mirror of
https://github.com/FoundationAgents/MetaGPT.git
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feat: merge geekan:dev
This commit is contained in:
莘权 马
commit
1df853158b
9 changed files with 140 additions and 457 deletions
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@ -1,58 +1,61 @@
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# #!/usr/bin/env python3
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# # _*_ coding: utf-8 _*_
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#
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# """
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# @Time : 2023/10/09 18:40:34
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# @Author : Stitch-z
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# @File : test_invoice_ocr.py
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# """
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#
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# import os
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# from pathlib import Path
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#
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# import pytest
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#
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# from metagpt.actions.invoice_ocr import GenerateTable, InvoiceOCR, ReplyQuestion
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#
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#
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# @pytest.mark.asyncio
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# @pytest.mark.parametrize(
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# "invoice_path",
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# [
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# "../../data/invoices/invoice-3.jpg",
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# "../../data/invoices/invoice-4.zip",
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# ],
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# )
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# async def test_invoice_ocr(invoice_path: str):
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# invoice_path = os.path.abspath(os.path.join(os.getcwd(), invoice_path))
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# filename = os.path.basename(invoice_path)
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# resp = await InvoiceOCR().run(file_path=Path(invoice_path), filename=filename)
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# assert isinstance(resp, list)
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#
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#
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# @pytest.mark.asyncio
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# @pytest.mark.parametrize(
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# ("invoice_path", "expected_result"),
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# [
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# ("../../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"}]),
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# ],
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# )
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# async def test_generate_table(invoice_path: str, expected_result: list[dict]):
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# invoice_path = os.path.abspath(os.path.join(os.getcwd(), invoice_path))
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# filename = os.path.basename(invoice_path)
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# ocr_result = await InvoiceOCR().run(file_path=Path(invoice_path), filename=filename)
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# table_data = await GenerateTable().run(ocr_results=ocr_result, filename=filename)
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# assert table_data == expected_result
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#
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#
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# @pytest.mark.asyncio
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# @pytest.mark.parametrize(
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# ("invoice_path", "query", "expected_result"),
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# [("../../data/invoices/invoice-1.pdf", "Invoicing date", "2023年02月03日")],
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# )
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# async def test_reply_question(invoice_path: str, query: dict, expected_result: str):
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# invoice_path = os.path.abspath(os.path.join(os.getcwd(), invoice_path))
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# filename = os.path.basename(invoice_path)
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# ocr_result = await InvoiceOCR().run(file_path=Path(invoice_path), filename=filename)
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# result = await ReplyQuestion().run(query=query, ocr_result=ocr_result)
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# assert expected_result in result
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#!/usr/bin/env python3
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# _*_ coding: utf-8 _*_
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"""
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@Time : 2023/10/09 18:40:34
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@Author : Stitch-z
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@File : test_invoice_ocr.py
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"""
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import json
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import os
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from pathlib import Path
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import pytest
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from metagpt.actions.invoice_ocr import GenerateTable, InvoiceOCR, ReplyQuestion
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@pytest.mark.asyncio
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@pytest.mark.parametrize(
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"invoice_path",
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[
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"../../data/invoices/invoice-3.jpg",
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"../../data/invoices/invoice-4.zip",
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],
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)
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async def test_invoice_ocr(invoice_path: str):
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invoice_path = os.path.abspath(os.path.join(os.getcwd(), invoice_path))
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filename = os.path.basename(invoice_path)
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resp = await InvoiceOCR().run(file_path=Path(invoice_path), filename=filename)
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assert isinstance(resp, list)
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@pytest.mark.asyncio
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@pytest.mark.parametrize(
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("invoice_path", "expected_result"),
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[
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(
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"../../data/invoices/invoice-1.pdf",
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[{"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"}]
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),
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],
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)
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async def test_generate_table(invoice_path: str, expected_result: list[dict]):
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invoice_path = os.path.abspath(os.path.join(os.getcwd(), invoice_path))
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filename = os.path.basename(invoice_path)
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ocr_result = await InvoiceOCR().run(file_path=Path(invoice_path), filename=filename)
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table_data = await GenerateTable().run(ocr_results=ocr_result, filename=filename)
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assert json.dumps(table_data) == json.dumps(expected_result)
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@pytest.mark.asyncio
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@pytest.mark.parametrize(
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("invoice_path", "query", "expected_result"),
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[("../../data/invoices/invoice-1.pdf", "Invoicing date", "2023年02月03日")],
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)
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async def test_reply_question(invoice_path: str, query: dict, expected_result: str):
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invoice_path = os.path.abspath(os.path.join(os.getcwd(), invoice_path))
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filename = os.path.basename(invoice_path)
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ocr_result = await InvoiceOCR().run(file_path=Path(invoice_path), filename=filename)
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result = await ReplyQuestion().run(query=query, ocr_result=ocr_result)
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assert expected_result in result
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@ -51,3 +51,13 @@ async def test_zhipuai_acompletion(mocker):
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resp = await zhipu_gpt.aask(prompt_msg)
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assert resp == resp_content
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def test_zhipuai_proxy(mocker):
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import openai
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from metagpt.config import CONFIG
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CONFIG.openai_proxy = "http://127.0.0.1:8080"
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_ = ZhiPuAIGPTAPI()
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assert openai.proxy == CONFIG.openai_proxy
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@ -1,63 +1,59 @@
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# #!/usr/bin/env python3
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# # _*_ coding: utf-8 _*_
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#
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# """
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# @Time : 2023/9/21 23:11:27
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# @Author : Stitch-z
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# @File : test_invoice_ocr_assistant.py
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# """
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#
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# import json
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# from pathlib import Path
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#
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# import pandas as pd
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# import pytest
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#
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# from metagpt.roles.invoice_ocr_assistant import InvoiceOCRAssistant, InvoicePath
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# from metagpt.schema import Message
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#
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#
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# @pytest.mark.asyncio
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# @pytest.mark.parametrize(
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# ("query", "invoice_path", "invoice_table_path", "expected_result"),
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# [
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# (
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# "Invoicing date",
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# Path("../../data/invoices/invoice-1.pdf"),
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# Path("../../../data/invoice_table/invoice-1.xlsx"),
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# [{"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"}],
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# ),
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# (
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# "Invoicing date",
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# Path("../../data/invoices/invoice-2.png"),
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# Path("../../../data/invoice_table/invoice-2.xlsx"),
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# [{"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"}],
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# ),
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# (
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# "Invoicing date",
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# Path("../../data/invoices/invoice-3.jpg"),
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# Path("../../../data/invoice_table/invoice-3.xlsx"),
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# [{"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"}],
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# ),
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# (
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# "Invoicing date",
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# Path("../../data/invoices/invoice-4.zip"),
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# Path("../../../data/invoice_table/invoice-4.xlsx"),
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# [
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# {"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"},
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# {"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"},
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# {"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"},
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# ],
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# ),
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# ],
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# )
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# async def test_invoice_ocr_assistant(
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# query: str, invoice_path: Path, invoice_table_path: Path, expected_result: list[dict]
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# ):
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# invoice_path = Path.cwd() / invoice_path
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# role = InvoiceOCRAssistant()
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# await role.run(Message(content=query, instruct_content=InvoicePath(file_path=invoice_path)))
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# invoice_table_path = Path.cwd() / invoice_table_path
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# df = pd.read_excel(invoice_table_path)
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# dict_result = df.to_dict(orient="records")
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# assert json.dumps(dict_result) == json.dumps(expected_result)
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#!/usr/bin/env python3
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# _*_ coding: utf-8 _*_
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"""
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@Time : 2023/9/21 23:11:27
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@Author : Stitch-z
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@File : test_invoice_ocr_assistant.py
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"""
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from pathlib import Path
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import pandas as pd
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import pytest
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from metagpt.roles.invoice_ocr_assistant import InvoiceOCRAssistant, InvoicePath
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from metagpt.schema import Message
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@pytest.mark.asyncio
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@pytest.mark.parametrize(
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("query", "invoice_path", "invoice_table_path", "expected_result"),
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[
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(
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"Invoicing date",
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Path("../../data/invoices/invoice-1.pdf"),
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Path("../../../data/invoice_table/invoice-1.xlsx"),
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{"收款人": "小明", "城市": "深圳", "总费用/元": 412.00, "开票日期": "2023年02月03日"},
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),
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(
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"Invoicing date",
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Path("../../data/invoices/invoice-2.png"),
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Path("../../../data/invoice_table/invoice-2.xlsx"),
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{"收款人": "铁头", "城市": "广州", "总费用/元": 898.00, "开票日期": "2023年03月17日"},
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),
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(
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"Invoicing date",
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Path("../../data/invoices/invoice-3.jpg"),
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Path("../../../data/invoice_table/invoice-3.xlsx"),
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{"收款人": "夏天", "城市": "福州", "总费用/元": 2462.00, "开票日期": "2023年08月26日"},
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)
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],
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)
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async def test_invoice_ocr_assistant(
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query: str, invoice_path: Path, invoice_table_path: Path, expected_result: dict
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):
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invoice_path = Path.cwd() / invoice_path
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role = InvoiceOCRAssistant()
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await role.run(Message(content=query, instruct_content=InvoicePath(file_path=invoice_path)))
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invoice_table_path = Path.cwd() / invoice_table_path
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df = pd.read_excel(invoice_table_path)
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resp = df.to_dict(orient="records")
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assert isinstance(resp, list)
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assert len(resp) == 1
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resp = resp[0]
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assert expected_result["收款人"] == resp["收款人"]
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assert expected_result["城市"] in resp["城市"]
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assert int(expected_result["总费用/元"]) == int(resp["总费用/元"])
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assert expected_result["开票日期"] == resp["开票日期"]
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@ -6,7 +6,7 @@
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@File : test_tutorial_assistant.py
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"""
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import shutil
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import aiofiles
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import pytest
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from metagpt.const import TUTORIAL_PATH
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@ -14,20 +14,17 @@ from metagpt.roles.tutorial_assistant import TutorialAssistant
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@pytest.mark.asyncio
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@pytest.mark.parametrize(("language", "topic"), [("Chinese", "Write a tutorial about Python")])
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@pytest.mark.parametrize(("language", "topic"), [("Chinese", "Write a tutorial about pip")])
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async def test_tutorial_assistant(language: str, topic: str):
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shutil.rmtree(path=TUTORIAL_PATH, ignore_errors=True)
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topic = "Write a tutorial about MySQL"
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role = TutorialAssistant(language=language)
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msg = await role.run(topic)
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assert "MySQL" in msg.content
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assert TUTORIAL_PATH.exists()
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# filename = msg.content
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# title = filename.split("/")[-1].split(".")[0]
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# async with aiofiles.open(filename, mode="r") as reader:
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# content = await reader.read()
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# assert content.startswith(f"# {title}")
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filename = msg.content
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async with aiofiles.open(filename, mode="r", encoding="utf-8") as reader:
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content = await reader.read()
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assert "pip" in content
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if __name__ == "__main__":
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@ -1,53 +0,0 @@
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#!/usr/bin/env python
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# -*- coding: utf-8 -*-
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"""
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@Time :
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@Author :
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@File : test_code_interpreter.py
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@Warning : open-interpreter 0.1.17 requires openai<0.29.0,>=0.28.0, but you have openai 1.6.0 which is incompatible.
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open-interpreter 0.1.17 requires tiktoken<0.5.0,>=0.4.0, but you have tiktoken 0.5.2 which is incompatible.
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"""
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# from pathlib import Path
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#
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# import pandas as pd
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# import pytest
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#
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# from metagpt.actions import Action
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# from metagpt.logs import logger
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# from metagpt.tools.code_interpreter import OpenCodeInterpreter, OpenInterpreterDecorator
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#
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# logger.add("./tests/data/test_ci.log")
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# stock = "./tests/data/baba_stock.csv"
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#
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#
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# # TODO: 需要一种表格数据格式，能够支持schame管理的，标注字段类型和字段含义。
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# class CreateStockIndicators(Action):
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# @OpenInterpreterDecorator(save_code=True, code_file_path="./tests/data/stock_indicators.py")
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# async def run(self, stock_path: str, indicators=["Simple Moving Average", "BollingerBands"]) -> pd.DataFrame:
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# """对stock_path中的股票数据, 使用pandas和ta计算indicators中的技术指标, 返回带有技术指标的股票数据，不需要去除空值, 不需要安装任何包；
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# 指标生成对应的三列: SMA, BB_upper, BB_lower
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# """
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# ...
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#
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#
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# @pytest.mark.asyncio
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# async def test_actions():
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# # 计算指标
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# indicators = ["Simple Moving Average", "BollingerBands"]
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# stocker = CreateStockIndicators()
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# df, msg = await stocker.run(stock, indicators=indicators)
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# assert isinstance(df, pd.DataFrame)
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# assert "Close" in df.columns
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# assert "Date" in df.columns
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# # 将df保存为文件，将文件路径传入到下一个action
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# df_path = "./tests/data/stock_indicators.csv"
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# df.to_csv(df_path)
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# assert Path(df_path).is_file()
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# # 可视化指标结果
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# figure_path = "./tests/data/figure_ci.png"
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# ci_ploter = OpenCodeInterpreter()
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# ci_ploter.chat(
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# f"使用seaborn对{df_path}中与股票布林带有关的数据列的Date, Close, SMA, BB_upper（布林带上界）, BB_lower（布林带下界）进行可视化, 可视化图片保存在{figure_path}中。不需要任何指标计算，把Date列转换为日期类型。要求图片优美，BB_upper, BB_lower之间使用合适的颜色填充。"
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# )
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# assert Path(figure_path).is_file()
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