Ollama
A RocketRide LLM node that routes pipeline traffic through a locally-hosted Ollama server.
What it does
Provides text generation against an Ollama server running on your own hardware. The node acts as an llm connection for agents and other nodes, and can also be driven directly through its questions and answers lanes. Because inference stays on-premise and requires no external API key, it fits privacy-sensitive or air-gapped deployments. Internally, it uses langchain-openai (ChatOpenAI) against Ollama's OpenAI-compatible /v1 endpoint.
Lanes
| Lane in | Lane out | Description |
|---|---|---|
questions | answers | Send a question directly, receive a generated answer |
Profiles
Default: Llama 3.3 (llama3_3).
| Profile | Model | Context |
|---|---|---|
llama3_3 (default) | llama3.3:latest | 128,000 |
llama4-latest | llama4:latest | 10,000,000 |
qwen3-latest | qwen3:latest | 128,000 |
View 20 more models
| Profile | Model | Context |
|---|---|---|
custom | (user-specified) | 16,385 |
llama3_1-8b | llama3.1:8b | 128,000 |
llama3_1-70b | llama3.1:70b | 128,000 |
llama3_1-405b | llama3.1:405b | 128,000 |
phi4-14b | phi4 | 16,000 |
llama3_2-3b | llama3.2 | 128,000 |
llama3_2-1b | llama3.2:1b | 128,000 |
mistral-7b | mistral | 32,000 |
qwen2_5-7b | qwen2.5 | 128,000 |
qwen2_5-0_5b | qwen2.5:0.5b | 128,000 |
qwen2_5-1_5b | qwen2.5:1.5b | 128,000 |
qwen2_5-3b | qwen2.5:3b | 128,000 |
qwen2_5-14b | qwen2.5:14b | 128,000 |
qwen2_5-32b | qwen2.5:32b | 128,000 |
qwen2_5-72b | qwen2.5:72b | 128,000 |
deepseek-r1-1_5b | deepseek-r1:1.5b | 128,000 |
deepseek-r1-7b | deepseek-r1:7b | 128,000 |
deepseek-r1-14b | deepseek-r1:14b | 128,000 |
deepseek-r1-32b | deepseek-r1:32b | 128,000 |
deepseek-r1-671b | deepseek-r1:671b | 128,000 |
Configuration
Pick a profile to prefill the Ollama model, context limit, and server URL. Use custom to supply another Ollama tag, context token count, output limit, and endpoint; its initial context value is 16,385 tokens and its output limit 4,096.
Server base URL
Point the node at the Ollama server, normally http://localhost:11434. If the URL does not end in /v1, the node appends it automatically, so both http://localhost:11434 and http://localhost:11434/v1 work.
Temperature and reasoning effort
Temperature defaults to 0. When it is left unset for a reasoning model such as gpt-oss, the node uses 1.0; set reasoning_effort to low, medium, or high when the selected model supports that control.
The OpenAI client requires a non-empty API key, so the node sends the placeholder dummy-key, which Ollama ignores.
Upstream docs
Schema
| Field | Type | Description | Default |
|---|---|---|---|
model | string | Model Ollama model | |
modelOutputTokens | integer | Output Tokens Most tokens the model may write in one reply (at least 1,024). Leave it empty to keep the node's default. Reasoning models count their thinking against this limit: set it well above the reply you expect, or they can spend it all thinking and return nothing. It cannot exceed Tokens; a larger value is lowered to it. | |
modelTotalTokens | number | Tokens Total Tokens | |
ollama.profile | string | Model LLM model | "llama3_3" |
reasoning_effort | string | Reasoning Effort Optional reasoning budget for reasoning models: low, medium, or high. Leave unset to let reasoning models auto-use 'low'; a value set here always wins. Ignored by non-reasoning models. | |
temperature | number | Temperature Sampling temperature. Left unset by default so ollama.py can choose: 0 for standard models, and 1.0 for reasoning models (gpt-oss, deepseek-r1, qwen3, qwq, ...) so they emit a final answer instead of looping on empty output. Set an explicit value here to override the auto behavior. |
Dependencies
langchain-openailangchain-corelangchain