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AI Provider Setup

Kamerplanter supports multiple AI providers that you can choose based on your hardware, privacy requirements, and budget. This page explains how to set up each provider and configure it in Kamerplanter.

Prerequisites

  • Kamerplanter is installed and running
  • Access to Settings > AI Provider (tenant admin or own settings)

Provider Overview

Provider Type Privacy Cost Recommendation
Ollama Local No data sharing Free Self-hosted
llama.cpp HTTP Server Local No data sharing Free Advanced users
OpenAI API Cloud Transferred to OpenAI (USA) Pay-per-token Best quality
Anthropic Claude API Cloud Transferred to Anthropic (USA) Pay-per-token Best quality
OpenAI-compatible APIs Local or Cloud Depends Variable Advanced users

Recommendation for getting started

If you self-host Kamerplanter: start with Ollama + gemma3:4b. This model runs on most desktop computers from 2020 onwards without a GPU and shares no data externally.

Ollama is a program that runs language models locally on your machine or server. No data leaves your network.

Hardware Requirements

Hardware RAM Recommended Model Response Time (Tip Cards)
Raspberry Pi 5, older NUCs 8 GB llama3.2:3b 15–30 seconds
Desktop/laptop from 2020+ 16 GB gemma3:4b 10–20 seconds
GPU 6–8 GB VRAM (GTX 1060, RX 580) — mistral:7b 2–5 seconds
GPU 12 GB VRAM (RTX 3060) — llama3.1:8b 1–3 seconds
GPU 16 GB VRAM and more — mistral-small:22b 2–5 seconds

Why small models work well

Kamerplanter sends a precise context (current phase, EC/pH/VPD, care history) directly to the model. A 4B model with concrete context produces better plant tips than a 70B model without context.

Installing Ollama

curl -fsSL https://ollama.com/install.sh | sh

The Ollama service starts automatically and is available at http://localhost:11434.

Download the installer from ollama.com/download and open the .dmg file.

After installation, the Ollama icon appears in the menu bar.

Download the installer from ollama.com/download and run it.

Ollama runs as a background service and is available at http://localhost:11434.

docker run -d --name ollama \
  -p 11434:11434 \
  -v ollama_data:/root/.ollama \
  ollama/ollama

With GPU support (NVIDIA):

docker run -d --name ollama \
  --gpus all \
  -p 11434:11434 \
  -v ollama_data:/root/.ollama \
  ollama/ollama

Downloading a Model

Open a terminal and download the recommended model:

# Recommended for most users (16 GB RAM)
ollama pull gemma3:4b

# For machines with less RAM (8 GB)
ollama pull llama3.2:3b

# For GPU users with 8+ GB VRAM
ollama pull mistral:7b

Test Ollama

Verify that Ollama works: 

ollama run gemma3:4b "What temperature does basil need during germination?"

Configuring in Kamerplanter

  1. Open Settings > AI Provider
  2. Click Add Provider
  3. Select Ollama
  4. Enter the URL: http://localhost:11434 (or your server's IP address)
  5. Select the model from the dropdown (or type gemma3:4b)
  6. Click Save, then Test Connection

Ollama on another machine

If Ollama runs on a different machine (e.g., a NAS), replace localhost with that machine's IP address. Ensure port 11434 is reachable on your network.

llama.cpp HTTP Server

llama.cpp is an alternative to Ollama for advanced users who want to use GGUF models directly from the Hugging Face community or other sources.

Starting the Server

# llama.cpp HTTP server (after compilation)
./llama-server \
  --model /path/to/model.gguf \
  --host 0.0.0.0 \
  --port 8080 \
  --ctx-size 4096

Configuring in Kamerplanter

  1. Open Settings > AI Provider
  2. Click Add Provider
  3. Select OpenAI-compatible (llama.cpp offers an OpenAI-compatible API)
  4. Enter the URL: http://localhost:8080
  5. Leave the API key field empty
  6. Enter the model name as local or the name of your GGUF model
  7. Click Test Connection

OpenAI API

OpenAI provides high-quality cloud models. Your plant data is transferred to OpenAI servers in the USA for every request.

Privacy notice

When using the OpenAI API, your plant data (phase, measurements, cultivar name, fertilization history) is transferred to OpenAI in the USA. When using a cloud provider for the first time, Kamerplanter asks for your GDPR consent. You can revoke this at any time under Settings > Privacy.

Creating an API Key

  1. Open platform.openai.com
  2. Sign in (or create an account)
  3. Navigate to API keys
  4. Click Create new secret key
  5. Copy the key (it is only shown once)

Configuring in Kamerplanter

  1. Open Settings > AI Provider
  2. Click Add Provider
  3. Select OpenAI
  4. Paste your API key
  5. Choose a model:
  6. gpt-4o-mini — affordable, fast, good for tip cards
  7. gpt-4o — best quality, higher cost
  8. Click Save
Model Strengths Approximate Cost
gpt-4o-mini Fast, affordable, good for simple diagnoses ~$0.001 per request
gpt-4o Best quality, complex reasoning ~$0.01 per request

Anthropic Claude API

Anthropic Claude is an alternative to OpenAI with strong analytical capabilities. Data is also transferred to servers in the USA.

Privacy notice

Analogous to the OpenAI API: your plant data is transferred to Anthropic servers in the USA for every request. GDPR consent is required.

Creating an API Key

  1. Open console.anthropic.com
  2. Sign in (or create an account)
  3. Navigate to API Keys
  4. Click Create Key
  5. Copy the key

Configuring in Kamerplanter

  1. Open Settings > AI Provider
  2. Click Add Provider
  3. Select Anthropic
  4. Paste your API key
  5. Choose a model:
  6. claude-haiku-4-5 — fast, affordable, good for tip cards
  7. claude-sonnet-4-6 — very good analysis quality
  8. Click Save
Model Strengths Approximate Cost
claude-haiku-4-5 Very fast, affordable ~$0.001 per request
claude-sonnet-4-6 Precise diagnoses, nuanced responses ~$0.008 per request

OpenAI-Compatible APIs

Many local and cloud services offer an OpenAI-compatible API. These include:

  • LM Studio — GUI application for local models (Windows/macOS/Linux)
  • vLLM — High-performance inference for servers
  • Together AI — Cloud service with open-source models
  • Mistral AI — Cloud service with Mistral models
  • Groq — Very fast cloud inference

Configuring in Kamerplanter

  1. Open Settings > AI Provider
  2. Click Add Provider
  3. Select OpenAI-compatible
  4. Enter the Base URL of the service (e.g., http://localhost:1234/v1 for LM Studio)
  5. Enter an API key if the service requires one (leave empty for local services)
  6. Enter the model name
  7. Click Test Connection

LM Studio example

LM Studio starts a local server at http://localhost:1234/v1. Model name: the name of the loaded model, e.g., lmstudio-community/gemma-3-4b-it-GGUF.

Provider Priority and Fallback

If you have multiple providers configured, you can set one as the default. If the default provider is unreachable, the system switches to the next active provider.

If no provider is available, the rule-based fallback activates: the system generates tip cards based on master data and the current phase — without a language model.

Frequently Asked Questions

Can I use different providers for different features?

Currently, Kamerplanter uses the configured default provider for all AI features. Per-feature provider selection (e.g., local for chat, cloud for diagnosis) is planned for a future release.

How can I control cloud provider usage costs?

OpenAI and Anthropic provide usage dashboards and budget limits in their control panels. Tip cards are generated daily in the background and cached (4 hours), which significantly reduces consumption.

Ollama won't start or is unreachable — what should I do?

Check: (1) Is the Ollama service running? (systemctl status ollama on Linux). (2) Is Ollama on port 11434? (curl http://localhost:11434). (3) Is the model downloaded? (ollama list).

The model responds in a different language — what can I do?

Kamerplanter sends all requests in German and instructs the model to respond in German. If the model still responds in another language, try a larger model (gemma3:4b instead of llama3.2:3b).

See Also