LibreChat and SillyTavern with Ollama: Local Chat Interfaces Compared

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Once you have Ollama running, the question becomes: what front-end do you actually talk to your models through? The terminal is fine for quick tests, but for daily use you want a proper chat interface — conversation history, model switching, file uploads, and a UI you’d actually want to spend time in. LibreChat and SillyTavern are two of the most popular self-hosted options, and they serve quite different use cases. LibreChat is a polished, multi-user ChatGPT replacement. SillyTavern is a feature-rich interface originally designed for roleplay and character-based conversations but increasingly used as a general-purpose local AI frontend. This guide covers what each does, how to connect them to Ollama, and when to use one versus the other.

LibreChat: The ChatGPT Replacement

LibreChat is explicitly designed to replicate and extend the ChatGPT experience — it looks and feels like ChatGPT but runs on your own infrastructure with your own models. The UI is polished and familiar: a conversation list on the left, a chat window in the centre, model selection at the top. If you want something you can hand to a non-technical colleague and have them use immediately without explanation, LibreChat is the right choice.

Installing LibreChat

git clone https://github.com/danny-avila/LibreChat.git
cd LibreChat
cp .env.example .env
docker compose up -d

LibreChat uses a multi-container Docker setup — it includes its own MongoDB database and Meilisearch instance. First startup takes a few minutes while images download. Access the UI at http://localhost:3080 and create an admin account on the first visit.

Connecting LibreChat to Ollama

Edit the librechat.yaml configuration file (or create one from the example) and add an Ollama endpoint:

endpoints:
  custom:
    - name: "Ollama"
      apiKey: "ollama"
      baseURL: "http://host.docker.internal:11434/v1/"
      models:
        default: ["llama3.2", "qwen2.5-coder:7b", "mistral"]
        fetch: true
      titleConvo: true
      titleModel: "llama3.2"
      modelDisplayLabel: "Ollama"

The fetch: true option pulls the model list from Ollama automatically rather than requiring you to list models manually. Set baseURL to http://host.docker.internal:11434/v1/ since LibreChat runs in Docker — this is the host-accessible URL from within a container on macOS and Windows Docker Desktop. On Linux, use the Docker bridge IP instead: http://172.17.0.1:11434/v1/.

Restart LibreChat after editing the config: docker compose restart. The Ollama endpoint appears in the model selector dropdown in the UI.

LibreChat Features Worth Knowing

Multi-user with authentication. LibreChat supports multiple user accounts with email/password authentication, OAuth (Google, GitHub, Discord), and LDAP. For team deployments where you want a shared LibreChat instance backed by Ollama on a capable server, the multi-user system handles access control cleanly.

File and image uploads. With a vision-capable Ollama model (LLaVA, Gemma 3, Moondream), LibreChat passes uploaded images to the model automatically. Document uploads (PDFs, text files) are extracted and added to the conversation context.

Conversation management. Full conversation history, folder organisation, search across past conversations, conversation sharing (shareable links). For users who have long AI conversation histories to manage, this is significantly better than the Ollama CLI or most simpler frontends.

Multiple endpoints simultaneously. You can configure LibreChat to connect to both Ollama and the OpenAI API (or Anthropic, Gemini, Azure) and switch between them per conversation. Useful if you use local models for most things but occasionally need a frontier model for a specific task — the same chat UI serves both.

SillyTavern: The Power User’s Frontend

SillyTavern started as a frontend for AI roleplay and creative writing — character cards, personas, world information, detailed system prompts, and elaborate context management. That heritage makes it exceptionally configurable for any use case that benefits from fine-grained control over how the model receives context. In 2025–2026, it’s grown significantly beyond roleplay into a general-purpose local AI frontend with a dedicated user base of developers and power users.

Installing SillyTavern

git clone https://github.com/SillyTavern/SillyTavern.git
cd SillyTavern
npm install
node server.js

Or with Docker:

docker run -d -p 8000:8000   -v sillytavern_data:/home/user/app/data   ghcr.io/sillytavern/sillytavern:latest

Access at http://localhost:8000. No account setup required — it opens directly to the chat interface.

Connecting SillyTavern to Ollama

In SillyTavern’s top bar, click the API connection icon (plug icon). Select “Ollama” from the API dropdown. Enter your Ollama URL (http://localhost:11434) and click Connect. SillyTavern fetches your available models and lets you select one. That’s the full setup — no config files to edit.

SillyTavern connects directly without Docker networking issues (since it’s typically run natively rather than in a container). If you do run it in Docker, use http://host.docker.internal:11434.

SillyTavern Features Worth Knowing

Advanced context management. SillyTavern gives you fine-grained control over the system prompt, character cards (persistent persona/role definitions), world info (background context injected at specific token positions), author’s notes, and memory summarisation. For applications where how context is assembled matters — long creative projects, complex assistant personas, research workflows with specific background context — this level of control is valuable.

Extensions ecosystem. SillyTavern has a large extensions library: web search integration, image generation triggers, text-to-speech, translation, knowledge base retrieval, and more. Many extensions work with Ollama as the backend. The extensions make it significantly more capable than a plain chat interface.

Sampler settings. Full access to generation parameters — temperature, top-p, top-k, repetition penalty, mirostat, and more — with per-preset saving. For users who care about output character and want to fine-tune how their model generates, SillyTavern exposes all the knobs.

Multiple personas and characters. Create different “characters” (system prompts and personas) and switch between them per conversation. Useful for having a strict technical assistant persona, a casual creative writing persona, and a structured research persona — each with its own system prompt and context configuration, selectable from a character card library.

Figure 1 — LibreChat vs SillyTavern: Feature Comparison

Feature LibreChat SillyTavern Setup difficultyModerate (multi-container Docker)Easy (Node.js or Docker) UI stylePolished, ChatGPT-likeFeature-dense, power user Multi-user / authBuilt-in (email, OAuth, LDAP)Single user (basic auth optional) Context controlStandard system promptAdvanced (world info, personas, depth) Extensions / pluginsGrowingLarge ecosystem Best forTeams, ChatGPT replacementPower users, creative, research

Which to Choose

The decision is fairly clear once you know your priorities. Choose LibreChat if you want a polished, familiar interface that works well for multiple users, if non-technical people will use it, or if you’re setting up a shared team AI assistant where a clean UX matters more than configurability. The ChatGPT-like interface lowers the learning curve to zero for anyone already familiar with ChatGPT, and the multi-user authentication system handles team deployments cleanly.

Choose SillyTavern if you’re a developer or power user who wants maximum control over how prompts are constructed, if you work with creative writing, roleplay, or complex character-based interactions, or if you want to experiment extensively with sampler settings and context management. The extensions ecosystem is also a strong reason to choose SillyTavern if there’s a specific integration you need — web search, image generation, TTS — that’s available as a SillyTavern extension but not in LibreChat.

Many users run both: LibreChat for day-to-day productivity tasks where the polished UI is pleasant to use, and SillyTavern for sessions where they want to experiment with specific prompt configurations or work on creative projects. Since both run locally alongside Ollama and use minimal resources when idle, keeping both installed costs nothing beyond the disk space for the Docker images.

Open WebUI: The Third Option Worth Mentioning

Any comparison of Ollama frontend options should mention Open WebUI — it’s arguably the most popular self-hosted Ollama interface and deserves a brief mention even in a guide focused on LibreChat and SillyTavern. Open WebUI sits between the two: more polished than SillyTavern, more flexible than a minimal chat interface, with model management, RAG, multi-user support, and a clean modern UI. If you haven’t tried it yet, it’s worth starting with Open WebUI before deciding whether you need LibreChat’s auth features or SillyTavern’s advanced context controls. Many users find Open WebUI is all they need, and it requires less setup than LibreChat while being more capable out of the box than SillyTavern for non-power-users.

docker run -d -p 3000:8080   --add-host=host.docker.internal:host.gateway   -v open-webui:/app/backend/data   --name open-webui   ghcr.io/open-webui/open-webui:main

Figure 2 — Ollama Chat Frontend Decision Guide

Your situation Recommended frontend Just getting started, want the easiest setupOpen WebUI Team deployment, multiple users, need authLibreChat Power user, want full control over prompts/samplersSillyTavern Creative writing, roleplay, character personasSillyTavern

Keeping Your Setup Running

Both LibreChat and SillyTavern benefit from a few maintenance habits. Update them periodically — both projects release frequently, and new versions often include bug fixes, UI improvements, and new features worth having. For LibreChat: git pull && docker compose pull && docker compose up -d. For SillyTavern: git pull && npm install && node server.js. Back up your data before updating — LibreChat stores conversations in MongoDB (back up the volume), SillyTavern stores everything in its data directory (just copy it). Configure auto-start so your frontend launches when your machine boots — a systemd service on Linux, a launchd plist on macOS, or a Docker restart policy. Once these habits are in place, the frontend becomes infrastructure you don’t think about — it’s just there when you open the browser, backed by whatever Ollama model you have loaded, handling conversations reliably day after day.

Security Considerations for Self-Hosted Frontends

Running a chat frontend that connects to Ollama introduces some security considerations worth thinking through before exposing anything beyond localhost. Neither LibreChat nor SillyTavern should be exposed to the public internet without proper authentication — LibreChat’s built-in auth handles this well for multi-user setups, but SillyTavern’s optional basic auth is minimal. For home network use accessible only from devices on your local network, the default setup is fine. For anything accessible from outside your home network — a VPN, a publicly accessible server, a cloud deployment — add a reverse proxy with HTTPS (Nginx + Let’s Encrypt or Caddy) in front of your frontend, enable authentication, and restrict access to known IP ranges where possible. The Ollama instance itself should remain on localhost or an internal network address, with the frontend acting as the only external entry point — never expose port 11434 directly to the internet without auth middleware, as it gives anyone who finds it unrestricted access to your models and compute.

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