diff --git a/metagpt/actions/clone_function.py b/metagpt/actions/clone_function.py
deleted file mode 100644
index 7053df97b..000000000
--- a/metagpt/actions/clone_function.py
+++ /dev/null
@@ -1,67 +0,0 @@
-from pathlib import Path
-
-from pydantic import Field
-
-from metagpt.actions.write_code import WriteCode
-from metagpt.llm import LLM
-from metagpt.logs import logger
-from metagpt.provider.base_llm import BaseLLM
-from metagpt.schema import Message
-from metagpt.utils.exceptions import handle_exception
-from metagpt.utils.highlight import highlight
-
-CLONE_PROMPT = """
-*context*
-Please convert the function code ```{source_code}``` into the the function format: ```{template_func}```.
-*Please Write code based on the following list and context*
-1. Write code start with ```, and end with ```.
-2. Please implement it in one function if possible, except for import statements. for exmaple:
-```python
-import pandas as pd
-def run(*args) -> pd.DataFrame:
-    ...
-```
-3. Do not use public member functions that do not exist in your design.
-4. The output function name, input parameters and return value must be the same as ```{template_func}```.
-5. Make sure the results before and after the code conversion are required to be exactly the same.
-6. Don't repeat my context in your replies.
-7. Return full results, for example, if the return value has df.head(), please return df.
-8. If you must use a third-party package, use the most popular ones, for example: pandas, numpy, ta, ...
-"""
-
-
-class CloneFunction(WriteCode):
-    name: str = "CloneFunction"
-    context: list[Message] = []
-    llm: BaseLLM = Field(default_factory=LLM)
-
-    def _save(self, code_path, code):
-        if isinstance(code_path, str):
-            code_path = Path(code_path)
-        code_path.parent.mkdir(parents=True, exist_ok=True)
-        code_path.write_text(code, encoding="utf-8")
-        logger.info(f"Saving Code to {code_path}")
-
-    async def run(self, template_func: str, source_code: str) -> str:
-        """将source_code转换成template_func一样的入参和返回类型"""
-        prompt = CLONE_PROMPT.format(source_code=source_code, template_func=template_func)
-        logger.info(f"query for CloneFunction: \n {prompt}")
-        code = await self.write_code(prompt)
-        logger.info(f"CloneFunction code is \n {highlight(code)}")
-        return code
-
-
-@handle_exception
-def run_function_code(func_code: str, func_name: str, *args, **kwargs):
-    """Run function code from string code."""
-    locals_ = {}
-    exec(func_code, locals_)
-    func = locals_[func_name]
-    return func(*args, **kwargs), ""
-
-
-def run_function_script(code_script_path: str, func_name: str, *args, **kwargs):
-    """Run function code from script."""
-    code_path = Path(code_script_path)
-    code = code_path.read_text(encoding="utf-8")
-    return run_function_code(code, func_name, *args, **kwargs)
diff --git a/metagpt/provider/zhipuai_api.py b/metagpt/provider/zhipuai_api.py
index e4b066a0c..df8c330b8 100644
--- a/metagpt/provider/zhipuai_api.py
+++ b/metagpt/provider/zhipuai_api.py
@@ -49,6 +49,9 @@ class ZhiPuAIGPTAPI(BaseLLM):
         zhipuai.api_key = config.zhipuai_api_key
         # due to use openai sdk, set the api_key but it will't be used.
         # openai.api_key = zhipuai.api_key  # due to use openai sdk, set the api_key but it will't be used.
+        if config.openai_proxy:
+            # FIXME: openai v1.x sdk has no proxy support
+            openai.proxy = config.openai_proxy
 
     def _const_kwargs(self, messages: list[dict]) -> dict:
         kwargs = {"model": self.model, "prompt": messages, "temperature": 0.3}
diff --git a/metagpt/roles/tutorial_assistant.py b/metagpt/roles/tutorial_assistant.py
index 5d1323371..bedf8b3be 100644
--- a/metagpt/roles/tutorial_assistant.py
+++ b/metagpt/roles/tutorial_assistant.py
@@ -90,4 +90,5 @@ class TutorialAssistant(Role):
         msg = await super().react()
         root_path = TUTORIAL_PATH / datetime.now().strftime("%Y-%m-%d_%H-%M-%S")
         await File.write(root_path, f"{self.main_title}.md", self.total_content.encode("utf-8"))
+        msg.content = str(root_path / f"{self.main_title}.md")
         return msg
diff --git a/metagpt/tools/code_interpreter.py b/metagpt/tools/code_interpreter.py
deleted file mode 100644
index 5592b0704..000000000
--- a/metagpt/tools/code_interpreter.py
+++ /dev/null
@@ -1,207 +0,0 @@
-#!/usr/bin/env python
-# -*- coding: utf-8 -*-
-"""
-@Time    :
-@Author  :
-@File    : code_interpreter.py
-@Warning : open-interpreter 0.1.17 requires openai<0.29.0,>=0.28.0, but you have openai 1.6.0 which is incompatible.
-           open-interpreter 0.1.17 requires tiktoken<0.5.0,>=0.4.0, but you have tiktoken 0.5.2 which is incompatible.
-"""
-
-# import inspect
-# import re
-# import textwrap
-# from pathlib import Path
-# from typing import Callable, Dict, List
-#
-# import wrapt
-# from interpreter.core.core import Interpreter
-#
-# from metagpt.actions.clone_function import (
-#     CloneFunction,
-#     run_function_code,
-#     run_function_script,
-# )
-# from metagpt.config import CONFIG
-# from metagpt.logs import logger
-# from metagpt.utils.highlight import highlight
-#
-#
-# def extract_python_code(code: str):
-#     """Extract code blocks: If the code comments are the same, only the last code block is kept."""
-#     # Use regular expressions to match comment blocks and related code.
-#     pattern = r"(#\s[^\n]*)\n(.*?)(?=\n\s*#|$)"
-#     matches = re.findall(pattern, code, re.DOTALL)
-#
-#     # Extract the last code block when encountering the same comment.
-#     unique_comments = {}
-#     for comment, code_block in matches:
-#         unique_comments[comment] = code_block
-#
-#     # concatenate into functional form
-#     result_code = "\n".join([f"{comment}\n{code_block}" for comment, code_block in unique_comments.items()])
-#     header_code = code[: code.find("#")]
-#     code = header_code + result_code
-#
-#     logger.info(f"Extract python code: \n {highlight(code)}")
-#
-#     return code
-#
-#
-# class OpenCodeInterpreter(object):
-#     """https://github.com/KillianLucas/open-interpreter"""
-#
-#     def __init__(self, auto_run: bool = True) -> None:
-#         interpreter = Interpreter()
-#         interpreter.auto_run = auto_run
-#         interpreter.model = CONFIG.openai_api_model or "gpt-3.5-turbo"
-#         interpreter.api_key = CONFIG.openai_api_key
-#         self.interpreter = interpreter
-#
-#     def chat(self, query: str, reset: bool = True):
-#         if reset:
-#             self.interpreter.reset()
-#         return self.interpreter.chat(query)
-#
-#     @staticmethod
-#     def extract_function(
-#         query_respond: List, function_name: str, *, language: str = "python", function_format: str = None
-#     ) -> str:
-#         """create a function from query_respond."""
-#         if language not in ("python"):
-#             raise NotImplementedError(f"Not support to parse language {language}!")
-#
-#         # set function form
-#         if function_format is None:
-#             assert language == "python", f"Expect python language for default function_format, but got {language}."
-#             function_format = """def {function_name}():\n{code}"""
-#         # Extract the code module in the open-interpreter respond message.
-#         # The query_respond of open-interpreter before v0.1.4 is:
-#         # [{'role': 'user', 'content': your query string},
-#         #  {'role': 'assistant', 'content': plan from llm, 'function_call': {
-#         #   "name": "run_code",  "arguments": "{"language": "python", "code": code of first plan},
-#         #   "parsed_arguments": {"language": "python", "code": code of first plan}
-#         #  ...]
-#         if "function_call" in query_respond[1]:
-#             code = [
-#                 item["function_call"]["parsed_arguments"]["code"]
-#                 for item in query_respond
-#                 if "function_call" in item
-#                 and "parsed_arguments" in item["function_call"]
-#                 and "language" in item["function_call"]["parsed_arguments"]
-#                 and item["function_call"]["parsed_arguments"]["language"] == language
-#             ]
-#         # The query_respond of open-interpreter v0.1.7 is:
-#         # [{'role': 'user', 'message': your query string},
-#         #  {'role': 'assistant', 'message': plan from llm, 'language': 'python',
-#         #   'code': code of first plan, 'output': output of first plan code},
-#         #  ...]
-#         elif "code" in query_respond[1]:
-#             code = [
-#                 item["code"]
-#                 for item in query_respond
-#                 if "code" in item and "language" in item and item["language"] == language
-#             ]
-#         else:
-#             raise ValueError(f"Unexpect message format in query_respond: {query_respond[1].keys()}")
-#         # add indent.
-#         indented_code_str = textwrap.indent("\n".join(code), " " * 4)
-#         # Return the code after deduplication.
-#         if language == "python":
-#             return extract_python_code(function_format.format(function_name=function_name, code=indented_code_str))
-#
-#
-# def gen_query(func: Callable, args, kwargs) -> str:
-#     # Get the annotation of the function as part of the query.
-#     desc = func.__doc__
-#     signature = inspect.signature(func)
-#     # Get the signature of the wrapped function and the assignment of the input parameters as part of the query.
-#     bound_args = signature.bind(*args, **kwargs)
-#     bound_args.apply_defaults()
-#     query = f"{desc}, {bound_args.arguments}, If you must use a third-party package, use the most popular ones, for example: pandas, numpy, ta, ..."
-#     return query
-#
-#
-# def gen_template_fun(func: Callable) -> str:
-#     return f"def {func.__name__}{str(inspect.signature(func))}\n    # here is your code ..."
-#
-#
-# class OpenInterpreterDecorator(object):
-#     def __init__(self, save_code: bool = False, code_file_path: str = None, clear_code: bool = False) -> None:
-#         self.save_code = save_code
-#         self.code_file_path = code_file_path
-#         self.clear_code = clear_code
-#
-#     def _have_code(self, rsp: List[Dict]):
-#         # Is there any code generated?
-#         return "code" in rsp[1] and rsp[1]["code"] not in ("", None)
-#
-#     def _is_faild_plan(self, rsp: List[Dict]):
-#         # is faild plan?
-#         func_code = OpenCodeInterpreter.extract_function(rsp, "function")
-#         # If there is no more than 1 '\n', the plan execution fails.
-#         if isinstance(func_code, str) and func_code.count("\n") <= 1:
-#             return True
-#         return False
-#
-#     def _check_respond(self, query: str, interpreter: OpenCodeInterpreter, respond: List[Dict], max_try: int = 3):
-#         for _ in range(max_try):
-#             # TODO: If no code or faild plan is generated, execute chat again, repeating no more than max_try times.
-#             if self._have_code(respond) and not self._is_faild_plan(respond):
-#                 break
-#             elif not self._have_code(respond):
-#                 logger.warning(f"llm did not return executable code, resend the query: \n{query}")
-#                 respond = interpreter.chat(query)
-#             elif self._is_faild_plan(respond):
-#                 logger.warning(f"llm did not generate successful plan, resend the query: \n{query}")
-#                 respond = interpreter.chat(query)
-#
-#         # Post-processing of respond
-#         if not self._have_code(respond):
-#             error_msg = f"OpenCodeInterpreter do not generate code for query: \n{query}"
-#             logger.error(error_msg)
-#             raise ValueError(error_msg)
-#
-#         if self._is_faild_plan(respond):
-#             error_msg = f"OpenCodeInterpreter do not generate code for query: \n{query}"
-#             logger.error(error_msg)
-#             raise ValueError(error_msg)
-#         return respond
-#
-#     def __call__(self, wrapped):
-#         @wrapt.decorator
-#         async def wrapper(wrapped: Callable, instance, args, kwargs):
-#             # Get the decorated function name.
-#             func_name = wrapped.__name__
-#             # If the script exists locally and clearcode is not required, execute the function from the script.
-#             if self.code_file_path and Path(self.code_file_path).is_file() and not self.clear_code:
-#                 return run_function_script(self.code_file_path, func_name, *args, **kwargs)
-#
-#             # Auto run generate code by using open-interpreter.
-#             interpreter = OpenCodeInterpreter()
-#             query = gen_query(wrapped, args, kwargs)
-#             logger.info(f"query for OpenCodeInterpreter: \n {query}")
-#             respond = interpreter.chat(query)
-#             # Make sure the response is as expected.
-#             respond = self._check_respond(query, interpreter, respond, 3)
-#             # Assemble the code blocks generated by open-interpreter into a function without parameters.
-#             func_code = interpreter.extract_function(respond, func_name)
-#             # Clone the `func_code` into wrapped, that is,
-#             # keep the `func_code` and wrapped functions with the same input parameter and return value types.
-#             template_func = gen_template_fun(wrapped)
-#             cf = CloneFunction()
-#             code = await cf.run(template_func=template_func, source_code=func_code)
-#             # Display the generated function in the terminal.
-#             logger_code = highlight(code, "python")
-#             logger.info(f"Creating following Python function:\n{logger_code}")
-#             # execute this function.
-#             try:
-#                 res = run_function_code(code, func_name, *args, **kwargs)
-#                 if self.save_code and self.code_file_path:
-#                     cf._save(self.code_file_path, code)
-#             except Exception as e:
-#                 logger.error(f"Could not evaluate Python code \n{logger_code}: \nError: {e}")
-#                 raise Exception("Could not evaluate Python code", e)
-#             return res
-#
-#         return wrapper(wrapped)
diff --git a/tests/metagpt/actions/test_invoice_ocr.py b/tests/metagpt/actions/test_invoice_ocr.py
index ddadda7e6..b3b93cf9f 100644
--- a/tests/metagpt/actions/test_invoice_ocr.py
+++ b/tests/metagpt/actions/test_invoice_ocr.py
@@ -1,58 +1,61 @@
-# #!/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
-#
-# import pytest
-#
-# from metagpt.actions.invoice_ocr import GenerateTable, InvoiceOCR, 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
+#!/usr/bin/env python3
+# _*_ coding: utf-8 _*_
+
+"""
+@Time    : 2023/10/09 18:40:34
+@Author  : Stitch-z
+@File    : test_invoice_ocr.py
+"""
+import json
+import os
+from pathlib import Path
+
+import pytest
+
+from metagpt.actions.invoice_ocr import GenerateTable, InvoiceOCR, 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 json.dumps(table_data) == json.dumps(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
diff --git a/tests/metagpt/provider/test_zhipuai_api.py b/tests/metagpt/provider/test_zhipuai_api.py
index d9cd23281..06f2cba62 100644
--- a/tests/metagpt/provider/test_zhipuai_api.py
+++ b/tests/metagpt/provider/test_zhipuai_api.py
@@ -51,3 +51,13 @@ async def test_zhipuai_acompletion(mocker):
 
     resp = await zhipu_gpt.aask(prompt_msg)
     assert resp == resp_content
+
+
+def test_zhipuai_proxy(mocker):
+    import openai
+
+    from metagpt.config import CONFIG
+
+    CONFIG.openai_proxy = "http://127.0.0.1:8080"
+    _ = ZhiPuAIGPTAPI()
+    assert openai.proxy == CONFIG.openai_proxy
diff --git a/tests/metagpt/roles/test_invoice_ocr_assistant.py b/tests/metagpt/roles/test_invoice_ocr_assistant.py
index e90182dde..48abb9eb8 100644
--- a/tests/metagpt/roles/test_invoice_ocr_assistant.py
+++ b/tests/metagpt/roles/test_invoice_ocr_assistant.py
@@ -1,63 +1,59 @@
-# #!/usr/bin/env python3
-# # _*_ coding: utf-8 _*_
-#
-# """
-# @Time    : 2023/9/21 23:11:27
-# @Author  : Stitch-z
-# @File    : test_invoice_ocr_assistant.py
-# """
-#
-# import json
-# from pathlib import Path
-#
-# import pandas as pd
-# import pytest
-#
-# from metagpt.roles.invoice_ocr_assistant import InvoiceOCRAssistant, InvoicePath
-# from metagpt.schema import Message
-#
-#
-# @pytest.mark.asyncio
-# @pytest.mark.parametrize(
-#     ("query", "invoice_path", "invoice_table_path", "expected_result"),
-#     [
-#         (
-#             "Invoicing date",
-#             Path("../../data/invoices/invoice-1.pdf"),
-#             Path("../../../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",
-#             Path("../../data/invoices/invoice-2.png"),
-#             Path("../../../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",
-#             Path("../../data/invoices/invoice-3.jpg"),
-#             Path("../../../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",
-#             Path("../../data/invoices/invoice-4.zip"),
-#             Path("../../../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: Path, invoice_table_path: Path, expected_result: list[dict]
-# ):
-#     invoice_path = Path.cwd() / invoice_path
-#     role = InvoiceOCRAssistant()
-#     await role.run(Message(content=query, instruct_content=InvoicePath(file_path=invoice_path)))
-#     invoice_table_path = Path.cwd() / invoice_table_path
-#     df = pd.read_excel(invoice_table_path)
-#     dict_result = df.to_dict(orient="records")
-#     assert json.dumps(dict_result) == json.dumps(expected_result)
+#!/usr/bin/env python3
+# _*_ coding: utf-8 _*_
+
+"""
+@Time    : 2023/9/21 23:11:27
+@Author  : Stitch-z
+@File    : test_invoice_ocr_assistant.py
+"""
+
+from pathlib import Path
+
+import pandas as pd
+import pytest
+
+from metagpt.roles.invoice_ocr_assistant import InvoiceOCRAssistant, InvoicePath
+from metagpt.schema import Message
+
+
+@pytest.mark.asyncio
+@pytest.mark.parametrize(
+    ("query", "invoice_path", "invoice_table_path", "expected_result"),
+    [
+        (
+            "Invoicing date",
+            Path("../../data/invoices/invoice-1.pdf"),
+            Path("../../../data/invoice_table/invoice-1.xlsx"),
+            {"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"},
+        ),
+        (
+            "Invoicing date",
+            Path("../../data/invoices/invoice-2.png"),
+            Path("../../../data/invoice_table/invoice-2.xlsx"),
+            {"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"},
+        ),
+        (
+            "Invoicing date",
+            Path("../../data/invoices/invoice-3.jpg"),
+            Path("../../../data/invoice_table/invoice-3.xlsx"),
+            {"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"},
+        )
+    ],
+)
+async def test_invoice_ocr_assistant(
+    query: str, invoice_path: Path, invoice_table_path: Path, expected_result: dict
+):
+    invoice_path = Path.cwd() / invoice_path
+    role = InvoiceOCRAssistant()
+    await role.run(Message(content=query, instruct_content=InvoicePath(file_path=invoice_path)))
+    invoice_table_path = Path.cwd() / invoice_table_path
+    df = pd.read_excel(invoice_table_path)
+    resp = df.to_dict(orient="records")
+    assert isinstance(resp, list)
+    assert len(resp) == 1
+    resp = resp[0]
+    assert expected_result["收款人"] == resp["收款人"]
+    assert expected_result["城市"] in resp["城市"]
+    assert int(expected_result["总费用/元"]) == int(resp["总费用/元"])
+    assert expected_result["开票日期"] == resp["开票日期"]
+
diff --git a/tests/metagpt/roles/test_tutorial_assistant.py b/tests/metagpt/roles/test_tutorial_assistant.py
index 3158a5fc1..4455e1bf6 100644
--- a/tests/metagpt/roles/test_tutorial_assistant.py
+++ b/tests/metagpt/roles/test_tutorial_assistant.py
@@ -6,7 +6,7 @@
 @File    : test_tutorial_assistant.py
 """
 import shutil
-
+import aiofiles
 import pytest
 
 from metagpt.const import TUTORIAL_PATH
@@ -14,20 +14,17 @@ from metagpt.roles.tutorial_assistant import TutorialAssistant
 
 
 @pytest.mark.asyncio
-@pytest.mark.parametrize(("language", "topic"), [("Chinese", "Write a tutorial about Python")])
+@pytest.mark.parametrize(("language", "topic"), [("Chinese", "Write a tutorial about pip")])
 async def test_tutorial_assistant(language: str, topic: str):
     shutil.rmtree(path=TUTORIAL_PATH, ignore_errors=True)
 
-    topic = "Write a tutorial about MySQL"
     role = TutorialAssistant(language=language)
     msg = await role.run(topic)
-    assert "MySQL" in msg.content
     assert TUTORIAL_PATH.exists()
-    # filename = msg.content
-    # title = filename.split("/")[-1].split(".")[0]
-    # async with aiofiles.open(filename, mode="r") as reader:
-    #     content = await reader.read()
-    #     assert content.startswith(f"# {title}")
+    filename = msg.content
+    async with aiofiles.open(filename, mode="r", encoding="utf-8") as reader:
+        content = await reader.read()
+        assert "pip" in content
 
 
 if __name__ == "__main__":
diff --git a/tests/metagpt/tools/test_code_interpreter.py b/tests/metagpt/tools/test_code_interpreter.py
deleted file mode 100644
index 71df6315b..000000000
--- a/tests/metagpt/tools/test_code_interpreter.py
+++ /dev/null
@@ -1,53 +0,0 @@
-#!/usr/bin/env python
-# -*- coding: utf-8 -*-
-"""
-@Time    :
-@Author  :
-@File    : test_code_interpreter.py
-@Warning : open-interpreter 0.1.17 requires openai<0.29.0,>=0.28.0, but you have openai 1.6.0 which is incompatible.
-           open-interpreter 0.1.17 requires tiktoken<0.5.0,>=0.4.0, but you have tiktoken 0.5.2 which is incompatible.
-"""
-
-# from pathlib import Path
-#
-# import pandas as pd
-# import pytest
-#
-# from metagpt.actions import Action
-# from metagpt.logs import logger
-# from metagpt.tools.code_interpreter import OpenCodeInterpreter, OpenInterpreterDecorator
-#
-# logger.add("./tests/data/test_ci.log")
-# stock = "./tests/data/baba_stock.csv"
-#
-#
-# # 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。
-# class CreateStockIndicators(Action):
-#     @OpenInterpreterDecorator(save_code=True, code_file_path="./tests/data/stock_indicators.py")
-#     async def run(self, stock_path: str, indicators=["Simple Moving Average", "BollingerBands"]) -> pd.DataFrame:
-#         """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；
-#         指标生成对应的三列: SMA, BB_upper, BB_lower
-#         """
-#         ...
-#
-#
-# @pytest.mark.asyncio
-# async def test_actions():
-#     # 计算指标
-#     indicators = ["Simple Moving Average", "BollingerBands"]
-#     stocker = CreateStockIndicators()
-#     df, msg = await stocker.run(stock, indicators=indicators)
-#     assert isinstance(df, pd.DataFrame)
-#     assert "Close" in df.columns
-#     assert "Date" in df.columns
-#     # 将df保存为文件，将文件路径传入到下一个action
-#     df_path = "./tests/data/stock_indicators.csv"
-#     df.to_csv(df_path)
-#     assert Path(df_path).is_file()
-#     # 可视化指标结果
-#     figure_path = "./tests/data/figure_ci.png"
-#     ci_ploter = OpenCodeInterpreter()
-#     ci_ploter.chat(
-#         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。"
-#     )
-#     assert Path(figure_path).is_file()