Documentation Index
Fetch the complete documentation index at: https://docs.moodmnky.com/llms.txt
Use this file to discover all available pages before exploring further.
Models
This guide covers the model management capabilities of the Ollama service.
Models Endpoint
Manage and query available AI models.
List Models Endpoint
GET /api/models
curl "https://ollama.moodmnky.com/api/models" \
-H "x-api-key: your_api_key"
{
"models": [
{
"name": "llama2",
"size": 3791730718,
"modified_at": "2024-03-20T15:23:44Z",
"details": {
"format": "gguf",
"family": "llama",
"parameter_size": "7B",
"quantization_level": "Q4_K_M"
}
}
]
}
Show Model Info Endpoint
GET /api/models/{model}
curl "https://ollama.moodmnky.com/api/models/llama2" \
-H "x-api-key: your_api_key"
{
"name": "llama2",
"size": 3791730718,
"modified_at": "2024-03-20T15:23:44Z",
"details": {
"format": "gguf",
"family": "llama",
"parameter_size": "7B",
"quantization_level": "Q4_K_M",
"license": "llama2",
"system_prompt": "You are a helpful AI assistant.",
"context_window": 4096,
"default_generation_params": {
"temperature": 0.7,
"top_p": 0.9,
"top_k": 40
}
}
}
Pull Model Endpoint
POST /api/models/pull
curl -X POST "https://ollama.moodmnky.com/api/models/pull" \
-H "x-api-key: your_api_key" \
-H "Content-Type: application/json" \
-d '{
"name": "llama2",
"insecure": false
}'
{"status":"pulling manifest"}
{"status":"pulling layers","digest":"sha256:..."}
{"status":"verifying sha256 digest"}
{"status":"writing manifest"}
{"status":"removing any unused layers"}
{"status":"success"}
Delete Model Endpoint
DELETE /api/models/{model}
curl -X DELETE "https://ollama.moodmnky.com/api/models/llama2" \
-H "x-api-key: your_api_key"
Available Models
| Model | Size | Description | Use Cases |
|---|
| llama2 | 7B | General purpose model | Text generation, chat, Q&A |
| codellama | 7B | Code-specialized model | Code completion, explanation |
| mistral | 7B | Instruction-tuned model | Task completion, reasoning |
| orca-mini | 3B | Lightweight model | Quick responses, testing |
Usage Examples
List Available Models
const response = await client.ollama.listModels();
console.log("Available models:", response.models);
const response = await client.ollama.getModel("llama2");
console.log("Model details:", response.details);
Pull New Model
const response = await client.ollama.pullModel({
name: "codellama",
insecure: false
});
// Handle streaming response
for await (const chunk of response) {
console.log("Pull status:", chunk.status);
}
Delete Model
await client.ollama.deleteModel("unused-model");
Model Management Best Practices
-
Model Selection
- Choose appropriate model size for task
- Consider memory and performance requirements
- Test models before production use
- Monitor model performance metrics
-
Resource Management
- Clean up unused models regularly
- Monitor disk space usage
- Implement model rotation policies
- Cache frequently used models
-
Security Considerations
- Verify model checksums
- Use secure connections for pulls
- Implement access controls
- Monitor model usage patterns
-
Performance Optimization
- Pre-load frequently used models
- Use appropriate quantization levels
- Monitor memory usage
- Implement model warm-up strategies
Error Handling
try {
const response = await client.ollama.pullModel({
name: "llama2"
});
} catch (error) {
switch (error.code) {
case "MODEL_NOT_FOUND":
console.error("Model not found in registry");
break;
case "INSUFFICIENT_SPACE":
console.error("Not enough disk space");
break;
case "PULL_ERROR":
console.error("Error pulling model:", error.message);
break;
}
}
Model Lifecycle Management
-
Initial Setup
- Model selection and testing
- Performance benchmarking
- Resource allocation
- Access control configuration
-
Maintenance
- Regular updates
- Performance monitoring
- Usage analytics
- Health checks
-
Retirement
- Usage evaluation
- Replacement planning
- Data migration
- Clean removal
Support & Resources
