mirror of
https://github.com/aljazceru/Auto-GPT.git
synced 2025-12-26 18:34:23 +01:00
7508e9941f
* Adds SELF_FEEDBACK_FILE_NAME * Add self-feedback logging to logs/Debug folder * Reformatting * Uses JSON file * Update agent.py Changes position * Update agent.py * Adds PROMPT_FEEDBACK_FILE_NAME * Update agent.py * Update agent.py * Reformatting * Update agent.py * Update agent.py * Changes file names * Update agent.py * Reformatting * Update agent.py * Changes conts names * Update agent_manager.py * Update agent_manager.py * HARD reset * Update test_get_self_feedback.py * Update test_get_self_feedback.py --------- Co-authored-by: merwanehamadi <merwanehamadi@gmail.com>
59 lines
2.1 KiB
Python
59 lines
2.1 KiB
Python
from datetime import datetime
|
|
|
|
from autogpt.agent.agent import Agent
|
|
from autogpt.config import AIConfig
|
|
from autogpt.llm import create_chat_completion
|
|
from autogpt.log_cycle.log_cycle import LogCycleHandler
|
|
|
|
|
|
def test_get_self_feedback(mocker):
|
|
# Define a sample thoughts dictionary
|
|
thoughts = {
|
|
"reasoning": "Sample reasoning.",
|
|
"plan": "Sample plan.",
|
|
"thoughts": "Sample thoughts.",
|
|
}
|
|
|
|
# Define a fake response for the create_chat_completion function
|
|
fake_response = (
|
|
"The AI Agent has demonstrated a reasonable thought process, but there is room for improvement. "
|
|
"For example, the reasoning could be elaborated to better justify the plan, and the plan itself "
|
|
"could be more detailed to ensure its effectiveness. In addition, the AI Agent should focus more "
|
|
"on its core role and prioritize thoughts that align with that role."
|
|
)
|
|
|
|
# Mock the create_chat_completion function
|
|
mock_create_chat_completion = mocker.patch(
|
|
"autogpt.agent.agent.create_chat_completion", wraps=create_chat_completion
|
|
)
|
|
mock_create_chat_completion.return_value = fake_response
|
|
|
|
# Create a MagicMock object to replace the Agent instance
|
|
agent_mock = mocker.MagicMock(spec=Agent)
|
|
|
|
# Mock the config attribute of the Agent instance
|
|
agent_mock.config = AIConfig()
|
|
|
|
# Mock the log_cycle_handler attribute of the Agent instance
|
|
agent_mock.log_cycle_handler = LogCycleHandler()
|
|
|
|
# Mock the create_nested_directory method of the LogCycleHandler instance
|
|
agent_mock.created_at = datetime.now().strftime("%Y%m%d_%H%M%S")
|
|
|
|
# Mock the cycle_count attribute of the Agent instance
|
|
agent_mock.cycle_count = 0
|
|
|
|
# Call the get_self_feedback method
|
|
feedback = Agent.get_self_feedback(
|
|
agent_mock,
|
|
thoughts,
|
|
"gpt-3.5-turbo",
|
|
)
|
|
|
|
# Check if the response is a non-empty string
|
|
assert isinstance(feedback, str) and len(feedback) > 0
|
|
|
|
# Check if certain keywords from input thoughts are present in the feedback response
|
|
for keyword in ["reasoning", "plan", "thoughts"]:
|
|
assert keyword in feedback
|