149 lines
5.0 KiB
Python
149 lines
5.0 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 tree_sitter
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import tree_sitter_python
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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-3-flash-preview'
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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 execute_agent(role: str, prompt: str, docs: list[str]) -> str:
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model = get_model_for_role(role)
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command_text = f"Use the mma-{role} skill. {prompt}"
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for doc in docs:
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command_text += f" @{doc}"
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cmd = ['gemini', '-p', command_text, '--output-format', 'json', '--model', model]
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try:
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process = subprocess.run(cmd, capture_output=True, text=True, shell=True)
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if not process.stdout and process.stderr:
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return f"Error: {process.stderr}"
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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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return f"Execution failed: {str(e)}"
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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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required=True,
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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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"prompt",
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type=str,
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help="The prompt for the tier"
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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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docs = get_role_documents(args.role)
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print(f"Executing role: {args.role} with docs: {docs}")
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result = execute_agent(args.role, args.prompt, docs)
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print(result)
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if __name__ == "__main__":
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main()
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import ast
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def get_dependencies(filepath):
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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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