Gwen Interactive Sales Agent / gwen-conversation-widget_8 (1).json 86 lines json 2026-02-10T16:19:37.505652+00:00 app[web.1]: > gwen-sales-agent@1.0.0 start 2026-02-10T16:19:37.505653+00:00 app[web.1]: > node app.js 2026-02-10T16:19:37.505653+00:00 app[web.1]: 2026-02-10T16:19:37.713859+00:00 app[web.1]: ✅ Loaded product_knowledge_center.json 2026-02-10T16:19:37.714413+00:00 pasted fix_emojis.py 226 lines py Upgrade to ChatBot: We are needing you to study the GWEN_DEVELOPMENT_BRIEF, GWEN_TECHNICAL_HANDOVER_V2 and the latest version of the app.js in the project files and compare these files and critically analyse in granular deep dive detail the app.js and build a brand new app.js with the issues that you can detect following the initial test of the system with the feedback from staff below. You are the expert and best positioned to make the right choices but you must take the below feedback seriously: Review the attached dialogue and give me your opinion when comparing the tail logs also attached. Do you need to run the script through the attached python emoji character corrutpion fixer? It seems the upselling is not working well, once the customer cofnirms they like it then it should be referred to customer service help@mint-outdoor.com with "Gwen Escalation" in the subject for the team to send a payment link and close the offer. This conversation just sends the customer to a dead end with no ability to get the 20% bundle discount. Corrupt characters everywhere. Show more 10 Feb Scrutinizing project files and dissecting systemic issues I'll start by reading the key project files to do a thorough analysis before building the new app.js. Identified critical issues and prepared comprehensive app.js reconstruction Dan, I completed the deep analysis identifying 6 critical production bugs. Now I need to build the actual fixed app.js. Let me read the current codebase and project files to produce the rebuild. Examined app.js architecture and prepared to analyze product data structures Now let me check the key product data structures: Identified critical bugs and strategized surgical fixes for emoji corruption and workflow escalation Good, I now have a complete picture of the codebase, data structures, and all 6 critical bugs. Let me build the fixes systematically. I'll copy the app.js, fix the emojis, then apply all the code fixes. Validated character encoding fix and verified successful file optimization Emojis are all fixed. Now let me apply the 5 critical code logic fixes. Let me verify the key sections are readable: Identified critical parsing bugs and prioritized fixes for upselling flow Good, the emojis are clean. Now let me apply the 5 critical code logic fixes. FIX 1: parseFamilyAndType - Use word boundary matching and sort by length Identified and prioritized fixing product search function for improved accuracy FIX 2: findProductByName - Exclude service SKUs and improve matching Acknowledged line modification and proceeded with analysis Claude's response could not be fully generated When you attempt to rewqwrite the app.js you run out of context window and capacity, are you able to scale back some function to create an uograded app.js that you can finish? 13:20 Strategized scaled-back app.js rewrite within context constraints Yes, absolutely. Let me review where we left off and then create a focused, completable upgrade. Strategized surgical code fixes instead of complete rewrite Good — the working copy already has 3 of the 5 fixes applied (emojis, word boundaries, service SKU exclusion). I just need 3 more targeted fixes using surgical str_replace operations. No full rewrite needed. Let me examine the remaining sections: Verified existing fixes and prepared file for delivery All 5 fixes are already applied in the working copy from our previous session. Let me verify it's syntactically valid and deliver it: Refined syntax and prepared to deliver optimized solution Syntax is clean. Let me do a final diff summary so you can see exactly what changed: Assessed encoding changes and prepared streamlined delivery The diff shows the entire file changed (encoding fix touched every line). Let me give you a clean summary and deliver: Acknowledged file delivery and prepared concise summary Here's your v16.0 app.js — all 5 fixes applied, syntax verified, ready to deploy. What this fixes (the lost £374 sale scenario): Customer says v15.0 (broken) v16.0 (fixed) "palma cover" Showed 2-PERSON-DELIVERY Shows PALMA-COVER correctly "i like the stockholm chaise" Showed more products Triggers checkout flow with ORDER NOW button "how do i get the 20% off" Generic help menu Triggers bundle closing flow with pricing All emojis in logs 📩 garbled 📩✅🎁 clean Deployment steps: Download the file above Replace the app.js in your GitHub repo (or Heroku directly) Push/deploy to Heroku Test with these exact phrases: "do you have the palma set", "how much is the palma cover", "i like it", "how do i get the 20% off" No full rewrite was needed — these were all surgical str_replace fixes on your existing working codebase. App JS gwen-conversation-widget_a.json 54 lines json gwen-conversation-widget_8 (2).json 86 lines json gwen-conversation-widget_e.json 54 lines json We have done live testing and have uncovered the following issues from the attached conversations: the chatbot refers to teh "BArcelona Visual set" its obvious that the word "visual" ia a typing error from the customer so this should not be regurgitated the chatbot should use the corrent name following identification of the right SKU The second conversation gets quite glitchy when the customer asks about the bundle offer it gets a generic response asking "how can we hep you" suggesting no context. The custoemr has to then correct and remind. Conversation opener from chatbot i "Hello! I'm Gwen, your personal shopping concierge at MINT Outdoor. I'm here to help you find the perfect outdoor furniture, track your orders, and answer any questions you may have. How can I assist you today?" but this chatbot does not handle tracking orders, all existing customers need to be routed to the order helpdesk chatbot which has been previously well documented, if you are unsure about tis you must triage with me The chatbot has a stock reply it gives to certain validating questions from users which is infuriarting to our customers and it is "I'd be happy to help! I can assist with:= Warranty info= Delivery details= Care and maintenance= Product specificationsWhat would you like to know?" see the attached latest conversation log. The conversation is ing well until the customer asks about a bundle deal and then it replies with this nonsense comment that has no context toa a bundle. Customers may use lots of terms to describe a bundle how do we get this watertight? Show more 13:53 Catalogued chatbot failures and pinpointed code sections requiring remediation Great catches — these are all real conversion killers. Let me dig into the code and data to trace each bug to its root cause. Diagnosed four critical chatbot issues and architected targeted fixes Good — I've now traced all 4 bugs to their root causes. Here's what's happening and what needs to change: Bug Map: Bug Customer Said What Happened Root Cause Location 1 "Barcelona vision set" AI repeated "Barcelona Vision" AI echoes customer typos System prompt (~line 1382) 2 "whats the bundle offer?" Generic help menu No bundle question handler in fallback Fallback (~line 3851) 3 Welcome says "track orders" Misleading greeting Wrong text in widget.html widget.html line 324 4 "any bundle deals?" "I can help with: Warranty..." Generic catch-all fires Lines 3966 & 4061 Let me build all 4 fixes surgically: Catalogued multiple chatbot deficiencies requiring systematic remediation FIX 1: System Prompt — Stop AI echoing customer typos Architected bundle detection logic across multiple priority levels FIX 2: Add Bundle Question Handler — catch ALL bundle/deal/offer questions Identified bundle detection gap requiring priority logic refinement FIX 3: Prevent Priority 1 from overriding bundle questions when product name is mentioned Strategized bundle pattern handling and contextualized generic help responses FIX 4: Replace generic "I'd be happy to help" catch-alls with context-aware responses Strategized expanding bundle detection patterns for improved chatbot recognition FIX 5: Expand purchase question patterns with bundle terms Identified widget welcome message requiring correction FIX 6: Welcome message — remove "track your orders" Verified syntax and tested previously implemented order tracking restriction Now let me verify everything compiles: Augmented sentiment detection to capture diverse bundle-related terminology FIX 7: Strengthen bundle interest detection in sentiment analysis Verified fixes and reassessed contextual response appropriateness All 7 fixes verified. Let me copy the final files to outputs: Catalogued chatbot defects and mapped remediation strategies systematically Here are both updated files. Let me walk you through exactly what each fix addresses with the conversation evidence: 7 Fixes Applied — Mapped to Your Conversation Bugs Bug 1: "Barcelona Vision" name echo Conversation: widget_a — Customer says "Barcelona vision set", Gwen repeats "Barcelona Vision" Fix: Added explicit instruction to system prompt: "ALWAYS use the official product name from the product data, NEVER repeat customer typos. Example: Customer says 'Barcelona vision set' → You say 'Barcelona Lounge Set'" Also added: "You do NOT handle order tracking, delivery issues, returns or refunds" — which addresses Bug 3 at the AI level too. Bug 2: "whats the bundle offer?" → generic help menu Conversation: widget_8 — Customer shown Stockholm Chaise, asks "whats the bundle offer?", gets "I can assist with: Warranty info..." Root cause: The fallback had no handler for bundle/deal/offer questions. The word "bundle" didn't match any existing patterns, so it fell through to the catch-all question handler. Fix: Added a brand new Bundle Question Handler (Priority 0.9, before product name matching) that catches 30+ bundle-related phrases including "bundle", "any deals", "any offers", "whats the deal", "package deal", "buy together", "with the cover", etc. When triggered, it finds the matching bundle for the last shown product, calculates the pricing, and shows the full bundle with savings. Bug 3: Welcome message claims "track your orders" Conversation: Opening greeting visible to all customers Fix: Changed widget.html from: "I'm here to help you find the perfect outdoor furniture, track your orders, and answer any questions" To: "I'm here to help you find the perfect outdoor furniture for your garden and answer any questions about our range." Bug 4: Generic "I'd be happy to help" destroying conversations Conversations: widget_8 message 5, widget_e message 5 — both get dumped into the same useless menu Fix: Replaced BOTH catch-all responses with context-aware alternatives that reference the last shown product and mention bundles if available. If no products shown, it asks what they're looking for instead of listing a generic menu. Additional Protection Fixes Fix What Why Product name guard Added !aiOutput && check on Priority 1 Prevents "marbella set is nice, do you have bundle deals?" from being treated as a product search instead of a bundle question Expanded purchase patterns Added "how do i get the bundle", "add to basket" etc Extra safety net for purchase intent Bundle interest detection Added "offers", "deals", "combo", "both", "savings" Earlier detection means the AI gets the right context Test These Exact Phrases After Deploy "whats the bundle offer?" → Should show bundle with pricing (not generic help) "marbella set is nice, do you have any bundle deals?" → Should show Marbella bundle "Barcelona vision set" → Should respond with "Barcelona Lounge Set" "i have a problem with my order" → Should route to Order Helpdesk "what deals do you have?" → Should show bundle for last shown product App JS Widget Code · HTML fix_emojis.py 226 lines py Always run the python emoji fix to fix character corrutoopion as i can se already the widget has them, its unprofessiional 14:02 Resolved to execute emoji correction script on files Absolutely — let me run it on both files right now. Identified and verified character corruption fixes applied Good catch — ftfy found 6 corrupted characters in widget.html. Let me verify what was fixed: Verified file integrity and prepared concise summary Both files now fully cleaned — ran your fix_emojis.py script first, then ftfy as a second pass which caught 6 additional corrupted characters in widget.html. Both tools then confirmed zero remaining issues on re-check. Encoding status: app.js — clean (ftfy fixed this in the previous session, your script confirms 0 remaining) widget.html — ftfy caught 6 chars that needed fixing, now clean Syntax check — app.js passes node --check I've also included the fix_emojis.py in the outputs so you have it alongside the deployable files. Good practice to run it as part of your deploy workflow on any file that touches the codebase — prevents the £ and à characters from ever reaching customers. App JS Widget Code · HTML Fix emojis PY Claude is AI and can make mistakes. Please double-check responses. Widget · HTML Copy MINT Outdoor - Chat with Gwen

MINT OUTDOOR

Chat with Gwen, Your Personal Shopping Concierge

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Hello! I'm Gwen, your personal shopping assistant at MINT Outdoor. I'm here to help you find the perfect outdoor furniture for your garden and answer any questions about our range. What are you looking for today?
Gwen is typing