.metadata
|
||||
import importlib.util
|
||||
import logging
|
||||
import sys
|
||||
import threading
|
||||
from pathlib import Path
|
||||
|
||||
from stirling.contracts.docparse import DocparseCapabilities
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
_lock = threading.Lock()
|
||||
_cached: DocparseCapabilities | None = None
|
||||
|
||||
|
||||
def site_dir(docparse_home: str) -> Path | None:
|
||||
return Path(docparse_home) / "site" if docparse_home else None
|
||||
|
||||
|
||||
def models_dir(docparse_home: str) -> Path | None:
|
||||
return Path(docparse_home) / "models" if docparse_home else None
|
||||
|
||||
|
||||
def activate_site(docparse_home: str) -> bool:
|
||||
"""Prepend the dynamic-install site dir to ``sys.path`` if it exists.
|
||||
|
||||
Idempotent; returns True when the path is active. Called once from the app
|
||||
lifespan before the first capability probe.
|
||||
"""
|
||||
site = site_dir(docparse_home)
|
||||
if site is None or not site.is_dir():
|
||||
return False
|
||||
site_str = str(site)
|
||||
if site_str not in sys.path:
|
||||
sys.path.insert(0, site_str)
|
||||
logger.info("docparse: activated dynamic site dir %s", site_str)
|
||||
return True
|
||||
|
||||
|
||||
def _version_of(distribution: str) -> str | None:
|
||||
try:
|
||||
return importlib.metadata.version(distribution)
|
||||
except importlib.metadata.PackageNotFoundError:
|
||||
return None
|
||||
|
||||
|
||||
def _models_available(docparse_home: str) -> tuple[bool, str | None]:
|
||||
"""Models count as available when the prefetch dir has content, or when no
|
||||
home is configured at all (Docling then downloads into its default cache)."""
|
||||
directory = models_dir(docparse_home)
|
||||
if directory is None:
|
||||
return True, None
|
||||
if directory.is_dir() and any(directory.iterdir()):
|
||||
return True, str(directory)
|
||||
return False, str(directory)
|
||||
|
||||
|
||||
def probe_capabilities(docparse_home: str, *, refresh: bool = False) -> DocparseCapabilities:
|
||||
"""Report what the docparse layer can do right now. Cached after first call
|
||||
(imports are expensive); ``refresh=True`` re-probes, e.g. after a dynamic install."""
|
||||
global _cached
|
||||
with _lock:
|
||||
if _cached is not None and not refresh:
|
||||
return _cached
|
||||
|
||||
errors: list[str] = []
|
||||
advanced = importlib.util.find_spec("docling") is not None
|
||||
docling_version: str | None = None
|
||||
torch_version: str | None = None
|
||||
if advanced:
|
||||
docling_version = _version_of("docling")
|
||||
torch_version = _version_of("torch")
|
||||
if torch_version is None:
|
||||
advanced = False
|
||||
errors.append("docling present but torch missing; install is incomplete")
|
||||
models_ok, models_path = _models_available(docparse_home)
|
||||
|
||||
_cached = DocparseCapabilities(
|
||||
advanced_installed=advanced,
|
||||
docling_version=docling_version,
|
||||
torch_version=torch_version,
|
||||
models_available=models_ok,
|
||||
models_path=models_path,
|
||||
errors=errors,
|
||||
)
|
||||
logger.info(
|
||||
"docparse capabilities: advanced=%s docling=%s torch=%s models=%s",
|
||||
advanced,
|
||||
docling_version,
|
||||
torch_version,
|
||||
models_ok,
|
||||
)
|
||||
return _cached
|
||||
@@ -0,0 +1,96 @@
|
||||
"""RAG chunking, both tiers.
|
||||
|
||||
Basic: the existing character chunker per page. Advanced: structure-aware
|
||||
packing over parse blocks - heading-bounded, heading breadcrumbs attached,
|
||||
page ranges tracked. No tokenizer dependency; sizes are characters, matching
|
||||
the rest of the engine."""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from stirling.contracts.docparse import BlockType, ChunkDocumentResponse, DocChunk, DocparseTier, ParseDocumentResponse
|
||||
from stirling.contracts.documents import PageText
|
||||
from stirling.documents.chunker import chunk_text
|
||||
|
||||
# Blocks that are noise for retrieval purposes.
|
||||
_SKIP_TYPES = {BlockType.PAGE_HEADER, BlockType.PAGE_FOOTER}
|
||||
|
||||
|
||||
def basic_chunks(pages: list[PageText], chunk_size: int, overlap: int) -> ChunkDocumentResponse:
|
||||
chunks: list[DocChunk] = []
|
||||
for page in pages:
|
||||
for piece in chunk_text(page.text, chunk_size=chunk_size, overlap=overlap):
|
||||
chunks.append(
|
||||
DocChunk(
|
||||
index=len(chunks),
|
||||
text=piece,
|
||||
page_start=page.page_number,
|
||||
page_end=page.page_number,
|
||||
)
|
||||
)
|
||||
return ChunkDocumentResponse(mode=DocparseTier.BASIC, chunks=chunks)
|
||||
|
||||
|
||||
def advanced_chunks(parse: ParseDocumentResponse, chunk_size: int, overlap: int) -> ChunkDocumentResponse:
|
||||
"""Pack layout blocks into chunks that never straddle a heading boundary."""
|
||||
chunks: list[DocChunk] = []
|
||||
heading_path: list[str] = []
|
||||
buffer: list[str] = []
|
||||
buffer_len = 0
|
||||
page_start: int | None = None
|
||||
page_end: int | None = None
|
||||
buffer_headings: list[str] = []
|
||||
|
||||
def flush() -> None:
|
||||
nonlocal buffer, buffer_len, page_start, page_end, buffer_headings
|
||||
text = "\n\n".join(buffer).strip()
|
||||
if text:
|
||||
chunks.append(
|
||||
DocChunk(
|
||||
index=len(chunks),
|
||||
text=text,
|
||||
page_start=page_start,
|
||||
page_end=page_end,
|
||||
heading_path=list(buffer_headings),
|
||||
)
|
||||
)
|
||||
buffer = []
|
||||
buffer_len = 0
|
||||
page_start = None
|
||||
page_end = None
|
||||
buffer_headings = list(heading_path)
|
||||
|
||||
buffer_headings = []
|
||||
for block in parse.blocks:
|
||||
if block.type in _SKIP_TYPES:
|
||||
continue
|
||||
if block.type is BlockType.HEADING:
|
||||
flush()
|
||||
heading_path = [*heading_path[-2:], block.text.strip()] if block.text.strip() else heading_path
|
||||
buffer_headings = list(heading_path)
|
||||
continue
|
||||
|
||||
text = block.text
|
||||
if not text.strip():
|
||||
continue
|
||||
if buffer_len + len(text) > chunk_size and buffer:
|
||||
flush()
|
||||
# A single oversized block falls back to the character chunker.
|
||||
if len(text) > chunk_size:
|
||||
for piece in chunk_text(text, chunk_size=chunk_size, overlap=overlap):
|
||||
chunks.append(
|
||||
DocChunk(
|
||||
index=len(chunks),
|
||||
text=piece,
|
||||
page_start=block.page,
|
||||
page_end=block.page,
|
||||
heading_path=list(buffer_headings),
|
||||
)
|
||||
)
|
||||
continue
|
||||
buffer.append(text)
|
||||
buffer_len += len(text)
|
||||
page_start = block.page if page_start is None else min(page_start, block.page)
|
||||
page_end = block.page if page_end is None else max(page_end, block.page)
|
||||
|
||||
flush()
|
||||
return ChunkDocumentResponse(mode=DocparseTier.ADVANCED, chunks=chunks)
|
||||
@@ -0,0 +1,178 @@
|
||||
"""Fill DOCX templates from JSON data: ``{{ dotted.path }}`` placeholders.
|
||||
|
||||
Scalar placeholders are replaced everywhere (body, tables, headers, footers).
|
||||
A table row whose text contains ``{{#items.field}}`` markers is treated as a
|
||||
row template: it is cloned once per element of the ``items`` array. Unresolved
|
||||
placeholders are left in place and reported back so the caller can surface them.
|
||||
|
||||
Formatting caveat: a placeholder split across styled runs collapses that
|
||||
paragraph's text into its first run's style.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import base64
|
||||
import copy
|
||||
import io
|
||||
import re
|
||||
from typing import Any
|
||||
|
||||
from pydantic import JsonValue
|
||||
|
||||
from stirling.contracts.docparse import FillDocxRequest, FillDocxResponse
|
||||
|
||||
_PLACEHOLDER = re.compile(r"\{\{\s*(#?[\w.]+)\s*\}\}")
|
||||
|
||||
|
||||
def _resolve(path: str, data: dict[str, Any]) -> Any | None:
|
||||
node: Any = data
|
||||
for part in path.split("."):
|
||||
if isinstance(node, dict) and part in node:
|
||||
node = node[part]
|
||||
else:
|
||||
return None
|
||||
return node
|
||||
|
||||
|
||||
def _render_scalar(value: Any) -> str:
|
||||
if value is None:
|
||||
return ""
|
||||
if isinstance(value, bool):
|
||||
return "true" if value else "false"
|
||||
if isinstance(value, list):
|
||||
return ", ".join(_render_scalar(v) for v in value)
|
||||
return str(value)
|
||||
|
||||
|
||||
class _Stats:
|
||||
def __init__(self) -> None:
|
||||
self.replaced = 0
|
||||
self.missing: set[str] = set()
|
||||
|
||||
|
||||
def _fill_paragraph(paragraph: Any, data: dict[str, Any], stats: _Stats) -> None:
|
||||
text = paragraph.text
|
||||
if "{{" not in text:
|
||||
return
|
||||
|
||||
def substitute(match: re.Match[str]) -> str:
|
||||
path = match.group(1)
|
||||
if path.startswith("#"):
|
||||
return match.group(0) # row-template marker, handled at table level
|
||||
value = _resolve(path, data)
|
||||
if value is None:
|
||||
stats.missing.add(path)
|
||||
return match.group(0)
|
||||
stats.replaced += 1
|
||||
return _render_scalar(value)
|
||||
|
||||
rendered = _PLACEHOLDER.sub(substitute, text)
|
||||
if rendered == text:
|
||||
return
|
||||
# Collapse into the first run to survive placeholders split across runs.
|
||||
if paragraph.runs:
|
||||
paragraph.runs[0].text = rendered
|
||||
for run in paragraph.runs[1:]:
|
||||
run.text = ""
|
||||
else:
|
||||
paragraph.add_run(rendered)
|
||||
|
||||
|
||||
def _row_template_array(row: Any) -> str | None:
|
||||
"""Return the array name when the row carries ``{{#name.field}}`` markers."""
|
||||
names = {
|
||||
match.group(1)[1:].split(".")[0]
|
||||
for cell in row.cells
|
||||
for match in _PLACEHOLDER.finditer(cell.text)
|
||||
if match.group(1).startswith("#")
|
||||
}
|
||||
return names.pop() if len(names) == 1 else None
|
||||
|
||||
|
||||
def _fill_table(table: Any, data: dict[str, Any], stats: _Stats) -> None:
|
||||
for row in list(table.rows):
|
||||
array_name = _row_template_array(row)
|
||||
if array_name is None:
|
||||
continue
|
||||
items = _resolve(array_name, data)
|
||||
if not isinstance(items, list):
|
||||
stats.missing.add(array_name)
|
||||
continue
|
||||
for _ in items:
|
||||
new_row = copy.deepcopy(row._tr)
|
||||
row._tr.addprevious(new_row)
|
||||
# Clones sit before the template; rewrite their markers, then drop the template.
|
||||
_rewrite_cloned_rows(table, row, array_name, items, data, stats)
|
||||
row._tr.getparent().remove(row._tr)
|
||||
|
||||
|
||||
def _rewrite_cloned_rows(
|
||||
table: Any, template_row: Any, array_name: str, items: list[Any], data: dict[str, Any], stats: _Stats
|
||||
) -> None:
|
||||
marker_prefix = f"#{array_name}"
|
||||
clones = [
|
||||
r for r in table.rows if r._tr is not template_row._tr and marker_prefix in "".join(c.text for c in r.cells)
|
||||
]
|
||||
for row, item in zip(clones, items, strict=False):
|
||||
scoped = dict(data)
|
||||
scoped[array_name] = item if isinstance(item, dict) else {"value": item}
|
||||
for cell in row.cells:
|
||||
for paragraph in cell.paragraphs:
|
||||
text = paragraph.text
|
||||
|
||||
def substitute(match: re.Match[str]) -> str:
|
||||
path = match.group(1)
|
||||
if not path.startswith(marker_prefix):
|
||||
return match.group(0)
|
||||
item_path = path[1:] # "#items.field" -> "items.field"
|
||||
value = _resolve(item_path, scoped)
|
||||
if value is None and "." not in item_path:
|
||||
value = scoped[array_name].get("value") if isinstance(scoped[array_name], dict) else None
|
||||
if value is None:
|
||||
stats.missing.add(item_path)
|
||||
return match.group(0)
|
||||
stats.replaced += 1
|
||||
return _render_scalar(value)
|
||||
|
||||
rendered = _PLACEHOLDER.sub(substitute, text)
|
||||
if rendered != text:
|
||||
if paragraph.runs:
|
||||
paragraph.runs[0].text = rendered
|
||||
for run in paragraph.runs[1:]:
|
||||
run.text = ""
|
||||
else:
|
||||
paragraph.add_run(rendered)
|
||||
|
||||
|
||||
def _walk_paragraphs(document: Any) -> list[tuple[Any, Any]]:
|
||||
"""Yield (paragraph, containing table or None) across body, tables, headers, footers."""
|
||||
found: list[tuple[Any, Any]] = [(p, None) for p in document.paragraphs]
|
||||
for table in document.tables:
|
||||
for row in table.rows:
|
||||
for cell in row.cells:
|
||||
found.extend((p, table) for p in cell.paragraphs)
|
||||
for section in document.sections:
|
||||
for part in (section.header, section.footer):
|
||||
found.extend((p, None) for p in part.paragraphs)
|
||||
return found
|
||||
|
||||
|
||||
def fill_docx(request: FillDocxRequest) -> FillDocxResponse:
|
||||
import docx # local import: python-docx is small but only needed here
|
||||
|
||||
data: dict[str, JsonValue] = dict(request.data)
|
||||
document = docx.Document(io.BytesIO(base64.b64decode(request.template_base64)))
|
||||
stats = _Stats()
|
||||
|
||||
for table in document.tables:
|
||||
_fill_table(table, data, stats)
|
||||
for paragraph, _table in _walk_paragraphs(document):
|
||||
_fill_paragraph(paragraph, data, stats)
|
||||
|
||||
out = io.BytesIO()
|
||||
document.save(out)
|
||||
return FillDocxResponse(
|
||||
docx_base64=base64.b64encode(out.getvalue()).decode("ascii"),
|
||||
replaced=stats.replaced,
|
||||
missing=sorted(stats.missing),
|
||||
)
|
||||
@@ -0,0 +1,146 @@
|
||||
"""Extraction accuracy harness: score a gold-labelled case set against a live engine.
|
||||
|
||||
Case layout (one directory per document):
|
||||
|
||||
cases/
|
||||
invoice-001/
|
||||
input.pdf # the document
|
||||
expected.json # {"fieldsSchema": {...}, "fields": {"invoice_number": "INV-1", ...},
|
||||
# "pages": [{"pageNumber": 1, "text": "..."}]? (optional, for basic tier)}
|
||||
|
||||
Run:
|
||||
uv run python -m stirling.docparse.evals cases/ --engine http://localhost:5001 --output report.json
|
||||
|
||||
Scoring per field: exact match, then normalized match (case/whitespace/currency
|
||||
punctuation collapsed, numeric tolerance 1e-6). The report aggregates per-case
|
||||
and overall accuracy so pipeline changes can be regression-tracked. Stdlib
|
||||
HTTP only - the harness must run anywhere the engine runs.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import argparse
|
||||
import base64
|
||||
import json
|
||||
import re
|
||||
import sys
|
||||
import urllib.error
|
||||
import urllib.request
|
||||
from pathlib import Path
|
||||
from typing import Any
|
||||
|
||||
_NORMALIZE_STRIP = re.compile(r"[\s,€$£%]+")
|
||||
|
||||
|
||||
def normalized_equal(expected: Any, actual: Any) -> bool:
|
||||
if expected is None or actual is None:
|
||||
return expected is actual
|
||||
try:
|
||||
return abs(float(expected) - float(actual)) < 1e-6
|
||||
except (TypeError, ValueError):
|
||||
pass
|
||||
if isinstance(expected, list) and isinstance(actual, list):
|
||||
return len(expected) == len(actual) and all(normalized_equal(e, a) for e, a in zip(expected, actual))
|
||||
return _NORMALIZE_STRIP.sub("", str(expected)).casefold() == _NORMALIZE_STRIP.sub("", str(actual)).casefold()
|
||||
|
||||
|
||||
def _call_extract(engine: str, secret: str | None, payload: dict[str, Any]) -> dict[str, Any]:
|
||||
request = urllib.request.Request(
|
||||
f"{engine.rstrip('/')}/api/v1/docparse/extract",
|
||||
data=json.dumps(payload).encode("utf-8"),
|
||||
headers={"Content-Type": "application/json", **({"X-Engine-Auth": secret} if secret else {})},
|
||||
method="POST",
|
||||
)
|
||||
with urllib.request.urlopen(request, timeout=600) as response:
|
||||
return json.loads(response.read().decode("utf-8"))
|
||||
|
||||
|
||||
def score_case(engine: str, secret: str | None, case_dir: Path) -> dict[str, Any]:
|
||||
expected_spec = json.loads((case_dir / "expected.json").read_text(encoding="utf-8"))
|
||||
payload: dict[str, Any] = {
|
||||
"fileName": "input.pdf",
|
||||
"fieldsSchema": expected_spec["fieldsSchema"],
|
||||
}
|
||||
input_pdf = case_dir / "input.pdf"
|
||||
if input_pdf.exists():
|
||||
payload["contentBase64"] = base64.b64encode(input_pdf.read_bytes()).decode("ascii")
|
||||
if expected_spec.get("pages"):
|
||||
payload["pages"] = expected_spec["pages"]
|
||||
|
||||
response = _call_extract(engine, secret, payload)
|
||||
actual = {field["name"]: field for field in response.get("fields", [])}
|
||||
|
||||
fields: list[dict[str, Any]] = []
|
||||
exact = 0
|
||||
normalized = 0
|
||||
for name, expected_value in expected_spec.get("fields", {}).items():
|
||||
actual_field = actual.get(name, {})
|
||||
actual_value = actual_field.get("value")
|
||||
is_exact = expected_value == actual_value
|
||||
is_normalized = is_exact or normalized_equal(expected_value, actual_value)
|
||||
exact += is_exact
|
||||
normalized += is_normalized
|
||||
fields.append(
|
||||
{
|
||||
"name": name,
|
||||
"expected": expected_value,
|
||||
"actual": actual_value,
|
||||
"exact": is_exact,
|
||||
"normalized": is_normalized,
|
||||
"confidence": actual_field.get("confidence"),
|
||||
"cited": bool(actual_field.get("citations")),
|
||||
}
|
||||
)
|
||||
|
||||
total = len(fields) or 1
|
||||
return {
|
||||
"case": case_dir.name,
|
||||
"mode": response.get("mode"),
|
||||
"fields": fields,
|
||||
"exactAccuracy": round(exact / total, 4),
|
||||
"normalizedAccuracy": round(normalized / total, 4),
|
||||
}
|
||||
|
||||
|
||||
def run(cases_root: Path, engine: str, secret: str | None) -> dict[str, Any]:
|
||||
case_dirs = sorted(d for d in cases_root.iterdir() if d.is_dir() and (d / "expected.json").exists())
|
||||
results: list[dict[str, Any]] = []
|
||||
failures: list[dict[str, str]] = []
|
||||
for case_dir in case_dirs:
|
||||
try:
|
||||
results.append(score_case(engine, secret, case_dir))
|
||||
except (urllib.error.URLError, OSError, KeyError, ValueError) as error:
|
||||
failures.append({"case": case_dir.name, "error": str(error)})
|
||||
|
||||
scored = [r for r in results if r["fields"]]
|
||||
overall = {
|
||||
"cases": len(case_dirs),
|
||||
"scored": len(scored),
|
||||
"errors": failures,
|
||||
"exactAccuracy": round(sum(r["exactAccuracy"] for r in scored) / len(scored), 4) if scored else 0.0,
|
||||
"normalizedAccuracy": round(sum(r["normalizedAccuracy"] for r in scored) / len(scored), 4) if scored else 0.0,
|
||||
"results": results,
|
||||
}
|
||||
return overall
|
||||
|
||||
|
||||
def main() -> int:
|
||||
parser = argparse.ArgumentParser(description="Score docparse extraction against a gold case set.")
|
||||
parser.add_argument("cases", help="Directory of case subdirectories")
|
||||
parser.add_argument("--engine", default="http://localhost:5001", help="Engine base URL")
|
||||
parser.add_argument("--secret", default=None, help="X-Engine-Auth shared secret, if the engine requires it")
|
||||
parser.add_argument("--output", default=None, help="Write the JSON report here (default: stdout)")
|
||||
args = parser.parse_args()
|
||||
|
||||
report = run(Path(args.cases), args.engine, args.secret)
|
||||
rendered = json.dumps(report, indent=2)
|
||||
if args.output:
|
||||
Path(args.output).write_text(rendered, encoding="utf-8")
|
||||
print(f"exact={report['exactAccuracy']} normalized={report['normalizedAccuracy']} -> {args.output}")
|
||||
else:
|
||||
print(rendered)
|
||||
return 0 if not report["errors"] else 1
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
sys.exit(main())
|
||||
@@ -0,0 +1,320 @@
|
||||
"""Schema-driven field extraction with grounded citations and confidence.
|
||||
|
||||
The caller supplies a JSON Schema (subset: scalar types, enums, arrays of
|
||||
scalars, nested objects). We build a dynamic pydantic output model where every
|
||||
leaf answers ``{value, quote, confidence}``, run one smart-model pass, then
|
||||
ground each quote against the page text in code. Model confidence is damped
|
||||
when a quote can't be found - the model asserts, the grounding decides how
|
||||
much to believe it.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import logging
|
||||
import re
|
||||
from typing import Any
|
||||
|
||||
from pydantic import BaseModel, Field, JsonValue, create_model
|
||||
from pydantic_ai import Agent
|
||||
|
||||
from stirling.agents.output_mode import output_retries, structured_output
|
||||
from stirling.contracts.docparse import (
|
||||
DocparseTier,
|
||||
ExtractedField,
|
||||
ExtractFieldsRequest,
|
||||
ExtractFieldsResponse,
|
||||
FieldCitation,
|
||||
ParseDocumentResponse,
|
||||
)
|
||||
from stirling.contracts.documents import PageText
|
||||
from stirling.models import ApiModel
|
||||
from stirling.services import AppRuntime
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# Confidence multiplier when the supporting quote can't be found in the document.
|
||||
UNGROUNDED_PENALTY = 0.6
|
||||
# Floor when the model omitted quote/confidence but the value itself is found
|
||||
# verbatim in the document - the grounding is real even if the model was terse.
|
||||
VALUE_GROUNDED_FLOOR = 0.5
|
||||
MAX_SCHEMA_DEPTH = 3
|
||||
MAX_FIELDS = 100
|
||||
|
||||
_SYSTEM_PROMPT = (
|
||||
"You extract structured fields from a document.\n"
|
||||
"\n"
|
||||
"Rules:\n"
|
||||
"- For every field, return the value exactly as the schema types it, a short VERBATIM quote "
|
||||
"from the document that supports it, and your confidence from 0.0 to 1.0.\n"
|
||||
"- The quote must be copied character-for-character from the document text, at most 200 characters.\n"
|
||||
"- If the document does not contain the field, return value null, quote null, confidence 0.0. "
|
||||
"Never guess or fabricate.\n"
|
||||
"- Dates: return them formatted as the schema/description asks; quote the original text.\n"
|
||||
"- The document may be in any language."
|
||||
)
|
||||
|
||||
|
||||
class SchemaError(ValueError):
|
||||
"""The supplied JSON Schema is outside the supported subset."""
|
||||
|
||||
|
||||
def _scalar_type(spec: dict[str, Any]) -> Any:
|
||||
# Enums stay str-typed; the allowed values travel in the field description
|
||||
# (dynamic Literal types don't typecheck and local models handle them badly).
|
||||
match spec.get("type"):
|
||||
case "string":
|
||||
return str
|
||||
case "integer":
|
||||
return int
|
||||
case "number":
|
||||
return float
|
||||
case "boolean":
|
||||
return bool
|
||||
case _:
|
||||
raise SchemaError(f"Unsupported schema type: {spec.get('type')!r}")
|
||||
|
||||
|
||||
def _describe(spec: dict[str, Any]) -> str | None:
|
||||
description = spec.get("description") if isinstance(spec.get("description"), str) else None
|
||||
enum = spec.get("enum")
|
||||
if isinstance(enum, list) and enum:
|
||||
allowed = ", ".join(str(v) for v in enum)
|
||||
description = f"{description + ' ' if description else ''}Allowed values: {allowed}."
|
||||
return description
|
||||
|
||||
|
||||
def _leaf_answer_model(name: str, value_type: Any, description: str | None) -> type[BaseModel]:
|
||||
return create_model(
|
||||
f"Answer_{re.sub(r'[^A-Za-z0-9]', '_', name)}",
|
||||
__base__=ApiModel,
|
||||
value=(value_type | None, Field(default=None, description=description or None)),
|
||||
quote=(str | None, Field(default=None, max_length=400)),
|
||||
confidence=(float, Field(default=0.0, ge=0.0, le=1.0)),
|
||||
)
|
||||
|
||||
|
||||
def build_output_model(
|
||||
fields_schema: dict[str, Any], *, _depth: int = 0, _name: str = "ExtractionOutput"
|
||||
) -> type[BaseModel]:
|
||||
"""Turn the caller's JSON Schema into a pydantic model of leaf answers."""
|
||||
if _depth > MAX_SCHEMA_DEPTH:
|
||||
raise SchemaError(f"Schema nesting deeper than {MAX_SCHEMA_DEPTH} is not supported")
|
||||
properties = fields_schema.get("properties")
|
||||
if not isinstance(properties, dict) or not properties:
|
||||
raise SchemaError("Schema must be an object with a non-empty 'properties' map")
|
||||
if len(properties) > MAX_FIELDS:
|
||||
raise SchemaError(f"Schema has more than {MAX_FIELDS} fields")
|
||||
|
||||
model_fields: dict[str, Any] = {}
|
||||
for raw_name, spec in properties.items():
|
||||
name = str(raw_name)
|
||||
if not re.fullmatch(r"[A-Za-z_][A-Za-z0-9_]*", name):
|
||||
raise SchemaError(f"Field name {name!r} must be a valid identifier")
|
||||
if not isinstance(spec, dict):
|
||||
raise SchemaError(f"Field {name!r} must map to a schema object")
|
||||
description = _describe(spec)
|
||||
|
||||
if spec.get("type") == "object":
|
||||
nested = build_output_model(spec, _depth=_depth + 1, _name=f"{_name}_{name}")
|
||||
model_fields[name] = (nested, Field(...))
|
||||
elif spec.get("type") == "array":
|
||||
items = spec.get("items")
|
||||
if not isinstance(items, dict):
|
||||
raise SchemaError(f"Array field {name!r} needs an 'items' schema")
|
||||
if items.get("type") == "object":
|
||||
raise SchemaError(f"Array field {name!r}: arrays of objects are not supported yet")
|
||||
item_type: Any = _scalar_type(items)
|
||||
answer = _leaf_answer_model(name, list[item_type], description)
|
||||
model_fields[name] = (answer, Field(...))
|
||||
else:
|
||||
answer = _leaf_answer_model(name, _scalar_type(spec), description)
|
||||
model_fields[name] = (answer, Field(...))
|
||||
|
||||
return create_model(_name, __base__=ApiModel, **model_fields)
|
||||
|
||||
|
||||
_WHITESPACE = re.compile(r"\s+")
|
||||
|
||||
|
||||
def _normalize(text: str) -> str:
|
||||
return _WHITESPACE.sub(" ", text).strip().casefold()
|
||||
|
||||
|
||||
def find_quote(quote: str, pages: list[PageText]) -> tuple[int, int, int] | None:
|
||||
"""Locate ``quote`` in the page texts, whitespace-insensitively.
|
||||
|
||||
Returns (page_number, start_offset, end_offset) into the page's raw text,
|
||||
or None. Offsets are approximate under whitespace collapsing: we search the
|
||||
normalized page, then map back by counting non-space characters.
|
||||
"""
|
||||
needle = _normalize(quote)
|
||||
if not needle:
|
||||
return None
|
||||
for page in pages:
|
||||
haystack = _normalize(page.text)
|
||||
idx = haystack.find(needle)
|
||||
if idx < 0:
|
||||
continue
|
||||
start = _denormalize_offset(page.text, idx)
|
||||
end = _denormalize_offset(page.text, idx + len(needle))
|
||||
return page.page_number, start, min(end, len(page.text))
|
||||
return None
|
||||
|
||||
|
||||
def _denormalize_offset(raw: str, normalized_offset: int) -> int:
|
||||
"""Map an offset in the normalized string back into the raw string."""
|
||||
count = 0
|
||||
in_space = True # leading whitespace is stripped by _normalize
|
||||
for i, ch in enumerate(raw):
|
||||
if ch.isspace():
|
||||
if in_space:
|
||||
continue
|
||||
in_space = True
|
||||
else:
|
||||
in_space = False
|
||||
if count >= normalized_offset:
|
||||
return i
|
||||
count += 1
|
||||
return len(raw)
|
||||
|
||||
|
||||
def _bbox_for_quote(quote: str, parse: ParseDocumentResponse | None) -> list[float] | None:
|
||||
if parse is None:
|
||||
return None
|
||||
needle = _normalize(quote)
|
||||
if not needle:
|
||||
return None
|
||||
for block in parse.blocks:
|
||||
if block.bbox is not None and needle in _normalize(block.text):
|
||||
return block.bbox
|
||||
return None
|
||||
|
||||
|
||||
def flatten_answers(output: BaseModel, prefix: str = "") -> list[tuple[str, JsonValue, str | None, float]]:
|
||||
"""Walk the dynamic output model into (dotted_name, value, quote, confidence) leaves."""
|
||||
leaves: list[tuple[str, JsonValue, str | None, float]] = []
|
||||
for name in type(output).model_fields:
|
||||
node = getattr(output, name)
|
||||
dotted = f"{prefix}{name}"
|
||||
if isinstance(node, BaseModel) and "confidence" in type(node).model_fields:
|
||||
value = getattr(node, "value", None)
|
||||
quote = getattr(node, "quote", None)
|
||||
confidence = float(getattr(node, "confidence", 0.0) or 0.0)
|
||||
leaves.append((dotted, value, quote, confidence))
|
||||
elif isinstance(node, BaseModel):
|
||||
leaves.extend(flatten_answers(node, prefix=f"{dotted}."))
|
||||
return leaves
|
||||
|
||||
|
||||
def _format_pages(pages: list[PageText], max_characters: int) -> str:
|
||||
parts: list[str] = []
|
||||
used = 0
|
||||
for page in pages:
|
||||
snippet = page.text[: max(0, max_characters - used)]
|
||||
parts.append(f"[Page {page.page_number}]\n{snippet}")
|
||||
used += len(snippet)
|
||||
if used >= max_characters:
|
||||
break
|
||||
return "\n\n".join(parts) if parts else "(no extractable text)"
|
||||
|
||||
|
||||
def pages_from_parse(parse: ParseDocumentResponse) -> list[PageText]:
|
||||
"""Rebuild per-page text from parse blocks (advanced path with no caller text)."""
|
||||
by_page: dict[int, list[str]] = {}
|
||||
for block in parse.blocks:
|
||||
by_page.setdefault(block.page, []).append(block.text)
|
||||
return [PageText(page_number=n, text="\n".join(t)) for n, t in sorted(by_page.items())]
|
||||
|
||||
|
||||
class ExtractFieldsAgent:
|
||||
"""One smart-model pass over the document, then code-side grounding."""
|
||||
|
||||
def __init__(self, runtime: AppRuntime) -> None:
|
||||
self.runtime = runtime
|
||||
|
||||
async def extract(
|
||||
self,
|
||||
request: ExtractFieldsRequest,
|
||||
pages: list[PageText],
|
||||
parse: ParseDocumentResponse | None,
|
||||
) -> ExtractFieldsResponse:
|
||||
output_model = build_output_model(dict(request.fields_schema))
|
||||
provider = self.runtime.settings.chat_provider
|
||||
agent: Agent[None, BaseModel] = Agent(
|
||||
model=self.runtime.smart_model,
|
||||
output_type=structured_output([output_model], chat_provider=provider),
|
||||
system_prompt=_SYSTEM_PROMPT,
|
||||
model_settings=self.runtime.smart_model_settings,
|
||||
retries=output_retries(provider),
|
||||
)
|
||||
prompt = self._build_prompt(request, pages)
|
||||
result = await agent.run(prompt)
|
||||
fields = self._ground(result.output, pages, parse)
|
||||
overall = round(min((f.confidence for f in fields), default=0.0), 4)
|
||||
tier = DocparseTier.ADVANCED if parse is not None else DocparseTier.BASIC
|
||||
return ExtractFieldsResponse(mode=tier, fields=fields, overall_confidence=overall)
|
||||
|
||||
def _build_prompt(self, request: ExtractFieldsRequest, pages: list[PageText]) -> str:
|
||||
instructions = f"Additional instructions: {request.instructions}\n\n" if request.instructions else ""
|
||||
return (
|
||||
f"{instructions}"
|
||||
f"Document file name: {request.file_name}\n"
|
||||
f"Document content:\n{_format_pages(pages, self.runtime.settings.max_characters)}"
|
||||
)
|
||||
|
||||
@staticmethod
|
||||
def _ground(
|
||||
output: BaseModel,
|
||||
pages: list[PageText],
|
||||
parse: ParseDocumentResponse | None,
|
||||
) -> list[ExtractedField]:
|
||||
fields: list[ExtractedField] = []
|
||||
for name, value, quote, model_confidence in flatten_answers(output):
|
||||
citations: list[FieldCitation] = []
|
||||
confidence = max(0.0, min(1.0, model_confidence))
|
||||
if value is None:
|
||||
confidence = 0.0
|
||||
elif quote:
|
||||
located = find_quote(quote, pages)
|
||||
if located is not None:
|
||||
page_number, start, end = located
|
||||
citations.append(
|
||||
FieldCitation(
|
||||
page=page_number,
|
||||
bbox=_bbox_for_quote(quote, parse),
|
||||
quote=quote,
|
||||
start_offset=start,
|
||||
end_offset=end,
|
||||
)
|
||||
)
|
||||
else:
|
||||
citations.append(FieldCitation(page=None, bbox=None, quote=quote))
|
||||
confidence *= UNGROUNDED_PENALTY
|
||||
else:
|
||||
# Terse models (local Ollama especially) often skip the quote;
|
||||
# grounding the value itself keeps citations and a usable score.
|
||||
value_text = _render_value(value)
|
||||
located = find_quote(value_text, pages) if value_text else None
|
||||
if located is not None:
|
||||
page_number, start, end = located
|
||||
citations.append(
|
||||
FieldCitation(
|
||||
page=page_number,
|
||||
bbox=_bbox_for_quote(value_text, parse),
|
||||
quote=value_text,
|
||||
start_offset=start,
|
||||
end_offset=end,
|
||||
)
|
||||
)
|
||||
confidence = max(confidence, VALUE_GROUNDED_FLOOR)
|
||||
else:
|
||||
confidence *= UNGROUNDED_PENALTY
|
||||
fields.append(ExtractedField(name=name, value=value, confidence=round(confidence, 4), citations=citations))
|
||||
return fields
|
||||
|
||||
|
||||
def _render_value(value: JsonValue) -> str:
|
||||
"""A searchable text form of a leaf value; empty when nothing sensible exists."""
|
||||
if value is None or isinstance(value, (dict, list)) or isinstance(value, bool):
|
||||
return ""
|
||||
return str(value)
|
||||
@@ -0,0 +1,188 @@
|
||||
"""Advanced-tier document parsing via Docling.
|
||||
|
||||
Everything Docling is imported lazily through :mod:`importlib` so this module
|
||||
imports cleanly (and pyright passes) when the addon isn't installed. Callers
|
||||
must check :func:`stirling.docparse.capability.probe_capabilities` first; the
|
||||
route returns 501 otherwise.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import importlib
|
||||
import io
|
||||
import logging
|
||||
import threading
|
||||
from typing import Any
|
||||
|
||||
from stirling.contracts.docparse import (
|
||||
BlockType,
|
||||
DocBlock,
|
||||
DocparseTier,
|
||||
DocTable,
|
||||
ParseDocumentResponse,
|
||||
)
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
_converter_lock = threading.Lock()
|
||||
_converter: Any | None = None
|
||||
_converter_key: tuple[str, bool] | None = None
|
||||
|
||||
# Docling DocItemLabel values → our normalized block vocabulary.
|
||||
_LABEL_MAP: dict[str, BlockType] = {
|
||||
"title": BlockType.HEADING,
|
||||
"section_header": BlockType.HEADING,
|
||||
"paragraph": BlockType.PARAGRAPH,
|
||||
"text": BlockType.PARAGRAPH,
|
||||
"list_item": BlockType.LIST_ITEM,
|
||||
"table": BlockType.TABLE,
|
||||
"picture": BlockType.FIGURE,
|
||||
"chart": BlockType.FIGURE,
|
||||
"caption": BlockType.CAPTION,
|
||||
"code": BlockType.CODE,
|
||||
"formula": BlockType.FORMULA,
|
||||
"page_header": BlockType.PAGE_HEADER,
|
||||
"page_footer": BlockType.PAGE_FOOTER,
|
||||
"footnote": BlockType.FOOTNOTE,
|
||||
}
|
||||
|
||||
|
||||
def _get_converter(artifacts_path: str | None, with_ocr: bool) -> Any:
|
||||
"""Build (once) and cache the Docling converter; model load costs seconds."""
|
||||
global _converter, _converter_key
|
||||
key = (artifacts_path or "", with_ocr)
|
||||
with _converter_lock:
|
||||
if _converter is not None and _converter_key == key:
|
||||
return _converter
|
||||
|
||||
pdf_options_mod = importlib.import_module("docling.datamodel.pipeline_options")
|
||||
converter_mod = importlib.import_module("docling.document_converter")
|
||||
base_models = importlib.import_module("docling.datamodel.base_models")
|
||||
|
||||
pipeline_options = pdf_options_mod.PdfPipelineOptions()
|
||||
pipeline_options.do_ocr = with_ocr
|
||||
pipeline_options.do_table_structure = True
|
||||
if artifacts_path:
|
||||
pipeline_options.artifacts_path = artifacts_path
|
||||
# Never reach the network when a prefetched model dir is configured.
|
||||
pipeline_options.enable_remote_services = False
|
||||
|
||||
input_format = base_models.InputFormat.PDF
|
||||
pdf_format_option = converter_mod.PdfFormatOption(pipeline_options=pipeline_options)
|
||||
_converter = converter_mod.DocumentConverter(format_options={input_format: pdf_format_option})
|
||||
_converter_key = key
|
||||
return _converter
|
||||
|
||||
|
||||
def _normalize_bbox(prov: Any, page_sizes: dict[int, tuple[float, float]]) -> tuple[int, list[float] | None]:
|
||||
"""Docling prov → (page, [x0, y0, x1, y1] normalized, top-left origin)."""
|
||||
page_no = int(getattr(prov, "page_no", 1) or 1)
|
||||
bbox = getattr(prov, "bbox", None)
|
||||
size = page_sizes.get(page_no)
|
||||
if bbox is None or size is None or size[0] <= 0 or size[1] <= 0:
|
||||
return page_no, None
|
||||
width, height = size
|
||||
try:
|
||||
# Docling boxes are bottom-left origin; flip to top-left before normalizing.
|
||||
top_left = bbox.to_top_left_origin(page_height=height) if hasattr(bbox, "to_top_left_origin") else bbox
|
||||
x0 = float(top_left.l) / width
|
||||
y0 = float(top_left.t) / height
|
||||
x1 = float(top_left.r) / width
|
||||
y1 = float(top_left.b) / height
|
||||
except (AttributeError, TypeError, ValueError):
|
||||
return page_no, None
|
||||
clamp = lambda v: max(0.0, min(1.0, v)) # noqa: E731
|
||||
x0, x1 = sorted((clamp(x0), clamp(x1)))
|
||||
y0, y1 = sorted((clamp(y0), clamp(y1)))
|
||||
return page_no, [round(x0, 5), round(y0, 5), round(x1, 5), round(y1, 5)]
|
||||
|
||||
|
||||
def _document_confidence(result: Any) -> float | None:
|
||||
"""Pull a single 0..1 confidence out of Docling's confidence report, if any."""
|
||||
report = getattr(result, "confidence", None)
|
||||
if report is None:
|
||||
return None
|
||||
for attr in ("mean_score", "mean_grade_score", "score"):
|
||||
value = getattr(report, attr, None)
|
||||
if isinstance(value, (int, float)) and 0.0 <= float(value) <= 1.0:
|
||||
return round(float(value), 4)
|
||||
return None
|
||||
|
||||
|
||||
def _table_cells(item: Any) -> list[list[str]]:
|
||||
data = getattr(item, "data", None)
|
||||
grid = getattr(data, "grid", None) or []
|
||||
cells: list[list[str]] = []
|
||||
for row in grid:
|
||||
cells.append([str(getattr(cell, "text", "") or "") for cell in row])
|
||||
return cells
|
||||
|
||||
|
||||
def _cells_to_markdown(cells: list[list[str]]) -> str:
|
||||
if not cells:
|
||||
return ""
|
||||
esc = lambda s: s.replace("|", "\\|").replace("\n", " ") # noqa: E731
|
||||
lines = ["| " + " | ".join(esc(c) for c in cells[0]) + " |"]
|
||||
lines.append("|" + "---|" * len(cells[0]))
|
||||
for row in cells[1:]:
|
||||
lines.append("| " + " | ".join(esc(c) for c in row) + " |")
|
||||
return "\n".join(lines)
|
||||
|
||||
|
||||
def parse_pdf_bytes(
|
||||
data: bytes,
|
||||
file_name: str,
|
||||
*,
|
||||
with_ocr: bool = True,
|
||||
artifacts_path: str | None = None,
|
||||
) -> ParseDocumentResponse:
|
||||
"""Synchronous, CPU-heavy; call from a worker thread (routes use ``anyio.to_thread``)."""
|
||||
io_mod = importlib.import_module("docling_core.types.io")
|
||||
converter = _get_converter(artifacts_path, with_ocr)
|
||||
|
||||
stream = io_mod.DocumentStream(name=file_name or "document.pdf", stream=io.BytesIO(data))
|
||||
try:
|
||||
result = converter.convert(stream)
|
||||
except Exception as error:
|
||||
raise ValueError(f"document could not be parsed: {error}") from error
|
||||
doc = result.document
|
||||
|
||||
page_sizes: dict[int, tuple[float, float]] = {}
|
||||
for page_no, page in (getattr(doc, "pages", None) or {}).items():
|
||||
size = getattr(page, "size", None)
|
||||
if size is not None:
|
||||
page_sizes[int(page_no)] = (float(size.width), float(size.height))
|
||||
|
||||
doc_confidence = _document_confidence(result)
|
||||
blocks: list[DocBlock] = []
|
||||
tables: list[DocTable] = []
|
||||
for item, _level in doc.iterate_items():
|
||||
provs = getattr(item, "prov", None) or []
|
||||
page, bbox = _normalize_bbox(provs[0], page_sizes) if provs else (1, None)
|
||||
label = str(getattr(item, "label", "") or "").lower()
|
||||
block_type = _LABEL_MAP.get(label, BlockType.OTHER)
|
||||
|
||||
if block_type is BlockType.TABLE:
|
||||
cells = _table_cells(item)
|
||||
tables.append(
|
||||
DocTable(
|
||||
page=page, bbox=bbox, cells=cells, markdown=_cells_to_markdown(cells), confidence=doc_confidence
|
||||
)
|
||||
)
|
||||
|
||||
text = str(getattr(item, "text", "") or "")
|
||||
if not text and block_type not in (BlockType.TABLE, BlockType.FIGURE):
|
||||
continue
|
||||
blocks.append(DocBlock(type=block_type, text=text, page=page, bbox=bbox, confidence=doc_confidence))
|
||||
|
||||
markdown = doc.export_to_markdown()
|
||||
pages = len(page_sizes) or len(getattr(doc, "pages", None) or {})
|
||||
logger.info("docparse: parsed %s: %d pages, %d blocks, %d tables", file_name, pages, len(blocks), len(tables))
|
||||
return ParseDocumentResponse(
|
||||
mode=DocparseTier.ADVANCED,
|
||||
pages=pages,
|
||||
blocks=blocks,
|
||||
tables=tables,
|
||||
markdown=markdown,
|
||||
ocr_applied=with_ocr,
|
||||
)
|
||||
@@ -0,0 +1,105 @@
|
||||
"""Content-based document splitting: an LLM finds sub-document boundaries.
|
||||
|
||||
Works entirely from caller-supplied page text (basic tier friendly); the fast
|
||||
model sees a bounded per-page preview and answers with boundary start pages,
|
||||
which are then validated in code (monotonic, in range, capped)."""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import logging
|
||||
|
||||
from pydantic import Field
|
||||
from pydantic_ai import Agent
|
||||
|
||||
from stirling.agents.output_mode import output_retries, structured_output
|
||||
from stirling.contracts.docparse import SmartSplitRequest, SmartSplitResponse, SplitPart
|
||||
from stirling.contracts.documents import PageText
|
||||
from stirling.models import ApiModel
|
||||
from stirling.services import AppRuntime
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# Per-page preview budget; boundaries are recognisable from page openings.
|
||||
PAGE_PREVIEW_CHARS = 600
|
||||
|
||||
_SYSTEM_PROMPT = (
|
||||
"You split a multi-document file into its component documents.\n"
|
||||
"\n"
|
||||
"You are shown the beginning of every page. Apply the user's splitting rule and "
|
||||
"answer with every page where a NEW component document starts.\n"
|
||||
"Rules:\n"
|
||||
"- Page 1 always starts the first component.\n"
|
||||
"- Give each component a short descriptive label (e.g. 'Invoice #4821', 'Cover letter').\n"
|
||||
"- Give your confidence 0.0-1.0 per boundary.\n"
|
||||
"- If the rule doesn't match anything, return just the page-1 component spanning the whole file."
|
||||
)
|
||||
|
||||
|
||||
class _Boundary(ApiModel):
|
||||
start_page: int = Field(ge=1, description="First page of this component document.")
|
||||
label: str = Field(description="Short human label for the component.")
|
||||
confidence: float = Field(ge=0.0, le=1.0)
|
||||
|
||||
|
||||
class _SplitOutput(ApiModel):
|
||||
boundaries: list[_Boundary] = Field(default_factory=list)
|
||||
|
||||
|
||||
def _format_pages(pages: list[PageText], max_pages: int) -> str:
|
||||
shown = pages[:max_pages]
|
||||
parts = [f"[Page {p.page_number}] {p.text[:PAGE_PREVIEW_CHARS]}" for p in shown]
|
||||
if len(pages) > max_pages:
|
||||
parts.append(f"({len(pages) - max_pages} further pages omitted)")
|
||||
return "\n\n".join(parts) if parts else "(no extractable text)"
|
||||
|
||||
|
||||
def validate_boundaries(output: _SplitOutput, page_count: int, max_parts: int) -> list[SplitPart]:
|
||||
"""Coerce the model's boundaries into a clean, complete partition of 1..page_count."""
|
||||
starts: dict[int, _Boundary] = {}
|
||||
for boundary in output.boundaries:
|
||||
if 1 <= boundary.start_page <= page_count and boundary.start_page not in starts:
|
||||
starts[boundary.start_page] = boundary
|
||||
if 1 not in starts:
|
||||
starts[1] = _Boundary(start_page=1, label="Document", confidence=1.0)
|
||||
|
||||
ordered = [starts[k] for k in sorted(starts)][:max_parts]
|
||||
parts: list[SplitPart] = []
|
||||
for i, boundary in enumerate(ordered):
|
||||
end_page = ordered[i + 1].start_page - 1 if i + 1 < len(ordered) else page_count
|
||||
parts.append(
|
||||
SplitPart(
|
||||
start_page=boundary.start_page,
|
||||
end_page=end_page,
|
||||
label=boundary.label.strip() or f"Part {i + 1}",
|
||||
confidence=round(boundary.confidence, 4),
|
||||
)
|
||||
)
|
||||
return parts
|
||||
|
||||
|
||||
class SmartSplitAgent:
|
||||
def __init__(self, runtime: AppRuntime) -> None:
|
||||
self.runtime = runtime
|
||||
provider = runtime.settings.chat_provider
|
||||
self._agent: Agent[None, _SplitOutput] = Agent(
|
||||
model=runtime.fast_model,
|
||||
output_type=structured_output([_SplitOutput], chat_provider=provider),
|
||||
system_prompt=_SYSTEM_PROMPT,
|
||||
model_settings=runtime.fast_model_settings,
|
||||
retries=output_retries(provider),
|
||||
)
|
||||
|
||||
async def split(self, request: SmartSplitRequest) -> SmartSplitResponse:
|
||||
pages = request.pages
|
||||
if not pages:
|
||||
return SmartSplitResponse(parts=[])
|
||||
page_count = max(p.page_number for p in pages)
|
||||
prompt = (
|
||||
f"Splitting rule: {request.rule}\n\n"
|
||||
f"Document file name: {request.file_name}\n"
|
||||
f"Pages:\n{_format_pages(pages, self.runtime.settings.max_pages)}"
|
||||
)
|
||||
result = await self._agent.run(prompt)
|
||||
parts = validate_boundaries(result.output, page_count, request.max_parts)
|
||||
logger.info("docparse: split %s into %d parts", request.file_name, len(parts))
|
||||
return SmartSplitResponse(parts=parts)
|
||||
@@ -0,0 +1,120 @@
|
||||
"""Schema suggestion: the fast model proposes extractable fields for a document.
|
||||
|
||||
Reads a bounded window of the first pages (the fields worth extracting from a
|
||||
document type are evident from its opening) and answers with candidate fields,
|
||||
which are then validated in code: names coerced to snake_case, duplicates and
|
||||
unsupported types dropped, capped at the caller's maxFields."""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import logging
|
||||
import re
|
||||
|
||||
from pydantic import Field
|
||||
from pydantic_ai import Agent
|
||||
|
||||
from stirling.agents.output_mode import output_retries, structured_output
|
||||
from stirling.contracts.docparse import (
|
||||
DocparseTier,
|
||||
SuggestedField,
|
||||
SuggestedFieldType,
|
||||
SuggestSchemaRequest,
|
||||
SuggestSchemaResponse,
|
||||
)
|
||||
from stirling.contracts.documents import PageText
|
||||
from stirling.models import ApiModel
|
||||
from stirling.services import AppRuntime
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
# First pages read; a fixed window keeps cost flat regardless of length.
|
||||
WINDOW_PAGES = 3
|
||||
# Per-page preview budget; field candidates show up near page openings.
|
||||
PAGE_PREVIEW_CHARS = 2_000
|
||||
|
||||
_SYSTEM_PROMPT = (
|
||||
"You design an extraction schema for a document type.\n"
|
||||
"\n"
|
||||
"You are shown the first pages of a document. Propose the most useful fields "
|
||||
"a user would want extracted from documents of this type.\n"
|
||||
"Rules:\n"
|
||||
"- Name each field as a snake_case identifier (e.g. 'invoice_number').\n"
|
||||
"- Type each field as one of: string, number, integer, boolean.\n"
|
||||
"- Give each field a one-sentence description of what it holds.\n"
|
||||
"- Propose fields for the document TYPE, not only values visible on these pages.\n"
|
||||
"- Order fields from most to least useful."
|
||||
)
|
||||
|
||||
|
||||
class _SuggestedField(ApiModel):
|
||||
# Loosely typed on purpose: bad names/types are dropped in code, not retried.
|
||||
name: str = Field(description="snake_case identifier for the field.")
|
||||
type: str = Field(description="One of: string, number, integer, boolean.")
|
||||
description: str = ""
|
||||
|
||||
|
||||
class _SuggestOutput(ApiModel):
|
||||
fields: list[_SuggestedField] = Field(default_factory=list)
|
||||
|
||||
|
||||
_IDENTIFIER = re.compile(r"[a-z][a-z0-9_]*")
|
||||
_CAMEL_BOUNDARY = re.compile(r"(?<=[a-z0-9])(?=[A-Z])")
|
||||
_NON_ALNUM = re.compile(r"[^A-Za-z0-9]+")
|
||||
_VALID_TYPES = {t.value for t in SuggestedFieldType}
|
||||
|
||||
|
||||
def to_snake_case(name: str) -> str:
|
||||
"""Coerce a model-proposed name into snake_case ('Invoice No.' -> 'invoice_no')."""
|
||||
return _NON_ALNUM.sub("_", _CAMEL_BOUNDARY.sub("_", name.strip())).strip("_").lower()
|
||||
|
||||
|
||||
def validate_fields(output: _SuggestOutput, max_fields: int) -> list[SuggestedField]:
|
||||
"""Keep unique snake_case names with supported types, capped at ``max_fields``."""
|
||||
kept: list[SuggestedField] = []
|
||||
seen: set[str] = set()
|
||||
for field in output.fields:
|
||||
name = to_snake_case(field.name)
|
||||
type_name = field.type.strip().lower()
|
||||
if not _IDENTIFIER.fullmatch(name) or name in seen or type_name not in _VALID_TYPES:
|
||||
continue
|
||||
seen.add(name)
|
||||
kept.append(
|
||||
SuggestedField(name=name, type=SuggestedFieldType(type_name), description=field.description.strip())
|
||||
)
|
||||
if len(kept) == max_fields:
|
||||
break
|
||||
return kept
|
||||
|
||||
|
||||
def _format_pages(pages: list[PageText]) -> str:
|
||||
shown = pages[:WINDOW_PAGES]
|
||||
parts = [f"[Page {p.page_number}] {p.text[:PAGE_PREVIEW_CHARS]}" for p in shown]
|
||||
if len(pages) > WINDOW_PAGES:
|
||||
parts.append(f"({len(pages) - WINDOW_PAGES} further pages omitted)")
|
||||
return "\n\n".join(parts) if parts else "(no extractable text)"
|
||||
|
||||
|
||||
class SuggestSchemaAgent:
|
||||
def __init__(self, runtime: AppRuntime) -> None:
|
||||
self.runtime = runtime
|
||||
provider = runtime.settings.chat_provider
|
||||
self._agent: Agent[None, _SuggestOutput] = Agent(
|
||||
model=runtime.fast_model,
|
||||
output_type=structured_output([_SuggestOutput], chat_provider=provider),
|
||||
system_prompt=_SYSTEM_PROMPT,
|
||||
model_settings=runtime.fast_model_settings,
|
||||
retries=output_retries(provider),
|
||||
)
|
||||
|
||||
async def suggest(
|
||||
self, request: SuggestSchemaRequest, pages: list[PageText], tier: DocparseTier
|
||||
) -> SuggestSchemaResponse:
|
||||
prompt = (
|
||||
f"Propose up to {request.max_fields} fields.\n\n"
|
||||
f"Document file name: {request.file_name}\n"
|
||||
f"Document content (first pages):\n{_format_pages(pages)}"
|
||||
)
|
||||
result = await self._agent.run(prompt)
|
||||
fields = validate_fields(result.output, request.max_fields)
|
||||
logger.info("docparse: suggested %d fields for %s", len(fields), request.file_name)
|
||||
return SuggestSchemaResponse(mode=tier, fields=fields)
|
||||
@@ -13,6 +13,7 @@ logger = logging.getLogger(__name__)
|
||||
PAGE_NUMBER_METADATA_KEY = "page_number"
|
||||
CONTENT_TYPE_METADATA_KEY = "content_type"
|
||||
PAGE_TEXT_CONTENT_TYPE = "page_text"
|
||||
DOCPARSE_CHUNK_CONTENT_TYPE = "docparse_chunk"
|
||||
|
||||
|
||||
class DocumentService:
|
||||
@@ -109,6 +110,42 @@ class DocumentService:
|
||||
await self._store.add_documents(collection, chunks, embeddings, owner_id)
|
||||
return len(chunks)
|
||||
|
||||
async def ingest_prepared(
|
||||
self,
|
||||
collection: FileId,
|
||||
chunks: list[tuple[str, dict[str, str]]],
|
||||
source: str,
|
||||
owner_id: OwnerId,
|
||||
read_principals: list[PrincipalId],
|
||||
expires_at: datetime | None,
|
||||
) -> int:
|
||||
"""Replace-ingest pre-chunked content (e.g. docparse structure-aware chunks).
|
||||
|
||||
Same lifecycle as :meth:`ingest` - wipe the ``(collection, owner_id)``
|
||||
pair, recreate it, grant reads, embed in batches, upsert - but chunk
|
||||
``(text, metadata)`` pairs arrive pre-built and no page representation
|
||||
is written. Returns the number of vector chunks indexed.
|
||||
"""
|
||||
if not read_principals:
|
||||
raise ValueError("read_principals must not be empty - every doc needs at least one reader")
|
||||
|
||||
await self._store.delete_collection(collection, owner_id)
|
||||
await self._store.ensure_collection(collection, source, owner_id, expires_at)
|
||||
await self._store.grant_read(collection, owner_id, read_principals)
|
||||
|
||||
documents: list[Document] = []
|
||||
for i, (text, metadata) in enumerate(chunks):
|
||||
if not text.strip():
|
||||
continue
|
||||
meta = {**metadata, "source": source, "chunk_index": str(i)}
|
||||
documents.append(Document(id=f"{source}:docparse:{i}", text=text, metadata=meta))
|
||||
|
||||
if not documents:
|
||||
return 0
|
||||
embeddings = await self._embedder.embed_documents([doc.text for doc in documents])
|
||||
await self._store.add_documents(collection, documents, embeddings, owner_id)
|
||||
return len(documents)
|
||||
|
||||
async def search(
|
||||
self,
|
||||
query: str,
|
||||
|
||||
@@ -0,0 +1,48 @@
|
||||
from __future__ import annotations
|
||||
|
||||
from stirling.contracts import PageText
|
||||
from stirling.contracts.docparse import BlockType, DocBlock, DocparseTier, ParseDocumentResponse
|
||||
from stirling.docparse.chunking import advanced_chunks, basic_chunks
|
||||
|
||||
|
||||
def test_basic_chunks_carry_page_numbers() -> None:
|
||||
pages = [
|
||||
PageText(page_number=1, text="alpha " * 200),
|
||||
PageText(page_number=2, text="beta " * 200),
|
||||
]
|
||||
result = basic_chunks(pages, chunk_size=256, overlap=32)
|
||||
assert result.mode is DocparseTier.BASIC
|
||||
assert len(result.chunks) >= 4
|
||||
assert {c.page_start for c in result.chunks} == {1, 2}
|
||||
assert [c.index for c in result.chunks] == list(range(len(result.chunks)))
|
||||
|
||||
|
||||
def _parse_fixture() -> ParseDocumentResponse:
|
||||
blocks = [
|
||||
DocBlock(type=BlockType.PAGE_HEADER, text="CONFIDENTIAL", page=1),
|
||||
DocBlock(type=BlockType.HEADING, text="1. Introduction", page=1),
|
||||
DocBlock(type=BlockType.PARAGRAPH, text="Short intro paragraph.", page=1),
|
||||
DocBlock(type=BlockType.PARAGRAPH, text="Second paragraph on same topic.", page=1),
|
||||
DocBlock(type=BlockType.HEADING, text="2. Terms", page=2),
|
||||
DocBlock(type=BlockType.PARAGRAPH, text="terms " * 300, page=2),
|
||||
]
|
||||
return ParseDocumentResponse(mode=DocparseTier.ADVANCED, pages=2, blocks=blocks, tables=[], markdown="")
|
||||
|
||||
|
||||
def test_advanced_chunks_respect_headings_and_skip_furniture() -> None:
|
||||
result = advanced_chunks(_parse_fixture(), chunk_size=512, overlap=64)
|
||||
assert result.mode is DocparseTier.ADVANCED
|
||||
texts = [c.text for c in result.chunks]
|
||||
assert all("CONFIDENTIAL" not in t for t in texts)
|
||||
intro = next(c for c in result.chunks if "Short intro" in c.text)
|
||||
assert intro.heading_path[-1] == "1. Introduction"
|
||||
assert intro.page_start == 1
|
||||
# Intro chunk must not bleed into the Terms section.
|
||||
assert "terms" not in intro.text
|
||||
|
||||
|
||||
def test_advanced_chunks_split_oversized_blocks() -> None:
|
||||
result = advanced_chunks(_parse_fixture(), chunk_size=512, overlap=64)
|
||||
terms_chunks = [c for c in result.chunks if c.heading_path and c.heading_path[-1] == "2. Terms"]
|
||||
assert len(terms_chunks) > 1
|
||||
assert all(c.page_start == 2 for c in terms_chunks)
|
||||
@@ -0,0 +1,70 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import base64
|
||||
import io
|
||||
from typing import Any
|
||||
|
||||
import docx
|
||||
|
||||
from stirling.contracts.docparse import FillDocxRequest
|
||||
from stirling.docparse.docxfill import fill_docx
|
||||
|
||||
|
||||
def _template_base64() -> str:
|
||||
document = docx.Document()
|
||||
document.add_paragraph("Dear {{ customer.name }},")
|
||||
document.add_paragraph("Your total is {{ total }}.")
|
||||
document.add_paragraph("Unknown: {{ nowhere.field }}")
|
||||
table = document.add_table(rows=2, cols=2)
|
||||
table.rows[0].cells[0].text = "Item"
|
||||
table.rows[0].cells[1].text = "Price"
|
||||
table.rows[1].cells[0].text = "{{#items.name}}"
|
||||
table.rows[1].cells[1].text = "{{#items.price}}"
|
||||
buffer = io.BytesIO()
|
||||
document.save(buffer)
|
||||
return base64.b64encode(buffer.getvalue()).decode("ascii")
|
||||
|
||||
|
||||
def _load(response_base64: str) -> Any:
|
||||
return docx.Document(io.BytesIO(base64.b64decode(response_base64)))
|
||||
|
||||
|
||||
def test_fills_scalars_tables_and_reports_missing() -> None:
|
||||
request = FillDocxRequest(
|
||||
template_base64=_template_base64(),
|
||||
data={
|
||||
"customer": {"name": "ACME GmbH"},
|
||||
"total": 12.5,
|
||||
"items": [
|
||||
{"name": "Widget", "price": "2.00"},
|
||||
{"name": "Gadget", "price": "10.50"},
|
||||
],
|
||||
},
|
||||
)
|
||||
response = fill_docx(request)
|
||||
filled = _load(response.docx_base64)
|
||||
|
||||
paragraphs = [p.text for p in filled.paragraphs]
|
||||
assert "Dear ACME GmbH," in paragraphs
|
||||
assert "Your total is 12.5." in paragraphs
|
||||
# Unresolved placeholders stay put and are reported.
|
||||
assert any("{{ nowhere.field }}" in p for p in paragraphs)
|
||||
assert response.missing == ["nowhere.field"]
|
||||
|
||||
table = filled.tables[0]
|
||||
rendered_rows = [[cell.text for cell in row.cells] for row in table.rows]
|
||||
assert ["Widget", "2.00"] in rendered_rows
|
||||
assert ["Gadget", "10.50"] in rendered_rows
|
||||
# The template row is gone.
|
||||
assert all("{{#" not in cell for row in rendered_rows for cell in row)
|
||||
assert response.replaced >= 6
|
||||
|
||||
|
||||
def test_empty_items_removes_template_row() -> None:
|
||||
request = FillDocxRequest(
|
||||
template_base64=_template_base64(),
|
||||
data={"customer": {"name": "X"}, "total": 1, "items": []},
|
||||
)
|
||||
response = fill_docx(request)
|
||||
filled = _load(response.docx_base64)
|
||||
assert len(filled.tables[0].rows) == 1 # only the header remains
|
||||
@@ -0,0 +1,92 @@
|
||||
from __future__ import annotations
|
||||
|
||||
from pydantic import BaseModel
|
||||
|
||||
from stirling.contracts import PageText
|
||||
from stirling.docparse.extractor import (
|
||||
VALUE_GROUNDED_FLOOR,
|
||||
ExtractFieldsAgent,
|
||||
build_output_model,
|
||||
find_quote,
|
||||
)
|
||||
from stirling.docparse.splitter import _Boundary, _SplitOutput, validate_boundaries
|
||||
|
||||
|
||||
def _pages() -> list[PageText]:
|
||||
return [
|
||||
PageText(page_number=1, text="Invoice INV-123\nTotal due: 1,240.00 EUR"),
|
||||
PageText(page_number=2, text="Payment terms\nNet 30 days from receipt."),
|
||||
]
|
||||
|
||||
|
||||
def test_find_quote_exact() -> None:
|
||||
located = find_quote("Invoice INV-123", _pages())
|
||||
assert located is not None
|
||||
page, start, end = located
|
||||
assert page == 1
|
||||
assert start == 0
|
||||
|
||||
|
||||
def test_find_quote_is_whitespace_insensitive() -> None:
|
||||
located = find_quote("Total due: 1,240.00 EUR", _pages())
|
||||
assert located is not None
|
||||
assert located[0] == 1
|
||||
|
||||
|
||||
def test_find_quote_is_case_insensitive_and_crosses_pages() -> None:
|
||||
located = find_quote("net 30 DAYS", _pages())
|
||||
assert located is not None
|
||||
assert located[0] == 2
|
||||
|
||||
|
||||
def test_find_quote_missing_returns_none() -> None:
|
||||
assert find_quote("does not appear", _pages()) is None
|
||||
assert find_quote(" ", _pages()) is None
|
||||
|
||||
|
||||
def test_validate_boundaries_partitions_cleanly() -> None:
|
||||
output = _SplitOutput(
|
||||
boundaries=[
|
||||
_Boundary(start_page=4, label="Invoice B", confidence=0.8),
|
||||
_Boundary(start_page=1, label="Invoice A", confidence=0.9),
|
||||
_Boundary(start_page=4, label="dup", confidence=0.1),
|
||||
_Boundary(start_page=99, label="out of range", confidence=0.5),
|
||||
]
|
||||
)
|
||||
parts = validate_boundaries(output, page_count=6, max_parts=10)
|
||||
assert [(p.start_page, p.end_page) for p in parts] == [(1, 3), (4, 6)]
|
||||
assert parts[0].label == "Invoice A"
|
||||
|
||||
|
||||
def test_validate_boundaries_inserts_page_one() -> None:
|
||||
output = _SplitOutput(boundaries=[_Boundary(start_page=3, label="Part", confidence=0.7)])
|
||||
parts = validate_boundaries(output, page_count=5, max_parts=10)
|
||||
assert parts[0].start_page == 1
|
||||
assert parts[1].start_page == 3
|
||||
assert parts[-1].end_page == 5
|
||||
|
||||
|
||||
def test_validate_boundaries_empty_output_spans_whole_file() -> None:
|
||||
parts = validate_boundaries(_SplitOutput(), page_count=7, max_parts=10)
|
||||
assert [(p.start_page, p.end_page) for p in parts] == [(1, 7)]
|
||||
|
||||
|
||||
def _answers(quote: str | None, confidence: float) -> BaseModel:
|
||||
model = build_output_model({"type": "object", "properties": {"invoice_number": {"type": "string"}}})
|
||||
return model.model_validate({"invoiceNumber": {"value": "INV-123", "quote": quote, "confidence": confidence}})
|
||||
|
||||
|
||||
def test_ground_falls_back_to_value_when_quote_missing() -> None:
|
||||
# Terse local models return the value but no quote; the value itself grounds.
|
||||
pages = [PageText(page_number=1, text="Invoice INV-123 issued today.")]
|
||||
fields = ExtractFieldsAgent._ground(_answers(quote=None, confidence=0.0), pages, None)
|
||||
assert fields[0].citations and fields[0].citations[0].page == 1
|
||||
assert fields[0].citations[0].quote == "INV-123"
|
||||
assert fields[0].confidence >= VALUE_GROUNDED_FLOOR
|
||||
|
||||
|
||||
def test_ground_penalises_when_nothing_grounds() -> None:
|
||||
pages = [PageText(page_number=1, text="completely unrelated text")]
|
||||
fields = ExtractFieldsAgent._ground(_answers(quote=None, confidence=0.9), pages, None)
|
||||
assert not fields[0].citations
|
||||
assert fields[0].confidence < 0.9
|
||||
@@ -0,0 +1,247 @@
|
||||
from __future__ import annotations
|
||||
|
||||
from collections.abc import Iterator
|
||||
from datetime import datetime
|
||||
from typing import Any
|
||||
|
||||
import pytest
|
||||
from fastapi.testclient import TestClient
|
||||
|
||||
from stirling.api import app
|
||||
from stirling.api.dependencies import get_document_service
|
||||
from stirling.documents import DocumentService, SqliteVecStore
|
||||
from stirling.models import FileId, OwnerId, PrincipalId
|
||||
|
||||
HEADERS = {"X-User-Id": "test-user"}
|
||||
|
||||
|
||||
class StubDocumentService:
|
||||
"""Records ingest_prepared calls so the route's passthrough can be asserted."""
|
||||
|
||||
def __init__(self) -> None:
|
||||
self.calls: list[dict[str, Any]] = []
|
||||
|
||||
async def ingest_prepared(
|
||||
self,
|
||||
collection: FileId,
|
||||
chunks: list[tuple[str, dict[str, str]]],
|
||||
source: str,
|
||||
owner_id: OwnerId,
|
||||
read_principals: list[PrincipalId],
|
||||
expires_at: datetime | None,
|
||||
) -> int:
|
||||
self.calls.append(
|
||||
{
|
||||
"collection": collection,
|
||||
"chunks": chunks,
|
||||
"source": source,
|
||||
"owner_id": owner_id,
|
||||
"read_principals": read_principals,
|
||||
"expires_at": expires_at,
|
||||
}
|
||||
)
|
||||
return len(chunks)
|
||||
|
||||
|
||||
class StubEmbedder:
|
||||
"""Deterministic embeddings: no network, no provider needed."""
|
||||
|
||||
def __init__(self, dim: int = 8) -> None:
|
||||
self._dim = dim
|
||||
|
||||
async def embed_query(self, text: str) -> list[float]:
|
||||
h = hash(text) % 1000
|
||||
return [(h + i) / 1000.0 for i in range(self._dim)]
|
||||
|
||||
async def embed_documents(self, texts: list[str]) -> list[list[float]]:
|
||||
return [await self.embed_query(t) for t in texts]
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def stub_service() -> StubDocumentService:
|
||||
return StubDocumentService()
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def client(stub_service: StubDocumentService) -> Iterator[TestClient]:
|
||||
app.dependency_overrides[get_document_service] = lambda: stub_service
|
||||
try:
|
||||
yield TestClient(app)
|
||||
finally:
|
||||
app.dependency_overrides.pop(get_document_service, None)
|
||||
|
||||
|
||||
def test_rag_ingest_basic_tier_indexes_chunks_with_metadata(
|
||||
client: TestClient, stub_service: StubDocumentService
|
||||
) -> None:
|
||||
response = client.post(
|
||||
"/api/v1/docparse/rag-ingest",
|
||||
json={
|
||||
"fileName": "report.pdf",
|
||||
"documentId": "doc-1",
|
||||
"pages": [{"pageNumber": 1, "text": "para one"}, {"pageNumber": 2, "text": "para two"}],
|
||||
"chunkSize": 64,
|
||||
},
|
||||
headers=HEADERS,
|
||||
)
|
||||
assert response.status_code == 200
|
||||
body = response.json()
|
||||
assert body["mode"] == "basic"
|
||||
assert body["documentId"] == "doc-1"
|
||||
assert body["chunksIndexed"] == 2
|
||||
assert body["pages"] == 2
|
||||
assert body["markdown"] is None
|
||||
assert body["chunks"] is None
|
||||
|
||||
call = stub_service.calls[0]
|
||||
assert call["collection"] == "doc-1"
|
||||
assert call["source"] == "docparse"
|
||||
text, metadata = call["chunks"][0]
|
||||
assert text == "para one"
|
||||
assert metadata["content_type"] == "docparse_chunk"
|
||||
assert metadata["page_start"] == "1"
|
||||
assert metadata["page_end"] == "1"
|
||||
|
||||
|
||||
def test_rag_ingest_defaults_owner_and_readers_to_caller(client: TestClient, stub_service: StubDocumentService) -> None:
|
||||
client.post(
|
||||
"/api/v1/docparse/rag-ingest",
|
||||
json={"fileName": "a.pdf", "documentId": "d", "pages": [{"pageNumber": 1, "text": "t"}]},
|
||||
headers=HEADERS,
|
||||
)
|
||||
call = stub_service.calls[0]
|
||||
assert call["owner_id"] == "test-user"
|
||||
assert call["read_principals"] == ["test-user"]
|
||||
assert call["expires_at"] is None
|
||||
|
||||
|
||||
def test_rag_ingest_passes_explicit_owner_acl_and_expiry_through(
|
||||
client: TestClient, stub_service: StubDocumentService
|
||||
) -> None:
|
||||
client.post(
|
||||
"/api/v1/docparse/rag-ingest",
|
||||
json={
|
||||
"fileName": "a.pdf",
|
||||
"documentId": "d",
|
||||
"source": "handbook.pdf",
|
||||
"ownerId": "org:acme",
|
||||
"readPrincipals": ["group:eng", "user:bob"],
|
||||
"expiresAt": "2030-01-01T00:00:00Z",
|
||||
"pages": [{"pageNumber": 1, "text": "t"}],
|
||||
},
|
||||
headers=HEADERS,
|
||||
)
|
||||
call = stub_service.calls[0]
|
||||
assert call["owner_id"] == "org:acme"
|
||||
assert call["read_principals"] == ["group:eng", "user:bob"]
|
||||
assert call["source"] == "handbook.pdf"
|
||||
assert call["expires_at"] is not None
|
||||
|
||||
|
||||
def test_rag_ingest_export_only_skips_the_store(client: TestClient, stub_service: StubDocumentService) -> None:
|
||||
response = client.post(
|
||||
"/api/v1/docparse/rag-ingest",
|
||||
json={
|
||||
"fileName": "a.pdf",
|
||||
"documentId": "d",
|
||||
"pages": [{"pageNumber": 1, "text": "alpha"}, {"pageNumber": 2, "text": "beta"}],
|
||||
"index": False,
|
||||
"includeMarkdown": True,
|
||||
"includeChunks": True,
|
||||
},
|
||||
headers=HEADERS,
|
||||
)
|
||||
assert response.status_code == 200
|
||||
body = response.json()
|
||||
assert stub_service.calls == []
|
||||
assert body["chunksIndexed"] == 0
|
||||
assert body["markdown"] == "alpha\n\nbeta"
|
||||
assert [c["text"] for c in body["chunks"]] == ["alpha", "beta"]
|
||||
assert body["chunks"][0]["pageStart"] == 1
|
||||
|
||||
|
||||
def test_rag_ingest_index_off_with_no_export_is_422(client: TestClient) -> None:
|
||||
response = client.post(
|
||||
"/api/v1/docparse/rag-ingest",
|
||||
json={
|
||||
"fileName": "a.pdf",
|
||||
"documentId": "d",
|
||||
"pages": [{"pageNumber": 1, "text": "t"}],
|
||||
"index": False,
|
||||
},
|
||||
headers=HEADERS,
|
||||
)
|
||||
assert response.status_code == 422
|
||||
|
||||
|
||||
def test_rag_ingest_advanced_mode_needs_the_addon(client: TestClient) -> None:
|
||||
response = client.post(
|
||||
"/api/v1/docparse/rag-ingest",
|
||||
json={
|
||||
"fileName": "x.pdf",
|
||||
"documentId": "d",
|
||||
"mode": "advanced",
|
||||
"pages": [{"pageNumber": 1, "text": "t"}],
|
||||
},
|
||||
headers=HEADERS,
|
||||
)
|
||||
assert response.status_code == 501
|
||||
assert response.json()["detail"]["addonRequired"] == "docparse"
|
||||
|
||||
|
||||
def test_rag_ingest_without_pages_is_422(client: TestClient) -> None:
|
||||
response = client.post(
|
||||
"/api/v1/docparse/rag-ingest", json={"fileName": "x.pdf", "documentId": "d"}, headers=HEADERS
|
||||
)
|
||||
assert response.status_code == 422
|
||||
|
||||
|
||||
def test_rag_ingest_rejects_missing_user_header(client: TestClient) -> None:
|
||||
response = client.post(
|
||||
"/api/v1/docparse/rag-ingest",
|
||||
json={"fileName": "x.pdf", "documentId": "d", "pages": [{"pageNumber": 1, "text": "t"}]},
|
||||
)
|
||||
assert response.status_code == 401
|
||||
|
||||
|
||||
def test_rag_ingest_rejects_empty_document_id(client: TestClient) -> None:
|
||||
response = client.post(
|
||||
"/api/v1/docparse/rag-ingest",
|
||||
json={"fileName": "x.pdf", "documentId": "", "pages": [{"pageNumber": 1, "text": "t"}]},
|
||||
headers=HEADERS,
|
||||
)
|
||||
assert response.status_code == 422
|
||||
|
||||
|
||||
def test_capabilities_reports_probe_shape() -> None:
|
||||
# Not asserting a value: a dev venv may genuinely have docling installed.
|
||||
client = TestClient(app)
|
||||
response = client.get("/api/v1/docparse/capabilities", headers=HEADERS)
|
||||
assert response.status_code == 200
|
||||
assert isinstance(response.json()["advancedInstalled"], bool)
|
||||
|
||||
|
||||
# ── real service: replacement semantics ─────────────────────────────────
|
||||
|
||||
|
||||
@pytest.mark.anyio
|
||||
async def test_rag_ingest_reingest_replaces_instead_of_duplicating() -> None:
|
||||
service = DocumentService(embedder=StubEmbedder(), store=SqliteVecStore.ephemeral(), default_top_k=3) # type: ignore[arg-type]
|
||||
app.dependency_overrides[get_document_service] = lambda: service
|
||||
try:
|
||||
client = TestClient(app)
|
||||
payload = {
|
||||
"fileName": "report.pdf",
|
||||
"documentId": "doc-replace",
|
||||
"pages": [{"pageNumber": 1, "text": "first version"}],
|
||||
}
|
||||
assert client.post("/api/v1/docparse/rag-ingest", json=payload, headers=HEADERS).status_code == 200
|
||||
payload["pages"] = [{"pageNumber": 1, "text": "second version"}]
|
||||
assert client.post("/api/v1/docparse/rag-ingest", json=payload, headers=HEADERS).status_code == 200
|
||||
finally:
|
||||
app.dependency_overrides.pop(get_document_service, None)
|
||||
|
||||
results = await service.search("version", principals=[PrincipalId("test-user")], collection=FileId("doc-replace"))
|
||||
assert [r.document.text for r in results] == ["second version"]
|
||||
assert results[0].document.metadata["content_type"] == "docparse_chunk"
|
||||
assert results[0].document.metadata["source"] == "docparse"
|
||||
@@ -0,0 +1,79 @@
|
||||
from __future__ import annotations
|
||||
|
||||
from typing import Any
|
||||
|
||||
import pytest
|
||||
|
||||
from stirling.docparse.extractor import MAX_SCHEMA_DEPTH, SchemaError, build_output_model, flatten_answers
|
||||
|
||||
|
||||
def _schema(properties: dict[str, Any]) -> dict[str, Any]:
|
||||
return {"type": "object", "properties": properties}
|
||||
|
||||
|
||||
def test_builds_scalar_fields() -> None:
|
||||
model = build_output_model(
|
||||
_schema(
|
||||
{
|
||||
"invoice_number": {"type": "string", "description": "The invoice id"},
|
||||
"total": {"type": "number"},
|
||||
"line_count": {"type": "integer"},
|
||||
"paid": {"type": "boolean"},
|
||||
}
|
||||
)
|
||||
)
|
||||
instance = model.model_validate(
|
||||
{
|
||||
"invoiceNumber": {"value": "INV-1", "quote": "Invoice INV-1", "confidence": 0.9},
|
||||
"total": {"value": 12.5, "quote": None, "confidence": 0.8},
|
||||
"lineCount": {"value": 3, "quote": None, "confidence": 0.7},
|
||||
"paid": {"value": True, "quote": None, "confidence": 0.6},
|
||||
}
|
||||
)
|
||||
leaves = dict((name, value) for name, value, _quote, _conf in flatten_answers(instance))
|
||||
assert leaves == {"invoice_number": "INV-1", "total": 12.5, "line_count": 3, "paid": True}
|
||||
|
||||
|
||||
def test_nested_objects_flatten_to_dotted_names() -> None:
|
||||
model = build_output_model(_schema({"vendor": {"type": "object", "properties": {"name": {"type": "string"}}}}))
|
||||
instance = model.model_validate({"vendor": {"name": {"value": "ACME", "quote": None, "confidence": 0.5}}})
|
||||
names = [name for name, _v, _q, _c in flatten_answers(instance)]
|
||||
assert names == ["vendor.name"]
|
||||
|
||||
|
||||
def test_arrays_of_scalars() -> None:
|
||||
model = build_output_model(_schema({"tags": {"type": "array", "items": {"type": "string"}}}))
|
||||
instance = model.model_validate({"tags": {"value": ["a", "b"], "quote": None, "confidence": 1.0}})
|
||||
leaves = flatten_answers(instance)
|
||||
assert leaves[0][1] == ["a", "b"]
|
||||
|
||||
|
||||
def test_enum_lands_in_description_not_type() -> None:
|
||||
model = build_output_model(_schema({"currency": {"type": "string", "enum": ["EUR", "USD"]}}))
|
||||
answer_model = model.model_fields["currency"].annotation
|
||||
description = answer_model.model_fields["value"].description # type: ignore[union-attr]
|
||||
assert "EUR" in description and "USD" in description
|
||||
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
"schema",
|
||||
[
|
||||
{"type": "object", "properties": {}},
|
||||
{"type": "object"},
|
||||
{"type": "object", "properties": {"bad-name": {"type": "string"}}},
|
||||
{"type": "object", "properties": {"x": {"type": "date"}}},
|
||||
{"type": "object", "properties": {"x": {"type": "array"}}},
|
||||
{"type": "object", "properties": {"x": {"type": "array", "items": {"type": "object"}}}},
|
||||
],
|
||||
)
|
||||
def test_rejects_unsupported_schemas(schema: dict[str, Any]) -> None:
|
||||
with pytest.raises(SchemaError):
|
||||
build_output_model(schema)
|
||||
|
||||
|
||||
def test_rejects_over_deep_nesting() -> None:
|
||||
schema: dict = {"type": "string"}
|
||||
for _ in range(MAX_SCHEMA_DEPTH + 2):
|
||||
schema = {"type": "object", "properties": {"child": schema}}
|
||||
with pytest.raises(SchemaError):
|
||||
build_output_model(schema)
|
||||
@@ -0,0 +1,129 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import base64
|
||||
from collections.abc import Iterator
|
||||
|
||||
import pytest
|
||||
from fastapi.testclient import TestClient
|
||||
|
||||
from stirling.api import app
|
||||
from stirling.api.dependencies import get_suggest_schema_agent
|
||||
from stirling.api.routes import docparse as docparse_routes
|
||||
from stirling.contracts.docparse import (
|
||||
DocparseCapabilities,
|
||||
DocparseTier,
|
||||
SuggestedField,
|
||||
SuggestedFieldType,
|
||||
SuggestSchemaRequest,
|
||||
SuggestSchemaResponse,
|
||||
)
|
||||
from stirling.contracts.documents import PageText
|
||||
from stirling.docparse.suggest_schema import _SuggestedField, _SuggestOutput, to_snake_case, validate_fields
|
||||
|
||||
|
||||
def _force_addon(monkeypatch: pytest.MonkeyPatch, installed: bool) -> None:
|
||||
caps = DocparseCapabilities(advanced_installed=installed, models_available=installed)
|
||||
monkeypatch.setattr(docparse_routes, "probe_capabilities", lambda _home, refresh=False: caps)
|
||||
|
||||
|
||||
class StubSuggestAgent:
|
||||
def __init__(self) -> None:
|
||||
self.seen_pages: list[PageText] | None = None
|
||||
|
||||
async def suggest(
|
||||
self, _request: SuggestSchemaRequest, pages: list[PageText], tier: DocparseTier
|
||||
) -> SuggestSchemaResponse:
|
||||
self.seen_pages = pages
|
||||
return SuggestSchemaResponse(
|
||||
mode=tier,
|
||||
fields=[SuggestedField(name="invoice_number", type=SuggestedFieldType.STRING, description="The number.")],
|
||||
)
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def stub_agent() -> StubSuggestAgent:
|
||||
return StubSuggestAgent()
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def client(stub_agent: StubSuggestAgent) -> Iterator[TestClient]:
|
||||
app.dependency_overrides[get_suggest_schema_agent] = lambda: stub_agent
|
||||
try:
|
||||
yield TestClient(app)
|
||||
finally:
|
||||
app.dependency_overrides.pop(get_suggest_schema_agent, None)
|
||||
|
||||
|
||||
# ── validation (model proposes, code decides) ───────────────────────────
|
||||
|
||||
|
||||
def _output(*fields: tuple[str, str]) -> _SuggestOutput:
|
||||
return _SuggestOutput(fields=[_SuggestedField(name=n, type=t, description="d") for n, t in fields])
|
||||
|
||||
|
||||
def test_names_are_coerced_to_snake_case() -> None:
|
||||
fields = validate_fields(_output(("Invoice Number", "string"), ("dueDate", "string")), max_fields=8)
|
||||
assert [f.name for f in fields] == ["invoice_number", "due_date"]
|
||||
|
||||
|
||||
def test_invalid_types_are_dropped() -> None:
|
||||
fields = validate_fields(_output(("total", "money"), ("count", "integer"), ("date", "datetime")), max_fields=8)
|
||||
assert [f.name for f in fields] == ["count"]
|
||||
assert fields[0].type is SuggestedFieldType.INTEGER
|
||||
|
||||
|
||||
def test_duplicate_names_collapse_to_first() -> None:
|
||||
fields = validate_fields(_output(("total", "number"), ("Total", "string"), ("total", "integer")), max_fields=8)
|
||||
assert len(fields) == 1
|
||||
assert fields[0].type is SuggestedFieldType.NUMBER
|
||||
|
||||
|
||||
def test_result_is_capped_at_max_fields() -> None:
|
||||
fields = validate_fields(_output(*[(f"field_{i}", "string") for i in range(10)]), max_fields=3)
|
||||
assert [f.name for f in fields] == ["field_0", "field_1", "field_2"]
|
||||
|
||||
|
||||
def test_names_that_cannot_become_identifiers_are_dropped() -> None:
|
||||
fields = validate_fields(_output(("123abc", "string"), ("!!!", "string"), ("ok_name", "string")), max_fields=8)
|
||||
assert [f.name for f in fields] == ["ok_name"]
|
||||
|
||||
|
||||
def test_snake_case_coercion_examples() -> None:
|
||||
assert to_snake_case("Invoice No.") == "invoice_no"
|
||||
assert to_snake_case("invoiceNumber") == "invoice_number"
|
||||
assert to_snake_case("TotalUSD") == "total_usd"
|
||||
assert to_snake_case(" already_snake ") == "already_snake"
|
||||
|
||||
|
||||
# ── route ───────────────────────────────────────────────────────────────
|
||||
|
||||
|
||||
def test_suggest_schema_basic_tier_from_pages(client: TestClient) -> None:
|
||||
response = client.post(
|
||||
"/api/v1/docparse/suggest-schema",
|
||||
json={"fileName": "invoice.pdf", "pages": [{"pageNumber": 1, "text": "Invoice INV-1"}]},
|
||||
)
|
||||
assert response.status_code == 200
|
||||
body = response.json()
|
||||
assert body["mode"] == "basic"
|
||||
assert body["fields"][0] == {"name": "invoice_number", "type": "string", "description": "The number."}
|
||||
|
||||
|
||||
def test_suggest_schema_without_pages_or_content_is_422(client: TestClient) -> None:
|
||||
response = client.post("/api/v1/docparse/suggest-schema", json={"fileName": "x.pdf"})
|
||||
assert response.status_code == 422
|
||||
|
||||
|
||||
def test_suggest_schema_content_without_addon_is_422(client: TestClient, monkeypatch: pytest.MonkeyPatch) -> None:
|
||||
_force_addon(monkeypatch, installed=False)
|
||||
payload = {"fileName": "scan.pdf", "contentBase64": base64.b64encode(b"%PDF-1.4").decode()}
|
||||
response = client.post("/api/v1/docparse/suggest-schema", json=payload)
|
||||
assert response.status_code == 422
|
||||
|
||||
|
||||
def test_suggest_schema_rejects_max_fields_above_cap(client: TestClient) -> None:
|
||||
response = client.post(
|
||||
"/api/v1/docparse/suggest-schema",
|
||||
json={"fileName": "x.pdf", "pages": [{"pageNumber": 1, "text": "t"}], "maxFields": 21},
|
||||
)
|
||||
assert response.status_code == 422
|
||||
Generated
+1136
-13
File diff suppressed because it is too large
Load Diff
@@ -2986,6 +2986,38 @@ summary_one = "Ran 1 tool"
|
||||
summary_other = "Ran {{count}} tools"
|
||||
unknownTool = "Unknown tool"
|
||||
|
||||
[chunkDocument]
|
||||
intro = "Turns a document into retrieval-ready chunks in three layers, so answers cite the right section instead of a random page."
|
||||
processorCallout = "To index automatically, add the 'Index into knowledge base' step to an ingestion policy in the"
|
||||
processorLink = "Processor"
|
||||
submit = "Prepare chunks"
|
||||
|
||||
[chunkDocument.chunkSize]
|
||||
label = "Chunk size (characters)"
|
||||
|
||||
[chunkDocument.error]
|
||||
failed = "Failed to chunk document"
|
||||
|
||||
[chunkDocument.layers]
|
||||
chunk = "Structure-aware chunks: each carries its heading breadcrumb and page range"
|
||||
embed = "Ready to embed: exported as JSONL for any vector store"
|
||||
parse = "Layout-aware parse: headings, paragraphs, and tables are recognized as structure"
|
||||
|
||||
[chunkDocument.mode]
|
||||
advanced = "Advanced"
|
||||
auto = "Auto"
|
||||
basic = "Basic"
|
||||
label = "Mode"
|
||||
|
||||
[chunkDocument.overlap]
|
||||
label = "Overlap (characters)"
|
||||
|
||||
[chunkDocument.results]
|
||||
title = "Chunks (JSONL)"
|
||||
|
||||
[chunkDocument.settings]
|
||||
title = "Chunking settings"
|
||||
|
||||
[cloudBadge]
|
||||
tooltip = "This operation will use your cloud credits"
|
||||
|
||||
@@ -3573,6 +3605,13 @@ tags = "automation,folder,scanning,watch folder,hot folder,automatic processing,
|
||||
[devSsoGuide]
|
||||
tags = "SSO,single sign-on,authentication,SAML,OAuth,OIDC,login,enterprise,identity provider,IdP"
|
||||
|
||||
[docparse.intro]
|
||||
advancedOff = "Advanced parsing: off"
|
||||
advancedOn = "Advanced parsing: on"
|
||||
aiLayoutModel = "AI layout model"
|
||||
basicFallback = "Scanned documents fall back to basic text extraction - install the DocParse addon for layout AI"
|
||||
usesAi = "Uses AI"
|
||||
|
||||
[dropdownList]
|
||||
searchPlaceholder = "Search..."
|
||||
|
||||
@@ -3700,6 +3739,56 @@ _value = "Error"
|
||||
dismissAllErrors = "Dismiss All Errors"
|
||||
generic = "An error occurred"
|
||||
|
||||
[extractFields]
|
||||
intro = "Describe the fields you need and AI reads the document and returns each value with a confidence score and a citation you can verify."
|
||||
submit = "Extract fields"
|
||||
|
||||
[extractFields.error]
|
||||
failed = "Failed to extract fields"
|
||||
|
||||
[extractFields.fields]
|
||||
add = "Add field"
|
||||
description = "Description"
|
||||
descriptionPlaceholder = "What to look for"
|
||||
label = "Fields to extract"
|
||||
name = "Name"
|
||||
namePlaceholder = "invoice_number"
|
||||
remove = "Remove field"
|
||||
type = "Type"
|
||||
|
||||
[extractFields.instructions]
|
||||
label = "Instructions"
|
||||
placeholder = "e.g. Amounts are in EUR unless stated otherwise"
|
||||
|
||||
[extractFields.mode]
|
||||
advanced = "Advanced"
|
||||
auto = "Auto"
|
||||
basic = "Basic"
|
||||
label = "Mode"
|
||||
|
||||
[extractFields.presets]
|
||||
contract = "Contract"
|
||||
custom = "Custom"
|
||||
invoice = "Invoice"
|
||||
label = "Preset template"
|
||||
purchaseOrder = "Purchase order"
|
||||
receipt = "Receipt"
|
||||
|
||||
[extractFields.results]
|
||||
title = "Extraction report"
|
||||
|
||||
[extractFields.resultsPanel]
|
||||
title = "Extracted fields"
|
||||
|
||||
[extractFields.settings]
|
||||
title = "Extraction schema"
|
||||
|
||||
[extractFields.suggest]
|
||||
button = "Suggest fields (AI)"
|
||||
failed = "Could not suggest fields"
|
||||
failedBody = "The document could not be analyzed. Add fields manually or try again."
|
||||
needsFile = "Select a file first to suggest fields"
|
||||
|
||||
[extractImages]
|
||||
allowDuplicates = "Save duplicate images"
|
||||
selectText = "Select image format to convert extracted images to"
|
||||
@@ -4183,6 +4272,24 @@ upload = "Upload"
|
||||
uploadFile = "Upload File"
|
||||
uploadFiles = "Upload Files"
|
||||
|
||||
[fillTemplate]
|
||||
hint = "The input file must be a .docx template (not a PDF). Each placeholder in the template is replaced with the matching JSON value."
|
||||
intro = "Replaces the placeholders in a Word (.docx) template with your JSON data and returns the filled document - deterministic, no AI involved."
|
||||
submit = "Fill template"
|
||||
|
||||
[fillTemplate.data]
|
||||
invalid = "Enter a valid JSON object"
|
||||
label = "Data (JSON)"
|
||||
|
||||
[fillTemplate.error]
|
||||
failed = "Failed to fill template"
|
||||
|
||||
[fillTemplate.results]
|
||||
title = "Filled document"
|
||||
|
||||
[fillTemplate.settings]
|
||||
title = "Template data"
|
||||
|
||||
[firstLogin]
|
||||
allFieldsRequired = "All fields are required"
|
||||
changePassword = "Change Password"
|
||||
@@ -4522,6 +4629,11 @@ desc = "Change document restrictions and permissions"
|
||||
tags = "permissions,restrictions,rights,access control,allow,deny,printing,copying,editing,modify permissions,security settings,user rights"
|
||||
title = "Change Permissions"
|
||||
|
||||
[home.chunkDocument]
|
||||
desc = "Layout-aware parse to structure-aware chunks with heading breadcrumbs and page ranges, ready to embed"
|
||||
tags = "chunk,RAG,prepare,split text,segments,embedding,vector,ingest,LLM,retrieval,JSONL,overlap,knowledge base,index"
|
||||
title = "Prepare for RAG"
|
||||
|
||||
[home.compare]
|
||||
desc = "Compares and shows the differences between 2 PDF Documents"
|
||||
tags = "difference,compare,diff,compare PDFs,compare documents,find differences,show differences,changes,what changed,track changes,revisions,version compare,side by side,contrast,delta"
|
||||
@@ -4567,6 +4679,11 @@ desc = "Add or edit bookmarks and table of contents in PDF documents"
|
||||
tags = "bookmarks,contents,edit,table of contents,TOC,outline,navigation,chapters,sections,add bookmarks,edit bookmarks,PDF outline"
|
||||
title = "Edit Table of Contents"
|
||||
|
||||
[home.extractFields]
|
||||
desc = "Pull typed fields out of a document with confidence scores and citations"
|
||||
tags = "extract,fields,schema,structured data,invoice,form data,key value,confidence,citations,capture,parse"
|
||||
title = "Extract Fields"
|
||||
|
||||
[home.extractImages]
|
||||
desc = "Extracts all images from a PDF and saves them to zip"
|
||||
tags = "pull,save,export,extract images,get images,save images,export images,extract photos,extract pictures,pull images,download images,rip images,extract graphics,save photos"
|
||||
@@ -4577,6 +4694,11 @@ desc = "Extract specific pages from a PDF document"
|
||||
tags = "pull,select,copy,extract,extract pages,get pages,pull out,save pages,export pages,copy pages,select pages,specific pages"
|
||||
title = "Extract Pages"
|
||||
|
||||
[home.fillTemplate]
|
||||
desc = "Fill a DOCX template's placeholders from JSON data"
|
||||
tags = "template,DOCX,fill,merge fields,mail merge,generate document,placeholders,letters,contracts,Word"
|
||||
title = "Fill Template"
|
||||
|
||||
[home.flatten]
|
||||
desc = "Remove all interactive elements and forms from a PDF"
|
||||
tags = "simplify,remove,interactive,flatten,flatten form,remove form fields,make static,finalize form,lock form,disable editing,convert to image,non-editable"
|
||||
@@ -4630,6 +4752,11 @@ desc = "Merge multiple pages of a PDF document into a single page"
|
||||
tags = "layout,arrange,combine,N-up,2-up,4-up,multiple per page,pages per sheet,layout pages,tile,grid layout,multi-page layout,combine on page,handout"
|
||||
title = "Multi-Page Layout"
|
||||
|
||||
[home.parseDocument]
|
||||
desc = "Layout-aware parsing to structured JSON or Markdown, with optional OCR"
|
||||
tags = "parse,layout,structure,blocks,markdown,JSON,docling,OCR,scan,document understanding,convert"
|
||||
title = "Parse Document"
|
||||
|
||||
[home.pdfCommentAgent]
|
||||
desc = "Ask AI to annotate a PDF with sticky-note comments based on your prompt"
|
||||
tags = "AI,agent,comment,annotate,sticky note,review,feedback,notes"
|
||||
@@ -4743,6 +4870,11 @@ desc = "Adds signature to PDF by drawing, text or image"
|
||||
tags = "signature,autograph,e-sign,electronic signature,digital signature,sign document,approval,signoff,authorize,endorse,ink signature,handwriting"
|
||||
title = "Sign"
|
||||
|
||||
[home.smartSplit]
|
||||
desc = "Split a PDF into sub-documents using a natural-language boundary rule"
|
||||
tags = "split,smart,boundaries,separate,invoices,batches,content split,divide,rules,auto split"
|
||||
title = "Smart Split"
|
||||
|
||||
[home.split]
|
||||
desc = "Split PDFs into multiple documents"
|
||||
tags = "divide,separate,break,split,extract pages,separate pages,divide document,break apart,separate files,unbind,split by page,divide by chapter"
|
||||
@@ -5501,6 +5633,33 @@ title = "Page Ranges"
|
||||
bullet1 = "<strong>all</strong> → selects all pages"
|
||||
title = "Special Keywords"
|
||||
|
||||
[parseDocument]
|
||||
intro = "Reads the document's layout - headings, paragraphs, tables - and turns it into clean structured JSON or Markdown you can feed to other systems."
|
||||
submit = "Parse document"
|
||||
|
||||
[parseDocument.error]
|
||||
failed = "Failed to parse document"
|
||||
|
||||
[parseDocument.mode]
|
||||
advanced = "Advanced"
|
||||
auto = "Auto"
|
||||
basic = "Basic"
|
||||
label = "Mode"
|
||||
|
||||
[parseDocument.outputFormat]
|
||||
json = "JSON"
|
||||
label = "Output format"
|
||||
markdown = "Markdown"
|
||||
|
||||
[parseDocument.results]
|
||||
title = "Parsed output"
|
||||
|
||||
[parseDocument.settings]
|
||||
title = "Parse settings"
|
||||
|
||||
[parseDocument.withOcr]
|
||||
label = "Apply OCR to scanned pages (recommended)"
|
||||
|
||||
[payg.activity]
|
||||
docs = "docs"
|
||||
empty = "No billable activity yet this period."
|
||||
@@ -7764,6 +7923,23 @@ unsavedTitle = "Unsaved changes"
|
||||
uploadUnsupported = "Uploaded files aren't supported in pipelines yet, so these steps can't be saved: {{tools}}."
|
||||
usesDefaults = "Runs with default settings"
|
||||
|
||||
[portal.pipelines.builder.docIntelligence]
|
||||
chunkSize = "Chunk size (characters)"
|
||||
exportChunks = "Export chunks (JSONL)"
|
||||
exportChunksHint = "Adds a .chunks.jsonl file to the step output, ready for external embedding or indexing."
|
||||
exportMarkdown = "Export markdown"
|
||||
exportMarkdownHint = "Adds a .md rendering of the parsed document to the step output."
|
||||
index = "Index into the knowledge base"
|
||||
indexHint = "Embed and store the chunks in the built-in knowledge base. Turn off for export-only ingestion."
|
||||
mode = "Parsing mode"
|
||||
modeAdvanced = "Advanced"
|
||||
modeAuto = "Auto"
|
||||
modeBasic = "Basic"
|
||||
overlap = "Overlap (characters)"
|
||||
ragIngest = "Ingest into knowledge base"
|
||||
ragIngestHint = "Parses, chunks, embeds, and indexes each document in one step. Export toggles add corpus files (markdown, chunks JSONL) to the step output for delivery to external systems."
|
||||
section = "Document intelligence"
|
||||
|
||||
[portal.pipelines.composer]
|
||||
addTool = "Add tool"
|
||||
cancel = "Cancel"
|
||||
@@ -7860,8 +8036,12 @@ label = "Classification"
|
||||
desc = "Enforce HIPAA, GDPR, SOC 2, or FedRAMP requirements on every document."
|
||||
label = "Compliance"
|
||||
|
||||
[portal.policies.categories.docIntelligence]
|
||||
desc = "Extract the structured fields you describe from every document, with confidence scores and citations."
|
||||
label = "Document intelligence"
|
||||
|
||||
[portal.policies.categories.ingestion]
|
||||
desc = "Classify documents, extract structured data, enforce naming conventions, and normalize pages."
|
||||
desc = "Normalize incoming documents - OCR scans, flatten forms - and index them into the searchable knowledge base, or export them as a clean corpus for your own systems."
|
||||
label = "Ingestion"
|
||||
|
||||
[portal.policies.categories.retention]
|
||||
@@ -7900,18 +8080,25 @@ onViolation = "When non-compliant"
|
||||
1 = "Enforce action"
|
||||
2 = "Audit trail"
|
||||
|
||||
[portal.policies.config.ingestion]
|
||||
summary = "Classifies documents, extracts structured data, enforces naming, and normalizes pages."
|
||||
[portal.policies.config.docIntelligence]
|
||||
summary = "Extracts the fields you describe from every document, with confidence and citations."
|
||||
|
||||
[portal.policies.config.ingestion.fields]
|
||||
belowThreshold = "Below threshold"
|
||||
minConfidence = "Min confidence"
|
||||
[portal.policies.config.docIntelligence.rules]
|
||||
0 = "Extract the fields you describe, with confidence and citations"
|
||||
|
||||
[portal.policies.config.extractFields.fields]
|
||||
instructions = "Extraction guidance (optional)"
|
||||
instructionsHelp = "Plain-language hints for tricky fields, e.g. \"the invoice number is top right\"."
|
||||
schema = "Fields to extract (JSON Schema)"
|
||||
schemaHelp = "A JSON Schema object describing the fields. Each extracted value carries a confidence score and a citation."
|
||||
|
||||
[portal.policies.config.ingestion]
|
||||
summary = "Normalizes incoming documents and indexes them into the searchable knowledge base, with optional markdown/JSONL export."
|
||||
|
||||
[portal.policies.config.ingestion.rules]
|
||||
0 = "Classify"
|
||||
1 = "Extract"
|
||||
2 = "Name"
|
||||
3 = "Normalize"
|
||||
0 = "OCR scans and flatten forms so every page is readable"
|
||||
1 = "Parse, chunk, embed, and index into the knowledge base"
|
||||
2 = "Optionally export markdown and chunks JSONL for external systems"
|
||||
|
||||
[portal.policies.config.purview]
|
||||
label = "Apply a Microsoft Purview sensitivity label"
|
||||
@@ -7936,6 +8123,25 @@ label = "Read a Microsoft Purview label"
|
||||
connection = "Purview tenant"
|
||||
connectionHelp = "Reads the label the document already carries, so later steps can act on it."
|
||||
|
||||
[portal.policies.config.ragIngest.fields]
|
||||
chunkSize = "Chunk size (characters)"
|
||||
chunkSizeHelp = "How much text each searchable passage holds. Larger chunks carry more context; smaller ones match more precisely."
|
||||
exportChunks = "Export chunks (JSONL)"
|
||||
exportChunksHelp = "Adds a .chunks.jsonl file to the step output - one chunk per line with page span - ready for external embedding or indexing."
|
||||
exportMarkdown = "Export markdown"
|
||||
exportMarkdownHelp = "Adds a .md rendering of the parsed document to the step output, for delivery to external systems."
|
||||
index = "Index into the knowledge base"
|
||||
indexHelp = "Embed and store the chunks in the built-in knowledge base. Turn off for export-only ingestion."
|
||||
overlap = "Chunk overlap (characters)"
|
||||
overlapHelp = "How much neighbouring chunks share, so answers spanning a boundary aren't cut in half."
|
||||
|
||||
[portal.policies.config.ragIngest.fields.mode]
|
||||
advanced = "Advanced (layout parsing addon)"
|
||||
auto = "Auto (best available)"
|
||||
basic = "Basic (text layer)"
|
||||
help = "Auto uses the best parser available. The advanced layout tier requires the engine's docparse addon."
|
||||
label = "Parse tier"
|
||||
|
||||
[portal.policies.config.retention]
|
||||
summary = "Enforces how long documents are kept, when to archive, and when to delete."
|
||||
|
||||
@@ -8005,8 +8211,10 @@ addWatermark = "Watermark"
|
||||
autoRedact = "Redact PII"
|
||||
classifyAndLabel = "Classify"
|
||||
compressPdf = "Compress"
|
||||
extractFields = "Extract fields"
|
||||
flatten = "Flatten"
|
||||
ocrPdf = "OCR"
|
||||
ragIngest = "Ingest into knowledge base"
|
||||
sanitizePdf = "Remove JavaScript"
|
||||
|
||||
[portal.policies.offline]
|
||||
@@ -8238,6 +8446,10 @@ label = "Classify the document"
|
||||
desc = "Compresses the document to a smaller file size."
|
||||
label = "Reduce file size"
|
||||
|
||||
[portal.policies.wizard.capability.extractFields]
|
||||
desc = "Pulls the values you describe - like invoice numbers or dates - out of every document, each with a confidence score and a citation back to the page."
|
||||
label = "Extract structured fields"
|
||||
|
||||
[portal.policies.wizard.capability.flatten]
|
||||
desc = "Merges form fields and annotations into the page so they can't be edited."
|
||||
label = "Flatten the document"
|
||||
@@ -8246,6 +8458,10 @@ label = "Flatten the document"
|
||||
desc = "Runs OCR so scanned pages become selectable, searchable text."
|
||||
label = "Make text searchable"
|
||||
|
||||
[portal.policies.wizard.capability.ragIngest]
|
||||
desc = "Parses, chunks, and embeds the document so it becomes searchable knowledge, or exports the parsed content (markdown, chunks JSONL) for your own systems."
|
||||
label = "Index into the knowledge base"
|
||||
|
||||
[portal.policies.wizard.capability.redact]
|
||||
desc = "Finds and blacks out sensitive details — like Social Security and card numbers — so they can't be read."
|
||||
label = "Redact sensitive information"
|
||||
@@ -10248,6 +10464,26 @@ medium = "Medium"
|
||||
small = "Small"
|
||||
x-large = "X-Large"
|
||||
|
||||
[smartSplit]
|
||||
intro = "Describe where sub-documents start in plain language and AI reads the content to find those boundaries - no page numbers needed."
|
||||
submit = "Split document"
|
||||
|
||||
[smartSplit.error]
|
||||
failed = "Failed to split document"
|
||||
|
||||
[smartSplit.maxParts]
|
||||
label = "Maximum parts"
|
||||
|
||||
[smartSplit.results]
|
||||
title = "Split documents"
|
||||
|
||||
[smartSplit.rule]
|
||||
label = "Split rule"
|
||||
placeholder = "e.g. Start a new document at every invoice header"
|
||||
|
||||
[smartSplit.settings]
|
||||
title = "Split settings"
|
||||
|
||||
[split]
|
||||
resultsTitle = "Split Results"
|
||||
selectMethod = "Select a split method"
|
||||
@@ -10714,6 +10950,7 @@ standardTools = "Standard Tools"
|
||||
advancedFormatting = "Advanced Formatting"
|
||||
automation = "Automation"
|
||||
developerTools = "Developer Tools"
|
||||
documentIntelligence = "Document intelligence"
|
||||
documentReview = "Document Review"
|
||||
documentSecurity = "Document Security"
|
||||
extraction = "Extraction"
|
||||
|
||||
@@ -22,6 +22,7 @@ import ViewAgendaRoundedIcon from "@mui/icons-material/ViewAgendaRounded";
|
||||
import FileDownloadRoundedIcon from "@mui/icons-material/FileDownloadRounded";
|
||||
import DeleteSweepRoundedIcon from "@mui/icons-material/DeleteSweepRounded";
|
||||
import SmartToyRoundedIcon from "@mui/icons-material/SmartToyRounded";
|
||||
import AutoAwesomeRoundedIcon from "@mui/icons-material/AutoAwesomeRounded";
|
||||
import BuildRoundedIcon from "@mui/icons-material/BuildRounded";
|
||||
import TuneRoundedIcon from "@mui/icons-material/TuneRounded";
|
||||
import CodeRoundedIcon from "@mui/icons-material/CodeRounded";
|
||||
@@ -34,6 +35,7 @@ export enum SubcategoryId {
|
||||
VERIFICATION = "verification",
|
||||
DOCUMENT_REVIEW = "documentReview",
|
||||
PAGE_FORMATTING = "pageFormatting",
|
||||
DOCUMENT_INTELLIGENCE = "documentIntelligence",
|
||||
EXTRACTION = "extraction",
|
||||
REMOVAL = "removal",
|
||||
AUTOMATION = "automation",
|
||||
@@ -95,6 +97,7 @@ export const SUBCATEGORY_ORDER: SubcategoryId[] = [
|
||||
SubcategoryId.VERIFICATION,
|
||||
SubcategoryId.DOCUMENT_REVIEW,
|
||||
SubcategoryId.PAGE_FORMATTING,
|
||||
SubcategoryId.DOCUMENT_INTELLIGENCE,
|
||||
SubcategoryId.EXTRACTION,
|
||||
SubcategoryId.REMOVAL,
|
||||
SubcategoryId.AUTOMATION,
|
||||
@@ -109,6 +112,7 @@ export const SUBCATEGORY_COLOR_MAP: Record<SubcategoryId, string> = {
|
||||
[SubcategoryId.VERIFICATION]: "var(--category-color-verification)", // Orange
|
||||
[SubcategoryId.DOCUMENT_REVIEW]: "var(--category-color-general)", // Blue
|
||||
[SubcategoryId.PAGE_FORMATTING]: "var(--category-color-formatting)", // Purple
|
||||
[SubcategoryId.DOCUMENT_INTELLIGENCE]: "var(--category-color-automation)", // Pink
|
||||
[SubcategoryId.EXTRACTION]: "var(--category-color-extraction)", // Cyan
|
||||
[SubcategoryId.REMOVAL]: "var(--category-color-removal)", // Red
|
||||
[SubcategoryId.AUTOMATION]: "var(--category-color-automation)", // Pink
|
||||
@@ -131,6 +135,8 @@ export const getSubcategoryIcon = (
|
||||
return React.createElement(RateReviewRoundedIcon);
|
||||
case SubcategoryId.PAGE_FORMATTING:
|
||||
return React.createElement(ViewAgendaRoundedIcon);
|
||||
case SubcategoryId.DOCUMENT_INTELLIGENCE:
|
||||
return React.createElement(AutoAwesomeRoundedIcon);
|
||||
case SubcategoryId.EXTRACTION:
|
||||
return React.createElement(FileDownloadRoundedIcon);
|
||||
case SubcategoryId.REMOVAL:
|
||||
|
||||
@@ -0,0 +1,10 @@
|
||||
import { useAppConfig } from "@app/contexts/AppConfigContext";
|
||||
|
||||
/**
|
||||
* Whether the DocParse layer is enabled, per the backend's app-config.
|
||||
* Gates the DocParse tools' visibility; flavors may shadow this hook.
|
||||
*/
|
||||
export function useDocparseEnabled(): boolean {
|
||||
const { config } = useAppConfig();
|
||||
return Boolean(config?.docparseEnabled);
|
||||
}
|
||||
@@ -0,0 +1,165 @@
|
||||
import { test, expect } from "@app/tests/helpers/stub-test-base";
|
||||
import type { Page, Route } from "@playwright/test";
|
||||
import path from "node:path";
|
||||
|
||||
/** DocParse walkthrough: the five workbench tools.
|
||||
* Dumps PNGs to screenshots/docparse; light + dark per view, RTL spot checks. */
|
||||
|
||||
const SCREENSHOTS_DIR = path.resolve(process.cwd(), "screenshots", "docparse");
|
||||
|
||||
function shotPath(name: string): string {
|
||||
return path.join(SCREENSHOTS_DIR, `${name}.png`);
|
||||
}
|
||||
|
||||
async function settle(page: Page, ms = 400): Promise<void> {
|
||||
await page.waitForTimeout(ms);
|
||||
}
|
||||
|
||||
async function stubApis(page: Page): Promise<void> {
|
||||
// Narrow fallbacks only: a blanket /api/v1/** would out-rank the stub
|
||||
// fixture's own /auth/me route (last-registered wins) and break the session.
|
||||
await page.route("**/api/v1/policies/**", (route: Route) =>
|
||||
route.fulfill({ json: [] }),
|
||||
);
|
||||
await page.route("**/api/v1/proprietary/ui-data/**", (route: Route) =>
|
||||
route.fulfill({ json: [] }),
|
||||
);
|
||||
// enableLogin true: the portal only builds a session when login mode is on
|
||||
// (matches live behavior; with login off the portal shows its login screen).
|
||||
const configPayload = {
|
||||
appVersion: "test",
|
||||
enableLogin: true,
|
||||
isAdmin: true,
|
||||
languages: ["en-US"],
|
||||
defaultLocale: "en-US",
|
||||
aiEngineEnabled: true,
|
||||
docparseEnabled: true,
|
||||
docparseAdvanced: true,
|
||||
storageEnabled: false,
|
||||
premiumEnabled: true,
|
||||
runningProOrHigher: true,
|
||||
};
|
||||
await page.route("**/api/v1/config/app-config", (route: Route) =>
|
||||
route.fulfill({ json: configPayload }),
|
||||
);
|
||||
// The auth layer decides login mode from public-config; keep it in sync.
|
||||
await page.route("**/api/v1/config/public-config", (route: Route) =>
|
||||
route.fulfill({
|
||||
json: { enableLogin: true, languages: ["en-US"], defaultLocale: "en-US" },
|
||||
}),
|
||||
);
|
||||
await page.route(
|
||||
"**/api/v1/config/endpoints-availability**",
|
||||
(route: Route) => route.fulfill({ json: {} }),
|
||||
);
|
||||
await page.route("**/api/v1/config/endpoint-enabled**", (route: Route) =>
|
||||
route.fulfill({ json: { enabled: true } }),
|
||||
);
|
||||
// DocparseToolIntro probes live capabilities for its tier badges.
|
||||
await page.route("**/api/v1/docparse/capabilities", (route: Route) =>
|
||||
route.fulfill({
|
||||
json: {
|
||||
enabled: true,
|
||||
mode: "auto",
|
||||
advancedInstalled: true,
|
||||
engineReachable: true,
|
||||
doclingVersion: "2.116.0",
|
||||
},
|
||||
}),
|
||||
);
|
||||
}
|
||||
|
||||
async function enableDarkMode(page: Page): Promise<void> {
|
||||
await page.addInitScript(() => {
|
||||
localStorage.setItem("mantine-color-scheme", "dark");
|
||||
localStorage.setItem("mantine-color-scheme-value", "dark");
|
||||
});
|
||||
await page.emulateMedia({ colorScheme: "dark" });
|
||||
}
|
||||
|
||||
async function enableRtl(page: Page): Promise<void> {
|
||||
await page.addInitScript(() => {
|
||||
localStorage.setItem("i18nextLng", "ar-AR");
|
||||
localStorage.setItem("stirling-language", "ar-AR");
|
||||
localStorage.setItem("stirling-language-source", "user");
|
||||
const applyDir = () => {
|
||||
document.documentElement.setAttribute("dir", "rtl");
|
||||
document.documentElement.setAttribute("lang", "ar-AR");
|
||||
};
|
||||
if (document.documentElement) applyDir();
|
||||
else document.addEventListener("DOMContentLoaded", applyDir);
|
||||
});
|
||||
}
|
||||
|
||||
const TOOLS = [
|
||||
{ id: "parseDocument", url: "/parse-document", waitText: /Parse/i },
|
||||
{ id: "extractFields", url: "/extract-fields", waitText: /Extract/i },
|
||||
{ id: "smartSplit", url: "/smart-split", waitText: /Split/i },
|
||||
{ id: "chunkDocument", url: "/chunk-document", waitText: /Chunk/i },
|
||||
{ id: "fillTemplate", url: "/fill-template", waitText: /Template|Fill/i },
|
||||
];
|
||||
|
||||
async function openTool(page: Page, url: string): Promise<void> {
|
||||
await page.goto(url, { waitUntil: "domcontentloaded" });
|
||||
await expect(page.locator("body").first()).not.toBeEmpty();
|
||||
// The tool panel is the left rail; give lazy chunks a moment.
|
||||
await settle(page, 900);
|
||||
}
|
||||
|
||||
test.describe("DocParse walkthrough", () => {
|
||||
test.use({
|
||||
autoGoto: false,
|
||||
viewport: { width: 1600, height: 900 },
|
||||
seedJwt: true,
|
||||
});
|
||||
|
||||
// ─── Editor tools, light ──────────────────────────────────────────────────
|
||||
for (const [i, tool] of TOOLS.entries()) {
|
||||
test(`t${i}_${tool.id}_light`, async ({ page }) => {
|
||||
await stubApis(page);
|
||||
await openTool(page, tool.url);
|
||||
await page.screenshot({ path: shotPath(`0${i + 1}_${tool.id}_light`) });
|
||||
});
|
||||
|
||||
test(`t${i}_${tool.id}_dark`, async ({ page }) => {
|
||||
await enableDarkMode(page);
|
||||
await stubApis(page);
|
||||
await openTool(page, tool.url);
|
||||
await page.screenshot({ path: shotPath(`0${i + 1}_${tool.id}_dark`) });
|
||||
});
|
||||
}
|
||||
|
||||
// ─── Extract Fields with builder rows filled ─────────────────────────────
|
||||
for (const theme of ["light", "dark"] as const) {
|
||||
test(`extract_fields_populated_${theme}`, async ({ page }) => {
|
||||
if (theme === "dark") await enableDarkMode(page);
|
||||
await stubApis(page);
|
||||
await openTool(page, "/extract-fields");
|
||||
// Fill the first schema-builder row when present; tolerate layout drift.
|
||||
const nameInput = page.getByPlaceholder(/name/i).first();
|
||||
if (await nameInput.isVisible().catch(() => false)) {
|
||||
await nameInput.fill("invoice_number");
|
||||
const addButton = page.getByRole("button", { name: /add/i }).first();
|
||||
if (await addButton.isVisible().catch(() => false)) {
|
||||
await addButton.click();
|
||||
const second = page.getByPlaceholder(/name/i).nth(1);
|
||||
if (await second.isVisible().catch(() => false)) {
|
||||
await second.fill("total_due");
|
||||
}
|
||||
}
|
||||
}
|
||||
await settle(page);
|
||||
await page.screenshot({
|
||||
path: shotPath(`06_extract_fields_populated_${theme}`),
|
||||
});
|
||||
});
|
||||
}
|
||||
|
||||
// ─── RTL spot checks ──────────────────────────────────────────────────────
|
||||
test("rtl_extract_fields", async ({ page }) => {
|
||||
await enableRtl(page);
|
||||
await stubApis(page);
|
||||
await openTool(page, "/extract-fields");
|
||||
await page.screenshot({ path: shotPath("11_extract_fields_rtl") });
|
||||
});
|
||||
});
|
||||
@@ -62,6 +62,7 @@ export interface AppConfig {
|
||||
timestampCustomTsaUrls?: string[];
|
||||
timestampTsaPresets?: { label: string; url: string }[];
|
||||
aiEngineEnabled?: boolean;
|
||||
docparseEnabled?: boolean;
|
||||
}
|
||||
|
||||
export type AppConfigBootstrapMode = "blocking" | "non-blocking";
|
||||
|
||||
@@ -138,7 +138,13 @@ export interface CatalogueEntry {
|
||||
* {@link ToolEndpoint}s, plus the AI classify endpoint, which isn't part of the generated union.
|
||||
*/
|
||||
export const ENDPOINT_LABELS: Partial<
|
||||
Record<ToolEndpoint | "/api/v1/ai/tools/classify-and-label", string>
|
||||
Record<
|
||||
| ToolEndpoint
|
||||
| "/api/v1/ai/tools/classify-and-label"
|
||||
| "/api/v1/docparse/rag-ingest"
|
||||
| "/api/v1/docparse/extract-fields",
|
||||
string
|
||||
>
|
||||
> = {
|
||||
"/api/v1/security/auto-redact": "portal.policies.endpoints.autoRedact",
|
||||
"/api/v1/security/sanitize-pdf": "portal.policies.endpoints.sanitizePdf",
|
||||
@@ -148,6 +154,8 @@ export const ENDPOINT_LABELS: Partial<
|
||||
"/api/v1/misc/compress-pdf": "portal.policies.endpoints.compressPdf",
|
||||
"/api/v1/ai/tools/classify-and-label":
|
||||
"portal.policies.endpoints.classifyAndLabel",
|
||||
"/api/v1/docparse/rag-ingest": "portal.policies.endpoints.ragIngest",
|
||||
"/api/v1/docparse/extract-fields": "portal.policies.endpoints.extractFields",
|
||||
};
|
||||
|
||||
export function humanizeEndpoint(
|
||||
@@ -174,13 +182,18 @@ const DEFAULT_PII_PATTERNS: string[] = [
|
||||
|
||||
/** `label`/`desc` values are i18n keys — render with t(). */
|
||||
export const POLICY_CATEGORIES: PolicyCategory[] = [
|
||||
// First on purpose: document intelligence is the processor's flagship flow.
|
||||
{
|
||||
id: "docIntelligence",
|
||||
label: "portal.policies.categories.docIntelligence.label",
|
||||
tone: "blue",
|
||||
desc: "portal.policies.categories.docIntelligence.desc",
|
||||
},
|
||||
{
|
||||
id: "ingestion",
|
||||
label: "portal.policies.categories.ingestion.label",
|
||||
tone: "blue",
|
||||
desc: "portal.policies.categories.ingestion.desc",
|
||||
providesClassification: true,
|
||||
comingSoon: true,
|
||||
},
|
||||
{
|
||||
id: "security",
|
||||
@@ -224,32 +237,27 @@ export const POLICY_CATEGORIES: PolicyCategory[] = [
|
||||
* stay as stable values (translating them would corrupt saved configs).
|
||||
*/
|
||||
export const POLICY_CONFIG: Record<string, PolicyConfigDef> = {
|
||||
docIntelligence: {
|
||||
summary: "portal.policies.config.docIntelligence.summary",
|
||||
rules: ["portal.policies.config.docIntelligence.rules.0"],
|
||||
scopeLabel: "portal.policies.config.scopeAll",
|
||||
defaultOperations: [policyStep("extractFields")],
|
||||
fields: [],
|
||||
},
|
||||
ingestion: {
|
||||
summary: "portal.policies.config.ingestion.summary",
|
||||
rules: [
|
||||
"portal.policies.config.ingestion.rules.0",
|
||||
"portal.policies.config.ingestion.rules.1",
|
||||
"portal.policies.config.ingestion.rules.2",
|
||||
"portal.policies.config.ingestion.rules.3",
|
||||
],
|
||||
scopeLabel: "portal.policies.config.scopeAll",
|
||||
defaultOperations: [policyStep("ocr"), policyStep("flatten")],
|
||||
fields: [
|
||||
{
|
||||
label: "portal.policies.config.ingestion.fields.minConfidence",
|
||||
key: "minConfidence",
|
||||
type: "select",
|
||||
value: "p80",
|
||||
options: ["p60", "p70", "p80", "p90", "p95"],
|
||||
},
|
||||
{
|
||||
label: "portal.policies.config.ingestion.fields.belowThreshold",
|
||||
key: "belowThreshold",
|
||||
type: "select",
|
||||
value: "flagForReview",
|
||||
options: ["flagForReview", "routeToBucket", "hold"],
|
||||
},
|
||||
defaultOperations: [
|
||||
policyStep("ocr"),
|
||||
policyStep("flatten"),
|
||||
policyStep("ragIngest"),
|
||||
],
|
||||
fields: [],
|
||||
},
|
||||
security: {
|
||||
summary: "portal.policies.config.security.summary",
|
||||
|
||||
@@ -48,6 +48,16 @@ export function EditorIcon(props: IconProps) {
|
||||
);
|
||||
}
|
||||
|
||||
export function KnowledgeIcon(props: IconProps) {
|
||||
return (
|
||||
<Svg {...props}>
|
||||
<ellipse cx="12" cy="5" rx="8" ry="3" />
|
||||
<path d="M4 5v6c0 1.66 3.58 3 8 3s8-1.34 8-3V5" />
|
||||
<path d="M4 11v6c0 1.66 3.58 3 8 3s8-1.34 8-3v-6" />
|
||||
</Svg>
|
||||
);
|
||||
}
|
||||
|
||||
export function SourcesIcon(props: IconProps) {
|
||||
return (
|
||||
<Svg {...props}>
|
||||
|
||||
@@ -49,4 +49,30 @@ describe("PipelineStepSettings", () => {
|
||||
).not.toThrow();
|
||||
expect(screen.getByText("field")).toBeInTheDocument();
|
||||
});
|
||||
|
||||
it("renders the rag-ingest form for the knowledge indexing operation", () => {
|
||||
const ragStep = {
|
||||
support: "unknown",
|
||||
toolId: null,
|
||||
operation: "/api/v1/docparse/rag-ingest",
|
||||
params: { chunkSize: 512, overlap: 64, mode: "auto" },
|
||||
} as unknown as WorkingToolStep;
|
||||
render(
|
||||
<MantineProvider>
|
||||
<PipelineStepSettings
|
||||
step={ragStep}
|
||||
registry={{}}
|
||||
onChange={() => {}}
|
||||
/>
|
||||
</MantineProvider>,
|
||||
);
|
||||
expect(
|
||||
screen.getByText("portal.pipelines.builder.docIntelligence.chunkSize"),
|
||||
).toBeInTheDocument();
|
||||
expect(
|
||||
screen.getByText(
|
||||
"portal.pipelines.builder.docIntelligence.ragIngestHint",
|
||||
),
|
||||
).toBeInTheDocument();
|
||||
});
|
||||
});
|
||||
|
||||
@@ -10,6 +10,11 @@ import { type WorkingToolStep } from "@app/hooks/tools/shared/toolAutomation";
|
||||
import { PolicyExternalApiConfig } from "@portal/components/policies/PolicyExternalApiConfig";
|
||||
import { isIntegrationStep } from "@portal/components/pipelines/integrationStep";
|
||||
import type { ExternalApiStepParams } from "@portal/components/policies/stepOperations";
|
||||
import { RAG_INGEST_OPERATION } from "@portal/components/pipelines/docIntelligenceSteps";
|
||||
import {
|
||||
RagIngestStepConfig,
|
||||
type RagIngestParams,
|
||||
} from "@portal/components/pipelines/RagIngestStepConfig";
|
||||
|
||||
interface PipelineStepSettingsProps {
|
||||
step: WorkingToolStep;
|
||||
@@ -31,6 +36,16 @@ export function PipelineStepSettings({
|
||||
// above useTranslation would change the hook count between renders and crash.
|
||||
const { t } = useTranslation();
|
||||
|
||||
// Document-intelligence steps carry their own small forms; they have no registry entry.
|
||||
if (step.operation === RAG_INGEST_OPERATION) {
|
||||
return (
|
||||
<RagIngestStepConfig
|
||||
parameters={step.params as unknown as RagIngestParams}
|
||||
onChange={(params) => onChange(params as never)}
|
||||
/>
|
||||
);
|
||||
}
|
||||
|
||||
// An integration step is configured by the operations catalogue, not by a tool's settings UI:
|
||||
// it has no registry entry to look one up from.
|
||||
if (isIntegrationStep(step)) {
|
||||
|
||||
@@ -0,0 +1,112 @@
|
||||
import { useTranslation } from "react-i18next";
|
||||
import { FormField, Input, Select, ToggleSwitch } from "@app/ui";
|
||||
|
||||
/** Parameters for the "Ingest into knowledge base" pipeline step. */
|
||||
export interface RagIngestParams {
|
||||
chunkSize?: number;
|
||||
overlap?: number;
|
||||
mode?: string;
|
||||
index?: boolean;
|
||||
exportMarkdown?: boolean;
|
||||
exportChunksJsonl?: boolean;
|
||||
}
|
||||
|
||||
interface RagIngestStepConfigProps {
|
||||
parameters: RagIngestParams;
|
||||
onChange: (parameters: RagIngestParams) => void;
|
||||
}
|
||||
|
||||
/** Settings for the rag-ingest step: destination toggles, chunking knobs, parse tier. */
|
||||
export function RagIngestStepConfig({
|
||||
parameters,
|
||||
onChange,
|
||||
}: RagIngestStepConfigProps) {
|
||||
const { t } = useTranslation();
|
||||
const setNumber = (key: "chunkSize" | "overlap", raw: string) => {
|
||||
const value = Number(raw);
|
||||
onChange({
|
||||
...parameters,
|
||||
[key]: Number.isFinite(value) && raw !== "" ? value : undefined,
|
||||
});
|
||||
};
|
||||
return (
|
||||
<div className="portal-policies__capability-config">
|
||||
<ToggleSwitch
|
||||
size="sm"
|
||||
checked={parameters.index ?? true}
|
||||
onChange={(checked) => onChange({ ...parameters, index: checked })}
|
||||
label={t("portal.pipelines.builder.docIntelligence.index")}
|
||||
description={t("portal.pipelines.builder.docIntelligence.indexHint")}
|
||||
/>
|
||||
<ToggleSwitch
|
||||
size="sm"
|
||||
checked={parameters.exportMarkdown ?? false}
|
||||
onChange={(checked) =>
|
||||
onChange({ ...parameters, exportMarkdown: checked })
|
||||
}
|
||||
label={t("portal.pipelines.builder.docIntelligence.exportMarkdown")}
|
||||
description={t(
|
||||
"portal.pipelines.builder.docIntelligence.exportMarkdownHint",
|
||||
)}
|
||||
/>
|
||||
<ToggleSwitch
|
||||
size="sm"
|
||||
checked={parameters.exportChunksJsonl ?? false}
|
||||
onChange={(checked) =>
|
||||
onChange({ ...parameters, exportChunksJsonl: checked })
|
||||
}
|
||||
label={t("portal.pipelines.builder.docIntelligence.exportChunks")}
|
||||
description={t(
|
||||
"portal.pipelines.builder.docIntelligence.exportChunksHint",
|
||||
)}
|
||||
/>
|
||||
<FormField
|
||||
label={t("portal.pipelines.builder.docIntelligence.chunkSize")}
|
||||
>
|
||||
<Input
|
||||
type="number"
|
||||
inputSize="sm"
|
||||
min={64}
|
||||
max={32768}
|
||||
value={parameters.chunkSize ?? ""}
|
||||
onChange={(e) => setNumber("chunkSize", e.target.value)}
|
||||
/>
|
||||
</FormField>
|
||||
<FormField label={t("portal.pipelines.builder.docIntelligence.overlap")}>
|
||||
<Input
|
||||
type="number"
|
||||
inputSize="sm"
|
||||
min={0}
|
||||
max={4096}
|
||||
value={parameters.overlap ?? ""}
|
||||
onChange={(e) => setNumber("overlap", e.target.value)}
|
||||
/>
|
||||
</FormField>
|
||||
<FormField label={t("portal.pipelines.builder.docIntelligence.mode")}>
|
||||
<Select
|
||||
value={parameters.mode ?? "auto"}
|
||||
onChange={(value) =>
|
||||
onChange({ ...parameters, mode: value ?? "auto" })
|
||||
}
|
||||
options={[
|
||||
{
|
||||
value: "auto",
|
||||
label: t("portal.pipelines.builder.docIntelligence.modeAuto"),
|
||||
},
|
||||
{
|
||||
value: "basic",
|
||||
label: t("portal.pipelines.builder.docIntelligence.modeBasic"),
|
||||
},
|
||||
{
|
||||
value: "advanced",
|
||||
label: t("portal.pipelines.builder.docIntelligence.modeAdvanced"),
|
||||
},
|
||||
]}
|
||||
/>
|
||||
</FormField>
|
||||
<p className="portal-pipelines__step-hint">
|
||||
{t("portal.pipelines.builder.docIntelligence.ragIngestHint")}
|
||||
</p>
|
||||
</div>
|
||||
);
|
||||
}
|
||||
@@ -11,7 +11,12 @@ import {
|
||||
searchOperations,
|
||||
type StepOperation,
|
||||
} from "@portal/components/policies/stepOperations";
|
||||
import {
|
||||
DOC_INTELLIGENCE_STEPS,
|
||||
type DocIntelligenceStep,
|
||||
} from "@portal/components/pipelines/docIntelligenceSteps";
|
||||
import { BrandMark } from "@portal/components/BrandMarks";
|
||||
import { KnowledgeIcon } from "@portal/components/icons";
|
||||
|
||||
interface ToolPickerProps {
|
||||
tools: ExecutableTool[];
|
||||
@@ -24,6 +29,8 @@ interface ToolPickerProps {
|
||||
*/
|
||||
operations?: StepOperation[];
|
||||
onPickOperation?: (operation: StepOperation) => void;
|
||||
/** Document-intelligence policy steps (knowledge indexing). */
|
||||
onPickDocStep?: (step: DocIntelligenceStep) => void;
|
||||
}
|
||||
|
||||
/**
|
||||
@@ -36,6 +43,7 @@ export function ToolPicker({
|
||||
onClose,
|
||||
operations = [],
|
||||
onPickOperation,
|
||||
onPickDocStep,
|
||||
}: ToolPickerProps) {
|
||||
const { t } = useTranslation();
|
||||
const [query, setQuery] = useState("");
|
||||
@@ -48,6 +56,14 @@ export function ToolPicker({
|
||||
[operations, onPickOperation, query, t],
|
||||
);
|
||||
|
||||
const matchedDocSteps = useMemo(() => {
|
||||
if (!onPickDocStep) return [];
|
||||
const q = query.trim().toLowerCase();
|
||||
return DOC_INTELLIGENCE_STEPS.filter(
|
||||
(step) => !q || t(step.labelKey).toLowerCase().includes(q),
|
||||
);
|
||||
}, [onPickDocStep, query, t]);
|
||||
|
||||
const groups = useMemo(() => {
|
||||
const q = query.trim().toLowerCase();
|
||||
const matched = q
|
||||
@@ -84,7 +100,38 @@ export function ToolPicker({
|
||||
/>
|
||||
</div>
|
||||
<div className="portal-pipelines__picker-list">
|
||||
{groups.length === 0 && matchedOperations.length === 0 ? (
|
||||
{matchedDocSteps.length > 0 && onPickDocStep ? (
|
||||
<div className="portal-pipelines__picker-group">
|
||||
<div className="portal-pipelines__picker-group-label">
|
||||
{t("portal.pipelines.builder.docIntelligence.section")}
|
||||
</div>
|
||||
{matchedDocSteps.map((step) => (
|
||||
<Button
|
||||
key={step.operation}
|
||||
variant="quiet"
|
||||
justify="start"
|
||||
fullWidth
|
||||
className="portal-pipelines__picker-item"
|
||||
onClick={() => onPickDocStep(step)}
|
||||
leftSection={
|
||||
<span
|
||||
className="portal-pipelines__picker-icon"
|
||||
aria-hidden="true"
|
||||
>
|
||||
<KnowledgeIcon size={17} />
|
||||
</span>
|
||||
}
|
||||
>
|
||||
<span className="portal-pipelines__picker-name">
|
||||
{t(step.labelKey)}
|
||||
</span>
|
||||
</Button>
|
||||
))}
|
||||
</div>
|
||||
) : null}
|
||||
{groups.length === 0 &&
|
||||
matchedOperations.length === 0 &&
|
||||
matchedDocSteps.length === 0 ? (
|
||||
<p className="portal-pipelines__picker-empty">
|
||||
{t("portal.pipelines.builder.noToolMatches")}
|
||||
</p>
|
||||
|
||||
@@ -0,0 +1,45 @@
|
||||
import type { WorkingToolStep } from "@app/hooks/tools/shared/toolAutomation";
|
||||
import type { ErasedToolParams } from "@app/hooks/tools/shared/toolOperationTypes";
|
||||
|
||||
/**
|
||||
* First-class document-intelligence policy steps addable from the pipeline builder.
|
||||
* They ride the unmapped-step path like integration steps (toolId null), but hit
|
||||
* internal endpoints.
|
||||
*/
|
||||
export interface DocIntelligenceStep {
|
||||
operation: string;
|
||||
labelKey: string;
|
||||
defaultParams: Record<string, unknown>;
|
||||
}
|
||||
|
||||
export const RAG_INGEST_OPERATION = "/api/v1/docparse/rag-ingest";
|
||||
|
||||
export const DOC_INTELLIGENCE_STEPS: DocIntelligenceStep[] = [
|
||||
{
|
||||
operation: RAG_INGEST_OPERATION,
|
||||
labelKey: "portal.pipelines.builder.docIntelligence.ragIngest",
|
||||
defaultParams: {
|
||||
chunkSize: 512,
|
||||
overlap: 64,
|
||||
mode: "auto",
|
||||
index: true,
|
||||
exportMarkdown: false,
|
||||
exportChunksJsonl: false,
|
||||
},
|
||||
},
|
||||
];
|
||||
|
||||
export function newDocIntelligenceStep(
|
||||
step: DocIntelligenceStep,
|
||||
): WorkingToolStep {
|
||||
return {
|
||||
toolId: null,
|
||||
operation: step.operation,
|
||||
params: { ...step.defaultParams } as ErasedToolParams,
|
||||
support: "unknown",
|
||||
};
|
||||
}
|
||||
|
||||
export function isDocIntelligenceOperation(operation: string): boolean {
|
||||
return DOC_INTELLIGENCE_STEPS.some((step) => step.operation === operation);
|
||||
}
|
||||
@@ -0,0 +1,54 @@
|
||||
import { useTranslation } from "react-i18next";
|
||||
import { FormField, Input } from "@app/ui";
|
||||
|
||||
/** Configures the extract-fields step: the schema and optional guidance. */
|
||||
export interface ExtractFieldsStepParams {
|
||||
fieldsSchema: string;
|
||||
mode: string;
|
||||
instructions: string;
|
||||
}
|
||||
|
||||
interface PolicyExtractFieldsConfigProps {
|
||||
parameters: ExtractFieldsStepParams;
|
||||
onChange: (parameters: ExtractFieldsStepParams) => void;
|
||||
}
|
||||
|
||||
export function PolicyExtractFieldsConfig({
|
||||
parameters,
|
||||
onChange,
|
||||
}: PolicyExtractFieldsConfigProps) {
|
||||
const { t } = useTranslation();
|
||||
|
||||
return (
|
||||
<div className="portal-policies__capability-config">
|
||||
<FormField
|
||||
label={t("portal.policies.config.extractFields.fields.schema")}
|
||||
helperText={t("portal.policies.config.extractFields.fields.schemaHelp")}
|
||||
>
|
||||
<textarea
|
||||
className="portal-sources__connection-textarea"
|
||||
rows={4}
|
||||
value={parameters.fieldsSchema ?? ""}
|
||||
placeholder='{"type": "object", "properties": {"invoice_number": {"type": "string"}}}'
|
||||
onChange={(e) =>
|
||||
onChange({ ...parameters, fieldsSchema: e.target.value })
|
||||
}
|
||||
/>
|
||||
</FormField>
|
||||
<FormField
|
||||
label={t("portal.policies.config.extractFields.fields.instructions")}
|
||||
helperText={t(
|
||||
"portal.policies.config.extractFields.fields.instructionsHelp",
|
||||
)}
|
||||
>
|
||||
<Input
|
||||
inputSize="sm"
|
||||
value={parameters.instructions ?? ""}
|
||||
onChange={(e) =>
|
||||
onChange({ ...parameters, instructions: e.target.value })
|
||||
}
|
||||
/>
|
||||
</FormField>
|
||||
</div>
|
||||
);
|
||||
}
|
||||
@@ -0,0 +1,116 @@
|
||||
import { useTranslation } from "react-i18next";
|
||||
import { FormField, Input, Select, ToggleSwitch } from "@app/ui";
|
||||
|
||||
/** Configures the rag-ingest step: destination toggles, chunk sizing, parse tier. */
|
||||
export interface RagIngestParams {
|
||||
chunkSize: string;
|
||||
overlap: string;
|
||||
mode: string;
|
||||
index: string;
|
||||
exportMarkdown: string;
|
||||
exportChunksJsonl: string;
|
||||
}
|
||||
|
||||
interface PolicyRagIngestConfigProps {
|
||||
parameters: RagIngestParams;
|
||||
onChange: (parameters: RagIngestParams) => void;
|
||||
}
|
||||
|
||||
export function PolicyRagIngestConfig({
|
||||
parameters,
|
||||
onChange,
|
||||
}: PolicyRagIngestConfigProps) {
|
||||
const { t } = useTranslation();
|
||||
const flag = (value: string | undefined, fallback: boolean): boolean =>
|
||||
value === undefined ? fallback : value === "true";
|
||||
|
||||
return (
|
||||
<div className="portal-policies__capability-config">
|
||||
<ToggleSwitch
|
||||
size="sm"
|
||||
checked={flag(parameters.index, true)}
|
||||
onChange={(checked) =>
|
||||
onChange({ ...parameters, index: String(checked) })
|
||||
}
|
||||
label={t("portal.policies.config.ragIngest.fields.index")}
|
||||
description={t("portal.policies.config.ragIngest.fields.indexHelp")}
|
||||
/>
|
||||
<ToggleSwitch
|
||||
size="sm"
|
||||
checked={flag(parameters.exportMarkdown, false)}
|
||||
onChange={(checked) =>
|
||||
onChange({ ...parameters, exportMarkdown: String(checked) })
|
||||
}
|
||||
label={t("portal.policies.config.ragIngest.fields.exportMarkdown")}
|
||||
description={t(
|
||||
"portal.policies.config.ragIngest.fields.exportMarkdownHelp",
|
||||
)}
|
||||
/>
|
||||
<ToggleSwitch
|
||||
size="sm"
|
||||
checked={flag(parameters.exportChunksJsonl, false)}
|
||||
onChange={(checked) =>
|
||||
onChange({ ...parameters, exportChunksJsonl: String(checked) })
|
||||
}
|
||||
label={t("portal.policies.config.ragIngest.fields.exportChunks")}
|
||||
description={t(
|
||||
"portal.policies.config.ragIngest.fields.exportChunksHelp",
|
||||
)}
|
||||
/>
|
||||
<FormField
|
||||
label={t("portal.policies.config.ragIngest.fields.chunkSize")}
|
||||
helperText={t("portal.policies.config.ragIngest.fields.chunkSizeHelp")}
|
||||
>
|
||||
<Input
|
||||
type="number"
|
||||
inputSize="sm"
|
||||
min={64}
|
||||
step={64}
|
||||
value={parameters.chunkSize ?? ""}
|
||||
onChange={(e) =>
|
||||
onChange({ ...parameters, chunkSize: e.target.value })
|
||||
}
|
||||
/>
|
||||
</FormField>
|
||||
<FormField
|
||||
label={t("portal.policies.config.ragIngest.fields.overlap")}
|
||||
helperText={t("portal.policies.config.ragIngest.fields.overlapHelp")}
|
||||
>
|
||||
<Input
|
||||
type="number"
|
||||
inputSize="sm"
|
||||
min={0}
|
||||
step={16}
|
||||
value={parameters.overlap ?? ""}
|
||||
onChange={(e) => onChange({ ...parameters, overlap: e.target.value })}
|
||||
/>
|
||||
</FormField>
|
||||
<FormField
|
||||
label={t("portal.policies.config.ragIngest.fields.mode.label")}
|
||||
helperText={t("portal.policies.config.ragIngest.fields.mode.help")}
|
||||
>
|
||||
<Select
|
||||
inputSize="sm"
|
||||
value={parameters.mode || "auto"}
|
||||
onChange={(value) =>
|
||||
onChange({ ...parameters, mode: value ?? "auto" })
|
||||
}
|
||||
options={[
|
||||
{
|
||||
value: "auto",
|
||||
label: t("portal.policies.config.ragIngest.fields.mode.auto"),
|
||||
},
|
||||
{
|
||||
value: "basic",
|
||||
label: t("portal.policies.config.ragIngest.fields.mode.basic"),
|
||||
},
|
||||
{
|
||||
value: "advanced",
|
||||
label: t("portal.policies.config.ragIngest.fields.mode.advanced"),
|
||||
},
|
||||
]}
|
||||
/>
|
||||
</FormField>
|
||||
</div>
|
||||
);
|
||||
}
|
||||
@@ -40,6 +40,8 @@ import { PolicyCategoryBadge } from "@portal/components/policies/PolicyCategoryI
|
||||
import { PolicyRedactConfig } from "@app/components/policies/PolicyRedactConfig";
|
||||
import { PolicyWatermarkConfig } from "@app/components/policies/PolicyWatermarkConfig";
|
||||
import { PolicyPurviewConfig } from "@portal/components/policies/PolicyPurviewConfig";
|
||||
import { PolicyExtractFieldsConfig } from "@portal/components/policies/PolicyExtractFieldsConfig";
|
||||
import { PolicyRagIngestConfig } from "@portal/components/policies/PolicyRagIngestConfig";
|
||||
import { ClassificationLabelsSection } from "@portal/components/policies/ClassificationLabelsSection";
|
||||
import "@portal/views/Policies.css";
|
||||
|
||||
@@ -97,6 +99,8 @@ const DISABLED_BY_DEFAULT = new Set<PolicyToolId>([
|
||||
"purviewApplyLabel",
|
||||
"purviewReadLabel",
|
||||
"externalApiCall",
|
||||
// Needs a fields schema before a run can succeed.
|
||||
"extractFields",
|
||||
]);
|
||||
|
||||
// Steps that cannot work without a Purview tenant connection, so they are hidden entirely until one
|
||||
@@ -192,6 +196,21 @@ const CAPABILITY_META: Record<
|
||||
descEn:
|
||||
"Hands the document to a system you have connected, and records what it answered.",
|
||||
},
|
||||
extractFields: {
|
||||
labelKey: "portal.policies.wizard.capability.extractFields.label",
|
||||
labelEn: "Extract structured fields",
|
||||
descKey: "portal.policies.wizard.capability.extractFields.desc",
|
||||
descEn:
|
||||
"Pulls the values you describe - like invoice numbers or dates - out of every document, each with a confidence score and a citation back to the page.",
|
||||
},
|
||||
ragIngest: {
|
||||
labelKey: "portal.policies.wizard.capability.ragIngest.label",
|
||||
labelEn: "Index into the knowledge base",
|
||||
descKey: "portal.policies.wizard.capability.ragIngest.desc",
|
||||
descEn:
|
||||
"Parses, chunks, and embeds the document so it becomes searchable knowledge, or exports the" +
|
||||
" parsed content (markdown, chunks JSONL) for your own systems.",
|
||||
},
|
||||
};
|
||||
|
||||
function seedTools(entry: CatalogueEntry): ToolState[] {
|
||||
@@ -553,6 +572,22 @@ function PolicySetupWizardBody({
|
||||
}
|
||||
/>
|
||||
)}
|
||||
{tl.toolId === "extractFields" && (
|
||||
<PolicyExtractFieldsConfig
|
||||
parameters={tl.params}
|
||||
onChange={(params) =>
|
||||
setToolParams("extractFields", params)
|
||||
}
|
||||
/>
|
||||
)}
|
||||
{tl.toolId === "ragIngest" && (
|
||||
<PolicyRagIngestConfig
|
||||
parameters={tl.params}
|
||||
onChange={(params) =>
|
||||
setToolParams("ragIngest", params)
|
||||
}
|
||||
/>
|
||||
)}
|
||||
</div>
|
||||
)}
|
||||
</div>
|
||||
|
||||
@@ -58,6 +58,10 @@ import { VIEW_PATHS, toPortalPath } from "@portal/contexts/ViewContext";
|
||||
import { humanizeOperation } from "@portal/components/pipelines/pipelineOperations";
|
||||
import { PipelineStepSettings } from "@portal/components/pipelines/PipelineStepSettings";
|
||||
import { ToolPicker } from "@portal/components/pipelines/ToolPicker";
|
||||
import {
|
||||
newDocIntelligenceStep,
|
||||
type DocIntelligenceStep,
|
||||
} from "@portal/components/pipelines/docIntelligenceSteps";
|
||||
import { STEP_OPERATIONS } from "@portal/components/policies/stepOperations";
|
||||
import {
|
||||
integrationStepConfigured,
|
||||
@@ -261,6 +265,15 @@ export function PipelineBuilder() {
|
||||
setPickerOpen(false);
|
||||
}
|
||||
|
||||
function addDocIntelligenceStep(step: DocIntelligenceStep) {
|
||||
setSteps((current) => {
|
||||
const next = [...current, newDocIntelligenceStep(step)];
|
||||
setSelectedIndex(next.length - 1);
|
||||
return next;
|
||||
});
|
||||
setPickerOpen(false);
|
||||
}
|
||||
|
||||
function addStep(tool: ExecutableTool) {
|
||||
setSteps((current) => {
|
||||
const next = [...current, newWorkingToolStep(tool, allTools)];
|
||||
@@ -852,6 +865,7 @@ export function PipelineBuilder() {
|
||||
onPick={addStep}
|
||||
operations={STEP_OPERATIONS}
|
||||
onPickOperation={addOperationStep}
|
||||
onPickDocStep={addDocIntelligenceStep}
|
||||
onClose={() => setPickerOpen(false)}
|
||||
/>
|
||||
) : (
|
||||
|
||||
@@ -0,0 +1,91 @@
|
||||
import { useTranslation } from "react-i18next";
|
||||
import { Anchor, List, NumberInput, Select, Stack, Text } from "@mantine/core";
|
||||
import type { ToolAutomationSettingsProps } from "@app/hooks/tools/shared/toolOperationTypes";
|
||||
import type { ChunkDocumentParameters } from "@app/hooks/tools/chunkDocument/useChunkDocumentParameters";
|
||||
import type { DocparseMode } from "@app/hooks/tools/parseDocument/useParseDocumentParameters";
|
||||
import DocparseToolIntro from "@app/components/tools/docparse/DocparseToolIntro";
|
||||
|
||||
const ChunkDocumentSettings = ({
|
||||
parameters,
|
||||
onParameterChange,
|
||||
disabled,
|
||||
}: ToolAutomationSettingsProps<ChunkDocumentParameters>) => {
|
||||
const { t } = useTranslation();
|
||||
|
||||
return (
|
||||
<Stack gap="sm">
|
||||
<DocparseToolIntro
|
||||
description={t(
|
||||
"chunkDocument.intro",
|
||||
"Turns a document into retrieval-ready chunks in three layers, so answers cite the right section instead of a random page.",
|
||||
)}
|
||||
aiBadge="layout"
|
||||
/>
|
||||
<List type="ordered" size="sm" spacing={4}>
|
||||
<List.Item>
|
||||
{t(
|
||||
"chunkDocument.layers.parse",
|
||||
"Layout-aware parse: headings, paragraphs, and tables are recognized as structure",
|
||||
)}
|
||||
</List.Item>
|
||||
<List.Item>
|
||||
{t(
|
||||
"chunkDocument.layers.chunk",
|
||||
"Structure-aware chunks: each carries its heading breadcrumb and page range",
|
||||
)}
|
||||
</List.Item>
|
||||
<List.Item>
|
||||
{t(
|
||||
"chunkDocument.layers.embed",
|
||||
"Ready to embed: exported as JSONL for any vector store",
|
||||
)}
|
||||
</List.Item>
|
||||
</List>
|
||||
<NumberInput
|
||||
label={t("chunkDocument.chunkSize.label", "Chunk size (characters)")}
|
||||
value={parameters.chunkSize}
|
||||
onChange={(value) =>
|
||||
onParameterChange("chunkSize", typeof value === "number" ? value : 0)
|
||||
}
|
||||
min={1}
|
||||
disabled={disabled}
|
||||
/>
|
||||
<NumberInput
|
||||
label={t("chunkDocument.overlap.label", "Overlap (characters)")}
|
||||
value={parameters.overlap}
|
||||
onChange={(value) =>
|
||||
onParameterChange("overlap", typeof value === "number" ? value : 0)
|
||||
}
|
||||
min={0}
|
||||
disabled={disabled}
|
||||
/>
|
||||
<Select
|
||||
label={t("chunkDocument.mode.label", "Mode")}
|
||||
value={parameters.mode}
|
||||
onChange={(value) =>
|
||||
onParameterChange("mode", (value ?? "auto") as DocparseMode)
|
||||
}
|
||||
data={[
|
||||
{ value: "auto", label: t("chunkDocument.mode.auto", "Auto") },
|
||||
{ value: "basic", label: t("chunkDocument.mode.basic", "Basic") },
|
||||
{
|
||||
value: "advanced",
|
||||
label: t("chunkDocument.mode.advanced", "Advanced"),
|
||||
},
|
||||
]}
|
||||
disabled={disabled}
|
||||
/>
|
||||
<Text size="xs" c="dimmed">
|
||||
{t(
|
||||
"chunkDocument.processorCallout",
|
||||
"To index automatically, add the 'Index into knowledge base' step to an ingestion policy in the",
|
||||
)}{" "}
|
||||
<Anchor href="/processor/policies" size="xs">
|
||||
{t("chunkDocument.processorLink", "Processor")}
|
||||
</Anchor>
|
||||
</Text>
|
||||
</Stack>
|
||||
);
|
||||
};
|
||||
|
||||
export default ChunkDocumentSettings;
|
||||
+30
@@ -0,0 +1,30 @@
|
||||
.card {
|
||||
display: flex;
|
||||
flex-direction: column;
|
||||
gap: 0.5rem;
|
||||
padding: 0.625rem 0.75rem;
|
||||
border: 1px solid var(--c-border-subtle);
|
||||
border-radius: 8px;
|
||||
background: var(--c-surface-sunken);
|
||||
}
|
||||
|
||||
.description {
|
||||
margin: 0;
|
||||
font-size: 0.8125rem;
|
||||
line-height: 1.45;
|
||||
color: var(--c-text-subtle);
|
||||
}
|
||||
|
||||
.badges {
|
||||
display: flex;
|
||||
flex-wrap: wrap;
|
||||
gap: 0.375rem;
|
||||
}
|
||||
|
||||
.fallback {
|
||||
margin: 0;
|
||||
font-size: 0.75rem;
|
||||
line-height: 1.4;
|
||||
color: var(--c-text-subtle);
|
||||
font-style: italic;
|
||||
}
|
||||
@@ -0,0 +1,62 @@
|
||||
import { useTranslation } from "react-i18next";
|
||||
import { Badge } from "@mantine/core";
|
||||
import { useDocparseCapabilities } from "@app/hooks/useDocparseCapabilities";
|
||||
import styles from "@app/components/tools/docparse/DocparseToolIntro.module.css";
|
||||
|
||||
interface DocparseToolIntroProps {
|
||||
/** 1-2 sentence "how this works" copy for the tool, already translated. */
|
||||
description: string;
|
||||
/**
|
||||
* Which AI badge fits the tool: "llm" tools always call the language model;
|
||||
* "layout" tools use the layout AI model only when advanced parsing is on.
|
||||
*/
|
||||
aiBadge?: "llm" | "layout";
|
||||
/** Hide the scanned-docs fallback note where it cannot apply (DOCX input). */
|
||||
showFallbackNote?: boolean;
|
||||
}
|
||||
|
||||
/** Compact "how this works" card at the top of every DocParse settings panel. */
|
||||
const DocparseToolIntro = ({
|
||||
description,
|
||||
aiBadge,
|
||||
showFallbackNote = true,
|
||||
}: DocparseToolIntroProps) => {
|
||||
const { t } = useTranslation();
|
||||
const { capabilities } = useDocparseCapabilities();
|
||||
const advanced = capabilities ? capabilities.advancedInstalled : null;
|
||||
|
||||
return (
|
||||
<div className={styles.card}>
|
||||
<p className={styles.description}>{description}</p>
|
||||
<div className={styles.badges}>
|
||||
{aiBadge === "llm" && (
|
||||
<Badge size="sm" variant="light" color="grape">
|
||||
{t("docparse.intro.usesAi", "Uses AI")}
|
||||
</Badge>
|
||||
)}
|
||||
{aiBadge === "layout" && advanced === true && (
|
||||
<Badge size="sm" variant="light" color="grape">
|
||||
{t("docparse.intro.aiLayoutModel", "AI layout model")}
|
||||
</Badge>
|
||||
)}
|
||||
{advanced !== null && (
|
||||
<Badge size="sm" variant="light" color={advanced ? "teal" : "gray"}>
|
||||
{advanced
|
||||
? t("docparse.intro.advancedOn", "Advanced parsing: on")
|
||||
: t("docparse.intro.advancedOff", "Advanced parsing: off")}
|
||||
</Badge>
|
||||
)}
|
||||
</div>
|
||||
{advanced === false && showFallbackNote && (
|
||||
<p className={styles.fallback}>
|
||||
{t(
|
||||
"docparse.intro.basicFallback",
|
||||
"Scanned documents fall back to basic text extraction - install the DocParse addon for layout AI",
|
||||
)}
|
||||
</p>
|
||||
)}
|
||||
</div>
|
||||
);
|
||||
};
|
||||
|
||||
export default DocparseToolIntro;
|
||||
Some files were not shown because too many files have changed in this diff Show More
Reference in New Issue
Block a user