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feat: Implement Document Intelligence as Content Extraction Engine

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This commit is contained in:
Mazurek Michal
2025-02-07 13:44:47 +01:00
parent e9d6ada25c
commit 35f3824932
8 changed files with 107 additions and 2 deletions
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backend/open_webui/routers/retrieval.py
+26 -1
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@@ -352,6 +352,10 @@ async def get_rag_config(request: Request, user=Depends(get_admin_user)):
"content_extraction": {
"engine": request.app.state.config.CONTENT_EXTRACTION_ENGINE,
"tika_server_url": request.app.state.config.TIKA_SERVER_URL,
"document_intelligence_config": {
"endpoint": request.app.state.config.DOCUMENT_INTELLIGENCE_ENDPOINT,
"key": request.app.state.config.DOCUMENT_INTELLIGENCE_KEY,
},
},
"chunk": {
"text_splitter": request.app.state.config.TEXT_SPLITTER,
@@ -402,9 +406,15 @@ class FileConfig(BaseModel):
max_count: Optional[int] = None
class DocumentIntelligenceConfigForm(BaseModel):
endpoint: str
key: str
class ContentExtractionConfig(BaseModel):
engine: str = ""
tika_server_url: Optional[str] = None
document_intelligence_config: Optional[DocumentIntelligenceConfigForm] = None
class ChunkParamUpdateForm(BaseModel):
@@ -479,13 +489,22 @@ async def update_rag_config(
request.app.state.config.FILE_MAX_COUNT = form_data.file.max_count
if form_data.content_extraction is not None:
log.info(f"Updating text settings: {form_data.content_extraction}")
log.info(
f"Updating content extraction: {request.app.state.config.CONTENT_EXTRACTION_ENGINE} to {form_data.content_extraction.engine}"
)
request.app.state.config.CONTENT_EXTRACTION_ENGINE = (
form_data.content_extraction.engine
)
request.app.state.config.TIKA_SERVER_URL = (
form_data.content_extraction.tika_server_url
)
if form_data.content_extraction.document_intelligence_config is not None:
request.app.state.config.DOCUMENT_INTELLIGENCE_ENDPOINT = (
form_data.content_extraction.document_intelligence_config.endpoint
)
request.app.state.config.DOCUMENT_INTELLIGENCE_KEY = (
form_data.content_extraction.document_intelligence_config.key
)
if form_data.chunk is not None:
request.app.state.config.TEXT_SPLITTER = form_data.chunk.text_splitter
@@ -564,6 +583,10 @@ async def update_rag_config(
"content_extraction": {
"engine": request.app.state.config.CONTENT_EXTRACTION_ENGINE,
"tika_server_url": request.app.state.config.TIKA_SERVER_URL,
"document_intelligence_config": {
"endpoint": request.app.state.config.DOCUMENT_INTELLIGENCE_ENDPOINT,
"key": request.app.state.config.DOCUMENT_INTELLIGENCE_KEY,
},
},
"chunk": {
"text_splitter": request.app.state.config.TEXT_SPLITTER,
@@ -887,6 +910,8 @@ def process_file(
engine=request.app.state.config.CONTENT_EXTRACTION_ENGINE,
TIKA_SERVER_URL=request.app.state.config.TIKA_SERVER_URL,
PDF_EXTRACT_IMAGES=request.app.state.config.PDF_EXTRACT_IMAGES,
DOCUMENT_INTELLIGENCE_ENDPOINT=request.app.state.config.DOCUMENT_INTELLIGENCE_ENDPOINT,
DOCUMENT_INTELLIGENCE_KEY=request.app.state.config.DOCUMENT_INTELLIGENCE_KEY,
)
docs = loader.load(
file.filename, file.meta.get("content_type"), file_path