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409 | class DocugamiReader(BaseReader):
"""Docugami reader.
Reads Documents as nodes in a Document XML Knowledge Graph, from Docugami.
"""
api: str = DEFAULT_API_ENDPOINT
"""The Docugami API endpoint to use."""
access_token: Optional[str] = os.environ.get("DOCUGAMI_API_KEY")
"""The Docugami API access token to use."""
max_text_length = 4096
"""Max length of chunk text returned."""
min_text_length: int = 32
"""Threshold under which chunks are appended to next to avoid over-chunking."""
max_metadata_length = 512
"""Max length of metadata text returned."""
include_xml_tags: bool = False
"""Set to true for XML tags in chunk output text."""
parent_hierarchy_levels: int = 0
"""Set appropriately to get parent chunks using the chunk hierarchy."""
parent_id_key: str = "doc_id"
"""Metadata key for parent doc ID."""
sub_chunk_tables: bool = False
"""Set to True to return sub-chunks within tables."""
whitespace_normalize_text: bool = True
"""Set to False if you want to full whitespace formatting in the original
XML doc, including indentation."""
docset_id: Optional[str]
"""The Docugami API docset ID to use."""
document_ids: Optional[Sequence[str]]
"""The Docugami API document IDs to use."""
file_paths: Optional[Sequence[Union[Path, str]]]
"""The local file paths to use."""
include_project_metadata_in_doc_metadata: bool = True
"""Set to True if you want to include the project metadata in the doc metadata."""
def __init__(
self,
api: str = DEFAULT_API_ENDPOINT,
access_token: Optional[str] = os.environ.get("DOCUGAMI_API_KEY"),
max_text_length=4096,
min_text_length: int = 32,
max_metadata_length=512,
include_xml_tags: bool = False,
parent_hierarchy_levels: int = 0,
parent_id_key: str = "doc_id",
sub_chunk_tables: bool = False,
whitespace_normalize_text: bool = True,
docset_id: Optional[str] = None,
document_ids: Optional[Sequence[str]] = None,
file_paths: Optional[Sequence[Union[Path, str]]] = None,
include_project_metadata_in_doc_metadata: bool = True,
):
self.api = api
self.access_token = access_token
self.max_text_length = max_text_length
self.min_text_length = min_text_length
self.max_metadata_length = max_metadata_length
self.include_xml_tags = include_xml_tags
self.parent_hierarchy_levels = parent_hierarchy_levels
self.parent_id_key = parent_id_key
self.sub_chunk_tables = sub_chunk_tables
self.whitespace_normalize_text = whitespace_normalize_text
self.docset_id = docset_id
self.document_ids = document_ids
self.file_paths = file_paths
self.include_project_metadata_in_doc_metadata = (
include_project_metadata_in_doc_metadata
)
def _parse_dgml(
self,
content: bytes,
document_name: Optional[str] = None,
additional_doc_metadata: Optional[Mapping] = None,
) -> List[Document]:
"""Parse a single DGML document into a list of Documents."""
try:
from lxml import etree
except ImportError:
raise ImportError(
"Could not import lxml python package. "
"Please install it with `pip install lxml`."
)
# helpers
def _xpath_qname_for_chunk(chunk: Any) -> str:
"""Get the xpath qname for a chunk."""
qname = f"{chunk.prefix}:{chunk.tag.split('}')[-1]}"
parent = chunk.getparent()
if parent is not None:
doppelgangers = [x for x in parent if x.tag == chunk.tag]
if len(doppelgangers) > 1:
idx_of_self = doppelgangers.index(chunk)
qname = f"{qname}[{idx_of_self + 1}]"
return qname
def _xpath_for_chunk(chunk: Any) -> str:
"""Get the xpath for a chunk."""
ancestor_chain = chunk.xpath("ancestor-or-self::*")
return "/" + "/".join(_xpath_qname_for_chunk(x) for x in ancestor_chain)
def _structure_value(node: Any) -> Optional[str]:
"""Get the structure value for a node."""
return (
"table"
if node.tag == TABLE_NAME
else node.attrib["structure"]
if "structure" in node.attrib
else None
)
def _build_framework_chunk(dg_chunk: Chunk) -> Document:
# Stable IDs for chunks with the same text.
_hashed_id = hashlib.md5(dg_chunk.text.encode()).hexdigest()
metadata = {
XPATH_KEY: dg_chunk.xpath,
ID_KEY: _hashed_id,
DOCUMENT_NAME_KEY: document_name,
STRUCTURE_KEY: dg_chunk.structure,
TAG_KEY: dg_chunk.tag,
}
text = dg_chunk.text
if additional_doc_metadata:
if self.include_project_metadata_in_doc_metadata:
metadata.update(additional_doc_metadata)
return Document(
text=text[: self.max_text_length],
metadata=metadata,
excluded_llm_metadata_keys=[XPATH_KEY, ID_KEY, STRUCTURE_KEY],
)
# Parse the tree and return chunks
tree = etree.parse(io.BytesIO(content))
root = tree.getroot()
dg_chunks = get_chunks(
root,
min_text_length=self.min_text_length,
max_text_length=self.max_text_length,
whitespace_normalize_text=self.whitespace_normalize_text,
sub_chunk_tables=self.sub_chunk_tables,
include_xml_tags=self.include_xml_tags,
parent_hierarchy_levels=self.parent_hierarchy_levels,
)
framework_chunks: Dict[str, Document] = {}
for dg_chunk in dg_chunks:
framework_chunk = _build_framework_chunk(dg_chunk)
chunk_id = framework_chunk.metadata.get(ID_KEY)
if chunk_id:
framework_chunks[chunk_id] = framework_chunk
if dg_chunk.parent:
framework_parent_chunk = _build_framework_chunk(dg_chunk.parent)
parent_id = framework_parent_chunk.metadata.get(ID_KEY)
if parent_id and framework_parent_chunk.text:
framework_chunk.metadata[self.parent_id_key] = parent_id
framework_chunks[parent_id] = framework_parent_chunk
return list(framework_chunks.values())
def _document_details_for_docset_id(self, docset_id: str) -> List[Dict]:
"""Gets all document details for the given docset ID."""
url = f"{self.api}/docsets/{docset_id}/documents"
all_documents = []
while url:
response = requests.get(
url,
headers={"Authorization": f"Bearer {self.access_token}"},
)
if response.ok:
data = response.json()
all_documents.extend(data["documents"])
url = data.get("next", None)
else:
raise Exception(
f"Failed to download {url} (status: {response.status_code})"
)
return all_documents
def _project_details_for_docset_id(self, docset_id: str) -> List[Dict]:
"""Gets all project details for the given docset ID."""
url = f"{self.api}/projects?docset.id={docset_id}"
all_projects = []
while url:
response = requests.request(
"GET",
url,
headers={"Authorization": f"Bearer {self.access_token}"},
data={},
)
if response.ok:
data = response.json()
all_projects.extend(data["projects"])
url = data.get("next", None)
else:
raise Exception(
f"Failed to download {url} (status: {response.status_code})"
)
return all_projects
def _metadata_for_project(self, project: Dict) -> Dict:
"""Gets project metadata for all files."""
project_id = project.get(ID_KEY)
url = f"{self.api}/projects/{project_id}/artifacts/latest"
all_artifacts = []
per_file_metadata: Dict = {}
while url:
response = requests.request(
"GET",
url,
headers={"Authorization": f"Bearer {self.access_token}"},
data={},
)
if response.ok:
data = response.json()
all_artifacts.extend(data["artifacts"])
url = data.get("next", None)
elif response.status_code == 404:
# Not found is ok, just means no published projects
return per_file_metadata
else:
raise Exception(
f"Failed to download {url} (status: {response.status_code})"
)
for artifact in all_artifacts:
artifact_name = artifact.get("name")
artifact_url = artifact.get("url")
artifact_doc = artifact.get("document")
if artifact_name == "report-values.xml" and artifact_url and artifact_doc:
doc_id = artifact_doc[ID_KEY]
metadata: Dict = {}
# The evaluated XML for each document is named after the project
response = requests.request(
"GET",
f"{artifact_url}/content",
headers={"Authorization": f"Bearer {self.access_token}"},
data={},
)
if response.ok:
try:
from lxml import etree
except ImportError:
raise ImportError(
"Could not import lxml python package. "
"Please install it with `pip install lxml`."
)
artifact_tree = etree.parse(io.BytesIO(response.content))
artifact_root = artifact_tree.getroot()
ns = artifact_root.nsmap
entries = artifact_root.xpath("//pr:Entry", namespaces=ns)
for entry in entries:
heading = entry.xpath("./pr:Heading", namespaces=ns)[0].text
value = " ".join(
entry.xpath("./pr:Value", namespaces=ns)[0].itertext()
).strip()
metadata[heading] = value[: self.max_metadata_length]
per_file_metadata[doc_id] = metadata
else:
raise Exception(
f"Failed to download {artifact_url}/content "
+ "(status: {response.status_code})"
)
return per_file_metadata
def _load_chunks_for_document(
self,
document_id: str,
docset_id: str,
document_name: Optional[str] = None,
additional_metadata: Optional[Mapping] = None,
) -> List[Document]:
"""Load chunks for a document."""
url = f"{self.api}/docsets/{docset_id}/documents/{document_id}/dgml"
response = requests.request(
"GET",
url,
headers={"Authorization": f"Bearer {self.access_token}"},
data={},
)
if response.ok:
return self._parse_dgml(
content=response.content,
document_name=document_name,
additional_doc_metadata=additional_metadata,
)
else:
raise Exception(
f"Failed to download {url} (status: {response.status_code})"
)
def load_data(
self,
docset_id: str,
document_ids: Optional[List[str]] = None,
access_token: Optional[str] = None,
) -> List[Document]:
"""Load data the given docset_id in Docugami.
Args:
docset_id (str): Document set ID to load data for.
document_ids (Optional[List[str]]): Optional list of document ids to load data for.
If not specified, all documents from docset_id are loaded.
"""
chunks: List[Document] = []
if access_token:
self.access_token = access_token
if not self.access_token:
raise Exception(
"Please specify access token as argument or set the DOCUGAMI_API_KEY"
" env var."
)
_document_details = self._document_details_for_docset_id(docset_id)
if document_ids:
_document_details = [
d for d in _document_details if d[ID_KEY] in document_ids
]
_project_details = self._project_details_for_docset_id(docset_id)
combined_project_metadata: Dict[str, Dict] = {}
if _project_details and self.include_project_metadata_in_doc_metadata:
# If there are any projects for this docset and the caller requested
# project metadata, load it.
for project in _project_details:
metadata = self._metadata_for_project(project)
for file_id in metadata:
if file_id not in combined_project_metadata:
combined_project_metadata[file_id] = metadata[file_id]
else:
combined_project_metadata[file_id].update(metadata[file_id])
for doc in _document_details:
doc_id = doc[ID_KEY]
doc_name = doc.get(DOCUMENT_NAME_KEY)
doc_metadata = combined_project_metadata.get(doc_id)
chunks += self._load_chunks_for_document(
document_id=doc_id,
docset_id=docset_id,
document_name=doc_name,
additional_metadata=doc_metadata,
)
return chunks
|
