AI API
The AI API provides endpoints for managing AI models, inference, training, and advanced AI operations.
Status: Roadmap
This API is on the development roadmap. The endpoints documented below represent the planned interface design.
Base URL
http://localhost:8080/api/v1/ai
Authentication
Uses the standard botserver authentication mechanism with appropriate role-based permissions.
Endpoints
Model Management
| Method |
Endpoint |
Description |
| GET |
/api/v1/ai/models |
List available models |
| GET |
/api/v1/ai/models/{model_id} |
Get model details |
| POST |
/api/v1/ai/models/deploy |
Deploy a new model |
| DELETE |
/api/v1/ai/models/{model_id} |
Remove a model |
Inference
| Method |
Endpoint |
Description |
| POST |
/api/v1/ai/inference |
Run inference on input data |
| POST |
/api/v1/ai/chat/completions |
Chat completion endpoint |
| POST |
/api/v1/ai/embeddings |
Generate embeddings |
Training
| Method |
Endpoint |
Description |
| POST |
/api/v1/ai/training/start |
Start a training job |
| GET |
/api/v1/ai/training/{job_id}/status |
Get training job status |
| POST |
/api/v1/ai/training/{job_id}/cancel |
Cancel training job |
Model Configuration
| Method |
Endpoint |
Description |
| GET |
/api/v1/ai/models/{model_id}/config |
Get model configuration |
| PUT |
/api/v1/ai/models/{model_id}/config |
Update model configuration |
Request Examples
List Available Models
models = GET "/api/v1/ai/models"
FOR EACH model IN models
TALK model.name + " - " + model.status
NEXT
Chat Completion
request = NEW OBJECT
request.model = "gpt-4"
request.messages = NEW ARRAY
request.messages.ADD({"role": "user", "content": "Hello, how are you?"})
response = POST "/api/v1/ai/chat/completions", request
TALK response.choices[0].message.content
Generate Embeddings
request = NEW OBJECT
request.input = "Convert this text to embeddings"
request.model = "text-embedding-3-small"
result = POST "/api/v1/ai/embeddings", request
embedding = result.data[0].embedding
Start Training Job
training_config = NEW OBJECT
training_config.base_model = "llama-2-7b"
training_config.dataset = "my-training-data"
training_config.epochs = 3
job = POST "/api/v1/ai/training/start", training_config
TALK "Training job started: " + job.id
Response Codes
| Code |
Description |
| 200 |
Success |
| 201 |
Created |
| 202 |
Accepted (for async operations) |
| 400 |
Bad Request |
| 401 |
Unauthorized |
| 403 |
Forbidden |
| 404 |
Model or resource not found |
| 429 |
Rate limit exceeded |
| 500 |
Internal Server Error |
Required Permissions
| Endpoint Category |
Required Role |
| Model Management |
admin or model_manager |
| Inference |
user or higher |
| Training |
admin or trainer |
| Model Configuration |
admin |
