This API is built using FastAPI and is designed to integrate with DreamBooth's AI models. It provides various endpoints for model training, running models, and querying their status.

• Setup
• Usage
  • Training a Model
  • Running a Model
  • Get Prediction
  • Get Training Status
  • Webhook
• API Endpoints
• Dependencies

1. Install FastAPI and other dependencies.
2. Set your REPLICATE_TOKEN and WEBHOOK_URL as env variables.
3. Optionally set DOCS_PASSWORD and DOCS_USERNAME for the fastapi docs page.
4. DD_AGENT_HOST, DD_TRACE_AGENT_PORT and DATADOG_SERVICE_NAME to configure datadog.
5. Set API_KEY to change api key for the endpoints.

Train a model by providing instance and class prompts, the maximum number of training steps, the model version, and the trainer version.

• instance_prompt (str)
• class_prompt (str)
• max_train_steps (int)
• model (str)
• trainer_version (str)
• file (UploadFile) - Zip file for training data

Run an already trained model.

• RunInput - The input parameters to run the model. It is a Pydantic model.
• version (str) - The version of the model to run.

Get the prediction result from a given URL.

• url (str) - The URL to fetch the prediction from.

Get the current status of a training operation using its training ID.

• training_id (str) - ID of the training operation

This endpoint receives payload data related to model training.

• POST /train_model/
• POST /run_model/
• GET /get_prediction/
• GET /get_training_status/{training_id}/
• POST /webhook/

• FastAPI
• DreamBoothAPI
• pydantic