feat(KnowledgeBase):Add Word97-2003 (.doc) Binary File parsing module (#2544)

This commit is contained in:
geebytes
2025-03-29 11:05:06 +08:00
committed by GitHub
parent 7c05bc1784
commit c86243aa62
16 changed files with 2724 additions and 524 deletions

View File

@@ -7,9 +7,12 @@
"USERNAME": "${localEnv:USER}"
},
"options": [
"--no-cache"
"--no-cache",
"--network=host"
]
},
"updateRemoteUserUID": false,
"remoteUser": "${localEnv:USER}",
"initializeCommand": ".devcontainer/init_env.sh",
"name": "dbgpt",
"workspaceFolder": "/app",

View File

@@ -1,8 +1,9 @@
FROM eosphorosai/dbgpt:latest
FROM eosphorosai/dbgpt-full:latest
ARG PYTHON_VERSION=3.11
ARG PIP_INDEX_URL="https://mirrors.aliyun.com/pypi/simple"
ARG PIP_INDEX_URL="https://pypi.tuna.tsinghua.edu.cn/simple"
ARG USERNAME
ARG DEFAULT_VEN=/opt/.uv.venv
ARG EXTRAS="base,proxy_openai,rag,storage_chromadb, storage_elasticsearch,cuda121,hf,quant_bnb,dbgpts"
ARG DEFAULT_VENV=/opt/.uv.venv
WORKDIR /app
COPY . .
USER root
@@ -11,30 +12,38 @@ USER root
# between the container user (root) and the host user,
# and to resolve the issue of the host user lacking write permissions.
RUN . .devcontainer/.env && \
groupadd -g $USER_GID $USERNAME && \
groupadd -g $USER_GID $GROUPNAME && \
useradd -u $USER_UID -g $USER_GID -m $USERNAME && \
chown -R $USER_UID:$USER_GID /app
RUN apt-get update && apt-get install -y \
git \
curl \
wget \
python${PYTHON_VERSION}-dev \
default-libmysqlclient-dev \
ssh zsh autojump curl git-flow vim sudo \
&& python${PYTHON_VERSION} -m pip install --upgrade pip \
&& python${PYTHON_VERSION} -m pip install --upgrade pipx \
&& pipx install -i $PIP_INDEX_URL uv --global \
&& chown -R $USERNAME:$USERNAME $DEFAULT_VEN \
&& chown -R $USERNAME:$GROUPNAME $DEFAULT_VENV \
&& echo "$USERNAME ALL=(ALL) NOPASSWD:ALL" > /etc/sudoers.d/$USERNAME \
&& chmod 0440 /etc/sudoers.d/$USERNAME
USER $USERNAME
ENV UV_LINK_MODE=copy \
PIP_INDEX_URL=$PIP_INDEX_URL \
VIRTUAL_ENV=$DEFAULT_VEN \
UV_PROJECT_ENVIRONMENT=$DEFAULT_VEN \
UV_PYTHON=$DEFAULT_VEN/bin/python3
VIRTUAL_ENV=$DEFAULT_VENV \
UV_PROJECT_ENVIRONMENT=$DEFAULT_VENV \
UV_PYTHON=$DEFAULT_VENV/bin/python3 \
UV_INDEX=$PIP_INDEX_URL \
UV_DEFAULT_INDEX=$PIP_INDEX_URL
RUN . $DEFAULT_VEN/bin/activate && \
uv pip install --prefix $VIRTUAL_ENV -r pyproject.toml --all-extras --index-url=$PIP_INDEX_URL && \
uv pip install --prefix $VIRTUAL_ENV -r requirements/dev-requirements.txt --index-url=$PIP_INDEX_URL && \
uv pip install --prefix $VIRTUAL_ENV -r requirements/lint-requirements.txt --index-url=$PIP_INDEX_URL && \
RUN sed -i "s|/app/\.venv|${FINAL_VENV_NAME}|g" /${DEFAULT_VENV}/bin/activate && \
pip config set global.index-url $PIP_INDEX_URL && \
pip config set global.trusted-host $(echo "$PIP_INDEX_URL" | sed -E 's|^https?://([^/]+).*|\1|') && \
. $DEFAULT_VENV/bin/activate && \
extras=$(echo $EXTRAS | tr ',' '\n' | while read extra; do echo "--extra $extra"; done | tr '\n' ' ') && \
uv sync -v --active --all-packages $extras --default-index $PIP_INDEX_URL && \
uv pip -v install --prefix $VIRTUAL_ENV -r requirements/dev-requirements.txt && \
uv pip -v install --prefix $VIRTUAL_ENV -r requirements/lint-requirements.txt && \
cp .devcontainer/dbgpt.pth /opt/.uv.venv/lib/python${PYTHON_VERSION}/site-packages/dbgpt.pth && \
python -c "import dbgpt; print(dbgpt.__version__)"

36
.devcontainer/README.md Normal file
View File

@@ -0,0 +1,36 @@
# Developing inside a Container
Use VS Code's Dev Container extension to build a containerized development environment. Leverage the eosphorosai/dbgpt:latest image as the development environment to avoid repeated dependency installations and improve development efficiency.
NOTE: **Compatible with Linux and Windows Subsystem for Linux (WSL) environments only.**
# Setup
- Follow the guide [Developing inside a Container](https://code.visualstudio.com/docs/devcontainers/containers) to set up the Dev Container:
- Install the **Dev Containers** extension.
- Before the first launch, please execute the .devcontainer/init_env.sh script in the project root directory in **host**
- Create `models` dir in project root and download text2vec-large-chinese to models/text2vec-large-chinese
- Use the shortcut `Ctrl+Shift+P` to open the command palette, then enter `Dev Containers: Open Folder in Container`.
# Develop
After successfully starting the Dev Container, open the terminal
- Activate the virtual environment
```bash
. /opt/.uv.venv/bin/activate
```
- Customize the configuration file
You can copy the configuration file to the `.devcontainer` directory and rename it to `dev.toml` to avoid committing your personal configurations to the repository.
```bash
cp configs/dbgpt-app-config.example.toml .devcontainer/dev.toml
```
- Start the service
```bash
dbgpt start webserver --config .devcontainer/dev.toml
```
# Create A Pull Request
Please refer to [CONTRIBUTING.md](../CONTRIBUTING.md). Before executing the make script or git commit, remember to deactivate the current virtual environment in the development environment.

View File

@@ -20,10 +20,19 @@ printf "OS=%s\nUSERNAME=%s\nUSER_UID=%s\nGROUPNAME=%s\nUSER_GID=%s\n" \
# sharing-git-credentials see https://code.visualstudio.com/remote/advancedcontainers/sharing-git-credentials
init_ssh_agent(){
if [[ -z "$SSH_AUTH_SOCK" || ! -S "$SSH_AUTH_SOCK" ]]; then
RUNNING_AGENT="$(ps -ax | grep '''ssh-agent -s''' | grep -v grep | wc -l)"
if [ "$RUNNING_AGENT" = "0" ]; then
ssh-agent -s &> $HOME/.ssh/ssh-agent
fi
eval $(cat $HOME/.ssh/ssh-agent) > /dev/null
ssh-add 2> /dev/null
echo $SSH_AUTH_SOCK
fi
# Define code block to insert (with unique identifier comment)
SSH_AGENT_CODE='# SSH Agent Auto Management[ID:ssh_agent_v1]
if [ -z "$SSH_AUTH_SOCK" ]; then
RUNNING_AGENT="$(ps -ax | grep '\''ssh-agent -s'\'' | grep -v grep | wc -l | tr -d '\''[:space:]'\'')"
if [[ -z "$SSH_AUTH_SOCK" || ! -S "$SSH_AUTH_SOCK" ]]; then
RUNNING_AGENT="$(ps -ax | grep '\''ssh-agent -s'\'' | grep -v grep | wc -l)"
if [ "$RUNNING_AGENT" = "0" ]; then
ssh-agent -s &> $HOME/.ssh/ssh-agent
fi
@@ -32,11 +41,7 @@ if [ -z "$SSH_AUTH_SOCK" ]; then
fi
# END_SSH_AGENT_CODE'
# Auto detect shell type
TARGET_FILE="$HOME/.bashrc"
if [[ "$SHELL" == *"zsh"* ]]; then
TARGET_FILE="$HOME/.zshrc"
fi
# Create .ssh directory if not exists
mkdir -p "$HOME/.ssh"
@@ -45,6 +50,9 @@ mkdir -p "$HOME/.ssh"
if ! grep -q 'END_SSH_AGENT_CODE' "$TARGET_FILE"; then
echo "Adding SSH agent management code to ${TARGET_FILE}..."
echo "$SSH_AGENT_CODE" >> "$TARGET_FILE"
if [[ "$SHELL" == *"zsh"* ]]; then
echo "$SSH_AGENT_CODE" >> "$HOME/.zshrc"
fi
echo "Code added successfully. Please run source ${TARGET_FILE} to apply changes immediately"
else
echo "Existing SSH agent code detected, no need to add again"

View File

@@ -35,8 +35,8 @@ fi
# Configuration section remains the same...
# Apply custom configuration
if [ -f /workspace/.devcontainer/zshrc-config ]; then
cp /workspace/.devcontainer/zshrc-config ~/.zshrc
if [ -f /app/.devcontainer/zshrc-config ]; then
cp /app/.devcontainer/zshrc-config ~/.zshrc
else
# Generate basic .zshrc if no custom configuration exists
cat << EOF >> ~/.zshrc

2
.gitignore vendored
View File

@@ -187,3 +187,5 @@ thirdparty
/i18n/locales/**/**/*_ai_translated.po
/i18n/locales/**/**/*~
configs/my
.devcontainer/dev.toml
test_docs

View File

@@ -118,3 +118,6 @@ Write necessary information about your changes and click "Create pull request".
That's it you made it 🐣⭐⭐
# Developing inside a Container
If you are using VS Code as your IDE for development, you can refer to the [configuration here](.devcontainer/README.md) to set up the Dev Containers development environment.

View File

@@ -118,6 +118,8 @@ COPY . .
# Fix the shebang of the dbgpt script
RUN sed -i "s|^#\!/app/\.venv/bin/python[0-9.]*|#!/${FINAL_VENV_NAME}/bin/python${PYTHON_VERSION}|" /${FINAL_VENV_NAME}/bin/dbgpt
RUN sed -i "s|^#\!/app/\.venv/bin/python[0-9.]*|#!/${FINAL_VENV_NAME}/bin/python${PYTHON_VERSION}|" /${FINAL_VENV_NAME}/bin/pip
RUN sed -i "s|/app/\.venv|${FINAL_VENV_NAME}|g" /${FINAL_VENV_NAME}/bin/activate
ENV PATH="${FINAL_VENV_NAME}/bin:$PATH" \
VIRTUAL_ENV="${FINAL_VENV_NAME}"
# Default command

View File

@@ -27,6 +27,7 @@ class DocumentType(Enum):
HTML = "html"
DATASOURCE = "datasource"
EXCEL = "xlsx"
DOC = "doc"
class KnowledgeType(Enum):

View File

@@ -31,6 +31,7 @@ rag = [
"bs4",
"python-pptx",
"python-docx",
"olefile",
"pypdf",
"pdfplumber",
]

View File

@@ -19,6 +19,7 @@ def __getattr__(name: str):
"CSVKnowledge": "csv",
"DatasourceKnowledge": "datasource",
"DocxKnowledge": "docx",
"Word97DocKnowledge": "doc",
"HTMLKnowledge": "html",
"MarkdownKnowledge": "markdown",
"PDFKnowledge": "pdf",
@@ -43,6 +44,7 @@ __all__ = [
"CSVKnowledge",
"DatasourceKnowledge",
"DocxKnowledge",
"Word97DocKnowledge",
"HTMLKnowledge",
"MarkdownKnowledge",
"PDFKnowledge",

View File

@@ -0,0 +1,627 @@
import struct
from typing import Any, Dict, List, Optional, Union
import olefile
from dbgpt.core import Document
from dbgpt.rag.knowledge.base import (
ChunkStrategy,
DocumentType,
Knowledge,
KnowledgeType,
)
class Word97DocParser:
"""Parser for Microsoft Word 97-2003 (.doc) binary files.
This module implements a parser for the legacy Word 97-2003 binary format (.doc),
based on the official Microsoft [MS-DOC] specification.
Specification Reference:
[MS-DOC]: Word (.doc) Binary File Format
https://learn.microsoft.com/en-us/openspecs/office_file_formats/ms-doc/ccd7b486-7881-484c-a137-51170af7cc22
Example:
>>> from doc import Word97DocParser
>>> with Word97DocParser("example.doc") as parser:
... paragraphs = parser.extract_text_by_paragraphs()
... for i, para in enumerate(paragraphs, 1):
... print(f"\nParagraph {i}:")
... print(para)
"""
# Mapping of special ANSI characters to Unicode
ANSI_TO_UNICODE = {
0x82: 0x201A,
0x83: 0x0192,
0x84: 0x201E,
0x85: 0x2026,
0x86: 0x2020,
0x87: 0x2021,
0x88: 0x02C6,
0x89: 0x2030,
0x8A: 0x0160,
0x8B: 0x2039,
0x8C: 0x0152,
0x91: 0x2018,
0x92: 0x2019,
0x93: 0x201C,
0x94: 0x201D,
0x95: 0x2022,
0x96: 0x2013,
0x97: 0x2014,
0x98: 0x02DC,
0x99: 0x2122,
0x9A: 0x0161,
0x9B: 0x203A,
0x9C: 0x0153,
0x9F: 0x0178,
}
# Mapping of nFib values to cbRgFcLcb sizes
FIB_VERSIONS = {
0x00C1: 0x005D, # Word 97
0x00D9: 0x006C, # Word 2000
0x0101: 0x0088, # Word 2002
0x010C: 0x00A4, # Word 2003
0x0112: 0x00B7, # Word 2007
}
def __init__(self, doc_path):
"""Initialize with path to Word document"""
self.doc_path = doc_path
self.ole = None
self.word_doc_stream = None
self.table_stream = None
self.fib_info = None
self.plc_pcd = None
def __enter__(self):
"""Context manager entry"""
self.open()
return self
def __exit__(self, exc_type, exc_val, exc_tb):
"""Context manager exit"""
self.close()
def open(self):
"""Open the OLE file and required streams"""
self.ole = olefile.OleFileIO(self.doc_path)
if not self.ole.exists("WordDocument"):
raise ValueError("WordDocument stream not found")
self.word_doc_stream = self.ole.openstream("WordDocument")
# Determine table stream name
table_stream_name = "0Table" if self.ole.exists("0Table") else "1Table"
self.table_stream = self.ole.openstream(table_stream_name)
def close(self):
"""Close all open resources"""
if self.ole:
self.ole.close()
self.ole = None
self.word_doc_stream = None
self.table_stream = None
def read_fib(self):
"""Read the File Information Block (FIB) from the WordDocument stream (2.5)"""
# Read FibBase (32 bytes)
fib_base = self.word_doc_stream.read(32)
# Unpack nFib (offset 2, size 2 bytes)
nFib = struct.unpack("<H", fib_base[2:4])[0]
if nFib not in self.FIB_VERSIONS:
raise ValueError(f"Unsupported nFib version: 0x{nFib:04X}")
# Skip csw (2 bytes at offset 32)
self.word_doc_stream.read(2)
# Skip FibRgW97 (28 bytes) and cslw (2 bytes)
self.word_doc_stream.read(28 + 2)
# Read FibRgLw97 (88 bytes)
fib_rg_lw = self.word_doc_stream.read(88)
ccpText = struct.unpack("<I", fib_rg_lw[12:16])[0] # Total character count
# Read cbRgFcLcb (2 bytes)
cb_rg_fc_lcb = struct.unpack("<H", self.word_doc_stream.read(2))[0]
# Read FibRgFcLcbBlob (variable size)
fib_rg_fc_lcb_blob = self.word_doc_stream.read(cb_rg_fc_lcb * 8)
# Skip cswNew (2 bytes) and FibRgCswNew (variable size)
csw_new = struct.unpack("<H", self.word_doc_stream.read(2))[0]
if csw_new > 0:
self.word_doc_stream.read(csw_new * 2)
# Extract fcClx and lcbClx from FibRgFcLcb97
fc_clx = struct.unpack("<I", fib_rg_fc_lcb_blob[0x108:0x10C])[0]
lcb_clx = struct.unpack("<I", fib_rg_fc_lcb_blob[0x10C:0x110])[0]
fc_plcf_bte_papx = struct.unpack("<I", fib_rg_fc_lcb_blob[0x68:0x6C])[0]
lcb_plcf_bte_papx = struct.unpack("<I", fib_rg_fc_lcb_blob[0x6C:0x70])[0]
self.fib_info = {
"nFib": nFib,
"fcClx": fc_clx,
"lcbClx": lcb_clx,
"ccpText": ccpText,
"fcPlcfBtePapx": fc_plcf_bte_papx,
"lcbPlcfBtePapx": lcb_plcf_bte_papx,
}
return self.fib_info
def read_clx(self, fc_clx, lcb_clx):
"""Read the CLX structure from the Table stream"""
self.table_stream.seek(fc_clx)
clx_data = self.table_stream.read(lcb_clx)
# For simplicity, we assume the data starts with Pcdt (0x02)
if clx_data[0] != 0x02:
raise ValueError("Expected Pcdt structure not found in CLX data")
return clx_data
def parse_plc_pcd(self, pcdt_data):
"""Parse the PLC structure containing PCDs(2.9.177)"""
# Get the size of PlcPcd structure
lcb = struct.unpack("<I", pcdt_data[1:5])[0]
plc_pcd_bytes = pcdt_data[5 : 5 + lcb]
# Calculate number of PCDs: n = (lcb - 4) // 12
n = (lcb - 4) // 12
# Parse aCP array (n+1 CPs, each 4 bytes)
aCP = [
struct.unpack("<I", plc_pcd_bytes[i * 4 : (i + 1) * 4])[0]
for i in range(n + 1)
]
# Parse aPcd array (n PCDs, each 8 bytes)
aPcd = []
for i in range(n):
start = (n + 1) * 4 + i * 8
pcd_bytes = plc_pcd_bytes[start : start + 8]
# Extract fc (bytes 2-6) and compression flag
fc_bytes = pcd_bytes[2:6]
fc = int.from_bytes(fc_bytes, byteorder="little", signed=False)
fcompressed = (fc >> 1) & 0x1
aPcd.append(
{
"fc": fc,
"start": aCP[i],
"end": aCP[i + 1],
"f_compressed": fcompressed,
}
)
self.plc_pcd = {"aCP": aCP, "aPcd": aPcd}
return self.plc_pcd
def _find_pcd_index(self, cp):
"""Find the index of the PCD containing the given character position"""
aCP = self.plc_pcd["aCP"]
for i in range(len(aCP) - 1):
if aCP[i] <= cp < aCP[i + 1]:
return i
return None
def get_paragraph_boundaries(self, cp):
"""Find paragraph boundaries for a given character position (2.4.2)"""
if not self.fib_info or not self.plc_pcd:
raise RuntimeError("Must read FIB and PLC/PCD first")
# Find the PCD containing this cp
i = self._find_pcd_index(cp)
if i is None:
return None
pcd = self.plc_pcd["aPcd"][i]
start_cp = self._find_paragraph_start(cp, i, pcd)
end_cp = self._find_paragraph_end(cp, i, pcd)
return (start_cp, end_cp)
def _find_paragraph_start(self, cp, i, pcd):
"""Find the start of the paragraph containing cp (algorithm 2.4.2)"""
# Step 3: Calculate fc and fc_pcd
fc_pcd = pcd["fc"]
# Let fcPcd be Pcd.fc.fc. Let fc be fcPcd + 2(cp PlcPcd.aCp[i]).
# If Pcd.fc.fCompressed is one, set fc to fc / 2, and set fcPcd to fcPcd/2.
fc = fc_pcd + 2 * (cp - self.plc_pcd["aCP"][i])
if pcd["f_compressed"]:
fc = fc // 2
fc_pcd = fc_pcd // 2
# Step 4: Read PlcBtePapx
self.table_stream.seek(self.fib_info["fcPlcfBtePapx"])
plcf_bte_papx_data = self.table_stream.read(self.fib_info["lcbPlcfBtePapx"])
a_fc, a_pn = self._parse_plcf_bte_papx(plcf_bte_papx_data)
# Handle case where a_fc is empty
if not a_fc:
return None
fc_last = a_fc[-1]
# Step 4 continued: Check fcLast
if fc_last <= fc:
if fc_last < fc_pcd:
# Step 8: Check if at beginning of document
if self.plc_pcd["aCP"][i] == 0:
return 0
# Step 9: Recurse with previous cp
return self._find_paragraph_start(
self.plc_pcd["aCP"][i], i - 1, self.plc_pcd["aPcd"][i - 1]
)
# Adjust fc and fc_last if needed
fc = fc_last
if pcd["f_compressed"]:
fc_last = fc_last // 2
fc_first = fc_last
else:
# Step 5: Find largest j where a_fc[j] <= fc
j = self._find_largest_index_le(a_fc, fc)
if j is None:
return None # Invalid cp
# Read PapxFkp
papx_fkp = self._read_papx_fkp(a_pn[j])
# print(f"papx_fkp:{papx_fkp}, j:{j}")
if not papx_fkp or not papx_fkp.get("rgfc"):
return None # Invalid data
# Step 6: Find largest k where rgfc[k] <= fc
k = self._find_largest_index_le(papx_fkp["rgfc"], fc)
if k is None:
return None # Invalid cp
# Check if cp is outside document range
if papx_fkp["rgfc"][-1] <= fc:
return None
fc_first = papx_fkp["rgfc"][k]
# Step 7: Calculate paragraph start
if fc_first > fc_pcd:
dfc = fc_first - fc_pcd
if not pcd["f_compressed"]:
dfc = dfc // 2
return self.plc_pcd["aCP"][i] + dfc
# Step 8: Check if at beginning of document
if self.plc_pcd["aCP"][i] == 0:
return 0
# Step 9: Recurse with previous cp
return self._find_paragraph_start(
self.plc_pcd["aCP"][i], i - 1, self.plc_pcd["aPcd"][i - 1]
)
def _find_paragraph_end(self, cp, i, pcd):
"""Find the end of the paragraph containing cp (algorithm 2.4.2)"""
fc_pcd = pcd["fc"]
fc = fc_pcd + 2 * (cp - self.plc_pcd["aCP"][i])
fc_mac = fc_pcd + 2 * (self.plc_pcd["aCP"][i + 1] - self.plc_pcd["aCP"][i])
if pcd["f_compressed"]:
fc = fc // 2
fc_pcd = fc_pcd // 2
fc_mac = fc_mac // 2
# Read PlcBtePapx
self.table_stream.seek(self.fib_info["fcPlcfBtePapx"])
plcf_bte_papx_data = self.table_stream.read(self.fib_info["lcbPlcfBtePapx"])
a_fc, a_pn = self._parse_plcf_bte_papx(plcf_bte_papx_data)
# Find largest j where a_fc[j] <= fc
j = self._find_largest_index_le(a_fc, fc)
if j is None or (a_fc and fc >= a_fc[-1]):
return self._find_paragraph_end(
self.plc_pcd["aCP"][i + 1], i + 1, self.plc_pcd["aPcd"][i + 1]
)
# Read PapxFkp
papx_fkp = self._read_papx_fkp(a_pn[j])
if not papx_fkp:
return None
# Find largest k where rgfc[k] <= fc
k = self._find_largest_index_le(papx_fkp["rgfc"], fc)
if k is None or (papx_fkp["rgfc"] and fc >= papx_fkp["rgfc"][-1]):
return None
fc_lim = papx_fkp["rgfc"][k + 1] if k + 1 < len(papx_fkp["rgfc"]) else fc_mac
if fc_lim <= fc_mac:
dfc = fc_lim - fc_pcd
if not pcd["f_compressed"]:
dfc = dfc // 2
return self.plc_pcd["aCP"][i] + dfc - 1
return self._find_paragraph_end(
self.plc_pcd["aCP"][i + 1], i + 1, self.plc_pcd["aPcd"][i + 1]
)
def _parse_plcf_bte_papx(self, data):
"""Parse PlcBtePapx structure (2.8.6)
Args:
data: Raw bytes of PlcBtePapx structure.
Returns:
(a_fc, a_pn): Tuple of two lists:
- a_fc: List of unsigned 4-byte integers (FC offsets).
- a_pn: List of unsigned 4-byte integers (PnFkpPapx entries).
Raises:
ValueError: If data is malformed or aFC is not sorted/unique.
"""
if len(data) < 12: # Minimum: 8 (aFC[0..1]) + 4 (aPnBtePapx[0])
return [], []
# Calculate number of aPnBtePapx entries (n)
n = (len(data) - 4) // 8
if (2 * n + 1) * 4 != len(data):
raise ValueError("Invalid PlcBtePapx size")
a_fc = []
a_pn = []
# Parse aFC (n+1 entries, each 4 bytes)
for i in range(n + 1):
offset = i * 4
fc = struct.unpack("<I", data[offset : offset + 4])[0]
a_fc.append(fc)
# Parse aPnBtePapx (n entries, each 4 bytes, starting after last aFC)
pn_offset = (n + 1) * 4
for i in range(n):
offset = pn_offset + i * 4
pn = struct.unpack("<I", data[offset : offset + 4])[0]
a_pn.append(pn)
# Validate aFC is strictly increasing (sorted and unique)
for i in range(len(a_fc) - 1):
if a_fc[i] >= a_fc[i + 1]:
raise ValueError("aFC must be strictly increasing")
return a_fc, a_pn
def _read_papx_fkp(self, pn):
"""Read PapxFkp structure from WordDocument stream.
Args:
pn: Page number (PnFkpPapx), offset = pn * 512.
Returns:
Dict with keys:
- "rgfc": List of FC offsets (4-byte unsigned integers).
- "rgbx": List of BxPap (1-byte integers).
- "papx_in_fkp": List of PapxInFkp raw bytes.
Raises:
ValueError: If FKP data is invalid.
"""
offset = pn * 512
self.word_doc_stream.seek(offset)
fkp_data = self.word_doc_stream.read(512)
if len(fkp_data) != 512:
raise ValueError("FKP size must be 512 bytes")
cpara = fkp_data[511] # Number of paragraphs (1 ≤ cpara ≤ 0x1D)
if not 1 <= cpara <= 0x1D:
raise ValueError(f"Invalid cpara: {cpara} (must be 1 ≤ cpara ≤ 29)")
# Parse rgfc (cpara + 1 entries, each 4 bytes)
rgfc = []
for i in range(cpara + 1):
fc_offset = i * 4
fc = struct.unpack("<I", fkp_data[fc_offset : fc_offset + 4])[0]
rgfc.append(fc)
# Parse rgbx (cpara entries, each 1 byte)
rgbx_start = (cpara + 1) * 4
rgbx = list(fkp_data[rgbx_start : rgbx_start + cpara])
# Parse PapxInFkp (variable size, located after rgbx)
papx_in_fkp_start = rgbx_start + cpara
papx_in_fkp_end = 511 # cpara is the last byte
papx_in_fkp = fkp_data[papx_in_fkp_start:papx_in_fkp_end]
return {
"rgfc": rgfc,
"rgbx": rgbx,
"papx_in_fkp": papx_in_fkp,
}
def _find_largest_index_le(self, array, value):
"""Find largest index where array[index] <= value"""
for i in reversed(range(len(array))):
if array[i] <= value:
return i
return None
def extract_text_by_paragraphs(self):
"""Extract text organized by paragraphs"""
self.word_doc_stream.seek(0)
self.table_stream.seek(0)
self.read_fib()
clx_data = self.read_clx(self.fib_info["fcClx"], self.fib_info["lcbClx"])
self.parse_plc_pcd(clx_data)
paragraphs = []
current_cp = 0
total_chars = self.fib_info["ccpText"]
while current_cp < total_chars:
boundaries = self.get_paragraph_boundaries(current_cp)
if not boundaries:
break
start, end = boundaries
if start > end:
break
paragraph_text = self._extract_text_range(start, end)
paragraphs.append(paragraph_text)
current_cp = end + 1
return paragraphs
def _extract_text_range(self, start_cp, end_cp):
"""Extract text between two character positions"""
text_chars = []
i = self._find_pcd_index(start_cp)
while i is not None and start_cp <= end_cp:
pcd = self.plc_pcd["aPcd"][i]
pcd_start = self.plc_pcd["aCP"][i]
pcd_end = self.plc_pcd["aCP"][i + 1]
# Determine range within this PCD
range_start = max(start_cp, pcd_start)
range_end = min(end_cp, pcd_end - 1)
if range_start > range_end:
i += 1
continue
fc = pcd["fc"]
compressed = pcd["f_compressed"]
for cp in range(range_start, range_end + 1):
if compressed:
offset = fc + (cp - pcd_start)
self.word_doc_stream.seek(offset)
char_byte = self.word_doc_stream.read(1)
char_code = char_byte[0]
char = chr(self.ANSI_TO_UNICODE.get(char_code, char_code))
else:
offset = fc + 2 * (cp - pcd_start)
self.word_doc_stream.seek(offset)
char_bytes = self.word_doc_stream.read(2)
char = char_bytes.decode("utf-16-le")
text_chars.append(char)
start_cp = range_end + 1
i += 1
return "".join(text_chars)
def extract_text(self):
"""Main method to extract text from the document"""
self.word_doc_stream.seek(0)
self.table_stream.seek(0)
fib_info = self.read_fib()
clx_data = self.read_clx(fib_info["fcClx"], fib_info["lcbClx"])
pcd_array = self.parse_plc_pcd(clx_data)
full_text = []
for pcd in pcd_array["aPcd"]:
start_cp, end_cp = pcd["start"], pcd["end"]
char_count = end_cp - start_cp
if char_count == 0:
continue
fc = pcd["fc"]
compressed = pcd["f_compressed"]
text_chars = []
for cp in range(start_cp, end_cp):
offset = (
fc + (cp - start_cp) if compressed else fc + 2 * (cp - start_cp)
)
self.word_doc_stream.seek(offset)
if compressed:
char_byte = self.word_doc_stream.read(1)
char_code = char_byte[0]
char = chr(self.ANSI_TO_UNICODE.get(char_code, char_code))
else:
char_bytes = self.word_doc_stream.read(2)
# decode char
char = char_bytes.decode("utf-16-le")
text_chars.append(char)
full_text.append("".join(text_chars))
return "".join(full_text)
class Word97DocKnowledge(Knowledge):
"""Microsoft Word 97-2003 (.doc)."""
def __init__(
self,
file_path: Optional[str] = None,
knowledge_type: Any = KnowledgeType.DOCUMENT,
encoding: Optional[str] = "utf-16-le",
loader: Optional[Any] = None,
metadata: Optional[Dict[str, Union[str, List[str]]]] = None,
**kwargs: Any,
) -> None:
"""Create Microsoft Word 97-2003 (.doc) Knowledge with Knowledge arguments.
Args:
file_path(str, optional): file path
knowledge_type(KnowledgeType, optional): knowledge type
encoding(str, optional): .doc encoding
loader(Any, optional): loader
"""
super().__init__(
path=file_path,
knowledge_type=knowledge_type,
data_loader=loader,
metadata=metadata,
**kwargs,
)
self._encoding = encoding
def _load(self) -> List[Document]:
"""Load doc document from loader."""
if self._loader:
documents = self._loader.load()
else:
docs = []
content = []
with Word97DocParser(self._path) as parser:
paragraphs = parser.extract_text_by_paragraphs()
for i, para in enumerate(paragraphs):
content.append(para)
metadata = {"source": self._path}
if self._metadata:
metadata.update(self._metadata) # type: ignore
docs.append(Document(content="\n".join(content), metadata=metadata))
return docs
return [Document.langchain2doc(lc_document) for lc_document in documents]
@classmethod
def support_chunk_strategy(cls) -> List[ChunkStrategy]:
"""Return support chunk strategy."""
return [
ChunkStrategy.CHUNK_BY_SIZE,
ChunkStrategy.CHUNK_BY_PARAGRAPH,
ChunkStrategy.CHUNK_BY_SEPARATOR,
]
@classmethod
def default_chunk_strategy(cls) -> ChunkStrategy:
"""Return default chunk strategy."""
return ChunkStrategy.CHUNK_BY_SIZE
@classmethod
def type(cls) -> KnowledgeType:
"""Return knowledge type."""
return KnowledgeType.DOCUMENT
@classmethod
def document_type(cls) -> DocumentType:
"""Return document type."""
return DocumentType.DOC

View File

@@ -171,6 +171,7 @@ class KnowledgeFactory:
from .csv import CSVKnowledge # noqa: F401
from .datasource import DatasourceKnowledge # noqa: F401
from .doc import Word97DocKnowledge # noqa: F401
from .docx import DocxKnowledge # noqa: F401
from .excel import ExcelKnowledge # noqa: F401
from .html import HTMLKnowledge # noqa: F401

View File

@@ -0,0 +1,20 @@
from pathlib import Path
import pytest
from ..doc import Word97DocKnowledge
@pytest.fixture
def mock_file_path():
file_path = Path(__file__).parent / "data" / "test_mock.doc"
return file_path.as_posix()
def test_load_from_docx(mock_file_path):
knowledge = Word97DocKnowledge(file_path=mock_file_path)
documents = knowledge._load()
actual = documents[0].content.replace("\r", "\n")
assert len(documents) == 1
assert actual == "This is the first paragraph.\n\nThis is the second paragraph.\n"
assert documents[0].metadata["source"] == mock_file_path

2489
uv.lock generated

File diff suppressed because one or more lines are too long