# flux-dev-lora

> Enables text-to-image generation using custom LoRA models. Generate consistent characters, styles, or branded visuals with high quality and fast results.

## Overview

- **Endpoint**: `POST https://api.muapi.ai/api/v1/flux_dev_lora_image`
- **Model ID**: `flux-dev-lora`
- **Category**: training
- **Variant**: Dev LoRA
- **Family**: flux
- **Cost**: 0.015 credits per call (some models compute cost dynamically based on params)

## API Usage

MuApi uses a **submit-then-poll** pattern: submit a job, get a `request_id`, then poll the predictions endpoint until `status` is `completed`. Optionally pass `?webhook=YOUR_URL` on the submit call to receive a POST callback when the job finishes (skip polling).

**Authentication**: send your MuApi key in the `x-api-key` header. Get one at https://muapi.ai/access-keys.

### 1. Submit a job

```http
POST https://api.muapi.ai/api/v1/flux_dev_lora_image
Content-Type: application/json
x-api-key: YOUR_API_KEY
```

**Minimum (required only):**

```json
{
  "prompt": "<prompt>",
  "model_id": {
    "model": "civitai:119351@317153",
    "weight": 1
  }
}
```

**Full example (all params):**

```json
{
  "prompt": "<prompt>",
  "model_id": {
    "model": "civitai:119351@317153",
    "weight": 1
  },
  "width": 1024,
  "height": 1024,
  "num_images": 1
}
```

**Response:**

```json
{
  "request_id": "abc123",
  "status": "processing"
}
```

### 2. Poll for the result

```http
GET https://api.muapi.ai/api/v1/predictions/{request_id}/result
x-api-key: YOUR_API_KEY
```

Possible `status` values: `queued`, `pending`, `processing`, `completed`, `failed`, `cancelled`. Poll every 2-5 seconds until terminal. When `completed`, the result URLs are in the `outputs` array.

**Example response when `completed`:**

```json
{
  "id": "abc123",
  "status": "completed",
  "outputs": [
    "https://cdn.muapi.ai/.../output.png"
  ],
  "urls": {
    "get": "https://api.muapi.ai/api/v1/predictions/abc123/result"
  },
  "created_at": "2026-05-08T12:34:56Z",
  "has_nsfw_contents": []
}
```

### cURL

```bash
# 1. Submit
REQUEST_ID=$(curl -s -X POST https://api.muapi.ai/api/v1/flux_dev_lora_image \
  -H "x-api-key: $MUAPI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"prompt":"<prompt>","model_id":{"model":"civitai:119351@317153","weight":1}}' | jq -r .request_id)

# 2. Poll until completed
while :; do
  RESP=$(curl -s https://api.muapi.ai/api/v1/predictions/$REQUEST_ID/result -H "x-api-key: $MUAPI_API_KEY")
  STATUS=$(echo "$RESP" | jq -r .status)
  [ "$STATUS" = "completed" ] && echo "$RESP" | jq .outputs && break
  [ "$STATUS" = "failed" ] && echo "$RESP" && exit 1
  sleep 3
done
```

### Python

```python
import os, time, requests

API = "https://api.muapi.ai/api/v1"
headers = {"x-api-key": os.environ["MUAPI_API_KEY"]}

r = requests.post(f"{API}/flux_dev_lora_image", headers=headers, json={"prompt":"<prompt>","model_id":{"model":"civitai:119351@317153","weight":1}})
request_id = r.json()["request_id"]

while True:
    res = requests.get(f"{API}/predictions/{request_id}/result", headers=headers).json()
    if res["status"] == "completed":
        print(res["outputs"]); break
    if res["status"] == "failed":
        raise RuntimeError(res.get("error")); 
    time.sleep(3)
```

## Input Schema

The API accepts the following input parameters:

- **`prompt`** (`string`, _required_):
  Text prompt describing the image. The length of the prompt must be between 2 and 3000 characters.

- **`model_id`** (`array`, _required_):
  The unique identifier of a LoRA model hosted on Civitai, used by the Flux Dev image generation system. This ID tells Flux Dev which specific LoRA model to apply during generation. You can find the model ID in the Civitai model URL (e.g., model_id: civitai:1642876@1864626).
  - **`model_id[].model`** (`string`, _optional_): The Civitai LoRA model ID.
  - **`model_id[].weight`** (`number`, _optional_): A list of LoRA models to use for generation. Each item must include an `id` (e.g., "civitai:1642876@1864626") and a `weight` between 0 and 4. You can include up to 4 models. The `id` can be found in the Civitai model URL. These models will be applied with the specified weights by the Flux Dev system during image generation.
    - Default: `1`

- **`width`** (`int`, _optional_):
  Width of the output image. The value must be divisible by 64, eg: 128...512, 576, 640...2048.
  - Default: `1024`

- **`height`** (`int`, _optional_):
  Height of the output image. The value must be divisible by 64, eg: 128...512, 576, 640...2048.
  - Default: `1024`

- **`num_images`** (`int`, _optional_):
  Number of images generated in single request. Each number will charge separately
  - Default: `1`

## Output Schema

The polling endpoint returns the following fields:

- **`id`** (`string`): The request ID.
- **`status`** (`string`): One of `queued`, `pending`, `processing`, `completed`, `failed`, `cancelled`.
- **`outputs`** (`array`): URLs to generated images/videos/audio. Empty until `status` is `completed`.
- **`urls.get`** (`string`): Self-link to re-fetch this prediction.
- **`error`** (`string` | `null`): Error message if `status` is `failed`.
- **`created_at`** (`string`): ISO-8601 timestamp of when the request was created.
- **`has_nsfw_contents`** (`array of boolean`): Per-output NSFW detection flags.

## Webhooks (optional)

Append `?webhook=https://your-server/path` to the submit URL. When the job reaches a terminal state, MuApi will POST the same shape as the polling response to your URL — no polling needed.

## Agent Integration

MuApi ships an MCP server and CLI so agents (Claude Code, Cursor, custom) can call this endpoint without writing HTTP code:

```bash
# Install the CLI
npm install -g muapi-cli

# Authenticate once
muapi auth login

# Expose all MuApi models as MCP tools to your agent
muapi mcp serve
```

The MCP server exposes tools that wrap submit + poll for every model, including `flux-dev-lora`. See `muapi --help` for category-specific shortcuts (`muapi image generate`, `muapi video from-image`, etc.).

## Related Models
- [Dev LoRA](https://muapi.ai/playground/flux-dev-lora)
- [Schnell](https://muapi.ai/playground/flux-schnell)
- [Pulid Image to Image](https://muapi.ai/playground/flux-pulid)
- [Redux Image to Image](https://muapi.ai/playground/flux-redux)
- [Flux LoRA Trainer](https://muapi.ai/playground/flux-lora-trainer)
- [Dev](https://muapi.ai/playground/flux-dev)
- [Krea Dev](https://muapi.ai/playground/flux-krea-dev)

## Resources
- [Playground Page](https://muapi.ai/playground/flux-dev-lora)
- [API Reference](https://muapi.ai/playground/flux-dev-lora?tab=2)
- [Global llms.txt](https://muapi.ai/llms.txt)