notebook-ollama

Recipe card from the charly-jupyter plugin (Images — the deployable catalog).

notebook-ollama – Ollama integration notebook data candy

Candy Properties

Property	Value
Dependencies	(none)
Packages	(none)
Services	(none)
Volumes	`workspace` -> `/workspace` (from jupyter)
Data	`data/ollama` -> `workspace` volume, dest: `ollama`
Install files	(none)

How It Works

This is a data candy — it uses the data: field in charly.yml to map a directory of notebooks to a named volume with a subdirectory destination:

info: "Ollama integration notebook collection"

data:
  - src: data/ollama
    volume: workspace
    dest: ollama

At build time, the contents of data/ollama/ are staged into /data/workspace/ollama/ inside the box.

At deploy time, charly config or charly update copies the staged data into the workspace volume at <workspace>/ollama/. The dest: ollama field places the notebooks in a subdirectory rather than the volume root.

Included Notebooks

6 Jupyter notebooks covering different Ollama client libraries:

Notebook	Library	Features
`00_Ollama_Requests.ipynb`	`requests`	Raw REST API: list, show, generate, chat, stream, embed, copy, delete
`01_Ollama_GPU.ipynb`	`requests`	GPU verification: nvidia-smi, inference metrics, VRAM monitoring
`02_Ollama_OpenAI.ipynb`	`openai`	OpenAI-compatible API: completions, chat, multi-turn, stream, embed
`03_Ollama_Library.ipynb`	`ollama`	Native Python library: all API operations + model management
`04_Ollama_HuggingFace.ipynb`	`ollama`	HuggingFace GGUF model import, verification, inference
`05_Ollama_Anthropic.ipynb`	`anthropic`	Anthropic-compatible API: chat, system prompts, streaming, tool calling, vision

Manifest: notebooks.yaml — structured catalog with title, description, and ordering.

Network Connectivity

The notebooks default to http://localhost:11434 for the Ollama API endpoint. Each notebook reads:

OLLAMA_HOST = os.getenv("OLLAMA_HOST", "http://localhost:11434")

When the ollama box is deployed via charly config ollama, its env_provide automatically injects OLLAMA_HOST=http://charly-ollama:11434 into the global charly.yml env. Any container configured after ollama (or reconfigured with --update-all) automatically gets the correct Ollama endpoint — no manual environment setup needed.

Setup:

charly config ollama --update-all    # deploys ollama + propagates OLLAMA_HOST to all
charly start ollama
charly start jupyter-ml-notebook   # OLLAMA_HOST already set via env_provide

Both containers must be on the same charly Podman network for DNS resolution to work.

See /charly-core:charly-config for --update-all and /charly-ollama:ollama for env_provide details.

Notebook Compatibility Notes

ollama Python library env var gotcha

The ollama Python library creates its HTTP client at import time by reading OLLAMA_HOST from os.environ. Module-level functions (ollama.list(), ollama.generate(), etc.) are bound methods on this cached client. Simply setting a Python variable doesn’t propagate to the library.

The notebooks use this pattern to handle both fresh kernels and re-runs:

import os
OLLAMA_HOST = os.getenv("OLLAMA_HOST", "http://localhost:11434")
os.environ["OLLAMA_HOST"] = OLLAMA_HOST

import ollama
import importlib; importlib.reload(ollama)  # Rebinds module functions

Pydantic model changes (ollama >= 0.4)

The newer ollama library returns Pydantic models, not dicts. Model names are accessed via .model attribute (not ["name"]), and the list is .models (not .get("models", [])):

# Old (dict access)
model_names = [m.get("model", "") for m in models.get("models", [])]

# New (Pydantic attribute access)
model_names = [m.model for m in models.models]

Default models

5 notebooks use llama3.2:latest (3.2B, Q4_K_M)
ollama_anthropic.ipynb uses ministral-3:3b-instruct-2512-q4_K_M

Pull models before running: charly shell ollama -c "ollama pull llama3.2"

Usage

jupyter-ml-notebook:
  candy:
    - jupyter-ml
    - notebook-templates
    - notebook-finetuning
    - notebook-ollama
    # ... other candies

# Deploy and start both services
charly config ollama && charly start ollama
charly config jupyter-ml-notebook && charly start jupyter-ml-notebook

# Pull a model, then open notebooks
charly shell ollama -c "ollama pull llama3.2"
# Open http://localhost:8888 -> navigate to ollama/

Used In Boxes

/charly-jupyter:jupyter-ml-notebook

/charly-image:layer — data field documentation and candy authoring rules
/charly-core:charly-config — data provisioning during charly config setup
/charly-core:deploy — volume backing configuration
/charly-jupyter:notebook-finetuning — sibling data candy pattern (Unsloth fine-tuning notebooks)
/charly-jupyter:notebook-templates — sibling data candy pattern (starter notebooks)
/charly-ollama:ollama — the Ollama binary candy (server side)
/charly-ollama:ollama — the standalone Ollama box (must be running for notebooks to connect)
/charly-jupyter:jupyter-ml-notebook — the box that includes this candy

When to Use This Skill

Use when the user asks about:

The notebook-ollama candy or its contents
Ollama API tutorial notebooks or integration examples
How Jupyter notebooks connect to a separate Ollama container
The ollama Python library env var or Pydantic API gotchas
Which client libraries and API features are covered

/charly-check:check — declarative testing (check: block, charly check box, charly check live)