211 lines
7.8 KiB
Python
211 lines
7.8 KiB
Python
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from __future__ import annotations
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import json
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import time
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import traceback
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from typing import Any, Dict, List
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from .config import load_config, workspace_path
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from .memory import append_journal, load_evolution, maybe_update_evolution, tail_journal
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from .ollama_client import chat
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from .tools import ToolExecutor, ToolError, parse_model_json
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ACTION_SCHEMA = r"""
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You must reply with ONLY a single raw JSON object (no markdown fences, no commentary) of this form:
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{
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"reflection": "short reasoning",
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"actions": [
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{"type": "list_dir", "path": "frontline/units"},
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{"type": "read_file", "path": "relative/path/from/repo/root.mq5"},
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{"type": "write_file", "path": "self-coding-agent/generated/example.txt", "content": "file contents"},
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{"type": "fetch_url", "url": "https://..."},
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{"type": "run_backtest", "strategy": "RSIReversalStrategy", "symbol": "XAUUSD", "start": "2023-01-01", "end": "2024-01-01", "timeframe": "H1"},
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{"type": "run_python", "script_relative": "backtesting/MT5/test_setup.py", "args": []}
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]
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}
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Rules:
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- Paths are relative to the repository root and must stay under allowed prefixes.
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- Prefer reading before writing; keep edits minimal and compile-friendly for MQL5.
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- Use fetch_url for MQL5 documentation pages when unsure about APIs.
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- run_backtest uses the repo's Python MT5 harness (MetaTrader 5 terminal must be installed/running).
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- If you only need to think, use an empty actions list.
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"""
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def build_system_message(cfg: Dict[str, Any]) -> str:
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mission = str(cfg.get("mission") or "").strip()
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prefixes = cfg.get("allowed_path_prefixes") or []
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return (
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mission
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+ "\n\nAllowed path prefixes (read/write/list):\n"
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+ "\n".join(f"- {p}" for p in prefixes)
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+ "\n\n"
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+ ACTION_SCHEMA
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)
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def build_user_message(
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iteration: int,
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last_results: str,
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journal_tail: str,
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evolution_hint: str,
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) -> str:
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parts = [
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f"Iteration: {iteration}",
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"Previous tool results (JSON):\n```json\n"
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+ last_results
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+ "\n```",
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]
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if journal_tail.strip():
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parts.append("Recent journal (tail):\n" + journal_tail)
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if evolution_hint.strip():
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parts.append("Evolution memory hint:\n" + evolution_hint)
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parts.append(
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"Plan the next improvements and output your JSON response. "
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"If this is iteration 1 and there is no parse error yet, prefer list_dir/read_file only; "
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"avoid run_backtest until you have read relevant code."
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)
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return "\n\n".join(parts)
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def run_loop(
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*,
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max_iterations: int | None = None,
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model: str | None = None,
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sleep_seconds: float | None = None,
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mt5_backtest_enabled: bool | None = None,
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) -> None:
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cfg = load_config()
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if mt5_backtest_enabled is not None:
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cfg.setdefault("mt5_backtest", {})["enabled"] = bool(mt5_backtest_enabled)
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ws = workspace_path(cfg)
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ex = ToolExecutor(cfg, ws)
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ollama = cfg.get("ollama") or {}
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base_url = str(ollama.get("base_url", "http://127.0.0.1:11434"))
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model_name = str(model or ollama.get("model", "llama3.2"))
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options = ollama.get("options") or {}
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loop_cfg = cfg.get("loop") or {}
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max_iters = int(max_iterations if max_iterations is not None else loop_cfg.get("max_iterations", 0))
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sleep_s = float(sleep_seconds if sleep_seconds is not None else loop_cfg.get("sleep_seconds", 2.0))
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err_limit = int(loop_cfg.get("consecutive_error_limit", 15))
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mem_cfg = cfg.get("memory") or {}
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journal_max = int(mem_cfg.get("journal_max_lines", 80))
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system = build_system_message(cfg)
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iteration = 0
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consecutive_errors = 0
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last_results_json = json.dumps({"info": "No previous tool results yet."})
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while True:
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iteration += 1
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if max_iters and iteration > max_iters:
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print(f"Stopping: reached max_iterations={max_iters}", flush=True)
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return
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ev = load_evolution(cfg)
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ev_notes = ev.get("notes") or []
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evolution_hint = ""
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if ev_notes:
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evolution_hint = json.dumps(ev_notes[-3:], ensure_ascii=False)
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journal_tail = tail_journal(cfg, journal_max)
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user = build_user_message(iteration, last_results_json, journal_tail, evolution_hint)
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messages: List[Dict[str, str]] = [
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{"role": "system", "content": system},
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{"role": "user", "content": user},
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]
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try:
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raw = chat(base_url, model_name, messages, options=options)
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try:
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plan = parse_model_json(raw)
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except json.JSONDecodeError:
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tail = raw if len(raw) <= 4000 else raw[:4000] + "\n...[truncated]..."
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print("Model returned non-JSON; raw (truncated):\n" + tail + "\n---", flush=True)
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raise
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actions = plan.get("actions") or []
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if not isinstance(actions, list):
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raise ValueError("actions must be a list")
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results: List[Dict[str, Any]] = []
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backtest_blob = ""
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max_actions = 12
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for i, action in enumerate(actions[:max_actions]):
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if not isinstance(action, dict):
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results.append({"ok": False, "error": "action must be an object"})
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continue
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try:
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r = ex.execute(action)
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results.append({"action": action, "result": r})
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if action.get("type") == "run_backtest":
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stdout = str((r or {}).get("stdout") or "")
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stderr = str((r or {}).get("stderr") or "")
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backtest_blob = stdout + "\n" + stderr
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except ToolError as e:
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results.append({"action": action, "result": {"ok": False, "error": str(e)}})
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except Exception as e:
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results.append(
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{"action": action, "result": {"ok": False, "error": f"{type(e).__name__}: {e}"}}
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)
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last_results_json = json.dumps(
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{
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"reflection": plan.get("reflection"),
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"parsed_ok": True,
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"tool_results": results,
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},
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ensure_ascii=False,
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)
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if backtest_blob.strip():
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maybe_update_evolution(cfg, iteration, backtest_blob)
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append_journal(
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cfg,
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{
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"iteration": iteration,
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"reflection": plan.get("reflection"),
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"actions": actions[:max_actions],
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"ok": True,
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},
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)
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consecutive_errors = 0
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print(
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f"[iter {iteration}] ok reflection={str(plan.get('reflection', ''))[:160]!r} "
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f"actions={len(actions[:max_actions])}",
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flush=True,
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)
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time.sleep(max(0.0, sleep_s))
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except KeyboardInterrupt:
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print("Interrupted by user; exiting.", flush=True)
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return
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except Exception as e:
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consecutive_errors += 1
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err_text = f"{type(e).__name__}: {e}\n{traceback.format_exc()[-4000:]}"
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print(err_text, flush=True)
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append_journal(
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cfg,
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{
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"iteration": iteration,
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"ok": False,
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"error": err_text,
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},
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)
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last_results_json = json.dumps({"parse_or_run_error": err_text}, ensure_ascii=False)
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backoff = min(300.0, float(2 ** min(consecutive_errors, 8)))
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if consecutive_errors >= err_limit:
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print(
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f"Many consecutive errors ({consecutive_errors}); sleeping {backoff:.1f}s before retry.",
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flush=True,
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)
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time.sleep(backoff)
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