Agentic AI Docker Stack

@huzaifa306

Hi, I can build and test the Docker Compose stack with Open WebUI, Ollama, Qwen3 14B, NanoClaw, persistent storage, MCP, browser tools, memory, and isolated execution. I will also configure easy switching between the local model and OpenAI. I have experience with Docker, Linux, local LLMs, and AI systems. I will deliver a tested project folder with the Docker Compose file, environment template, required scripts, and simple README.

@naminghn

Hi there, I understand you're looking for a complete Docker Compose deployment of the Agentic AI Stack. I can create a customizable setup for you that requires only the .env configuration. Not only will I ensure all components—including Open WebUI, Ollama, and NanoClaw—are properly configured, but I will also conduct thorough testing to deliver a robust solution. Your satisfaction is my priority and I guarantee that I will deliver you a high-quality result. Regards, Ali

@codeandcommand

I can set this up with docker-compose, Ollama for local models plus OpenAI fallback, and wire the API keys and networking so containers talk cleanly. I can start right now and have a working stack ready by tomorrow. The 20-60 EUR range and timeline here are starting points based on the post, final numbers depend on which agent framework and models you're running. Want me to send a quick scope doc so we can get moving?

@GobindSawarn

My name is Govind Sawarn, and I have over six years of experience as a professional who values timeliness, attention to detail, and consistent communication. My skills in API Integration and Docker Compose make me an excellent candidate for your project requiring the creation of a Docker Compose deployment for your Agentic AI stack. I understand the critical requirement of testing and delivering a fully functional solution for your training program with no hassle on your end. With regards to the server aspect, I have worked with various hosting environments and know how to customize deployments based on server capacities. Your 32GB RAM, CPU-only server would be skillfully configured by me through my Docker expertise to work efficiently with 1-16 CPUs to accommodate around 10 users seamlessly.

@lazarr4

Hello, A similar agentic AI stack I deployed for a research team handled 12 concurrent users on a 32 GB RAM server without crashes. Open WebUI and NanoClaw will run in separate containers, each with its own user-space and persistent volumes for Ollama models and chat history. LiteLLM will sit between the services, letting you switch between local Qwen3 14B and OpenAI via the same API endpoint—just update the .env key. The whole stack starts with docker compose up. Participants get stable access, no port conflicts, and zero public exposure for Ollama or internal APIs. Everything is pre-configured and tested locally before you deploy; only the .env values need adjustment. Drop the folder on the server, run docker compose up, and it should just work. Thanks, Lazar

@anshumanvermaUK

Hi, I can create and thoroughly test the complete Docker Compose Agentic AI stack with Open WebUI, Ollama/Qwen3, NanoClaw, persistent volumes, MCP support, and configurable model providers. I’d also include LiteLLM to make switching between local Ollama and OpenAI models straightforward. Thanks Anshuman

@ahmaddar2970

Accepted under manual override. I will deliver a ready-to-run Docker Compose project for the described Agentic AI stack, focused on a clean .env-based setup, persistent volumes, and practical testing before handoff. I’ll include the compose file, example environment config, required scripts/configuration, and a concise README so you can deploy by filling in settings and running docker compose. I’ll also keep the setup aligned with your constraints: Open WebUI for private user workspaces, Ollama with configurable Qwen3 14B and automatic model pull, internal services kept private, and a clear path to switch between local and OpenAI-backed models. If LiteLLM improves that abstraction cleanly, I’ll include it; otherwise I’ll suggest the simplest robust alternative. The deliverable will be organized as a single project folder and tested for startup consistency and service wiring as far as possible within the provided requirements.

@naseeb1995

Hello Your project Agentic AI Docker Stack sounds exciting, and I would love to contribute. I specialize in AI-powered automation, intelligent agents, workflow optimization, API integrations, custom chatbots, and OpenAI solutions. I build systems that simplify operations, improve productivity, and reduce manual workload. My focus is always on delivering reliable solutions that support long-term business success. Best Regards, Naseeb A.

@miguelcen64

Hello, The key part of this project is **making Open WebUI, Ollama, and NanoClaw run as a ready-to-run Docker Compose stack with clean isolation and only .env setup**. I can help you handle this accurately and efficiently without overcomplicating the process. I have hands-on experience with **API Integration, Docker Compose, and Ubuntu**, including deployments where services needed persistent volumes and controlled exposure. For your project, I would focus on wiring the compose services, validating Ollama model startup with configurable model selection, and structuring private versus shared workspaces so the final result is stable and easy to run. I can start immediately and expect to complete this within 7 days. One detail I'd like to confirm before starting: **should LiteLLM route both Open WebUI and NanoClaw through a single OpenAI-compatible endpoint, or only be used for future provider switching?** Best regards, Miguel

@jtolbert0175

Hi env. The technical challenge here is to ensure smooth integration and isolation of various components like multi user Open WebUI workspaces and shared NanoClaw agents using Docker volumes for persistent data while ensuring Ollama remains unexposed publicly. I've previously set up similar Docker environments for scalable AI applications using Docker Compose and API integration, ensuring secure handling of models and persistent states. My experience with AI-driven SaaS platforms aligns perfectly with achieving reliable deployments. I appreciate your choice of handling Nginx Proxy Manager separately, as this modularity facilitates maintenance and scalability. I can help design this stack, ensuring all configurations are tested and ready for deployment. Let's discuss how this setup can perfectly suit your needs during the training sessions. Thanks, Jonathan

@ManojVala09

I’m currently working as a Software Engineer, with hands-on experience in the same technologies and requirements outlined in your project description. I’ve been working on Python-based backend development, APIs, AI/ML, LLM integrations, RAG, and scalable application development in real-world projects. Based on the requirements, I believe my experience aligns well with what you’re looking for, and I can contribute effectively from the start. I’d be happy to discuss your requirements and understand the project in more detail. Let’s build something great together!