autogen/test/agentchat/contrib/test_gpt_assistant.py
KazooTTT a122ffe541
Fix/typo (#1034)
* fix: typo

* fix: typo

* fix: typo of function name

* fix: typo of function name of test file

* Update test_token_count.py

---------

Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
2023-12-22 16:00:46 +00:00

255 lines
8.3 KiB
Python

import pytest
import os
import sys
import autogen
from autogen import OpenAIWrapper
sys.path.append(os.path.join(os.path.dirname(__file__), ".."))
from test_assistant_agent import KEY_LOC, OAI_CONFIG_LIST # noqa: E402
try:
import openai
from autogen.agentchat.contrib.gpt_assistant_agent import GPTAssistantAgent
from autogen.oai.openai_utils import retrieve_assistants_by_name
skip_test = False
except ImportError:
skip_test = True
config_list = autogen.config_list_from_json(
OAI_CONFIG_LIST, file_location=KEY_LOC, filter_dict={"api_type": ["openai"]}
)
def ask_ossinsight(question):
return f"That is a good question, but I don't know the answer yet. Please ask your human developer friend to help you. \n\n{question}"
@pytest.mark.skipif(
sys.platform in ["darwin", "win32"] or skip_test,
reason="do not run on MacOS or windows or dependency is not installed",
)
def test_gpt_assistant_chat():
ossinsight_api_schema = {
"name": "ossinsight_data_api",
"parameters": {
"type": "object",
"properties": {
"question": {
"type": "string",
"description": "Enter your GitHub data question in the form of a clear and specific question to ensure the returned data is accurate and valuable. For optimal results, specify the desired format for the data table in your request.",
}
},
"required": ["question"],
},
"description": "This is an API endpoint allowing users (analysts) to input question about GitHub in text format to retrieve the related and structured data.",
}
name = "For test_gpt_assistant_chat"
analyst = GPTAssistantAgent(
name=name,
llm_config={"tools": [{"type": "function", "function": ossinsight_api_schema}], "config_list": config_list},
instructions="Hello, Open Source Project Analyst. You'll conduct comprehensive evaluations of open source projects or organizations on the GitHub platform",
)
analyst.register_function(
function_map={
"ossinsight_data_api": ask_ossinsight,
}
)
ok, response = analyst._invoke_assistant(
[{"role": "user", "content": "What is the most popular open source project on GitHub?"}]
)
executable = analyst.can_execute_function("ossinsight_data_api")
analyst.reset()
threads_count = len(analyst._openai_threads)
analyst.delete_assistant()
assert ok is True
assert response.get("role", "") == "assistant"
assert len(response.get("content", "")) > 0
assert executable is False
assert threads_count == 0
@pytest.mark.skipif(
sys.platform in ["darwin", "win32"] or skip_test,
reason="do not run on MacOS or windows or dependency is not installed",
)
def test_get_assistant_instructions():
"""
Test function to create a new GPTAssistantAgent, set its instructions, retrieve the instructions,
and assert that the retrieved instructions match the set instructions.
"""
name = "For test_get_assistant_instructions"
assistant = GPTAssistantAgent(
name,
instructions="This is a test",
llm_config={
"config_list": config_list,
},
)
instruction_match = assistant.get_assistant_instructions() == "This is a test"
assistant.delete_assistant()
assert instruction_match is True
@pytest.mark.skipif(
sys.platform in ["darwin", "win32"] or skip_test,
reason="do not run on MacOS or windows or dependency is not installed",
)
def test_gpt_assistant_instructions_overwrite():
"""
Test that the instructions of a GPTAssistantAgent can be overwritten or not depending on the value of the
`overwrite_instructions` parameter when creating a new assistant with the same ID.
Steps:
1. Create a new GPTAssistantAgent with some instructions.
2. Get the ID of the assistant.
3. Create a new GPTAssistantAgent with the same ID but different instructions and `overwrite_instructions=True`.
4. Check that the instructions of the assistant have been overwritten with the new ones.
"""
name = "For test_gpt_assistant_instructions_overwrite"
instructions1 = "This is a test #1"
instructions2 = "This is a test #2"
assistant = GPTAssistantAgent(
name,
instructions=instructions1,
llm_config={
"config_list": config_list,
},
)
assistant_id = assistant.assistant_id
assistant = GPTAssistantAgent(
name,
instructions=instructions2,
llm_config={
"config_list": config_list,
"assistant_id": assistant_id,
},
overwrite_instructions=True,
)
instruction_match = assistant.get_assistant_instructions() == instructions2
assistant.delete_assistant()
assert instruction_match is True
@pytest.mark.skipif(
sys.platform in ["darwin", "win32"] or skip_test,
reason="do not run on MacOS or windows or dependency is not installed",
)
def test_gpt_assistant_existing_no_instructions():
"""
Test function to check if the GPTAssistantAgent can retrieve instructions for an existing assistant
even if the assistant was created with no instructions initially.
"""
name = "For test_gpt_assistant_existing_no_instructions"
instructions = "This is a test #1"
assistant = GPTAssistantAgent(
name,
instructions=instructions,
llm_config={
"config_list": config_list,
},
)
assistant_id = assistant.assistant_id
# create a new assistant with the same ID but no instructions
assistant = GPTAssistantAgent(
name,
llm_config={
"config_list": config_list,
"assistant_id": assistant_id,
},
)
instruction_match = assistant.get_assistant_instructions() == instructions
assistant.delete_assistant()
assert instruction_match is True
@pytest.mark.skipif(
sys.platform in ["darwin", "win32"] or skip_test,
reason="do not run on MacOS or windows or dependency is not installed",
)
def test_get_assistant_files():
"""
Test function to create a new GPTAssistantAgent, set its instructions, retrieve the instructions,
and assert that the retrieved instructions match the set instructions.
"""
current_file_path = os.path.abspath(__file__)
openai_client = OpenAIWrapper(config_list=config_list)._clients[0]
file = openai_client.files.create(file=open(current_file_path, "rb"), purpose="assistants")
name = "For test_get_assistant_files"
assistant = GPTAssistantAgent(
name,
instructions="This is a test",
llm_config={
"config_list": config_list,
"tools": [{"type": "retrieval"}],
"file_ids": [file.id],
},
)
files = assistant.openai_client.beta.assistants.files.list(assistant_id=assistant.assistant_id)
retrieved_file_ids = [fild.id for fild in files]
expected_file_id = file.id
assistant.delete_assistant()
openai_client.files.delete(file.id)
assert expected_file_id in retrieved_file_ids
@pytest.mark.skipif(
sys.platform in ["darwin", "win32"] or skip_test,
reason="do not run on MacOS or windows or dependency is not installed",
)
def test_assistant_retrieval():
"""
Test function to check if the GPTAssistantAgent can retrieve the same assistant
"""
name = "For test_assistant_retrieval"
assistant_first = GPTAssistantAgent(
name,
instructions="This is a test",
llm_config={"config_list": config_list},
)
candidate_first = retrieve_assistants_by_name(assistant_first.openai_client, name)
assistant_second = GPTAssistantAgent(
name,
instructions="This is a test",
llm_config={"config_list": config_list},
)
candidate_second = retrieve_assistants_by_name(assistant_second.openai_client, name)
try:
assistant_first.delete_assistant()
assistant_second.delete_assistant()
except openai.NotFoundError:
# Not found error is expected because the same assistant can not be deleted twice
pass
assert candidate_first == candidate_second
if __name__ == "__main__":
test_gpt_assistant_chat()
test_get_assistant_instructions()
test_gpt_assistant_instructions_overwrite()
test_gpt_assistant_existing_no_instructions()
test_get_assistant_files()