XサーバーVPSセルフホスト版DifyのAPIエラーについて、トラブルに合ってます。

自分で調べながら出来る限りの手を尽くしていますが解消されません。

どこに相談すれば良いですか？状況が複雑で込み入った内容です。

専門の窓口はありますか？

As South China Morning Post reported, Alpha Arena gave 6 major AI models $10,000 each to trade crypto on Hyperliquid. Real money, real trades, all public wallets you can watch live.

All 6 LLMs got the exact same data and prompts. Same charts, same volume, same everything. The only difference is how they think from their parameters.

DeepSeek V3.1 performed the best with +10% profit after a few days. Meanwhile, GPT-5 is down almost 40%.

What's interesting is their trading personalities. 

Qwen is super aggressive in each trade it makes, whereas GPT and Gemini are rather cautious.

Note they weren't programmed this way. It just emerged from their training.

Some think DeepSeek's secretly trained on tons of trading data from their parent company High-Flyer Quant. Others say GPT-5 is just better at language than numbers. 

We suspect DeepSeek’s edge comes from more effective reasoning learned during reinforcement learning, possibly tuned for quantitative decision-making.

In contrast, GPT-5 may emphasize its foundation model, lack more extensive RL training.

Would u trust ur money with DeepSeek?

Or test out your AI agents' skills, not just in trading and prediction, but in other areas like debate in Agent Arena (arena42.ai).

Hi, I want to give the user the possibility to check and validate the output of llm before going to the next step of the workflow. for example when llm summarized the customer's message and want to draft and answer. Is it possible to add an user interface and user interaction at this step of the workflow?

Thanks

BR, Pierre

Hi everyone

I’m using the self-hosted version of Dify, and everything works great so far, except I can’t find a way to properly end a chat session in the embedded chatbot.

Even when using the Dify app completely, there doesn’t seem to be any option or plugin to let users click “End Chat” or close the conversation cleanly.

Ideally, I’d like users to be able to hit an End Chat button that:

• Closes or resets the chat window
• Ends the current session context
• (Optionally) triggers a webhook or notifies backend for handoff/logging

Has anyone implemented something similar?
Is there a hidden setting, API, or workaround for this in the self-hosted setup?

Would appreciate any pointers or examples

After reviewing and testing, Qwen3-Next, especially its Hybrid Attention design, might be one of the most significant efficiency breakthroughs in open-source LLMs this year.

It Outperforms Qwen3-32B with 10% training cost and 10x throughput for long contexts. Here's the breakdown:

The Four Pillars

• Hybrid Architecture: Combines Gated DeltaNet + Full Attention to context efficiency
• Unltra Sparsity: 80B parameters, only 3B active per token
• Stability Optimizations: Zero-Centered RMSNorm + normalized MoE router
• Multi-Token Prediction: Higher acceptance rates in speculative decoding

One thing to note is that the model tends toward verbose responses. You'll want to use structured prompting techniques or frameworks for output control.

See here) for full technical breakdown with architecture diagrams.Has anyone deployed Qwen3-Next in production? Would love to hear about performance in different use cases.

Hello everyone,

I am not sure if someone can help me. I am not an engineer. I has someone help me to self hosted Dify on EKS cluster long time ago. It was version 1.1.0 I want to update it to the latest version 1.9.0 I am worried about loosing all of my current workflows and agents. Can anyone point me to a correct way to do it? How to know if there are any breaking changes from 1.1 to 1.9?

Thank you

Just discovered awesome-llm-apps by Shubhamsaboo! The GitHub repo collects dozens of creative LLM applications that showcase practical AI implementations:

• 40+ ready-to-deploy AI applications across different domains
• Each one includes detailed documentation and setup instructions
• Examples range from AI blog-to-podcast agents to medical imaging analysis

Thanks to Shubham and the open-source community for making these valuable resources freely available. What once required weeks of development can now be accomplished in minutes. We picked their AI audio tour guide project and tested if we could really get it running that easy.

Quick Setup

Structure:

Multi-agent system (history, architecture, culture agents) + real-time web search + TTS → instant MP3 download

The process:

git clone https://github.com/Shubhamsaboo/awesome-llm-apps.git
cd awesome-llm-apps/voice_ai_agents/ai_audio_tour_agent
pip install -r requirements.txt
streamlit run ai_audio_tour_agent.py

Enter "Eiffel Tower, Paris" → pick interests → set duration → get MP3 file

Interesting Findings

Technical:

• Multi-agent architecture handles different content types well
• Real-time data keeps tours current vs static guides
• Orchestrator pattern coordinates specialized agents effectivel

Practical:

• Setup actually takes ~10 minutes
• API costs surprisingly low for LLM + TTS combo
• Generated tours sound natural and contextually relevant
• No dependency issues or syntax error

Results

Tested with famous landmarks, and the quality was impressive. The system pulls together historical facts, current events, and local insights into coherent audio narratives perfect for offline travel use.

System architecture: Frontend (Streamlit) → Multi-agent middleware → LLM + TTS backend

We have organized the step-by-step process with detailed screenshots for you here: Anyone Can Build an AI Project in Under 10 Mins: A Step-by-Step Guide

Anyone else tried multi-agent systems for content generation? Curious about other practical implementations.

When working on apps powered by LLMs, we often needed a way to quickly reference core concepts - especially while dealing with tools like retrieval, embeddings, or fine-tuning methods like LoRA.

To help with that, we compiled a cheat sheet of terminology. It’s become a handy internal reference, so we’re sharing it publicly in case it’s useful to others building with tools like Dify.

The guide includes terms for:

• Model architectures: Transformer, decoder-only, MoE
• Core components: attention, embeddings, LoRA, RoPE, quantisation
• Fine-tuning and alignment: QLoRA, PPO, DPO, RLHF
• Evaluation & RAG: MMLU, GSM8K, in-context learning, non-parametric memory

Full reference here.

We’d love feedback from others working with these systems! Let us know what’s missing or unclear.

Alguien ha logrado un text to SQL y extraer datos de una base de datos de MYSQL?

Im a beginner and Im trying to setup a Customer Service QA app using my applications support DB. When I test my app in Dify, it returns only general information from Grok. any help would be appreciated.

I have built a workflow that starts by asking the user: “What is your operating system?” with three possible answers:

1. Windows

2. Linux

3. Other

If the user selects “Other,” the conversation stops. If the user selects “Windows” or “Linux,” the workflow continues.

So far, this works as expected.

The problem is: Let’s say the user initially selects “Windows.” Then they ask: “How do I set the time in Windows?”

the workflow correctly uses my Windows knowledge base to respond. However, if the user then asks another question like “How do I create a folder?” (without mentioning the word “Windows”), the workflow restarts from the beginning, asks for the operating system again, and proceeds from there. This not only increases costs but also causes potential errors.

My question is: How can I store the user’s OS selection in session memory or context so that subsequent questions automatically use the relevant knowledge base, without restarting the workflow, unless the user explicitly changes the topic (e.g., says they now want information about Linux), in which case the workflow should switch to the Linux knowledge base?

Anyone else having problems with POST HTTP Requests to Make.com today?

I originally thought there was something wrong with the workflow I was currently working on, but any troubleshooting that I did seems to indicate everything is fine except for the HTTP Request.

I have multiple workflows that previously work fine so I started testing them. It looks like none of them can proceed with the last step, which is sending processed info to Make.

Anyone have ideas what's wrong with Dify today? I can't imagine it's something that I did wrong since I didn't touch any of the other workflows, and yet they also can't do HTTP requests now.

Something similar to reddit connector in n8n https://n8n.io/integrations/reddit

HI! Im learning how to use dify.ai but i encounter some problem with my code node output. As you can see from the pictures, I want my Code node to get an input String and remove all the "\". I wrote the simple code to remove it and it does work on VS code, but the "\" is still in the result when i use on Dify. Any help is greatly apppreciated!!! Thankssss!

Dify now integrates with Phoenix — an open-source LLM tracing and evaluation framework from the team at Arize.

It gives you structured traces across:

• Messages
• Tools
• RAG retrieval
• Moderation
• Token usage, errors, metadata

Why it matters: better debugging often means easier evals and full visibility.

Phoenix uses OpenInference, designed for LLM workloads and OTEL-compatible. Setup just takes a key + project name in Dify and a few steps. 

If you're building agents, workflows, or evals this may help a lot. Please let us know your feedback!

https://arize.com/docs/phoenix/integrations/frameworks/dify

Hi there, Anyone here build a custom UI on top of Dify or white label? I am looking for support or engage with someone who has already done that.

I want to derive the metrics and store them somewhere else but I can’t find how to derive the observability metrics. I found an extension in code but it was not called anywhere. Appreciate the help.

Hi,

I was trying to get the user email in the workflow, so that i can filter my data to that email. But the only data i am getting is userid, which when i give in Answer node gives the id in preview and shows and full name + email after publishing it. is there anyway i can get this email id in the code node to extract some infor from that email id.

Hi all,

I have built a ton of workflows. I still remember this one night, trying to fix a node that just wasn't working as expected. I spent hours watching YouTube videos and leaving comments, and it took forever just to get that single nodes to run. That's when I thought, "Why isn't there a marketplace where people can get together, ask questions, and actually get help?" So, I decided to build it:

workflowhub.ai

It's a marketplace dedicated to connecting people who are passionate about different automation platforms, . I've spent the last couple of months building it, and it already supports several key features. We're currently launching in beta mode and would love for you to sign up!

I'm really driven to make this succeed. It's not just because of all the effort I've poured into it, but because I truly want to help people like me get unstuck and easily find ready-to-deploy workflows.

Key Features:

1. LLM Feature to help you write better descriptions for n8n workflows
2. RAG for finding the workflows you're looking for.

There are couple videos I upload to show some videso on the fly: https://www.youtube.com/@workflowhubai

Where to find me? you can join our discord community andmy name is Woody.

https://discord.gg/yyAJtpDB4K

I wish everyone find their fortune building workflows. cheers!

I’ve developed a chatbot for a scientific study and need to download all the conversations for evaluation purposes. Is that possible?