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Still Stuck At Http Request (❗Need Help❗)
So I was able to Set up my whole Http request for my Instagram chatbot and everything is working and sometime Instagram chat I am also getting replies but sometime I just simply don't get any reply Like when I asked "what services do you guys provide?" and chatgpt and I also believe that problem is when AI agent reply it also include " \r \t \n \\ \" * message is not delivered and for that reason http is not send replies. I have done this HTTP configuration AS you guys can see in the photo. Give Suggestions how to fix?
Still Stuck At Http Request (❗Need Help❗)
2 likes • 18h
When you write manual JSON in n8n like "text": "{{ $json.reply }}", any unescaped double quotes, raw line breaks (\n), or tabs generated by ChatGPT break the JSON string syntax, causing Meta's API to reject it or n8n to throw a bad JSON error. The cleanest fix is to stop using raw JSON in the HTTP Request node—change Specify Body from "Using JSON" to "Using Fields Below". Add recipient.id as {{ $json.senderid }} and message.text as {{ $json.reply }}. When you use individual fields, n8n automatically handles string escaping and JSON serialization under the hood so newlines and quotes won't crash the request.
Ai image generation
does anyone know how to train open ai image models in best way so that it will generate the kind of images i want it to generate for my saas app i have written backend prompts but sometimes its still struggling and giving misdirected output
1 like • 18h
Since OpenAI doesn't allow direct model training/fine-tuning for DALL-E 3, backend prompt drifting usually happens because DALL-E's internal safety/enhancement layer reinterprets your text. To lock in consistency, use a fast LLM (like GPT-4o-mini) as a pre-processing middleware that takes user inputs and outputs a strictly formatted, parameter-heavy prompt (specifying lighting, camera angle, medium, and color palette) before calling the image API. If you strictly require custom image model training for specific visual assets or characters, switching your SaaS backend to FLUX LoRAs hosted on Fal.ai or Replicate will give you far more deterministic control than OpenAI alone.
LangChain's new posts on building agent 'harnesses' look useful, but they create a trap for builders.
The hardest part of a complex agent build is often the architecture. So when LangChain publishes posts on their 'paid media agent' or a generic agent 'harness', it's tempting to treat them as a blueprint. The gotcha is that these are high-level concepts, not implementations. The articles don't include code, performance metrics, or the actual challenges they hit. They show you the big boxes in the diagram but skip the hard parts: the exact tool schemas the API retry logic, the specific validation layer that keeps the agent from breaking on an edge case You end up with a map that's missing all the roads. If you've built a custom agent harness, what's one piece of the glue code validation, state management retries that the public case studies always seem to skip?
1 like • 18h
The missing road in almost every conceptual architecture is partial execution state recovery. High-level diagrams assume a multi-tool execution path is atomic either the whole sequence succeeds, or it fails. In reality, an agent might successfully execute 2 out of 3 external API calls before hitting a timeout or rate limit on the third. Without a custom transaction log or state checkpointing in your harness, retrying the run means re-executing actions that already succeeded (like double-posting or making duplicate API calls).
Starting out (2)
"I'm looking for a video course or tutorial that walks through building a SaaS subscription business from start to finish — specifically selling AI-powered apps to other businesses. Ideally it would cover: - Setting up subscriptions and recurring billing - Role-based access control (admin vs. regular users, so not everyone has full permissions) - Multi-tenancy — letting each business client have their own isolated workspace - Payment onboarding for clients, so they can connect their own bank accounts and receive money directly (e.g. Stripe Connect) - Everything else needed to launch and run it
2 likes • 18h
For multi-tenancy, RBAC, and Stripe Connect payouts, a full-stack Next.js + Supabase (or PostgreSQL) architecture is usually the cleanest path forward. Instead of buying a single course that might be outdated, search for tutorials focusing on "Supabase Multi-Tenant RLS" for workspace data isolation, "Clerk / Kinde Auth" for instant organization-level role permissions (admin vs user), and "Stripe Connect Express API" for client payout onboarding. Building on top of an established B2B SaaS boilerplate that already has these enterprise features configured will save you hundreds of hours of edge-case development.
Need help with whatsapp OAuth account
In n8n I was building a whatsapp lead flow where the client texts to whatsapp and the flow gets triggered. The issue is, it requires the meta dev acc for like every whatsapp. But if I were to sell it to a client, it is not a realistic option. It doesn't send otp sometimes and creating it is a pain plus clients wouldn't want to give their credentials of that. So what is the most easiest way of avoiding all that tantrum and make it so that client remains satisfied and I don't end up doing something that the client dislikes? What do you guys usually ise in thiß situation?
Need help with whatsapp OAuth account
3 likes • 1d
@Ahsan Zahid glad that helped
1 like • 1d
@Ahsan Zahid I fo have request will you be able to write a shout-out post about my help here in the community win section, that whould be really helpful of you
1-10 of 1,230
Muhammad Khan
6
251 points to level up
@muhammad-khan-7966
Hey I build AI agents that do actual work one saved a client 84 hours a week. n8n, Claude, Retell AI, that stack. Open to new client work right now

Active 18h ago
Joined Aug 16, 2025
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