Build Local “Mediator” Bridge: MT4 (Benson EA) ⇄ ChatGPT (Flow) with Scheduled Screenshots & Auto-Toggle Controls

MQL4 통합 Forex Python

명시

Scope

Implement a local automation bridge consisting of:

  1. MQL4 Helper EA(s):

    • Take scheduled screenshots from 3 MT4 chart windows (roles: standard , active_open , third_panel ) at 01:30 and 13:30 local machine time.

    • Send the screenshots via WebRequest() to a local Mediator app.

  2. Mediator App (Python FastAPI or NodeJS):

    • Collect all three screenshots for the same time slot, call ChatGPT (Flow) via API using a strict JSON schema, validate the response, and write the output to Shared/settings.json .

    • The JSON file contains toggle flags (AUTO ON/OFF and M1/M5/M15) for Silver (XAGUSD) and Gold (XAUUSD).

    • If a role is missing or JSON is invalid, the mediator safely ignores the update (no overwrite).

  3. Benson EA Integration:

    • The existing Benson EA (runs on another MT4 chart) will read the settings.json (or Global Variables mirrored from it) and apply the flags automatically — without needing to open the EA input dialog.

  4. Compatibility:

    • Must support both single-terminal (multiple chart windows) and multi-terminal setups (shared folder communication).


Environment

  • Windows VPS / PC running MetaTrader 4

  • Local loopback connection: http://127.0.0.1:5000

  • Shared folder path: C:\BensonBridge\Shared\

  • ChatGPT API key will be provided by client.


Key Requirements

  • Roles for helper EAs: standard , active_open , third_panel .

  • Collector logic waits for all three roles before a single ChatGPT call.

  • Strict JSON schema validation before any update.

  • Atomic writes to settings.json (no partial files).

  • Logging and error handling (Flow failure, missing role, invalid schema).

  • Clean, documented code (Python + MQL4) with clear variable names.

  • Simple, silent operation (headless).

  • One-click setup (Windows Task Scheduler or service mode).


Deliverables

  • Benson_Helper_EA.mq4 (source + compiled .ex4 )

  • Mediator source (Python FastAPI) + requirements.txt + .env.example

  • flow_schema.json (JSON schema)

  • Logs and sample output ( decisions_latest.json )

  • Step-by-step README / setup guide

  • Short demo screencast (2–5 min) showing:

    • Automatic screenshot, mediator collection, Flow call, settings.json written, and Benson reacting.


Timeline & Milestone Table

Phase Description Deliverables Duration Payment
1. Design & Stubs Confirm architecture, create folder structure, dummy endpoints, stub EAs, test screenshot & WebRequest. Folder skeleton + working stub EA + mock API. Day 1–2 20%
2. Screens & Collector Logic Implement scheduled screenshots (01:30 / 13:30), mediator collector for roles, test local JSON logging. Working collector (no API yet). Day 2–3 30%
3. Flow Integration & Validation Connect to ChatGPT (Flow) API, enforce strict JSON schema, write settings.json , add logs & error handling. End-to-end pipeline working. Day 4–5 30%
4. Final Testing & Handoff Integration with Benson EA (flags read), cleanup, docs, and screencast demo. Final code + guide + video. Day 6–7 20%

🕒 Estimated Total Duration: 4–6 working days (one week total).
You may set deadline = 7 days in the MetaQuotes post for buffer.


Acceptance Tests

  1. At 01:30 and 13:30, three screenshots are saved and mediator receives all roles → one ChatGPT call → valid settings.json written.

  2. Missing role → no Flow call; last settings persist (safe default).

  3. Invalid JSON from Flow → no change applied, error logged.

  4. In single-terminal mode: Benson reads Global Variables or settings.json and flips AUTO / TFs correctly.

  5. In multi-terminal mode: all terminals share the same settings.json , and Benson reacts correctly.

  6. Logs record every action (timestamp, slot, success/failure).


Budget

Fixed price — fair market rate.

$200

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