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Specifiche
Scope
Implement a local automation bridge consisting of:
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MQL4 Helper EA(s):
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Take scheduled screenshots from 3 MT4 chart windows (roles: standard , active_open , third_panel ) at 01:30 and 13:30 local machine time.
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Send the screenshots via WebRequest() to a local Mediator app.
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Mediator App (Python FastAPI or NodeJS):
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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 .
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The JSON file contains toggle flags (AUTO ON/OFF and M1/M5/M15) for Silver (XAGUSD) and Gold (XAUUSD).
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If a role is missing or JSON is invalid, the mediator safely ignores the update (no overwrite).
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Benson EA Integration:
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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.
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Compatibility:
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Must support both single-terminal (multiple chart windows) and multi-terminal setups (shared folder communication).
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Environment
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Windows VPS / PC running MetaTrader 4
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Local loopback connection: http://127.0.0.1:5000
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Shared folder path: C:\BensonBridge\Shared\
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ChatGPT API key will be provided by client.
Key Requirements
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Roles for helper EAs: standard , active_open , third_panel .
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Collector logic waits for all three roles before a single ChatGPT call.
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Strict JSON schema validation before any update.
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Atomic writes to settings.json (no partial files).
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Logging and error handling (Flow failure, missing role, invalid schema).
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Clean, documented code (Python + MQL4) with clear variable names.
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Simple, silent operation (headless).
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One-click setup (Windows Task Scheduler or service mode).
Deliverables
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Benson_Helper_EA.mq4 (source + compiled .ex4 )
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Mediator source (Python FastAPI) + requirements.txt + .env.example
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flow_schema.json (JSON schema)
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Logs and sample output ( decisions_latest.json )
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Step-by-step README / setup guide
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Short demo screencast (2–5 min) showing:
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Automatic screenshot, mediator collection, Flow call, settings.json written, and Benson reacting.
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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
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At 01:30 and 13:30, three screenshots are saved and mediator receives all roles → one ChatGPT call → valid settings.json written.
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Missing role → no Flow call; last settings persist (safe default).
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Invalid JSON from Flow → no change applied, error logged.
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In single-terminal mode: Benson reads Global Variables or settings.json and flips AUTO / TFs correctly.
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In multi-terminal mode: all terminals share the same settings.json , and Benson reacts correctly.
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Logs record every action (timestamp, slot, success/failure).
Budget
Fixed price — fair market rate.
$200