feat: add models list endpoint

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2026-04-09 20:51:20 +02:00
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# TODO
- Race condition on jwks token refresh
- Rate Limiting
git tag -d v1.0.0; git push origin :refs/tags/v1.0.0; git tag -a v1.0.0 -m "Release v1.0.0"; git push origin v1.0.0
git tag -d v1.0.0; git push origin :refs/tags/v1.0.0; git tag -a v1.0.0 -m "Release v1.0.0"; git push origin v1.0.0
# 🦙 Ollama Rust API Wrapper
A high-performance Rust API wrapper around Ollama, providing an OpenAI-compatible interface, model lifecycle management, and advanced runtime features.
---
# 🚀 Features
* ✅ OpenAI-compatible API (`/v1/...`)
* ⚡ Streaming (Server-Sent Events)
* 🧠 Model lifecycle management (load/unload)
* 🔐 API key authentication (optional)
* 📊 Usage tracking & observability
* 🔀 Model routing & abstraction
* 🧩 Extensible architecture (multi-provider ready)
---
# 📡 API Endpoints
## 1. Core LLM API (OpenAI-compatible)
### Chat Completions
```
POST /v1/chat/completions
```
### Text Completions
```
POST /v1/completions
```
### Embeddings
```
POST /v1/embeddings
```
### List Models
```
GET /v1/models
```
---
## 2. Model Lifecycle Management
### Load (Warmup)
```
POST /v1/models/{model}/load
```
```json
{
"keep_alive": "10m"
}
```
---
### Unload (Free Memory)
```
POST /v1/models/{model}/unload
```
Internally uses:
```json
{
"model": "...",
"keep_alive": 0
}
```
---
### Reload (Optional)
```
POST /v1/models/{model}/reload
```
---
## 3. Model Management
### Pull Model
```
POST /v1/models/pull
```
### Delete Model
```
DELETE /v1/models/{model}
```
---
## 4. Runtime & Observability
### Model Status
```
GET /v1/models/{model}/status
```
### List Loaded Models
```
GET /v1/runtime/models
```
---
## 5. Streaming
Enable streaming with:
```json
{
"stream": true
}
```
Response format (SSE):
```
data: {"choices":[{"delta":{"content":"Hello"}}]}
data: {"choices":[{"delta":{"content":" world"}}]}
data: [DONE]
```
---
## 6. Health Checks
```
GET /health
GET /ready
```
---
# 🧠 Internal Mapping (Ollama)
| Wrapper Endpoint | Ollama Endpoint |
| ------------------------- | --------------- |
| /v1/chat/completions | /api/chat |
| /v1/completions | /api/generate |
| /v1/embeddings | /api/embeddings |
| /v1/models | /api/tags |
| /v1/models/pull | /api/pull |
| DELETE /v1/models/{model} | /api/delete |
| load/unload | /api/generate |
---
# ⚙️ Configuration
### Docker (optional default)
```yaml
environment:
- OLLAMA_KEEP_ALIVE=10m
```
> Note: Request-level `keep_alive` overrides this value.
---
# 🔧 Advanced Features
## 🔀 Model Routing
Use abstract model names:
```json
{
"model": "fast"
}
```
Example mapping:
```
fast → llama3:8b
smart → llama3:70b
code → deepseek-coder
```
---
## 📊 Usage Tracking
```
GET /v1/usage
```
Tracks:
* request count
* latency
* per-model usage
---
## 🔐 Authentication
```
Authorization: Bearer sk-xxxx
```
Endpoints:
```
POST /v1/keys
DELETE /v1/keys/{id}
```
---
## 🚦 Rate Limiting
* Requests per minute
* Tokens per minute
Returns:
```
429 Too Many Requests
```
---
## 🧠 Sessions (Context Management)
```
POST /v1/sessions
POST /v1/sessions/{id}/chat
```
Stores conversation history server-side.
---
## ⚡ Caching
* Embeddings
* Deterministic prompts (temperature = 0)
---
## 🧩 Tool / Function Calling
Supports structured tool execution:
```json
{
"tools": [
{
"name": "function_name",
"parameters": {}
}
]
}
```
---
## 📦 Batch Requests
```
POST /v1/batch
```
---
## 🧠 Auto Eviction
```
POST /v1/runtime/evict
```
Strategies:
* LRU
* memory threshold
---
## 🧾 Logs
```
GET /v1/logs
```
---
## 📚 Embedding Store (Optional)
```
POST /v1/documents
POST /v1/search
```
---
## 🔔 Async Jobs / Webhooks
```
POST /v1/jobs
```
---
# 🏗️ Architecture
```
Client → Rust API → Ollama → Response
```
### Layers:
* HTTP (Axum)
* Service layer (business logic)
* Provider abstraction
* Ollama client
---
# 🔌 Provider Abstraction (Future-Proof)
```rust
trait LlmProvider {
async fn chat(...);
async fn embeddings(...);
}
```
Supports:
* Ollama (current)
* OpenAI (future)
* Others
---
# ⚠️ Notes
* Ollama has no native unload endpoint → simulated via `keep_alive = 0`
* Streaming uses NDJSON → converted to SSE
* Chunk handling must be robust (partial JSON)
---
# 🎯 Roadmap
* [ ] Full OpenAI compatibility
* [ ] Multi-node routing
* [ ] GPU-aware scheduling
* [ ] Web UI dashboard
* [ ] Distributed inference
---
# 🧠 Summary
This project turns Ollama into:
👉 A local OpenAI-compatible API
👉 A controllable model runtime
👉 A foundation for a full LLM gateway
---
# 📜 License
MIT