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LocalAI/docs/content/getting-started/try-it-out.md
mudler's LocalAI [bot] 40d35c0385 docs: onboarding overhaul, dedup, and error docs (#7711) (#10895)
* docs: fix CPU image tag (latest, not latest-cpu)

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* docs: use canonical localai/localai registry in models guide

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* docs: replace dead llama-stable backend with llama-cpp

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* docs: correct mitm-proxy intercept config and redaction tier

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* docs: fix text-to-audio endpoint and broken notice block

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* docs: fix VAD example, stale FAQ, broken link, CLI list, whats-new dump

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* docs: add end-to-end 'build your first agent' walkthrough

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---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
Co-authored-by: Ettore Di Giacinto <mudler@localai.io>
2026-07-17 22:08:20 +02:00

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+++
disableToc = false
title = "Try it out"
weight = 4
url = '/basics/try/'
icon = "rocket_launch"
+++
Once LocalAI is installed, you can start it (either by using docker, or the cli, or the systemd service).
By default the LocalAI WebUI should be accessible from http://localhost:8080. You can also use 3rd party projects to interact with LocalAI as you would use OpenAI (see also [Integrations]({{%relref "integrations" %}}) ).
After installation, install new models by navigating the model gallery, or by using the `local-ai` CLI.
{{% notice tip %}}
To install models with the WebUI, see the [Models section]({{%relref "features/model-gallery" %}}).
With the CLI you can list the models with `local-ai models list` and install them with `local-ai models install <model-name>`.
You can also [run models manually]({{%relref "getting-started/models" %}}) by copying files into the `models` directory.
{{% /notice %}}
You can test chat models from the CLI without keeping a separate `curl` command around:
```bash
# Terminal 1
local-ai run
# Terminal 2
local-ai chat --model qwen3-4b
```
`local-ai chat` connects to a running LocalAI server, opens an interactive chat prompt, and exits when you type `/exit`, `/quit`, or `/bye`. Use `/models` to list installed models, `/model <name>` to switch models, and `/clear` to reset the current conversation. If the server exposes exactly one model, LocalAI uses that model automatically:
```bash
# Terminal 1
local-ai run qwen3-4b
# Terminal 2
local-ai chat
```
When more than one model is configured, pass `--model` with the installed model name to avoid ambiguity. Use `--endpoint` to connect to a non-default server, for example `local-ai chat --endpoint http://127.0.0.1:8081 --model qwen3-4b`.
You can also test out the API endpoints using `curl`. A few examples are listed below.
{{% notice note %}}
Each example assumes you have already installed the model it names. The chat and function-calling examples below use `qwen3-4b` (install it from the Models page or with `local-ai run qwen3-4b`). The other examples name a model for the task they show (`gpt-4-vision-preview` for vision, `tts-1` for text to speech, `whisper-1` for transcription, `text-embedding-ada-002` for embeddings); replace each with the name of a model you have installed for that task.
{{% /notice %}}
### Text Generation
Creates a model response for the given chat conversation. [OpenAI documentation](https://platform.openai.com/docs/api-reference/chat/create).
<details>
```bash
curl http://localhost:8080/v1/chat/completions \
-H "Content-Type: application/json" \
-d '{ "model": "qwen3-4b", "messages": [{"role": "user", "content": "How are you doing?", "temperature": 0.1}] }'
```
</details>
### GPT Vision
Understand images.
<details>
```bash
curl http://localhost:8080/v1/chat/completions \
-H "Content-Type: application/json" \
-d '{
"model": "gpt-4-vision-preview",
"messages": [
{
"role": "user", "content": [
{"type":"text", "text": "What is in the image?"},
{
"type": "image_url",
"image_url": {
"url": "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg"
}
}
],
"temperature": 0.9
}
]
}'
```
</details>
### Function calling
Call functions
<details>
```bash
curl http://localhost:8080/v1/chat/completions \
-H "Content-Type: application/json" \
-d '{
"model": "qwen3-4b",
"messages": [
{
"role": "user",
"content": "What is the weather like in Boston?"
}
],
"tools": [
{
"type": "function",
"function": {
"name": "get_current_weather",
"description": "Get the current weather in a given location",
"parameters": {
"type": "object",
"properties": {
"location": {
"type": "string",
"description": "The city and state, e.g. San Francisco, CA"
},
"unit": {
"type": "string",
"enum": ["celsius", "fahrenheit"]
}
},
"required": ["location"]
}
}
}
],
"tool_choice": "auto"
}'
```
</details>
### Anthropic Messages API
LocalAI supports the Anthropic Messages API for Claude-compatible models. [Anthropic documentation](https://docs.anthropic.com/claude/reference/messages_post).
<details>
```bash
curl http://localhost:8080/v1/messages \
-H "Content-Type: application/json" \
-H "anthropic-version: 2023-06-01" \
-d '{
"model": "gpt-4",
"max_tokens": 1024,
"messages": [
{"role": "user", "content": "How are you doing?"}
],
"temperature": 0.7
}'
```
</details>
### Open Responses API
LocalAI supports the Open Responses API specification with support for background processing, streaming, and advanced features. [Open Responses documentation](https://www.openresponses.org/specification).
<details>
```bash
curl http://localhost:8080/v1/responses \
-H "Content-Type: application/json" \
-d '{
"model": "gpt-4",
"input": "Say this is a test!",
"max_output_tokens": 1024,
"temperature": 0.7
}'
```
For background processing:
```bash
curl http://localhost:8080/v1/responses \
-H "Content-Type: application/json" \
-d '{
"model": "gpt-4",
"input": "Generate a long story",
"max_output_tokens": 4096,
"background": true
}'
```
Then retrieve the response:
```bash
curl http://localhost:8080/v1/responses/<response_id>
```
</details>
### Image Generation
Creates an image given a prompt. [OpenAI documentation](https://platform.openai.com/docs/api-reference/images/create).
<details>
```bash
curl http://localhost:8080/v1/images/generations \
-H "Content-Type: application/json" -d '{
"prompt": "A cute baby sea otter",
"size": "256x256"
}'
```
</details>
### Text to speech
Generates audio from the input text. [OpenAI documentation](https://platform.openai.com/docs/api-reference/audio/createSpeech).
<details>
```bash
curl http://localhost:8080/v1/audio/speech \
-H "Content-Type: application/json" \
-d '{
"model": "tts-1",
"input": "The quick brown fox jumped over the lazy dog.",
"voice": "alloy"
}' \
--output speech.mp3
```
</details>
### Audio Transcription
Transcribes audio into the input language. [OpenAI Documentation](https://platform.openai.com/docs/api-reference/audio/createTranscription).
<details>
Download first a sample to transcribe:
```bash
wget --quiet --show-progress -O gb1.ogg https://upload.wikimedia.org/wikipedia/commons/1/1f/George_W_Bush_Columbia_FINAL.ogg
```
Send the example audio file to the transcriptions endpoint :
```bash
curl http://localhost:8080/v1/audio/transcriptions \
-H "Content-Type: multipart/form-data" \
-F file="@$PWD/gb1.ogg" -F model="whisper-1"
```
</details>
### Embeddings Generation
Get a vector representation of a given input that can be easily consumed by machine learning models and algorithms. [OpenAI Embeddings](https://platform.openai.com/docs/api-reference/embeddings).
<details>
```bash
curl http://localhost:8080/embeddings \
-X POST -H "Content-Type: application/json" \
-d '{
"input": "Your text string goes here",
"model": "text-embedding-ada-002"
}'
```
</details>
{{% notice tip %}}
Don't use the model file as `model` in the request unless you want to handle the prompt template for yourself.
Use the installed model's own name as the `model` value, the same way you would pass a model name to OpenAI. For instance `qwen3-4b` for chat, or `gpt-4-vision-preview` for a vision model you have installed under that name.
{{% /notice %}}