feat(mma): Implement context injection using ASTParser in run_worker_lifecycle
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@@ -1,5 +1,7 @@
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import ai_client
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from typing import List, Optional
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from models import Ticket, Track, WorkerContext
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from file_cache import ASTParser
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class ConductorEngine:
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"""
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@@ -34,15 +36,35 @@ class ConductorEngine:
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)
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run_worker_lifecycle(ticket, context)
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def run_worker_lifecycle(ticket: Ticket, context: WorkerContext):
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def run_worker_lifecycle(ticket: Ticket, context: WorkerContext, context_files: List[str] = None):
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"""
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Simulates the lifecycle of a single agent working on a ticket.
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Calls the AI client and updates the ticket status based on the response.
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"""
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context_injection = ""
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if context_files:
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parser = ASTParser(language="python")
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for i, file_path in enumerate(context_files):
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try:
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with open(file_path, 'r', encoding='utf-8') as f:
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content = f.read()
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if i == 0:
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view = parser.get_curated_view(content)
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else:
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view = parser.get_skeleton(content)
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context_injection += f"\nFile: {file_path}\n{view}\n"
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except Exception as e:
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context_injection += f"\nError reading {file_path}: {e}\n"
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# Build a prompt for the worker
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user_message = (
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f"You are assigned to Ticket {ticket.id}.\n"
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f"Task Description: {ticket.description}\n"
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)
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if context_injection:
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user_message += f"\nContext Files:\n{context_injection}\n"
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user_message += (
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"Please complete this task. If you are blocked and cannot proceed, "
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"start your response with 'BLOCKED' and explain why."
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)
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@@ -69,6 +69,58 @@ def test_run_worker_lifecycle_calls_ai_client_send():
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# user_message is passed as a keyword argument
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assert ticket.description in kwargs["user_message"]
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def test_run_worker_lifecycle_context_injection():
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"""
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Test that run_worker_lifecycle can take a context_files list and injects AST views into the prompt.
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"""
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ticket = Ticket(id="T1", description="Task 1", status="todo", assigned_to="worker1")
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context = WorkerContext(ticket_id="T1", model_name="test-model", messages=[])
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context_files = ["primary.py", "secondary.py"]
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from multi_agent_conductor import run_worker_lifecycle
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# We mock ASTParser which is expected to be imported in multi_agent_conductor
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with patch("ai_client.send") as mock_send, \
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patch("multi_agent_conductor.ASTParser") as mock_ast_parser_class, \
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patch("builtins.open", new_callable=MagicMock) as mock_open:
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# Setup open mock to return different content for different files
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file_contents = {
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"primary.py": "def primary(): pass",
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"secondary.py": "def secondary(): pass"
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}
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def mock_open_side_effect(file, *args, **kwargs):
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content = file_contents.get(file, "")
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mock_file = MagicMock()
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mock_file.read.return_value = content
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mock_file.__enter__.return_value = mock_file
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return mock_file
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mock_open.side_effect = mock_open_side_effect
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# Setup ASTParser mock
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mock_ast_parser = mock_ast_parser_class.return_value
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mock_ast_parser.get_curated_view.return_value = "CURATED VIEW"
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mock_ast_parser.get_skeleton.return_value = "SKELETON VIEW"
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mock_send.return_value = "Success"
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run_worker_lifecycle(ticket, context, context_files=context_files)
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# Verify ASTParser calls:
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# First file (primary) should get curated view, others (secondary) get skeleton
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mock_ast_parser.get_curated_view.assert_called_once_with("def primary(): pass")
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mock_ast_parser.get_skeleton.assert_called_once_with("def secondary(): pass")
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# Verify user_message contains the views
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_, kwargs = mock_send.call_args
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user_message = kwargs["user_message"]
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assert "CURATED VIEW" in user_message
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assert "SKELETON VIEW" in user_message
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assert "primary.py" in user_message
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assert "secondary.py" in user_message
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def test_run_worker_lifecycle_handles_blocked_response():
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"""
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Test that run_worker_lifecycle marks the ticket as blocked if the AI indicates it cannot proceed.
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