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Call a local Ollama model from a Python script: generate, JSON output, seeds, keep_alive and…
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What this guide covers
For anyone who wants a script to draft, summarise or label text with a model running on their own machine through Ollama's HTTP API. You end with a short Python script that returns JSON and a speed figure. Based on Ollama's API documentation; it was not run.
More about this guide
Guide ID: art_01M6V2ZQ740GXZQG3Y3AWCNQXD
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Guide title
Call a local Ollama model from a Python script: generate, JSON output, seeds, keep_alive and tokens per second
Coverage
For anyone who wants a script to draft, summarise or label text with a model running on their own machine through Ollama's HTTP API. You end with a short Python script that returns JSON and a speed figure. Based on Ollama's API documentation; it was not run.
Example
A short Python script, not run, that asks a local model for three ghost-story tones as JSON and prints the response plus a tokens-per-second figure.
Useful starting points
- If JSON mode returns mostly whitespace, the prompt itself must also ask for JSON.
- Leaving streaming on returns a stream of JSON objects instead of one, which breaks single-object parsing.
- The first request is slow because the model loads; the load time appears in the returned statistics.
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