File size: 11,234 Bytes
9abace2 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 | """
PDF Parser
Part of SOVEREIGN PYTHON LLM ENGINE
Parse PDF documents to extract text, metadata, images.
"""
from typing import Any
from pathlib import Path
from dataclasses import dataclass
import io
from ...core.evidence import WORMLedger
@dataclass
class PDFDocument:
"""Parsed PDF document"""
text: str
pages: int
metadata: dict[str, Any]
images: list[bytes]
tables: list[dict] | None = None
class PDFParser:
"""
PDF document parser.
Supports multiple backends:
- pypdf2 (lightweight, pure Python)
- pdfplumber (tables support)
- pymupdf (fast, best quality)
"""
def __init__(
self,
backend: str = "pypdf2",
extract_images: bool = False,
extract_tables: bool = False,
worm_ledger: WORMLedger | None = None
):
"""
Initialize PDF parser.
Args:
backend: Parser backend ("pypdf2", "pdfplumber", "pymupdf")
extract_images: Whether to extract images
extract_tables: Whether to extract tables
worm_ledger: Optional WORM ledger
"""
self.backend = backend
self.extract_images = extract_images
self.extract_tables = extract_tables
self.worm_ledger = worm_ledger
# Validate backend
if backend not in ("pypdf2", "pdfplumber", "pymupdf"):
raise ValueError(f"Unknown backend: {backend}")
async def parse(self, file_path: Path) -> PDFDocument:
"""
Parse PDF file.
Args:
file_path: Path to PDF file
Returns:
PDFDocument with extracted content
"""
if self.backend == "pypdf2":
return await self._parse_pypdf2(file_path)
elif self.backend == "pdfplumber":
return await self._parse_pdfplumber(file_path)
elif self.backend == "pymupdf":
return await self._parse_pymupdf(file_path)
async def parse_bytes(self, pdf_bytes: bytes) -> PDFDocument:
"""
Parse PDF from bytes.
Args:
pdf_bytes: PDF file bytes
Returns:
PDFDocument
"""
if self.backend == "pypdf2":
return await self._parse_pypdf2_bytes(pdf_bytes)
elif self.backend == "pdfplumber":
return await self._parse_pdfplumber_bytes(pdf_bytes)
elif self.backend == "pymupdf":
return await self._parse_pymupdf_bytes(pdf_bytes)
async def _parse_pypdf2(self, file_path: Path) -> PDFDocument:
"""Parse using pypdf2"""
try:
import pypdf
except ImportError:
raise ImportError("pypdf is required. Install: pip install pypdf")
import asyncio
def _sync_parse():
reader = pypdf.PdfReader(str(file_path))
# Extract text
text_parts = []
for page in reader.pages:
text_parts.append(page.extract_text())
text = "\n\n".join(text_parts)
# Extract metadata
metadata = {}
if reader.metadata:
metadata = {
"title": reader.metadata.get("/Title", ""),
"author": reader.metadata.get("/Author", ""),
"subject": reader.metadata.get("/Subject", ""),
"creator": reader.metadata.get("/Creator", ""),
"producer": reader.metadata.get("/Producer", ""),
}
# Extract images (if requested)
images = []
if self.extract_images:
for page in reader.pages:
if "/XObject" in page["/Resources"]:
x_object = page["/Resources"]["/XObject"].get_object()
for obj in x_object:
if x_object[obj]["/Subtype"] == "/Image":
try:
img_data = x_object[obj].get_data()
images.append(img_data)
except Exception:
pass
return PDFDocument(
text=text,
pages=len(reader.pages),
metadata=metadata,
images=images
)
# Run in thread pool
return await asyncio.to_thread(_sync_parse)
async def _parse_pypdf2_bytes(self, pdf_bytes: bytes) -> PDFDocument:
"""Parse bytes using pypdf2"""
try:
import pypdf
except ImportError:
raise ImportError("pypdf is required")
import asyncio
def _sync_parse():
reader = pypdf.PdfReader(io.BytesIO(pdf_bytes))
text_parts = []
for page in reader.pages:
text_parts.append(page.extract_text())
text = "\n\n".join(text_parts)
metadata = {}
if reader.metadata:
metadata = {
"title": reader.metadata.get("/Title", ""),
"author": reader.metadata.get("/Author", ""),
}
return PDFDocument(
text=text,
pages=len(reader.pages),
metadata=metadata,
images=[]
)
return await asyncio.to_thread(_sync_parse)
async def _parse_pdfplumber(self, file_path: Path) -> PDFDocument:
"""Parse using pdfplumber (best for tables)"""
try:
import pdfplumber
except ImportError:
raise ImportError("pdfplumber is required. Install: pip install pdfplumber")
import asyncio
def _sync_parse():
with pdfplumber.open(file_path) as pdf:
# Extract text
text_parts = []
for page in pdf.pages:
text = page.extract_text()
if text:
text_parts.append(text)
text = "\n\n".join(text_parts)
# Extract tables (if requested)
tables = []
if self.extract_tables:
for page in pdf.pages:
page_tables = page.extract_tables()
for table in page_tables:
# Convert to dict format
if table and len(table) > 0:
headers = table[0]
rows = []
for row in table[1:]:
row_dict = dict(zip(headers, row))
rows.append(row_dict)
tables.append({"headers": headers, "rows": rows})
# Metadata
metadata = pdf.metadata or {}
return PDFDocument(
text=text,
pages=len(pdf.pages),
metadata=metadata,
images=[],
tables=tables if tables else None
)
return await asyncio.to_thread(_sync_parse)
async def _parse_pdfplumber_bytes(self, pdf_bytes: bytes) -> PDFDocument:
"""Parse bytes using pdfplumber"""
try:
import pdfplumber
except ImportError:
raise ImportError("pdfplumber is required")
import asyncio
def _sync_parse():
with pdfplumber.open(io.BytesIO(pdf_bytes)) as pdf:
text_parts = []
for page in pdf.pages:
text = page.extract_text()
if text:
text_parts.append(text)
return PDFDocument(
text="\n\n".join(text_parts),
pages=len(pdf.pages),
metadata=pdf.metadata or {},
images=[]
)
return await asyncio.to_thread(_sync_parse)
async def _parse_pymupdf(self, file_path: Path) -> PDFDocument:
"""Parse using pymupdf (fastest, best quality)"""
try:
import fitz # PyMuPDF
except ImportError:
raise ImportError("PyMuPDF is required. Install: pip install pymupdf")
import asyncio
def _sync_parse():
doc = fitz.open(file_path)
# Extract text
text_parts = []
for page in doc:
text_parts.append(page.get_text())
text = "\n\n".join(text_parts)
# Extract images
images = []
if self.extract_images:
for page in doc:
image_list = page.get_images()
for img in image_list:
xref = img[0]
try:
base_image = doc.extract_image(xref)
images.append(base_image["image"])
except Exception:
pass
# Metadata
metadata = doc.metadata
doc.close()
return PDFDocument(
text=text,
pages=len(doc),
metadata=metadata,
images=images
)
return await asyncio.to_thread(_sync_parse)
async def _parse_pymupdf_bytes(self, pdf_bytes: bytes) -> PDFDocument:
"""Parse bytes using pymupdf"""
try:
import fitz
except ImportError:
raise ImportError("PyMuPDF is required")
import asyncio
def _sync_parse():
doc = fitz.open(stream=pdf_bytes, filetype="pdf")
text_parts = []
for page in doc:
text_parts.append(page.get_text())
metadata = doc.metadata
doc.close()
return PDFDocument(
text="\n\n".join(text_parts),
pages=len(doc),
metadata=metadata,
images=[]
)
return await asyncio.to_thread(_sync_parse)
# Tool registration helper
async def parse_pdf_tool(
file_path: str,
extract_images: bool = False,
extract_tables: bool = False
) -> dict:
"""
Tool wrapper for PDF parsing.
Args:
file_path: Path to PDF file
extract_images: Extract images
extract_tables: Extract tables
Returns:
Dictionary with parsed content
"""
parser = PDFParser(
backend="pypdf2",
extract_images=extract_images,
extract_tables=extract_tables
)
result = await parser.parse(Path(file_path))
return {
"text": result.text,
"pages": result.pages,
"metadata": result.metadata,
"images_count": len(result.images),
"tables": result.tables
}
|