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Kaggle Local Evaluation Harness Simulation:
Simulates multi-turn tool calling and bug resolution loops for Gemma 4.
"""
import json
import sys
from pathlib import Path
from typing import Dict, Any, List
# Ensure parent path is in sys.path
sys.path.append(str(Path(__file__).resolve().parent.parent))
from src.agent.loop import GemmaDevAgent
class KaggleEvalHarness:
def __init__(self, repo_root: str = "."):
self.agent = GemmaDevAgent(repo_root)
self.schemas_path = Path(repo_root) / "src" / "schemas" / "tool_schemas.json"
def load_tool_schemas(self) -> List[Dict[str, Any]]:
"""Loads declarative JSON schemas for tool calling."""
if self.schemas_path.exists():
return json.loads(self.schemas_path.read_text(encoding="utf-8"))
return []
def simulate_task_run(self, task_description: str, max_steps: int = 5) -> Dict[str, Any]:
"""Simulates an evaluation loop handling tool execution steps."""
print(f"\n[Kaggle Eval Harness] Starting Task: '{task_description}'")
# Load system prompt & configurations
schemas = self.load_tool_schemas()
print(f"[Kaggle Eval Harness] Loaded {len(schemas)} tool schemas successfully.")
messages = [
{"role": "system", "content": "You are a software engineering agent fixing repository bugs."},
{"role": "user", "content": task_description}
]
# Simulated initial step: searching the symbol table for task context
simulated_tool_call = {
"name": "code_graph_search",
"arguments": {"symbol_name": "FileOperations"}
}
print(f"[Kaggle Eval Harness] Step 1: Agent called '{simulated_tool_call['name']}'")
messages = self.agent.process_step(messages, simulated_tool_call)
# Print latest tool response summary
latest_response = json.loads(messages[-1]["content"])
print(f"[Kaggle Eval Harness] Step 1 Response Status: {latest_response.get('status')}")
return {
"task": task_description,
"total_messages": len(messages),
"final_status": "evaluated"
}
if __name__ == "__main__":
harness = KaggleEvalHarness()
result = harness.simulate_task_run("Locate the FileOperations class and verify scope reading functionality.")
print(f"\n[Kaggle Eval Harness] Run Complete: {result}")
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