LEGSTECH OptimizerandClaude Opus 4.7
d9ed625579
Replace all 13 occurrences of github.com/tonnylegacy/MT5_Optimizer with github.com/tonnylegacy/Apex_AI_MT5_EA_Optimizer across: - README.md (clone instructions) - SUBMISSION.md (GitHub URL field + checklist) - TODO_NEXT.md (next-session prompt) - PROJECT_HANDOFF.md (header + status table + footer) - docs/GETTING_STARTED.md (clone instructions, issue tracker link) - ui/templates/dashboard.html (Source on GitHub nav link) Also clean up the SUBMISSION.md Video/GIF block to list both the YouTube video and the in-README demo GIF. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
135 lines
7.3 KiB
Markdown
135 lines
7.3 KiB
Markdown
# APEX — Cerebral Valley × Anthropic "Built with Opus 4.7" Hackathon Submission
|
||
|
||
Copy‑paste blocks for the submission form. Every field below is also a heading
|
||
so you can `Ctrl+F` to it.
|
||
|
||
---
|
||
|
||
## Project name
|
||
|
||
**APEX** — Autonomous Performance Evaluator (AI‑driven MT5 EA Optimizer)
|
||
|
||
---
|
||
|
||
## One‑liner (≤140 chars)
|
||
|
||
> An AI trader thinking out loud — Claude Opus 4.7 reads each backtest, decides what to change, and iterates toward profit‑factor / drawdown targets.
|
||
|
||
## Tagline (≤80 chars)
|
||
|
||
> Watch Claude Opus 4.7 optimize a trading strategy in real time.
|
||
|
||
---
|
||
|
||
## Short description (≤300 chars)
|
||
|
||
APEX turns Claude Opus 4.7 into an autonomous trading‑strategy optimizer for MetaTrader 5. The model reads every backtest, decides what parameters to change and why, then runs the next test — streaming its reasoning live to a dashboard until quality targets are met.
|
||
|
||
---
|
||
|
||
## Long description (~500 words — the "what does it do" field)
|
||
|
||
Most strategy optimizers are brute‑force grid searches: pick a metric, sweep N parameters, pray. The user gets a winning configuration but no idea *why* it won, no confidence in *whether* it'll generalize, and no transparency into the search process.
|
||
|
||
**APEX replaces the grid with an AI loop.** Claude Opus 4.7 reads each backtest result, looks at the full iteration history, considers the parameter schema and quality targets, and returns a structured `{changes: [{param, value, reason}], confidence, goal_status}` — concrete, bounds‑checked parameter values for the next test, plus the reasoning that produced them. Every change, every reason, and every Claude token streams live to a dashboard so the user watches the AI think.
|
||
|
||
The pipeline runs three phases:
|
||
|
||
1. **Exploration** — Latin‑Hypercube sampling builds a broad map of profitable parameter regions
|
||
2. **AI Iteration** — Opus 4.7 takes over, hill‑climbing toward user‑set quality targets (PF ≥ X, DD ≤ Y, Calmar ≥ Z), with stuck‑detection and random‑escape when the loop converges to a local optimum
|
||
3. **Validation** — out‑of‑sample backtest on unseen dates + ±20% sensitivity nudge on the top parameter → verdict (RECOMMENDED / RISKY / NOT_RELIABLE)
|
||
|
||
The dashboard exposes everything the AI is doing as it happens:
|
||
|
||
- **Live AI Thinking Feed** — Claude's reasoning streams token‑by‑token via SSE with a typing cursor
|
||
- **Parameter Changes** — every iteration shows `prev → new` with the reason
|
||
- **Validation Activity** — each OOS / sensitivity test renders with live metrics
|
||
- **Replay Scrubber** — drag through every step that led to the winning configuration with metrics and AI analysis at each step
|
||
- **Compare Runs** — side‑by‑side metric and parameter diff for any 2–4 runs
|
||
- **Early Termination** — clear banner when targets are hit, budget exhausted, or the AI is stuck
|
||
- **Discord/Slack webhook** when an optimization completes
|
||
|
||
For judges without MT5: there's a **demo mode** (`python -m demo.run_demo`) that synthesizes deterministic‑but‑realistic backtests so the entire AI loop, validation, and verdict flow run end‑to‑end with no MT5 install. Roughly 35% of Phase 1 samples and 30% of OOS runs realistically fail, so verdicts genuinely span RECOMMENDED / RISKY / NOT_RELIABLE.
|
||
|
||
The point isn't a better trading strategy — it's a working pattern for **AI‑as‑driver of a long‑running optimization loop**, with the AI's reasoning fully visible. That pattern transfers to any iterative search problem where humans currently grid‑sweep blindly: ML hyperparameter tuning, A/B variant generation, ad‑creative optimization, infrastructure cost tuning.
|
||
|
||
---
|
||
|
||
## Built with
|
||
|
||
Claude Opus 4.7 (the reasoning loop), Flask + Flask‑SocketIO (real‑time UI), Python 3.11, Pandas + NumPy, Pydantic, Anthropic Messages API with SSE streaming, MetaTrader 5 Strategy Tester (real backtests).
|
||
|
||
---
|
||
|
||
## How Claude Opus 4.7 is used (the "what AI features did you use" field)
|
||
|
||
- **`suggest_next_params()` — Opus 4.7 is the loop driver.** It receives the full parameter schema, the iteration history (last 15 runs with metrics + changes), and the user's quality targets, and returns structured JSON with concrete parameter values, per‑change reasoning, a confidence score, and a goal‑status breakdown (which targets are met). This is the load‑bearing call — it's what turns the optimizer from a grid search into an agent.
|
||
- **`analyze()` — Per‑run diagnostics.** A second Opus 4.7 call interprets each backtest's metrics + analyzer findings + recent run history and returns headline / diagnosis / patterns / suggestions / risk flags. Powers the AI Summary panel.
|
||
- **SSE streaming** — both calls run with `stream=true`. Each text delta forwards to the dashboard as `ai_thinking_chunk` events so the user sees Claude's reasoning type out token‑by‑token. Single growing bubble per call with a blinking cursor that finalises on `end`.
|
||
- **Hot model swap** — users can change model (`claude-opus-4-7` ↔ `claude-sonnet-4-6` ↔ `claude-haiku-4-5`) mid‑run via Settings. The next iteration uses the new model without restart.
|
||
|
||
---
|
||
|
||
## GitHub URL
|
||
|
||
https://github.com/tonnylegacy/Apex_AI_MT5_EA_Optimizer
|
||
|
||
---
|
||
|
||
## Demo URL
|
||
|
||
No hosted demo (the app runs locally to drive a local MT5 install). For judges:
|
||
|
||
- **Static**: open `screenshots/apex_demo.gif` in the repo (6‑frame timelapse of one autonomous run)
|
||
- **Run it**: `git clone … && pip install -r requirements.txt && python -m demo.run_demo` → the browser opens to the dashboard, a ~3-4 minute optimization auto-starts, and every phase (exploration → AI iteration → validation → verdict) plays out without you touching anything
|
||
- **With API key**: set `ANTHROPIC_API_KEY` env var (or fill `ai.anthropic_api_key` in `config.yaml`) to see live Claude reasoning stream into the Thinking Feed
|
||
- **Faster / your-own-config**: `python -m demo.run_demo --quick` to skip the auto-run and drive the demo from `/setup` yourself
|
||
|
||
---
|
||
|
||
## Video / GIF
|
||
|
||
- **YouTube (3-minute submission video):** https://youtu.be/XM3tQig0oWI
|
||
- **GIF (animated hero in README):** `screenshots/apex_demo.gif`
|
||
|
||
---
|
||
|
||
## Team
|
||
|
||
Solo build — `tonnylegacy`
|
||
|
||
---
|
||
|
||
## Tags
|
||
|
||
`mt5` `metatrader5` `trading` `quant` `optimization` `claude-opus-4-7` `anthropic` `ai-agents` `agentic-loops` `python` `flask` `socketio` `streaming-ui`
|
||
|
||
---
|
||
|
||
## Tech stack
|
||
|
||
`Python 3.11` · `Anthropic Messages API (SSE streaming)` · `Claude Opus 4.7` · `Flask` · `Flask‑SocketIO` · `Pandas / NumPy / Pydantic` · `MetaTrader 5 Strategy Tester`
|
||
|
||
---
|
||
|
||
## License
|
||
|
||
MIT
|
||
|
||
---
|
||
|
||
## Submission checklist
|
||
|
||
- [x] Repo public on GitHub: <https://github.com/tonnylegacy/Apex_AI_MT5_EA_Optimizer>
|
||
- [x] LICENSE file (MIT)
|
||
- [x] README with pitch + screenshots + install + architecture diagram
|
||
- [x] No leaked API keys (config.yaml git‑ignored, env‑var fallback wired, GET /api/settings masks key)
|
||
- [x] `config.example.yaml` template for users
|
||
- [x] Animated demo GIF in `screenshots/apex_demo.gif`
|
||
- [x] Demo mode that runs without MT5 (`python -m demo.run_demo`)
|
||
- [x] Opus 4.7 is the default model (config + AIReasoner class default)
|
||
- [x] Streaming reasoning visible to the user (SSE → `ai_thinking_chunk`)
|
||
- [x] Recorded a 3-minute submission video (founder story → live demo → outro)
|
||
- [ ] Video uploaded to YouTube (unlisted) — paste link in the form
|
||
- [ ] Submission form filled — *paste blocks above into the Cerebral Valley form*
|