Lumoswitch · Agent console & AI toolbox
Get your AI tools ready
Start in the desktop app: connect a model, configure an Agent or open a workspace. Add Skills, MCP and optional companions when you need them.
Models
Choose a local or online connection and understand where requests run.
Agents
Find, install, configure and verify a supported Agent.
Workspace
Start a small task, review actions and check the result.
Skills
Discover reusable capabilities and install them where you need them.
MCP
Review tool server settings before applying them to an Agent.
QQ Big Fish
Pair private or group chat, shape its personality and manage memory.
Desktop pets
Adjust appearance, sound, movement and quiet time.
Help and updates
Troubleshoot a connection and keep your saved data when updating.
Using the cloud API? The console, upstream and API references remain available in the sidebar. Older manual Agent instructions remain accessible and are marked Deprecated.
Cloud API quickstart (retained)
Lumoswitch quickstart
Lumoswitch is an LLM access platform and console for AI applications, agents, and developer tools. A Lumoswitch access key can reach configured model providers while Lumoswitch synchronizes fixed, failover, automatic model selection, and load-balancing policies to Lumoswitch Runtime.
What you will have
- Optional provider keys for connected upstreams
- Platform models and/or connected model resources
- Model selection and failover rules
- A base URL for your selected downstream protocol
- A Lumoswitch access key whose full value is shown only once
Prerequisites
- A Lumoswitch account with console access.
- No provider key is needed when using only platform models.
- To connect an upstream, prepare a provider key that can list and invoke models.
Never paste real keys into documentation, screenshots, source control, or chat. Lumoswitch does not reveal stored upstream secrets in console lists.
Connect in five steps
1. Choose model sources
Open Quickstart. Platform models appear directly. Add a provider and key only when you also need connected models. Platform models and connected models have the same role in later routing and candidate selection. You can continue without a connected upstream. See Upstreams.
2. Discover models
This step shows platform models and fetches connected models from enabled upstreams. You may inspect later steps and save a draft when no model is available, but a callable API configuration still needs at least one healthy routable candidate. See Model resources.
3. Choose a routing mode
| Mode | Candidates | Behavior |
|---|---|---|
| Fixed | Exactly 1 | Uses one model and returns its error on failure |
| Failover | 1 or more, in priority order | Advances after the current candidate fails |
| Auto routing | 2 or more, ordered lightest to strongest | Lumoswitch Runtime selects a tier from request complexity |
| Least busy | 2 or more | Selects the candidate with the fewest active requests |
| Lowest latency | 2 or more | Selects the candidate with the lowest observed response latency |
Auto-routing order maps candidates onto the SIMPLE, MEDIUM, COMPLEX, and REASONING tiers; adjacent tiers reuse candidates when fewer than four are selected. Least-busy and lowest-latency modes do not treat list order as priority.
4. Configure downstream output
Set the default client-facing model name and select the client formats to expose. OpenAI uses a /v1 Base URL; Anthropic and Gemini use the inference origin. After creation, the configuration editor can add more client-facing model mappings that target either the whole routing policy or one candidate. Saving creates an API configuration and its initial access key.
Platform models never bypass routing or receive a special direct-access key. Add them to candidates and configure routing exactly like connected models.
5. Save the credentials
Copy the base URL and access key before closing the dialog.
The complete access key is shown once. Store it immediately in a secrets manager or environment variable.
Make the first request
export LUMOSWITCH_BASE_URL="https://api.lumoswitch.com/v1"
export LUMOSWITCH_API_KEY="your-lumoswitch-access-key"curl "$LUMOSWITCH_BASE_URL/models" \
-H "Authorization: Bearer $LUMOSWITCH_API_KEY"curl "$LUMOSWITCH_BASE_URL/chat/completions" \
-H "Authorization: Bearer $LUMOSWITCH_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "lumos-chat",
"messages": [{"role": "user", "content": "Say hello in one sentence."}]
}'Replace lumos-chat with the client-facing model name from your API configuration.
Supported endpoints
GET /v1/models
POST /v1/chat/completions
POST /v1/responses
POST /v1/embeddings
POST /v1/messages
POST /v1/messages/count_tokens
POST /v1beta/models/{model}:generateContent
POST /v1beta/models/{model}:streamGenerateContent
POST /v1beta/models/{model}:countTokensGemini also supports the /models/{model}:... aliases. See Protocols and compatibility for the exact public route allowlist and authentication boundary.
Next steps
- Confirm the full chain on the Dashboard.
- Tune routing and limits in API configurations.
- Isolate applications or environments with Projects.
Lumoswitch Docs
Explore the Lumoswitch desktop Agent console and AI toolbox. Start with models, Agents, workspace tasks, Skills and MCP, with cloud API guides retained.
Desktop user guide
Use the Lumoswitch desktop Agent console and AI toolbox: connect models, configure Agents, add Skills and MCP, start a workspace task, and find help.