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Merge pull request #3582 from nickovs/tika-document-text

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feat: Support Tika for document text extraction
This commit is contained in:
Timothy Jaeryang Baek
2024-07-01 17:07:40 -07:00
committed by GitHub
parent 62ba6a2413 7aa35a3757
commit 3c1ea24374
5 changed files with 181 additions and 41 deletions
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147
backend/apps/rag/main.py
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@@ -91,6 +91,8 @@ from config import (
SRC_LOG_LEVELS,
UPLOAD_DIR,
DOCS_DIR,
TEXT_EXTRACTION_ENGINE,
TIKA_SERVER_URL,
RAG_TOP_K,
RAG_RELEVANCE_THRESHOLD,
RAG_EMBEDDING_ENGINE,
@@ -146,6 +148,9 @@ app.state.config.ENABLE_RAG_WEB_LOADER_SSL_VERIFICATION = (
ENABLE_RAG_WEB_LOADER_SSL_VERIFICATION
)
app.state.config.TEXT_EXTRACTION_ENGINE = TEXT_EXTRACTION_ENGINE
app.state.config.TIKA_SERVER_URL = TIKA_SERVER_URL
app.state.config.CHUNK_SIZE = CHUNK_SIZE
app.state.config.CHUNK_OVERLAP = CHUNK_OVERLAP
@@ -390,6 +395,10 @@ async def get_rag_config(user=Depends(get_admin_user)):
return {
"status": True,
"pdf_extract_images": app.state.config.PDF_EXTRACT_IMAGES,
"text_extraction": {
"engine": app.state.config.TEXT_EXTRACTION_ENGINE,
"tika_server_url": app.state.config.TIKA_SERVER_URL,
},
"chunk": {
"chunk_size": app.state.config.CHUNK_SIZE,
"chunk_overlap": app.state.config.CHUNK_OVERLAP,
@@ -419,6 +428,11 @@ async def get_rag_config(user=Depends(get_admin_user)):
}
class TextExtractionConfig(BaseModel):
engine: str = ""
tika_server_url: Optional[str] = None
class ChunkParamUpdateForm(BaseModel):
chunk_size: int
chunk_overlap: int
@@ -452,6 +466,7 @@ class WebConfig(BaseModel):
class ConfigUpdateForm(BaseModel):
pdf_extract_images: Optional[bool] = None
text_extraction: Optional[TextExtractionConfig] = None
chunk: Optional[ChunkParamUpdateForm] = None
youtube: Optional[YoutubeLoaderConfig] = None
web: Optional[WebConfig] = None
@@ -465,6 +480,11 @@ async def update_rag_config(form_data: ConfigUpdateForm, user=Depends(get_admin_
else app.state.config.PDF_EXTRACT_IMAGES
)
if form_data.text_extraction is not None:
log.info(f"Updating text settings: {form_data.text_extraction}")
app.state.config.TEXT_EXTRACTION_ENGINE = form_data.text_extraction.engine
app.state.config.TIKA_SERVER_URL = form_data.text_extraction.tika_server_url
if form_data.chunk is not None:
app.state.config.CHUNK_SIZE = form_data.chunk.chunk_size
app.state.config.CHUNK_OVERLAP = form_data.chunk.chunk_overlap
@@ -501,6 +521,10 @@ async def update_rag_config(form_data: ConfigUpdateForm, user=Depends(get_admin_
return {
"status": True,
"pdf_extract_images": app.state.config.PDF_EXTRACT_IMAGES,
"text_extraction": {
"engine": app.state.config.TEXT_EXTRACTION_ENGINE,
"tika_server_url": app.state.config.TIKA_SERVER_URL,
},
"chunk": {
"chunk_size": app.state.config.CHUNK_SIZE,
"chunk_overlap": app.state.config.CHUNK_OVERLAP,
@@ -987,6 +1011,41 @@ def store_docs_in_vector_db(docs, collection_name, overwrite: bool = False) -> b
return False
class TikaLoader:
def __init__(self, file_path, mime_type=None):
self.file_path = file_path
self.mime_type = mime_type
def load(self) -> List[Document]:
with (open(self.file_path, "rb") as f):
data = f.read()
if self.mime_type is not None:
headers = {"Content-Type": self.mime_type}
else:
headers = {}
endpoint = app.state.config.TIKA_SERVER_URL
if not endpoint.endswith("/"):
endpoint += "/"
endpoint += "tika/text"
r = requests.put(endpoint, data=data, headers=headers)
if r.ok:
raw_metadata = r.json()
text = raw_metadata.get("X-TIKA:content", "<No text content found>")
if "Content-Type" in raw_metadata:
headers["Content-Type"] = raw_metadata["Content-Type"]
log.info("Tika extracted text: %s", text)
return [Document(page_content=text, metadata=headers)]
else:
raise Exception(f"Error calling Tika: {r.reason}")
def get_loader(filename: str, file_content_type: str, file_path: str):
file_ext = filename.split(".")[-1].lower()
known_type = True
@@ -1037,47 +1096,55 @@ def get_loader(filename: str, file_content_type: str, file_path: str):
"msg",
]
if file_ext == "pdf":
loader = PyPDFLoader(
file_path, extract_images=app.state.config.PDF_EXTRACT_IMAGES
)
elif file_ext == "csv":
loader = CSVLoader(file_path)
elif file_ext == "rst":
loader = UnstructuredRSTLoader(file_path, mode="elements")
elif file_ext == "xml":
loader = UnstructuredXMLLoader(file_path)
elif file_ext in ["htm", "html"]:
loader = BSHTMLLoader(file_path, open_encoding="unicode_escape")
elif file_ext == "md":
loader = UnstructuredMarkdownLoader(file_path)
elif file_content_type == "application/epub+zip":
loader = UnstructuredEPubLoader(file_path)
elif (
file_content_type
== "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
or file_ext in ["doc", "docx"]
):
loader = Docx2txtLoader(file_path)
elif file_content_type in [
"application/vnd.ms-excel",
"application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
] or file_ext in ["xls", "xlsx"]:
loader = UnstructuredExcelLoader(file_path)
elif file_content_type in [
"application/vnd.ms-powerpoint",
"application/vnd.openxmlformats-officedocument.presentationml.presentation",
] or file_ext in ["ppt", "pptx"]:
loader = UnstructuredPowerPointLoader(file_path)
elif file_ext == "msg":
loader = OutlookMessageLoader(file_path)
elif file_ext in known_source_ext or (
file_content_type and file_content_type.find("text/") >= 0
):
loader = TextLoader(file_path, autodetect_encoding=True)
if app.state.config.TEXT_EXTRACTION_ENGINE == "tika" and app.state.config.TIKA_SERVER_URL:
if file_ext in known_source_ext or (
file_content_type and file_content_type.find("text/") >= 0
):
loader = TextLoader(file_path, autodetect_encoding=True)
else:
loader = TikaLoader(file_path, file_content_type)
else:
loader = TextLoader(file_path, autodetect_encoding=True)
known_type = False
if file_ext == "pdf":
loader = PyPDFLoader(
file_path, extract_images=app.state.config.PDF_EXTRACT_IMAGES
)
elif file_ext == "csv":
loader = CSVLoader(file_path)
elif file_ext == "rst":
loader = UnstructuredRSTLoader(file_path, mode="elements")
elif file_ext == "xml":
loader = UnstructuredXMLLoader(file_path)
elif file_ext in ["htm", "html"]:
loader = BSHTMLLoader(file_path, open_encoding="unicode_escape")
elif file_ext == "md":
loader = UnstructuredMarkdownLoader(file_path)
elif file_content_type == "application/epub+zip":
loader = UnstructuredEPubLoader(file_path)
elif (
file_content_type
== "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
or file_ext in ["doc", "docx"]
):
loader = Docx2txtLoader(file_path)
elif file_content_type in [
"application/vnd.ms-excel",
"application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
] or file_ext in ["xls", "xlsx"]:
loader = UnstructuredExcelLoader(file_path)
elif file_content_type in [
"application/vnd.ms-powerpoint",
"application/vnd.openxmlformats-officedocument.presentationml.presentation",
] or file_ext in ["ppt", "pptx"]:
loader = UnstructuredPowerPointLoader(file_path)
elif file_ext == "msg":
loader = OutlookMessageLoader(file_path)
elif file_ext in known_source_ext or (
file_content_type and file_content_type.find("text/") >= 0
):
loader = TextLoader(file_path, autodetect_encoding=True)
else:
loader = TextLoader(file_path, autodetect_encoding=True)
known_type = False
return loader, known_type

16
backend/config.py
View File

@@ -885,6 +885,22 @@ WEBUI_SESSION_COOKIE_SECURE = os.environ.get(
if WEBUI_AUTH and WEBUI_SECRET_KEY == "":
raise ValueError(ERROR_MESSAGES.ENV_VAR_NOT_FOUND)
####################################
# RAG document text extraction
####################################
TEXT_EXTRACTION_ENGINE = PersistentConfig(
"TEXT_EXTRACTION_ENGINE",
"rag.text_extraction_engine",
os.environ.get("TEXT_EXTRACTION_ENGINE", "").lower()
)
TIKA_SERVER_URL = PersistentConfig(
"TIKA_SERVER_URL",
"rag.tika_server_url",
os.getenv("TIKA_SERVER_URL", "http://tika:9998"), # Default for sidecar deployment
)
####################################
# RAG
####################################