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opportunity
Discord Shop Bot + Merchant Control Panel Development
Discord Shop Bot + Merchant Control Panel Development I am looking for an experienced developer to build a Discord shop bot with a web-based merchant control panel. The bot will allow merchants to sell products directly through Discord using an interactive checkout flow connected to my payment gateway APIs. CORE BOT FUNCTION Certain roles in Discord should be able to start a purchase session using a command such as: /pay @customer Once started, the customer will go through a guided shopping experience inside Discord. SHOPPING FLOW 1. Product Selection Customer sees product categories Then selects products Then selects product variations (each variation may have a different price) 2. Cart System Customer can add multiple items Customer can go back and add additional items before checkout 3. Order Questions Customers are asked questions related to the category or product Merchants can define these questions in the control panel 4. Coupon Codes Customer is asked if they have a coupon code Coupons are created in the merchant panel Coupons can apply to specific products or categories 5. Tips Customer is asked if they want to send a tip Merchant can enable or disable tips in the panel Customer can enter the tip amount 6. Payment Options Customer is given two payment options: Pay Pay with Crypto Both options will connect to my existing payment gateway API. PAYMENT CONFIRMATION Once payment is confirmed: Customer receives a message saying: "Thank you, we have received your payment." An order log message is sent to a merchant log channel containing: Customer details Items purchased Answers to order questions Payment details Under the order message there should be a button: RED: Needs Action When the merchant processes the order they click the button and it changes to: GREEN: Completed REWARDS / POINTS SYSTEM The bot should support a customer reward system. Customers earn 1 point for every £1 spent. Merchants can choose which categories or products earn points. Merchants can set the value of 1 point in the panel. During checkout the customer enters their email address. The bot checks if the email already has a points balance. If points exist the bot asks: "Would you like to use your points?" Customers can check their points balance anytime using: /points They will enter their email to see their current balance. Merchants must also be able to manually add, remove, or edit points from the panel. REFERRAL SYSTEM Customers can refer others using: /refer Flow: User enters their email User enters the new customer’s email Then: A thank you message is sent to the person who referred The message content can be customized in the merchant panel A log message is sent to a channel showing: Email A referred Email B When the referred customer makes a purchase, the referrer receives reward points. Merchants can set referral rewards in the panel. Rewards can apply to specific categories or products. The reward value is set as money but given as points. MERCHANT CONTROL PANEL A simple web-based panel is required where merchants can manage everything. Server Settings Enable or disable features Set admin roles Set log channels Set currency Payment Settings Enter crypto wallet address for payouts Enter wallet address for crypto payments Enable or disable payment methods Products Create categories Add products Add product variations Set prices Add order questions Edit or delete products Coupons Create coupon codes Set which categories or products they apply to Rewards Enable reward system Set point value Select which products or categories earn points Referral System Enable referrals Set reward amounts Choose which products or categories give referral rewards Customers View customer emails View points balances Manually edit or remove points CURRENCY Default currency should be GBP. Merchants should also be able to change currency to: EUR USD IMPORTANT The panel must be very simple and easy to use. Each section should include help text explaining what the feature does so merchants do not get confused. API I already have the payment gateway APIs for: Pay (https://documenter.getpostman.com/view/15018241/2sBXc7JiY7 will use Multi-provider Mode) Pay with Crypto (https://documenter.getpostman.com/view/52669564/2sBXcGDfCj) will use muiti hosted feature) These will be provided to the developer. WHAT I AM LOOKING FOR Experienced Discord bot developer Experience building admin panels or dashboards Clean and scalable code Good communication If you have built Discord shop bots, payment bots, or e-commerce bots before, please include examples in your proposal. DO NOT MESSAGE IF YOU CANNOT DO THIS. I LOOKING TO HAVE THIS CREATED WITHIN 7 DAYS AND I NEED THE PERSON TO LOAD THIS ONTO MY VPS SO ITS ALL WORKING. If you are David Olusanya on here do NOT send me a proposal you are a scammer
opportunity
Extract blood test data from PDF documents that have been OCR'd
The objective is to build a structured blood test database that allows pathology results to be viewed, edited, filtered, and exported to Excel via a web-based HTML interface. The system stores results in a clean, standardised format so trends can be analysed accurately over time. Using AI-assisted OCR, I have built a local Python extraction pipeline that converts PDF pathology reports into machine-readable text and inserts structured data into a SQLite database. The majority of blood tests extract correctly, including canonical test name, result value, unit, and reference range. However, I have reached a specific technical issue with three markers: • CRP (C-reactive protein) • ESR • GLU (Glucose) The OCR output clearly contains the correct lines, and debug logs confirm they are processed. Yet no rows are inserted for these markers. The failure appears to occur between canonical matching, numeric extraction, or validation logic. Current System Architecture The system runs locally and consists of: • extraction_core_2.py (main engine) • Supporting modules for OCR preprocessing, lab dictionary building, regex matching, and validation • SQLite backend • Schema-driven canonical lab dictionary • Controlled fuzzy fallback logic • HTML viewer for results display and Excel export Pipeline flow: Convert PDF to image (pdf2image) Preprocess Run Tesseract OCR Clean and normalise text Match against canonical lab dictionary Extract: canonical test name numeric result unit reference range Validate Insert into SQLite The engine is deterministic and rule-based. The Specific Problem Example OCR line: CRP H 5.2 mg/L 0-5 OCR text is correct. NUMBER_PATTERN matches. The canonical dictionary contains the test. Yet: Inserted 0 rows from 0126251OrderReport_23B00006604_CRP.pdf Likely failure points include: • Canonical containment match failing due to normalisation • Flag tokens (“H”, “L”) interfering with numeric capture • Numeric extraction anchored incorrectly • Validation rejecting due to strict range formatting • Unit pattern mismatch (e.g. mmol/L) • Dictionary indexing issue • Match overridden by another lab name • Guard conditions too strict If validation fails, the row is rejected silently. All other panels extract correctly. The issue appears isolated. What Is Required This is not a rebuild. We do not want: • Re-architecture • Experimental AI guessing logic • Large-scale changes • Expanded fuzzy matching We need: 1. Precise Diagnosis Identify exactly where CRP, ESR, and GLU are failing insertion and which rule is causing rejection. 2. Minimal Safe Fix Implement a targeted correction that: • Adjusts canonical matching if required • Anchors numeric extraction correctly • Allows flag tokens without blocking capture • Relaxes only necessary validation checks • Preserves deterministic behaviour 3. Zero Regression • No impact to currently working panels • No performance degradation • No uncontrolled fuzzy expansion 4. Modular Implementation If appropriate: • Implement as small isolated module or • Cleanly adjust matching block The existing architecture should remain intact. Constraints The system is designed to be: • Deterministic • Schema-driven • Reproducible • Forensic-grade We cannot introduce probabilistic or unpredictable behaviour. Longer-Term Goal After stabilising extraction: • Migrate to web deployment • Enable structured uploads • Add trend analysis • Later incorporate AI-assisted interpretation Immediate priority: Stabilise deterministic extraction for CRP, ESR, and GLU without breaking the existing engine. Materials Provided Uploaded: • Full extraction_core_2.py (text format) • Screenshot of HTML viewer • Sample PDF files • Export showing required output Additional materials available on request: • Sample OCR blocks • Canonical dictionary entries • Regex patterns • Validation logic • Database schema • Debug logs This is a focused debugging and refinement request. I have spent many hours attempting to isolate the issue and now require an experienced developer to identify the blocking condition and implement a practical fix. I have been advised this should take 1–2 hours for a senior developer. Looking for a swift turnaround.
