feat: open-source release — AI-driven autonomous optimization with live visibility
Major upgrade making the AI loop visible and the project ready for public release. UI / UX - Live AI Thinking Feed: streams reasoning, decisions, and outcomes per iteration - Parameter Changes panel: prev → new + reason for every AI-driven edit - Validation Activity panel: out-of-sample + sensitivity runs with live metrics - Early Termination banner: surfaces why optimization stopped (targets met, no profit, budget, stuck, user stop) - 3-phase tracker renamed Exploration / Iteration / Validation with live N/total - Best Result modal exposes Evolution Path showing how the AI arrived at the winner - Run-detail modal accessible from every recent run row - Setup form validation (dates, walk-forward order, params selection, AI targets) - Pause button removed; misleading sidebar nav consolidated to Dashboard / New Run / Reports / Source Backend - AIGuidedLoop streams ai_thinking, param_changes, ai_targets_met, ai_stuck - Pipeline emits validation_start / validation_run_start / validation_run_complete / validation_done - Pipeline emits early_termination on every early-stop path - /api/best_result returns best run + full evolution chain - /api/run/<id> + /api/runs sorted by ts - AIReasoner falls back to ANTHROPIC_API_KEY env var when config is a placeholder - Demo mode (APEX_DEMO_MODE=1) generates deterministic synthetic backtests so judges can run end-to-end without MT5 Open-source readiness - README.md with pitch, demo flow, architecture diagram, quickstart, event reference - LICENSE (MIT) - config.example.yaml template (config.yaml now git-ignored) - requirements.txt: added anthropic / requests / psutil / beautifulsoup4, capped majors - .gitignore: secrets, *.set, scratch screenshots, ea_registry.yaml - demo/run_demo.py: one-command offline demo runner - 10 polished screenshots for README + judge review
This commit is contained in:
LEGSTECH Optimizer
@@ -124,17 +124,28 @@ def stop():
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@app.route("/api/history")
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def history():
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"""Score history for chart — built from pipeline results."""
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"""Full run history for chart/table restoration — includes in-progress runs."""
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if pipeline is None:
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return jsonify([])
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if hasattr(pipeline, '_completed_runs') and pipeline._completed_runs:
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# Sort newest first by timestamp (ts field added in _make_run_dict)
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runs = sorted(pipeline._completed_runs,
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key=lambda r: r.get("ts", ""), reverse=True)
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return jsonify(runs)
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# Fallback: post-phase ranked results
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results = pipeline.phase1_results + pipeline.phase2_results
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return jsonify([
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{
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"run_id": r.run_id,
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"score": round(r.score, 4),
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"calmar": round(r.calmar, 3),
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"passing": r.passing,
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"phase": r.phase,
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"run_id": r.run_id,
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"score": round(r.score, 4),
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"net_profit": round(r.net_profit, 2),
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"calmar": round(r.calmar, 3),
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"profit_factor": round(r.profit_factor, 3),
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"max_drawdown": round(r.max_drawdown, 2),
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"total_trades": r.total_trades,
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"win_rate": round(r.win_rate, 1),
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"passing": r.passing,
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"phase": r.phase,
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}
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for r in results
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])
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@@ -203,7 +214,7 @@ def runs_list():
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import json, re
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runs = []
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if REPORTS_DIR.exists():
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for run_dir in sorted(REPORTS_DIR.iterdir(), reverse=True):
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for run_dir in REPORTS_DIR.iterdir():
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if not run_dir.is_dir():
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continue
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summary = run_dir / "summary.json"
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@@ -218,9 +229,108 @@ def runs_list():
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runs.append(data)
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except Exception:
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pass
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# Sort by timestamp field (newest first)
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runs.sort(key=lambda r: r.get("ts", ""), reverse=True)
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return jsonify(runs[:50])
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@app.route("/api/run/<run_id>")
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def run_detail(run_id):
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"""Return full detail for one run: metrics + params + AI insight + .set link."""
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import json, re
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run_dir = REPORTS_DIR / run_id
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if not run_dir.exists():
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return jsonify({"error": "Run not found"}), 404
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def read_json(path):
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try:
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txt = path.read_text(encoding="utf-8")
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txt = re.sub(r'\bNaN\b', 'null', txt)
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txt = re.sub(r'\bInfinity\b', 'null', txt)
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return json.loads(txt)
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except Exception:
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return None
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summary = read_json(run_dir / "summary.json") or {}
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params = read_json(run_dir / "parameters.json") or {}
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ai_insight = read_json(run_dir / "ai_insight.json")
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# Also check live pipeline for AI insight (current session, not yet on disk)
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if ai_insight is None and pipeline and hasattr(pipeline, '_run_insights'):
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ai_insight = pipeline._run_insights.get(run_id)
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# Detect .set file
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set_files = list(run_dir.glob("*.set"))
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set_url = f"/download_set/{run_id}" if set_files else None
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return jsonify({
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**summary,
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"params": params,
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"ai_insight": ai_insight,
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"set_url": set_url,
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"has_set": bool(set_files),
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})
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@app.route("/api/best_result")
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def best_result():
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"""
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Return the current best run plus its evolution path — the ordered sequence
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of AI iterations that led to it (so the user can see how the AI arrived).
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"""
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if not pipeline:
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return jsonify({"error": "No best result yet — optimization has not started."}), 404
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best_run = None
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if getattr(pipeline, "final_result", None):
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best_run = pipeline.final_result
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elif getattr(pipeline, "_live_best", None):
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best_run = pipeline._live_best
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if best_run is None:
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return jsonify({"error": "No best result yet — no passing run found so far."}), 404
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# Build evolution path: walk through _completed_runs up to (and including) the best
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evolution = []
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for r in getattr(pipeline, "_completed_runs", []):
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phase = r.get("phase", "")
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if not (phase.startswith("phase1") or phase.startswith("phase2")):
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continue
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ai_insight = r.get("ai_insight") or {}
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evolution.append({
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"run_id": r.get("run_id"),
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"phase": phase,
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"ts": r.get("ts"),
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"score": r.get("score"),
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"net_profit": r.get("net_profit"),
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"profit_factor": r.get("profit_factor"),
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"calmar": r.get("calmar"),
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"max_drawdown": r.get("max_drawdown"),
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"passing": r.get("passing"),
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"changes": ai_insight.get("changes") or [],
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"analysis": ai_insight.get("analysis") or ai_insight.get("diagnosis") or "",
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"is_best": r.get("run_id") == best_run.run_id,
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})
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if r.get("run_id") == best_run.run_id:
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break
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return jsonify({
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"run_id": best_run.run_id,
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"score": round(best_run.score, 4),
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"net_profit": round(best_run.net_profit, 2),
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"profit_factor": round(best_run.profit_factor, 3),
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"calmar": round(best_run.calmar, 3),
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"max_drawdown": round(best_run.max_drawdown, 2),
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"win_rate": round(best_run.win_rate, 1),
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"total_trades": best_run.total_trades,
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"passing": best_run.passing,
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"phase": getattr(best_run, "phase", "phase2_ai"),
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"params": best_run.params,
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"evolution": evolution,
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"set_url": f"/download_set/{best_run.run_id}",
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})
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# ── SocketIO ──────────────────────────────────────────────────────────────────
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@socketio.on("connect")
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@@ -229,6 +339,220 @@ def on_connect():
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emit("status_sync", pipeline.get_status())
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@app.route("/api/ai_insight/latest")
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def ai_insight_latest():
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"""Return the latest AI insight from the running pipeline."""
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if pipeline and hasattr(pipeline, 'get_latest_insight'):
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insight = pipeline.get_latest_insight()
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if insight:
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return jsonify(insight)
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return jsonify(None)
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@app.route("/api/ai_insights")
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def ai_insights_all():
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"""Return all AI insights from this session."""
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if pipeline and hasattr(pipeline, 'get_all_insights'):
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return jsonify(pipeline.get_all_insights())
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return jsonify([])
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@app.route("/api/settings", methods=["GET"])
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def get_settings():
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import yaml
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config_path = BASE_DIR / "config.yaml"
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try:
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with open(config_path, encoding="utf-8") as f:
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cfg = yaml.safe_load(f) or {}
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ai_cfg = cfg.get("ai", {})
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mt5_cfg = cfg.get("mt5", {})
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broker_cfg = cfg.get("broker", {})
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thresh_cfg = cfg.get("thresholds", {})
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return jsonify({
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"ai": {
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"enabled": ai_cfg.get("enabled", True),
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"anthropic_api_key": ai_cfg.get("anthropic_api_key", ""),
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"model": ai_cfg.get("model", "claude-opus-4-7"),
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"timeout_seconds": ai_cfg.get("timeout_seconds", 30),
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},
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"mt5": {
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"terminal_exe": mt5_cfg.get("terminal_exe", ""),
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"appdata_path": mt5_cfg.get("appdata_path", ""),
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"mql5_files_path": mt5_cfg.get("mql5_files_path", ""),
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"tester_timeout_seconds": mt5_cfg.get("tester_timeout_seconds", 120),
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"tester_model": mt5_cfg.get("tester_model", 1),
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},
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"broker": {
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"timezone_offset_hours": broker_cfg.get("timezone_offset_hours", 3),
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"deposit": broker_cfg.get("deposit", 10000),
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"leverage": broker_cfg.get("leverage", 500),
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},
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"thresholds": {
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"min_trades": thresh_cfg.get("min_trades", 30),
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"min_profit_factor": thresh_cfg.get("min_profit_factor", 1.2),
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"min_calmar": thresh_cfg.get("min_calmar", 0.5),
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"max_oos_degradation": thresh_cfg.get("max_oos_degradation", 0.3),
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"sensitivity_tolerance": thresh_cfg.get("sensitivity_tolerance", 0.15),
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},
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})
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except Exception as e:
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return jsonify({"error": str(e)}), 500
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@app.route("/api/settings", methods=["POST"])
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def save_settings():
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import yaml
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config_path = BASE_DIR / "config.yaml"
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data = request.get_json(silent=True) or {}
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try:
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with open(config_path, encoding="utf-8") as f:
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cfg = yaml.safe_load(f) or {}
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for section in ["ai", "mt5", "broker", "thresholds"]:
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if section in data and isinstance(data[section], dict):
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if section not in cfg:
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cfg[section] = {}
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cfg[section].update(data[section])
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with open(config_path, "w", encoding="utf-8") as f:
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yaml.dump(cfg, f, default_flow_style=False, allow_unicode=True)
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return jsonify({"ok": True})
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except Exception as e:
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return jsonify({"ok": False, "error": str(e)}), 500
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@app.route("/api/ea/register", methods=["POST"])
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def ea_register():
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"""Register a new EA profile."""
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from ea.registry import EARegistry, EAProfile
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data = request.get_json(silent=True) or {}
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try:
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reg = EARegistry(str(BASE_DIR / "config.yaml"))
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profile = EAProfile(
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name=data["name"],
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ex5_file=data.get("ex5_file", data["name"]),
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set_template=data["set_template"],
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symbol=data.get("symbol", "XAUUSD"),
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timeframe=data.get("timeframe", "H1"),
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mode=data.get("mode", "generic"),
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)
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reg.register(profile)
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return jsonify({"ok": True, "name": profile.name})
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except Exception as e:
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return jsonify({"ok": False, "error": str(e)}), 400
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@app.route("/api/ea/list")
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def ea_list():
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"""List all registered EAs."""
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from ea.registry import EARegistry
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try:
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reg = EARegistry(str(BASE_DIR / "config.yaml"))
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profiles = reg.list_all()
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return jsonify([{
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"name": p.name,
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"symbol": p.symbol,
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"timeframe": p.timeframe,
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"mode": p.mode,
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"set_template": p.set_template,
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} for p in profiles])
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except Exception as e:
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return jsonify([])
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@app.route("/ai_insights")
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def ai_insights_page():
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"""Legacy alias — AI insights now live inline on the dashboard."""
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return redirect("/dashboard")
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@app.route("/api/ea/scan")
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def ea_scan():
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"""Scan common MT5 locations for .ex5 and .set files."""
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import glob as _glob
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import os
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home = Path(os.path.expanduser("~"))
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appdata = Path(os.environ.get("APPDATA", home / "AppData" / "Roaming"))
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desktop = home / "Desktop"
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# Directories to scan for .ex5 files — MetaQuotes terminal data dirs
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ex5_dirs = []
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mq_base = appdata / "MetaQuotes" / "Terminal"
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if mq_base.exists():
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for td in mq_base.iterdir():
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if td.is_dir():
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ex5_dirs.append(td / "MQL5" / "Experts")
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ex5_dirs.append(Path("C:/Program Files/MetaTrader 5/MQL5/Experts"))
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ex5_dirs.append(Path("C:/Program Files (x86)/MetaTrader 5/MQL5/Experts"))
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# Scan .ex5 files (skip Examples / Advisors / Free Robots subfolders — likely default)
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SKIP_DIRS = {"Examples", "Advisors", "Free Robots", "Market"}
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ex5_found = []
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seen_names = set()
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for d in ex5_dirs:
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if not d.exists():
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continue
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for f in d.rglob("*.ex5"):
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if any(part in SKIP_DIRS for part in f.parts):
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continue
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name = f.stem
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if name not in seen_names:
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seen_names.add(name)
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ex5_found.append({
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"name": name,
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"path": str(f).replace("\\", "/"),
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"dir": str(f.parent).replace("\\", "/"),
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})
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# Scan .set files — Desktop, Desktop subfolders, MT5 tester agents
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set_dirs = [desktop]
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# Desktop subfolders (1 level deep)
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for item in desktop.iterdir() if desktop.exists() else []:
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if item.is_dir():
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set_dirs.append(item)
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# MT5 tester agent MQL5/Files
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tester_base = appdata / "MetaQuotes" / "Tester"
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if tester_base.exists():
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for td in tester_base.rglob("MQL5/Files"):
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set_dirs.append(td)
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set_found = []
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seen_set = set()
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for d in set_dirs:
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if not d.exists():
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continue
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for f in d.glob("*.set"):
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key = f.name
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if key not in seen_set:
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seen_set.add(key)
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set_found.append({
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"name": f.stem,
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"filename": f.name,
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"path": str(f).replace("\\", "/"),
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})
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# Build best-match hints: for each ex5, find the most likely .set file
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def best_set_for(ea_name):
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ea_lower = ea_name.lower()
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# exact match first
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for s in set_found:
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if s["name"].lower() == ea_lower:
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return s["path"]
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# prefix/suffix match
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for s in set_found:
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sl = s["name"].lower()
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if ea_lower in sl or sl in ea_lower:
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return s["path"]
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return ""
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for ea in ex5_found:
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ea["suggested_set"] = best_set_for(ea["name"])
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return jsonify({
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"ex5": ex5_found,
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"set": set_found,
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})
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# ── Launch ────────────────────────────────────────────────────────────────────
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def open_browser():
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@@ -242,4 +566,4 @@ if __name__ == "__main__":
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print(" Opening browser at http://localhost:5000")
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print("=" * 60)
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threading.Thread(target=open_browser, daemon=True).start()
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socketio.run(app, host="0.0.0.0", port=5000, debug=False, use_reloader=False)
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socketio.run(app, host="0.0.0.0", port=5000, debug=False, use_reloader=False, allow_unsafe_werkzeug=True)
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Reference in New Issue
Block a user