To send a prompt to a language model running on your computer, install Ollama, download a model, then call Ollama’s local chat API from Python. This walkthrough uses Ollama’s documented gemma4:e2b example and the official Python client. It is a local-development setup, not guidance for exposing a model server to the internet.
What you need for a local LLM API in Python
- A supported macOS, Windows, or Linux computer with Ollama installed.
- Python and a terminal. The documentation used here does not specify a Python version or a tested cross-platform matrix, so use a Python version supported by the current Ollama package.
- Disk space and memory appropriate for the model you choose.
Ollama’s current quickstart model example, Gemma 4 E2B, is about 7.2 GB to download. Ollama recommends 8 GB of available VRAM, or unified memory on a Mac, for that example. Those figures apply to this model example, not to every local model. Larger context windows need more memory; with less VRAM, Ollama may use system RAM, which can make responses slower. See the Ollama quickstart for current installation options and model guidance.
Install Ollama and download a model
- Install Ollama for your operating system using the official download page. Open the Ollama app where applicable, or follow the terminal setup shown for your platform.
- Open a terminal and download the model from the quickstart example:
ollama pull gemma4:e2b - Wait for the download to finish. Model identifiers may change as the library evolves; check the current quickstart if this name is unavailable.
A model name can include a tag, such as :e2b. The API reference says the tag is optional and defaults to latest; using an explicit tag makes it clear which model identifier your example requests. See Ollama’s API reference.
Start or confirm the local server
Ollama provides a local API at http://localhost:11434/api. On macOS and Windows, the app typically runs the service after launch. The quickstart specifically instructs Linux users to start the server with this command if it is not already running:
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ollama serveKeep that terminal open while you use the API. If the server is already active, starting another instance is unnecessary. Local requests do not need an API key, as Ollama states in its API introduction.
Send a first local LLM API request
The chat endpoint is http://localhost:11434/api/chat. A chat request supplies the model and a list of role-tagged messages. Set stream to false to receive one response object rather than a stream of objects.
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curl http://localhost:11434/api/chat -d '{
"model": "gemma4:e2b",
"messages": [
{"role": "user", "content": "Explain what a local API does in one sentence."}
],
"stream": false
}'The response contains a message object; its content field is the model’s reply. The API reference describes the request and response behavior, including streaming, at Ollama’s API reference.
Run an LLM locally with Python
Ollama’s Python README documents installing the client with pip, calling chat, and reading response.message.content. Create a project folder, install the package, and save the following as chat.py:
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python -m pip install ollamafrom ollama import chat
response = chat(
model="gemma4:e2b",
messages=[
{"role": "user", "content": "Explain what a local API does in one sentence."}
],
)
print(response.message.content)Run it in the same Python environment where you installed the package:
python chat.pyThe call waits for the response, then prints its text. This follows the official Python example; it is not a claim of independent testing. See the Ollama Python repository README for the client’s current instructions.
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Choose between the Ollama and OpenAI-compatible Python clients
If you already use the OpenAI Python client, Ollama also provides an OpenAI-compatible API at http://localhost:11434/v1. The quickstart demonstrates the chat completions endpoint. The two documented paths differ as follows:
| Path | Endpoint | Where response text appears | Coverage |
|---|---|---|---|
| Ollama Python client | Ollama /api/chat endpoint |
response.message.content |
Uses Ollama’s Python client; see the official README. |
| OpenAI-compatible client | http://localhost:11434/v1/chat/completions |
choices[0].message.content |
Compatibility covers a subset of the original OpenAI API. |
The compatibility endpoint does not require a local API key. Ollama’s quickstart shows the request pattern and the choices[0].message.content response path; the API introduction documents the base URL. Read the quickstart and API introduction before adapting code that relies on other OpenAI features.
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What local means—and what it does not guarantee
This project sends requests to a server on your own computer. That does not, by itself, establish that every configuration is private or secure if you expose the service beyond your machine. The documented setup here is for local development; do not treat it as production deployment guidance.
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