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5 Commits

Author SHA1 Message Date
Lorenze Jay
78621d6b7b Merge branch 'main' into bugfix/allow-empthy-input-to-end-human-input 2025-02-20 08:47:20 -08:00
Brandon Hancock
abbcacc440 Drop extra logs that were causing confusion 2025-02-20 11:16:56 -05:00
Brandon Hancock
6d85c788ad fix failing test part 2 2025-02-19 13:36:00 -05:00
Brandon Hancock
aa350ae530 fix failing test 2025-02-19 13:22:50 -05:00
Brandon Hancock
33b9cd35e9 imporve HITL 2025-02-19 13:00:51 -05:00
5 changed files with 31 additions and 562 deletions

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@@ -114,10 +114,15 @@ class CrewAgentExecutorMixin:
prompt = ( prompt = (
"\n\n=====\n" "\n\n=====\n"
"## HUMAN FEEDBACK: Provide feedback on the Final Result and Agent's actions.\n" "## HUMAN FEEDBACK: Provide feedback on the Final Result and Agent's actions.\n"
"Respond with 'looks good' to accept or provide specific improvement requests.\n" "Please follow these guidelines:\n"
"You can provide multiple rounds of feedback until satisfied.\n" " - If you are happy with the result, simply hit Enter without typing anything.\n"
" - Otherwise, provide specific improvement requests.\n"
" - You can provide multiple rounds of feedback until satisfied.\n"
"=====\n" "=====\n"
) )
self._printer.print(content=prompt, color="bold_yellow") self._printer.print(content=prompt, color="bold_yellow")
return input() response = input()
if response.strip() != "":
self._printer.print(content="\nProcessing your feedback...", color="cyan")
return response

View File

@@ -548,10 +548,6 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
self, initial_answer: AgentFinish, feedback: str self, initial_answer: AgentFinish, feedback: str
) -> AgentFinish: ) -> AgentFinish:
"""Process feedback for training scenarios with single iteration.""" """Process feedback for training scenarios with single iteration."""
self._printer.print(
content="\nProcessing training feedback.\n",
color="yellow",
)
self._handle_crew_training_output(initial_answer, feedback) self._handle_crew_training_output(initial_answer, feedback)
self.messages.append( self.messages.append(
self._format_msg( self._format_msg(
@@ -571,9 +567,8 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
answer = current_answer answer = current_answer
while self.ask_for_human_input: while self.ask_for_human_input:
response = self._get_llm_feedback_response(feedback) # If the user provides a blank response, assume they are happy with the result
if feedback.strip() == "":
if not self._feedback_requires_changes(response):
self.ask_for_human_input = False self.ask_for_human_input = False
else: else:
answer = self._process_feedback_iteration(feedback) answer = self._process_feedback_iteration(feedback)
@@ -581,27 +576,6 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
return answer return answer
def _get_llm_feedback_response(self, feedback: str) -> Optional[str]:
"""Get LLM classification of whether feedback requires changes."""
prompt = self._i18n.slice("human_feedback_classification").format(
feedback=feedback
)
message = self._format_msg(prompt, role="system")
for retry in range(MAX_LLM_RETRY):
try:
response = self.llm.call([message], callbacks=self.callbacks)
return response.strip().lower() if response else None
except Exception as error:
self._log_feedback_error(retry, error)
self._log_max_retries_exceeded()
return None
def _feedback_requires_changes(self, response: Optional[str]) -> bool:
"""Determine if feedback response indicates need for changes."""
return response == "true" if response else False
def _process_feedback_iteration(self, feedback: str) -> AgentFinish: def _process_feedback_iteration(self, feedback: str) -> AgentFinish:
"""Process a single feedback iteration.""" """Process a single feedback iteration."""
self.messages.append( self.messages.append(

View File

@@ -23,7 +23,6 @@
"summary": "This is a summary of our conversation so far:\n{merged_summary}", "summary": "This is a summary of our conversation so far:\n{merged_summary}",
"manager_request": "Your best answer to your coworker asking you this, accounting for the context shared.", "manager_request": "Your best answer to your coworker asking you this, accounting for the context shared.",
"formatted_task_instructions": "Ensure your final answer contains only the content in the following format: {output_format}\n\nEnsure the final output does not include any code block markers like ```json or ```python.", "formatted_task_instructions": "Ensure your final answer contains only the content in the following format: {output_format}\n\nEnsure the final output does not include any code block markers like ```json or ```python.",
"human_feedback_classification": "Determine if the following feedback indicates that the user is satisfied or if further changes are needed. Respond with 'True' if further changes are needed, or 'False' if the user is satisfied. **Important** Do not include any additional commentary outside of your 'True' or 'False' response.\n\nFeedback: \"{feedback}\"",
"conversation_history_instruction": "You are a member of a crew collaborating to achieve a common goal. Your task is a specific action that contributes to this larger objective. For additional context, please review the conversation history between you and the user that led to the initiation of this crew. Use any relevant information or feedback from the conversation to inform your task execution and ensure your response aligns with both the immediate task and the crew's overall goals.", "conversation_history_instruction": "You are a member of a crew collaborating to achieve a common goal. Your task is a specific action that contributes to this larger objective. For additional context, please review the conversation history between you and the user that led to the initiation of this crew. Use any relevant information or feedback from the conversation to inform your task execution and ensure your response aligns with both the immediate task and the crew's overall goals.",
"feedback_instructions": "User feedback: {feedback}\nInstructions: Use this feedback to enhance the next output iteration.\nNote: Do not respond or add commentary." "feedback_instructions": "User feedback: {feedback}\nInstructions: Use this feedback to enhance the next output iteration.\nNote: Do not respond or add commentary."
}, },

View File

@@ -1,7 +1,6 @@
"""Test Agent creation and execution basic functionality.""" """Test Agent creation and execution basic functionality."""
import os import os
from datetime import UTC, datetime, timezone
from unittest import mock from unittest import mock
from unittest.mock import patch from unittest.mock import patch
@@ -9,7 +8,7 @@ import pytest
from crewai import Agent, Crew, Task from crewai import Agent, Crew, Task
from crewai.agents.cache import CacheHandler from crewai.agents.cache import CacheHandler
from crewai.agents.crew_agent_executor import CrewAgentExecutor from crewai.agents.crew_agent_executor import AgentFinish, CrewAgentExecutor
from crewai.agents.parser import AgentAction, CrewAgentParser, OutputParserException from crewai.agents.parser import AgentAction, CrewAgentParser, OutputParserException
from crewai.knowledge.source.base_knowledge_source import BaseKnowledgeSource from crewai.knowledge.source.base_knowledge_source import BaseKnowledgeSource
from crewai.knowledge.source.string_knowledge_source import StringKnowledgeSource from crewai.knowledge.source.string_knowledge_source import StringKnowledgeSource
@@ -999,23 +998,35 @@ def test_agent_human_input():
# Side effect function for _ask_human_input to simulate multiple feedback iterations # Side effect function for _ask_human_input to simulate multiple feedback iterations
feedback_responses = iter( feedback_responses = iter(
[ [
"Don't say hi, say Hello instead!", # First feedback "Don't say hi, say Hello instead!", # First feedback: instruct change
"looks good", # Second feedback to exit loop "", # Second feedback: empty string signals acceptance
] ]
) )
def ask_human_input_side_effect(*args, **kwargs): def ask_human_input_side_effect(*args, **kwargs):
return next(feedback_responses) return next(feedback_responses)
with patch.object( # Patch both _ask_human_input and _invoke_loop to avoid real API/network calls.
CrewAgentExecutor, "_ask_human_input", side_effect=ask_human_input_side_effect with (
) as mock_human_input: patch.object(
CrewAgentExecutor,
"_ask_human_input",
side_effect=ask_human_input_side_effect,
) as mock_human_input,
patch.object(
CrewAgentExecutor,
"_invoke_loop",
return_value=AgentFinish(output="Hello", thought="", text=""),
) as mock_invoke_loop,
):
# Execute the task # Execute the task
output = agent.execute_task(task) output = agent.execute_task(task)
# Assertions to ensure the agent behaves correctly # Assertions to ensure the agent behaves correctly.
assert mock_human_input.call_count == 2 # Should have asked for feedback twice # It should have requested feedback twice.
assert output.strip().lower() == "hello" # Final output should be 'Hello' assert mock_human_input.call_count == 2
# The final result should be processed to "Hello"
assert output.strip().lower() == "hello"
def test_interpolate_inputs(): def test_interpolate_inputs():

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