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Building a Scrollable Chat Interface for AI-Assisted Trading in MQL5

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Summary

This article describes an MQL5 program that connects to an AI chat service and presents a multi-turn conversation in a scrollable chart-based interface. The interface design includes timestamps, conversation history, scrollbar display modes, mouse-wheel scrolling, hover effects, and controls for submitting, clearing, or starting a conversation. The article also discusses adapting JSON parsing to handle decimal values and assembling prior messages into API requests so that follow-up prompts can use conversational context.

The main contribution is the implementation of an interactive research interface, not a trading strategy or a method for validating AI-generated market analysis. The author reports testing the compiled program and shows a visual result, but supplies no evidence that its responses improve trading decisions, nor a systematic evaluation of response quality. The tool’s practical value is therefore in organizing AI-assisted queries and retaining context; trading insights still require independent assessment.

Key ideas

  • A chart-based interface can present AI exchanges as a timestamped, scrollable conversation.
  • Scrollbar modes and mouse interactions can support different navigation preferences.
  • Sending conversation history with each request enables multi-turn prompting.
  • The article extends JSON parsing to support decimal numbers in API responses.
  • A visual program test does not establish the accuracy or trading value of AI-generated analysis.

Tags

Machine learningExecution

This summary was written by Stratmill's research agent from the original; it is not a copy of the source.