301 lines
12 KiB
Python
301 lines
12 KiB
Python
import argparse
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import subprocess
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import json
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import os
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import tomllib
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import tree_sitter
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import tree_sitter_python
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import ast
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import datetime
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LOG_FILE = 'logs/mma_delegation.log'
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def generate_skeleton(code: str) -> str:
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"""
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Parses Python code and replaces function/method bodies with '...',
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preserving docstrings if present.
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"""
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try:
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PY_LANGUAGE = tree_sitter.Language(tree_sitter_python.language())
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parser = tree_sitter.Parser(PY_LANGUAGE)
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tree = parser.parse(bytes(code, "utf8"))
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edits = []
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def is_docstring(node):
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if node.type == "expression_statement" and node.child_count > 0:
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if node.children[0].type == "string":
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return True
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return False
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def walk(node):
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if node.type == "function_definition":
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body = node.child_by_field_name("body")
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if body and body.type == "block":
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indent = " " * body.start_point.column
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first_stmt = None
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for child in body.children:
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if child.type != "comment":
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first_stmt = child
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break
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if first_stmt and is_docstring(first_stmt):
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start_byte = first_stmt.end_byte
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end_byte = body.end_byte
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if end_byte > start_byte:
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edits.append((start_byte, end_byte, f"\n{indent}..."))
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else:
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start_byte = body.start_byte
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end_byte = body.end_byte
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edits.append((start_byte, end_byte, "..."))
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for child in node.children:
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walk(child)
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walk(tree.root_node)
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edits.sort(key=lambda x: x[0], reverse=True)
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code_bytes = bytearray(code, "utf8")
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for start, end, replacement in edits:
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code_bytes[start:end] = bytes(replacement, "utf8")
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return code_bytes.decode("utf8")
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except Exception as e:
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return f"# Error generating skeleton: {e}\n{code}"
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def get_model_for_role(role: str) -> str:
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"""Returns the specific model to use for a given tier role."""
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if role == 'tier1-orchestrator' or role == 'tier1':
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return 'gemini-3.1-pro-preview'
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elif role == 'tier2-tech-lead' or role == 'tier2':
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return 'gemini-2.5-flash-lite'
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elif role == 'tier3-worker' or role == 'tier3':
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return 'gemini-2.5-flash-lite'
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elif role == 'tier4-qa' or role == 'tier4':
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return 'gemini-2.5-flash-lite'
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else:
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return 'gemini-2.5-flash-lite'
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def get_role_documents(role: str) -> list[str]:
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if role == 'tier1-orchestrator' or role == 'tier1':
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return ['conductor/product.md', 'conductor/product-guidelines.md']
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elif role == 'tier2-tech-lead' or role == 'tier2':
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return ['conductor/tech-stack.md', 'conductor/workflow.md']
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elif role == 'tier3-worker' or role == 'tier3':
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return ['conductor/workflow.md']
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return []
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def log_delegation(role, full_prompt, result=None, summary_prompt=None):
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os.makedirs('logs/agents', exist_ok=True)
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timestamp = datetime.datetime.now().strftime('%Y%m%d_%H%M%S')
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log_file = f'logs/agents/mma_{role}_task_{timestamp}.log'
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with open(log_file, 'w', encoding='utf-8') as f:
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f.write("==================================================\n")
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f.write(f"ROLE: {role}\n")
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f.write(f"TIMESTAMP: {datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S')}\n")
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f.write("--------------------------------------------------\n")
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f.write(f"FULL PROMPT:\n{full_prompt}\n")
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f.write("--------------------------------------------------\n")
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if result:
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f.write(f"RESULT:\n{result}\n")
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f.write("==================================================\n")
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# Also keep the master log
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os.makedirs(os.path.dirname(LOG_FILE), exist_ok=True)
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display_prompt = summary_prompt if summary_prompt else full_prompt
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with open(LOG_FILE, 'a', encoding='utf-8') as f:
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f.write(f"[{datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S')}] {role}: {display_prompt[:100]}... (Log: {log_file})\n")
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return log_file
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def get_dependencies(filepath: str) -> list[str]:
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"""Identify top-level module imports from a Python file."""
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try:
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with open(filepath, 'r', encoding='utf-8') as f:
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tree = ast.parse(f.read())
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dependencies = []
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for node in tree.body:
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if isinstance(node, ast.Import):
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for alias in node.names:
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dependencies.append(alias.name.split('.')[0])
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elif isinstance(node, ast.ImportFrom):
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if node.module:
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dependencies.append(node.module.split('.')[0])
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seen = set()
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result = []
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for d in dependencies:
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if d not in seen:
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result.append(d)
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seen.add(d)
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return result
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except Exception as e:
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print(f"Error getting dependencies for {filepath}: {e}")
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return []
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def execute_agent(role: str, prompt: str, docs: list[str]) -> str:
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model = get_model_for_role(role)
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# Advanced Context: Dependency skeletons for Tier 3
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injected_context = ""
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# Whitelist of modules that sub-agents have "unfettered" (full) access to.
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# These will be provided in full if imported, instead of just skeletons.
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UNFETTERED_MODULES = ['mcp_client', 'project_manager', 'events', 'aggregate']
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if role in ['tier3', 'tier3-worker']:
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for doc in docs:
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if doc.endswith('.py') and os.path.exists(doc):
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deps = get_dependencies(doc)
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for dep in deps:
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# Only try to generate skeletons for files that exist in the local dir
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dep_file = f"{dep}.py"
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# Optimization: If the dependency is already in 'docs' (explicitly provided),
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# do NOT inject its skeleton/full context again as a dependency.
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if dep_file in docs:
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continue
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if os.path.exists(dep_file) and dep_file != doc:
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try:
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if dep in UNFETTERED_MODULES:
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with open(dep_file, 'r', encoding='utf-8') as f:
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full_content = f.read()
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injected_context += f"\n\nFULL MODULE CONTEXT: {dep_file}\n{full_content}\n"
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else:
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with open(dep_file, 'r', encoding='utf-8') as f:
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skeleton = generate_skeleton(f.read())
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injected_context += f"\n\nDEPENDENCY SKELETON: {dep_file}\n{skeleton}\n"
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except Exception as e:
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print(f"Error gathering context for {dep_file}: {e}")
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# Check for token-bloat safety: if injected_context is too large, truncate it
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if len(injected_context) > 15000:
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injected_context = injected_context[:15000] + "... [TRUNCATED FOR COMMAND LINE LIMITS]"
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# MMA Protocol: Tier 3 and 4 are stateless.
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if role in ['tier3', 'tier3-worker']:
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system_directive = "STRICT SYSTEM DIRECTIVE: You are a stateless Tier 3 Worker (Contributor). " \
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"Your goal is to implement specific code changes or tests based on the provided task. " \
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"You have access to tools for reading and writing files (e.g., read_file, write_file, replace). " \
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"CRITICAL: You CANNOT execute PowerShell scripts or run shell commands directly. " \
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"If you need to verify code or run tests, output the full PowerShell script inside a " \
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"markdown code block (e.g., ```powershell) and state that it needs to be executed. " \
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"Follow TDD and return success status or code changes. No pleasantries, no conversational filler."
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elif role in ['tier4', 'tier4-qa']:
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system_directive = "STRICT SYSTEM DIRECTIVE: You are a stateless Tier 4 QA Agent. " \
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"Your goal is to analyze errors, summarize logs, or verify tests. " \
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"You have access to tools for reading files and exploring the codebase. " \
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"CRITICAL: You CANNOT execute PowerShell scripts or run shell commands directly. " \
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"If you need to run diagnostics, output the PowerShell script and request execution. " \
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"ONLY output the requested analysis. No pleasantries."
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else:
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system_directive = f"STRICT SYSTEM DIRECTIVE: You are a stateless {role}. " \
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"ONLY output the requested text. No pleasantries."
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command_text = f"{system_directive}\n\n{injected_context}\n\n"
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# Manually inline documents to ensure sub-agent has context in headless mode
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for doc in docs:
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if os.path.exists(doc):
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try:
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with open(doc, 'r', encoding='utf-8') as f:
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content = f.read()
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command_text += f"\n\nFILE CONTENT: {doc}\n{content}\n"
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except Exception as e:
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print(f"Error inlining {doc}: {e}")
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command_text += f"\n\nTASK: {prompt}\n\n"
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# Use subprocess with input to pipe the prompt via stdin, avoiding WinError 206.
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# We use -p 'mma_task' to ensure non-interactive (headless) mode and valid parsing.
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# Whitelist tools to ensure they are available to the model in headless mode.
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allowed_tools = "read_file,write_file,replace,list_directory,glob,grep_search,search_files,get_file_summary"
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ps_command = (
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f"if (Test-Path 'C:\\projects\\misc\\setup_gemini.ps1') {{ . 'C:\\projects\\misc\\setup_gemini.ps1' }}; "
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f"gemini -p 'mma_task' --allowed-tools {allowed_tools} --output-format json --model {model}"
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)
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cmd = ['powershell.exe', '-NoProfile', '-Command', ps_command]
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try:
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process = subprocess.run(cmd, input=command_text, capture_output=True, text=True, encoding='utf-8')
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result = process.stdout
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if not process.stdout and process.stderr:
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result = f"Error: {process.stderr}"
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# Log the attempt and result
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log_file = log_delegation(role, command_text, result, summary_prompt=prompt)
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print(f"Sub-agent log created: {log_file}")
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stdout = process.stdout
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start_index = stdout.find('{')
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if start_index != -1:
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json_str = stdout[start_index:]
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try:
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data = json.loads(json_str)
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return data.get('response', stdout)
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except json.JSONDecodeError:
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return stdout
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return stdout
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except Exception as e:
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err_msg = f"Execution failed: {str(e)}"
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log_delegation(role, command_text, err_msg)
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return err_msg
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def create_parser():
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parser = argparse.ArgumentParser(description="MMA Execution Script")
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parser.add_argument(
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"--role",
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choices=['tier1', 'tier2', 'tier3', 'tier4', 'tier1-orchestrator', 'tier2-tech-lead', 'tier3-worker', 'tier4-qa'],
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help="The tier role to execute"
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)
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parser.add_argument(
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"--task-file",
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type=str,
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help="TOML file defining the task"
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)
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parser.add_argument(
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"prompt",
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type=str,
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nargs='?',
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help="The prompt for the tier (optional if --task-file is used)"
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)
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return parser
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def main():
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parser = create_parser()
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args = parser.parse_args()
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role = args.role
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prompt = args.prompt
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docs = []
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if args.task_file and os.path.exists(args.task_file):
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with open(args.task_file, "rb") as f:
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task_data = tomllib.load(f)
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role = task_data.get("role", role)
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prompt = task_data.get("prompt", prompt)
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docs = task_data.get("docs", [])
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if not role or not prompt:
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parser.print_help()
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return
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if not docs:
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docs = get_role_documents(role)
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# Extract @file references from the prompt
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import re
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file_refs = re.findall(r"@([\w./\\]+)", prompt)
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for ref in file_refs:
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if os.path.exists(ref) and ref not in docs:
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docs.append(ref)
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print(f"Executing role: {role} with docs: {docs}")
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result = execute_agent(role, prompt, docs)
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print(result)
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if __name__ == "__main__":
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main()
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