mirror of
https://github.com/FoundationAgents/MetaGPT.git
synced 2026-05-11 08:42:38 +02:00
Merge pull request #11 from Stitch-z/feature-invoice-ocr-assistant
Feature/invoice ocr assistant
This commit is contained in:
commit
d104777ed9
15 changed files with 599 additions and 3 deletions
|
|
@ -3,7 +3,7 @@ FROM nikolaik/python-nodejs:python3.9-nodejs20-slim
|
|||
|
||||
# Install Debian software needed by MetaGPT and clean up in one RUN command to reduce image size
|
||||
RUN apt update &&\
|
||||
apt install -y git chromium fonts-ipafont-gothic fonts-wqy-zenhei fonts-thai-tlwg fonts-kacst fonts-freefont-ttf libxss1 --no-install-recommends &&\
|
||||
apt install -y libgomp1 git chromium fonts-ipafont-gothic fonts-wqy-zenhei fonts-thai-tlwg fonts-kacst fonts-freefont-ttf libxss1 --no-install-recommends &&\
|
||||
apt clean && rm -rf /var/lib/apt/lists/*
|
||||
|
||||
# Install Mermaid CLI globally
|
||||
|
|
|
|||
39
examples/invoice_ocr.py
Normal file
39
examples/invoice_ocr.py
Normal file
|
|
@ -0,0 +1,39 @@
|
|||
#!/usr/bin/env python3
|
||||
# _*_ coding: utf-8 _*_
|
||||
|
||||
"""
|
||||
@Time : 2023/9/21 21:40:57
|
||||
@Author : Stitch-z
|
||||
@File : invoice_ocr.py
|
||||
"""
|
||||
|
||||
import asyncio
|
||||
import os
|
||||
|
||||
from metagpt.roles.invoice_ocr_assistant import InvoiceOCRAssistant
|
||||
from metagpt.schema import Message
|
||||
|
||||
|
||||
async def main():
|
||||
relative_paths = [
|
||||
"../tests/data/invoices/invoice-1.pdf",
|
||||
"../tests/data/invoices/invoice-2.png",
|
||||
"../tests/data/invoices/invoice-3.jpg",
|
||||
"../tests/data/invoices/invoice-4.zip"
|
||||
]
|
||||
# Get the current working directory
|
||||
current_directory = os.getcwd()
|
||||
# The absolute path of the file
|
||||
absolute_file_paths = [os.path.abspath(os.path.join(current_directory, path)) for path in relative_paths]
|
||||
|
||||
for path in absolute_file_paths:
|
||||
role = InvoiceOCRAssistant()
|
||||
await role.run(Message(
|
||||
content="Invoicing date",
|
||||
instruct_content={"file_path": path}
|
||||
))
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
asyncio.run(main())
|
||||
|
||||
223
metagpt/actions/invoice_ocr.py
Normal file
223
metagpt/actions/invoice_ocr.py
Normal file
|
|
@ -0,0 +1,223 @@
|
|||
#!/usr/bin/env python3
|
||||
# _*_ coding: utf-8 _*_
|
||||
|
||||
"""
|
||||
@Time : 2023/9/21 18:10:20
|
||||
@Author : Stitch-z
|
||||
@File : invoice_ocr.py
|
||||
@Describe : Actions of the invoice ocr assistant.
|
||||
"""
|
||||
|
||||
import os
|
||||
import zipfile
|
||||
from enum import Enum
|
||||
from pathlib import Path
|
||||
|
||||
import pandas as pd
|
||||
|
||||
from typing import Dict, List
|
||||
from paddleocr import PaddleOCR
|
||||
|
||||
from metagpt.actions import Action
|
||||
from metagpt.const import INVOICE_OCR_TABLE_PATH
|
||||
from metagpt.logs import logger
|
||||
from metagpt.prompts.invoice_ocr import EXTRACT_OCR_MAIN_INFO_PROMPT, REPLY_OCR_QUESTION_PROMPT
|
||||
from metagpt.utils.common import OutputParser
|
||||
from metagpt.utils.file import File
|
||||
|
||||
|
||||
class FileExtensionType(Enum):
|
||||
"""Enum representing file extensions and their associated types.
|
||||
Each enum member consists of a tuple containing the file extension and its associated type.
|
||||
|
||||
"""
|
||||
|
||||
ZIP = (".zip", "zip")
|
||||
PDF = (".pdf", "pdf")
|
||||
PNG = (".png", "png")
|
||||
JPG = (".jpg", "jpg")
|
||||
|
||||
@classmethod
|
||||
def get_extension_list(cls) -> List[str]:
|
||||
"""Get a list of file extensions.
|
||||
|
||||
Returns:
|
||||
A list of file extensions as strings.
|
||||
"""
|
||||
return [ext.value[0] for ext in cls]
|
||||
|
||||
@classmethod
|
||||
def get_type_list(cls) -> List[str]:
|
||||
"""Get a list of file types.
|
||||
|
||||
Returns:
|
||||
A list of file types as strings.
|
||||
"""
|
||||
return [ext.value[1] for ext in cls]
|
||||
|
||||
|
||||
class InvoiceOCR(Action):
|
||||
"""Action class for performing OCR on invoice files, including zip, PDF, png, and jpg files.
|
||||
|
||||
Args:
|
||||
name: The name of the action. Defaults to an empty string.
|
||||
language: The language for OCR output. Defaults to "ch" (Chinese).
|
||||
|
||||
"""
|
||||
|
||||
def __init__(self, name: str = "", *args, **kwargs):
|
||||
super().__init__(name, *args, **kwargs)
|
||||
|
||||
@staticmethod
|
||||
async def _check_file_type(filename: str) -> str:
|
||||
"""Check the file type of the given filename.
|
||||
|
||||
Args:
|
||||
filename: The name of the file.
|
||||
|
||||
Returns:
|
||||
The file type based on FileExtensionType enum.
|
||||
|
||||
Raises:
|
||||
Exception: If the file format is not zip, pdf, png, or jpg.
|
||||
"""
|
||||
file_ext = None
|
||||
for ext in FileExtensionType:
|
||||
if filename.endswith(ext.value[0]):
|
||||
file_ext = ext.value[1]
|
||||
break
|
||||
|
||||
if not file_ext:
|
||||
raise Exception("The invoice format is not zip, pdf, png, or jpg")
|
||||
|
||||
return file_ext
|
||||
|
||||
@staticmethod
|
||||
async def _unzip(file_path: Path) -> Path:
|
||||
"""Unzip a file and return the path to the unzipped directory.
|
||||
|
||||
Args:
|
||||
file_path: The path to the zip file.
|
||||
|
||||
Returns:
|
||||
The path to the unzipped directory.
|
||||
"""
|
||||
file_directory = file_path.parent
|
||||
with zipfile.ZipFile(file_path, 'r') as zip_ref:
|
||||
for zip_info in zip_ref.infolist():
|
||||
# Use CP437 to encode the file name, and then use GBK decoding to prevent Chinese garbled code
|
||||
relative_name = zip_info.filename.encode('cp437').decode('gbk')
|
||||
unzip_dir, name = relative_name.split("/")
|
||||
if name:
|
||||
full_filename = file_directory / relative_name
|
||||
await File.write(full_filename.parent, name, zip_ref.read(zip_info.filename))
|
||||
|
||||
unzip_path = file_directory / unzip_dir
|
||||
logger.info(f"unzip_path: {unzip_path}")
|
||||
return unzip_path
|
||||
|
||||
async def run(self, file_path: Path, filename: str, *args, **kwargs) -> list:
|
||||
"""Execute the action to identify invoice files through OCR.
|
||||
|
||||
Args:
|
||||
file_path: The path to the input file.
|
||||
filename: The name of the input file.
|
||||
|
||||
Returns:
|
||||
A list of OCR results.
|
||||
"""
|
||||
file_ext = await self._check_file_type(filename)
|
||||
|
||||
if file_ext == FileExtensionType.ZIP.value[1]:
|
||||
# OCR recognizes zip batch files
|
||||
unzip_path = await self._unzip(file_path)
|
||||
file_list = os.listdir(unzip_path)
|
||||
ocr_list = []
|
||||
|
||||
for filename in file_list:
|
||||
invoice_file_path = unzip_path / filename
|
||||
# Identify files that match the type
|
||||
if filename.split(".")[-1] in FileExtensionType.get_type_list():
|
||||
ocr = PaddleOCR(use_angle_cls=True, lang="ch", page_num=1)
|
||||
ocr_result = ocr.ocr(str(invoice_file_path), cls=True)
|
||||
ocr_list.append(ocr_result)
|
||||
return ocr_list
|
||||
|
||||
else:
|
||||
# OCR identifies single file
|
||||
ocr = PaddleOCR(use_angle_cls=True, lang="ch", page_num=1)
|
||||
ocr_result = ocr.ocr(str(file_path), cls=True)
|
||||
return [ocr_result]
|
||||
|
||||
|
||||
class GenerateTable(Action):
|
||||
"""Action class for generating tables from OCR results.
|
||||
|
||||
Args:
|
||||
name: The name of the action. Defaults to an empty string.
|
||||
language: The language used for the generated table. Defaults to "ch" (Chinese).
|
||||
|
||||
"""
|
||||
|
||||
def __init__(self, name: str = "", language: str = "ch", *args, **kwargs):
|
||||
super().__init__(name, *args, **kwargs)
|
||||
self.language = language
|
||||
|
||||
async def run(self, ocr_results: list, filename: str, *args, **kwargs) -> Dict[str, str]:
|
||||
"""Processes OCR results, extracts invoice information, generates a table, and saves it as an Excel file.
|
||||
|
||||
Args:
|
||||
ocr_results: A list of OCR results obtained from invoice processing.
|
||||
filename: The name of the output Excel file.
|
||||
|
||||
Returns:
|
||||
A dictionary containing the invoice information.
|
||||
|
||||
"""
|
||||
table_data = []
|
||||
pathname = INVOICE_OCR_TABLE_PATH
|
||||
pathname.mkdir(parents=True, exist_ok=True)
|
||||
|
||||
for ocr_result in ocr_results:
|
||||
# Extract invoice OCR main information
|
||||
prompt = EXTRACT_OCR_MAIN_INFO_PROMPT.format(ocr_result=ocr_result, language=self.language)
|
||||
ocr_info = await self._aask(prompt=prompt)
|
||||
invoice_data = OutputParser.extract_struct(ocr_info, dict)
|
||||
if invoice_data:
|
||||
table_data.append(invoice_data)
|
||||
|
||||
# Generate Excel file
|
||||
filename = f"{filename.split('.')[0]}.xlsx"
|
||||
full_filename = f"{pathname}/{filename}"
|
||||
df = pd.DataFrame(table_data)
|
||||
df.to_excel(full_filename, index=False)
|
||||
return table_data
|
||||
|
||||
|
||||
class ReplyQuestion(Action):
|
||||
"""Action class for generating replies to questions based on OCR results.
|
||||
|
||||
Args:
|
||||
name: The name of the action. Defaults to an empty string.
|
||||
language: The language used for generating the reply. Defaults to "ch" (Chinese).
|
||||
|
||||
"""
|
||||
|
||||
def __init__(self, name: str = "", language: str = "ch", *args, **kwargs):
|
||||
super().__init__(name, *args, **kwargs)
|
||||
self.language = language
|
||||
|
||||
async def run(self, query: str, ocr_result: list, *args, **kwargs) -> str:
|
||||
"""Reply to questions based on ocr results.
|
||||
|
||||
Args:
|
||||
query: The question for which a reply is generated.
|
||||
ocr_result: A list of OCR results.
|
||||
|
||||
Returns:
|
||||
A reply result of string type.
|
||||
"""
|
||||
prompt = REPLY_OCR_QUESTION_PROMPT.format(query=query, ocr_result=ocr_result, language=self.language)
|
||||
resp = await self._aask(prompt=prompt)
|
||||
return resp
|
||||
|
||||
|
|
@ -36,6 +36,7 @@ YAPI_URL = "http://yapi.deepwisdomai.com/"
|
|||
TMP = PROJECT_ROOT / "tmp"
|
||||
RESEARCH_PATH = DATA_PATH / "research"
|
||||
TUTORIAL_PATH = DATA_PATH / "tutorial_docx"
|
||||
INVOICE_OCR_TABLE_PATH = DATA_PATH / "invoice_table"
|
||||
|
||||
SKILL_DIRECTORY = PROJECT_ROOT / "metagpt/skills"
|
||||
|
||||
|
|
|
|||
39
metagpt/prompts/invoice_ocr.py
Normal file
39
metagpt/prompts/invoice_ocr.py
Normal file
|
|
@ -0,0 +1,39 @@
|
|||
#!/usr/bin/env python3
|
||||
# _*_ coding: utf-8 _*_
|
||||
|
||||
"""
|
||||
@Time : 2023/9/21 16:30:25
|
||||
@Author : Stitch-z
|
||||
@File : invoice_ocr.py
|
||||
@Describe : Prompts of the invoice ocr assistant.
|
||||
"""
|
||||
|
||||
COMMON_PROMPT = "Now I will provide you with the OCR text recognition results for the invoice."
|
||||
|
||||
EXTRACT_OCR_MAIN_INFO_PROMPT = COMMON_PROMPT + """
|
||||
Please extract the payee, city, total cost, and invoicing date of the invoice.
|
||||
|
||||
The OCR data of the invoice are as follows:
|
||||
{ocr_result}
|
||||
|
||||
Mandatory restrictions are returned according to the following requirements:
|
||||
1. The total cost refers to the total price and tax. Do not include `¥`.
|
||||
2. The city must be the recipient's city.
|
||||
2. The returned JSON dictionary must be returned in {language}
|
||||
3. Mandatory requirement to output in JSON format: {{"收款人":"x","城市":"x","总费用/元":"","开票日期":""}}.
|
||||
"""
|
||||
|
||||
REPLY_OCR_QUESTION_PROMPT = COMMON_PROMPT + """
|
||||
Please answer the question: {query}
|
||||
|
||||
The OCR data of the invoice are as follows:
|
||||
{ocr_result}
|
||||
|
||||
Mandatory restrictions are returned according to the following requirements:
|
||||
1. Answer in {language} language.
|
||||
2. Enforce restrictions on not returning OCR data sent to you.
|
||||
3. Return with markdown syntax layout.
|
||||
"""
|
||||
|
||||
INVOICE_OCR_SUCCESS = "Successfully completed OCR text recognition invoice."
|
||||
|
||||
112
metagpt/roles/invoice_ocr_assistant.py
Normal file
112
metagpt/roles/invoice_ocr_assistant.py
Normal file
|
|
@ -0,0 +1,112 @@
|
|||
#!/usr/bin/env python3
|
||||
# _*_ coding: utf-8 _*_
|
||||
|
||||
"""
|
||||
@Time : 2023/9/21 14:10:05
|
||||
@Author : Stitch-z
|
||||
@File : invoice_ocr_assistant.py
|
||||
"""
|
||||
|
||||
import os
|
||||
from pathlib import Path
|
||||
|
||||
import pandas as pd
|
||||
from metagpt.actions.invoice_ocr import InvoiceOCR, GenerateTable, ReplyQuestion
|
||||
from metagpt.prompts.invoice_ocr import INVOICE_OCR_SUCCESS
|
||||
from metagpt.roles import Role
|
||||
from metagpt.schema import Message
|
||||
|
||||
|
||||
class InvoiceOCRAssistant(Role):
|
||||
"""Invoice OCR assistant, support OCR text recognition of invoice PDF, png, jpg, and zip files,
|
||||
generate a table for the payee, city, total amount, and invoicing date of the invoice,
|
||||
and ask questions for a single file based on the OCR recognition results of the invoice.
|
||||
|
||||
Args:
|
||||
name: The name of the role.
|
||||
profile: The role profile description.
|
||||
goal: The goal of the role.
|
||||
constraints: Constraints or requirements for the role.
|
||||
language: The language in which the invoice table will be generated.
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
name: str = "Stitch",
|
||||
profile: str = "Invoice Ocr Assistant",
|
||||
goal: str = "OCR identifies invoice files and generates invoice main information table",
|
||||
constraints: str = "",
|
||||
language: str = "ch",
|
||||
):
|
||||
super().__init__(name, profile, goal, constraints)
|
||||
self._init_actions([InvoiceOCR])
|
||||
self.language = language
|
||||
self.filename = ""
|
||||
self.origin_query = ""
|
||||
self.orc_data = None
|
||||
|
||||
async def _think(self) -> None:
|
||||
"""Determine the next action to be taken by the role."""
|
||||
if self._rc.todo is None:
|
||||
self._set_state(0)
|
||||
return
|
||||
|
||||
if self._rc.state + 1 < len(self._states):
|
||||
self._set_state(self._rc.state + 1)
|
||||
else:
|
||||
self._rc.todo = None
|
||||
|
||||
async def _act(self) -> Message:
|
||||
"""Perform an action as determined by the role.
|
||||
|
||||
Returns:
|
||||
A message containing the result of the action.
|
||||
"""
|
||||
msg = self._rc.memory.get(k=1)[0]
|
||||
todo = self._rc.todo
|
||||
if isinstance(todo, InvoiceOCR):
|
||||
self.origin_query = msg.content
|
||||
file_path = msg.instruct_content.get("file_path")
|
||||
self.filename = os.path.basename(file_path)
|
||||
if not file_path:
|
||||
raise Exception("Invoice file not uploaded")
|
||||
|
||||
resp = await todo.run(Path(file_path), self.filename)
|
||||
if len(resp) == 1:
|
||||
# Single file support for questioning based on OCR recognition results
|
||||
self._init_actions([GenerateTable, ReplyQuestion])
|
||||
self.orc_data = resp[0]
|
||||
else:
|
||||
self._init_actions([GenerateTable])
|
||||
|
||||
self._rc.todo = None
|
||||
content = INVOICE_OCR_SUCCESS
|
||||
elif isinstance(todo, GenerateTable):
|
||||
ocr_results = msg.instruct_content
|
||||
resp = await todo.run(ocr_results, self.filename)
|
||||
|
||||
# Convert list to Markdown format string
|
||||
df = pd.DataFrame(resp)
|
||||
markdown_table = df.to_markdown(index=False)
|
||||
content = f"{markdown_table}\n\n\n"
|
||||
else:
|
||||
resp = await todo.run(self.origin_query, self.orc_data)
|
||||
content = resp
|
||||
|
||||
msg = Message(content=content, instruct_content=resp)
|
||||
self._rc.memory.add(msg)
|
||||
return msg
|
||||
|
||||
async def _react(self) -> Message:
|
||||
"""Execute the invoice ocr assistant's think and actions.
|
||||
|
||||
Returns:
|
||||
A message containing the final result of the assistant's actions.
|
||||
"""
|
||||
while True:
|
||||
await self._think()
|
||||
if self._rc.todo is None:
|
||||
break
|
||||
msg = await self._act()
|
||||
return msg
|
||||
|
||||
|
|
@ -195,7 +195,8 @@ class OutputParser:
|
|||
except (ValueError, SyntaxError) as e:
|
||||
raise Exception(f"Error while extracting and parsing the {data_type}: {e}")
|
||||
else:
|
||||
raise Exception(f"No {data_type} found in the text.")
|
||||
logger.error(f"No {data_type} found in the text.")
|
||||
return [] if data_type is list else {}
|
||||
|
||||
|
||||
class CodeParser:
|
||||
|
|
|
|||
|
|
@ -1,3 +1,5 @@
|
|||
paddlepaddle==2.4.2
|
||||
paddleocr>=2.0.1
|
||||
aiohttp==3.8.4
|
||||
#azure_storage==0.37.0
|
||||
channels==4.0.0
|
||||
|
|
@ -42,4 +44,5 @@ pytest-mock==3.11.1
|
|||
open-interpreter==0.1.4; python_version>"3.9"
|
||||
ta==0.10.2
|
||||
semantic-kernel==0.3.10.dev0
|
||||
tabulate==0.9.0
|
||||
|
||||
|
|
|
|||
BIN
tests/data/invoices/invoice-1.pdf
Normal file
BIN
tests/data/invoices/invoice-1.pdf
Normal file
Binary file not shown.
BIN
tests/data/invoices/invoice-2.png
Normal file
BIN
tests/data/invoices/invoice-2.png
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 464 KiB |
BIN
tests/data/invoices/invoice-3.jpg
Normal file
BIN
tests/data/invoices/invoice-3.jpg
Normal file
Binary file not shown.
|
After Width: | Height: | Size: 466 KiB |
BIN
tests/data/invoices/invoice-4.zip
Normal file
BIN
tests/data/invoices/invoice-4.zip
Normal file
Binary file not shown.
72
tests/metagpt/actions/test_invoice_ocr.py
Normal file
72
tests/metagpt/actions/test_invoice_ocr.py
Normal file
|
|
@ -0,0 +1,72 @@
|
|||
#!/usr/bin/env python3
|
||||
# _*_ coding: utf-8 _*_
|
||||
|
||||
"""
|
||||
@Time : 2023/10/09 18:40:34
|
||||
@Author : Stitch-z
|
||||
@File : test_invoice_ocr.py
|
||||
"""
|
||||
|
||||
import os
|
||||
from pathlib import Path
|
||||
from typing import List
|
||||
|
||||
import pytest
|
||||
|
||||
from metagpt.actions.invoice_ocr import InvoiceOCR, GenerateTable, ReplyQuestion
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
@pytest.mark.parametrize(
|
||||
"invoice_path",
|
||||
[
|
||||
"../../data/invoices/invoice-3.jpg",
|
||||
"../../data/invoices/invoice-4.zip",
|
||||
]
|
||||
)
|
||||
async def test_invoice_ocr(invoice_path: str):
|
||||
invoice_path = os.path.abspath(os.path.join(os.getcwd(), invoice_path))
|
||||
filename = os.path.basename(invoice_path)
|
||||
resp = await InvoiceOCR().run(file_path=Path(invoice_path), filename=filename)
|
||||
assert isinstance(resp, list)
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
@pytest.mark.parametrize(
|
||||
("invoice_path", "expected_result"),
|
||||
[
|
||||
(
|
||||
"../../data/invoices/invoice-1.pdf",
|
||||
[
|
||||
{
|
||||
"收款人": "小明",
|
||||
"城市": "深圳市",
|
||||
"总费用/元": "412.00",
|
||||
"开票日期": "2023年02月03日"
|
||||
}
|
||||
]
|
||||
),
|
||||
]
|
||||
)
|
||||
async def test_generate_table(invoice_path: str, expected_result: List[dict]):
|
||||
invoice_path = os.path.abspath(os.path.join(os.getcwd(), invoice_path))
|
||||
filename = os.path.basename(invoice_path)
|
||||
ocr_result = await InvoiceOCR().run(file_path=Path(invoice_path), filename=filename)
|
||||
table_data = await GenerateTable().run(ocr_results=ocr_result, filename=filename)
|
||||
assert table_data == expected_result
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
@pytest.mark.parametrize(
|
||||
("invoice_path", "query", "expected_result"),
|
||||
[
|
||||
("../../data/invoices/invoice-1.pdf", "Invoicing date", "2023年02月03日")
|
||||
]
|
||||
)
|
||||
async def test_reply_question(invoice_path: str, query: dict, expected_result: str):
|
||||
invoice_path = os.path.abspath(os.path.join(os.getcwd(), invoice_path))
|
||||
filename = os.path.basename(invoice_path)
|
||||
ocr_result = await InvoiceOCR().run(file_path=Path(invoice_path), filename=filename)
|
||||
result = await ReplyQuestion().run(query=query, ocr_result=ocr_result)
|
||||
assert expected_result in result
|
||||
|
||||
106
tests/metagpt/roles/test_invoice_ocr_assistant.py
Normal file
106
tests/metagpt/roles/test_invoice_ocr_assistant.py
Normal file
|
|
@ -0,0 +1,106 @@
|
|||
#!/usr/bin/env python3
|
||||
# _*_ coding: utf-8 _*_
|
||||
|
||||
"""
|
||||
@Time : 2023/9/21 23:11:27
|
||||
@Author : Stitch-z
|
||||
@File : test_invoice_ocr_assistant.py
|
||||
"""
|
||||
|
||||
import os
|
||||
import pandas as pd
|
||||
from typing import List
|
||||
|
||||
import pytest
|
||||
|
||||
from metagpt.roles.invoice_ocr_assistant import InvoiceOCRAssistant
|
||||
from metagpt.schema import Message
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
@pytest.mark.parametrize(
|
||||
("query", "invoice_path", "invoice_table_path", "expected_result"),
|
||||
[
|
||||
(
|
||||
"Invoicing date",
|
||||
"../../data/invoices/invoice-1.pdf",
|
||||
"../../../data/invoice_table/invoice-1.xlsx",
|
||||
[
|
||||
{
|
||||
"收款人": "小明",
|
||||
"城市": "深圳市",
|
||||
"总费用/元": 412.00,
|
||||
"开票日期": "2023年02月03日"
|
||||
}
|
||||
]
|
||||
),
|
||||
(
|
||||
"Invoicing date",
|
||||
"../../data/invoices/invoice-2.png",
|
||||
"../../../data/invoice_table/invoice-2.xlsx",
|
||||
[
|
||||
{
|
||||
"收款人": "铁头",
|
||||
"城市": "广州市",
|
||||
"总费用/元": 898.00,
|
||||
"开票日期": "2023年03月17日"
|
||||
}
|
||||
]
|
||||
),
|
||||
(
|
||||
"Invoicing date",
|
||||
"../../data/invoices/invoice-3.jpg",
|
||||
"../../../data/invoice_table/invoice-3.xlsx",
|
||||
[
|
||||
{
|
||||
"收款人": "夏天",
|
||||
"城市": "福州市",
|
||||
"总费用/元": 2462.00,
|
||||
"开票日期": "2023年08月26日"
|
||||
}
|
||||
]
|
||||
),
|
||||
(
|
||||
"Invoicing date",
|
||||
"../../data/invoices/invoice-4.zip",
|
||||
"../../../data/invoice_table/invoice-4.xlsx",
|
||||
[
|
||||
{
|
||||
"收款人": "小明",
|
||||
"城市": "深圳市",
|
||||
"总费用/元": 412.00,
|
||||
"开票日期": "2023年02月03日"
|
||||
},
|
||||
{
|
||||
"收款人": "铁头",
|
||||
"城市": "广州市",
|
||||
"总费用/元": 898.00,
|
||||
"开票日期": "2023年03月17日"
|
||||
},
|
||||
{
|
||||
"收款人": "夏天",
|
||||
"城市": "福州市",
|
||||
"总费用/元": 2462.00,
|
||||
"开票日期": "2023年08月26日"
|
||||
}
|
||||
]
|
||||
),
|
||||
]
|
||||
)
|
||||
async def test_invoice_ocr_assistant(
|
||||
query: str,
|
||||
invoice_path: str,
|
||||
invoice_table_path: str,
|
||||
expected_result: List[dict]
|
||||
):
|
||||
invoice_path = os.path.abspath(os.path.join(os.getcwd(), invoice_path))
|
||||
role = InvoiceOCRAssistant()
|
||||
await role.run(Message(
|
||||
content=query,
|
||||
instruct_content={"file_path": invoice_path}
|
||||
))
|
||||
invoice_table_path = os.path.abspath(os.path.join(os.getcwd(), invoice_table_path))
|
||||
df = pd.read_excel(invoice_table_path)
|
||||
dict_result = df.to_dict(orient='records')
|
||||
assert dict_result == expected_result
|
||||
|
||||
|
|
@ -95,7 +95,7 @@ def test_parse_data():
|
|||
"""xxx xx""",
|
||||
list,
|
||||
None,
|
||||
Exception,
|
||||
[],
|
||||
),
|
||||
(
|
||||
"""xxx [1, 2, []xx""",
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue